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562 articles for “combined model”
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A Lightweight Cost-Sensitive Explainable Ensemble Framework for Early Heart Disease Risk Prediction
Abstract: Cardiovascular disease is still one of the leading causes of death, and hence, the early prediction of risk is a very important task in preventive medicine. Although recent studies have shown encouraging results in the application of machine learning algorithms to the prediction of heart disease, it has been noticed that most of the algorithms are more concerned with accuracy-driven optimization than the concerns of safety and false negatives. In …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Pneumonia Identification Using Explainable Artificial Intelligence
Abstract: Pneumonia, including tuberculosis (TB), remains one of the leading causes of death worldwide, especially in regions where access to healthcare is limited. Early and accurate diagnosis is critical for effective treatment and better patient outcomes, but traditional methods are time-consuming and require specialized expertise. This study explores the use of advanced deep learning models VGG16, VGG19, and ResNet50 to detect pneumonia and TB from chest X-ray images. By leveraging transfer …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 01–11 Read article
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Integration of Vertical Axis Wind Turbines into Urban Environments: Feasibility and Design Considerations
Abstract: Abstract This study aims to comprehensively investigate the performance of Savonius rotor wind turbines through a combination of numerical simulations and experimental testing. Initially, 3-dimensional CAD software Solidworks and ANSYS will be utilized to design detailed models of the turbines. Numerical meshes will then be generated around these models using FLUENT software, incorporating the k-ε turbulence model to simulate fluid flow fields. Parameters such as drag coefficient, lift coefficient, pressure …
Published in Journal of Aerospace Engineering & Technology · Vol. 14, Issue 2, 2024 · pp. 20–25 Read article
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The Clinical Landscape of Wogonin: Advancing Targeted Treatments for Chronic Diseases
Abstract: The traditional Chinese medicinal herb Scutellaria baicalensis Georgi, commonly known as Chinese skullcap or Huang-Qin, has long been used to treat a variety of conditions, including cancer, viral infections, and seizures. Its pharmacological effects are largely attributed to the high concentration of flavones, particularly wogonoside, and its aglycone derivative, wogonin. Among the bioactive compounds found in S. baicalensis, wogonin has garnered the most scientific attention due to its potent therapeutic …
Published in Research & Reviews: A Journal of Pharmacognosy · Vol. 12, Issue 1, 2025 · pp. 46–52 Read article
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ANN Approach to Forecasting the Strength of Nano Silica Incorporated Geopolymer Composite
Abstract: Coal and steel industry by-products, such as fly ash (FA) and blast furnace slag (GGBS), have gained significant attention as precursors for geopolymer concrete (GPC) due to their high aluminosilicate content, offering a sustainable alternative to conventional cement. Nano silica (NS), recognized for its exceptional pozzolanic activity and ability to refine microstructure, has shown potential to enhance the mechanical and durability properties of GPC. This study investigates the influence of …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 267–278 Read article
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Optimizing Urban Mobility with AI-Based Traffic Management
Abstract: Urban mobility is a pressing concern in modern cities, plagued by issues like traffic congestion and pollution. This research involves, "Optimising Urban Mobility with AI-based Traffic Management", delves into the potential of Artificial Intelligence (AI) to revolutionize traffic management. Focusing on AI algorithms, data analytics, and sensor technologies, the research aims to enhance traffic flow, reduce congestion, and improve overall efficiency. Through statistical analysis and simulations, the research evaluates the …
Published in Trends in Transport Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 34–43 Read article
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Evaluation of Agro-based Adsorbents for Oil Spill Remediation in Freshwater and Saltwater Environments: Kinetic and Adsorption Model Analysis
Abstract: Environmental pollution caused by oil spills poses significant risks to both human health and ecosystems, particularly in regions like Nigeria’s Niger Delta, where oil spills are frequent. Conventional methods for oil spill cleanup have limitations, which has prompted research into alternative, more effective techniques. This study investigates the use of agro-based materials, specifically plantain and banana species, combined with clay soil as adsorbents for oil removal in freshwater and saltwater …
Published in Journal of Petroleum Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 22–32 Read article
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Deep Learning Enhanced Compressive Sensing for Wireless IoT Data Optimization and Weather Monitoring.
Abstract: This research explores the application of deep learning and compressive sensing in order to optimize data traffic in non-orthogonal multiple access (NOMA)-based wireless internet of things (IoT) networks and weather monitoring. Such a framework would be very effective and overcome pilot attacks and reconstruction losses for secure data transmission. In this regard, a strong communication model has been adopted based on power-domain NOMA for simultaneous wireless transmission by multiple IoT …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 2, 2024 · pp. 20–36 Read article
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Bayesian Optimization–Driven Operating Parameter Tuning for Maximizing Methane Yield in Anaerobic Digestion
Abstract: To achieve maximum methane production in an anaerobic digestion (AD) process, a combination of various operational parameters must be tuned nonlinearly in the digestion ecosystem. The conventional trial and error optimization methods are slow, resource consuming, and in most instances, cannot model the intricate parameter interaction in biogas production. The current work introduces a Bayesian Optimization-based model to optimize the set of conditions to maximize the level of methane produced …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 1–8 Read article
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Problems and Difficulties in the Additive Manufacturing of Composites with Carbon Fiber Reinforcement for Medical Application
Abstract: Amputation is more prevalent than one may think due to an accident, war, or disease. Prosthetics and associated orthotics have a combined global market value of $2.8 billion. Carbon fibre has found a market due to increased demand for foot prostheses. Fused deposition modeling (FDM) is a rapidly advancing three-dimensional (3D) printing technique. PEEK (polyether-ether-ketone) is a biocompatible, high-performance polymer that could potentially be utilised as an orthopedic surgery implant …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 1, Issue 1, 2023 · pp. 8–12 Read article
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Exploring the Genetic and Environmental Factors Contributing to Ovarian Cancer in Women in Mumbai, India
Abstract: Background: Ovarian cancer incidence in Mumbai has risen by 30% over the past decade, with an age-standardized rate of 9.1 per 100,000 women, contrasting stable trends in Western nations. This study investigates the interplay of genetic and environmental factors driving this disparity in Mumbai’s diverse population. Methods: A hospital-based case-control study was conducted at a hospital, enrolling 200 epithelial ovarian cancer cases (aged 30–70 years) and 400 age-matched controls. Germline …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 3, 2025 · pp. 12–17 Read article
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Cognitive AI-Based Quality Control and Operational Optimization of Polymer Composites for Healthcare Applications
Abstract: The use of polymer composite materials in healthcare is on the rise because of their adjustable mechanical characteristics, biocompatibility and structural flexibility. Yet, it is difficult to ensure stable quality of such composites due to process-related defects, heterogeneity of the material and the lack of real-time adaptive control. The proposed study suggests the use of cognitive AI-based framework of quality control and optimization of operation of polymer composite systems which …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 571–591 Read article
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Industrial Prognostics via Ensemble Machine Learning: An Uncertainty Aware Framework for RUL Estimation on NASA FD004 Telemetry
Abstract: Estimating the Remaining Useful Life (RUL) of industrial machinery in real-time is now vital for both operational safety and smart resource management. In the aviation industry, turbofan engines deal with constantly shifting flight conditions, making traditional, scheduled maintenance both expensive and prone to error. This paper addresses the flaws in common “point-prediction” AI models, which offer a single failure date without any margin for error, by introducing a new, uncertainty-aware …
Published in Journal of Aerospace Engineering & Technology · Vol. 16, Issue 2, 2026 Read article
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Power Management and Control of Hybrid Energy Storage System in a Standalone DC Microgrid
Abstract: The limited supply of fossil fuels and the growing global energy demand create global energy challenges. Power production systems based on renewable energy have become more prevalent due to increased challenges. As renewable power sources become more prevalent, erratic environmental conditions increase uncertainty in power production, control, and operation. To cope with these weather conditions, some support systems, such as storage devices, use renewable energy sources (RES). The hybrid energy …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 14, Issue 3, 2024 · pp. 41–52 Read article
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Hybrid Approach for Community Detection Using Deep Learning Techniques
Abstract: Community detection in complex networks is a fundamental problem with applications across diverse domains, ranging from social networks to biological systems and beyond. Traditional methods based on graph theory have been widely used for identifying communities within networks. However, the intricate and evolving nature of modern networks demands more sophisticated approaches. This research work proposes a hybrid approach that combines the strengths of deep learning techniques with traditional community detection …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 3, 2024 · pp. 18–26 Read article
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Algebraic Foundations of AES (Advanced Encryption Standard): Group Theory and Finite Field Applications in Symmetric Cryptography
Abstract: This paper presents a mathematical study of symmetric cryptographic algorithms, with a particular emphasis on the Advanced Encryption Standard (AES), which is one of the most widely used encryption schemes in modern security applications. The study highlights how abstract mathematical frameworks such as group theory, finite fields, and vector space concepts provide the foundation for the design, implementation, and analysis of AES. By approaching the algorithm from a mathematical perspective, …
Published in Recent Trends in Mathematics · Vol. 2, Issue 1, 2025 · pp. 12–16 Read article
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Real-Time Browser-Based Early Warning System for Cyberbullying Detection in Online Platforms
Abstract: The rise in social networking through internet-based communication tools, Instagram, and YouTube, to name a few, significantly increases the risk of cyberbullying, thereby increasing psychological trauma on users, especially children, through adverse emotional states like anxiety, depression, etc. For a long time, researchers have been enhancing detection tools to counter cyberbullying, but their ability to detect only after the fact, along with limited support for English-based architecture, is a major …
Published in International Journal of Computer Science Languages · Vol. 4, Issue 1, 2026 · pp. 09–15 Read article
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Data Security using Cloud Computing Adaption Framework
Abstract: AbstractIt is important to provide real-time data security for huge amount of data in cloud computing. A recent survey on cloud security stated that security of users’ data has the highest priority as well as concern. This can be able to achieve with an approach, which is systematic, adoptable and well structured. Therefore, here a framework called as Cloud Computing Adoption Framework (CCAF) has been developed which has been customized …
Published in Journal of Computer Technology & Applications · Vol. 7, Issue 3, 2016 · pp. 25–32 Read article
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Integrating Atmospheric Science: Understanding Greenhouse Gases, Aerosols, and Air Quality Dynamics
Abstract: Atmospheric science investigates the Earth’s atmospheric systems to understand their composition, dynamics, and the implications for climate, weather, and air quality. This review explores five primary areas within the field: atmospheric composition, atmospheric modeling, remote sensing, air pollution, and boundary layer dynamics, highlighting critical challenges and advancements. Rising levels of greenhouse gases (GHGs), including carbon dioxide and methane, continue to drive global warming, while feedback mechanisms—like cloud interactions and surface …
Published in International Journal of Atmosphere · Vol. 1, Issue 1, 2024 · pp. 32–35 Read article
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DFT/Data Guided Predictive Modelling of Absorption Maxima in the OLED Rubrene Derivatives
Abstract: This study investigates the optical properties of rubrene derivatives to develop an accurate predictive model for absorption maxima using computational chemistry and chemoinformatic techniques. We benchmarked various quantum chemical methods, identifying that the M06-2X/aug-cc-pVDZ method in dichloromethane (DCM) provided the strongest correlation with experimental data. Key molecular descriptors such as band gap, ionization potential, and electrophilicity index were calculated and analyzed using principal component analysis (PCA) to identify significant factors …
Published in International Journal of Cheminformatics · Vol. 4, Issue 1, 2026 · pp. 41–56 Read article