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Research ArticleOpen accessIn the abstractA Study on Factors Influencing MBA Decision After Bachelor’s Using Hybrid Model Combining ANN With Principal Component AnalysisKittipol Wisaeng, Benchalak MuangmeesriThis study comprehensively examines the complex relationship between various individual characteristics and individuals’ expectations after obtaining a bachelor’s degree, particularly in determining whether to pursue a Master of Business Administration (MBA). Utilizing a well structured, hypothesized framework, we examine several key variables directly influencing this critical decision-making process. The examined variables include, but are not limited to, demographic information, academic … …Journal of Computer Science, Vol. 21, Issue 9 · 13 Oct 2025 · 2,247 accessesView PDFCite
Research ArticleOpen accessIn the abstractCrop Yield Prediction in Niger Using Machine Learning TechniquesMahaman Lawali Inoussa Garba, Naroua Harouna, Chaibou Kadri et al.Agriculture is the most impactful sector on Niger's economic growth. Stresses related to climate change and the environment are leading to a continuous decline in crop yield. Accurate crop yield forecasting is of paramount importance for farmers, government, policy makers, and other stakeholders to make most appropriate decisions regarding resource allocation and food security. This study examines the power of … …Journal of Computer Science, Vol. 21, Issue 8 · 16 Sep 2025 · 5,799 accessesView PDFCite
Research ArticleOpen accessIn the abstractEmpirical Study on Modified Pre-Trained CNN Architectures for Fitzpatrick17k Skin Diseases Prediction ModellingSteven Matthew, Nur Afny Catur Andryani, Rojali et al.Preventing missed diagnosis of skin diseases is critical for enhancing patient outcomes. Technology support empowered by AI based algorithms have been recently developed to minimize the burden. Convolutional Neural Networks (CNNs) are increasingly utilized for image classification tasks including skin's diseases prediction modelling. Its advancement architectures such as pre-trained models, VGG16 andResNet50 provide a strong foundation to up-skill the prediction … …Journal of Computer Science, Vol. 21, Issue 7 · 8 Jul 2025 · 3,938 accessesView PDFCite
Research ArticleOpen accessIn the abstractSmart Weather Data Management System for Sustainable Agriculture in Maharashtra Using Machine LearningAishwarya V. Kadu, Kuraparthi Tirumala V. ReddyAgriculture will benefit greatly from efficient weather data sustainable management. Data can be utilized to schedule the prediction yield, crop growth, and irrigation. This paper collects real-time meteorological station data via APIs, primarily focusing on the weather data sustainable management system and data related to Maharashtra Wardha, India, which is involved in a live series period. Agriculture can make potential … …Journal of Computer Science, Vol. 21, Issue 7 · 7 Jul 2025 · 3,516 accessesView PDFCite
Research ArticleOpen accessIn the abstractEcological Function Evaluation of Soil and Water Conservation Measures for Power Transmission and Transformation Project Construction Based on Remote Sensing and it’s Improvement PathYang Han, Songsong Wang, Yanhui Yang et al.Assessing ecological functions is critical for determining the efficacy of soil and water conservation measures, especially during the development of power transmission and transformation projects. Efficient conservation practices are essential for reducing ecological effects and guaranteeing sustainable development. This research aims to create a resilient model, Ecological Function Prediction for Conservation Effectiveness (EFP-CE) that will classify conservation effectiveness as either … …American Journal of Engineering and Applied Sciences, Vol. 18, Issue 1 · 17 Mar 2025 · 7,737 accessesView PDFCite
Research ArticleOpen accessIn the abstractPerformance Prediction Model for Predictive Maintenance Based on K-Nearest Neighbor Method for Air Navigation Equipment FacilitiesRachmat Hidayat, Ditdit Nugeraha UtamaThe aging of air navigation facilities leads to a decline in equipment performance and reliability, posing significant challenges for aviation organizations in the large-scale replacement of outdated systems, as well as in managing budgets and resources. To address these issues, a performance prediction model for equipment was developed using the K-Nearest Neighbor (KNN) method, aimed at enhancing maintenance planning and … …Journal of Computer Science, Vol. 21, Issue 4 · 4 Mar 2025 · 5,661 accessesView PDFCite
Research ArticleOpen accessIn the abstractRandom Forest-Based Genome Analysis for Disease Association and SNP Marker IdentificationXiangdong LiuAt present, genomic data analysis has the problems of insufficient model interpretation and limited computational efficiency in disease association research. As a powerful machine learning algorithm, Random Forest has demonstrated excellent ability in processing complex and multi-dimensional data sets and has gradually become a popular tool in the field of bioinformatics. The purpose of this paper is to explore how … …American Journal of Biochemistry and Biotechnology, Vol. 21, Issue 2 · 25 Jul 2025 · 5,536 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntelliHealth: A Machine Learning Driven Disease Detectionand Diet recommendation SystemAnkita Wadhwan, Priyanka Chawla, Sandeep Kaur, Usha MittalPeople all around the world are afflicted with various ailments. An accurate diagnosis can lower the risk of significant health problems developing, but an inaccurate diagnosis could have adverse implications. In this study, an ensemble-based strategy "IntelliHealth" has been presented to identify disorders of the thyroid, liver, and breast cancer using three machine learning (ML) approaches consisting of Support Vector … …Journal of Computer Science, Vol. 21, Issue 6 · 28 May 2025 · 5,239 accessesView PDFCite
Research ArticleOpen accessIn the abstractXAI_MLPCNN: A Novel Explainable AI-Based Deep Learning Framework for Stress IdentificationFateh Bahadur Kunwar, Rakesh Kumar Yadav, Hitendra Singh, Nitin TripathiOver the past ten years, there has been a lot of emphasis focusedon the development of Artificial Intelligence (AI) and Machine Learning(ML)-based mental health treatments. To increase practitioners' and patients'trust in AI applications, AI systems need to explain their actions. This iscalled Explainable AI (XAI). While significant progress has been achievedin stress prediction models, XAI has not advanced as much. … …Journal of Computer Science, Vol. 21, Issue 5 · 6 May 2025 · 6,173 accessesView PDFCite
Review ArticleOpen accessIn the abstractDeep Learning in Early Alzheimer’s Disease’s Detection: A Comprehensive Survey of Classification, Segmentation and Feature Extraction MethodsRubab Hafeez, Sadia Waheed, Syeda Aleena Naqvi et al.Alzheimer’s disease is a deadly neurological condition, impairing important memory and brain functions. Alzheimer’s disease promotes brain shrinkage, ultimately leading to dementia. Dementia diagnosis typically takes 2.8-4.4 years after the first clinical indication. Advancements in computing and information technology have led to many techniques for studying Alzheimer's disease. Early identification and therapy are crucial for preventing Alzheimer's disease, as early-onset … …Journal of Computer Science, Vol. 21, Issue 5 · 26 Apr 2025 · 5,774 accessesView PDFCite