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1977 articles for “integrity” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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IoT Sensors to Monitor Pipeline Pressure and Flow Rate Combined with ML-Algorithms to Detect Leakages
Abstract: In the field of fluid mechanics, pipelines are the lifeblood of industries, transporting everything from natural gas and oil to water and chemicals. Maintaining their integrity is paramount for safety, economic efficiency, and environmental protection. Traditional leak detection methods explained in fluid mechanics can be slow, expensive, and sometimes fail to identify small leaks early enough to prevent significant damage. However, the convergence of Internet of Things (IoT) and Machine …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 2, 2025 · pp. 40–48 Read article
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Radiation-Resilient AI: Next-Generation Robotic Systems with Adaptive Machine Learning for Nuclear Facility Management
Abstract: The increasing complexity of nuclear facility operations, decommissioning activities, and emergency response scenarios necessitate the development of advanced autonomous systems capable of functioning in highly radioactive environments. This paper presents a comprehensive review of radiation-resilient artificial intelligence systems integrated with next-generation robotic platforms, specifically designed for nuclear facility management applications. We examine the convergence of adaptive machine learning algorithms, radiation-hardened hardware architectures, and intelligent robotic systems that can operate autonomously …
Published in Journal of Thermal Engineering and Applications · Vol. 15, Issue 2, 2025 · pp. 12–21 Read article
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Fuzzy Probability Distributions and Their Applications in Uncertain Data Analysis
Abstract: This study explores the use of fuzzy probability distributions in data analysis under uncertain conditions, with a specific focus on their implementation in evaluating call center customer satisfaction. Traditional probability models rely on precise parameters, often failing to account for the inherent variability and subjectivity present in real-world data. In contrast, fuzzy probability distributions, which integrate fuzzy logic principles, offer a more adaptable and realistic framework for addressing such complexities. …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 3, 2024 · pp. 1–8 Read article
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VHDL Programming for Side-Channel Attack Countermeasures in IoT Security
Abstract: The Internet of Things (IoT) landscape is expanding rapidly, connecting billions of devices across diverse domains. This interconnectedness, while offering unprecedented convenience and efficiency, also creates a fertile ground for security vulnerabilities. Among these threats, side-channel attacks (SCAs) pose a significant risk, particularly targeting the cryptographic implementations that underpin IoT security. SCAs exploit information leaked from the physical execution of cryptographic algorithms, such as power consumption, timing variations, and electromagnetic …
Published in Journal of VLSI Design Tools and Technology · Vol. 15, Issue 2, 2025 · pp. 20–33 Read article
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The Role of Simulation and Digital Twins in Enhancing Mechanical Production Efficiency: A Systematic Review
Abstract: In the evolving landscape of smart manufacturing, simulation technologies and digital twin (DT) systems have emerged as pivotal tools for enhancing the efficiency, agility, and sustainability of mechanical production processes. This systematic review investigates how the integration of simulations and DTs contributes to performance improvements across various stages of mechanical manufacturing—ranging from design and process optimization to predictive maintenance and real-time monitoring. While simulations provide the ability to model, test, …
Published in Journal of Production Research & Management · Vol. 15, Issue 2, 2025 · pp. 31–36 Read article
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IoT-Based Smart Electrical Board Using Google Assistant: An Enhanced Approach
Abstract: The Internet of Things (IoT) has revolutionized home automation by enabling seamless connectivity between smart devices and cloud services. By enabling intelligent and remote control of home systems like lighting, security, and climate control, this integration greatly enhances user control, convenience, and efficiency. The study introduces an improved IoT smart electrical board that can be connected to Google Assistant to enable voice commands for controlling household appliances. By combining modern …
Published in Journal of VLSI Design Tools and Technology · Vol. 15, Issue 2, 2025 · pp. 1–5 Read article
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Dynamic Mechanical Analysis of Carbon Fiber Reinforced Polymer Composites
Abstract: This study investigates the thermal decomposition and mechanical properties of Fiber-Reinforced Polymer Composites (FRPCs) using Dynamic Mechanical Analysis (DMA). The research focuses on improving the recycling and recovery process of Carbon Fiber-Reinforced Polymers (CFRPs), addressing environmental concerns regarding their disposal. By analyzing the effects of different heating rates (5°C and 10°C per minute) and atmospheric conditions (nitrogen, oxygen, and a combination of both), the study identifies optimal parameters for maximizing …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 386–393 Read article
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The Role of Polymer Chemistry in Developing a Novel Polymer-Based Retromolar Endotracheal Tube
Abstract: This study presents the development and characterization of a novel polymer-based modified endotracheal tube designed for retromolar intubation. The tube is manufactured using medical-grade polyvinyl chloride (PVC) with reinforced polymeric structures to enhance flexibility while maintaining lumen integrity. The incorporation of a preformed lateral curvature mitigates airway resistance and airflow reduction caused by manual bending, ensuring an optimal balance between rigidity and adaptability. Additionally, the integration of polymer-based ligature wires …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 14–20 Read article
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Biomedical Applications in Polymer Chemistry Innovations
Abstract: In recent years, polymers and composite materials have been extensively utilized in fabricating electro-mechanical devices for medical applications, including gum massagers for edentulous patients. These devices aid in oral tissue stimulation, improving circulation and overall gum health. This paper explores the application of polymer chemistry in the fabrication of a compact electro-mechanical gum massager designed for edentulous individuals. The device employs biocompatible elastomeric polymers that offer flexibility, durability, and controlled …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 861–868 Read article
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Dielectric Elastomers in Actuation and Energy Applications: Material Behavior and Design Strategies
Abstract: Dielectric elastomers (DEs), a class of electroactive polymers, have attracted significant attention for their ability to undergo large, reversible deformations under electric stimulation. This unique capability makes them highly suitable for a range of actuation and energy harvesting applications, especially in the emerging fields of soft robotics, flexible electronics, artificial muscles, and sustainable power generation systems. DEs offer compelling advantages such as low weight, mechanical flexibility, high energy density, and …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 3, Issue 1, 2025 · pp. 13–18 Read article
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Conductive Polymers for Electro-Mechanical Systems: Structure–Property Relationships and Mechanical Behavior Under Stress
Abstract: Conductive polymers represent a unique class of functional materials that combine the electrical characteristics of metals with the mechanical flexibility of polymers. These dual properties are critical for the next generation of electro-mechanical systems, including wearable sensors, soft robotics, structural health monitoring (SHM), and biomedical actuators. However, the mechanical performance of conductive polymers under diverse stress conditions—such as elongation, cyclic loading, bending, and impact—remains a key challenge, limiting their long-term …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 3, Issue 1, 2025 · pp. 25–30 Read article
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Analysis of a Battery Pack Module for a Formula Student Car
Abstract: This research aims to evaluate the development of a high-voltage accumulator system that meets established standards of safety and operation. It examines key components, protocols, and techniques used in its creation while assessing performance in electronic cooling and structural integrity. Polymers, serving as electrical insulators and flame retarders, have found an interesting application in EV battery packs. This study focuses on polycarbonate materials' ability to withstand thermal and structural loads …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 320–339 Read article
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Isolation and Characterization of Glucuronide Compound from Luffa Tuberosa (Roxb.) for Potential Applications in Polymer Chemistry
Abstract: This study explores the isolation process of glucuronide compounds from Luffa tuberosa (Roxb.) using an efficient and cost-effective method. The extracted compound, Gypsogenin-3β-O-β-D-Methyl glucuronide, is characterized using spectroscopic techniques such as IR, NMR, and Mass Spectrometry. The polymeric nature of glucuronide-based compounds and their potential applications in polymer and composite materials are discussed. The findings highlight the suitability of glucuronide derivatives in biomedical, pharmaceutical, and polymeric drug delivery systems. Additionally, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 566–572 Read article
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Machine Learning Pipelines: A Survey on Automation, Scalability, and Deployment Strategies
Abstract: Machine learning (ML) has become a critical enabler of intelligent applications across domains, requiring robust, efficient, and scalable deployment workflows. This review paper provides an in-depth overview of machine learning pipelines, emphasizing three key dimensions: automation, scalability, and deployment methodologies. It begins by exploring automation techniques that reduce manual effort in data ingestion, preprocessing, model selection, and hyperparameter tuning. Tools such as AutoML, TFX, and workflow orchestration platforms are examined …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 17–28 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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Shell Programming with Sensor Systems and Applications for Human Cognition
Abstract: Shell programming provides a flexible interface to sensor systems, enabling robust scripting for real-time data acquisition and processing, as well as integration with perception components. Such sensors have human analogs—tactile, physiological, and behavioral—and are increasingly embedded within health, mobile, and smart environments to capture fine-grained details of human cognition. Using shell scripts, the system can automatically collect sensor data, fuse multimodal data, and perform adaptive behavioral monitoring, allowing researchers and …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 41–45 Read article
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Assessing Air Quality, Climate Change, and Migration Dynamics in Delhi NCR: A System Dynamics Approach
Abstract: As climate change accelerates and environmental degradation worsens, urban centers like Delhi NCR are under increasing pressure from internal migration. Poor air quality—especially in rural and peri-urban regions—emerges both as a driver of out-migration and a deterrent for in-migration to already burdened cities. This study develops a system dynamics (SD) model that integrates climate variables, air pollution metrics, economic indicators, governance quality, and migration behavior to simulate population flows into …
Published in Recent Trends in Mathematics · Vol. 2, Issue 1, 2025 · pp. 7–11 Read article
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Retrieval Augmented Generation for Question Answering in Financial Documents
Abstract: In recent years, the integration of Question Answering (QA) with the Retrieval Augmented Generation (RAG) system has transformed to interact with numerous documents. It uses Natural Language Processing (NLP) techniques to improve accuracy and relevant responses derived from huge documents. RAG integrates the advantages of the retrieval and generation process, which allows systems to generate natural responses and extract context from multiple sources. The main reason to use RAG is …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 2, 2025 · pp. 62–68 Read article
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Forecasting Commodity Prices Using Deep Learning Techniques: An Empirical Evidence from India
Abstract: Commodity price forecasting is instrumental in financial markets, providing framework for investment choices and risk management practices. Traditional models, including statistical and machine learning approaches, have limitations in capturing the nonlinear and volatile nature of commodity prices. Deep learning (DL) techniques have emerged as promising alternatives, leveraging advanced neural networks to enhance predictive accuracy. This study presents a thorough and comprehensive examination of deep learning applications in commodity price prediction, …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 08–12 Read article
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Exploration of Advanced Phase Change Materials for Thermal Energy Storage in Renewable Energy Systems: An Overview
Abstract: Phase Change Materials (PCMs) are increasingly vital for improving thermal energy storage (TES) systems. Their ability to absorb and release heat efficiently makes them ideal for renewable energy applications, enhancing energy efficiency, reducing waste, and supporting sustainable energy solutions across various sectors like solar power and building temperature regulation. Their ability to store and release latent heat during phase transitions makes them ideal for addressing the intermittency of renewable energy …
Published in Journal of Thermal Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 10–14 Read article