Pattern Recognition in Situation Awareness Systems

Major: lnformation Systern and Technologies
Code of subject: 8.126.00.M.028
Credits: 3.00
Department: Information Systems and Networks
Lecturer: prof Yevhen Burov
Semester: 4 семестр
Mode of study: денна
Мета вивчення дисципліни: The purpose of studying the discipline is to form young scientists' system knowledge in the field of information technology with a specialty in system analysis, to develop philosophical and linguistic competences, to form universal skills of a researcher, sufficient for conducting and successfully completing scientific research and further professional and scientific activities for building systems with situational awareness .
Завдання: The study of an academic discipline involves the formation and development of competencies in graduate students: general: - ability to abstract thinking, analysis and synthesis; - knowledge and understanding of the subject area and understanding of the profession; - the ability to communicate in the state language both orally and in writing; - the ability to communicate in a foreign language; - skills in using information and communication technologies; - the ability to conduct research at the appropriate level; - the ability to learn and master modern knowledge; - the ability to search, process and analyze information from various sources; - ability to adapt and act in a new situation; - ability to generate new ideas (creativity); - the ability to identify, pose and solve problems; - the ability to make informed decisions; - ability to work in a team; - the ability to communicate with representatives of other professional groups of different levels (with experts from other fields of knowledge/types of economic activity); - the ability to work in an international context; - ability to develop and manage projects; - the ability to work autonomously. professional: - the ability of a flexible way of thinking, which makes it possible to understand and solve problems and tasks of pattern recognition, while maintaining a critical attitude to established scientific concepts; - the ability to use in-depth theoretical and fundamental knowledge in the field of system analysis to solve complex problems of building systems with situational awareness; - the ability to formulate, analyze and synthesize solutions to scientific problems at an abstract level by decomposing them into components that can be investigated separately in their more and less important aspects; - the ability to communicate with colleagues from this area regarding scientific achievements, both at the general level and at the level of specialists, the ability to make oral and written reports, discuss scientific topics in native and English languages
Learning outcomes: 1. Possession of in-depth professional knowledge and practical skills for solving complex problems in the field of information technologies and system analysis in particular. 2. The ability to demonstrate systematic knowledge of modern research methods in the field of building autonomous intelligent systems. 3. Ability to demonstrate in-depth knowledge in the field of scientific research - pattern recognition in systems with situational awareness; 4. The ability to demonstrate an understanding of the impact of technical solutions in a public, economic and social context.
Required prior and related subjects: Distributed information systems and technologies
Summary of the subject: Within the scope of the discipline, the issues of defining systems with situational awareness, models of such systems, JDL framework, use of ontologies and logical derivation in systems with situational awareness are considered; use of pattern recognition methods in such systems; methods of classification and clustering; use of Bayesian theory in pattern recognition tasks; teaching systems with and without a teacher; methods of grouping; use of neural networks for pattern recognition; structural pattern recognition.
Опис: Main definitions and models of systems with situational awareness General characteristics of the problem of pattern recognition in systems with CO. Methods of classification and clustering Bayesian decision theory in recognition tasks Evaluation of parameters and training with a teacher Non-parametric methods Linear separating functions Learning without a teacher and grouping Analysis of scenes Analysis of spatial frequencies Using neural networks for pattern recognition Structural pattern recognition
Assessment methods and criteria: Current monitoring of practical, seminar classes is carried out in order to identify the graduate student's readiness for classes in the following forms: • a selective oral survey before the start of classes; • assessment of the graduate student's activity in the course of classes, submitted proposals, original solutions, clarifications and definitions, additions to previous answers, etc. • the result of a graduate student's defense of laboratory work Control questions are divided into: • a) test tasks – choose the correct answers; • b) problematic – creation of problematic situations; • c) situational tasks – to determine the answer according to a certain situation; • d) issues of a reproductive nature - determination of practical significance; The final control is carried out based on the results of the current control and performance of the control work.
Критерії оцінювання результатів навчання: Current control - 50 points, exam - 50 points.
Recommended books: Базова 1. Дуда Р. Распознавание образов и анализ сцен./ Р.Дуда, П.Харт.- М.:Мир, 1976.-C.507. 2. Marques de Sa. Pattern Recognition. Concepts, methods and applications./ Marques de Sa.- Springer, 2001.- P.328. 3. Grenander U. Pattern theory:from representation to inference./ Grenander U, Miller M.- Oxford university press, 2007.- P. 609. 4. Закревский А. Логика распознавания./ Закревский А.Д.-Минск:Наука и техника, 1988.-С. 119 Допоміжна 1. Salerno J. Building a Framework For Situation Awareness./ Salerno J, Hinman M., Boulware D./ Proc. of 7th International Conference Of Information Fusion, 2004. 2. Farahbod R. Integrating Abstract State Machines and Interpreted Systems for Situation Analysis Decision Support Design./ Farahbod, Roozbeh, Uwe Glasser, Eloi Bosse, and Adel Goutouni//Prioc of the 11th International Conference on Information Fusion, 2008. 3. Baumgartner N. A Software Architecture for Ontology-Driven Situation Awareness./ Baumgartner, N;W.Retschitzegger, W.Schwinger//Proc. of the 23rd Annual ACM Symposium on Applied Computing, 2008. 4. Durso, F. Comprehension and Situation Awareness/ Durso, Francis T., Katherine A. Rawson, and Sara Girotto //Handbook of Applied Cognition, Second Edition.- John Wiley & Sons Ltd, 2008