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Found 6374 publications

Cognitive aspects of agent-based based evacuation simulation

Csaba Hajdu F. Hajdu Rajmund Kuti

Publication Name: 2025 IEEE 16th International Conference on Cognitive Infocommunications Coginfocom 2025

Publication Date: 2025-01-01

Volume: Unknown

Issue: Unknown

Page Range: 19-24

Description:

Efficient evacuation is an important task, since it can save people's lives. In Hungary, to design evacuation, mostly standardized calculations are used, which take into account, for example, the number and age of the people, but not the human behaviour. Human behaviour can be included in agent-based simulations. In this paper, the evacuation simulation of a classroom taking into account cognitive behaviour like panic and reaction time is presented. Moreover, based on the cognitive aspects of agent-based simulations, a new architecture is proposed, which can be used to further develop the presented simulations.

Open Access: Yes

DOI: 10.1109/CogInfoCom66819.2025.11200742

N-best Design Options with Strategical Differences in Process Network Synthesis

Ákos Orosz Sin Yong Teng Ferenc Friedler

Publication Name: Chemical Engineering Transactions

Publication Date: 2025-01-01

Volume: 120

Issue: Unknown

Page Range: 409-414

Description:

The main goal of Process Network Synthesis is usually to find the lowest-cost process for a given problem. Since the model is not able to account for every parameter of an industrial realisation, the decision makers prefer to have alternatives, which can be provided when generating the n-best solutions. This, however, comes with another issue, specifically that several of the near-optimal solutions are almost identical to the optimal one, and only differ in one or two operating units. Thus, the next step to improve the generation of feasible and performant alternatives is to provide process designs with meaningful differences from the optimum. Meaningful differences between designs have to be defined by the decision makers. These are differences that the decision makers consider as major strategic questions, while other changes in the process constitute fine details where simply selecting the lowest cost option is enough. The current work describes a branch-and-bound algorithm that is able to generate the n-best strategically different process designs. The difference between considering and ignoring strategic differences when generating n-best solutions is illustrated via a case study.

Open Access: Yes

DOI: 10.3303/CET25120069

TURNING THE TRIPLE BURDEN OF UKRAINIAN DEPOPULATION INTO A QUADRUPLE BURDEN: THE RESULTS OF A SURVEY AMONG UKRAINIAN REFUGEE WOMEN

Sándor Remsei Eva Berde

Publication Name: Economics and Sociology

Publication Date: 2025-01-01

Volume: 18

Issue: 1

Page Range: 296-312

Description:

The effects of the Russian-Ukrainian war on Ukraine's demographic landscape are immense. One key consideration is whether Ukrainian refugee women intend to return to their country after the war ends. If the return is planned, the question of whether they would wish to have children is also relevant. This study explored these issues by surveying women who fled to Hungary and the Netherlands. Among those surveyed, 42% did not plan to return under any circumstances, and only 12% intended to return even if their home area came under Russian control. Logistic regression was used to identify factors influencing the intention to return, with reluctance to have additional children and income earned through employment emerging as the strongest explanatory factors. However, we found only modest associations between the intention to return and other variables. Our findings suggest that deeply rooted personal preferences shape these women’s plans.

Open Access: Yes

DOI: 10.14254/2071-789X.2025/18-1/16

New alternatives to private car transport for different powertrains in Hungary - Trends in the petrol, diesel and electric drive solutions

Eniko Nagy Karl Eva Mark Viktor Katai Gyorgy Molnar

Publication Name: Ines 2025 29th IEEE International Conference on Intelligent Engineering Systems 2025 Proceedings

Publication Date: 2025-01-01

Volume: Unknown

Issue: Unknown

Page Range: 285-289

Description:

As time passes and technology becomes more impressive, more ways exist to process, store and visualise data, contributing to data analytics' power. The most common process is to collect data from different sources and store it in some file format. Some process then passes the acquired information to a data warehouse where the data can be stored and queried. Once the right data and tables have been selected, they are imported and exported to a visualisation system, where reports can be generated from the available information. All that remains is to create a custom website where the reports can be displayed. In this paper, we work with data related to petrol, diesel, and electric vehicles. The dataset was synthetically generated using a simulation model developed by the author to reflect realistic automotive scenarios. An ETL process will import the data into the data warehouse, which will be stored for subsequent analysis. The information is then exported from the data warehouse to be processed by the visualisation program and used to make statements. This process aims to demonstrate how the values derived from the generated data transition from their raw form to a visualised state. Given the current global transformation of the automotive industry, this topic was selected due to its relevance and the widespread impact of these changes. The study aims to generate various analytical statements, such as the average engine power across different car brands or the average fuel consumption per 100 kilometres for specific vehicle types.

Open Access: Yes

DOI: 10.1109/INES67149.2025.11078211

Migration of highly skilled workers as a driver of digital economy development

Yuriy Bilan Halyna Mishchuk Olena Oliinyk

Publication Name: Knowledge and Performance Management

Publication Date: 2025-01-01

Volume: 9

Issue: 2

Page Range: 113-123

Description:

The migration of highly skilled workers and its impact on productivity, competitiveness, and innovative development is becoming an increasingly relevant area of scientific research in the context of rapid digitalization of the economy. In this regard, the article aims to explore the relationship between the migration of highly skilled workers and digital economy development (using the example of EU countries). The study was conducted using correlation analysis and parametric data analysis methods, based on EU countries’ statistics on the migration of highly skilled workers, macroeconomic digitalization indicators, and the adoption of digital technologies at the business level. The results confirm that highly skilled migrants positively affect aggregate indicators of economic digitalization: correlation coefficients with the Global Digitalization Index and the DiGiX Digital Index are 0.735 and 0.692, respectively, and are statistically significant. At the company level, a significant influence of highly skilled migrants on the use of specific digital technologies in EU companies was confirmed. In particular, there is a strong correlation between the “Foreign Highly Skilled Personnel” indicator from the IMD World Talent Ranking 2024 and digital intensity indicators (level of application of key business-related digital technologies), as well as business activity in using big data analytics technologies: the correlation coefficients are 0.770 and 0.689, respectively, and are statistically significant. The proposed approach to analyzing the relationship between highly skilled worker migration and the digital development outcomes of companies and host countries can be used to develop and adjust knowledge and human resource productivity management strategies at both the micro- and macroeconomic levels.

Open Access: Yes

DOI: 10.21511/kpm.09(2).2025.09

Advanced Examination Systems: Applying Fuzzy Logic and Machine Learning Methods in Education

Eniko Nagy Karl Eva Gyorgy Molnar

Publication Name: Iccc 2025 IEEE 12th International Joint Conference on Cybernetics and Computational Cybernetics Cyber Medical Systems Proceedings

Publication Date: 2025-01-01

Volume: Unknown

Issue: Unknown

Page Range: 231-235

Description:

In our paper, we present an innovative educational assessment system that attempts to overcome the limitations of traditional educational evaluation methods by applying machine learning, artificial intelligence, fuzzy logic, and advanced mathematical techniques. This system can provide a more objective and personalized assessment of students' knowledge. Current examination systems in educational institutions are outdated and do not meet modern societal and technological requirements. A central element of the system is the application of fuzzy logic, which allows for handling uncertainties in knowledge assessment. Using the FP-growth algorithm and the fuzzy analytical hierarchy process (AHP) aids in optimizing the evaluation process and enables a more profound analysis of students' performance. During the system's development, we aim to adaptively manage the difficulty level of questions, taking into account students' prior performance and individual capabilities. The study highlights the security risks and efficiency issues of current 'manual' question compilation methods. The new system aims to minimize these risks while improving the quality of education and reducing the workload of educators.

Open Access: Yes

DOI: 10.1109/ICCC64928.2025.10999148

Current Issues in Effective Learning: Methodological and Technological Challenges and Opportunities Based on Modern ICT and Artificial Intelligence

Eniko Nagy Gyorgy Molnar

Publication Name: Eai Springer Innovations in Communication and Computing

Publication Date: 2025-01-01

Volume: Unknown

Issue: Unknown

Page Range: 1-11

Description:

Today, the discourse around the current issues of effective learning is increasingly centred on modern information and communication technologies (ICT) and artificial intelligence (AI)-based methodological and technological solutions. ICT tools, such as online learning platforms, virtual classrooms and digital textbooks, have significantly transformed the educational environment, providing opportunities for personalised learning and remote access. In addition, AI-based applications, such as student performance analysis and curriculum customisation, are opening up new horizons in education. AI can create adaptive learning systems that continuously adapt to the needs and progress of students, thus increasing the effectiveness of learning. But these new technologies and methods also bring with them a number of challenges. One major challenge is digital inequality, as not all students have access to ICT tools and the Internet. Furthermore, educators need to continuously develop their digital competences to keep up with technological developments and effectively integrate new methods into teaching. There are also ethical issues, in particular data protection and student privacy. New opportunities include the use of learning analytics to help educators better understand learning processes and identify areas where students need help. Interactive and gamified learning materials developed with the help of AI can make learning more motivating and enjoyable, thereby increasing student engagement. Overall, the integration of modern ICT and AI-based methods and technologies into education offers significant benefits, but their successful implementation requires adequate infrastructural support, continuous training for teachers and digital access for students. This article provides a brief summary of all these phenomena, trends, opportunities and good practices.

Open Access: Yes

DOI: 10.1007/978-3-031-81261-3_1

The 4th Global Conference on Parliamentary Studies: Current Scientific Discourses on Parliaments in a Digital Age

Péter Smuk Áron Ősze

Publication Name: International Journal of Parliamentary Studies

Publication Date: 2025-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

This report intends to summarize the academic discussions on actual parliamentary issues at the conference that took place in Athens, 13 June 2025.

Open Access: Yes

DOI: 10.1163/26668912-bja10115

EXPLORING THE RELATIONSHIP BETWEEN SERVICE PREFERENCES AND DIGITAL INFORMATION SOURCES IN THE CONTEXT OF ACTIVE TOURISM

Lóránt Dávid Gyula Fodor Zsolt Hollósy Ivett Vargáné Gálicz

Publication Name: Geojournal of Tourism and Geosites

Publication Date: 2025-01-01

Volume: 62

Issue: 4

Page Range: 2233-2239

Description:

The aim of the research is to explore the relationships between the different forms of active tourism and the service needs that arise, and the role of the use of information sources in the decision-making of active tourism participants. The closed-ended questionnaire survey investigated respondents' hiking habits, the services they use and the sources of information on active tourism. The questionnaire was completed by 169 people who had hiked in the Lake Velence area, their responses were analysed using SPSS and Excel programs. Cluster analysis was used to ide ntify different groups of active tourism participants, depending on the type of tours they prefer, the services they use and the sources of information they r ely on. ANOVA (one-way analysis of variance) was used to test whether different types of active tourism influence the use of services and to identify which services are most important for each group. In addition, a Pearson correlation matrix was constructed to show the relationships between each of the quantitative variables. The research contributes t o a better understanding of how different forms of active tourism and different information sources shape the service needs of active tourism participants, which can help to target the development of tourism services and the transition to the circular tour ism.

Open Access: Yes

DOI: 10.30892/gtg.62420-1586