Research ArticleOpen accessIn the keywordsRobust Template Matching Using Orthogonal Legendre Moment InvariantsKhalid M. HosnyProblem statement: Template matching is a famous methodology that has a wide range of applications in image and signal processing. For a template and input image, template matching methodology finds the partial input image that is most closely matches the template image in terms of specific criterion such as the Euclidean distance or cross-correlation. Approach: In this study, a fast … …Journal of Computer Science, Vol. 6, Issue 10 · 30 Jul 2010 · 7,617 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA New Three-Term Preconditioned Gradient memory Algorithm for Nonlinear Optimization ProblemsAbbas Y. AL-Bayati, Ivan S. LatifIn the present study, we proposed a three-term of preconditioned gradient memory algorithms to solve a nonlinear optimization problem. The new algorithm subsumes some other families of nonlinear preconditioned gradient memory algorithms as its subfamilies with Powell's Restart Criterion and inexact Armijo line searches. Numerical experiments on twenty one well-known test functions with various dimensions generally encouraged and showed that … …Journal of Mathematics and Statistics, Vol. 4, Issue 2 · 30 Jun 2008 · 6,781 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAn Effective Data Transformation Approach for Privacy Preserving ClusteringR. R. Rajalaxmi, A. M. NatarajanA new stream of research privacy preserving data mining emerged due to the recent advances in data mining, Internet and security technologies. Data sharing among organizations considered to be useful which offer mutual benefit for business growth. Preserving the privacy of shared data for clustering was considered as the most challenging problem. To overcome the problem, the data owner published … …Journal of Computer Science, Vol. 4, Issue 4 · 30 Apr 2008 · 7,112 accessesView PDFCite
Research ArticleOpen accessIn the abstractCooling Load Prediction in the Under-Actuated Zone with Multilayer Perceptron Artificial Neural NetworkYaddarabullah, Aedah Abd Rahman, Amna SaadThis study focuses on addressing the challenge of predicting cooling loads in under-actuated zones, where the variability in occupant behavior, environmental conditions, and electronic usage creates complex dynamics. Traditional models like Support Vector Regression (SVR) and E-Lastic-Net (ELN) often struggle to capture these non-linear relationships, leading to inefficient Heating, Ventilation, and Air Conditioning (HVAC) management and increased energy consumption. To … …Journal of Computer Science, Vol. 21, Issue 3 · 27 Jan 2025 · 5,300 accessesView PDFCite
Research ArticleOpen accessIn the abstractModified U-Net With VGG11-BN Encoder and Frost Filter Based Pre-Processing for Copy Move Forgery LocalizationAshutosh Pandey, Niranjan Lal, Ashish Kumar ChakravertiCopy-move forgery is a widely used forgery method in digital image forensics, which involves copying and pasting a part of an image into another part of the image to hide or duplicate the visual information. This makes it difficult to detect such manipulations, particularly when the regions are subjected to geometric and photometric transformations. A Frost Filter-Enhanced Encoder-Decoder U-Net is … …Journal of Computer Science, Vol. 22, Issue 10 · 6 Oct 2026 · 457 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Analysis of Fraud Detection Methods in Banking Using Machine Learning TechniquesYoussef Tounsi, Ennouri TaziFraud detection in banking requires algorithms that balance classification performance, computational efficiency, and regulatory interpretability, criteria that are rarely benchmarked together. We present a comprehensive evaluation of nine machine learning approaches (Logistic Regression, Decision Tree, Random Forest, SVM, SGD, XGBoost, CatBoost, LightGBM, and MLP) across three datasets differing in size, imbalance severity, and feature type (synthetic, real-world PCA-anonymized, and large-scale … …Journal of Computer Science, Vol. 22, Issue 6 · 22 Jun 2026 · 1,341 accessesView PDFCite
Research ArticleOpen accessIn the abstracte-Governance Practices in Nepal: Opportunities, Challenges, and Strategies from the Local LevelReg Bahadur Bhandari, Nirav Bhatta et al.This research explores the integration of digital tools for e-governance at local levels in Nepal, with a particular emphasis on the current state of digitalization and the opportunities and challenges encountered at the local level. We collected data using a qualitative research methodology, conducting semi-structured interviews and reviewing relevant documents. The findings reveal substantial advancements in digital tools for public … …Journal of Computer Science, Vol. 22, Issue 1 · 16 Feb 2026 · 2,189 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimized XGBoost for Ethereum Fraud Detection: A Cost-Sensitive ApproachSupriya P., Rubah Sheriff, Shreya Padaki et al.In today’s technologically advancing world, many fields from finance to healthcare and education are shifting toward a digital and decentralized format. A significant transformation is underway with the currency of the masses. Blockchain-based cryptocurrencies like Bitcoin and Ethereum allow users to generate fungible tokens anonymously through smart contracts. However, these features also facilitate illicit transactions and cybercrimes like fraud, phishing, … …Journal of Computer Science, Vol. 21, Issue 12 · 10 Jan 2026 · 2,770 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdvanced Hierarchical Deep Learning Approach for Intrusion Detection: Hyperparameter Tuning and Performance Evaluation on the CICIDS DatasetAjeet Singh, Azath M, Shahazad Niwazi Qurashi et al.Intrusion Detection Systems (IDS) are essential in the communication security and integrity of contemporary network architectures. This study introduces a novel advanced hierarchical deep learning model for network intrusion detection using the CICIDS dataset-2019. To improve the detection accuracy, the proposed model architecture builds several deep learning layers embedded with hyperparameters' optimization. Additional preprocessing steps, including over-sampling and min-max scaling, … …Journal of Computer Science, Vol. 21, Issue 11 · 26 Dec 2025 · 2,148 accessesView PDFCite