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Research ArticleOpen accessIn the abstractConvolution Neural Networks of Dynamically Sized Filters with Modified Stochastic Gradient Descent Optimizer for Sound ClassificationManu Pratap Singh, Pratibha RashmiDeep Neural Networks (DNNs), specifically Convolution Neural Networks (CNNs) are found well suited to address the problem of sound classification due to their ability to capture the pattern of time and frequency domain. Mostly the convolutional neural networks are trained and tested with time-frequency patches of sound samples in the form of 2D pattern vectors. Generally, existing pre-trained convolutional neural … …Journal of Computer Science, Vol. 20, Issue 1 · 13 Dec 2023 · 5,781 accessesView PDFCite
Research ArticleOpen accessIn the abstractBlockchain Integrated Distributed Threshold Elliptic Curve Cryptography Framework for Scalable and Secure Cloud Data StorageNaga Swetha Dhulipudi, Balaji SavadamThe development of cloud computing offers scalable processing capabilities, thereby enabling organizations to store and process sensitive data in the cloud. However, it faces crucial security challenges, as existing cryptographic and blockchain systems suffer from poor scalability and centralized key management, which creates a single point of failure and introduces vulnerabilities to both quantum and classical attacks. This research proposes … …Journal of Computer Science, Vol. 22, Issue 11 · 19 Oct 2026 · 395 accessesView PDFCite
Research ArticleOpen accessIn the abstractStudent Course Recommendation System Using Semantic Aware Temporal Gating With Time TransformerJoshi Vinay Kumar, Dahlia Sam, N. KanyaCourse recommendation system works by analyzing users’ interests and recognizes their historical behavior such as course enrollment and previously watched videos to recommend relevant courses. However, the existing course recommendation systems in Massive Open Online Courses (MOOCs) face challenges in capturing complex semantic information, which impacts student requirements with an unsatisfied recommendation. By combining historical behaviors without temporal awareness, the … …Journal of Computer Science, Vol. 22, Issue 11 · 9 Oct 2026 · 580 accessesView PDFCite
Research ArticleOpen accessIn the abstractAlternative Monitoring Approach for IPTVAngel Ignatov, Hristo Toshkov Hristov, Jan Latal et al.IPTV emerged in the late 1990s as a solution for delivering Video on Demand (VoD) and live television over managed networks. Its widespread adoption accelerated after the expansion of broadband internet and the introduction of web technologies such as HTML5 and adaptive streaming protocols (MPEG-DASH and HLS), which enabled television content to be streamed directly through web browsers. Across Europe, … …Journal of Computer Science, Vol. 22, Issue 11 · 8 Oct 2026 · 430 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
Research ArticleOpen accessIn the abstractReal-Time Monitoring and Injury Risk Warning Algorithm Based on Data Fusion of Motor Muscle ContractionGuomin Wang, Jingying HuangThe existing sports injury warning algorithms are difficult to achieve dynamic injury risk modeling based on individual muscle characteristics while ensuring real-time fusion efficiency of multimodal signals. This article proposes a real-time muscle contraction state perception and injury risk warning algorithm based on adaptive weighted feature fusion and lightweight temporal modeling. The system synchronously collected surface electromyography (sEMG), Inertial Measurement … …American Journal of Biochemistry and Biotechnology, Vol. 22, Issue 3 · 10 Aug 2026 · 1,089 accessesView PDFCite
Research ArticleOpen accessIn the abstractEpileptic Seizure Detection from EEG Signal Using Progressive Channel Selection and Deep LearningSuraiya Akter Mumu, Shupta Das, M. A. H. Akhand et al.Epileptic Seizures (ES), marked by abrupt abnormal electrical discharges in the brain, represent the primary symptom of epilepsy, making timely and accurate detection critical because of their unpredictable recurrence and potentially severe consequences. The Electroencephalogram (EEG), a widely used, non-invasive, and economical method for monitoring brain activity, plays a key role in automated ES detection through Machine Learning (ML) and … …Journal of Computer Science, Vol. 22, Issue 6 · 8 Jul 2026 · 1,393 accessesView PDFCite
Research ArticleOpen accessIn the abstractDesigning the Future: A Blockchain-Based Framework for Transparent and Secure ElectionsJayesh Solanki, Divyakant MevaBlockchain-based electronic voting systems have been identified as a solution to enhance the transparency, security, and efficiency of modern electoral processes. However, the existing system has three major problems, which include scalability, privacy issues, and cybersecurity attacks. The researcher proposed an innovative solution to develop an electronic voting system with enhanced security, scalability, and transparency of voters' information. This paper … …Journal of Computer Science, Vol. 22, Issue 6 · 16 Jun 2026 · 1,291 accessesView PDFCite
Research ArticleOpen accessIn the abstractTowards an Explainable Approach: Hybrid Residual Network and SVM for Automated Brain Tumor Detection and ClassificationKamini Lamba, Shalli RaniThe abnormal growth of brain cells leads to tumor formation, which can be fatal if not detected and treated promptly. Given the complexity of brain tumors, early detection is critical in healthcare. Traditional radiology-based tumor detection is prone to human error and delays. Hence, a computer- assisted method is needed for accurate and efficient diagnosis. With the rapid advancements in … …Journal of Computer Science, Vol. 22, Issue 1 · 11 Feb 2026 · 1,427 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Facial Expression Recognition Accuracy Through Haar Cascade-Based Feature ExtractionThambusamy Velmurugan, Lakshminarayanan MeenaFacial Expression Recognition (FER) has a significant interest because of its increased applications in Human-Computer Interaction (HCI), like video interactions, emotion analysis, image indexing, and retrieval and many more. In the discipline of computer vision, pattern recognition, and artificial intelligence FER has become an extremely active research topic. A crucial component of FER systems is feature extraction, which involves identifying … …Journal of Computer Science, Vol. 21, Issue 12 · 21 Jan 2026 · 1,656 accessesView PDFCite