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Research ArticleOpen accessIn the abstractCapsule Defect Detection and Classification Using Enhanced MobileNet ModelWenqing Bian, Yongzhi Huang, Baolian Shan, Yanting ChangThe quality of capsules has a direct impact on human health. However, defects inevitably arise during the capsule manufacturing process, and manual sorting is required. Most studies on capsule defects focus on detecting surface imperfections and those on internal capsule defects remain relatively limited. This study classifies four types of capsules using the deep learning model MobileNet, aiming to accurately … …American Journal of Biochemistry and Biotechnology, Vol. 20, Issue 4 · 5 Nov 2024 · 5,203 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparison of Multivariate Adaptive Regression Splines and Classification Regression Tree for Prediction of Body Weight of Bapedi SheepMadumetja Cyril Mathapo, Ramaisela Barley Mthembu, Albino Joas Tsenane et al.The study aimed to compare the performance of multiple adaptive regression splines and classification regression trees for the prediction of the body weight of Bapedi sheep. A total of 100 Bapedi sheep aged between one and five years old of different sexes were employed. The study measured the following: Body Length (BL), Withers Height (WH), Heart Girth (HG), Rump Height … …American Journal of Animal and Veterinary Sciences, Vol. 19, Issue 3 · 12 Jul 2024 · 5,184 accessesView PDFCite
Research ArticleOpen accessIn the abstractPM2.5 Prediction Using Homogenous and Heterogenous Ensemble Learning: A Comprehensive EvaluationShrabani Medhi, Minakshi GogoiAir pollution is a global issue. PM2.5 is considered to be the most dangerous pollutant. Prediction of PM2.5 concentration is important so that effective measures can be taken beforehand. A multitude of machine learning methodologies have been employed in forecasting PM2.5 levels, utilizing diverse combinations of ensemble classifiers and regressors. However, there are three important issues that need to be … …Journal of Computer Science, Vol. 20, Issue 9 · 20 Jun 2024 · 5,176 accessesView PDFCite
Research ArticleOpen accessIn the abstractTesting React Native Mobile Apps: Pruning GUI Model ApproachRand Marwan Khalil Ibrahim, Samer ZeinThe mobile app market is still in continual growth. People are migrating to smartphone mobile devices to accomplish their daily activities while working, playing, and communicating with others. From the developers' perspective, there exists a wide variety of platforms, technologies, and architecture choices for developing and testing mobile apps. However, because of the constant changes in software applications and the … …Journal of Computer Science, Vol. 20, Issue 6 · 12 Mar 2024 · 6,070 accessesView PDFCite
Research ArticleOpen accessIn the abstractMeasuring Customers’ Satisfaction Using Sentiment Analysis: Model and ToolAhmed Alqurafi, Tawfeeq AlsanoosyCustomer reviews are a valuable data resource for business owners and companies. Customers frequently write reviews on many platforms, such as eBay or Amazon. These reviews show, for instance, to what extent customers are satisfied with a service or a product. Therefore, these reviews can be used by companies and business owners to improve their services or products. However, numerous … …Journal of Computer Science, Vol. 20, Issue 4 · 7 Feb 2024 · 6,471 accessesView PDFCite
Research ArticleOpen accessIn the abstractMachine Learning Oceanographic Data for Prediction of the Potential of Marine ResourcesDenny Arbahri, Oky Dwi Nurhayati, Imam MuditaMarine data and information are very important for human survival, therefore this data and information is attractive to investors because of the potential economic value. This data and information has been difficult to obtain, the solution to overcome this is by analyzing oceanographic data for 2009-2019 collected from the marine database belonging to the Agency for the Study and Application … …Journal of Computer Science, Vol. 20, Issue 2 · 8 Jan 2024 · 5,970 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Conceptual Framework for Efficient and Sustainable Pruning Techniques in Deep Learning ModelsNyalalani Smarts, Rajalakshm Selvaraj, Venumadhav KuthadiThis research paper proposes a conceptual framework and optimization algorithm for pruning techniques in deep learning models, its focus is on key challenges such as model size, computational efficiency, inference speed and sustainable technology development. The aim of the framework is to transition from large neural networks to sparse, efficient models, indicating the benefits of pruning in improving model scalability … …Journal of Computer Science, Vol. 21, Issue 5 · 26 Apr 2025 · 5,268 accessesView PDFCite
Research ArticleOpen accessIn the abstractArtificial Intelligence and Mathematical Modelling-Based Techniques to Improve Social Media MarketingKiran Chaudhary, Mohammad Naquibur Rahman, Nabeela Hasan et al.The Businessperson is using social media to do marketing of their product. Almost all people use social media. Most people relate to social media. Social media marketing is beneficial in making the product more popular and easy ways to introduce the product to everyone in economical ways. In this study, we introduce the concept of machine learning and mathematical models … …Journal of Computer Science, Vol. 21, Issue 1 · 5 Dec 2024 · 5,478 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Analysis of Fraud Detection Methods in Banking Using Machine Learning TechniquesYoussef Tounsi, Ennouri TaziFraud detection in banking requires algorithms that balance classification performance, computational efficiency, and regulatory interpretability, criteria that are rarely benchmarked together. We present a comprehensive evaluation of nine machine learning approaches (Logistic Regression, Decision Tree, Random Forest, SVM, SGD, XGBoost, CatBoost, LightGBM, and MLP) across three datasets differing in size, imbalance severity, and feature type (synthetic, real-world PCA-anonymized, and large-scale … …Journal of Computer Science, Vol. 22, Issue 6 · 22 Jun 2026 · 1,341 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnalysis of Student Mental Health Dataset Using Mining TechniquesYemima Monica Geasela, Devi Yurisca Bernanda, Johanes Fernandes Andry et al.This study utilizes a decision tree model in RapidMiner to analyze a dataset from Kaggle, comprising 200 student records. Among these, 70 students reported mental health issues, while 130 did not. Strikingly, a significant majority of 58 out of the 70 students with mental health concerns do not seek assistance from professionals. This study underscores the pressing issue of underutilization … …Journal of Computer Science, Vol. 20, Issue 1 · 22 Dec 2023 · 6,963 accessesView PDFCite