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Research ArticleOpen accessIn the keywordsMitigating the Evidence-Related Factors in Automated Fact-CheckingAruna Shankar, Narayanan Kulathuramaiyer, Johari Bin Abdullah, Muthukumaran PakkirisamyThe rapid proliferation of digital misinformation highlights the urgent need for robust automated fact-checking systems that can accurately distinguish truth from falsehood. A persistent challenge for these systems is the occurrence of false positives, where truthful information is incorrectly flagged as misleading due to limitations in evidence assessment, including insufficient evidence, logical inconsistencies, and conflicting information. This research introduces a … …Journal of Computer Science, Vol. 21, Issue 3 · 13 Feb 2025 · 5,992 accessesView PDFCite
Research ArticleOpen accessIn the keywordsFUSION OF COLOR AND MODIFIED WEBER’S LAW DESCRIPTOR BASED HUMAN SKIN DETECTIONC. Prema, D. ManimegalaiSkin detection in images or videos plays a vital role in a wide range of image processing applications like face detection, face tracking, gesture analysis, human-computer interaction etc. Due to its high processing speed and invariant against rotation, it has received significant interest in pattern recognition and computer vision. The robustness of skin detection using color information depends on real … …Journal of Computer Science, Vol. 10, Issue 9 · 19 Apr 2014 · 6,397 accessesView PDFCite
Research ArticleOpen accessIn the keywordsResearch Proposal: An Intrusion Detection System Alert Reduction and Assessment Framework Based on Data MiningKarim Al-Saedi, Selvakumar Manickam, Sureswaran Ramadass et al.The Intrusion Detection System (IDS) generates huge amounts of alerts that are mostly false positives. The abundance of false positive alerts makes it difficult for the security analyst to identify successful attacks and to take remedial actions. Such alerts to have not been classified in accordance with their degree of threats. They further need to be processed to ascertain the … …Journal of Computer Science, Vol. 9, Issue 4 · 8 May 2013 · 7,709 accessesView PDFCite
Research ArticleOpen accessIn the keywordsDermoscopic Image Segmentation using Machine Learning AlgorithmL. Padma Suresh, K.L. Shunmuganathan, S.H. Krishna VeniProblem statement: Malignant melanoma is the most frequent type of skin cancer. Its incidence has been rapidly increasing over the last few decades. Medical image segmentation is the most essential and crucial process in order to facilitate the characterization and visualization of the structure of interest in medical images. Approach: This study explains the task of segmenting skin lesions in … …American Journal of Applied Sciences, Vol. 8, Issue 11 · 7 Oct 2011 · 7,342 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Computer Aided Diagnosis System for Lung Cancer Detection\Using Support Vector MachineM. Gomathi, P. ThangarajProblem statement: Computer Tomography (CT) has been considered as the most sensitive imaging technique for early detection of lung cancer. Approach: On the other hand, there is a requirement for automated methodology to make use of large amount of data obtained CT images. Computer Aided Diagnosis (CAD) can be used efficiently for early detection of Lung Cancer. Results: The usage … …American Journal of Applied Sciences, Vol. 7, Issue 12 · 31 Dec 2010 · 8,285 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntrusion-Resistant Multi-Hop Communication Protocol for Secure Wireless Sensor NetworksRakesh Ranjan, Vaishali Singh, Hitendra SinghModern Internet of Things (IoT) systems are based on Wireless Sensor Networks (WSNs), which can be distributed to various environments to perform a range of sensing and data aggregation. Their intrinsic deficiencies in computation, energy, and bandwidth, however, make them very vulnerable to routing-layer attacks like black hole and selective forwarding as well as Sybil intrusion. The current studies on … …Journal of Computer Science, Vol. 22, Issue 6 · 1 Jul 2026 · 935 accessesView PDFCite
Research ArticleOpen accessIn the abstractSmart and Secure Anomaly Detection in IoT Using Quantum Inspired Kernel Ensemble LearningAbrar M. AlajlanThe exponential growth of the Internet of Things networks has greatly increased the attack surface for cyber threats, necessitating the use of strong and perceptive anomaly detection systems. Traditional intrusion detection systems often struggle with high false alarm rates, limited generalization, and inefficiency in processing high-dimensional heterogeneous IoT data. To address this issue, a novel Hybrid Quantum-Enhanced Kernel Ensemble Learning … …Journal of Computer Science, Vol. 22, Issue 3 · 12 Mar 2026 · 1,762 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Video Tampering Detection Using Dynamic Temporal LSTM With Adaptive CNNGurpreet Kour Khalsa, Rakesh Ahuja, Rattan Deep AnejaIn the domain of information technology, video tampering detection has become hyper critical principally with the increase in deep fake as everyone is having affordable access to the internet. The long established methods lack in detecting the manipulated content specifically for temporal disordered and variant frames. In order to overcome such issues, the suggested innovative method encompasses Dynamic Temporal Warping … …Journal of Computer Science, Vol. 22, Issue 3 · 7 Mar 2026 · 2,015 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Context-Aware Temporal Convolutional Network for Water Replacement Prediction in Catfish Biofloc Ponds With Imbalanced Event HandlingYaddarabullah, Inanpi Hidayati Sumiasih, Mutiara Dewi PuspitawatiWater replacement is a biologically critical yet under-automated decision in biofloc-based aquaculture systems. Mistimed actions can destabilize microbial ecosystems, elevate fish mortality, and compromise sustainability through excessive water usage. Traditional rule-based heuristics often fail to account for the nonlinear and multiscale dynamics of pond environments. To address this, we propose a Context-Aware Temporal Convolutional Network (CA-TCN), a rare-event classification framework … …Journal of Computer Science, Vol. 22, Issue 3 · 5 Mar 2026 · 1,664 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Approach Based on Federated Learning for the Identification of Man in the Middle Attacks in IOT Networks Using BlockchainSarumathi S, Juliet Johny, Minal Khandare et al.Federated Learning (FL) enables cooperative model training across dispersed edge devices while protecting data privacy and providing localized insights without the need for centralized data aggregation. In the Internet of Things (IoT), federated learning enables cooperative model training among dispersed edge devices while protecting data privacy and providing localized insights without the need for centralized data aggregation. Nevertheless, Federated Learning’s … …Journal of Computer Science, Vol. 22, Issue 2 · 23 Feb 2026 · 1,613 accessesView PDFCite