Research ArticleOpen accessAll words, across the recordIoT-Based Smart Hydroponic System for Nutrient Management Using Predictive Machine Learning AlgorithmsPalash Gourshettiwar, K. T. V. ReddyHydroponics, an efficient cultivation method, benefits significantly from the precision and adaptability that Machine Learning (ML) algorithms can offer, along with the real-time monitoring facilitated by the devices using the Internet of Things (IoT). This study summarises the latest research and discusses how Machine Learning and the IoT work together, focusing on nutrient optimization, plant development, and resource efficiency. The … …Journal of Computer Science, Vol. 22, Issue 3 · 11 Mar 2026 · 3,046 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordComparative Analysis of Laboratory Measured and PVTP Software DataOluwasanmi Samuel Teniola, Mercy Isaiah OkegbemiCubic Equations of State (EOS), including the Peng-Robinson (PR) and Soave-Redlich-Kwong (SRK) models, are foundational in petroleum engineering for modeling the thermodynamic behavior of hydrocarbon systems. These EOS are widely used to predict phase behavior and Pressure-Volume-Temperature (PVT) properties, which are crucial for reservoir simulation, production forecasting, and enhanced oil recovery. However, their predictive accuracy diminishes when applied to complex … …American Journal of Engineering and Applied Sciences, Vol. 18, Issue 1 · 20 Dec 2025 · 2,761 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordEarly Diagnosis of Parkinson's Disease Through Voice Analysis and Machine LearningAmrita Naik, Mohd Sahil Khan, Akhilesh Manoj Saraf et al.Parkinson’s Disease (PD) is a progressive neurological disorder, and its prevalence has increased considerably in recent years. Early and accurate diagnosis plays a crucial role in effective treatment, but identifying the disease in its early stages remains challenging, especially for non-specialist clinicians. This study presents a predictive analytics framework for detecting Parkinson's disease using voice-based features. To improve the diversity … …Journal of Computer Science, Vol. 22, Issue 11 · 9 Oct 2026 · 637 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordExplainable MedAttn-ResNet50 for Automated Kidney Tumor Classification from CT Images With Grad-CAM VisualizationD. Vetrithangam, Pramod Kumar, Shilpasree S. et al.Kidney tumor classification from CT imaging remains challenging due to CT-specific intensity variations, tumor heterogeneity, and limited clinically meaningful interpretability in existing deep learning models. To address these limitations, we propose an Explainable MedAttn-ResNet50 framework that integrates radiology-driven preprocessing, multi-scale feature extraction, and medical attention mechanisms within a unified architecture. The preprocessing pipeline applies radiology-inspired intensity normalization, contrast enhancement, and … …Journal of Computer Science, Vol. 22, Issue 8 · 13 Aug 2026 · 1,120 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordAnchoring Public Health Forecasts: High-Precision Obesity Prevalence Estimation Via Hybrid Geodemographic Ensemble RegressionTrenton Ward, Isaac OsunmakindeObesity remains a major driver of chronic disease and rising healthcare costs in the United States. Yet, most existing predictive models rely on single-model classifiers and rarely incorporate spatial structure or ensemble-based regression, thereby limiting their ability to capture geodemographic variation. This study introduces a hybrid unsupervised–supervised ensemble framework that integrates K-Means spatial profiling with a Stacking Regressor to address … …Journal of Computer Science, Vol. 22, Issue 7 · 31 Jul 2026 · 632 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordAnalyzing Temperature-Dependent Thermal Properties of Biomaterials Using Machine Learning MethodsArmaghan Shalbaftabar, Kristen Rhinehardt, Dhananjay KumarThis research utilizes machine learning models ANN, Random Forest, and Decision Tree to predict material properties of Ti-based biomaterials, including Young’s modulus, density, thermal conductivity, and specific heat at various temperatures. Data was sourced using web scraping and Plot Digitizer, validated against literature, and analyzed in Excel. The ANN model achieved strong performance, with R² = 0.980874 for TiAl and … …American Journal of Engineering and Applied Sciences, Vol. 18, Issue 1 · 12 Sep 2025 · 4,634 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordComparative Analysis on Prediction of Chronic KidneyDisease by various Machine Learning ModelsNikhil Verma, Tripti Sharma, Bobbinpreet Kaur, Ayush DograChronic Kidney Disease (CKD) is a prevalent global healthconcern, which is affecting a number of people in the whole world. Earlydetection & precise checking of CKD are really important for essentialsupervision & intervention to prevent disease progression and associatedcomplications. Machine learning (ML) models have emerged as favourabletools for CKD detection due to their ability to analyse complex data patternsand provide … …Journal of Computer Science, Vol. 21, Issue 6 · 24 May 2025 · 5,939 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordIntelligent Identification and Sorting of Chinese Herbs Recommend a String-Level Predictive Electromechanical SystemWenyi Zhang, Gang Wang, Xiaofei Xu et al.Based on the analysis of a large number of Chinese medicinal materials, a mobile robot visual function research and development experimental domestic chips electromechanical arm-controller, which was constructed using a typical kernel algorithm recommended by Chinese medicinal materials visual recognition, which the cascade Electromechanical Control System was based on iterative learning electromechanical control for multi-joint manipulators. The original and improved … …American Journal of Biochemistry and Biotechnology, Vol. 20, Issue 2 · 11 Jul 2024 · 4,273 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordComparative Analysis of the Efficacy of Landslide Susceptibility ModelsJordan Henrique de Souza, Gislaine dos Santos, Gabriela Guimarães Gouvêa de Oliveira et al.This research aims to analyze the efficacy of SHALSTAB, IPT, SAGA, SMORPH and modified SMORPH models in evaluating landslide susceptibility. Statistical analysis concerning both the efficacy of the models in the prediction of landslide risks and the concordance between the models according to landslide occurrence or non-occurrence was performed. For this work, logistic regression, Receiver Operating Characteristic (ROC) curves, Kappa … …American Journal of Environmental Sciences, Vol. 15, Issue 3 · 31 May 2019 · 8,839 accessesView PDFCite
Review ArticleOpen accessAll words, across the recordA Systematic Review Regarding the Prediction of Academic PerformancePercy De-La-Cruz, Rommel Rojas-Coaquira, Hugo Vega-Huerta et al.The prediction of students' academic performance is an area of great concern for universities and educational institutions since academic performance is one of the most important aspects of the learning process. To analyze this behavior, this study makes a critical analysis of the topic of interest and aims to review, analyze and summarize the latest research advances related to the … …Journal of Computer Science, Vol. 18, Issue 12 · 23 Dec 2022 · 8,602 accessesView PDFCite