"System design" master's degree training program

1. General description

The new specialty 8.06010301 «System design» is included to the direction 6.050101 «Computer sciences» of specialists training and is affined with the specialty 8.06010201 «Information technologies of design». It embraces the stage of the preliminary design, when the possible requirement specification is formed, based on the analysis of data flows of the future system and its purpose, research of its function, and selection of the efficient algorithms. 

The system design is interdisciplinary methodology of construction of the intellectual environments intended for solving the tasks of research and design of complex objects (systems, processes) of different physical nature by computer tools and with active involvement of people (experts, analysts, engineers, researchers, designers etc).

A system design specialist engages in the solving of wide spectrum of tasks, related to the collection of useful data to reach the goal, the analysis of that data, the construction of methods and models of processing that data, the development of variants of structures and architectures of complex objects and the selection of optimal project decisions that will realize a design aim.

The objects of research in the system design are various objects of the category of the complex systems and processes. They are: information environments (for example, distributed computer systems, semantic Web and Grid), objects of scientific researches of other domains (for example, space or biological objects), complex technical systems (for example, integrated electronic circuits or the hybrid integrated electronic-mechanical systems), ecological systems, technological or business processes and others like that. Thus, the results of the system design in some cases can be represented as the concrete project technical decisions, and in another cases - as certain generalizations, predictions or recommendations based on the collection and processing of large volumes of data and its mining with the use of the automated computer tools.

System design, as well as the system analysis, is aimed on research of the complex systems and processes, with their design requiring complex approach with the use of mathematical methods, computer technologies, and also interaction between experts (or analysts, in other words - researchers) and computer systems. Unlike the system analysis with the primary objective of problem solving by making decisions on the basis of mathematical methods of research, the primary objective of the system design is the use of computer tools for the solving of tasks, related to development or data-intensive research. Thus, both the system analysis and the system design can be considered as disciplines that mutually complement one another and aimed at the analysis, research and design of the complex systems.

As long as the main tools of the system design are the distributed computer systems, that help to gather and analyze useful data (as the basis of decisions to be generated), thus, the main components of all system design procedures are the discovery and  intelligent processing of data in computer networks. A modern scientific equipment and computer modeling are the sources of large volumes of data requiring the powerful computing  resources and new scientific methods of data analysis and organization. First of all this is actual for Earth sciences (satellite research of Earth), medicine, high energy physics, life sciences, "green" energy, nanotechnologies and others.  The data is geographically distributed usually, as well as the scientists that cooperate in the achieving their goals. The volumes of data are doubled, approximately, every year.  In 2009 the volume of 40 exabytes (еxabyte=1E18) of data was generated. Unfortunately, all presently existing data storages are unable to store such large volumes.

The data management is based on the use of software and hardware, that  provide  the preprocessing of «raw» data, its archiving and maintenance, discovery and comprehensive intelligent analysis. Therefore one can distinguish four different types of related technologies data assimilation, data storing, high-performance computing and intelligent data processing (knowledge discovery). Modern science (electronic science = е-science) deals with processing of potentially enormous volumes of information regardless of its geographic location and requires the high-intensive complex calculations as well as the effective communication and collaboration of scientists during their research. Taking into account the limited nature of resources that exists in any society, the only way to satisfy these modern requirements is coordinated resource sharing. It is necessary to provide access for scientists and specialists of different organizations and countries to existing computers, data storages, applications, devices, networks, taking into account the variety and heterogeneity of these resources within the limits of the distributed computing environment. 

Therefore nowadays the need for the new kind of specifically trained specialists is very urgent. Their training would include such directions as:

  • System adjustment of different kinds of data, data interoperability, semantic definition of data.
  • Languages and systems of knowledge representation. Properties of knowledge. Models of knowledge representation. Methodology of work with knowledge.
  • Intelligent  technologies  of Data Mining  for knowledge discovery and formalization. Knowledge expansion. An inference from knowledge.
  • Pattern and image recognition. Scene analysis. Machine vision. Machine training. Models of training. Problem solving planning.
  • High-performance computing systems. Distributed data storage and processing systems.
  • Principles of organization and functioning of the distributed intelligent systems. Virtualization tools for grid and cloud resources. Hardware and software. Elementary component basis.
  • Metadata for resource discovery, data exchange and reuse.
  • Semantic web- and grid services. Mathematical methods of the “soft calculations” (neural network calculations, fuzzy logic and other) built on the base of the artificial intelligence methods for the development of the hybrid distributed systems.
  • International standards for the intelligent software environments frameworks development (for example, standards of multi-agent platforms).
  • Modern numerical methods of mathematical modeling and their parallel variants; the application of methods of multi-criteria optimization is with functional and parametric limitations.
  • Tools for intelligent systems development. Tools for distributed data processing systems simulation. Programming languages for the intelligent systems.
  • Multimodal interface of user - computer interaction et al.
  • Applied intelligent systems. Development of the distributed applications for different domains with the use of paradigms of the intelligent programming.

The emergence of such specialty corresponds to a task of an assistance to development of science and technologies in accordance with new calls and priorities of international science,  improvement of scientific and technical management of data and of their use, that is put before the world community by international organization of CODATA (Committee on Data for Science and Technology)  and its International Data Academy (IDA), both coordinated by the International Council for of Science of the UNO.

In Russia there are a few master's degree programs (552819 - Computer analysis and data interpretation, 552822 – Distributed automated systems, 552814 - Methods of analysis and synthesis of project decisions,  552805 - Intelligent systems, 552811 - Databases, 552812  - Multimedia systems and computer graphics, 552821 - Digital signal processing, 552826 -Automated systems of scientific research and integration tests) that deal with the separate aspects of the Ukrainian master's degree program «System design».


2. System design and knowledge engineering

For the same reasons recently in a number of foreign leading institutions of higher education the new master's degree speciality “Data & Knowledge Engineering” was introduced, as a need for fast access to necessary information became an important condition for the successful participating in scientific, economic, cultural and social processes both at work, in affairs with public institutions, at home, in shops and banks, in schools, universities etc. Information can be considered as structured data that have a context meaning. So what is knowledge then? Knowledge is brief representation of information that binds together structured data and summarizes previous experience at higher level. Knowledge represents general, stable and long-term information in some area, while data express concrete, changeable and brief information. Certainly, information that is consumed contains both data and knowledge in itself. Together they fold the kernel of the intelligent systems.  Knowledge engineering deals with the basic problems of creation of intelligent problem solvers and is an important constituent of the system design.

The «System design» curriculum offers the unique combination of courses of computer sciences, applied mathematics and artificial intelligence to the students. From the computer sciences’ side much attention is paid for software, programming, algorithmization and logic, but not on a hardware. Courses on applied mathematics are worked out so that students could quickly in practice become familiar with important concepts and methods. Artificial intelligence allows logic inferring depending on available knowledge.

System design prepares master's degrees for the successful professional career in modern society in what information and knowledge are central factors. The world scientific community with the help of data and knowledge develops measures and new technologies as an answer to the calls to humanity at the beginning of 21th century: lack of power resources and drinking water, contamination of environment and the change of climate, spreading of diseases, a disbalance between the growing Earth population and ability of producing the sufficient amount of food, a global «informative boom», when the volumes of data to process on computers have reached the petabytes volume. A wide spectrum of possibilities of application of the knowledge and abilities in society (science, ІT, medicine, biology, economy, business management and many other industries) is opened to the specialists of «System design».


3. Involving the students to scientific research and topics of master's degree works

Scientific research of master's degree trainees of the «System design» speciality is conducted on the base of: High-performance computing center of NTUU “KPI” with one of the most powerful in supercomputers in Ukraine connected to the national grid infrastructures of Ukraine and European EGEE; Ukrainian World Data Center branch, connected through the network with similar World Centers in 52 countries of the world; the leading institutes of NASU (ITP, IMBG, IC, IPME, Institute of geophysics etc), where grid technologies are widely used and developed; and joint scientific-educational laboratories of IASA-Samsung (South Korea) and KPI- Melexis (Belgium).

The subjects of master's degrees research projects include:

  • Data preprocessing for the intelligent analysis
  • Automatic knowledge discovery.
  • Methods and tools for grid and web- technologies composition, in particular, web- services and  grid- services.
  • Grid applications for the scientific-technical and socio-economic activities, in particular, for solving the problems of optimal design of the complex technical objects and systems.
  • Tools for data generating, storing and intelligent processing; the use of data in the development of databases in engineering, energetics, meteorology domains etc.
  • Methods for the effective utilization of existing grid resources by means of the data mining; and creation of the pioneer software complex of the automated decision making systems.
  • Grid support for the common master’s training courses in educational establishments of different countries.
  • Semantic grid  for science and engineering. Semantic grid framework for engineering virtual organizations (VO) support.
  • Semantic representation of grid resource and its integration with grid service broker.
  • The grid service interoperability provision on the base of ontologies and their automatic composition.
  • Grid and cloud technologies
  • Grid- infrastructures and their components simulation.
  • Development of ontologies for the information resources of Ukrainian WDC.
  • Geoinformatics grid system.
  • Systems-on-a-chip (SoC) design.



4. Basic and selective disciplines of “System design” mater’s degree training

Semester 9 (25.5 credits)
1. Data discovery and preprocessing
2. Distributed environments for high-performance parallel computing
3. Data mining in distributed environments
4. Functional and logic programming
5. Knowledge discovery in databases
6. Semantic web- and grid services
7. Self-organizing systems
8. Module to choose
9. Module to choose

Semester 10 (23.5 credits)
1. Distributed decision making and logic inference systems
2. Computer vision and 3D modeling
3. Multi-agent systems
4. Expert systems based on fuzzy logic and neural networks
5. Pattern recognition
6. Multimodal user interface
7. Multi-criteria and mini-max optimization methods
8. Module to choose
9. Module to choose

Semester 11 (10 credits)
1. Distributed data processing systems modeling tools
2. Knowledge protection (security and anti-attack countermeasures)
3. IT for business
4. Module to choose
5. Module to choose

Modules to choose:
1. Geographic information systems (GIS)
2. Computer games
3. Embedded systems
4. Bioinformatics
5. Project management
6. Multimedia systems
7. Genetic algorithms and evolution programming
8. Systems-on-a-chip (SoC) design

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