1. No category

HOW TO GET A PH.D.: Methods and Practical Hints
(2006-2007)
http://www.infotech.oulu.fi/GraduateSchool/ICourses/2006
/to_phd_2006.html
Aarne Mämmelä v. 1.01 30.10.2006
VTT TECHNICAL RESEARCH CENTRE OF FINLAND
III RESEARCH METHODS: FROM PROBLEM AND
HYPOTHESIS TO EXPERIMENTS
•Introduction
•Research & development
•Choosing a problem
•Formation of concepts and theories
•Order and creativity
•Empirical-inductive method
•Conclusions
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Table of Contents
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Introduction
Research and development
Values of science
IEEE code of ethics
Researcher and advisor
Choosing a problem
Concepts and theories
Formation of concepts
Formation of theories
Analysis, simulations, and experiments
Theories of truth
Creativity
Sequential and iterative order
Empirical-inductive method of discovery
Reductionism and holism
Hypothetico-deductive method of verification
Hierarchies
What is guiding our work
Fundamental problems
Technology: natural science and engineering
History of electronics
Brief history of scientific method
Conclusions
References
Recommended reading
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48
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97
99
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Introduction
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Journey of Exploration: Columbus
•Problem: a new way to India
•Competing hypotheses: over the Atlantic
(Spain), around Africa (Portugal)
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What is Research All About: Problem and Hypothesis
Answer
(hypothesis)
Experience
(analogies)
Criticism
(testing)
Question
(problem)
•No general systematic methods exist to discover
hypotheses (creativity needed as in the arts [Nagel79])
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Research and Development [Jain97]
•research: discover new knowledge (new regularities)
• basic research (no specific application in mind)
• applied research (ideas into operational form)
•development: systematic use of the existing knowledge
•research and development are closely related
•in research a prototype is often developed
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Product Life Cycle
•consumer and customer needs
•product requirements (translation of customer
needs into technical terms)
•product concept (description of the technology,
primary features, and form of a product)
•product specifications (description of a product to
be designed which operates in the environment
specified in the product requirements)
•purchase, implementation, manufacturing,
distribution, marketing, installation, operation,
maintenance
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Performance [Bock01]
•Performance metric a function whose output is
performance value
•Performance value numerical value of the
performance metric, to be compared with the
performance requirement
•Performance requirement desired performance
value
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Accuracy and uncertainty [amc03], [ISO Guide 99]
Accuracy the closeness of agreement between a measurement result and the
accepted reference value (the accepted true value of the measurand),
includes the terms trueness and precision, expressed with uncertainty
Trueness the closeness of agreement between the average value obtained from
a large series of measurement results and the accepted reference value,
includes systematic errors only
Precision the closeness of agreement between independent measurement
results obtained under stipulated conditions, includes random errors only
Uncertainty parameter that characterizes the dispersion of the quantity values
that are being attributed to a measurement, includes systematic and random
errors, expressed for example with standard deviation (if known systematic
errors are first removed), or coverage interval (confidence interval) and
coverage probability (confidence level)
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Science, technology and engineering [Jain97]
•science: organized or systematic body of knowledge
[Nagel79]
•technology: the ways we provide ourselves with the
material objects of our civilization, application of
scientific knowledge for practical ends in
engineering, medicine, agriculture, etc.
•natural sciences and engineering sciences differ in
the object of study
•natural sciences (also called “science”, inc.
physics, chemistry, and biology): objects in the
nature
•engineering sciences: objects (products,
services, methods) not found in the nature, using
results of mathematics and natural sciences
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Scientific Method
•“a method of research, in which a problem is
identified, relevant data are gathered, a hypothesis
is formulated [discovery], and the hypothesis is
empirically tested [verification]”[Random House99]
•data is collected through observation or experiment
•testing is done for verification or falsification of the
hypotheses
•inference based on many competing hypotheses is
called strong inference [Wilson99]
•two tools of control: observations and experiments
(guarantees correspondence with reality) and
mathematical analysis (guarantees coherence)
Note. Verification, confirmation, and justification are
synonymous terms in philosophy of science. The
opposite is falsification or refutation.
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Features of science [Wilson99]
•Generality (theories describe general regularities,
causal relations, nature is not capricious)
•Reproducibility (repeatability, inductive predictions,
correspondence between the theory and reality,
consensus among researchers by independent tests)
•Coherence (unity or consistency, causal and
deductive relationships, no contradictions)
•Parsimony (economy, Ockham’
s razor: simplest
theories are most elegant)
•Heuristics (good science results in additional
inventions)
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Why is research important? [Hicks99]
•New knowledge is discovered
•Prestige for yourself and for your
employer
•Know the state of the art and teach
it to your colleagues and customers
•Know the history and see the trends
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Why is research exciting?
•Intellectual pleasure: you learn to know something
very deeply [Feynman99].
•Thrill: you work like a detective when looking for
existing knowledge.
•New knowledge: you discover something that did not
exist previously.
•Prestige: you will become a doctor and an
internationally known expert [Hicks99].
•Spirit of the scientific community: special research
culture, freedom to think, suspect and criticize
authorities, impersonal judgments of discoveries,
integrity (= honesty) [Jain97].
•Unique communication network: you meet the most
intelligent people in the world in your field [Jain97].
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“Republic of Science” [Polanyi62]
1. Free cooperation
• independent scientists cooperate freely (no superior above them),
all results are public, each step decided by the most competent
person, steps are unpredictable (free discussions crucial to work
like a “super-brain”)
• isolation of scientists would prohibit progress
2. No authorities
• each scientist understands only a tiny fraction of the total
domain of science (closely knit organization, overlapping
neighborhoods)
• scientific opinion it is not held by any single human mind (no
authorities), but is established between scientists
3. Invisible hand
• scientific merit measured by plausibility, scientific value and
originality
• preference given to the most promising scientists and subjects to
yield the maximum advantage (cf. “invisible hand”in Adam
Smith’
s [1776] economy theory)
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Three Basic Values of Science
1. Criticism
• aim of objective criticism is to improve the
quality of research and to avoid groupthink
2. Integrity (honesty)
• giving credit to the contributions of others and
taking into account the limitations of available
data
• reporting only about what has been observed and
everything what has been observed
3. Publicity
• everyone has the possibility to know about
others’contributions (Polanyi’
s jigsaw puzzle)
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Researcher and Organization
ROLE OF ORGANIZATION
ROLE OF RESEARCHER
1. History and state of the art
I d ea
2. Vision and roadmap
3. Fundamental principles and
problems
4. Research problems and projects
L ite ratu re review
P ro b lem an d
h y p oth ese s
5. Marketing, recruiting, investing
6. Project plans
7. Research culture and education
E x p e rim e n ts/
a n aly sis
Sy stem
(p roto ty p e)
T h eo ry/ p a p er
(n e w k n ow led g e)
8. Integration of results
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IEEE Code of Ethics (extract)
[www.ieee.org/portal/pages/about/whatis/code.html]
Members of IEEE commit themselves to the highest
ethical and professional conduct and agree:
•to avoid real or perceived conflicts of interest;
•to be honest and realistic in stating claims or
estimates based on available data;
•to seek, accept, and offer honest criticism of work,
to acknowledge and correct errors, and to credit
properly the contributions of others;
•to avoid injuring others, their property, reputation,
or employment by false or malicious action;
•to assist colleagues and co-workers in their
professional development and to support them in
following this code of ethics.
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Requirements for the Success as a Researcher
Requirements for success
•analytical, curious, need for autonomy and change, flexible,
collaborative, tolerant of ambiguity, criticalness (avoid
groupthink) [Jain97]
•knowledge of literature, technical skills, communication skills
(knowledge of languages, social and pedagogical skills), and
creativity (original thinking) [Loehle90]
How does a researcher work?
•make always notes in a notebook
•make summaries on what has been learned
•make plans for the future all the time (outlines, roadmaps,
visions)
•discuss, ask questions and argue (criticism)
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Official Requirements for a Doctor
•major subject: deep familiarity with own research
area and its societal significance, ability to
independently discover new scientific knowledge,
and preparation of a doctoral thesis and its
successful public defence
•minor subject: good familiarity with other related
research areas
•scientific general studies: good familiarity with
historical development and basic problems, as
well as research and design methods of engineering
sciences
Source: University of Oulu, www.ttk.oulu.fi/opinnot
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Special Studies
•Equivalent to 70 credits (opintopiste, op) or 40-45 credits
(opintoviikko, ov), excluding the doctoral thesis
•Major subject must be related to some major subject of a
degree program in the faculty (40-55 credits (op) or 25-35
credits (ov)), may include courses in advanced studies
(marked with S) of the basic degree program
•Minor subject must be related to a professorship of the
university or some other native or foreign university (10-25
credits (op) or 9-17 credits (ov)), may include courses in
advanced and subject studies (marked with S or A) of the
basic degree program
•Scientific general studies (5-10 credits (op) or 3-5 credits
(ov)), may include courses in subject and general studies
(marked with A or P) of the basic degree program, no
language studies accepted
•60 credits (op) correspond to 1600 hours (one academic year)
Source: University of Oulu, www.ttk.oulu.fi/opinnot
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Progress of Doctoral Studies (1)
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Progress of Doctoral Studies (2)
•The student must have a master’
s degree and good familiarity with
the planned major subject (usually shown by good marks in the major
subject in the master’
s degree).
•Standard time for doctoral studies is four years (for a full-time
student).
•The advisor (supervisor) of the degree is a professor or doctor (often a
docent) representing the major subject.
•The manuscript of the thesis is pre-examined (in maximum of three
months) by at least two pre-examiners or referees from outside the
faculty, and the manuscript is then published if the statements are
positive (pre-examination is organized by the department council).
•In the public defence there are one or two opponents and custos
(chairman), who is usually the advisor of the degree.
•The opponents write a statement about the thesis and its defence (in
maximum of four weeks, usually on the same day).
•The faculty council accepts the thesis based on the statement (grading
is pass or excellent) and the dean gives a certification.
Source: University of Oulu, www.ttk.oulu.fi/opinnot
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Advisor is your best friend
•The local advisor is any doctor familiar with the topic
and usually working for the same employer
•Look for a good advisor [Sternberg81]
•Be there for the length of your project
•Experience on research in the same area (must be
a doctor)
•Pedagogical skills, know the large picture, know
literature
•Respected by colleagues, critical, tough
methodologist
•Interested in your topic, gives comments, you
respect him or her
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How to keep your advisor?
•Orient your advisor (system model, block diagrams,
table of contents).
•Follow instructions (make notes and read them), but
also discuss and argue.
•Write concise progress reports (organize the
material, limit the scope).
•Show initiative, get into the driver’
s seat from the
back seat [Sternberg81], do not just wait that
everything is made ready for you, the advisor gives
you ways of thinking.
•If you show that you do not appreciate the work of
the advisor, this is one certain way to loose the
advisor.
•Collaboration in research implies writing papers
together, the advisor needs also credit for his or her
work, otherwise he or she is frustrated.
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Research Methods: Discovery and verification
[Honderich05]
Methods of discovery
•empirical-inductive method [Kragh02]
•iterative method [Bohm87]
•reductive method [Wilson99]
•systems engineering [Bohm87], [Checkland99]
Methods of verification
•hypothetico-deductive method [Rosenberg00]
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Sources of knowledge [Honderich05]
•deductive and inductive reasoning
•experience, observation and experiment, improved
instruments [Derry99]
•analogy [Bohm87], [Feynman98]
•abduction (Russel’
s chicken [Deutsch98]), intuition,
imagination, dream (Descartes: reductionism
[Wilson99], Kekulé: benzene [Hudson92], Mendeleyev:
periodic system of elements [Strathern00])
•patterns and discrepancies in data, serendipity
[Derry02]
•wild guess [Losee01], brainstorming [Davis97],
telepathy, clairvoyance, precognition, etc.
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Choosing a Problem [Loehle90]
•right problem, right timing, right approach
[Hamming93], difficulty of problem and its likely
payoff
•opportunities for you
•other person is wrong (show what is right)
•contradictory experiments
•terminological confusion
•more experience needed to solve problems
•discussions (most new ideas are generated by
talking with others[Jain97])
•experiments (start them early, use
experimental-inductive approach)
•literature (find out existing knowledge)
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Formation of Concepts and Theories
• We learn by induction (bottom up, generalization
from examples to models) [Felder88]
• We present theories by deduction (top down, from
models to results)
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Formation of Concepts [Niiniluoto02]
•A definition names a wider class to which something
belongs and distinguishing properties [Honderich05]
•Elementary terms and concepts: no definitions given to
avoid an endless loop of definitions [Rosenberg00]
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Division of a System into Parts and Properties –
Different Views [Honderich05]
• system is a combination of parts forming a
unitary whole
• complexity refers to number of parts and their
relations
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Set-member and part-whole relations [Honderich05]
• A whole consists of parts, properties, relations,
and events.
• A process is a series of changes with some unity
or unifying principle (time is the dimension of
change).
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Resources are Converted into Properties
[Checkland99], [Honderich05]
•performance is the manner in which something
reacts or fulfils its intended purpose
•complexity measures the efficiency in using the
basic resources, for example materials (size and
weight), energy, time (delay) and capital (cost)
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Temperature
Pressure
Humidity
Vibration
Resources are converted into properties (2)
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Observation and Theory [Wohlin00]
•In engineering a hypothesis (defined in system
specifications) is usually an idea of the relationship
between the cause and effect (defined in system
requirements)
•Theoretical model is always only an approximation
of observation in real world (prototypes include tacit
knowledge [Leppälä03], e.g., Stradivarius violin)
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Prototype
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Theoretical Model
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Taxonomy of theories [Rosenberg00]
1. Axiomatic systems –ideal form of theory
• theorems are derived deductively (= analysis) from
definitions and axioms
• two forms: Hilbertian axiomatic systems in formal
sciences (mathematics, logic, set theory, computer
science) and hypothetico-deductive systems in
empirical sciences
2. Theories based on sets of theoretical models
• results are derived by analysis (deduction) from the
definitions and assumptions of the model
• usually used in science and engineering, for example
ideal gas, Bohr model of atom
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Taxonomy of models [Honderich05]
1. Physical models
• small- or large-scale material constructions (miniature
or micro-models and macro-models), for example metal
model of the double-helix of DNA by Watson and Crick
2. Theoretical models
• internal structure of the system mapped to the model,
simplifying assumptions made
• models are used for prediction purposes (scientific work
in engineering uses theoretical models), prediction is
done by using analysis (deduction)
• mathematically intractable models can be simulated
with a computer
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Theoretical models [Niiniluoto02]
• there is some analogy between the reality and the
model
• mathematical models are (1) deterministic, (2)
probabilistic, or (3) their combinations (regressive
models, for example Gauss-Markov model)
• models usually include parameters or states that
may be estimated, for example with a Kalman filter
Regressive model
(f(x) is a regression function
and ε(i) is an error term)
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Taxonomy of scientific explanations [Nagel79]
1. Deductive explanations
• deductive systems
2. Probabilistic explanations
• probabilistic models
3. Teleological explanations
• in suspect in natural sciences
3. Genetic explanations
• evolution theory
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Taxonomy of scientific laws [Nagel79]
1. Sequential laws
a. Causal laws (Newtonian mechanics, relativity
theory)
b. Developmental laws (incomplete description,
historical and genetic descriptions)
2. Functional laws
a. Statical laws (Boyle-Charles’law for ideal gases)
b. Dynamical laws (Galileo’
s law for freely falling
bodies)
3. Probabilistic laws
• neither causal nor deductive (tossing of a cube,
quantum theory)
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Model and Results
• The theoretical model implies all the results since they
are derived deductively or “revealed”from the model,
i.e., the model includes all the results in a “nutshell”
(some regularity described).
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Taxonomy of Axiomatic Systems [Niiniluoto02]
Hilbertian axiomatic
systems
• used on formal sciences
• no interpretation made
• the axioms are assumptions
and initially the theorems
are hypotheses or
conjectures, which are
proved by deriving them
deductively from axioms
• examples: logic, arithmetics,
geometry, set theory,
probability theory
Hypothetico-deductive
systems
• used in empirical sciences
• interpretations made
• initially axioms are
hypotheses that are verified
indirectly by comparing the
results with reality
• examples: Newtonian
mechanics, quantum
mechanics, hypotheticodeductive systems are used
also in biology and social
sciences
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Comparison of Theories
[Honderich05], [Rosenberg00]
Axiomatic system
Model-based theory
Primitive
symbols
Primitive
terms
Definitions
Definitions
Rules of
inference
Model and
assumptions
Rules of
analysis
Theorems
Results
Rules of
formation
Rules of
verification
Axioms
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Theoretical Model and IMRAD Structure
[Day98], [Rosenberg00]
Primitive
terms
Introduction
Definitions
Materials and
methods
Model and
assumptions
Rules of
analysis
Results
Discussion
Results
Rules of
verification
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Analysis, simulations, and experiments (1)
Analysis
Simulation
Prototype
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Analysis, simulations, and experiments (2)
1. Mathematical analysis (theoretical model)
• creates best scientific papers
• simple, mathematically tractable problem, must be often linear
(numerical results needed)
2. Simulations (numerical analysis of the theoretical model)
• complicated systems can be developed rapidly, but slow to simulate
• basic idea: lower level blocks are simplified and idealized (hierarchy)
• key problem: realistic models for the environment (e.g. channel)
3. Prototyping (empirical research)
• more convincing than “pure”simulations, not so flexible, slow and
expensive to develop complicated systems
• environment (channel) simulators still needed (approximations!), field
tests expensive, repeatability?
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Building a prototype
• Build the prototype from complete components
• as high integration as possible
• Build a focused prototype instead of comprehensive
prototype [Ulrich95]
• demonstrate the novel properties
• Build a scaled prototype [Honderich05]
• macroscopic or microscopic (miniature) model
• example: use 100 Hz instead of 1000 Hz (time scaled
down by ten, spatial dimensions scaled up by ten)
• Build a virtual prototype
• simulation models are time-scaled models
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Experiment (Set of Tests) [Wohlin00]
• Tests are either deterministic or statistical
• One independent variable is changed and other
independent variables are set at a fixed level
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Verification, validation, and certification
[Calvez93]
•verification is establishing the truth of a hypothesis,
usually by experiment or observation (in science),
confirmation that a system satisfies the system
requirements, or a design step satisfies the
requirements of the higher hierarchy level in a
laboratory environment
•validation is verification that the system satisfies the
expectations in the field, i.e., verification of system
requirements that may be incomplete, or confirmation
that a design step satisfies the requirements at the
same hierarchy level
•certification is an external validation given by an
accredited authority
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Theories of Truth [Honderich05]
•Coherence: a statement is true if it is “coheres”(is
consistent) with other statements (for example
axiomatic system due to deduction)
•Correspondence: correspondence between a
theoretical model and reality (verification using
hypothetico-deductive method)
•Pragmatism: works out most effectively in practice
(important in engineering)
•Consensus: common opinion among researchers
(paradigms may be wrong, however)
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Novelty and Paradigm
Paradigm is an unquestioned theory or set of beliefs,
existing world-view (concept introduced by T. Kuhn
in 1962) [Honderich05].
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Creativity: Edge of Order and Chaos
Order
Chaos
Creativity
•You must have something on which to build (order,
systematic work) and something to move (chaos,
flexibility)
•Ways to improve creativity: analogies, symmetries,
relations, extremes, opposites
•Working habits: well defined problem, quiet time
(“lazyness”), new environment, mental barriers
avoided [Loehle90]
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Analogies Improve Creativity
LENGTH
FURNITURE (WEIGHT)
HEIGHT
REMOVAL VAN
TIME
BIT (ENERGY)
BANDWIDTH
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TIME SLOT
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Communications Improve Creativity
Other researchers
Encouragement, criticism
YOURSELF
Landmark
Advisor
Paper
Oral communications
Written communications
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Creativity: Order and Chaos
•Creativity is easily lost [Bohm87]
•fragmentation and specialization due to reductionism:
language difficulties due to special terminology (new terms
formed from abbreviations)
•paradigms (existing world-view is unquestioned)
•Creativity can be improved by [Bohm87]
•systems analysis
• understand what your colleague is doing as a part of a
larger system
•communications
• use analogies in communications, explain your system
model and terms (Feynman: explain it to your grandmother)
•analogies or metaphors
• a bridge between different concepts, for example Newton:
apple = moon, Einstein: time = space, energy = mass
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How to Improve Creativity
•Generation of ideas
•brainstorming (unrestrained offering of
ideas)
•systematic search for solutions
•ready-made question lists
•association, connection between ideas
•subconscious (“incubation”)
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Order: Sequential Process [Bohm92]
•Sequential process is characterized by a regular
sequence of events [Bohm87, Honderich05]
•In project design this kind of process is called
waterfall model where the project is divided into
rather independent phases [Calvez93, Leppälä03]
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Order: Iterative Process [Bohm92]
• Iterative or generative process is an overall process
from which the manifest form of things emerges
creatively, internal interrelations are included,
especially iterations
• In project design this kind of process is called spiral
model: the whole process is repeated and each time
the result improves [Calvez93], [Leppälä03]
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V Model (V Cycle) [Calvez93]
•in research use first (1) reduction (analysis): divide problem into
simple subproblems, divide systems into simple subsystems, use
hierarchy and modularity and then (2) bottom-up approach
(synthesis)
•in documents use top-down approach (analysis)
•in teaching use both bottom-up and top-down approaches
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EmpiricalEmpirical-Inductive Method of Discovery
• Problem is divided into subproblems (this is
called reduction)
• Model is derived by using experience (often
analogies used).
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Iterative research method
• You must work iteratively since the problem and hypotheses
are initially not very clear (a chicken and egg problem)
• In the beginning it is difficult to understand the literature
• Experience is gained by own experiments and discussions
• Reporting and publishing will improve the quality of research
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Reductionism and Holism
[Checkland99], [Honderich05]
•reductionism: theory that every complex
phenomenon can be explained by analyzing the
simplest, most basic physical mechanisms that are
in operation during the phenomenon (scientific
approach)
•holism: theory that whole entities have an
existence other than as the mere sum of their parts
(systems approach)
•emergence: occurrence of properties at higher
levels of organization which are not predictable
from properties found at lower levels [Nagel79],
for example transparency of water, temperature
of a gas
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Reductive approach
• Break the problem down and then generalize the results
(“break down and reassemble”)
• “Practical people often balk at this approach [reduction,
idealizations] since the idealized situations may be so far
removed from those of use as to appear highly academic.”
[Wilson90]
• We present the results explicitly by deduction (top down),
but we learn through induction (bottom up)
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Hypothetico-Deductive Method of Verification
• The scientific verification method is called hypotheticodeductive method [Honderich05]: the theoretical model
acts as a hypothesis, which is verified indirectly by
comparing the results given by the theoretical model with
the corresponding experimental results given by the reality.
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Elements of Discovery - Summary [Derry99]
•Patterns in data: periodic table of elements, drifting of
continents, biogeography of ecosystems
•Improved instruments: cryogenics and
superconductivity, microscope and microbes, radio
telescope and quasars
•Discrepancies: discovery of Argon, barometer, and
Neptune
•Hypothetico-deductive method: smallpox vaccine
•Consequencies of assumptions: energy band
structure in solids
•Serendipity (luck): X-rays, penicillin
•Imagination and dream: structure of benzene
•Intuition
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Different Hierarchies
Description Levels
Nested Hierarchy
Layered Pattern
(Successive Layers)
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Description Levels [Calvez93]
•functional model a structural (topological) model where a
structure is built using functions and relations between them
•behavioral model a model which describes the behavior of
internal functions of a system, specification of algorithms for the
functions
•executive model implementation model that specifies the
physical parts of the system, consisting of processors, memories,
and communication nodes
•An alternative description in three domains: structural domain,
behavioral domain and physical domain [Gajski88]
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Nested Hierarchy [Checkland99]
•Levels mentioned in [Gajski88] from bottom to top:
circuit, logic, microarchitectural, algorithmic, and
system level
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Layered Pattern [Tanenbaum96]
•Open Systems Interconnection (OSI) model inc. (from bottom to
top) physical layer, data link layer, network layer, transport layer,
session layer, presentation layer, and application layer
•Each layer produces a coherent set of services to the upper layers
through a public interface (lower layers seldom use upper layers
and these exceptions must be carefully documented)
•Advantages: support for standardization, dependencies are kept
local, exchangeability, maintainability, and portability
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Summary of Design Hierarchies
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Causality
•Backwards and downwards causality are in suspect in
natural science.
•Scientific theories are deterministic and deductive
(relativity theory) or probabilistic (quantum theory)
[Nagel79].
•Scientific theories describe (question how?) but do not
strictly speaking explain (question why?).
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What is Guiding Our Work
Systems
engineering
History &
roadmaps
Fundamental
limits
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System models,
relationships,
complexity analysis
Reviews of literature
Physical limits,
optimal systems,
performance analysis
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Fundamental Limits (about 1850-1950)
•second law of thermodynamics (Carnot, Clausius)
•absolute zero (Kelvin)
•upper velocity limit (Einstein)
•uncertainty principle (Heisenberg)
•incompleteness theorem (Goedel)
•speed of transmission of intelligence (Nyquist)
•channel coding theorem (Shannon)
Refs. [Lundheim02], scienceworld.wolfram.com
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Some Fundamental Engineering Problems
Sun
Information
Energy
Energy
Nature
Materials
Energy
Factory
Information
Products/
Services
Waste
Waste
People
People
•Problems: Distribution of information, energy,
materials, products, and services, transportation of
people, waste management, etc.
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Some Open Problems in Engineering
•General theory of systems (philosophy of
technology, hierarchy theory) [Checkland99]
•Semantic information theory (Shannon’
s statistical
information theory does not cover the meaning of
the information, only the amount of information)
[Checkland99]
•Network information theory (statistical information
theory covers only isolated links) [Cover91]
•Frame problem (how a machine could decide the
frame of reference or context) [Honderich05]
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Fundamental Problems in Information Engineering
Energy
Save/
Display
Information
Distribution
Storage
Processing
•Problems: Transfering, storing, processing and
displaying of information, storing of energy, etc.
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Why are Some Design Problems
Difficult to Solve? [Michalewicz04]
•no single performance metric that describes the quality of any
proposed solution is available, but a set of performance metrics that
should be weighted
•the number of solutions in the search space is so large as to forbid an
exhaustive search for the best answer and the iterative methods
(by trial and error) are too slow or unreliable to find the optimum
solution
•the possible solutions are so heavily constrained that constructing
even one feasible answer is difficult (reduction is used to simplify the
problem and this adds an additional constraint)
•the performance metric is noisy or varies with time (need an entire
series of solutions)
•our models may be too simplified so that any result is essentially
useless
•some psychological barrier prevents us from discovering a solution
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Technology: Natural Science and Engineering
Technosystem
Ecosystem
Human beings
Society
Organic nature
Humanities
Social science
Energy
Science
Materials/laws
Products/
services
Inorganic nature
Engineering
Waste
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Sciences, Practices, and Technology
[Wilson99], [Schwanitz99]
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Example: History of Telecommunications
[Haykin01], [Proakis01]
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Cultural History [Boyer91]
1636
USA
Mayas
Letters
Hieroclyphics
Egypt -1500
-3000
Greek alphabet
Latin letters (-500)
Etruscans 300 900
-800 -600
Phoenicians
Semites
Greece Rome
Macedonia
529
Rome
300
Babylon
Europe
Europe
1088
1100
Alexandria
415
Arabia
Sumerians
-3200
-2000
Cuneiform writing
-538
-500
1123
India
Numbers (500-876)
China
1200
1280
-1500
Japan
500
-3000
-2000
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1620
1632
1637
-1000
1
1877
1000
2000
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Legends (see previous page)
Start of ancient science (Thales)
Start of Greek writing
End of ancient science
(Academy closed)
-800 -600
Greece Rome
Influence
(writing)
529
Influence
(other)
Europe
Europe
1088
1620
First university
(Bologna) 1632
1637
1100
Start of modern science
(Bacon, Galilei, Descartes)
Indian-Arabian numbers
to Europe
Arabia
622
1123
Arabian calendar Omar Khayyam dies
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Roadmap and Vision of Telecommunications (1)
Ad hoc networks
WPAN
Digital broadcast
Mobile DVB
Multicast/unicast
Wireless Internet
Mobile universal
Mobile Internet
Satellite positioning
FWA
Supermacrocells
Mobile 3D voice
Megacells
Multi-sense interaction True virtual reality
Haptic interaction
3D telepresence
Mobile wide-screen
2000
2010
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2020
2030
2040
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Roadmap and Vision of Telecommunications (2)
Telesocializing?
Worm holes?
Telepathy?
ANSIBLE?
Quantum comms?
Direct MMI?
3000
Intergalactic network?
Teleportation?
Nanobots?
4000
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Time machines?
Holodeck?
5000
Real-time Internet?
6000
7000
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Comments to Roadmap and Vision [Clute95]
•direct man machine interface (MMI) refers to a direct wired interface to
human brains
•haptic interaction refers to the sense of touch, multi-sense interaction refers
to all the five senses
•holodeck refers to telepresence and virtual reality combined: all involved are
in a virtual environment
•nanobot is a small robot moving in human brains and controlled wirelessly,
it makes wireless direct MMI possible
•telepresence refers to presence in an existing environment for example as a
hologram; it does not need glasses, but it needs a material (for example
water vapor) to which the hologram is projected
•teleportation: the theoretical portation of matter through space by converting
it into energy and then reconverting it at the terminal point
•virtual reality: computer-generated simulation of three-dimensional images
of environment or sequence of events that someone using special equipment
(glasses, dress) may view and interact with a seemingly physical way
•worm hole: a hypothetical space-time tunnel or channel connecting a black
hole with another universe
•quantum communications
refers to teleportation of quantum88 states
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•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
Brief History of Electronics [Dummer97]
1729 Wire conductor and insulator, Gray
1745 Capacitor, von Kleist and von Muschenbrock
1785 Coulomb’
s law (inverse square law), Coulomb
1793 Optical telegraph, Chappe [Huurdeman03]
1800 Battery, Volta
1808 Atomic theory, Dalton
1820 Electromagnetism, Oersted
1820 Ampère’
s laws, Ampère
1826 Ohm’
s law, Ohm
1828 Fourier analysis, Fourier
1831 Electromagnetic induction, Faraday (Henry 1830)
1833 Computer (mechanical), Babbage
1837 Telegraphy, Morse
1837 Electric motor, Davenport
1843 Fax machine, Bain (commercial 1946)
1845 Kirchhoff’
s laws, Kirchhoff
1848 Boolean algebra, Boole
1865 Maxwell’
s equations, Maxwell
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Brief History of Electronics [Dummer97]
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
1876 Telephone, Bell
1883 Light bulb, Edison
1887 Aerial, Hertz
1889 Automatic telephone exchange, Strowger
1893 Waveguide, Thomson (experimental 1936)
1895 X-rays, Röntgen
1896 Wireless telegraphy, Marconi
1897 Electron, Thomson
1897 Oscilloscope, Braun
1898 Magnetic recording, Poulsen
1900 Quantum theory, Planck
1904 Vacuum tube, Fleming (diode), de Forest (triode, 1906)
1905 Theory of relativity, Einstein
1906 Radio broadcasting, Fessenden (commercial 1919)
1911 Atomic theory, Rutherford
1911 Superconductivity, Onnes
1912 Superheterodyne radio receiver, Fessenden and Armstrong
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Brief History of Electronics [Dummer97]
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
1919 Television (electronic), Zworygin (commercial broadcasting 1939)
1921 Radio dispatch service for police cars, USA [Sklar01, p. 776]
1924 Radar, Appleton et al.
1925 Thermal noise, Thomson
1927 Negative feedback amplifier, Black
1927 Cable television, Bell Telephone Co (real growth in the 1960’
s)
1928 Sampling theory, Nyquist
1928 Diversity reception, Beverage et al.
1929 Color television, Bell Laboratories
1929 Microwave communications, Clavier
1929 Coaxial cable, Affel and Espensched
1931 Stereophonic sound reproduction, Blumlein and Bell Labs
1933 Frequency modulation (FM), Armstrong
1934 Liquid crystal display (LCD), Dreyer
1937 Pulse-code modulation (PCM), Reeves
1937 Xerox photocopy method, Carlson (success in the 1960s)
1940 Cybernetics, Wiener
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Brief History of Electronics [Dummer97]
• 1940s Mobile cellular system (concept), Bell Labs
• 1943 Computer (ENIAC, Electronic Numerator, Integrator and
Computer), University of Pennsylvania
• 1943 Traveling wave tube (TWT), Kompfner et al.
• 1943 Printed wiring, Eisler
• 1945 Computer theory, von Neumann
• 1946 Stored program, Turing
• 1946 Public mobile telephone service, USA
• 1947 Chirp radar, Bell Labs
• 1948 Transistor (bipolar), Bardeen, Brattain, and Shockley
• 1948 Information theory, Shannon
• 1948 Holography, Gabor
• 1950 Phase-locked loop
• 1950 Floppy disc, Nakamats
• 1950s Voice-band modem (modulator and demodulator), MIT and Bell
Labs
• 1950s Global Positioning System (GPS), Getting (operational 1993)
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Brief History of Electronics [Dummer97]
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
1957 Fortran (Formula Translator) computer language
1958 Video tape recorder (also color), Ampex
1958 Laser, Schalow and Townes
1958 Stored program switch, Bell Labs (commercial 1960)
1959 Integrated circuit, Kilby (concept 1952)
1960 Light emitting diode (LED), Allen and Gibbons
1960 Computer-aided design (CAD), military, USA
1960 Linear integrated circuit (operational amplifier), USA
1960 Telephone electronic switching system, Bell Labs
1961 Mini tape cassette, Philips
1961 Minicomputer, Digital Equipment Inc.
1961 Packet switching, Kleinrock [Huurdeman03]
1962 Satellite communication, Telstar I, USA
1963 Electronic calculator, Bell Punch Co
1963 Transistor-transistor logic (TTL), Sylvania
1963 Teletext
1963 Hypertext (concept), Nelson [Huurdeman03]
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Brief History of Electronics [Dummer97]
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
1964 Wordprocessor, IBM
1965 Electronic typewriter, IBM
1965 Mouse, Englebart
1965 Virtual reality, military, USA
1966 Optical fibres, Kao and Hockham
1968 Complementary metal-oxide-semiconductor (CMOS) logic, USA
1968 High definition television (HDTV), Nippon Broadcasting
Corporation
1969 Internet, Arpanet (Advanced Research Project Agency Network,
renamed Internet in 1985)
1969 Semiconductor memory system, Agusta, Moore, and Tu
1970 Unix operating system, Bell Labs and University of California at
Berkeley
1970 Large scale integration (LSI)
1971 Autoradiopuhelin (ARP), Finland
1971 Microprocessor, Hoff
1972 Microcomputer, Intel
1972 Video games, Magnavox
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Brief History of Electronics [Dummer97]
• 1972 Electronic mail (e-mail), Arpanet, USA
• 1973 Hard disc
• 1973 Transmission control protocol (TCP), Cerf and Kahn
[Huurdeman03)
• 1974 Barcode, USA
• 1975 Video Home System (VHS) recorder, Japan Victor Company (JVC)
• 1975 Laser printer, IBM
• 1977 Open Systems Interconnection (OSI) reference model,
International Standards Organization (ISO)
• 1979 Compact disc (CD), Philips
• 1979 Digital signal processor (DSP)
• 1979 Mobile cellular system (Mobile Control Station, MCS), Japan
• 1980 Very large scale integration (VLSI)
• 1981 Mobile cellular system (Nordic Mobile Telephone, NMT), Europe
• 1981 Microsoft Disc Operating System (MS-DOS), Gates
• 1981 Personal computer (PC), IBM
• 1985 Hard disc card, Plus Development Corp.
• 1985 Digital video recorder, Sony
• 1985 Compact disc read only memory (CD-ROM), Philips
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Brief History of Electronics [Dummer97]
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
1984 Graphical user interface (GUI), Apple
1985 Windows, Microsoft
1987 Digital audio broadcasting (DAB), Europe (operational 1995)
1988 Internet available outside the USA, inc. Finland
1989 Application-specific integrated circuit (ASIC)
1989 C language standard (C++ 1996), ANSI
1989 Hypertext markup language (HTML), Berners-Lee [Huurdeman03]
1990 World Wide Web (WWW), Berners-Lee (commercial 1994)
1991 Hypertext transfer protocol (HTTP) and uniform resource locator
(URL), Berners-Lee and Caillau [Huurdeman03]
1991 Global System for Mobile Communication (GSM), international
[Huurdeman03)
1992 Internet browser, Mosaic (Netscape in 1994, Explorer in 1995)
1995 Digital versatile disc (DVD), international
1995 Short message service (SMS), GSM [Huurdeman03]
1996 Java language
1997 Digital video broadcasting - terrestrial (DVB-T), international
(operational 1998)
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Brief History of Electronics [Dummer97]
• 1997 Wireless local area networks (WLAN) (IEEE 802.11 standard),
IEEE
• 1999 Wireless access protocol (WAP), international [Huurdeman03]
• 2000 Voice over Internet Protocol (VoIP) (standard), ITU and IETF
[Huurdeman03]
• 2001 Universal Mobile Telecommunications System (UMTS),
international [Huurdeman03]
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Brief History of Scientific Method [Losee01]
• Aristotle (300s BC), first philosopher of science and systematic
classifier, developer of inductive-deductive method, Aristotelian world
view, four aspects of causation including material cause (what?),
formal (structural) cause, efficient cause (how?) and final (teleological)
cause (why?)
• F. Bacon (1620), founder of modern philosophy of science, inductiveexperimental method, accepted only material and efficient causes,
divorce between science and theology
• R. Descartes (1637), founder of modern philosophy, rationalism,
ontological reductionism (atomism), deductive hierarchy of
propositions, hypotheses based on analogies
• G. Galilei (1638), start of empirism, idealizations in analysis,
demonstration of inadequacy of Aristotle’
s physics, breakthrough of
Copernician world view
• I. Newton (1687), method of analysis and synthesis (hypotheticodeductive method), reduction of laws of terrestrial (by Galileo) and
planetary (by Kepler) motion to Newtonian mechanics, distinction
between axiomatic system (abstract) and its empirical application
(concrete)
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Recent Progress
• discussion on theories of scientific progress
continued [Losee01]
• from prescriptive to descriptive philosophy of
science
• evolutionary analogy in the progress of
science (naturalism)
• realist-antirealist controversy
• breakthrough of numerical methods
• failure of analytical method for example in
system theory
• interest in computability theory
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Conclusions (1)
Idea
Literature review
Problem and
hypotheses
Experiments/
analysis
System
(prototype)
Theory/paper
(new knowledge)
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Conclusions (2)
Answer
(hypothesis)
Experience
(analogies)
Criticism
(testing)
Question
(problem)
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Conclusions (3)
•use bottom-up (inductive) approach in research,
which is essentially a learning process
•use top-down (deductive) approach in technical
documents (reviews, monographs), this will make
the presentation compact and easy to follow for
experts (use IMRAD structure)
•use bottom-up approach in teaching (tutorials,
textbooks), and integrate results by using the topdown approach
•remember that a doctoral thesis is not a textbook
(writing a textbook is a large challenge), write the
thesis for experts in the field
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Conclusions (4): Iterative research method
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Conclusions (5): Theory and practice
• A good research project emphasizes theoretical
results (usually system models) and uses
prototypes for verification and validation of the
new results
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Final conclusions
Idea
Literature review
Problem and
hypotheses
Experiments/
analysis
System
(prototype)
Theory/paper
(new knowledge)
General hints
• use bibliographies to improve your efficiency
in literature reviews (start from books and
reviews, see the introduction of original papers)
• learn the terminology, write a classification
(taxonomy) for the state of the art, and see
historical trends
• define a problem and hypotheses (use bottomup empirical-inductive approach, make
experiments early in your project)
• start to outline the paper right from the
beginning (there will never be “
more time”
),
emphasize good organization, use top-down
deductive approach in documents
• reserve time for all phases in your project plan
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Researcher’s Checklist (1)
•Funding, project plan, time schedule, needed competence,
related areas, analogies, measurable milestones after some
months, rough results for each year
•Motivation, also long-term motivation, applications
•Problem and rough competing hypotheses, which are refined
iteratively, fundamental problems preferred
•Performance metrics for both performance and complexity
•Reference results (trivial cases, complete data with optimal
processing, earlier solutions, benchmarks), confidence intervals
for statistical results
•Literature review, landmark books and papers, hierarchical
classification of ideas, keywords, databases, good authors
•System model, a priori knowledge, block diagram to show division
into parts and relationships, idealizations, linear or nonlinear
model, parameters, hierarchy and modularity
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Researcher’s Checklist (2)
•Bottom up approach, from simple towards more complicated,
reduce the problem into simple idealized and separate
subproblems, make experiments (empirical-inductive approach
preferred), remove nonidealities (distortions, interference) step by
step, present results top down (hypothetico-deductive approach)
•Discussion via brief technical reports, which are revised, good
organization, good grammar, concise and accurate text, clearly
defined terms
•Publications, novelty, significance, correctness, readability, 1-2
good conference papers per year, 1-2 journal papers after three
years
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Final Word: Focus
“General Groves -- asks
Oppenheimer [the leader of
the Manhattan project that
developed the atomic
bomb] -- what it will take
to get the Gadget [atomic
bomb] built. “Focus,”
Oppie answers, naming a
critical element at every
Great Group.”[Bennis98]
Source of the figure: Associated Press
(http://www.infoplease.com/spot/m
m-beamon.html)
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References (1)
• [amc03] “Terminology –the key to understanding analytical science. Part
1: Accuracy, precision and uncertainty,”AMC Technical Brief, September
2003 (www.rsc.org/pdf/amc/brief13.pdf).
• W. Bennis and P. W. Biederman, Organizing Genius: The Secrets of
Creative Collaboration. Addison Wesley, 1998.
• P. Bock, Getting It Right: R&D Methods for Science and Engineering.
Academic Press, 2001.
• D. Bohm and F. D. Beat, Science, Order and Creativity. Bantam Books,
1987.
• C. B. Boyer, A History of Mathematics. Wiley, 2nd revision edition, 1991.
• J. Clute and P. Nicholls (Eds.), The Encyclopedia of Science Fiction, reprint
ed. St. Martin’
s Press, 1995.
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VTT TECHNICAL RESEARCH CENTRE OF FINLAND
References (2)
• M. Davis, Scientific Papers and Presentations. Academic Press, 1997.
• R. A. Day, How to Write and Publish a Scientific Paper, 5th ed. Oxyx Press,
1998.
• J. P. Calvez, Embedded Real-Time Systems: A Specification and Design
Methodology. John Wiley & Sons, 1993.
• P. Checkland, Systems Thinking, Systems Practice: A 30-Year Retrospective.
Wiley, 1999.
• T. M. Cover and J. A. Thomas, Elements of Information Theory. Wiley,
1991.
• D. Deutsch, Fabric of Reality. Penguin, 1998.
• R. M. Felder and L. K. Silverman, “Learning and teaching styles in
engineering education,”Engineering Education, pp. 674-681, April 1988.
• R. P. Feynman, The Meaning of It All. Perseus Publishing, 1998.
• R. P. Feynman, The Pleasure of Finding Thíngs Out. Perseus Publishing,
1999.
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VTT TECHNICAL RESEARCH CENTRE OF FINLAND
References (3)
•D. D. Gajski, Silicon Compilation. Addison-Wesley, 1988.
•R. W. Hamming, “You and your research,”IEEE Potentials, pp. 3740, October 1993.
•S. Haykin, Communication Systems. 4th ed. Wiley, 2001.
•D. Hicks, “Six reasons to do long-term research,”Research and
Technology Management, pp. 8-11, July-August 1999.
•Honderich (Ed.), The Oxford Companion to Philosophy, 2nd ed. Oxford
Univ Press, 2005.
•J. Hudson, The History of Chemistry. Chapman and Hall, 1992.
•A. Huurdeman, The Worldwide History of Telecommunications. Wiley,
2003.
•ISO Guide 99:2004 International vocabulary of basic and general
terms in metrology (VIM) (draft in revision)
(www.ntmdt.ru/download/vim.pdf).
•R. K. Jain and H. C. Triandis, Management of Research and
Development Organizations: Managing the Unmanageable. John Wiley
& Sons, 1997.
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References (4)
•R. N. Kostoff, “Science and Technology Roadmaps,”IEEE
Transactions on Engineering Management, vol. 48, pp. 132-143, May
2001.
•H. Kragh, Quantum Generations: A History of Physics in the Twentieth
Century, reprint ed. Princeton University Press, 2002.
•E. Kreyszig, Advanced Engineering Mathematics, 5th ed. John Wiley
& Sons, 1983.
•K. Leppälä et al., Professional Virtual Design of Smart Products. IT
Press, 2003.
•C. Loehle, “A guide to increased creativity in research - inspiration or
perspiration?”BioScience, vol. 40, pp. 123-129, February 1990,
limnology.wisc.edu/courses/zoo955/publications/Wk04_Research/L
oehle_1990_Guide_to_Creativity.pdf.
•J. Losee, A Historical Introduction to the Philosophy of Science, 4th ed.
Oxford Univ Press, 2001.
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References (5)
•Lars Lundheim, “On Shannon and ‘
Shannon’
s Formula’
,”
Telektronikk, vol. 98, no. 1-2002, pp. 20-29, www.tuilmenau.de/site/mt/uploads/media/
shannonLarsTelektronikk02.pdf.
•Z. Michalewicz and D. B. Fogel, How to Solve It: Modern Heuristics,
2nd ed. Springer, 2004.
•E. Nagel, Structure of Science: Problems in the Logic of Scientific
Explanation. Hackett Pub Co, 1979.
•I. Niiniluoto, Johdatus tieteenteoriaan: Käsitteen- ja
teorianmuodostus, 3rd ed. Otava, 2002.
•I. Niiniluoto, Tieteellinen päättely ja selittäminen. Otava, 1983.
•M. Polanyi, “The republic of science: Its political and economic
theory,”Minerva, vol. 1, pp. 54-74, 1962,
www.compilerpress.atfreeweb.com/Anno%20Polanyi%20Republic20
%of%20Science%201962.htm.
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References (6)
•J. G. Proakis, Digital Communications. 4th ed. McGraw-Hill, 2001.
•A. Rosenberg, Philosophy of Science: A Contemporary Introduction.
Routlegde, 2000.
•Random House Webster’s Concise College Dictionary. New York:
Random House, 1999.
•D. Schwanitz, Bildung: Alles was man wissen muss. Frankfurt,
Germany: Eichborn, 1999.
•B. Sklar, Digital Communications: Fundamentals and Applications,
2nd ed. Prentice Hall, 2001.
•P. Strathern, Mendeleyev‘s Dream: The Quest for the Elements.
Thomas Dunne Books, 2001.
•A. S. Tanenbaum, Computer Networks, 3rd ed. Prentice Hall, 1996.
•K. Ulrich and S. Eppinger, Product Design and Development.
McGraw-Hill, 1995.
•Webster’s Third New International Dictionary of the English Language,
Unabridged (a Merriam-Webster). Cologne, Germany: Könemann,
1993.
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References (7)
•E. B. Wilson, An Introduction to Scientific Research, rev. ed. Dover
Publications, 1990.
•E. O. Wilson, Consilience: The Unity of Knowledge. Random House,
1999.
•C. Wohlin et al., Experimentation in Software Engineering: An
Introduction, Springer, 1999.
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Recommended Reading (1)
Writing instructions
• R. A. Day and B. Gastel, How to Write and Publish a Scientific Paper, 6th ed.
Oryx Press, 2006, 320 pp. (Explains the IMRAD structure of a paper.)
• T. N. Huckin and L. A. Olsen, Technical Writing and Professional Communication
for Nonnative Speakers, 2nd ed. McGraw-Hill, 1991 (1983), xxii + 746 pp. (In
addition to writing instructions, this book covers the grammar of the English
language.)
• N. J. Higham, Handbook of Writing for the Mathematical Sciences, 2nd ed.
Society for Industrial and Applied Mathematics, 1998 (1993), xvi + 302 pp. (This
book is recommended for mathematical writing.)
Dictionaries
• Merriam-Webster’
s Collegiate Dictionary, 11th ed. Merriam-Webster, 2003
(1898), 1664 pp. (ISBN 0877798095). (Recommended by most publishers.
Available also at www.m-w.com where you can also listen to the pronunciation.
The dictionary first presents etymology and uses historical order of definitions.)
• Random House Webster’
s College Dictionary. 2nd ed. Random House, 2001
(1947, 1991), 1600 pp. (The definitions start from the most common or current
meanings first.)
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Recommended Reading (2)
Research methods and philosophy of science
• P. Bock, Getting It Right: R&D Methods for Science and Engineering. Academic
Press, 2001, xvii + 406 pp. (The author is a professor in engineering and he has
given a similar course on research methodology for several years.)
• A. Rosenberg, The Philosophy of Science: A Contemporary Introduction, 2nd ed.
Routledge, 2005 (2000), 204 pp. (This is a general textbook about philosophy of
science in English, although quite brief and written for undergraduate students.)
Systems engineering
• L. Skyttner, General Systems Theory: Perspectives, Problems, Practice, 2nd ed.
World Scientific Publishing Company, 2006 (2001), 536 pp. (This book covers
many general system theories as information theory, which makes the book very
suitable for students working for example in signal processing.)
• P. Checkland, Systems Thinking, Systems Practice: Includes a 30-year
Retrospective, new ed. Wiley, 1998 (1981), 66 + xiv + 330 pp. (This book
includes an extensive history of systems-based methodology starting from the
ancient Greek science.)
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Recommended Reading (3)
History of science and technology
• J. E. McClellan III and H. Dorn, Science and Technology in World History: An
Introduction, 2nd ed. John Hopkins Univ Press, 2006 (1999), 496 pp. (The book
covers the history of the last 12,000 years since the beginning of agriculture.)
• W. A. Atherton, From Compass to Computer: A History of Electrical and
Electronics Engineering. San Francisco Press, 1984, 337 pp.
• J. Gribbin, The Scientists: A History of Science Told through the Lives of Its
Greatest Inventors. Random House, 2003, 672 pp. (This is a book about general
history of science, but covers only the times since Copernicus from 1543 when he
published his work.)
• D. C. Lindberg, The Beginnings of Western Science: The European Scientific
Tradition in Philosophical, Religious, and Institutional Context, 600 B.C. to A.D.
1450. University of Chicago Press, 1992, 474 pp. (The early history of science is
covered.)
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