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71 results for “Comparative Evaluation”
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Research ArticleOpen accessIn the abstractPredictive Mathematical Modeling and Classification of Retail Sales Orders Using AI Machine Learning TechniquesMohammad Subhi Al-Batah, Mowafaq Salem Alzboon, Hamzeh ZureigatThis study presents a systematic mathematical model known as a low-code approach to classifying retail sales orders by size using AI machine learning techniques within the Orange Data Mining platform. Leveraging a real-world sales dataset sourced from Kaggle, we implemented and evaluated ten classification models, including ensemble learners (AdaBoost, Gradient Boosting), probabilistic classifiers (Naïve Bayes), distance-based methods (kNN), and interpretable … …Journal of Computer Science, Vol. 22, Issue 3 · 10 Mar 2026 · 1,567 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdvancing Stroke Lesion Segmentation With U-Net Variants: Classical, Transfer Learning, and MRI Sequence-Specific Customized ApproachesSonia Flora Panesar, Amit P. GanatraIschemic stroke, caused by restricted cerebral blood flow, is a leading cause of death and disability worldwide. Accurate segmentation of stroke lesions in MRI is essential for timely diagnosis but remains labor-intensive when done manually. This study presents a comparative evaluation of three U-Net variants for automated ischemic stroke lesion segmentation using the ISLES 2022 dataset: (1) Classical U-Net with … …Journal of Computer Science, Vol. 22, Issue 2 · 27 Feb 2026 · 1,791 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Deep Learning Approach for Tomato Leaf Disease Detection Using Optimized CNN ArchitectureSunil K. Vithalani, Vipul K. DabhiEarly disease detection in plants is essential for sustaining agricultural yield and guaranteeing food security. A comparative analysis of transformer-based and convolutional based deep learning models for classifying tomato leaf diseases is presented. Specifically, it examines the performance of a Vision Transformer (ViT), tested both in a form of scratch training setup and through transfer learning, against well-known CNN architectures … …Journal of Computer Science, Vol. 22, Issue 1 · 7 Feb 2026 · 3,917 accessesView PDFCite
Research ArticleOpen accessIn the abstractImmunomodulatory and Antioxidant Activities of Selenium-Enriched Polysaccharides from Epimedium and Isatis IndigoticaRui Zhang, Jin Li, Jiajia ZhouThis study aims to investigate the effects of selenium modification on polysaccharides derived from two traditional Chinese medicinal herbs-Epimedium (Yinyanghuo) and Isatis root (Banlangen)-in enhancing immune function and antioxidant activity. The purpose is to explore the relationship between structure and function, providing a theoretical basis for the development of efficient plant-based functional antioxidants. Polysaccharides were extracted using an optimized enzymatic … …American Journal of Biochemistry and Biotechnology, Vol. 21, Issue 4 · 3 Feb 2026 · 1,933 accessesView PDFCite
Research ArticleOpen accessIn the abstractImproving Diabetes Risk Prediction Using Ensemble Boosting and SMOTE-Based Class BalancingKittipol Wisaeng, Pankom Sriboonlue, Benchalak MuangmeesriAccurate diabetes prediction is vital for early intervention, optimized resource allocation, and minimizing long-term complications. This study presents a comparative evaluation of traditional and advanced machine learning models for diabetes classification using a structured clinical dataset. Seven baseline algorithms were assessed against five advanced ensemble methods: CatBoost, LightGBM, XGBoost, Voting Ensemble, and Stacking Ensemble. To improve algorithm learning, the Synthetic … …Journal of Computer Science, Vol. 22, Issue 1 · 1 Feb 2026 · 1,976 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Experimental Study on the Embedded Software Development Approach Using TI-RTOSAloysio Augusto Rabello de Carvalho, Luiz Eduardo Galvão MartinsEmbedded systems have experienced significant growth in recent years. These systems, which power a wide range of devices from smart appliances to industrial machinery, have become integral to our daily lives and industries. However, this rapid expansion introduces new challenges for developers. A critical decision involves whether to employ a Real-Time Operating System (RTOS) or to forgo it, depending on … …Journal of Computer Science, Vol. 21, Issue 6 · 17 Jul 2025 · 3,068 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Semantic Web Retrieval Through Ontology-Driven Feature Extraction: A Novel PropositionMeer Hazar Khan, Muhammad Imran Sharif, Mehwish Mehmood et al.Web images represent unstructured data sets which often lead to challenges when users try to locate distinct images via text-based searches on the web. Such difficulties stem from different factors, e.g., redundant image storage, irrelevant metadata tags, and incorrect associations. To overcome this issue, we propose a semantic model based on the ontology language that enables users to find images … …Journal of Computer Science, Vol. 20, Issue 5 · 23 Feb 2024 · 5,562 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Analysis of Risk Management Strategies for Additive Manufacturing Supply ChainsBandar Altubaishe, Jahlani Clarke, Christina McWilliams, Salil DesaiSupplier selection is an important strategic decision to be made in additive manufacturing supply chains. This paper presents a hybrid Analytic Hierarchy Process-Preference Ranking Organization Method for Enrichment of Evaluations (AHP-PROMETHEE) algorithms-based Failure Mode and Effects Analysis (FMEA) for supplier selection in a risk-based environment. Our approach is contrasted with an FMEA based on a Fuzzy Analytic Hierarchy Process (FAHP) … …American Journal of Applied Sciences, Vol. 16, Issue 8 · 17 Oct 2019 · 8,581 accessesView PDFCite
Research ArticleOpen accessIn the abstractSlime Mould Reproduction: A New Optimization Algorithm for Constrained Engineering ProblemsRajalakshmi Sakthivel, Kanmani SelvaduraiIn recent explorations of biologically inspired optimization strategies, the Slime Mould Reproduction (SMR) algorithm emerges as an innovative meta-heuristic optimization technique. This algorithm is deeply rooted in the reproductive dynamics observed in slime molds, particularly the intricate balance these organisms strike between local and global spore dispersal. By replicating this balance, the SMR algorithm deftly navigates between exploration and exploitation … …Journal of Computer Science, Vol. 20, Issue 1 · 21 Dec 2023 · 5,943 accessesView PDFCite
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 PDFCite