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Publications - 6374

Finite element analysis of switched reluctance motor with rotor position based control

Miklós Kuczmann Daniel Marcsa

Publication Name: Pollack Periodica

Publication Date: 2016-12-01

Volume: 11

Issue: 3

Page Range: 153-164

Description:

This research presents a field-circuit coupled parallel finite element model of a switched reluctance motor embedded in a simple closed loop control system. The parallel numerical model is based on the Schur-complement method coupled with an iterative solver. The used control system is the rotor position based control, which is applied to the FEM model. The results and parallel performance of the voltage driven finite element model are compared with the results from the current driven model. Moreover, the results of the start-up of the loaded motor show why the model accuracy is important in the control loop.

Open Access: Yes

DOI: 10.1556/606.2016.11.3.14

Adaptive Highway Traffic Management: A Reinforcement Learning Approach for Variable Speed Limit Control with Random Anomalies

Bálint Kővári Bálint Pelenczei István Gellért Knáb László Palkovics Tamás Bécsi

Publication Name: Proceedings of the International Conference on Informatics in Control Automation and Robotics

Publication Date: 2024-01-01

Volume: 2

Issue: Unknown

Page Range: 117-124

Description:

Efficient traffic flow management on highway scenarios is crucial for ensuring safety and minimizing emissions through the reduction of so-called shockwave effects. In this paper, we propose a novel approach based on cooperative Multi Agent Reinforcement Learning for optimizing traffic flow, utilizing Variable Speed Limit Control in dynamic simulation environments with random anomalies. Our method leverages Reinforcement Learning to adaptively adjust speed limits on distinct road sections in response to alternating traffic conditions, thereby improving not only general traffic flow parameters, but also reducing sustainability measures overall. Through extensive simulations in a Simulation of Urban MObility environment, we demonstrate the superiority of our approach in enhancing traffic flow efficiency and robustness compared to alternative solutions found in literature. Our findings reveal an enhanced performance of RL-based VSL control over traditional approaches due to its generalizability, which contributes to the progression of Intelligent Transportation Systems by presenting a proactive and adaptable resolution for highway traffic management within dynamic real-world contexts.

Open Access: Yes

DOI: 10.5220/0012920700003822

Towards the resilience quantification of (military) unmanned ground vehicles

Áron Ballagi Árpád Tóth Rudolf Krecht Alex Suta

Publication Name: Cleaner Engineering and Technology

Publication Date: 2023-06-01

Volume: 14

Issue: Unknown

Page Range: Unknown

Description:

In the case of Unmanned Ground Vehicles (UGVs), resilience can be an economical, an environmental, but most importantly, a mission-critical question as well: mission failure caused by the lack of resilience in some cases might imply the loss of the UGV, which could lead to human and financial losses and environmental damage. Thus, the aim of this article is to provide a methodology for UGV resilience analysis by introducing a generalizable method that can be applied both for complete UGV systems and subsystems, and leads to resilience quantification. After proposing a specific resilience definition for UGVs, this article proposes a method for UGV resilience assessment using process graphs, created based on the system components and the expected behavior of UGVs. To provide a context for the introduced solution, existing methods applied for UGV resilience assessment are briefly mentioned. The application of the proposed method is showcased on the perception subsystem of a UGV, finalized with the evaluation of the achieved results.

Open Access: Yes

DOI: 10.1016/j.clet.2023.100644

Comparison of the results of bioelectric impedance analysis (BIA) and the anthropometry (Drinkwater-Ross & Parizkova) method in young elite athletes

Balázs Fügedi László Suszter Zsolt Szakály

Publication Name: Journal of Physical Education and Sport

Publication Date: 2023-01-01

Volume: 23

Issue: 1

Page Range: 247-254

Description:

BACKGROUNDː The literature provides relatively few and incomplete studies on comparisons of body composition measurement procedures, especially when related to sport experience, gender and age. The purpose of this study was to compare and contrast the applicability of the bioelectric impedance (BIA) and the fourcomponent anthropometry (Drinkwater-Ross) methods among young athletes. METHODSː 142 school-aged competitive athletes (nmale=71; nfemale=71, Mage=11.72±2.33) from a suburb in Hungary participated in the study. Data collection included standard Drinkwater-Ross anthropometric fractionation (bone mass, muscle and fat mass, and residual mass, estimated by equations) and bioelectrical impedance analysis with measured muscle mass (SMM_Inbody) and body fat percentage (PBF%Inbody) methods. In order to better understand the higher standard correlations of the methods, Parízkova percentage of body fat (Parízkova BF%) was also included in the analysis. Data analysis was performed by gender and age range. RESULTSː According to the data, it seems that the muscle mass estimated by BIA (SMM Inbody) is higher than the Drinkwater-Ross estimation (eMM) both in males and females and in each age-group. Also, muscle mass is overestimated, meanwhile body fat% (PBF% Inbody) is underestimated by BIA compared to Parízkova BF%. However, our results show significant correlations (0.60.9, p<.001) between estimated fat mass and muscle mass in all cases (eMM, eFM); similarly, the estimated body fat percentages in all cases were strongly correlated (Parízkova BF% and PBF% Inbody). CONCLUSIONSː Correlational analyses proved that estimation of body fat mass, muscle mass, and percentage of body fat by BIA measurement are closely associated with both Drinkwater-Ross anthropometric fractionation and Parízkova. Our findings suggest that the (BIA) predictive performance is equally appropriate as other reference techniques (e.g. Drinkwater-Ross, Parízkova) in the case of young athletes. Consequently, both the device (bioelectrical impedance device) and the ease of use of the results make for a truly user-friendly and scientifically supported procedure.

Open Access: Yes

DOI: 10.7752/jpes.2023.01030

Numerical methods for digitally synthetic holograms

Lotfi Abdelhakim

Publication Name: Civil Comp Proceedings

Publication Date: 2012-01-01

Volume: 100

Issue: Unknown

Page Range: Unknown

Description:

The main purpose of this paper is to develop a program package which generates artificial holograms by numerical methods and these computer generated holograms are numerically reconstructed. For the calculation of light propagation needed in the generation of holograms or in the reconstruction of the object from the hologram, two strategies are used. The first is the Fourier-based algorithm where the diffraction integral is approximated as a convolution integral, allowing computation using the fast Fourier transform algorithm. The second uses finite difference discretization to solve the parabolic wave equation. Numerical tests that assess the accuracy of these algorithms are presented. © Civil-Comp Press, 2012.

Open Access: Yes

DOI: DOI not available

Efficiency and accuracy investigation of the Craig-Bampton method through continuum vibration tests

Péter Horváth

Publication Name: Aip Conference Proceedings

Publication Date: 2018-01-05

Volume: 1922

Issue: Unknown

Page Range: Unknown

Description:

The paper investigates and shows the efficiency and accuracy of the Craig-Bampton model order reduction method on the analysis of a cantilever beam and rod with harmonic excitation. The results of different finite element- and Craig-Bampton models are compared to the analytical (closed-form) continuum vibration results as reference.

Open Access: Yes

DOI: 10.1063/1.5019121

Assessment of Advanced Machine and Deep Learning Approaches for Predicting CO2 Emissions from Agricultural Lands: Insights Across Diverse Agroclimatic Zones

Tamás Ratonyi Attila Vad Endre Harsányi Manouchehr Gorji Sana Arshad Adrian Nagy Safwan Mohammed Morad Mirzaei Firas Alsilibe Main Al-Dalahme

Publication Name: Earth Systems and Environment

Publication Date: 2024-12-01

Volume: 8

Issue: 4

Page Range: 1109-1125

Description:

Prediction of carbon dioxide (CO2) emissions from agricultural soil is vital for efficient and strategic mitigating practices and achieving climate smart agriculture. This study aimed to evaluate the ability of two machine learning algorithms [gradient boosting regression (GBR), support vector regression (SVR)], and two deep learning algorithms [feedforward neural network (FNN) and convolutional neural network (CNN)] in predicting CO2 emissions from Maize fields in two agroclimatic regions i.e., continental (Debrecen-Hungary), and semi-arid (Karaj-Iran). This research developed three scenarios for predicting CO2. Each scenario is developed by a combination between input variables [i.e., soil temperature (Δ), soil moisture (θ), date of measurement (SD), soil management (SM)] [i.e., SC1: (SM + Δ + θ), SC2: (SM + Δ), SC3: (SM + θ)]. Results showed that the average CO2 emission from Debrecen was 138.78 ± 72.04 ppm (n = 36), while the average from Karaj was 478.98 ± 174.22 ppm (n = 36). Performance evaluation results of train set revealed that high prediction accuracy is achieved by GBR in SC1 with the highest R2 = 0.8778, and lowest root mean squared error (RMSE) = 72.05, followed by GBR in SC3. Overall, the performance MDLM is ranked as GBR > FNN > CNN > SVR. In testing phase, the highest prediction accuracy was achieved by FNN in SC1 with R2 = 0.918, and RMSE = 67.75, followed by FNN in SC3, and GBR in SC1 (R2 = 0.887, RMSE = 79.881). The performance of MDLM ranked as FNN > GRB > CNN > SVR. The findings of the research provide insights into agricultural management strategies, enabling stakeholders to work towards a more sustainable and climate-resilient future in agriculture.

Open Access: Yes

DOI: 10.1007/s41748-024-00424-x

Telemedicine adoption in Hungary: insights from two representative population surveys (2021–2024)

Bence Döbrössy Zsuzsa Győrffy Edmond Girasek

Publication Name: BMC Health Services Research

Publication Date: 2026-12-01

Volume: 26

Issue: 1

Page Range: Unknown

Description:

Background: Despite increased interest, data on telemedicine adoption and patterns of use remain scarce. This study aims to fill this gap by analysing sociodemographic trends in telemedicine use in Hungary between 2021 and 2024. Methods: Two nationwide representative surveys were conducted in Hungary: a Computer Assisted Telephone Interview (CATI) with 1,500 participants in October 2021 and an online survey with 1,100 participants in February 2024. Both samples were stratified by gender, age, settlement type, and education. A Telemedicine Index, encompassing (a) online appointment booking and referral requests (b) video or phone teleconsultations (c) email communication with the doctor (d) sharing images with the doctor (e) sharing medical documentation with the doctor and (f) allowing the doctor to monitor changes in health status via smartphone was constructed. Statistical analyses included descriptive statistics, ANOVA, and multinomial logistic regression to assess sociodemographic factors associated with telemedicine use. Results: Telemedicine adoption increased between 2021 and 2024. The Telemedicine Index rose from Mean = 1.025 to Mean = 1.702. The proportion of non-users dropped from 43.5% to 21.0%. While initial disparities in 2021 showed women, younger individuals, higher educated people and urban residents using telemedicine more, these gaps narrowed significantly by 2024. Family support, indicated by living with a partner, positively influenced telemedicine adoption in both periods, emphasizing its role in facilitating use, especially among older adults and those with children. Analysis confirmed that education, age, gender, and family status are significantly associated with telemedicine use. Conclusion: Telemedicine has become increasingly integrated into Hungarian healthcare, with a shift from pandemic-driven necessity to broader societal adoption. While sociodemographic disparities persist, they have largely narrowed. The crucial role of social and family support in facilitating telemedicine use, particularly for vulnerable groups, highlights a key area for future interventions.

Open Access: Yes

DOI: 10.1186/s12913-026-14262-2

Effect of a five-week beta-alanine supplementation on the performance, cardio-respiratory system, and blood lactate level in well-trained rowing athletes: A double-blind randomized pre–post pilot study

Ferenc Ihász Erzsébet Mák Márta Veresné Bálint Dóra Nagy László Suszter Zsolt Szakály Zoltán Alföldi

Publication Name: Journal of Physical Education and Sport

Publication Date: 2020-09-01

Volume: 20

Issue: 5

Page Range: 2501-2507

Description:

Intense exercise by top-level athletes significantly lowers the pH of muscle and blood, which leads to fatigue. Beta-alanine (BA) supplementation can increase carnosine levels in skeletal muscle, which can delay a decrease in pH in the muscles. Previous studies have shown that multiple doses of BA supplementation were effective for people of different physical fitness and age. The purpose of this double-blind, randomized, controlled study is to investigate the effect of a five-week BA supplementation on well-trained, experienced rowing athletes at approximately the median dose of previous studies, which determined that 50 mg day−1 kg−1 of body weight was an effective daily dose. Two groups were formed in the spiroergometric study. One group received BA supplementation, while the control group did not. Five weeks after the first test (T1), the second test (T2) occurred, and the blood lactate levels were measured before and after the tests (Pre[La-]b; Post[La-]b). The maximum mean values of different physiological load parameters showed no significant difference. In the BA group, the mean lactate level was significantly lower after the T2 measurement (Post[La-]b) compared to those of T1 (P = 0.01) and the control group, i.e., T1 (P = 0,008), T2 (P = 0,028). The mean time and performance of the second measurement of the BA group increased [T1 = 582,7 ± 88,2 (s); T2 = 636,4 ± 106,6 (s)] but the result is not significant. In summary, the five-week dose of 50 mg day−1 kg−1 of body weight, which is 3.845 day−1 for the group average, lowers the blood lactate levels after the tests (Post[La-]b) but does not increase the athlete's performance. For well-trained athletes, during a five-week supplementation, it is not advisable to lover the value below 4–6 g day−1 with the dietary supplement to achieve an ergogenic effect.

Open Access: Yes

DOI: 10.7752/jpes.2020.05341