Code. BIS43 Lessons per week: L 2 hours; Labs 2 hour

Transcription

1 Name of the course Computer networks and network administration Lectures and Labs Code BIS43 L 2 hours; Labs 2 hour Semester: 7 Number of credits: 5 Assoc. Prof. PhD. Eng. Pavlinka G. Radoyska, pradoiska@abv.bg COURSE STATUS IN THE CURRICULUM: Compulsory for students of specialty "Informatics and software science" at the Faculty of Mathematics and Informatics degree "Bachelor" at Technical University Sofia. AIMS AND OBJECTIVES OF THE COURSE: Getting to know the basic principles of network communications, network protocols, network mediums, principles of the network devices operations and the different types of addresses. Building skills on configuration principles of intermediate and end network devices, monitoring and documentation of their operations, troubleshooting. DESIRIPTION OF THE COURSE: Computer networks are considered in the context of OSI and TCP / IP model. Covered are basic network protocols (format of messages and algorithm of work); physical and logical addressing and principles of construction of the addressing schemes; types of transmission media. Students learn the principles of operation of intermediate network devices, their configuration technology for building and managing local and virtual networks, configuration and management of routing protocols. PREREQUISITES: Basic knowledge in computers and good skills in using Internet resources are required. TEACHING METHODS: Lectures by multimedia presentations and discussions on some problems and troubleshooting approaches. Labs that include: current web-based tests; practical exercises on network simulator under the guidance of assistant. Training materials - full lectures, tests and assignments for practical exercises are published in a special training course in system for web-based training. METHOD OF ASSESSMENT: Form of control is a "exam". Students grades are calculated based on the grades of intermediate tests, weight 40% and a final test, weight 60%. INSTRUCTION LANGUAGE: Bulgarian BIBLIOGRAPHY: [1] P. Radoyska, course on Computer Network, Bulgarian); [2] Debra Litaldzhon Shindar, Computer Networks, SoftPress, 2003 (in Bulgarian); [3] K. Boianov, Ch. Turlakov Dim. Todorov, L. Boianov, Vl. Dimitrov, PEF. Zheliazkov Principles of computer networks. INTERNET. Apiinfotsentar Kotlarski, 2003 (in Bulgarian); [4] Microsoft Corporation, TCP/IP Training, SoftPress, 2005(in Bulgarian); [5] Cisco Networking Academy, Introduction to Networks Course Booklet, Cisco Press, 2013; [6] Troy McMillan, Cisco: Computer networks basics, AleksSoft, 2016 (in Bulgarian)

2 Name of the course: Software Design and Integration Code: BIS44 Semester: 7 Number of credits: 6 Lectures, laboratory work, course work L 2 hours, LW 2 hours Assoc. Prof. Veska Gancheva (FCST), tel: , vgan@tu-sofia.bg COURSE STATUS IN THE CURRICULUM: Compulsory course for the students of specialty Informatics and Software Science, Bachelor degree programme at the Faculty of Applied Mathematics and Informatics, Technical University Sofia. AIMS AND OBJECTIVES OF THE COURSE: The objective of the course is to provide students with the knowledge and skills for software design and integration as a practical course and basic knowledge about the methods and tools for design, development and integration of software. The whole process of software development - from the technical assignment, design, programming, integration, testing, deployment and maintenance is being studied. : Students get acquainted with basic concepts of software project, life cycle of the software product, and management of software process. Topics related to development process; modeling of structure, content and behavior; engineering, validation and management of requirements; methods and tools for designing and integrating software systems are discussed. Methods and tools for software production; software reuse; critical, embedded, distributed and real-time systems are studied. The curriculum is illustrated by appropriate programming practice for solving tasks related to designing and integrating software. PREREQUISITES: Basic knowledge in Object Oriented Programming, Information Systems, and Operating Systems. TEACHING METHODS: Lectures, delivered by using demonstration materials in electronic format, presented within multimedia environment; Laboratory practice, case studies and application demos, carried out in a networked computer laboratory with appropriate software installed. Learning resources are provided to the students by means of a content management system. METHOD OF ASSESSMENT: Exam on theory and practice. INSTRUCTION LANGUAGE: Bulgarian. BIBLIOGRAPHY: 1. Erik Klimczak, Design for Software: A Playbook for Developers, 1st Edition, John Wiley & Sons, Gregor Hohpe, Bobby Woolf, Enterprise Integration Patterns: Designing, Building, and Deploying Messaging Solutions, Addison Wesley, Boyd L. Summers, Effective Methods for Software and Systems Integration, CRC Press, T. Erl, SOA Design Patterns, Prentice Hall, Kenneth S. Rubin, Essential Scrum: A Practical Guide to the Most Popular Agile Process, Addison-Wesley Signature Series, Craig Larman, Applying UML and Patterns: An Introduction to Object- Oriented Analysis and Design and Iterative Development, 3rd ed., Pearson Education, Mike Cohn, Succeeding with Agile: Software Development Using Scrum, Addison-Wesley Signature Series, Hassan Gomaa, Software Modeling and Design: UML, Use Cases, Patterns, and Software Architectures, Cambridge University Press, Scott Millett, Nick Tune, Patterns, Principles, and Practices of Domain-Driven Design, 1st Edition, John Wiley & Sons, 2015.

3 Name of the course Numerical Methods for Differential Equations Lectures, seminars, selftraining Code: BIS45 Term: 7 L - 2 hours; S 2, selftraining 6 Number of credits: 6 Prof. Michail Todorov, PhD in Mathematics, Dept of Applied Mathematics and Informatics (FAMI), phone , mtod@tu-sofia.bg, homepage: COURSE STATUS IN THE CURRICULUM: Compulsory subject for the regular and correspondence students in Faculty of Applied Mathematics and Informatics by the Technical University of Sofia, subject Computer and Software Science concerning the educational and qualification degree Bachelor AIMS AND OBJECTIVES OF THE COURSE: The topics under consideration have an applied trend and are inseverably bound with the modern engineering teaching. The teaching in Numerical Methods for Differential Equations seeks after both the acquiring of the mathematical tools and successful applying them to treatment of concrete енгинееринг problems. : Topics of the following parts of mathematics are considered: Math Biology, Ecology, Econometry, Differential and Integral Conservation Laws, Fourier Method and Wave Phenomena, Parabolic Equations and Heat Processes, Elliptic Equations, Harmonic Functions, Potential Theory, Preliminaries and Examples of Nonlinear Nonintegrable Dynamical Systems, Numerical and/or Analytical approach: integrability-nonintegrability, correctness-regularization, conservation-dissipation, stability-blow-up, explicit or implicit schemes, coordinate and splitting by physical factors, ADI methods as a tool for multidimensional problems, orthogonal and inclinegonal bases and transformations PREREQUISITES: Knowledge from the higher school is required. TEACHING METHODS: The lectures and group seminars at a black board in the classical manner are presented. The instructor shares the concept about joining of the lectures and seminars. The best assistant is the instructor. The instructor is open to implement other advanced ways of teaching according the student interest. METHOD OF ASSESSMENT: Written exam in the end of the term preceded by two midterm exams. The assessment is according a formula. INSTRUCTION LANGUAGE: Does not matter Bulgarian or English BIBLIOGRAPHY: The students use their lecture and seminar notes. They are allowed to use any manuals and textbooks appointed by the class instructor

4 DESCRIPTON OF THE COUSE Name of the course: Big Data Analytics and Knowledge Data Discovery Code: BIS49 Semester: 8 Lectures and laboratory work L 2 hours, LW 2 hours Number of credits: 3 Prof. Dr. Eng. Plamenka Borovska (FAMI), Tel: , pborovska@tu-sofia.bg, Faculty of Applied Mathematics and Informatics, COURSE STATUS IN THE CURRICULUM: Compulsory for the students of Faculty of Applied Mathematics and Informatics (FAMI),, specialty "Informatics and Software Sciences", Bachelor Degree. AIMS AND OBJECTIVES OF THE COURSE: The aim of the course is students to get acquainted with the concepts and characteristics of Big data and Big data streams as a new frontier for innovation, competitiveness and productivity in the digital era, as well as with the challenges, methods and algorithms for Big data analytics and knowledge data discovery (KDD). At the end of their training, students will acquire knowledge and skills to work with high-tech platforms and ecosystems to analyze Big data and gain experience in working in a real experimental working research environment. : The course studies the essence and characteristics of Big data, the Big data ecosystem, as well as methods and algorithms for knowledge data discovery based on rules and models. The methods and techniques for building up computational workflows for data analysis are presented, incuding data preprocesing, knowledge discovery and post-processing, encompassing results visualization and interpretation as well as assessing the interest and significance of the knowledge discovered. Intelligent decision-making methods are studied. PREREQUISTES: applied computational intelligence, synthesis and analyses of algorithms, applied programming in Java, etc. TEACHING METHOODS: Lectures are supported by multimedia, laboratory work and class discussions. Laboratory work consolidates the lecture material. METHOD OF ASSESSMENT: Ongoing control over the semester with computer tests via the electronic learning platform and individual assignments. INSTRUCTION LANGUADGE: Bulgarian. BIBLIOGRAPHY: 1. Lecture presentations and labs instruction manual in Big Data Analytics and Knowledge Data Discovery on the moodle e-learning platform http//:borovska.com 2. M Chen, S. Mao, Y. Liu, Big Data: A Survey, Springer Science+Business Media New York 2014.

5 Name of the course: ROBUST CONTROL OF INFORMATION SYSTEMS Lectures and laboratory work, exam Code: BIS50 Semester: 8 L 2 hours; LW 2 hours Number of credits: 3 LECTURERS: Prof. D.Sc. Emil K. Nikolov (FA), tel.: , Technical University of Sofia; еmail address: nicoloff@tu-sofia.bg ; Assoc. Prof. PhD Nina G. Nikolova (FA), tel.: , ; еmail address: ninan@tu-sofia.bg; Assoc. Prof. PhD Vesela A. Karlova (FA), tel.: , ; еmail address: vaks@tusofia.bg COURSE STATUS IN THE CURRICULUM: Compulsory for the students specialty Informatics and Software Science programme of the Faculty of Applied Mathematics and Informatics in educational-qualification degree bachelor. AIMS AND OBJECTIVES OF THE COURSE: At the end of the training students are expected to be able to apply the methodology of fractal operators for integration and differentiation and their approximations in the algorithms for the management of information systems, using methods for analytical synthesis of: QFT (Quantitative Feedback Theory), FDM (Frequency Domain Methods), RMM (Robust Model Matching Methods); TGFC (Theory of Generalized Fractional Calculus). : main themes - the theoretical foundations of integral transformations, theory of generalized fractional calculus and their applications in robust control of information systems PREREQUISITES: Control Theory, Industrial Automation, Logic Control, Multivariable Control Systems, Theory of Fractional Robust Control Theory. TEACHING METHODS: Lectures, using slides, case studies, laboratory work, work in teams, protocols and exam METHOD OF ASSESSMENT: Two one-hour assessments at mid and end of semester (80%), laboratories (20%), exam INSTRUCTION LANGUAGE: Bulgarian 1. BIBLIOGRAPHY: 1. Трендафилов И., E. Николов, Г. Венков, Л. Цоков (2010), Приложения на математиката в инженерните науки 1, Sofia 2011, 2011 Издателство на Технически Университет-София, ISBN , 258 р.; 2. Николов E. (2010), Робастно Фрактално Управление (предиктивни и алгебрични методи; системи с разпределени параметри), София 2010, 2010 Издателство на Технически Университет-София, 2010, ISBN , 375 р.; 3. Николов E. (2006), Робастни системи (приложни методи за управление на технологични процеси - II част), София 2006, 2006 Издателство на Технически Университет-София, ISBN , 144 p.; 4. Весела А. Карлова-Сергиева (2013), Проектиране на системи за управление с гарантирано качество, 2013 Издателство на Технически Университет-София, ISBN ,163 стр.; 5. Николов E. (2015), Фрактално управление - част 2 (приложения на оператори от обобщеното дробно смятане в системите за управление, филтри), Sofia 2015, 2015 Издателство на Технически Университет-София, ISBN , 198 р.; 6. Николов E. (2016), Фрактално управление - част 3 (анализ на качеството при априорна неопределеност), София 2016, 2016 Издателство на Технически Университет-София, ISBN , 260 р; 7. Николов E. (2004), Специални математически функции и фрактални оператори, София 2004, 2004 Издателство на Технически Университет-София, ISBN , 2004, 108 p; 8. Николов E. (2004), Фрактални алгоритми и режекторни регулатори, София 2004, 2004 Издателство на Технически Университет-София, ISBN , 2004, 208 p.; 9. Nikolov E., D. Jolly, N. Nikolova, B. Benova (2006), Commande Robuste, Sofia 2006, 2006 Publishing House of Technical University of Sofia, 2006, ISBN , 216 p; 10. Сапунджиев Г. (2005), Информационни системи в индустрията, София 2005, 2005 Издателство на Технически Университет-София, 180 стр