Széchenyi István University

A threshold-based spatial framework for evaluating energy and crop-light trade-offs in agrivoltaic systems

Agrivoltaic systems are increasingly considered a viable strategy to reconcile photovoltaic electricity generation with agricultural production and reduce land-use conflict. Their design requires a quantitative understanding of how layout affects both energy yield and crop-releva...

Reliability-Audited Explainable AI for Multi-Class Skin-Lesion 2 Triage Under Cross-Device Domain Shift

Background/Objectives: Reliable skin-lesion AI requires evaluation beyond the development distribution. This study assessed whether a source-developed multi-class system preserves discrimination and reliability when transferred to an unseen smartphone-acquired domain. Methods: A...

Multi-Objective Circular Economy Optimisation for Seismic Retrofit of Reinforced Concrete Shear Walls

Growing global demand for resilient and sustainable infrastructure requires seismic retrofit strategies that simultaneously enhance structural performance and minimise environmental impact. This study presents a multi-objective optimisation framework that integrates circular econ...

From resource structuring to continuance intention in food sharing apps: the moderating role of digital resources in hospitality

Purpose Food sharing apps are increasingly adopted by hospitality businesses to facilitate surplus food redistribution, improve operational coordination, and support sustainability initiatives. However, existing research has primarily focused on consumer adoption and initial plat...

From AI Compute Growth to Grid Stress: A Conditional Scenario-Screening Framework for the EU-27 and the United Kingdom to 2035

AI-led data-centre expansion requires distinctions between annual electricity, coincident power, conditional headroom exposure and emissions. We develop a scenario-screening framework for 28 European countries in 2030 and 2035. An illustrative 62.25 TWh regional benchmark combine...

Do AI and Lexicon-Based ESG Scores Converge? Evidence from IPO Prospectuses in an Emerging Market

The growing use of artificial intelligence (AI) to evaluate Environmental, Social, Governance (ESG) scoring from corporate disclosures raises questions about alignment with conventional lexicon-based scores. Such alignment can be problematic as a lexicon-based approach quantifies...

Climate resilience through economic development, energy transition and sustainable development: insights from wavelet coherence approach

Purpose Adjusted net savings (ANS) is a pivotal indicator of sustainable development, combining environmental costs, resource depletion and economic performance. While ANS fosters short-term environmental accountability, its focus on immediate economic gains may undermine long-te...

Mixed uncertainty information and volatility in the green bond market based on a new two-regime GARCH-MIDAS extension model

Purpose This study pioneers a novel two-regime Generalized Autoregressive Conditional Heteroskedasticity–Mixed Data Sampling (GARCH-MIDAS) extension model to disentangle the dual dynamics of traditional drivers and mixed uncertainty indicators in green bond market volatility. Unl...

Digital Asset Adoption and Regional Digital Inequality: Descriptive Evidence from the United States, EU-10, V4, and IMT-GT

Background Digital asset adoption varies substantially across regions despite improvements in digital infrastructure. This study examines whether digital infrastructure, financial inclusion, and regulatory clarity are associated with regional differences in digital asset adoption...

A Large-Scale Industrial End-of-Line Vibroacoustic Dataset for Electric Drive Units Under a Variable-Speed Braking Condition

End-of-line vibroacoustic testing identifies abnormal noise and vibration before an electric drive leaves production, yet public datasets rarely capture production scale, heterogeneity, repeated testing, and multiple signal domains. This Data Descriptor presents 58,249 processed...

AI knowledge capability and innovation: the power of cognitive processing and empowerment

Purpose This study aims to integrate ideas from organizational learning theory with new AI capabilities to investigate how AI-driven knowledge processes may improve innovation performance. Specifically, this study explores the process in which AI-based (AI Ba) knowledge productio...

From Benchmark Accuracy to Industrial Evidence: A Registered Systematic Map and Nested Experiment-Level Audit of Validation Credibility in AI-Based Rotating-Machinery Fault Diagnosis

Artificial intelligence (AI) methods for rotating-machinery diagnosis based on vibration and acoustic signals are often evaluated on benchmark splits that do not establish physical independence or industrial generalization. This registered study combined a PRISMA-aligned systemat...

A systematic review of the performance durability and sustainability of sugarcane bagasse ash as a mineral filler in asphalt mixtures

The increasing demand for sustainable pavement materials has stimulated interest in sugarcane bagasse ash (SCBA) as an alternative mineral filler in asphalt mixtures. This systematic review critically evaluates the mechanical performance, durability, and sustainability of SCBA-mo...

FuzzPrismEdge: dynamic resource allocation in edge AI via context-aware fuzzy gating

Abstract The use of Deep Neural Networks (DNNs) on autonomous Internet of Things (IoT) devices is bottlenecked and causes accelerated battery degradation, memory exhaustion and thermal throttling due to constant inference demands. While the current literature largely deals with t...

Artificial Intelligence-Driven Sensor Network Approach for Optimizing Halted Product Delivery in E-Commerce Platforms

Sensor network architectures incorporated with artificial intelligence are exploited for process automation in e-commerce platforms. Specifically, product management is automated through sale-based tracking, enabled by the rapid exchange of information within the sensor network....

Versatile Operational Optimization of Combined Heat and Power Systems Using the Graph Theory

Abstract The operation of combined heat and power (CHP) systems often requires switching between configurations to meet varying demands and operating requirements. This paper presents a hybrid framework for the structural optimization of integrated heat and power systems using P-...

Employee Responses to Crisis-Related Organizational Change: Evidence from Hungarian SMEs

Empirical research on organizational behavior contributes significantly to the examination of workplace impacts and to a deeper understanding of the underlying drivers of employee behavior. The long-term sustainability of organizations operating in VUCA environments depends large...

Self-Identified Natural Wine Producers in Hungary: An Exploratory Survey of Producer Characteristics and Motivations

Natural wines are produced with minimal or no additives, utilizing organic cultivation methods and emphasizing the high-quality and unique characteristics of terroir. In the last decade, natural wines have received considerable attention; however, the number of scientific publica...

Physical Performance Profiles of Highly Trained U14–U19 Youth Soccer Players: Age-Category Differences and Associations with Maturity Offset

This study aimed to examine age- and maturity-related differences in anthropometric characteristics, body composition, functional movement, and field-based physical performance among U14–U19 male youth soccer players. Seventy academy players completed anthropometric and body comp...

Beyond Platform Work: Algorithmic Management in Platform Labor and Traditional Organizations—The Hungarian Experience

Algorithmic management (AM) is spreading rapidly in platform work and traditional employment, yet empirical research remains platform-centric and skewed towards Western Europe, North America and China, leaving Central and Eastern Europe, especially Hungary, largely absent. This p...