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421 articles for “R Tree”
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ML Analysis of Factors Affecting Vaccination in Rural Children: A Machine Learning Approach
Abstract: Vaccination remains one of the most effective public health interventions for preventing childhood diseases, yet rural regions in India continue to experience uneven immunization coverage due to multiple socioeconomic and geographic barriers. This research applies machine learning techniques to identify and analyze the major determinants influencing childhood vaccination uptake in rural communities. The study utilizes survey-based demographic, socioeconomic, and healthcare-related parameters to build predictive models that classify children as vaccinated …
Published in International Journal of Vaccines · Vol. 3, Issue 2, 2026 Read article
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User Engagement in Mobile Applications: Modeling and Predicting
Abstract: The mobile ecosystem is expanding rapidly, making app developers highly competitive. To keep users engaged, apps can anticipate when they might disengage, allowing developers to implement intervention tactics. This work demonstrates that it is possible to accurately forecast user disengagement using numerical models. The framework includes Cox proportional hazards, negative binomial, random forest, boosted-tree, and optimized agglomerative hierarchical clustering models. A 12-month observation dataset from a trash recycling app development …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 10, Issue 3, 2023 · pp. 1–7 Read article
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Analyzing Potential Leads Data to Improve Marketing Strategies
Abstract: To develop a lead scoring model using multiple machine learning models and create a user-friendly web application, the first step is to clearly define the problem and collect relevant data from various sources such as CRM, website, social media, email campaigns, etc. After cleaning and pre-processing the data, identify the essential features that can affect the lead score and split the data into training and testing sets. Next, select a …
Published in E-Commerce for Future & Trends · Vol. 10, Issue 2, 2023 · pp. 18–25 Read article
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Enhancing Energy Efficiency in Air Handling Units Through AI Driven Optimization
Abstract: This research explores the implementation of artificial intelligence (AI) in enhancing the energy efficiency of Air Handling Units (AHUs) in manufacturing facilities. The study proposes a comprehensive solution architecture that incorporates temperature and humidity sensors within AHUs, utilizing RS485 for data communication. The collected data undergoes exploratory analysis, which informs the training of a decision tree algorithm, chosen for its accuracy and compatibility with edge gateways. The algorithm's predictions enable …
Published in International Journal of Industrial and Product Design Engineering · Vol. 2, Issue 2, 2024 · pp. 19–28 Read article
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Performance of Artificial Neural Network for Tree Species Identification using Sentinel-2 Data
Abstract: Accurate land cover mapping, especially concerning vegetation, is crucial for effective land use policy planning and sustainable forest management. Hence, achieving accuracy in mapping requires a deep understanding of composition changes, vegetation conditions, and the spatial distribution of tree species. In the spatial context of tree species, it holds significant potential for applications including invasive species monitoring, delineating contaminated areas, and biodiversity conservation. However, traditional methods for tree species identification …
Published in Journal of Remote Sensing & GIS · Vol. 15, Issue 2, 2024 · pp. 12–21 Read article
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Tank Water Quality Analysis Using Machine Learning
Abstract: Tank Water quality is a critical factor for public health, agriculture, as well as industry. Continuous monitoring of tank water quality: temperature, humidity, water level, CO2 concentration, and pH, is vital for safe usage. Using machine learning, real-time data analysis can detect anomalies, predict issues, and optimize water management, ensuring timely responses and improved safety. This intelligent approach enhances decision-making and maintains water quality effectively in various environments.We develop an …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 2, 2025 · pp. 27–34 Read article
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Ashok Chal (Saraka indica Linn.) for Women’s Health: A Literary Review
Abstract: The ashok tree is one of the most antique herbal plants used since ancient times by the ancient physicians for various women’s health conditions. Ashok means without sorrow as it keeps the women healthy and youthful. It is distributed in various parts of India and is obtained easily. It has various pharmacological activates which were proven by several pharmacological and clinical trials. It has been appropriately said to be a …
Published in Research & Reviews : Journal of Herbal Science · Vol. 6, Issue 3, 2017 · pp. 12–16 Read article
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Fructifying of Electricity Utilizing Wind Leaf –PV Combination Model
Abstract: Abstract—In recent days renewable energies are used to produce electricity which is available at no cost. In this project wind and solar energy are used to fructify electricity with the assistance of aero leaves and solar panels. Few aero leaves are structured in the form of a tree, for producing high power. This tree uses tiny blades which are inbuilt with the aero leaves to produce electricity from wind energy. …
Published in Current Trends in Information Technology · Vol. 9, Issue 2, 2019 · pp. 14–19 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 · Vol. 1, Issue 3, 2024 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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Comparative Analysis of Supervised Learning Algorithms
Abstract: Supervised learning is a fundamental and widely used branch of machine learning in which models are trained on labeled datasets, meaning that each input is associated with a known output. Supervised learning algorithms develop predictive capability by understanding the mapping between input variables and corresponding output labels, enabling them to accurately forecast outcomes for previously unseen data. Due to this capability, supervised learning has found extensive applications across diverse domains …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 25–30 Read article
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The association between emotional intelligence and job satisfaction among secondary school teachers employed by particular high schools of Bagalkot
Abstract: Background: The success of an individual hinges on several personal factors. In this age of globalization, where culture, science, economy and society are exchanged globally, emotional intelligence seems to be the missing currency. A person’s ability to handle emotions with wisdom is referred to as emotional intelligence. Those with emotional intelligence are guaranteed a positive simultaneity domestically, socially and professionally. Such individuals are better capable of managing their emotions and …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 2, 2024 · pp. 13–20 Read article
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Predictive Modeling and Optimization of Tensile and Flexural Strength in FDM 3D Printing Using Decision Trees and Bayesian Optimization.
Abstract: This research investigates predictive modelling and optimization technique for the tensile and flexural strength of PlA (Poly Lactic Acid) in Fused Deposition Modelling (FDM) 3D printing. Employing Decision Trees and Bayesian Optimization enhances comprehension and control of 3D printing process. Precise model predicts PLA material properties based on input parameters. Methodology involves rigorous data preprocessing, encompassing, cleaning, transformation, and normalization. Hyperparameter optimization via grid search systematically explores configurations, optimizing model …
Published in Journal of Polymer & Composites · Vol. 11, Issue 12, 2023 · pp. 203–214 Read article
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Massive Data Capturing and Transmission using Big Data Analytics Model with Machine Learning Prediction
Abstract: Deep learning techniques are widely used in many branches of research and engineering, including language processing, image classification, and speech recognition. Similar to this, processing vast amounts of data is restricted by a number of classical data processing approaches. To deal with information progressively with incredible exactness and effectiveness, huge information investigation requests spic and span, complex calculations in light of machine and profound learning methods. Recent research has, however, …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 9, Issue 3, 2022 · pp. 23–30 Read article
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Structure-Property Modeling and Engineering Optimization of Biodegradable Starch-Cellulose Biofoams for Sustainable Packaging
Abstract: Since the packaging industry is an engineered product with complex composites that involve a close relationship between composition, processing, and performance, optimization of formulation, cellular morphology, and engineering performance of biodegradable starch-based biofoams presents a considerable challenge. This study proposes a machine-learning-aided structure–property modeling framework to design and optimize starch-based biodegradable biofoams for sustainable packaging applications. A physics-informed synthetic dataset consisting of 10,000 formulations was created based on engineering relationships …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article
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A Systematic Review for Heart Disease Prediction Using AIML Algorithms
Abstract: Cardiovascular diseases (CVDs), commonly known as heart diseases, have consistently held the position of being the primary global cause of mortality for many years. They are also the most serious illness in India and the rest of the world. So, a method that is reliable, accurate, and easy to use is needed to find these diseases early and start the right treatment. Using a variety of medical datasets, machine learning …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 3, 2023 · pp. 53–61 Read article
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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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Hand-Writing Recognition Using Structural, Statistical Features
Abstract: One of the very crucial challenges in pattern recognition operations is handwriting recognition, often known as handwritten number recognition. The processing of bank checks, the sorting of postal mail, the entry of data into forms, etc. are all procedures involving number recognition. The ability to create an efficient algorithm that can retrieve handwritten integers submitted by drug users via a scanner, tablet, and other digital gadgets is at the core …
Published in Journal of Electronic Design Technology · Vol. 14, Issue 1, 2023 · pp. 8–14 Read article
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Design and Validation of Low Power High Speed area effective comparator using CMOS Technology
Abstract: The most fundamental arithmetic comparisons in a digital comparator involve comparing two numbers that are greater than, less than, or equal to each other. While doing enormous level arithmetic comparisons, a digital comparator needs more space, which results in higher power consumption and a delayed response. This can be solved by using N-bit comparator with two modules using 45GPDK CMOS Technology. An N-bit comparator can operate at extremely high speeds …
Published in Recent Trends in Electronics Communication Systems · Vol. 10, Issue 2, 2023 · pp. 20–29 Read article
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Evaluation of the antioxidants potential and total phenolic contents of the Albbizia siris a drug plant
Abstract: Free radicals are the major problems of the world today. They are formed endogenously as well as exogenously by different kinds of metabolic processes in the body. Some of them are highly toxic process causing considerable damage to the system and produce several kindsof disorders. Antioxidants are the substance which reduces the formation of free radicals inthe body and are responsible for degradation of free radical and reactive oxygen species …
Published in Research and Reviews: A Journal of Toxicology · Vol. 9, Issue 1, 2019 · pp. 21–25 Read article