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Research ArticleOpen accessIn the abstractEnhancing IoT RPL Protocol Security Against Black Hole Attacks with Deep Learning TechniquesKrari Ayoub, Hajami Abdelmajid, Toubi Ayoub, Mihi SoukainaAs the Internet of Things (IoT) extends its reach into critical infrastructures, it encounters escalating security threats, particularly black hole attacks that jeopardize network communication. The growing use of IoT in essential services underscores the need for robust network integrity. Driven by this urgency, our research has developed a sophisticated detection framework that effectively identifies black hole attacks within IoT … …Journal of Computer Science, Vol. 20, Issue 11 · 18 Oct 2024 · 5,000 accessesView PDFCite
Research ArticleOpen accessIn the abstractCrime Rate Analysis and Mapping from Socio-Economic Data Using Deep Neural NetworksSanthosh Sankara, Nadeson SugithaCrime prediction is the attempt to identify and mitigate future criminal activity. Crime is typically "unpredictable"; it cannot be predicted in advance. Addressing the roots of crime has long been a priority for researchers. Extracting causality from data is difficult if the relevant data aspects are not selected. In this research activity, an innovative classification framework is defined which is … …Journal of Computer Science, Vol. 20, Issue 10 · 17 Aug 2024 · 5,089 accessesView PDFCite
Research ArticleOpen accessIn the abstractLT-LBP-Based Spatial Texture Feature Extraction with Deep Learning for X-Ray ImagesPankaja Lakshmi P., Sivagami M.The novel logarithmic transformation of Local Binary Pattern (LT-LBP) for texture feature extraction is used with Deep Learning (DL) models. The Computational complexity in the DL models asymptotically increases with the data sesssst and the depth of the layers in Convolutional Neural Networks (CNN). Pre-processing the images before training the DL model holds a strong impact on the operation speed … …Journal of Computer Science, Vol. 20, Issue 1 · 18 Dec 2023 · 7,190 accessesView PDFCite
Research ArticleOpen accessIn the abstractAutomated Face Detection, Recognition and Gender Estimation Applied to Person IdentificationMd Hannan, Md Rafiqul Islam, Md Ashraful Haque et al.Face detection, recognition and gender estimation are one of the most significant research areas in computer vision, not only because of the challenging nature of faces as an object but also due to the countless applications that require the application of face detection, tracking and recognition. Although many significant types of research on face detection, recognition and gender estimation problems … …Journal of Computer Science, Vol. 15, Issue 3 · 27 Mar 2019 · 9,492 accessesView PDFCite
Research ArticleOpen accessIn the abstractSymbolic Aggregate approXimation-Local Binary Pattern Feature Descriptor Combination for Automatic Facial Expression RecognitionSumithra M.D., M. Abdul RahimanAutomatic identification of facial expression is a significant research area which is anticipated for real time processing in Human-Computer Interaction domain. Along with an efficient classifier for assigning the class label to each of the input face image, it is very necessary to have a strong feature vector for training the classifier. This paper proposes an effectual combination of Local … …Journal of Computer Science, Vol. 15, Issue 1 · 8 Jan 2019 · 7,513 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 abstractFuzzy Modeling for Multi-Label Text Classification Supported by Classification AlgorithmsBeatriz Wilges, Gustavo Mateus, Silvia Nassar et al.The ever-increasing amount of information on the Web is organized in structured, semi-structured and unstructured data. Text classification systems, capable of handling such different structures, may facilitate the work of important tasks such as indexation and information retrieval in search engines. The objective of this research is to develop a method for the classification of documents into multiple categories with … …Journal of Computer Science, Vol. 12, Issue 7 · 22 Aug 2016 · 7,215 accessesView PDFCite
Research ArticleOpen accessIn the abstractAUTHORSHIP CATEGORIZATION IN EMAIL INVESTIGATIONS USING FISHER’S LINEAR DISCRIMINANT METHOD WITH RADIAL BASIS FUNCTIONA. Pandian, Md. Abdul Karim SadiqEmail plays a vital role in faster communication. Lots of mails are sent to common public with falsified information that appears to be a realistic. It is mandatory to trace the origin of the email and the authors/systems responsible for generating such emails. Representative signatures of email are to be generated using lexical and syntactic based methods. The signature of … …Journal of Computer Science, Vol. 10, Issue 6 · 31 Jan 2014 · 6,686 accessesView PDFCite
Research ArticleOpen accessIn the abstractHALF OF THRESHOLD ALGORITHM: AN ENHANCED LINEAR ADAPTIVE SKIPPING TRAINING ALGORITHM OR MULTILAYER FEEDFORWARD NEURAL NETWORKSManjula Devi Ramasamy, Kuppuswami Subbaraya GounderMultilayer Feed Forward Neural Network (MFNN) has been successfully administered architectures for solving a wide range of supervised pattern recognition tasks. The most problematic task of MFNN is training phase which consumes very long training time on very huge training datasets. An enhanced linear adaptive skipping training algorithm for MFNN called Half of Threshold (HOT) is proposed in this research … …American Journal of Applied Sciences, Vol. 11, Issue 1 · 22 Nov 2013 · 7,016 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