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25th IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2024

作者： Lozhnikov, Aleksey E. Ryspayeva, Cholpon K. Luchko, Oleg N. Nyshanbai, Nazgul kyzy Marenko, Valentina A. Faculty of IT and Computer Systems Omsk State Technical University Omsk Russia Institute of Intercultural Communication and Psychology International University of IT Bishkek Kyrgyzstan Dept. of Computer Science Mathematics and Natural Sciences Omsk Humanitarian Academy Omsk Russia Lab. of Methods for Converting and Presenting Information Sobolev Institute of Mathematics Omsk Russia

ISBN: (纸本)9798350389234

Various needs for specific professional knowledge manifest different levels of perseverance in students to complete the educational process from the start to its logical end. This process is a key feature of any learning format. These arguments determine the relevance to investigate the process of self-regulation in educational activity. The purpose of the work is to build the models that characterize self-regulation of the student’s cognitive activity and involvement in knowledge acquisition. To achieve the purpose, the following tasks are to be solved. 1. Review of scientific publications. 2. Building graphical and cognitive models of the problem under study. 3. Analysis of models using statistical and IT approach. 4. Formulation of conclusions. Statistical analysis shows that the level of self-regulation of behavior among the students in the city of Bishkek is higher than among the students in the city of Omsk. As for the level of self-regulation of educational activities, it is higher among the students in Omsk than among the students in Bishkek. As a result, it is found that the factors "motivation" of the student learning activity and the factor "flexibility" in actions are decisive for the investigation of the phenomenon. The results of q-connectivity show that the vertices of the graph of a cognitive model with high-dimensional simplexes are these factors. The obtained results are recommended to specialists in the field of pedagogical science to manage the educational system as a whole. © 2024 IEEE.

关键词： Contrastive Learning

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Student Perceptions of AI-Enhanced Adaptive Learning Systems: A Pilot Survey 7

Student Perceptions of AI-Enhanced Adaptive Learning Systems...

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7th IEEE International Conference and Workshop Obuda on Electrical and Power Engineering, CANDO-EPE 2024

作者： Katonane Gyonyoru, Klara Ida Katona, Jozsef Institute of Social Sciences University of Dunaujvaros Department of Organizational Development and Communication Science Dunaujvaros Hungary Institute of Computer Engineering University of Dunaujvaros Department of Software Development and Application Dunaujvaros Hungary John Von Neumann University GAMF Faculty of Engineering and Computer Science Kecskemet Hungary Budapest Business University Faculty of Finance and Accountancy Department of Applied Quantitative Methods Budapest Hungary

ISBN: (纸本)9798331531119

Artificial Intelligence (AI) significantly enhances adaptive learning by personalizing and tailoring instruction to individual student needs. AI analyzes data in real-time to create personalized learning paths based on students' strengths, weaknesses, and preferences, which keeps students engaged and motivated. A major benefit of AI in adaptive learning is the provision of real-time feedback and assessment, allowing students to correct mistakes promptly and understand concepts more thoroughly. AI-based intelligent tutoring systems are primarily intended to simulate personalized tutoring processes that guide students in complex problem-solving and answering questions. It is convenient in teaching mathematics, sciences, and languages. AI also supports inclusive education, dealing with diversified learning requirements and styles, such as those of learners with disabilities. For the teacher, AI acts as a reflector of student performance so that one can intervene early and make adjustments in the method of instruction by creating effective learning environments. AI technology is a field in constant development and harbors the potential to change the face of adaptive learning, bringing an upswing in educational outcomes. This article will summarize the advantages and features that merit improvement of the AI-embedded adaptive learning systems with student feedback. © 2024 IEEE.

关键词： Contrastive Learning

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"It’s like an explosion": Cyberwarfare harms for civilian population in Ukraine during the Russian invasion

"It’s like an explosion": Cyberwarfare harms for civilian p...

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2025 CHI Conference on Human Factors in Computing Systems, CHI EA 2025

作者： Kulyk, Oksana Kickbusch, Jari Mayer, Peter IT University of Copenhagen Copenhagen Denmark Department of Mathematics and Computer Science University of Southern Denmark Odense Denmark Institute of Applied Informatics and Formal Description Methods Karlsruhe Institute of Technology Karlsruhe Germany

ISBN: (纸本)9798400713958

Studies on civilian costs of cyberwarfare operations are crucial in understanding how to protect the population in large-scale cyberattacks conducted by state actors. In this preliminary study, we conduct interviews (N=5) focusing on the harms experienced by Ukrainian civilians due to Russian cyberwarfare operations since the start of the full-scale invasion in 2022 as well as mitigation measures for protection of the civil society. The findings include harms such as lack of information, lack of access to essential services, physical harms, anxiety and lack of trust in the government. The study shows that cyberwarfare operations have the potential of causing severe harm to civilians and that there is a need for future studies to be conducted and adopted by institutions in order to develop measures to mitigate, not only in Ukraine but in any countries in risk of such attacks. © 2025 Copyright held by the owner/author(s).

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Current Trends in Artificial Intelligence for Educational Advancements

Current Trends in Artificial Intelligence for Educational Ad...

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2024 International Conference on Decision Aid sciences and Applications, DASA 2024

作者： Al-Tarawneh, Abdallah M. A. Alomoush, Reem Abdelkareem Ul Islam, Tanveer Janjua, Jamshaid Iqbal Abbas, Tahir Ihsan, Anaum Al-Ahliyya Amman University Clinical Psychology Amman Jordan Yarmouk University Faculty of Educational Sciences Department of Curricula and Methods of Teaching Jordan TIMES Institute Department of Computer Science Multan60000 Pakistan Lahore Pakistan

ISBN: (纸本)9798350369106

The focus of this paper is the integration of artificial intelligence (AI) within the educational field including but not limited to, adaptive learning, teaching evaluation, online learning environments, and individualized instruction. The authors investigate the positive role of AI in enhancing teaching performance and the quality of students' learning experiences. The study aims to demonstrate what role AI may play in the course of education development and practice improvement. It also sheds light on the limitations AI will have in the realm of education, such as accessibility, data ownership, and ethical issues. The paper does not contain only the limitations but the opportunities for this technology as well and describes how AI could be effectively incorporated into education, subsequently providing insights into the evolution of AI-based educational transformation. © 2024 IEEE.

关键词： Federated learning

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Intelligent Problem Solving Model and its Cross Research Directions Based on Factor Space and Extenics

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Annals of Data science 2022年第3期9卷 469-484页

作者： Li, Xingsen Zeng, Junlin Liu, Haitao Wang, Peizhuang Institute of Extenics and Innovation Methods Guangdong University of Technology Guangzhou510006 China School of Computer Science Guangdong University of Technology Guangzhou510006 China Institute of Intelligent Engineering and Mathematics Liaoning Technical University Fuxin123000 China

Artificial intelligence technology has made important progress in machine learning and problem-solving with relatively determined boundary conditions. However, the more common open problems with uncertain boundary conditions in management practice still depend on the experience mastered by individuals. The combination of Extenics, Factor Space, and knowledge management will potentially solve this kind of problem intelligently to a extent. Based on Extenics and factor space theory, this paper studies the Extension model of open problems, explores the intelligent expansion mechanism of factor knowledge in big data environment, and constructs the double integration of multi granularity factor knowledge space and expert experience knowledge. We try to make Extenics and factor space theory complement each other in the field of problem solving, reveal the knowledge expansion mechanism of open problem solving in the big data environment, provide a novel theoretical perspective and method basis for knowledge based intelligent service on factor mining. This paper will also provide theoretical research directions for building a new generation of problem-oriented new factor knowledge base, promote the deep integration of knowledge management and artificial intelligence leading to a new direction of knowledge engineering based on factor space and Extenics. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Knowledge management

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Use of digital platforms for enhancing academic performance. Systematic Review 7

Use of digital platforms for enhancing academic performance....

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7th IEEE International Conference and Workshop Obuda on Electrical and Power Engineering, CANDO-EPE 2024

作者： Costescu, Cristina Anamaria Şogor, Mǎlina Pǎlimariu, Sabina Katona, Jozsef Tufar, Ioana Avram, Carla Maria Babe-Bolyai University Special Education Department Cluj-Napoca Romania Institute of Computer Engineering University of Dunaujvaros Department of Software Development and Application Dunaujvaros Hungary John Von Neumann University GAMF Faculty of Engineering and Computer Science Kecskemet Hungary Budapest Business University Faculty of Finance and Accountancy Department of Applied Quantitative Methods Budapest Hungary

ISBN: (纸本)9798331531119

The purpose of this study was to determine the effect of technology-based interventions on academic performance. To achieve this purpose a systematic review was conducted. Within the scope of this study EBSCO, Springer, ProQuest, science Direct, Wiley Online Library, Taylor and Francis Online, databases were scanned, and 18 studies were included in the review. Our results show that the iPad is the most preferred digital device for enhancing math and reading skills and significant results can be seen when used. Similar positive effects were observed with other technological devices, reinforcing the effectiveness of technology as a tool for supporting academic performance. This evidence underscores the value of incorporating digital devices in educational strategies, particularly for improving key academic skills. © 2024 IEEE.

关键词： academic performance children digital devices

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The Reliability of Information Sources: Student Perceptions and Educational Opportunities 7

The Reliability of Information Sources: Student Perceptions ...

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7th IEEE International Conference and Workshop Obuda on Electrical and Power Engineering, CANDO-EPE 2024

作者： Kollar, Anita Mihalovicsne Katona, Jozsef Obuda University Institute of Electronics and Communication Systems Kandó Kálmán Faculty of Electrical Engineering Budapest Hungary John Von Neumann University GAMF Faculty of Engineering and Computer Science Kecskemet Hungary Budapest Business University Faculty of Finance and Accountancy Department of Applied Quantitative Methods Budapest Hungary Department of Software Development and Application Institute of Computer Engineering University of Dunaujvaros Dunaujvaros Hungary

ISBN: (纸本)9798331531119

The modern digital age demands the skills to be able to assess information. In the current world, access to information and knowledge is abundant from different sources. Indeed, high-quality data are much needed in education and professional development, as the quality and accuracy of information directly influence the process of learning and decision-making. The study aims to investigate the perceptions of computer science students at the University of Dunaújváros related to the credibility of diverse information sources. Within a questionnaire, on a voluntary answer basis, 68 students took part, 59 males and nine females. This work is aimed at assessing the degree to which the surveyed students evaluate information sources based on a five-point Likert scale. The data shows that students find print books and textbooks as the most reliable sources;social media are the least reliable. The study also supports the importance of source credibility evaluation, for which lateral reading techniques and AI-based news source credibility identification systems can be helpful. These findings suggest the necessity of bettering the educational approaches to foster better source criticism skills in the students, especially for online content and social media. The study generally contributes to understanding the information society and helps prepare students to obtain and use reliable and accurate information in their future careers. Using AI-based tools and systems can then further support these educational efforts with robust mechanisms to evaluate information credibility in an ever more complex digital landscape. © 2024 IEEE.

关键词： Data reliability

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MUTUAL COVERINGS OF CONES OF MONOTONE FUNCTIONS AND ESTIMATES OF THEIR INTEGRAL MAJORANTS

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Journal of Mathematical sciences (United States) 2023年第6期271卷 714-732页

作者： Bakhtigareeva, E.G. Goldman, M.L. Karshygina, G. Zh. Department of Function Theory Steklov Mathematical Institute of Russian Academy of Sciences 8 Gubkina Street Moscow 119991 Russian Federation Department of Methods of Teaching Mathematics and Computer Science Karaganda Buketov University 28 University Street Karaganda 100024 Kazakhstan

Questions of mutual covering and equivalence of cones of monotone functions and the corresponding estimates of their majorants are studied. Two types of coverings are considered: pointwise and integral. They correspond to pointwise and integral estimates of the majorants on these cones. The results obtained are used to derive formulas that allow estimating pointwise and integral majorants of decreasing rearrangements for generalized Riesz and Bessel potentials. © 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

关键词： Cones of decreasing rearrangements of potentials Cones of monotone functions Generalized Riesz potentials Integral majorants on cones Pointwise and integral coverings

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Scenario Approach for Parametric Markov Models 21st

Scenario Approach for Parametric Markov Models

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21st International Symposium on Automated Technology for Verification and Analysis, ATVA 2023

作者： Liu, Ying Turrini, Andrea Hahn, Ernst Moritz Xue, Bai Zhang, Lijun State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Institute of Intelligent Software Guangzhou Guangzhou China Formal Methods and Tools University of Twente Enschede Netherlands

ISBN: (纸本)9783031453281

In this paper, we propose an approximating framework for analyzing parametric Markov models. Instead of computing complex rational functions encoding the reachability probability and the reward values of the parametric model, we exploit the scenario approach to synthesize a relatively simple polynomial approximation. The approximation is probably approximately correct (PAC), meaning that with high confidence, the approximating function is close to the actual function with an allowable error. With the PAC approximations, one can check properties of the parametric Markov models. We show that the scenario approach can also be used to check PRCTL properties directly – without synthesizing the polynomial at first hand. We have implemented our algorithm in a prototype tool and conducted thorough experiments. The experimental results demonstrate that our tool is able to compute polynomials for more benchmarks than state-of-the-art tools such as PRISM and Storm, confirming the efficacy of our PAC-based synthesis. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Polynomial approximation

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A Logic for Reasoning about Aggregate-Combine Graph Neural Networks

arXiv

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arXiv 2024年

作者： Nunn, Pierre Sälzer, Marco Schwarzentruber, François Troquard, Nicolas University of Rennes IRISA CNRS France Theoretical Computer Science / Formal Methods University of Kassel Germany Gran Sasso Science Institute L’Aquila Italy

We propose a modal logic in which counting modalities appear in linear inequalities. We show that each formula can be transformed into an equivalent graph neural network (GNN). We also show that a broad class of GNNs can be transformed efficiently into a formula, thus significantly improving upon the literature about the logical expressiveness of GNNs. We also show that the satisfiability problem is PSPACE-complete. These results bring together the promise of using standard logical methods for reasoning about GNNs and their properties, particularly in applications such as GNN querying, equivalence checking, etc. We prove that such natural problems can be solved in polynomial space. Copyright © 2024, The Authors. All rights reserved.

关键词： Graph neural networks

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