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205 articles for “forest”
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Integrative Machine Learning Approaches for Predicting the Rheological Behaviour of Soft Magnetorheological Elastomers
Abstract: Magnetorheological Elastomers (MREs) are advanced composite materials known for their ability to alter mechanical properties under external magnetic fields, making them highly valuable in adaptive damping systems, vibration control, and smart devices. The accurate prediction of rheological behavior in soft MREs remains a significant challenge due to the complex interplay between material composition and magnetic fields. To address this challenge, this study employs a multi-pronged approach that integrates traditional material …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 1083–1096 Read article
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A Hybrid Machine Learning Approach for Cardiovascular Disease Prediction
Abstract: Heart disease ranks among the top causes of death globally. Accurately predicting cardiovascular conditions has become a key challenge in the realm of clinical data analysis. It has been shown that machine learning is an effective means of assisting with predicting and decision-making based on the large volume of data produced by the medical industry. In this study, we describe a unique approach that increases the prediction accuracy of heart-related …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 69–75 Read article
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A Survey of Several Machine Learning (ML) Algorithms for Security Solution in Internet of Things (IoT) Networks
Abstract: The Internet of Things (IoT) refers to the integration of physical objects with the Internet, allowing for connectivity and monitoring. This idea has garnered immense attention from researchers and users alike, driven by the widespread accessibility of the Internet. It spans a wide range of devices, including smart versions of conventional appliances, innovative tools tailored for Internet-enabled ecosystems, and sensors that leverage connectivity to revolutionize industries such as manufacturing, healthcare, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 1–11 Read article
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Identification and Prioritization of Critical Erosion Prone and Water Potential Areas of Manandragarh Watershed Using HEC-HMS for Management
Abstract: This study was carried out at Indira Gandhi Krishi Vishwavidyalaya, Raipur (CG) on hydrological modelling and development of soil and water conservation plan for critical erosion prone and water potential sub-watersheds of Manendragarh watershed of upper Hasdeo subbasin in Chhattisgarh using Hydrological Engineering Centre-Hydrological Modelling System (HEC-HMS). The Hydrological Engineering Centre-Geo Hydrological Modelling System (HEC-Geo HMS) was utilized for developing the model setup, while the HEC-HMS model was employed to …
Published in Research & Reviews : Journal of Ecology · Vol. 14, Issue 1, 2025 · pp. 26–44 Read article
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IoT-based Heart Attack Prediction System Using Machine Learning
Abstract: Heart disease, particularly heart attacks, is one of the leading causes of mortality worldwide. Timely detection and prompt intervention play a vital role in significantly improving the survival rates of individuals at risk of cardiac events. Unfortunately, most traditional healthcare systems are not equipped with mechanisms for continuous, real-time monitoring of patients' cardiovascular health. This limitation makes it extremely difficult for healthcare providers to identify warning signs early enough to …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 2, 2025 · pp. 1–5 Read article
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Statistical Models for Predicting Genetic Variability and Disease Susceptibility
Abstract: Differences in genetics are key to understanding why some individuals are more prone to certain diseases than others. Recent advancements in genomic research, combined with statistical modeling techniques, have made significant strides in predicting disease risk based on genetic factors. This review explores the application of statistical models for predicting genetic variability and their role in disease susceptibility. We discuss traditional methods like linear regression and genome-wide association studies (GWAS), …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 30–34 Read article
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Atmospheric Boundary Layer Processes: Impacts on Weather Patterns and Climate Change
Abstract: The atmospheric boundary layer (ABL) is a vital component of the Earth's climate system, acting as the interface between the terrestrial surface and the overlying atmosphere. This layer, typically extending from the surface to a height of a few hundred meters, is characterized by strong gradients in meteorological variables such as temperature, humidity, wind speed, and atmospheric pressure. Understanding the dynamics of the ABL is essential for comprehending weather phenomena, …
Published in International Journal of Atmosphere · Vol. 1, Issue 2, 2024 · pp. 22–25 Read article
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Diversity and Sustainability: The Role of Traditional Fruit Trees in Uttarakhand Agricultural Landscape
Abstract: Uttarakhand state is characterized by a rich diversity of traditional fruit trees. Uttarakhand is largely a mountainous state, with only around 10% of its overall geographical area being plains, and more than three-quarters (78%) of its total people relying on agriculture for survival. The state's geographical features and climatic circumstances are suited for growing temperate and subtropical fruit crops. It provides a variety of agro-geoclimatic conditions that are ideal for …
Published in International Journal of Land · Vol. 1, Issue 2, 2024 · pp. 22–25 Read article
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Greenhouse Gas Emissions, Land Use, and Sustainable Natural Resource Management: A Review
Abstract: Greenhouse gas (GHG) emissions, changes in land use, and the exploitation of natural resources are significant obstacles to achieving global sustainable development goals. These interconnected challenges have far-reaching implications for environmental stability, economic growth, and societal well-being.Urbanization, deforestation, and agriculture are examples of land use activities that significantly increase greenhouse gas emissions. Agricultural activities release methane and nitrous oxide, while deforestation leads to carbon dioxide emissions by reducing forest cover, …
Published in International Journal of Sustainability · Vol. 2, Issue 1, 2025 · pp. 7–11 Read article
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Enhancing Credit Card Fraud Detection Using Device Fingerprinting and Behavioral Biometrics
Abstract: Credit card fraud is a growing global concern, with financial losses projected to reach $ 43.47 billion by 2028. Credit card fraud poses a major challenge in the financial industry, resulting in substantial financial losses and security risks. This research introduces a Machine Learning-based Credit Card Fraud Detection System designed to improve the accuracy of fraud identification. Due to the imbalanced nature of fraud datasets, SMOTE (Synthetic Minority Over-sampling Technique) …
Published in Journal Of Network security · Vol. 13, Issue 2, 2025 · pp. 40–50 Read article
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Cucumis Sativus: A Review
Abstract: The family Cucurbitaceae includes the cucumber (Cucumis sativus L.). 30 species of Cucumis are distributed in Africa and Asia. One of the first vegetables to be farmed, cucumbers are native to the tropics. It has almost 3,000 years of historical documentation (Yawalkar, 1985). Widespread cultivation of Cucumis sativus (CS) is found in Bangladesh (including the Chittagong Hill Tracts, Gazipur, Sherpur, Cox's Bazar, Tangail, and other forests), the Indian subcontinent, and …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 15, Issue 2, 2025 Read article
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Prediction of Customer Churn Using Machine Learning Classification Models
Abstract: Customer churn prediction is a critical task in both the telecommunication and medical industries, where retaining customers or patients is essential for ensuring long-term profitability and maintaining high-quality service. To address this, a range of machine learning models—including logistic regression, decision trees, random forests, gradient boosting machines, and support vector machines—were employed to accurately forecast churn behavior. Prior to model training, the dataset underwent thorough preprocessing, which included handling missing …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 86–92 Read article
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ML-Based Predictive Modeling of Mechanical Properties in 3D-Printed Polymer Composites for IoT Applications
Abstract: This study aims to develop an interpretable and high-accuracy machine learning framework for predicting the mechanical properties of 3D-printed fiber-reinforced polymer composites, with a focus on structure–property correlations relevant to polymer processing and functional performance. Composite specimens based on PLA and ABS matrices were fabricated using FDM with varying weight fractions (5–20 wt%) of carbon and glass fibers. Standardized mechanical testing (ASTM D638, D256, D790) was performed to evaluate tensile …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 61–78 Read article
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Transformer Health Monitoring System
Abstract: Rising demands for reliable and efficient power distribution in modern electric control grid increasingly call up for robust monitoring systems for critical substructure. Being a vital part of the power conduction system, transformer are subjected to mechanical, electrical, and environmental stresses, which, if not properly controlled, can cause failures. In this project, we propose a Transformer Health Monitoring System (THMS) using machine learning (ML) models and real-time monitoring method to …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 1–9 Read article
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Eye Disease Classification Using K-means Clustering Algorithm and Ensemble Classification Approach
Abstract: In this study, we present a comprehensive approach for the classification of eye diseases, specifically targeting normal, cataract, glaucoma, and diabetic retinopathy conditions. This research uses a dataset from Kaggle, which provides a wide and varied collection of retinal images to ensure good representation. The methodology encompasses advanced image processing and machine learning techniques to ensure accurate diagnosis and prediction. The preprocessing phase involves a series of image enhancement techniques …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 2, 2025 · pp. 15–27 Read article
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Machine Learning Approach to Predict the Performability and Emissions of Diesel Engine Fueled with Doped Biodiesel Blend
Abstract: Enhancing the performability and emission characteristics of diesel engines has been a difficult task in light of growing concerns about global warming and other negative effects, as diesel accounts for 70% of global energy demand. In this study, engine performance and exhaust emissions for various fuel blends were thoroughly evaluated using machine learning techniques to predict engine emission and performance behavior. We focused on biodiesel blend and nanoparticle additive concentration …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 1, 2025 · pp. 1–12 Read article
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Analyzing the Role of Fiber Composition in Drying Behavior: A Comparative and Predictive Approach
Abstract: This research presents a comprehensive analysis of the drying behavior and thermal response of three distinct fabric types: 100% Cotton, 100% Polyester, and a Polyester blend (65/35), under meticulously controlled environmental conditions. The Polyester blend (65/35) consists of 65% Polyester and 35% Cotton, combining characteristics of both fibers. The investigation focuses on understanding how fiber composition impacts drying time, moisture retention, and thermal characteristics. Experimental trials were conducted using standardized …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 1–11 Read article
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Controlling Animals and People Near Railway Tracks Using the Internet of Things
Abstract: A lot of people are opting to use the train instead of the bus now as bus tickets have become so expensive. In order to keep the railroad network running well, it is necessary to constantly inspect and monitor the tracks. Till now, the train track inspection process and monitoring system are done manually, which is laborious and wasteful since human error is likely to happen at any point. Because …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 2, 2025 · pp. 01–10 Read article
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Optimizing Mechanical and Durability Properties of Eco-Friendly Composite Materials Using Recycled Fillers and ML Techniques
Abstract: The increasing demand for sustainable construction materials has intensified the exploration of recycled fillers as partial or full replacements for natural aggregates in composite materials. This study investigates the mechanical and durability performance of polymer matrix composites incorporating processed recycled fillers derived from construction and demolition (C&D) waste. Three distinct processing methods were employed to prepare the recycled fillers: untreated (URF), single processed (SPRF), and double processed (DPRF), with replacement …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 269–309 Read article
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Tribological Performance and Wear Coefficient Prediction of AA2024–TiC Composites via Python-Based Machine Learning
Abstract: Determining wear coefficient accurately serves as a critical factor to maximize engineering materials' tribological characteristics. The experiment examines the wear characteristics of TiC-reinforced AA2024 aluminum alloy subjected to different tribological operating conditions. A pin-on-disc tribometer performed wear tests under different conditions of load and TiC weight fraction and sliding speed and duration. ANOVA statistical results show that load intensity and TiC reinforcement density stand out as principal variables that affect …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 1099–1112 Read article