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119 articles for “data memory”
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Research ArticleOpen accessEvery word in the titleVolatility-Aware Hybrid Memory Architecture for Real-Time and Persistent Big Data SystemsMohammed Elhabib Maicha, Mohammed Redha BouzidiAs data volumes and real-time analytics demands grow, DRAM only memory systems struggle to scale cost-efficiently and sustainably. We present VA-HMA, a volatility-aware hybrid memory architecture that combines DRAM and Non-Volatile Memory (NVM) with a lightweight, machine-learned placement layer and endurance-aware fault tolerance. VA-HMA continuously monitors access patterns and applies a Random Forest–based predictor to guide batched page migrations and … …Journal of Computer Science, Vol. 22, Issue 6 · 27 Jun 2026 · 1,214 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Hybrid Model of Bidirectional Long-Short Term Memory and CNN for Multivariate Time Series Classification of Remote Sensing DataSawsan Morkos GharghoryClassification of multivariate time series has got massive attention in the last decade. The traditional modeling classifiers are complicated patterns and are incompetent to capture the dependencies of multivariate time series data. To include both of the effective features and the embedded relationships in the multivariate time series, a new hybrid model which incorporates both Convolutional Neural Network (CNN) and … …Journal of Computer Science, Vol. 17, Issue 9 · 29 Sep 2021 · 6,686 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleModified ACS Centroid Memory for Data ClusteringAyad Mohammed Jabbar, Ku Ruhana Ku-Mahamud, Rafid SagbanAnt Colony Optimization (ACO) is a generic algorithm, which has been widely used in different application domains due to its simplicity and adaptiveness to different optimization problems. The key component that governs the search process in this algorithm is the management of its memory model. In contrast to other algorithms, ACO explicitly utilizes an adaptive memory, which is important to … …Journal of Computer Science, Vol. 15, Issue 10 · 11 Oct 2019 · 7,641 accessesView PDFCite
Research ArticleOpen accessIn the keywordsEmploying Hybrid Serial Cascaded Adaptive Network for Anomaly Detection and Prevention in IoT Time Series Data With Optimal Interdomain RoutingKante Satyanarayana, K. VenkateshNowadays, emerging Internet of Things (IoT) in data processing becomes interested research topic and is used for various applications. This varies from big data processing and analytics for accumulating entire sensor data to detect and generate long-term trends. Nevertheless, this results in the requirement for resources like the execution of power, memory, and bandwidth, in which resource-constrained IoT tools suffers … …Journal of Computer Science, Vol. 22, Issue 1 · 21 Feb 2026 · 1,466 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Note towards Reshaping Java's FeaturesN. S. Kutti, Z. A. Al-Khanjari, H. A. Ramadhan, J. FiaidhiProgramming Languages continually go through the refinement process due to several findings such as lack of robustness, lack of flexibility, lack of simplicity and lack of standard. This may require pruning undesirable features, sometimes softening of hard nature of some features and adding new features to improve the scope of the languages. Recently Java has emerged as a refined language … …Journal of Computer Science, Vol. 1, Issue 4 · 30 Dec 2005 · 6,496 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Study of the Production Rules for Context Inference of Wetland Water Quality on Ubiquitous Sensor Network Middleware FrameworkSo-Young Im, Ryum-Duck OhProblem statement: With gradually increasing movement to live together with nature, artificial wetlands are increasing as well. And the wind of change blows at the rivers and streams, thereby increasing the need for management systems. Conclusion/Recommendations: Accordingly, this study aims to design production rules for wetland environment context inference and establish application system by using JESS and the rule-based system … …Journal of Computer Science, Vol. 8, Issue 3 · 13 Jan 2012 · 6,851 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
Review ArticleOpen accessIn the abstractHuman Activity Recognition at the Edge: A Systematic Review of Machine Learning Models, Deployment Constraints, and Latency Energy Accuracy Trade offsJose Antonio Rojas Guillén, Wini Ebelin Quispe Bautista, Arturo Gamarra MorenoHuman Activity Recognition (HAR) has become a key component of intelligent healthcare monitoring, assisted living, sports analytics, smart environments, and wearable computing. However, the migration of HAR models from cloud-centered architectures to edge, embedded, mobile, and wearable platforms introduces constraints related to computational capacity, memory footprint, battery consumption, inference time, and real-time responsiveness. This study presents a systematic literature review … …Journal of Computer Science, Vol. 22, Issue 8 · 7 Sep 2026 · 593 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Intelligent Hybrid Machine Learning Model for Paddy Disease DetectionS. Hrushikesava Raju, S. Adinarayna, U. Sesadri et al.Most countries rely on paddy/rice as a preferred staple crop due to its desirable agronomic characteristics. However, during the growth cycle, undetected or delayed identification of diseases can significantly reduce crop yield. To address this, machine learning approaches are increasingly employed for early-stage disease detection. Traditional Recurrent Neural Networks (RNNs), while useful for sequential data, suffer from limitations such as … …Journal of Computer Science, Vol. 22, Issue 4 · 29 Apr 2026 · 1,747 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimized WFST-Based ASR for Arabic: Balancing Memory, Speed, and AccuracyWael A. Sultan, Mourad S. Semary, Sherif M. AbdouWeighted Finite-State Transducers (WFSTs) have revolutionized Automatic Speech Recognition (ASR) by enabling significantly faster decoding speeds compared to traditional systems that build the search space progressively. However, applying WFSTs to morphology-rich languages such as Arabic presents challenges due to the large vocabulary, resulting in extensive networks that exceed the memory capacity of standard CPUs. This study introduces various strategies to … …Journal of Computer Science, Vol. 22, Issue 2 · 23 Feb 2026 · 1,442 accessesView PDFCite