FACULTY OF COMPUTER SCIENCE AND INFORMATION TECHNOLOGY

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Oct 29, 2013 (3 years and 7 months ago)

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FACULTY OF COMPUTER SCIENCE AND INFORMATION TECHNOLOGY

LIST OF COURSES FOR EXCHANGE STUDENTS

ACADEMIC YEAR 2013/2014




Course title

ALGORITHMIC TRICKS IN DIGITAL SIGNAL & IMAGE PROCESSING

Teaching method

Lectures and cl ass exercises

Person respo
nsible for
the course

Prof. Al eksandr Cariow

E
-
mail address to the person
responsible for the course

atariov@wi.zut.edu.pl

Course code

(if applicable)


ECTS points

4

Type of course

el ective

Level of course

Fi rst cycl e (S1)

Semester

wi nter/summer

Langu
age of instruction

Engl ish

Hours per week

Lecture: 1

h

cl ass exercises: 1 h

Hours per semester

Lectures: 15 h

cl ass exercises: 15

h

Objectives of the course

At the end of the course, the student shoul d be abl e to:

Understand algorithms for digital convol
ution, discrete Fouri er, Wavel et and other orthogonal
transformations;

u
nderstand and development fast algorithms for processi ng of l arge data sets
such as signals and images. Find effective algorithmic solutions to mi ni mi ze the computati onal
compl exity i n

solving various DSP probl ems. Provi de a thorough understandi ng and worki ng
knowledge of design, analysis and compari son of computati on compl exi ty of DSP al gori thms.

Entry requirements

General entry requi rements, fi rst cycl e

Course contents

Overvi ew of b
asic methods and problems of digital signal processi ng. Presentati on of the basi c
operations of digital signal and image processing in the form of matri x
-
matri x and vector
-
matri x
products. Defining a core set of reference structures of matrices, which faci
litates the cal cul ati on
of vector
-
matrix products. Demonstration of new tricks and receptions to reducing the number of
ari thmetic operations in calculating the vector
-
matrix products. Examples of synthesi s al ternate
al gorithms for vector
-
matrix transforma
tions with a reduced number of ari thmeti c operati ons.
Synthesis of fast algorithms for solvi ng the basic DSP and image processi ng probl ems (ci rcl e and
l i near convolution, FDWT/IDWT, DCT, DFT, Hartley, Haar, Wal sh
-
Hadamard, Sl ant, Lapped and
other discrete
transforms). The DSP chip structures evaluation for the i mplementati on of vari ous
DSP tasks.

Assessment methods

Gradi ng pol i cy: Homework’s (2 credi ts), project (2 credi ts) and fi nal repot

Recommended readings

[1].

Richard E. Blahut
, Fast Algorithms for Digita
l Signal Processing
,

Addi son
-
Wesl ey Publ i sher,

1985, ISBN
-
10: 0201101556


[2].

L.R. Rabiner, B. Gold,
Theory and Application of Digital Signal Processing
, Prenti ce Hal l, 1975,
ISBN 013914101
-
4.

[3].

J.G. Proakis and D.G. Manolakis,
Digital Signal Processing: Princi
ples, Algorithms, and


2

Applications
, Prenti ce Hal l, 3rd Edi ti on, 1996, ISBN 013373762
-

4.

[4].

A.V. Oppenhei m and R.W. Schafer,
Digital Signal Processing
, Prenti ce Hal l, 1975, ISBN
013214635
-
5.

[5].

M.H. Hayes,
Digital Signal Processing
, Schaum’s Outline Series, McGr
aw Hi l l, 1999, ISBN 0
-
07
-
027389
-
8.

[6].

A.
Ţari ov (A. Cari ow),

Algorithmic Aspects of Computing Rationalization in Digital Signal
Processing,
West Pomeranian University of Technology press., 2011, ISBN 978
-
83
-
7663
-
098
-
4
(i n Pol i sh).

Additional information

none




Course title

COMPUTER AND TELECOM
MUNICATION NETWORKS

Teaching method

l ecture and l aboratory

Person responsible for
the course

Ph.D. Eng. Remigiusz Ol ejnik

E
-
mail address to the person
responsible for the course

rol ejnik@wi.zut.edu.pl

Course code

(if applicable)


ECTS points

4

Type of course

compulsory

Level of course

S1

Semester

wi nter or summer

Language of instruction

Engl ish

Hours per week

2 (l ecture) + 2 (l aboratory)

Hours per semester

60

Objectives o
f the course

Knowl edge of reference model s, network standards, protocol s of data l i nk l ayer, network,
transport and application layers. Knowledge of current wired and wi rel ess network sol uti ons.
Abi l ity of network’s performance evaluation. Ability of si mpl
e UomeIoffi ce ne瑷ork bui l Ti ng⸠
ŁaVic algori瑨mV of Ta瑡 linkⰠn整eork anT applica瑩on l aX敲 i mpl敭敮瑡瑩on abili瑹⸠MiagnoVing of
workstati on’s network probl ems abi l i ty.

Entry requirements

Basics of programming; Architecture of computer systems; Operati n
g systems fundamental s

Course contents

Introduction to computer networks. Physical layer, transmission media, multiplexing techniques,
ci rcui t and packet switching. Data l i nk l ayer, error detecti on, fl ow control, ALOHA and CSMA
protocols, protocols withou
t collisions, Ethernet, wireless local area networks, i nterconnecti ng.
Network l ayer, routing algorithms and protocols, quality of service, Internet Protocol. Transport
l ayer, protocol s, addressi ng, fl ow control,

UDP, TCP and RTP protocols, Nagle’s and Cl a
rke’s al gori thms. Appl i cati on l ayer, DNS, e
-
mai l Ⱐ
PPPⰠmul 瑩meTi a appl i ca瑩onV of 瑨e ne瑷orkV.

Assessment methods

Wri tten exam (l ecture); wri tten reports (l aboratory).

Recommended readings

1. A. S. Tanenbaum, D. J. Wetheral l “Computer Networks” (5
th

edi
ti on), Pears on Educati on,
Bos ton 2011

2. M. Has s an, R. Jai n, “Hi gh Performance TCP/I P Networki ng”, Prenti ce Hal l, 2003

Additional information










3


Course title

COMPUTER NETWORK DESIGN FUNDAMENTALS

Teaching method

l ecture, l aboratory and project

P
erson responsible for
the course

Ph.D. Eng. Remigiusz Ol ejnik

E
-
mail address to the person
responsible for the course

rol ejnik@wi.zut.edu.pl

Course code

(if applicable)


ECTS po
ints

4

Type of course

el ective

Level of course

S1

Semester

wi nter/summer

Language of instruction

Engl ish

Hours per week

1 (l ecture) + 1 (l aboratory) + 1
(project)

Hours per semester

45

Objectives of the course

Knowl edge of algorithms and methods for d
esigning wired and wireless networks. Knowledge of
network simulators and the ability to assess the performance of i ndi vi dual network sol uti ons.
Abi l i ty to desi gn smal l networks usi ng computer
-
ai ded desi gn tool s.

Entry requirements

Good knowl edge of compu
ter and tel ecommuni cati on networks pri nci pl es.

Course contents

Lecture:

The process of computer network design. Al gori thms for desi gni ng LAN and WAN. Desi gn of
wi reless networks. Methods for evaluating the performance of computer networks. Optimization
of

network projects. Methods and tool s for computer
-
ai ded des i gn. Parametri c des i gn of
computer networks. Structured cabl i ng s ys tems.

Laboratory
:

I ntroduction to OPNET I T Guru environment. Performance eval uati on: LAN connecti on to the
I nternet, mul ti
-
LAN, ap
pl i cati ons over the WAN. The i mpact s tudy: Frame Rel ay network
parameters on the performance of the WAN environment, the TCP wi ndow s i ze on appl i cati on
performance. Us e a fi rewal l to manage network traffi c. Performance tes ti ng of databas e
applicati ons i n a

networked envi ronment. Performance compari s on of di fferent network
technol ogi es (wi red and wi rel es s ).

Project:

I ntroducti on to computer
-
ai ded des i gn of computer networks: tool s and al gori thms.
I mpl ementation of a specialized computer program implementing
the algorithm for des i gni ng a
LAN or WAN. I mplementation of network design for a particular application with simulati on and
analysis of performance in OPNET I T Guru envi ronment. Discussion of programs and projects.

Assessment methods

Lecture
-

wri tten e
xam. Laboratory
-

credit on the basis of partial evaluations performed duri ng
the s emes ter. Project
-

eval uati on of s ubmi tted network des i gn.

Recommended readings

1. T. G. Robertazzi “Pl anni ng Tel ecommuni cati on Networks ”, I EEE Pres s, Pi s cataway 1999

2⸠M.

Hassan, R. Jain “High Performance TCP/I P Networking”, Prenti ce Hal l, Upper Sadl e Ri ver
㈰〳

3. A. Kershenbaum “Telecommunications Network Design Algorithms”, McGraw
-
Hi l l ⰠNew York
ㄹ㤳

4. A. S. Tanenbaum, D. J. Wetheral l “Computer Networks” (5
th

edi ti on),

Pears on Educati on,
Bos ton 2011

5. G. Hi gginbottom “Performance Eval uati on of Communi cati on Networks ”, Artech Hous e,
NorwooT 1998

Additional information








4


Course title

LaTeX


DOCUMENT PREPARATION SYSTEM FOR ENGINEERS

Teaching method

l ecture and l a
boratory

Person responsible for
the course

Ph.D. Eng. Remigiusz Ol ejnik

E
-
mail address to the person
responsible for the course

rol ejnik@wi.zut.edu.pl

Course code

(if applicabl
e)


ECTS points

2

Type of course

opti onal

Level of course

S1

Semester

wi nter/summer

Language of instruction

Engl ish

Hours per week

1 (l ecture) + 1 (l aboratory)

Hours per semester

30

Objectives of the course

Practi cal ski l l s i n typesetti ng of engi neeri
ng documents usi ng LaTeX

system.

Entry requirements


Course contents

Lecture:

Description of the installation and initialization of the package, setting of environment variabl es,
hyphenation file. LaTeX i nput file and the principles of i ts building, perm
anent el ements of the
fi l e. Structure of the document: the divi si on of the document i nto parts, chapters, secti ons,
paragraphs, etc., title page, the main file and i ncluded files, creating of a table of contents, tabl e
of fi gures and tables, attaching a bi
bliography, creating an index, references to the label s, usage
of the counters. Defining own classes of documents: bui l di ng of the styl e defi ni ti on fi l e and
possibilities of changing i ts content. Defining of running heads for page headi ngs and footers,
def
i ning of parameters for l ists, floating objects, defining of headers for chapter and subsections,
changing of the format of the table of contents and bibliography. Predefined cl asses of document
and format, format definition file declared in the preamble (
page si ze, the type of numberi ng,
margi ns, running head, footer). Defining the type and size of fonts, speci al characters, accents,
Pol i sh diacritic characters. Length measures, horizontal and vertical spacing, references, breaking

l i nes and pages. Definin
g of indivisible elements. Mul ti pl e col umns usage. Greek and Cyri l l i c
al phabet. Mathematical texts: mathematical environment, using mathematical expressi ons and
symbols (indices, fractions, roots, equations and thei r systems, matri ces, compl ex formul as),
s
pacing and bold i n math mode. Special text structures: defi ni ng mi ni pages, l i sts and tabl es,
creati ng pictures and including them i nto document, language of geometri c fi gures defi ni ti on.
Changes to the definitions, creating of own definitions and defining
a new environment. Creating
new variable objects. Correction of the errors: error messages and warni ngs i n LaTeX and TeX,
error correcti on capabi l i ti es.

Laboratory:

Preparing of documents of i ncreasing complexity; changing of the font type and size, defi ni
ng of
the text l ayout, tables, complex mathematical formulas and mathemati cal texts; creati ng and
i nserting pictures; analysis of style files and preparation own styles for journal s, books, reports
and thesis; merging results of all exercises in a single d
ocument wi th the form of a book, wi th
tabl e of contents, bi bl i ography, appendi ces and i ndex.

Assessment methods

Lecture
-

oral exam. Laboratory work
-

evaluation of submitted document that has been prepared
duri ng the course.

Recommended readings

1. L. L
amport “LaTeX: A Document Preparati on System”, Addi son
-
PeVl eXⰠŁoV瑯n 1994

2⸠F⸠Mi 瑴el bacU
et al
. “The LaTeX Companion (Tools and Techniques for Computer Typesetti ng)”,
ATTi Von
-
PeVl eXⰠŁoV瑯n 2004

Additional information






5


Course title

DIGITAL WATERMAR
KING

Teaching method

Lectures and project

Person responsible for
the course

Ph.D. Eng. Mi rosław Łazoryszczak

E
-
mail address to the person
responsible for the course

ml azoryszczak@wi.zut.edu.pl


Course
code

(if applicable)


ECTS points

2

Type of course

opti onal

Level of course

S1

Semester

s ummer

Language of instruction

Engl ish

Hours per week

Lecture: 1 h, Project: 1 h

Hours per semester

Lectures: 15 h, Project: 15

h

Objectives of the course

One of
the challenges of the digital world is I ntellectual Property protecting. This cours e i ntroduces
s ome techniques of the Digital Rights Managements i n the form of Digital Watermarking i n graphi cs
and audi o domai ns.

Entry requirements

Bas ic programming skill
s (C/C++), i ntroduction to digital signal processing, basic knowledge of Matlab

Course contents

Nature of sound and l imitations of the Human Audio System, i mages and l imi tati ons of the Human
Vi s ual System, classification of Digital Watermarks, basic techn
iques of data hiding and retri evi ng i n
graphic container, l east s igni fi cant bi t codi ng, echo hi di ng, s pread s pectrum codi ng, advanced
methods of digital watermarking in audio environment, watermark s ecuri ty and i mmuni ty to the
mos t popul ar technol ogi cal tr
ans formati ons and i ntended attacks

Assessment methods

Grade and project work

Recommended readings

1.

Arnold M., Schmucker M., Wolthusen S. D.:
Techniques and Applications of Digital
Watermarking and Content Protection
, Artech House, 2003.

2.

Cox I. J., Miller
M. L., Bloom J. A.:
Digital Watermarking
, The Morgan Kaufmann Seri es i n
Mul ti medi a Informati on and Systems, Morgan Kaufman Publ i shers, San Franci sco 2002.

3.

Gruhl D., Bender W., Lu A.:
Echo Hiding
, i n Information Hiding: Fi rst International Workshop, Vol.
11
74 of Lecture Notes i n Computer Sci ence, Cambri dge, U.K., Spri nger
-
Verl ag, 1996.

4.

Katzenbeisser S., Petitcolas F. A. P. (eds.): Information Hiding Techniques for Steganography and
Digital Watermarking, Artech House, Norwood MA, 2000.

Additional information





Course title

AUDIO SIGNAL PROCESSING

Teaching method

Lectures and l aboratories

Person responsible for
the course

Ph.
D. Eng. Mi rosław Łazoryszczak

E
-
mail address to the person
responsible for the course

ml azoryszczak@wi.zut.edu.pl


Course code

(if applicable)


ECTS points

2



6

Type of course

opti onal

Level of course

S1

Semester

s ummer

Language of instruction

Engl ish

Hours per week

Lecture: 1 h, Laboratory: 1 h

Hours per semester

Lectures: 15 h, Laboratories:
15

h

Objectives of the course

An analysis of sound i s important area of interest i n multimedi a processi ng. Nowa
days audi o i s
al most digital, however i nput and output of audio systems still remai n anal og. Therefore, i n thi s
course selected topics of audio acquisi ti on and si gnal processi ng techni ques are consi dered.

Entry requirements

i ntroducti on to di gi tal si gnal
processi ng, basi c knowl edge of Matl ab

Course contents

basics of sound, audio perception, acoustical signal acquisi ti on, transducers


mi crophones and
speakers, recording studios: acoustics and equipment, audi o si gnal representati ons and sound
analysis, di
gital filters, sound effects, sound modeling and synthesis, selected applications of audi o
processi ng: noi se reducti on, automati c recogni ti on of musi c,

Assessment methods

grade, l ab work

Recommended readings

1.

Rochesso D.: Introducti on to Sound Processi ng,

2003,
http://profs.sci.univr.i t/~rocchess/htmls/corsi/SoundProcessing/SoundProcessi ngBook/sp.pdf

2.

Smi th S. W.: Di gi tal Si gnal Processi ng. A Practi cal Gui de for Engi neers and Sci enti sts,
http://www.dspgui de.com/pdfbook.htm

3.

Eargl e J.: The Mi crophone Book, El
sevi er, Focal Press, 2005

4.

Everest F. A.: Master Handbook of Acousti cs, 2001

5.

Kostek B.: Soft Computi ng i n Acousti cs, Spri nger
-
Verl ag, 1999.

Additional information





Course title

COMPU
TER SYSTEM ARCHITECTURE

Teaching method

Lectures and l aboratories

P
erson responsible for
the course

Ph.D. Eng. Mari usz Kapruziak

E
-
mail address to the person
responsible for the course

mkapruziak@wi.zut.edu.pl


Course code

(if applicable)


ECTS points

4

Type of course

obl
igatory

Level of course

S1

Semester

wi nter/summer

Language of instruction

Engl ish

Hours per week

Lecture: 2, l abs: 2.

Hours per semester

Lecture: 30, l abs: 30.

Objectives of the course

Computer architectures, s tarting from von
-
Neumman and fi rs t el ectro
ni cs computers endi ng i n
s upercomputers based on networks of superscalar machines, low power pervas i ve computi ng and
modern al ternati ves to cl as s i cal s chema (l i ke reconfi gurabl e computi ng).

Entry requirements

none

Course contents

Von Neumann machine and
advent of commercial computers, basics of executi on and control uni t
functi onality (on example of x86 and PI C architecture), memory hi erarchy and cache memory (i ts
i nfluence on efforts on program code optimization in particular), ARM archi tecture and l ow p
ower


7

designs (like palmtops, smartphones), protected mode and i ts i nfl uence on modern operati on
systems, driver design for MS Wi ndows and Linux systems. Instruction Level Paralellism (especi al l y
superscalar and VLIW/DSP architectures). Modern microprocesso
rs. Supercomputers and networks
of computers aimed to solve particular problems. Reconfigurable systems and modern al ternati ves
to von Neumann machi nes.

Assessment methods

Fi nal Exam and Laboratory reports

Recommended readings

1) W. Stal l i ngs, Computer O
rgani zati on and Archi tecture, Prenti ce Hal l 2003

2) J. Stokes, Insi de the Machi ne, No Starch Press, 2007

3) P.E. Ceruzzi, A Hi story of Modern Computi ng, The MIT Press 2003

4) J. Si l c, B. Robic, T Ungerer, Processor Architecture From Datafl ow to Superscal ar

and Beyond,
Spri nger Verl ag 1999

5) W. Oney, Programmi ng the Mi crosoft Wi ndows Dri ver Model, Mi crosoft Press 2003

6) P. Raghavan, A. Lad, S. Neelakandan, Embedded Linux System Design and Development, Auerbach
Publ i cati ons 2006

7) P. Orwi ck, G. Smi th, Deve
loping Drivers with the Wi ndows Dri ver Foundati on, Mi crosoft Press
2007

8) D. Bovet, Understandi ng the Li nux Kernel, O’Rei l l y 2005

9) K. Kaspersky, Code Opti mi zati on: Effecti ve Memory Usage, A
-
Li st Publ i shi ng 2003

Additional information





Course title

FPGA

DESIGN AND RECONFIGURABLE COMPUTING


Teaching method

Lectures and l aboratories

Person responsible for
the course

Ph.D. Eng. Mari usz Kapruziak

E
-
mail address to the person
responsible for the course

mka
pruziak@wi.zut.edu.pl


Course code

(if applicable)


ECTS points

4

Type of course

el ective

Level of course

S1

Semester

wi nter/summer

Language of instruction

Engl ish

Hours per week

Lecture: 1, l abs: 2.

Hours per semester

Lecture: 15, l abs: 30.

Object
ives of the course

Teach how to deal wi th and encourage to use reconfigurable devices as a well
-
established alternative
to von
-
neumann and DSP proces s ors.

Entry requirements

none

Course contents

FPGA/CPLD devi ces architecture, Verilog l anguage, basics of

VHDL l anguage, Sys temVerilog and TLM
(Trans acti on Level Model i ng), s ynthes i s methodol ogy, emergi ng and experi mental/future
reconfi gurabl e archi tectures, dynami c reconfi gurati on, typi cal s oft
-
proces s or des i gns, FPGA
i mpl ementati ons of DSP al gori thms.

Asse
ssment methods

Fi nal Exam and Laboratory reports

Recommended readings

1. C.M. Maxfi el d, The Des i gn Warri or’s Gui de to FPGAs, Li nacre Hous e 2004

2) Xi l i nxⰠSpar瑡n
-
3 FPGA Fami l X Compl e瑥 Ma瑡VUee琬W2007

3) S⸠Su瑨erlanTⰠS⸠MaviTmannⰠP⸠Flak攬eSXV瑥WV敲il
og for M敳ignⰠA GuiT攠瑯 UVi ng SXV瑥mVeri l og
for HarTware MeVi gn anT MoTel i ngⰠSpri nger

4) O⹋⸠ParUi ⰠVLSI Mi gi 瑡l Si gnal ProceVVi ng SXV瑥mVⰠJoUn Pi l eX F SonV 1999

5) S⸠Oi l 瑳ⰠATvanceT FPGA MeVi ngⰠJoUn Pi l eX F SonVⰠ2007



8

6) S. S. Bhattacharyya, Hardw
are/Software Co
-
synthesi s of DSP Systems, Programmabl e Di gi tal
Si gnal Processors, 2001

7) L. Wanhammar, DSP Integrated Ci rcui ts, Academi c Press 1999

8) H. Corporal, Mi croprocessor Archi tectures from VLIW to TTA, John Wi l ey & Sons 1998

Additional informati
on





Course title

MICROPROCESSOR DESIGN AND SOFT
-
PROCESSORS

Teaching method

Lectures and laboratories

Person responsible for
the course

Ph.D. Eng. Mariusz Kapruziak

E
-
mail address to the person
responsible for the course

mkapruziak@wi.zut.edu.pl


Course code

(if applicable)


ECTS points

5

Type of course

elective

Level of course

S1

Semester

wi nter/summer

Language of instruction

Engl ish

Hours per week

Lecture: 2, l abs: 1, project:t 1

Hours per semest
er

Lecture: 30, l abs: 15, project:
15

Objectives of the course

Designing unique processors dedi cated for parti cul ar tasks, deep understandi ng of processor
functi onal i ty and acqui ri ng ski l l s to desi gn your own processor.

Entry requirements

Computer System

Archi tecture, FPGA Desi gn and reconfi gurabl e computi ng

Course contents

Di fferent i mpl ementati ons of ALU from i nsi de; synthesi s of control uni t; Internal bus
i mplementations and i ts alternatives; low power technologies


me瑨oTologi敳Ⱐi瑳 aTvan瑡geV anT
pi 瑦allV; cacU攬eVup敲Vcalar VcU敭敳 anT o瑨敲 probabiliV瑩c al瑥Wna瑩v敳; formal me瑨oTol ogi eV for
aVV敳Ving proc敳Vor p敲formanc攠anT UarTware
-
Vof瑷ar攠coVXn瑨敳iV; MSP Vp散ific T敳ignVⰠTXnami c
i nV瑲uc瑩on V整eproc敳VorV anT proc敳VorV wi瑨 TXnamic V瑲u
c瑵r攻 arraXV anT n整eorkV of proc敳VorV
i n one cUi p⸠Commerci al anT open projec瑳 for proceVVor TeVi gn on FPGA.

Assessment methods

Fi nal Exam and Laboratory reports

Recommended readings

1) P. Ienne, R. Leupers, Customizable Embedded Processors: Design T
echnologies and appl i cati ons,
Morgan Kaufmann, 2006

2) J. Nurmi, Processor Desi gn: System
-
On
-
Chi p Computi ng for ASICs and FPGAs, Spri nger 2007

3) D. Li u, Ki ndle, Embedded DSP Processor Design, Volume 2: Appl i cati on Speci fi c Instructi on Set
Processors, Mo
rgan Kaufmann 2008

4) W. Stal l i ngs, Computer Organi zati on and Archi tecture, Prenti ce Hal l 2003

5) J. Stokes, Insi de the Machi ne, No Starch Press, 2007

6) J. Si l c, B. Robic, T Ungerer, Processor Architecture From Datafl ow to Superscal ar and Beyond,
Spri nger

Verl ag 1999

7) K. Kaspersky, Code Opti mi zati on: Effecti ve Memory Usage, A
-
Li st Publ i shi ng 2003

Additional information










9

Course title

MACHINE VISION AND ROBOT ALGORITHMS ON
FPGA

Teaching method

Lectures and l aboratori es

Person responsible for
the
course

Ph.D. Eng. Mari usz Kapruziak

E
-
mail address to the person
responsible for the course

mkapruziak@wi.zut.edu.pl


Course code

(if applicable)


ECTS points

4

Type of course

opti onal

Level of course

S1

Semester

wi nter/summer

Language of instruction

Engl ish

Hours per week

Lecture: 2, l abs: 1, project: 1.

Hours per semester

Lecture: 30,l abs: 15, project:
15.

Objectives of the course

Designing structures for algorithms on FPGA to implement visual signal
processing. Usage of FPGA in
fi el ds where conventi onal and DSP al gori thms do not cope wel l.

Entry requirements

FPGA Desi gn and reconfi gurabl e computi ng

Course contents

Cl assical matrix processing of vi sual signals, FPGA for threshol di ng and fi l teri ng;

morphol ogi cal
operations on FPGA; edge detection i n application of estimating placement of electronic component
on PCB board; Hough transform and its irregular random structure on FPGA; FPGA for random and
dynamic structures; FPGA for 3D processing; camer
a interfaces and their support i n FPGA devi ces

Assessment methods

Fi nal exam and l aboratory reports

Recommended readings

1) E.R. Davi es, Machi ne Vi si on, Theory, Al gori thms, Practi cal i ti es, Morgan Kaufmann 2005

2) C.Woehl er, 3D Computer Vi si on: Effi ci ent
Methods and Appl i cati ons, Spri nger 2009

3) RB.K. Horn, Robot Vi si on, The MIT Press 1986

4) J. Bi l l ngsl ey, R.Bradbeer, Mechatroni cs and Machi ne Vi si on i n Practi ce, Spri nger 2007

5) J.Deschamps, G.Bioul, G.D.Sutter, Synthesis of Ari thmeti c Ci rcui ts: FPGA, AS
IC and Embedded
Systems, Wi l ey
-
Intersci ence 2006

6) S. Mann, Intel l i gent Image Processi ng, Wi l ey
-
IEEE 2001

7) N. Kehtarnavaz, M.Gamadia, Real
-
Time Image and Vi deo Processing: From Research to Real i ty,
Morgan&Cl aypool Publ i shers 2006

Additional information





Course title

BRAIN
-
COMPUTER INTERFACE

Teaching method

l ecture, l aboratory

Person responsible for
the course

Ph.D. Hab. Izabela Rejer

E
-
mail address to the person
responsible for the course

i rejer@wi.zut.e
du.pl


Course code

(if applicable)


ECTS points

4

Type of course

opti onal

Level of course

S1/S2/S3

Semester

wi nter/summer

Language of instruction

Engl ish



10

Hours per week

L:2, Lab: 2

Hours per semester

L: 30, Lab: 30

Objectives of the course

The aim
of the course is to teach students how to use an electroencephalographic devi ce to create
an i nterface whi ch al l ow to communi cate wi th the machi ne di rectl y vi a the brai n acti vi ty.

Entry requirements

None

Course contents

1.

Brai n
-
computer i nterface (BCI)
-

an overvi ew

2.

Di fferent types of BCI

3.

Mai n aspects of brai n structure and functi onal i ty

4.

Methods for measuri ng the brai n acti vi ty

5.

BCI i nterference cycl e

6.

Paradi gms for measuri ng EEG si gnal s

7.

Theoreti cal and practi cal aspects of processi ng an EEG si gnal

8.

Method
s for cl assi fyi ng EEG si gnal s

9.

Prepari ng an experi mental setup for creati ng BCI data set

10.

Creati ng a BCI data set composed of EEG si gnal s recorded duri ng l abs

11.

Extracti ng features from the recorded data set

12.

Trai ni ng a cl assi fi er

13.

Creati ng a BCI

14.

Testi ng the cr
eated BCI i n real condi ti ons

Assessment methods

Project work: creati ng a brai n
-
computer i nterface

Recommended readings

None hard l i terature

Sci enti fi c papers whi ch wi l l be handed duri ng l ectures.

Additional information

None




Course

title

MOBILE APP
LICATION DEVELOPMENT

Teaching

method

Lectures

and

l aboratories

Person

responsible

for

the

course

Ph.D.

Eng.

Radosław
Maci aVYcYXk

E
-
mail

address

to

the

person

responsible

for

the

course

rmaci aszczyk@wi.zut.edu.pl


Course

code


(if

applicable)


ECTS

point
s

4

Type

of

course

optional

Level

of

course

S1

Semester


wi nter/summer

Language

of

instruction

English

Hours

per

week

Lecture:

1

Labs:

1

Project:

1

Hours

per

semester

Lecture:

15

Labs:

15

P
roject:

15.

Objectives

of

the

course

Course providers concepts,

tools and APIs needed to create applications for mobile devices with
Android OS

Entry

requirements

Required:

Knowledge

of

at

l e a s t

one

obj e ct

progra mmi ng

l a ngua ge

Pre f e rre d:

J a va

l a ngua ge

Course

contents

I ntroduci ng to mobi l e devi ce,The Hi story of Andro
i d, Appl i cati on Fundame nta l s, Acti vi ty l i f e cycl e,
Us e r I nterface, Sensors, Threads a nd Servi ces, Stori ng a nd re tri evi ng data, Networki ng, Mul ti medi a,
Loca ti on Se rvi ce s.



11

Assessment

methods

Fi nal

exam

and

l aboratory

reports

Recommended

readings

1. Ian F. D
arwin, Android Cookbook, Problems and Solutions for Android Developers, O'Rei l l y 2012

2. Zi gurd Mednieks, Laird Dornin, G. Blake Meike, Masumi Nakamura, Programmi ng Androi d, 2nd
Edi ti on
-
Java Programmi ng for the New Generati on of Mobi l e Devi ces, O'Rei l l y 2
012

3. Mark L. Murphy, The Busy Coder's Gui de to Androi d Devel opment, CommonsWare


Di gi tal
versi on
-

http://commonsware.com/Androi d/

4.
http://d.androi d.com

Additional

information





Course title

SPEECH AND AUDIO A
NALYSIS

Teaching method

Lectures and Laboratories

Person responsible for
the course

Ph.D. Eng. Tomasz Mąka

E
-
mail address to the person
responsible for the course

tmaka@wi.zut.edu.pl

Course code

(if applicable)


ECTS points

3

Type of course

el ective

Level of course

S1

Semester

s ummer

Language of instruction

Engl ish

Hours per week

Le
cture: 1h

Laboratory: 1h

Hours per semester

Lectures: 15h

Laboratories: 15h

Objectives of the course

Introduction to acoustic signals analysis focuses on information extraction from speech and musical
si gnals.

Entry requirements

El ementary knowledge of d
igital signal processing and physics. Basics of probability theory, statistics
and data mi ni ng al gori thms. Good ski l l s i n programmi ng.

Course contents

Speech and audi o parametri zati on. Voi ce parameters extracti on. Fundamental frequency
estimation. Voice a
ctivity detection. Speech/Music discrimination. Speaker i denti fi cati on. Tempo
and beat esti mati on of musi cal si gnal s. Speech recogni ti on of i sol ated words. Vocal tract
normal i zati on. Speech and audi o segmentati on. Musi c genre recogni ti on.

Assessment meth
ods

Laboratories: software implementations of discussed algorithms

Lectures: written exam

Recommended readings

1.

S. V. Vaseghi, "Advanced Digital Signal Processing and Noise Reduction", 4th edition,
John Wiley
& Sons, Ltd
., 2008

2.

P. Rose, "Forensic Speaker I
dentification",
Taylor & Francis, 2002

3.

P. Vary and R. Martin, "Digital Speech Transmission",
John Wiley & Sons Ltd., 2006

4.

J. O. Smith, "Spectral Audio Signal Processing", W3K Publishing, 2011

5.

A. M. Kondoz, "Digital Speech",
John Wiley & Sons Ltd., 2004

Ad
ditional information





Course title

BASH
-

COMMAND LANGUAGE INTERPRETER



12

Teaching method

Lectures and l aboratories

Person responsible for
the course

Ph.D. Eng. Magdalena Szaber

E
-
mail address to the person
responsible for the course

mszaber@wi.zut.edu.pl


Course code

(if applicable)


ECTS points

2

Type of course

opti onal

Level of course

S1

Semester

wi nter / s ummer

Language of instruction

Engl ish

Hours per week

1 (l ecture)

1 (l aboratory)

Hours per seme
ster

30

Objectives of the course

Practi cal ski l l s, al l owi ng the user to type command and scri pts whi ch cause acti ons.

Entry requirements

none

Course contents

Bash is the most popular shell using i n the Unix systems or command l anguage i nterpreter. U
si ng
manual, type commands, script definition, make scripts, use text editors (vi, vi m, pico,nano), special
character, variables and parameters, file operator, redi recti on, quoti ng, ari thmeti c operati ons,
numerical constans, arithmetic evaluation, tables,
condi ti onal s, l oop for whi l e unti l, functi ons.

Assessment methods

Fi nal Exam and Laboratory reports

Recommended readings

1. B
ash Cookbook: Sol uti ons and Exampl es for bas
h Users
, Carl Al bi ng, JP Vossen, Ca
meron
Newham, O'Rei l l y, 2007

2. Learni ng the Bash Shel l by Cameron Newham and Bi l l Rosenbl att, O'Rei l l y, 2005

3.
http://www.gnu.org/software/bash/manual/

4.
http://www.fel i xgers.de/teachi ng/shel l s/shel l s.html

5.
http://tl dp.org/LDP/abs/html/

Additional information





Course title

NUMERICAL METHODS

T
eaching method

Lecture, l aboratories

Person responsible for
the course

Ph.D Eng. Anna Barcz

E
-
mail address to the person
responsible for the course

abarcz@wi.zut.edu.pl

Course code

(if applicable)


ECTS point
s

2

Type of course

Obl i gatory

Level of course

S1

Semester

Wi nter

Language of instruction

Engl ish

Hours per week

1

Hours per semester

15

Objectives of the course

The knowledge of the basic numerical methods within the scope of approximation, i ntegrati o
n and
numerical differentiation. Student will know how to use the Matlab to solve the numerical problems.



13

Entry requirements

The basi cs of hi gher mathemati cs, programmi ng ski l l s.

Course contents

Introducti on to Matl ab; Introducti on to Numeri cal Methods;
Interpol ati on and Pol ynomi al
Approxi mati on; Sol uti on of Li near Equati ons; Sol uti on of Nonl i near Equati ons; Numeri cal
Di fferentiation; Numerical Integration; Numerical Solution of Ordinary Differential Equations: Ini ti al
Val ue Probl ems.

Assessment methods

Lecture: test

Laboratori es: conti nuos assessment

Recommended

readings

1.

J.H. Matthews and K.D. Fink, Numerical Methods using Matlab, 4th Edition, Pearson
-

Prenti ce
Hal l, New Jersey, 2004

2.

J.C. Butcher, Numerical Methods for Ordinary Differential Equations,

Second Edi ti on (Second
Edi ti on), John Wi l ey & Sons, Ltd, 2008

Additional information





Course title

PROGRAMMABLE CONTROL DEVICES

Teaching method

Lecture and laboratory

Person responsible for
the course

Ph.D. Eng. Sławomir Jaszczak

E
-
mail address to the person
responsible for the course

sjaszczak@wi.zut.edu.pl

Course code

(if applicable)


ECTS points

2

Type of course

el ective

Level of course

S2

Semester

s
ummer or wi nter

Language of instruction

Engl ish

Hours per week

1 (L) + 1 (Lab)

Hours per semester

15(L) + 30(l ab)

Objectives of the course

The outcome of the course i s basic knowledge in programming indus tri al control devi ces and the
abi lity to using the
m in real ti me s ystems. Students will be abl e to des i gn, bui l d and i mpl ement
control algorithms dedicated to the real ti me control s ys tems. Ladder Di agram, Functi on Bl ock
Di agram, Automati on Bas i c, Structure Text bas i c programmi ng s ki l l s wi l l be acqui red.

Entry requirements

Phys i cs, mathemati cs, i nformati cs, el ectroni cs

Course contents

(L): Programmabl e control l ers (phys i cal and l ogi cal cons tructi on, memory organi zati on),
programming of PLC controllers (a short i ntroduction to basic programming languages
(LD, ST, FBD),
general rules related to the development and i mpl ementati on of control al gori thms,I/O s i gnal
s tandards ); Exampl es of appl i cati on).

(Lab) A compl ete cours e of programmi ng PLC control l ers, di vi ded i nto two parts a l ogi c and
conti nuous process
control, using GE VersaMaxMi cro and/or B&R control l ers, (connecti ng a PLC
control ler with a computer and a plant (a process or machine to be control l ed), a di agnos ti c and
s tarting of the PLC i n real conditions, i mpl ementati on of l ogi c functi ons, ti mers,
counters, PI D
al gori thms (cl as s i cal and fuzzy vers i ons ).

Assessment methods

conti nuous as s es s ment, project work, grade

Recommended readings

1.
Bryan L.A., Bryan E.A. Programmable Controll ers Theory and i mpl ementati on. I ndus tri al Text
Company,Mari etta 19
97.

2.
Astrom K., Hagglund T. PID controllers : Theory, design and tuning, Instrument Society of America,
NY, 1995.

3.
Manual s from GE and Bernecker&Rei ner



14

Additional information

Maxi mum 5 students i n one l aboratory group.

A practi cal part of the course i
s related to programming various control devices e.g. PLC control l ers
mai nl y from Bernecker&Rei ner (X20 control l ers and power panel s) and GE (VersaMax Mi cro
control l ers).





Course title


DATA ANALYSIS AND MACHINE LEARNING



Teaching method

Lectures (1
5h), laboratories (15h)


Person responsible for the

course

Ph.D. Hab. Eng. Przemysław Klęsk

E
-
mail address to the person
responsible for the course

pkl esk@wi.zut.edu.pl

Course code

(if applicable)


ECTS points

3

Type of course

Facultative, optional

Level of course

S2

Semester

wi nter or summer

Language of

instruction

Engl ish

Hours per week

Lecture 1h, l aboratories 1h

Hours per semester

Lectures 15h, l aboratories 15h

Objectives of the course

To expl ain to
students the posing of learning problems based on the data. To teach s tudents l earni ng
al gorithms and data
-
anal ys i s techni ques wi th focus on the general i zati on property and model
compl exi ty s el ecti on.

Entry requirements

Bas i cs of hi gher mathemati cs. Good
s ki l l s i n programmi ng.

Course contents

Recollections of elements of probability theory and statistics. Pri ncipal component analysis. Margi n of
s eparation i n pattern recognition and Support Vector Machines algorithm. Regression estimation tastk
and Multiva
riate Adaptive Regression Splines algori thm. Cl us teri ng anal ys i s


O
-
meanV al gori 瑨m.


Assessment methods

Lecture: wri tten exam

Laboratori es: programs (Matl ab) i mpl ementi ng the al gori thms and s hort wri tten tes ts

Recommended

readings

1.

Hastie, T. and Tibsh
irani, R. and Friedman, J., “The Elements of Statistical Learni ng: Data Mi ni ng,
Inference, and Predi cti on”, Spri nger, 2009



Bi shop, C., “Pattern recognition and machine l earning”, Information Science and Stati sti cs, 2007

Additional information





Course
title

DATA MINING ALGORITHMS

Teaching method

Lectures (15h), laboratories (30h)

Person responsible for the
course

Ph.D. Hab.
Eng. Przemysław Klęsk

E
-
mail address to the person
responsible for the course

pkl esk@wi.zut.edu.pl

Course code

(if applicable)


ECTS points

3



15

Type of course

obl igatory

Level of course

S2

Semester

wi nter or s
ummer

Language of

instruction

Engl ish

Hours per week

Lecture 1h, l aboratories 2h

Hours per semester

Lectures 15h, l aboratories 30h

Objectives of the course

To s how to students different types of data
-
mining/learning tasks that can be related to large da
ta sets.
To teach them algorithms to s olve these tasks and to discover interes ti ng patterns i n the data s ets.

Entry requirements

Bas i cs of hi gher mathemati cs. Good s ki l l s i n programmi ng.

Course contents

Recollections of elements of probability theory and

statisti cs. Pattern recogni ti on wi th naïve Bayes
cl assifier. I nduction (s earch) of association rules in shopping data
-

“A pri ori ” al gori thm. I nducti on of
deci sion rules, Pareto
-
optimal rules, rules assessment measures. Pattern recogni ti on wi th deci s i on
t
rees


CART al gori thm, tree pruni ng techni ques.

Assessment methods

Lecture: wri tten exam

Laboratori es: programs (Matl ab) i mpl ementi ng the al gori thms and s hort wri tten tes ts

Recommended

readings

1.

Hastie, T. and Ti bshirani, R. and Friedman, J., “The Elemen
ts of Statistical Learni ng: Data Mi ni ng,
Inference, and Predi cti on”, Spri nger, 2009

2.

Bi shop, C., “Pattern recognition and machine l earning”, Information Science and Stati sti cs, 2007

Additional information





Course title


INTRODUCTION TO ARTIFICIAL INTEL
LIGENCE

Teaching method

Lectures (15h), laboratories (15h)

Person responsible for the
course

Ph.D. Hab.
Eng. Przemysław Klęsk

E
-
mail address to the person
responsible for the course

pkl esk@wi.zut.edu.pl

Course code

(if applicable)


ECTS points

3

Type of course

obl igatory

Level of course

S1

Semester

wi nter

Lan
guage of

instruction

Engl ish

Hours per week

Lecture 1h, l aboratories 1h

Hours per semester

Lectures 15h, l aboratories 15h

Objectives of the course

To teach students algorithms allowing to s olve elementary problems pos ed wi thi n AI. I n parti cul ar:
s earch p
roblems, game
-
playing problems, pattern recognition probl ems and di s crete opti mi zati on
probl ems.

Entry requirements

Bas ics of hi gher mathemati cs. Good s ki l l s i n programmi ng and object
-
ori ented programmi ng.

Course contents

Probl ems posed within AI and def
initions of artificial thinking (Turing's i mitation game, Mi nsky's views).
Search problems: sudoku, minimal s udoku, s liding puzzle, n
-
queens problem; and graph
-
based s earch
al gorithms: A*, Best
-
First
-
Search, Dijkstra's al gori thm. Games
-
pl ayi ng probl ems: ch
es s, checkers,
connect 4; and tree
-
s earch al gori thms: MI N
-
MAX, al pha
-
beta pruni ng. Pattern recogni ti on wi th
el ementary neural networks: Rosenblatt's perceptron, multi
-
layer
-
perceptron. Dis crete opti mi zati on
probl ems: knapsack probl em, travel i ng s al es man pr
obl em; s ol u
ti ons wi th geneti c al gori thms.



16

Assessment methods

Lecture: wri tten exam

Laboratories: programs (Java/C++, Matlab) i mpl ementi ng the al gori thms and short wri tten tests

Recommended

readings

1.

Zhang, W., “State
-
Space Search: Al gorithms, Complexity
, Extensions, and Applications”, Spri nger,
1999.

2.

Hayki n, S., “Neural networks. A comprehensi ve foundati on”. Macmi l l an Col l ege Publ i shi ng
Company, New York, 1994.

3.

Prepared materi al s avai l abl e onl i ne at: wi ki zmsi.zut.edu.pl

Additional information





Cours
e title

METHODS OF ARTIFICIAL INTELLIGENCE IN COMPUTER GAMES

Teaching method

Lectures (15h), laboratories (15h)

Person responsible for the
course

Ph.D. Hab. Eng. Przemysław Kl ęsk

E
-
mail address to the person
responsible for the course

pkl esk@wi.zut.edu.pl

Course code

(if applicable)


ECTS points

3

Type of course

Facultative, advanced

Level of course

S2

Semester

s ummer

Language of


instruction

Engl ish

Hours per week

Lecture 1h, l aboratories 1h

Hours per s
emester

Lectures 15h, l aboratories 15h

Objectives of the

course

To teach students advanced techniques/algorithms in search problems and games
-
pl ayi ng probl ems.
Special regard to: games of i mperfect i nformati on and games wi th random el ements, dynami c or
on
l i ne
-
obs ervabl e envi ronments.

Entry requirements

Bas ics of higher mathematics. I ntroduction to artificial i ntelligence. Good s ki l l s i n programmi ng and
object
-
ori ented programmi ng.

Course contents

Search problems in dynamic envi ronments or environments wi
th i mperfect i nformati on


M⨯S瑥n瑺
al gori瑨m⸠Nl 敭敮WV of gam攠瑨敯rX


Yero
-
Vum gam敳ⰠMI N䥍AX 瑨eoremⰠop瑩mal mi xeT V瑲a瑥gXⰠ
NaVU 敱uilibrium⸠Łra敳V paraTox⸠Gam敳 wi瑨 瑲e攠repr敳敮瑡瑩onVⰠgam敳 compl數i瑹 meaVur敳⸠Fail
-
Vof琬Wfail
-
UarT alpUa b整e

pruningⰠOnu瑨
-
Moor攠瑨敯rem⸠Qui敳c敮c攬erefu瑡瑩on 瑡bl敳Ⱐkill敲 U敵riVWic⸠
Scou琠algori瑨mⰠYero
-
wiT瑨 V敡rcU winTowV (negamaxⰠnegaVcou琩⸠Nxpec瑩 mi ni max⸠Mon瑥carl o
approacUeV 瑯 carT gameV⸠Rei nforcemen琠l earni ngⰠQ
-
l earni ng al gori 瑨m.

Assessment

methods

Lecture: wri tten exam

Laboratories: i nventive programs written i n pai rs competi ng agai ns t programs by other s tudents

Recommended

readings

1.

Zhang, W., “State
-
Space Search: Al gorithms, Complexity, Extensions, and Applications”, Spri nger,
ㄹ㤹1



Lara
mee, D. “Chess Programmi ng I
-
V”, 2000.



Knuth, D.E. and Moore, R.W., “An analysis of Alpha
-
Beta Pruni ng”, Arti fi ci al Intel l i gence, 1975

Additional information









17

Course title

PATTERN RECOGNITION METHODS

Teaching method

Lectures (15h), laboratories (1
5h)

Person responsible for the
course

Ph.D. Hab.
Eng. Przemysław Klęsk

E
-
mail address to the person
responsible for the course

pkl esk@wi.zut.edu.pl

Course code

(if applicable)


ECTS points

3

Type of course

Facultative optional

Level of course

S2

Semester

s
ummer

Language of

instruction

Engl ish

Hours per week

Lecture 1h, l aboratories 1h

Hours per semester

Lectures 15h, l aboratories
15h

Objectives of the

course

To show to students di fferent types of l earni ng tasks. To teach students advanced aspects on
gene
ral i zati on and convergence i n stati sti cal l earni ng.

Entry requirements

Basi cs of hi gher mathemati cs. Good ski l l s i n programmi ng.

Course contents

El ements of Vapnik's Statistical Learning Theory. Observational setting, l earni ng machi ne, true error
and sam
ple error, Chernoff's inequality, uniform convergence, Vapnik bounds on true error, sampl e
compl exity, Vapnik
-
Chervonenkis dimension. Support Vector Machines al gori thm. Temporal pattern
recogni ti on, random p
rocesses, Hi dden Markov model s.

Assessment metho
ds

Lecture: written exam

Laboratories: programs (Matlab) implementing the algorithms and short written tests

Recommended


readings

1.

Vapni k, V., “Stati sti cal Learni ng Theory”, Wi l ey and Sons, 1998

2.

Hastie, T. and Ti bshirani, R. and Friedman, J., “The Element
s of Statistical Learning: Data Mi ni ng,
Inference, and Predi cti on”, Spri nger, 2009

3.

Bi shop, C., “Pattern recognition and machine l earning”, Information Science and Stati sti cs, 2007

Additional information





Course title

EXPERT SYSTEMS

Teaching method

L
ecture and laboratory

Person responsible for
the course

Ph.D. Eng. Joanna Kołodziejczyk

E
-
mail address to the person
responsible for the course

jkol odziejczyk@wi.zut.edu.pl

Course code

(if applicable)

O6/03

ECTS points

2

Type of course

el ective

Level of cour
se

S3

Semester

s ummer

Language of instruction

Engl ish

Hours per week

1 (L) + 1 (Lab)

Hours per semester

15(L) + 15(l ab)



18

Objectives of the course

The outcome of the course i s basic knowledge in expert systems and the ability to recognize areas of
i mplem
entation. Students will be able to design, build and i mplement rul e
-
based expert systems.
Prol og and CLIPS basi c programmi ng ski l l s wi l l be acqui red.

Entry requirements

Al gori thms and data structures

Course contents

(L) A

bri ef introduction to expert sys
tems i ncl udi ng the most promi nent exampl es.


Knowl edge
representation paradigms (with emphasis on rul e
-
based systems). Study of l ogi c and i nference
rul es.

Basic aspects of reasoning under uncertainty. Systems under uncertainty: Bayesian reasoni ng,
certai nt
y factors and fuzzy expert systems.

(Lab) Prol og programmi ng for expert systems. CLIPS basi cs i ncl udi ng rul e
-
based systems
devel opment.

Assessment methods

conti nuous assessment, project work, grade

Recommended readings

1.

Russel S., Norvi g P.: ‘Arti fi ci al I
ntel l i gence A modern approach’ Prenti ce Hal l, 2003

2.

Ivan Bratko, ‘Prol og programmi ng for AI’ 2001

Additional information

Maxi mum 5 students i n one l aboratory group.




Course title

ARTIFICIAL NEURAL NETWORKS AND THEIR APPLICATION IN SYSTEM MODELING

Tea
ching method

Lectures (15h) and laboratories (15h)

Person responsible for
the course

Prof. Andrzej Pi egat

E
-
mail address to the person
responsible for the course

api egat@wi.zut.edu.pl

Course code

(if applicabl
e)


ECTS points

3

Type of course

Facultative, optional

Level of course

S1, S2, S3

Semester

Wi nter / summer

Language of instruction

Engl ish

Hours per week

Lectures 2h, l aboratories 2h,

Every second week

Hours per semester

Lectures 15h, l aboratories
15h

Objectives of the course

Teaching students how neural networks are constructed, how do they l earn and how they can be
appl i ed to sol ve real tasks i n any branch of i ndustry, economy, etc.

Entry requirements

Basi c knowl edge of hi gh mathemati cs

Course con
tents

General construction of neural networks, meaning of wei ght and threshol d coeffi ci ents, expert
-
adaptation of coefficients, adaptation with error
-
back
-
propagation method, special phenomena i n
neural networks and practical advices referring to appl i cati
ons of neural networks, exampl es of
appl i cati on of neural net
works to real probl em sol uti on.

Assessment methods

Wri tten exam

Recommended

readings

1.

Haykin S.; Neural networks. A comprehensive foundation. Macmillan College Publishing
Company, New York, 199
4.

2.

Masters T.: Practical network recipes in C++. Academic Press Inc, 1993.

3.

Brown M., Harris C.; Neurofuzzy adaptive modeling and control. Prentice Hall International (UK)
Limited, 1994.



19

Additional information

Arti fi cial neural networks are part of artific
ial i ntelligence constructi ng si mi l arl y to human neural
networks and possessing ability to l earn from examples representing the probl em under sol uti on.
They are wi del y used i n techni cal, economi c, medi cal and other appl i cati ons.




Course title

KNOWLEDGE
EXTRACTION FROM DATA WITH ROUGH SET METHOD AND ITS
APPLICATIONS

Teaching method

Lectures (15h), l aboratori es (15h)

Person responsible for
the course

Prof. Andrzej Pi egat

E
-
mail address to the person
responsible for the course

api egat@wi.zut.edu.pl

Course code

(if applicable)


ECTS points

3

Type of course

Facultative, optional

Level of course

S1, S2, S3

Semester

Wi nter / summer

Language of instruction

Engl ish

Hours per week

1h l ectures, 1h laboratories

Ho
urs per semester

15h l ectures, 15h l aboratories

Objectives of the course

Teaching students how to extract easily understandable knowledge from large data basis concerning
any area (techni cal, economi c, medi cal ) wi th rough s ets.

Entry requirements

Bas i c k
nowl edge of hi gh mathemati cs

Course contents

Uncertainty of i nformation, consistent and inconsistent data, elementary conditional sets, concepts,
attri bute reduction, atomic rul e extraction, rule reduction and aggregation, evaluation of rul e bas e,
example
s of application of rough sets i n technical, economic and medi cal probl ems (data bas i s ).

Assessment methods

I ndi vi dual homework

Recommended readings

1.Pol kowski L.; Rough sets. Mathematical foundations. Physica
-
Verlag. A Springer
-
Verl ag Company,
2002,

2
. Pol kowski L., Skowron A. (editors); Rough sets in knowl edge di scovery. Physi ca
-
Verl ag, Berl i n,
1998.

3. Pal S.K., Skowron A. (editors); Rough fuzzy hybridization: a new trend in decision
-
making. Springer
-
Verl ag, Si ngapore, 1999.

Additional information

T
here are few methods able to extract knowledge from numerical and ordered data bases but rough
sets i s the onl y one that i s abl e to extract knowl edge from data basi s contai ni ng any type of
vari ables: numerical, qualitative, ordered and non
-
ordered variable
s. Rough set theory i s a branch of
arti fi ci al i ntel l i gence.




Course title

ESSENTIALS OF FUZZY LOGIC AND ITS APPLICATION TO SYSTEM MODELING AND
CONTROL

Teaching method

Lectures (15h), l aboratories (15h)

Person responsible for
the course

Prof. Andrzej

Pi egat

E
-
mail address to the person
responsible for the course

api egat@wi.zut.edu.pl

Course code

(if applicable)


ECTS points

5



20

Type of course

Facultative, optional

Level of course

S1,S2, S3

Semester

Wi nter

/ summer

Language of instruction

Engl ish

Hours per week

Lectures 2h, l aboratories 2h

Hours per semester

Lectures 15h, l aboratories
15h.

Objectives of the course

To teach students how expert knowledge can be i mplemented in computers in form of models to

support solution of real problems from any area, e.g. technical, economic, medical problems, etc.

Entry requirements

Basi c knowl edge of hi gh mathemati cs

Course contents

Numeri cal and linguistic values, construction of one
-
variable membership functions,

constructi on of
rul e basi s from expert knowl edge, constructi on of fuzzy model s from data wi th neuro
-
fuzzy
networks, application of fuzzy l ogic in modeling and control of techni cal, economi c, medi cal and
other probl ems.

Assessment methods

An i ndi vi dual ho
mework (i ndi vi dual project)

Recommended

readings

1.

Pi egat A.;Fuzzy model i ng and control. Physi ca
-
Verl ag, Hei del berg, New York, 2001

2.

Brown M., Harri s C.; Neurofuzzy adaptive modeling and control. Prentice Hall International (UK)
Li mi ted, 1994.

3.

Pedrycz W., F
ernando G.; Fuzzy systems engineering. Toward human
-
centric computing. Wi l ey
-
Intersci ence, Hoboken, New Jersey, 2007.

Additional information

Fuzzy l ogic is a modern branch of artificial intelligence that allows modeling of human, mostly expert
knowledge a
nd i ts use to solve difficult real problems or to control industrial plants, ships, air
-
plains,
etc. It al so finds wide application in scientific i nvestigations. It i s easy understandabl e for peopl e
(human
-
fri endl y).




Course title

CAD/CAE
SYSTEMS

Tea
ching method

l ecture, l aboratory exerci ses

Person responsible for the
course

Ph.D. Eng. Marci n Pluciński

E
-
mail address to the person
responsible for the course

mpl ucinski@wi.zut.edu.pl

Course code

(if applicable)


ECTS points

2

Type of course

obl igatory

Level of course

S1

Semester


s ummer

Language of instruction

Engl ish

Hours per week

l ecture: 1 hour

l ab. exercises: 2 hours

Hours per semester

l ecture: 15 hours

l ab. exercises: 30 hours

Objectives of the course

The fi rst objective of this course is to give fundamental knowledge abo
ut the basics of Matlab as wel l
as practi cal s ki l l s i n worki ng and programmi ng i n thi s s ys tem.

The s econd objective is to teach students the basic commands necessary for profes s i onal 2D and 3D
drawi ng and des i gn us i ng AutoCAD.

Entry requirements

I ntroduct
i on to Computer Sci ence

Course contents

The fi rst part of the course i ntroduces the student to the programming i n MATLAB to develop s cientific
and engineering models. The s tudent wi l l be abl e to wri te begi nner l evel programs that i ncl ude
condi tional state
ments, repetition l oops, i nput/output of fi l es, modul ar programmi ng i ncl udi ng
s ubprograms, and matri x mani pul ati on. Mai n topi cs:

-

i ntroducti on to Matl ab envi ronment,



21

-

defi ni ng matri ces,

-

matri x mani pul ati ons,

-

data structures,

-

2D and 3D graphi cs,

-

creati ng Matl ab functi ons,

-

Si mul i nk and other advanced Matl ab subjects.


The second part of the course introduces the student to the CAD systems (basi c concepts, hi story,
mai n features and tasks, structure of the system, basics of geometri c model i ng)
. Duri ng l aboratory
exerci ses, student wi l l work i n AutoCAD envi ronment. Mai n topi cs:

-

navi gati ng the worki ng envi ronment,

-

creati ng basi c drawi ngs,

-

mani pul ati ng and al teri ng objects,

-

drawi ng organi zati on and i nqui ry commands,

-

di mensi oni ng,

-

pl
otti ng dra wi ngs,

-

3D founda ti ons,

-

s i mpl e s ol i ds,

-

crea ti ng s ol i ds & s urfa ces from 2D objects,

-

modi fyi ng i n 3D s pa ce,

-

vi s ua l i za ti on

Assessment methods

l ecture: exa m

l a bora tory exerci s es: eva l ua ti on of s tudent dra wi ngs a nd progra ms

Recommende
d readings

MATLAB


the La ngua ge of Techni ca l Computi ng, The Ma thWorks I nc.

AutoCAD 2009


us er's Gui de, Autodes k I nc.

(both a va i l a bl e onl i ne)

Additional information





Course title

THE MULTI
-
CRITERIA DECISION
-
MAKING METHODS

Teaching method

Lecture an
d laboratory

Person responsible for
the course

M.Sc. Eng. Wojci ech Sałabun

E
-
mail address to the person
responsible for the course

ws alabun@wi.zut.edu.pl

Course code

(if applicable)


ECTS points

5

Type of co
urse

El ective

Level of course

S1

Semester

Wi nter

Language of instruction

Engl ish

Hours per week

2L + 1Lab

Hours per semester

30L + 15Lab

Objectives of the course

The acquisition of decision
-
making skills based on the method of Multi
-
Criteria Decision
-
M
aking
(MCDM).

Entry requirements

None

Course contents

Lecture:

1.

Description of decision making problems (structure, elements etc.)

2.

Review of the MCDM methods (achievements and main directions of researches)

3.

The WSM and WPM methods (examples, application,
benefits, defects, etc.)

4.

The AHP and ANP methods (examples, application, benefits, defects, etc.)

5.

The ELECTRE methods (examples, application, benefits, defects, etc.)

6.

The TOPSIS methods (examples, application, benefits, defects, etc.)



22

7.

The Fuzzy methods in
decision
-
making (examples, application, benefits, defects, etc.)

Workshop:

1.

Sol vi ng decision problems by using WSM and WPM methods

2.

Sol vi ng decision problems by using TOPSIS methods

3.

Sol vi ng decision problems by using AHP methods

4.

Sol vi ng decision problems by
using ELECTRE methods

5.

Sol vi ng decision problems by using AHP methods

6.

Sol vi ng decision problems by using Fuzzy Logic

Assessment methods

Lecture: oral exam

Workshop: project work

Recommended

readings

1.

Tri antaphyllou E., Multi
-
Criteria Decision Making Meth
ods: A Comparative Study, Kl uwer, 2010.

2.

Kahraman c., Fuzzy Multi
-
Criteria Decision Making: Theory and Applications with Recent
Devel opments, Springer Optimization and Its Applications, 2009

3.

Saaty T. L. and Vargas L. G., Models, Methods, Concepts & Applicat
ions of the Analytic Hierarchy
Process, Springer 2012.

4.

Greco S. and Ehrgott M., Figueira J.R. Trends i n Multiple Cri teria Decision Analysis, Springer
2012.

5.

Rogers M. G., Bruen M., Maystre Lucien
-
Yves, ELECTRE and Decision Support: Methods and
Appl ications

in Engineering and Infrastructure Investment, Kl uwer, 2010.

6.

Greco S. et al., Multiple Cri teria Decision Analysis: State of the Art Surveys, International Series in
Operations Research & Management Science, 2004

Additional information





Course title

C
OLOR MANAGEMENT

Teaching method

l ecture and l aboratory

Person responsible for
the course

PhD eng Przemyslaw Korytkowski

E
-
mail address to the person
responsible for the course

pkorytkowski@zut.edu.pl


Cour
se code

(if applicable)


ECTS points

4

Type of course

el ective

Level of course

S1

Semester

Wi nter / s ummer

Language of instruction

Engl ish

Hours per week

Lecture


2 Uour

Labora瑯rX


2 UourV

Hours per semester

60

Objectives of the course

Before the
completion of this course each student should be able to:



Describe colour phenomena



Understand various colour spaces (CIE LAB, CIE XYZ, CIE xyY, CIE LUV, RGB, CMYK)



Measure colour parameters using spectrophotometer



Understand ICC profiles



Organize a relia
ble colour management system

Entry requirements


Course contents

Course outline:

1.

Human colour reception

2.

Standard colour spaces

3.

Colour measurement

4.

ICC profiles

5.

Devices calibration

6.

Colour Management System



23

Assessment methods

conti nuous assessment

Recomme
nded readings

1.

Fraser, B., C. Murphy, F. Bunting, Real World Color Management, Peachpit Press, 2004.

2.

Sharma, A., Understanding Color Management, Delmar Cengage Learning, 2003

3.

Gi orgianni, E.J., T.E. Madden, M.A. Kri ss, Digital Color Management: Encoding Solu
tions, Wiley,
2009

4.

www.eci.org

5.

www.col or.org

Additional information





Course title

COMPUTER MODELLING AND SIMULATION

Teaching method

l ecture and l aboratory

Person responsible
for
the course

PhD eng Przemyslaw Korytkowski

E
-
mail address to the person
responsible for the course

pkorytkowski@zut.edu.pl


Course code

(if applicable)


ECTS points

3

Type of course

el ective

Level of cou
rse

S2

Semester

Wi nter / s ummer

Language of instruction

Engl ish

Hours per week

Lecture


1 Uour

Labora瑯rX


2 UourV

Hours per semester

45

Objectives of the course

Before the completion of this course each student should be able to:



Understand how comp
uter simulation works



Realize a modelling project using computer simulation



Understand how randomness should be taken into consideration while modelling

Entry requirements

Basics of probability theory and statistics

Course contents

Thi s course will provi
de a comprehensive coverage on system modelling, statistical theory, and
programming skill which are essential for carryi ng out simulation. Main topics on statistical theory
wi l l be illustrated with modelling and simulation exercises. Simulating with a gen
eral computer
l anguage and a simulation package are required.

Course outline:

1.

Introduction to modelling

2.

Approaches to computer simulation

3.

Input data modelling

4.

Design of experiments for simulation study

5.

Output data analysis

Assessment methods

conti nuous as
sessment

Recommended readings

1.

Kelton, W.D., R.P. Sadowski, N.B. Sweets, Simulation with Arena, McGraw Hill, 2009.

2.

Banks, J., J.S. Carson, B.L. Nelson, D.M. Nicol, Discrete
-
Event System Simulation, Prentice Hall,
2009.

3.

Law, A.M., W.D. Kelton, Simulation Mo
delling and Analysis, McGraw Hill, 2000.

4.

Altiok, T., B. Melamed, Simulation Modeling and Analysis with ARENA, Academic Press, 2007.

Additional information







24

Course title

LEAN MANAGEMENT

Teaching method

l ecture and project

Person responsible for
the
course

Przemyslaw Korytkowski

E
-
mail address to the person
responsible for the course

pkorytkowski@zut.edu.pl


Course code

(if applicable)


ECTS points

4

Type of course

el ective

Level of course

S2

Semester


Wi nter / s ummer

Language of instruction

Engl ish

Hours per week

Lecture


2 hour

Laboratory


2 hours

Hours per semester

60

Objectives of the course

Before the completion of this course each student should be able to:



Describe wastes in manufacturing en
vironment



Understand l ean principles



Impl ement a small l ean project i n a manufacturing environment



Asses a current situation on a production l ine



Realize a Value Stream Mapping project

Entry requirements

Introduction to manufacturing systems; Quality man
agement; Basic of probability and statistics

Course contents

Course outline:

1.

Wastes

2.

5S programme

3.

Push and pull production

4.

Val ue Stream Mapping and Value Stream Design

5.

Standardization

6.

Internal l ogistics

7.

Kanban

8.

Total Productive Maintenance

9.

Producti on levell
ing

10.

Sustainable management

Assessment methods

conti nuous assessment

Recommended readings

1.

Womack, J.P., D.T.Jones, D.Ross, The machine that changed the world, Harperperennial, 1990.

2.

Ford, H., Today and Tomorrow, Productivity Press, 2003.

3.

Ohno, T., Toyota
Production system, Productivi ty Press, 1998.

4.

Womack, J.P., D.T. Jones, Lean Thinking, Free Press, 2003.

5.

Li ker, J., M. Hoseus, Toyota Culture, McGraw Hill, 2008.

Additional information





Course title

MANAGEMENT AND BUSINESS COMMUNICATION VIRTUALISATION

Teaching method

Lecture

Person responsible for
the course

Ph.D. Eng. Pi otr Sulikowski

E
-
mail address to the person
responsible for the course

psulikowski@wi.zut.edu.p
l


Course code

(if applicable)


ECTS

points

2



25

Type of course

compulsory

Level of course

S2

Semester

s ummer

Language of instruction

Engl ish

Hours per week

1

Hours per semester

15

Objectives of the course

Students should demonstrate knowledge of key theories in organisations and be able t
o apply them
to the analysis of organisational issues. Students shoul d understand the i mportance of vi rtual
organisations in the modern world, be aware of the ways they are created and how they functi on.
Students should learn to pay attention to precision
, accuracy, and well
-
defined language in business
communi cati on.

Entry requirements

Thorough knowledge i n the fields of Organisation and Management as well as Information Systems.
Information Technology background.

Course contents

Vi rtual Organi sati ons:

Genesi s, Features, Cl assi fi cati on. Informati on Systems i n Vi rtual
Organi sati ons. Busi ness Communi cati on. Trust Management. Informati on Soci ety.

Assessment methods

Major end
-
of
-
term written & oral exam plus smaller mi d
-
lecture quizzes during the term.

Re
commended readings

1.
Warner M., Wi tzel M.: Managi ng i n Vi rtual Organi sati ons. London: I nternati onal Thomson
Busi ness Press, 2004.

2.
Col l ins S.: Communication in a Virtual Organisation. Mason, OH: Thompson
-
South Western, 2003.

3.
Grudzewski W., Hejduk I.
, Sankowska A., Wantuchowicz M.: Trust Management i n Vi rtual Work
Envi ronments. Boca Raton, FL: CRC Press, 2008.

Additional information





Course title

DATA PROCESSING IN ONLINE MARKETING AND MANAGEMENT SYSTEMS

Teaching method

Lecture / l aboratories

Person responsible for
the course

Phd eng Jarosław Jankowski

E
-
mail address to the person
responsible for the course

jjankowski@wi.zut.edu.pl


Course code

(if applicable)

Wi nter/summer

ECTS points

4

Type
of course

Compulsory

Level of course

S1

Semester


Language of instruction

english

Hours per week

2 Lecture, 2 Laboratories

Hours per semester

60

Objectives of the course

The use

of selected

algorithms and methods i n the expl orati on f data i n web syste
ms towards
personalization and i ncrease of their effectiveness.
Applicati ons of deci si on support systems i n
management and marketi ng targeted to onl i ne envi ronment.

Entry requirements

HTML programmi ng

Course contents

1) Personal i zati on of web appl i cati on
s

2) Opti mi za ti on of we b i nte rf a ce s towa rds hi ghe r conve rs i ons

3) Re comme ndi ng s ys te ms a nd col l a bora ti ve f i l te ri ng i n e comme rce pl a tf orms

4) Te xt mi ni ng a nd we b docume nts a na l ys i s

5) Da ta cl a s s i f i ca ti on i n onl i ne s ys te ms

6) Mi ni ng a s s oci a ti on rul e s f rom w
e b re pos i tori e s

7) Soci a l ne twork a na l ys i s



26

8) Informati on di ffusi on i n soci al networks

9) Data processi ng i n vi rtual worl ds and massi ve mul ti pl ayer systems

10) Fuzzy data processi ng i n the Internet systems

11) Opti mi zati ons
of i nternet adverti si ng servers

Assessment methods

-

wri tten exam

-

project work

-

conti nuous assessment

Bibliography

1.

Data Mi ning the Web: Uncoveri ng Patterns i n Web Content, Structure, and Usage, Zdravko
Markov, Dani el Larose , 2007

2.

Soci al Network Analysis: Methods and Applications,
Stanley Wasserman, Katheri ne Faust,1994

3.

Personalization Techniques And Recommender Systems, Guld
en Uchyi gi t, Matthew Y Ma, 2008

Additional information





Course title

DATA PROCESSING AND PERSONALIZATION OF WEB SYSTEMS

Teaching method

Lecture / l aborat
ories

Person responsible for
the course

PhD eng
Jarosław Jankowski

E
-
mail address to the person
responsible for the course

jjankowski@wi.zut.edu.pl


Course code

(if applicable)


ECTS points

4

Type of cour
se

Compulsory

Level of course

S1

Semester

Wi nter/summer

Language of instruction

english

Hours per week

2 Lecture, 2 Laboratories

Hours per semester

60

Objectives of the course

The use

of selected

algorithms and methods in the explorati on of data i n we
b systems towards
personalization and i ncrease of their effectiveness i n management and marketing.
Appl i cati ons of
deci si on support systems i n management and marketi ng targeted to onl i ne envi ronment.

Entry requirements


Course contents

1) Personal i zati on

of web appl i cati ons

2) Opti mi zati on of web i nterfaces towards hi gher conversi ons

3) Recommendi ng systems and col l aborati ve fi l teri ng i n ecommerce pl atforms

4) Text mi ni ng and web documents anal ysi s

5) Data cl assi fi cati on i n onl i ne systems

6) Mi ni ng assoc
i ati on rul es from web reposi tori es

7) Soci al network anal ysi s

8) Informati on di ffusi on i n soci al networks

9) Data processi ng i n vi rtual worl ds and massi ve mul ti pl ayer systems

10) Fuzzy data processi ng i n the Internet systems

11) Opti mi zati ons of i nternet
adverti s
i ng servers

Assessment methods

-

wri tten exam

-

project work

-

conti nuous assessment

Bibliography

1.

Data Mining the Web: Uncovering Patterns in Web Content, Structure, and Usage, Zdravko
Markov, Daniel Larose , 2007

2.

Social Network Analysis: Methods

and Applications, Stanley Wasserman, Katherine Faust,1994

3.

Personalization Techniques And Recommender Systems, Gulden Uchyigit, Matthew Y Ma, 2008

Additional information




27


Course title

DYNAMIC WEBSITES AND DOCUMENTS

Teaching method

Lecture / l aboratori
es

Person responsible for
the course

PhD eng
Jarosław Jankowski

E
-
mail address to the person
responsible for the course

jjankowski@wi.zut.edu.pl


Course code

(if applicable)


ECTS points

2

Type of course

Compulsory

Level of course

S1

Semester

Wi nter/summer

Language of instruction

english

Hours per week

1 Lecture, 2 Laboratories

Hours per semester

45

Objectives of the course

The use

of selected

tools in the

desi gn and devel opment of

web appl i cati ons

wi
th parti cul ar
emphasis on

the active elements
. I ntegrating within application
components of

DOM,

CSS

and
using
them i n modeling the

presentation l ayer
, access
to elements of

the document via

Java

Script,

use of

val i dators
, the use of
XML for

data transmiss
ion,

the integration of

components

using

asynchronous

technol ogi es

l i ke AJAX and wi th l i brari es l i ke JQuery.

Entry requirements

HTML programmi ng

Course contents

1) Document Object Model

2) The pres entati on l ayer of appl i cati ons and CSS

3) I ntegrati on of

Java Scri pt i n acti ve documents

4) JQuery and dynami c programmi ng

5) Communi cati on wi th the s erver us i ng XML

6) AJAX

and as ynchronous programmi ng

Assessment methods

-

wri tten exam

-

project work

-

conti nuous as s es s ment

Recommended readings

1.
jQuery i
n Acti on, Bear Bi beaul t, Yehuda Katz , 2010

2.
JavaScri pt: The Defi ni ti ve Gui de: Acti vate Your Web Pages, Davi d Fl anagan, 2011

3.
Profes s i onal Ajax, Ni chol as C. Zakas, Jeremy McPeak, Joe Fawcett, 2006

4.
Ajax: The Defi ni ti ve Gui de, Anthony T. Hol dener I I I,

2008

Additional information





Course title

DYNAMIC DOCUMENTS PROGRAMMING

Teaching method

Lecture / l aboratories

Person responsible for
the course

PhD eng
Jarosław Jankowski

E
-
mail address to the person
responsible for the course

jjankowski@wi.zut.edu.pl


Course code

(if applicable)


ECTS points

2

Type of course

Compulsory

Level of course

S1

Semester

Wi nte
r/summer

Language of instruction

english



28

Hours per week

1 Lecture, 2 Laboratories

Hours per semester

45

Objectives of the course

The use

of selected

tools in the

desi gn and devel opment of

web appl i cati ons

wi th parti cul ar
emphasis on

the active elements
.

Integrating within application
components of

DOM,

CSS

and
using
them i n modeling the

presentation l ayer
, access
to elements of

the document via

Java

Script,

use of

val i dators
, the use of
XML for

data transmission,

the integration of

components

using

async
hronous

technol ogi es

l i ke AJAX and wi th l i brari es l i ke JQuery.

Entry requirements

HTML programmi ng

Course contents

1) Document Object Model

2) The presentati on l ayer of appl i cati ons and CSS

3) Integrati on of Java Scri pt i n acti ve documents

4) JQuery and

dynami c programmi ng

5) Communi cati on wi th the server usi ng XML

6) AJAX

and asynchronous programmi ng

Assessment methods

-

wri tten exam

-

project work

-

conti nuous assessment

Recommended readings

1.
jQuery i n Acti on, Bear Bi beaul t, Yehuda Katz , 2010

2.

JavaScri pt: The Defi ni ti ve Gui de: Acti vate Your Web Pages, Davi d Fl anagan, 2011

3.
Professi onal Ajax, Ni chol as C. Zakas, Jeremy McPeak, Joe Fawcett, 2006

4.
Ajax: The Defi ni ti ve Gui de, Anthony T. Hol dener III, 2008

Additional information





Course titl
e

SOFTWARE TESTING

Teaching method

Lecture and laboratory exercises

Person responsible for
the course

Ph.D. Mi rosław Mościcki

E
-
mail address to the person
responsible for the course

mmoscicki@wi.zut.edu.pl


Course code

(if applicable)


ECTS points

4

Type of course

opti onal

Level of course

S1

Semester

wi nte
r/summe
r

Language of instruction

Engl ish

Hours per week

Lecture: 1 hours

Lab. Exerci ses: 2 hours

Hours per semester

Lecture: 15 hours

Lab. Exerci ses: 30 hours

Objectives of the course

To gai n knowl edge about s oftware tes ti ng proces s. Fami l i ari zati on wi th

tes ti ng tool s and
methodology. Knowledge about various test levels and s cope. Learning about software tes ter rol e.

Entry requirements

Requi red: Knowl edge of at l eas t one object programmi ng l anguage

Preferred: Java l anguage cours e compl eted

Course conte
nts

1.

Software quality


baVi c concepW



Tests


瑹peV anT l evel V



Software testing process

4.

Test design

5.

Testing with unit tests

6.

GUI level tests

7.

Robot Framework and Robot IDE tools

8.

Sikuli GUI testing tool

9.

Introduction to web applications testing



29

10.

Conti nuous i nte
grati on (wi th tool s)

Assessment methods

Each student should complete l aboratory exercises and pass theoretical exam in order to compl ete
the course. In case of exceptional performance during the labs, student can be excuses from the
exam wi th top grade ma
rk.

Recommended readings

1. Il ene Burnstei n. "Practi cal Software Testi ng", Spri nger, 2002

2. Marni e L. Hutcheson, "Software Testi ng Fundamental s: Methods and Metri cs", Wi l ey, 2003

3. KSHIRASAGAR NAIK, PRIYADARSHI TRIPATHY, "Software Testing and Qual i ty As
surance Theory
and Practi ce, Wi l ey, 2008

4. ISTQB Certi fi ed Tester Foundati on Level Syl l abus

Additional information





Course title

JAVA

J2EE

Teaching method

Lecture and laboratory exercises

Person responsible for
the course

Ph.D. Eng. Krzysztof Kras
ka

E
-
mail address to the person
responsible for the course

kkraska@wi.zut.edu.pl


Course code

(if applicable)


ECTS points

4

Type of course

optional

Level of course

S1

Semester

wi nter/summer

Language of inst
ruction

Engl ish

Hours per week

Lecture: 1 hours

Lab. exercises: 2 hours

Hours per semester

Lecture: 15 hours

Lab. Exerci ses: 30 hours

Objectives of the course

Familiarization with Java J2EE application framework and i ts concepts. Learn how to bui l d vari o
us
J2EE types of applications: JSP, JSF, basic EJB. Gai n knowl edge about JPA and i ts mos t common
i mpl ementati on (Hi bernate). Di s coveri ng J2EE appl i cati on s ervers.

Entry requirements

Requi red: Knowl edge of at l eas t one object programmi ng l anguage

Preferre
d: Java l anguage cours e compl eted

Course contents

1.

Introducti on to Java J2EE, types of appl i cati ons, basi c pri nci pl es

2.

J2EE worki ng envi ronment


appl i ca瑩on VerverⰠ



In瑲oTuc瑩on 瑯 Java Server PageV (JSP)H



ATvanceT JSP backenT beanVⰠexpreVVi o
n l anguageH



MVC approacU



Java Server FaceV



Java anT SQL Ta瑡baVeV



Java PerVi V瑥nce API (JPA)



Hi berna瑥

㄰1

J2NN frameworkV

ㄱ1

NJŁ

Assessment methods

Each student should complete l aboratory exercises and pass theoretical exam in order to co
mpl ete
the course. In case of exceptional performance during the labs, student can be excuses from the
exam wi th top grade mark.

Recommended readings

1.

Rod Johnson
-

Expert One
-
on
-
One J2EE Design and Development

2.

Bryan Basham, Kathy Sierra, Bert Bates
-

Head

First Servlets and JSP

3.

Kathy Sierra, Bert Bates
-

Head First EJB

Additional information




30


Course title

JAVA PROGRAMMING

Teaching method

Lecture and laboratory

Person responsible for
the course

Ph.D. Eng. Tomasz Wierciński

E
-
mail address to the person

responsible for the course

twi ercinski@wi.zut.edu.pl


Course code

(if applicable)


ECTS points

6

Type of course

el ective, optional

Level of course

S1

Semester

s ummer

Language of instruction

Engl ish

Hou
rs per week

Lecture: 1 hours

Lab. exercises: 2 hours

Hours per semester

Lecture: 15 hours

Lab. Exerci ses: 30 hours

Objectives of the course

1. Fami l i ar wi th the s yntax and s tructures of the Java l anguage

2. Knows how to anal yze and i mpl ement s ource code i
n Java l anguage

3. Understands the need for further development of professional s kills i n the field of Java l anguage

Entry requirements

1. Programmi ng bas i cs

2. Object programmi ng

Course contents

1. Data types and objects

2. Operators

3. Control i ns truct
i ons

4. Packages

5. Excepti ons

6. Encaps ul ati on, i nheri tance, pol ymorphi s m

7. Parametri zed types

8. I nput
-
output operati ons

9. Threads

10. GUI programmi ng

Assessment methods

wri tten exam, project work

Recommended readings

1. Thi nki ng i n Java (4th Edi ti on
), Bruce Eckel, Prenti ce Hal l, 2006

2. Java Programming (Oracle Press), Poornachandra Sarang, McGraw
-
Hill Osborne Media, 1 editi on,
January 20, 2012

3. Java, A Beginner's Guide, 5th Edition, McGraw
-
Hill Os borne Medi a; 5 edi ti on, Augus t 16, 2011

Additional

information

group l i mi t: 10 pers ons




Course title

CREATIVE PROBLEM SOLVING

Teaching method

Lectures, workshops

Person responsible for
the course

Prof. Antoni Wiliński,

PU⹄⸠Nng⸠ Anna SamborVka
-
OwcYarek

E
-
mail address to the person
responsible for the course

as amborska@wi.ps.pl


Course code

(if applicable)


ECTS points

3



31

Type of course

obl igatory

Leve
l of course

S1

Semester

wi nter/summer

Language of instruction

Engl ish

Hours per week

2

Hours per semester

l ectures: 15

works hops: 15

Objectives of the course

To develop the skills and techniques to generate new and i nnovati ve i deas and trans l ate new
so
l uti ons i nto pra cti ca l te rms a nd s tra te gi e s. Stude nts wi l l pra cti ce:



a ppl yi ng l ogi cal a nd cre ati ve a pproaches to s ol vi ng i nf orma ti cs probl e ms a nd ma k i ng
de ci s i ons;



a da pti ng to di f f e re nt thi nk i ng s tyl e s i n group a nd te a m e nvi ronme nts;



re cogni zi ng a nd re
movi ng ba rri e rs to i ndi vi dua l a nd group cre a ti vi ty to f os te r a n
i nnova ti ve work e nvi ronme nt.

Entry requi rements

No re qui re ments

Course contents

1.

Introduction to creativity: creativity barriers, creati vi ty recogni ti on, creati vi ty devel opment.

2.

Creati vi ty a
nd personal i ty, psychometri cs: Brai nstyl es, MBTI.

3.

Innovati ons and entrepreneurs: 7 l evel s of change, Creati ve Success Meter.

4.

Thi nking about thinking: combinatorial, transformative, cri tical, analytical and visionary thinking.
SCAMPER and other techni ques.

5.

Team devel opment and team rol es, Ri guette’s chai ns.

6.

Group methods of i dea generation: brainstormi ng, brai nwri ti ng, 5W1H, i dea sel ecti on and
eval uati on: C
-
box, 6 thi nki ng hats.

7.

Creati ve Probl em Sol vi ng Process by Osborn
-
Parnes.


Vi sual creati vi ty techni qu
es: Ishi kawa Di agram, Lotus Bl ossom Techni que, Mi ndmappi ng.

Assessment methods

Credi t

Recommended readings

1.

Buzan T., The Mi nd Map Book: “Radiant Thinking
-

Major Evol uti on i n Human Thought”, BBC
Acti ve, 3rd edi ti on, 2003.

2.

Buzan T., “Supercreativity


an
Interactive Guidebook”, Audio Renai ssance Tapes, Inc., 1988.

3.

De Bono E., “Si x Thi nki ng Hats”, Back Bay Books; 2 edi ti on, 1999.

4.

De Bono E., “Lateral Thi nki ng: Creati vi ty Step by Step”, Harper Col ophon, 1973.

5.

Mi l l er M., “Brainstyles: Change Your Li fe Wi thout

Changing Who You Are”, Si mon & Schuster,
1997.

6.

Von Oech R., “Whack on the Side of the Head: How You Can Be More Creative”, Business Pl us,
2008.

7.

Proctor T., “Creati ve Probl em So9l vi ng for Managers”. Routl edge 3
rd

ed., 2010

8.

Smi th R., “The 7 Levels of Change
: Different Thinking for Different Results”, Tapestry Press, 2nd
edi ti on, 2002.

Additional information





Course title

DIGITAL IMAGE PROCESSING

Teaching method

Lectures, l aboratories

Person responsible for
the course

P
P
a
a
w
w
e
e
ł
ł


F
F
o
o
r
r
c
c
z
z
m
m
a
a
ń
ń
s
s
k
k
i
i

E
-
mail address
to the person
responsible for the course


Course code

(if applicable)


ECTS points

4



32

Type of course


Level of course


Semester

wi nter

Language of instruction

Engl ish

Hours per week


Hours per semester

Lectures 1h/week

Laboratories 2h/week

Objectives

of the course

Di gi tal Image Processing focuses on various i mage representations, i mage acqui si ti on techni ques
and basic processing methods. The main goal of the l ecture is ai med at al gori thms and practi cal
aspects of digital i mage processi ng such as el eme
ntary i mage features and characteri sti cs,
hi stogram manipulations, spatial fi l teri ng and transformati ons. Duri ng l aboratori es sel ected
al gori thms wi l l be real i zed as computer programs i n MATLAB envi ronment.

Entry requirements

El ementary numerical recipes
, elementary programming skills, elementary matrix algebra

Course contents



Image representati ons (col or spaces, i mage features),



Image fi l teri ng (spati al domai n, frequency domai n),



Image compressi on (l ossy and l osel ess),

Image transforms (Fouri er Transfor
m, Cosi ne Transform, Haar Transform),

Assessment methods

Laboratories: each student will have to wri te several computer programs related to the algorithms
presented during lectures.

Lectures: fi nal test

Recommended readings

1.

T. Pavl idis, Al gorithms for Gr
aphics and Image Processing, Computer Sci ence Press, Rockvi l l e,
Maryl and, 1982, (416 pp). Translated into Russi an (1986), Pol i sh (1987), Chi nese (1988), and
German (1990). Incl uded i n Dr. Dobb's CD of Graphi cs Programmi ng, 1995. GC:573

2.

W. Pratt, Di gi tal I
mage Processi ng, John Wi l ey & Sons; 2 edi ti on (Apri l 1991)

3.

R. Gonzalez, R. Woods, and Eddins, Digital Image Processing Using MATLAB 2nd Ed. Gatesmark
Publ i shi ng. 2009

4.

A. K. Jai n, Fundamentals of Digital Image Processing, Prenti ce Hal l; US ed edi ti on (Octob
er 3,
1988)

Additional information





Course title

COMPUTER MUSIC

Teaching method

Lecture, l aboratory

Person responsible for
the course

M.Sc. Eng.
Łukasz Mazurowski

E
-
mail address to the person
responsible for the course

l mazurowski@wi.zut.edu.pl


Course code

(if applicable)


ECTS points

4

Type of course

Opti onal

Level of course

S2

Semester

Wi nter

Language of instruction

Engl ish

Hours per week

2

Hours per semester

15


Lec瑵re

ㄵ1


Labora瑯rX

Objectives of the course

Students successfully completing this module should be able to:




demonstrate knowledge of key issues in contemporary computer music.



analyze problems in computer music analysis, representation, and creation.



synthesize solutions to such problems on the basis of contemporary tools and theories.



evaluate such solutions using appropriate methods



manage their own learning in terms of acqui
ring disciplinary knowledge from academic
literature



evaluate their own solutions



33



work autonomously



sol ve complex problems



develop and apply software development skills in the production of software for crea
tive
tasks in the music domain.

Entry requiremen
ts

A good standard of computer l iteracy is required as programming will be involved (prior
programming or musical experience would be helpful but is not cri tical).

Course contents

The course will cover three key aspects of computer music: representation,
creativity and analysis
addressed through theory and practice. It will cover sound, music as organized sound, and specific
applications (e.g. music information retrieval ). Students will be strongly encouraged to explore both
sci entific and artistic aspect
s of the course through programming exercises to generate sound and
music i n contemporary vi sual/ textual music and programming l anguages. Students will be expected
to compose a short algorithmic work using the computer and a concert will be held at the en
d of the
course to showcase compositions produced using the techniques taught and developed.

Assessment methods

Lectures, l aboratories, and demonstrations of techniques. Students will be given weekly


exercises
to expl ore and practice techniques.


The cou
rse has the following assessment components:




Wri tten examination (2 hours, 60%)



Al gori thmic composition (audio file, source code) (40%)


To pass the course students must:

Gai n
an overall mark of 50% or above

Recommended readings

1.

Mi randa E. R.: Composing
Music with Computers, Focal Press, 2001,

2.

Casey M. A. et al: Content
-
Based Music Information Retrieval: Current Directions and
Future Challenges, IEEE 96, Issue: 4, 2008, p. 668


696

3.

Larti llot O., Toiviainen P.: A MATLAB TOOLBOX FOR MUSICAL FEATURE EXTRACT
ION FROM
AUDIO, Proc. of the 10th Int. Conference on Digital Audio Effects (DAFx
-
07), Bordeaux,
France, September 10
-
15, 2007, on
-
l ine:
http://i smir2007.ismir.net/proceeding
s/ISMIR2007_p127_lartillot.pdf

Additional information





Course title

JAVA WEB APPLICATIONS DEVELOPMENT

Teaching method

Lecture, workshop

Person responsible for
the course

Ph.D. Eng. Pi otr Czapiewski

E
-
mail address to the person
responsible for the
course

pczapiewski@wi.zut.edu.pl


Course code

(if applicable)


ECTS points

3

Type of course

opti onal

Level of course

S1

Semester

wi nter/summer

Language of instruction

Engl ish

Hours per week

2

Hours per

semester

30

Objectives of the course

Understanding web applications concepts and architecture. Practical knowledge of web applications
development using Java language and selected frameworks.

Entry requirements

Object ori ented programming, relational da
tabases concepts and SQL, basic knowledge of HTML
and CSS , basics of Internet organization and protocols, basic knowledge of Java l anguage



34

Course contents

1.

Introducti on to web appl i cati on concepts and archi tecture.

2.

Introducti on to Java web appl i cati on dev
el opment (Java Servl ets, JSP)

3.

Design patterns for web applications development (Front Control l er, Model Vi ew Control l er)

4.

Web appl i cati on frameworks (Spri ng MVC, JSF)

Assessment methods

Oral exam (web applications concepts and architecture) and practical p
roject (developing a web
application).

Recommended readings

1)

L. Shkl ar, R. Rosen, “Web Application Architecture: Pri nciples, Protocols and Practi ces”, Wi l ey
2009

2)

K. Si erra, B. Bates, "Head Fi rst Java", O'Rei l l y 2005

3)

B. Basham, K. Si erra, B. Bates, "Head Fi
rst Servl ets and JSP", O'Rei l l y 2008

4)

D. Geary, C. S. Horstmann, "Core JavaServer Faces", Prenti ce Hal l 2010

5)

C. Wal l s, "Spri ng i n Acti on", Manni ng 2011

Additional information





Course title

WEB SERVICES DEVELOPMENT

Teaching method

Lecture, workshop

P
erson responsible for
the course

Ph.D. Eng. Pi otr Czapiewski

E
-
mail address to the person
responsible for the course

pczapiewski@wi.zut.edu.pl


Course code

(if applicable)


ECTS points

2

Type of course

op
ti onal

Level of course

S1

Semester

wi nter/summer

Language of instruction

Engl ish

Hours per week

1

Hours per semester

15

Objectives of the course

Understanding web servi ces concepts and architecture (SOAP, REST). Practical knowl edge of web
servi ce devel
opment usi ng Java l anguage and sel ected frameworks (JAX
-
WS, JAX
-
RS).

Entry requirements

Object ori ented programmi ng, rel ati onal databases concepts and SQL, basi cs of Internet
organi zati on and protocol s, basi c knowl edge of Java l anguage, basi c knowl edge of

XML

Course contents

1.

Role of web services in application integration

2.

SOAP web services: concepts and architecture

3.

Developing SOAP web services using Java (JAX
-
WS)

4.

REST web services: concepts and architecture

5.

Developing REST web services using Java (JAX
-
RS
)

6.

Testing web services

Assessment methods

Oral exam (web servi ces concepts and architecture) and practical project (developing a web servi ce
server and cl i ent).

Recommended readings

1)

K. Sierra, B. Bates, "Head First Java", O'Reilly 2005

2)

M. Kalin, "Java We
b Services: Up and Running", O'Reilly 2009

3)

B. Burke, "RESTful Java with Jax
-
RS", O'Reilly 2009

Additional information







35

Course title

PHP
WEB APPLICATIONS DEVELOPMENT

Teaching method

Lecture, workshop

Person responsible for
the course

Ph.D. Eng. Pi ot
r Czapiewski

E
-
mail address to the person
responsible for the course

pczapiewski@wi.zut.edu.pl

Course code

(if applicable)


ECTS points

3

Type of course

opti onal

Level of course

S1

Semester

wi nter/summe
r

Language of instruction

Engl ish

Hours per week

2

Hours per semester

30

Objectives of the course

Understanding web applications concepts and architecture, MVC design pattern i n particular.
Practi cal knowledge of web applications development using PHP la
nguage and selected
frameworks.

Entry requirements

Object ori ented programming, relational databases concepts and SQL, basic knowledge of HTML
and CSS , basics of Internet organization and protocols

Course contents

1.

Introducti on to web appl i cati on concept
s and archi tecture.

2.

PHP Web appl i cati on devel opment

a.

I ntroducti on to PHP l a ngua ge

b.

Ba s i cs of web devel opment us i ng PHP (forms, s es s i ons, da ta ba s e a cces s )

3.

Design patterns for web applications development (Front Control l er, Model Vi ew Control l er)

4.

Web appl i cat
i on frameworks

Assessment methods

Oral exam (web applications concepts and architecture) and practical project (developing a web
application).

Recommended readings

1)

L. Shkl ar, R. Rosen,
Web Application Architecture: Principles, Protocols and Practices
, Wi
l ey
2009

2)

R. Ni xon,
Learning PHP, MySQL, and JavaScript: A Step
-
By
-
Step Guide to Creating Dynamic
Websites
, O’Rei l l y 2009

3)

A. Saray,
Professional PHP Design Patterns
, Wrox 2009

4)

Zend,
Zend Framework: The Official Programmer’s Reference Guide
, Apress 2010

5)

F. L
yman,
Pro Zend Framework Techniques: Build a Full CMS Project
, Apress 2009

Additional information