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Research ArticleOpen accessIn the abstractBlockchain-Enabled Decisive Red Fox Optimizer-Based Feature Selection With Deep Learning-Based Intrusion Detection SystemC. Ananth, S. Sathiyarani, N. MohananthiniRecently, Intrusion Detection Systems (IDS) using Deep Learning (DL) models become useful in accomplishing network security. The selected features serve as input to the DL model, which is trained on labelled datasets to learn intrinsic patterns distinguishing malicious from normal network behaviour. DL techniques like Convolutional Neural Networks (CNN) are usually utilized. The seamless combination of Public Blockchain (BC) technology … …Journal of Computer Science, Vol. 21, Issue 12 · 20 Jan 2026 · 1,714 accessesView PDFCite
Research ArticleOpen accessIn the abstractImproving Routing Discovery Based Velocity-Aware Probabilistic Using AODV with Link Prediction in Mobile Ad-hoc NetworksZaid BassfarThe current process associated with enhancing the QoS in routing for MANETs has reserved a high importance due to the limitation of available route discovery in dynamic topology. The conventional methods of route discovery schemes in MANETs are commonly designed in order to estimate the number of nodes in routes using the standard probabilistic models. Such models are utilized by … …American Journal of Applied Sciences, Vol. 14, Issue 8 · 1 Aug 2017 · 7,655 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Hybridized BERT-Based Approach for Crime News Collection and Classification from Online NewspapersAshour Ali, Shahrul Azman Mohd Noah, Lailatul Qadri Zakaria, Saeed Amer Al AmeriCrime news analysis is crucial for understanding criminal activity, enhancing public safety, and informing policy decisions. The exponential growth and unstructured nature of online news articles, however, present significant challenges for efficient and accurate information extraction. This study aims to enhance the efficiency and accuracy of crime news data collection and classification through advanced Natural Language Processing (NLP) techniques and … …Journal of Computer Science, Vol. 21, Issue 9 · 16 Oct 2025 · 2,288 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Enhanced Algorithm for Small Object Detection based on Thermal Imaging Using YOLOv8-EPBRavina Gupta, Sarika Jain, Manoj KumarObject detection is one of the most important and challenging problems in the computer vision domain. Using the power of deep models, researchers have carefully explored and made significant contributions to increasing the effectiveness of object detection and related tasks, such as object identification, localization, and segmentation. This progress is due to the rapid progress of deep learning in the … …Journal of Computer Science, Vol. 21, Issue 6 · 13 Jun 2025 · 4,212 accessesView PDFCite
Research ArticleOpen accessIn the abstractClassification of X-Ray Images Using Convolutional Neural Network and Automatic Hyper-Parameter Selection to Detect Tuberculosis (TB)Biswaranjan Debata, Rojalina Priyadarshini, Sudhir Kumar Mohapatra, Tarikwa Tesfa BedaneTuberculosis (TB) is a major public health issue in India, contributing significantly to the global burden of respiratory diseases. This study introduces a Convolutional Neural Network (CNN)--based model for the early and cost-effective detection of TB using chest X-ray images. The proposed model, featuring 13 layers and automated hyperparameter selection, classifies images as infected or not infected. It is evaluated … …Journal of Computer Science, Vol. 21, Issue 2 · 21 Jan 2025 · 6,983 accessesView PDFCite
Research ArticleOpen accessIn the abstractSentiment Analysis on User Reviews of Snapchat in IndonesiaEvaristus Didik Madyatmadja, Brigita Christabel Surya Winata, Evelyn Pradhan et al.This research explores the sentiment expressed in Snapchat user reviews within the Indonesian context, leveraging advanced natural language processing techniques and classification models. With a focus on the Indonesian user base, 8,015 reviews from the Google Play Store were analyzed using naive bayes, Support Vector Machines (SVM), and random forest models. The results indicated that the random forest model outperformed … …Journal of Computer Science, Vol. 21, Issue 1 · 2 Jan 2025 · 5,591 accessesView PDFCite
Research ArticleOpen accessIn the abstractTruncated Estimate in Log-Binomial Model: Algorithm and SimulationLuyan Dai, Yang Li, Ye ShenProblem statement: Relative risk has concrete meanings of comparing two groups and measuring the association between exposures and outcomes in medical and public health studies. Log-binomial model, using a log link function on binary outcomes, is straightforward to estimate risk ratios, whereas generates boundary problems. When the estimates are located near the boundary of constrained parameter space, common approaches or … …Current Research in Biostatistics, Vol. 2, Issue 1 · 7 May 2012 · 8,291 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Study on the Behavior of Volatility in Saudi Arabia Stock Market Using Symmetric and Asymmetric GARCH ModelsAjab Al Freedi, Ahmed Shamiri, Zaidi IsaProblem statement: This study examines several stylized facts (heavy-tailedness, leverage effect and persistence) in volatility of stock price returns exploiting symmetric and asymmetric GARCH family models for Saudi Arabia. Approach: This study is carried out using closing stock market prices over 15 years covering the period 1 January 1994 to 31 March 2009. The sample period is divided into three … …Journal of Mathematics and Statistics, Vol. 8, Issue 1 · 7 Feb 2012 · 7,577 accessesView PDFCite
Research ArticleOpen accessIn the abstractSteel Plates Faults Diagnosis with Data Mining ModelsMahmoud Fakhr, Alaa M. ElsayadProblem statement: Over the last two decades, Fault Diagnosis (FD) has a major importance to enhance the quality of manufacturing and to lessen the cost of product testing. Actually, quick and correct FD system helps to keep away from product quality problems and facilitates precautionary maintenance. FD may be considered as a pattern recognition problem. It has been gaining more … …Journal of Computer Science, Vol. 8, Issue 4 · 31 Jan 2012 · 11,378 accessesView PDFCite
Research ArticleOpen accessIn the abstractForecasting the Spanish Stock Market Returns with Fractional and Non-Fractional ModelsGuglielmo Maria Caporale, Juncal Cunado, Luis A. Gil-AlanaProblem statement: The content of this note was to assess the forecasting accuracy of various models of the Spanish stock market returns. Approach: We use daily data on the IBEX 35 for the time period January 4th, 2001-March 28th, 2006 and employ both fractional and non-fractional models. Results: The results on the prediction errors for the out-of-sample forecasts indicate that … …American Journal of Economics and Business Administration, Vol. 3, Issue 4 · 8 Dec 2011 · 7,316 accessesView PDFCite