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Found 6427 publications

Leader of Digital Cooperation? – Scientific Mapping Engaging Leadership

Beatrix Séllei Heléna Krén Gyorgy Molnar

Publication Name: Acta Polytechnica Hungarica

Publication Date: 2022-01-01

Volume: 19

Issue: 11

Page Range: 207-227

Description:

In this time of digitalization, leaders have to face new challenges and concentrate on engaging subordinates, due to the hybrid working conditions. One of these challenges is the Digital Competence Expectations for Public School Leaders, published in 2021, by the Digital Pedagogical Development Working Group. The emerging importance of engagement is supported by a great deal of scientific research. However, it is still questionable… what directly determines engagement and affects subordinates in the engaging process? Our review aims to analyze the characteristics of engaging leadership and leaders’ behavior, which contributes to the engagement of coworkers. Taking the challenges of the digital world into consideration, we make some practical suggestions for future leaders and HR professionals, in order to strengthen their organizations and retain valuable employees.

Open Access: Yes

DOI: 10.12700/APH.19.11.2022.11.11

Design of B-spline neural networks using a bacterial programming approach

Cristiano Cabrita János Botzheim António E. Ruano Laszlo T. Koczy

Publication Name: IEEE International Conference on Neural Networks Conference Proceedings

Publication Date: 2004-12-01

Volume: 3

Issue: Unknown

Page Range: 2313-2318

Description:

The design phase of B-spline neural networks represents a very high computational task. For this purpose, heuristics have been developed, but have been shown to be dependent on the initial conditions employed. In this paper a new technique, Bacterial Programming, is proposed, whose principles are based on the replication of the microbial evolution phenomenon. The performance of this approach is illustrated and compared with existing alternatives.

Open Access: Yes

DOI: 10.1109/IJCNN.2004.1380987

Mobile Robot Environment Representation Through Fuzzy Signatures-Integrated Quadtrees

Csaba Hajdu Ahmet Mehmet Karadeniz Laszlo T. Koczy

Publication Name: Romanian Journal of Information Science and Technology

Publication Date: 2025-01-01

Volume: 28

Issue: 1

Page Range: 103-116

Description:

This paper presents an innovative environment representation technique for mobile robots, incorporating obstacle detection within their operational space. Leveraging the fuzzy signature method, this approach uses quadtrees for efficient data organization. A set of fuzzy rules evaluates feature points to ascertain the relevance of identified obstacles. These points and their fuzzy associations are systematically arranged using a quadtree structure. The environmental model is reconstructed by traversing this tree and applying the established fuzzy rules. This paper has achieved a high-resolution grid representation of 0.1m within a 20m×20m area. Notably, the inference operation completes in just 0.5 ms, underscoring the method’s efficiency. Additionally, the technique is optimized for low memory consumption, demonstrating effective resource management even on older PCs, such as an Intel Core Duo 2 with 16 GB RAM. This representation is designed to support advanced robotic functions, such as obstacle navigation in a distributed computing environment.

Open Access: Yes

DOI: 10.59277/ROMJIST.2025.1.09

A novel behavior model based estimation method for the traffic capacity of signalized intersections

Jozsef Homlok Katalin Kovács

Publication Name: 17th ITS World Congress

Publication Date: 2010-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Traffic systems are man-made systems in which the human component as a complex factor plays a significant part. (1) The realistic modeling of them is extremely complicated. The aim of the paper is to present a traffic behavior model of inhomogeneous driver-populations and a corresponding estimation method. The traffic behavior model is developed for describing traffic flow in a signalized intersection. It works with inhomogeneous driver populations; different type of drivers may make different decisions in the same traffic situation. This way various driver types can be defined like aggressive, normal or conservative etc. drivers. The model focuses on the movement and the behavior of the inhomogeneous driver-populations approaching a signalized intersection, passing the amber signal light. The developed estimation method is intended to define the distribution of different driver types. This theory can allow an extensive and more complex traffic analysis on a more sensitive scale. The paper details the steps of the estimation process and the validation and introduces the results of the application of the estimation method with real experiments.

Open Access: Yes

DOI: DOI not available

A Preliminary Study on Laser Surface Texturing of Passenger Car Engine Piston Rings

András Lajos Nagy Attila Schweighardt Gabor Laki Gergely Kovács

Publication Name: Fme Transactions

Publication Date: 2025-01-01

Volume: 53

Issue: 2

Page Range: 252-259

Description:

Laser surface texturing offers a possible solution for reducing friction between sliding surfaces in engineering applications. Optimized surface topography can also contribute to reduced wear and elevated longevity by modifying the load and speed-dependent friction state in a system. This preliminaryexperimental study investigates the applicability of affordable fibre laser marking systems for microtexturing piston rings, in order to achieve a measurable reduction in friction under subsystem model conditions. A selection of textures are applied to chromium-coated cast iron piston rings. The resulting surface topographies are characterized through confocal microscopy and subjected to friction testing. A correlation analysis is conducted on surface topography parameters to identify key laser process parameters. Findings indicate an improvement in the range of 7–8% in terms of friction coefficient with appropriate texture size.

Open Access: Yes

DOI: 10.5937/fme2502252L

Improved fuzzy-based single-stroke character recognizer

A. Tormási Laszlo T. Koczy

Publication Name: Proceedings of the 2013 Joint Ifsa World Congress and NAFIPS Annual Meeting Ifsa NAFIPS 2013

Publication Date: 2013-10-31

Volume: Unknown

Issue: Unknown

Page Range: 430-435

Description:

In this paper we present two modified and improved versions of the formerly published Fuzzy-Based Single-Stroke Character Recognizer (FUBAR) algorithm. After introducing the original method, the study investigates the effects of two different improvements of the designed algorithm. The first extension is the use of symbol-dependent fuzzy grids to extract symbol features; the second one is the use of rule weights in hierarchical rule-bases. The accuracy and efficiency of the extended FUBAR algorithms are compared to previous results. © 2013 IEEE.

Open Access: Yes

DOI: 10.1109/IFSA-NAFIPS.2013.6608439

Generative AI-driven transition to circular and responsible supply chains: Unpacking the dynamics of eco-centric design intelligence and ethical responsiveness

Eszter Lukács Jiyang Cheng Sabrine Mallek

Publication Name: Technological Forecasting and Social Change

Publication Date: 2026-04-01

Volume: 225

Issue: Unknown

Page Range: Unknown

Description:

The study focuses on understanding how the use of generative Artificial Intelligence (AI) can beneficially result in circular supply chain transformation while embedding design intelligence, ethical intelligence, and predictive intelligence within socio-technical systems. This study proposes and validates a model that integrates generative eco-design intelligence, predictive circular supply chain planning, and ethical generative AI awareness, which collectively affect circular supply chain resilience and socio-environmental value realization, mediated by Sustainable process reconfiguration capability and AI-enabled stakeholder co-creation. To test the hypothesis, data were collected from 264 professionals in supply chain and technology-related industries in the USA. As the findings suggest, generative eco-design intelligence, predictive circular supply chain planning, and ethical generative AI awareness significantly enhance sustainable process reconfiguration capability, which drives AI-enabled stakeholder co-creation. A serial mediation model indicates that Generative AI capabilities affect circular supply chain resilience and socio-environmental value realization via sustainable process reconfiguration capability and AI-enabled stakeholder co-creation. To our surprise, the regenerative policy ambidexterity negatively moderates the relationship between AI-enabled stakeholder co-creation and the realization of socio-environmental value. The results provide actionable advice for managers implementing generative AI in sustainable supply chains. Instead of focusing solely on algorithmic efficiency, if an organization can develop reconfiguration capability and engage stakeholders, it would generate systemic sustainability benefits.

Open Access: Yes

DOI: 10.1016/j.techfore.2025.124522

The Role of Media in Sponsorship Decision Making During Covid-19: A Malaysian Perspective

Nurzihan Hassim Suffian Hadi Ayub Rosli Mohammed Mohamad Noor Salehhuddin Sharipudin Kim Shyan Fam

Publication Name: Jurnal Komunikasi Malaysian Journal of Communication

Publication Date: 2022-01-01

Volume: 38

Issue: 2

Page Range: 182-197

Description:

COVID-19 has impacted not only human lives, but also business organisations. The repercussions of the pandemic on global businesses include sustaining the value of a firm that could benefit stakeholders, such as the challenge for sponsored properties to attain sponsorship through a period of financial struggles and the capacity of a sponsor to provide it. It is imperative for business-to-business (B2B) communities to evaluate criteria and risks of sponsorship to instil public trust and consequently result in value creation for firms. At the same time, the role of the media is pivotal to create visibility of this partnership and achieve set sponsorship aims. With that said, the objective of this study is to explore the role of sponsorship decision making by Malaysian organisations during the pandemic and how the media have strengthened relationship marketing between businesses and their stakeholders; by examining the determinant factors of using media as an activation in sponsorship and the criteria of using media in sponsorship. The qualitative study conducted interviews with 13 corporate communication and marketing managers in Malaysia that are involved directly with sponsorship activation. The findings highlight the sponsorship ecosystem through the Malaysian media and B2B perspectives that would guide practitioners in making strategic decisions on B2B sponsorship matters, particularly on the relational approaches and media engagement should be seen as part of good business conduct. Future recommendation of this research is to seek the perceptions of consumers on the congruence of relationship marketing through sponsor-sponsored properties collaboration in Malaysian media.

Open Access: Yes

DOI: 10.17576/JKMJC-2022-3802-11

Classification of preeclampsia according to molecular clusters with the goal of achieving personalized prevention

Offer Erez Adi L. Tarca Nándor Gábor Than Dániel Györffy Zoltán Papp Simona W. Rossi Sándor Nagy Roberto Romero Máté Posta Nándor Ács Gábor Szalai András Szilágyi Olga Török Petronella Hupuczi

Publication Name: Journal of Reproductive Immunology

Publication Date: 2024-02-01

Volume: 161

Issue: Unknown

Page Range: Unknown

Description:

The prevention of pre-eclampsia is difficult due to the syndromic nature and multiple underlying mechanisms of this severe complication of pregnancy. The current clinical distinction between early- and late-onset disease, although clinically useful, does not reflect the true nature and complexity of the pathologic processes leading to pre-eclampsia. The current gaps in knowledge on the heterogeneous molecular pathways of this syndrome and the lack of adequate, specific diagnostic methods are major obstacles to early screening and tailored preventive strategies. The development of novel diagnostic tools for detecting the activation of the identified disease pathways would enable early, accurate screening and personalized preventive therapies. We implemented a holistic approach that includes the utilization of different proteomic profiling methods of maternal plasma samples collected from various ethnic populations and the application of systems biology analysis to plasma proteomic, maternal demographic, clinical characteristic, and placental histopathologic data. This approach enabled the identification of four molecular subclasses of pre-eclampsia in which distinct and shared disease mechanisms are activated. The current review summarizes the results and conclusions from these studies and the research and clinical implications of our findings.

Open Access: Yes

DOI: 10.1016/j.jri.2023.104172