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435 articles for “sub-modeling”
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A simple analytical theory for the preliminary structural design of submarine
Abstract: An Underwater Vehicle (UV) is designed to function underwater and range from an Autonomous UV to a submarine. The main difficulty that UV designers face is minimizing the weight of the pressure hull to maximize payload and propulsion velocity while reducing construction cost and time by employing appropriate material and design approaches. Herein, we examine applications geared toward submarines as well as the creation and development of an analytical model …
Published in Journal of Offshore Structure and Technology · Vol. 11, Issue 1, 2024 · pp. 1–11 Read article
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Formation and Fabrication of A 3D- Printed Polymer Propeller for Improved Propulsion and Minimal Acoustic Emission: A Comparative Study for Small Unmanned Vehicles
Abstract: The current research focuses on a comparative analysis of propeller designs to identify an option that enhances thrust efficiency while minimizing acoustic noise. The study evaluates three distinct types of propellers: the traditional three-blade propeller, the Sharrow propeller, and a novel aero propeller featuring an air foil-shaped cross-section. To facilitate a hands-on analysis, these propellers were produced using 3D printing technology, specifically employing ABS filament through a Fused Deposition Modelling …
Published in Journal of Polymer & Composites · Vol. 13, Issue 2, 2025 · pp. 252–261 Read article
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Optimizing Mechanical and Durability Properties of Eco-Friendly Composite Materials Using Recycled Fillers and ML Techniques
Abstract: The increasing demand for sustainable construction materials has intensified the exploration of recycled fillers as partial or full replacements for natural aggregates in composite materials. This study investigates the mechanical and durability performance of polymer matrix composites incorporating processed recycled fillers derived from construction and demolition (C&D) waste. Three distinct processing methods were employed to prepare the recycled fillers: untreated (URF), single processed (SPRF), and double processed (DPRF), with replacement …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 269–309 Read article
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Application of Grey Wolf Optimizer (GWO) strategy for Malware Analysis
Abstract: The ever-evolving landscape of cybersecurity necessitates continuous advancements in malware analysis techniques. This study explores the deployment of the Grey Wolf Optimizer (GWO) algorithm as a novel bio-inspired optimization mechanism to address the challenges posed by modern malware threats. The primary objective is to enhance various facets of malware analysis, including feature selection, parameter optimization, and the overall efficacy of malware detection models. The study begins by introducing the GWO …
Published in International Journal of Wireless Security and Networks · Vol. 1, Issue 2, 2023 · pp. 43–53 Read article
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Role of Carboxylesterases in Xenobiotic Metabolism and Detoxification: Insights for Cheminformatics Approaches
Abstract: Xenobiotics, which include a wide range of environmental pollutants, food additives, drugs, and carcinogens, are foreign chemical entities that enter the human body and may accumulate, leading to toxic effects. Phase I and phase II metabolic responses are among the detoxification procedures that are necessary to lessen these negative consequences. This review highlights the pivotal role of carboxylesterases (CES), enzymes involved in the hydrolysis of ester, amide, and thioester bonds …
Published in International Journal of Cheminformatics · Vol. 2, Issue 2, 2024 · pp. 9–17 Read article
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The Integrity of Eadic-Hofstee Plot Model to Predict the kinetic Parameters of Crude Oil Degradation using Vernonia amygdalina Stem
Abstract: The integrity of Eadic-Hofstee concept was tested for the determination of the functional coefficients and parameters of crude oil degradation kinetics. The techniques enhanced the relationship between the substrate divided by the specific rate of the substrate degradation against substrate concentration (TPH). The investigation reveals the values of the biokinetic parameters of maximum specific rate of substrate degradation (Vmax) and the equilibrium constant values of the substrate degradation (Ks). The …
Published in Journal of Petroleum Engineering & Technology · Vol. 14, Issue 2, 2024 · pp. 37–47 Read article
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Performance-Based Wind Response Analysis of Tall RCC Iregular Structures Using Autodesk Revit and Robot Structural Analysis
Abstract: The increasing trend of vertical construction has made wind effects a critical consideration in the design of tall reinforced concrete (RCC) buildings. The response of such structures is largely governed by their geometric configuration, stiffness characteristics, and modelling accuracy under wind loading conditions Wind loads are evaluated based on standard provisions such as IS 875 (Part 3): 2015, which provide essential guidelines for structural safety This study focuses on evaluating …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 3, 2026 Read article
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Describing Microbial Growth Rate in Solid Suspended Media using Monod and Haldane Models
Abstract: This work details the procedure for curve fitting the Monod and Haldane’s growth models in for solid suspended media such as food waste; in order to determine their parameters for solid suspended media such as food waste. Seven different batch runs; each with initial substrate concentration were studied at constant temperature. A modified method was used to quantify the mass of microbes during the rection process and data obtained were …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 11, Issue 1, 2024 Read article
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Malicious Network Traffic Detection Using Hybrid Feature Selection with Ensemble Neural Network
Abstract: The detection of malicious network traffic is a critical aspect of cybersecurity, aiming to protect sensitive data and maintain the integrity of network systems. This study introduces a novel approach that combines hybrid feature selection with ensemble neural networks to enhance the accuracy and efficiency of malicious network traffic detection. The dataset used in this study was obtained from Kaggle and offers a wide-ranging and varied collection of network traffic …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 27, Issue 3, 2025 Read article
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Thermal Management of Different Composites Materials Using a Convergent and Straight Vortex Tube
Abstract: The present study focuses on an in-depth and meticulous exploration into the intricate realm of thermal management in three distinct yet widely utilized composite materials—namely, Liquid Crystal Polymer (LCP) Composites, Glass Fiber Reinforced Polymers (GFRPs), and Aramid Fiber Composites (Kevlar). This investigation employs an innovative counter-flow vortex tube system, meticulously analyzing and comparing the thermal efficiency of these materials under different intake configurations. Specifically, two distinct geometrical intake designs—a straight …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 252–266 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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Strategic Solutions: How Mathematics Reshapes Industrial Landscapes
Abstract: One of the earliest and most fundamental fields of the physical sciences is mathematics. It has a significant impact on industrial enterprises' bottom lines and enhances their performance in the current data-driven market. One subfield of applied mathematics is industrial mathematics. It concentrates on issues that arise in the industry and seeks answers that are pertinent to the sector. The use of mathematical models and techniques to diverse industry difficulties …
Published in International Journal of Industrial and Product Design Engineering · Vol. 2, Issue 1, 2024 · pp. 16–23 Read article
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Survey of Predictive Models for Safe Route Predicting Using Machine Learning Techniques
Abstract: Safe route prediction is essential for the well-being and security of individuals in urban and rural environments. Machine learning techniques leverage historical data, real-time information, and algorithms to estimate the safety levels of different routes. The objective of safe route planning is to minimize risks, including crime-prone areas and accidents, reducing potential harm, property damage, and emotional distress. However, challenges arise from the complex and dynamic nature of urban environments, …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 11, Issue 1, 2024 · pp. 13–22 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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LLM Evolution: Secrets and Disadvantages
Abstract: The advancement of large language models (LLMs) has initiated a significant transformation in artificial intelligence, with substantial effects on fields including natural language processing, machine learning, and human-computer interaction. This research examines the diverse improvements in LLMs, emphasizing significant milestones from early models such as GPT-2 to contemporary state-of-the-art designs. The investigation highlights the novel training methodologies, such as unsupervised learning and transfer learning, which have markedly improved the capabilities …
Published in Journal of Web Engineering & Technology · Vol. 12, Issue 1, 2025 · pp. 25–36 Read article
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The Mediating Role of Label Trust in Shaping Green Purchase Attitudes Among Young Consumers: Sustainable Chemical Transparency in FMCG Packaging
Abstract: This study looks at the function of Perceived Chemical Transparency (PCT) in influencing consumers' Green Purchase Attitude (GPA) in the Fast-Moving Consumer Goods (FMCG) sector, with Label Trust (LT) serving as a significant mediating factor and Environmental Concern (EC) acting as a direct predictor. Based on the Theory of Planned Behavior and Signaling Theory, the study hypothesizes that clear disclosure of chemical and polymer-related information increases trust in eco-labels and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1308–1319 Read article
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High-Definition Electroencephalography: A New Horizon in Neurological Pathology Research
Abstract: The advent of high-density electroencephalography (HD-EEG) has catalyzed a paradigm shift in the exploration of neurological pathologies. This editorial underscore its transformative potential in elucidating brain dynamics and refining diagnostic approaches for a spectrum of conditions, spanning from epilepsy and dementia to cognitive impairments in preterm infants. Our objective is to optimize the utility of HD-EEG by emphasizing the imperative for methodological homogenization and fostering collaborative endeavors. The remarkable spatial …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 2, 2024 · pp. 15–21 Read article
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An Extensive Analysis of Computer-Aided Drug Design for Novel Psychotropic and Neurological Substances
Abstract: A comprehensive review of the use of computer-aided drug design (CADD) in the creation of innovative neurologic and neuropsychiatric medications is given in this article. It discusses the challenges in traditional drug discovery approaches and highlights the role of computational methods in accelerating the identification and optimization of drug candidates targeting psychiatric and neurological disorders. The method of finding new drugs has been completely transformed by Computer-Aided Drug Design (CADD), …
Published in International Journal of Brain Sciences · Vol. 1, Issue 2, 2024 · pp. 19–27 Read article
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Role of Artificial Intelligence in Simulation and Therapeutics in Neurodegenerative Diseases
Abstract: Neurodegenerative diseases, such as Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, etc., are a cause of significant mortality rates due to a lack of curative treatments and their complex nature. Traditional therapeutic methodologies have several disadvantages such as slow diagnosis and a lack of effective treatments. They mainly focused on the management of the disease rather than curing it. The integration of artificial intelligence in the simulation and therapeutics of neurodegenerative …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 19–29 Read article
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The Green Cost of Generative Ai: Environmental Sustainability Implications of Large-Scale Ai Systems
Abstract: Generative Artificial Intelligence (GenAI) has advanced rapidly in scale and complexity, enabling powerful capabilities in automated content creation, multimodal reasoning and real-time decision support across sectors. While these systems offer significant technological and economic benefits, their environmental implications are not fully examined. Large-scale GenAI models rely on high-performance computing infrastructure that consumes substantial energy and resources throughout their lifecycle, raising critical sustainability concerns. This paper offers a sustainability-oriented assessment of …
Published in International Journal of Sustainability · Vol. 3, Issue 1, 2026 · pp. 12–20 Read article