192 articles for “experimental models”

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 · 1,542 accessesView PDF Cite

Research ArticleOpen accessIn the abstractThe Efficiency of Seven-Variable Box-Behnken Experimental Design with Varying Center Runs on Full and Reduced Model TypesMary Paschal Iwundu, Joan CosmosResponse Surface Methodology is widely used in the optimization of industrial processes and products that depend on several experimental variables. One of the most tested and efficient second-order Response Surface Methodology designs is the Box-Behnken Design. This research explores the efficiency of a seven-variable Box-Behnken design with varying center runs, on full and reduced quadratic models. Backward Elimination and Forward … …Journal of Mathematics and Statistics, Vol. 18, Issue 1 · 8 Dec 2022 · 7,089 accessesView PDF Cite

Research ArticleOpen accessIn the abstractCardiovascular Disease Prediction through Ensembled Transfer Learning on Cardiac Magnetic Resonance ImagingSibu Cyriac, Sivakumar R., Nidhin RajuCardiovascular Diseases (CVD) cause more deaths worldwide than most of the other diseases. The diagnosis of cardiovascular disease from Magnetic Resonance Imaging plays a major role in the medical field. The technological revolution contributed a lot to increase the effectiveness of CVD diagnosis. Many Artificial Intelligence methods using Deep Learning models are available to assist the cardiologist in the diagnosis … …Journal of Computer Science, Vol. 18, Issue 11 · 2 Nov 2022 · 6,169 accessesView PDF Cite

Research ArticleOpen accessIn the abstractBoosting Arabic Named Entity Recognition with K-Fold Cross Validation on LSTM and Bi-LSTM ModelsHamid Sadeq Mahdi Alsultani, Ahmed H. AliwyNamed-Entity-Recognition(NER) is one of the most important Information-Extraction (IE) use cases, whichis used to improve the performance of Natural Languages Processing (NLP) tasks,such as Relation-Extraction (RE), Question-Answering (QA). Recently, Arabic NER is tackled in differentways by researchers. In this study, we assess the performance of two widelyused models, namely, LSTM and Bi-LSTM on the NER task in the Arabic languageand … …Journal of Computer Science, Vol. 18, Issue 9 · 6 Sep 2022 · 6,317 accessesView PDF Cite

Research ArticleOpen accessIn the abstractMulti Resources and Constraints Based Consolidation Model to Mitigate the Energy ExtravaganceArchana Patil, Rekha PatilTo design green clouds with optimal energy and resource consumption, the host consolidation process became the most prominent cloud management policy today. In case of a consolidation, the underloaded host's VMs are shifted to the other hosts to control the energy extravagance at a data center. The consolidation process is considered an NP-hard problem, as it depends on several computational … …Journal of Computer Science, Vol. 18, Issue 7 · 28 Jul 2022 · 5,861 accessesView PDF Cite

Research ArticleOpen accessIn the abstractAdaptive Synthetic Oversampling Algorithm for Handling Class Imbalance in Multi-Class Data Stream ClassificationPriya S., Annie UthraConcept drift and class imbalanced data are major challenging processes involved in modern streaming data classification. Particularly, when integrated with difficult factors like the existence of noise, overlapping class distribution, concept drift, and data imbalance can considerably affect the classifier results. In addition, various challenges affect the performance of the existing oversampling schemes such as SMOTE and its derivatives. Regardless … …Journal of Computer Science, Vol. 18, Issue 7 · 26 Jul 2022 · 5,809 accessesView PDF Cite

Research NotesOpen accessIn the abstractMetadata Stewardship and Quality in Telecom SectorBhola Gan Chaudhuri, Shalli RaniThe spread of the telecom network infrastructure, constellations of satellites and the use of the Internet of Things (IoT) have brought about unprecedented volumes of heterogeneous information which facilitate the contemporary monitoring systems of the environment and the earth. Metadata control and information quality have also become significant in the telecom industry in controlling data reliably, enhancing data services, and … …Journal of Computer Science, Vol. 22, Issue 10 · 22 Oct 2026 · 335 accessesView PDF Cite

Research ArticleOpen accessIn the abstractAssessing Bi-LSTM Model’s Performance in Identifying AI Generated Text in Digital MediaTinashe Crispen Garidzira, William Tichaona Vambe, Courage MatoboboThe rapid growth of AI-generated content from ChatGPT, Gemini, and many others poses significant challenges in digital media. There are increasing instances of text generated by machine learning models being indistinguishable from human-written text. This calls for an effective way of detecting and distinguishing text generated by AI from human text. Using a Cross-Industry Standard Process for Data Mining (CRISP-DM) … …Journal of Computer Science, Vol. 21, Issue 8 · 8 Oct 2025 · 2,416 accessesView PDF Cite

Research ArticleOpen accessIn the abstractPM-ViT a Framework for the Recognition of Emotions and Proclivity toward Mental Illness Using Facial ExpressionsPriti Rai Jain, Syed Mohammad Khurshaid Quadri, Anuradha KhattarAutomated emotion recognition is being used as a powerful technology in various fields in the present times. Facial Emotion Recognition (FER) aims to identify the emotional states of individuals based on their facial expressions. While in recent years, Convolutional Neural Networks (CNNs) have shown noteworthy performance in image classification tasks, however, the latest adoption of transformers for computer vision tasks … …Journal of Computer Science, Vol. 21, Issue 3 · 27 Jan 2025 · 7,061 accessesView PDF Cite

Research ArticleOpen accessIn the abstractGlass Strength for Impact and Blast LoadingMatthias Förch, Frank WellershoffGlass strength is highly influenced by strain rate. This material behaviour is well known in structural glass design and implemented in various standards. The strength of architectural glass is determined by component tests with a defined strain rate of 2 N/(mm2s), providing favourable terms for testing. As typical effects of actions on facades result in lower or higher strain rates, … …International Journal of Structural Glass and Advanced Materials Research, Vol. 5, Issue 1 · 7 May 2021 · 8,115 accessesView PDF Cite