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152 articles for “B-trees”
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An Automated Smart Contract Repair Framework for Reentrancy, Integer Overflow, and Denial- of-Service Vulnerabilities
Abstract: This paper introduces a novel static analysis framework designed to bridge a long-standing gap in Ethereum smart contract security: the disconnect between vulnerability detection and automated remediation. Although widely adopted tools such as Slither and Oyente are highly effective at identifying security weaknesses, they stop short of providing actionable fixes. As a result, developers manually patch vulnerabilities, a process that is not only time-consuming but also susceptible to human error …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 31–41 Read article
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Algorithmic Strategies for Complex Data Handling: Optimizing Data Structures for Enhanced Computational Performance
Abstract: We live in an age of big data and processing very large often complicated datasets can be crucial to efficient algorithmic performance. This paper discusses different algorithmic techniques when working with difficult data and how to arrange your information structures correctly for better functionality in large-scale methods. It checks the impact of different algorithms like sorting, searching, and hashing in boosting its processing speed as well as memory use. This …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 2, 2024 · pp. 1–10 Read article
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Fertilizer Prediction Using Machine Learning
Abstract: Fertilizer prediction is a critical aspect of modern agriculture, aimed at optimizing resource utilization while maximizing crop yields. In recent years, machine learning (ML) techniques have emerged as powerful tools for addressing this challenge by leveraging data-driven approaches to predict the optimal type and quantity of fertilizer required for different crops and soil conditions. This research paper provides a comprehensive review of the existing literature and methodologies employed in fertilizer …
Published in Journal of Mechatronics and Automation · Vol. 11, Issue 2, 2024 · pp. 26–35 Read article
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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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Analyzing and Predicting Academic Behavior from Peer Pressure Indicators Using Machine Learning
Abstract: The academic achievement of a student is determined by their capability, but also by the companions with whom they associate. Friends can have a positive impact on students' motivation for school, and at times friends are distractions leading to a lack of attention on their school assignments. This particular study focuses on the number and quality of companions students associate with and to what extent that could be used as …
Published in International Journal of Education Sciences · Vol. 3, Issue 2, 2026 Read article
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Analyzing and Predicting Academic Behavior from Peer Pressure Indicators Using Machine Learning
Abstract: The academic achievement of a student is determined by their capability, but also by the companions with whom they associate. Friends can have a positive impact on students' motivation for school, and at times friends are distractions leading to a lack of attention on their school assignments. This particular study focuses on the number and quality of companions students associate with and to what extent that could be used as …
Published in International Journal of Education Sciences · Vol. 3, Issue 2, 2026 · pp. 1–7 Read article
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Progress in Renal Tumor Surgery: The Role of 3D Surgical Planning in Partial Nephrectomy
Abstract: Renal cell carcinoma is the most common form of kidney cancer, representing 2–3% of global cases, with the highest incidence in Western Europe. For small renal tumors, partial nephrectomy is the preferred treatment, where the tumor is surgically removed. This procedure does not affect oncological outcomes, allowing part of the kidney to remain functional. During tumor removal, the surgeon minimizes excessive bleeding and improves visibility by cutting off the arterial …
Published in Research and Reviews : Journal of Surgery · Vol. 14, Issue 3, 2025 · pp. 35–40 Read article
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CHROMAWEAR: An AI Assisted Personalized Fashion Design Recommender System for Diverse Skin Tones to Enhance Fashion Choices
Abstract: In the age of fashion, we receive the same question every day: What should I wear today to look nice? The fashion industry is always changing, welcoming inclusivity and diversity. Still, despite the advancements, there are difficulties meeting people's varied needs, especially with regard to skin tone. This research work presents a personalized fashion design recommender system with artificial intelligence support to improve the fashion choices of people with different …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 49–58 Read article
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Formulation Challenges in Long-acting Injectable Small Molecules: Emerging Strategies and Perspectives
Abstract: Long-acting injectable (LAI) formulations represent a transformative approach in pharmacotherapy, particularly for conditions demanding sustained drug exposure over weeks to months. Although biologics have dominated this space historically, the adaptation of LAI technology to small molecules presents a distinct and complex set of challenges rooted in physicochemical properties, manufacturing scalability, and regulatory expectations. This review systematically addresses the principal formulation barriers encountered in developing LAI small-molecule products, including aqueous solubility …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 13, Issue 2, 2026 Read article
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Evaluating the Economic and Ecological Importance of Traditional Fruit Trees in Uttarakhand
Abstract: This study investigates the distribution, morphological characteristics, phyto-constituents, and conservation practices of traditional fruit trees in Uttarakhand, India. The region, characterized by its mountainous terrain and diverse climatic conditions, hosts a variety of fruit species, including apple, pear, peach, plum, khumani, walnut, mango, litchi, malta, santra, lemon, aonla, guava, and pomegranate. Data on morphological traits were collected from hilly and valley areas, emphasizing their traditional importance and nutraceutical values. Furthermore, …
Published in International Journal of Land · Vol. 1, Issue 2, 2024 · pp. 06–21 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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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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Design and Development of Onion Storage Shade for Better Ventilation and Longer Life
Abstract: Onions are one of the most important cash crops for farmers in India and many other countries. However, most harvested onions are lost every year due to improper storage. Traditional storage methods, such as keeping onions in heaps under trees, in closed rooms, or in poorly ventilated sheds, do not provide sufficient airflow. As a result, moisture accumulates, leading to sprouting, fungal growth, rotting, and physical damage. These losses reduce …
Published in International Journal of Trends in Horticulture · Vol. 3, Issue 1, 2026 · pp. 31–41 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
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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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Climate Change Including Forest Fire Prediction using Machine Learning and Deep Learning
Abstract: Climate change alludes to long haul shifts in temperatures and atmospheric conditions. These movements might be regular, for example, through varieties in the sun-oriented cycle. In any case, since the 1800s, human exercises have been the fundamental driver of climate change, basically because of consuming fossil fuels like coal, oil and gas. Many individuals think climate change mostly implies hotter temperatures. Be that as it may, the temperature climb is …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 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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An Overview on AI-Driven IoT Based Decision Making in Climate change Study: KSK approach in Climate Change Study
Abstract: As the Earth’s climate enters a state of unprecedented volatility, the traditional methods of ecological observation—characterized by delayed reporting and fragmented data—are no longer sufficient. This study investigates the paradigm shift toward AI-driven IoT (KSK Approach)-based decision-making frameworks as the primary frontier in climate science. By deploying a "planetary nervous system" of interconnected sensors—measuring everything from soil moisture in the Sahel to glacial melt rates in the Arctic—we generate a …
Published in International Journal of Climate Conditions · Vol. 3, Issue 1, 2026 · pp. 1–10 Read article
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Species Interdependence and Biodiversity
Abstract: For the survival of every species, a reliance on compatible counterparts is essential. This compatibility can be examined through various aspects, with food and shelter emerging as the most common yet crucial factors. In the realm of plants, sustenance plays a pivotal role in ensuring survival. Whether it be a tree, shrub, ground cover, creeper, climber, or any other category, the availability of sufficient food is paramount. The prospects of …
Published in Research & Reviews : Journal of Ecology · Vol. 13, Issue 2, 2024 · pp. 1–7 Read article
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The Nutritional Value of Moringa Plant as a Superfood: A Comprehensive Review
Abstract: Moringa oleifera, commonly known as the "miracle tree," has garnered global attention for its rich nutritional profile and diverse medicinal properties. This review article comprehensively explores the nutritional composition and health benefits of Moringa, highlighting its potential as a superfood. The plant is rich in essential nutrients, including proteins, vitamins, minerals, and bioactive compounds, such as flavonoids and phenolic acids. These constituents contribute to its antioxidant, anti-inflammatory, antimicrobial, and anti-cancer …
Published in International Journal of Sustainability · Vol. 1, Issue 2, 2024 · pp. 20–23 Read article