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Keyword: Maintenance
Explainable AI for SSD Failure Prediction: Using LIME and SHAP for Transparency
by Saurav Kant Kumar
Journal of Engineering Research and Sciences, Volume 5, Issue 4, Page # 1-16, 2026; DOI: 10.55708/js0504001
Abstract: Artificial Intelligence (AI) has become increasingly crucial for modern data centers for automating tasks ranging from anomaly detection to predictive maintenance. Nevertheless, a significant limitation of underlying machine learning (ML) models is their “black box” nature. This lack of transparency limits trust among stakeholders who require visibility into model decisions. We address this lack of… Read More
(This article belongs to the Section Artificial Intelligence – Computer Science (AIC))
Experimental Study of the Short-Circuit Current Performance of \(10\,\mathrm{kA_{R.M.S}}\) and \(20\,\mathrm{kA_{R.M.S}}\) Polymer Surge Arrester
by Cristian-Eugeniu Sălceanu, Daniela Iovan and Daniel-Constantin Ocoleanu
Journal of Engineering Research and Sciences, Volume 4, Issue 12, Page # 15-24, 2025; DOI: 10.55708/js0412002
Abstract: To study the behavior of metal oxide surge arresters at short-circuit current, this paper presents an experimental study on four pieces of 36 kV, \(10\,\mathrm{kA_{R.M.S}}\) and \(20\,\mathrm{kA_{R.M.S}}\) surge arresters at different values of short-circuit current. Prior to the experiments, each surge arrester was electrically pre-faulted with a power frequency overvoltage without any physical modification. The tests… Read More
(This article belongs to the Special Issue on Special Issue on Multidisciplinary Sciences and Advanced Technology (SI-MSAT 2025) and the Section Electrical Engineering (ELE))
Magnetic AI Explainability: Retrofit Agents for Post-Hoc Transparency in Deployed Machine-Learning Systems
by Maikel Leon
Journal of Engineering Research and Sciences, Volume 4, Issue 8, Page # 31-40, 2025; DOI: 10.55708/js0408004
Abstract: Artificial intelligence already influences credit allocation, medical diagnosis, and staff recruitment, yet most deployed models remain opaque to decision makers, regulators, and the citizens they affect. A new wave of transparency mandates across multiple jurisdictions will soon require organizations to justify automated decisions without disrupting tightly coupled production pipelines that have evolved over the years.… Read More
(This article belongs to the Special Issue on Special Issue on Multidisciplinary Sciences and Advanced Technology (SI-MSAT 2025) and the Section Artificial Intelligence – Computer Science (AIC))