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Research ArticleOpen accessEvery word in the titleFramework for the Adaptive Learning of Higher Education Students in Virtual Classes in Peru Using CRISP-DM and Machine LearningMaryori Bautista, Sebastian Alfaro, Lenis WongDuring the COVID-19 pandemic, virtual education played a significant role around the world. In post-pandemic Peru, higher education institutions did not entirely dismiss the online education modality. However, this virtual education system maintains a traditional teaching-learning model, where all students receive the same content material and are expected to learn in the same way; as a result, it has not … …Journal of Computer Science, Vol. 20, Issue 5 · 26 Feb 2024 · 5,885 accessesView PDFCite
Review ArticleOpen accessEvery word in the titleHuman Activity Prediction Studies Using Wearable Sensors and Machine LearningDivya Sharma, Usha ChauhanNowadays, Human Activity Recognition (HAR) systems have become so demanding that they find applications in the field of assisted living systems, elderly healthcare systems, smart homes, healthcare monitoring applications, surveillance systems, etc. Due to its increasing demand in computer science; machine learning and deep learning have brought a paradigm shift in the area of sensor-based recognition systems. Providing accurate information … …Journal of Computer Science, Vol. 20, Issue 4 · 14 Feb 2024 · 7,201 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleFuel Prediction Model for Driving Patterns Using Machine Learning TechniquesManjunath TK, Ashok Kumar PSIn recent years, the demand for fuel efficiency has become a crucial aspect of the automotive industry. Predicting fuel economy accurately is essential for optimizing vehicle performance and reducing environmental impact. This proposed model presents a machine learning-based approach for developing a fuel prediction model using the real dataset. The model aims to predict fuel efficiency for different drivers by … …Journal of Computer Science, Vol. 20, Issue 3 · 29 Jan 2024 · 5,480 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleFactors Influencing Student Individual Performance of University XYZ Through the Use of Mobile Learning Management SystemStanley Limonthy, Evaristus Didik MadyatmadjaThis study investigates the impact of unsupervised learning within mobile Learning Management Systems (LMS) on student individual performance at university XYZ, Indonesia. We conducted data collection through online questionnaires distributed to university XYZ students and employed Partial Least Squares Structural Equation Modeling (PLS-SEM) for analysis. Our research extends the information system success model by integrating pedagogical and technological dimensions, specifically … …Journal of Computer Science, Vol. 20, Issue 3 · 27 Jan 2024 · 4,982 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleSecuring Mobile Devices from Malware: A Faceoff Between Federated Learning and Deep Learning Models for Android Malware ClassificationNarayan Subramanian, Logesh Ravi, Mithin Jain Shaan et al.Amidst the escalating threats of android malware, urgency mounts to detect issues while safeguarding user privacy. Traditional machine learning and deep learning methods, dealt with scalability challenges and privacy compromises, finding a potential remedy in federated learning. This study introduces a groundbreaking federated learning-based methodology and compares federated learning with traditional deep learning techniques for Android malware classification, employing renowned … …Journal of Computer Science, Vol. 20, Issue 3 · 23 Jan 2024 · 6,284 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleDeep Transfer Learning Approach for Student Attendance System During the COVID-19 PandemicSlimane Ennajar, Walid BouarifiMarking students' attendance has been a challenge during the COVID-19 pandemic. It is a time-consuming task due to the abnormally high number of students present during a learning session; many studies have been proposed to improve the system. However, there are still issues with each of these systems; we have employed deep transfer learning techniques using six pre-trained convolutional neural … …Journal of Computer Science, Vol. 20, Issue 3 · 16 Jan 2024 · 6,010 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleMachine 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 accessEvery word in the titleLightweight Deep Learning Model for TFT-LCD Pixel Defect Detection Using MobileNetV2J. Sheikshabjan, K. Dhanakodi, A.T. Rajamanickam et al.The proposed methodology aims to achieve high classification accuracy while maintaining computational efficiency and minimizing inference latency, making it highly suitable for real-time industrial inspection scenarios. This study evaluated five traditional transfer learning models (VGG16, ResNet50, MobileNetV2, Xception, and InceptionV3) for comparison in pixel defect detection. MobileNetV2-based implementation demonstrated a competitive average test accuracy of 0.9916, outperforming several baselines while … …Journal of Computer Science, Vol. 22, Issue 8 · 8 Sep 2026 · 673 accessesView PDFCite
Review ArticleOpen accessEvery word in the titleHuman 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 accessEvery word in the titleEnhancing SQL Injection Detection: A Machine Learning Approach Using Network Flow DataP. Vinoth, K. Muthamil Sudar, S. MuthukumarBackground: SQL injection is one of the cyberattacks which occurs in web application vulnerabilities. It targets the poor input validation and enables the attackers to inject malicious queries into the database fields in any application. It will grant access to unauthorized users and data modification, or they will take control over the complete database. To prevent this, there are several … …Journal of Computer Science, Vol. 22, Issue 8 · 18 Aug 2026 · 1,051 accessesView PDFCite