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20 results for “Streaming Data”
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Research ArticleOpen accessPhrase in the titleAnomaly Detection Algorithms for Streaming Data: Performance ComparisonZirije HasaniToday’s most of the data are streaming time-series data, where is very important anomaly detection over this data because gives significant information of possible critical situations. Detecting anomalies in big streaming data is yet difficult task because we have to process them in real time, even before they are stored and instantly alarm on potential threats. For real time streaming … …Journal of Computer Science, Vol. 16, Issue 7 · 18 Jul 2020 · 7,288 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleTowards a Generic Multimodal Architecture for Batch and Streaming Big Data IntegrationSiham Yousfi, Maryem Rhanoui, Dalila ChiadmiBig Data are rapidly produced from various heterogeneous data sources. They are of different types (text, image, video or audio) and have different levels of reliability and completeness. One of the most interesting architectures that deal with the large amount of emerging data at high velocity is called the lambda architecture. In fact, it combines two different processing layers namely … …Journal of Computer Science, Vol. 15, Issue 1 · 31 Jan 2019 · 7,646 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleIMPLEMENTATION OF CENTRAL QUEUE BASED REALTIME SCHEDULER FOR MULTIPLE SOURCE DATA STREAMINGV. Kaviha, V. Kannan, S. RaviReal-time data packet sources are required to remain robust against different security threats. This study proposes a real-time secure scheduling strategy for data transmission to enhance the communication throughput and reduce the overheads. The proposed system combines real-time scheduling with security service enhancement, error detection and realtime scheduler based on EDF algorithm using uc/os-II real time operating system, implemented on … …Journal of Computer Science, Vol. 10, Issue 9 · 22 Apr 2014 · 6,381 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAdaptive Synthetic Oversampling Algorithm for Handling Class Imbalance in Multi-Class Data Stream ClassificationPriya S., Annie UthraConcept drift and class imbalanced data are major challenging processes involved in modern streaming data classification. Particularly, when integrated with difficult factors like the existence of noise, overlapping class distribution, concept drift, and data imbalance can considerably affect the classifier results. In addition, various challenges affect the performance of the existing oversampling schemes such as SMOTE and its derivatives. Regardless … …Journal of Computer Science, Vol. 18, Issue 7 · 26 Jul 2022 · 5,809 accessesView PDFCite
Research ArticleOpen accessIn the keywordsData Streams Curation for Better Machine Learning Functionality and Result to Serve IoT and other Applications: A SurveyHaya Salah, Islam Al-Omari, Jaber Alwidian et al.Data Curation on data streams is effective in operating and reducing costs of BIG DATA analytic. Basically, analytic preparation requires data curation of available heterogeneous data sets available in big data clusters and such analytic process becomes harder when it comes to the concept of conducting the curation process on Data-on-Motion, in order to come at actionable insights and valuable … …Journal of Computer Science, Vol. 15, Issue 10 · 1 Nov 2019 · 8,722 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 abstractOptimized Movie Recommendation Using Hybrid Jaccard-Based K-Means Clustering Using Apache SparkShiba Prasad Dash, Rajesh Kumar Sahoo, Ram Chandra Barik et al.The need for recommendations specific to each person's interests is growing every day, making recommendation systems increasingly important in people's lives. Researchers have paid close attention to the rapid expansion of e-commerce businesses and online video streaming services like Hotstar, YouTube, and Netflix. The collaborative filtering-based RS system aims to suggest such films or videos to users based on their … …Journal of Computer Science, Vol. 22, Issue 9 · 23 Sep 2026 · 602 accessesView PDFCite
Research ArticleOpen accessIn the abstractVolatility-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
Review ArticleOpen accessIn the abstractBibliometric Analysis of Missing Value Imputation (MVI) Research Using Python and VOSviewer: Trends and Future DirectionsSamsul Arifin, Muhammad Faisal, Edwin Kristianto Sijabat et al.Incomplete data is a pervasive issue in data science, posing significant challenges for statistical analysis and machine learning applications. Missing Value Imputation (MVI) has thus emerged as a critical area of research aimed at mitigating data quality issues and improving decision-making accuracy. This study presents a comprehensive bibliometric analysis of MVI research using Scopus-indexed publications from 2000 to 2024. The … …Journal of Computer Science, Vol. 21, Issue 12 · 20 Jan 2026 · 1,961 accessesView PDFCite
Research ArticleOpen accessIn the abstractOnline ML Streaming-Based Leading Ensemble Classifier for Intrusion Detection in IoTNeeraj Sharma, Neelu NihalaniIn the present decade, preventing IoT networks from malicious attacks and to ensure the privacy and integrity of data by strengthening their cybersecurity perspective is a critical concern. Traditional methods alone are not sufficient to detect multiple attacks. IDS-based system plays a crucial role to maintain security due to continuous expanding nature of IoT networks. Traditional methods alone are often … …Journal of Computer Science, Vol. 21, Issue 10 · 16 Dec 2025 · 2,078 accessesView PDFCite