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Hindustan Journal
A JOURNAL OF HINDUSTAN INSTITUTE OF TECHNOLOGY & SCIENCE
CHENNAI, INDIA
Vol. 6, 2013
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ii
PANEL OF ADVISORS
PANEL OF REVIEWERS
Dr. BVSSS PRASAD
APPLIED SCIENCES
Professor of Mechanical Engineering,
lIT, Madras
Dr. C.Indira
Dr. K.Nithyanandam
Dr. S. SHANMUGAVEL
Dr. I.Sasirekha
Professor, Department of Electronics and
Communication Engineering,
Anna University. Chennai
BUILDING SCIENCES
Dr. V.Subbiah
Dr. R.Angeline Prabhavathy
Dr. A. ALPHONES
Dr. Ravikumar Bhargava
Associate Professor, Division of Communication
Engineering
School of Electrical and Electronics Engineering,
Nanyang Technological University, Singapore
Dr. Jessy Rooby
Dr. P.S.Joanna
Dr. Sheeba Chander
Dr. P. RAMESHAN
COMPUTING SCIENCES
Director & Professor (Strategic Management)
lIM, Rohtak
Dr. Anitha S. Pillai
Dr. Rajeswari Mukesh
Dr. G.L. DUTTA
Dr. E.R.Naganathan
Chancellor,
K.L. University, Vijayawada
Dr. S.Nagarajan
Ms. P.Ranjana
Dr. HARSHA SIRISENA
Ms. S.Lakshmi Sridevi
Emeritus Professor,
Electrical & Computer Engineering,
University of Canterbury, Chirstchurch,
New Zealand.
Ms. S.Vijayalakshmi
ELECTRICAL SCIENCES
Dr. R.Devanathan
Dr. LAKMI JAIN
Dr. M.J.S.Rangachar
Professor of Knowledge Based Engineering,
Founding Director of the KES Centre,
Electrical and Information Engineering,
University of South Australia, Adelaide.
Dr. P.M.Rubesh Anand
Dr. PAUL APPASAMY
MECHANICAL SCIENCES
Dr. A.K.Parvathy
Ms. Manjula Pramod
Honorary Professor,
Madras School of Economics, Chennai.
Dr. D.G.Roy Chowdhury
Dr. B.Venkataraman
Dr. N. GANAPATHI SUBRAMANIAM
Dr. G.Ravikumar Solomon
Professor , Quantum - Functional Semiconductor
Research Center,
Dongguk University,
Republic of Korea
Dr D.Dinakaran
Dr. T.Jeyapovan
Dr. Hyacinth J. Kennady
Dr. A.Anitha
iii
Scanning the Issue
The current issue of Hindustan Journal of impulse noise detection techniques in
provides articles of varied interest to readers. images. Prakash and Kumaraguru Diderot
In the area of Building Sciences, the paper explain and review the commonly used cyclic
by Karuppiah and Angeline Prabhavathy redundancy checking algorithm for verifying
discusses the prospect of shear strengthening data integrity. Helen and Arivazhagan
of reinforced concrete beams using carbon propose the use of temporally ordered routing
fiber reinforced polymer. Nagarajan and algorithm along with medium access control
Ravi K. Bhargava analyse the role of trees to overcome bandwidth limitation.
Under the section on Mechanical Sciences,
Jeya Pradha and Mahendran evaluate the
evaporative heat transfer characteristics of a
refrigerant mixture using computational fluid
dynamics. Ravikumar and Saravanan describe
the design and fabrication of a chilling system
to reach a very low temperature to meet
the requirements of specific applications.
Viswanathan, Sengottuvel and Arun review
Under the section on Computing Sciences, the application of electrical discharge
Kodhai, Bharathi and Balathiripurasundari machine for the machining of hard materials.
propose a filtering scheme for wireless
Under Education and Library Sciences,
sensor networks to address bogus reports, Aby Sam and Akkara Sherine eloquently
false report injection attacks and denial of discuss the role of community colleges in
services. Thiyagarajan, Rasika, Sivasankari nation building and describe a success story
and Sophana Jennifer propose an artificial to drive home their point. Bhaskaran Nair
neural network based anomaly detection argues passionately the case for an integrated
technique to detect changes in medical reading professional programme on teaching
in a patient monitoring system. SreeVidhya English as a second language. Boopalan,
proposes a new fuzzy clustering algorithm Nithyanandam and Sasirekha gaze at the
which can handle efficiently outlier as well crystal ball and wonder about the future role
as natural data. Deeptha and Rajeswari of the librarian in an information era.
Mukesh propose a genetic algorithm based
Finally, we conclude the issue with a list
selection model to improve the quality of of forthcoming conferences for the benefit of
service performance in the context of web our readers.
services development.
and plants in the hospital premises in order
to improve the well- being of recuperating
patients. Thulasi Gopal provides an analysis
of the design of an Integrated Silk Park at
Kanchipuram to bring back its lost glory.
Karthigeyan argues the case for the speedy
implementation of high speed rail links in
India citing the successful story of high speed
trains in China.
Under the section on Electrical Sciences,
the paper by Priya and Seshasayanan
proposes a method to improve the efficiency
Dr. R.DEVANATHAN
Chief Editor
iv
Contents
BUILDING SCIENCES
Shear Strengthening of RC Beam Using Carbon
Fiber Reinforced Polymer Sheet
1
Pl. Karuppiah and R. Angeline Prabhavathy.
A Qualitative Research on the Role of Landscape
Architecture in and around Hospital Premises as an
Aid to Medical Treatment in Chennai
7
R. V. Nagarajan and Ravi K. Bhargava
A Research on Nuances of Silk Weaving and Designing a
Handloom Hub at Kanchipuram
15
Ar . Thulasi Gopal
A Case for the Development of High Speed Rail Link in India
21
D. Karthigeyan
COMPUTING SCIENCES
HMAC Filtering Scheme for Data Reporting in Wireless Sensor
Network26
E.Kodhai, P.Bharathi and D.Balathiripurasundari
An Efficient Neural Network Technique to Detect Collective
Anomalies in E-Medicine
36
G.Thiyagarajan, C.M.Rasika, B.Sivasankari and S.Sophana Jennifer
Deriving Intelligence from Data through Text Mining 42
C.T.Sree Vidhya
Web Service Assortment through Genetic Algorithm and XML
Deeptha R and Rajeswari Mukesh
v
50
HINDUSTAN JOURNAL, VOL. 6, 2013
ELECTRICAL SCIENCES
Improving the Efficiency of Impulse Noise Estimation
55
S.V.Priya and R.Seshasayanan
Review of Cyclic Redundancy Checking Algorithm
61
Prakash V R and Kumaraguru Diderot P.
Optimization of Temporally Ordered Routing Algorithm
(TORA) in Ad-Hoc Network
67
D.Helen and D.Arivazhagan
MECHANICAL SCIENCES
Evaluation of Evaporative Heat Transfer Characteristics
of CO2/Propane Refrigerant Mixtures in a Smooth
Horizontal Tube using CFD
71
S.Jeya Pratha and S.Mahendran
Design and Fabrication of Ultimate Chilling System
78
T.S.Ravikumar and S.Saravanan
Review of Electrical Discharge Machining Process
83
K.Viswanathan, P.Sengottuvel and J.Arun
EDUCATION AND LIBRARY SCIENCES
Community Colleges to SEmpower the Youth to
Transcend Social Barriers
88
Aby Sam and Akkara Sherine
Continuous Professional Development (CPD):
A Proposal for an Integrated Programme in
Teaching English as a Second Language (TESL)
97
P Bhaskaran Nair
Librarianship in Digital Era
101
E. Boopalan, K. Nithyanandam and I. Sasirekha
FORTHCOMING CONFERENCES
106
vi
HINDUSTAN JOURNAL, VOL. 6, 2013
Shear Strengthening of RC Beam Using Carbon Fiber
Reinforced Polymer Sheet
PL. Karuppiah and R. Angeline Prabhavathy
Abstract — The technique of strengthening of
reinforced concrete beam with externally bonded
Carbon Fiber Reinforced Polymer (CFRP) has
been successfully applied in Civil Engineering. This
paper discusses the effect of shear strengthening of
RC beams on the stress distribution, initial crack,
crack propagation and ultimate strength. The
experimental programme includes testing of five
simply supported reinforced concrete beams of
which four beam specimens are cast with bonding
CFRP and the remaining one beam without CFRP
which is considered as the control beam. The CFRP
epoxy bonded specimens are specimens, with full
side wrap (FSW), one side u wrap at shear (SUWS),
vertical wrap stirrups (VWS) and inclined wrap
stirrups (IWS). Mix design of M30 concrete is
adopted and the mix proportion is arrived at. Based
on the mix proportion, the specimens are cast. The
deflection, shear failure, cracking and ultimate
load for rectangular beams bonded with CFRP
are investigated. The experiments are conducted
to predict the critical load, cracks and increase in
strength. It is concluded that in beams bonded
with side u wrap stirrups (SUWS), there is a delay
in the formation of initial crack and the ductility
ratio is higher, which is desirable in earthquake
prone areas. The general and regional behaviour of
concrete beams with bonded CFRP are studied with
the help of strain gauges. The appearance of the first
crack and the crack propagation in the structure up
to failure is monitored and discussed for the control
and the strengthened beams.1
Intex terms — CFRP wrap, U-wrap, Carbon fiber.
PL. Karuppiah and R. Angeline Prabhavathy are
in School of Building Sciences, Hindustan University,
Chennai, India, (e-mail: plkaruppiah@hindustanuniv.
ac.in, [email protected]).
I.  Introduction
Carbon Fiber composites and reinforced polymer
offer unique advantages in many applications where
conventional materials cannot provide satisfactory
service life. Carbon fiber reinforced polymer (CFRP) is
a very strong and light fiber reinforced polymer which
contains carbon fiber. The polymer which is most often
used is epoxy, but other polymers such as polyester,
vinyl ester or nylon are sometimes used. The composite
may contain other fibers such as Kevlar, aluminum,
glass fibers as well as carbon fibers. The use of CFRP
is advantageous, because it is easier to maintain a
relatively uniform epoxy thickness throughout the
bonding length. By using CFRP wrap, the shear
strength and stiffness increase substantially reducing
shear cracking.
This paper provides the results of an experimental
investigation on using CFRP sheets to prevent local
cracks around shear region in reinforced concrete
beams.
II.  Literature Review
Norris et al. (1997) investigated the shear and
flexural strengthening of RC beam with carbon fiber
sheets. The CFRP sheets were epoxy bonded to the
tension face and web of concrete beams to enhance
their flexural and shear strengths. When the CFRP
sheets were placed perpendicular to cracks in the beam,
a large increase in stiffness and strength was observed
and there was no difference in the behavior between
the pre-cracked beams and the un-cracked ones at the
ultimate level. It was concluded that CFRP (carbon
fiber reinforced plastic) sheets increased the strength
and stiffness of existing concrete beams when bonded
to the web and tension face.
2 HINDUSTAN JOURNAL, VOL. 6, 2013
Chaallal et al. (1998) studied the shear strengthening
of RC beams using externally bonded side CFRP sheets.
It is concluded that diagonal side CFRP (Carbon fiber
reinforcement plastic) strips outperformed vertical
side strips for shear strengthening in terms of crack
propagation, stiffness and shear strength.
Alex Li et al. (2001) investigated the shear
strengthening of RC beam with externally bonded
CFRP sheets. The results of tests performed in the
study indicated that stiffness increased while increasing
the area of the CFRP sheet at the flanks and the strain
gauge measurements showed that strengthening the
entire lateral faces of the beam was not necessary.
For the strengthened beam, the ultimate strength had
a significant increase when compared with the normal
beam. Spadea et al. (2001) studied the strength and
ductility of RC beams repaired with bonded CFRP
laminates. The results showed that significant increase
in strength was obtained by strengthening with bonded
CFRP laminates.
Charlo Pellegrino et al. (2002) investigated the
shear strengthening of reinforced concrete beams using
fiber reinforced polymer. Except for the control tests, all
the tests were done on beams with side-bonded CFRP
sheets. The comparison between the experimental and
the theoretical values were made and it was found
that the shear capacity increment is due to Carbon
Fiber Reinforced Polymer. Tavakkolizadeh et al.
(2003) investigated the strengthening of steel-concrete
composite girders using carbon fiber reinforced
polymer sheets. The result indicated that the loadcarrying capacity of a steel-concrete composite girder
improved significantly and the ultimate load-carrying
capacities of the girders significantly increased by 44,
51, and 76% for 1, 3 and 5 layers respectively.
Kesse et al. (2007) investigated the experimental
behaviour of reinforced concrete beams strengthened
with pre-stressed CFRP shear straps. He concluded
that the pre-stressed CFRP strap strengthening system
showed good results and it is an effective means of
significantly increasing the shear capacity of existing
concrete structures.
From the review of literature, it has been found
out that much work has not been done on shear
strengthening of RC beams with different types of
CFRP wraps. Therefore the shear strengthening of RC
beams with CFRP wrap is discussed in this paper.
III.  Experimental Program
In the experiment program of this research, tests are
conducted on reinforced concrete beams with external
bonding of CFRP sheets in the shear zone. The beams
are tested under two-point loading to investigate their
structural behaviour. The objective of this experimental
investigation is to determine the
●● Structural behaviour of RC beam;
●● Shear strength of RC beam;
●● Shear failure of RC beam and
●● S
hear strengthening of RC beam using CFRP
sheets.
Experimental investigations always show
the real behaviour of the structure, an element or a
joint. Five rectangular RC beams are cast and tested
under two point loading. Out of five beams, one is a
control beam. The CFRP epoxy bonded specimens are
specimens with full side wrap, one side u wrap at shear,
vertical wrap stirrups and inclined wrap stirrups. The
following are the dimensions of the beam.
A.  3.1 Beam Dimension Details
Size: 2000 x150 x 250 mm
Effective cover:
20 mm
Grade of concrete:
M30
B.  3.2 Type of material
Sheet: Carbon fibre reinforced polymer
Glue for bonding: Nitowrap 30 (Base),
Nitowrap 410 Harder, Nitowrap 410 Base.
IV.  Specimen Details
Tests are carried out on five reinforced
concrete beam specimens and all are strengthened for
shear capacity using external bonded CFRP wraps.
The beam with 150 x 250 mm cross section and 2000
mm clear span are simply supported and subjected to
two concentrated static loads. Steel stirrups of 8mm
diameter are placed at 160 mm spacing along the beam
length for all beams. Fig. 1 shows the Test setup and
Fig. 2 shows the setup of vertical wrap stirrups. Table 1
shows the details of specimens and reinforcement.
KARUPPIAH AND ANGELINE PRABHAVATHY: SHEAR STRENGTHENING OF RC BEAM 3
A.  Properties of Nitowrap
Tables 2 to 4 show the properties of Nitowrap CF,
Nitrowrap 30(primer), and Nitrowrap 410 (Saturant)
respectively.
Table 2. Nitowrap CF
Fibre orientation
Fig. 1. Test setup
Unidirectional
Weight of fibre
200 g/m2
Density of fibre
1.80g/cc
Fibre thickness
0.30mm
Ultimate elongation (%)
1.5
Tensile strength
3500 N/mm2
Tensile modulus
285 x103 N/mm2
Table 3. Nitowrap 30, Primer
Colour
Fig. 2. Setup of Vertical wrap stirrups
Table 1. Details of specimen and reinforcement
Details of
Types
beam
of beam
Control
beam
Full side
wrap
Testing
of beam
(days)
Reinforcement in beam
Longitudinal
Stirrups
CB
FSW
SUWS
shear
wrap
2-10# @ top
28
Vertical
IWS
and 2-12# @
bottom
8mm #
stirrups @
160mm
C/C
stirrups
Inclined
wrap
Application
temperature
150C - 400C
Viscosity
Thixotropic
Density
1.25 - 1.26 g/cc
Pot Life
2 hours at 300C
Cure time
5 days at 300C
Table 4. Nitowrap 410, saturant
Density
1.14 g/cc
Pot life
25 min. @ 270C
Full cure
7 days
B.  Surface preparation
Side U
wrap at
Pale yellow to amber
VWS
stirrups
V.  Material Properties
The concrete used in the experimental program is M20
and steel with nominal yield strength of 415 N/mm2 is
used as the longitudinal reinforcement.
It is ensured that concrete surfaces are free from oil
residues, demoulding agents, curing compounds, grout
holes and protrusions. Structural damages are repaired
by using epoxy grouting/ appropriate mortar from the
Renderoc range. All depressions, imperfections etc. are
repaired by using Nitocote VF/ Nitomortar FC, epoxy
putty.
The base and hardener are thoroughly mixed in a
container for 3 minutes. Mechanical mixing using a
heavy-duty slow speed (300-500 rpm) drill, fitted with
a mixing paddle is done.
The mixed material of Nitowrap 30 epoxy primer
is applied over the prepared and cleaned surface. It
is applied with a brush and allowed to dry for about
24 hours before application of saturant. The mixed
material of Nitowrap 410 saturant is applied over the
tack free primer.
4 HINDUSTAN JOURNAL, VOL. 6, 2013
VI.  Results And Discussions
Five simply supported reinforced concrete beam
specimens are tested which include one control beam,
and four CFRP epoxy bonded specimens with full side
wrap (FSW), one side u wrap at shear (SUWS), vertical
wrap stirrups (VWS) and inclined wrap stirrups (IWS).
The load deflection behaviour, first crack load, finial
crack load and maximum deflection are studied.
A.  Load – Deflection behaviour
Table 5 shows the Comparison of Ultimate Load and
Maximum Deflection.
Si. No.
Specimen
First
Crack
Load (kN)
Ultimate
Load (kN)
Maximum
Deflection
(mm)
Table 5. Comparison of Ultimate Load and Maximum
Deflection
1
CB
33.5
123.9
32.6
2
FSW
51.8
158.8
14.3
3
SUWS
41.9
122.5
32.4
4
IWS
22.6
122.4
22.4
5
VWS
54
134.8
26.8
Fig. 5. Bar chart of maximum deflection
From Fig. 3, it can be seen that the first crack is
delayed in the case of FSW and VWS beams. Fig. 4
shows that the final crack is delayed only in the case of
FSW beam.
Fig. 5 shows that the deflection is minimum in the
case of FSW beam. Fig. 6 shows the Load Vs deflection
behaviour of the various beam specimens.
The comparison of initial crack, final crack and
deflection of various specimens are shown in Fig 3 to 5.
Fig. 6. Load Vs Deflection Behaviour of All Beam specimens.
Fig. 3. Bar chart of first crack load
From the load – deflection behaviour, it can be seen
that the load carrying capacity is maximum for FSW
beam but brittle failure occurs.
In SUWS beam, the initial crack occurs at 41.9 kN
which is 25% higher than that of the control beam. The
ductility ratioes also higher in SUWS beam which is
desirable in earthquake prone areas.
B.  Failure Pattern
Fig. 7 shows the cracking pattern of a control beam.
The initial crack occurs at 33.5 kN and final crack at
123.9 kN. The ultimate load is 123.9 kN.
Fig. 4. Bar chart of final crack
KARUPPIAH AND ANGELINE PRABHAVATHY: SHEAR STRENGTHENING OF RC BEAM 5
Fig. 7. Cracking pattern of Control beam
Fig. 8 shows the cracking pattern of FSW
specimen. The initial crack occurs at 51.1 kN and final
crack at 157.5 kN. The ultimate load is 158.8 kN. Total
CFRP covered area is 1400 mm (Length), and 170 mm
(Height).
Fig. 10. Cracking pattern of IWS specimen
Fig. 11 shows the cracking pattern of VWS
specimen. The initial crack occurs at 54 kN and final
crack at 129 kN. The ultimate load is 129 kN. Vertical
CFRP stirrups 100mm wide are wrapped at 90o.
Fig. 8. Cracking pattern of FSW specimen
Fig. 9 shows the cracking pattern of SUWS
specimen. The initial crack occurs at 41.9 kN and final
crack at 122.6 kN. The ultimate load is 122.6 kN. CFRP
is wrapped in the shear area as U section, with a width
of 250 mm.
Fig. 11. Crack pattern of VWS specimen
Debonding of CFRP wraps occurred after the initial
crack appeared. Fig. 12 to Fig. 15 show the debonding
of CFRP.
Fig. 9. Cracking pattern of SUWS specimen
Fig. 10 shows the cracking pattern of IWS
specimen. The initial crack occurs at 22.6 kN and
final crack at 123.8 kN. The ultimate load is 123.8 kN.
Inclined CFRP stirrups are wrapped at an angle of 60o
with a width of 60 mm.
Fig. 12. Debonding of FSW specimen
6 HINDUSTAN JOURNAL, VOL. 6, 2013
Sudden failure of FSW beam occurred at the
ultimate load.
●● C
ompared to all other specimens deflection of FSW
specimen is less and load bearing capacity is more.
However brittle failure occurs.
●● I n SUWS beam, the initial crack occurs at 41.9 kN
which is 25% higher than that of the control beam.
The ductility ratio is also higher in SUWS beam
which is desirable in earthquake prone areas.
References
Fig. 13. Debonding of SUWS specimen
[1] T
om Norris et al. (1997), Shear And Flexural
Strengthening Of RC Beams With Carbon Fiber
Sheets. Journal of Structural Engineering 123,
903-911.
[2] O
. Chaalla. et al. (1998), Shear Strengthening
Of RC Beams by Externally Bonded Side CFRP
Strips. Journal of Composites for Construction,
2, 111-113.
[3] A
lex Li, et al. (2001), Shear Strengthening Of RC
Beams With Externally Bonded CFRP Sheets.
Journal of Structural Engineering,127, 374-380.
Fig. 14. Debonding of IWS specimen
[4] G
. Spadea et al. (2001), Strength And Ductility
Of RC Beams Repaired With Bonded CFRP
Laminates, Journal of Bridge Engineering, 6,
349-355.
[5] C
arlo Pellegrino et al. (2002), Fiber Reinforced
Polymer Shear Strengthening of Reinforced
Concrete Beams with Transverse Steel
Reinforcement. Journal of Composites for
Construction, 6, 104-111.
Fig. 15. Debonding of VWS specimen
VII.  Conclusion
Tests were performed in externally applied epoxybonded CFRP. Based on the test results the following
conclusions are drawn.
[6] M
. Tavakkolizadeh, et al.(2003), Strengthening of
Steel-Concrete Composite Girders Using Carbon
Fiber Reinforced Polymers Sheets. Journal of
Structural Engineering, 129, 30-40.
[7] G
yamera Kesse et al., (2007), Experimental
Behavior of Reinforced Concrete Beams
Strengthened with Prestressed CFRP Shear
Straps. Journal of Composites for Construction,
11, 375-383.
HINDUSTAN JOURNAL, VOL. 6, 2013
A Qualitative Research on the Role of Landscape
Architecture in and around Hospital Premises as an Aid to
Medical Treatment in Chennai.
R. V. Nagarajan and Ravi K. Bhargava
Abstract — The milieu of the hospitals ought to be
healthy and hygienic for the patients to recuperate
from their illness. The role of trees and plants
in a hospital premises is considered a dynamic
parameter in the creation of the hospital quality.
This paper attempts to discern the ratio of minimum
land / area required for the medicinal landscape
to the area of hospital units. The very question of
how to border out the minimum quantity of trees
required for a hospital landscape is the prime aim
of this research. Secondly, what are the aspects (air
purification, killing bacteria, noise reduction, etc.)
to be considered in the selection of trees, is the next
level of research. Finally, aided by statistical results
of a survey conducted in hospitals, this research
narrows down to the ratio (x:y) for a typical hospital
premises, where ‘x’ is the minimum area required
for ‘n’ number of occupants (patients, non-patients,
hospital-staff, etc.) and ‘y’ is the minimum open
space required for the medicinal landscape to be
executed for a Healthy Hospital.1
Index terms — Landscape, Hospital, Treatment.
I.  Introduction
“Research gathered over recent years has highlighted
the countless benefits to people, wildlife and the
environment that come from planting trees and creating
new woodland habitat. It is obvious trees are good
things,” says Clive Anderson.
R.V. Nagarajan and Ravi K. Bhargava are in School
of Architecture, Hindustan University, Chennai, India,
(e-mail: [email protected])
The belief that plants and gardens are beneficial for
patients in healthcare environments is more than one
thousand years old, and appears prominently in Asian
and Western cultures [1].
The awareness of the positive influence of the
outdoor environment on patients’ healing process
has long been present in hospital architecture. The
term healing garden applies to the gardens that
promote recuperation from illness. In this context,
‘healing’ does not necessarily refer to curing, but to
the overall improvement of well-being.Integration
and unity of hospital buildings and their surrounding
outdoor spaces contribute to the creation of hospital
as a ‘small city within a city’, with its own specific
patterns of use [2].
II.  Characteristics of Plants
Plants possess the ability of escalating the pain tolerance
effects in the patients so as to enable them to recuperate
from their illness or surgery. This ability of the plants
is found nil in the first case and comparatively higher
in the third case than the second one in the following
category [3]:
1. No plants
2. Foliage plants
3. Foliage + Flowering plants
Patients in hospital rooms with plants and flowers
have significantly showed more positive physiological
responses, lower ratings of pain, anxiety and fatigue,
and more positive feelings and higher satisfaction
about their rooms than the patients who are kept in
8 HINDUSTAN JOURNAL, VOL. 6, 2013
rooms without plants [4]. Findings of such researches
suggested that plants in a hospital environment
could be noninvasive, inexpensive, and an effective
complementary medicine for patients recovering from
abdominal surgery.
Researchers who have assessed the impact of
nature/plants on human health have suggested that
nature and plant experiences are positively associated
with human physical [5], psychological [6], emotional
[7], and cognitive health [8]. In addition, viewing
nature/plants is linked to pain reduction, less need for
analgesics, and fast recovery from surgery [9].
For many years, the importance of aesthetics in
relevance to the health was not experimentally proven
as the additional quality of plants. Apart from the
recuperation of illness, aesthetic of plants is another
important philosophical discipline which must be added
to the ambience of hospital for the further betterment to
both the patients and the doctors. High quality nursing
care includes the aesthetic dimension [10].
Aesthetics influences a person’s feelings, both
physical and psychological. Both aesthetic and nonaesthetic surroundings create an impression and affects
a person consciously or unconsciously [11].
III. Method to Calculate Green Areas
for Any Site
According to the Green Guide for Health Care, the
following formula is for the calculation of the required
green area: Natural Habitat Area = (Site Area x Site Size
Factor) / Floor Space Ratio, where Floor Space Ratio =
Gross Constructed Area including all service spaces and
excluding parking areas / Site Area and Site Size Factor
= (1/√Site Area) x 10 (usually around 0.15) [12].
The main difference between the calculation of
green areas for any site and with hospital site is the
nature of the people occupying it. The prime aim of
this research is to find out the variation in the level of
the ratio in the above formula framed by the GGHC
(Green guide for Health Care), with the level of the
ratio in hospital site, particularly concentrating on the
landscape features.
the buildings, 15% for internal communication routes
and parking, 50% for vacant area (25-30% in case of
hospitals with a limited capacity for future growth) out
of which 10% is reserved for recreational areas.
In brief, they should be planned according to
following requirements: (1) to create opportunities for
movement and exercise; (2) to offer a choice between
social interaction and solitude; (3) to provide both direct
and indirect contacts with nature and other positive
distractions [13].
Several studies of non-patient groups (such as
university students) as well as patients have consistently
shown that simply looking at environments dominated
by greenery, flowers, or water -- as compared to built
-scenes lacking nature (rooms, buildings, towns) -- is
significantly more effective in promoting recovery or
restoration from stress.
To promote the speed of postoperative recovery and
to improve the quality of life during hospitalizations, it
is important to provide patients with not only the best
treatment possible, but also to remove such sources of
stress and to counter them with positive distractions.
V.  Interior Plants
When plants were added to the interior space, the
participants were more productive (12% quicker
reaction time on the computer task) and less stressed
(systolic blood pressure readings lowered by one to
four units). Immediately after completing the task,
participants in the room with plants present reported
feeling more attentive (an increase of 0.5 on a selfreported scale from one to five) than people in the room
with no plants [14].
Regardless of the physical air quality benefits, people
generally have an affinity to being around plants. Many
studies have proven a link to plants and their beneficial
psychological effects on people, including increases in
productivity and decreases in stress levels [15].
IV.  Design Considerations for Hospital
Landscaping
In 2006, many studies were published that indicated
that simply having three small potted plants can
significantly reduce (50-75%) the total VOC (Volatile
Organic Compound) levels in a real office of 30-50m3
size [16]. The only consideration was that the level of
total VOC needed to be above 100ppb - a concentration
level that is much lower than acceptable limits.
In an ideal case, optimal distribution of the total site area
of a hospital complex should be the following: 30% for
The National Aeronautics and Space Administration
studies on indoor landscape plants and their role in
NAGARAJAN AND BHARGAVA:A QUALITATIVE RESEARCH ON THE ROLE OF LANDSCAPE 9
improving indoor air quality included reports on toxins
common to the interior environment, specifically
benzene, formaldehyde, and trichloroethylene [17].
The following list of plants typically used in the
interior environment outlines the plants found to be
more effective in air purification, based on the NASA
studies [18].
1. A
echmeafasciata (Excellent for formaldehyde and
xylene)
2. A
glaonemamodestum (Excellent for benzene and
toluene)
3. Aloe vera (Excellent for formaldehyde)
4. C
hamaedorea Bamboo (Excellent for benzene and
formaldehyde)
5. C
hlorophytumelatum (Excellent
monoxide and formaldehyde)
for
carbon
6. C
hrysanthemum morifolium (Excellent
trichloroethylene, good for benzene
formaldehyde)
specialized for a single disease. 3. A hospital located in
the outskirts.
Following hospitals in Chennai were selected for
the survey: 1. Rajiv Gandhi Government Hospital,
Central, Chennai. 2. Cancer Institute, Adyar, Chennai
and 3. Kamakshi Memorial Hospital, Velachery Road,
Chennai.
VII. Selection of People for Survey
It was already planned that the selection of the people
for survey was as per the requirement of the research.
So, the people for survey were categorized into four
following types: 1. with respect to occupation, 2. with
respect to their age, 3. with respect to the time of survey
and 4. with respect to their gender.
for
and
7. D
endrobium Orchid (Excellent for acetone,
ammonia, chloroform, ethyl acetate, methyl
alcohol, formaldehyde and xylene)
8. Dieffenbachia maculate (Good for formaldehyde)
9. D
racaena deremensis (Excellent for benzene and
trichloroethylene, good for formaldehyde)
10. Dracaena marginata (Excellent for benzene, good
for formaldehyde and trichloroethylene)
11. Dracaena
Massangeana
formaldehyde)
(Excellent
Fig. 1. Occupation
for
VI. Surveillance in Hospitals in Chennai
As the aim of this research was conceptualized to
calculate the ratio of the minimum open space required
for landscape in a hospital to the built up space of the
site, the research was further proceeded to organize
a survey with the people who inhabit the hospital
premises.
Surveys were carried out in three major hospitals
in Chennai in the following categories: 1. a hospital
in the populated / noisy zone of the city. 2. A hospital
Fig. 2. Age
10 HINDUSTAN JOURNAL, VOL. 6, 2013
(b)
Fig. 3. Time
(c)
Fig. 4. Gender
VIII. Report on The Surveillance
(d)
The following are the statistical ripostes for the
questionnaire prepared for the survey:
(e)
Fig. 6. Sub categories of fig. 5.
Fig. 5. Liking of parts of Hospital
(a)
Fig. 7. Duration in Hospital
NAGARAJAN AND BHARGAVA:A QUALITATIVE RESEARCH ON THE ROLE OF LANDSCAPE 11
Fig. 8. Noise Level
Fig. 11. Elements missing in Hospital
Fig. 9. Smoke / Dust in premises
Fig. 12. Inside the building-1
Fig. 10. Preferred surroundings
Fig. 13. Inside the building-2
12 HINDUSTAN JOURNAL, VOL. 6, 2013
1. 5 7.5% People feel comfort in the place where the
following trees are planted: Azardirastraindica,
Ficusreligiousa, Ficusbengalinensis, Flowering
trees and Pongameapinnata.
2. 6 3.7% of people desperately want some mode of
system to enhance their breathing comfort, and
50% among them recommended plants inside the
building.
Fig. 14. Trees liked
3. A
s most of the previous researches proved, 45%
of the people surveyed preferred flowering plants
in their vicinity and they expressed that they felt
relaxed compared to the people who were not
having flowering plants in their rooms.
4. E
qually, 40% of people preferred earth walkway
and also lawn in the open space of the premises.
5. 6 5% of people complained that the process of
shedding leaves of trees is irritable than the
problems of insects over it (32% complained of
insects).
6. A
mong the people surveyed, 75% of patients, 65%
of non - patients and 78% of staff members of
hospital prefer to rest under the tree during midday.
7. A
ge wise, 82% of above 55 age people preferred
noiseless area than the active / noisy area.
Fig. 15. Trees recommended
8. A
lmost 95% of the women prefer to rest inside the
building than resting under trees, street-benches or
anywhere in open spaces.
9. A
lmost 88% of the men patients whose rooms were
not having plants felt boredom and wanted to move
around, when the same feeling was felt by only
15% of the men patients whose rooms had plants.
10. Almost 90%of all age group men and women who
are patients prefer to have a walk in either in the
morning or in the evening in the road which has
trees, than the road which does not have them.
Fig. 16. Trees disliked
11. Area Calculation of the First hospital: Total Area
- 61,336.0716 sq.m and the total open space is
22,114.0452 sq.m.
IX. Synthesis of The Survey
12. Area Calculation of the Second hospital: Total
area - 31,567.9558 sq.m and the total open space is
16,423.8566 sq.m
From the above report of the survey conducted in three
hospitals in Chennai, the following are the syntheses
observed:
13. Area Calculation of the Third hospital: Total Area:
- 12,437.2557 sq.m and the total open space is
3,211.7854 sq.m
NAGARAJAN AND BHARGAVA:A QUALITATIVE RESEARCH ON THE ROLE OF LANDSCAPE 13
14. The satisfaction level of the people staying in the
premises in terms of overall aspects, synthesized
from all the three hospitals is as follows: 71.35%,
83.75% and 56.21% are the percentage of the
satisfaction level measured from the first, second
and third hospitals respectively.
15. With the above satisfaction levels measured, the
total built up area, total open space area and the site
area of all the three premises are multiplied with
the percentages of the satisfaction level.
16. 71.35% of 22,114.0452sq.m. =x
17. 83.75% of 16,423.8566 sq.m= y
18. 56.21% of 3,211.7854 sq.m= z
19. Built up spaces of all the three premises are
considered as a, b and c respectively.
X. Calculation of Ratio of Minimum Open
Space for A Hospital
(x+y+z) / 3 = Xos
where x, y, z are the satisfied open area for a hospital
and Xos is the factor for open space.
(a+b+c) / 3 = Ybs
where a, b, c are the built up area of the hospital
buildings and Ybs is the factor for built up space.
XI. Conclusion
Considerations”, Architecture and Civil
Engineering Vol. 8, No 3, 2010, pp. 293 - 305
[3] S
.-H. Park, R.H. Mattson, E. Kim (2011), “Pain
Tolerance Effects of Ornamental Plants in a
Simulated Hospital Patient Room”, Department
of Horticulture, Forestry and Recreation
Resources, Kansas State University.
[4] S
eong-Hyun Park and Richard H. Mattson,
(2009) “Effects of Flowering and Foliage Plants
in Hospital Rooms on Patients Recovering from
Abdominal Surgery”, Department of Horticulture,
Forestry and Recreation Resources, Kansas State
University.
[5] C
hang, C. and P. Chen. (2005). “Human response
to window views and indoor plants in the
workplace”, Hort Science 40:pp.1354–1359.
[6] K
aplan, R. and S. Kaplan. (1995), “The experience
of nature: A psychological perspective”, Ulrich’s,
Ann Arbor, MI.
[7] A
dachi, M., C.L.E. Rode, and A.D. Kendle.
(2000), “Effects of floral and foliage displays on
human emotions”, HortTechnology 10:pp.59–63.
[8] C
imprich, B. (1993), “Development of an
intervention to restore attention in cancer
patients”, Cancer Nurs. 16:pp.83–92.
[9] D
iette, G., E. Haponik, and H. Rubin. (2003),
“Distraction therapy with nature sights and sounds
reduces pain during flexible bronchoscopy”,
Chest 12:pp.941–948.
The research concludes that Xos:Ybs is the ratio of
minimum open spaces to the built up space of a hospital
premises.
[10] S
ynnøveCaspari, (2006), “The aesthetic
dimension in hospitals - an investigation into
strategic plans”, International Journal of Nursing
Studies 43 pp.851–859.
References
[11] U
lrich, R., (1991), “Effects of interior design on
wellness. Theory on recent scientific research”,
Journal of Health Care and Interior Design, 3.
[1] U
lrich, R. S. and R. Parsons (1992), “Influences
of passive experiences with plants on individual
well-being and health. In D. Relf (Ed.)”, The
role of horticulture in humanwell-being and
social development, Portland, Timber Press, pp.
93-105.
[2] D
ejanaNedučin,
“Milena
Krklješ,
NađaKurtović-Folić”, “Hospital Outdoor
Spaces - Therapeutic Benefits And Design
[12] G
reen Guide for Health Care, Version 2.2, SS
Credit 5.1., Site Development: Protect or Restore
Open Space or Habitat, 2007, www.gghc.com,
p.6 23.
[13] Ulrich,
R.S., Cooper-Marcus, C., Barnes, M.
(Eds.), (1999), “Effects of Gardens on Health
Outcomes: Theory and Research, in Healing
Gardens: Therapeutic Benefits and Design
14 HINDUSTAN JOURNAL, VOL. 6, 2013
Recommendations”, John Wiley & Sons, New
York, pp. 27-86.
[14] V
irginia I. Lohr, Caroline H. Pearson-Mims,
and Georgia K. Goodwin, “Interior Plants
May Improve Worker Productivity and Reduce
Stress In A Windowless Environment”,
Department of Horticulture and Landscape
Architecture Washington State University,
Pullman, WA 99164-6414
[15] R
yan Hum and Pearl Lai (2007), “Assessment of
Biowalls: An Overview of Plant- and Microbial-
based Indoor Air Purification System”.
[16] W
ood, R.A., Burchett, M.D., Alquezar, R.,
Orwell, R.L., Tarran, J. and F. Torpy. (2006). “The
potted-plant microcosm substantially reduces
indoor air VOC pollution: I. office field-study”,
Water, Air, and Soil Pollution, 175, pp.163-180.
[17] P
rescod, A.W. (1992). “More indoor plants as air
purifiers”, Pappus, 11:4.
[18] U
nited States Environmental Protection Agency
(1991), “Sick building syndrome”, Air and
Radiation, Indoor Air Facts, 4.
HINDUSTAN JOURNAL, VOL. 6, 2013
A Research on Nuances of Silk Weaving and Designing a
Handloom Hub at Kanchipuram
Ar. Thulasi Gopal.
Abstract — The lost platform of silk weaving industry
in Kanchipuram has been identified in order to
bring back the lost glory of original silk weaving
techniques, process and products through down to
earth planning and designing patterns. A particular
community has been confined to these industries. The
idea of the silk parks with appropriate infrastructure
is to create awareness among others to take up
this profession. Deliberate research and extensive
interaction with the weaving community has gone
into evolving this design concept. The weaving
community was widely studied on their everyday
lifestyle, weaving activity, duration to complete each
activity, spacial organization, proximity of spaces
etc., in order to meet the requirements in the Silk
Park. Apart from these, the supporting activities
like cocoon reeling and dyeing activities and their
spaces were studied. Weaver’s psychology which
results in the sari designs, creativity etc., was taken
into account for giving a suitable design solution.
Emotions related to the occupational spaces resulted
in interior-exterior connectivity, to avoid solitude.
Traditional Kanchipuram weavers’ house and their
elements were studied to incorporate those features
into the design. The challenge in the output was
how all the versatile activities of silk weaving can be
designed under one roof, bringing in wholesomeness
through form, tone, style, texture, hue, and bringing
unity, balance and continuity. The design created
would provide people involved with a comfortable
living environment that they are longing for and
contribute to India’s gross domestic product.1
Index Terms — Silk Weaving, Handloom, Spatial
Organization, Design, Interior-exterior connectivity.
Ar. Thulasi Gopal is in School of Architecture,
Hindustan, Chennai, India, (e-mail: gopal.aarthi@
gmail.com)
I.
Introduction
Tamil Nadu has a rich cultural history and legacy that
spans several areas. All of these need to be preserved
for posterity as they remind the people of its enormity
and feat. It has a world class brilliances to showcase,
which needs to be nurtured and suitably promoted to
support the branding and economic outcomes.
One such craft that needs to be reinstated from a
declining trend is Silk weaving. India is the secondlargest Silk producer in the world, next to China and
major sourcing base for international retail players.
According to Tamil epic ‘Silapadikaram’ the Silk
handloom weaving activity is said to have existed
since second Century AD at Kanchipuram. It is one of
the traditional centers of Silk weaving and handloom
industries that is losing its identity.
The Scheme for Integrated Textile Park was
approved by Central Government of India to facilitate
setting up of Textile parks with world class infrastructure
and amenities. The Government of Tamilnadu has
proposed to bring a Silk park at Kanchipuram. Seventy
five acres of land allotted by the Government of Tamil
Nadu for the purpose is located at Kilkathirpur village,
Kanchipuram Taluk and District.
II. Constraints
The Silk and other textile industries are still community
driven i.e. a particular community is confined to these
industries. The idea of the Silk parks with appropriate
infrastructure is to create awareness among a lot of
others to take up this profession. This in turn keeps
the industry in the head front of Indian economic
development and increases the demand for Indian
textiles in International markets.
16 HINDUSTAN JOURNAL, VOL. 6, 2013
Sriperumbudhur industrial area is situated 35 kms
away from Kanchipuram which attracts people to work
there due to time flexibility, better income and less hard
work (when compared to weaving), suitable transport
facilities, allowances etc., provided by the companies
such as Hyundai, Nokia etc.
III. Objectives
The objectives of the project are
●● To design a prime handloom hub
●● T
o re-establish the traditional and cultural value of
ancient silk weaving which is the prime occupation
of the temple city and its surrounding villages and
village hamlets of Kanchipuram.
●● T
o encourage the occupation, by providing the
workers with better functioning environment and
resources that would take the economy of the rural
sector to a superior stature.
●● T
o bring back the lost platform for the weavers
to market their products, avoid duplicate market
players and also to showcase the culture.
IV. Methodology
The methodology proposed to be adopted are
●● Understanding the site surroundings and services.
●● Understanding the occupation and workplace.
●● Weavers’ needs/opinions through questionnaires.
●● Comparison of history against recent happenings.
●● T
echniques in the field to choose the best for
today’s scenario.
●● Requirement framing in detail.
●● C
ase study- comparative study of Ayangarkulam
(weaving village and Pillayarpalayam weaving
town).Analysis of the common and the contrasting
features and characteristics.
●● Formulating conceptual ideas.
●● D
evelopment of concepts into schemes and into
final design output.
V.
Scope and Nature of Activities in The
Complex
The spaces planned on site are: Administration and
expo hall, Research center and training, Marketing area,
Warehouse, Cocoon reeling, Garment unit, Canteen
and hostel , Dyeing unit –CETP, Weaving cluster,
Residential cluster, Central hub – OAT, health care,
child care., Restaurant, Guest house, Multipurpose
area, Temple along with the pond, and other Services.
The main focus in the design was given to the Dyeing
cluster, Weaving cluster and the Residential Cluster.
VI. Challenges Faced
The challenges faced include
●● Bringing in different activities in one complex.
●● Bringing wholesomeness in the design.
●● Creating buffer spaces between each block.
●● Proximity between all the spaces.
●● Connectivity and flow of functions.
●● S
egregating the different residential, floating,
working and shopping population.
●● Meeting the workplace requirements.
●● Innovations for enhanced productivity of silk
products.
VII. Analysis Along With Evolution
of Design
Deliberate research and extensive interaction with the
weaving community has gone into evolving this design
concept. Their needs have been understood and have
been approached accordingly.
The site, on entry, will have the administrative
blocks, followed by the marketing blocks with a
research and testing center. This is to facilitate effective
marketing of the products as well as to ensure the
quality of the products. There is an industry, behind
the marketing area, which is to produce woven Silk
garments. The need for original silk sarees is decreasing
day by day and hence the requirement of the weavers
too is receding. To change this situation, silk can be
used to produce various other useful garments, apart
from sarees. They can be in accordance with the current
trends in fashion. This will escalate the demand for
woven silk garments which will in turn increase the
demand for the weavers.
THULASI GOPAL:A RESEARCH ON NUANCES OF SILK WEAVING 17
After a detailed discussion with the village weavers,
it was found that they are not very keen with the idea
of shifting to a new alien location. Hence the design is
done in such a way so as to provide them with the most
homely environment possible.
The weaving looms customized is specific to match
the needs of the Kanchipuram weavers. The houses
planned in the Silk Park are categorized into two main
styles, as per the requirements of the weavers. After
documentation, observation and analysis with the
weaving community of Kanchipuram, it was understood
that they are broadly segregated into two groups, based on
their economic needs. The houses have been constructed
in such a way so as to cater to their needs.
One of the concepts adopted by the earth institute
at Auroville is CSEB – Compressed Stabilized Earth
Blocks. The soil at the site was observed to be sandy
clayey soil, one such type of soil which is used for
making CSEB blocks which can be used for construction.
This does not require any skilled labours at work, and
hence can be a source of income to the local dwellers,
who necessarily are not weavers, surrounding the site.
As mentioned, the site is located 7 km away from the
original weaving society; hence the locales here too
will have an opportunity to gain through employing the
concept. A large water body, for example, a typical pond
is created that facilitates water distribution to different
areas on site through the tank which is a focal feature on
site. The mud evacuated to create these water bodies will
be used for CSEB block making. Burnt bricks replaced
by CSEB blocks provide a sustainable concept.
There are farming areas around each housing
sectors, which will enable food production. This
offers them an additional source of income, as well
as an alternate food source. There are green areas
designed all around the site which acts as a buffer
space, segregating the diversified functions involved
in weaving a saree.
The central focus of this site is a multipurpose area
with a temple, a water body, commercial spaces, which
will provide the platform necessary for the weavers
to hold fares. It is to break the monotonous weaving
routine and to provide them with some relaxation. The
fares are also a means of interaction and communication
with weaving communities from other districts and
states. Thus holding fares and exposition summons
collaborative work from other communities, along with
exchange of various important ideas and tools, which
will not only improvise the silk weaving techniques but
also make them aware of the current trends in the market.
All the silk saree shops can be shifted under the silk
society’s supervision so that adulteration is minimized
and originality is maintained. Training centers can be
proposed with Government certified courses on silk
weaving to attract younger generation into this activity,
Fig.1, 2 and 3 describe the process, design features
and the concepts adopted respectively in regard to the
proposal of the handloom hub at Kanchipuram.
VIII. CONCLUSION
Combination of traditional and contemporary
architecture is done which targets site planning level to
weaving machine design customized for the weavers.
Macro level to micro level planning is undertaken.
Material from site is used for construction which can
involve local dwellers who can be benefited apart from
the main target - the weavers. Dyeing areas which were
earlier inside the Kanchipuram towns causing pollution,
will be shifted here where the CETP is set up to solve the
issue of pollution. Considering the hot humid climate,
features like courtyard have been adopted to give a
natural day lighting and stack effect thus maintaining
a suitable indoor environment. Better workspace is
created which will result in better productivity. Efficient
usage of energy, water, and other resources is seen.
Measures are taken to protect occupants health and
improve employee productivity. Maximum reduction
in waste, pollution and environmental degradation is
seen into. CSEB blocks, which are green materials are
extensively used in the construction.
BIBILIOGRAPHY
http://www.silkclick.com
http://www.csapl.co.in/industrial.asp
http://www.thehindu.com/todays-paper/tp-national/
tp-tamilnadu/site-identified-for-silk-park-inkancheepuram/article168017.ece
http://www.kanchipuramdistrict.com/
http://smehorizon.sulekha.com/advancementmade-panipat-weaving-industry-sustain_textilesviewsitem_8253
http://www.oldandsold.com/articles04/textiles16.shtml
http://environmental_impact_assessment
Fig. 1. Silken Archinomy - The process
18 HINDUSTAN JOURNAL, VOL. 6, 2013
Fig. 2. Sliken Archinomy - Design Features
THULASI GOPAL:A RESEARCH ON NUANCES OF SILK WEAVING 19
Fig. 3. Silken Archinomy - Concepts Adopted
20 HINDUSTAN JOURNAL, VOL. 6, 2013
HINDUSTAN JOURNAL, VOL. 6, 2013
A Case for the Development of High Speed Rail Link in India
D. Karthigeyan
Abstract — Indian Railways is an Indian stateowned enterprise, owned and operated by
the Government of India through the Ministry of
Railways. It is one of the world’s largest railway
networks comprising 115,000 km (71,000 mi) of
track over a route of 65,000 km (40,000 mi) and
7,500 stations. India is a country with more than
1.2 billion population, which includes 35 cities with
more than 1 million people each as per Census 2011.
Its urban population is increasing day by day, and
the rail network forms the lifeline of the country,
where majority of the people are poor and cannot
afford to travel by air. Under these circumstances,
India which is aiming to become a global super
power by 2050 requires high speed rail network
similar to China, which has the world’s largest
high speed railway network of more than 10,000
km. In this context, India needs to have a quality
and affordable high speed rail network for its poor
people to connect its major metropolitan areas
and to decongest the which are transforming to
megalopolition areas.1
list of countries which currently have a commercial
high speed rail network. The average speed of trains in
developed nations is around 200 kmph whereas in India,
the maximum speed of any train hardly exceeds 150
kmph. Rajdhani and Shatabdi are among the fastest trains
which run nearly at a speed of 120 kmph. On the other
hand, India’s neighbour China has built world’s largest
high speed railway network of about 10,463 Km long
[2]. China also has the largest single track length between
Beijing and Guangzhou which is 2,298 km. China has
world’s fastest trains running at the speed of 380 kmph.
It is surprising to see that the high-speed railway network
in China was developed in a short span of five years. The
proposal for high speed trains had come to fore in 1990 in
that country and work had started in 2007.
Index terms — High speed rail network, Bullet train,
Transportations.
I. Introduction
High-speed rail is a type of rail transport that operates
significantly faster than traditional rail traffic, using
an integrated system of specialized rolling stock and
dedicated tracks. The first such system began operation
in Japan in 1964 and was widely known as the bullet
train. Even though India has one of the world’s largest
railway networks, it is yet to find itself a place in the
D. Karthigeyan is in School of Architecture, Hindustan
University, Chennai, India, (e-mail: dkarthikeyan@
hindustanuniv.ac.in)
Fig. 1. High speed rail in China
In 2015 China will have 18,000km of high speed
rail. Just five years after China’s high-speed rail system
opened. It is carrying nearly twice as many passengers
each month as the country’s domestic airline industry.
With traffic growing at 28 percent a year for the last
several years, China’s high-speed rail network will
handle more passengers by early next year than the 54
million people a month who board domestic flights in
the United States.
22 HINDUSTAN JOURNAL, VOL. 6, 2013
China’s high-speed rail system has emerged
as an unexpected success story. Economists and
transportation experts cite it as one reason for China’s
continued economic growth when other emerging
economies like India are faltering due to the global
economic slowdown.
Chinese workers are now more productive.
The productivity gains occur when companies find
themselves within a couple of hours’ of train ride of
tens of millions of potential customers, employees
and rivals. Companies are opening research and
development centers in more glamorous cities like
Beijing and Shenzhen with abundant supplies of
young, highly educated workers, and having them take
frequent day trips to factories in cities with lower wages
and land costs, like Tianjin and Changsha. Businesses
are also customizing their products more through
frequent meetings with clients in other cities, part of a
broader move up the ladder toward higher value-added
products.
Airlines in China have largely halted service on
routes of less than 300 miles when high-speed rail links
open. They have reduced service on routes of 300 to
470 miles. The double-digit annual wage increases give
the Chinese enough disposable income that domestic
airline traffic has still been growing 10 percent a year.
Currently, China’s high-speed rail service costs
significantly less than similar systems in developed
countries, but is considerably more expensive than
conventional rail service. For the 419 km trip from
Beijing to Jinan, High Speed Rail costs US$30 and
takes 1 hour 32 minutes, while a conventional train
costs US$12 and takes about 6 hours. By comparison,
the Acela train from Washington DC to New York City
covering a slightly shorter distance of 370 km costs
US$152–180 and takes 2 hour 50 minutes [3].
Chinese government have a major plan with
respect to high speed rail network, by connecting
it to the whole of Asia and European Continent, so
that all its freight travel will happen through this
network, which in turn will make the Chinese a
global leader in the trade and commerce. In this
connection, Chinese government even plans to build
a high-speed rail line connecting its south-western
city of Kunming to New Delhi and Lahore, part of a
17-country transcontinental rail project which is part
of its pan-Asian high-speed rail link. After many
years of negotiations with other Asian countries,
China has finally reached agreements with several
Central Asian countries and got the green signal to
its ambitious pan-Asian high-speed rail link, which
envisages connecting cities in China to Central Asia,
Iran, Europe, Russia and Singapore.
II. High Speed Rail Network
There is no standard or a global definition for it;
however, there are certain parameters that are unique to
high-speed rail, which are
●● U
IC (International Union of Railways) and EC
Directive 96/58 define high-speed rail as systems
of rolling stock and infrastructure which regularly
operate at or above 250 km/h (155 mph) on new
tracks, or 200 km/h (124 mph) on existing tracks.
However lower speeds can be required by local
constraints.
●● A
definitive aspect of high speed rail is the use
of continuous welded rail which reduces track
vibrations and discrepancies between rail segments
enough to allow trains to pass at speeds in excess of
200 km/h (124 mph).
●● D
epending on design speed, banking and the forces
deemed acceptable to the passengers, curve radius
is above 4.5 kilometres (2.8 mi) and for lines
capable of 350 km/h (217 mph) running, typically
at 7 to 9 kilometres (4.3 to 5.6 mi).
A. Parameters of A High Speed Travel:
●● The frequency of service,
●● Regular-interval timetables,
Fig. 2. China’s Pan-Asian high-speed rail link
●● A high level of comfort,
KARTHIGEYAN:A CASE FOR THE DEVELOPMENT OF HIGH SPEED RAIL 23
●● A
pricing structure adapted to the needs of
customers,
improve transportation efficiency and to conserve the
depleting resources.
●● Complement with other forms of transport,
High speed rail network is the best choice for
distances of 500-700 km, where airlines cannot match;
below 200 km, road transport has an edge; beyond
1,000 km, air option may be better.
●● More on-board and station services.
III.Indian Government Context
Fig. 3. Inside first class cabin of high speed train in France
In India, high speed trains are often referred to as “bullettrains”. One of the first proposals by the Government of
India to introduce high-speed trains was mooted in the
mid-1980s by then Railway Minister. A high speed rail
line between Delhi and Kanpur via Agra was proposed.
An internal study found the proposal unviable at that
time due to the high cost of construction and inability of
travelling passengers to bear much higher fares than what
was changed for normal trains. The Railways instead
introduced Shatabdi trains which ran at 130 km/h.
B. On The Eco-Friendly Atmosphere:
●● T
ransport is responsible for 25% of the world’s
carbon dioxide (Co2) emissions, with 80 – 90%
coming from cars and highway trucks, and only 2
% from rail.
●● O
n high-speed railways the energy consumption
per passenger-kilometer is three and half times less
than for a bus, five times less than for air and ten
times less than for a private car.
●● T
he social cost of noise, dust, carbon dioxide, nitric
oxide and sulfur oxide emission for high-speed rail
is one fourth of road transport and one-sixth for air.
●● I t requires the construction of an eight-lane
highway to provide the same capacity as a double
track high-speed railway line [1].
Worldwide concerns over depleting fossil fuel
reserves, climate change, overcrowded airports, delayed
flights and congested roads have conspired with the
high speed rail technology as the only alternative.
High speed rail entails much less land usage than
motorways: a double track rail line has more than thrice
the passenger carrying capacity of a six-lane highway
while requiring less than half the land.
India is a relatively small country with a huge
population and it will be too costly to build highways
so high-speed rail network will be a better option to
Fig. 4. Potential high speed rail corridors in India
The Indian Ministry of Railways’ in its whitepaper Vision 2020 submitted to the Parliament on
December 2009 envisages the implementation of
regional high-speed rail projects to provide services at
250-350 km/h, and planning for corridors connecting
commercial, tourist and pilgrimage hubs. Six corridors
have already been identified and feasibility studies
have been started,
1. Delhi-Chandigarh-Amritsar, 2. Pune-Mumbai-Ahmadabad,
24 HINDUSTAN JOURNAL, VOL. 6, 2013
3. Hyderabad-Dornakal-Vijayawada-Chennai, 4. Howrah-Haldia, 5. Chennai-Bangalore-Coimbatore-Ernakulam, 6. Delhi-Agra-Lucknow-Varanasi-Patna.
These high-speed rail corridors will be built as
elevated corridors in keeping with the pattern of
habitation and the constraint of land.
Two new routes were later proposed by Indian
Railways, namely ●● A
hmadabad - Dwarka, via Rajkot, Jamnagar and
the other from Rajkot to Veraval via Junagadh [4]
A. Approach to High-Speed
Indian Railways’ approach to high-speed is on
incremental improvement on the existing conventional
lines for up to 200 km/h, with a forward vision of speed
above 250 km/h on new tracks with state-of-the-art
technology.
B. Upgrade Tracks for 160-200 Km/H
The approach is to upgrade the dedicated passenger
tracks with heavier rails, and build the tracks to a close
tolerance geometry fit for 160-200 km/h. High-speed
tracks to be maintained and inspected using automation
to ensure required track geometry. There is a need
to perform more frequent inspection to ensure high
confidence of safety at high-speed.
C. Likely Initial Lines
In India, trains in the future with speed of 250-350 km/h,
are envisaged to run on elevated corridors, to prevent
trespassing by animals and people. This is an excellent
way to isolate high-speed train tracks.
D. Project Execution
The cost of building high speed rail tracks is about Rs
70 crore/km (U$15.6m/km), compared with Rs 6 crore/
km of normal rail tracks.
will exclusively deal with the proposed ambitious high
speed rail corridor projects. It will handle tendering,
pre-feasibility studies, awarding of contracts and
execution of the projects. All high-speed rail lines will
be implemented through public private partnership
(PPP) mode on a Design, Build, Finance, Operate and
Transfer (DBFOT) basis.
IV. Prospect of High Speed Train Operation
in India
Mumbai – Ahmadabad rail line is likely to be the
first high speed rail network project in India which
the central government plans to take in the next five
year plan. Central Government is likely to make
some important announcements on this project in
the upcoming Budget session of the Parliament,
and the state government of Maharashtra is keeping
its fingers crossed as till now the share between
the centre and the state government is yet to be
announced.
Both France and Japan Governments have shown
interest in this line which covers a distance of 500
kilometers (312 miles) and expected to cost around
Rs.65,000 crores. Both the governments have taken a
feasibility study and are likely to submit the report by
March 2014. Both the governments are hopeful, that
their technology will be utilized in building this high
speed rail network. Their feasibility study includes
defining “high speed” for India (which could be 300350 km per hour), the fares and the finance practices,
including public-private partnerships.
On the technology front, what separates the French
high-speed train technology from the Japanese, who
pioneered the system, is that TGV trains of France
could be operated at a normal speed (160 kmph), and
on special sections, shifted to peak speeds. This made
it possible to integrate them easily with the existing
railways. Costs are high for such systems but when
supplied with cheap Indian labor the total cost will
come down drastically.
E. High Speed Rail Corporation of India Ltd
Indian Railways set up a corporation called High Speed
Rail Corporation of India Ltd (HSRC) in July 2012 that
Fig. 5. Rail link from Mumbai to Ahmadabad
KARTHIGEYAN:A CASE FOR THE DEVELOPMENT OF HIGH SPEED RAIL 25
The quickening pace of commercial co-operation
comes with India and Japan -- both democracies
-- eyeing the rise of China with increasing unease,
as Beijing presses territorial claims with growing
insistence [5]
With this regard, Japan has already submitted its
final report of the feasibility study on upgrading the
speed of the existing Mumbai-Ahmadabad route to
160-200 km per hour and further consultations on the
report between the two countries are on.
V. Benefits in The Indian Context
In India, out of all the benefits, discussed earlier,
the reduced journey time has been the overriding
consideration in the adoption of high-speed rail work.
On the basis of the current experiences in the world, it
has been observed that when the distances are between
300 to 600 Km, and the travel time by the high-speed
train is less than 2 – 2.5 hours, the market share of
passengers for the high-speed rail is at least 75-80%.
This percentage decreases dramatically when the travel
time of train increases to 4 to 5 hours and a round trip
during the day is not possible.
High speed train operation will play a significant
role in the de-congestion of megalopolis towns of
Delhi, Kolkata, Mumbai, Chennai, etc. Operationally,
high-speed trains can optimally connect cities 500 to
1,000 km apart, and in one of the best-known sectors,
Paris-Lyon, the peak capacity is 12,000 passengers per
hour at 1,000 people per train, providing service once
in four minutes.
VI. Conclusion
Once the Indian government decides, it should not take
more than 4-5 years to have high-speed trains running
on Indian soil. The benefits for a common man will be
like,
●● W
ith less than one hour of journey time, it will
then be possible to live in the salubrious climate of
Chandigarh and commute to Delhi for work.
●● A
bullet train between Bangalore and Mysore
(about 88 miles) will decongest Bangalore and
one can reach Mysore in 30 minutes. This train
will bridge the travel time between Bangalore and
Mysore and pave way for their development as
twin cities.
●● H
igh-speed rail lines from Bangalore to Chennai
(180 miles) are also under discussion by the
Government of India. Then we might reach
Chennai within an hour from Bangalore by the
surface transport. [6]
References
[1] M
undrey, “Tracking for High speed trains in
India”, January, 2010, RITES Journal.
[2] h ttp://zeenews.india.com/news/world/china-shigh-speed-bullet-train-network-exceed-10-000km_879426.html
[3]
h ttp://www.globalresearch.ca/eurasian-economicboom-and-geopolitics-china-s-land-bridge-toeurope-the-china-turkey-high-speed-railway
[4] h ttp://www.mapsofindia.com/railways/highspeed-rail-corridors.html
[5] h ttp://www.ibtimes.com/next-stop-bangalorejapan-may-help-south-india-build-high-speedrail-system-1408542
[6]
h ttp://www.indianexpress.com/news/india-japanto-study-highspeed-rail-feasibility/1134280/
HINDUSTAN JOURNAL, VOL. 6, 2013
HMAC Filtering Scheme for Data Reporting in
Wireless Sensor Network
E. Kodhai, P. Bharathi and D. Balathiripurasundari
Abstract — Wireless Sensor Networks consist of a large
number of small sensor nodes, high processing power,
limited in usage of efficient security mechanisms and
susceptible to possible node compromise, passive
and active attacks. These restrictions make them
extremely vulnerable to a variety of attacks. Mostly
public key cryptographic techniques are found to be
more work prone with the secure exchange of keys,
mainly lengthy hash operations with high processing
rounds etc. Even though these techniques do not
provide adequate verification process of reports from
source to sink, they do not completely mitigate false
report injection attacks and Denial of Service attacks.
In this work we propose a HMAC’ed filtering scheme
for secure transmission of data and we propose a
technique called encryption of combined hashes which
filters bogus reports and then specifically addresses
false report injection attacks and Denial of Services.
It has three phases which are Key Pre-distribution,
Key Dissemination and Report Forwarding Phase.
The legitimacy of the report being forwarded by the
cluster head is collectively endorsed by a preset value
and achieved by Message Authentication codes. In
our proposed scheme the increase in performance is
achieved through control messages, increasing secure
data transmission and addressing false data reports.1,2
Index Terms — Wireless Sensor Network, mobile
relay nodes, wireless routing, bandwidth, energy
consumption.
E. Kodhai and P. Bharathi are in Department of
Information Technology, Sri Manakula Vinayagar
Engineering College, Pudhucherry, India. (e-mail:
[email protected], [email protected])
D. Balathiripurasundari is in DotNet TCS Corporate,
Chennai. (e-mail: [email protected].)
I.  Introduction
Sensor networks are dense wireless networks which
are small in size, very low-cost and which collect and
disseminate environmental data. Wireless Sensor
Networks (WSNs) facilitates monitoring and controlling
of physical environments from remote locations with
better accuracy. They have applications in a various
fields such as environmental usage, military requirement
and gathering sensing information in inhospitable places.
Sensor nodes have various energy and calculating
constraints because of their inexpensive nature and ad
hoc method of deployment.
The number of nodes in a WSN is usually much
larger than that in an ad hoc network. Sensor nodes
are more resource constrained in terms of power,
computational capabilities, and memory. Sensor nodes
are typically randomly and densely deployed (e. g., by
aerial scattering) within the target sensing area. The postdeployment topology is not predetermined. Although in
many cases the nodes are static in nature, the shape and
size might change frequently because the sensor nodes
and the wireless channels are prone to failure.
II.  System Model
Some of the existing schemes for Filtering False
Reports in WSN are Statistical En-route Filtering
(SEF), Interleaved hop-by-hop authentication (IHA)
and Providing Location aware End- to-End Data
Security (LEDS). The details of these techniques are
discussed briefly in the following sub-sections.
A.  Statistical En-route Filtering (SEF)
Ye et al. [12] proposed a statistical En-route filtering
(SEF) scheme based on probabilistic key distribution.
KODHAI ET AL.: HMAC FILTERING SCHEME FOR DATA REPORTING 27
In SEF, a global key pool is divided into n partitions,
each containing m keys. Every node randomly picks k
keys from one partition. When some event occurs, each
sensing node (that detects this event) creates a Message
Authentication Code (MAC) for its report using one
of its random keys. The cluster-head aggregates the
reports from the sensing nodes and guarantees each
aggregated report contains T MACs that are generated
using the keys from T different partitions, where T is a
predefined security parameter. Given that no more than
T-1 nodes can be compromised, each forwarding node
can detect a false report with a probability proportional
to 1/n. The filtering capacity of SEF is independent
of the network topology, but constrained by the value
of n. To increase the filtering capacity, we can reduce
the value of n , however, this allows the adversaries to
break all partitions more easily. In addition, since the
keys are shared by multiple nodes, the compromised
nodes can impersonate other nodes and report some
forged events that “occur” in other clusters.
B.  Interleaved Hop-By-Hop Authentication (IHA)
Zhu et al. [13] proposed an interleaved hop by hop
authentication (IHA) scheme. In this scheme, the
base station periodically initiates an association
process enabling each node to establish pair wise
keys with other nodes that are t+1 hops away, where
t is called the security threshold value. In IHA, each
sensing node creates a MAC using one of its multihop
pairwise keys, and a legitimate report should contain
t+1 distinct MACs. Since every multihop pairwise
key is distinguishable, IHA can tolerate up to t level
compromised nodes in each cluster instead of in the
whole network as SEF does. However, IHA requires
a fixed path for transmitting control messages between
the base station and each cluster-head, which cannot
be assured by some routing protocols such as GPSR
and GEAR. Moreover, the high communication
overhead incurred by the association process makes
IHA unsuitable for networks whose topologies change
frequently.
C.  Providing Location Aware End- To-End
Data Security
Providing Location aware End-to-End Data Security
(LEDS) design overcomes the limitations of the existing
hop-by-hop security paradigm and achieves an efficient
and effective end-to-end security paradigm in WSN. It
exploits the static and location-aware nature of WSNs,
and proposes a novel location-aware security approach
through two seamlessly integrated building blocks: a
location-aware key management framework and an
end-to-end data security mechanism. In this method,
each sensor node is implemented with several types of
balanced secret keys, some of which are intended to
provide end-to-end data confidentiality, and others are
to provide both end-to-end data authenticity and hopby-hop authentication. All the keys are measured at
each sensor node independently from keying materials
pre-loaded before network deployment and the location
information is obtained after network disposal, without
inducing new communication overhead, for shared key
establishment.
III.  Problem Definition
Each of the existing schemes for Fig. 1. Statistical
En-route Filtering (SEF), interleaved hop-by-hop
authentication (IHA) and Providing Location aware
End- to-End Data Security address false report
injection attacks and or DoS attacks. However they all
have some constraints. SEF is independent of network
shape and size, but it has a limited number of filtering
capacity and cannot prevent impersonating attacks on
legitimate nodes. IHA has a drawback, that is, it must
periodically establish multihop pair wise keys between
nodes. Further, it refers to a located path between the
base station and each cluster-head to transmit messages
in both directions, which cannot be assured due to the
dynamic topology of sensor networks or due to the use
of some underlying routing protocol.
LEDS utilizes location-based keys to filter false
report. It assumes that sensor nodes can determine
their locations in a short period of time. However, this
is note practical approach, because many localization
approaches take quite long and are also vulnerable
to malicious attacks. It also tries to address selective
forwarding attacks by allowing a whole cell of nodes
to forward one report; however, this incurs high
communication overhead.
Later, we have discussed the routing protocol
AODV on which the proposed scheme is to be
executed. AODV takes care of the route discovery
and maintenance process thereby easing the proposed
scheme to concentrate on the En-route filtration
28 HINDUSTAN JOURNAL, VOL. 6, 2013
capacity and the mitigation of false report injection
attacks and DoS attacks.
A.  Introduction
IV.  Design
In this chapter we describe our proposed security scheme
called HMAC’ed Filtering Scheme for Data Dissemination
in WSN. This scheme addresses false report injection
attacks and DoS attacks such as Selective forwarding
and Report disruption in WSN. The multifunctional key
management framework is used in this scheme which
involves authentication keys. Similar to SEF and IHF
discussed in section 3 our proposed En-route filtering
scheme also uses the key distribution mechanism
employed in WSN. Unlike other schemes which either
lack strong filtering capacity or cannot support highly
dynamic sensor networks, our scheme uses a hash chain
of authentication keys which are used to endorse reports.
Meanwhile, a legitimate report should be authenticated by
a certain number of nodes. First each node disseminates its
key to forwarding nodes. Then, after sending reports, the
sending nodes disclose their keys, allowing the forwarding
nodes to verify their reports. It can be explained with the
help of the following figure 1.
encrypt the authentication keys which are collectively
used for producing MAC of the report and later used
for the report’s collective endorsement.
B.  Problem Formulation
The vast targeted terrain where the sensor nodes are
deployed is divided into multiple cells after network
deployment. We assume that sensor nodes within a cell
form a cluster which contains n nodes. In each cluster
of a cell a node is randomly selected as a cluster head
as in figure 2. When an event of interest happens in any
of these cells, the sensing nodes of that particular cell
detects the event and broadcasts it to the cluster head.
The cluster head aggregates the reports and forwards
the aggregated report through the report authentication
area down to the sink. The topologies of WSNs change
frequently either because nodes are prone to failure or
because they need to switch their states between Active
and Sleeping for saving energy. As sensor networks
are not tamper-resistant, it can be compromised
by adversaries. Each cluster may contain some
compromised nodes, which may in turn collaborate
with each other to generate false reports by sharing the
secret key information. In this project work we intend
to provide solutions for attacks like bogus data injection
and denial of services (selective forwarding attack &
report disruption) that can be launched by adversaries
to degrade node’s life time and the critical information
carried by them.
Fig. 1. Key Derivation
Under this scheme control messages are used
to disseminate and disclose the keys to forwarding
sensor nodes and later allow nodes to verify the keys
by decrypting them and finding a shared secret key. To
accomplish this every sensor node maintains 2 secret
key pools and a seed key. A series of authentication
keys can be derived from this seed key when there is
a need. Hence when a shared secret key is found its
corresponding authentication keys are derived and
stored in the memory of sensor nodes. Thus the keys
selected randomly from the key pools are used to
Fig. 2. Cluster Formation and report forwarding
Route to Sink
We consider
N- Total no. of nodes present in the targeted terrain
n- Average no. of nodes in each cell
KODHAI ET AL.: HMAC FILTERING SCHEME FOR DATA REPORTING 29
l- Size of the cell
t- no. of correct endorsements to validate a report
x- no. of compromised nodes in a cell
Cluster head intimates events to sink periodically
and finds a routing path called Report Forward Route.
We consider that x nodes inject malicious data to
reports periodically to drain out battery life. These x
nodes inject bogus data by simply offering a wrong
MAC to the collective endorsement. Due to the wrong
MAC in t endorsements the legitimate event report has
the possibility of being dropped by a legitimate node
or even a legitimate report share can be dropped by
an adversary near to the sink which is called Report
Disruption attack. When multiple clusters disseminate
keys at the same time, some forwarding nodes need to
store the authentication keys of different clusters. Hence
the nodes closer to the base station need to store more
authentication keys than others do because they are
usually the hot spots and have to serve more clusters.
Our aim is thus to mitigate the false data injection at
early route with minimal overhead, improved network
life time, confidentiality and authentication.
report contains distinct MACs depending upon the
number of the cluster members.
In our scheme, each node possesses a sequence
of auth-keys that form a hash chain. Before sending
the reports, the cluster-head disseminates the first
auth-keys of all nodes to the forwarding nodes that are
located on multiple paths from the cluster-head to the
base station. The reports are organized into rounds,
each containing a fixed number of reports. In every
round, each sensing node chooses a new auth-key to
authenticate its reports.
To facilitate verification of the forwarding nodes,
the sensing nodes disclose their auth-keys at the end of
each round. Meanwhile, to prevent the forwarding nodes
from abusing the disclosed keys, a forwarding node can
receive the disclosed auth-keys, only after its upstream
node overhears that it has already broadcast the reports.
Receiving the disclosed keys, each forwarding node
verifies the reports, and informs its next-hop node to
forward or drop the reports based on the verification
result. If the reports are valid, it discloses the keys to its
next-hop node after overhearing.
C.  Design of the Project
There are 3 phases involved in the project and the
relationships between them are shown in figure 3.
Fig. 3. Relationship between phases
When an event occurs within some cluster, the
cluster-head collects the sensing reports from sensing
nodes and aggregates them into the aggregated reports.
Then, it forwards the aggregated reports to the base
station through a set of forwarding nodes. In our
scheme, each sensing report contains one MAC that
is produced by a sensing node using its authentication
key (called auth-key for short), while each aggregated
Fig. 4. Overall process of key distribution and Report Forwarding
The processes of verification, overhearing, and
key disclosure are repeated by the forwarding nodes
as shown in figure 4 at every hop until the reports are
dropped or delivered to the base station. Specifically,
our scheme can be divided into three phases: (i) key
pre-distribution phase, (ii) key dissemination phase,
and (iii) report forwarding phase. In the key pre-
30 HINDUSTAN JOURNAL, VOL. 6, 2013
distribution phase, each node is preloaded with a
distinct seed key from which it can generate a hash
chain of its auth-keys. In the key dissemination phase,
the cluster-head disseminates each node’s first authkey to the forwarding nodes, which will be able to filter
false reports later. In the report forwarding phase, each
forwarding node verifies the reports using the disclosed
auth-keys and disseminated ones. If the reports are
valid, the forwarding node discloses the auth-keys
to its next-hop node after overhearing that node’s
broadcast. Otherwise, it informs the next-hop node to
drop the invalid reports. This process is repeated by
every forwarding node until the reports are dropped or
delivered to the base station.
where K (n) is the authentication message collected by
CH from the sensing nodes and aggregated to K (n).
D.  Algorithm
2. T
o verify the authenticity of the authentication
keys in K (t), υj checks if each authentication
key it stored can be generated by hashing a
corresponding key in K (t) in a certain number of
times. If not, it is either replayed or forged and K
(t) should be dropped.
STEP 1: Cluster Head (CH) collects sensing reports as
in figure 4, from sensor nodes and generates a
number of aggregated reports.
R1, R2, R3
CH sends these aggregated reports plus an OK
message to next hop υj.
Aggregated report must contain t Message
Authentication Codes (MACs) from each sensing node
with a distinct Z key. Aggregated report R looks as
follows.
R={r(υi ),...,r(υi )}.
t
1
where υi ,...,υi denote t sensing nodes.
1
t
Since every sensing node reports the same event
information E, only one copy of E is kept in the
aggregated report R.
STEP 2: Receiving the aggregated reports and OK,
υj forwards them to next hop, υj +1. CH
overhears the broadcast of aggregated reports
from υj.
STEP 3: Overhearing the broadcast from υj, the CH
discloses the authentication keys to υj by
message K (t)
K(t) = {Auth(υi ),..., Auth(υi )}
1
t
where K (t) contains authentication keys of υi ,...,υi .
1
t
It has the same format as K (n), but contains only t
authentication keys.
STEP 4: Receiving K (t), υj first checks the authenticity
of disclosed keys using the disseminated ones
that it decrypted from K (n) earlier. Then,
it verifies the integrity and validity of the
reports by checking the MACs of the reports
using the disclosed keys.
V.  Verification Process
1. T
o verify the validity of K (t), υj checks if K (t) is
in correct format and contains t distinct indexes of
z- keys (secret keys picked randomly from global
key pool Z). If not, it drops K (t).
3. T
o verify the integrity and validity of reports R1,
R2… υj checks the MACs in these reports using
the disclosed authentication key that it decrypts
from K (t).
STEP 5: If the reports are valid, υj sends an OK
message to υj +1. Otherwise it informs υj +1
to drop invalid reports.
STEP 6: Similar to step 2, υj +1 forwards the reports
to next hop.
STEP 7: Similar to step 3, after overhearing the
broadcast from υj +1, υj discloses K (t) to υj
+1.
STEP 8: Every forwarding node repeats step 4 to step
7 until the reports are dropped or delivered to
the base station.
VI. Simulation Results
A.  Introduction
In this section, we will start with an introduction to the
simulation tool called NS-2, the ways of configuring it
KODHAI ET AL.: HMAC FILTERING SCHEME FOR DATA REPORTING 31
to run sensor networks, and implementation details of
the Enroute filtering scheme.
B.  Simulation Tool
3. C
onfiguration of Phenomenon node’s pulse rate
and phenomenon type.
4. Configuration of Sensor nodes.
5. Attaching sensor agents.
NS-2 is an event driven network simulator developed at
University of California at Berkeley, USA, as a REAL
network simulator projects in 1989 and was developed
with the cooperation of several organizations. NS is not
a finished tool that can manage all kinds of network
model. It is actually still an on-going effort of research
and development.
6. A
ttaching UDP agent and sensor application to
each node.
NS is a discrete event network simulator where the
timing of events is maintained by a scheduler and able
to simulate various types of network such as LAN and
WPAN according to the programming scripts written
by the user. Besides that, it also implements a variety of
applications, protocols such as TCP and UDP, network
elements such as signal strength, traffic models such as
FTP and CBR, router queue management mechanisms
such as Drop Tail and many more.
Implementation Details Of HMAC’ed Filtering
Scheme
There are two languages used in NS-2; C++
and OTcl (an object oriented extension of Tcl). The
compiled C++ programming hierarchy makes the
simulation efficient and execution times faster. The
OTcl script which is written by the users models the
network with its own specific topology, protocols and
all requirements needed. The form of output produced
by the simulator also can be set using OTcl. The OTcl
script is written creating an event scheduler object and
network component object together with network setup
helping modules. The simulation results produced after
running the scripts can be used either for simulation
analysis or as an input to graphical software called
Network Animation (NAM).
7. Starting the Phenomenon node.
8. Starting the Sensor Application.
Implementation Of Md5 Hashing Technique
MD5 Hashing technique is used to produce hash of the
sensor report. To accomplish this task MD5 algorithm
is implemented in tcl script for NS-2 simulation. The
steps describing its process are listed below
1. Append the padding bits
2. Append length
3. Initialize the Message Digest buffer
4. Process the message in 512 bit blocks
5. Resultant 128 bit Message Digest.
Implementation of Key Comparison Process and
Report Delivery
1. C
onfiguration of Phenomenon channel and Data
channel.
As the reports are sent in rounds containing distinct n
number of reports, it is not needed to send the whole
K (t) which contains all the first authentication keys
of the sensor nodes. Instead we can send alone the n
number of t authentication keys which will now enable
faster deciphering of the MAC-ed reports. In order to
filter the false packets at the earlier route, this K (n) is
discarded in the nodes nearer to the sink. The above
said process is accomplished in the following ways.
Keys are randomly picked up from a matrix and they
are used for producing HMAC of the report. The cluster
head now receives all the first authentication keys from
the cluster members packs them in K (n) and sends to
the Report forwarding nodes.
2. C
onfiguration of Phenomenon nodes with the
PHENOM “routing” protocol.
The Cluster members sense the events and produce
HMAC of the report and then send them collectively
Configuration of sensor network simulations:
Setting up a sensor network in NS-2 follows the same
format as mobile node simulations. Places where
sensor network simulations differ from a mobile node
simulation are listed below.
32 HINDUSTAN JOURNAL, VOL. 6, 2013
to Cluster Heads. The Cluster head now collectively
endorses the received HMAC’s with the preset value.
The comparison of keys in K(n) and the key obtained
from HMAC ’ed report are verified and forwarded by
the cluster heads to their one hop report forwarding
nodes. When the HMAC offered by a sensor node is
found to be illegitimate, i. e. , if the key found in the
HMAC is different from the collectively endorsed
report, cluster head marks node as attacker which is
shown in Figure 5.
Simulation Environment
The proposed secure scheme of Dynamic enroute
filtering is implemented in NS-2.27 simulator. The
simulation consists of 24 sensor nodes out of which
4 nodes in green color are cluster heads; some nodes
are configured to be attackers and a base station. The
network is randomly deployed in a terrain dimension
of 600m X 600m with the following simulation
environment shown in Table 1.
Table 1. Simulation Environment
PARAMETER
Channel
Propagation
Fig. 5. Identification of Attacker through collective
endorsement
Implementation of Collective Endorsement of Sensor
reports.
Sensor reports are HMACed as the result of HMAC
algorithm implemented in TCL script with the keys
randomly picked up from the assigned key matrix. Those
reports are further divided into small authenticated
shares in the range of 16 bytes each and are sent in
rounds from the cluster members to the cluster head in
order to prevent Report disruption attack.
A report disruption attack when launched by an
attacker will make the complete legitimate share of
sensor report abruptly dropped by a legitimate cluster
head by simply offering an illegitimate MAC to the
collective share. Hence through collective endorsement,
the whole sensor reports are further divided into small
authenticated shares such that even when an attacker
offers illegitimate HMAC, the cluster head will be able
to recover the complete collective share with the help
of legitimate shares received from its members.
VALUE
Channel/Wireless
channel
Radio Propagation
Ray Ground
Model
Phy/WirelessPhy
MAC
Mac/802_11
Interface Queue
Queue/Drop Tail
Link Layer
LL
Interface Queue
Size
Channel Type
Propagation/Two
Network Interface
Antenna
DESCRIPTION
Antenna/Omni
Antenna
5000(in packets)
Network Interface
Type
Medium Access
Control Type
Interface Queue
Type
Link Layer
Antenna Model
Maximum packet
in interface Queue
Routing Protocol
AODV
Routing Protocol
Data Rate
11Mbps
Data Transfer Rate
Interface Queue
Size
50
Terrain Dimension
600m X 600m
Simulation Time
100 Seconds
Packet Size
1026Bytes
Number of Nodes
25
Reception- rx
Energy Model
Power 0. 3(J/bits)
Transmission- tx
Power 0. 5(J/bits)
Maximum packets
in Interface Queue.
Terrain Dimension
of the network
Total duration of
the simulation
Size of the CBR
traffic packet
Number of nodes
in the Scenario
Power
Consumption
Model
KODHAI ET AL.: HMAC FILTERING SCHEME FOR DATA REPORTING 33
Performance Metrics & Evaluation
The performance metrics are used to measure the
performance of the proposed system.
Filtering capacity
Filtering capacity of the proposed scheme is defined
as the average number of hops that a false report can
be detected by the forwarding node at every hop or
the fraction of number of false reports filtered to the
number of hops travelled.
Energy savings
Energy savings of the proposed scheme is defined as the
energy consumption in transmission, reception and the
computations due to the extra fields which incur extra
overhead. We evaluate the length of a normal report
without using any filtering scheme and then compare
the length of an authenticated report in the next phases
of the review.
shown in Figure 6, packet loss seems to be very high
when there is increase in the attacker’s count. Attackers
try to launch selective forwarding attack, report
disruption attack and false report injection attack in
which the total availability requirement of the critical
information is lost leading to total energy drain of the
resource constrained sensor nodes or false positives or
false negatives intimation at the base station. Under this
state the malicious node drops all the packets from a
selective node or selective packets from a node leading
to a huge packet loss in the network as discussed in
the Threat and Trust model of section 2. With Enroute
Filtering mechanism packet loss is reduced to 40%
which is achieved by the identification of attacker
nodes through collective endorsement implemented in
the cluster heads.
Performance metrics determine the performance
of a particular scheme in the presence of constraints
related to domain oriented advantages and drawbacks.
We have evaluated our Enroute mechanism in terms of
throughput and packet loss.
Packet loss
Mobility-related packet loss may occur at both the
network layer and the MAC layer. When a packet
arrives at the network layer, the routing protocol
forwards the packet if a valid route to the destination
is known. Otherwise, the packet is buffered until a
route is available. A packet is dropped in two cases: the
buffer is full when the packet needs to be buffered and
the time that the packet has been buffered exceeds the
limit. It can be evaluated with the formula given below.
acket Loss (in packets) = DataAgtSent − DataAgt
P
Rec
where AGT– agent trace (used in new trace file
format)
Scenario: Packet Loss Vs Number of Attacker nodes:
Same scenario is maintained in which Packet loss
is computed by varying the number of attackers. As
Fig. 6. Packet Loss Vs Number of Attacker node
VII. Conclusion
A major challenge for a Wireless Sensor Network lies
in the energy constraint at each node, which poses
a fundamental limit on the network life time. Even
though there are many enroute filtering schemes
available in the literature they either fail to support the
dynamic nature of the sensor networks or they cannot
efficiently mitigate the adversary’s activities. Hence
this enroute filtering scheme is currently an area of
much research among the security professionals.
Generally AODV performs better than many other ondemand protocols under high mobility, large network
scenarios. When the size of the network is large and
highly mobile the frequency of the link failure is
also high. Due to this, latency and control load of the
network is also increased. Also due to the attacker’s
34 HINDUSTAN JOURNAL, VOL. 6, 2013
single illegitimate MAC there is a threat of dropping
the complete legitimate share.
In this work, we propose a HMAC’ed filtering
scheme for WSN that utilizes the dissemination of
authentication keys for filtering false data injection
attacks and DoS attacks. In our scheme, each node
uses its own authentication keys to authenticate the
reports and a legitimate report should be endorsed by
t nodes. The authentication keys of each node form a
hash chain and are updated in each round. The Enroute
scheme also yielded a better attacker detection and
mitigation framework together with disseminated
key structure. We thus analyzed the performance
metrics of the Enroute Filtering scheme with AODV
protocol in terms of Throughput and Packet Loss and
the results are also discussed. In future we intend
to compare the performance of Enroute Filtering
Scheme implemented with the security protocols such
as SPINS etc.
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HINDUSTAN JOURNAL, VOL. 6, 2013
An Efficient Neural Network Technique to Detect Collective
Anomalies in E-Medicine
G. Thiyagarajan, C.M. Rasika, B. Sivasankari and S.Sophana Jennifer
Abstract — Anomaly detection methods can be
very useful in recognising the pattern and detecting
the attack. The anomalies can be detected due to
several reasons, such as condition of the patient,
errors in the instruments, or recording errors. The
input instance can be taken as a spatio-temporal
data (space and time) for detecting the anomalies in
any dataset. In this paper, we propose a collective
anomaly technique to detect anomalies in such data.
In addition, auto-associative networks are used to
reconstruct the input pattern and make them free
from errors. The results give us hope that these
techniques may provide the basis of intelligent
monitoring systems that alert clinicians to the
occurrence of unusual events or decisions.12
Index terms — Collective anomaly, IDS, Neural
Network, Auto associative network.
I.  Introduction
With the current medical procedures and the healthy
lifestyles of many, the average lifetime expectancy is
ever increasing. Technical advances incorporated with
wide and accurate knowledge of the human anatomy
have allowed healthcare professionals the ability to
handle almost any scenario that they encounter in
individuals at hospitals and emergency treatment
G. Thiyagarajan is Assistant professor, Dept of
Computer Science, P.B College of Engineering, Chennai,
Tamilnadu, India, (e-mail: sivashankaripitam@gmail.
com).
C.M. Rasika, B. Sivasankari and S. Sophana
Jennifer are PG students, Dept of Computer Science
and Engineering, P.B college of Engineering, Chennai,
Tamilnadu, India.
facilities. As the average individual lifetime expectancy
has increased, this has also directly impacted on
our population and as such, a shortage of qualified
healthcare professionals to treat the sick and needy has
become an issue.
Unlike the signature-based intrusion detection
systems (IDS) in common use, anomaly-based IDSs
have the potential to detect previously unseen, or zeroday, attacks. However, anomaly detection systems can
be evaded through carefully crafted attacks and they
often produce a large number of false positives. To
build a successful anomaly detection system, we must
develop detection methods that are better at detecting
attacks but without misclassifying legitimate function.
The key to this trade-off lies in the nature of the
generalization performed by a given anomaly detection
method. If the method generalizes too much over
training examples, then it will be easy for attackers
to craft attacks that resemble normal behaviour; if
it generalizes too little, then previously unseen but
legitimate function will generate false alarms. Careful
control of generalization then is central to solving both
problems. Anomaly detection refers to the problem
of finding patterns in data that do not match to the
expected behaviour. These unmatched patterns are often
referred to as anomalies, outliers, jarring observations,
exceptions, abnormality, surprises, peculiarities, or
corrupted in different application domains.
II.  Background
Collective Anomalies: If the collection of related data
instances is anomalous with respect to the entire data set,
then it is termed a collective anomaly. The single data
instances in a collective anomaly may not be anomalies
by themselves, but their existences together as a group is
THIYAGARAJAN ET AL.: AN EFFICIENT NEURAL NETWORK TECHNIQUE 37
anomalous. Collective anomalies have been explored for
sequence data, graph data, and spatial data. It should be
noticed that while point anomalies can exist in any data
set, collective anomalies can occur only in data sets in
which data instances are related. In contrast, existence
of contextual anomalies depends upon the readiness
of context aspects in the data. Any point anomaly or a
collective anomaly can also be a contextual anomaly
if it is analyzed with respect to a context. Hence the
point anomaly detection problem or collective anomaly
detection problem can be transformed to a contextual
anomaly detection problem through integrating the
context information.
Figure 1 is an example of a human electrocardiogram
output. The highlighted region represents an anomaly
because the same low value exists for an abnormally
long time (which corresponds to an Atrial Premature
Contraction). Note that the low value by itself is not
an anomaly.
It should be noted that this collection of events is an
anomaly, but the individual events are not considered
as anomalies when they occur in other locations in the
sequence.
Fig. 1. Collective anomaly corresponding to an
Atrial Premature Contraction in an human
electrocardiogram output.
The techniques used for detecting collective
anomalies are very different when compared to the
point and contextual anomaly detection techniques.
For a brief review of the research done in the field of
collective anomaly detection, the reader is referred to
an extended version of this survey.
In this paper, we focus on collective anomaly
detection in medical readings, and we propose a new
approach based on neural network algorithms to detect
abnormal values. First we use collective anomaly
method to detect abnormal records, and when detected,
we apply neural network. Our proposed result is
intended to provide reliability in medical essentials
used for continuous monitoring of patient, where we
detect anomalies in a patient’s health, and differentiate
between the individual entering a censorious health
state and false readings.
The design and function of neural networks simulate
some functionality of biological brains and neural
systems. The advantages of neural networks are their
adaptive-learning, self-governing and fault-tolerance
capabilities. For these outstanding abilities, neural
networks are used for pattern recognition applications.
III.  Proposed Approach
Neural network models in artificial intelligence are
usually referred to as artificial neural networks (ANNs);
these are essentially simple mathematical models
defining a function f : X → Y or a distribution over X or
both X and Y, but sometimes models are also intimately
associated with a particular learning algorithm or learning
rule. A common use of the phrase ANN model really
means the definition of a class of such functions (where
members of the class are obtained by varying parameters,
connection weights, or specifics of the architecture such
as the number of neurons or their connectivity).
The word network in the term ‘artificial neural
network’ refers to the inter–connections between the
neurons in the different layers of each system. A typical
example is a system having three layers. The first layer
has input neurons which send data via synapses to the
second layer of neurons, and then via more synapses to
the third layer of output neurons. More complex systems
will have more layers of neurons with some having
increased layers of input neurons and output neurons.
The synapses store parameters called “weights” that
manipulate the data in the calculations.
An ANN is typically defined by three types of attributes:
1. T
he pattern between the different layers of neurons
is interconnected
2. T
he learning process used to update the weights of
the interconnections
3. T
he activation function which converts a neuron’s
weighted input to its output activation.
38 HINDUSTAN JOURNAL, VOL. 6, 2013
A. Filtering: Filtering is removing surplus
information or data from input. Depending on the
application, the filter algorithm or method will change.
For example, consider finger print identification. Each
time we scan our fingerprints through a (non-ink)
fingerprint device, the scanned output may be different.
The difference may be due to a change in contrast or
brightness or in the background of the image. There
could be some falsehood. In order to process the
input, we may need only lines in the fingerprints and
we may not need the other parts or background of the
fingerprint. In order to filter out the surplus portion
of the image and replace it with a white background,
we need a filtering feature. After the image is filtered
through the filtering mechanism, we will get standard
clean finger prints only with lines, which in turn helps
with the mechanism of feature extraction.
B. Feature extraction: Feature extraction is a process
of studying and extracting useful information from the
filtered input patterns. The derived information may be
of general features, which are valued to ease further
processing. For example, in image recognition, the
extracted features will contain information about gray
shade, texture, shape or context of the image. This is
the ultimate information used in image processing. The
process involved in feature extraction and the extracted
features are application dependent.
C. Classification: Classification is the final stage
of the recognition of pattern.Classifictaion is the stage
where an automated system declares that the input object
belongs to a particular category. By using the method
of Clustering Classification, the patterns of the targeted
classes are represented using vectors whose components
are real numbers. By the usage of clustering properties,
we can easily classify the unknown pattern. If the target
vectors are far apart in the arrangement of the geometry,
it is easy to categorize the unknown patterns. If they are
present nearby or if there is any overlap in the cluster
arrangement, we need more complicated algorithms to
classify the unknown patterns. One simple algorithm
based on the clustering concept is Minimum-DistanceClassification. This method evaluates the distance
between the unknown pattern and the chosen set of
known patterns and determines which known pattern
is nearby to the unknown and, finally, the unknown
pattern is placed under the known pattern to which it
has minimal distance. This algorithm works well when
the target patterns are far apart.
IV.  Evaluation of Clustering Results
Evaluation of clustering results is commonly referred to
as cluster validation. There have been several proposals
for a measure of similarity between two clustering
schemes. Such a measure can be used to compare how
well different data clustering algorithms perform on a
set of data. These measures are usually tied to the type
of criterion being considered in assessing the quality of
a clustering method.
A.  Internal Evaluation
When a clustering result is evaluated based on the data
that was clustered itself, this is called internal evaluation.
These methods usually assign the best score to the
algorithm that produces clusters with a high similarity
within a cluster and a low similarity between clusters.
One drawback of using internal criteria in cluster
evaluation is that high scores on an internal measure do
not necessarily result in effective information retrieval
applications. Additionally, this evaluation is biased
towards algorithms that use the same cluster model. For
example k-means clustering naturally optimizes object
distances, and a distance-based internal criterion will
likely overrate the resulting clustering.
Therefore, the internal evaluation measures are
best suited to get some insight into situations where
one algorithm performs better than another, but this
shall not imply that one algorithm produces more valid
results than another. Validity as measured by such an
index depends on the claim that this kind of structure
exists in the data set. An algorithm designed for certain
kinds of models will not perform well if the data set
contains a radically different set of models, or if the
evaluation measures a radically different criterion.
For example, k-means clustering can only find convex
clusters, and many evaluation indexes assume convex
clusters. On a data set with non-convex clusters neither
the use of k-means, nor of an evaluation criterion that
assumes convexity, is sound. The following methods
can be used to assess the quality of clustering algorithms
based on internal criterion:
B.  Davies–Bouldin Index
The Davies–Bouldin index can be calculated by the
following formula:
THIYAGARAJAN ET AL.: AN EFFICIENT NEURAL NETWORK TECHNIQUE 39
DB =
 σi + σ j 
1 n
max 
∑

i
≠
j
n i =1
 d (ci , c j ) 
where n is the number of clusters, Cx is the centroid of
cluster x, σ x is the average distance of all elements in
cluster x to centroid Cx , and d(Ci, Cj) is the distance
between centroids Ci and Cj. Since algorithms that
produce clusters with low intra-cluster distances (high
intra-cluster similarity) and high inter-cluster distances
(low inter-cluster similarity) will have a low Davies–
Bouldin index. The clustering algorithm that produces a
collection of clusters with the smallest Davies–Bouldin
index is considered the best algorithm based on this
criterion.
Dunn index (J. C. Dunn 1974): The Dunn index aims
to identify dense and well-separated clusters. It is
defined as the ratio between the minimal inter-cluster
distance to maximal intra-cluster distance. For each
cluster partition, the Dunn index can be calculated by
the following formula:



d (i, j )
D = min  min 

1≤ i ≤ n 1≤ j ≤ n , i ≠ j max

1≤ k ≤ n d ( k )  


where d(i, j) represents the distance between clusters
i and j, and d(k) measures the intra-cluster distance
of cluster k. The inter-cluster distance d(i, j) between
two clusters may be any number of distance measures,
such as the distance between the centroids of the
clusters. Similarly, the intra-cluster distance d(k) may
be measured in a variety of ways, such as the maximal
distance between any pair of elements in cluster k. Since
internal criterion seek clusters with high intra-cluster
similarity and low inter-cluster similarity, algorithms
that produce clusters with high Dunn index are more
desirable.
External evaluation: In external evaluation,
clustering results are evaluated based on data that was
not used for clustering, such as known class labels and
external benchmarks. Such benchmarks consist of a set
of pre-classified items, and these sets are often created
by human (experts). Thus, the benchmark sets can be
thought of as a gold standard for evaluation. These
types of evaluation methods measure how close the
clustering is to the predetermined benchmark classes.
However, it has recently been discussed whether this
is adequate for real data, or only for synthetic data sets
with a factual ground truth, since classes can contain
internal structure and the attributes present may not
allow separation of clusters or the classes may contain
anomalies. Additionally, from a knowledge discovery
point of view, the reproduction of known knowledge
may not necessarily be the intended result.
Some of the measures of quality of a cluster
algorithm using external criterion include:
Rand measure (William M. Rand 1971): The Rand
index computes how similar the clusters (returned
by the clustering algorithm) are to the benchmark
classifications. One can also view the Rand index as a
measure of the percentage of correct decisions made by
the algorithm. It can be computed using the following
formula:
RI =
TP + TN
TP + FP + FN + TN
where TP is the number of true positives, TN is the
number of true negatives, FP is the number of false
positives, and FN is the number of false negatives.
One issue with the Rand index is that false positives
and false negatives are equally weighted. This may
be an undesirable characteristic for some clustering
applications. The F-measure addresses this concern.
F-measure: The F-measure can be used to balance
the contribution of false negatives by weighting recall
through a parameter β ≥ 0. Let precision and recall be
defined as follows:
P=
TP
TP + FP
R=
TP
TP + FN
where P is the precision rate and R is the recall rate.
We can calculate the F-measure by using the following
formula:
Fβ =
( β + 1) ⋅ P ⋅ R
β2 ⋅P + R
Notice that when β = 0, F0 = P.
In other words, recall has no impact on the
F-measure when β = 0, and increasing β allocates
40 HINDUSTAN JOURNAL, VOL. 6, 2013
an increasing amount of weight to recall in the final
F-measure.
for-chance variant of this that has a reduced bias for
varying cluster numbers.
Pair-counting F-Measure is the F-Measure applied
to the set of object pairs, where objects are paired with
each other when they are part of the same cluster. This
measure is able to compare clustering methods with
different numbers of clusters.
C.  Clustering Axioms
Jaccard index: The Jaccard index is used to quantify
the similarity between two data sets. The Jaccard index
takes on a value between 0 and 1. An index of 1 means
that the two datasets are identical, and an index of 0
indicates that the datasets have no common elements.
The Jaccard index is defined by the following formula:
J ( A, B) =
A∩ B
TP
=
A ∪ B TP + FP + FN
This is simply the number of unique elements
common to both sets divided by the total number of
unique elements in both sets.
Fowlkes–Mallows index (E. B. Fowlkes & C. L.
Mallows 1983): The Fowlkes-Mallows index computes
the similarity between the clusters returned by the
clustering algorithm and the benchmark classifications.
The higher the value of the Fowlkes-Mallows index
the more similar the clusters and the benchmark
classifications are. It can be computed using the
following formula:
FM =
TP
TP
⋅
TP + FP TP + FN
where TP is the number of true positives, FP is the
number of false positives, and FN is the number of
false negatives. The FM index is the geometric mean of
the precision and recall P and R, while the F-measure
is their harmonic mean. Moreover, precision and recall
are also known as Wallace’s indices B1 and B11.
Confusion matrix: A confusion matrix can be used
to quickly visualize the results of a classification (or
clustering) algorithm. It shows how different a cluster
is from the gold standard cluster.
The Mutual Information is an information theoretic
measure of how much information is shared between
a clustering and a ground-truth classification that can
detect a non-linear similarity between two clustering
methods. Adjusted mutual information is the corrected-
Given that there is a myriad of clustering algorithms
and objectives, it is helpful to reason about clustering
independently of any particular algorithm, objective
function, or generative data model. This can be achieved
by defining a clustering function as one that satisfies a
set of properties. This is often termed as an Axiomatic
System. Functions that satisfy the basic axioms are
called clustering functions.
A partitioning function acts on a set S of n ≥ 2 points
along with an integer k > 0, and pairwise distances
among the points in S. The points are not assumed to
belong to any specific larger set or space; the pairwise
distances are the only data the partitioning function
has about them. We may label the points in S using the
numbers {1,2,..., n}. The pair wise distances define a
distance function d : S × S → R which should have the
properties of a semi metric: for any i, j ∈ S, we must
have d(i,j) ≥ 0, d(i,j) = d(j,i), and d(i,j) = 0if and only if
i = j. In other words, the distances must be nonnegative,
symmetric, and two points have distance zero if and
only if they are the same point.
Consistency: Fix k. Let d be a distance function,
and d’ be a F(d,k)-transformation of d. Then
F(d,k) = F(d’,k). In other words, suppose that we run
the partitioning function F on d to get back a particular
partitioning Γ. Now, with respect to Γ, if we shrink incluster distances or expand between-cluster distances
and run F again, we should still get back the same
result - namely Γ .The partitioning function F is forced
to return a fixed number of clusters: k. If this were not
the case, then the above three properties could never be
satisfied by any function.
In many popular clustering algorithms such as
k-means, Single-Linkage, and spectral clustering,
the number of clusters to be returned is determined
beforehand by the human user or other methods – and
passed into the clustering function as a parameter.
V.  Conclusion
In this paper, we proposed a collective anomaly and autoassociative Neural Network to detect anomalies in patient
healthcare .The proposed approach achieves both spatial
and temporal analysis for anomaly detection. We have
THIYAGARAJAN ET AL.: AN EFFICIENT NEURAL NETWORK TECHNIQUE 41
evaluated our approach on real medical data set with many
(real and synthetic) anomalies. Our results demonstrate the
ability of the proposed approach to achieve low false alarm
rate with a high detection accuracy.
[8] A
. S. Raghuvanshi, R. Tripathi, and S. Tiwari
(2011), “Machine Learning Approach for
Anomaly Detection in Wireless Sensor Data”,
International Journal of Advances in Engineering
& Technology, vol. 1, no. 4, pp.47–61.
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oonam Dabas and Rashmi Chaudhary, “Survey
of Network Intrusion Detection Using K-Mean
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[13] L
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HINDUSTAN JOURNAL, VOL. 6, 2013
Deriving Intelligence from Data Through Text Mining
C.T. Sree Vidhya
Abstract — Clustering or classification of data
is an important activity in partitioning the data
point into similarity classes. Fuzzy clustering
algorithms provide a fuzzy description of the
discovered structure. The main advantage of
fuzzy clustering is the ability to model uncertainty
within the data. The problem with Fuzzy C-Means
(FCM) is that the membership of a data point in a
cluster depends directly on the membership value
of the other cluster centers and this sometimes
happens to produce undesirable results. Another
important task in data mining process is detecting
the outliers. The isolation of outliers is important
both for improving the quality of original data
and for reducing the impact of outlying values in
the process of knowledge discovery in databases.
The drawback of detecting outliers through
conventional method, such as crisp clustering
techniques, is sensitivity to noise and outliers.
This paper proposes a method that overcomes
these drawbacks. The proposed method initially
performs improved FCM algorithm. The algorithm
uses as simple expression to calculate membership
value. Further, the improved FCM algorithm
is used to detect outliers. Diabetes database is
used to test the result. Here diabetic persons are
considered as customers (patients) from which
intelligence is derived. The patients record are in
document format.1
Index Terms — Text mining, Clustering, Fuzzy
Clustering, and Diabetes Analysis.
C.T. Sree Vidhya is in School of Computing Sciences,
Hindustan University, Chennai, India, (e-mail:
[email protected])
I.  Introduction
A. Text Mining
Text mining or knowledge discovery from text (KDT)
— for the first time mentioned in Feldman et al.[1] —
deals with the machine supported analysis of text. It
uses techniques from information retrieval, information
extraction as well as natural language processing (NLP)
and connects them with the algorithms and methods
of KDD, data mining, machine learning and statistics
[7]. Thus, one selects a similar procedure as with the
KDD process, whereby not data in general, but text
documents are in focus of the analysis.
Text mining essentially corresponds to information
extraction — the extraction of facts from texts. Text
mining can be also defined similar to data mining as
the application of algorithms and methods from the
fields of machine learning and statistics to texts with
the goal of finding useful patterns. For this purpose, it
is necessary to pre-process the texts accordingly. Many
authors use information extraction methods, natural
language processing or some simple pre-processing
steps in order to extract data from texts. To the extracted
data, data mining algorithms can then be applied.
B. Cluster Analysis
Cluster analysis is a technique for breaking data down into
related components in such a way that patterns and order
becomes visible. It aims at sifting through large volume of
data in order to reveal useful information in the form of new
relationships, patterns, or clusters, for decision making by a
user. Clusters are natural groupings of data items based on
similarity metrics or probability density models. Clustering
algorithms map a new data item into one of several
known clusters. In fact, cluster analysis has the virtue of
strengthening the exposure of patterns and behaviour as
SREE VIDHYA: DERIVING INTELLIGENCE FROM DATA THROUGH TEXT MINING 43
more and more data becomes available [12]. A cluster has
a centre of gravity which is basically the weighted average
of the cluster. Membership of a data item in a cluster can
be determined by measuring the distance from each cluster
centre to the data point [13]. The data item is added to a
cluster for which this distance is a minimum.
II.  Fuzzy Logic
A. Fuzzy Theory
The modelling of imprecise and qualitative knowledge,
as well as handling of uncertainty at various stages is
possible through the use of fuzzy sets. Fuzzy logic is
capable of supporting, to a reasonable extent, human
type reasoning in a natural form by allowing partial
membership for data items in fuzzy subsets. Integration
of fuzzy logic with data mining techniques has become
one of the key constituents of soft computing in
handling the challenges posed by the massive collection
of natural data. Fuzzy logic is logic of fuzzy sets.
A Fuzzy set has, potentially, an infinite range of
truth values between one and zero. Propositions in
fuzzy logic have a degree of truth, and membership
in fuzzy sets can be fully inclusive, fully exclusive, or
some degree in between [13].The fuzzy set is distinct
from a crisp set in that it allows the elements to have
a degree of membership. The core of a fuzzy set is its
membership function: a function which defines the
relationship between a value in the sets domain and its
degree of membership in the fuzzy set. The relationship
is functional because it returns a single degree of
membership for any value in the domain [11].
µ = f ( s, x) (1)
Here,
μ is he fuzzy membership value for the element
s is the fuzzy set
x is the value from the underlying domain.
Fuzzy sets provide a means of defining a
series of overlapping concepts for a model variable
through degrees of membership. The values from the
complete universe of discourse for a variable can have
memberships in more than one fuzzy set.
B. Fuzzy Clustering
The central idea in fuzzy clustering is the non-unique
partitioning of the data in a collection of clusters. The
data points are assigned membership values for each of
the clusters. The fuzzy clustering algorithms allow the
clusters to grow into their natural shapes [15]. In some
cases the membership value may be zero indicating
that the data point is not a member of the cluster under
consideration. Many crisp clustering techniques have
difficulties in handling extreme outliers but fuzzy
clustering algorithms tend to give them very small
membership degree in surrounding clusters [14].
The non-zero membership values, with a maximum
of one, show the degree to which the data point
represents a cluster. Thus fuzzy clustering provides a
flexible and robust method for handling natural data
with vagueness and uncertainty. In fuzzy clustering,
each data point will have an associated degree of
membership for each cluster. The membership value is
in the range zero to one and indicates the strength of its
association in that cluster.
III.  Related Work
A. Outlier Detection Approaches
There is no single universally applicable or generic
outlier detection approach. Therefore, many approaches
have been proposed to detect outliers. These approaches
can be classified into four major categories based on
the techniques used [18], which are: distribution-based,
distance-based, density-based and clustering-based
approaches.
Distribution-based approaches [19, 20, 21] develop
statistical models (typically for the normal behaviour)
from the given data and then apply a statistical test to
determine if an object belongs to this model or not.
Objects that have low probability to belong to the
statistical model are declared as outliers. However,
distribution-based approaches cannot be applied in
multidimensional scenarios because they are uni-variate
in nature. In addition, a prior knowledge of the data
distribution is required, making the distribution-based
approaches difficult to be used in practical applications
[18].
In the distance-based approach [6, 7, 22, 23],
outliers are detected as follows. Given a distance
measure on a feature space, a point q in a data set is
an outlier with respect to the parameters M and d, if
there are less than M points within the distance d from
q, where the values of M and d are decided by the user.
44 HINDUSTAN JOURNAL, VOL. 6, 2013
The problem with this approach is that it is difficult to
determine the values of M and d.
Density-based approaches [17, 25] compute the
density of regions in the data and declare the objects in
low dense regions as outliers. In [17], the authors assign
an outlier score to any given data point, known as Local
Outlier Factor (LOF), depending on its distance from its
local neighbourhood. A similar work is reported in [25].
Clustering-based approaches [9, 18, 19, 20]
consider clusters of small sizes as clustered outliers.
In these approaches, small clusters (i.e., clusters
containing significantly less points than other
clusters) are considered outliers. The advantage of the
clustering-based approaches is that they do not have to
be supervised. Moreover, clustering-based techniques
are capable of being used in an incremental mode (i.e.,
after learning the clusters, new points can be inserted
into the system and tested for outliers).
Custem and Gath [19, 18] present a method based
on fuzzy clustering. In order to test the absence or
presence of outliers, two hypotheses are used. However,
the hypotheses do not account for the possibility of
multiple clusters of outliers.
sensitive to outliers, and hence may not give accurate
results.
B. FCM Fuzzy Algorithm [10]
Fuzzy c-means clustering involves two processes:
the calculation of cluster centres and the assignment
of points to these centres using a form of Euclidian
distance. This process is repeated until the cluster
centres stabilize. The algorithm is similar to k-means
clustering in many ways but it assigns a membership
value to the data items for the clusters within a range of
0 to 1. So it incorporates fuzzy set concepts of partial
membership and forms overlapping clusters to support
it. The algorithm needs a fuzzification parameter m
in the range [1, n] which determines the degree of
fuzziness in the clusters. When m reaches the value
of 1 the algorithm works like a crisp partitioning
algorithm and for larger values of m the overlapping of
clusters tends to be more. The algorithm calculates the
membership value μ with the formula,
 1  1
 
 d ji  m − 1
µ j ( xi ) =  
p  1 
1
∑ k =1  d  m − 1
 ji 
Jiang et. al. [20] presented a two-phase method to
detect outliers. In the first phase, the authors proposed
a modified k-means algorithm to cluster the data, and
then, in the second phase, an Outlier- Finding Process
(OFP) is proposed. The small clusters are selected and
regarded as outliers, using minimum spanning trees.
where
In [9] clustering methods have been applied. The
key idea is to use the size of the resulting clusters as
indicators of the presence of outliers. The author uses
a hierarchical clustering technique. A similar approach
was reported in [22].
p is the number of specified clusters
Acuna and Rodriguez [20] performed the PAM
algorithm followed by the Separation Technique (termed
PAMST). The separation of a cluster A is defined as the
smallest dissimilarity between two objects; one belongs
to Cluster A and the other does not. If the separation is
large enough, then all objects that belong to that cluster
are considered outliers. In order to detect the clustered
outliers, one must vary the number k of clusters until
obtaining clusters of small size with a large separation
from other clusters are obtained.
In [22], the authors proposed a clustering- based
approach to detect outliers. The k-means clustering
algorithm is used. As mentioned in [13], the k means is
(2)
μj(xi) is the membership of xi in the j-th cluster
dji is the distance of xi in cluster cj
m is the fuzzification parameter
dki is the distance of xi in cluster Ck
The new cluster centres are calculated with these
membership values using the expression, where
Cj =
∑ i  µ j ( xi ) mx
∑ i  µ j ( xi ) m
i
Cj is the centre of the j-th cluster
(3)
xi is the i-th data point
μj the function which returns the membership
m is the fuzzification parameter
This is a special form of weighted average. We
modify the degree of fuzziness in xi’s current membership
and multiply this by xi. The product obtained is divided
by the sum of the fuzzified membership. The first loop
of the algorithm calculates membership values for the
data points in clusters and the second loop recalculates
SREE VIDHYA: DERIVING INTELLIGENCE FROM DATA THROUGH TEXT MINING 45
the cluster centres using these membership values.
When the cluster centre stabilizes (when there is no
change) the algorithm ends (see Table 1).
Step 3: For the rest of the points not determined in step
2, remove a point temporarily and recalculate
the objective function.
Table 1. Fuzzy C Means Algorithm
To detect the outliers in the rest of the clusters
(if any), we (temporarily) remove the point from the
data set and re-execute the c-means algorithm. If the
removal of a point causes a noticeable decrease in the
objective function value, the point is considered as an
outlier; otherwise, it is not.
initialize p=number of clusters
initialize m=fuzzification parameter
initialize Cj (cluster centers)
Repeat
For i=1 to n :Update μj(xi) applying (3)
For j=1 to p :Update Ci with(4)with current μj(xi)
Until Cj estimate stabilize
Since the membership value varies strictly from 0
to 1, initializing the threshold value to 0.5 produces a
better result in cluster centre calculation.
C. Limitations of the algorithm
The fuzzy c-means approach to clustering suffers from
several constraints that affect its performance [14].
1. T
he main drawback is from the restriction that the
sum of membership values of a data point xi in all the
clusters must be one as in (4), and this tends to give
high membership values for the outlier points. So the
algorithm has difficulty in handling outlier points.
2. S
econdly the membership of a data point in a
cluster depends directly on the membership values
of other cluster centres and this sometimes happens
to produce undesirable results.
∑
p
µ ( xi ) = 1
j =1 j
(4)
In fuzzy c-means method a point will have partial
membership in all the clusters.
3. T
he expression (3) for calculating the new cluster
centres finds a special form of weighted average
of all the data points. The third limitation of the
algorithm is that due to the influence (partial
membership) of all the data members, the cluster
centres tend to move towards the centre of all the
data points [10].
4. T
he fourth constraint of the algorithm is its inability
to calculate the membership value if the distance of
a data point is zero.
D. Existing Outlier detection method
The basic structure of the method is as follows;
Step 1: Execute the FCM algorithm to produce a set of
k clusters as well as the objective function.
Step 2: Determine small clusters and consider the
points belonging to these clusters as outliers.
IV. The Modified Fcm (Mfcm)
In c-means algorithm, the membership of a point in a
cluster is calculated based on its membership in other
clusters. Many limitations of the algorithm arise due to
this and in the new method the membership of a point
in a cluster centre depends only on its distance in that
cluster. For calculating the membership values, we use
a simplee expression as given in (5).
µ j ( xi ) =
max (d j ) − d ji
max (d j )
(5)
where
µ j ( xi ) is the membership of the xi in the jth cluster
max (d j ) is the maximum distance in the cluster c j
d ji is the distance of xi in the cluster c j
The membership function (5) will generate
values closer to one for smaller distances (dji) and a
membership value of zero for the maximum distance.
If the distance of a data point is zero then the function
returns a membership value of one and thus it
overcomes the fourth constraint of c-means algorithm.
The membership values are calculated only based on
the distance of a data member in the cluster and due to
this, the modified FCM [25] does not suffer from the
first and second constraints of c-means algorithm.
V.  Proposed Method
The proposed method incorporates the idea of using a
simple expression (5) to detect outliers.
A. The basic steps of the proposed algorithm,
1. Perform modified FCM where membership value is
calculated using a simple expression
46 HINDUSTAN JOURNAL, VOL. 6, 2013
Initialize p = number of clusters
Initialize m (fuzzification parameter)
Initialize
(cluster centers)
Initialize α (threshold value)
Repeat
For i=1 to n: Update µ j ( xi ) applying (5)
For k=1 to p:
Sum=0
Count=0
For i=1 to n :
If μ(xi) is maximum in Ck then
If μ(xi)>=α
Sum=Sum+xi
count=count + 1
Ck=Sum/count
2. Determine small clusters and consider the points
that belong to these clusters as outliers.
3. For the rest of the points,
For each point i
DO
remove a point, pi,
re-calculate the objective function applying (5)
If μ(xi)>=α : then classify point pi as an outlier and
return
it back to the set;
End DO
End
VI.  Methodology
An expert system which employs fuzzy c Means for the
diagnosis of diabetes is developed in an environment
characterized by Microsoft Window XP professional
Operating System and the idea is implemented and
executed using Weka Data Mining tool.
An approach for analyzing clusters to identify
meaningful pattern for determining whether a
patient suffers from diabetes or not is presented. The
system provides a guide for diagnosis of diabetes
within a decision making framework. The process
for the medical diagnosis of diabetes starts when an
individual consults a physician (doctor) and presents
a set of complaints (symptoms). The physician then
requests further information from the patients. Data
collected include patient’s previous state of health,
living condition and other medical conditions. A
physical examination of the patient’s condition is
conducted and in most cases, a medical observation
along with medical test(s) is carried out on the patient
prior to medical treatment.
From the symptoms presented by the patient, the
physician narrows down the possibilities of the illness
that corresponds to the apparent symptoms and make
a list of the conditions that could account for what
is wrong with the patient. These are usually ranked
in possibility order (low, moderate and high). The
physician then conducts a physical examination of
the patient, studies his or her medical records and ask
further questions, as he goes in an effort to rule out as
many of the potential conditions as possible. When the
list has been narrowed down to a single condition, it
is called differential diagnosis and provides the basis
for a hypothesis of what is ailing the patient. Until the
physician is certain of the condition present; further
medical tests are performed or schedule such as medical
imaging, scan, X-rays in part to confirm or disprove
the diagnosis or to update the patient’s medical history.
Upon completion of the diagnosis by the physician,
a treatment plan is proposed, which includes therapy
and follow-up (further meeting and test to monitor
the ailment and progress of the treatment if needed).
Review of diagnosis may be conducted again if there
is a failure of the patient to respond to treatment
that would normally work. The physician may carry
out a precise diagnosis, which requires a complete
physical evaluation to determine whether the patient
has diabetes. The examining physician accounts for
possibilities of having diabetes through an interview,
physical examination and laboratory test. A thorough
diagnostic evaluation may include a complete history
of the following:
a. Ancestors Medical history?
b. When the symptoms started?
Once the medical examination is done, the patient
may suffer one of the following diabetic types [13]:
Type 1 diabetes- it is determined usually by age, i.e.
age below 25.
Type 2 diabetes- it is determined by insulin level and
age above 25.
SREE VIDHYA: DERIVING INTELLIGENCE FROM DATA THROUGH TEXT MINING 47
Gestational diabetes- determined in pregnant
female.
diabetes database which was available in Diabetes Care
Centre.
Once the process of medical examination is
done, the patient medical report is generated either in
structured or unstructured format. These reports can be
analyzed and studied for further insights which lead to
more patterns of information or diagnosis methods.
In the dataset constructed for this domain, the age
feature simply represents the age of the patient. Every
other feature was given a degree in the range of 0 to
3. Here, 0 indicates that the feature was not present, 3
indicates the largest amount possible, and 1, 2 indicate
the relative intermediate values.
VII.  Results and Discussion
The names and id numbers of the patients were
recently removed from the database.
In order to find the effectiveness of the new algorithm,
we applied it with a small data set to demonstrate the
functioning of the algorithm in detail. The algorithm is
also tested with real data collected from Diabetes Care
Centre.
To design the Diabetes Risk Assessment System
for diagnosis of diabetes, we design a system which
consists of a set of parameters needed for diagnosis
(here, we are using 10 basic and major parameters) as
presented in Table 1.
Table 1. Parameters for Diabetes Diagnosis
S.No
SYMPTOMS
Number of Instances: 75
Number of Attributes: 11
The different form of symptoms of diabetes constitutes
the parameters of the knowledge base. The fuzzy set of
parameters represented by P which is defined as {P1,P2 ... Pn}
where Pj represents jth parameter and n represents
the number of parameters (here n=10).
The fuzzy C-means algorithm provides the rules for
the partitioning of patients into a number of homogenous
classes with respect to a suitable similarity measure. In
this paper, the patients were classified into five form of
diabetes, that are mentioned in Table 2.
1
Often Thirst
2
Excessive Hunger
3
Frequent Urination
4
Sudden Weight Loss
5
Blurred Vision
1
Heart
6
Numbness
2
Vision
7
Slow healing of Yeast Infection
3
Kidney
8
Hard to heal Infection
4
Nerves
9
Dry or Itchy skin
5
Gums or Teeth
10
Age
The patients who suffer any of the six symptoms
listed in the table 1 have all the chances to suffer any
one of organ failure listed in Table 2.
A. Diabetes Datasets
The database used for this work is Diabetes Database.
The data sets are obtained from one of the Diabetes
Health care organization in Chennai called SS Diabetes
Diagnostic Centre.
In this section, we examine performance of proposed
algorithm and compare it with FCM algorithm on the
Table 2. Classes (Organ Affected)
S.No
Risk of Organ to Failure
Table 3. Outlier Membership
Methods
Final Cluster
Centers
Outlier Membership
C1 - 2.79 , 47.65
.37
C2 - 3.29 , 204.4
.63
New
C1 - 1.52,166.20
0
Method
C2 - 5.49,172.11
0
C Means
The new algorithm is capable of giving very
low membership values to the outlier points. From
Table 3, it is clear that the new fuzzy clustering
method we propose is better than the conventional c
48 HINDUSTAN JOURNAL, VOL. 6, 2013
means algorithm in handling outlier points and in the
calculation of new cluster centers.
Finally, after detecting and removing outliers, FCM
is performed once again to derive possibility of persons
prone to develop future risk of organ failure as shown
in Table 4.
Table 4. Evaluvation Result
CLASSES
CLUSTERED INSTANCES
Heart
17(23%)
Vision
26(35%)
Kidney
14(19%)
Nerves
15(20%)
Gums & Teeth
3(4%)
VIII.  Conclusion
A good clustering algorithm produces high quality
clusters to yield low inter cluster similarity and high
intra cluster similarity. Many conventional clustering
algorithms like k-means and fuzzy c-means algorithm
achieve this on crisp and highly structured data. But
they have difficulties in handling unstructured data
which often contain outlier data points. The proposed
new fuzzy clustering algorithm combines the positive
aspects of both crisp and fuzzy clustering algorithms. It
is more efficient in handling the natural data with outlier
points than both k-means and fuzzy c-means algorithm.
It achieves this by assigning very low membership
values to the outlier points. But the algorithm has
limitations in exploring highly structured crisp data
which is free from outlier points. The efficiency of the
algorithm has to be further tested on a comparatively
larger data set.
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HINDUSTAN JOURNAL, VOL. 6, 2013
Web Service Assortment through Genetic Algorithm and XML
Deeptha R and Rajeswari Mukesh
Abstract — Owing to the rapid development of
Web tools, web based applications gradually use
diverse programming languages and platforms
today. On the other hand Web service technologies
were presented to ease the incorporation of
web applications on heterogeneous platforms.
Nevertheless, fewer works have been done on
issues related to the eminence of composite
services. The quality of Web services has received
much attention as it relates to the service discovery
process. This study uses the selection model along
with the concept of quality of service (QoS) in order
to improve the quality of service performance of
current Web services in the discovery development.
It also practices a selection model as the substance
for selecting Web services, leading to simulations
of generalizing QoS concert when implemented in
sequence. Nevertheless, computation of optimal
service composition needed exponential time
in the number of services. As of this, genetic
algorithm quickly discovers the best-fitting
service composition. Lastly, we notch and sort
each service composition created on the service
requesters’ favorites towards QoS. The results of
the experiment show that considering workflow
QoS in selecting service composition improves the
actual QoS presentation. At the same time, using
genetic algorithm the service composition delivers
an improvement in the resolution interval.1
Index terms — Web services, Genetic algorithm,
Workflow, XML, QoS, Service selection,
Deeptha R and Rajeswari Mukesh are in School of
Computing Sciences, Hindustan University, Chennai,
India. (e-mail: [email protected], rajeswarim@
hindustanuniv.ac.in)
I.  Introduction
As generations of Web applications and technologies
arise, different types of web service providers arise
in relation to these new technologies. To allow these
applications or services to perform in a heterogeneous
operating system, numerous Web services specifications
were developed. These stipulations include WSDL,
XML, SOAP, and the UDDI data argument standard
linking to Web services, the one that finds Web services
based on one’s desires. The extra web services are
obtainable, but it is more difficult to find the most suitable
service for an unambiguous solicitation. Although Web
services deliver a universal data conversation platform
and offer methods that characterize the service recovery
interfaces, a service supplicant may not be able to find
appropriate Web services basically by consuming
search keywords. Even if a service is created that
caters to the functional necessities, it is indistinct if the
quality routine of that service can satisfy the requester’s
needs. Though the existing UDDI structure does not yet
deliberate the quality of service (QoS) when searching
for services, there is a need to consider the QoS [1].
Though previous studies have largely focused on the
quality of a single provision, much work has previously
been done in the field of Web services. But, real-world
requests frequently need to incorporate facilities into
a workflow [2]. This study seeks to control a path for
service activists to find the service arrangement that
delivers the expected QoS. Once a service is collected
comprising of several sub-tasks, each sub-task will
disturb the general tendency of the overall service.
Though many models have been devised for Web
service selection, making a composite Web service not
only correct and reliable but also with an optimal QoS
remains a significant challenge.
DEEPTHA AND RAJESWARI MUKESH: WEB SERVICE ASSORTMENT THROUGH GENETIC 51
II.  Related Work
A.  Web Service Selection
Some web service tools are available that selects web
services that are reliable. Figure.1 shows the various
service selections presently available for web service
selection. When selecting an implementation for
one web service, a particular operation for extra web
service in the composite web service framework should
also be selected [3]. For example, when structuring
a house broker web service, if we select a particular
broker web service that only receives payments
made by Master cards, before that we need to select
a payment web service that admits Master cards. This
kind of constraints is called dependency constraint.
Furthermore, in the web service selection there might
be certain web service operations that conflict with each
other. When selecting an implementation for one web
service, we must not select a particular implementation
for additional web service in the compound web service
framework. This kind of constraints is called conflict
constraint [4]. In the web service selection system, both
dependency constraints and conflict constraints must
be measured. Numerous optimal
Web Service Selecon
WSDL-based
Structure
Text
Ontology-based
Semancs
Semancs
Keyword
Tree
Semancs
WSMO
String
Graph
Semancs
OWL-S
IR model
Signature
Semancs
Surveying the current works, we classify existing
approaches and researches into three types,
●● Active workflow provision engagement
●● QoS- attentive service selection
●● Transactional-attentive
The approaches belonging to the first class, as
in [9][10][11][12][13], mostly address the problem
happening at the major step in design time. It automates
the production of workflow. These existing studies do
not use the perfect architecture and constraints. The
importance to integrate transactional and QoS-attentive
service selection has been stated in [14]. A selection
algorithm taking into account transactional and QoS
aspects is proposed. It is a remarkable work to integrate
transactional and QoS attentive selection. However, it
still asks for a pre-defined, handcrafted workflow and
it only supports local-optimal QoS attentive because
it is done in a transactional manner. According to the
classification, most approaches only have one of the
characteristics namely dynamic workflow, transactional
or QoS attentive. In other words, each approach only
automates solution or a part of the design time process.
These detailed design process contains a sequential path,
and not an optimal selection of web services. Therefore,
our objective is to provide a one-stepped, full automation
approach for Web service composition in design time.
III.  Web Service Assortment Through Ga
and Xml
A.  Quality of Service
WSDL-S
Fig. 1. Web Service Selection Hierarchy
web service selection glitches have been intensively
considered and dissimilar methods have been suggested
in the past few studies [5], [6], [7], [8]. These optimal
web service selection and composition problems with
constraints remain open. From the computational point
of view, web service selection problem is usually a
controlled and a combinatorial optimization problem.
Thus genetic algorithms might be effective and
operative to solve such problems.
QoS can be used to express the non-functional requirements
of network community research. Some studies have
defined QoS in distributed systems like how one can
express the desired QoS for a system as well as how
requests can be delivered to a resource manager to satisfy
QoS requirements. QoS originated as a research topic in
the fields of networking, system middleware and real time
computing. At present, related research on the quality of
Web services has contributed greatly to improving the
quality of Web services [15]. Figure.2 shows the GA based
implementation of house broker architecture. Although the
broker mechanism can use the service’s basic description
to easily obtain the required services, this only gives access
52 HINDUSTAN JOURNAL, VOL. 6, 2013
to information recorded during service registration and
does not provide any indication of the state or quality
of the service. Henceforth, in real implementation of
the service, circumstances occasionally arise where the
service is unable to function or the quality fails to satisfy
users’ requirements. As mentioned in [16] several QoS
problems are encountered in Web service facilities, such
as in what way to control whether services conform to the
performance necessities, and whether they could provide
a high gradation of consistency for making key chores of
a system. The discussion is then focused on QoS issues
and proposed a new Web service discovery framework
and a discovery model. In our proposed house broker
architecture, web services are executed according to
the best optimal solution of services given by user [17].
Once house broker service gets logged in, it evaluates the
possible web service and chooses the optimal solution.
B.  Genetic algorithm
Service
Requester
Request
QoS
Service Provider
GA
XML
Web Service
QoS Monitoring
No
The genetic algorithm (GA) is a search technique
developed by Holland [1970] used to find precise or
estimated solutions to optimization and search problems
[18]. The Genetic algorithms are a precise class of
evolutionary algorithms that use techniques inspired by
evolutionary ecology incorporating inheritance, mutation,
selection, and crossover [19]. Control parameters of
genetic algorithms include population size, boundary
rate, chromosome code, and aptness function in addition
to the termination condition [20]. Genetic algorithms can
be employed in the search for optimal composition [21].
Though, binary genetic algorithms can find the optimal
solution in this case, too much time is used in multipart
encoding and decoding procedures, there are too many
limitations and a large number of bits are prerequisite to
represent them. As a result encoding and decoding will
slow down the searching speed of the system. On the
other hand, real-valued genetic algorithms do not have
this drawback. In addition, most real world optimization
glitches need real-valued parameters [22]. Using realvalued genetic algorithms to solve problems not only
makes it more convenient to manage parameters, but
also eliminates the complicated computation of encoding
and decoding, and further enhances the correctness of
the system. Our implementation relates real-valued
coding schemes to the dynamic coding glitches in
various workflow states and feature an enhanced genetic
algorithm to select optimal web services composition
tactics from many complex strategies on the basis of
universal QoS constraints [23]. A superior fitness task
and an alteration policy were planned in the work. The
outcomes revealed that the enhanced genetic algorithm
can advance efficiently the compound service plan that
fulfilled the global QoS provisions. Also, the conjunction
of genetic algorithm improved and presented a quickly
convergent population diversity treatment for web service
selection with global QoS limitations. In that study, an
improved initial population policy and an evolution
policy were planned and implemented on a variety of
populations and a virtual matrix coding scheme. This GA
implementation will choose the optimal broker service
according to the QoS.
IV.  Conclusion
Service
Sasfacon
Fig. 2. GA based Service Selection for House Broker
Service discovery is a key aspect in the SOA research
community. In this work, we hve proposed a real-world and
adaptive Web Service discovery framework which is to be
created on ontology comparison. When the framework was
built, the web service requestor, after accessing the desired
DEEPTHA AND RAJESWARI MUKESH: WEB SERVICE ASSORTMENT THROUGH GENETIC 53
web service, can find a list of comparable Web services
in the order of similarity. To more closely match QoS to
the requirements of service requesters, this study applies
genetic algorithm to optimize the simulated deduction of
workflow QoS. Based on the weights supplied by service
activists, we advance the discovery process to composite
services. Our tests show that actual QoS presentation of
complex facilities is better when seeing workflow than
when not seeing workflow in the initial stage of service
selection. Using the weights can also move the selection
closer to the QoS preferences of service requesters. The
tests also display that genetic algorithm can condense the
period required to obtain the optimal service arrangement.
It is initially supposed that when there is solely one
workflow sub-task, it would not matter whatever collection
plan is accepted. However, reproduction shows that even
when the service quantity is one, when there is a recursive
progression applied more than once, dissimilar collection
policies resolve selection of diverse tasks. As an outcome,
the thought of complete workflow QoS is important in the
primary phase of service selection.
V.  Future Work
The proposed evaluation model has shown that the
performance of the new genetic algorithm may not
be as stable as that of the testing of the web service
and that it considers only the front end of the system.
Future work will focus on improving the performance
of new genetic algorithm with database connectivity
and testing functionalities.
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Benatallah, LZ Zeng, “QoS-Aware Middleware
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Gaaloul, S Bhiri, and M Rouached, (2010)
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Lécué, A Léger (2006) ”A formal model for Web
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Lajmi, C Ghedira, and K Ghedira (2009)”CBR
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[9] J unli Wang, Zhijun Ding, Changjun Jiang
(2006)“GAOM: Genetic Algorithm based
Ontology Matching,” Proc. of the IEEE Asia
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[10] F
uyong Yuan, Jian Liu, Chunxia Yin, Yulian
Zhang (2008) “A Novel Methodology for Web
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[11] E
yhab Al-Masri and Qusay H. Mahmoud, (2007)
“WSCE: A Crawler Engine for Large-Scale
Discovery of Web Services,” IEEE International
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[12] U
ddam Chukmol, Aïcha-Nabila Benharkat,
Youssef Amghar, (2008) “Enhancing Web Service
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System”, IEEE 4th International Conference on
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[13] C
olin Atkinson, Philipp Bostan, Oliver Hummel,
Dietmar Stoll, “A Practical Approach to Web
Service Discovery and Retrieval”, IEEE
54 HINDUSTAN JOURNAL, VOL. 6, 2013
International Conference on Web Services-2007,
pp. 241-248.
[14] S
hen Derong, Yu Ge, C Yu, Kou Yue, N Tiezheng,
(2005) “An Effective Web Services Discovery
Strategy for Web Services Composition,” Proc.
of the 5th International Conference on Computer
and Information Technology, pp. 257-263.
[15] M
ohamed Gharzouli, Mahmoud Boufaida, (2009) “A
Generic P2P Collaborative Strategy for Discovering
and Composing Semantic Web services,” Fourth
International Conference on Internet and Web
Applications and Services, pp-449-454.
[16] C
hen Wu, Elizabeth Chang (2008) “Searching
services on the Web-A public Web services
discovery approach”, Third International IEEE
Conference on Signal Image Technologies and
Internet Based System, pp-321-328.
[17] J Wang, Z Ding, C Jiang, (2006) “GAOMGenetic Algorithm based Ontology Matching”,
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on Services Computing, pp-617-620.
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uyong Yuan, Jian Liu, Chunxia Yin, Y Zhang
(2008) “A Novel Methodology for Web Services
Discovery in Gnutella-like Networks,” Third
International IEEE Conference on Signal Image
Technologies and Internet Based System, pp231-238.
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yhab Al-Masri, Qusay H. Mahmoud (2007)
“WSCE-A Crawler Engine for Large-Scale
Discovery of Web Services”, IEEE International
Conference on Web Services, pp. 1104-1111.
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Zhang, Y Ma, (2009) “Dynamic
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Compositions Based on Global QoS Evaluations”,
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ohamed Gharzouli, M Boufaida (2009)
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pp.449-454.
HINDUSTAN JOURNAL, VOL. 6, 2013
Improving the efficiency of Impulse Noise Estimation
S.V. Priya and R. Seshasayanan
Abstract — Impulse noise estimation is as important
as the filtering process, as the efficiency of filtering
depends on the estimation techniques employed.
In this paper, we propose certain enhancements to
improve the efficiency of impulse noise estimation
techniques. As the orientation of noise plays a
major role in the estimation process, we utilize
the directional sub-windows or kernels to find
the directivity of the noise distribution. Based on
the outputs delivered by the individual kernels,
the decision making system decides if the pixel is
corrupted by noise. Also the confidence level of the
estimation process is stored for further processing
along with the noise removal. Thus more flexibility is
given to the noise estimator through the directional
kernels to improve the efficiency of the estimation
process. Also we consider MAD and S-Estimate as
the two major estimators before a firm decision
is made. MAD and S-Estimates are calculated for
all the kernels and based on the outputs of each
estimator the decision is made. Experiments reveal
that the noise estimation efficiency can go as high as
90% detection even for highly corrupted images.1,2
Index terms — Directional windows, Impulse noise
detection, ROAD, MAD.
I.  Introduction
The image statistics proposed by Yiqiu Dong et al [1] was
efficient to detect the random valued impulse noise even
if the image is corrupted by 60% noise and a two stage
algorithm was used to denoise the images. A universal
S.V. Priya is
Research Scholar, Faculty of Electronics
Engineering, Sathyabama University, Chennai, India (e-mail:
[email protected])
R. Seshasayanan is Associate Professor, Dept. of
ECE, Anna University, Chennai, India
noise filter introduced by Roman Garnett et al [2] used the
local statistic based on rank-ordered absolute difference
(ROAD) and it was used for denoising the mixed noises
with both random valued impulse noise and Gaussian
noise. The directional-difference based noise detector
proposed by Xuming Zhang et al used four directional
windows with predefined threshold value and compared
the absolute mean of those four directional windows
with the pixel of interest to classify the pixel [3, 13].
The iterative application of non-linear function is used to
classify the pixel and the applied function progressively
improving the separation gray level, thereby the
difference between corrupted and uncorrupted pixel is
increased [4]. The triangle-based linear interpolation
algorithm with optimized tuning parameters using the
differential evolution algorithm is used to classify the
pixels and to enhance the details while filtering [5].
The sorted quadrant median vector (SQMV) scheme
proposed by Chih-Hsing Lin et al, [7] utilizes the edge
and texture information to classify the corrupted noise
as impulse noise, Gaussian noise, or noise-free. The
advanced boundary discriminative noise detection
algorithm compares the difference between the pixel of
interest and the pixels with high and low intensity in the
window considered [7] and hence the current pixel can be
classified. The pixels are divided into four groups using
the robust outlyingness ratio (ROR) by Bo Xiong et al [8]
and different decision rules are used to find the corrupted
pixel using an iterative framework. The decision-treebased impulse noise detector used by Chih-Yuan Lien
et al [9] along with edge-preserving filter reconstructed
the intensity value of noisy pixels and the corresponding
VLSI architecture run with a speed of 200MHz by using
TSMC 0.18µm technology. A difference type noise
detector proposed by S.-Q. Yuan et al [10] improves the
misclassification and proves to be efficient.
A novel operator proposed acts as a hybrid filter
obtained by appropriately combining a median filter,
56 HINDUSTAN JOURNAL, VOL. 6, 2013
an edge detector, and a neuro-fuzzy network and the
most distinctive feature of the proposed operator over
most other operators is that it offers excellent line,
edge, detail, and texture preservation performance
while, at the same time, effectively removing noise
from the input image [14]. A new filtering scheme
based on contrast enhancement within the filtering
window is proposed and it filters the image iteratively
till the stopping criteria [15]. A novel filtering scheme
based on threshold Boolean filtering, where the binary
slices of an image are implemented is proposed in [16].
A modified boundary discriminative noise detection
(BDND) is a powerful class of filters which effectively
filters the image corrupted by impulse noise [17].
To make an accurate decision, an iterative switching
median is used along with two robust and reliable
decision criteria [18]. A switching bilateral filter (SBF)
with a texture and noise detector for universal noise
removal is proposed in [19] and the sorted quadrant
median vector (SQMV) scheme includes important
features such as edge or texture information.
The sub windows are denoted by W 1 , W 2 , ...W 12 .
i, j
i, j i, j
the pixels considered centered around (i , j ) and are
given as follows:
1
W = {(i − 2, j + 2), (i − 1, j + 1), (i − 1, j + 2), (i , j + 1),
i, j
(i , j + 2), (i + 1, j + 1), (i + 1, j + 2), (i + 2, j + 2)}
2
W = {(i + 1, j − 1), (i + 1, j + 1), (i + 1, j + 2), (i + 2, j − 2),
i, j
(i + 2, j − 1), (i + 2, j ), (i + 2, j + 1), (i + 2, j + 2)}
3
W = {(i − 2, j − 2), (i − 1, j − 2), (i − 1, j − 1), (i , j − 2),
i, j
(i , j − 1), (i + 1, j − 2), (i + 1, j − 1), (i + 2, j − 2)}
4
W = {(i − 2, j − 2), (i − 2, j − 1), (i − 2, j ), (i − 2, j + 1),
i, j
(i − 2, j + 2), (i − 1, j − 1), (i − 1, j ), (i − 1, j + 1)}
5
W = {(i + 1, j − 1), (i + 1, j ), (i + 1, j + 1),
i, j
(i + 2, j − 1), (i + 2, j ), (i + 2, j + 1)}
II.  Review of the State of the Art Impulse
Noise Detectors
A. Statistics based Noise Detectors
Various statistics-based noise detectors [4, 13] have
emerged with robust performance in terms of noise
detection. These noise detectors play a vital role to
detect the noisy pixel in a given image, so that the
detected noisy pixels can be replaced with a predicted
pixel value by suitable filters.
The most recent and widely used noise detectors are,
ROAD, ROLD, MAD, S-Estimate. A detailed analysis
of these techniques are available in the literature.
III.  Impact of Directional Sub-Windows on
Noise Detection
We use a 5X5 main window for detecting noise
pixels even in highly corrupted images. Any of the
twelve sub-windows can be chosen from the 5X5
main window based on the spatial distribution of the
noise pixels. By decomposing the main window into
various sub-windows, the corrupted pixels in the edges
can be calculated. Thus including the directionality in
detecting the corrupted pixels certainly improves the
detector efficiency.
6
W = {(i − 1, j − 1), (i − 1, j ), (i − 1, j + 1),
i, j
(i − 2, j − 1), (i − 2, j ), (i − 2, j + 1)}
7
W = {(i − 1, j + 1), (i − 1, j + 2), (i , j + 1),
i, j
(i , j + 2), (i + 1, j + 1), (i + 1, j + 2)}
8
W = {(i − 1, j − 1), (i − 1, j ), (i − 1, j + 1), (i , j − 1),
i, j
(i , j + 1), (i + 1, j − 1), (i + 1, j ), (i + 1, j + 1)}
9
W = {(i − 1, j − 2), (i − 1, j − 1), (i , j − 2),
i, j
(i , j − 1), (i + 1, j − 2), (i + 1, j − 1)}
10
W
= {(i − 2, j + 1), (i − 2, j + 2), (i − 1, j ),
i, j
(i − 1, j + 1), (i − 1, j + 2), (i , j + 1)}
11
W = {(i , j − 1), (i + 1, j − 2), (i + 1, j − 1),
i, j
(i + 1, j ), (i + 2, j − 2), (i + 2, j − 1)}
12
W
= {(i , j + 1), (i + 1, j ), (i + 1, j + 1),
i, j
(i + 1, j + 2), (i + 2, j + 1), (i + 2, j + 2)}
13
W = {(i − 2, j − 2), (i − 2, j − 1), (i − 1, j − 2),
i, j
(i − 1, j − 1), (i − 1, j ), (i , j − 1)}
PRIYA AND SESHASAYANAN: IMPROVING THE EFFICIENCY OF IMPULSE NOISE ESTIMATION 57
of the kernel chosen. The window size can be varied
depending on the noise densities and can be dynamically
updated for each centre pixel considered. The whole
process is carried out for the complete image covering
all the pixels segmented from the original image which
have the foreground details.
The noise detection for the various noise densities is as
follows:
x (i , j ) ∈ (Tmax , Tmin ) , where (Tmax, Tmin) are the
1. threshold values from histogram of the given
image.
Fig. 1. Sub-Windows with various shapes
The coordinates of the sub-windows are shown
in figure. 1 and are expressed as equations. From an
exhaustive simulation performed on various images, we
found that these thirteen sub-windows are suitable for
a 5X5 window considered. For increased noise density
the size of the window will be increased preserving the
shape of the sub-windows. A decision based algorithm
tracks the output of each of the sub-windows based on
the hierarchical ROAD (HR) value (i.e) ROAD based
on the cumulative rank (CR).
IV.  Iterative and Adpative estimation using
s-estimate
To estimate the rician noise in a rician distributed image,
we follow an iterative and adaptive procedure which
involves the calculation of S-estimate dynamically
changing the window size from 5×5 to 21×21, based on
the amount of noise pixels in the given local region. The
S-estimate is calculated by taking a 5×5 window with
various kernel directions and based on the threshold
value (T), the centre pixel in the original image is
flagged noisy. Based on the S-estimate computed for all
the directional sub-windows, the pixel can be flagged
as corrupted or not.
V.  Algorithm for Adaptive S-Estimate Based
Estimation of Rician Noise
The S-estimate calculated for a pixel of interest is
not robust enough if the window size considered is
constant and the performance of the estimation based
on S-estimate can be improved by choosing the size
2. S ( k ) = med i {med j ti − t j } and calculate S(k)
over the window(x,y), where x, y = −(2n + 1) to
+ (2 n + 1) and k = 1, 2, 3...(2 n + 1)
2
3. The S-estimate S(k) is synthesized for window size
of different lengths. The optimum window size for
the local region is fixed based on the S-estimate and
the threshold values, thus dynamically changing
the window size will yield the best estimation for
various noise levels.
4. Incremental S-index values = sort the estimated S
values [S(1), S(2), … , S(2n+1),]
5. max(i , j ) = max ( S ( k ) ) .
From the maximum obtained S(k) and the threshold
value and the value of the centre pixel taken, the pixel
can be flagged corrupted or un-corrupted by Rician
noise. This procedure can be iterated till the stopping
criteria has been accomplished or for a predefined
number of iterations.
VI.  Comparison of Noise Detection
Performance
The quality of the noise detector can be assessed
based on its accuracy of detecting the corrupted pixel
and also it should not misinterpret the uncorrupted
pixel as corrupted. Hence we assess the quality
of the noise detector using the fundamental two
metrics [3].
• N
f denotes the number of noise-free pixels wrongly
classified as corrupted.
• N
m denotes the corrupted pixels which are
misclassified as noise free one.
58 HINDUSTAN JOURNAL, VOL. 6, 2013
Using the Nf and Nm values for a given image the
quality assessment of the detector can be performed.
It is easy to detect a corrupted pixel when the image is
corrupted only by salt and pepper noise.
Fig. 2. Dependency between rank of ROAD and the amount
of noise added
If the image is corrupted by random value
impulse noise, the detection process is tedious as the
randomness of the pixel value increases the complexity
of the detection process. There are few well known
techniques, such a SD-ROM and ACWM filters with
good detector performance, but they fail to maintain
both the Nf and Nm value simultaneously. Fig. 2 shows
the plot between applied noise percentage and the
number of noise pixels detected for various ranks. The
rank value indicates the least absolute difference values
considered while calculating ROAD. We call this
as DROAD, and stands for Dynamic ROAD, which
dynamically selects the number of absolute differences
that should be considered when concluding a pixel as
corrupted. The plot in Fig.3 clearly shows that, the
detection strictly depends on the rank value chosen for
various noise percentages. From Fig.2 the rank value
of 5 has peak detection for 55% noise which is again
confirmed in Fig.3.
Fig. 3. Number of corrupted pixels detected
for various ranks
Table 1. Noise
Noise
level
detected (%) for various CR
Cumulative Rank (CR)
1
2
3
4
5
6, 7
5%
22.85
39.65
64.15
85.24
97.31
99.10
10%
22.80
39.06
62.32
82.49
95.08
97.20
15%
22.46
38.40
60.25
79.63
93.13
95.51
20%
22.11
37.64
58.34
76.95
91.36
94.18
25%
21.35
36.40
55.93
73.92
89.44
92.82
30%
20.51
34.63
53.20
70.87
87.52
91.29
35%
19.57
33.04
50.64
68.00
85.62
89.77
40%
18.61
31.19
47.92
65.06
83.55
87.87
45%
17.70
29.20
45.18
62.33
81.49
86.06
50%
16.79
27.15
42.48
59.66
79.27
84.01
55%
16.11
25.68
40.39
57.69
77.44
82.12
60%
15.51
24.08
38.22
55.75
75.34
79.97
65%
14.93
22.85
36.61
54.15
73.30
77.74
70%
14.41
21.64
34.95
52.41
70.99
75.16
75%
14.26
21.12
34.33
51.79
69.19
73.00
80%
13.98
20.68
34.03
51.10
67.15
70.56
The plot between various rank values and the number of
corrupted pixels detected by the detector is depicted in Fig.
4. From the simulation conducted, a rank value of 3 and 5
will be suitable for better detector performance. To further
increase the efficiency of the detector, we go for finding
the hierarchical dynamic ROAD (HDROAD), where the
decision is based on the cumulative rank (CR) value. A
CR=1 indicates that ROAD value corresponding to rank=1
are considered by the detector. A CR=7 shows that the
ROAD values pertaining to rank = 1 to 7 are considered.
From the simulation performed, the detection performance
increases as CR value increases and gets saturated when
CR=5 as shown in Fig. 4. This techniques is called as
HDROAD, where the dynamicity is in terms of window
size, shape and the rank of ROAD. Table I shows the data
of noise detected for various CR. Table II compares the
estimation efficiency of HD-ROAD and the S-Estimate.
Fig. 4. Detector performance for various Cumulative
Ranks (CR)
PRIYA AND SESHASAYANAN: IMPROVING THE EFFICIENCY OF IMPULSE NOISE ESTIMATION 59
Table 2. Comparison of HD ROAD and S-Estimate based
Estimation Techniques
Noise level
HDROAD with
Bets CR
S-Estimate with
Dynamic Kernel
5%
99.10
99.33
10%
97.20
98.02
15%
95.51
96.21
20%
94.18
95.30
25%
92.82
93.27
30%
91.29
92.31
35%
89.77
90.56
40%
87.87
89.03
45%
86.06
87.29
50%
84.01
85.32
55%
82.12
83.75
60%
79.97
81.92
65%
77.74
78.99
70%
75.16
77.07
75%
73.00
75.76
80%
70.56
72.43
VII.  Conclusion
The noise estimation algorithm based on HDROAD
with best CR and the estimation based on S-Estimate
are compared. S-Estimate is applied for all the
directional sub-windows and the best known value
and hence the best decision taken is considered further.
Certainly, the S-Estimate applied for various directional
kernels improve the efficiency of noise estimation.
The improvement in the noise etimation efficiency
gives more freedom to improve the efficiency of the
noise removal filters. The calculation of S-Estimate
is a computationally heavy process and needs to
be optimized to make it suitable for fast estimation
intended for real-time scenarios.
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HINDUSTAN JOURNAL, VOL. 6, 2013
Review of Cyclic Redundancy Checking Algorithm
Prakash V R and Kumaraguru Diderot P
Abstract — Cyclic redundancy check (CRC) is
a traditionally used error detection method in
networks. This paper describes CRC algorithm using
the long division method and the representation of
binary stream of data in polynomial form. CRC
using modulo-2 arithmetic has also been explained.
The algorithm is more useful in areas where memory
requirement is limited.1,
Index Term — Cyclic Redundancy Check, Algorithm,
Polynomials.
I.  Introduction
CRC [1] is a very powerful and easily implemented
technique to obtain data reliability. The CRC technique
is used to verify the integrity of blocks of data called
Frames. Using this technique, the transmitter appends an
extra n bit sequence to every frame called Frame Check
Sequence (FCS). FCS holds redundant information
about the frame that helps the receiver detect errors
in the frame. CRC is one of the most commonly used
techniques for error detection in data communications.
The CRC was invented by W. Wesley Peterson in
1961; the 32-bit polynomial used in the CRC function
of Ethernet and many other standards is the work of
several researchers and was published in 1975.Cyclic
redundancy codes (also known sometimes as cyclic
redundancy checks) have a long history of use for error
detection in computing. Book [2][3] are among the
commonly cited standard reference works for CRCs.
A treatment more accessible to non-specialists can
be found in book [4]. A CRC can be thought of as a
(non-secure) digest function for a data word that can
Prakash V R and Kumaraguru Diderot P are in
School of Electrical Sciences, Hindustan University,
Chennai, India, (e-mail: [email protected],
[email protected]).
be used to detect data corruption. Mathematically, a
CRC can be described as treating a binary data word as
a polynomial over GF (2) (i.e., with each polynomial
coefficient being zero or one) and performing
polynomial division by a generator polynomial [5]
G(x). The generator polynomial will be called a CRC
polynomial for short. CRC polynomials are also known
as feedback polynomials, in reference to the feedback
taps of hardware-based shift register implementations.
The remainder of that division [6] operation provides
an error detection value that is sent as a Frame Check
Sequence (FCS) within a network message or stored
as a data integrity check. Whether implemented in
hardware or software, the CRC computation takes the
form of a bitwise convolution of a data word against a
binary version of the CRC polynomial. Error detection
[7] is performed by comparing an FCS computed on a
piece of retrieved or received data against the FCS value
originally computed and either sent or stored with the
original data. An error is declared to have occurred if
the stored FCS and computed FCS values are not equal.
However, as with all digital signature schemes, there
is a small, but finite, probability that a data corruption
that inverts a sufficient number of bits in just the right
pattern will occur and lead to an undetectable error. The
minimum number of bit inversions required to achieve
such undetected errors (i.e., the HD value) is a central
issue in the design of CRC polynomials.
The essence of implementing a good CRC-based error
detection scheme is picking the right polynomial.
The prime factorization of the generator polynomial
brings with it certain potential characteristics, and in
particular gives a trade-off between maximum numbers
of possible detected errors vs. data word length for
which the polynomial is effective. Many polynomials
are good for short words but poor at long words, and
the converse. There are relatively few polynomials
that are excellent for medium-length data words
while still being good for relatively long data words.
62 HINDUSTAN JOURNAL, VOL. 6, 2013
Unfortunately, prime factorization of a polynomial is
not sufficient to determine the achieved HD value for
any particular message length. A polynomial with a
promising factorization might be vulnerable to some
combination of bit errors, even for short message
lengths. Thus, factorization characteristics suggest
potential capabilities, but specific evaluation is required
of any polynomial before it is considered suitable for
use in a CRC function.
II.  The CRC Generation Process
CRC algorithms augment bit streams with functions of
the content of the streams. In this way it is easier for
CRC algorithms to detect errors. To avoid self-failures
the functions used by CRC algorithms need to be as
‘close’ to 1:1 as possible. CRC algorithms treat each
bit stream as a binary polynomial B(x) and calculate
the remainder R(x) from the division of B(x) with a
standard ‘generator’ polynomial G(x). The binary
words corresponding to R(x) are transmitted together
with the bit stream associated with B(x). The length of
R(x) in bits is equal to the length of G(x) minus one.
At the receiver side CRC algorithms verify that R(x)
is the correct remainder. Long division is performed
using modulo-2 arithmetic. Additions and subtractions
in module-2 arithmetic are ‘carry-less’. In this way
additions and subtractions are equal to the exclusive OR
(XOR) logical operation. Table 1 shows how additions
and subtractions are performed in modulo-2 arithmetic.
Table 1: Modulo-2 Arithmetic
0+0 = 0-0 = 0
dividend is equal to ‘1000111011000’. The long division
process begins by placing the 5 bits of the divisor below
the 5 most significant bits of the dividend. The next step
in the long division process is to find how many times
the divisor ‘11011’ ‘goes’ into the 5 most significant
bits of the dividend ‘10001’. In ordinary arithmetic
11011 goes zero times into 10001 because the second
number is smaller than the first. In modulo-2 arithmetic,
however, the number 11011 goes exactly one time into
10001. To decide how many times a binary number goes
into another in modulo-2 arithmetic, a check is being
made on the most significant bits of the two numbers.
If both are equal to ‘1’ and the numbers have the same
length, then the first number goes exactly one time into
the second number, otherwise zero times. Next, the
divisor 11011 is subtracted from the most significant
bits of the dividend 10001 by performing an XOR
logical operation. The next bit of the dividend, which
is ‘1’, is then marked and appended to the remainder
‘1010’. The process is repeated until all the bits of the
dividend are marked. The remainder that results from
such long division process is often called CRC or CRC
‘checksum’ (although CRC is not literally a checksum).
Figure 2: Accelerating the Long Division Using Table
Lookups [8][9]
0+1 = 0-1 = 1
Figure
1+0 = 1-0 = 1
III.  Polynomial Arithmatic
1+1 = 1-1 = 0
While the division scheme described in the previous
section is very similar to the check summing schemes
called CRC schemes, the CRC schemes are in fact a bit
weirder, and we need to delve into some strange number
systems to understand them. The word you will hear
all the time when dealing with CRC algorithms [10] is
the word “polynomial”. A given CRC algorithm will
be said to be using a particular polynomial, and CRC
algorithms in general are said to be operating using
polynomial arithmetic. Instead of the divisor, dividend
(message), quotient, and remainder being viewed as
positive integers, they are viewed as polynomials
with binary coefficients. This is done by treating each
1: Long Division using Modulo-2 Arithmetic
Figure 1 shows a long division example. In the
example, the divisor is equal to ‘11011’ whereas the
PRAKASH AND KUMARAGURU DIDEROT : REVIEW OF CYCLIC REDUNDANCY 63
number as a bit-string whose bits are the coefficients
of a polynomial. For example, the ordinary number
23 (decimal) is 17 (hex) and 10111 binary and so it
corresponds to the polynomial:
1*x^4 + 0*x^3 + 1*x^2 + 1*x^1 + 1*x^0
or, more simply:
x^4 + x^2 + x^1 + x^0
Using this technique, the message, and the divisor
can be represented as polynomials and we can do all
our arithmetic just as before, except that now it’s all
cluttered up with Xs.
IV.  Binary Arithmatic With No Carries
Adding two numbers in CRC arithmetic is the same
as adding numbers in ordinary binary arithmetic
except there is no carry. This means that each pair
of corresponding bits determines the corresponding
output bit without reference to any other bit positions.
For example:
10011011
+11001010
------------01010001
------------There are only four cases for each bit position:
0+0=0
0+1=1
1+0=1
1+1=0 (no carry)
Subtraction is identical:
10011011
-11001010
------------01010001
------------with
0-0=0
0-1=1 (wraparound)
1-0=1
1-1=0
In fact, both addition and subtraction in CRC
arithmetic are equivalent to the XOR operation, and
the XOR operation is its own inverse. This effectively
reduces the operations of the first level of power
(addition, subtraction) to a single operation that is its
own inverse. This is a very convenient property of the
arithmetic.
By collapsing of addition and subtraction, the
arithmetic discards any notion of magnitude beyond
the power of its highest one bit. While it seems clear
that 1010 is greater than 10, it is no longer the case that
1010 can be considered to be greater than 1001. To see
this, note that you can get from 1010 to 1001 by both
adding and subtracting the same quantity:
1010 = 1010 + 0011
1010 = 1010 - 0011
This makes nonsense of any notion of order. Having
defined addition, we can move to multiplication and
division. Multiplication is absolutely straightforward,
being the sum of the first number, shifted in accordance
with the second number.
1101
x
1011
-------1101
1101.
0000
1101.
---------1111111 Note: The sum uses CRC addition
----------Division is a little messier as we need to know when
“a number goes into another number”. To do this, we
invoke the weak definition of magnitude defined earlier:
that X is greater than or equal to Y iff the position of
the highest 1 bit of X is the same or greater than the
position of the highest 1 bit of Y. In dealing with CRC
multiplication and division, it is worth getting a feel for
the concepts of MULTIPLE and DIVISIBLE.
64 HINDUSTAN JOURNAL, VOL. 6, 2013
If a number A is a multiple of B then what this
means in CRC arithmetic is that it is possible to
construct A from zero by XORing in various shifts of
B. For example, if A was 0111010110 and B was 11, we
could construct A from B as follows:
0111010110
=
.......11……
+....11...........
+...11............
.11...............
However, if A is 0111010111, it is not possible to
construct it out of various shifts of B so it is said to be
not divisible by B in CRC arithmetic. Thus we see that
CRC arithmetic is primarily about XORing particular
values at various shifting offsets.
The division yields a quotient, which we throw
away, and a remainder, which is the calculated
checksum. This ends the calculation. Usually, the
checksum is then appended to the message and the
result is transmitted. In this case the transmission would
be: 11010110111110. At the other end, the receiver can
do one of two things:
a. Separate the message and checksum. Calculate
the checksum for the message (after appending W
zeros) and compare the two checksums.
b. Checksum the whole lot (without appending zeros)
and see if it comes out as zero!
simply use the divide instruction of whatever machine
we are on. The first is that we have to do the divide in
CRC arithmetic. The second is that the dividend might
be ten megabytes long, and today’s processors do not
have registers that big. So to implement CRC division,
we have to feed the message through a division register.
At this point, we have to be absolutely precise about
the message data. In all the following examples the
message will be considered to be a stream of bytes
(each of 8 bits) with bit 7 of each byte being considered
to be the most significant bit (MSB). The bit stream
formed from these bytes will be the bit stream with
the MSB (bit 7) of the first byte first, going down to
bit 0 of the first byte, and then the MSB of the second
byte and so on. With this in mind, we can sketch an
implementation of the CRC division. For the purposes
of example, consider a polynomial with W=4 and the
polynomial=10111. Then, perform the division; we
need to use a 4-bit register:
The augmented message is the message followed
by W zero bits.) This might look a bit messy, but all
we are really doing is “subtracting” various powers
(i.e. shifting) of the polynomial from the message until
there is nothing left but the remainder.
VI CRC Software Implementation
These two options are equivalent. However, in the
next section, we will be assuming option b because it is
marginally mathematically cleaner.
Following are the steps for implementing a CRC in
software. The steps for CRC computation are followed
at the transmitter side and that for CRC Checking are
followed at the receiver side.
A summary of the operation of the class of CRC
algorithms:
Steps of CRC computation at transmitter
1. C
hoose a width W and a polynomial G (of width
W).
3. D
ivide M’ by G using CRC arithmetic. The
remainder is the checksum.
●● T
o compute an n-bit binary CRC, line the bits
representing the input in a row, and position the
(n+1)-bit pattern representing the CRC’s divisor
(called a “generator polynomial”) underneath the
left-hand end of the row.
V. CRC Implementation
●● S
tart with the message to be encoded: 10001110 =
X7 + x 3 + x 2 +x 1
2. Append W zero bits to the message. Call this M’.
To implement a CRC algorithm all we have to do is
CRC division. There are two reasons why we cannot
●● T
his is first padded with zeroes corresponding to the
bit length n of the CRC. Here is the first calculation
for computing a 16-bit CRC:
PRAKASH AND KUMARAGURU DIDEROT : REVIEW OF CYCLIC REDUNDANCY 65
10001110 0000000000000000 <--- input right padded
by 16 bits
10001000000100001
x16+x12+x5+1
<---
divisor
(17
bits)
=
--------------------------------------------
checks its MSB bit. If value of MSB is ‗0‘ then data is
copied as it is into temporary register r1 otherwise the
data is XOR‘ed with the generator polynomial to store
the result in the register r1. Then data is left shifted by
one bit and same operation is repeated.
000001100001000010000000 <--- result
At last the result of CRC computation called as
checksum is assigned to crc register.
Three Steps
reg [7:0] message;
The divisor is XOR‘ed into the input
reg [16:0] poly; // store generator polynomial
Note: in other words, the input bit above each 1-bit in
the divisor is toggled
reg[23:0] data_in1;
The divisor is then shifted one bit to the right, and
the process is repeated until the divisor reaches the
right-hand end of the input row. Here is the entire
calculation:
●● 1 00011100000000000000000 <--- input right
padded by 16 bits
●● 10001000000100001 <--- divisor
●● 000001100001000010000000 <--- result
●● 10001000000100001 <--- divisor
●● 0100101000000000100 <--- result
●● 10001000000100001 <--- divisor
●● ----------------- -------------------------●● 0111000001000110 <---remainder (16 bits)
reg[16:0] r1; // to store intermediate result
reg [15:0] crc; // output port to store crc
computation result i.e checksum
integer i; // loop counter
poly = 17’b10001000000100001;
always @ (data_in1, message)
begin
data_in1 = {message, 16’b0000000000000000}; //
append 16 zero bits to the message
if (data_in1[23] == 0)
r1 = data_in1[23:7];
else
r1 = data_in1[23:7] ^ poly[16:0];
Since the leftmost divisor bit zeroed every input bit it
touched, when this process ends the only bits in the
input row that can be nonzero are the n bits at the righthand end of the row. These n bits are the remainder of
the division step, and will also be the value of the CRC
function called as checksum.
for (i = 6; i >=0; i = i-1)
●● T
he validity of a received message can easily be
verified by performing the above calculation again,
this time with the check value added instead of
zeroes.
else
The remainder should equal zero if there are no
detectable errors.
end
Algorithm of Software Implementation
CRC is basically used to detect errors from noise
in digital data transmission. The technique is also
sometimes applied to data storage devices, such as
a disk drive. They also have been turned to verify
the integrity of files in a system in order to prevent
The program initializes the register named ‗poly‘ to
binary value of CRC-CCITT generator polynomial
equivalent, appends 16 zero bits to the message and
begin
r1 = {r1[15:0], data_in1[i]};
if (r1[16] == 0)
r1 = r1;
r1 = r1 ^ poly;
end
VII Conclusion
66 HINDUSTAN JOURNAL, VOL. 6, 2013
tampering and suggested as a possible algorithm for
manipulation detection codes.
References
[1] H
ardware Design and VLSI Implementation
of a Byte-wise CRC Generator Chip. IEEE
Transactions on consumer Electronics, 41 (1):
195-200, February 1995.
[2] P
eterson, W. & E. Weldon, Error-Correcting
Codes, MIT Press, Second Edition, 1972.
[3] L
in, Shu & D. Costello, Error Control Coding,
Prentice-Hall, 1983.
[4] W
ells, R., Applied coding and information theory
for engineers, Prentice-Hall, 1999.
[5] T
. B. Pei and C. Zukowski (1992), “HighSpeed Parallel CRC Circuits in VLSI”, IEEE
Transaction on Communications, vol. 40, no. 4.
[6] M
. Braun, J. Friedlich, J. Lembert, and Grun,
Parallel CRC computation in FPGAs, FPL’96
Workshop on Field Programmable Logic
and Applications, Darmstadt, Germany, Sep.
1996.
[7] P
. Hlavka, V. Rehak, A. Smrcka, P. Simecek, D.
Safranek, and T. Vojnar, 2011, supported by the
CESNET activity ―Programmable hardware.
Formal Verification of the CRC Algorithm
Properties.
[8] A
n approach for a Standard Polynomial for
Cyclic.
[9] R
edundancy Check. International Journal of
Computer.
[10] Applications (0975 – 8887), December 2011.
[11] L
attice semiconductorCorporation, April 2011
Reference Design RD1105. Cyclic Redundancy
Checks in USB.
HINDUSTAN JOURNAL, VOL. 6, 2013
Optimization of Temporally Ordered Routing Algorithm
(TORA) in Ad-hoc Network
D. Helen and D. Arivazhagan
Abstract — The Temporally Ordered Routing
Algorithm (TORA) is a distributed routing protocol
for ad-hoc network. TORA is able to operate more
effectively whenever the topological variations
occur. TORA is a reactive protocol, the routes are
formed between source to destination on a demand
basis. TORA proceeds with the link reversal
algorithm and Directed Acyclic Graph (DAG) to
sustain the path at the destination. The topological
diversity may affect the network parameters such as
network size, bandwidth and network connection.
If the network size is increased then the usage of
the available bandwidth is decreased. It indicates
the delay in the transmission. TORA can be put
on Medium Access Control (MAC), to provide the
multi-hop routing. In this paper, use of TORA along
with MAC is proposed to overcome the bandwidth
limitation. The bandwidth usage may increase by
introducing multiple channel with different rates.
The network can be utilized most effectively by
using multiple channels in the network.1,2
Index terms — Distributed, Topology, Reactive,
Multi-hop, Bandwidth, Channel.
I.  Introduction
Ad-hoc networks are formed without any predefined
architecture [14, 15]. The ad-hoc network is dynamic,
distributed [7] and provides multi-hop routing between
D. Helen is Research Scholar, Department of
Information Technology, AMET University , Chennai.
(e-mail: [email protected]).
D. Arivazhagan is HOD, Department of Information
Technology, AMET University , Chennai. (e-mail: it_
[email protected]).
the host and the network. The TORA [1] is an adhoc network, where it is planned to recreate the route
whenever the topology has altered. TORA guarantees
that the routes are created loop-free, and provide
numerous routes between source to destination [2].
TORA can also perform more efficiently at the point
of link flops and it can propagate the data packets from
the point of link failure. TORA works more reliably in
a larger network whenever the topology modification
has ensued. The network shape may vary whenever the
topological changes have to occur. This may degrade the
network parameters such as network size, bandwidth
and connection. If the network size is expanded then the
bandwidth availability will be reduced in the network.
In the proposed paper, the bandwidth utilization is
enhanced by using multiple channel in the ad-hoc
network. This can be achieved by applying the TORA
in Medium Access Control (MAC). The MAC is widely
accepted by IEEE 802.11 [17]. The MAC protocol is
used to share the medium by several hosts. The paper
plans to use multiple channel according to the MAC
protocol which allows the increase of the throughput
without delay in packet delivery.
II.  Protocol Overview
The Temporally Ordered Routing Algorithm (TORA) is
an efficient routing protocol. The goal of the protocol is
to utilize the bandwidth most effectively in the network
when the topological fluctuations happen. The process of
the protocol can be described in the following way. The
origin host wants to define the path to the target. Routes
are reestablished whenever the topological variation
occurs. TORA performs effectively during the topology
alteration and network partition. The idea of the protocol
is to increase the bandwidth utilization by introducing
multiple channel with different rates in the ad-hoc
network. The TORA can work on every destination
68 HINDUSTAN JOURNAL, VOL. 6, 2013
during routing. TORA routine uses three control packets.
They are, Query (QRY), Update (UPD) and Clear
(CLR). QRY packets are used by the originating host
to examine the destination host. This examination is
accomplished via flooding [10]. Update (UPD) packets
are needed to arrange and remain with the routes. During
route arrangement and preservation every host maintains
a rate which is determined by the height of the host.
Links are assigned from the origin to the target with the
height of the neighboring host. CLR packets are used
to eradicate the routes. Detaching of the route happens,
when the host is no longer needed or during network
partition. The elimination of route at the host is fixed and
its height is null. Thus the bandwidth upstairs may be
reduced by introducing multiple channel in the network.
The network information may be upgraded during the
topological change and link failure. The illegal links are
removed by the update and packets are cleared.
III.  Process of TORA
TORA fundamentally performs the following functions
to form the network:
Route Formation: The route must be created from
the original host to the neighbor host. The routes are
created with directed links from the source to target.
Route Maintenance: The routes are recreated
whenever the topological changes occur or during
network partition.
Route Elimination: The routes are deleted whenever
the links are no longer needed and all the invalid routes
are detached from the network.
TORA builds the network with Directed Acyclic
Graph (DAG) at the destination. The path in the
DAG is directed depending upon the height of the
neighboring host. During the topological change,
routes are renewed instantly at the destination.
Relation to the adjacent host with an unacquainted or
null height is considered as an undirected link which
is not used for flooding. The route creation technique
converts an undirected network into a DAG at the end
point by conveying direction to the links. A graph
G(H,E) is a directed graph with H host and E edges
and each edge in the graph has a related path. The
graph without any cycle is known as DAG as shown
in fig 1. Link Reversal algorithm works with DAG.
If there is no downlink in the network link reversal
algorithm changes the direction of the path.
Fig. 1. Overview of the Directed Acyclic Graph (DAG).
Each destination, has a quintuple which is related
to every host. A new reference level is defined every
time when a host drops its last downlink due to the
network partition. The quintuple is defined as
H=(τi, oidi, ri, δi, i)
where τi - time of a network partition
oidi-Source ID used to define the reference level
ri - single bit where 0 indicates an exclusive level
and 1 indicates a replicated level
δi - common reference level
i - host ID
The quintuple describes the host. The height of two
hosts may be the same depending on their reference
level. Assume that “i” is the original host and “j” is
the neighbor host. If the height of “j” is greater than
“i” then the link is uplink from “i” to “j”, otherwise
it is downlink. Whenever the host “i” has a fresh
neighbor “k”, host “i” accommodates the new host by
determining the height to the new host and preserves
the link situation in an array.
IV.  Link Reversal Algorithm in TORA
In situation, such as, when the host has no downstream
link to the network in DAG, the link reversal algorithm
works most effectively. The algorithm, changes the
direction of the link in DAG whenever the host does
not have any downstream link. The link reversal is
done in a two ways [13]:
1) Full Reversal Method: In this method each host
other than target does not have any outbound link in
which situation it reverses the direction of the entire
network.
2) Partial Reversal Method: Each host maintains
the list of its neighbor hosts. The reversal method
HELEN AND ARIVAZHAGAN: OPTIMIZATION OF TEMPORALLY ORDERED ROUTING ALGORITHM 69
changes the direction if the host does not belong to that
list. Fig: 2 explains the link creation and maintenance
according to TORA.
Fig. 2. (a) Foot creation (showing link direction assignment) (b) Route maintenance in TORA.
VI.  Simulation Results
The throughput of the TORA is based on the number of
packets spread in the network. The throughput of the host
is compared between TORA and LMR (Light Weight
Mobile Routing) [12]. Fig. 3 shows that TORA performs
more effectively than LMR based on the network
utilization. The throughput is increased by using TORA
along with multiple channel MAC protocol. Thus the
average delay between source and destination may be
overcome by increase in the network utilization. Output
of fig 3 illustrates that TORA is better than LMR in the
sense that bandwidth utilization is increased by using
TORA along with the MAC protocol.
Bandwidth Utilization
V.  Applicability of TORA
Whenever the topological deviation has occurred it
may affect the following parameters of the network.
●● Network Size.
●● Bandwidth.
●● Network Connection.
TORA is able to work more effectively in a larger
network. If the network structure changes due to the
arrival of a new entering node it leads to increase in the
size of the network, decrease in the available bandwidth
usage and makes alteration in the network connection.
One of the unique characters of ad-hoc network is the
limited bandwidth. If the network size is increased
or network connection is extended then the available
bandwidth usage may decrease and it may lead to delay
in packet delivery. TORA can apply Medium Access
Control (MAC), to run in a multi-hop environment. To
overcome the delay in packet delivery in the proposed
paper, we propose multiple channels with different
bandwidths. Using multiple channels allows maximum
utilization of bandwidth in the network. The utilization
can be measured as
Utilization=pkt_size * successful_pkt time * no_channel
where pkt_size refers the total number of bits in the
packet, successful_pkt determines number of packets
received by destination, time represents the average
time to deliver the packet and no_channel is the total
number of channels in the network.
Fig. 3. Bandwidth Utilization TORA vs LMR
VII.  Conclusion
This paper suggested the extreme distributed routing
algorithm TORA. The algorithm is well matched for a
ad-hoc network. The protocol is scheduled to recreate
the network whenever the links get fragmented. The
TORA combines with link reversal algorithm and DAG
to sustain the route at the destination. The paper has
proposed the use of the TORA along with MAC to
increase the network utilization to overcome the limited
usage of bandwidth.
References
[1] R
oyer, E.; Toh C.K. (1999) “A review of current
routing protocols for ad hoc mobile wireless
networks”, IEEE Personal communications,
pp.46-55
70 HINDUSTAN JOURNAL, VOL. 6, 2013
[2] J. Jaffe and F. Moss, “A responsive distributed
routing algorithm for computer networks”, IEEE
Transaction on Communications, COM-30,
No.7, 1982.
[3] E
. Gafni and D. Bertsekas, “Distributed
algorithms for generating loop-free routes in
networks with frequently changing topology”,
IEEE Transaction on Communications, COM-29,
No.1, 1981.
[4] S
.Murthy and J.J GarciaLuna Aceves, “An
Efficient Routing Protocol for Wireless
Networks,” ACM Journal of Mobile Networks
and Applications, Special issue on Routing in
Mobile Communication Networks, Vol.1, No.2,
pp.183-197, 1996
[5] P
ark, V., Corson, M. S: “A performance
comparison of TORA and Ideal Link-State
routing”, USA.
[6] C
Perkins and P. Bhagwat, “Highly dynamic
destination sequenced distance vector routing
(DSDV) for mobile computers”, ACM
SIGCOMM.
[7] C
. E. Perkins, E. M. Royer, and S. R. Das, “Ad
Hoc On- Demand Distance Vector (AODV)
Routing”, Internet Draft, draft-ietf- manetaodv10.txt, work in progress, 2002.
[8] A
nuj K. Gupta, Dr. Harsh Sadawarti and Dr.
Anil K. Verma, “Performance analysis of AODV,
DSR & TORA Routing Protocols,” International
Journal of Engineering and Technology, Vol.2,
No.2, 2010.
[9] S
uresh
Kumar
and
Jogendra
Kumar,
“Comparative Analysis of Proactive and Reactive
Routing Protocols in Mobile Ad-Hoc Networks
(Manet)”, Journal of Information and Operations
Management, Vol. 3, Issue 1, 2012.
[10] D
. Bertsekas and R. Gallager, Data Networks
(Prentice-Hall, 1982).
[11] V
. Park and M. S. Corson, “A Highly Adaptive
Distributed Routing Algorithm for Mobile
Wireless Networks”, Proc. of IEEE INFOCOM
‘97, Kobe, Japan.
[12] M
.S. Corson and A. Ephremides, A distributed
routing algorithm for mobile wireless networks,
Wireless Networks 1, 1995.
[13] Charles
E. Perkins, Ad hoc networking, 2000,
Addison-Wesley Professional.
[14] P
ark, V.; Corson, M. S: Internet draft; Temporally
ordered Routing Algorithm (TORA), version 1,
Functional Specification, 2001.
[15] IEEE Computer Society. IEEE 802.11 Standard,
IEEE Standard For Information Technology.
HINDUSTAN JOURNAL, VOL. 6, 2013
Evaluation of Evaporative Heat Transfer Characteristics of
CO2/Propane Refrigerant Mixtures in a Smooth
Horizontal Tube Using CFD.
Jeya Pratha.S and Mahendran.S
ABSTRACT — This study presents an evaluation
of the evaporative heat transfer characteristics of
CO2/propane refrigerant mixtures in a smooth
horizontal tube using CFD (Computational Fluid
Dynamics). First a theoretical design has been made
to understand the operating conditions and flow
regimes of CO2/propane refrigerants at various
heat flux, inlet temperature and several mass
compositions. The copper tube with outer diameter
of 5 mm and length of 1.44 m was selected as the
test section. The inner diameter of test tube is 4.0
mm. The heat transfer characteristic has been
theoretically designed by considering heat fluxes
from 15 to 60 Kw/m2, inlet temperatures from -5
to 10 oC and for several compositions (75/25, 50/50,
25/75 wt%). Among CO2/propane refrigerant
mixtures, the heat transfer characteristics are much
better than those of any other compositions when the
composition is 25/75 (wt%). Finally a suitable 3-D
model has been created with the specified dimensions
using CFX software for analyzing the heat transfer
characteristics of refrigerant mixtures.1
Index Terms — Evapourative heat transfer,
Computational fluid dynamics, Refrigerant, mixture
global warming.
I.  Introduction
Conventional refrigerants such as CFC, HCFC, and HFC
with good chemical and thermophysical characteristics
Jeya Pratha.S and Mahendran.S are in School of
Mechanical Sciences, Hindustan University, Chennai,
India, (e-mail: [email protected])
have caused environmental issues of stratospheric ozone
depletion and global warming. From this aspect, the
use of conventional refrigerants such as CFC, HCFC
and HFC refrigerants has been restricted to protect the
environment and we pay much attention to investigating
new refrigerants for the air-conditioning and refrigeration
industry. There has been a strong need to develop
alternative refrigerants with the lower direct global
warming potential (DGWP) and the lower indirect global
warming potential (IDGWP). As a result, among many
natural refrigerants such as ammonia, hydrocarbons,
carbon dioxide, water, air, etc., we chose carbon dioxide
which has gained remarkable attention because of its zero
ozone depletion potential (ODP) and far smaller global
warming potential (GWP). Moreover, carbon dioxide
has excellent thermodynamic characteristics such as
non-flammability and non toxicity. However, it has a few
disadvantages such as high operating pressure and low
efficiency. Therefore, we propose mixtures of CO2 and
propane (R290) which may be a promising refrigerant
since they can contemporarily reduce the problems related
to high operating pressure of CO2 and the flammability
of hydrocarbon refrigerant, because propane (R290) is
flammable, but can be an excellent refrigerant in lowcharge refrigeration units due to higher energy efficiency
and good environmental compatibility.
Global warming refers to the rising average
temperature of Earth’s atmosphere and oceans and its
projected continuation. In the last 100 years, Earth’s
average surface temperature increased by about 0.8 °C
(1.4 °F) with about two thirds of the increase occurring
over just the last three decades. An increase in global
temperature will cause sea levels to rise and will change
the amount and pattern of precipitation, and a probable
72 HINDUSTAN JOURNAL, VOL. 6, 2013
expansion of subtropical deserts. Proposed responses
to global warming include mitigation to reduce
emissions, adaptation to the effects of global warming,
and geoengineering to remove greenhouse gases from
the atmosphere or reflect incoming solar radiation
back to space. The Kyoto Protocol is the only legally
binding emissions agreement and only limits emissions
through the year 2012.Nonetheless, in the 2010 Cancun
Agreements, member nations agreed that urgent action
is needed to limit global warming to no more than 2.0
°C (3.6 °F) above pre-industrial levels. Current scientific
evidence, however, suggests that 2 °C is the “threshold
between ‘dangerous and ‘extremely dangerous’ climate
change”, that this much warming is possible during
the lifetimes of people living today and that steep
reductions in global emissions must be made by 2020
in order to have a 2-out-of-3 chance of avoiding global
warming in excess of 2 °C. All refrigerants in use today
can contribute to global warming as greenhouse gases
and this is why there are regulations in place to limit
their use. These refrigerants will eventually be phased
out and replaced with more palatable alternatives.
Chemicals with the highest global warming potential
are hydrochlorofluorocarbons, such as those found
in refrigeration and cooling systems. The values for
hydrochlorofluorocarbons range from 120 to 12,240
over their atmospheric lifetime. When these numbers are
broken down, it takes only one molecule of refrigerant
gas to cause harm to the ozone layer. The refrigerant
R-113 Trichlorotrifluoroethane has one of the highest
global warming potential values at 4800, while the
refrigerant R-114 Dichlorotetrafluoroethane has one
of the lowest values at 3.9. The alternative refrigerants
being developed have no impact on global warming
and are being used in the production of all types of new
refrigeration and air conditioning systems.
II.  Literature Survey
Jin Min Cho et al [1] investigated a study which presents
evaporative heat transfer characteristics of CO2/
propane refrigerant mixtures in horizontal, and vertical
smooth and micro-fin tubes. The effect of mass flux,
heat flux, inlet temperature and several compositions
have been investigated and analyzed. The copper tube
with outer diameter of 5 mm and length of 1.44 m was
selected as the test sections. Average inner diameters of
test tubes are 4.0 mm and 4.13 mm, respectively. The
tests were conducted at mass fluxes from 212 to 656 kg/
m2, heat fluxes from 15 to 60 kW/m2, inlet temperatures
from -10 to 30°C, and for several compositions (75/25,
50/50, 25/75 wt %). Among CO2/propane refrigerant
mixtures, the heat transfer characteristics are much
better than those of any other compositions when the
composition is 75/25 (wt %). Finally, the heat transfer
coefficients of CO2/propane refrigerant mixtures
in the vertical tube are 5–10% higher than those in
horizontal tubes. In Min Soo Kim et al [2], heat transfer
characteristics show different tendency according
to the tube orientations such as horizontal, vertical
and inclined positions. In this study, evaporative heat
transfer characteristics and pressure drop of CO2 and
CO2/propane mixtures flowing upward are investigated
in inclined smooth and micro-fin tubes. Smooth and
micro-fin tubes with outer diameter of 5 mm and length
of 1.44 m with inclination angle of 450 were chosen as
test tubes. Average inner diameters of test tubes are 4.0
mm (smooth tube) and 4.13mm (micro-fin tube). The
tests were conducted at mass fluxes from 212 to 656kg/
m2 s, saturation temperatures from -5 to 10 oC and heat
fluxes from 15 to 60 Kw/m2 for CO2. In addition, for
CO2/propane mixtures, the test was carried out at inlet
temperatures from -10 to 30 0c for several compositions
(75/25,50/50,25/75wt%) with the same mass fluxes,
heat fluxes applied for CO2. Heat transfer coefficients
in inclined tube are approximately 1.8–3 times higher
than those in horizontal tube and the average pressure
drop of inclined tube exists between that of horizontal
and vertical tubes. Mathur, G.D et al [3] noted that
Carbon dioxide among natural refrigerants has gained
a considerable attention as an alternative refrigerant
due to its excellent thermophysical properties. In-tube
evaporation heat transfer characteristics of carbon
dioxide were experimentally investigated and analyzed
as a function of evaporating temperature, mass flux,
heat flux and tube geometry. Heat transfer coefficient
data during evaporation process of carbon dioxide
were measured for 5 m long smooth and micro-fin
tubes with outer diameters of 5 and 9.52 mm. The
tests were conducted at mass fluxes of from 212 to
656 kg/m2, saturation temperatures of from 0 to 20 0C
and heat fluxes of from 6 to 20 kW/m2. The difference
of heat transfer characteristics between smooth and
micro-fin tubes and the effect of mass flux, heat flux,
and evaporation temperature on enhancement factor
(EF) and penalty factor (PF) were presented. Average
evaporation heat transfer coefficients for a micro-fin
tube were approximately 150 to 200% for 9.52 mm OD
tube and 170 to 210% for 5 mm OD tube higher than
those for the smooth tube at the same test conditions.
JEYA PRATHA AND MAHENDRAN:EVALUATION OF EVAPORATIVE HEAT TRANSFER 73
The effect of pressure drop expressed by measured
penalty factor of 1.2 to 1.35 was smaller than that of
heat transfer enhancement. Carbon di oxide among
natural refrigerants has gained considerable attention
as an alternative refrigerant due to its excellent
thermophysical properties. In the study by S.H. Yoon
et. al [4], transcritical refrigeration cycle using carbon
dioxide was considered, and the evaporation process
was investigated by experiment and analysis. The
paper presents the measured heat transfer coefficients
and pressure drop during evaporation process of carbon
dioxide in a horizontal smooth tube. The test section
was made of a seamless stainless steel tube with the
inner diameter of 7.53 mm, and length of 5 m. Heat was
provided by a direct heating method to the test section.
Experiments were conducted at saturation temperatures
of −4 to 20 °C, heat fluxes of 12 to 20 kWm−2 and mass
fluxes of 200 to 530 kgm−2 s−1. A comparison of different
heat transfer correlations applicable to evaporation of
carbon dioxide has been made. Based on the experiments
for the evaporation heat transfer, useful correlation
was developed. The ideal refrigeration or heat pump
cycle for a given purpose is defined in G. Lorentzen
[5] by the boundary conditions of the application and
is completely independent of the refrigerant used. The
real cycle should approach the theoretical ideal as
closely as practically possible. The thermodynamic and
heat transfer properties of the refrigerant are important
in this respect. Natural substances such as ammonia,
propane and carbon dioxide are often better than the
present halocarbons in this regard. By using simple
methods of safety it is possible to use these three natural
fluids for practically all conventional refrigeration and
heat pump systems.
heat flux condition, a long test section was established.
The magnetic pump circulates subcooled liquid from
the liquid receiver to the pre-heater. The subcooling heat
exchanger and pre-heater are installed to adjust the inlet
quality of the refrigerant to a desired value. The mass flow
meter is installed before the pre-heater to measure the flow
rate of the refrigerant in the liquid phase. After exiting the
mass flow meter, refrigerants enter the test section and
then they are evaporated while flowing through the tube.
The subcooled liquid is heated by the test tube which is
heated by the supplied electricity with a low voltage, high
current power supply (Joule heating). After leaving the test
section, CO2/propane refrigerant mixture is cooled down
in another counter flow heat exchanger and the vapor
generated in the test section is condensed. Pump draws the
liquid from the condenser to complete the cycle. With the
reference of this working model, a theoretical design has
been done to evaluate the results of various heat transfer
coefficient.
IV.  Experimental Setup
III.  Work Progressed
Fig. 1. Experimental setup
In our work, in order to find the heat transfer characteristics
of the proposed mixtures of refrigerants, an experimental
apparatus has been chosen from [1]. A schematic diagram
of the experimental apparatus and test section to investigate
the evaporation heat transfer characteristics inside a tube is
referred as that the test loop consisting of a magnetic gear
pump, mass flow meter (estimated error of 0.23%), preheater and test section is shown in fig 1. A test section of
OD 5 mm and thickness 4 mm over a length of 1.4 m used
is shown in fig. 2 and 3. The inlet quality of the test section
was adjusted by the electric power input supplied to the
pre-heater. In order to avoid the thermal entry length effect
on heat transfer, and to achieve high exit qualities at a low
Fig. 2. Test Section - Cross section
74 HINDUSTAN JOURNAL, VOL. 6, 2013
5). The model made of copper with thermal conductivity
of 406.7 (w/mk) and a free Tetrahedral meshing is given
to get better results. (fig.6)
Fig. 3. Test section
V.  Theoretical Design for Evaluating The
Heat Transfer Coefficient
To find the heat transfer coefficient of proposed
mixtures at various heat flux, inlet temperature and
mass compositions, a test section [1] of OD 5 mm
and thickness 4 mm over a length of 1.4 m (In fig.1)
has been chosen. Here the evaluation of heat transfer
coefficient is done by using the expression,
Q=h*As *(Tf - Ts)
Fig. 4. Cross sectional view of the model
where
Q – Heat Transfer rate in Kw
As – surface area of the test section in m2
Tf – Inlet fluid temperature in K
Ts – Saturation temperature of the refrigerant
mixture at the corresponding mass compositions in
liquid phase in K.
Note:
The saturation temperature of the refrigerant mixtures
are chosen from REFPROP for its corresponding mass
composition and its pressure.
VI.  Model for Analysis
The 2-D model created for analyzing the heat transfer
characteristics for various Heat flux, Inlet temperature
and Mass compositions contains 4 mm inner diameter
and overall length of 1.4 m is shown below (Fig.4 and
Fig. 5. Isometric view of the model
JEYA PRATHA AND MAHENDRAN:EVALUATION OF EVAPORATIVE HEAT TRANSFER 75
reduced operating pressure is one of the great benefits
and may enhance the COP of the system. Therefore,
CO2/propane refrigerant mixtures can be a promising
refrigerant by reducing operating pressure of CO2.
When the composition of CO2 in the mixture is higher,
the heat transfer coefficient is comparatively low than
that of any other compositions because of relatively
strong contribution of CO2 during heat transfer. On the
contrary, when the composition of propane increases
the heat transfer coefficient is getting increased. The
graphical representation placed below provides the
characteristics of heat transfer with various mass
compositions, heat flux and inlet temperature.
For Inlet Temperature = -50c
Fig. 7. Graph showing variation of heat transfer coefficient
with inlet temperature -50c
For Inlet Temperature = 00c
Fig. 6. Meshed model
VII.  Experimental Results (Fig 7-10)
In the work, reported in this paper, the evaporative
heat transfer characteristics of CO2/propane refrigerant
mixtures were investigated for various mass fluxes, heat
fluxes, inlet temperatures and several compositions.
In addition, evaporative heat transfer coefficients
according to flow type such as horizontal flow was also
investigated. When the composition of CO2/propane is
75/25 (wt%), the value of heat transfer coefficient was
the least. Moreover, when using 75/25 of CO2/propane
mixture for refrigeration or air-conditioning system,
Fig. 8. Graph showing variation of heat transfer coefficient
with inlet temperature 00c
76 HINDUSTAN JOURNAL, VOL. 6, 2013
For Inlet Temperature = 5 (0c)
Fig. 9. Graph showing variation of heat transfer coefficient
with inlet temperature 50c
For Inlet Temperature = 10 (0c)
of CO2 (75/25 CO2/propane) because of partial dry-out
along the circumference because the surface tension and
viscosity of carbon dioxide is much smaller than those
of conventional refrigerants, but for other mixtures and
pure propane, heat transfer coefficients have a tendency
to decrease at a low mass quality region and they increase
again due to convective boiling. When the composition
of CO2/propane is 75/25 (wt%), the value of heat transfer
coefficient was the least and for (25/75) is the maximum.
In a future work with the designed values of heat
transfer coefficients of various parameters, a suitable
heat transfer analysis has to be done by using CFX/
FLUENT software with the 2-D model created to
validate them. With this better study of problem
associated during solving the heat transfer analysis in a
2-D model, a 3-D model has to be designed to validate
the results obtained theoretically. This requires a better
knowledge about the problems associated with phase
change in flow through cylinders, surface tension and
friction associated with them.
References
[1] J in Min Cho, Yong Jin Kim, Min Soo Kim (2010),
“Experimental studies on the characteristics of
evaporative heat transfer and pressure drop of
CO2/propane mixtures in horizontal and vertical
smooth and micro-fin tubes”, in International
Journal of Refrigeration 33, 170 – 179.
Fig. 10. Graph showing variation of heat transfer coefficient with inlet temperature 100c
VIII.  Conclusion
This paper presents the measured heat transfer coefficients
during evaporation process of carbon dioxide in a
horizontal smooth tube. Carbon dioxide among natural
refrigerants has gained considerable attention as an
alternative refrigerant due to its excellent thermophysical
properties. In tube evaporation heat transfer characteristics
of carbon dioxide were experimentally investigated and
analyzed as a function of evaporating temperature, heat
flux and tube geometry. Heat transfer coefficients show
a tendency to decrease at the beginning of evaporating
process for pure CO2 and mixture with high composition
[2] Jin Min Cho, Yong Jin Kim, Min Soo Kim
(2010), “Experimental studies on the evaporative
heat transfer and pressure drop of CO2 and CO2/
propane mixtures flowing upward in smooth and
micro-fin tubes with outer diameter of 5 mm
for an inclination angle of 450”, in international
Journal of Refrigeration 33, 922 – 931.
[3] J in Min Cho, Min Soo Kim (2007), “Experimental
studies on the evaporative heat transfer and
pressure drop of CO2 in smooth and micro-fin
tubes of the diameters of 5 and 9.52 mm”, in
International Journal of Refrigeration 30, 986 –
994 .
[4] S
.H. Yoon, E.S. Cho, Y.W. Hwang, M.S. Kim,
K.D. Min, Y.C. Kim (2004), “Characteristics of
evaporative heat transfer and pressure drop of
carbon dioxide and correlation development”,
International Journal of Refrigeration 27, 111 119.
JEYA PRATHA AND MAHENDRAN:EVALUATION OF EVAPORATIVE HEAT TRANSFER 77
[5] J ung, D.S., Lee, H.S., Bae, D.S., Ha, J.C., (2005),
“Nucleate boiling heat transfer coefficients of
flammable refrigerants on various enhanced
tubes”, International Journal of Refrigeration 28,
451–455.
[6] K
im, J.H., (2005), “Studies on the vapor-liquid
equilibria of carbon dioxide/propane mixture and
their performance in an airconditioning system”,
Ph.D. thesis, School of Mechanical and Aerospace
Engineering, Seoul National University, Korea.
[7] K
im, Y.J., Cho, J.M., Kim, M.S., (2008),
“Experimental study on the evaporative heat
transfer and pressure drop of CO2 flowing
upward in vertical smooth”, and micro-fin tubes
with the diameter of 5 mm. International Journal
of Refrigeration 31, 771–779.
[8] L
ee, H.S., Phan, T.T., Yoon, J.I., (2006),
“Characteristics of hydrocarbon refrigerants on
evaporating heat transfer and pressure drop.”,
International Journal of Air-Cond. Ref. 14, 102–
109.
[9] M
athur, G.D., (1998), “Heat transfer coefficient
for propane (R-290), isobutene (R600), and 50/50
mixture of propane and isobutene”, ASHRAE
Trans.: Symp., 1159–1172.
[10] K
im, Y.J., Cho, J.M., Kim, M.S., (2008),
“Experimental study on the evaporative heat
transfer and pressure drop of CO2 flowing
upward in vertical smooth and micro-fin”, tubes
with the diameter of 5 mm. International Journal
of Refrigeration 31, 771–779.
[11] Y
.C. Kim, K.J. Seo, J.T. Chung (2002),
“Evaporation heat transfer characteristics of
R-410A in 7 and 9.52 mm smooth/micro-fin
tubes”, International Journal of Refrigeration 25,
716 - 730.
[12] E
.W. Lemmon, M.O. McLinden, M.L. Huber
(2002), “Reference Fluid Thermodynamic
and Transport Properties (PEFPROP)”, NIST
Standard Reference Database 23, Version 7.0.
Gaithersburg (MD, USA):National Institute of
standard and Technology.
[13] G
. Lorentzen (1994), “Revival of carbon dioxide
as a refrigerant”, International Journal of
Refrigeration 17 (5) 292 - 301.
[14] D
.S. Jung, M. McLinden, R. Radermacher,
D. Didion (1989), “A study of flow boiling
heat transfer with refrigerant mixtures”,
International Journal of Heat Mass Transfer
32, 1751 – 1764.
HINDUSTAN JOURNAL, VOL. 6, 2013
Design and Fabrication of Ultimate Chilling System
T. S. Ravikumar and S. Saravanan
Abstract — This paper demonstrates the working of
ultimate chilling system which can be used in the
pharmaceuticals industry, R&D centres to preserve
medicines etc. Ultimate chilling system is a three
stage cascade refrigeration system. The main
purpose of this system is to produce temperature
less than -60˚C and to maintain that temperature
constant in a conditioned space. This system has one
main system and two sub systems. Each system has
a different refrigerant (R134A, R404A, and R23).
The main system has R23 as refrigerant. Sub system
1 has R134A as refrigerant and sub system 2 has
R404A as refrigerant. Sub system 1 evaporator acts
as a condenser for sub system 2, then sub system
2 evaporator acts as a condenser for the main
system. By using these three systems temperature
less than -60˚C can be achieved. The “coefficient of
performance” calculations are also presented. 1
bigger operating pressure range. Cascade refrigeration
system is most commonly used in low temperature
application such as pharmaceuticals industry, to
preserve medicines; research & development etc., This
system can achieve refrigeration effect at a slower rate.
Cascade refrigeration system can achieve up to -50˚C.
To rectify this drawback, in ultimate chilling system
three systems are used which consists of one main
system and two subsystems. This system can achieve
refrigeration effect at a faster rate and it can achieve
temperature less than -60˚C. It can maintain temperature
for any requirement. In this R23 refrigerant is used in
the main system. R404A and R134A refrigerants are
used in subsystems.
Index terms — Chilling system, cascade refrigeration
system, refrigerant
I.  Introduction
A cascade refrigeration system can be considered to
be equivalent to two independent vapor-compression
systems linked together in such a way that the
evaporator of the high-temperature system becomes the
condenser of the low-temperature system. However, the
working media of the two systems are separated from
each other. This therefore, allows the use of different
refrigerants working at different temperature ranges
to achieve the desired effect, which would otherwise,
need to be achieved by a single refrigerant working at a
T. S. Ravikumar and S. Saravanan are in School of
Mechanical Sciences, Hindustan University, Chennai,
India (email: [email protected])
Fig. 1. Block diagram of ultimate chilling system.
II.  Components of Ultimate Chilling System
The components of different subsystems are as follows:
A.  Subsystem 1:
Refrigerant: R134A, reciprocating compressor, air
cooled condenser, capillary tube & tube in tube heat
exchanger1.
RAVIKUMAR AND SARAVANAN:DESIGN AND FABRICATION OF ULTIMATE CHILLING SYSTEM 79
B.  Subsystem 2:
Refrigerant: R404A, reciprocating compressor, air
cooled condenser, capillary tube & tube in tube heat
exchanger 2.
C.  Main System:
Refrigerant: R23, reciprocating compressor, air cooled
condenser, capillary tube, evaporator coil & fan.
III.  Working Principles of Ultimate Chilling
System
When the system is switched on, timers are used to
switch on the subsystem 2 and the main system. First
subsystem1 is switched on after two minutes delay
subsystem 2 is switched on. After four minutes delay
main system is switched on. Subsystem1 (R134A)
compressor starts running and compresses the low
temperature and low pressure gas refrigerant from the
suction line to high temperature and high pressure gas
refrigerant. Then the refrigerant is sent to the air-cooled
condenser. In this, the gas refrigerant condenses to
liquid refrigerant. Liquid refrigerant is passed through
a capillary tube to the tube in tube heat exchanger1.
In capillary tube liquid refrigerant expands at a low
temperature and a low pressure. Tube in tube heat
exchanger1 acts as an evaporator for subsystem 1 and
secondary condenser for subsystem 2. In tube in tube
heat exchanger, low temperature and low pressure
liquid refrigerant from subsystem1 (R134A) condense
the refrigerant from the subsystem2 (R404A). Then
low temperature and low pressure gas refrigerant from
the tube in tube heat exchanger is sent to the suction
line of compressor. The cycle continues in subsystem 1.
In Subsystem2 (R404A) compressor starts
running. It compresses the low temperature and low
pressure gas refrigerant from the suction line to a high
temperature and high pressure gas refrigerant. Then
the refrigerant is sent to air-cooled condenser. In this
gas refrigerant condenses to liquid refrigerant. Liquid
refrigerant is passed to tube in tube heat exchanger1.
In this further condensation takes place. Then low
temperature liquid refrigerant is sent to the tube in tube
heat exchanger2 through capillary tube. In capillary
tube liquid refrigerant expands at a low temperature
and low pressure. Tube in tube heat exchanger 2 acts as
an evaporator for subsystem 2 and secondary condenser
of the main system. In tube in tube heat exchanger2
low temperature and low pressure liquid refrigerant
from subsystem2 (R404A) condense the refrigerant
from the main system (R23). Then low temperature and
low pressure gas refrigerant from the tube in tube heat
exchanger is send to the suction line of compressor.
The cycle continues in subsystem 2.
In the main system (R23) compressor starts running.
It compresses the low temperature and low pressure gas
refrigerant from the suction line to a high temperature
and high pressure gas refrigerant. Then the refrigerant is
sent to the air-cooled condenser. In this, gas refrigerant
condenses to liquid refrigerant. Liquid refrigerant is
passed to the tube in tube heat exchanger2. In this,
further condensation takes place. Liquid refrigerant is
passed through a capillary tube to an evaporator coil.
In capillary tube liquid refrigerant expands at a low
temperature and low pressure. Refrigerant absorbs heat
in an evaporator coil. Then low temperature and low
pressure gas refrigerant from an evaporator is send to
the suction line of the compressor. The cycle continues
in the main system.
Fig. 2. Schematic diagram of ultimate chilling system.
IV.  Design Calculation
The following outlines the design calculations:
A.  Evaporator Calculation:
(Before Fabrication)
Available data:
1. Evaporator load = 3. 516 KW
2. Shell and coil evaporator
3. Internal diameter of the copper pipe = 7. 9375 x
10-3 m
4. Outer diameter of the copper pipe = 9. 525 x 10-3 m
80 HINDUSTAN JOURNAL, VOL. 6, 2013
5. Inlet evaporator temperature = -65°C (208 K)
6. Outlet evaporator temperature = -35°C (238 K)
7. Mass flow rate of R23= 1799 Kg/sec
Nusselt number = 0.023 x (1.56 x 106)0.8 x (3.5)0.3
=3016. 115
Nusselt number=h0DO/K
3016.11 =
8. Velocity = 32. 546 m/sec
hi × 7.9375 × 10 −3
= 23115.59 kJ/kg
0.073
h0 =23115. 59 w/ m2k
Table 1. From R23 property table
Temperature
Thermal conductivity
Prandtl number
°C
K(w/m K)
-Pr-
-65
0. 073
4
-35
0. 073
3. 5
To find U:
U =
1
= 11505. 022W/m 2 k
1 1
+
hi ho
To find Q:
Q =m CP ΔT Watts
Solution:
Q = 1799 x 0.950 x (238 – 208) = 51271. 5 W
Inside flow:
Q=51271. 5 W
32.546 × 7.9375 × 10 −3
= 1.168 × 106
Re= μdi/ν =
0.211 × 10 −3
To find AREA:
Nusselt number =0.023 Re0.8 prn
Nusselt no =0.023 x (1.168 x 106)0.8 x 40.3= 2490. 577
Nusselt number=hiDi/K
hi × 7.9375 × 10 −3
= 22905.46 W / m 2 k
2490.577
0.073
hi = 22905. 46 w/ m2k
32.546 × 9.525 × 10
0.198 × 10 −6
51271. 5 =11505. 022 x A x (238 – 208)W
A=0. 1485 m2 To find length of the evaporator:
A=pDL
0. 1485 = p x 9.524 x 10-3 x L
Outside flow:
Re = μdo/ν =
Q =UA ΔT Watts
L =4. 964 ≈ 5m
−3
= 1.56 × 106
Nusselt number =0.023 Re0.8 prn
After Fabrication total length of the evaporator coil
=5m
V. Coefficient of performance calculation
for ultimate chilling system:
Fig. 3. Pressure(P)-Enthalpy(H)diagram Fig. 4. Temperature (T)-Entropy(S) diagram
RAVIKUMAR AND SARAVANAN:DESIGN AND FABRICATION OF ULTIMATE CHILLING SYSTEM 81
A.  Main System (R23):
COP2 =
1-2 =isentropic compression in the compressor
2-3=constant pressure heat rejection in the condenser
3-4=isentropic expansion in the expansion device
4-1=constant pressure heat addition in an evaporator
5-6 =isentropic compression in the compressor
6-7=constant pressure heat rejection in the condenser
7-8=isentropic expansion in the expansion device
8-5=constant pressure heat addition in an evaporator
C.  Subsystem1 (R134A):
10-11=constant pressure heat rejection in the condenser
11-12=isentropic expansion in the expansion device
12-9=constant pressure heat addition in an evaporator
Available data:
Table 2. From refrigerant temperature and pressure chart
R404A
R134A
temperature
pressure
k
bar
KJ/kg
KJ/kg
238
8. 5
340. 7
-
293
30. 7
365. 6
208. 6
253
3. 071
355. 16
-
303
14. 28
378. 14
244. 03
263
2. 006
244. 52
-
323
13. 85
276. 01
149. 41
Solution:
COPR23
COP2 × COPR134 A
2.347 × 3.02
=
= 1.11
COP2 + COPR134 A + 1 2.347 + 3.02 + 1
COPULTIMATE CHILLING SYSTEM = 1.11
Expressions
h −h
340.7 − 208.6
= 1 4 =
= 5.30
h2 − h1 365.6 − 340.7
COPR 404 A =
h5 − h8 355.16 − 244.03
=
= 4.83
h6 − h5 378.14 − 355.16
COPR134 A =
h9 − h12
244.52 − 149.41
=
= 3.02
h10 − h11 276.01 − 244.52
Re= μdi/ν
(1)
Nusselt number=hiDi/K
(2)
Nusselt number = 0.023 Re0.8 prn(3)
Outside flow:
Re= μdo/ν
(4)
Nusselt number=hoD0/K
(5)
Nusselt number = 0.023 Re0.8 prn(6)
9-10 =isentropic compression in the compressor
R23
COPULTIMATE CHILLING SYSTEM =
Inside flow:
B.  Subsystem2 (R404A):
refrigerant
COPR 23 × COPR 404 A
5.30 × 4.83
=
= 2.347
COPR 23 + COPR 404.4 + 1 5.30 + 4.83 + 1
1
( W/m 2 k ) 1 1
+
hi ho
Q =m CP ΔT watts
U=
(7)
(8)
Q =UA ΔT Watts
h −h
COPR23 = 1 4
h2 − h1 COPR 404 A
(10)
h −h
= 5 8
h6 − h5 COPR134 A =
COP2 =
(9)
(11)
h9 − h12
h10 − h11 (12)
COPR 23 × COPR 404 A
COPR 23 × COPR 404 + 1 COPULTIMATE CHILLING SYSTEM =
(13)
COPZ × COPR134 A
COPZ × COPR134 A + 1 (14)
VI. Abbreviations
Re = Reynolds Number (non-dimensional)
μ= velocity (m/s)
ν = kinematic viscosity (m2/s)
di=internal diameter of copper pipe(m)
hi =inner heat transfer coefficient(W/ m2k)
K= Thermal conductivity (W/m K)
Pr= Prandtl number (non-dimensional)
82 HINDUSTAN JOURNAL, VOL. 6, 2013
do=outer diameter of copper pipe (m)
ho =outer heat transfer coefficient(W/ m2k)
Q= heat transfer (watts)
m= Mass flow rate (kg/sec)
CP=specific heat(kj/kg k)
ΔT=temperature difference (K)
U=overall heat transfer coefficient (W/ m2 k)
A=area (m2)
VII. Conclusions
In this paper the design and fabrication of an ultimate
cooling system carried out has been described. The result
obtained from the project reported in this paper is:
Conditioned space temperature= -60°C
Coefficient of performance =1. 11
References
[1] A
SHRAE, (1990) “Refrigeration Systems and
Applications Handbook”, ASHRAE Inc. Atlanta.
[2] A
rora (2002), “Refrigeration and Air
conditioning”, 2nd edition, Tata McGraw Hill,
New Delhi.
[3] C
ourse In Refrigeration & Air-conditioning by
Sc Arora, Domkundwar.
[4] D
evanshu pyasi (2010), “Performance analysis
of 404a/508b Cascade Refrigeration cycle for
low temperature”, International Journal of
Engineering Science and Technology (IJEST),
Vol. 2, No. 8, pp. 302-306.
[5] H
ossein Amooie (2012), “performance analysis
of co2/nh3 cascade refrigeration system using
ANNs”. Journal of Advanced Computer Science
and Technology, Vol. 5, No. 4, pp. 222-225.
[6] K
apadia (2011), “Comparative Assessment of
a Cascade refrigeration cycle with different
refrigerant pair”, International Conference on
Current Trends in Technology, Vol. 7, No. 5, pp.
106-116.
[7] M
urat HOS_ OZ (2005), “Performance
Comparison of Single-Stage and Cascade
Refrigeration Systems using R134a as the
Working Fluid”, Turkish Journal of Engineering
Environmental Science, Vol 2, No. 15, pp. 27-32.
[8]
rekh A. D., Tailor P. R. , 2012. “Thermodynamic
P
Analysis of R507A-R23 Cascade Refrigeration
System.” International Journal of Aerospace and
Mechanical Engineering, Vol. 2, No. 72, pp. 342-345.
[9] S
tocker WF, “Industrial refrigeration handbook”,
McGraw Hill, New York, 1998.
[10] T
ailor (2012), “Thermodynamic Analysis of
R507A-R23Cascade Refrigeration System”,
International Journal of Aerospace and Mechanical
Engineering, Vol. 9, Vo. 24, pp. 22-27.
HINDUSTAN JOURNAL, VOL. 6, 2013
Review of Electrical Discharge Machining Process
K.Viswanathan, P. Sengottuvel and J. Arun
Abstract — Machining of hard materials like,
hardened steel, super alloys, carbides, ceramics with
intricate shapes and profiles poses challenges when
carried out with conventional machining process.
Non-conventional machining processes are used to
machine materials of different characteristics like
conductive, non-conductive, composites of any size
and shape and with high precision and surface quality
[1]. Electrical Discharge Machining (EDM) is one of
the most effective non-conventional processes best
suited for machining of hard materials. EDM is a
thermal material removal process and achieves high
metal removal rate, better surface finish, and greater
dimensional accuracy with less tool wear. EDM finds
wide application in aerospace, automobile, defence,
medical and other industries [9]. In this paper
different EDM process and the critical parameters
that affect the process are described. 1,2,3
Index terms — Electrical Discharge Machine,
Material Removal Rate, Tool Wear Rate, Surface
Roughness.
I.  Introduction
Conventional machining such as turning, milling
and drilling show ineffectiveness in machining of
advanced materials, like composites, ceramics, super
alloys as it results in poor MRR, excessive TWR and
K.Viswanathan is Associate Professor, School of
Mechanical Sciences, Hindustan University, Chennai,
India
P. Sengottuvel is Professor, Mechatronics
Engineering, Bharath University, Chennai, India.
(email: [email protected])
J. Arun is PG Student, Sri Shanmuga College of
Engineering & Technology, Tiruchengodu, Tamilnadu,
India
increased SR [9]. The advanced materials have superior
properties like high strength, high bending stiffness,
good damping capacity, low thermal expansion, better
fatigue characteristics. These make them a potential
material for industrial application [8]. Manufacturing
industries face challenges posed by these advanced
materials which are hard to machine, requiring high
precision, surface quality and increased machining
cost. Non-conventional machining process overcomes
these hurdles and offers a fitting solution with advanced
methodology. The EDM, one of the non-conventional
machining processes, has firmly established its use in
the production of forming tool, dies and machining of
advanced materials [7].
II.  History of EDM Process
The Russian scientists Boris and Natalya investigated
(1943) the wear caused by sparking between tungsten
electrical contacts. This phenomenon was reversed
to use controlled sparking as an erosion method [2].
In 1947, American scientists developed a process
to remove broken drills and taps from aluminium
castings by sparking. The process initially started
with 60 sparks per second which further developed
upto 1000 sparks per second. First EDM machine
was produced in 1950. Die sinking machine became
reliable and produced surfaces with controlled
quality. During 1976 first CNC – EDM machine was
produced. Research on EDM process control emerged
in 1980 [3]. During 1990 use of fuzzy control, neural
networks, surface methodology, central composite
design, and Taguchi optimisation lead to further
developments [1].
III.  EDM Working Principle
EDM is a material removal process from work piece by
recurring current discharge between two electrodes – the
84 HINDUSTAN JOURNAL, VOL. 6, 2013
tool and the workpiece. Both electrodes are separated
by a dielectric liquid and subject to an electric voltage
as shown in Figure.1 [3]. Tool electrode is moved
downwards towards the work material until the spark
gap is small enough, when the intensity of electric field
between electrodes becomes greater than the strength of
dielectric, allowing current to flow between electrodes
[4]. The impressed voltage is great enough to ionize
the dielectric. Short duration discharges (measured in
microseconds) are generated in a liquid dielectric gap,
which separates tool and workpiece. The material in
the form of debris is removed with the erosive effect of
the electrical discharges from tool and workpiece.EDM
does not make direct contact between the electrode and
the workpiece [9]. This eliminates mechanical stresses,
chatter and vibration problems during machining [11].
EDM is a thermal material process and has three phases
such as Ignition phase, Discharge phase and End of
pulse [2]. The thermal energy generates a channel of
plasma between the cathode and anode at a temperature
of 8000 to 12,000°C [6]. When the pulsating direct
current supply occurs at the rate of 15,000–30,000
Hz, the plasma channel breaks down [5]. This causes
a sudden reduction in the temperature allowing the
dielectric fluid in circulation to implore the plasma
channel and flush the molten material from the pole
surfaces in the form of microscopic debris. EDM
processes are extensively used in prototype production
in aerospace, auto, electronics and medical industry [1].
Also EDM processes are used in Coinage die making,
small hole drilling and machining of intricate shapes
and profiles [9].
sinking), Wire EDM, Dry EDM and Rotary disk
electrode EDM [4].
A.  Die Sinking
In Die Sinking EDM process, the tool electrode is the
replica of the machined profile of the work material [12]
.This process enables manufacturing of accurate and
complex shaped cavities. Die Sinking EDM consists
of an electrode and workpiece submerged in dielectric
fluids. Figure 2 shows the schematic diagram of Die
Sinking EDM, electrode and workpiece are connected
to a suitable power supply, which generates an electric
potential between both the parts [8]. As electrode
approaches the work piece, dielectric breakdown occurs
in fluids forming a plasma channel and spark jumps.
As base metal is eroded, spark gap increases. Hence
electrode is lowered automatically so that process is
continued [12].
Fig. 2. Schematic diagram of Die-sinking EDM [KozakJ.
Rajurkar K.P.2000]
Die sinking provides close tolerances, high surface
finish and a finished product with little or no burring.
It can also cut exotic materials and hard materials
with little or no polishing after the process. Die
sinking cuts very thin or delicate materials without
damaging [12].
B.  Wire EDM
Fig. 1. Schematic diagram of EDM
[Bhavesh A. Patel et al, 2013]
IV.  Types of EDM
The Electrical Discharge Machines are classified
based on the working principles as Sinker EDM (Die
EDM wire cutting uses a metallic wire to cut a
programmed contour in a workpiece. Thin wire is
fed from a spool, and it is held between upper and
lower guides, which are made of diamond. These
guides are CNC controlled and can move in multi
axis independently. This gives rise to the ability to
cut intricate shapes like circle at bottom and square
at the top [13]. Cutting forces are low and hence, less
VISWANATHAN ET AL.: REVIEW OF ELECTRICAL DISCHARGE MACHINING PROCESS 85
residual stress is caused. Extrusion dies and blanking
punches are very often machined by wire cutting. The
wire is usually made of brass or stratified copper, and
is between 0.1 and 0.3 mm diameter and accuracy of
machining is up to one µm [3]. Wire EDM can be either
one cut or it will be roughed and skimmed. For one cut,
the wire ideally passes through a solid part and drops
a slug or scrap piece when it is done. During the skim
cut, the wire is passed back over the roughed surface
again with a lower power setting and low pressure
flush. A skim pass can remove the material up to 0.005
mm or as little as 0.0003 mm. In roughing (i.e. the first
cut) the water is forced into the cut at a high pressure in
order to provide plenty of cooling and eliminate eroded
particles as fast as possible whereas in skimming the
water flows gently over the burn so as not to deflect the
wire [8].
C.  Dry EDM
Dry EDM uses gas-liquid mixture as the two phases
of the dielectric fluid. It has the advantage of the
concentration of liquid and properties of dielectric
fluid to meet the desired performance responses. In
dry EDM, tool electrode is formed to be thin walled
pipe [10]. High MRR can be obtained cutting high
strength engineering materials in the presence of
oxygen high-pressure gas or air supplied through
the pipe. The role of the gas is to remove the debris
from the gap and to cool the inter electrode gap. The
technique was developed to decrease the pollution
caused by the use of liquid dielectric that leads to
production of vapour during machining and the cost
to manage the waste. Helium and argon gas can be
used as a dielectric medium to drill holes using copper
electrodes [14]. Introducing oxygen gas into the
discharge gap increases the material removal rate in
water as a dielectric medium.
D.  Rotary Disc Electrode EDM
Machining by using Rotary Disk Electrode is
developed in recent years. Study of micro electro
mechanical Systems (MEMS) have resulted in the
manufacture of small size products such as micropumps, micro-engines and micro-robots that have
been successfully used in industrial applications [11].
The technique of precision machining for such small
devices has become increasingly important. Rotary
disc electrode electrical discharge machining is one
of the variant process in which unwanted material is
removed in the form of debris by a series of recurring
electrical discharges created by electric pulse
generators in microseconds between rotary tool called
disc and workpiece in the presence of dielectric fluid
like kerosene or distilled water. Experimental study
reveals that in rotary EDM, material removal rate is
improved [7].
V.  Important parameters of EDM
The various important parameters of EDM’s are:
●● S
park On-time (pulse on time or Ton) is duration
in μs between the current allowed to flow per
cycle. Material removal is directly proportional to
the amount of energy applied during this on-time
period. This energy is really controlled by the peak
current and the length of the on-time [1].
●● S
park Off-time (pause time or Toff ) is the time
duration in μs between the sparks is off-time. This
time allows the molten material to solidify and to
wash out the arc gap. This parameter affects the
speed and the stability of the cut. The too short offtime will cause sparks to be unstable [9].
●● A
rc gap (or gap) is the distance between the
electrode and workpiece during the process of
EDM. It may be called as spark gap. Spark gap is
maintained by servo system [11].
●● D
ischarge current (current) is directly proportional
to the material removal rate and is measured in
Amps [7].
●● D
uty cycle (τ) is a percentage of the on-time relative
to the total cycle time. It is calculated by dividing
the on-time by the total cycle time [6]
●● V
oltage (V) is a potential measured by volt, which
influences the material removal rate
●● O
ver cut is a clearance per side between the
electrode and the workpiece after the marching
operation.
●● M
RR, TWR and SF are the main process outputs of
EDM. Overall lower process efficiency and high
TWR are the challenges in EDM process, Coating
of tool electrode with novel materials for tool
material or tool wear compensation in addition to
86 HINDUSTAN JOURNAL, VOL. 6, 2013
conventional method of using multiple electrodes
are suggested [9].
●● Influence of parameters:
EDM process consists of a RC type generator. This
generator can produce pulses from few tens of nanoseconds to a few micro-seconds. Experiments are
being conducted for machining a specimen of 50mm
diameter of 6mm thickness by using copper electrode
with four geometries circle, square, rectangle and
triangle. The power supply can vary voltage levels from
45V to 120 V. The input parameters are capacitance,
discharge voltage and electrode materials and the
responses included were MRR, and the SF.The S/N
ratios are used to analyze the responses for a given set
of input parameters [4]. Experimental results for SF
and MRR vs. current intensity are depicting that as the
pulse on time and pulse off time difference increases
the MRR and SR both give negative results and that
MRR decreases and SR increases. But as they come
nearer to each other both the output parameters show
good results [3].
VI.  Conclusion
EDM has emerged as the most cost effective and
high precision machining process in the past years.
The machining capacity to remove hard and difficult
to machine parts has made EDM as one of the most
important machining processes. A review of the
research trends for the last 50 years in EDM process;
its applications and influence of critical parameters
have been presented. EDM plays a significant role in
medical, optical, jewellery, automotive and aeronautic
industry. Such applications require machining of high
strength temperature resistant (HSTR) materials, which
demand strong research and development and prompt
EDM machine tool manufacturers to improve the
machining characteristics. Hence, further research is
required to explore effective means of improving the
performance of the EDM process.
References
[1] S
engottuvel, P., Satishkumar, S. and Dinakaran,
D., “Optimization of Multiple Characteristics of
EDM Parameters Based on Desirability Approach
and Fuzzy Modeling” Journal of Procedia
Engineering, Vol.64, pp.1069-1078 (2013).
[2] A
nand Pandey and Shankar Singh, (2010)
“Current research trends in variants of Electrical
Discharge Machining” International Journal of
Engineering Science and Technology, Vol.2(6),
pp.2174-2181.
[3] A
morim F.L, and Weingaertner W.L, “Diesinking electrical discharge machining of a
high-strength copper-based alloy for injection
moulds” Journal of the Brazilian Society
of Mechanical Sciences and Engineering,
Vol.26(2), 2004.
[4] B
havesh A. Patel, and Patel D. S, “Influence
of electrode geometry and process parameters
on surface quality and MRR in EDM using
Artificial Neural Network”, Vol.3(1), pp.16451647 (2013).
[5] B
ojorquez, B. Marloth, R.T, and Es-Said, O.S.,
“Formation of a crater in the work piece on an
electrical discharge machine”, Engineering
Failure analysis, Vol.9, pp.93–97 (2002).
[6] G
eough, J.A. Electro discharge machining in
Advanced McMethods of Machining, Chapman
& Hall, London, p.130. 1988
[7] H
assan,
EI-Hofy, Advanced
Machining
Processes. McGraw-Hill, pp. 36-37 (2005).
[8] K
ozakJ.Rajurkar K.P., “Selected Problems
of Hybrid Machining Processes”, Advances
in Manufacturing Science and Technology,
Vol.109, pp: 360-366 (2001).
[9] S
engottuvel, P., Satishkumar, S. and Dinakaran,
D., “Multi Objective Optimization of Process
Parameters During Electrical Discharge
Machining of Inconel 718 Using Desirability
Approach”, International Journal of Applied
Mechanics and Materials, Vol.159, pp.176-180,
(2012).
[10] M
anish Vishwakarma, VishalParashar and Khare
V.K., “Advancement in Electric Discharge
machining on metal matrix composite materials
in recent: A Review”, International Journal of
Scientific and Research Publications, Vol.2(3),
pp: 2250-3153, 2012.
VISWANATHAN ET AL.: REVIEW OF ELECTRICAL DISCHARGE MACHINING PROCESS 87
[11] M
aradiaa U, Boccadorob M, Stirnimannc
J, Beltramib I, Kustera, and Wegenera K, “Diesink EDM in meso-micro machining” Proc. of
5th Conference on High Performance Cutting.
Institute of Machine Tools and Manufacturing,
ETH Zurich, Zurich 8092, Switzerland, 2012.
[12] S
ingh S, Maheshwari S. and Pandey P.C,
“Investigations into the electric discharge
machining of hardened tool steel using different
electrode materials”, Journal of Materials
Processing Technology, Vol.149, pp. 272–277,
2004.
[13] S
engottuvel, P., Satishkumar, S. and Dinakaran,
D., “Optimization of Electrical Discharge
Machining Parameters for Inconel 718 Using Grey
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Journal of Manufacturing Engineering, Vol.6,
255-259, 2011.
HINDUSTAN JOURNAL, VOL. 6, 2013
Community Colleges to SEmpower the Youth to Transcend
Social Barriers
Aby Sam and Akkara Sherine
Abstract — India is faced with a problem of unskilled
and unqualified school drop-outs who complain of
non-availability of jobs. Though the country claims
to have a large number of educational institutions,
one of the greatest concerns is the low Gross
Enrolment Ratio (GER) of 12.5% which is far less
than the global average. Adolescents aged between
10-19 years in India, form 21.4 percent of the total
population (National Youth Policy 2000). The need of
the hour is a skilled adolescent populace for which
Hindustan Community College (HCC) has taken the
initiative to work for the welfare of the people and
prevent the drop-out students from becoming street
vendors, labourers and antisocial elements which is a
threat to the social fabric of the country. The author
has coined the term “SEmpower” wherein “S” refers
to the skills needed to equip or ‘Empower’ the youth
through skills and need based education. The paper
presents the case study and the success story of the
students enrolled in HCC over the period of three
years. The statistics claims that 91.6% have been
placed and 8.4% have opted for higher education.1,2
Index terms — People-skills, skill-based and needbased education, SEmpower-“S”-skills to Empower.
I.  Introduction
Hindustan Group of Institutions has taken an initiative
to provide need-based and skill-based education to
the adolescents who have been deprived of higher
Aby Sam is Director, Hindustan University, Chennai,
India, (e-mail: [email protected])
Akkara Sherine is in Department of Applied Sciences,
Hindustan University, Chennai, India, (e-mail:
[email protected])
education due to financial and social constraints.
Hindustan Community College (HCC) was established
in the year 2010, in association with Indian Centre for
Research and Development of Community Education
(ICRDCE), Chennai and Tamil Nadu Open University
(TNOU) and Industries. HCC offers a number of skill
development courses of one year duration aimed at
empowering the rural and economically backward
students from neighbouring villages, who have dropped
out from formal education system or those who could
not pursue higher education due to various economic
constraints. The target group enrolled in the programme
were school dropouts working as construction workers,
casual labourers, house maids and cleaners and school
drop outs. The main aims of the establishment of
Hindustan Community College are:
●● To provide skill-based education, provide an apt
livelihood, and enhance education and eligibility
for employment for the poor, marginalized and
disadvantaged sections of the society without any
disparity.
●● O
ffer appropriate, need driven programmes
keeping abreast with the latest trends in the field of
education, emphasizing on skills-set requirements
of the employers.
●● T
o open new routes to career shaping of students,
focus on holistic developments, develop the
students to face the real world and develop people
skills and help them transcend the social barriers.
Need analysis formed an important step to find
the employment needs in the local area before the
establishment of the community college. The courses
offered comprised Desktop publishing, Computer
Application and Data Entry, Hardware Servicing, Barbending and Steel Reinforcement, Health Assistance,
ABY SAM AND AKKARA SHERINE:COMMUNITY COLLEGES TO SEMPOWER 89
Ophthalmic Technical course and Beautician course.
The syllabus also included training in Communication
Skills, Computing Skills, Work Skills, and hands on
experience for employment in collaboration with more
than ten industries.
II.  The Concept of Community College
The Community College is an alternative system of
education, which is aimed at the empowerment of
the disadvantaged and the underprivileged (Urban
poor, Rural poor, Tribal poor and Women) through
appropriate skills development leading to gainful
employment in collaboration with the local industry and
the community and achieve skills for employment and
self employability of the above sections of people in the
society. It is an innovative educational alternative that
is rooted in the community providing holistic education
and eligibility for employment to the disadvantaged.
The Community College promotes job oriented, work
related, skill-based and life coping education. The key
words of the Community College system are access,
flexibility in curriculum and teaching methodology, cost
effectiveness and equal opportunity, collaboration with
industrial, commercial and service sectors of the local
area, responding to the social needs and issues of the
local community, internship and job placement within
the local area, promotion of self employment and small
business development, declaration of competence and
eligibility for employment.
Indian education system has created a large pool of men
and women with robust scientific and technological
capabilities, sensitive humanist and philosophical
thoughts and profound capability. The statistics
represented in the bar chart given below as Fig. 1, Fig.
2 and Fig. 3 indicates the growth of education system
in the country in the Universities, Colleges and the
strength of students enrolled during the period 19502013.
Fig. 1. Students enrolled in Universities
Fig. 2. Students enrolled in Colleges
III.  Economic Scenario in India
India is the largest democracy in the world with 1.3 billion
population and the 10th largest economy in the world by
GDP. It is the third largest economy by purchasing power
parity. India is the youngest nation in the world having
54% population under the age group of 25 years. The
average age by 2020 is 29 years as compared to 40 in US,
34 in China, 47 in Europe and 46 in Japan. There is a total
workforce of 459 million people. The challenge existing
is the lack of penetration of nation’s economic and
infrastructural progress into the hinterland (rural areas)
which is a case of unbalanced development.
IV.  Education Scenario in India
India boasts of having the third largest education system
in the world. In the past 65 years (post independence),
Fig. 3. Strength of students in 1950 & 2013
As against 30 Universities, 700 Colleges and
400,000 students in 1950 now there are 19 - 20 million
students in 600 Universities and 35000 colleges. Yet the
current GER is 12 – 12.5% which is far below global
average. Govt. of India has set a highly impressive
and aggressive target of achieving 30% GER by 2020,
which means enrolment of 40 million students as
against 18 - 20 million now at the tertiary level. The
most important question that arises here is the fate of
the youth.
90 HINDUSTAN JOURNAL, VOL. 6, 2013
V.  Statistics of School Dropouts at Various
Levels
According to a survey in 2001 and 2008 the drop
out percentage of students at primary level, middle
school level and secondary level is as indicated in
the chart.
This research paper focuses on the fate of all those
youth who drop out of formal education system between
the age of 11 – 17 years and the remedy, responsibility
and initiatives focusing on under privileged youth.
These children in the age group 11-17 years are left to
face life and its challenges without appropriate skills
and knowledge and finally become part of cheap labour
forces to be exploited. Few may even land up in the
hands of anti-social elements like illicit liquor trade,
smuggling, theft, and underworld activities etc. which
become a threat to social and economic fabric of the
nation.
VI.  Concept of Community College
Fig. 4. Drop-out rates in school--2008
.
Fig. 5. Drop-out rates in school --2001
The survey in 2008 as represented in Fig. 4 indicates
that 160 million students enroll in primary school,
out of which 10 to 12% only reach the tertiary level
(higher education), 90% dropout at various stages due
to various reasons, like affordability, poor economic
condition, other priorities etc. In the state of Tamil
Nadu according to statistics by National Information
Centre (2001) as represented in Fig. 5 the dropout rate
was 14.5% at primary, 35.6% at middle school, 57.5%
at high school and 82.3% at higher secondary level.
The statistics indicates that roughly 50% dropout at
each stage of schooling.
The main keywords of the community college is based
on “Including The Excluded Giving The Best To The
Least” and it is an alternative system of education,
aimed at the empowerment of the disadvantaged and the
underprivileged (Urban poor, Rural poor, Tribal poor
and Women). This leads to gainful employment through
appropriate skill development in collaboration with the
local industries and the community or self employment.
The Community college is an innovative educational
alternative that is rooted in the community. In India
exclusion from main stream of society is mainly due
to social exclusion based on caste, religion etc. which
is now brought to a minimal scale through various
efforts of State & Central Governments, NGOs etc. The
economic exclusion is based on poverty unemployment
and social insecurity. The second keyword is to give
“The Best to Least” i.e. to extend the benefits of social
and economic reforms, technological and scientific
advancement and industrial growth to people living in
rural areas and difficult terrains.
India has the largest share of youth population
which needs to be channelized into diverse and multilevel occupational areas. Only 5% of Indian labour
workforce between the age 20-24 years have obtained
the required skills-set as expected by the employers.
Skill development has become a national agenda in
India and is getting a major policy thrust. India has set
an ambitious target of creating a 500 million globally
employable workforce by 2022. Community Colleges
in India serve the purpose of fulfilling the needs of the
school-dropouts and enable them to acquire the necessary
skills for livelihood and formal qualification for social
status and social recognition. The term “SEmpower”
refers to empower and equip the youth with the requisite
ABY SAM AND AKKARA SHERINE:COMMUNITY COLLEGES TO SEMPOWER 91
skills based on the needs of the industry. The sole aim of
the Hindustan Community College is to SEmpower the
youth and overcome the social barriers.
Luckerson Victor in the article, “Career Strategies:
Can Community Colleges Put Americans Back to
Work?” explains the role of community colleges. He
states that “community colleges have long played a
key role as an entry way to better career opportunities
for adults in the workforce” [1]. Research proves that
the regular courses and curriculum in most of the
colleges are insufficient. Specific skills-set training
is the need of the hour for training the adolescents
to meet the requirements of the employers. The term
‘people skills’ or ‘soft skills’, a complex concept, has
several synonyms. It is called “World Skills” in the
US and Australia; “Employability skills”, in Canada
and Australia; “Core skills” or “Common skills” in the
UK; “Key skills” in the UK, Australia and Germany;
“Critical enabling skills” in Australia, “Transferrable
skills” in France; “Trans-disciplinary goals” in
Switzerland; “Process independent qualifications” in
Denmark; and “Basic skills,” “Necessary skills,” and
“Workplace know-how” in the US. Robert W. Glenn
and Katheryn C. Keene of the Issues Management
Group summarized the findings of the “Smyth County
Workforce Development Demand Profile 2003” thus:
There was virtually an across-the-board unanimous
profile of skills and characteristics needed to make a
good employee. While often referred to as “soft skills”
in virtually all other studies, these interviews clearly
prove that such skills are as important, than traditional
hard skills to an employer looking to hire--regardless of
industry or job type. The most common traits, mentioned
by virtually every employer, were positive work ethic,
attitude and desire to learn and be trained [2].
People Skills are the most sought after skills by
the employers. Explicit training in these skills will
ensure better performance in the world of work and
also help the individuals to tackle problems in reallife situations. Introduction of people skills training
as a part of the curriculum in Hindustan Community
College ensured the youth to succeed in education, job
training, independent living, community participation,
and ultimately help in the workplace.
VII.  Which Skills are Needed to Succeed?
National Collaborative on Workforce and Disability
(NCWD) for Youth in the article, “Helping Youth
Develop Soft Skills for Job Success: Tips for Parents
and Families.” explains the importance of skills:
In the 1990s, several initiatives attempted to classify
the types of skills needed to succeed in the workplace
and adult life. Included among these efforts was the
1991 Secretary of Labor’s Commission on Achieving
Necessary Skills (SCANS) and the Equipped for the
Future Framework (EFF), which was the result of a
10-year initiative by the National Institute for Literacy
(NIFL). The NIFL effort is the most holistic in that it
addresses some key foundational “hard skills,” specifically
reading, writing, and mathematics skills along with the
important soft skills needed not only in the workplace but
as members of families and society [3].
VIII.  Drop-Out Crisis
According to Sunita Chugh, “The dropout problem
is pervasive in the Indian education system. Many
children, who enter school, are unable to complete
secondary education and multiple factors are
responsible for children dropping out of school” [4].
The probable risk factors are prevalent even before
the students enroll in school. The main causes for the
drop outs are poverty, parents with poor educational
background, weak family structure, pattern of schooling
of sibling, and lack of pre-school experiences. The
school drop-outs are primarily attributed to economic
status and poor parental education. To reiterate this
point several researchers have consistently found that
socio-economic status, most commonly measured by
parental education and income, is a powerful predictor
of school achievement and dropout behavior (Bryk and
Thum, 1989) [5].
To better help the students stay in the education
system, schools are adopting a whole school approach
where the entire school community is involved in
providing support to students who are potential
drop-outs, and resources are synthesized to meet the
three aspects of these students’ needs – emotional,
behavioural and learning needs.
IX.  Role of Community Colleges in India
Getting high school dropouts back on the path to graduate
from high school, enroll in higher education and enter
a promising career requires collaboration among the
stakeholders namely the students, parents, educational
92 HINDUSTAN JOURNAL, VOL. 6, 2013
institutions and employers. Community colleges must
play a big role in these efforts. Community colleges
can play a big role in increasing the Gross Enrolment
Ratio (GER) in the country too. Human Resource
Development Minister of India, Kapil Sibal, opined in
the global summit that, “community colleges could play
a significant role in addressing the shortage of skilled
workforce . . . admitting that skill development was a
big challenge for the government, he said plans were
on the anvil to start 100 colleges during the current
academic session to impart vocational training. Of
these 100 community colleges, Canada will collaborate
in setting up of 10 colleges” [6].
The Indian Centre for Research and Development
of Community Education (ICRDCE) has pioneered
the formation of Community Colleges in India and
initiated the implementation of an alternative system
of education for the poor and downtrodden from 1995.
Dr. Fr. Xavier Alphonse, S.J., Director ICRDCE, spoke
about the Community Colleges as an Alternative System
of Education and mentioned in the interview that “the
vital aspect in the community colleges is the industryinstitution linkages . . . the three components that are
focused in the entire curriculum of the community
college system revolves around the - Attitude, Skills
and Knowledge” [7].
The community college programme provides a
specially customised and more holistic programme for
students better suited to vocational education. It aims
to help these students stay in the education system and
equip them with the necessary skills and values for
work life. The students’ performance is evaluated by
the teachers handling life skills and work place skills.
Self analysis of the individual students is also taken
into account as part of the self-evaluation process to
enhance the confidence of the students.
X.  Role of Community Colleges at Global
Level
Community colleges have a major role in global
prosperity. It accounts for a special responsibility for
workforce development and through partnerships with
business and industry. The major role of community
colleges is to develop skills-set requisites of potential
employers, provide job training, retraining, certification,
and skills improvement. In addition, they assume
primary responsibility, in the public system, for offering
developmental courses, programs, and other educational
services for individuals who seek to develop the skills
needed to pursue college-level study or enter the
workforce. Community colleges across the globe cater
to the students’ requirements by providing a conducive
and comfortable environment where the ideas, needs
and contributions of all the students are respected and
taken care of. Apart from the primary focus of catering to
the workforce needs the academic and personal support
services are also provided at the community colleges.
The importance and the role of community colleges
by President Barack Obama in the article “Building
American Skills through Community Colleges”
emphasize that, “In an increasingly competitive world
economy, America’s economic strength depends upon
the education and skills of its workers. In the coming
years, jobs requiring at least an associate degree are
projected to grow twice as fast as those requiring no
college experience. To meet this need, two national
goals were set: by 2020, America will once again have
the highest proportion of college graduates in the world,
and community colleges will produce an additional 5
million graduates” [8].
As the largest part of the nation’s higher education
system, community colleges enroll more than 6 million
students and are growing rapidly. They feature affordable
tuition, open admission policies, flexible course
schedules, and convenient locations. Community colleges
are the “unsung heroes” of the American education
system, President Obama said during a White House
summit on community colleges. Community Colleges
are particularly important for students who are older,
working, or need remedial classes. Community colleges
work with businesses, industry and government to create
tailored training programs to meet economic needs
like nursing, health information technology, advanced
manufacturing, and green jobs. In the article by Elizabeth
Redden, “The ‘Community College’ Internationally,” the
need for skills development and its recognition at global
level is reiterated by Tully Cornick, Executive Director
of Higher Education for Development, which coordinates
collaborations between American colleges and the United
States Agency for International Development. According
to Cornick, “There is a recognition around the world,
and it manifests itself somewhat differently (in different
countries), that community colleges, as one element of
higher education system, have something very significant
to offer to segments of the population – youth at risk, or
those who left school and realize that they need skills
development” [9].
ABY SAM AND AKKARA SHERINE:COMMUNITY COLLEGES TO SEMPOWER 93
In Australia, learning offered by community
colleges has changed over the years. By the 1980s
many colleges had recognised a community need for
computer training and since then thousands of people
have been up-skilled through IT courses. In Philippines
a community school functions as elementary or
secondary school at daytime and towards the end of the
day converts into a community college. This type of
institution offers night classes under the supervision of
the same principal, and the same faculty members who
are given part-time college teaching load.
Industries play an important role in community
colleges. In several community colleges across India,
many industry representatives offer to teach the students
based on the skills-set requisites. This is a boon for the
stakeholders namely the students, the institution and
the industry. The guidelines for the curriculum are also
offered by the industries and it is incorporated in the
community college. This further enhances the career
prospects of the students enrolled in such colleges.
XI.  Vision and Mission of the Community
Colleges world-wide
The Vision of the Community College is to be
of the Community, for the Community and by the
Community and to produce responsible citizens. The
Community College promotes job oriented, work
related, skill - based and life coping education. The key
words of the Community College system are access,
flexibility in curriculum and teaching methodology, cost
effectiveness and equal opportunity in collaboration
with industrial, commercial and service sectors of the
local area and responding to the social needs and issues
of the local community, internship and job placement
within the local area, promotion of self employment and
small business development, declaration of competence
and eligibility for employment.
XII.  Views of the Industrial Collaborators
The Industrial Collaborators find the Community
College System being initiated by service minded
organisation and the delivery of the Community College
System is excellent because it determines the future of
the student and helps the school dropouts. They also
observe that there is a close scrutiny and feedback
on the student throughout the training. The system is
most suitable for the economically weaker sections.
The community Colleges show the way for the poor to
come up. The Industrial Collaborators feel that they are
also sharing in the mission, reaching out to the poor and
the most deserving. The Community College is a bold
concept in the field of education [10].
XIII.  21st Century Skills Development and
Community College Curriculum
The fundamental changes in the economy, jobs, and
businesses are driving new, different skill demands.
Today more than ever, individuals must be able to
perform non-routine, creative tasks if they are to
succeed. While skills like self-direction, creativity,
critical thinking, and innovation may not be new to the
21st century, they are newly relevant in an age where the
ability to excel at non-routine work is not only rewarded,
but expected as a basic requirement. Whether a high
school graduates plans to enter the workforce directly,
or attend a vocational school, community college, or
university, it is a requirement to be able to think critically,
solve problems, communicate, collaborate, find good
information quickly, and use technology effectively.
These are today’s survival skills—not only for career
success, but for personal and civic quality of life as well.
To succeed in academics, career and life in the 21st
century, students must be supported in mastering both
content and skills. “Curriculum and Instruction: A 21st
Century Skills Implementation Guide” produced by
the Partnership for 21st Century Skills gives a detailed
account of the 21st century skills that include:
Core subjects--21st century content: global
awareness, financial, economic, business and
entrepreneurial literacy, civic literacy and health and
wellness awareness, learning and thinking skills: critical
thinking and problem solving skills, communication
skills, creativity and innovation skills, collaboration
skills, contextual learning skills and information and
media literacy skills, information and communications
technology literacy, Life skills: leadership, ethics,
accountability, adaptability, personal productivity,
personal responsibility, people skills, self-direction and
social responsibility [11].
For students, proficiency in 21st century skills—
the skills, knowledge and expertise students must
master to succeed in college, work and life—should
be the outcome of a 21st century education. To be
“educated” today requires mastery of core subjects,
21st century themes and 21st century skills. And both
94 HINDUSTAN JOURNAL, VOL. 6, 2013
students and educators need learning environments that
are conducive to results [12].
Hindustan Community College, “Life and Career
Skills” syllabus is based on the aspects listed out by
the 21st Century Skills mentioned above. Today’s life
and work environments require far more than thinking
skills and content knowledge. The ability to navigate
the complex life and work environments in the globally
competitive information age requires students to pay
rigorous attention to develop adequate life and career
skills. The curriculum of the community college also
includes English as part of the core subject. In 2006,
Caser Lotto & Barrington conducted a survey of 400
business executives and managers, asking respondents
to rank the relative importance of 20 skills and fields of
knowledge to the job success of new workforce entrants
at three education levels: high school, two-year college
or technical school, and four-year college.
The respondents ranked three skills among the top
five most important skills and fields of knowledge for
all three groups of new entrants: (1) professionalism/
work ethic, (2) teamwork/collaboration, and (3) oral
communication. In comparison, science knowledge
was ranked 17th in importance in the list of 20 skills
and fields of knowledge for high school graduates
and 16th in importance for two- and four-year college
graduates. Intercommunication and communication
skills rank high among the skills-set requisites of the
employers [13].
Young people who learn to communicate in
highly effectively ways – listening well, speaking, and
writing clearly and persuasively – within and outside
of the digital world will have a key skill to be highly
competitive in today’s world (Envision EMI White
Paper 2010) [14].
XIV.  Statistics of Students in HCC
Statistics of students enrolled in Hindustan Community
College from the year of its establishment 2010,
indicates that there has been a constant increase in the
intake of the students who are economically poor, and
it caters to the needs of all categories of students below
10th, 10th failed, 10th passed, 12th failed, 12th passed
and school drop outs. The Community Colleges have
been serving the socially backward groups Scheduled
Castes (SC), Scheduled Tribes (ST), Most Backward
Class (MBC) and Backward Class (BC). They account
for 92%, thus transcending social barriers. HCC also
serves 87% of the economically weaker sections who
have their monthly family income below Rs. 3000.
Fig. 6. HCC--Statistics of students enrolled,
passed and placed
The above graphical representation indicates the
number of students enrolled in the course, students
passed and students placed in three batches namely I
Batch 2009-2010, II Batch 2010-2011 and III Batch
2011-2012 of Hindustan Community College. The
study of the graph above indicates that in Batch I—39
students were enrolled, 39 students passed and 34
students were placed. In Batch II—75 students were
enrolled, 75 passed and 62 students were placed. In
Batch III—84 students were enrolled, 84 students
passed and 77 students placed. The statistics indicates
100% pass percentage, 91.6% placed and survey
showed that the remaining 8.4% students opted for
higher education.
XV.  Highlights of the Hindustan Community
College (HCC) Curriculum
The curriculum of the Hindustan Community College
has four distinct parts: life skills, work skills,
internship and preparation for employment. The aim
of the curriculum offered for the students at HCC is to
bring the classroom and the real world together. The
students are engaged in experiential learning driven by
questions and problems that are interesting, relevant
ABY SAM AND AKKARA SHERINE:COMMUNITY COLLEGES TO SEMPOWER 95
and thought-provoking. The teaching methodology
adopted in various community colleges is as follows:
lecture, interactive, discussion, seminar and tutorial
methods.
The discussions with the teachers handling the
classes at Hindustan Community college revealed that
69% of the teachers opt for interactive method and
31% opt for lecture methods of teaching methodology.
Since the statistics reveals that teachers are opting for
interactive methodology it indicates that the teachers
have realized the importance of interactive teaching
methodology over the lecture method. The students are
given opportunities to collaborate on diverse teams,
speak, listen, resolve conflicts, think critically and
creatively to set goals, create plans, solve problems and
make decisions, all while interacting with their academic
peers. The activities embedded in the curriculum are
also focused on the self-awareness of the students and
also self-examination, assessment and monitoring of
their progress, and encourage them to prepare personal
and leadership development plans. This promotes a
high level of self-awareness about their strengths, areas
of need, beliefs, values, and goals. The evaluation and
assessment of skills done by the Community College is
based on: self-assessment, assessment of the life skills
and work skills by teachers and internship supervisor
at the works spot. The students in community colleges
are trained to have sound personal ethics and it refers to
the character of an individual which forms an important
component of people skills. “Personal Ethics develops
the Personal Effectiveness of the students and it results
in effective learning outcomes and peps up their job
prospects” Sherine et al.,(2012) [15].
Hindustan
Community
College
syllabus
emphasizes the importance of personal ethics as an
important component of people skills. Martin Luther
King Jr. says:
Intelligence plus character--that is the goal of
true education. The complete education gives one not
only power of concentration, but worthy objectives
upon which to concentrate. The broad education will,
therefore, transmit to one not only the accumulated
knowledge of the race but also the accumulated
experience of social living. If we are not careful,
our colleges will produce a group of close-minded,
unscientific, illogical propagandists, consumed with
immoral acts. Be careful, “brethren!” Be careful,
“teachers”! [16]
XVI.  Conclusion
This research paper concludes highlighting the
importance of community college and its unique
feature in giving skills training to students empowering
the target learners in life coping skills and working
skills. The teaching methodology, the curriculum and
the assessment methods adopted in this institution
are unique and beneficial to the students. The study
shows that the majority of the students belonging to
the economically backward groups of society, and
the school drop outs transcending the social barriers,
are the beneficiaries of the programme offered by the
community college. It is noteworthy to mention that a
student of HCC was selected for one year training in the
USA as part of the Indo-US Community Scholarship
scheme initiated by the US Consulate in New Delhi,
India. Hindustan Community College fulfills the needs
of the students and has successfully conducted the
courses for three years. The institution has a record of
91.5% placement of students and the remaining 8.5%
have opted for higher education.
If one Institution can reach out to 200 – 300
deprived and excluded section of youth, empowering
them with required skills and helping them to come out
their societal and economic barriers to a world of new
hope, new status and life style, think of the changes,
countless organisations, institutions and corporate-big
or small, can make.
References
[1] V
ictor Luckerson, “Can Community Colleges Put
Americans Back to Work” Time.com. 28 Nov.
2012. Web 4 Feb. 2013. <http://business.time.
com/2012/11/28/can-community-colleges-putamericans-back-to-work/#ixzz2JDwgXqw2>.
[2] G
lenn, Robert and Katheryn Keene.“Smyth
County Industry Council. Workforce Demand
Profile 2003.” The Issues Management Group.
25 Jan. 2004.
[3] N
ational Collaborative on Workforce and
Disability for Youth, “Helping Youth Develop
Soft Skills for Job Success: Tips for Parents and
Families.” Web 4 Feb. 2013. <http://www.ncwdyouth.info/information-brief-28>.
96 HINDUSTAN JOURNAL, VOL. 6, 2013
[4] C
hugh, Sunita. “Dropout in Secondary
Education: A Study of Children Living in
Slums of Delhi” NUEPA Ocassional Paper
37, 2011. http://www.nuepa.org/Download/
Publications/Occasional%20Paper%20
No.%2037.pdf
[5] B
ryk and Thum, (1989): The Effects of High
School Organization on Dropping out: An
Exploratory Investigation, American Educational
Research Journal 26(3) 353-383.
[6] India to set up 100 community colleges: Sibal
Press Trust of India / New Delhi September 06,
2012, Web. 6 Feb. 2013. <http://www.businessstandard.com/generalnews/news/india-toset100-community-colleges-sibal/53051/>.
[7] C
hristian Manager “Community Colleges as an
Alternative System of Education” Interview with
Fr. Xavier Alphonse. Christian Manager. http://
www.cimindia.in/cm/Au-sp20-28.pdf
[8] “ Building American Skills through Community
Colleges.”
http://www.whitehouse.gov/sites/
default/files/100326-community-college-factsheet.pdf .
[11] “Curriculum and Instruction: A 21st Century
Implementation Guide” Partnership for 21st
Century Skills. http://p21.org/storage/documents/
p21-stateimp_curriculuminstruction.pdf
[12] “
21st
Century
Skills
Education
&
Competitiveness: A Resource and Policy Guide”
Partnership for 21st Century Skills.http://www.
p21.org/storage/documents/21st_century_skills_
education_and_competitiveness_guide.pdf
[13] C
asner-Lotto J, Barrington L. “Are they really
ready to work”? Washington, DC: Conference
Board, Partnership for 21st Century Skills,
Corporate Voices for Working Families, and
Society for Human Resource Management; 2006.
Web. 5 Feb. 2013. http://www.conference-board.
org/Publications/describe.cfm?id=1218
[14] B
uilding the Foundation for a Lifetime of
Success” Envision EMI White Paper June, 2010.
Web 5 Feb 2013. http://www.envisionemi.com/
pdf/Whitepaper_Experiential_Leadership_
Education.pdf
[9] E
lizabeth Redden, The ‘Community College’
Internationally, Web. June 16, 2010 http://www.
insidehighered.com/news/2010/06/16/intl
[15] A
kkara Sherine, A Rajkumar and N. Jose Pravin,
“Study on People Skills Enhances Learning
Outcomes and Peps up Job Placement using
Combined Overlap Block Fuzzy Cognitive
Maps (COBFCMS)” http://www.ijcaonline.org/
archives/volume57/number8/9136-3336
[10] R
esearch study on ‘Impact & Prospects of
the Community College system in India’
Aug 2003--Madras Centre for Research and
Development of Community Education–Chennai
[16] M
artin Luther King Jr., “The Purpose Of Education.”
Morehouse College Student Paper, The Maroon
Tiger, 1947. http://www.drmartinlutherkingjr.
com/thepurposeofeducation.htm
HINDUSTAN JOURNAL, VOL. 6, 2013
Continuous Professional Development: A Proposal for an
Integrated Programme in Teaching English as a
Second Language
P. Bhaskaran Nair
Abstract — The term ‘professionalism’ has become
the buzzword in almost all walks of life, erasing
border lines between occupations and professions.
Even the most ancient occupations -- agriculture
and trade -- are getting professionalized. Teaching,
which has hitherto been considered as everyone’s
cup of tea, and a field which anyone had anytime
access to, too has started demanding a high degree
of professionalism. Teaching English as a second
language (TESL) has become an internationally
acclaimed programme in higher education with
an optimal degree of professionalism embedded
in it. In India too, a few universities have started
offering pedagogical-cum- professional oriented
programmes in TESL, along with the conventional
programmes in literature. This paper tries to
present the rationale for introducing a seven-year
integrated programme in teaching English as a
second language with formal or action research
following it, so that teaching English becomes a
profession in its true sense.1
Index Terms — Continuous professional
development, Teaching English as a second language,
Action research, Integrated programme.
I.  TESL in India: The Maladies
Just have a look at some of the strange happening in the
field of (or in the name of ) English language education.
First, anyone, with or without even a bachelor’s degree
in any discipline, ‘becomes’ a teacher one fine morning
P. Bhaskaran Nair is in School of Applied Sciences,
Hindustan
University,
Chennai,
India
(e-mail:
[email protected]).
and starts teaching English! Many schools appoint
professionally unqualified people as teachers, and later
get them ‘deputed’ for training courses such as BEd.
and DTE.
Secondly, a few others with a bachelor’s degree and
a professional degree (BEd.) in some other discipline
teach English with the blessings of the governments.
Some of them have somehow managed to get a pass
minimum in the examination in the common English
component after repeated efforts! Thirdly, a young man
or woman, with a minimum degree of performance in the
PG programme straight away walks into a PG class and
starts ‘lecturing’ to the class without any professional
training in the field! Fourthly, a BEd. programme,
which is expected to give the teacher trainees the basics
of pedagogic principles and an initiative into teaching
profession has been reduced to an academic ritual of
four to seven months, across the universities in India.
If this is the pre-service scenario of teaching
professionals, the quality of in-service training
programmes which are meant for enhancing academic
excellence, is still worse. Higher education sector does
not seem to believe in excelling academic quality of
teachers through any kind of pre-service professional
training like a diploma or degree as we do have for
teaching in schools. Programmes such as Refresher
Courses and Orientation Programmes for a few days
conducted periodically by Academic Staff Colleges
have become an instance of academic ritual, if not
farce. (Exceptions may be there.) In-service teacher
training programmes in English for school teachers
are usually conducted in the regional language, to
the greater comfort of the ‘resource persons’ as well
as the participants! The real but pathetic picture of
the in-service teacher training programmes in general
98 HINDUSTAN JOURNAL, VOL. 6, 2013
has been presented by a practicing teacher in a small
volume, (See Hemraj Bhat, 2010).
What about the student community? Those poor
creatures, who are led by the carrot ahead of them called
marks and grades in the examinations, seldom get
dissatisfied with their performance either in the class or
in the examinations. While in class, regional language
comes to their help (quite often, following the model
of their English teacher)! In the public examinations
at the end of class X and XII, the strongest claimants
for ‘moderation marks’ are Mathematics and English.
Thus, students get through these hurdles without much
effort on their part.
Finally, how do the prime stakeholders, the parents,
respond or react to these eventualities? There seem to
have quite a few options before them. Adapt to the
system and, thereby be part of it, as the majority does it.
Secondly, express their dissatisfaction to the mainstream
education system by admitting their children in the socalled self-financing English medium schools, without
knowing that things are worse there, inside! Thirdly,
send them to professional courses (mainly, Engineering
and Medicine) where there is no English component in
the entrance examination, and thereby ensure a double
benefit—getting rid of the nuisance called English and
ensure a better career and a financially more secure
future for their children!
II.  Still, Not Beyond Remediation
Remediation is not something impossible. But the
teacher-researchers’ lamentation over the poor learner
performance at conferences and seminars does not
address the issue at all. The obvious reason, of course
is: “Physician, heal thyself first!” The quality of the
content as well as language of the papers presented
at these academic gatherings ( in the areas of both
language and literature) as revealed from the published
abstracts and proceedings themselves will attest the
remark made above.
The key academic issues underlying the facts
listed above can only be addressed by bringing in
professionalism to the academic programmes. The
term ‘professionalism’ needs to be clearly defined in
this context.
In general use, a ‘professional’ is a trained
and qualified specialist who displays a high
standard of competent conduct in their
practice. …The term ‘professionalism’ is
regularly used in a constitutive sense to
refer to practitioners’ knowledge, skills, and
conduct. In discussions on teacher education,
professionalism issues are often addressed
through questions such as What should
teachers know? and How should teachers
go about their business?(Leung,C.2009, p.
49).
One effective way of addressing this malady which
afflicts teaching of English—at least to avoid such a
fate in future—rests with the university departments
which have academic autonomy and have a say in such
matters. A seven-year integrated programme in English
Literature and Teaching Second Language (ELTSL)
can address most, if not all of the shortcomings of the
existing UG and PG programmes in English, currently
being offered by the Indian universities. A proposal to
this effect follows.
III.  Structure of the Programme
The fourteen-semester Integrated programme can be
perceived in three stages: The first six semesters as a
UG programme, the following four semesters as a PG
programme (with provision for lateral entry through an
entrance examination), and the last four semesters, as
a professional programme. At each terminal point, that
is, at the end of the sixth, tenth and fourteenth semester
the student is entitled for different degrees such as the
bachelor’s, Master’s and Professional’s. As a result, the
student can terminate the course at the end of the first
stage and still can have vertical growth, taking diversion
into journalism, Mass Media, Communication and so
on; or pursue professional programmes such as Law.
In the same way, new admissions can be made into the
programme at the beginning of the seventh semester on
the basis of an entrance examination which does justice
to the course contents of the first six semesters. Again,
the student must be free to leave the programme at the
end of the tenth semester with a Master’s degree.
IV.  Course Contents
It will be rather untimely to restrict the contents of
the whole programme at this point of proposal; but at
the same time, it seems imperative to suggest a broad
BHASKARAN NAIR: ONTINUOUS PROFESSIONAL DEVELOPMENT 99
outline of the contents spread over the three stages.
They are as follows:
Stage i. The Under graduate
English language: 50%
English and Other Literatures in Translation: 50%
Stage ii. The Post graduate
English language: 40 %
English and other literatures: 60%
Stage iii. Professional
Teaching English language and literature: Theory 75%
Practice: 25%
The allocation outlined above, no need to say, is
tentative. Alteration is part of the system. The details of
the syllabi can be worked out at the appropriate time.
V.  Research / CPD
The pedagogic functioning of the university
department which offers the integrated programme
proposed above does not end with producing a
professional who is expected to meet the challenges of
the profession well. It further demands the department
to promote academic research in the field of TESL
along with the conventional areas such as literature
and cultural studies. It must also sponsor ongoing (and,
never ending) academic events leading to continuous
professional development (CPD) in the form of inservice teacher education, action research and so on.
That is to say, it is the department’s duty to provide a
permanent platform for its former students who have
entered the teaching profession to periodically meet
and discuss issues related to the teaching-learning of
English. Such periodic events can be in the form of
workshops, conferences, self help groups (SHGs),
special interest groups(SIGs), non-governmental
organizations (NGOs) and so on.
VI.  Action Research in Focus
As hinted above, the programme does not come to an
end by the end of the fourteenth semester; it is only
the first half, the second half being CPD in the form
of in-service teacher education programme, action
research etc. along with formal academic research.
Action research is less known in academic circles,
especially among college teachers.
What is action research? A cluster of mutually
complementing definitions (since each is liable to be
incomplete by itself) is given below.
“Action research is a process of systematic
reflection, enquiry and action carried out by individuals
about their own professional practice’ (Frost,2002,p.25).
“ Action research is a term used to describe
professionals studying their own practice in order to
improve it” (GTCW,2002,p.15).
“ Educational action research is an enquiry which
is carried out in order to understand, to evaluate, and
then to change, in order to improve some educational
practice (Bassey, 1998,p. 93).
“Action research combines a substantive act
with a research procedure; it is action disciplined by
enquiry, a personal attempt at understanding while
engaged in a process of improvement and reform
(Hopkins,2002,p.42).
“When applied to teaching, [action research]
involves gathering and interpreting data to better
understand an aspect of teaching and learning and
applying the outcomes to improve practice (GTCW,
2002,p.15).
“Action research is a flexible spiral process which
allows action (change, improvement) and research
(understanding, knowledge) to be achieved at the same
time (Dick,2002).
“ Action research is … usually described as cyclic
with action and critical reflection taking place in turn.
The reflection is used to review the previous action and
plan the next one’ (Dick, 1997).
“ Action research is … an approach which has
proved to be particularly attractive to educators because
of its practical, problem-solving emphasis…” (Bell,
1999,p.10).
(The compilation of definitions above has been
quoted from Action Research (p.3- 4)
Put together these definitions will tell us how
important it is for a teacher to be an active action
researcher as well, so that professionalism can be
attained in teaching career.
100 HINDUSTAN JOURNAL, VOL. 6, 2013
VII.  Expected Outcome
One may doubt the relevance of claiming a special if not
superior status for the English Department. Introducing
a volume on English language teacher education, the
editors Anne Burns and Jack C. Richards state:
One of the simple facts in the present time
is that the English language skills of a good
proportion of citizenry are seen as vital if
a country is to participate actively in the
global economy and to have access to the
information and knowledge that provide
the basis for both social and economic
development. Central to this emphasis are
English teaching and English language
teachers. There is consequently increasing
demand worldwide for competent English
teachers and for more effective approaches
to their preparation and professional
development.
The expected outcome of a University department
of English offering such a course and engaging
in the ongoing follow up programmes of CPD is
multidirectional. First, the maladies listed at the outset
of this paper which are currently gripping the body
called English language teaching, can be prevented the
most successful way. ( As the saying goes, prevention
is better than cure.) The products of such a programme
will be well equipped to meet any challenge of an
English classroom, since (s)he is likely to have acquired
adequate competence in the fields such as Theoretical
linguistics, Applied linguistics, Second language
acquisition, Educational psychology, Second language
pedagogy and English literature.
Secondly, such a University department will be
functioning as a beacon (to borrow a phrase from
Jawaharlal Nehru’s celebrated convocation address at
Allahabad University, interestingly in the context of
defining the role of a University in the independent
India). How Nehru envisages the role of a university in
terms of guiding the youth, and thereby the entire nation
is applicable in its true spirit in the case of a teachingresearch department as well. Think of the day in which
teachers of English—of all levels, from pre-primary to
university—located far and near, old students or not,
being constantly in touch with the university department
for consultation, guidance, meeting, sharing and thus
contributing to the infinite growth of the department,
and in turn, the whole University. Into that University
department, let me awake!
References
[1] B
hat, Hemraj, (2010), “The Diary of a School
Teacher”, Tr. Sharada Jain. Bangalore, Azim
Premji Foundation.
[2] B
urns, Anne. (1999), “Collaborative Action
Research”, Cambridge, Cambridge University
Press.
[3] B
urns, Anne and J.C. Richards. (2009), “Second
Language Teacher Education”, Cambridge,
Cambridge University Press
[4] C
ostella, Patrick.J.M. (2003), “Action Research”,
London, Continuum Publishers.
[5] L
eung, Contant. (2009), “Second Language
Teacher Professionalism”. In Burns, Anne and
J.C.
[6] R
ichards. (2009), “Second Language Teacher
Education”, Cambridge, Cambridge University
Press.
[7] T
udor, Ian. (1996), “Learner-centredness as
English Language Education”, Cambridge,
Cambridge University Press.
HINDUSTAN JOURNAL, VOL. 6, 2013
Librarianship in Digital Era
E. Boopalan, K. Nithyanandam and I. Sasirekha
Abstract — In this age of Information Technology,
there have been so many opportunities for the
librarians for involvement in an informationbased society including electronic and multimedia
publishing, internet based-information services,
global networking, web based digital resources etc.
Digital libraries require the digital librarians
(DL) to be essentially a type of specialist librarian
who has to manage and organize the digital library,
handle the specialized tasks of massive digitization,
storage, access, digital knowledge mining, digital
reference services, electronic information services,
search co-ordination, and manage the archive and its
access. This article highlights the roles and functions
of a DL in information retrieval, content delivery,
navigation, and browsing. It denotes the DL’s
interface functions, roles, skills and competencies
for the management of digital information systems
in the important areas of imaging technologies,
optical character recognition, markup languages,
cataloguing, metadata, multimedia indexing
and database technology, user interface design,
programming, and Web technology.1,
Index terms — Digital Era, Digital Library, Library
Management, Librarianship, Cloud Computing
I.  Introduction
Most people believe that internet can replace the library
and they can get all types of informational sources from
it. Therefore, the librarians should take on the challenge
of guiding the users on how to evaluate and identify
the accurate and correct sources using the right method.
E. Boopalan, K. Nithyanandam and I. Sasirekha are
in School of Applied Sciences, Hindustan University,
Chennai, India (e-mail: [email protected], cl@
hindustanuniv.ac.in, [email protected])
This can be achieved only if the librarians are well
prepared and are aware of the new transformational
changes occurring in the libraries.
Traditionally librarians are known as individuals
working in the library building and are responsible
in carrying out tasks such as: cataloging, acquisition,
circulation, customer service, user education, etc. They
are also involved in acquiring, organizing and preserving
the printed materials besides helping and guiding the
readers in searching and locating the information they
need. In the last decade this situation has been rapidly
changed due to the advancement in information
technology, communication and internet connection. For
centuries librarians have been known as the information
providers using the manual and traditional methods
but now due to current trends, librarians need to adapt
to the new working environment which will help them
in providing faster, complete and effective ways of
accessing information for their users. The ultimate goal
of a Digital librarian is to facilitate access to information
just-in-time to the critical needs of end users and
additionally to facilitate electronic publishing.
The digital librarian plays a distinctive and dynamic
role in easy accessing of computer held digital information
including abstracts, indexes, full-text databases, sound
and video recording in the digital formats. For finding
the right information at the right time, the research,
education and training, learning and developmental
work and disseminating to the user in required format
are the basic requirements of Digital librarian.
II.  Role of a Digital Librarian
In this digital era, librarians have to change themselves
as the information profession is changing. The new
generation of library users or “technology savvy users”
realized that they need help from the librarians to guide
and teach them how to search and access information
102 HINDUSTAN JOURNAL, VOL. 6, 2013
using the latest technology and internet facilities
provided by the library. In order to change, librarians
need to be aware and be ready to take on the new
responsibility such as:
A. Information Organizer and Provider – Able to
provide services and instructions regardless of place or
time.
B. Librarian as an Instructor – The most important
task carried by the new version of Librarian/
Information Professional is in educating their library
users. Librarians often carry out information searches
requested by the users especially in Academic
Libraries. This situation can be quite burdensome
for some librarians since a small number of librarians
need to serve a very large number of requests from
various library users. It is necessary for the users to do
the information searching or research themselves and
to help them in this matter; librarians need to educate
them first. From time to time, the number and variety
of information sources available, whether from printed
sources or via the World Wide Web, have increased
greatly, and users are having difficulties in keeping up
with all of the choices now open to them. Therefore,
librarians need to educate their library users on how
to search, find, evaluate and store the information.
Librarians in most IPTA/IPTS have greatly enhanced
their provision of user education, especially in regards to
electronic sources of information, which is now known
as the most dominant activity by Librarians. Cataloging,
Circulation and Customer Service is slowly being
delegated to paraprofessionals. Librarians now have the
same important roles as academic staff whereby they
are involved in giving training and guidance especially
in the use of electronic journals from many different
publishers, abstracts and indexes databases, databanks,
CD-ROM publications, document delivery services,
citation styles, evaluation criteria for internet sources
and many more. In short, librarians are the information
literacy experts.
C. Navigator, Browsing and Filtering Experts –
Librarians should be aware of the new trends in
technology and approaches. They should be able to
know and understand how the digital reference services
works and extract the electronic information from
digital information sources.
D. Consultant – Librarians should be prepared to
answer any queries by users. There is no reason for them
to delay the process. In order to adapt to the digital era,
ways for the librarians to answer all questions enquired
by the library users either through email, facebook,
twitter, skype, telephone, etc. need to be identified. A
library can also upload videos about itself in Youtube
for users who want to know more about that particular
library.
III.  Digital Library Access Tools
There are various tools available to use in digital
information systems and they facilitate in accessing,
searching, browsing, navigating, retrieving, indexing,
storing, organizing and dissemination of digitized
information. The list given below is the digital
information sources and pools, and these are used as
digital access tools which ultimately aim to facilitate
universal access to all:
Online public access catalogues (OPACs): metadatabases (describe, provide link to other databases/
digital information sources; online databases (KnightRider, OCLC, MEDLINE).
Internet-based tools: e-mail networks, mailing
lists, electronic conferences, World Wide Web, Website
home pages, Wide Area Information Services (WAIS),
Web browsers, Gopher systems, and Veronica Archie,
FTP, Telnet, Usenet, Newsgroups, BBS, List servers,
discussion groups.
Digital networks/networking:
BLAISE, MEDLINE, NICNET, DELNET, AGRIS,
INIS and all sorts of networks.
Further, access is needed to:
●● Hypertext/Hypermedia.
●● Multimedia (high bandwidth computer networks).
●● Multimedia networking protocols.
●● Cellular and pager networks.
●● Electronic publishing tools.
●● Net-dwelling software agents.
●● Electronically fax/commercial vendors.
●● Telephone/TV
IV.  Role of Cloud Computing in Libraries
Cloud computing is a completely new technology and
it is known as the third revolution after PC and Internet.
BOOPALAN ET AL : LIBRARIANSHIP IN DIGITAL ERA 103
Cloud computing is an enhancement of distributed
computing, parallel computing, grid computing and
distributed databases. Among these, grid and utility
computing are known as predecessors of cloud
computing. Cloud computing has large potential for
libraries. Libraries may put more and more content into
the cloud. Using cloud computing, user would be able
to browse a physical shelf of books, CDs or DVDs or
choose to take out an item or scan a bar code into his
mobile device. All historical and rare documents would
be scanned into a comprehensive, easily searchable
database and would be accessible to any researcher.
Many libraries already have online catalogues and
share bibliographic data with OCLC. More frequent
online catalogues are linked to consortium that share
resources.
Data storage in cloud is a main function of libraries,
particularly for those with digital collections. Storing
large digital files can stress local server infrastructure.
The files need to be backed up, maintained, and
reproduced for patrons. This can strain the data
integrity as well as hog bandwidth. Moving data
to the cloud may be a leap of faith for some library
professionals. On the surface it is believed that library
would have some control over this data or collections.
However, with faster retrieval times for requests and
local server space it could improve storage solutions
for libraries. Cloud computing or IT infrastructure that
exists remotely, often gives users increased capacity
and less need for updates and maintenance, and has
gained wider acceptance among librarians.
V.  Cloud Computing in Libraries
The advantages of Cloud computing are:
●● Cost saving
●● Flexibility and innovation
●● User centric
VI.  Cloud libraries
The examples of Cloud Libraries includs:
●● OCLC
●● Library of Congress (LC)
●● Exlibris
●● Polaris
●● Scribd
●● Discovery Service
●● Google Docs / Google Scholar
●● Worldcat
●● Encore
VII.  Competencies and Skills of a Digital
Librarian
The competency of a digital librarian is represented
by different sets of skills, attitudes and values that
enable a digital librarian to work as digital information
professional or digital knowledge worker and digital
knowledge communicator.
The following are the skills and competencies
required for a digital librarian in the management of
digital information systems and digital libraries:
A.  Internet, WWW:
●●
Navigation, browsing, filtering;
●● Retrieving, accessing, digital document analysis;
●● D
igital reference services, electronic information
services;
●● S
earching network databases in a number of digital
sources and Websites;
●● Openness
●● C
reating home pages,
downloading techniques;
content
conversion,
●● Transparency
●● WEB publishing, electronic publishing;
●● Interoperability
●● Representation
●● A
rchiving digital documents, locating digital
sources;
●● Availability anytime anywhere
●● Digital preservation and storage;
●● Connect and Converse
●● Electronic messaging, connectivity skills;
●● Create and collaborate
●● WEB authoring.
104 HINDUSTAN JOURNAL, VOL. 6, 2013
B.  Multimedia, digital technology, digital media
processing:
●● M
ultimedia indexing, image processing, objectoriented processing;
●● I
nteractive
digital
visualization;
communications
and
●● C
ataloguing and classification of digital documents,
digital content;
●● S
earching and retrieval of text, images and other
multimedia objects;
●● Speech recognition, image visualization;
●● A
dvanced processing capabilities exploiting digital
medium;
●● C
onferencing
techniques
teleconferencing, video conferencing.
including
librarian, digital information professional, cybrarian,
and information broker. A different view of the future
might be one where a ``digital library’’ is more like a
``knowledge warehouse’’, where a complex system
of professionals whose expertise supports access
to information acts as an intermediary to a variety
of digital and other sources (Kuny and Cleveland,
1998). It is especially important to understand that the
ultimate goal is not just to facilitate access to digital
information just-in-time to the critical want of endusers and additionally electronic publishing, but to
create and develop digital knowledge channels, digital
knowledge sources which allow synergy between
partners leading to mutual exchange and enrichment of
digital knowledge domain.
IX.  Challenges in Digital Era
The challenges to be faced in the digital era are:
C.  Digital information system, online, optical
information:
●● New generation of learners
●● I
nterfacing online and off-ramps, twists and turns
of digital knowledge;
●● Privacy/Confidentiality
●● Development of digital information sources;
●● Technology Challenges
●● Digitization of print collections;
●● Manpower
●● Competency to manage CD-ROM network station;
●● Collection of e-digital resources
●● D
evelopment of machine readable catalogue
records;
●● Organizational structure
●● Design and development of databases;
●● D
esign and development of software agents for
digital libraries;
●● Conversion of print media into digital media;
●● Knowledge in digital knowledge structures.
VIII.  Transformation as a Digital Librarian
In future, the librarian would mostly become an online
worker, supporting the citizen/worker by selling
services. Finding relevant information faster than the
competitors, faster than a non-information-worker can
do, and surviving on the basis of superior knowledge
of the networks and digital information resources
available through them would be his main concern. We
already have the words to describe these roles: digital
●● Copyright Act
●● Online/Virtual Crimes and Security
●● Preservation/Archiving Digital Resources
●● Lack of clarity in vision
X.  Conclusion
The digital librarian will become the guardian of
digital information and will be the vehicle to preserve
democratic access to information. The digital librarian’s
role will be increasingly towards offering consultancy
to the users in their efforts in providing digital reference
services, electronic information services, navigating,
searching and retrieval of digitized information through
Web documents that span the Universal Digital Library
or the Global Digital Library. The digital librarian will
be an embodiment of a digital information professional
or digital knowledge worker, who will ensure that the
digital libraries are used effectively and with ease.
Digital librarians with newly acquired skills can
BOOPALAN ET AL : LIBRARIANSHIP IN DIGITAL ERA 105
play a meaningful and leading role in the networked
information society of the millennium. Digital
librarians add values and can make digital libraries truly
useful and user friendly. The knowledge that ``digital
librarians’’ bring to this knowledge environment would
make sense of a multiplicity of digital collections and
resources, provide access to a network of key contacts,
identify cost-effective strategies for information
retrieval, and assist users in the publication and creation
of new knowledge.
References
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Efthimoadis, E. N., Gilliland- Swetland, A. J.,
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digital libraries”. Retrieved 2012 from http://dlis.
gseis.ucla.edu/DL/UCLA_DL_Report.html
[2] E
guavoen, O. E. L. (2011). “Attitudes of Library
Staff to the Use of ICT: The Case of Kenneth
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[3]
adehan, O. A., & Ali, H. (2010). “Educational
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Needs of Librarians in the Digital Environment: Case
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[4] G
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[5] H
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