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Found 6383 publications

The effect of the preload determination process on dynamic mechanical properties

Dániel Feszty Balázs Vehovszky Attila Schweighardt

Publication Name: Journal of Physics Conference Series

Publication Date: 2023-01-01

Volume: 2677

Issue: 1

Page Range: Unknown

Description:

NVH simulation and experimental methods are getting more and more important because of the increased customer needs for reliability and comfort. In order to obtain appropriate NVH simulation results accurate material properties have to be provided as input parameters. In case of the dynamic mechanical property determination of acoustic viscoelastic foams the results may vary greatly depending on the measurement settings and the quality of the measurement. This study evaluates the effect of the preload determination process on dynamic mechanical properties and the repeatability of the dynamic compression tests. Finally, conclusions are drawn and suggestions are made for the settings.

Open Access: Yes

DOI: 10.1088/1742-6596/2677/1/012007

Creating Own AI Datasets from Different Language Sources Efficiently: Advantages, Disadvantages and Best Pracitces to Make Own Datasets

Zoltan Balogh Eniko Nagy Jozsef Cserko Gyorgy Molnar

Publication Name: Cando EPE 2023 Proceedings IEEE 6th International Conference and Workshop Obuda on Electrical and Power Engineering

Publication Date: 2023-01-01

Volume: Unknown

Issue: Unknown

Page Range: 155-158

Description:

Artificial Intelligence (AI) has become a ubiquitous technology that has the potential to revolutionize many industries. However, AI requires access to vast amounts of data to achieve its full potential. By understanding these data sources and the best practices for working with them, we can unlock the full potential of AI and create groundbreaking solutions that benefit society as a whole. Data sources can be utilized to train AI algorithms, including structured and unstructured data, but finding relevant datasets is challenging. The main problem is the international sources. Most of the datasets are available only in English or other common languages. However these are good sources, but translating them is expensive and time-consuming. This paper shows how to generate own datasets from open-source data with translation.

Open Access: Yes

DOI: 10.1109/CANDO-EPE60507.2023.10417973

The Painlevé analysis and computational technique for new wave solutions with its numerical validation to the complex short pulse equation

D. U. Ozsahin Abeer S. Alnahdi Hijaz Ahmad Reda A. Ibrahim D. U. Ozsahin

Publication Name: Kuwait Journal of Science

Publication Date: 2026-04-01

Volume: 53

Issue: 2

Page Range: Unknown

Description:

This article aims to derive novel varieties of exact solitonic wave solutions to the complex short pulse equation using an effective technique known as the Riccati-Bernoulli sub-ODE method (RBSODM), which does not conform to the balance rule. For the first time, the resonance induced by the arbitrariness of the singular manifold is analyzed in the proposed model through the application of Painlevé analysis (PA). The complex short pulse (CSP) equation models the behaviour of ultra-short optical pulses in nonlinear media. It serves as a more accurate model than the non-linear Schrödinger equation when the pulse width approaches the optical cycle scale. The proposed model incorporates both dispersion and Kerr-type nonlinearity, capturing the essential features of femtosecond pulse dynamics. Diverse types of rogue wave soliton solutions have been extracted such as bright soliton, dark soliton, W-like soliton, M-like soliton, and higher-order breather soliton. Moreover, the numerical approximations for all obtained analytical traveling wave solutions have been implemented by using the Haar wavelet approach (HWA). A comparison between the obtained analytical and numerical solutions is presented. Two-dimensional and three-dimensional graphical simulations are generated using the Mathematica software. The graphical simulations demonstrates the novelty of the obtained results and facilitate the interpretation of the dynamical properties of the proposed model.

Open Access: Yes

DOI: 10.1016/j.kjs.2026.100556

Polycyclic aromatic hydrocarbons in surface water and bed sediments of the Hungarian upper section of the Danube River

István Vass Andrea Szabo´ Nagy János Szabo´ Gábor Simon

Publication Name: Environmental Monitoring and Assessment

Publication Date: 2013-06-01

Volume: 185

Issue: 6

Page Range: 4619-4631

Description:

This study was performed to elucidate the distribution, concentration trend and possible source of polycyclic aromatic hydrocarbons (PAHs) in surface water and bed sediments of the Hungarian upper section of the Danube River and the Moson Danube branch. A total of 217 samples (water and sediments) were collected from four different sampling sites in the period of 2001-2010 and analysed for the 16 priority US Environmental Protection Agency PAHs. Concentrations of total 16 PAHs (ΣPAHs) in water samples ranged from 25 to 1,208 ng/L, which were predominated by two- and three-ring PAHs. The ΣPAH concentrations in sediments ranged from 8.3 to 1,202.5 ng/g dry weight. Four-ring PAHs including fluoranthene and pyrene were the dominant species in sediment samples. A selected number of concentration ratios of specific PAH compounds were calculated to evaluate the possible sources of PAH contamination. The ratios reflected a pattern of pyrogenic input as a major source of PAHs. The levels of PAHs determined were compared with other sections of the Danube and other regions of the world. © 2012 Springer Science+Business Media Dordrecht.

Open Access: Yes

DOI: 10.1007/s10661-012-2892-6

REVISION OF THE ORIBATID MITE GENUS AMBOROPPIA (ACARI, ORIBATIDA, OPPIIDAE), WITH DESCRIPTION OF A NEW SUBGENUS AND SPECIES FROM MEXICO

Sergey G. Ermilov Jenő Kontschán

Publication Name: Acta Zoologica Academiae Scientiarum Hungaricae

Publication Date: 2023-01-01

Volume: 69

Issue: 4

Page Range: 313-321

Description:

A new oribatid mite subgenus of the genus Amboroppia (Oribatida, Oppiidae) –A. (Quintanoppia) subgen. n., with A. (Quintanoppia) defectofossulata sp. n. as type species – is described, based on material collected from Mexico. It can be distinguished from the nominate subgenus by the absence concavities between rostrum and transcostula and behind transcostula, and the presence of strong teeth on lateral sides of prodorsum. A revised generic diagnosis, identification key and data on distribution and habitats of representatives of Amboroppia are presented.

Open Access: Yes

DOI: 10.17109/AZH.69.4.313.2023

Proximal Policy Optimization-based Task Offloading Framework for Smart Disaster Monitoring using UAV-assisted WSNs

Dragan Pamucar Rajesh Kumar Dhanaraj C. N. Vanitha Mahmoud Ahmad Al-Khasawneh P. Anusuya

Publication Name: Methodsx

Publication Date: 2025-12-01

Volume: 15

Issue: Unknown

Page Range: Unknown

Description:

Unmanned Aerial Vehicles (UAVs) are increasingly employed in Wireless Sensor Networks (WSNs) to enhance communication, coverage, and energy efficiency, particularly in disaster monitoring and remote surveillance scenarios. However, challenges such as limited energy resources, dynamic task allocation, and UAV trajectory optimization remain critical. This paper presents Energy-efficient Task Offloading using Reinforcement Learning for UAV-assisted WSNs (ETORL-UAV), a novel framework that integrates Proximal Policy Optimization (PPO) based reinforcement learning to intelligently manage UAV-assisted operations in edge-enabled WSNs. The proposed approach utilizes a multi-objective reward model to adaptively balance energy consumption, task success rate, and network lifetime. Extensive simulation results demonstrate that ETORL-UAV outperforms five state-of-the-art methods Meta-RL, g-MAPPO, Backscatter Optimization, Hierarchical Optimization, and Game Theory based Pricing achieving up to 9.3 % higher task offloading success, 18.75 % improvement in network lifetime, and 27 % reduction in energy consumption. These results validate the framework's scalability, reliability, and practical applicability for real-world disaster-response WSN deployments. • Proposes ETORL-UAV: Energy-efficient Task Offloading using Reinforcement Learning for UAV-assisted WSNs • Leverages PPO-based reinforcement learning and a multi-objective reward model • Demonstrates superior performance over five benchmark approaches in disaster-response simulations

Open Access: Yes

DOI: 10.1016/j.mex.2025.103472

Integration of MULTIMOORA algorithm combined with circular q-rung orthopair fuzzy information for optimizing player positioning

Dragan Pamucar Zeeshan Ali Asma Farhad Kifayat Ullah

Publication Name: Scientific Reports

Publication Date: 2025-12-01

Volume: 15

Issue: 1

Page Range: Unknown

Description:

The following paper presents a new analytical framework for the optimization of player positioning, a methodology with significant practical implications. The method implements the multi-objective optimization by ratio analysis with full multiplicative form (MULTIMOORA) in a decision-making context in which several non-commensurable performance variables have to be combined. The application of Dombi operationalizes the framework by prioritizing weighted aggregation operators coupled with circular q-rung orthopair fuzzy sets (Cq-ROFSs). The Cq-ROFSs allow multidimensional representation of uncertainty, and allow dynamic actions upon the fuzzy parameter q, such that both intuitionistic fuzzy sets and Pythagorean fuzzy sets are subsets. Two Dombi prioritized operators on Cq-ROFSs are thereby devised a Cq-ROFSs Dombi prioritized weighted averaging operator (Cq-ROFSDPWA) and a Cq-ROFSs Dombi prioritized weighted geometric operator (Cq-ROFSDPWG). Results from empirical experiments are reported that demonstrate the performance of the resulting methodology, highlighting its practical relevance. The fundamental properties of these operators are also examined. The proposed aggregation operators are applied within the MULTIMOORA technique to assess their effectiveness. Numerical examples demonstrate that the methods yield logical and consistent results across different decision-making scenarios. Comparative analyses further highlight the advantages of the Cq-ROFSDPWA and Cq-ROFSDPWG operators over existing approaches.

Open Access: Yes

DOI: 10.1038/s41598-025-18795-0

Artificial Intelligence in the Learning Process of the Subject 'Didactics' with Special Regard to Preparation for Oral Examinations

Laszlo Kadocsa Gyula Gubán Levente Juhász Gyorgy Molnar

Publication Name: Cinti 2025 IEEE 25th International Symposium on Computational Intelligence and Informatics Proceedings

Publication Date: 2025-01-01

Volume: Unknown

Issue: Unknown

Page Range: 319-326

Description:

The issue of higher education examinations, particularly oral examinations, has been addressed in numerous studies as early as the 1970s. Both Hungarian and international experts in educational science drew attention to a number of questions concerning higher education, including the problems related to assessment. This topic has remained a key area of inquiry in higher education, and in recent times it has become an acute issue again, particularly with the rise of objective assessment methods and the opportunities offered by computerbased testing. The aim of our study is to present: the application of AI in the learning process of the subject of Didactics, in students' preparation for examinations; the areas of student use and their opinions regarding the learning of Didactics; and the experiences drawn from the analysis of exam results and exam outlines. Our research methods include literature review, the use of artificial intelligence support, student questionnaires, and the analysis of exam outlines.

Open Access: Yes

DOI: 10.1109/CINTI67731.2025.11311837

VARIOUS APPROACHES TO INFLUENCE MELATONIN LEVEL IN SHEEP REPRODUCTION

Zsolt Becskei Dóra Fürlinger Anikó Móczáné Pleskó Edina Kárpáti András Gáspárdy László Gulyás

Publication Name: Veterinarski Glasnik

Publication Date: 2023-01-01

Volume: 77

Issue: 1

Page Range: 16-34

Description:

A new field of research in reproductive biology was heralded by the discovery of melatonin in 1958. The concentration of melatonin follows light-dark cycles with significantly higher concentrations during darkness. The authors present the importance of the melatonin protein hormone by focusing on the reproductive processes in domestic sheep. In their literature review, they report that sheep melatonin levels show daily and seasonal rhythms. In sheep as a seasonal breeder and short-day animal species, seasonal increases in melatonin production stimulate sexual activity. The authors describe innovative possibilities for regulating melatonin levels in sheep production. The use of exogenous melatonin brings forward the expression of the sexual cycle. It increases the fertility rate, the number of lambs born, and the chances of survival of twin lambs. Melatonin is a neuroprotection compound against cerebral hypoxia and the development of inflammatory processes in the growing foetus and the newborn lamb.

Open Access: Yes

DOI: 10.2298/VETGL220308007K