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152 articles for “B-trees”
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Cyber Security Evaluation for a Petroleum Refinery Using Attack Tree Methodology and Economic Indexes
Abstract: Information Technology (IT) is vital and valuable to our society. An important type of IT system is Supervisory Control and Data Acquisition (SCADA) systems. The most common misconception regarding the security of SCADA was that this network was electronically isolated from other networks and hence attackers could not access them. Over the years SCADA systems have become incorporated with other IT systems, which has made them becoming increasingly vulnerable to …
Published in Emerging Trends in Chemical Engineering 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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Effect of Particle Size on Recovery of Moringa (Moringa oleifera) Seeds Oil and Quality Characterization
Abstract: Utilization of various plant parts of the moringa tree is gaining interest nowadays due to their versatile quality characteristics. Different parts of the moringa tree, like leaves, flowers, fruits, seeds, and barks, are distinguished well in the decade due to their inherent nutritional as well as medicinal properties. Moringa seed oil has potential quality characteristics like other well-regarded oils, viz., olive oil, coconut oil. The objective of this study was …
Published in Research & Reviews : Journal of Herbal Science · Vol. 14, Issue 1, 2025 · pp. 1–14 Read article
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A Review Article on Oroxylum indicum: A Versatile Medicinal Tree
Abstract: Oroxylum indicum, commonly known as the Indian trumpet tree or Shyonaka, is a medicinal plant belonging to the Bignoniaceae family. It is widely used in traditional medicine systems such as Ayurveda for treating various ailments including neurodegenerative diseases, cardiovascular conditions, arthritis, hepatitis, malignancies, diarrhea, fever, and jaundice. The plant's therapeutic properties are primarily attributed to its rich content of bioactive flavonoids, which exhibit notable anti-cancer, anti-inflammatory, and analgesic effects. Found …
Published in Research & Reviews: A Journal of Pharmacognosy · Vol. 13, Issue 2, 2026 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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Comparative Analysis of Heart Disease Prediction System
Abstract: In the present world, where heart illnesses are on the rise, it is crucial to forecast these diseases. Performing the task on heart disease is a bit difficult and it must be finished precisely and successfully. Heart disease identification relies heavily on Machine Learning (ML) and data mining approaches. The primary focus of the review paper is that patients are easily prone to cardiac diseases depending on medical traits. Using …
Published in International Journal of Advance in Molecular Engineering · Vol. 1, Issue 1, 2023 · pp. 1–6 Read article
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Multiple Disease Prediction Using Machine Learning Algorithms
Abstract: The incorporation of machine learning algorithms into healthcare has transformed disease prediction and diagnosis. This research introduces a method for predicting various diseases using machine learning techniques. A comprehensive dataset, consisting of patient records, medical histories, and key disease-related features, was utilized to build predictive models. Data preprocessing methods, including feature selection and normalization, were implemented to clean and prepare the dataset. Several machine learning algorithms, such as Decision Trees, …
Published in Research and Reviews : A Journal of Immunology · Vol. 14, Issue 3, 2024 · pp. 34–38 Read article
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Gene Annotation of Cancer Vaccine for Homo sapiens
Abstract: Objectives: Gene annotation helps us to deduce the structural and functional aspects of a gene that encodes for a functional protein in our body. Thus, by determining the coding sequence and gene location we can derive meaningful insights as to what these genes do in our body. In this study, an unknown gene, cancer vaccine for Homo sapiens has been studied and annotated. Methods: This study was based on a …
Published in International Journal of Molecular Biotechnological Research · Vol. 2, Issue 1, 2024 · pp. 1–14 Read article
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Implementation of Energy-efficient Axial Fans for Air Handling Unit Using AI Model
Abstract: This research explores the integration of energy-efficient axial fans in Air Handling Units (AHUs) within a large automotive manufacturing facility to enhance HVAC (heating, ventilation, and air conditioning) performance and reduce energy consumption. Standard AHUs in the facility’s clean rooms and other spaces utilize traditional blower fans, which primarily rely on static pressure, limiting their efficiency. By replacing these with electronically commutated (EC) axial flow fans, which leverage both static …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 11, Issue 3, 2024 · pp. 28–34 Read article
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A Study and Prediction of Psychological Disorders Through Machine Learning
Abstract: Physical illness is very much visible but not psychological illness therefore, it requires more attention and care. Psychological disorders also known as psychiatric disorders refer to a wide range of conditions affecting a person’s thought process, leading to significant changes in the behavior of an individual. The most prevalent psychological disorders include depression, anxiety disorders, and post-traumatic stress disorder (PTSD). Symptoms of psychological disorders vary greatly but include common symptoms …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 2, Issue 2, 2024 · pp. 32–38 Read article
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Customer Churn Prediction Using ML Algorithms
Abstract: Comprehending customer churn is essential for businesses aiming to enhance and sustain customer relationships. This study introduces a machine learning approach aimed at forecasting customer churn by leveraging demographic and behavioral data. Our research involved developing predictive models using support vector machines (SVM), random forests, and decision trees, evaluating their efficacy using real-world data from the telecom industry. Our findings underscore that random forests consistently outperform SVM and decision trees …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 2, 2024 · pp. 70–75 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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A Survey On Leveraging Machine Learning for Phishing Attack Prediction and Detection
Abstract: Phishing is one of the biggest cybersecurity threats that exploits user trust by masquerading as a legitimate site or email to steal personal and sensitive information. A state- of-the-art-phishing detection systems survey, this review showcases the evolution from traditional list-based techniques, including blacklisting and whitelisting to machine learning and deep learning models. While list-based systems cannot evolve to detect new and zero-day attacks, the ML algorithms of Decision Tree, Random …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 3, 2025 · pp. 1–10 Read article
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The Assessment of Electric Vehicle Fire Risk Using the Failure Tree Analysis
Abstract: With the global shift toward sustainable transportation, the widespread adoption of electric vehicles (EVs) is rapidly becoming a reality, largely driven by growing environmental awareness and concerns over climate change. However, alongside this transition comes a set of emerging challenges, most notably, the increasing incidence of EV-related fire hazards, which have attracted significant public and media scrutiny. This situation highlights the urgent need for a detailed and systematic approach to …
Published in Journal of Industrial Safety Engineering · Vol. 12, Issue 2, 2025 · pp. 27–38 Read article
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Advancements in Data Structures: Bridging the Gap Between Theory and Real-world Applications
Abstract: In the rapidly advancing landscape of computer science, this study unfolds a comprehensive exploration of Data Structures, spanning from foundational principles to cutting-edge innovations. Data structures form the backbone of computational processes, and this study aims to dissect and illuminate their pivotal role. Beginning with fundamental concepts such as Arrays, Linked Lists, Stacks, and Queues, the narrative progresses to intricate structures like Trees, Graphs, and Hash Tables. Practical applications in …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 1, 2024 · pp. 14–20 Read article
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Using Machine Learning for Key phrase Extraction in Digital Libraries
Abstract: Machine learning has revolutionized various aspects of information retrieval, including key phrase extraction in digital libraries. Key phrase extraction is crucial for summarizing and categorizing vast amounts of textual data, enabling efficient search and retrieval processes. This study explores the application of machine learning techniques for automatic key phrase extraction in digital libraries. We review various supervised and unsupervised learning algorithms, including deep learning models, that are employed to identify …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 8–13 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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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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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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Terminalia arjuna: The Medicinal Tree
Abstract: Over 85% of the medications used in both conventional and alternative medical systems come from plant sources. The stem bark of Terminalia arjuna (T. arjuna) is rich in minerals, flavonoids, and glycosides. T. arjuna bark is unique because flavonoids have been shown to have anti-inflammatory, lipid-lowering, and antioxidant properties, and glycosides are cardiotonic. A variety of topics related to its ethnomedical, phytochemical, pharmacological, and clinical significance to different medical conditions …
Published in Research and Reviews : A Journal of Ayurvedic Science, Yoga and Naturopathy · Vol. 12, Issue 3, 2025 · pp. 27–34 Read article