Each semester you can choose one of the following elective courses from the Master's degree programme Energy Informatics. You can also select courses from other Master’s degree programmes in Hagenberg (e.g., MCM, SIS, SE) and in Wels (e.g., SES, AMM, IPM, EE) after consultation with the Head of Studies.
In this course, students will explore how technology can be used to effectively sense and report information about environmental behaviours to promote awareness and enable positive behaviour change. Students will learn the fundamental concepts of human-computer interaction and user-centered design thinking.
The following three modules will be covered: fundamentals and methodology (environmental psychology, user perception and recognition, human performance models, perceptual memory), how to design and prototype (user-centered design, experience design, prototyping, wizard of oz techniques, interactive prototyping tools, physical prototyping), how to evaluate (design evaluation, heuristics, quantitative and qualitative evaluation methods, observe and measure, scales of measurement, experiment design, data analysis).
The main goal of this course is understanding of electric and hybrid car principles, knowing the aspects of environmental impacts and the principles for energy supply, understanding concepts for energy efficiency improvement and load feedback to electrical grids with special respect to smart grids.
The following topics will be covered: types of electrical cars, comparison of electric and combustion engine concepts, dominant energy consumption effects, environmental impact, electrical drives, battery systems, auxiliary consumers in cars and aspects of consumption decreasing, safety aspects, and charging aspects.
The course is aimed to give an overview about different optimization approaches on the basis of which graduates should be able to decide which optimization strategy to choose for a concrete task.
The following topics wil be covered: introduction and basic definitions, taxonomy of optimization methods, examples of optimization problems, heuristic optimization vs. exact methods, motivation and survey of metaheuristic optimization algorithms, trajectory based methods, hill-climbing methods, simulated annealing, tabu-search, population based methods, ant colony optimization (ACO), particle swarm optimization (PSO), genetic algorithms (GA), evolution strategies (ES), genetic programming (GP), and hybrid methods.
Projects should prepare students as realistically as possible for their later professional lives with concrete case studies and consolidate the connection to theoretical teaching content through the independent study of real themes. Team work (2-4 persons) and the capacity for team work should be promoted, as well as individual initiative, the quick assessment of complex situations and flexible reaction in unexpected situations. The project should be assigned to one of courses of the current semester or in addition to the Master’s theses project to the Master’s theses itself. A coach/advisor is assigned to the projects. Immanent project goal is the extraction of a suitable Master’s thesis topic.
Fundamental knowledge of well-tested software design techniques and patterns on the architectural and component side is crucial to develop flexible and maintainable software architecture.
Therefore, this elective course covers the following topics: software architecture design process, process models, software pattern, architectural pattern (layers, pipes and filters, MVC, blackboard etc.), design pattern (builder, factory, command, decorator, strategy etc.), idioms, and anti-pattern.
This course is a step-by-step description of the software metrics. It includes introduction to foundations of measurement theory, models of software engineering measurement, software products metrics, software process metrics and measuring management.
The following topics will be covered: software metrics (e. g., code coverage, kloc, bugs/kloc, cyclomatic complexity, function points, cohesion and coupling), black box and white box testing, unit tests, integration tests, system test, regression tests, testing of non-functional properties, test plans, testing tools, automated testing, testing and the software development process, test-driven development, model-based testing, GUI-testing, UML testing profile, TTCN-3 (testing and test control notation), and certifications.