Research ArticleOpen accessIn the abstractAn Enhanced Algorithm for Small Object Detection based on Thermal Imaging Using YOLOv8-EPBRavina Gupta, Sarika Jain, Manoj KumarObject detection is one of the most important and challenging problems in the computer vision domain. Using the power of deep models, researchers have carefully explored and made significant contributions to increasing the effectiveness of object detection and related tasks, such as object identification, localization, and segmentation. This progress is due to the rapid progress of deep learning in the … …Journal of Computer Science, Vol. 21, Issue 6 · 13 Jun 2025 · 4,218 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Vision-Based Approach to Real-Time Trust Evaluation within Multiagent SystemsAlan Kruger, Sun YiAs robotic autonomy increases, single-agent systems are evolving into more complex multiagent systems that require more factors for successful implementation. In exchange for this complexity, applications such as autonomous delivery services and reconnaissance swarms become possible when they are infeasible with only one agent. By incorporating Trust into the multiagent system, the complexity of the agent-to-agent relationships can be managed … …Journal of Mechatronics and Robotics, Vol. 9, Issue 1 · 21 Mar 2025 · 7,944 accessesView PDFCite
Research ArticleOpen accessIn the abstractPandemic Analysis and Preparedness Using a Three Layer Machine Learning ApproachArtika Singh, Manisha JailiaOutbreak analysis provides research-based information and data to enable scientific decision-making to manage an effective response to a pandemic. Pandemic analysis has its own set of challenges, such as limited data, the need for real time analysis, and the complexity of outbreak patterns. This study proposes a hybrid approach to manage such a spread through a 3-layer machine learning-based outbreak … …Journal of Computer Science, Vol. 22, Issue 11 · 15 Oct 2026 · 632 accessesView PDFCite
Research ArticleOpen accessIn the abstractAttribute Reduction in Bipolar Intuitionistic Fuzzy Relation SystemWeiyuan Wang, Qian WangBipolar intuitionistic fuzzy relation system (BIFRS) effectively characterize the bipolarity in real-world data by introducing positive and negative membership and non-membership degrees. To address redundancy caused by high-dimensional attributes, this paper proposes an attribute reduction method based on bipolar intuitionistic discernibility matrices. By constructing positive discernibility matrix M+∗ matrix M−∗ and negative discernibility , we systematically identify the minimal attribute … …Journal of Mathematics and Statistics, Vol. 22, Issue 1 · 16 Jul 2026 · 1,070 accessesView PDFCite
Research ArticleOpen accessIn the abstractDetecting Anomalies in IoT Using Intuitionistic Fuzzy Clustering AlgorithmsVijo Arul Selvi M., Fehmin Nadira Laskar, Fokrul Alom Mazarbhuiya et al.Intuitionistic Fuzzy Sets (IFS) are convenient ways to represent the vagueness and uncertainty inherent in any dataset. There are many uses of these. One such use is the Fuzzy C-Means (FCM) algorithm, which clusters the data objects into a pre-assigned (c) number of fuzzy clusters, which has been adopted in many fields, namely, pattern classification, anomaly detection, fraud identification, etc. … …Journal of Computer Science, Vol. 22, Issue 2 · 2 Mar 2026 · 1,606 accessesView PDFCite
Research ArticleOpen accessIn the abstractPerformance Analysis of Two Famous Cryptographic Algorithms on Mixed DataEmmanuel Abidemi Adeniyi et al.The rapid development of digital data sharing has made information security a crucial concern in data communication. The information security system heavily relies on encryption methods. These algorithms employ strategies to increase data secrecy and privacy by obscuring the information, which only those parties who have the accompanying key can decode or decrypt. Nevertheless, these methods also use a lot … …Journal of Computer Science, Vol. 19, Issue 6 · 29 May 2023 · 6,026 accessesView PDFCite
Research ArticleOpen accessIn the abstractEfficient Decoding Algorithm for Binary Quadratic Residue Codes Using Reduced Permutation SetsHamza Boualame, Mostafa Belkasmi, Idriss ChanaThe Quadratic Residue (QR) codes have a rich mathematic structure. Unfortunately, their Algebraic Decoding (AD) is not generalizable for all QR codes. In this study, an efficient hard decoding algorithm is proposed to generalize the decoding of the binary systematic Quadratic Residue (QR) codes. The proposed decoder corrects t erroneous bits or less, in the received word, based on a … …Journal of Computer Science, Vol. 19, Issue 4 · 3 Apr 2023 · 6,020 accessesView PDFCite
Research ArticleOpen accessIn the abstractData Clustering-based Metaheuristic for Physical Internet Supply Chain NetworkAbdelsamad Chouar, Samir Tetouani, Aziz Soulhi, Jamila ElalamiIn this study, a data clustering-driven technique is proposed for a Physical Internet Supply Chain Network (PI-SCN) to reduce data complexity, process time compression, and lankness of process optimization. Given a set of data points, a clustering algorithm aims to classify each data-points into a specific group. Each group should have similar properties and/or features, while data points in different … …Journal of Computer Science, Vol. 18, Issue 4 · 21 Apr 2022 · 6,476 accessesView PDFCite
Research ArticleOpen accessIn the abstractBig Data Framework for Predicting Infectious Diseases to Improve Healthcare by Discovering New Symptom PatternsAmal Mohamed Mounir, Mohamed Ibrahim Marie, Laila Abd-ElhamidThe utilization of big data in infectious disease control represents a captivating opportunity, as these novel data streams offer the potential to enhance the timeliness of preventive measures. Various healthcare providers in both the public and private sectors generate, store, and analyse extensive datasets to enhance the quality of services they deliver. Recently, the outbreak of the new coronavirus, COVID-19, … …Journal of Computer Science, Vol. 20, Issue 10 · 2 Aug 2024 · 4,922 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Learning Approach to Mitigate DDoS Attacks in SDNHema Surendrakumar Dhadhal, Paresh Kotak, Parvez Faruki, Atul GonsaiThe rise of Distributed Denial of Service (DDoS) attacks remains a significant obstacle to network security and availability. This abstract presents a new hybrid model for DDoS mitigation in Software-Defined Networking (SDN) environments, combining a Semi-supervised Deep Extreme Learning Machine (Semi-Deep ELM) with a hybrid architecture. SDN's centralized control and programmability create an ideal platform for implementing advanced mitigation strategies. … …Journal of Computer Science, Vol. 20, Issue 9 · 5 Jul 2024 · 5,345 accessesView PDFCite