School of Computing and IT (JA)
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A HETEROGENEOUS DEEP ENSEMBLE APPROACH FOR ANOMALY DETECTION IN CLASS IMBALANCED ENERGY CONSUMPTION DATA
(international journal of artificial intelligence and applications, 2025)The integrity and efficiency of modern energy grids are increasingly reliant on accurate anomaly detection within energy consumption data. However, class imbalance poses significant challenges, where normal consumption ... -
Natural Language Processing with Transformer-Based Models: A Meta-Analysis
(Tech Science Press, 2025)The natural language processing (NLP) domain has witnessed significant advancements with the emergence of transformer-based models, which have reshaped the text understanding and generation landscape. While their ... -
A Unified U-Net-Vision Mamba Model with Hierarchical Bottleneck Attention for Detection of Tomato Leaf Diseases
(Tech Science Press, 2025)Tomato leaf diseases significantly reduce crop yield; therefore, early and accurate disease detection is required. Traditional detection methods are laborious and error-prone, particularly in large-scale farms, whereas existing ... -
SYSTEMATIC REVIEW OF VEHICULAR AD-HOC NETWORKS TRUST-BASED MODELS
(international journal of wireless mobile networks, 2025)Vehicular Ad-hoc Networks (VANETs) are specialized type of Mobile Ad-hoc Networks (MANETs) developed to support vehicle-to-vehicle and vehicle-to-infrastructure communication. Security threats in these networks include ... -
Metaheuristic Techniques for Test Case Optimization: A Systematic Literature Review
(Software Testing, Test Case Production, Metaheuristic Techniques, Optimization, UML, 2025)Test case production is a crucial phase in the software testing lifecycle that consumes significant time, effort, and cost. As such, it is considered an optimization problem that can be addressed using metaheuristic ... -
A SYSTEMATIC REVIEW OF AD-HOC ONDEMAND DISTANCE VECTOR ROUTING PROTOCOL FOR PERFORMANCE IMPROVEMENT IN MOBILE AD-HOC NETWORKS
(2025)Routing protocols are fundamental in establishing linkages and communication amongst nodes in Mobile Ad-hoc Networks (MANET). Since Ad-hoc On-demand Distance Vector (AODV) protocol shuns loops and minimizes route broadcasts ... -
SYSTEMATIC REVIEW OF MODELS USED TO HANDLE CLASS IMBALANCE IN ANOMALY DETECTION FOR ENERGY CONSUMPTION
(International Journal of Artificial Intelligence and Applications (IJAIA), 2024)The widespread integration of Smart technologies into energy consumption systems has brought about a transformative shift in monitoring and managing electricity usage. The imbalanced nature of anomaly data often results ... -
Scaling Robotics Education: A Systematic Review of Technologies, Frameworks, and Equity Dimensions
(International Journal of Computer Applications Technology and Research, 2025)Robotics education is increasingly essential for preparing learners with skills in STEM, programming, and artificial intelligence. Yet, scaling such education equitably remains a global challenge. This study systematically ... -
Integrating Artificial Intelligence in Open, Distance, and e-Learning (ODeL): A Systematic Literature Review
(International Journal of Computer Applications Technology and Research, 2025)Artificial Intelligence (AI) is increasingly transforming Open, Distance, and e-Learning (ODeL) by enhancing personalization, automating assessments, and enabling immersive learning environments. This study employs a ... -
Integrating Mobile STEM Labs and Digital Technologies to Enhance STEM Education in Marginalized Regions of Kenya: A Systematic Literature Review
(International Journal of Computer Applications Technology and Research, 2025)This systematic literature review explores the integration of mobile STEM labs and digital technologies including artificial intelligence (AI), robotics and e-learning platforms as tools for enhancing STEM education in ... -
A HETEROGENEOUS DEEP ENSEMBLE APPROACH FOR ANOMALY DETECTION IN CLASS IMBALANCED ENERGY CONSUMPTION DATA
(International Journal of Artificial Intelligence and Applications (IJAIA), 2025)The integrity and efficiency of modern energy grids are increasingly reliant on accurate anomaly detection within energy consumption data. However, class imbalance poses significant challenges, where normal consumption ... -
A COMPARATIVE ANALYSIS OF CLASS IMBALANCE HANDLING TECHNIQUES FOR DEEP MODELS IN THE DETECTION OF ANOMALIES IN ENERGY CONSUMPTION
(International Journal of Artificial Intelligence and Applications (IJAIA), 2024)Detecting anomalies in energy consumption is critical for efficient energy management, fault detection, and sustainability. However, the challenge of class imbalance, where normal consumption data vastly outweighs anomalous ... -
Explainable Artificial Intelligence: A Comprehensive Review of Techniques, Applications, and Emerging Trends
(International Journal of Scientific Research in Computer Science and Engineering, 2025)The growing reliance on opaque deep learning models in critical domains has intensified the demand for transparency, accountability, and interpretability of artificial intelligence systems. Explainable Artificial Intelligence ... -
Building Trust in AI: How Ethics, Standards, and Blockchain are Redefining Global Governance
(International Journal of Computer and Information Technology, 2026)The rapid advancement of Artificial Intelligence (AI) has amplified concerns around trust, transparency, and accountability in automated decision-making systems. This paper explores the foundational concept of AI with ... -
Ensemble Feature Selection for Network Intrusion Detection: Combining Information Gain and Random Forest with Recursive Feature Elimination
(International Journal of Computer and Information Technology, 2024)Network intrusion detection systems (NIDS) are essential for protecting computer networks against cyberattacks. The selection of a nominal set of essential features that may adequately discriminate malicious traffic from ... -
Comparative Analysis of Deep Learning Models for Crop Diseases and Pest Classification
(International Journal of Formal Sciences: Current and Future Research Trends (IJFSCFRT), 2025)The deep learning models for crop diseases and pest classification research examined how deep learning might improve farming methods, particularly to accurately classify pests and diseases that affect crops. The importance ... -
Comparative Analysis of Machine Learning Algorithms Accuracy for Maize Leaf Disease Identification
(nternational Journal of Formal Sciences: Current and Future Research Trends (IJFSCFRT), 2023)The number of data points predicted correctly out of the total data points is known as accuracy in image classification models. Assessment of the accuracy is very important since it compares the correct images to the ones ... -
A Model for Face Recognition using EigenFace Algorithm
(International Journal of Formal Sciences: Current and Future Research Trends, 2023)The use of a computer to recognize a person by the means of their face is what is known as face recognition in artificial intelligence. The term biometrics is an umbrella term that includes face recognition as well as ... -
Architecture of Deep Learning Algorithms in Image Classification: Systematic Literature Review
(International Journal of Formal Sciences: Current and Future Research Trends (IJFSCFRT), 2023)The development of deep learning algorithms has led to major improvements in image classification, a key problem in computer vision. In this study, the researcher provide an in-depth analysis of the various deep learning ... -
An Empirical Analysis of Encoder Decoder (U Net) Variants for Medical Image Segmentation
(International Journal of Scientific Research in Computer Science and Engineering, 2025)U-Net convolutional neural networks have become a cornerstone in medical image processing, particularly for complex segmentation tasks. However, with the proliferation of various U-Net variants, it is imperative to evaluate ...
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