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360 articles for “prediction tool”
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Advanced Computational Models for Predicting Molecular Interactions
Abstract: Understanding molecular interactions is essential for a number of disciplines, including biochemistry, materials science, and medication development. Traditional experimental methods, while accurate, are often time-consuming and expensive. Advanced computational models have emerged as powerful tools to predict molecular interactions efficiently. In order to predict the behavior and interactions of molecules at the atomic and subatomic levels, this paper reviews the most recent developments in computational techniques, such as machine learning …
Published in International Journal of Advance in Molecular Engineering · Vol. 2, Issue 1, 2024 · pp. 8–13 Read article
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Simulation and Experimental Analysis of Abuse Testing for Prediction of Life Cycle for Lithium Ion Battery Cell and Pack Level
Abstract: Lithium-ion batteries play a crucial role in contemporary technology, serving as the power source for everything from consumer gadgets to electric vehicles. However, their safety and longevity are significant influenced by the reperformance under extreme conditions, commonly referred to as ab use testing .This paper explores the simulation and analysis of ab use testing and life cycle prediction for lithium-ion batteries at both the cell and pack levels. Abuse testing …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 2, Issue 2, 2024 · pp. 1–24 Read article
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Microalbuminuria as an Independent Screening Tool in Patients with Myocardial Infarction
Abstract: Acute Myocardial Infarction (AMI) is a condition in which there is an inadequate supply of blood and oxygen to a portion of myocardium; most common cause being atherosclerosis of coronary vessels. Microalbuminuria (MAU) is defined as urinary albumin-to-creatinine ratio (UACR) of 30–300 mg/g. It is considered as marker of generalized endothelial dysfunction and vasculopathy and suggested to contribute to the formation of atherosclerotic lesion and ultimately leading to risk of …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 6, Issue 2, 2017 · pp. 41–45 Read article
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Soft Computing Based Prediction of Deviator Stress of Waste Plastic Reinforced Sand
Abstract: In the recent past, the soft computing techniques have received a significant attention for solution of the geotechnical stability problems. Following the trend, the present study tries to explore the use of different soft computing techniques such as random forest regression, support vector machines (SVM) RBF kernel, SVM poly kernel and M5P model tree for the prediction of deviator stress of sand reinforced with waste plastic strips. The deviator stress …
Published in Journal of Geotechnical Engineering · Vol. 6, Issue 3, 2019 · pp. 1–7 Read article
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Versatile CNC Machine for Tabletop Use Enhanced with Machine Learning Integration
Abstract: In the realm of tabletop multipurpose CNC machines, the integration of machine learning represents a groundbreaking advancement potentially revolutionary in the field of desktop manufacturing. This research explores the seamless incorporation of machine learning algorithms into tabletop CNC machines to enhance their capabilities, performance, and user experience. Through case studies and examples, we demonstrate the profound impact of machine learning integration in key areas of CNC machining, such as accurate …
Published in Journal of Polymer & Composites · Vol. 11, Issue 8, 2023 · pp. 353–361 Read article
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An Immunohistochemical Study to Assess the Role of Myofibroblasts in Diagnosing and Predicting the Outcome of Oral Squamous Cell Carcinoma
Abstract: Background: Squamous cell carcinoma (SCC) accounts for approximately 94% of all oral malignancies, hence establishing oral squamous cell carcinoma (OSCC) as one of the top 10 most prevalent malignant tumors. Cells with several functions, such as macrophages and myofibroblasts, play a vital role in the biological behavior of tumors. This study aimed to assess and evaluate the prevalence of myofibroblasts (MF) and macrophages in SCCs occurring in the oral region. …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 2, Issue 1, 2024 · pp. 13–17 Read article
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A Hybrid Machine Learning Approach for Cardiovascular Disease Prediction
Abstract: Heart disease ranks among the top causes of death globally. Accurately predicting cardiovascular conditions has become a key challenge in the realm of clinical data analysis. It has been shown that machine learning is an effective means of assisting with predicting and decision-making based on the large volume of data produced by the medical industry. In this study, we describe a unique approach that increases the prediction accuracy of heart-related …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 69–75 Read article
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Computational Study of Sombor Index on Generalized Abid–Waheed Graphs for Polymer Modeling
Abstract: This study investigates the topological properties of generalized Abid Waheed graphs. Development of theoretical models in chemistry, reducing computational complexity while analysing large molecules or networks Abid Waheed graphs play a significant role. Motivated by these findings, the research was extended to encompass generalized Abid Waheed graphs, characterized by r cycles of order s. A notable similarity between Abid Waheed graphs and Jahangir graphs was observed. The potential applications of …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 267–274 Read article
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Land surface dynamics: A Multiphysics Approach to Modeling Mass Transport
Abstract: Land surface dynamics are governed by complex interactions among hydrological, atmospheric, and geomorphological processes that collectively drive the transport of mass across terrestrial environments. Traditional modeling approaches often isolate individual mechanisms, limiting their ability to capture the coupled feedbacks that shape landscape evolution. This study presents a multiphysics framework for modeling mass transport on land surfaces, integrating fluid flow, sediment transport, heat exchange, and chemical reactions within a unified computational …
Published in International Journal of Land · Vol. 2, Issue 2, 2025 · pp. 31–36 Read article
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Risk Based Estimation in Construction Projects
Abstract: Final cost of a project is always subjected to many variables and assumptions. A single value estimate only represents one of the many possible conditions that can arise in the future. Hence a cost estimate should be represented as a range of values rather than a single value. Construction projects are complex project which involve many uncertainties. Uncertainties in activities can be a threat to the project objective or an …
Published in Journal of Construction Engineering, Technology & Management · Vol. 12, Issue 3, 2022 · pp. 24–36 Read article
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AI Enabled Pharma Supply Chain Market
Abstract: Pharmaceutical supply chains are changing because of artificial intelligence (AI). The pharmaceutical industry has always had to deal with uncertainty. From the start of research to the final delivery of medicines to patients, it faces scientific risks, government rules, and supply chain problems. In recent years, these challenges have gotten worse because there is more drug shortage, political issues are messing up transportation, and regulators are asking for more openness …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 17, Issue 2, 2026 Read article
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Early Heart Failure Recognition for Infants Using Machine Learning
Abstract: The care of newborn infants remains a significant responsibility for healthcare professionals, as ensuring infant survival can often be complex and demanding. Conditions such as heart failure and cardiac arrest in infants are life-threatening and require prompt diagnosis and treatment. Detecting cardiac problems at an early stage can greatly enhance survival outcomes and minimize serious complications. In recent years, machine learning (ML) approaches have become valuable tools for predicting cardiovascular …
Published in International Journal of Emergency and Trauma Nursing and Practices · Vol. 4, Issue 1, 2026 · pp. 1–5 Read article
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Experimental Analysis and Validation of Cellulose Fibre Insulation Structures Considering Thermal Properties
Abstract: Cellulose fibre insulation structures made from used newspaper can be installed in attics, filling gaps between doors and windows. Many researchers focused on loose-filled cellulose fibre insulation. This study investigates the thermal conductivity, R- Value and thermal transmittance of cellulose fibre insulation manufactured from recycled cellulose materials with densities ranging from 280 to 360 kg / m³ and specimen thicknesses of 10 – 30 mm. A total of 25 structures …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article
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Artificial Intelligence based Sustainable Decision Intelligence for Climate Action
Abstract: This paper proposes a Sustainable Decision Intelligence (SDI) framework to address the limitations of traditional climate policy through AI-driven analytics. By reviewing literature from 2020–2026, the study examines the impact of Artificial Intelligence (AI) on climate forecasting, energy optimization, and biodiversity monitoring, categorizing these tools into predictive, optimization, and policy intelligence layers. While acknowledging critical hurdles like data bias and computational energy costs, the research argues that integrating AI into …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Machine Learning Based Early Cataract Detection: A Predictive Modeling Approach
Abstract: Cataracts, characterized by dense cloudy areas in the eye’s lens, afflict more than 50% of elderly individuals, leading to impaired vision and potential blindness. Detecting cataracts at an early stage is crucial to facilitate simpler treatments, as neglecting the condition may necessitate complex eye surgery. To address this issue, we are creating a predictive system that identifies cataract disease by analyzing user-provided eye features. To achieve this, we leverage OpenCV, …
Published in International Journal of Computer Science Languages · Vol. 1, Issue 2, 2023 · pp. 1–8 Read article
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Advances in Biological Systems Modeling for Predicting Drug Effects in Chronic Disease
Abstract: Biological systems modeling has emerged as a promising tool for understanding and predicting the effects of drugs in the treatment of chronic diseases. Chronic diseases, such as diabetes, cardiovascular diseases, and neurodegenerative disorders pose significant challenges to traditional drug development due to their complex, multifactorial nature. Systems biology approaches, which integrate computational modeling with experimental data, provide a holistic view of disease mechanisms and treatment responses. This review explores recent …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 17–22 Read article
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Designing an AI-Based Platform for Stock Market Prediction
Abstract: The AI-Based Platform for Stock Market Prediction is an advanced tool designed to forecast stock prices and market trends using artificial intelligence. This platform combines machine learning algorithms, real-time financial data, and sentiment analysis to provide investors with actionable insights. The platform uses advanced predictive techniques like Long Short-Term Memory (LSTM) networks and Gradient Boosting Machines to generate precise and reliable forecasts. Additionally, it incorporates interactive visualizations and portfolio optimization …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 3, 2025 · pp. 14–19 Read article
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Three-Dimensional Finite Element Modeling Study of Stress Distribution in Calcaneal Fracture
Abstract: The calcaneus is one of the biggest load-bearing tarsal bone in human body and therefore, many authors stress the importance of its biomechanical modeling and analysis in several aspects. We predicted possible fracture lines’ characteristics throughout the reconstruction of three-dimensional finite element modeling from CT slices and biomechanical analysis of stress state within talo-calcaneal complex, and its clinical validity was identified by comparing with radiographic/intraoperative findings. We reconstructed the 3-D …
Published in Research and Reviews : Journal of Surgery · Vol. 10, Issue 2, 2021 · pp. 11–34 Read article
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Electronic Resources of University Libraries: AI-Driven Management and Optimization
Abstract: In order to maximize accessibility, utilization, and efficiency, university libraries’ growing reliance on electronic resources (ER) has prompted the creation of sophisticated management techniques. The difficulty of handling enormous volumes of data has increased as educational institutions move from conventional physical collections to massive digital repositories. A key instrument in revolutionizing library operations, artificial intelligence (AI) offers creative ways to improve retrieval methods, manage digital resources more effectively, and customize …
Published in Journal of Advancements in Library Sciences · Vol. 12, Issue 3, 2025 · pp. 8–15 Read article
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Mechanical Performance Assessment of Hybrid FRP Laminates with Carbon Fiber Core Using Experimental and Numerical Approaches
Abstract: The high strength-to-weight ratio, corrosion resistance and design flexibility of Fiber-reinforced polymer (FRP) composites have attracted considerable attention in aerospace, automotive and structural applications. This work presents an experimental and finite element study on the tensile and flexural behavior of epoxy-based hybrid FRP laminates. Five laminate configurations were manufactured, including a unidirectional carbon fiber laminate and four hybrid laminates, Kevlar–Carbon–Kevlar (K/C/K), Glass–Carbon–Glass (G/C/G), Kevlar–Carbon–Glass (K/C/G), and Glass–Carbon–Kevlar (G/C/K). For all …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article