54 results for “memory-based learning”

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Research ArticleOpen accessIn the abstractNasal Administration of Quercetin Liposomes Improves Memory Impairment and Neurodegeneration in Animal Model of Alzheimer's DiseaseTerdthai Tong-un, Supaporn Muchimapura, Jintanaporn Wattanathorn, Wathita PhachonpaiProblem statement: At present, the development of protective strategy against Alzheimer’s Disease (AD) is increasing its importance due to the high prevalence of AD, a limitation of therapeutic efficacy and its high impacts on economic and social aspects. The development of the preventive and therapeutic strategy to protect against the path physiology induced by free radicals in AD from antioxidant … …American Journal of Agricultural and Biological Sciences, Vol. 5, Issue 3 · 30 Sep 2010 · 7,743 accessesView PDF Cite

Research ArticleOpen accessIn the abstractGenetic Algorithm Based Probabilistic Motif Discovery in Unaligned Biological SequencesM. Hemalatha, K. VivekanandanFinding motif in biosequences is the most important primitive operation in computational biology. There are many computational requirements for a motif discovery algorithm such as computer memory space requirement and computational complexity. To overcome the complexity of motif discovery, we propose an alternative solution integrating genetic algorithm and Fuzzy Art machine learning approaches for eliminating multiple sequence alignment process. Problem … …Journal of Computer Science, Vol. 4, Issue 8 · 31 Aug 2008 · 6,729 accessesView PDF Cite

Research ArticleOpen accessIn the abstractA Backpropagation Neural Network for Computer Network SecurityKhalil ShihabIn this paper, an efficient and scalable technique for computer network security is presented. On one hand, the decryption scheme and the public key creation used in this work are based on a multi-layer neural network that is trained by backpropagation learning algorithm. On the other hand, the encryption scheme and the private key creation process are based on Boolean … …Journal of Computer Science, Vol. 2, Issue 9 · 30 Sep 2006 · 19,535 accessesView PDF Cite

Research ArticleOpen accessIn the abstractDigital Hardware Implementation of a Neural System Used for Nonlinear Adaptive PredictionHassène Faiedh, Chokri Souani, Kholdoun Torki, Kamel BesbesNeural networks have been widely used for many applications in digital communications. They are able to give solutions to complex problems due to their nonlinear processing and their learning and generalization. Neural networks are one of the key technologies for the communication domain and accordingly a special effort may be expected to be paid to real time hardware implementation issues. … …Journal of Computer Science, Vol. 2, Issue 4 · 30 Apr 2006 · 6,763 accessesView PDF Cite

Research ArticleOpen accessIn the abstractEvolving Fuzzy Neural Network for Phishing Emails DetectionAmmar ALmomani, Tat-Chee Wan, Altyeb Altaher et al.One of the broadly used internet attacks to deceive customers financially in banks and agencies is unknown “zero-day” phishing Emails “zero-day” phishing Emails is a new phishing email that it has not been trained on old dataset, not included in black list. Accordingly, the current paper seeks to Detection and Prediction of unknown “zero-day” phishing Emails by provide a new … …Journal of Computer Science, Vol. 8, Issue 7 · 4 Jun 2012 · 8,005 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordDual-Branch Shape Texture Learning With Pyramid Residual and Sobel Edge Layers for Rice Variety ClassificationM Pradeep, M SiddappaAutomated rice variety classification categorizes rice types based on features, such as grain texture, shape, color, and size. Traditional handcrafted feature-based models fail at rice classification due to lighting variations, background noise, and environmental conditions, leading to overlapping visual characteristics and frequent misclassification. To address these challenges, this research proposes a novel Dual-Branch Convolutional Neural Network with Pyramid Residual Units … …Journal of Computer Science, Vol. 22, Issue 9 · 24 Sep 2026 · 627 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordA Hybrid Grey Wolf Optimizer and Deep Transfer Learning-Based Intrusion Detection System for IoTKapil Shrivastava, Manish Tiwari, Prasun ChakrabartiThe rapid proliferation of Internet of Things (IoT) devices has driven significant advancements in connectivity and automation, but it has also introduced substantial cybersecurity risks, including intrusions and cyberattacks. To address these challenges, this study proposes a hybrid intrusion detection framework that combines advanced optimization techniques with ensemble deep learning to enhance detection accuracy and computational efficiency. The proposed framework … …Journal of Computer Science, Vol. 22, Issue 2 · 17 Feb 2026 · 1,506 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordEnhancing Dam Safety and Management: Long Short-Term Memory Based Predictive Models for Accurate Alert ForecastingNisha C. M, N. ThangarasuDam management and early alert systems are critical for effective water resource management. Accurate prediction of dam alert signals facilitates proactive decision-making, thereby aiding in the effective management and reduction of potential risks linked to dam operations. Within this research, Long Short-Term Memory (LSTM) networks are utilized to forecast dam alert signals issued from the dam by leveraging daily parameters, … …Journal of Computer Science, Vol. 22, Issue 1 · 6 Feb 2026 · 1,626 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordDeep Learning-Based Spectrum Sensing in Cognitive Radio Networks using Stacked LSTM: Performance Analysis of SNR and BERKavitha Veerappan, Seetharaman GopalakrishnanRapid evolution of wireless communication technologies and emergence of 5G networks have addressed lack of spectrum resources, highlighting the need for innovative topologies to improve the spectrum utilization. Due to this reason, Cognitive Radio (CR) has evolved as an optimized solution to overcome these difficulties by allowing dynamic spectrum access, thereby reducing the under-usage of available spectrum. Considering this, precise … …Journal of Computer Science, Vol. 21, Issue 11 · 19 Dec 2025 · 2,219 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordAspect 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 PDF Cite