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160 articles for “trees”
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Experimental Investigation and Surface Morphology Study on Areca Fiber Composite Material
Abstract: Composites manufactured from areca fibers had their characteristics assessed in recent research. Shape and size were determined by cutting the stem. It takes six months to dry the fibers once they are taken from the tree stem. Because pectin, cellulose, hemicellulose, and lignin make up the bulk of it. It has great regeneration capacity and is a resource material made of wood fibers. The untreated and chemically treated fibers are …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 459–468 Read article
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Low-cost Feed Resources for Sustainable Dairying: Exploring Conventional, Agro-Industrial, and Non-Conventional Feeds to Optimize Nutritional Adequacy
Abstract: This study explores the potential of cost-effective feed resources to enhance the sustainability of dairy farming by focusing on conventional, agro-industrial, and non-conventional feed alternatives. Rising feed costs remain a significant challenge =124ed5y7u-8 n dairy production, and optimizing feed efficiency is crucial for maintaining profitability and sustainability. Conventional feed resources, including roughages and pastures, provide the foundation for dairy cow diets, yet their nutritional content varies seasonally and geographically. Agro-industrial …
Published in Research & Reviews : Journal of Ecology · Vol. 14, Issue 2, 2025 · pp. 11–27 Read article
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Harnessing Hydrolgeological Parametrs: Prediction of Water Probability and Levels for Water Well Construction Using Ai-Enabled Models
Abstract: The AI-Based Decision Support System for Water Well Construction utilizes data from the National Aquifer Mapping and Management System (NAQUIM) and employs advanced AI techniques like regression analysis, decision trees, and neural networks. This system predicts crucial parameters for water well construction, including location suitability, water-bearing zone depths, and groundwater quality. By integrating large datasets such as lithology, geophysical logs, and aquifer maps provided by the Central Ground Water Board …
Published in Journal of Water Resource Engineering and Management · Vol. 12, Issue 1, 2025 · pp. 16–28 Read article
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Machine Learning-Based Approach for Heart Disease Prediction
Abstract: Heart disease is a significant global health challenge, with early diagnosis and prediction being essential for reducing mortality rates. Machine Learning (ML), an efficiently developing field within Artificial Intelligence, provides innovative methods for analyzing complex clinical data to predict heart disease. This review examines the basic machine learning techniques, data, and metrics used in cardiovascular disease prediction. It explores the role of supervised learning, such as decision trees and logistic …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 64–73 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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Implementing Machine Learning in Data Classification
Abstract: Data classification forms an essential aspect of artificial intelligence (AI) and soft computing, helping a great deal in the transformation of raw data into knowledge that forms the basis of numerous applications, such as fraud detection, medical diagnostics, and natural language processing. This study discusses the challenges and the state of the art in data classification, as far as scalability, noise handling, and feature selection optimization are concerned. It gives …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 2, 2025 · pp. 15–22 Read article
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Development and Evaluation of Sodium Hydroxide-Treated Jujube Pit Reinforced Epoxy Composites
Abstract: The automotive sector has experienced a tremendous transformation, propelled by the increasing demand for materials that provide a balance between mechanical performance, economic efficiency, and environmental sustainability. In accordance with worldwide sustainability goals, the trend has moved toward the utilization of lightweight, recyclable, and biodegradable materials in modern vehicle architecture. Natural composite materials, which are derived from renewable resources such as seeds, leaves, and tree barks, have gained considerable attention …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 494–501 Read article
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Computer Aided Diagnosis of Breast Cancer using Machine Learning Techniques
Abstract: Breast cancer is one of the significant health problems that lead to early mortality in women, especially those between 40 and 55 years of age all over the world. In recent years, the number of breast cancer cases among women has risen significantly, making early and accurate diagnosis more important than ever. Computer-aided diagnostic (CAD) tools have become valuable in supporting radiologists by enhancing the precision of breast cancer detection. …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 27, Issue 2, 2025 · pp. 1–11 Read article
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Neurodevelopmental Effects of Cell Tower Radiation in Children: A Longitudinal Study
Abstract: This study investigates the impact of radiation exposure from cell phone towers on the neurodevelopmental outcomes of children aged 0–5 years. A prospective cohort approach was employed to assess key developmental parameters, including Gross Motor Skills, Fine Motor Skills, and sleep disorders. Given the increasing presence of wireless communication infrastructure, understanding its potential effects on early childhood development is crucial for public health.To analyze the collected data, advanced machine learning …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 2, 2025 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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Automated Fault Identification and Tracking in Power Transmission Networks Using GPS
Abstract: Power transmission lines are vulnerable to faults caused by environmental factors, aging infrastructure, and external disturbances such as falling trees or animal contact. Prompt and accurate detection and location of these faults are essential to ensure uninterrupted power delivery, reduce equipment damage, and minimize downtime. This project presents an automatic fault detection and location system using GPS technology integrated with a microcontroller-based sensing module. The proposed system continuously monitors voltage …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 37–43 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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AI for Cybersecurity: Deploying Machine Learning for Network Traffic Anomaly Detection
Abstract: The growing sophistication of cyberattacks and the growth of network traffic necessitate sophisticated anomaly detection methods. This study overviews the use of artificial intelligence (AI) and machine learning (ML) to counter these challenges, as noted in current studies. It analyses supervised learning (SVM, Decision Trees), unsupervised learning (K-means, DBSCAN), and deep learning (CNNs, RNNs, Auto-encoders) approaches, considering their strengths and weaknesses. The research integrates current developments in AI/ML-based network anomaly …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 2, 2025 · pp. 1–10 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
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Heat Stress Mitigation in Resource-Constrained Dairy Farming Systems: Practical Strategies for Sustainable Development
Abstract: Heat stress poses a critical threat to dairy production, particularly in resource-constrained systems prevalent across tropical and subtropical regions. Elevated ambient temperatures, compounded by high humidity, directly impair feed intake, milk yield, reproductive efficiency, and overall animal welfare. In low-resource settings, conventional cooling technologies such as automated fans, sprinklers, and climate-controlled housing remain economically inaccessible. Therefore, cost-effective, locally adaptable, and sustainable solutions are essential for maintaining productivity and animal health. …
Published in International Journal of Climate Conditions · Vol. 2, Issue 2, 2025 · pp. 1–12 Read article
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A Machine Learning Approach to Forecasting Outcomes in Limited Overs Cricket
Abstract: This study explores the application of machine learning techniques to forecasting outcomes in limited overs cricket matches, with a particular focus on One Day Internationals (ODIs). The research investigates how classification algorithms can be effectively utilized to analyze both contextual and dynamic factors that influence match results, including venue details, toss decisions, team strength, and historical performance records. By employing a structured methodology encompassing feature selection, data preprocessing, model training, …
Published in Recent Trends in Sports · Vol. 2, Issue 2, 2025 · pp. 09–19 Read article
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A Comprehensive Analysis of Classification Methods for Churn Prediction in Financial Services
Abstract: Persistent issues that affect long-term revenue in the banking sector include excessive client attrition. Customary churn models depend on measures related to customer satisfaction, which often result in low predictive accuracy due to their subjective nature. This study proposes an effective early warning model to address customer churn in financial services. Data is preprocessed through cleaning, one-hot encoding, Z-score normalization, and Min-max scaling. To handle class imbalance, the SMOTE algorithm …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 2, 2025 · pp. 47–61 Read article
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Ramifications of Industrial Pollution: Problems and Ways to Fix Them
Abstract: Pollution from industry is still one of the largest environmental challenges of the 21st century. It hurts the air, water, and land all around the world. This page discusses about the primary kinds of pollutants that arise from factories, such as heavy metals, particles, and toxic chemicals. It studies at how industrial emissions affect people and the environment, such as by causing respiratory problems, harming ecosystems, and changing the climate. …
Published in International Journal of Pollution: Prevention & Control · Vol. 3, Issue 2, 2025 · pp. 1–5 Read article
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Extraction, Stability, and Application of Natural Dye from Spathodea campanulata Flower: A Study on Shelf Life, Yield, and Fabric Dyeing Potential
Abstract: The growing demand for sustainable and eco-friendly alternatives to synthetic dyes has led to increased interest in natural dye sources. Spathodea campanulata, commonly known as the African Tulip Tree, is a potential source of natural dye due to its vibrant floral pigments. This study focuses on the extraction, yield, stability, and application of the dye obtained from Spathodea campanulata flowers. The dye was extracted using an aqueous method, and its …
Published in Research & Reviews : Journal of Botany · Vol. 14, Issue 3, 2025 · pp. 8–15 Read article
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An Integrated Autonomous Rover-Drone System for Intelligent Exploration and Environmental Monitoring
Abstract: This paper presents a hybrid autonomous exploration platform integrating a ground rover and aerial drone, enhanced by swarm intelligence and a custom-trained YOLO V8 object detection model. The rover is equipped with GPS, IMU, and environmental sensors (DHT11, MQ135, BMP180), while the drone performs real-time aerial mapping and obstacle prediction. A YOLO V8 model, trained on 500 annotated terrain images (six classes: rocks, pits, trees, water, animals, vegetation), achieves a …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 2, 2025 · pp. 43–61 Read article