Research ArticleOpen accessIn the abstractOmega Network Hash ConstructionChai Wen Chuah, Azman SamsudinProblem statement: Cryptographic hash functions are important cryptographic primitives. They are commonly used for data integrity checking and data authentication. Most of the cryptographic hash functions are based on the Merkle-Damgård construction. The basic Merkle-Damgård construction runs over the input sequentially, which can lead to problems when the input size is large since the computation time increases linearly. Approach: Therefore, … …Journal of Computer Science, Vol. 5, Issue 12 · 31 Dec 2009 · 7,127 accessesView PDFCite
Research ArticleOpen accessIn the abstractOn the Probability Density Function of the Test Statistic for One Nonlinear GLR Detector Arising from fMRIFangyuan NanRecently an important and interesting nonlinear generalized likelihood ratio (GLR) detector emerged in functional magnetic resonance imaging (fMRI) data processing. However, the study of that detector is incomplete: the probability density function (pdf) of the test statistic was draw from numerical simulations without much theoretical support and is therefore, not firmly grounded. This correspondence presents more accurate (asymptotic) closed form … …Journal of Mathematics and Statistics, Vol. 3, Issue 2 · 30 Jun 2007 · 7,108 accessesView PDFCite
Research ArticleOpen accessIn the abstractNew Algorithm for Digital Video EncryptionSamsul Arifin, Wihikanwijna, Tuga Mauritsus et al.This research aims to propose a safe digital video data alternative employing symmetric cryptography and an encryption technique using Partition. The Hill Cipher method requires a square key matrix with an inverse modulo the unimodular matrix is one of the unique matrices with an inverse. The encryption mechanism is modulo matrix multiplication, with shift cipher encryption employed to encrypt defective … …Journal of Computer Science, Vol. 19, Issue 7 · 19 Jun 2023 · 6,400 accessesView PDFCite
Research ArticleOpen accessIn the abstractLENGTH BIASED BETA-PARETO DISTRIBUTION AND ITS STRUCTURAL PROPERTIES WITH APPLICATIONNareerat Nanuwong, Winai BodhisuwanThe concept of length biased distribution can be employed in development of proper models for lifetime data. Its method is adjusting the original probability density function from real data and the expectation of those data. This adjustment can bring about to correct conclusions of models. Therefore, we introduced the Length Biased Beta-Pareto (LBBP) distribution, so-called a new generalized of Pareto … …Journal of Mathematics and Statistics, Vol. 10, Issue 1 · 11 Jan 2014 · 7,242 accessesView PDFCite
Research ArticleOpen accessIn the abstractNeural Network in Modeling Malaysian Oil Palm YieldZuhaimy Ismail, Azme KhamisProblem statement: Forecasting of palm oil yield has become an important element in the management of oil palm industry for proper planning and decision making. The importance of yield forecasting has led us to explore modeling of palm oil yield for Malaysia using the most recent development of Artificial Neural Network (ANN). The main issue in yield forecasting is to … …American Journal of Applied Sciences, Vol. 8, Issue 8 · 19 Jul 2011 · 8,581 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Ensemble of Gaussian Mixture Model and Support Vector Machines for Network Intrusion DetectionOlujimi Daniel Alao, Sheriff Alimi, Shade Oluwakemi Kuyoro et al.NetworkIntrusion Detection Systems (NIDS) can protect computer networks and computersystems by detecting abnormal network packets and taking agreed action plans,such as notifying an administrator or rejecting the network packets. In this study,the aim is the implementation of NIDS with improved performance using anensemble of Support Vector Machines (SVMs) and the Gaussian Mixture Model(GMM). Four SVMs with Radial Basis Function (RBF), … …Journal of Computer Science, Vol. 18, Issue 9 · 21 Sep 2022 · 6,123 accessesView PDFCite
Research ArticleOpen accessIn the abstractBuilding Probability Functions by Persian CurveAbdolrasoul Ranjbaran, Mohammad Ranjbaran, Fatema RanjbaranConstruction of a probability function for a given random data is the main theme of several branches of human knowledge, where it is an active area of study. In spite of great developments, the solution needs extensive effort and the results contain epistemic uncertainty. In this study, making use of the logical reasoning and concise mathematical logics, a method called … …International Journal of Structural Glass and Advanced Materials Research, Vol. 4, Issue 1 · 31 Oct 2020 · 8,156 accessesView PDFCite
Research ArticleOpen accessIn the abstractTAGN-IDC: Implicit Discrete Constraints for Tsunami Aware Graph Neural Networks in Spatial Evacuation RoutingSularno, Wendi Boy, Putri Anggraini et al.Tsunami evacuation route requires rapid identification of safe evacuation paths under dynamically changing hazard conditions. A major challenge is incorporating hard binary road-blockage constraints caused by tsunami inundation while maintaining end-to-end differentiability for deep learning models. Existing approaches commonly rely on continuous relaxations or stochastic sampling techniques, which either compromise physical feasibility or increase computational complexity. This study proposes the … …Journal of Computer Science, Vol. 22, Issue 9 · 24 Sep 2026 · 711 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnimal Health Prediction Using Hybrid CNN Based BiLSTM Classification Model: A Deep Learning ApproachJ. Rathi, A. SumathiAccurate prediction of animal diseases is vital in veterinary medicine, as it can substantially enhance animal health outcomes and mitigate economic losses, making it a critical task that warrants attention and innovative solutions. This paper proposes a novel approach to animal condition classification, leveraging an Auto-encoder-based feature selection process and an Improved Hybrid Convolutional Neural Networks (CNN) with Bidirectional (Bi-LSTM) … …Journal of Computer Science, Vol. 22, Issue 5 · 20 May 2026 · 1,488 accessesView PDFCite