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Research ArticleOpen accessIn the abstractDeep Learning Approaches for Early Detection of Skin Cancer Disease Detection Using Segmentation and Classification with Severity AnalysisPunam R. Patil, Ritu TandonThe utmost prevalent type of the disease, skin cancer claims millions of lives every year, poses a serious public health threat particularly melanoma, which is often fatal if not detected early. Early diagnosis is crucial, yet traditional methods frequently fall short due to image quality limitations and the complexity of visual differentiation. With an emphasis on severity analysis, this study … …Journal of Computer Science, Vol. 21, Issue 9 · 24 Nov 2025 · 2,051 accessesView PDFCite
Research ArticleOpen accessIn the abstractMethodology of the Development of Production Digital Twins Using a Simulation ExperimentSnježana Križanić, Neven VrčekThe simulation experiment evaluates whether the business process model accurately replicates real-world operations and whether the digital twin functions in real-time. A digital twin of a production business process is a virtual representation of its real-world counterpart. Its aim is to monitor the execution of the actual production business process in order to detect irregularities and production downtimes early and … …Journal of Computer Science, Vol. 21, Issue 6 · 13 Jun 2025 · 4,805 accessesView PDFCite
Research ArticleOpen accessIn the abstractXAI_MLPCNN: A Novel Explainable AI-Based Deep Learning Framework for Stress IdentificationFateh Bahadur Kunwar, Rakesh Kumar Yadav, Hitendra Singh, Nitin TripathiOver the past ten years, there has been a lot of emphasis focusedon the development of Artificial Intelligence (AI) and Machine Learning(ML)-based mental health treatments. To increase practitioners' and patients'trust in AI applications, AI systems need to explain their actions. This iscalled Explainable AI (XAI). While significant progress has been achievedin stress prediction models, XAI has not advanced as much. … …Journal of Computer Science, Vol. 21, Issue 5 · 6 May 2025 · 6,161 accessesView PDFCite
Research ArticleOpen accessIn the abstractBangla↔English Machine Translation Using Attention-based Multi-Headed Transformer ModelArgha Chandra Dhar, Arna Roy, M. A. H. Akhand et al.Machine Translation (MT) refers to translate texts or documents from the source language into the target language without human intervention. Any MT model is language-dependent and its development requires grammar, phrase rules, vocabulary, or relevant data for the particular language pair. Hitherto, little research on MT for Bangla-English is reported in the literature, although Bangla is a major language. This … …Journal of Computer Science, Vol. 17, Issue 10 · 10 Nov 2021 · 8,469 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdvanced Facial Emotion Recognition Using DCNN-ELM: A Comprehensive Approach to Preprocessing, Feature Extraction and Performance EvaluationBoopalan K., Satyajee Srivastava, K. Kavitha et al.As a subfield of affective computing, Facial Emotion Recognition (FER) teaches computers to read people's facial expressions to determine their emotional state. Because facial expressions convey 55% of an individual's emotional and mental state in the whole range of face-to-face communication, Facial Emotion Recognition is crucial for connecting humans and computers. Improvements in the way computer systems (robotic systems) interact … …Journal of Computer Science, Vol. 21, Issue 1 · 30 Nov 2024 · 5,899 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Learning Perspective on Assessing and Elevating Engineering Student’s PerformanceKandula Neha, Ram KumarIn addressing the need for successful frameworks to break down understudy execution, this study presents a profound learning-based approach for thorough understudy execution examination inside instructive establishments. The framework intends to evaluate understudies' presentation levels and distinguish those qualified for positions, needing extra help, or in danger of exiting. Utilizing a Long Momentary Memory (LSTM) model, a sort of intermittent … …Journal of Computer Science, Vol. 20, Issue 11 · 21 Sep 2024 · 4,495 accessesView PDFCite
Research ArticleOpen accessIn the abstractONCODIAG Select and Test (ST) Algorithm: An Approximate Clinical Reasoning Model for Diagnosing and Monitoring Breast CancerO.N. Oyelade, A.A. Obiniyi, S.B. JunaiduClinical reasoning involves coordinated thinking strategies targeted at gathering and analyzing relevant information to arrive at a high-quality clinical solution to patients' medical problems. The correctness and proper choice of clinical reasoning approach chosen by a clinician or machine affect the accuracy and acceptability of the diagnosis; moreover, another challenge that usually surfaces during clinical reasoning is the burden of … …Current Research in Bioinformatics, Vol. 9, Issue 1 · 22 Feb 2020 · 8,936 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntegrating (OLAP) Online Analytical Processing With a Fast Algorithm for Epileptic Seizures DetectionIlyas Zidane, Wajih Rhalem, Nordine ZidaneEpilepsy is a neurological disorder characterized by recurrent seizures, significantly impacting the quality of life of patients. Effective detection and analysis of epileptic seizures are crucial for timely intervention and management. This paper presents the integration of a fast algorithm for epileptic seizures detection with an OLAP (Online Analytical Processing) system using a star schema data warehouse model. By leveraging … …Journal of Computer Science, Vol. 22, Issue 10 · 12 Oct 2026 · 678 accessesView PDFCite
Review ArticleOpen accessIn the abstractHuman Activity Recognition at the Edge: A Systematic Review of Machine Learning Models, Deployment Constraints, and Latency Energy Accuracy Trade offsJose Antonio Rojas Guillén, Wini Ebelin Quispe Bautista, Arturo Gamarra MorenoHuman Activity Recognition (HAR) has become a key component of intelligent healthcare monitoring, assisted living, sports analytics, smart environments, and wearable computing. However, the migration of HAR models from cloud-centered architectures to edge, embedded, mobile, and wearable platforms introduces constraints related to computational capacity, memory footprint, battery consumption, inference time, and real-time responsiveness. This study presents a systematic literature review … …Journal of Computer Science, Vol. 22, Issue 8 · 7 Sep 2026 · 593 accessesView PDFCite
Research ArticleOpen accessIn the abstractAutoencoder-Based Intrusion Detection for ARP Poisoning in SDN ControllersKago Seemela, Banyatsang Mphago, Thabo Semong, Phephisa MethulaAddress Resolution Protocol (ARP) poisoning is still a critical control plane attack in Software Defined Networks (SDNs), and spoofing of ARP mappings can trick SDNs controller and accomplish man in the middle, eavesdropping and denial of service attacks. Current SDN intrusion detection systems of ARP attacks rely on supervised learning and labelled attack data which is rather expensive and not … …Journal of Computer Science, Vol. 22, Issue 7 · 21 Jul 2026 · 869 accessesView PDFCite