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Research ArticleOpen accessIn the abstractPHASEY: A Contrastive Learning Approach for Enhanced Human Gait Phases RecognitionUrvashi, Deepak Kumar, Vinay Kukreja, Ayush DograHuman gait has gained much attention in behavioral biometrics as it possesses unique and distinctive characteristics. Gait phases, which describe the different patterns of human walking, are significant for the analysis and understanding of movement in an individual. Hence, the identification of gait phases is important for the accurate determination and interpretation of walking patterns, ranging from healthcare and security … …Journal of Computer Science, Vol. 21, Issue 8 · 16 Sep 2025 · 4,643 accessesView PDFCite
Research ArticleOpen accessIn the abstractTwitter Sentiment Analysis Using Machine Learning and Deep Learning TechniquesSafa Khalid Al Sarayrah, Noor Mahmoud Alkudah, Hesham Yousef Al-kharabshehThis research investigates the use of Machine Learning (ML) and Deep Learning, including BiLSTM approaches, for Sentiment Analysis (SA) of consumer reviews on social media sites. Businesses are increasingly depending on online reviews to determine customer satisfaction due to social media's explosive growth. We used three classification models, the assessment of these attitudes uses Naive Bayes (NB), Support Vector Machine … …Journal of Computer Science, Vol. 21, Issue 8 · 1 Sep 2025 · 6,818 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntelligent Intrusion Detection System Using RF, SVM, and DT: A Comparison-Based KDD Data SetWalaa Hassan Elashmawi, Alaa Sheta, Ahmad Al-QeremThe rapid growth of technology has brought about many advantages, but has also made networks more susceptible to security threats. Intrusion Detection Systems (IDS) play a vital role in protecting computer networks against malicious activities. Given the dynamic and constantly evolving nature of cyber threats, these systems must continuously adapt to maintain their effectiveness. Machine Learning (ML) methods have gained … …Journal of Computer Science, Vol. 21, Issue 8 · 28 Aug 2025 · 5,821 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimization-Based Feature Selection and Ensemble Machine Learning Algorithms for Breast Cancer ClassificationSatyabrata Patro, Jyotirmaya Mishra, Bhavani Sankar PandaBreast cancer, which originates in a woman's breast tissue, is acknowledged to be a significant study topic in the medical field. For a long time, there has been a serious concern with the classification of breast cancer. Thus, to effectively categorize the breast cancer dataset, machine learning methods are designed and implemented. In previous research, the algorithms have classification accuracy … …Journal of Computer Science, Vol. 21, Issue 7 · 17 Jul 2025 · 3,180 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Vertical Stacking-Based Ensemble Deep Learning Model for Early Diagnosis of Alzheimer's Disease Using Multimodal MRI ScansParvatham Niranjan Kumar, Lakshmana Phaneendra MaguluriEarly detection of Alzheimer's Disease (AD) is crucial for timely interventions that can slow disease progression, enhance quality of life, and assist with future planning. Convolutional Neural Networks (CNNs) are an efficient method for processing image-based data. In this work, we used CNN-based deep learning models to extract structural information from structural MRI (sMRI) and brain neuron connectivity patterns from … …Journal of Computer Science, Vol. 21, Issue 6 · 14 Jun 2025 · 3,106 accessesView PDFCite
Research ArticleOpen accessIn the abstractSentiment Analysis Using Light Weight - Gradient Boosting Machine based Feature SelectionBikku Ramavath, Srikanth Kadainti, Nemani SubashSentiment analysis is a significant task in Natural Language Processing (NLP) that differentiates the emotions and opinions expressed in text or reviews. The sentiment analysis is challenging due to the complex language patterns and inappropriate or redundant features used for classification. In this research, the Light Weight - Gradient Boosting Machine (LWGBM) based feature selection is proposed to choose relevant … …Journal of Computer Science, Vol. 21, Issue 5 · 26 May 2025 · 4,709 accessesView PDFCite
Review ArticleOpen accessIn the abstractDeep Learning in Early Alzheimer’s Disease’s Detection: A Comprehensive Survey of Classification, Segmentation and Feature Extraction MethodsRubab Hafeez, Sadia Waheed, Syeda Aleena Naqvi et al.Alzheimer’s disease is a deadly neurological condition, impairing important memory and brain functions. Alzheimer’s disease promotes brain shrinkage, ultimately leading to dementia. Dementia diagnosis typically takes 2.8-4.4 years after the first clinical indication. Advancements in computing and information technology have led to many techniques for studying Alzheimer's disease. Early identification and therapy are crucial for preventing Alzheimer's disease, as early-onset … …Journal of Computer Science, Vol. 21, Issue 5 · 26 Apr 2025 · 5,774 accessesView PDFCite
Research ArticleOpen accessIn the abstractNonnegative Matrix Factorization Features Extraction and Ensemble Methods Classifier for ECG Image ClassificationHussain K. Ibrahim, Shawkat K. Guirguis, Hend A. ElsayedThis study is a novel proposed classification system for ECG image classification. This proposed system uses nonnegative matrix factorization for feature extraction and ensemble methods for classification, and the results are compared with the features extracted by the principal component analysis, kernel principal component analysis, and independent component analysis. Although algorithms find image classification challenging, humans typically find it easy. … …Journal of Computer Science, Vol. 21, Issue 4 · 15 Mar 2025 · 4,874 accessesView PDFCite
Research ArticleOpen accessIn the abstractNovel Depression Classification Framework Using Optimal Feature Integration with Hybrid Convolution (1D/3D) Based Adaptive Residual DenseNetB. Manjulatha, Suresh PabbojuThis study introduces a novel depression classification method by incorporating multimodal data to reduce this limitation and improve the accuracy of depression diagnosis. In the beginning, the multimodal data such as speech signal, Electroencephalographic (EEG), and text data is obtained from the benchmark datasets. These acquired text data are subjected to the text pre-processing phase, where the stemming, character removal, … …Journal of Computer Science, Vol. 21, Issue 3 · 25 Feb 2025 · 5,869 accessesView PDFCite
Review ArticleOpen accessIn the abstractCybercrime in the AI Era: Definitions, Classification, Severity Assessment and the Role of AI in Combating ThreatsNorah Sultan Alshahrani, Fahd Saleh Alotaibi, Khaled Hamed Alyoubi, Muhammad Sher RamzanThe growing prevalence, complexity and financial impact of cybercrimes pose significant challenges for law enforcement agencies worldwide. Many organizations are utilizing different technologies such as cloud technology to improve speed, accuracy, and reliability. However, without proper security measures, the risk is still vital against cyberattacks. Cybercrime can lead to various negative outcomes, including theft, fraud, financial losses, a decline in … …Journal of Computer Science, Vol. 21, Issue 3 · 12 Feb 2025 · 7,164 accessesView PDFCite