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Infocommunication Systems Modelling
Major: Hardware and software devices of infocommunication systems
Code of subject: 6.172.10.E.082
Credits: 4.00
Department: Electronics and Information Technology
Lecturer: Hlinenko Larysa
Semester: 6 семестр
Mode of study: денна
Завдання: The study of the course provides for the development of student competences:
general competences:
- GC1. Ability to abstract thinking, analysis and synthesis;
- GC7. Ability to learn and master modern knowledge;
- GC8. Ability to identify, formulate and solve problems
- GCIS. Ability to systematic thinking.
professional competences:
- PC4. Ability to perform computer modelling of devices, systems and processes using universal application software packages;
- PC6.3. Ability to model and optimise telecommunication facilities at different stages of design
Learning outcomes: By the end of the study, learners are expected to:
– know fundamentals of methodology of infocommunication systems modelling, apply the system approach to the modelling
– be able to create and investigate the mathematical models of the of infocommunication systems and their constituents;
– be able to plan and realize computer experiments with models applying modern information technologies;
– be able to apply the acquired modelling skills in the process of analysis and synthesis of the of infocommunication systems and their constituents;
– be able to present modelling results and to substantiate the conclusions while discussing them with other students
As a result of studying the discipline, the student must be able to demonstrate the following programme learning outcomes:
PLO 1. KN C10. Ability to demonstrate knowledge and skills in conducting experiments, data collection and modelling of electronic and telecommunication systems and networks
PLO 2. SC 1. To analyse, argue, make decisions in solving specialised problems and practical problems of telecommunications and radio engineering, which are characterised by complexity and incomplete certainty of conditions
PLO 3. SC 13. Apply knowledge and understanding to solve problems of synthesis and analysis in information and communication systems that are characteristic of the chosen specialisation
PLO 4. SC 14. To think systematically and apply creative abilities to the formation of fundamentally new ideas
PLO 5. AiB2. Ability to recognise the need for lifelong learning in order to deepen acquired and acquire new professional knowledge
Required prior and related subjects: – Higher mathematics, part 1 and part 2
– Programming (with specialisation), part 1 and part 2
– Radioelectronic devices design
Summary of the subject: The course studies the basics of the methodology of modelling technical systems and physical processes that find application in the design and operation of information and communication systems. The essence and general principles of modelling the technical systems; characteristics, stages and tools for building mathematical models are considered. The course includes studying the basics of graph theory and representation of mathematical models as graphs; principles and tools for modelling the physical subsystems of infocommunication systems at the macro level, the fundamentals of building mathematical models based on experimental dependencies as well as the basics of simulation modelling of infocommunication systems as queuing systems.
Опис: 1.Introduction. Subject, purpose and objectives of the course. Technical system (TS) as an object of modelling. Properties of technical systems. Large complex systems. Information and communication systems as a type of large complex TS.
2.Basic concepts and approaches to modelling TS. The concept of model and modelling. Modelling as a way of knowing reality. Model as a structure for storing and acquiring knowledge. Conditions of adequacy and interpretability of the model. Fundamentals of the theory of model building. The main stages of the modelling process. Information reduction in the modelling process. Ways to implement the main stages of model building. Modelling of complex systems. Modelling of software.
3.Representation and methods of model research. Semantics and syntax of models. Methods of TS research in model building (at the empirical, theoretical levels). Classification of models (by syntax and research method). Material and ideal models and their varieties.
4. Fundamentals of building mathematical models. The process of creating a mathematical model. Ways of representing objects in mathematical models, forms of recording. Classification and classification features of mathematical models. Basic requirements for mathematical models and their characteristics: accuracy, efficiency, adequacy, area of adequacy. Acceptable area of model adequacy and methods of its determination.
5.Representation of mathematical models in the form of graphs. Basic concepts of graph theory. Properties and types of graphs. Trees of a graph. Representation of information given by a graph in numerical form. Matrices of incidents, adjacencies, contours and intersections (M-matrix) and rules for their construction.
Computational (mathematical) models of radio electronic devices. The first and second unified forms of structural models, their comparative characteristics.
6.Statistical modelling. Fundamentals of correlation and regression analysis
7. Optimisation problems in the design of information and communication systems. Modelling of optimisation problems as mathematical programming problems and computer support for their solution by Microsoft Excel Solver and ORMM add-ins. Representation of mathematical models of infocommunication systems in the form of graphs. Optimisation problems on graphs
8. Equivalent diagrams of various physical subsystems of information and communication systems. Basic notation, purpose and algorithm of construction for different subsystems, connections between subsystems of different nature.
9. Mathematical model of a deterministic system at the macro level. Basic physical subsystems and their component and topological equations. Analogies between phase variables for different physical subsystems. Component and topological equations of different physical subsystems.
10. Methods of constructing mathematical models at the macro level. Obtaining topological equations based on the M-matrix. Generalised method of building a complete mathematical model at the macro level and its modification
11. Modelling ICS by means of similarity theory and dimensionality
12. Modelling of random processes in complex systems based on the theory of Markov processes Modelling of queuing systems in the class of continuous Markov processes.
Simulation modelling. Simulation model of a queuing system
Assessment methods and criteria: Oral and written examinations while performing and defending practical tasks, control quizzes, testing in the VLE
Критерії оцінювання результатів навчання: – Current control: laboratory reports, individual exercises, oral interviewing, written tests (60 %)
– Final control: control procedure - written and verbal graded test (40 %): written examination (test) - 34 points; oral interviewing (verbal examination) - 6 points
Current control (PC)
Performing laboratory work - 20 points
Performing individual tasks - 19 points
Current (by topic) and intermediate control testing in the GNS - 21 points
Control testing and assignments - 40 points
Total for the discipline - 100 points
Laboratory work is graded on the basis of the accuracy, completeness and self-efficacy of the solutions obtained for each of the tasks:
- the results obtained are correct, complete and self-determined - 100% of the maximum score;
- correct, complete and obtained with significant help and corroboration from the teacher - 90% of the maximum mark;
- the solutions obtained in the work are correct, but incomplete and obtained with significant assistance and corroboration from the teacher - 75% of the maximum grade;
- the results obtained contain mistakes, but the approach to obtaining a solution and the use of tools for obtaining a solution is correct - 50% of the maximum score.
Preliminary and control tests are conducted in a virtual learning environment and the score is given automatically for all test tasks. For the task type "essay" 100% of the maximum score is given in manual mode for a fully correct and complete performance, 85% - overall correct performance with minor errors in calculations; 75% for failure to solve the problem with some mistakes in the solution; 50% - for significant mistakes and incomplete solution based on the correct approach; 30% - for formulation of the correct approach without implementation of the solution.
Порядок та критерії виставляння балів та оцінок: 100-88 points - ("excellent") is assigned for a high level of knowledge (some inaccuracies are allowed) of the educational material of the component contained in the main and additional recommended literature sources, the ability to analyse the phenomena studied in their interconnection and development, clearly, concisely, logically, consistently answer the questions posed, the ability to apply theoretical provisions in solving practical problems; 87-71 marks - ("good") is given for a generally correct understanding of the educational material of the component, including calculations, reasoned answers to the questions posed, which, however, contain certain (insignificant) shortcomings, for the ability to apply theoretical provisions in solving practical problems; 70 - 50 points - ("satisfactory") is assigned for poor knowledge of the educational material of the component, inaccurate or poorly reasoned answers, with a violation of the sequence of presentation, for poor application of theoretical provisions in solving practical problems; 49-26 points - ("not certified" with the possibility of retaking the semester control) is assigned for ignorance of a significant part of the educational material of the component, significant errors in answering questions, inability to apply theoretical provisions in solving practical problems; 25-00 points - ("unsatisfactory" with mandatory re-study) is assigned for ignorance of a significant part of the component's educational material, significant errors in answering questions, inability to navigate when solving practical problems, ignorance of the main fundamental provisions.
Recommended books: 1. Павлиш В.А., Гліненко Л.К., Шаховська Н. Б. Основи інформаційних технологій: підручник. Львів: Видавництво Львівської політехніки, 2018. – 620 c.
2. Пасічник В.В., Виклюк Я.І., Камінський Р.М. Моделювання складних систем. Л.: Новий світ-2000. -404 с.
3. Гліненко Л.К., Сухоносов О.Г. Основи моделювання технічних систем. - Навчальний посібних для студентів вузів технічних спеціальностей. - Львів: “Ніка-ПЛЮС”. - 1999. - 204 с.
4. Томашевський В.М. Моделювання систем. Підручник для студентів ВНЗ. – К.: Видавнича група BHV. – 2007. – 352 с., іл
5. Стеценко, І.В. Моделювання систем: навч. посіб. [Електронний ресурс, текст] / І.В. Стеценко ; М-во освіти і науки України, Черкас. держ. технол. ун-т. – Черкаси : ЧДТУ, 2010. – 399 с.
6. Павлиш В.А., Гліненко Л.К. Основи інформаційних технологій і систем: навч. посібник / В.А.Павлиш, Л.К. Гліненко. - Львів: Видавництво львівської політехніки, 2013. - 500 с.
7. Математичне моделювання телекомунікаційних систем та мереж: навчальний посібник. / Є.М. Чернихівський — Львів: Видавництво Львівської політехніки, 2011. — 272 с.
8. Методи оптимізації і дослідження операцій: Навч. посіб. для студ. вищ. навч. закл. / Н. О. Гончарова, А. І. Ігнатюк, Н. А. Ма лиш та ін. — К.: МАУГІ, 2005. — 304 с.
9. Гунько С. Особливості використання табличного процесора Microsoft Excel для статистичного аналізу емпіричних даних //С.Гунько // Науковий вісник Східноєвропейського національного університету імені Лесі Українки. – 2014. - № 8. – C. 41-44.
10. http://vns.lpnu.ua/course/view.php?id=5413
11. http://science.lpnu.ua/mmc Сайт журналу Mathematical Modeling and Computing
12. https://www.journals.elsevier.com/applied-mathematical-modelling Сайт журналу Applied Mathematical Modelling
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