Daniela Borissova

A conceptual approach for development of educational Web-based e-testing system

Abstract The paper describes a conceptual approach for development of educational Web-based e-testing system. The system aims to improve the effectiveness of the learning process by providing features for flexible adjusting of the testing process. The tutors and learners can interact with the e-testing system by choosing different options for testing – easy questions, advanced questions, sequential or shuffle order, random generated questions within given range. The e-testing system can be used by students for self-testing or by tutors for official examination. When used for official examination the test results information is sent to the examiner by e-mail. The system files are stored on the server-side and are accessible through Web-browser. A prototype of e-testing system illustrating the proposed approach is developed by means of HTML and JavaScript languages. It was used for “ C Programming Language ” course students self-testing and official examination. The experimental results demonstrated that the implementation of the proposed approach is quite helpful to facilitate the understanding and implementation of teachers’ attitudes toward Web-based e-testing tools application.

Wind Park Layout Design Using Combinatorial Optimization

The energy sector has essential influence on climate change and atmospheric pollution. Wind energy, being a clean and renewable energy, can greatly contribute to decreasing of the air pollution negative impacts. Generally speaking, the production of renewable energy from wind can have a positive socioeconomic benefit – it not only help to reduce the climate changing but also support meeting of the long-term world economical goals. Taking that into account, many countries are encouraging the building of industrial wind parks. The building of a wind park is an expensive and complex task involving a wide range of engineering and scientific knowledge. The design of a wind park can have profound implications for its future profitability. Sustainable wind park development has to be done in an ecological way which means evaluating of the all possible positive and negative influences on the environment. The development of new wind energy projects requires also a significant consideration of land use issues. One of the most important factors in selecting a wind energy site is the availability of proper wind resources. The wind itself is a variable source of energy. The ability of a wind turbine to extract power from varying wind is a function of three main factors – the wind power availability, the power curve of the generator, and the ability of the turbine to respond to wind fluctuations (Ustuntasa & Şahin, 2008). Wind turbines are available in various sizes and power output. They are designed to operate over a range of wind speeds (3-25 m/s) and can be erected singly by an individual property owner or grouped together to form a wind farm (wind park) connected to a public grid (Rodman & Meentemeyer, 2006). The common challenge for the wind park designer is to maximize the energy capture within the given restrictions (White et al., 1997; Kusiak & Song, 2010). As there is pressure to build more compact wind farms to optimize land utilization, an determination of array losses for very close turbine spacing is required (Smith et al., 2006). The investigations on wind energy using essentially cover four principal topics (Ettoumi et al., 2008). The first one deals with the sensors and instrumentation used for wind measurements. The second one examines the evaluation of wind energy potential for a given region using various statistical approaches. The third is focused on the design and characterization of wind energy turbines. The fourth is the design and development of wind parks. The results of investigations in those areas are used by wind park planners to develop cost-effective wind parks.

An intelligent approach to optimal predictive maintenance strategy defining

The rapid growth of industries has complicated the systems functioning and has intensified the maintenance process. This emphasizes the need for effective maintenance planning. The improvement in maintenance technology relies on predictive maintenance, which is based on the determination of a machine condition while in operation. Maintenance planning is complex problem involving condition monitoring and expert knowledge. In the paper, an intelligent approach to optimal predictive maintenance strategy defining is proposed. It is based on methodology for predictive maintenance that increases reliability by determining the optimal maintenance strategy. For the goal, an algorithm based on cost-benefit analysis and optimization tasks solution is developed. The proposed approach to optimal predictive maintenance is demonstrated on the example of real vibrating feeder data. The results of numerical illustration show the applicability of intelligent decision making for optimal predictive maintenance strategy defining.

Approaches for diagnostic and predictive maintenance

Approaches to diagnostics and predictive maintenance of technological equipment are presented in the paper. Different techniques are analyzed using intelligent approaches to fault diagnosis. Results from application of passive and active thermography are presented. Active thermography is acknowledged as one of the most powerful tools for nondestructive control to localize cracks and defects in depth like metals, composite materials and polymers. An original stand for active thermography for defect localizations in the volume of the research sample – material or a detail is shown. The communication between the researcher and the controlling software is realized by the elaborated specialized humanmachine interface.

Business Intelligence System via Group Decision Making

Abstract In the paper a business intelligence tool based on group decision making is proposed. The group decision making uses a combinatorial optimization modeling technique. It takes into account weighted coefficients for evaluation criteria assigned by decision makers together with their scores for the alternatives in respect of these criteria. The proposed optimization model for group decision making considers also the knowledge level of the group members involved as decision makers. This optimization model is implemented in three-layer architecture of Web application for business intelligence by group decision making. Developed Web application is numerically tested for a representative problem for software choice considering six decision makers, three alternatives and 19 evaluation criteria. The obtained results show the practical applicability and effectiveness of the proposed approach.

A COMBINATORIAL OPTIMIZATION RANKING ALGORITHM FOR REASONABLE DECISION MAKING

The focus of the paper is on a quantitative decision making strategy that could underline the decision making process. A decision making model based on multicriteria optimization and devices ranking algorithm are developed. This approach could be used to support the reasonable choice making in many real life problems when a variety of alternatives and conflicting user requirements exist. The algorithm is numerically illustrated and its applicability is demonstrated on the example of real mobile phones data for three different scenarios of user preferences.

Group Decision Making for Selection of Supplier Under Public Procurement

The article deals with problem of group decision making for selection of supplier under public procurement. For the goal, a generalized algorithm for multi-attributes group decision-making is proposed. The distinguish feature of the described algorithm is consideration of knowledge and experience of each expert from the group by using of weighted coefficients. Simple additive weighting and weighted product model are modified to cope with the differences in experts’ knowledge and experience. The applicability of proposed group decision making algorithm is illustrated by using of new modified utility functions for simple additive weighting and weighted product model. The numerical testing considers a real-life problem for selection of the most preferable supplier of personal computers under a public procurement. The results demonstrate the flexibility of proposed approach when using a group of experts with different expertise.

Combinatorial Optimization Model for Group Decision-Making

Abstract In the article a combinatorial optimization model for group decision-making problem is proposed. The described model relies on extended simple additive weighting model. A distinctive feature of the proposed model is consideration of the importance of experts’ opinions by introducing weighted coefficient for each of experts. This allows flexible adjustment of differences in knowledge and experience of the group members responsible to determine most preferable alternative to be achieved. The numerical application is illustrated by an example for software engineering adopted from D. Krapohl. The obtained results show the practical applicability of the proposed combinatorial optimization model for group decision-making.

A Framework for Development of e-learning System for computer programming: Application in the C programming Language

This paper describes a framework for development of e-learning system for computer programming. The proposed framework includes not only the necessary course materials and the corresponding tests and exercises, but also offers an integrated environment to test written programming codes. The described approach corresponds to recent trend in distance education by providing massive open online course for unlimited participation and accessible through the Internet. The modern capabilities of ICT and database are integrated to support the learning process in a user friendly environment. The functionality of the e-learning framework is composed of five basic modules for learning content, testing, exercises, questions and answers, and help module. The described framework is implemented in developed e-learning system for C programming language. The e-learning system was tested in real educational environment and was very well accepted both of students and teachers. The preliminary results show applicability of the system leading to improvement in the acquired knowledge and C programming skills. This was confirmed by decreasing the number of students failed on the C programming exam.

A Two-Stage Placement Algorithm with Multi-Objective Optimization and Group Decision Making

Abstract Atwo-stage placement algorithm with multi-objective optimization and group decision making is proposed. The first stage aims to determineaset of design alternatives for objects placement by multi-objective combinatorial optimization. The second stage relies on business intelligence via group decision-making based on solution of optimization task to makeachoice of the most suitable alternative. The design alternatives are determined by means of weighted sum and lexicographic methods. The group decision making is used to evaluate determined design alternatives toward the design parameters. The described algorithm is used for wind farm layout optimization problem. The results of numerical testing demonstrate the applicability of the proposed algorithm.