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34 articles for “multiple regression method”
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Heavy Metal Exposure in Industrial Workers of Punjab
Abstract: Background: Particularly for those in sectors such textiles, metallurgy, and electronics, heavy metal exposure in industrial environments is a major health issue. A range of negative health effects can result from metal exposure including lead (Pb), cadmium (Cd), chromium (Cr), arsenic (As), and nickel (Ni), including neurological, pulmonary, and renal ones. There is little information available on the degree of heavy metal exposure industrial workers in Punjab, India experience. Objective: …
Published in Research and Reviews: A Journal of Toxicology · Vol. 15, Issue 3, 2025 · pp. 1–7 Read article
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Evaluating an ai-supported experiential learning intervention: a quasi-experimental study of the joyful saturday model for student engagement and holistic development
Abstract: Student disengagement, declining academic motivation, and passive classroom participation remain major challenges in modern higher education systems. Traditional lecture-based teaching methods often fail to accommodate diverse learning styles and do not sufficiently promote active participation or collaborative learning. To address these challenges, the present study evaluates the effectiveness of Joyful Saturday, a structured experiential learning initiative designed to improve student engagement, motivation, and holistic development through interactive academic activities supported …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 1, 2026 · pp. 79–88 Read article
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A Comprehensive Investigation of Bagging-Based Ensemble Methods for Improving Machine Learning Model Robustness
Abstract: Machine learning models such as Decision Trees, Logistic Regression, and K-Nearest Neighbors are widely used for classification tasks due to their simplicity and interpretability. However, these models often suffer from high variance, overfitting, and poor generalization when applied to real-world datasets, particularly those that are small, noisy, or imbalanced, as commonly encountered in healthcare, finance, and cybersecurity applications. To address these limitations, this research proposes a Bagging (Bootstrap Aggregating)-based ensemble …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 24–34 Read article
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Aerodynamic Optimization of UAV Wings Using Machine Learning
Abstract: Unmanned Aerial Vehicles (UAVs) are increasingly deployed across defense, transportation, agriculture, and environmental monitoring, demanding improved aerodynamic efficiency to enhance endurance, stability, and payload capacity. Traditional aerodynamic optimization approaches, relying on computational fluid dynamics (CFD) simulations and wind tunnel experiments, are often time-consuming and computationally expensive. This study proposes a machine learning (ML)-driven framework for the aerodynamic optimization of UAV wing geometries, aiming to significantly reduce design cycles while improving …
Published in International Journal on Drones · Vol. 2, Issue 1, 2026 · pp. 1–7 Read article
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Workplace Violence against Women (WPVAW): The Experience among Healthcare Providers in Nigeria
Abstract: Background: Across the world today, the workplace just like any other public space a woman could find herself has become a place where the woman folk get abused by all categories of people they come in contact with, be it colleagues, service consumers, their relations amongst others.Aim: The study was aimed at assessing the prevalence of workplace violence against women, severity and perpetrators of abuse among healthcare providers in the …
Published in Research and Reviews: A Journal of Health Professions · Vol. 8, Issue 1, 2018 · pp. 42–46 Read article
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A Study to Assess the Risk Factors Associated with Sudden Death in Population on Hemodialysis
Abstract: Background: Patients with chronic kidney disease (CKD) receiving maintenance hemodialysis (HD) experience disproportionately high mortality, with sudden death remaining a leading cause. Multiple clinical, biochemical, and care-related factors influence outcomes, yet comprehensive risk stratification models and the role of dialysis timing and early nephrology care remain inadequately explored in resource-limited settings. Objectives: This study aimed to (i) identify clinical and biochemical risk factors associated with mortality in HD patients, (ii) …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 16, Issue 1, 2026 · pp. 14–19 Read article
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Assessment and Associated Factors of Adjustment Disorder with Mixed Depression and Anxiety of Hospitalized Patients with Pandemic Disease, COVID-19 in Ethiopia, East Africa, 2020
Abstract: AbstractBackground: Globally, the 2019 coronavirus disease (COVID-19) pandemic has raised international concern. According to world meters report, 4,545,167 cases, 1,715862 recoveries, 303,847 deaths and spread to 213 countries, and significant number increasing from day to day since December 2019. Mental health is becoming an issue that cannot be ignored in our fight against it. This study aimed to explore the prevalence, and factors linked to anxiety and depression in hospitalized …
Published in Research and Reviews: A Journal of Health Professions · Vol. 10, Issue 2, 2020 · pp. 57–65 Read article
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Impact of Anxiety and Affect on Quality of Life among Youth
Abstract: Youth well-being is an important phenomenon comprising physical, psychological, and social health, where the psychological factors such as anxiety and affect play an essential role in determining Quality of Life (QOL). Young people experience multiple transitions and they are at risk of anxiety disorders that in turn can have adverse effects on academic achievement, physical health, emotional well-being and relationships. Furthermore, affect has a role in the management of emotions …
Published in International Journal of Education Sciences · Vol. 3, Issue 1, 2026 · pp. 1–13 Read article
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An Innovative Approach to Find the Optimum Lubricant for Diverse Applications Based on Scikit-Learn Library Using Python
Abstract: This paper presents an innovative approach for finding the optimum lubricant using the Scikit-learn library in Python. The proposed approach uses a linear regression model to analyze a dataset of lubricant properties and performance, specifically the viscosity, wear, and friction. The model is trained on the dataset to predict the wear and friction for a given viscosity, which can be used to identify the optimum lubricant. By analyzing a dataset …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 25–35 Read article
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Prevalence and Factors Associated with Overweight/Obesity in Public Servants, Tigray, Ethiopia: The Case of Mekelle City
Abstract: Introduction: Noncommunicable diseases (NCDs) remain the major causes of mortality. In Africa and sub-Saharan countries prevalence of NCDs is rising due to many reasons. About 80% of deaths due to NCDs are common in low and middle-income countries including Ethiopia. Overweight and obesity are leading risk factors for a number of chronic NCDs. Objective: The aim of this research was to estimate the magnitude and factors associated with overweight/obesity among …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 7, Issue 3, 2018 · pp. 39–46 Read article
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Passenger car fuel economy: Insights from big data analytics
Abstract: The increasing availability of real-world vehicle telematics through On-Board Diagnostics II (OBD-II) systems has enabled data-driven evaluation of passenger car fuel economy beyond conventional laboratory-based test cycles. While standardized certification procedures ensure repeatability, they often fail to capture the influence of real-world traffic conditions, driver behaviour, and transient vehicle operation. This study presents a structured Big Data Analytics (BDA) approach for analysing high-frequency OBD-II data collected from a gasoline passenger …
Published in Journal of Automobile Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 9–21 Read article
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Comparison of Models of Machine Learning and Hyperparameter Optimization Methods on Various Datasets
Abstract: The most likely phase in achieving powerful and robust machine learning models is probably the hyperparameter tuning step. The traditional exhaustive methods of search (grid search and others) ensure that the search space is covered, but are computationally inexpensive; random search is less expensive and can still miss good regions; and lastly, the modern model-based and population-based methods (Bayesian optimization, tree-structured Parzen estimator (TPE), genetic algorithms) are thought to provide …
Published in Recent Trends in Programming languages · Vol. 13, Issue 1, 2026 · pp. 35–42 Read article
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Real-Time Cab Fare and ETA Prediction Using API Integration
Abstract: The exponential proliferation of ride-hailing platforms has necessitated the formulation of sophisticated and highly responsive predictive models for cab fare estimation and estimated time of arrival (ETA) computation. This work elucidates a robust framework leveraging real-time application programming interface (API) integration from Uber and Ola within a Flutter-based ecosystem to enhance predictive analytics. By assimilating real-time geospatial data, dynamic pricing algorithms, and latency-optimized API responses, this study investigates the empirical …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 08–15 Read article
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Machine Learning-Assisted Design and Optimization of Lightweight Polymer Composites for IoT-Enabled Automotive Applications
Abstract: This study aims to develop an integrated machine learning and optimization framework for the intelligent design of lightweight polymer composites suited for IoT-enabled automotive applications. The goal is to enhance material performance while satisfying multiple design constraints such as mechanical strength, thermal stability, and process compatibility. A curated dataset of polymer composite formulations was used to train a Random Forest Regression (RFR) model capable of predicting tensile strength, thermal conductivity, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 12–27 Read article