Computer Science Index

This article presents and describes in detail an interactive method of teaching and gathering feedback from students by applying internet‐based survey systems and utilizing smart devices. Real‐time survey results are monitored and analyzed by university staff and the lecturers, and these results are visible to other students as well. The presented method is probably the fastest and easiest way to receive feedback from students while increasing their interest and participation in lectures and laboratory work. The proposed method combines multiple means of gathering feedback from students, which include surveys, consultations, and group discussions. This interactive method has been applied for 5 years at the Faculty of Electronics, Vilnius Gediminas Technical University, Vilnius, Lithuania. After analyzing 10 years of available statistical data, which included 5 years when the presented interactive survey method was applied, a 4–6% increase in student performance was observed. Therefore, we conclude that this is perhaps a direct consequence of applying the discussed interactive method. In addition, after analyzing student surveys, it has been observed that 86.37% of students evaluated the use of smart devices positively in conjunction with this teaching method process. The students also positively evaluated the teaching process overall, and highly encouraging responses were received to questions asking to rate class activities and class atmosphere using this interactive survey method—87.79% and 91.68%, respectively. A large number of positive responses reflect a positive student attitude towards the use of such interactive surveys in the study process and supports their benefits aimed at increasing the overall quality of education.

In this paper, we develop and investigate the parallel numerical algorithms for three different state‐of‐the‐art numerical methods for solving the non‐local problems described by fractional powers of elliptic operators. These methods transform the non‐local problem into some local differential problems of elliptic or parabolic type. A two‐level parallelization approach is applied to construct the efficient parallel algorithms using the domain decomposition and master‐slave methods, to deal with the increase in computational complexity. We show and compare the serial and parallel solution times that are required to achieve similar accuracy of the solution using different algorithms. Results of extensive convergence tests are presented solving a three‐dimensional test problem with known decrease of the solution's convergence rate depending on the fractional power coefficient. We analyze and discuss the non‐trivial question, which parallel algorithm is recommended to achieve certain accuracy for the given fractional power coefficient.

Rough set theory has been used extensively in fields of complexity, cognitive sciences, and artificial intelligence, especially in numerous fields such as expert systems, knowledge discovery, information system, inductive reasoning, intelligent systems, data mining, pattern recognition, decision-making, and machine learning. Rough sets models, which have been recently proposed, are developed applying the different fuzzy generalisations. Currently, there is not a systematic literature review and classification of these new generalisations about rough set models.Therefore, in this review study, the attempt is made to provide a comprehensive systematic review of methodologies and applications of recent generalisations discussed in the area of fuzzy-rough set theory. On this subject, the Web of Science database has been chosen to select the relevant papers. Accordingly, the systematic and metaanalysis approach, which is called “PRISMA,” has been proposed and the selected articles were classified based on the author and year of publication, author nationalities, application field, type of study, study category, study contribution, and journal in which the articles have appeared. Based on the results of this review, we found that there are many challenging issues related to the different application area of fuzzy-rough set theory which can motivate future research studies.