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174 results for “task performance”
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Research ArticleOpen accessIn the abstractA Lightweight PyBullet-Based Framework for Fast Reinforcement Learning Prototyping on 6-DOF Robotic ArmsNgoc Kim Khanh Nguyen, Anh Thu Mang, Quang NguyenControlling 6-Degree-of-Freedom (6-DOF) robotic arms for precise manipulation tasks is challenging due to kinematic redundancy and the complexity of existing simulation environments like MuJoCo or ROS-Gazebo. This paper presents ArmReach6DOFEnv, a lightweight, open-source simulation framework built on PyBullet for rapid Reinforcement Learning (RL) prototyping on 6-DOF robotic arms. Using a Universal Robot Description Format (URDF) model, the environment supports a … …Journal of Mechatronics and Robotics, Vol. 9, Issue 1 · 11 Feb 2026 · 3,071 accessesView PDFCite
Research ArticleOpen accessIn the abstractDiscrete to Continuous Algorithm for Optimal Channel Selection to Detect Alcoholism through EEG RecordingsHayat Sedrati, Wajih Rhalem et al.Alcoholism is a serious public health issue, and early diagnosis of this brain disease can be performed by analyzing Electroencephalogram (EEG) signals. However, the high dimensionality of EEG datasets requires significant computational time and resources for the automatic processing of EEG signals. This study proposes a novel method to reduce EEG dataset dimensionality using a Discrete to Continuous algorithm (DtC) … …Journal of Computer Science, Vol. 19, Issue 1 · 17 Jan 2023 · 5,904 accessesView PDFCite
EditorialOpen accessIn the abstractVolume 2: and SGAMR Goes!Chiara Bedon, Mario D’Aniello, Flavio StochinoThe year 2018 starts with a great confirmation for SGAMR! The journal has been selected to host the extended version of some selected papers presented during the 6th International Workshop on Design in Civil and Environmental Engineering (DCEE2017), held at the University of Cagliari (Italy) during November 2017. A summary of selected papers from highly ranked, international scientists can be … …International Journal of Structural Glass and Advanced Materials Research, Vol. 4, Issue 1 · 28 Aug 2020 · 5,737 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnomaly 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 accessIn the abstractFeasibility Analysis of Non-Preemptive Periodic Systems from Infeasibility PerspectiveNasro Min-AllahDue to simple implementation, non-preemptive scheduling has the advantage over preemptive counterpart when it comes to deployment of real-time systems. Accordingly, many feasibility techniques have been established to answer schedulability of the task set for non-preemptive case. The time complexity of exact condition for non-preemptive under dynamic priority assignment is of pseud-polynomial nature. Recently, efforts are made to decrease the … …Journal of Computer Science, Vol. 15, Issue 9 · 9 Sep 2019 · 7,617 accessesView PDFCite
Research ArticleOpen accessIn the abstractEfficient Music Auto-Tagging with Convolutional Neural NetworksShaleen Bengani, S. Vadivel, J. Angel Arul JothiTechnology is revolutionizing the way in which music is distributed and consumed. As a result, millions of songs are instantly available to millions of people, on the Internet. This has created the need for novel music search and discovery services. Music is often searched using descriptive keywords, or tags, based on the content of the song. Hence, one very important … …Journal of Computer Science, Vol. 15, Issue 8 · 27 Aug 2019 · 7,841 accessesView PDFCite
Research ArticleOpen accessIn the abstractReal Time Anomaly Detection in Massive Data Streams with ELK StackJakup Fondaj, Zirije HasaniReal time anomaly detection is very popular topic nowadays this because the number of data generated every day is larger and larger. Facing with the phenomena of Big Data is not an easy task. The main aim of this research is to fine appropriate architecture for real-time big data analytic and its main task is to detect anomalies in this … …Journal of Computer Science, Vol. 15, Issue 6 · 17 Jun 2019 · 7,794 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Great Deluge Algorithm with Bi-Decay Rate for Efficient Task Scheduling in Grid ComputingKaiLun Eng, Abdullah Muhammed, Sazlinah Hasan, Mohamad Afendee MohamedTo realise the utmost idea of global collaborative resource sharing with Grid computing, the fundamental scheduling process is playing a critical role. However, scheduling in Grid computing environment is a well-known NP-complete problem. In this study, we propose a new extension of Great Deluge algorithm with an effective diversification strategy for the Grid scheduling problem. The proposed approach, namely BiGD, … …Journal of Computer Science, Vol. 15, Issue 3 · 7 Mar 2019 · 7,720 accessesView PDFCite
Research ArticleOpen accessIn the abstractUsability Assessment of E-Commerce Systems Using McCall’s Quality ModelSiti Solehah Othman, A Noraziah, Roslina Mohd SidekE-commerce platforms rely fundamentally on business database transaction systems that must balance user experience with security and data integrity. Traditional usability assessment methodologies often overlook critical security elements and transactional integrity requirements. This study employs McCall's Quality Model to comprehensively evaluate the usability characteristics of three prominent e-commerce platforms: Temu, Shopee, and Lazada. Through structured task-based evaluations and Likert-scale questionnaires, … …Journal of Computer Science, Vol. 21, Issue 11 · 19 Dec 2025 · 2,541 accessesView PDFCite
Research ArticleOpen accessIn the abstractSentiment Analysis Using Light Weight - Gradient Boosting Machine based Feature SelectionBikku Ramavath, Srikanth Kadainti, Nemani SubashSentiment analysis is a significant task in Natural Language Processing (NLP) that differentiates the emotions and opinions expressed in text or reviews. The sentiment analysis is challenging due to the complex language patterns and inappropriate or redundant features used for classification. In this research, the Light Weight - Gradient Boosting Machine (LWGBM) based feature selection is proposed to choose relevant … …Journal of Computer Science, Vol. 21, Issue 5 · 26 May 2025 · 4,695 accessesView PDFCite