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444 articles for “Dynamic analysis”
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A Sustainable EOQ Model for Declining Products Incorporating Cubic Demand, Variable Deterioration, Partial Backlogging, and Carbon Emission Optimization
Abstract: In this paper proposes a sustainable Economic Order Quantity (EOQ) model for inventory systems involving decaying items under cubic time-dependent demand, variable decaying rates, and partial backlogging while absolutely considering carbon emission costs. The model reflects practical market actions where demand initially increases and afterwards declines over time, and decay depends on the age of the item. To demonstrate the current model's applicability as well as evaluate the trade-off between …
Published in International Journal of Industrial and Product Design Engineering · Vol. 4, Issue 1, 2026 · pp. 20–28 Read article
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Thermally Adaptive Bio-Inspired VLSI Interconnect Model for Next-Generation Embedded Systems
Abstract: The increasing complexity of next-generation embedded systems has intensified the challenges associated with power dissipation, thermal instability, signal integrity, and interconnect reliability in Very Large- Scale Integration (VLSI) architectures. This research proposes a thermally adaptive bio-inspired VLSI interconnect model designed to enhance communication efficiency and thermal resilience in advanced embedded platforms. The proposed model integrates bio-inspired adaptive routing principles with dynamic thermal-aware interconnect management to optimize data transmission under varying …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 2, 2026 Read article
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Fractal-Entropy Guided Adaptive Signal Reconstruction for Non-Stationary Biomedical and Communication Systems
Abstract: This paper presents a novel Fractal-Entropy Guided Adaptive Signal Reconstruction (FEG- ASR) framework designed for accurate processing of non-stationary signals in biomedical and communication systems. The proposed approach integrates fractal dimension analysis with entropy- based feature evaluation to capture the intrinsic complexity and irregularity of time-varying signals. By dynamically adapting reconstruction parameters based on fractal-entropy measures, the method effectively separates noise from meaningful signal components while preserving critical information. The …
Published in Current Trends in Signal Processing · Vol. 16, Issue 1, 2026 Read article
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Enzyme Stability Prediction using BERT and CNN-A Deep Learning Approach for Enhanced Biocatalysis
Abstract: An important factor in determining the efficacy of industrial enzymes used in various biotechnological applications is their stability. The goal of this study is to develop a predictive model for industrial enzyme stability, which is essential to the efficiency of these enzymes in biotechnological applications. The research takes a comprehensive strategy to comprehend the parameters affecting enzyme stability by combining statistical analysis, deep learning algorithms (BERT and CNN), and molecular …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 14, Issue 2, 2024 · pp. 19–35 Read article
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Data Mining for E-Commerce and Social Media: Insights and Future Research Directions
Abstract: The fast expansion of e-commerce and social media has heralded a new era of data-rich settings, with enormous quantities of user interactions, preferences, and transactions generated on a daily basis. Data mining has developed as a critical strategy for leveraging big datasets, allowing businesses to gain concrete knowledge and drive decision-making. Data mining in e-commerce improves operational efficiency and user pleasure by allowing for personalized recommendations, consumer segmentation, fraud detection, …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 1, 2025 · pp. 14–23 Read article
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Network Security and Risk Technologies
Abstract: This research work delves into the dynamic domain of network security risk, providing a comprehensive analysis of corruption of data. The study explores strategic models aimed at strengthening network defenses in response to the continually changing threat environment. In the past, network security has relied on various technologies to mitigate risks, which include Firewalls, Virtual Private Networks (VPNs) and Encryption Protocols. The research scrutinizes the role of technologies such as …
Published in Journal Of Network security · Vol. 13, Issue 3, 2025 · pp. 26–34 Read article
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Investigation on Thermal and Modal Analysis of Brake Disc Made of SS410 And SS304 Using ANSYS
Abstract: The Primary purpose of the investigation is to investigate the vibration and noise that are present in the braking system. As a result of the application of braking force, the kinetic energy of the vehicle was transformed into heat, sound, and vibrational energy. The dynamic structural characteristics of the components that make up the braking system are closely linked to the modal behaviour, which refers to the vibration modes that …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 346–358 Read article
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Centrality in Social Network Analysis: A Comprehensive Review for Students
Abstract: Centrality, a fundamental concept in social network analysis (SNA), plays a pivotal role in understanding the structural dynamics and information flow within networks. This studyoffers an extensive examination of centrality metrics and their utilization in diverse fields. We begin by defining centrality and exploring its significance in characterizing the importance of nodes within a network. Subsequently, we delve into the literature review by different authors and most employed centrality metrics, …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 2, 2023 · pp. 1–8 Read article
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Efficient Clustering Techniques for Data Stream Mining
Abstract: Data mining mainly works on a massive database for storing heavy amount of data. It is generally essential for extracting the meaning insights from the massive, continuously growing database. The traditional method often struggles with sheer volume and the dynamic nature of the modern data. Data stream mining allows for the real-time analysis, means insights are generated as the data arrives, and not after the long batch process. This continuous …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 2, 2025 · pp. 26–32 Read article
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Magnetorheological Composite Dampers for Railway Wagon Suspension: Modelling Validation and Performance Analysis
Abstract: Railway wagons encounter continuous vibrations due to track irregularities, resulting in reduced ride comfort and higher dynamic loads. Conventional suspension systems based on springs, hydraulic dampers, or air suspensions provide only limited vibration mitigation. This work investigates the application of magnetorheological (MR) fluid-based dampers, where a polymeric carrier oil (silicone oil) reinforced with carbonyl iron particles serves as a smart composite suspension medium. The MR fluid is synthesized and characterized …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 43–63 Read article
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Modal Analysis of RC Masonry Infill Model and Prototype Frames with Openings
Abstract: Modal evaluation is the technique of figuring out the inherent dynamic traits of the shape in phrases of herbal frequencies and mode shapes and the usage of them to create a mathematical version for its dynamic behavior. The dynamics of a structure is defined by frequency and position. Modal evaluation offers the records regarding to exceptional modes of vibration, exceptional form that may be taken up via way of means …
Published in Journal of Structural Engineering and Management Read article
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Signal Drift Compensation in Polymer-Based Wearable Biosensors Using Data Processing Techniques
Abstract: Polymer-based wearable biosensors have emerged as promising platforms for continuous physiological monitoring due to their mechanical flexibility, low operating voltage, and compatibility with soft biological interfaces. However, their long-term deployment remains challenging because of signal drift caused by polymer ageing, hydration–dehydration cycles, ionic trapping, and environmental variations. These effects introduce baseline fluctuations and sensitivity degradation, which compromise the reliability and interpretability of physiological measurements. This study proposes a data-processing–driven framework …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 197–207 Read article
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Revealing the Hemodynamic Orchestra: Contrasting Analysis of Blood Flow Patterns in a Bifurcated Carotid Artery
Abstract: Understanding blood flow patterns in the carotid artery (CA) is crucial for detecting cardiovascular diseases. Computational fluid dynamics simulations compared non-Newtonian (non-Newt) and Newtonian (Newt) models under pulsatile and laminar flow. CA geometry was accurately designed using ANSYS Space Claim & Fusion360, and simulations were run in ANSYS Fluent. Discrepancies between non-Newt and Newt models were found, especially in bifurcation's distal regions prone to plaque. Pressure ranged from 27.870 Pa …
Published in Journal of Polymer & Composites · Vol. 11, Issue 13, 2023 · pp. 229–247 Read article
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Numerical Analysis of Straight Wire and Helical Wire wrap 2x2 Rod Bundle with Supercritical Water
Abstract: Investigations using computational fluid dynamics (CFD) have been conducted on a 2x2 rod bundle that has been wrapped with both straight and helical spacer wires. The bundle has been wrapped with both types of spacer wires. There have been investigations conducted in this regard. The wires that have been coiled have been wrapped around another rod bundle that has been looped around them. An examination and investigation into the employment …
Published in Journal of Nuclear Engineering & Technology · Vol. 15, Issue 3, 2025 · pp. 1–5 Read article
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Harnessing Machine Learning for Stock Movement Prediction: A Review of Current Approaches
Abstract: Stock price prediction is a crucial task in financial analysis, aiding investors and traders in making informed decisions. This study investigates the use of deep learning methods, particularly Long Short-Term Memory (LSTM) networks, for predicting stock prices based on historical market data. The dataset, sourced from Yahoo Finance, consists of time-series stock price data, which is preprocessed, feature-engineered, and visualized to improve prediction accuracy. The model's performance is assessed using …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 29–40 Read article
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Digital Frontiers in Life Sciences: The Transformative Role of Computing in Modern Biology
Abstract: The integration of computers in the biological sciences has revolutionized research and experimentation, facilitating advancements in areas such as genomics, bioinformatics, systems biology, and ecological modeling. The ability to process vast amounts of biological data efficiently has transformed how scientists study complex biological systems and phenomena. Computational tools enable the analysis of DNA sequences, protein structures, metabolic pathways, and ecological dynamics, which were previously beyond the reach of traditional laboratory …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 1, 2026 Read article
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Comprehensive Introduction: Epoxy and Polyurethane Floor Coatings—A Critical Evaluation for Modern Industrial Applications
Abstract: Industrial flooring systems are essential for ensuring operational durability, safety, and longevity in demanding environments. Epoxy and polyurethane (PU) coatings represent two predominant technologies, each offering distinct mechanical, chemical, and aesthetic profiles tailored to specific performance requirements. Epoxy systems, formed through the crosslinking of bisphenol-A-based resins with amine hardeners, excel in high-strength, chemically aggressive settings due to their superior hardness, adhesion, and chemical inertness. In contrast, PU coatings, synthesized from …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 13, Issue 1, 2026 · pp. 14–23 Read article
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Computational Approaches to Understanding Cellular Signaling Pathways
Abstract: Cellular signaling pathways are fundamental in regulating vital processes, such as cell growth, differentiation, and apoptosis. The intricate and interconnected nature of these signaling networks requires sophisticated methods for their analysis. Computational approaches, including mathematical modeling, network analysis, and machine learning, have revolutionized the way researchers analyze and simulate cellular signaling. This article provides a comprehensive overview of computational strategies employed to model signaling pathways, with a focus on integrating …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 2, Issue 2, 2024 · pp. 8–13 Read article
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Comparative Analysis of Serial and Parallel Robot Mechanisms for Industrial Automation
Abstract: Serial and parallel manipulators represent two major mechanical architectures in industrial automation, each with distinct strengths and trade-offs. This study presents a detailed comparative analysis of serial-chain (open-kinematic) robots and parallel-kinematic manipulators (PKMs) with a focus on industrial automation tasks. It covers kinematics, static accuracy and stiffness, dynamics and actuation requirements, control and calibration burdens, workspace and singularity behaviour, and practical industrial considerations (cost, integration, safety, maintenance). Serial robots, exemplified …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 2, 2025 · pp. 22–26 Read article
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Exploring AI-Driven Student Performance Analysis as a Dimension of an AI-Powered Assessment and Feedback System: A Comprehensive Review
Abstract: The rapid proliferation of artificial intelligence (AI) in educational technology has heralded a paradigmatic transformation in assessment methodologies, transitioning from static, summative evaluations to dynamic, data-driven systems that emphasize continuous formative feedback. This comprehensive review interrogates AI-driven student performance analysis as a cardinal dimension of AI-powered assessment and feedback systems (AI-PAFS), synthesizing findings from forty-five rigorously curated open-access empirical studies published between 2015 and 2024. Employing a methodological lens, the …
Published in Current Trends in Information Technology · Vol. 16, Issue 1, 2025 · pp. 24–31 Read article