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Abstract Synchronous reluctance motors (SynRMs) are increasingly critical in industrial and traction applications due to their high efficiency, magnet-free construction, and thermal robustness. However, fault diagnosis f...

Abstract Epidemiological cohorts often collect self-reported oral health (SROH) questionnaires but lack clinical periodontal measurements. We developed a selective, explainable machine learning (ML) pipeline that can ass...

Abstract Roadside areas are major sources of traffic-related air pollutant emissions. This study identified the spatial distribution of roadside pollutants using Unmanned Aerial Vehicle (UAV) measurements and predicted t...

Abstract Alzheimer’s disease, a progressive neurodegenerative disorder, presents a growing global health challenge due to its increasing prevalence and lack of accessible early diagnostic methods. Even though it has en...

Abstract While housing price prediction is well-studied, the prediction of large-scale housing conditions remains underexplored due to data limitations. This paper addresses this gap by developing a machine-learning mode...

Abstract Remote sensing is increasingly employed today for the creation of wall-to-wall vegetation maps of protected areas. The main objective of this study was to evaluate whether it is feasible to develop a remote sens...