Mathematics lectures could be very challenging task for the both, teachers and pupils, since there are large education material which should be acquired throughout 1 year. Therefore there is need to improve the lectures in order to make it more interesting and attractive for pupils especially. In order to find a way how to improve the lectures, there is need to make statistical analysis in order to detect which factors are the most dominant for the mathematics lecture performance. For such a purpose, in this study soft computing approach, namely, adaptive neuro fuzzy inference system (ANFIS) was used. The ANFIS should determine what the qualitative influence of the several factors on the mathematics performance is. The results confirm that the application for education software could produce the best results in mathematics lecture.
E‐learning, as a complex system, includes distance learning, teaching materials in various forms and shapes, group and individual learning processes, as well as interactive and tutorial work. To increase the effectiveness and efficiency of the e‐learning system, it is necessary first of all to consider the characteristics of students and their learning styles. Based on the data collected in various ways, in surveys, using the distance learning dystem (DLS) Moodle, based on the subjective assessment of the subject teachers, as well as based on data from the business information system, the student preferences are determined. Then, based on these data, an adaptation is made, a process that adapts the work of the DLS based on student knowledge. The primary goals that can be achieved through the adjustment of the e‐learning system are to improve the design and usefulness of the course, help with finding information on the course, more efficient searching and placement of search results in the context of students' interest, as well as increasing students' loyalty to a higher education institution.
This paper is a result of its author's work, whose goal was to examine the role of globalization in the change of organization models and intensification of its competitiveness, following trade liberalization. In addition, the goal was to define competitive advantages, which the companies have to develop in order to survive in a highly competitive global market. The study has shown that market expansion does not mean that only big business subjects will be able to make a profit. Also, the analysis has shown that there is no correlation between a big market and success of big businesses. In other words, globalization rewards the companies which are innovative and competitive, regardless of the company's size and country of origin.
The present time is characterized on the one hand, by a wealth of material goods and a high level of technological development, and on the other hand, by the destruction of nature and the environment. Not often, man is deprived of pure nature, clean water and air. Today we can firmly state that if nature defines our existence and our relationship with it in general, the development of ecological awareness can help change our relationship with nature, and promote more responsible behavior towards it. This paper analyzes the concept and elements of ecological awareness, ecological news factors, the importance of ecological awareness. The research that is presented was conducted in several cities in the Republic of Serbia, by filling in a survey of 10 questions, in the period from April to May 2021. Based on completely random sampling, 105 participants from the territory of several cities in the Republic of Serbia (Kragujevac, Niš, Belgrade, Vranje and Loznica) were selected.
Innovations are one of the most important factors in the competitiveness of the enterprises in modern business conditions. Innovation is defined as the process of creating new (and differentiated) value for customers in the market, which can create a sustainable competition advantage. The goal of innovation is to create more successful future of the company, but this success does not happen by itself, but a purposeful implementation of the innovation process is required - which requires, in the first place, the planning of all phases and sub-processes.
Preliminary notesThis paper analyzed the possibility of monitoring the parameter OEE for "Serbia Railways" JSC. Transpatternation of indicators and of pattern for OEE in order to make them appropriate for use in railway infrastructure is known as Overall Railway Infrastructure Effectiveness -ORIE. This work represented a model for calculation of ORIE. It is proven that the program, which works at Swedish railways, can be adapted in order to make it functional for infrastructure of "Serbia Railways" JSC. Also, this work includes conducted adaptation and proposal of ORIE patterns which will satisfy specific needs for calculation of values for "Serbia Railways" JSC. Using the case study, it is calculated for three railway relations in Section for infrastructure of Požarevac that the value of ORIE based on real data differs in rang from 47,95 % to 60,71 %.
Keywords: effectiveness; infrastructure; quality; railways
Ukupna efektivnost željezničke infrastrukture kao faktor kvalitete na željeznici SrbijePrethodno priopćenje U radu je analizirana mogućnost praćenja parametra OEE kod infrastrukture "Železnice Srbije" ad. Transformacija indikatora i obrasca za OEE u odgovarajući koji se koristi za željezničku infrastrukturu zove se ukupna efektivnost željezničke infrastrukture (overall railway infrastructure effectiveness -ORIE). U radu je predstavljen model za izračun ukupne efektivnost željezničke infrastrukture (ORIE). Dokazano je da se program, koji funkcionira na Švedskim željeznicama, može prilagoditi da funkcionira i na infrastrukturi "Železnice Srbije" ad. U radu je izvršena prilagodba i prijedlog obrazaca ORIE koji će zadovoljiti specifične potrebe za izračun vrijednosti za "Železnice Srbije" ad. Studijom slučaja izračunato je za tri relacije pruga u Sekciji za infrastrukturu čvora Požarevac, da se vrijednost ORIE utemeljena na realnim podacima razlikuje od 47,95 % do 60,71 %.
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