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001-es BibID:	BIBFORM135243
Első szerző:	Dawod, Abdaljbbar Babiker Abdaljbbar (Ph.D. student)
Cím:	Railway Track Quality Inspection via GLasso with Zerocrossing Segmentation / Abdaljbbar B. A. Dawod; Gyorgy Terdik
Dátum:	2026
Megjegyzések:	This study presents an approach for monitoring the transient variations in the multivariate coefficient of variation (MCV) using one-sided downward and upward control charts. Zero-crossing segmentation was employed to form subgroups, enabling efficient detection of process shifts. The methodology was applied to track geometry data collected from multiple railway sections across Hungary. Control charts were developed using both Maximum Likelihood Estimation (MLE) and Graphical Lasso (GLasso) techniques for estimating the precision matrix. Comparative analysis revealed that GLasso-based MCV charts with zero-crossing segmentation outperformed their MLE-based counterparts in detecting process changes.
ISBN:	978-3-032-13897-2 978-3-032-13898-9
Tárgyszavak:	Műszaki tudományok Informatikai tudományok könyvfejezet könyvrészlet GLasso Railway track MSPC
Megjelenés:	p. 244-250. -
További szerzők:	Terdik György (1949-) (matematikus, informatikus)
Pályázati támogatás:	TKP2021-NKTA-34 Egyéb
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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001-es BibID:	BIBFORM133134
Első szerző:	Dawod, Abdaljbbar Babiker Abdaljbbar (Ph.D. student)
Cím:	Mapping Cognitive-Behavioral Networks : A Graphical Lasso Approach to Dependence Structure Visualization / Abdaljbbar B. A. Dawod, György Terdik
Dátum:	2025
Megjegyzések:	This article presents a comprehensive review of statistical methods for estimating graphical model structures across both Gaussian and non-Gaussian distributions. We examine Gaussian Graphical Models (GGMs), highlighting their limitations and introducing a robust implementation of the Graphical Lasso (GLasso) to address these challenges. The proposed methodology can be extended to count data, including multivariate binary, multinomial, and Poisson distributions, with robust estimation techniques developed for each case. Our comparative analysis demonstrates that GLasso-based partial correlation matrices produce sparser and more interpretable dependency structures compared to Maximum Likelihood Estimation (MLE) based partial correlation matrices. To validate our approach, we analyze two real-world Cognitive-Behavioral datasets. The first application visualizes symptom network structures in Post- Traumatic Stress Disorder (PTSD), while the second examines dependency patterns among key factors in student emotional monitoring. The results consistently show that GLasso outperforms the MLE in visualizing the dependence structure, offering both computational efficiency and improved interpretability. These findings provide practical insights for researchers analyzing complex dependency structures, particularly in psychological and behavioral studies where interpretable graphical models are essential. The robust methodologies presented here advance current approaches to graphical model estimation while maintaining statistical reliability across diverse data types.
ISBN:	9798350356922
Tárgyszavak:	Természettudományok Matematika- és számítástudományok konferenciacikk folyóiratcikk GLasso Conditional independence Partial correlation dynamic-networks
Megjelenés:	2025 IEEE 16th International Conference on Cognitive Infocommunications (CogInfoCom) /CogInfo (szerk.). - 2025 (2025), p. 1-6. -
További szerzők:	Terdik György (1949-) (matematikus, informatikus)
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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001-es BibID:	BIBFORM118837
Első szerző:	Dawod, Abdaljbbar Babiker Abdaljbbar (Ph.D. student)
Cím:	Use of Zero-crossings Segmentation for Track Quality Assessment / Abdaljbbar B. A. Dawod; Terdik, György
Dátum:	2024
ISSN:	2064-5228
Megjegyzések:	This study concerns track quality assessment of standard-gauge railways in the context of the Hungar- ian railway system. Data gathered by multipurpose track recording vehicles matched the EN 13,848 requirements. Track Quality Index (TQI) measurement systems (The Federal Railroad Administration (FRA), the Netherlands', and the Chinese TQI) are considered where three types of predetermined segment techniques: separate, moving, and Zero-crossings segmentation are employed. The impor- tance of track segmentation in quality assessment, which affects maintenance planning, is shown by key findings. For heterogeneous data, the TQIs might be deceptive, highlighting the need for alterna- tives. The robustness of the Zero-crossings method makes it possible to analyze deterioration factors in great detail and in some efficient way. Longer analytical segments and smoothing of the data improved precision. Based on empirical data, we advise considering a Zero-crossings strategy for precise and efficient track-quality evaluations. With the help of this study, track quality can be better evaluated for train systems.
Tárgyszavak:	Természettudományok Matematika- és számítástudományok idegen nyelvű folyóiratközlemény hazai lapban folyóiratcikk Track Quality Indices Track geometry, Signal processing, Zero-crossing, Empirical Mode Decompo- sition, FRA Geometry TQI Netherlands TQI Chinese TQ
Megjelenés:	Acta Technica Jaurinensis. - 17 : 1 (2024), p. 8-21. -
További szerzők:	Terdik György (1949-) (matematikus, informatikus)
Pályázati támogatás:	TKP2021-NKTA-34 Egyéb
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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