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77 articles for “Long Memory”
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Research ArticleOpen accessIn the keywordsMachine Learning and Deep Learning for Phishing Email Classification using One-Hot EncodingSikha Bagui, Debarghya Nandi, Subhash Bagui, Robert Jamie WhiteRepresentation of text is a significant task in Natural Language Processing (NLP) and in recent years Deep Learning (DL) and Machine Learning (ML) have been widely used in various NLP tasks like topic classification, sentiment analysis and language translation. Until very recently, little work has been devoted to semantic analysis in phishing detection or phishing email detection. The novelty of … …Journal of Computer Science, Vol. 17, Issue 7 · 23 Jul 2021 · 10,936 accessesView PDFCite
Research ArticleOpen accessIn the keywordsPerformance Evaluation of Deep Learning Networks on Printed Odia CharactersSanjibani Sudha Pattanayak, Sateesh Kumar Pradhan, Ramesh Chandra MalikDeep machine learning includes a series of layers to mimic the working of the human brain for taking a decision. Deep learning networks have shown good results in character recognition in the past. This paper evaluates the performance of different deep learning networks like Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM) based recurrent neural network and Convolutional LSTM on … …Journal of Computer Science, Vol. 16, Issue 7 · 25 Jul 2020 · 6,785 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAnamnestic Immune Response Eight Years After Immunization of Primates with a Multivalent HIV-1 GP120 Variable Peptide VaccineRebecca Rivera, Kyung Hee Kang, David E. Anderson et al.Successful development of an effective HIV vaccine hasn’t occurred yet partly as a consequence of the antigenic variation deployed by HIV-1 to escape the immune system. Our laboratory is dedicated to develop a single peptide synthesis approach to create multivalent peptides representing hypervariable epitopes of the gp120 envelope glycoprotein of HIV-1. Our previous study showed that our HIV HECs are … …American Journal of Immunology, Vol. 9, Issue 1 · 13 Mar 2013 · 7,209 accessesView PDFCite
Research ArticleOpen accessIn the keywordsBiomedicine and Informatics Model of Alzheimer's DiseaseKang Cheng, Chang-Hua ZouIn a perspective of biomedicine and informatics, the mechanism of Alzheimer's, senile amnesia, or other aging-associated and cognitive impairment related diseases involve four important informative processing procedures: propagation, consolidation, retrieval and cognition, In this study, we systematically model the four procedures based on published experimental data. When modeling the propagation, we develop an equivalent circuit of biological membrane to describe … …American Journal of Biochemistry and Biotechnology, Vol. 3, Issue 3 · 28 May 2007 · 6,824 accessesView PDFCite
Research ArticleOpen accessIn the keywordsNelson and Plosser Revisited: Evidence from Fractional ARIMA ModelsGuglielmo Maria Caporale, Luis A. Gil-AlanaIn this study fractionally integrated ARIMA (ARFIMA) models are estimated using an extended version of Nelson and Plosser[1]’s data set. The analysis employs[11]’s maximum likelihood procedure. Such a parametric approach requires the model to be correctly specified in order for the estimates to be consistent. A model-selection procedure based on diagnostic tests on the residuals, together with several likelihood criteria, … …American Journal of Applied Sciences, Vol. 2, Issue 4 · 30 Apr 2005 · 6,715 accessesView PDFCite
Research ArticleOpen accessIn the keywordsStrong Dependence at the Long Run and the Cyclical Frequencies in the Specification of the US Unemployment RateL. A. Gil-AlanaThis study deals with the presence of long range dependence at the long run and the cyclical frequencies in the specification of the US unemployment rate. We use a parametric procedure that permits us to test unit and fractional roots in raw time series. The results show that both the long run and the cyclical structures present a component of … …American Journal of Applied Sciences, Vol. 2, Issue 2 · 28 Feb 2005 · 6,501 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAutomated Medical Image Captioning with Soft Attention-Based LSTM Model Utilizing YOLOv4 AlgorithmPaspula Ravinder, Saravanan SrinivasanThe medical image captioning field is one of theprominent fields nowadays. The interpretation and captioning of medical imagescan be a time-consuming and costly process, often requiring expert support. Thegrowing volume of medical images makes it challenging for radiologists tohandle their workload alone. However, addressing the issues of high cost andtime can be achieved by automating the process of medical image … …Journal of Computer Science, Vol. 20, Issue 1 · 16 Dec 2023 · 6,651 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAspect Category Detection Using Bi-LSTM-Based Deep Learning for Sentiment Analysis for HindiAshwani Gupta, Utpal SharmaIn the field of sentiment analysis, the notion of aspect category identification lays emphasis on identifying the aspect categories in a specific review phrase. The purpose of this research is to propose a novel approach to the identification of aspect categories in reviews that are published in Hindi. The training and evaluation of a supervised model that is based on … …Journal of Computer Science, Vol. 20, Issue 11 · 18 Sep 2024 · 4,606 accessesView PDFCite
Research ArticleOpen accessIn the keywordsForecasting of Multistep Multivariate Financial Data Through GSO Algorithm Infused Vanilla LSTM ModelNikhitha Pai, Ilango Velchamy, Nithya B RameshPredicting time series in the financial domain requires using models that can do sequence processing tasks. One such model is the LSTM model which belongs to the family of deep learning networks. The performance measure of LSTM in a regression task is to bring down the error in the predicted values. In this study, a novel fused LSTM model integrating … …Journal of Computer Science, Vol. 19, Issue 7 · 10 Jul 2023 · 6,074 accessesView PDFCite
Research ArticleOpen accessIn the abstractHMA-RAG: A Hierarchical Memory Augmented Retrieval Augmented Generation Framework for Fake News DetectionAfnan Altarjami, Sawsan AlshattnawiExisting methods for detecting fake news, such as traditional machine learning and transformer-based models, often work as separate classifiers that do not use outside evidence, historical knowledge, or ways to make the results easier to understand. This paper presents a framework that combines retrieval augmentation and hierarchical memory to overcome three primary constraints: Insufficient external evidence, the absence of memory, … …Journal of Computer Science, Vol. 22, Issue 9 · 7 Sep 2026 · 735 accessesView PDFCite