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110 articles for “Hybrid Systems”
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Research ArticleOpen accessIn the abstractEnsemble Learning-Based Hybrid Explainable Intrusion Detection System With SMOTE for Enhanced Detection and Interpretability in CybersecurityMohammad Subhi Al-Batah, Taqieddin AldrousWith cyberattacks becoming increasingly sophisticated, there is a growing need for Intrusion Detection Systems (IDS) that are both accurate and interpretable. This study introduces a hybrid IDS framework that integrates Random Forest (RF) and Light Gradient Boosting Machine (LGBM) classifiers with the Synthetic Minority Over-sampling Technique (SMOTE) to address class imbalance. To enhance transparency and trust, the system also incorporates … …Journal of Computer Science, Vol. 22, Issue 5 · 19 May 2026 · 1,284 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid Pipelines for Intelligent Human Resources Text Classification: LLMs, RAG, and Generative AISoumia Chafi, Mustapha Kabil, Abdessamad KamoussThe digital transformation of Human Resources Information Systems (HRIS) requires advanced approaches to process unstructured textual data originating from Curriculum Vitae (CVs), cover letters, and job postings. Traditional text classification methods exhibit limitations when faced with current needs for contextual understanding and fine-grained skill detection. This paper proposes a hybrid pipeline combining advanced text classification, contrastive learning (SimCSE, Contriever), Retrieval-Augmented … …Journal of Computer Science, Vol. 22, Issue 4 · 22 Apr 2026 · 1,513 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Learning Synergy: CNNs and Transformers for Epidemic Outbreak ForecastingAlexander R., Shakthi Priya V., Sumathi G. et al.An Accurate prediction of outbreaks is extremely crucial for taking proactive public health interventions, distributing limited resources, and controlling a disease. This paper assesses and also compares the performances of the available deep learning models, namely, Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM) networks, and Bidirectional Long Short-Term Memory (BiLSTM) networks, in predicting. CNNs are best for feature extraction … …Journal of Computer Science, Vol. 21, Issue 12 · 23 Jan 2026 · 2,120 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimized Movie Recommendation Using Hybrid Jaccard-Based K-Means Clustering Using Apache SparkShiba Prasad Dash, Rajesh Kumar Sahoo, Ram Chandra Barik et al.The need for recommendations specific to each person's interests is growing every day, making recommendation systems increasingly important in people's lives. Researchers have paid close attention to the rapid expansion of e-commerce businesses and online video streaming services like Hotstar, YouTube, and Netflix. The collaborative filtering-based RS system aims to suggest such films or videos to users based on their … …Journal of Computer Science, Vol. 22, Issue 9 · 23 Sep 2026 · 613 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnxiety-Focused Classification Using Smartphone-Based Gait Analysis and Deep Learning ModelsMinchan Kang, Gou-Sung Degbey, Hyunhwa Lee et al.Mood disorders, such as anxiety, significantly impact individual well-being and present challenges to healthcare systems globally. Traditional screening methods, including self-administered symptom questionnaires, provide valuable insights into symptoms but may miss dynamic fluctuations. This study explores the potential of smartphone inertial sensors and deep learning models for anxiety risk classification. Using gait data from 36 participants, collected via smartphone accelerometers … …Journal of Computer Science, Vol. 22, Issue 7 · 16 Jul 2026 · 826 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Hybrid Grey Wolf Optimizer and Deep Transfer Learning-Based Intrusion Detection System for IoTKapil Shrivastava, Manish Tiwari, Prasun ChakrabartiThe rapid proliferation of Internet of Things (IoT) devices has driven significant advancements in connectivity and automation, but it has also introduced substantial cybersecurity risks, including intrusions and cyberattacks. To address these challenges, this study proposes a hybrid intrusion detection framework that combines advanced optimization techniques with ensemble deep learning to enhance detection accuracy and computational efficiency. The proposed framework … …Journal of Computer Science, Vol. 22, Issue 2 · 17 Feb 2026 · 1,512 accessesView PDFCite
Research ArticleOpen accessIn the abstractEconomic Evaluation of Standalone Hybrid PV–H2 with Storage SystemAdeyinka Victor Adebayo, Samuel Oladeji, Hussein Kehinde Adebayo, Ismaheel Oyeyemi OladejoThis study evaluates the economic performance of a standalone hybrid PV-H2 system with battery storage for small-scale electricity demand. The methodology involves comparing various configurations of standalone PV, storage, and hybrid PV-H2 systems under different discount rates and evaluation periods. Economic indicators such as Net Present Value (NPV), Payback Period, and Discounted Annualized Return (AAR) determine financial viability. Results indicate … …American Journal of Engineering and Applied Sciences, Vol. 18, Issue 1 · 4 Mar 2025 · 7,123 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid SIFT-DCT Approach for Face Matching of BuddhaStatues: Addressing Negative Similarity Metrics with SHashingLinda Marlinda, Fikri Budiman et al.Art and cultural heritage rely on image processing techniques forpreservation and analysis. A key challenge in this study is accuratelydetecting highly similar Buddha faces despite variations in lighting, rotation,and minor facial differences. This paper proposes a Content-Based ImageRetrieval (CBIR) framework that integrates Discrete Cosine Transform(DCT) and Scale-Invariant Feature Transform (SIFT) to enhance face-matching accuracy. The system is tested on a … …Journal of Computer Science, Vol. 21, Issue 7 · 29 Jul 2025 · 3,493 accessesView PDFCite
Research ArticleOpen accessIn the abstractMulti-Source Cyber Intrusion Detection Using Ensemble Machine LearningTaskeen Ali Khan, Sara Abbas, Biswaranjan Senapati et al.The increased usage of digital technologies across businesses has led to an increase in cybercrime. It is difficult for existing intrusion detection systems to detect highly skilled hacking attempts; however, machine learning has been suggested as a way around these drawbacks. The purpose of this study is to evaluate how well various machine learning algorithms identify and stop cyberattacks in … …Journal of Computer Science, Vol. 21, Issue 1 · 14 Dec 2024 · 5,705 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid Framework 4.0 for Enterprise Architecture in the Context of Teleworkingkouassi Thomas, Brou Pacôme, Koffi Kanga et al.Context and justification: The outbreak of the COVID-19 pandemic has triggered a profound change in the business landscape, forcing companies around the world and their information systems to fundamentally rethink their operational models to adapt to an uncertain and complex environment. The digital transformation of businesses and the era of information technology and remote storage are having an impact on … …Journal of Computer Science, Vol. 20, Issue 12 · 4 Nov 2024 · 4,737 accessesView PDFCite