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56 results for “Information Matrix”
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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 · 3,099 accessesView PDFCite
Research ArticleOpen accessIn the abstractModified ACS Centroid Memory for Data ClusteringAyad Mohammed Jabbar, Ku Ruhana Ku-Mahamud, Rafid SagbanAnt Colony Optimization (ACO) is a generic algorithm, which has been widely used in different application domains due to its simplicity and adaptiveness to different optimization problems. The key component that governs the search process in this algorithm is the management of its memory model. In contrast to other algorithms, ACO explicitly utilizes an adaptive memory, which is important to … …Journal of Computer Science, Vol. 15, Issue 10 · 11 Oct 2019 · 7,641 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Test on the Multivariate Behrens–Fisher Problem in High–Dimensional Data by Block Covariance EstimationParanut Sukcharoen, Samruam ChongcharoenIn this paper, we proposed a new testing statistic for testing the equality of mean vectors from two multivariate normal populations when the covariance matrices are unknown and unequal in high–dimensional data. A new test is proposed based on the idea of keeping more information from the sample covariance matrices as much as possible. A proposed test is invariant under … …Journal of Mathematics and Statistics, Vol. 15, Issue 1 · 2 Apr 2019 · 7,369 accessesView PDFCite
Research ArticleOpen accessIn the abstractStroke Risk Assessment with Classical ML MethodsMohammad Aref Alshraideh, Najwan Alshraideh, Abedalrahman Alshraideh et al.Stroke, often caused by a disruption in the supply of essential oxygen, blood, and nutrients to the brain, represents a significant global health challenge. Due to limited resources, developing countries like Ethiopia face unique obstacles in identifying and treating strokes. This study explores the potential of Machine Learning (ML) techniques to predict stroke risk and facilitate early detection and intervention. … …Journal of Computer Science, Vol. 21, Issue 1 · 18 Dec 2024 · 4,649 accessesView PDFCite
Research ArticleOpen accessIn the abstractPerformance Analysis of LDA, AdaBoost and Ensemble Bag Classifiers for Automatically Recognizing Nine Common Facial ExpressionsM.D. Sumithra, M. Abdul RahimanFacial expression recognition holds a prominent role in today’s digital world with more Human –Computer Interaction happening in day to day life. Successful identification of facial expressions needs extraction of descriptive attributes from the active facial patches and accurate classification. This paper is presented with the comparison of three multi class classifiers namely Linear Discriminant Analysis, AdaBoost and Ensemble bag. … …Journal of Computer Science, Vol. 14, Issue 9 · 27 Sep 2018 · 7,787 accessesView PDFCite
Research ArticleOpen accessIn the abstractCommunity Aware Recommendation System with Explicit and Implicit Link PredictionMuhammed E Abd Alkhalec Tharwat, Mohd Farhan Md Fudzee, Shahreen Kasim et al.Recommendation systems are essential tools that help users discover content they may be interested in, amidst the vast amount of information available online. However, current methods, such as using historical user-item interactions and collaborative filtering, have limitations in accurately predicting user preferences. Our research aims to address these challenges and improve the performance of recommendation systems. In this article, we … …Journal of Computer Science, Vol. 19, Issue 8 · 19 Jul 2023 · 5,858 accessesView PDFCite
Research ArticleOpen accessIn the abstractBlind Pre-Coder for MIMO System Capacity EnhancementEman Al Khader, Shereen S. IsmailIn this study, linear scheme at the transmitter is proposed as a blind pre-coder to improve the performance and enhance the channel capacity of MIMO systems with certain configurations for transmitting and receiving antennas over fading channels. This is accomplished by generating a specific linear pre-coder matrix without having any prior information about the Channel State (CS) matrix. Simulation results … …American Journal of Engineering and Applied Sciences, Vol. 10, Issue 1 · 11 Jan 2017 · 7,688 accessesView PDFCite
Research ArticleOpen accessIn the abstractModelling the Error Term of Australia Gross Domestic ProductAyodele Abraham Agboluaje, Suzilah Ismail, Chee Yin YipThe main aim of this study is to model the Gross Domestic Product (GDP) with the new Combine White Noise (CWN) Model and compare the results with the Vector Autoregressive (VAR) Model and Exponential Generalized Autoregressive Conditional Heteroscedasticity (EGARCH) Model which are the existing models. The CWN model estimation yields best results with least information criteria and high log likelihood … …Journal of Mathematics and Statistics, Vol. 12, Issue 4 · 2 Nov 2016 · 6,930 accessesView PDFCite
Research ArticleOpen accessIn the abstractIMAGE ENCRYPTION BASED ON SINGULAR VALUE DECOMPOSITIONNidhal K. El Abbadi, Adil Mohamad, Mohammed Abdul-HameedImage encryption is one of the most methods of information hiding. A novel secure encryption method for image encryption is presented in this study. The proposed algorithm based on using singular value decomposition SVD. In this study we start to scramble the image data according to suggested keys (two sequence scrambling process with two different keys) to finally create two … …Journal of Computer Science, Vol. 10, Issue 7 · 19 Feb 2014 · 7,113 accessesView PDFCite
Research ArticleOpen accessIn the abstractON REDUCED SCALAR EQUATIONS FOR SYNCHRONOUS BOOLEAN NETWORKSAli Muhammad Ali Rushdi, Adnan Ahmad AlsogatiA total description of a synchronous Boolean network is typically achieved by a matrix recurrence relation. A simpler alternative is to use a scalar equation which is a possibly nonlinear equation that involves two or more instances of a single scalar variable and some Boolean operator(s). Further simplification is possible in terms of a linear reduced scalar equation which is … …Journal of Mathematics and Statistics, Vol. 9, Issue 3 · 10 Sep 2013 · 6,665 accessesView PDFCite