DJEMBA NSEYA Chantal, KAFUNDA KATALAY Pierre, KITONDUA LUBANZADIO Richard, KASIAMA NGI ONKOR Joseph, LUBONGO MUEMBE Georgine, OKITOLONDA NDJATE Emile & SHAKO KONDE Marie Francine·Asian Journal of Research in Computer Science·2026
This study explores the application of gradient descent optimization and loss functions for depression prediction through multidimensional analysis of behavioral, psychological, and social factors. A logistic regression model was trained on a set of 1,631 records. Experimental re...
Open access
Research Article10.9734/ajrcos/2026/v19i1803
In an information technology landscape increasingly dominated by high-level abstraction layers, configuration management frameworks, and sophisticated Infrastructure as Code (IaC) platforms, the role of foundational shell scripting often faces scrutiny regarding its continued rel...
Open access
Research Article10.9734/ajrcos/2026/v19i1801
The Residue Number System (RNS) offers significant advantages in parallel, carry-free arithmetic for highperformance computing but remains critically vulnerable to errors during transmission and computation. Traditional error detection approaches rely on post-processing reverse c...
Open access
Research Article10.9734/ajrcos/2026/v19i1802
This review synthesizes current understanding of decoherence pathways across leading hardware platforms and explains why several experimentally observed noise features—drift, burst events, coherent components, correlated and non-Markovian structure, and leakage—can be disproporti...
Open access
Research Article10.9734/ajrcos/2025/v18i12800
Machine learning (ML) and deep learning (DL) approaches have shown increasing promise for heart disease prediction, but comprehensive evidence regarding their effectiveness compared to traditional clinical methods, implementation challenges, and real-world deployment readiness re...
Open access
Research Article10.9734/ajrcos/2025/v18i12799
This review studies the evolution of object detection methodologies, from traditional to modern deep learning techniques, including CNNs (Convolutional Neural Networks), YOLO (You Only Look Once) variants (v1–v8), and ViTs (Vision Transformers). A systematic analysis of 49 studie...
Open access
Research Article10.9734/ajrcos/2025/v18i12798
Objective: Machine learning provides powerful tools for analyzing large datasets; however, it faces challenges such as high computational costs and overfitting. To overcome these issues techniques that reduce the dimensionality of data are frequently used. Dimensionality reductio...
Open access
Research Article10.9734/ajrcos/2025/v18i12797
Criminal activities in the Kaduna-Abuja Highway have been an enormous security risk to the commuters, residents, and economic growth in Northern Nigeria. Conventional law enforcement approaches are still reactive and lack data, which restricts the anticipatory and preemptive acti...
Open access
Research Article10.9734/ajrcos/2025/v18i12796
In an increasingly interconnected global environment, the need for seamless multilingual communication via mobile devices is growing. This paper presents the design, development, and evaluation of a real-time multi-lingual Android system application translator (RT-MLAST), which i...
Open access
Research Article10.9734/ajrcos/2025/v18i12795
Cyber malware attacks, coupled with a lack of digital learning skills, can create significant issues in educational spheres where digitalization is in its infancy. This research integrates Educational Data Mining (EDM) methodologies to address the lack of actionable, predictive a...
Open access
Research Article10.9734/ajrcos/2025/v18i12792