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Publications - 6525

Optimal Planning of Routes, Schedules, and Charging Times of Automated Guided Electric Vehicles

Botond Bertok Károly Kalauz Márton Frits Petar Sabev Varbanov

Publication Name: Energies

Publication Date: 2026-02-01

Volume: 19

Issue: 3

Page Range: Unknown

Description:

In traditional industry setups, Automated Guided Vehicles (AGVs) follow trajectories planned together with the layout of the storage or production facility and supported by fixed markers on the floor or on the walls. Traffic rules manage the avoidance of multiple vehicles, while fleet management gets movement and transportation commands completed as soon as possible. In contrast, recent developments in navigation and advanced computing, sensor, and communication capabilities make their free movement safe and manageable. Detailed route planning and scheduling can guarantee that the vehicles keep a safe distance in time and space. A recent challenge of electric AGVs is that their charging may take several hours, which must be factored into their schedule. This has made minimal energy demand a key objective alongside earliest delivery and strictly meeting the deadlines. This paper presents a method for detailed routing and scheduling of AGV fleets to minimize energy consumption while considering battery levels and charging times. The optimization method is illustrated by a case study where multiple delivery tasks are performed by synchronized movement of vehicles on a complex warehouse layout. In the optimal solution, the scheduled waiting times for collision avoidance are utilized by the vehicles to pre-charge their batteries.

Open Access: Yes

DOI: 10.3390/en19030813

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

Comparative Assessment of Machine Learning Approaches for Early Lung Cancer Diagnosis

Satyanand Singh Garvit Maheshwari Domonkos Tinka Babita Tiwari

Publication Name: Emerging Science Journal

Publication Date: 2026-02-01

Volume: 10

Issue: 1

Page Range: 20-54

Description:

Lung cancer, a leading cause of cancer-related mortality worldwide, often escapes early detection due to the absence of distinct symptoms in its initial stages. This work investigates how Machine Learning (ML) might improve early diagnosis by analyzing Electronic Health Records (EHR) data. Multiple ML models were developed and evaluated on a synthetic dataset created to replicate real-world patient characteristics, allowing controlled experimentation while safeguarding privacy. Model performance was tuned using both conventional optimization methods and nature-inspired approaches, with the aim of balancing predictive accuracy and computational efficiency. In our synthetic dataset experiments, ensemble learners optimized with metaheuristic techniques reached accuracy levels approaching 99 percent while maintaining computational efficiency and generally outperformed simpler baselines. The contribution of this work lies in exploring the integration of GFO and WOA for feature selection and hyperparameter tuning of XGBoost, together with a soft-voting ensemble. This approach provides an experimental pathway for enhancing predictive performance under computational constraints. However, as the dataset is synthetic, the conclusion remains experimental; validation against clinical records will be essential before translation into practice.

Open Access: Yes

DOI: 10.28991/ESJ-2026-010-01-02

Simulation of the Turning Assistant in Road Traffic Accident Reconstruction

Dániel Feszty Gyula Kőfalvi Istvan Lakatos Ferenc Ignácz Andreas Moser

Publication Name: Future Transportation

Publication Date: 2026-02-01

Volume: 6

Issue: 1

Page Range: Unknown

Description:

The accurate simulative reconstruction of blind spot accidents requires innovative simulation methods. The objective of this paper is to analyze the avoidability of a specific blind spot accident and assess the impact of various parameters as if an active turning assistant had been installed in the truck. Additionally, it proposes a novel adaptation of the turning assistant system, along with an adapted simulation model tailored for drawbar trailers. The analyses presented in this paper were performed using PC-Crash accident simulation software, applying the “Active Safety” module. After performing a simulation of an accident involving a right-turning truck with a center axle trailer and a pedestrian, the avoidability of the accident was examined by simulating the scenario as if the truck involved in the accident had been equipped with an active turning assistant system. Subsequently, a parameter analysis was conducted to analyze the effect of changes in the active turning assistant’s parameters and changes in the pedestrian’s direction of entry on the avoidability of the accident. In doing so, we determined the parameters for the worst-case (collision) and the best-case (no collision) scenarios. Finally, an adaptation and further development of the active turning assistant, along with a corresponding simulation method for drawbar trailers, are proposed.

Open Access: Yes

DOI: 10.3390/futuretransp6010013

Motives underlying water sport tourist behaviour: a segmentation approach

László Tóth Miklós Bánhidi Noémi Gyömbér Kinga Zsuzsanna Nagy Kata Tóth

Publication Name: World Leisure Journal

Publication Date: 2021-01-01

Volume: 63

Issue: 1

Page Range: 109-127

Description:

Sport tourism is a heterogeneous phenomenon with diverse motivations. However, the field of water sport tourism has not yet been intensely analyzed. The purpose of this study was twofold. Firstly, the study aimed to unfold the consumer profile of water sport tourists. Secondly, the role of demographic variables and behavioural attributes concerning flow experience in the activities was unveiled. Since flow has the potential of sustaining participation in physical activity pursuits as well as raising destination loyalty, its analysis in the field of leisure and tourism is of utmost interest. A quantitative research method was chosen. The subjects were 297 Hungarian water sport participants. Data were analyzed through k-means clustering and a multivariate general linear model using SPSS software. First, the cluster analysis yielded four clusters based on sport and tourism motivations, namely: Sport-oriented, Leisure-ignoring, Leisure-oriented, Social-oriented groups. Second, in the “Absorption in the Activity” dimension of flow experience, females demonstrated higher scores than males, and participants showed significant differences according to their skill levels. Furthermore, as a predictor variable, flow Absorption influenced expenses on sport lessons, while desired skill level affected the frequency of practising. These findings contribute to reaching water sport tourists more adequately.

Open Access: Yes

DOI: 10.1080/16078055.2021.1888002

Design and Implementation of a Modular Smart Home System Using ESP32 and Apple HomeKit Integration

Stefan Koprda Zoltan Balogh Gyorgy Molnar

Publication Name: Sisy 2025 IEEE 23rd International Symposium on Intelligent Systems and Informatics Proceedings

Publication Date: 2025-01-01

Volume: Unknown

Issue: Unknown

Page Range: 125-130

Description:

This paper presents a modular smart home system integrating ESP32 microcontrollers with Apple HomeKit ecosystem to address scalability and data retention challenges in residential IoT deployments. The proposed solution employs the HomeSpan library for HomeKit-Compatible accessories, enabling secure local communication while maintaining compatibility with Apple's Home application. The key scientific contribution lies in the hybrid architecture combining real-time HomeKit control with a dedicated REST API server featuring SSL encryption and API-key authentication for historical data collection. The system addresses Apple Home app's limitation of lacking data retention capabilities through automated 5-minute data transmission intervals to a secure MariaDB database. Performance evaluation demonstrates stable operation across multiple sensor types (DHT22, PIR motion sensors) and actuators with modular deployment flexibility. Comparative analysis shows improved data persistence and analytics capabilities over standard HomeKit implementations while maintaining the security benefits of local communication protocols. The implementation achieves practical IoT deployment suitable for residential environments with enhanced comfort, safety, and energy efficiency monitoring capabilities.

Open Access: Yes

DOI: 10.1109/SISY67000.2025.11205419

PAST, PRESENT AND FUTURE OPPORTUNITIES OF STRATEGIC PURCHASING OF HEALTHCARE SERVICES IN HUNGARY

Kapócs Gábor Dózsa Csaba László

Publication Name: Lege Artis Medicinae

Publication Date: 2026-01-01

Volume: 36

Issue: 4-5

Page Range: 199-210

Description:

In recent decades, the Strategic Purchasing of Healthcare Services has become one of the defining pillars of the operation of mandatory health insurance and national health care systems – not only in the healthcare and health insurance systems of economically developed countries, but increasingly in developing countries as well. The Strategic Purchasing of Healthcare Services aims at the conscious development of the health insurance package: for the early dissemination of new cost-effective healthcare technologies, the sustainable operation of an efficient, high quality healthcare system and improved access for the population. In Hungary, a comprehensive development proposal for the establishment of the Strategic Purchasing of Healthcare Services was already prepared in the first decade of 2000s, by the implementation of the National Health Insurance Fund. These partially led to results, but to this day, a comprehensive Strategic Purchasing of Healthcare Services with embedded resources at the level of laws and government decrees and an appropriate institutional system and resources is still missing. In this study, we partly explore these antecedents, and partly provide an international outlook on current practices of other countries. However, we mainly update the domestic proposals intented for a new health policy administration with a potentially different approach.

Open Access: Yes

DOI: 10.33616/lam.36.0199

Effect of Simulated Transport Conditions on Microbiological Properties of Bottled Natural Mineral Water

Balázs Ásványi E. Lakatos Péter Böröcz Renáta Tihanyi-Kovács F. Bánáti L. Varga

Publication Name: Water Switzerland

Publication Date: 2023-05-01

Volume: 15

Issue: 9

Page Range: Unknown

Description:

Bottled mineral water is distributed globally through complex supply chains, making it available far beyond its bottling plants. In low-viscosity food matrices, invisible changes may occur due to shaking. The primary purpose of this research was to investigate the potential correlation between the intensity of mechanical agitation and the number of detectable microorganisms in bottled mineral water. The simulation of dynamic mechanical vibration was conducted using both time-accelerated and real-time tests. Freshly bottled natural mineral water and commercially available mineral water brands from different bottling locations and times were subjected to random vibration at three intensities as specified by the ASTM D-4169-16 standard, which simulates road transport on semi-trailer trucks. The study investigated the specific growth rate, the generation time, and the maximum cell numbers of microorganisms. The quantitative PCR (qPCR) technique was used to determine and compare the concentrations of microbes. Dynamic mechanical vibration affected the microbiome of mineral waters, influencing growth rates and generation times. In the case of waters from different bottling locations and times, the specific growth rate varied significantly for each water and for each intensity. This finding demonstrates that the microbiome composition of the water source and the interaction between microbes influence the response to mechanical impact. The time-accelerated test was shown to be suitable for analyzing the reaction of the microbiome of the tested matrix to the intensity and duration of vibration. The applied test protocol enabled the monitoring of changes in cell numbers by qPCR. All three intensities of the time-accelerated method were effective in testing the effects of real-time mechanical agitation on the microbiome.

Open Access: Yes

DOI: 10.3390/w15091757

Determination of center of gravity and moment of inertia using dynamic testing method

Balázs Vehovszky Zoltán Gazdagh Martin Kaszab

Publication Name: Advances in Acoustics Noise and Vibration 2021 Proceedings of the 27th International Congress on Sound and Vibration Icsv 2021

Publication Date: 2021-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

The knowledge of a vehicle's center of gravity (COG) and moment of inertia (MOI) are important from vehicle dynamic and comfort points of view. These parameters can be determined from the CAD model of the vehicle, however, manufacturing inaccuracies and additional elements can modify the values, and experimental validation can be necessary. The determination of COG (and even MOI) can be carried out using classical physical methods, but a more convenient and sophisticated method is offered based on dynamic testing data. The method is known and accessible even in commercial testing software, but a clear recommendation for the optimal input data and the expected accuracy is still not available. The purpose of this study is to define the influencing factors of the measurement and quantify their effect. The introduced method is based on the evaluation of the frequency response functions in the mass-line region. Input data were obtained by using impulse hammer excitation and accelerometers for measuring the response of the structure. The measurements and the evaluations were performed in Siemens LMS Test.Lab software using Rigid Body Calculator module. The results of the dynamic measurement are compared to CAD data and to the COG value got from simple static measurement.

Open Access: Yes

DOI: DOI not available