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168 articles for “Performance Metrics”
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Research ArticleOpen accessIn the abstractUncertainty-Aware Ensemble Models for Improved Defect Detection in Noisy DataMadhavi Perla, Gadi Lava Raju, A Radha Krishna et al.Software defect prediction plays a crucial role in ensuring software quality and reliability, especially as modern systems become more complex and data rich. This study introduces an uncertainty-aware ensemble learning framework aimed at improving defect classification performance in noisy and imbalanced datasets, particularly those from the PROMISE and NASA KC1 repositories. The proposed model integrates multiple classifiers in a multi-learner … …Journal of Computer Science, Vol. 22, Issue 4 · 27 Apr 2026 · 1,549 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Context Aware Deep Learning Framework for Multi-Level Arabic Fake News Detection Using Hybrid Linguistic RepresentationsNoor Mahmoud Alkudah, Somia Abufakher, Raja Masadeh et al.The rapid spread of false information on social media has made it even more important to be able to spot false news, especially in Arabic-speaking areas where language is more complicated and news is organized in a hierarchy. Recent research show that deep learning and transformer-based models work well, but most of them only look at performance metrics and don't … …Journal of Computer Science, Vol. 22, Issue 3 · 27 Mar 2026 · 1,577 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Distillation GAN Model for Network Intrusion DetectionChandrakala C B, Sai Sreevall, Raghudathesh G PThis study presents a distillation-based Generative Adversarial Network (GAN) model designed for intrusion detection in network systems. A Teacher-Student architecture is proposed, in which a single teacher generator is utilized to train both the teacher discriminator and the student discriminator. The model was trained to identify anomalies present in network traffic intrusions by tuning the min-max loss function in GANs. … …Journal of Computer Science, Vol. 22, Issue 2 · 5 Mar 2026 · 1,560 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Dam Safety and Management: Long Short-Term Memory Based Predictive Models for Accurate Alert ForecastingNisha C. M, N. ThangarasuDam management and early alert systems are critical for effective water resource management. Accurate prediction of dam alert signals facilitates proactive decision-making, thereby aiding in the effective management and reduction of potential risks linked to dam operations. Within this research, Long Short-Term Memory (LSTM) networks are utilized to forecast dam alert signals issued from the dam by leveraging daily parameters, … …Journal of Computer Science, Vol. 22, Issue 1 · 6 Feb 2026 · 1,632 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Analysis of Wavelet, Curvelet, and Contourlet Transforms for Denoising Liver CT ImagesMajzoob Kamalaldin Omer AbdalrahmanLiver cancer is one of the leading causes of mortality worldwide, and early detection using CT imaging plays a critical role in patient survival. However, the quality of CT scans is often degraded by noise, particularly in low-dose imaging intended to minimize radiation exposure. This study presents a comprehensive comparison of three multiresolution transform techniques, namely the wavelet, curvelet, and … …Journal of Computer Science, Vol. 22, Issue 1 · 4 Feb 2026 · 2,124 accessesView PDFCite
Research ArticleOpen accessIn the abstractEvaluating Machine Translation for Domain Specific Low-Resource Nepali-English Language Pairs: The Impact of Tokenization on Statistical and Neural TechniquesAmit Kumar Roy, Bipul Syam PurkayasthaIn the modern era, the field of Machine Translation (MT) has seen a significant shift towards Neural Machine Translation (NMT) techniques, which have surpassed traditional Statistical Machine Translation (SMT) models in terms of the quality of translation. Despite this, the efficacy of these techniques may differ based on the language combination in consideration. While SMT is somewhat more flexible in … …Journal of Computer Science, Vol. 21, Issue 12 · 24 Jan 2026 · 1,926 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Comparative Study of Machine Learning Algorithms for Skin Cancer DetectionVineeth Victor, Amit Kumr Tyagi, Khushboo Tripathi et al.The skin is the largest organ in the human body, covering an area of around 20 square feet. Our skin keeps us safe from germs and the environment, helps us regulate our body temperature, and gives us the ability to feel touch, heat, and cold. More than 95 percent of all skin cancers are caused by ultraviolet (UV) radiation. UV … …Journal of Computer Science, Vol. 21, Issue 12 · 23 Jan 2026 · 1,869 accessesView PDFCite
Research ArticleOpen accessIn the abstractLatent Feature-Based Trust-Aware Model for Service Delegation in Social Internet of Things (SIoT)Rahul, Venkatesh, Satish B BasapurThe integration of social networking concepts into the Internet of Things (IoT) paradigm has given rise to Social IoT (SIoT) ecosystems, aiming to address challenges related to network navigation, service discovery, and service composition. A fundamental issue in SIoT is the careful selection of trustworthy devices that provide services. A service provider can offer multiple and diverse services, and different … …Journal of Computer Science, Vol. 21, Issue 12 · 9 Jan 2026 · 1,806 accessesView PDFCite
Review ArticleOpen accessIn the abstractMachine Learning Techniques for Software Bug Prediction: A Systematic ReviewSyahana Nur’Ain Saharudin, Koh Tieng Wei, Kew Si NaThe goal of software bug prediction is to identify the software modules that will have the likelihood to get bugs by using some fundamental project resources before the real testing starts. Due to high cost in correcting the detected bugs, it is advisable to start predicting bugs at the early stage of development instead of at the testing phase. There … …Journal of Computer Science, Vol. 16, Issue 11 · 14 Nov 2020 · 9,386 accessesView PDFCite
Research ArticleOpen accessIn the abstractMesh Simplification by Curvature-Enhanced Quadratic Error MetricsPaolo Pellizzoni, Gianpaolo SavioPolygonal meshes have a significant role in computer graphics, design and manufacturing technology for surface representation and it is often required to reduce their complexity to save memory. An efficient algorithm for detail retaining mesh simplification is proposed; in particular, the method presented is an iterative edge contraction algorithm based on the work of Garland and Heckberts. The original algorithm … …Journal of Computer Science, Vol. 16, Issue 8 · 7 Sep 2020 · 8,416 accessesView PDFCite