In the paper, we have analysed curricula of the several subjects in lower grades of the primary school in Republika Srpska. Blum's taxonomy was used in the analysis (cognitive and psycho-motor area) and SMART system of evaluating learning outcomes. There have been three subject areas included (the world around us, speech, expression, crating and rhythm, sport and music), in the first grade ten subjects (Serbian, Mathematics, Natural and Social Sciences, etc.), and pedagogical work with the class, which are being studied from the second to the fifth class. The aim of the analysis was to determine knowledge and skills which students should gain in the lower grades of the primary school. We have achieved this aim by determination of the outcomes adequacy based on the above stated criteria, levels of knowledge and skills, which are required, as well as estimation of how much each teaching unit requires certain level of students' knowledge and whether there is the trend of more requirements when passing one grade and entering the other. The results of the analysis show that students are required the lowest level of understanding and gaining (on average 60% of outcomes are on this level), and higher levels require only application (about 15%). This relation varies, depending on the subject. When we talk about skills, they are at the level of precision, and this is sufficient for this age. The rising requirements for students, through learning outcomes have not been observed, because from grade to grade the outcomes are on the same level. This means that we do not work sufficiently at the quality improvement, but on quantity improvement of knowledge.

Evaluation of electric fields induced in the patient during body rotations in the static magnetic field of a MRI-LINAC system Adnan Trakic, Limei Liu, Hector Sanchez Lopez, Luca Zilberti, Feng Liu, Ewald Weber, and Stuart Crozier The School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, QLD, Australia, Divisione Elettromagnetismo, Istituto Nazionale di Ricerca Metrologica, Torino, Italy

The main purpose of this paper is to present the finding of a research into modern management tools usage in companies in Bosnia and Herzegovina, in the climate of economic downturn. In trying to reduce uncertainty of business conditions in recession, and to create a sustainable competitive advantage, the necessity of an adequate response to changes and challenges for companies through the usage of management tools is gaining momentum. In this paper, we have presented research results of modern management tools usage and the level of satisfaction for companies that are operating in Bosnia and Herzegovina, in the context of financial crisis and economic downturn, and against the backdrop of the set targets of these companies. Results stem from a survey conducted among 46 executives in companies of all sizes, sectors, forms of organization and ownership. Regarding practical implications, the paper points to the usage of modern management tools in companies, following the global trends of tried-and-true management tools, positively correlated with the satisfaction coming from their implementation. We must emphasize that companies in Bosnia and Herzegovina are focusing more on usage of management tools that are promoting improved customer relationship management and customer segmentation, in the climate of persistent economic downturn. We believe that building stronger management capacities is under way for companies doing business in Bosnia and Herzegovina, as well as the implementation of some new data management tools. In this process of implementing new tools, additional managerial training of the staff is needed, which is supported by our survey findings.

It is well known that the process of tuning a fuzzy logic controller is almost always a very complex task, which is time consuming, very laborious and often requires expert knowledge of the controlled system. Mapping of fuzzy logic controller's parameters (rule base and membership functions of input(s) and output(s)) into a performance measure in a closed analytical form is near impossible to get, and thus the use of any classical optimization method is automatically ruled out. Knowing this, genetic algorithms with a fitness function in a form of cumulative response error represent a good choice of the optimization method. This approach enables the use of offline optimization of membership functions' parameters (which are being coded into chromosomes). Sugeno-Takagi fuzzy logic controllers with a proportional and a derivative component, and also with a fixed rule base are used in this approach. Experimental results of both simulations and validations on real systems are given in this paper and they show the good performance of this approach.