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001-es BibID:	BIBFORM126610
035-os BibID:	(Scopus)85214781534
Első szerző:	Kocsis Imre (matematikus, gépészmérnök)
Cím:	A comprehensive review of key cyber-physical systems, and assessment of their education challenges / Kocsis Imre, Burján-Mosoni Boglárka, Balajti István
Dátum:	2025
ISSN:	2169-3536
Megjegyzések:	The importance of cyber-physical systems (CPS) continues to grow today, with AI applications in the CPS design principles that formulate smart cyber-physical systems (S-CPS). These called Extended Cyber-Physical Systems (E-CPS) or Next Generation Cyber-Physical Systems (NG-CPS) are expanding to address more complex problems such as the impact of intellectualization on human roles and the social embedding of heterogeneous systems. The industrial metaverse for smart manufacturing and its novel characteristics require new types of advanced cyber-physical coordinated situational awareness and active defense against cyber-attacks. These new challenges raise the profile of engineering education at the university level, while the addition of new skills requires rigorous preparatory work and the development of tailored requirements for effective knowledge transfer methods that meet the educational needs of the current environment. Students need to be prepared to manage information and influence decision-makers effectively. This article presents a pedagogical approach to teaching CPS as an advanced undergraduate subject by integrating elements of competency and personal development into daily classroom activities. This reflects the circumstances and demands of everyday engineering work, focusing on soft skills such as time management, precision, accuracy, focus, communication, teamwork, and also applying the methods of continuous accountability and reward. The specific tasks and assessment techniques simulate real-life situations in the industry, and R&D activities, where the students became efficient engineers, researchers and later on could fulfil the position of reliable BOSSs. The conclusions are based on individual and group interviews conducted with students in Hungarian and international mechatronics undergraduate programs.
Tárgyszavak:	Bölcsészettudományok Neveléstudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk cyber-physical systems artificial intelligence cyber and personal security challengebased learning
Megjelenés:	IEEE Access. - 13 (2025), p. 8898-8911. -
További szerzők:	Burján-Mosoni Boglárka (1985-) (informatikus, matematikus) Balajti István (1955-) (Távolfelderítő radarok)
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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001-es BibID:	BIBFORM131893
Első szerző:	Manzoor, Waleed
Cím:	Mental workload detection and assessment through statistical features extraction and optimization using GEL-RF method for EEG signals using N-back dataset / Waleed Manzoor, Noman Naseer, Imran Fareed Nizami, Syed Hammad Nazeer, Husam A. Neamah
Dátum:	2025
ISSN:	2169-3536
Megjegyzések:	Mental workload (MW) assessment measures the cognitive effort required to perform tasks and is crucial in fields such as aviation, clinical medicine, and healthcare. This study addresses the critical need to optimize cognitive load and resource allocation by evaluating MW through EEG-based analysis. Recently, MW assessment using EEG signals has gained importance, as they show a high correlation with specific cognitive processes and MW. Although previous studies have employed various techniques for MW assessment using EEG, detailed statistical feature selection remains underexplored. This work analyzes the N-back dataset, a standard benchmark for cognitive load, using four combinations of binary and multiclass classification to assess three MW levels. We propose a novel model, which integrates genetic, evolutionary and linear (GEL) feature selection techniques with a Random Forest (RF) classifier as GEL-RF model. Experimental results demonstrate that the GEL-RF model achieves classification accuracies of 97% for binary tasks and 96.3% for multiclass tasks MW assessment, outperforming existing methods. These results shows that our proposed model can improve MW assessment accuracy, helping to increase safety and efficiency in demanding mental tasks.
Tárgyszavak:	Műszaki tudományok Informatikai tudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk Mental Workload Assessment (MWA) Statistical Features Electroencephalogram (EEG) Genetic, Evolutionary, Linear (GEL) search algorithms N-back Random Forest (RF)
Megjelenés:	IEEE Access. - 13 (2025), p. 140118-140138. -
További szerzők:	Naseer, Noman Nizami, Imran Fareed Nazeer, Syed Hammad Neamah, Husam A. (1990-) (mérnök)
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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001-es BibID:	BIBFORM127270
Első szerző:	Zamri, Siti Norziahidayu Amzee
Cím:	The Mixed Partition Dimension : A New Resolvability Parameter in Graph Theory / Siti Norziahidayu Amzee Zamri, Sikander Ali, Muhammad Azeem, Husam A. Neamah, Bandar Almohsen
Dátum:	2025
ISSN:	2169-3536
Megjegyzések:	In this article, we introduce a novel graph-theoretical parameter called the mixed partition dimension and apply it to the path graph and the hexagonal network. This parameter builds on the concept of resolvability in graphs, integrating vertex-based partition dimensions with edge-oriented strategies to characterize the complexity of graph structures. It is the extension of the mixed metric dimension and partition dimension. Suppose Let R = {W1,W2,...,Wk} be a partition of the vertex set V (G) of a graph G = (V,E), where W1 ? W2 ? ··· ? Wk = V(G) and Wi ? Wj = ? fori= j. Each subset Wi is non-empty, mutually disjoint, and collectively covers all vertices. The partition set Rpm) is called mixed resolving partition set if it satisfies: For any two distinct vertices x,y ? V , there exists Wi ? R such that:d(u, Wi)= d(v,Wi), for any two distinct edges e1,e2 ? E, there exists Wi ? R such that:d(e1,Wi)= d(e2,Wi) and for any vertex u ? V and edge e ? E, there exists Wi ? R such that: d(u,Wi)= d(e,Wi). The mixed partition dimension of G is the minimum number of subsets in a mixed resolving partition set Rpm). This parameter provides a unified measure of a graph`s complexity by accounting for both vertex and edge distinguishability, offering new insights into the structure of complex networks.
Tárgyszavak:	Műszaki tudományok Informatikai tudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk partition resolving set edge partition dimension partition dimension mixed partition dimension hexagonal network
Megjelenés:	IEEE Access. - 13 (2025), p. 60122-60130. -
További szerzők:	Ali, Sikander Azeem, Muhammad Neamah, Husam A. (1990-) (mérnök) Almohsen, Bandar
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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