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1960 articles for “Ma-ul-Shae’er” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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A Review of Machine Learning Applications in Web Data Mining
Abstract: The rapid development of Internet technology has resulted in a rapidly changing and intricate digital environment that requires new methods for organizing and evaluating online data. This study examines the use of machine learning (ML) in web data mining, focusing on its ability to extract relevant insights from huge amounts of online data. Web data mining, which is divided into three categories: content mining, structure mining, and use mining, uses …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 1, 2025 · pp. 39–47 Read article
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Understanding Metabolic Syndrome and its Nutritional Management
Abstract: Metabolic syndrome (MetS) is a collection of risk factors, especially when at least three occur together, including abdominal obesity, dyslipidemia, low high-density lipoprotein cholesterol (HDL-c) levels, hypertension, and insulin resistance. MetS is linked to an increased risk of diabetes and cardiovascular diseases (CVDs) if treatment is not received.The causes of MetS include both genetic and acquired factors that contribute to issues such as insulin resistance, chronic low-grade inflammation, and obesity. …
Published in International Journal of Sustainability · Vol. 2, Issue 1, 2025 · pp. 26–37 Read article
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Utilizing Machine Learning to Evaluate the Connection between Poisson's Ratio and the Petrophysical Properties of Reservoir Rocks
Abstract: The Poisson's ratio is a crucial cornerstone, illuminating our understanding of geomechanical behaviour in wells during the dynamic drilling process and the inspiring recovery journey. This research rigorously employs machine learning methods to analyse the significant impact of geophysical parameters on the Poisson ratio in hydrocarbon reservoirs found in oil fields. The analysis utilized data from multiple oil and gas fields, highlighting the crucial relationships between the Poisson ratio, the …
Published in Journal of Petroleum Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 33–43 Read article
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Investigation of the Hall and Nernst-Ettingshausen Effects in Diluted Magnetic Semiconductors
Abstract: This review explores the Hall and Nernst-Ettingshausen effects in various magnetic systems, including diluted magnetic semiconductors (DMS), topological insulators, superconductors, and novel composite materials. In DMS, the interplay of ferromagnetism and magnetic impurities introduces unique transport behaviors, particularly influencing the anomalous Hall effect (AHE) and thermomagnetic phenomena. We also examine the Nernst-Ettingshausen effect (NE) in topological insulators and superconductors, revealing the influence of band topology and vortex-like excitations. Special attention …
Published in Research & Reviews : Journal of Physics · Vol. 13, Issue 3, 2024 · pp. 1–5 Read article
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Integration of GIS and AI in Urban Planning and Disaster Management
Abstract: The rapid pace of urbanization, combined with the increasing frequency and intensity of natural disasters, necessitates the development of innovative solutions for urban planning and disaster management. Geographic information systems (GIS) and artificial intelligence (AI) have emerged as transformative technologies capable of addressing these challenges. GIS provides a robust framework for spatial data analysis, while AI enhances decision-making through predictive analytics and automation. This paper explores the integration of GIS …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 1, 2025 · pp. 20–36 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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Innovative Approaches to Luminescence: Exciton-Polariton Lasers and Quantum Confinement in 2D Materials
Abstract: The phenomenon known as luminescence occurs when an external energy of any kind excites a substance's electronic state, and the excited energy is released as light. Luminescence is the absence of heat produced by light emission. Luminescence comes in a variety of forms, including thermoluminescence, bioluminescence, and chemiluminescence. Examples of luminescence include flat-screen TVs, LED lights, and bioluminescent phytoplankton. The measurement of the emission spectrum produced when previously excited atoms …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 2, Issue 1, 2024 · pp. 26–33 Read article
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Role of Machine Vision in Autonomous Vehicles: A Review
Abstract: The integration of machine vision in autonomous vehicles (AVs) is a critical advancement in the field of intelligent transportation systems. Machine vision systems enable AVs to perceive their environment, understand road conditions, detect obstacles, and make real-time decisions necessary for safe navigation. These systems rely heavily on image processing techniques, which have evolved significantly over the past decade, leading to improved performance in complex driving scenarios. These developments are largely …
Published in Trends in Machine design · Vol. 12, Issue 1, 2025 · pp. 38–43 Read article
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Nutritional Management of Polycystic Ovarian Disease: Integrating Unani and Contemporary Approaches
Abstract: In Unani medicine, dietary management, known as Ilaj bil Ghiza, plays a vital role in restoring humoral balance and maintaining a healthy temperament (mizaj). This principle aligns with modern medical understanding, particularly in conditions, like polycystic ovarian syndrome (PCOS), which is often associated with insulin resistance and obesity. Modifying dietary habits has shown promise in improving both metabolic and reproductive functions in PCOS patients. Unani scholars attribute PCOS to a …
Published in Research & Reviews : A Journal of Unani, Siddha and Homeopathy · Vol. 12, Issue 2, 2025 · pp. 1–6 Read article
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Selection of Appropriate Porous Material for Designing and Developing Hybrid Absorptive Muffler: A Wave 1-D Based Approach
Abstract: In this study, glass wool and rock wool are used as sound-absorbing materials to assess the sound transmission loss (STL) of hybrid absorptive mufflers. Improving the muffler's acoustic performance and assessing how well these materials attenuate noise are the main goals. Rock wool, which offers greater thermal resistance and broader frequency absorption, is contrasted with glass wool, which is renowned for its lightweight construction and high-frequency absorption. Wave 1-D simulation …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 148–160 Read article
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High-Performance Aluminum Matrix Composites Reinforced with Graphene Nanoplatelets a Study on Mechanical and Thermal Behaviour
Abstract: This study investigates the effect of graphene nanoplatelets (GNPs) on the mechanical and thermal properties of aluminum matrix composites (AMCs) fabricated using the powder metallurgy route. Aluminum alloy Al-6061 powder was reinforced with varying GNP concentrations (0, 0.5, 1, 2, and 3 wt%), followed by uniaxial compaction and sintering. The influence of GNP content on the composite’s structural integrity, strength, and thermal behavior was thoroughly evaluated through tensile testing, hardness …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 38–49 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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State of the Art: A Pandemic Big HealthCare Analytics Solution: Image Data Classification Using Quantum MAML
Abstract: The modern age is facing many pandemic healthcare problems, e.g., covid 19, infections, inflammations, and many more, leading to critical, deadly situations. Survival rate can be increased with proper diagnosis of such data. We have proposed one of the implementations based on a medical image dataset for classification using deep reinforcement learning (RL) with quantum computing. Deep RL is the combination of DL (deep learning), generative adversarial network (GAN), and …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 2, 2024 · pp. 1–9 Read article
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Advances in Polymer Chemistry for Biomedical Applications: Innovations in Composite Materials
Abstract: Polymer chemistry has seen remarkable progress in recent years, particularly in the biomedical field, where novel polymeric materials are transforming the development of medical devices. These advancements have led to the creation of biocompatible, durable, and multifunctional polymer-based solutions that enhance patient care, surgical precision, and treatment outcomes. The application of polymer chemistry in biomedical sciences has revolutionized medical device manufacturing. Polymers offer unique advantages such as flexibility, biocompatibility, and …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 287–292 Read article
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Cardiovascular Modeling with Computational and Mathematical Methods
Abstract: The cardiovascular system, a complex network responsible for delivering life-sustaining oxygen and nutrients throughout the body, is a prime target for advanced understanding and improved therapies. Due to the inherent difficulties in directly observing internal physiological processes and the complexities of interactions within the system, computational and mathematical modeling have emerged as powerful tools in cardiovascular research. This article explores the significance of these methods in unveiling the heart's secrets …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 2, 2025 · pp. 11–21 Read article
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Study of Algebraic Structures in Discrete Mathematics and Its Applications
Abstract: Algebraic structures such as groups, rings, fields, semi groups, and lattices form the foundational framework of discrete mathematics. These structures are defined by specific sets and operations that follow algebraic laws, enabling a systematic approach to problem-solving in various domains. This paper explores the theoretical principles of these algebraic systems and highlights their vital role in computer science, cryptography, automata theory, coding theory, and software engineering. By examining their properties …
Published in Emerging Trends in Symmetry · Vol. 1, Issue 1, 2025 · pp. 35–40 Read article
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Neurophysiological Effects of Chanting the Gayatri Mantra on Students of Allied Health Sciences: A Study among 1200 Students at Paramedical College, Desh Bhagat University
Abstract: Background: The Gayatri Mantra, a sacred Vedic chant, is traditionally believed to offer numerous benefits, including mental clarity, stress reduction, and cognitive enhancement. Despite anecdotal evidence supporting these claims, scientific research on its neurophysiological effects, especially within educational settings, remains limited. This study investigates the impact of chanting the Gayatri Mantra on brain activity, stress levels, and cognitive performance among 1200 students in the Allied Health Sciences program at Paramedical …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 2, 2025 Read article
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Machine Learning-Based Disease Prediction: A Comparative Analysis for Diabetes, Brain Tumor, and Parkinson's Disease
Abstract: This paper presents a web-based disease prediction system that integrates machine learning and deep learning techniques to assist in the early detection of Parkinson’s Disease, Diabetes, and Brain Tumors. By utilizing clinical data and MRI images, the platform provides rapid and interpretable predictions to support proactive health management. Logistic Regression models are applied to classify structured datasets for predicting Parkinson’s disease and Diabetes, making use of their effectiveness in binary …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 44–54 Read article
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Polymeric Materials in Drug Delivery: Applications in Topical Formulations
Abstract: Polymeric materials play a crucial role in modern drug delivery systems, particularly in topical formulations. These materials enhance drug stability, control release rates, and improve bioavailability, making them essential components in pharmaceutical advancements. Polymers such as chitosan, hydrogels, and emulsifying agents are widely utilized in immediate-release topical formulations, where they contribute to improving therapeutic efficacy by ensuring uniform drug distribution, increased solubility, and enhanced skin penetration. The integration of polymer-based …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 34–41 Read article
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Smart Environmental Noise Monitoring System Using IoT and Machine Learning for Urban Pollution Control
Abstract: Human race has steadily evolved over past centuries. Development of new technology, vigorous research, consistent efforts, indomitable will to find solutions for the problems, are the key factors to shape our future in way that everyone gets safe, secure and satisfactory life. Construction industries provides basic but most valuable service or product or we can say that construction industries fulfill the basic needs of individual and group of people by …
Published in Journal of Structural Engineering and Management · Vol. 12, Issue 3, 2025 Read article