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340 articles for “reliability modeling”
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Harnessing Marine Byproducts and Optimization of Biopolymer Extraction Quality Using Response Surface Methodology and Study of Its Physicochemical Properties
Abstract: Chitosan, a versatile biopolymer derived from chitin, holds immense potential across various industries owing to its antimicrobial, antioxidant, and biocompatible properties. This study aims to optimize the deacetylation process of chitin, sourced from shrimp shells, using Response Surface Methodology (RSM) to produce high-quality chitosan. The Box-Behnken Design (BBD) was employed to evaluate the effects of temperature, time, and alkali concentration on the degree of deacetylation (DD%), a key determinant of …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 125–139 Read article
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Multi-Scale Analysis of Polymer Based Energy Storage Systems for High Performance Battery Applications
Abstract: The energy storage systems based on polymers are becoming promising materials for the next generation of high performance batteries because of their excellent mechanical flexibility, improved safety, and favorable electrochemical properties. Even with computational tools in Python, polymer-based energy storage systems remain plagued by poor ionic conductivity, complicated electrochemical reactions and potential thermal runaway. Therefore, a multi-scale model is proposed to improve battery performance, thermal stability, reliability, and large-scale deployment …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1035–1048 Read article
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An Adaptive Approach for Real-Time Embedded System Design, Analysis and Optimization
Abstract: Real-time embedded systems are critical components in various domains, such as automotive, aerospace, healthcare, and industrial automation. The design, analysis, and optimization of these systems are vital to ensure their reliable and efficient operation. In this paper, we propose an adaptive approach for real-time embedded systems that aims to address the challenges faced during the development process while maintaining high-quality results. Our approach leverages adaptive techniques to dynamically adjust the …
Published in International Journal of Solid State Innovations & Research · Vol. 1, Issue 1, 2023 · pp. 8–14 Read article
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Structure–Property Correlation of Infill Topology and Density on Tensile and Flexural Performance of FDM-Printed PLA and ABS
Abstract: Additive Manufacturing (AM), particularly Fused Deposition Modeling (FDM), has become a widely adopted manufacturing technology due to its design flexibility, low cost, and capability for rapid prototyping. However, the mechanical performance of FDM-printed components is strongly influenced by internal structural parameters such as infill pattern and infill density, in addition to the intrinsic material behaviour. This study investigates the structure–property relationship between infill topology, density, and mechanical performance of PLA …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 4, Issue 1, 2026 · pp. 26–37 Read article
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Effects of Reels and short videos on human mind and Academic Life
Abstract: The rapid rise of short-form video platforms such as Instagram Reels, TikTok, and YouTube Shorts has fundamentally reshaped the way people consume information and entertainment. While these applications offer quick engagement and social connection, their excessive use has raised serious concerns about their psychological and academic impacts. This research investigates the relationship between short-form video addiction, mindfulness, academic anxiety, and academic engagement among university students. Drawing upon the theoretical framework …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 2, 2026 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
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Stock Market Prediction Using Machine Learning: Techniques, Challenges, and Future Directions
Abstract: The continuous advancement of machine learning (ML) technologies has significantly transformed the field of financial forecasting, particularly in the area of stock market prediction. The ability to accurately forecast stock price movements and market trends plays a crucial role in supporting informed investment strategies and effective risk management. This paper provides a comprehensive review of recent developments in the application of ML techniques for predicting stock market behavior. It classifies …
Published in E-Commerce for Future & Trends · Vol. 13, Issue 1, 2026 · pp. 10–16 Read article
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Experimental Validation and Implementation Framework for Optimized Methane Yield Prediction in Anaerobic Digestion
Abstract: The correct validation and realistic application of optimized anaerobic digestion (AD) models are essential steps in transferring biogas production systems to real-life. This paper outlines an experimental validation and deployment pipeline of an AI-optimized model of the methane yield prediction model based on the application of more advanced machine learning and Bayesian optimization methods. Others The validated surrogate-assisted optimization model was tested with controlled laboratory-scale AD experiments at optimized operating …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 4, Issue 1, 2026 · pp. 25–32 Read article
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Statistical Modeling for Weld Quality Assessment using AI SAW Welding of Mild Steel
Abstract: The main issue to the industries that apply Submerged Arc Welding (SAW) is quality assurance since the structural integrity dictates safety and the performance of the industry. The existing system of checking manuals is not only time consuming but also has human errors that make it mandatory to deploy automated intelligent systems. This study carries out an extensive comparison of the leading approaches based on the use of Artificial Intelligence …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 892–907 Read article
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Optimizing Heat Dissipation: Analysis of Air Cooled Fins for Electronic Equipments
Abstract: This paper focuses on the thermal management of electronic components in modern technologies like RADAR electronics, UAV and Drone technologies,Automotive Electronic Components etc. The main objective of this research is to design and develop an efficient heat dissipation system, using fins, for an electronic component with dimensions of 80 x 300 mm, dissipating 30W heat. The process starts by calculating essential parameters for fin design, followed by modeling the fins …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 3, 2025 · pp. 26–50 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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Study on the Profile and Flow Field Variation of Parachute Coating by Seven-hole Probe Method
Abstract: In general, the parachute test is a long test cycle, expensive, and difficult to measure with accuracy, which makes it a very laborious and time-consuming task. Therefore, attempts have been made to overcome this by using a parachute test stand or by simulation, but in our country, there is no numerical simulation of the parachute and there is no research on it. In this paper, the variation of the shape …
Published in Journal of Aerospace Engineering & Technology · Vol. 14, Issue 1, 2024 · pp. 26–37 Read article
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Predicting Multiple Diseases Using Machine Learning: A Data-Driven Approach
Abstract: The increasing prevalence of chronic and life-threatening diseases highlights the need for innovative healthcare solutions that enable early detection and proactive management. The Multiple Disease Prediction Platform is a web-based system utilizing machine learning (ML) and deep learning (DL) algorithms to analyze user-inputted health data, generating real-time predictions of potential health risks. By leveraging Python’s Streamlit library, the platform provides an interactive and accessible diagnostic experience, eliminating the need for …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 16–35 Read article
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IoT-Enabled Remote Patient Monitoring System Using Wearable Sensors
Abstract: In recent years, the Internet of Things (IoT) has revolutionized healthcare by enabling seamless connectivity between patients, medical devices, and healthcare professionals. The increasing demand for continuous health monitoring and early disease detection has driven the development of IoT-based remote patient monitoring systems. This paper presents an IoT-enabled framework that integrates wearable physiological sensors, wireless communication modules, and cloud- based analytics to facilitate real-time health tracking. The proposed system continuously …
Published in Recent Trends in Electronics Communication Systems · Vol. 13, Issue 1, 2026 Read article
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A Mathematical Perspective on Recent Cloud-Computing Trends for Scalable and Secure Social-Media Platforms
Abstract: Cloud computing underpins modern social-media platforms by providing elastic compute, storage, and data-processing pipelines capable of absorbing highly bursty workloads. This paper surveys recent cloud-native trends—serverless and event-driven design, container orchestration, edge/CDN offload, streaming analytics, and privacy-enhancing security controls—and formalizes their impact through a compact mathematical model. We express workload volatility using arrival-rate functions, use queueing-based capacity sizing to derive auto-scaling rules, and formulate an optimization objective that balances cost …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 35–40 Read article
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Deep Learning Applications in Bone Fracture Detection for Improved Radiographic Diagnostics
Abstract: Bone fracture detection is a critical aspect of medical diagnostics, traditionally relying on manual interpretation of radiographic images by experienced radiologists. This discipline has undergone a revolution with the introduction of machine learning (ML), which can improve accuracy, shorten diagnosis times, and lessen human error. This study investigates the use of different machine learning methods to enhance and automate the identification of bone fractures in radiography pictures. We utilized a …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 17–22 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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Impact of Fracture in Geometrical, Material, and Load Rate Characteristics on J-Integral
Abstract: The present study investigates the influence of load rate, geometrical parameters, and material properties on the J-integral behavior of AA2050-T84 aluminum-lithium alloy using three-dimensional elastic–plastic fracture mechanics (EPFM) analysis. Finite element simulations were carried out using the ABAQUS software to evaluate crack driving forces in compact tension (C(T)) specimens under various mechanical and thermal conditions. The study focuses on the combined effects of strain rate, temperature-dependent strain hardening, specimen thickness …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 4, Issue 1, 2026 · pp. 38–45 Read article
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Enhancement in Biomedical Polymer Nanocomposites: Biocompatibility and Mechanical Property Predictions using Machine Learning
Abstract: A machine learning (ML)-based framework is developed and validated through experimental analysis and comparative modeling to enhance system dependability and improve prediction performance. The proposed framework includes key stages such as data preprocessing, feature evaluation, model training, and performance benchmarking to determine the most effective prediction technique. Several machine learning models were evaluated, including Ensemble models, Artificial Neural Networks (ANN), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 275–296 Read article
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House Price Estimation Using Linear Regression: A Machine Learning Perspective
Abstract: House price prediction plays a crucial role in the real estate industry, helping buyers, sellers, and investors make well-informed decisions. Accurate estimation of property values enables stakeholders to assess market trends, plan investments, and minimize financial risks. This study focuses on the application of linear regression, a fundamental and widely used machine learning algorithm, to predict house prices based on multiple influencing factors. These factors include location, property size, number …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 Read article