information day 2nd cycle [združljivostni način]

INFORMATION DAY

The study program COMPUTERSCIENCE AND INFORMATION

TECHNOLOGY 2nd Bologna cycle

APPLICATION DEADLINES

� 1st application period (for non EU nationals)

� from publication of the Call until 31 May 2018 (by webportal eVŠ: http://portal.evs.gov.si/prijava/)

� Enrollment deadline by 29 June 2018

https://www.um.si/en/Study/about/Pages/CALL-FOR-APPLICATION-INTO-POSTGRADUATE-STUDY-PROGRAMMES-OF-THE-UNIVERSITY-OF-MARIBOR-FOR-THE-ACADEMIC-YEAR-2018_19-.aspx

Institute of Computer Science https://cs.feri.um.si/en/

APPLICATION DEADLINES

� 2nd application period (for non EU nationals)

� From 9 July until 10 September 2018 if positions are not filled in the first application period and faculties decide to publish a list of vacancies (by web portal eVŠ: http://portal.evs.gov.si/prijava/)

� Enrollment deadline by 25 September 2018

https://www.um.si/en/Study/about/Pages/CALL-FOR-APPLICATION-INTO-POSTGRADUATE-STUDY-PROGRAMMES-OF-THE-UNIVERSITY-OF-MARIBOR-FOR-THE-ACADEMIC-YEAR-2018_19-.aspx


ADMISSION REQUIREMENTSCandidates who completed the following may apply for the master’s (2nd-cycle) programme “Computer Science and Information Technologies”:

� A bachelor’s (1st-cycle) programme in the relevant field: computing (48), physical science (broad programmes-440), physics and astronomy (441), mathematics and statistics (46);

� A bachelor’s vocational programme adopted prior to 11 June 2004 and a specialisation programme adopted prior to 11 June 2004 in the relevant field: computing (48). These candidates are typically awarded 60 ECTS credits and may enrol in the second year provided they satisfy the transfer criteria laid down in the accredited study programme;


ADMISSION REQUIREMENTS� A bachelor’s (1st-cycle) programme in one of the following fields:

mechanics and metal work (521), electricity and energy (522), electronics and automation (523). Prior to enrolment, candidates must fulfil study obligations corresponding 24 ECTS credits under the bachelor’s (first-cycle) programme, a training programme or by taking placement tests. Candidates must fulfil the following obligations: “Programming II” (6 ECTS), Algorithms and Data Structures” (6 ECTS),

Computer Architecture (6 ECTS), Operating Systems (6 ECTS);

� …

https://www.um.si/studij/financiranje/inovativna-shema-2010/Documents/1819FERIAN.pdf


AVAILABLE POSITIONS

� for Slovenian citizens and EU nationals: 60

� for Slovenians without Slovenian citizenship and foreign

nationals: 40


LIMITED ENROLMENT AND SELECTION

PROCEDURE

If the number of applications exceeds the number of positions available, the programme shall be understood as having limited enrolment. In the selection procedure, candidates will be ranked according to the academic performance under the bachelor’s (first-cycle) programme(grade point average including bachelor’s thesis –100%)


PROGRAM STRUCTURE

� 2 years

� 120 ECTS

� Project oriented study

� Diversity of content

� Connection with research work


1st YEAR

Course Lecturer ECTS

Winter semester

SOFTWARE SYSTEMS DEVELOPMENT AND MANAGEMENT KOKOL PETER 5

SELECTED ALGORITHMS STRNAD DAMJAN 5

CLOUD COMPUTING DEPLOYMENT AND MANAGEMENT ZAMUDA ALEŠ 5

WEB TECHNOLOGIES OJSTERŠEK MILAN 5

COMPUTER MULTIMEDIA ŽALIK BORUT 5

DOMAIN-SPECIFIC MODELLING LANGUAGES KOSAR TOMAŽ 5

Summer semester

COMPUTER PROCESSING OF SIGNALS AND IMAGES HOLOBAR ALEŠ 6

PROJECT SUBJECT I 6

PROJECT SUBJECT II 6

PROJECT SUBJECT III 6

PROJECT SUBJECT IV 6


1st YEAR


Project 1: INTELLIGENT INFORMATION TECHNOLOGIES

SELECTED COMBINATORIAL ALGORITHMS MONGUS DOMEN 6

INTELLIGENT SYSTEMS ZORMAN MILAN 6

INTEROPERABILITY SYSTEMS AND INTELLIGENT SERVICES FISTER IZTOK 6

LANGUAGE TECHNOLOGY BOŠKOVIĆ BORKO 6

Project 2: COMPUTER METHODOLOGIES AND APPLICATIONS

LANGUAGE TECHNOLOGY BOŠKOVIĆ BORKO 6

UBIQUITOUS COMPUTING ČREPINŠEK MATEJ 6

ALGORITHMS FOR BIGDATA ANALYSIS MONGUS DOMEN 6

NEURO, NANO AND QUANTUM COMPUTING HOLOBAR ALEŠ 6


2nd YEAR


Winter semester

PROJECT SUBJECT V 6

PROJECT SUBJECT VI 6

PROJECT SUBJECT VII 6

PROJECT SUBJECT VIII 6

OPTIONAL SUBJECT I 6

Summer semester

OPTIONAL SUBJECT II 6

MASTER’S THESIS 24


2nd YEAR


Project 1: INTELLIGENT INFORMATION TECHNOLOGIES

ADVANCED IMAGE PROCESSING POTOČNIK BOŽIDAR 6

EVOLUTIONARY COMPUTATIONS MERNIK MARJAN 6

LEAN MANAGEMENT IN ENGINEERING ZORMAN MILAN 6

COMPUTER ANIMATION STRNAD DAMJAN 6

Project 2: COMPUTER METHODOLOGIES AND APPLICATIONS

ADVANCED IMAGE PROCESSING POTOČNIK BOŽIDAR 6

ALGORITHMS FOR REMOTE SENSING DATA PROCESSING MONGUS DOMEN 6

OPTIMIZATION METHODS KORŽE DANILO 6

COMPUTER VISION POTOČNIK BOŽIDAR 6


2nd YEAR

OPTIONAL SUBJECT I and OPTIONAL SUBJECT II Lecturer ECTS

VIRTUAL MACHINES AND COMPUTER RESOURCE MANAGEMENT POTOČNIK BOŽIDAR 6

MATHEMATICS IN COMPUTER SCIENCE PETERIN IZTOK 6

SOFTWARE QUALITY KOKOL PETER 6


From users need, to satisfied user and successful product with engineering approaches

1. User is the king! We identify the needs of all stakeholders of the product

2. We select the most suitable design model

3. We plan! We use modern tools, software repositories, our own and experiences of othersdevelopers

4. Give user the best possible product

Testni smetnjak

Software Systems Development and Management


Institute of Computer Science

Selected Algorithms

Upgrade the knowledge of basic algorithmsand data structures with:

1. Encryption algorithms, which includes the

methods for generation and testing of prime

numbers, on which the algorithm RSA for

public-key cryptography is based.

2. Solving real-world optimization problemsusing linear programming and network flow

algorithms.

3. Advanced data structures: balanced trees,

B-trees.

4. Approximative problem solving, where a

near-optimal solution is needed in limited time.

https://cs.feri.um.si/en/

Computing in the front row of global development:

from algorithms to biggest computer applications.

1. Infrastructure and algorithms: high-performance

computing, parallel and distributed systems;

MapReduce, MPI, and VirtualBox.

2. Virtualization IaaS, Saas, Paas:

through on-demand resources to largest architectures

for smart, social, and contract networks;

Hadoop and Yarn, Google File System and AppEngine.

3. Big Data and security: from Google services,

Facebook, Twitter, Amazon Web Services, Apple, and

Microsoft Azure to dApp and securing your solutions.

Cloud computing

Virtualizing compute

services execution

Distributed storage

Cloud ComputingDeployment and Management


Web technologiesDo you want to learn about the

technologies used in developing

of web applications?

Are you interested in how to

develop a web-based application

that uses cloud services and

blockchain?

Do you want to develop

semantic and service-oriented

web applications?

Do you want to develop a search

engine or a recommender

system?


The main emphasis of the subject is on multimedia data types based on lossy data compression. Lossy image compression is in focus.

1. Metric for error measurement, intuitive lossy

methods.

2. Discrete cosine transform, wavelet transform,

filters and databanks, SPIHT

3. Standards JPEG, JPEG-LS, JBIG, JPEG2000

4. Alternative approaches: data-dependent

triangulation, space filling curves, fractal techniques.

Computer Multimedia


There are problems that are easier to present as a small programming language, called domain-specific (modeling) language.

1. Why do we need a language? Difficult

presentation of the problem.

2. How do we start? Identification of the problem

domain.

3. What is the solution? Text-based or visual-based

programming language.

Use case scenarioIn the graphical user-interface,

several sequential steps are

required to achieve the

desired effect.

Domain-Specific Modeling

Languages

PametniTelefon ;)


Computer Processing of Signals and Images

Data presentation in different domainsThe fastest and the most spatially efficient algorithms for data processing

are implemented in the presentation domain, where the data is written as

compactly as possible. Which data should be presented in analytical form,

which in frequency, which in time-frequency, which in wavelet and which in

the Z domain and what are the benefits of representation in these domains?

Adaptive filtering and artefact removalReal-world signals contain noise. How do we remove this noise and how do we evaluate the information in the signal or image as efficiently as possible?

Signal analysis and processing analysisHow and by how much can we increase the accuracy of data processing in different domains without sacrificing memory or processing time?


Pattern recognition in various types of text data, like

genome for example, is often based on combinatorial

problems:

� Comparison of sets

� Search for common substrings and their alignment

� Array mapping operations ...

Selected Combinatorial Algorithms

This subject focuses on techniques for

designing effective pattern recognition

algorithms using:

� Dynamic programming,

� Optimization techniques: branch and

bound, divide and conquer, ...

� Analysis of graphs and prefix and suffix

trees, ...


It is almost impossible to avoid Intelligent systems in the last few years as users. But do we even know where they lie in wait for us? Do we have the potential to develop new IS that will make life easier for us?

We will cover the following topics:

� Concepts of designing and learning IS.

� Types of knowledge search and presentation with IS.

� Methods of IS evaluation.

� Ethical questions related to IS.

� Challenges for the future.

Intelligent Systems


Interoperability (multiagent) system consists of a number of intelligent agents, which interact with one another.

To successfully interact, they must:

� cooperate,

� coordinate,

� negotiate.

They mimic processes in human society as well as

other inspirations from the nature by their

operating.

They incorporate a knowledge from various

scientific disciplines.

Interoperability Systems

and Intelligent Services


Language TechnologyTeach a computer to use the natural language as a communicationtool and as a data source for solving various problems.

� A set of technologies that are designed with the purpose to process

the natural language.

� The natural language is used as the input and output data stream.

� Tasks: text segmentation, natural language detection, spelling

correction, document classification, sentiment analysis, plagiarism

detection and natural language translation.



As creators, advocates and critics, we start the path of creating a new product.

1. Who and why? We identify the need.

For example care for the dog, care for the

environment, absence from home ...

2. Where and when? We identify the place and make

sure that it is embedded in the current environment.

For example dog food, overturned bin, incoming mail

...

3. How? We prototype the idea.

For example see pictures of student products.

Ubiquitous Computing

Care for the dog (weighing food)

Test trashbin

SmartPhone

Smart mailbox

Massive data is a moving target. It cannot be

processed efficiently by traditional methods, since it

is characterized by (to) large:

� Volume

� Velocity

� Variety

Algorithms for BigData Analysis

One of the fastest growing areas (with tripled

value of the global marked to 2026). Its topics

include:

� Social sensing

� Predicting financial trends

� User analyzes and recommendations

systems

� Rendering multidimensional data


Neuro, Nano and Quantum Computing

Neuromorphic computingOur brain is a wonderful pattern recognition and natural

intelligence machine. What does it have in common with

Intel's Loihi and what's with Apple's A11 processor?

Brain-computer interfacesHow can we automatically measure user‘s mood, read thoughts and predict people's decisions up to 8 seconds in advance?

Quantum computingThe superposition and entanglement of quantum states are unimaginably different from our classical world experiences. And yet they support ultimate parallel computing and extremely secure communication. The first quantum processors are already here! How do they work and what are the algorithms for them?

brain 3.0

100 quantum bits can store more classic bits of

information than there are atoms in the known universe!


1. We capture 2D, 3D and even 4D images with a wide variety of cameras. E.g., thermal, polarization,

hyperspectral, „medical“, Kinect, „mobiles“…

2. We algorithmically correct, remove, emphasize information in images. For example, we correct

colours, remove noise…

3. We automatically identify regions and their properties in diverse image spaces. E.g., eye area,

terrain with high humidity in the SAR image…

4. We combine a processing with a classification. E.g., grain of oat is healthy, tumour is not cancerous,

Janez has arrived…

Advanced Image Processing

SAR image(Where is water?)

Are colours 'real‘?

Is photomontage?



To understand theoretical basics of evolutionary algorithms and in-depth understanding of their operation.

� Multi-criteria optimization.

� Adaptive and self-adaptive parameter control.

� How different metaheuristics perform search?

� How to compare different metaheuristics?

� Nature inspired metaheuristics.

Evolutionary Computations

Multi-criteria

optimization

Simulation of textiles

Process control

Each engineer's goal is to be excellent in his work and to offer hisproducts and services that will be of the highest quality, at the best price and delivered at the right moment.

But, do we even know how to achieve this?

Lean Metodology is already a proven approach, which we will introduce into

software engineering and integrate it with SPICE and functional safety.

The above three are, among other things, the basis for high-quality software

development in the automotive industry.

Lean Management in Engineering


Institute of Computer Science

Computer Animation

Make virtual environments in computergraphics more interesting by:

1. Capturing and interpolating the moving

objects‘ trajectories.

2. Detecting and resolving object collisions.

3. Animating objects using kinematic

chains and inverse kinematics.

4. Adding special effects with particle

systems (explosions, smoke, fire).

5. Using behavioral animation

(crowd simulation).

https://cs.feri.um.si/en/

Advanced remote sensing technologies allow for

monitoring the processes on the Earth‘s surface

with near forensic precision:

� Laser scanning

� Radar

� Multi- and Hyperspectral imaging

Algorithms for Remote Sensing Data

Processing

This subject focuses on:

� Fusion of heterogeneous data sources

� Techniques for processing point-

clouds, radar, and mutli/hypespectral

images

� Change detection and recognition of

objects on the Earth’s surface


In today's world, we are faced daily by solving a multitude of different optimization problems.

The course will help to learn:

How to identify an engineering or other problem

and write it down in the form of a model (or a

system of equations).

How to find and choose appropriate methods for

solving different types of constrained or

unconstrained problems (finding optimal

solutions).

How to deal with combinatorial optimization:

for example, with different graph colorings and

other algorithms using graphs.

Optimization Methods


From sequence of 2D images (video) we determine

1. Shape (geometry). We reconstruct 3D position of

objects in the scene and camera parameters

(motion).

2. Appearance (photometry). We understand why

and how exactly this kind of image was created, as

we have it.

3. Shape + appearance. We recognize objects,

events, biometric properties of people, interpret the

scene, create advanced non-contact user

interfaces...

Computer Vision

Capture of scene(video)

3D shape

Girl is smiling


1. Virtual machines and OS for distributed environments. We understand a difference between

classical OS and OS for distributed environments.

Hypervisor of type 1 or 2, what is more appropriate

for us? Mobile virtualization, but does this also exist?

2. OS for mobile devices and real-time OS. Have

they something in common? Memory management,

process scheduling, synchronizationare necessary?

3. Protection and security in OS, fault tolerance, performance evaluation. What is mine is not public.

Can computer system run even faster? Everything

revolves around availability and usability.

Virtual Machines and Computer

Resource Management

Virtualize:yes or np?

Special OS

Must like this?


"To measure is to know.„ Lord Kelvin

Why? User expectations are increasing, products are becoming more and more complex, more and more tools are available, developers need to be more agile, quality is part of the product, security is becoming more and more important ...

How? We measure, test, optimize, increase reliability, build fault resistant systems, use modern tools ...

User satisfaction = Software Quality

Software Quality


RULES, DOCUMENTS AND FORMS

� UM FERI web pagehttps://feri.um.si/en/study/programmes/second-cycle/

� UM web pagehttps://www.um.si/en/Study/about/Pages/default.aspx

Course descriptions:

� https://aips.um.si/PredmetiBP5/Main.asp?Mode=prg&Zavod=15&Jezik=A&Leto=2018&Nacin=1&Program=BM20


EMPLOYMENT OPTIONS

� Among the most sought professions in the EU

� Among the most promising professions in the EU

� Great job opportunities
