TY  - JOUR
AU  - Gyimesi, András
TI  - Competitive balance in the post-2024 Champions League and the European Super League: A simulation study
JF  - JOURNAL OF SPORTS ECONOMICS
J2  - J SPORTS ECON
PY  - 2024
PG  - 28
SN  - 1527-0025
DO  - 10.1177/15270025241249362
UR  - https://m2.mtmt.hu/api/publication/34821718
ID  - 34821718
AB  - The proposal of the European Super League and the 2024/25 reform of the UEFA Champions League are both major events in European club football. This study compares the competitive balance (CB) of these new tournament formats with the previous Champions League format. Short-, mid- and long-term CB are quantified by measuring the average uncertainty of match outcomes, the ratio of stakeless matches, and the recurrence ratio of teams in knockout rounds. A simulation method is applied using the teams, their seeding, and Elo ratings in the 2020/21 and 2021/22 Champions League seasons. Results suggest that the 2024/25 reform improves CB, especially in match uncertainty and the occurrence of stakeless matches. In comparison, the Star League of the European Super League concept of December 2023 is superior concerning average match uncertainty. However, it has a worse CB regarding stakeless matches and dynamic CB. Reasons and suggestions for improvement are also discussed.
LA  - English
DB  - MTMT
ER  - 

TY  - CHAP
AU  - Kiss, T
AU  - Ullah, A
AU  - Terstyanszky, G
AU  - Kao, O
AU  - Becker, S
AU  - Verginadis, Y
AU  - Michalas, A
AU  - Stankovski, V
AU  - Kertész, Attila
AU  - Ricci, E
AU  - Altmann, J
AU  - Egger, B
AU  - Tusa, F
AU  - Kovács, József
AU  - Lovas, Róbert
ED  - Barolli, L
TI  - Swarmchestrate: Towards a Fully Decentralised Framework for Orchestrating Applications in the Cloud-to-Edge Continuum
T2  - Advanced Information Networking and Applications
PB  - Springer Nature Switzerland
CY  - Cham
SN  - 9783031579318
T3  - Lecture Notes on Data Engineering and Communications Technologies, ISSN 2367-4512 ; 203.
PY  - 2024
SP  - 89
EP  - 100
PG  - 12
DO  - 10.1007/978-3-031-57931-8_9
UR  - https://m2.mtmt.hu/api/publication/34795721
ID  - 34795721
LA  - English
DB  - MTMT
ER  - 

TY  - BOOK
AU  - Vu, V T
AU  - Sename, O
AU  - Gáspár, Péter
AU  - Trong, T D
TI  - Active Anti-Roll Bar Control Design for Heavy Vehicles
PB  - Springer Nature Singapore
CY  - Singapore
PY  - 2024
SP  - 405
SN  - 9789819713592
DO  - 10.1007/978-981-97-1359-2
UR  - https://m2.mtmt.hu/api/publication/34794830
ID  - 34794830
LA  - English
DB  - MTMT
ER  - 

TY  - JOUR
AU  - Tesone, Alessio
AU  - Tettamanti, Tamás
AU  - Varga, Balázs
AU  - Bifulco, Gennaro Nicola
AU  - Pariota, Luigi
TI  - Multiobjective Model Predictive Control Based on Urban and Emission Macroscopic Fundamental Diagrams
JF  - IEEE ACCESS
J2  - IEEE ACCESS
VL  - 12
PY  - 2024
SP  - 52583
EP  - 52602
PG  - 20
SN  - 2169-3536
DO  - 10.1109/ACCESS.2024.3387664
UR  - https://m2.mtmt.hu/api/publication/34788066
ID  - 34788066
AB  - Increasing motorization represents a severe problem worldwide, also affecting the emission levels of the road network. Accordingly, congestion management has obtained growing importance because of its strong economic, social, and environmental implications. Macroscopic Fundamental Diagram (MFD) based traffic control is a popular and efficient approach in this scientific field. In our research work the urban network has been divided into homogeneous regions, each of them characterized by its own MFD, and they are regulated using a network-level control scheme. The proposed Multiobjective Model Predictive Control (M-MPC) takes into account the congestion and <italic>CO</italic>2 emission levels of the urban network, modelled by the emerging Emission Macroscopic Fundamental Diagram (e-MFD). The applied strategy has been demonstrated in a realistic traffic scenario (Luxembourg City) using validated microscopic traffic simulation. According to the introduced multiobjective approach, the control method can better exploit the road network capacity while efficiently reducing traffic-induced emissions. Authors
LA  - English
DB  - MTMT
ER  - 

TY  - JOUR
AU  - Dózsa, Tamás
AU  - Jurdana, V
AU  - Segota, S B
AU  - Volk, János
AU  - Radó, János
AU  - Soumelidis, Alexandros
AU  - Kovács, Péter
TI  - Road Type Classification Using Time-Frequency Representations of Tire Sensor Signals
JF  - IEEE ACCESS
J2  - IEEE ACCESS
VL  - 12
PY  - 2024
SP  - 53361
EP  - 53372
PG  - 12
SN  - 2169-3536
DO  - 10.1109/ACCESS.2024.3382931
UR  - https://m2.mtmt.hu/api/publication/34786414
ID  - 34786414
LA  - English
DB  - MTMT
ER  - 

TY  - JOUR
AU  - Pedone, Gianfranco
AU  - Váncza, József
AU  - Szaller, Ádám
TI  - Exploring hidden pathways to sustainable manufacturing for cyber-physical production systems
JF  - HELIYON
J2  - HELIYON
VL  - 10
PY  - 2024
IS  - 8
PG  - 19
SN  - 2405-8440
DO  - 10.1016/j.heliyon.2024.e29004
UR  - https://m2.mtmt.hu/api/publication/34786003
ID  - 34786003
LA  - English
DB  - MTMT
ER  - 

TY  - JOUR
AU  - Liu, Y
AU  - Wang, P
AU  - Lee, C
AU  - Tóth, Roland
TI  - Attitude Takeover Control for Noncooperative Space Targets Based on Gaussian Processes with Online Model Learning
JF  - IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
J2  - IEEE T AERO ELEC SYS
PY  - 2024
SP  - 1
EP  - 17
PG  - 17
SN  - 0018-9251
DO  - 10.1109/TAES.2024.3361886
UR  - https://m2.mtmt.hu/api/publication/34779718
ID  - 34779718
N1  - Control Systems Group, Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands            
            Flight Dynamics and Control Laboratory, Department of Aerospace Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea            
            Export Date: 9 April 2024            
            CODEN: IEARA
LA  - English
DB  - MTMT
ER  - 

TY  - JOUR
AU  - Ogbolu, Melvin
AU  - Kozlovszky, Miklós
TI  - Assessment of HPV Knowledge and Awareness among Students and Staff at IBB University, Niger State, Nigeria: Implications for Health Education and Prevention
JF  - HEALTHCARE
J2  - HEALTHCARE-BASEL
VL  - 12
PY  - 2024
IS  - 6
SP  - 665
PG  - 16
SN  - 2227-9032
DO  - 10.3390/healthcare12060665
UR  - https://m2.mtmt.hu/api/publication/34776261
ID  - 34776261
N1  - BioTech Research Center, University Research and Innovation Center, Óbuda University, Budapest, 1034, Hungary            
            John von Neumann Faculty of Informatics, Óbuda University, Budapest, 1034, Hungary            
            Medical Device Research Group, LPDS, Institute for Computer Science and Control, SZTAKI), Hungarian Research Network (HUN-REN, Budapest, 1111, Hungary            
            Export Date: 12 April 2024            
            Correspondence Address: Ogbolu, M.O.; BioTech Research Center, Hungary; email: ogbolu.melvin@nik.uni-obuda.hu            
            Correspondence Address: Kozlovszky, M.; John von Neumann Faculty of Informatics, Hungary; email: kozlovszky.miklos@nik.uni-obuda.hu
AB  - In Nigeria, statistics reveal that there is a high rate of cervical cancer among women and a significant lack of awareness surrounding Human Papillomavirus (HPV), which poses a substantial risk of HPV infection. This cross-sectional survey, conducted at Ibrahim Badamasi Babangida (IBB) University, focuses on adapting and exploring the factors that influence a 20-item scale to measure HPV knowledge, evaluating knowledge-associated patterns and HPV-associated risk factors. We examined HPV vaccination rates, infection awareness, vaccine awareness, and the impact of ethnicity on HPV knowledge. Various validated forms were adapted to measure HPV awareness and knowledge. Non-parametric tests addressed non-normality. Data were presented using median and IQR and categorical data were frequency-based. Bivariate tests (Mann–Witney, Kruskal Wallis) explored knowledge-associated factors, while quantile regression (75th percentile) examined HPV knowledge factors. Variables were considered statistically significant at p < 0.05. The adapted 20-item knowledge scale revealed strong reliability (Cronbach’s alpha = 0.913), ensuring internal consistency. The median knowledge score was 0, with an interquartile range (IQR) of 0–5. Our findings revealed a significant lack of awareness and knowledge about HPV; only 34.8% of the population were aware of HPV infection and 25.0% were familiar with HPV vaccination. Furthermore, ethnicity was found to be significantly associated with knowledge of HPV. This study emphasizes the necessity for targeted interventions to enhance HPV awareness, especially within specific ethnic groups. Despite a robust knowledge scale, educational initiatives such as seminars/conferences about HPV and cervical cancer remain crucial in addressing this gap, ultimately reducing HPV infection and cervical cancer risks in Nigeria.
LA  - English
DB  - MTMT
ER  - 

TY  - JOUR
AU  - Dózsa, Tamás
AU  - Őri, P
AU  - Szabari, M
AU  - Simonyi, Ernő
AU  - Soumelidis, Alexandros
AU  - Lakatos, István
TI  - Brake Disc Deformation Detection Using Intuitive Feature Extraction and Machine Learning
JF  - MACHINES
J2  - MACHINES
VL  - 12
PY  - 2024
IS  - 4
PG  - 21
SN  - 2075-1702
DO  - 10.3390/machines12040214
UR  - https://m2.mtmt.hu/api/publication/34758553
ID  - 34758553
AB  - In this work we propose proof-of-concept methods to detect malfunctions of the braking system in passenger vehicles. In particular, we investigate the problem of detecting deformations of the brake disc based on data recorded by acceleration sensors mounted on the suspension of the vehicle. Our core hypothesis is that these signals contain vibrations caused by brake disc deformation. Since faults of this kind are typically monitored by the driver of the vehicle, the development of automatic fault-detection systems becomes more important with the rise of autonomous driving. In addition, the new brake boosters separate the brake pedal from the hydraulic system which results in less significant effects on the brake pedal force. Our paper offers two important contributions. Firstly, we provide a detailed description of our novel measurement scheme, the type and placement of the used sensors, signal acquisition and data characteristics. Then, in the second part of our paper we detail mathematically justified signal representations and different algorithms to distinguish between deformed and normal brake discs. For the proper understanding of the phenomenon, different brake discs were used with measured runout values. Since, in addition to brake disc deformation, the vibrations recorded by our accelerometers are nonlinearly dependent on a number of factors (such as the velocity, suspension, tire pressure, etc.), data-driven models are considered. Through experiments, we show that the proposed methods can be used to recognize faults in the braking system caused by brake disc deformation.
LA  - English
DB  - MTMT
ER  - 

TY  - CHAP
AU  - Dózsa, Tamás
AU  - Fridli, Sándor
AU  - Kovács, Péter
ED  - Nicolai, Spicher
ED  - Theresa, Bender
ED  - Philip, Hempel
TI  - Modeling CT images in the presence of beam hardening​
T2  - Proceedings of the Workshop Biosignal 2024
PB  - University of Göttingen
CY  - Göttingen
PY  - 2024
SP  - 1
EP  - 5
PG  - 5
UR  - https://m2.mtmt.hu/api/publication/34754671
ID  - 34754671
LA  - English
DB  - MTMT
ER  -