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152 articles for “B-trees”
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Applying Kruskal's Algorithm in Supply Chain Management for Cost-Effective Network Optimization
Abstract: Transportation route optimization and cost reduction are major difficulties in today's dynamic and complicated supply chain systems. To produce economical and effective network designs, this study investigates the use of Kruskal's algorithm for supply chain network optimization. The algorithm guarantees that all supply chain nodes, including delivery hubs, warehouses, and distribution centers, relate to the lowest possible total transportation cost by building the minimum spanning tree (MST). The study shows …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 1, 2025 · pp. 49–54 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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Cloud-driven Fraud Detection: Evaluating Decision Tree and Random Forest Classifiers for Credit Card Transaction Security
Abstract: With the alarming rise in global financial fraud, necessitating substantial annual losses, modern techniques for fraud detection are continuously evolving across various business domains. Fraud detection involves constant monitoring of user activities to estimate, perceive, or prevent undesirable behaviour. Cloud Computing emerges as a promising solution, accelerating application deployment, fostering creativity and innovation, reducing costs, and enhancing overall business acumen. This study introduces a cloud-driven approach to fraud detection, specifically …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 1, 2024 · pp. 13–27 Read article
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A Comprehensive Review on Pharmacological and Therapeutic Uses of Azadirachta Indica in the Treatment of Various Diseases
Abstract: In ancient medicine, the majority of illnesses were treated with plants and phyto-compounds. The most beneficial traditional medicinal plant is Azadirachta indica (Neem). In Ayurveda, it has several therapeutic effects. One of the most adaptable medicinal herbs, it exhibits a broad range of biological action. It possesses medicinal qualities, including anti-microbial, and high efficacy and safety agents. The biologically active components of this plant have a wide range of uses. …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 1, 2025 · pp. 14–25 Read article
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ASSESSING OF FOREST STRUCTURE USING EARTH OBSERVATION DATA: ACASE STUDY IN MUNESSA FOREST, OROMIA REGION, ETHIOPIA
Abstract: Forest structure is essential for estimating forest-related carbon emissions, analyzing forest degradation, and quantifying the effectiveness of forest restoration initiatives. However, forest structure quantification is only limited to the specific area of interest without considering the whole forest coverage. Remote sensing data can easily deliver a large area to assess forest structure. Therefore, this study aims to assess forest structure of Munessa Natural Forest by integrating satellite based light detection …
Published in International Journal of Land Read article
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Electromagnetic and Dielectric Performance of Polymer–Ceramic Composite Substrates for Fractal-Based IoT-Antenna Fabrication
Abstract: Polymer–ceramic composite substrates play a crucial role in determining the electromagnetic performance, mechanical stability, and thermal reliability of radio-frequency devices. In this work, a polymer-based composite substrate is systematically investigated for its suitability in compact IoT and RFID antenna applications. A fractal-structured antenna is employed as a functional test platform to evaluate the dielectric behavior, impedance characteristics, and radiation efficiency of the composite substrate. Novelty of the proposed reader antenna …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1518–1534 Read article
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A Comprehensive Review of Green Hybrid Polymer–Inorganic Composite Systems Incorporating Palm Tree Ash and Titanium Dioxide
Abstract: The increasing requests on sustainable and high performance systems have motivated extensive investigations on polymer-based hybrid systems with bio-derived and/or functional inorganic fillers. In this review, the importance of palm tree ash (PTA) and titanium dioxide (TiO₂) as synergistic fillers for polymer–inorganic hybrid composites, particularly about structure–property relations, interfacial adhesion and durability performance, is discussed. Agricultural waste-derived palm tree ash (PTA) plays as a silica-rich filler which not only aids …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1811–1820 Read article
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Review on Elaeocarpus Ganitrus (Rudraksha)
Abstract: The seed of Elaeocarpus Ganitrus, also known as Rudraksha, is renowned for its electromagnetic characteristics. Recent scientific research has demonstrated that this seed possesses natural electromagnetic properties which can effectively treat various chronic diseases. This study focuses on the phytochemical screening and thin layer chromatographic analysis of the extract obtained from Elaeocarpus Ganitrus seeds, which belong to the Elaeocarpaceae family. Bombay, and is commonly grown as an ornamental tree in …
Published in Research & Reviews: A Journal of Pharmacognosy · Vol. 11, Issue 2, 2024 · pp. 8–15 Read article
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Enhancement in Biomedical Polymer Nanocomposites: Biocompatibility and Mechanical Property Predictions using Machine Learning
Abstract: A machine learning (ML)-based framework is developed and validated through experimental analysis and comparative modeling to enhance system dependability and improve prediction performance. The proposed framework includes key stages such as data preprocessing, feature evaluation, model training, and performance benchmarking to determine the most effective prediction technique. Several machine learning models were evaluated, including Ensemble models, Artificial Neural Networks (ANN), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 275–296 Read article
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Azadirachta Indica: A herbal Panacea in Dentistry– An Update
Abstract: Azadirachta indica better known as Neem, an evergreen tree. It has long been used by the people of India for the treatment of various ailments because of its medicinal properties. It has anti-bacterial, anti-cariogenic, anti-helminthic, anti-diabetic, antioxidant, astringent, anti-viral, cytotoxic, and anti- inflammatory activity. Nimbidin, Azadirachtin and nimbinin are active compounds present in Neem that are responsible for their anti-viral activity. Neem bark is used as an active ingredient in …
Published in Research and Reviews: A Journal of Dentistry 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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E-Commerce Platform for Agricultural Products
Abstract: The e-commerce platform for agricultural products reported here is designed to solve the problems faced by shop owners, such as managing data, billing, and selling products. In many rural areas, awareness of technology is still low. By introducing this project, rural shopkeepers can learn to use new technologies, making their work easier, faster, and more efficient. Our platform specifically targets village shopkeepers, aiming to help them improve profits. It includes …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 2, 2025 · pp. 28–34 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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Optimization of Robotic Path Planning Algorithms for Autonomous Material Handling Systems
Abstract: For autonomous systems for handling materials (AMHS) to operate as efficiently as possible in industrial and logistical settings, robotic route planning is essential. This study examines many robotic route planning algorithms, emphasizing their use, ways of optimization, and difficulties in material handling systems. To improve the effectiveness, precision, and computational viability of these algorithms, the study also examines a number of optimization strategies, including machine learning, parallelization, heuristic search, and …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 2, Issue 2, 2024 · pp. 15–20 Read article
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Risk Assessment of Nitration Process Using HAZOP and Fault Tree
Abstract: The present study addresses the safety issues associated with the nitration reactions. Since the nitration reaction is highly exothermic in nature exhibiting intense heat during the operation and may explode if wrongly handled, the risk assessment of nitration reaction is absolutely necessary. In the present work, the production of Ortho Nitro Chloro Benzene (ONCB) and Para Nitro Chloro Benzene (PNCB) is considered to perform the risk assessment of the nitration …
Published in Journal of Industrial Safety Engineering · Vol. 11, Issue 3, 2024 · pp. 18–23 Read article
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Assessment of Agricultural Potentials and Constraints of Natural Resources Management for Research Implementation in Gedeo Zone South Ethiopia Region
Abstract: This study aimed at assessing agricultural potentials and constraints of natural resources management for research implementation in Gedeo zone south Ethiopia Region. The result indicates that the use of organic and inorganic fertilizers was not efficient and the crop yield was decreasing from year to year. Use of organic fertilizer is for only high value crops of enset and coffee without determined rate. Farmers were not practiced organic fertilizers like …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 2, 2026 · pp. 82–93 Read article
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Comprehensive Evaluation of Quercetin from Bauhinia purpurea for Its Anti-Acne and Anti-Inflammatory Potential, Including Advances in Quercetin-Loaded Nanogel Formulation
Abstract: Acne vulgaris is among the most prevalent chronic inflammatory dermatoses in clinical dermatology, afflicting a substantial proportion of the global adolescent and adult population. Conventional pharmacotherapies — including topical retinoids, benzoyl peroxide, and systemic antibiotics — remain the therapeutic mainstay; however, their long-term utility is progressively undermined by adverse cutaneous reactions, systemic toxicity, and the rising prevalence of antibiotic-resistant Cutibacterium acnes strains. These limitations have intensified scientific interest in plant-derived …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 13, Issue 2, 2026 Read article
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Money Laundering Transaction with Machine Learning
Abstract: This study discusses the use of machine learning algorithms to discover firms that are prone to money laundering. The purpose of this research is to develop, describe, and test a machine learning model for determining which bank transactions should be physically scrutinized for money laundering activities. To train a supervised machine learning model, three categories of historical data are required: legitimate "normal" transactions, transactions flagged as suspicious by the bank's …
Published in Current Trends in Information Technology · Vol. 14, Issue 2, 2024 · pp. 1–15 Read article
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Assessing of Forest Structure Using Earth Observation Data: A Case Study in Munessa Forest, Oromia Region, Ethiopia
Abstract: Understanding forest structure is crucial for estimating carbon emissions associated with forests, assessing forest degradation, and evaluating the success of forest restoration efforts. However, forest structure quantification is limited to the area of interest without considering the whole forest coverage. Forest structure may be easily assessed over a wide area using data from remote sensing. Thus, by combining ground observation with satellite-based light detection and ranging (LiDAR) and Sentinel 2 …
Published in International Journal of Land · Vol. 2, Issue 1, 2025 · pp. 28–37 Read article