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421 articles for “R Tree”
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Cutting-edge Deep Learning Methods for Predicting and Detecting Cardiovascular Diseases
Abstract: Cardiovascular diseases (CVDs) remain a major global health issue, highlighting the need for improved early detection and risk assessment methods. This research investigates the efficacy of both deep learning and traditional machine learning methods in forecasting cardiovascular diseases (CVDs). We evaluate a variety of models, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Multilayer Perceptrons (MLPs), Long Short-Term Memory (LSTM) networks, as well as Logistic Regression (LR), Decision Trees …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 36–42 Read article
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Analysis of Disease and Risk Prediction using ML
Abstract: This paper comprises of efficient machine learning algorithms used in predicting diseases through symptoms. As, the health industry has a huge amount of data for various fields, so we want to make a system where we can use various other applications of machine learning on health industry. This all had been done to make better medical decisions and also for rise in the accuracy. As an accurate analysis and early …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 7, Issue 1, 2020 · pp. 7–13 Read article
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Environmental Impact of Ghaf Tree (Prosopis cineraria) on Heavy Metals Concentration in Atmosphere
Abstract: The Ghaf is a hardy tree, drought-resistant, and can grow up to ten meters in height, it tree produces small, yellow flowers which attractive to many habitats, like bees, insects, and birds. The leaves and pods of the Ghaf tree have significant antioxidant and anti-inflammatory properties and can be used in new drug development. Ghaf trees can adapt to changing environmental conditions and planting Ghaf trees could be an effective …
Published in International Journal of Minerals · Vol. 1, Issue 1, 2024 · pp. 1–7 Read article
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Bank Loan Prediction by using Logistic Regression
Abstract: In the modern era of science and technology, the banking sector is also growing very fast and a lot of people are applying for bank loans. But the bank has limited assets and can be granted to limited number of people only, so the bank must ensure that the person whom the loan is granted is eligible enough to pay it back. So, in this study, we will try to …
Published in E-Commerce for Future & Trends · Vol. 8, Issue 2, 2021 · pp. 17–21 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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Morphological and Biomass Performance of Indigenous Agroforestry Tree Species Seedlings under Different Provenances at Nursery Level, in Central Ethiopia
Abstract: Multipurpose trees are significantly important for climate change resistance in such a way that they contribute to both climate change adaptation and mitigation. In addition, they have important economic and social benefits for the livelihoods of farmers and also have a considerable effect on the GDP of the country. Therefore, to improve species’ adaptation in specific, site genetics fitness is an important factor. Therefore, the objective of the research was …
Published in Research & Reviews : Journal of Botany · Vol. 11, Issue 3, 2022 · pp. 47–58 Read article
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Advancing Healthcare Systems: A Machine Learning Approach to Multi-Disease Prediction
Abstract: The integration of machine learning algorithms in healthcare has revolutionized the way we approach disease prediction and diagnosis. An attempt to employ machine learning techniques to forecast numerous diseases is presented in this study. A diverse dataset containing patient records, medical history, and relevant features for various diseases was used to develop predictive models. Feature selection and normalization were among the preprocessing methods used to clean and prepare the data. …
Published in Journal of Electronic Design Technology · Vol. 16, Issue 1, 2025 · pp. 1–6 Read article
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Evaluation of Credit Risk of Bank Customers with a Hybrid Approach of Data Mining Techniques
Abstract: Credit risk poses the most significant threat to financial and monetary institutions. Banks strive to offer loans that generate high returns while minimizing risk. Achieving this requires the ability to accurately identify and classify credit customers, both individuals and legal entities, according to their likelihood of fully meeting their obligations. This classification is done using relevant financial and non-financial criteria. The primary goal of this study is to assess the …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 63–81 Read article
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RTL-to-GDSII Flow Optimization for Low-Power 32-bit RISC-V Processor
Abstract: This paper presents the implementation and optimization of a 32-bit RISC-V processor, transitioning from Register Transfer Level (RTL) design to final GDSII using Synopsys Fusion Compiler over 32nm technology node. The processor architecture is based on the RV32I base instruction set and incorporates a 5-stage pipeline to achieve a balanced trade-off between performance and design complexity. The design methodology involved RTL synthesis, gate-level netlist generation, and successive physical design stages …
Published in Journal of VLSI Design Tools and Technology · Vol. 15, Issue 3, 2025 · pp. 1–10 Read article
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Design and Implementation of Carry Select Adder based On Wallace tree Multiplier using Adiabatic Logic
Abstract: The Wallace tree multiplier construction using a carry select adder (CSA) and this paper discusses adiabaticlogic. The proposed design aims to reduce power consumption while maintaining high performance.Adiabatic logic is employed to reduce power dissipation by recycling energy during the logic transitions. TheWallace tree multiplier is used to perform fast multiplication of two large numbers by breaking down themultiplication process into smaller sub-tasks. The CSA is used as the adder …
Published in Journal of VLSI Design Tools and Technology · Vol. 13, Issue 2, 2023 · pp. 21–31 Read article
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Decomposition of Dynamic Graphs in Memory Saving with Effective Programming
Abstract: This study proposes a simple and effective heuristic to save memory in effective programming on tree decompositions when solving a graph optimization problem. The introduced “anchor technique” is based on a tree-like set covering problem. We substantiated our findings by experimental results. Our strategy has negligible computational overhead concerning running time but achieves memory savings for nice tree decompositions and path decompositions between 60% and 98%.
Published in Recent Trends in Programming languages · Vol. 1, Issue 3, 2014 · pp. 7–12 Read article
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Machine Learning Regression Based Approach for Prediction of the Ultimate Tensile Strength of Tungsten Inert Gas Welded Joints
Abstract: Many leaders in technology education have shown that the main difference between the technical design process and the process of engineering construction analysis and efficiency [1–3]. The engineering analysis phase of the construction process is where the mathematical and scientific models principles are used to help the designer predict the design results. The engineering feasibility phase process is a systematic process that uses structural elements and conditions to allow the …
Published in Trends in Machine design · Vol. 8, Issue 2, 2021 · pp. 1–10 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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Traversal Speed Comparison of BFS and DFS in Balanced and Skewed Binary Trees
Abstract: In this paper, we provide an analysis of how well both breadth-first search (BFS) and depth-first search (DFS) algorithms perform while wandering through two kinds of binary trees: balanced and skewed. The research was motivated by the practical application of storing files and directories in a certain type of parent-child relationship through the use of hierarchical file systems (e.g., windows explorer). The result of measuring how fast and versatilely these …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 2, 2026 Read article
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Mapping of Crop Management Factor (C) for Sylhet Sadar using Remote Sensing and GIS
Abstract: Sylhet Sadar suffers from excessive rainfall causing the enormous soil loss in this area. C-factor is one of the most important parameter of the Universal Soil Loss Equation (USLE) and revised version of USLE for estimating soil loss. The current study was conducted for determining the crop management factor (C) using remote sensing (RS) and geographical information system (GIS) tools. Satellite images (Landsat 7 ETM+ of 2000, 2010 and Landsat …
Published in Journal of Remote Sensing & GIS · Vol. 11, Issue 3, 2020 · pp. 35–46 Read article
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Modernizing Pharmacovigilance: Leveraging AI,Automation, and Real-World Data for Drug Safety
Abstract: Pharmacovigilance, or PV, is “the pharmacological science relating to the detection, assessment, understanding, and prevention of adverse effects, mainly long term and short-term adverse effects of medicines.” PV’s specific objectives are to increase patient care and safety when using medications and all medical and paramedical therapies; assist in evaluating the benefits, drawbacks, efficacy, and risks of medications, ensuring their safe, prudent, and more effective use; and promote clinical training, education, …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 · pp. 21–30 Read article
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A Review on Pharmacological Activities of Garcinia Indica
Abstract: The plant Garcinia indica having active constituents like xanthones, flavonoids, benzophenones, lactones, and phenolic acids D-Leucine, fukugicide, xanthochymol, isogarcinol, isoxanthochymol, Cambogic acid, HCA, HCA lactone, mangostin, GB-1, GB-2, amentoflavone and garcinol. The plant is screened for Antioxidant and Hepatoprotective activity, Antimicrobial, Cytotoxic Effects, Anti-fungal activity, Anti-neoplastic activity, Anti-bacterial activity, Anti-fungal activity, Anti-bacterial activity, Anti-inflammatory activity, Hypoglycaemic activity, Anti-ulcer activity, Neuroprotective Effects, Anti-obesity activity, Antiaging activity. The present review is therefore, …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 10, Issue 3, 2021 · pp. 16–20 Read article
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Characterization of Ber (Ziziphus mauritiana) Genotypes
Abstract: The deciduous or evergreen trees and shrubs belonging to the genus Ziziphus with more than 100 species, disseminated in the tropical and subtropical regions of the world deals sufficient plants genetic resources appropriate for arid and semi-arid climates to enrich food security. Among some of the species, like Z. mauritiana occur in closely every continent and is thought to have great genetic diversity. In China and India, the outdated selection …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 8, Issue 1, 2019 · pp. 11–23 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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Structure–Property Modeling of Cement-Based Multi-Component Composites Using Ensemble Machine Learning and Explainable Feature Attribution
Abstract: Accurate prediction of compressive strength is central to structure–property optimization, quality control, and sustainability-driven design in cement-based composite materials. Cementitious systems represent heterogeneous multi-phase composites composed of reactive binder matrices and dispersed aggregate phases, whose macroscopic mechanical performance emerges from complex nonlinear interactions among constituents and curing-dependent microstructural evolution. This study develops a data-driven structure–property modeling framework to quantify the nonlinear dependence of compressive strength on multi-component composite composition and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 112–131 Read article