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Found 6674 publications

The impact of historical traditions on the regulation and practice of the preferential naturalization of Hungarians living outside the borders

Mónika Ganczer

Publication Name: Hungarian Journal of Legal Studies

Publication Date: 2023-06-19

Volume: 63

Issue: 4

Page Range: 352-373

Description:

The study presents the impact of the historical origin of the making and application of law through a specific example. The regulation of nationality, a pivotal field of constitutional law, is considered a sovereign right of the Hungarian state which is exercised in line with Article G) of the Fundamental Law and Act No. LV of 1993 on Hungarian Citizenship. Hungarian naturalization practice, however, significantly changed in the wake of the amendment of the respective act: Hungarians living outside the borders have been entitled to preferential naturalization since 2011. This study aims to prove that this legislative action, which remarkably followed the designation of the day of the conclusion of the Trianon Peace Treaty as the Day of National Unity the previous year, was obviously influenced by historical considerations. The primary objective of preferential naturalization was to grant Hungarian nationality to persons of Hungarian origin whose ancestors had lost their Hungarian nationality in the aftermath of historical events involving the transfer of territories to neighbouring states. The study's point of departure is the Trianon Peace Treaty, the first major instrument to have a profound effect on the nationality of millions of Hungarians. The study explores the peculiar interpretation and application of treaty provisions relating to territorial changes and reveals the flaws in legal regulation which further contributed to the formation of a large community of Hungarians living outside the borders. Having surveyed the historical background, the analysis proceeds to examine the impact of historical traditions on the underlying motives and current domestic regulation of preferential naturalization. Evidence includes the broad scope of eligible persons, the wide range of documents accepted to prove descent, the verification of the required command of language, and the practical implementation of the procedure of naturalization. Research findings convincingly display the far-reaching effects of historical traditions on the regulation and practice of preferential naturalization in Hungary.

Open Access: Yes

DOI: 10.1556/2052.2023.00412

Strategic Business Resilience Affecting Green and Renewable Energy-Related Financial Literacy in Mexico

Csongor Czipf Absalón J. Salmerón- Zapata José G. Vargas- Hernandez

Publication Name: Data Driven Esg Strategy Implementation Through Business Intelligence

Publication Date: 2025-08-12

Volume: Unknown

Issue: Unknown

Page Range: 87-114

Description:

This research investigates the multifaceted relationship between strategic business resilience and financial literacy in the green and renewable energy industry of Mexico. As Mexico transitions to sustainable energy sources, it is ever more critical to comprehend how companies formulate resilience strategies while maintaining financial literacy for industry growth and economic stability. The key findings indicate that companies with robust resilience mechanisms exhibit enhanced capacity for financial planning, risk assessment, and investment decision- making in renewable energy projects. The study identifies critical factors like adaptive leadership, technology integration, stakeholder engagement, and adherence to regulations as primary drivers of both resilience and financial literacy.

Open Access: Yes

DOI: 10.4018/979-8-3373-5142-1.ch004

Comparison of the English and German Concepts of Contract

Judit Beck

Publication Name: Journal on European History of Law

Publication Date: 2025-01-01

Volume: 16

Issue: 2

Page Range: 87-93

Description:

This paper focuses on the English and German concepts of contract. Among other things, our aim is to examine the relationship between the concept of contract and imperial imperialism. In the course of the study, we examine the development and evolution of contract concepts, as well as some similarities and differences between English and German contract law. Among our aims is to show that there is a link between the development of the field of contract law and imperialism. In the course of the study, we will primarily apply the historical and comparative legal methodologies.

Open Access: Yes

DOI: DOI not available

Optimization of Tribological Properties in Cement Dust and Rock Wool Reinforced Composites: Experimental Study and Decision-Making Analysis

Gusztáv Fekete Vedant Singh Meizi Wang Sharafat Ali Tej Singh

Publication Name: Journal of Composites Science

Publication Date: 2026-06-01

Volume: 10

Issue: 6

Page Range: Unknown

Description:

This study investigates the effect of waste cement dust (CD) and rock wool (RW) inorganic fiber on the tribological performance of brake friction composite materials. Five formulations were fabricated by varying CD from 65 to 45 wt.% and RW from 5 to 25 wt.% and evaluated for tribological properties on a Chase friction testing machine in accordance with IS 2742 test procedures. The results show that composites containing higher CD and lower RW exhibited higher coefficients of friction, lower friction variability, and improved fade resistance. In contrast, composites containing higher RW and lower CD showed improved recovery characteristics and substantially enhanced wear resistance. The performance coefficient of friction decreased from about 0.521 to 0.442 as the formulation shifted from CD-rich to RW-rich compositions, while the variability coefficient increased from about 0.364 to 0.516. The highest wear was recorded for the composite containing 65 wt.% CD and 5 wt.% RW inorganic fiber, whereas the lowest friction fluctuations were obtained for the composite containing 55 wt.% CD and 15 wt.% RW inorganic fiber. Finally, a simple ranking process-based decision-making technique was employed to evaluate the overall performance of all the composites, suggesting 55 wt.% CD as the optimal content. These findings confirm the potential of waste CD as a viable functional constituent in brake friction composites when combined with RW inorganic fiber in an optimized manner.

Open Access: Yes

DOI: 10.3390/jcs10060317

Localization robustness improvement for an autonomous race car using multiple extended Kalman filters

Krisztian Enisz Erno Horváth Istvan Szalay

Publication Name: Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering

Publication Date: 2025-08-01

Volume: 239

Issue: 9

Page Range: 3771-3783

Description:

In this paper, we introduce a vehicle localization method designed for the SZEnergy race car, which competes in the Shell Eco-marathon. The proposed method comprises four different extended Kalman filter-based localization algorithms and a selection algorithm that determines the most suitable one based on vehicle speed, GNSS availability, and signal quality. The low-speed Kalman filters are based on a kinematic vehicle model while the high-speed variants are based on a dynamic vehicle model. Several measurements were performed during test maneuvers to evaluate the performance of the filters. The proposed method succesfully handles sensor miscalibration and GNSS outages.

Open Access: Yes

DOI: 10.1177/09544070241266281

Innovation Allocation Dilemma: AI, R&D, and Policy Effects on U.S. Renewable Electricity

József Poór Mohammad Fakhrul Islam Md Emon Ahmed Clapher Ankur Gomes Clinton Anthony Heaven Gomes Md Zahid Hasan

Publication Name: Journal of Human Earth and Future

Publication Date: 2026-06-01

Volume: 7

Issue: 2

Page Range: 292-311

Description:

Despite holding the world's second-largest portfolio of green technology patents, the U.S. is still behind the developed economies in energy efficiency outcomes, which is responsible for creating an innovation allocation dilemma in renewable electricity deployment. This study addresses the fundamental question of the optimal resource allocation among competing innovation pathways by investigating the comparative impacts of artificial intelligence (AI) innovation, green technology innovation (GTI), research and development (R&D) expenditures, and environmental policy stringency (EPS) have on the U.S. renewable electricity contribution rate (ECR) over a period of 33 years (1990-2022). Applying the autoregressive distributed lag (ARDL) model, this study highlights the fact that the interaction between R&D investment and per capita gross domestic product (GDP) significantly influences ECR with a long-term elasticity of about 91%. Second, EPS also has a highly significant and robust elasticity of about 62% for ECR gains. AI innovation, however, shows mixed effects: the initial positive short-run contributions fade away in the long run without sustained complementary investments. With respect to asymmetric effects, negative shocks convey larger benefits to renewable energy than positive ones, a finding that questions the conventional technology deployment. The findings support policymakers making R&D investments a priority over patent-based strategies, reallocating government expenditures from direct spending to market mechanisms.

Open Access: Yes

DOI: 10.28991/HEF-2026-07-02-01

Customer sentiment analysis and prediction of halal restaurants using machine learning approaches

Mst Farjana Rahman Md Shamim Hossain Md Kutub Uddin Kamal Hossain

Publication Name: Journal of Islamic Marketing

Publication Date: 2023-06-07

Volume: 14

Issue: 7

Page Range: 1859-1889

Description:

Purpose: There is a strong prerequisite for organizations to analyze customer review behavior to evaluate the competitive business environment. The purpose of this study is to analyze and predict customer reviews of halal restaurants using machine learning (ML) approaches. Design/methodology/approach: The authors collected customer review data from the Yelp website. The authors filtered the reviews of only halal restaurants from the original data set. Following cleaning, the filtered review texts were classified as positive, neutral or negative sentiments, and those sentiments were scored using the AFINN and VADER sentiment algorithms. Also, the current study applies four machine learning methods to classify each review toward halal restaurants into its sentiment class. Findings: The experiment showed that most of the customer reviews toward halal restaurants were positive. The authors also discovered that all of the methods (decision tree, linear support vector machine, logistic regression and random forest classifier) can correctly classify the review text into sentiment class, but logistic regression outperforms the others in terms of accuracy. Practical implications: The results facilitate halal restaurateurs in identifying customer review behavior. Social implications: Sentiment and emotions, according to appraisal theory, form the basis for all interactions, facilitating cognitive functions and supporting prospective customers in making sense of experiences. Emotion theory also describes human affective states that determine motives and actions. The study looks at how potential customers might react to a halal restaurant’s consensus on social media based on reviewers’ opinions of halal restaurants because emotions can be conveyed through reviews. Originality/value: This study applies machine learning approaches to analyze and predict customer sentiment based on the review texts toward halal restaurants.

Open Access: Yes

DOI: 10.1108/JIMA-04-2021-0125

Wear Scar Classification with Convolutional Neural Network

A. L. Nagy Zsolt Tabakov

Publication Name: Lecture Notes in Networks and Systems

Publication Date: 2025-01-01

Volume: 1345 LNNS

Issue: Unknown

Page Range: 13-20

Description:

This article categorizes the wear features of ball-on-disc type specimens into two classes using a Tensorflow Convolutional Neural Network network. The convolutional neural network is employed for image classification, specifically in the field of tribology, involving surface analysis and wear characterization.

Open Access: Yes

DOI: 10.1007/978-3-031-87620-2_2

Robust techno-economic optimization of energy hubs under uncertainty using active learning with artificial neural networks

Shady H.E.Abdel Aleem Aya M.A. Heikal Ragab A. El-Sehiemy Almoataz Y. Abdelaziz

Publication Name: Scientific Reports

Publication Date: 2025-12-01

Volume: 15

Issue: 1

Page Range: Unknown

Description:

Energy hubs (EHs) are considered a promising solution for multi-energy resources, providing advanced system efficiency and resilience. However, their operation is often challenged by the need for techno-economic trade-offs and the uncertainties related to supply and demand. This research presents a multi-objective optimizing framework for EH operations tackling these techno-economic aspects under uncertainty. Utilizing artificial neural networks (ANN)-based active learning (AL), the proposed approach dynamically enhances the model’s capability to achieve optimal scheduling and planning while considering complex, fluctuating energy demands and system constraints. The optimization approach under uncertainty provides robust predictive abilities across various scenarios, allowing the system to optimize energy management effectively, enhancing operational efficiency while minimizing overall energy losses, costs, and emissions. Results demonstrate significant improvements in system reliability, cost efficiency, and flexible operation, validating the effectiveness of ANN-based AL to optimize EHs management and ensure sustainable operation complexities. The AL algorithm enhances the ANN model’s predictive ability, resulting in a 57.9% decrease in operating costs and a 0.010682 loss of energy supply probability (LESP) value. It ensures energy efficiency while sustaining system flexibility, adapting to frequent load dynamics and intermittent renewable energy supply. The algorithm minimizes electrical and thermal deviations, achieving a balance of flexible operation with efficient energy management. Despite uncertainties and intermittent renewable energy supply, the AL optimizes renewables utilization and demand adjustments, reducing energy losses, costs, and emissions by 80.3The optimized system achieves an output of 13,687.8 kW per day. The system’s implementation is performed using MATLAB R2023b software, ensuring precision and efficiency.

Open Access: Yes

DOI: 10.1038/s41598-025-12358-z