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Publications - 6374

Critical impact of automobile industry with advanced decision support system and Aczél-Alsina Hammy mean operators

Dragan Pamucar Zeeshan Ali Abrar Hussain Kifayat Ullah

Publication Name: Scientific Reports

Publication Date: 2026-12-01

Volume: 16

Issue: 1

Page Range: Unknown

Description:

The automobile industry plays a pivotal role in global economic development, technological innovation, and sustainable mobility solutions. It drives advancements in engineering, manufacturing, and smart technologies and influences transportation systems. A decision analysis system in the automobile industry serves as a structured framework to evaluate complex choices involving design, production, supply chain, marketing, and sustainability strategies based on vague human information. To achieve the main goal of this article, we explore the concepts of spherical fuzzy sets (SFSs) for handling uncertainty and vagueness in human judgments. The SFS is a more efficient and broader fuzzy framework that has extensive information about an object. Besides the concepts discussed in the fuzzy framework, we also modify the theory of Hamy mean (HM) models under Aczel Alsina operations. By combining two different theories of Aczel Alsina operations and Hamy mean models, we derive a family of mathematical models, namely spherical fuzzy Aczel Alsina Hamy mean (SFAHM) and spherical fuzzy Aczel Alsina weighted Hamy mean (SFAWHM) operators. Moreover, another generalization of the Dual HM (DHM) models is modified in the form of spherical fuzzy Aczel Alsina DHM (SFADHM) and spherical fuzzy Aczel Alsina weighted DHM (SFAWDHM) operators. Some reliable and appropriate characteristics are also studied to demonstrate the flexibility of the proposed operators. An intelligent decision algorithm of the multi-attribute group decision-making (MAGDM) problem is discussed to resolve real-life applications and a group of expert’s opinions. To see the effectiveness and reliability of newly developed terminologies, we discussed a numerical example to choose desirable alternatives under an automobile industry system. The influence study is also presented here by setting numerous parametric values in the currently discussed methodologies. To showcase the validation and superiority of diagnosed mathematical models, we establish a comparative study to compare the results of invented approaches with the results of existing terminologies.

Open Access: Yes

DOI: 10.1038/s41598-025-24344-6

Exchange rate impacts on international trade

Laszlo Vasa Robert Magda Jalil Mehtiyev

Publication Name: Economic Annals Xxi

Publication Date: 2021-07-10

Volume: 190

Issue: 5

Page Range: 12-22

Description:

As international trade activities are increased, there are more regulative practices which might be barriers to trade. One of such hindrances is exchange rate volatility that afects trade activities both directly and indirectly. Exchange rate volatility of currencies can afect the trade engagements and as well as the trade balance of a country. One of the implications of the study is that the impacts of monetary policy changes on trade activities can be noticed signifcantly in the long-term. While impacts on export levels are usually immediate, import levels are changed in long-run. The research analyzes the correlation between infation and devaluation and clearly states their impacts on trade balance. The case study about devaluation of the currency of Azerbaian elaborates the impacts of currency volatility on exports which is illustrated and analyzed in this research. Moreover, infation and devaluation correlations and their impacts on import level of a country are studied through correlation and multiple regression analyses based on the data exported from OECD and World Bank. The results conclude that exchange rate volatility signifcantly impacts the trade balance in terms of imports and exports. Given the results, exchange rate is a non-trade barrier and afects foreign trade.

Open Access: Yes

DOI: 10.21003/EA.V190-02

The Role of Regulatory Sandboxes in FinTech Innovation: A Comparative Case Study of the UK, Singapore, and Hungary

János Kálmán

Publication Name: Fintech

Publication Date: 2025-06-01

Volume: 4

Issue: 2

Page Range: Unknown

Description:

Regulatory sandboxes have emerged as policy instruments designed to support FinTech innovation while maintaining supervisory oversight. By allowing firms to test financial products in controlled environments, sandboxes aim to reduce regulatory uncertainty and facilitate market entry. Despite their growing adoption, empirical evidence of their effectiveness remains limited, particularly in emerging markets. This study explores the impact of regulatory sandboxes on innovation and market access through a qualitative comparative case study of the United Kingdom, Singapore, and Hungary. Drawing on document analysis and thematic coding, the research evaluates sandbox design, regulatory support, and innovation outcomes across the three jurisdictions. Findings show that sandboxes enhance access to funding, accelerate product development, and foster regulator–firm collaboration. While the UK and Singapore benefit from mature ecosystems and structured frameworks, Hungary illustrates sandbox potential in developing markets. The paper contributes to FinTech regulation literature and provides policy recommendations for optimizing sandbox design across varied institutional contexts.

Open Access: Yes

DOI: 10.3390/fintech4020026

Computational Wear Prediction in Total Knee Replacements as a Function of Replacement Size

Natalia Dilna Gusztáv Fekete Hai Qiao Wang Márton Máté Izolda Popa-Müller Karol Nemoga

Publication Name: Advances in Transdisciplinary Engineering

Publication Date: 2024-01-01

Volume: 59

Issue: Unknown

Page Range: 494-500

Description:

Wear is the third most important factor that restricts the longevity of total knee replacements (TKRs). Wear is particularly influenced by load, local kinematics between the contact surfaces and presumably by the geometry of the contact surfaces. This article investigated, by means of multibody models, how wear in total knee replacements is affected by the size of a TKR or by TKR-related geometric parameters during gait motion. As a result, it has been established that wear rate increases linearly as a function of TKR size, while the impact of TKR-related geometric parameters can be described by linear or quadratic functions. One can conclude that the newly introduced dimensionless parameters can provide guidelines to effectively minimize wear in TKRs.

Open Access: Yes

DOI: 10.3233/ATDE240585

Eddy current analysis with nonlinearity

Miklós Kuczmann Daniel Marcsa

Publication Name: Pollack Periodica

Publication Date: 2008-08-01

Volume: 3

Issue: 2

Page Range: 97-109

Description:

The paper deals with an eddy current field problem as a case study. The aim is to find the solution of the problem by the help of the Finite Element Method (FEM), and the T, , potential formulation taking the nonlinearity of the material into account. The effect of nonlinearity has been approximated with an inverse tangent type analytical model. The nonlinearity has been handled by the polarization method coupled with the Fixed-point iteration technique. © 2008 Akadémiai Kiadó.

Open Access: Yes

DOI: 10.1556/Pollack.3.2008.2.9

AI-powered biomechanical modeling for ACL-reconstructed knees: predicting knee joint contact forces via computer vision and deep learning

Yaodong Gu Gusztáv Fekete Meizi Wang Liangliang Xiang Datao Xu Huiyu Zhou Tianle Jie Zhifeng Zhou Tianxiao Chen Qincheng Ge Yi Yuan Ukadike Chris Ugbolue

Publication Name: Journal of Neuroengineering and Rehabilitation

Publication Date: 2026-12-01

Volume: 23

Issue: 1

Page Range: Unknown

Description:

Background: Patients undergoing anterior cruciate ligament reconstruction (ACLR) are at high risk of osteoarthritis or secondary injuries, with abnormal knee contact forces (KCFs) identified as a key factor in joint degeneration. Traditional KCF assessment relies on expensive lab systems while advances in computer vision and AI now enable low-cost alternatives. However, currently available methods oversimplify knee mechanics and neglect compensatory movements, highlighting the urgent need for intelligent, real-time monitoring tools for personalized rehabilitation. Therefore, the aim of this study was to develop and validate an integrated, non-invasive framework for accurate KCFs prediction in ACLR patients during daily activities. We hypothesized that combining enhanced musculoskeletal modeling with a deep learning architecture incorporating spatiotemporal attention would improve the prediction accuracy across multiple movement tasks. Methods: This study simultaneously recorded three daily movements of 29 post-ACLR patients using both Vicon and OpenCap. Motion trajectories captured by Vicon were imported into OpenSim for musculoskeletal modeling and KCFs calculation. Dataset comprising OpenCap-derived kinematics and OpenSim-computed KCFs was used to train 3 learning models for the prediction of KCFs in ACLR patients across different movements. Results: Among three models, CNN-BiGRU-Attention model demonstrated the best predictive performance across all three movement tasks (R2walking = 0.973 ± 0.003, R2running = 0.982 ± 0.004, R2descending stairs = 0.951 ± 0.007). CNN and self-attention mechanism collectively enhanced the model's ability to capture key features in ACLR patients' movement data, thereby improving KCF prediction accuracy. Furthermore, for the three daily activities, all models showed superior KCFs prediction performance in running and stair-descent tasks compared to walking. Conclusion: The developed framework successfully achieved high-precision prediction of KCFs. This technological breakthrough not only provides a real-time quantitative tool for rehabilitation monitoring in patients with ACLR, but also facilitates a paradigm shift from static laboratory analysis to dynamic real-time monitoring, with broad application prospects in sports medicine, rehabilitation engineering.

Open Access: Yes

DOI: 10.1186/s12984-026-01939-2

Scalar hysteresis measurement using FFT

Miklós Kuczmann

Publication Name: Journal of Optoelectronics and Advanced Materials

Publication Date: 2008-01-01

Volume: 10

Issue: 7

Page Range: 1828-1833

Description:

The paper deals with a possible realization of eliminating the effect of noise in scalar hysteresis measurements. The measured signals have been transformed into the frequency domain, and after applying digital filter, the spectrums of the filtered signals have been transformed back to the time domain. The proposed technique results in an accurate noise removal algorithm. The paper illustrates a fast controlling algorithm applying the inverse of the actually measured hysteresis loop, and another proportional one to measure distorted flux pattern. Developing the mentioned algorithms aims the controlling of more complicated phenomena, i.e. measuring the vector hysteresis characteristics.

Open Access: Yes

DOI: DOI not available

Big data in the food supply chain: a literature review

John G. Keogh Abderahman Rejeb Karim Rejeb

Publication Name: Journal of Data Information and Management

Publication Date: 2022-03-01

Volume: 4

Issue: 1

Page Range: 33-47

Description:

The emergence of big data (BD) offers new opportunities for food businesses to address emerging risks and operational challenges. BD denotes the integration and analysis of multiple data sets, which are inherently complex, voluminous and are often of inadequate quality and structure. While BD is a well-established method in supply chain management, academic research on its application in the food ecosystem is still lagging. To fill this knowledge gap and capture the latest developments in this field, a systematic literature review was performed. Forty-one papers were selected and thoroughly examined and analysed to identify the enablers of BD in the food supply chain. The review primarily attempted to obtain an answer to the following research question: “What are the possibilities of leveraging big data in the food supply chain?“ Six significant benefits of applying BD in the food industry were identified, namely, the extraction of valuable knowledge and insights, decision-making support, improvement of food chain efficiencies, reliable forecasting, waste minimization, and food safety. Finally, some challenges and future research directions were outlined.

Open Access: Yes

DOI: 10.1007/s42488-021-00064-0

Shear Buckling Resistance of I-Beams with Partially Stiffened Webs

G. Hajdú Hartmut Pasternak

Publication Name: Advances in Transdisciplinary Engineering

Publication Date: 2024-01-01

Volume: 59

Issue: Unknown

Page Range: 358-365

Description:

This paper presents the results of laboratory tests and numerical analysis for plate girders with partial height end stiffeners. Design rules for rigid end posts and non-rigid end posts are given in EN 1993-1-5:2006 but the shear resistance of partially stiffened webs is not mentioned. The use of non-tightly fitted stiffeners is hazardous due to insufficient investigations of the real behaviour. To discover this problem parametric studies on beams with different web slenderness are examined with the usage of advanced numerical simulations. The accuracy of the EN 1993-1-5:2006 standard design rule for partially stiffened beams is also examined. The results of the numerical simulations shows that the shear buckling capacity of girders is lower than the design recommendation where the height of the web stiffener is b5% of the web height. For girders with full height stiffeners the EN 1993-1-5:2006 standard leads conservative results.

Open Access: Yes

DOI: 10.3233/ATDE240567