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55 articles for “modeling and simulation methodologies”
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Genetic Variability and Statistical Methods: Key Insights for Computational Genetics Research
Abstract: Genetic variability, defined as the differences in DNA sequences among individuals, serves as the foundation of evolutionary biology and plays a pivotal role in species’ adaptability, resilience, and overall survival. Advances in genomic technologies, particularly high-throughput sequencing, have enabled unprecedented exploration of genetic diversity, fostering the growth of computational genetics. This interdisciplinary field combines statistical methods and computational tools to analyze genetic data, identify patterns, and link phenotypes to genotypes. …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 3, 2024 · pp. 19–23 Read article
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A Sustainable and Green Prototyping Framework for Low-carbon and Resource-efficient Virtual Product Development
Abstract: The increasing emphasis on sustainable manufacturing has intensified the need for environmentally responsible design and development methodologies for polymer and polymer-composite materials, where material selection, processing routes, and waste generation play a critical role in overall environmental impact. This paper presents a Sustainable and Green Prototyping (SGP) framework that integrates Virtual Prototyping (VP), Life Cycle Assessment (LCA), and multi-objective optimization to systematically reduce carbon footprint, energy consumption, and material waste …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 459–471 Read article
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Representation-Theoretic Symmetry Reduction and Fuzzy-Grey Optimization of Modular Vibration Systems
Abstract: This paper presents a representation-theoretic framework for symmetry-aware vibration control in modular structural systems. Exploiting cyclic symmetry, the mass, damping, and stiffness operators are block-diagonalised into irreducible representations, reducing the full structural dynamics to a collection of lower-dimensional modal subsystems. This decomposition provides both computational efficiency and a rigorous mathematical description of symmetry-preserving dynamic behaviour. To account for imperfections arising in practical implementations, near-symmetry defects in stiffness and damping are …
Published in Emerging Trends in Symmetry · Vol. 2, Issue 1, 2026 · pp. 22–30 Read article
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Pathophysiology Reimagined: Integrating Systems Biology and AI for Disease Understanding
Abstract: Pathophysiology, the study of disease mechanisms at molecular, cellular, and systemic levels, has traditionally relied on reductionist approaches that often fail to capture the complex, dynamic, and interconnected nature of biological systems. Diseases such as cancer, neurodegenerative disorders, and infectious diseases arise from intricate interactions among genetic, epigenetic, metabolic, and environmental factors, necessitating integrative, data-driven methodologies for a deeper understanding. Systems biology has emerged as a powerful approach by leveraging …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 2, 2025 · pp. 63–71 Read article
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Machine Learning-Assisted Design and Optimization of Lightweight Polymer Composites for IoT-Enabled Automotive Applications
Abstract: This study aims to develop an integrated machine learning and optimization framework for the intelligent design of lightweight polymer composites suited for IoT-enabled automotive applications. The goal is to enhance material performance while satisfying multiple design constraints such as mechanical strength, thermal stability, and process compatibility. A curated dataset of polymer composite formulations was used to train a Random Forest Regression (RFR) model capable of predicting tensile strength, thermal conductivity, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 12–27 Read article
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Assessing the Robustness of Machine Learning Models for Wireless Intrusion Detection Under Adversarial Traffic Perturbations
Abstract: As the Internet of Things (IoT) devices and wireless communication networks continue to grow rapidly, protecting systems from cyber threats has become increasingly important. Machine learning–based intrusion detection systems (IDS) have shown strong potential in detecting abnormal and malicious network activities, yet their effectiveness and resilience when facing adversarial attacks are still not sufficiently explored. This research evaluates Machine Learning (ML) models–XGBoost, random forest, and multi-layer perceptron (MLP)—in detecting attacks …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 29–34 Read article
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Leveraging Generative AI for Test Case Creation in Complex Systems
Abstract: Modern software systems exhibit increasing complexity, demanding sophisticated testing methodologies to ensure reliability and functionality. Traditional manual testing approaches often struggle to keep pace with this complexity, leading to inadequate test coverage and increased risk of unforeseen issues. This study explores the potential of Generative AI (GAI) in revolutionizing test case creation for complex systems. We delve into the practical application of GAI techniques, such as Variational Autoencoders (VAEs) and …
Published in Recent Trends in Programming languages · Vol. 12, Issue 3, 2025 · pp. 16–22 Read article
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Enhancing Robot Autonomy: Integrating AI for Advanced Decision-making in Autonomous Robotic Systems
Abstract: The capabilities of autonomous robotic systems have been drastically changed by the rapid progress in artificial intelligence (AI) technologies. In this work, we investigate the integration of AI approaches to improve robot autonomy by presenting even more advanced mechanisms for decision-making. Almost all traditional robotic systems involve predefined algorithms, making them unable to cope with dynamic environments. They can also help with learning based on machine learning and deep learning …
Published in Journal of Advancements in Robotics · Vol. 11, Issue 3, 2024 · pp. 28–37 Read article
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Role of Generative AI in Redefining Data Analytics
Abstract: The rapid evolution of data-driven technologies has introduced both significant challenges and promising opportunities within the field of data analytics. Among the most impactful advancements is Generative Artificial Intelligence (Generative AI), a groundbreaking subset of AI that is reshaping how data is interpreted, generated, and utilized. Unlike traditional analytical tools that rely solely on existing data patterns, generative AI possesses the capability to create synthetic data, simulate complex scenarios, and …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 2, 2025 · pp. 01–07 Read article
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Aerodynamic Optimization of UAV Wings Using Machine Learning
Abstract: Unmanned Aerial Vehicles (UAVs) are increasingly deployed across defense, transportation, agriculture, and environmental monitoring, demanding improved aerodynamic efficiency to enhance endurance, stability, and payload capacity. Traditional aerodynamic optimization approaches, relying on computational fluid dynamics (CFD) simulations and wind tunnel experiments, are often time-consuming and computationally expensive. This study proposes a machine learning (ML)-driven framework for the aerodynamic optimization of UAV wing geometries, aiming to significantly reduce design cycles while improving …
Published in International Journal on Drones · Vol. 2, Issue 1, 2026 · pp. 1–7 Read article
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Development and Performance Evaluation of Hybrid Solar Water Heating and Distillation Systems for Sustainable Water Supply: A Comprehensive Review
Abstract: This review article delves into the comprehensive examination of hybrid solar water heating and distillation systems, underscoring their pivotal role in addressing global water and energy challenges. With the increasing scarcity of clean water and the growing demand for sustainable energy solutions, these hybrid systems offer a promising dual-purpose approach. The article synthesizes the latest advancements in technology, design methodologies, and performance evaluation metrics, providing a holistic view of the …
Published in Recent Trends in Fluid Mechanics · Vol. 11, Issue 1, 2024 · pp. 8–19 Read article
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Cyber-Secure IoT Framework for Monitoring Fiber-Reinforced Polymer Composites Using Embedded Sensors
Abstract: The present research paper suggests a cyber-safe Internet of Things system in real-time monitoring of fiber-reinforced polymer composites with inbuilt sensors. It is aimed at enhancing structural health maintenance, using sensual, intelligent analysis, and data protection in the same platform. Multi-layer architecture An embedded sensor, signal processing, anomaly detection and lightweight layer of cyber-security are developed. Experimental validation is done under controlled conditions and the performance is measured by these …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 434–458 Read article
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Evaluation of Critical MMAW Welding Defects Using Computer Simulation in Industrial Manufacturing Systems
Abstract: Manufacturing is one of the key sectors of any countries GDP and welding is one of the prime manufacturing processes of the manufacturing sector. Welding has several notable advantages over mechanical joining techniques, including higher structural integrity, design flexibility, and cost and weight lowers. Welded products/structures are subjected to serious issues of residual stresses and distortions. The performance and sturdiness of the welded structures are severely impacted by weld remaining …
Published in International Journal of Industrial and Product Design Engineering · Vol. 3, Issue 2, 2025 · pp. 18–26 Read article
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AI-Designed Functionally Graded Polymer Composites for Multifunctional Thin Films
Abstract: The design of multifunctional polymer composite thin films requires simultaneous optimization of mechanical, optical, barrier, and thermal properties—objectives often in conflict when using conventional homogeneous materials. This study presents an artificial intelligence-driven framework for designing functionally graded material (FGM) architectures in polymer nanocomposite thin films. We integrated machine learning with physics-based modeling to optimize compositional gradients across film thickness, achieving superior performance compared to homogeneous and discrete multilayer alternatives. A …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1026–1041 Read article
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Simulation and Experimental Analysis of Heat Treatment for Steel Tie Rods: A Review
Abstract: The study is related to the actual heat treatment and simulation of the physical deformation of the steel tie rod and compares the observations for process optimization. The general methodology is to go for either traditional or induction hardening after getting the chemical composition of the material, followed by tempering, which is a key technique for improving the mechanical properties of materials, strength, hardness, etc., and to release stresses. This …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 1, 2025 · pp. 43–51 Read article