Research ArticleOpen accessIn the abstractDistributed Vehicle Tracking System Using Image Processing TechniquesIehab Abdul Jabbar Kamil, Mohanad Abdulsalam Al-AskariIn this part of the research, an implementation of a distributed vehicle tracking system that uses image processing techniques for real-time automobile surveillance is done. The system uses OpenCV, Pytesseract and Optical Character Recognition (OCR) for the extraction of the license plate information from vehicle images to identify and track vehicles. By doing so, distributed computing enables the system to … …Journal of Computer Science, Vol. 21, Issue 8 · 9 Oct 2025 · 2,263 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 · 4,695 accessesView PDFCite
Research ArticleOpen accessIn the abstractStock Closing Price Forecasting Using LSTM, Sentiment Analysis, Kalman FilterAssel Abdildayeva, Galymzhan Nurtugan, Guldana Taganova, Ardak AkhmetovaThe article explores the problem of predicting the closing prices of stocks using an innovative approach that combines methods of machine learning, sentiment analysis and noise filtering. The focus is on the development and testing of a comprehensive model that integrates recurrent neural networks (LSTM) for time series analysis, the GPT-3 language model for processing and analyzing textual data from … …Journal of Computer Science, Vol. 20, Issue 11 · 4 Sep 2024 · 6,262 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredictive Mathematical Modeling and Classification of Retail Sales Orders Using AI Machine Learning TechniquesMohammad Subhi Al-Batah, Mowafaq Salem Alzboon, Hamzeh ZureigatThis study presents a systematic mathematical model known as a low-code approach to classifying retail sales orders by size using AI machine learning techniques within the Orange Data Mining platform. Leveraging a real-world sales dataset sourced from Kaggle, we implemented and evaluated ten classification models, including ensemble learners (AdaBoost, Gradient Boosting), probabilistic classifiers (Naïve Bayes), distance-based methods (kNN), and interpretable … …Journal of Computer Science, Vol. 22, Issue 3 · 10 Mar 2026 · 1,567 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Distillation GAN Model for Network Intrusion DetectionChandrakala C B, Sai Sreevall, Raghudathesh G PThis study presents a distillation-based Generative Adversarial Network (GAN) model designed for intrusion detection in network systems. A Teacher-Student architecture is proposed, in which a single teacher generator is utilized to train both the teacher discriminator and the student discriminator. The model was trained to identify anomalies present in network traffic intrusions by tuning the min-max loss function in GANs. … …Journal of Computer Science, Vol. 22, Issue 2 · 5 Mar 2026 · 1,549 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Deep Learning Approach for Tomato Leaf Disease Detection Using Optimized CNN ArchitectureSunil K. Vithalani, Vipul K. DabhiEarly disease detection in plants is essential for sustaining agricultural yield and guaranteeing food security. A comparative analysis of transformer-based and convolutional based deep learning models for classifying tomato leaf diseases is presented. Specifically, it examines the performance of a Vision Transformer (ViT), tested both in a form of scratch training setup and through transfer learning, against well-known CNN architectures … …Journal of Computer Science, Vol. 22, Issue 1 · 7 Feb 2026 · 3,917 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Dam Safety and Management: Long Short-Term Memory Based Predictive Models for Accurate Alert ForecastingNisha C. M, N. ThangarasuDam management and early alert systems are critical for effective water resource management. Accurate prediction of dam alert signals facilitates proactive decision-making, thereby aiding in the effective management and reduction of potential risks linked to dam operations. Within this research, Long Short-Term Memory (LSTM) networks are utilized to forecast dam alert signals issued from the dam by leveraging daily parameters, … …Journal of Computer Science, Vol. 22, Issue 1 · 6 Feb 2026 · 1,626 accessesView PDFCite
Research ArticleOpen accessIn the abstractA 2-Tier Stacking Ensemble Classifier for Disease ClassificationK. Sukanya Varshini, R. Annie UthraDiarrhea, dysentery, and dehydration are top of the list of high mortality-causing diseases in children under the age group of five. Despite the tremendous growth of machine learning in the field of medical research, still, some areas remain untouched, especially, the pediatric department. Since medical data is used in the proposed work, even a slight increase in the accuracy of … …Journal of Computer Science, Vol. 19, Issue 7 · 7 Jun 2023 · 5,785 accessesView PDFCite
Research ArticleOpen accessIn the abstractOnline ML Streaming-Based Leading Ensemble Classifier for Intrusion Detection in IoTNeeraj Sharma, Neelu NihalaniIn the present decade, preventing IoT networks from malicious attacks and to ensure the privacy and integrity of data by strengthening their cybersecurity perspective is a critical concern. Traditional methods alone are not sufficient to detect multiple attacks. IDS-based system plays a crucial role to maintain security due to continuous expanding nature of IoT networks. Traditional methods alone are often … …Journal of Computer Science, Vol. 21, Issue 10 · 16 Dec 2025 · 2,078 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Analysis of GPT-4o and Gemini 1.5 Pro in Thai Exam SettingsKasidis Miankamnerd, Taechasith KangkhuntodThis study presents a comparative analysis of two advanced AI models, GPT-4o and Gemini 1.5 Pro, within the context of Thai standardized exams. The selected tests include POSN Biology, POSN Mathematics, A-Level Thai Language, and A-Level Social Studies, chosen based on consultations with educational experts to ensure relevance. Each AI model was tested three times on these exams to ensure … …Journal of Computer Science, Vol. 21, Issue 1 · 30 Dec 2024 · 7,200 accessesView PDFCite