Research ArticleOpen accessIn the abstractAn Accurate Mango Pest Identification Employing the Gaussian Mixture Model and Expectation-Maximization (EM) AlgorithmD. Lita Pansy, M. MuraliMangoes are fruits that originated in South and Southeast Asia. Mango fruits are consumed in high volume worldwide. However, fruit, stem, root, and mango leaves are damaged by pests, and it has a significant negative impact on mango production. Many works were developed for the pest detection of mango; but, none of the works concentrated on the practical applicability and … …Journal of Computer Science, Vol. 21, Issue 1 · 3 Dec 2024 · 5,063 accessesView PDFCite
Review ArticleOpen accessIn the abstractMachine Learning Integration for Precise Facial Micro-Expression RecognitionViola Bakiasi Shtino, Markela Muça, Senada BushatiThis study advances facial micro-expression recognition through innovative machine-learning techniques, addressing critical needs in psychology, security, and human-computer interaction. The purpose of this study is to improve micro-expression recognition through the optimization of feature transformation and machine learning algorithms. We introduce a novel approach combining Kernel Principal Component Analysis (KPCA) and Uniform Manifold Approximation and Projection (UMAP) for dimensionality reduction, … …Journal of Computer Science, Vol. 20, Issue 11 · 22 Oct 2024 · 5,592 accessesView PDFCite
Research ArticleOpen accessIn the abstractCrime Rate Analysis and Mapping from Socio-Economic Data Using Deep Neural NetworksSanthosh Sankara, Nadeson SugithaCrime prediction is the attempt to identify and mitigate future criminal activity. Crime is typically "unpredictable"; it cannot be predicted in advance. Addressing the roots of crime has long been a priority for researchers. Extracting causality from data is difficult if the relevant data aspects are not selected. In this research activity, an innovative classification framework is defined which is … …Journal of Computer Science, Vol. 20, Issue 10 · 17 Aug 2024 · 5,089 accessesView PDFCite
Research ArticleOpen accessIn the abstractA New Hybrid Model to Predict the Performance of Trainee Teachers Based on Clustering and ClassificationYissam Lakhdar, Khawla EL-Bendadi, Brahim BakkasThis article explores how artificial intelligence, particularly machine learning, can be used to assess and predict the performance of trainee teachers in Morocco. Considering the country's focus on integrating technology into education and the challenges posed by the COVID-19 pandemic, the authors propose a novel hybrid model that combines clustering and classification algorithms. This model aims to understand the Information … …Journal of Computer Science, Vol. 20, Issue 9 · 26 Jun 2024 · 5,100 accessesView PDFCite
Research ArticleOpen accessIn the abstractData Analytics for Imbalanced DatasetMadhura Prabha R, Sasikala SThe primary issue in real-time big data classification is imbalanced datasets. Even though we have many balancing techniques to reduce imbalance ratio which is not suitable for big data that has scalability issues. This study is envisioned to explore different balancing techniques with experimental study. We tried comparing the effectiveness of various balancing strategies, including cutting-edge approaches for severely unbalanced … …Journal of Computer Science, Vol. 20, Issue 2 · 11 Jan 2024 · 5,473 accessesView PDFCite
Research ArticleOpen accessIn the abstractPandemic Analysis and Preparedness Using a Three Layer Machine Learning ApproachArtika Singh, Manisha JailiaOutbreak analysis provides research-based information and data to enable scientific decision-making to manage an effective response to a pandemic. Pandemic analysis has its own set of challenges, such as limited data, the need for real time analysis, and the complexity of outbreak patterns. This study proposes a hybrid approach to manage such a spread through a 3-layer machine learning-based outbreak … …Journal of Computer Science, Vol. 22, Issue 11 · 15 Oct 2026 · 614 accessesView PDFCite
Research ArticleOpen accessIn the abstractGait Analysis Combining Sports Biomechanics and ImagingChao ZhuAiming at the problems of marker positioning error, soft tissue interference, and insufficient personalized modeling ability in traditional gait analysis, this study proposes a gait assessment method that integrates sports biomechanics and multimodal imaging analysis. Firstly, based on the public OU-ISIR gait database, a Convolutional Neural Network (CNN) is used to extract the key gait features in the human silhouette … …American Journal of Biochemistry and Biotechnology, Vol. 22, Issue 2 · 20 Jul 2026 · 850 accessesView PDFCite
Research ArticleOpen accessIn the abstractSmart and Secure Anomaly Detection in IoT Using Quantum Inspired Kernel Ensemble LearningAbrar M. AlajlanThe exponential growth of the Internet of Things networks has greatly increased the attack surface for cyber threats, necessitating the use of strong and perceptive anomaly detection systems. Traditional intrusion detection systems often struggle with high false alarm rates, limited generalization, and inefficiency in processing high-dimensional heterogeneous IoT data. To address this issue, a novel Hybrid Quantum-Enhanced Kernel Ensemble Learning … …Journal of Computer Science, Vol. 22, Issue 3 · 12 Mar 2026 · 1,762 accessesView PDFCite
Research ArticleOpen accessIn the abstractDetecting Anomalies in IoT Using Intuitionistic Fuzzy Clustering AlgorithmsVijo Arul Selvi M., Fehmin Nadira Laskar, Fokrul Alom Mazarbhuiya et al.Intuitionistic Fuzzy Sets (IFS) are convenient ways to represent the vagueness and uncertainty inherent in any dataset. There are many uses of these. One such use is the Fuzzy C-Means (FCM) algorithm, which clusters the data objects into a pre-assigned (c) number of fuzzy clusters, which has been adopted in many fields, namely, pattern classification, anomaly detection, fraud identification, etc. … …Journal of Computer Science, Vol. 22, Issue 2 · 2 Mar 2026 · 1,600 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Metaheuristic-Optimized Feature Selection for Early-Stage Diabetes Prediction With SHAP-Guided Insight into Influential AttributesEsmay Azam Rochy, Jannatul Ferdaus, Uzzal Biswas et al.Diabetes is a metabolic disorder that causes elevated blood glucose. This long-term health condition can lead to cardiovascular diseases, stroke, kidney failure, visual impairment, neuropathy, and even death in critical cases. So, a Computer-Aided Diagnostic (CAD) system is necessary to diagnose diabetes automatically. A clinician can utilize a machine learning-based CAD system that automatically diagnoses many people. This paper will … …Journal of Computer Science, Vol. 22, Issue 2 · 24 Feb 2026 · 1,736 accessesView PDFCite