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276 results for “proposed mechanism”
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Research ArticleOpen accessIn the keywordsAn Effective Queue Management Scheme for Data CommunicationSheela Thavasi, Nityanandam NatarajanProblem statement: The growth in the needs of Internet applications that transmit massive amount of data has led to the emergence of Effective Queue Management. Approach: Queues were used to smooth spikes in incoming packet rates and to allow the router sufficient time for packet processing. When the waiting time is less a better queue management is ensured thereby resulting … …Journal of Computer Science, Vol. 7, Issue 3 · 7 Mar 2011 · 7,762 accessesView PDFCite
Review ArticleOpen accessIn the keywordsPotential Effects of Adropin in Subarachnoid HemorrhageZahra Hasanpour Segherlou, Mohammad Reza Hosseini Siyanaki, Brandon Lucke-WoldSubarachnoid Hemorrhage (SAH) typically, occurs in patients over 55 years of age and can cause a significant loss of productivity. SAH also has a high mortality rate and those who survive often suffer from early and secondary brain injuries that can result from the condition. By gaining a better understanding of the pathophysiology of SAH, it may be possible to … …Neuroscience International, Vol. 13, Issue 1 · 21 Jul 2023 · 9,246 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid BiGRU-BiLSTM Model for Real-Time ECG Arrhythmia Detection Using Wearable SensorsPrem Narayan Singh, Rajendra Prasad MahapatraAccurate and real-time detection of cardiac arrhythmias is essential for timely medical intervention. Advances in wearable devices and deep learning have made it feasible to continuously monitor electrocardiogram (ECG) signals, facilitating early identification of abnormal heart rhythms. For arrhythmia detection, this study presents a hybrid deep learning architecture combining Bidirectional Gated Recurrent Units (Bi-GRU) and Bidirectional Long Short-Term Memory (Bi-LSTM). … …Journal of Computer Science, Vol. 22, Issue 5 · 5 Jun 2026 · 1,336 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Occlusion Aware Facial Expression Recognition Model Using Fitness Based Cheetah Optimizer and Adaptive Multi-Scale ViT-CNN With Attention MechanismA. Reddy Prasad, A. RajeshAs a highly nuanced aspect of human communication, facial expression recognition presents a computationally complex problem, making it a prominent area of research in computer vision and affective computing. Problems like poor image quality, occlusions, inconsistent illumination, and head attitude changes are frequently observed in images taken from unstructured sources such as the internet that affect the accuracy of facial … …Journal of Computer Science, Vol. 21, Issue 12 · 29 Jan 2026 · 1,969 accessesView PDFCite
Research ArticleOpen accessIn the abstractDehazing Mechanism Using Auto-Encoder with Intensity Attention SystemRajat Tiwari, Bhawna Goyal, Ayush DograIn the modern world, images play a significant medium for communication. Primarily, it is easily transferred and disseminated across various platforms which allows the people to express their ideology and perceptions. Conversely, images can be prone the environmental conditions as the image quality can be affected by the weather circumstances. Particularly, haze images minimize the whole clarity and visibility of … …Journal of Computer Science, Vol. 20, Issue 12 · 25 Nov 2024 · 4,523 accessesView PDFCite
Research ArticleOpen accessIn the abstractClassification Model of Traditional Chinese Medicine Prescription Decocting Duration Combining Text Convolutional Neural Network with Attention MechanismZhibiao Li et al.The decocting time of Traditional Chinese Medicine (TCM) formulas is crucial for therapeutic effects. To better capture the important characteristics related to the decocting time of TCM formulas, a formula decocting time classification model TextCNN-attention that integrates the attention mechanism and Text Convolutional Neural Network is proposed. This model predicts the decocting time of formulas and divides them into long-term, … …American Journal of Biochemistry and Biotechnology, Vol. 20, Issue 4 · 26 Sep 2024 · 4,372 accessesView PDFCite
Research ArticleOpen accessIn the abstractPrivacy-Preserving Deep Federated Learning on the Edge Using Homomorphic Encryption and Secure Multiparty ComputationNoman Aasif Gudur, Mohamed El-Dosuky, Sherif KamelThe increasing volume of consumer data necessitates reliable edge devices for personalized user experiences. Federated Learning (FL) offers a state-of-the-art approach to decentralized machine learning by leveraging data distributed across multiple client devices. However, user data privacy remains vulnerable to corruption through feature heterogeneity and malicious attacks. While several privacy-preserving techniques have been previously implemented, they suffer from implementation constraints … …Journal of Computer Science, Vol. 21, Issue 11 · 21 Dec 2025 · 4,392 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Regularization Mechanism for Combating Class Imbalance Problem in Intrusion Detection System for Defending DDoS Attack in SDNNarender M, Yuvaraju B NIntegration of deep learning into Intrusion Detection Systems (IDS) for Software Defined Networking (SDN) is an emerging field of research. Most of the datasets used to build IDS are highly imbalanced, especially in the case of DDoS attacks, which account for a larger percentage of malicious samples than normal traffic. As a result of a class imbalance, the classification result … …Journal of Computer Science, Vol. 19, Issue 3 · 24 Feb 2023 · 5,668 accessesView PDFCite
Research ArticleOpen accessIn the abstractEW-GAT: Edge-Weighted Graph Attention Framework for Patient-Aware Heart Disease Classification Using Feature-to-Feature Similarity GraphsRamakrishna Reddy Badveli, Nijaguna Gollara Siddappa, Sundeep Kumar KanipakapatnamHeart disease remains an important cause of global death, requiring accurate and clinically interpretable prediction models. However, traditional Machine Learning (ML) methods often fail to capture meaningful dependencies among clinical features and lack robustness across diverse patient populations. To overcome these issues, this research introduces an Edge-Weighted Graph Attention Network (EW-GAT) for patient-aware heart disease classification. The approach first models … …Journal of Computer Science, Vol. 22, Issue 7 · 25 Jul 2026 · 920 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Learning Synergy: CNNs and Transformers for Epidemic Outbreak ForecastingAlexander R., Shakthi Priya V., Sumathi G. et al.An Accurate prediction of outbreaks is extremely crucial for taking proactive public health interventions, distributing limited resources, and controlling a disease. This paper assesses and also compares the performances of the available deep learning models, namely, Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM) networks, and Bidirectional Long Short-Term Memory (BiLSTM) networks, in predicting. CNNs are best for feature extraction … …Journal of Computer Science, Vol. 21, Issue 12 · 23 Jan 2026 · 2,120 accessesView PDFCite