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EXAMINING THE VISIBILITY OF SOCIAL RESPONSIBILITY ON THE WEBSITES OF HUNGARIAN STATE UNIVERSITIES

Adrienn Reisinger Zsolt Dános

Publication Name: Deturope

Publication Date: 2021-01-01

Volume: 13

Issue: 3

Page Range: 58-72

Description:

The paper investigates university social responsibility at Hungarian universities by examining their websites. Although the concept of university social responsibility has existed for nearly 20 years, the scope of its research and theoretical literature still falls far short of that of corporate social responsibility. There is extant literature on the topic including case studies from around the world showing the importance of university social responsibility. Nevertheless, the scope of thematic analysis of the topic is very narrow with only a few pieces of comprehensive systematic research published so far, and the theoretical literature only highlights the work of some major researchers. Due to the complexity of the topic, the amount of previous literature attempting to explore the effects of university social responsibility is also limited. The aim of this paper is to investigate how terms relating to social responsibility appear on the websites of Hungarian universities. In autumn 2019 research was carried out involving twenty-one universities. The paper analyses how social responsibility is visible on university websites based on given keywords. The research employed quantitative content analysis. The hypothesis was that based on visibility the same university categories can be formed according to the size and profile of the institutions. According to the authors’ present knowledge no such research has been carried out in Hungary so far. There are some university website researches in different countries but with different purposes with the special focus on sustainability. So the method of the present research is an attempt to find out how to measure the social responsibility visibility of universities and how to make categorizations based on the analyses. The limitation of the research is, among others, that universities have different search engines on their websites, which can lead to the misinterpretation of results. The main findings are that the visibility of social responsibility based on website analyses depends not only on the size and profile of the institutions; therefore, the investigation of visibility can contribute to the creation of new categories proving that social responsibility is far beyond the size or profile of the universities. The findings can help institutions develop the conscious communication of their social responsibility activity, and provide assistance to the research community.

Open Access: Yes

DOI: 10.32725/det.2021.019

The Labour Movement, Marxism, Northern Leftists, Feminist Socialism and Student Rebels in Nigeria, 1963-78

Adam Mayer Baba Aye

Publication Name: Revolutionary Movements in Africa an Untold Story

Publication Date: 2023-01-01

Volume: Unknown

Issue: Unknown

Page Range: 96-120

Description:

No description provided

Open Access: Yes

DOI: DOI not available

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

Miklós Kuczmann Dániel 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

Assessing Levee Stability Under Climate Change: A Case Study of Szigetköz, Ásványráró

Edina Koch Samuel Alexandro Silitonga Emmanuel Saah Tambah

Publication Name: Chemical Engineering Transactions

Publication Date: 2025-01-01

Volume: 121

Issue: Unknown

Page Range: 127-132

Description:

Levees are critical flood protection structures, safeguarding communities and ecosystems from riverine flooding. However, climate change-induced alterations in precipitation patterns, flood magnitudes, and soil stability pose significant challenges to levee performance. This study evaluates the stability and resilience of the Ásványráró levee in the Szigetköz region, northwest Hungary, under projected climate change impacts. The research employs a combination of geotechnical field data and numerical modelling to assess levee behaviour under various stress conditions. Cone Penetration Testing (CPT) was conducted to determine the geotechnical properties of levee foundation soils, providing insights into stratigraphy, permeability, and shear strength. These data were incorporated into Plaxis 2D finite element modelling to simulate flood scenarios, seepage effects, and potential failure mechanisms under different climate projections. Overall, the results showed that climate change significantly increases levee vulnerability through enhanced seepage, deformation, and hydraulic loading. Results indicate that increased flood intensity and prolonged inundation exacerbate levee instability through overtopping, seepage-induced erosion, and slope failure. The findings highlight the necessity for proactive levee reinforcement strategies and adaptive management of levee systems. This study underscores the importance of integrating climate change projections into levee design and maintenance plans, providing a framework for policymakers and engineers to enhance flood resilience in vulnerable regions. By adopting advanced geotechnical assessments and numerical simulations, the research contributes to the development of more robust and climate-adaptive flood defence systems.

Open Access: Yes

DOI: 10.3303/CET25121022

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

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

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

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