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107 articles for “Predictive Maintenance”
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Metamaterial-Based Thermal Shielding Structures for Reusable Hypersonic Space Transportation Systems
Abstract: The rapid development of reusable hypersonic space transportation systems has intensified the need for advanced thermal protection technologies capable of withstanding extreme aerodynamic heating conditions encountered during atmospheric re-entry and sustained hypersonic flight. Conventional thermal shielding materials often suffer from high structural weight, limited adaptability, thermal fatigue, and degradation under repeated thermal cycling. This study proposes a novel Metamaterial-Based Thermal Shielding Structure for Reusable Hypersonic Space Transportation Systems, integrating engineered …
Published in Journal of Aerospace Engineering & Technology · Vol. 16, Issue 2, 2026 Read article
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IoT-Connected Transparent Conductive Polymer–Silver Nano-wire Electrodes for Real-Time Performance Monitoring of Flexible Solar Panels
Abstract: Flexible photovoltaic technologies have emerged as promising energy harvesting solutions for wearable electronics, portable power systems, and Internet of Things (IoT)-enabled smart devices. However, the limited mechanical durability of conventional transparent conductive electrodes and the lack of integrated real-time monitoring restrict their long-term reliability. This study presents an IoT-connected transparent conductive polymer–silver nanowire (PEDOT:PSS–AgNW) hybrid electrode for flexible solar panels, combining high optoelectronic performance with continuous wireless performance monitoring. The …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article
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Marine Algal Fiber Reinforced Bio-Composites with Embedded Humidity Sensors for Coastal Smart Infrastructure
Abstract: The development of sustainable structural materials with integrated sensing capabilities has emerged as an effective strategy for improving the durability and resilience of coastal infrastructure exposed to aggressive marine environments. In this study, a multifunctional marine algal fiber reinforced bio-composite incorporating an embedded flexible humidity sensor was developed for real-time structural health monitoring applications. Marine macroalgae (Ulva lactuca) fibers were chemically functionalized using 3-aminopropyltriethoxysilane (APTES) to enhance fiber–matrix interfacial adhesion …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article
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Layered Metal–Polymer Hybrid Laminates with Embedded Impact Sensors for Connected Automotive Panels
Abstract: The increasing demand for lightweight, intelligent, and structurally reliable automotive components has accelerated the development of multifunctional hybrid materials capable of simultaneously providing superior mechanical performance and real-time structural health monitoring. In this study, a novel layered metal-polymer hybrid laminate incorporating an embedded flexible impact sensor was developed for connected automotive panel applications. The laminate was fabricated using AA6061-T6 aluminum alloy face sheets and a thermoplastic polyurethane interlayer through hot-press …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article
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A Review on Social Distancing ID Card
Abstract: The frequency of fire accidents in homes, industries, and public spaces has increased due to electrical faults, human negligence, and flammable materials. Traditional fire-fighting systems often depend on human presence and manual intervention, which delays the response time. To overcome this limitation, this project presents an Automatic Fire Extinguisher System based on Arduino and IoT technology for real- time detection and suppression of fire. Gas, temperature, and flame sensors are …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 Read article
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Pothole Detection utilising Machine Learning: A Review
Abstract: Potholes must be found and fixed quickly in order to maintain infrastructure, maximize transportation systems, and guarantee road safety. Using the Sequential API and the Keras library, this study presents a neural network model for pothole detection. Convolutional layers with ReLU activation, global average pooling, dense layers with dropout, and softmax activation for binary classification make up the model architecture. Image loading, resizing, array conversion, labeling, shuffling, normalization, and one-hot …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 1, 2025 · pp. 35–43 Read article
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Application-Driven Rule-Based Framework for Lubrication Failure Modes in Industrial Systems
Abstract: Modern lubricants increasingly rely on polymer-based composites, integrating synthetic base oils, polymer thickeners and solid additives like MoS₂ and PTFE for high-performance applications. These formulations not only enhance thermal and mechanical stability but also enable low-friction operation across diverse industrial conditions. Lubrication-related failures represent a critical cause of unplanned downtime and reduced reliability in industrial machinery. This paper presents an application-driven, rule-based framework designed to assess and mitigate lubrication failure …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 522–531 Read article
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Strategy for Improving Software Maintenance Using Machine Learning for Security Requirements: A Review
Abstract: Within the area of software technical education, the significance of software defect discovery has increased as a research focus to enhance program reliability. By maximizing testing resources and assisting developers in identifying potential problems using program defect predictions, program dependability is increased. Applying software engineering (SE) techniques to critical and intricate systems, like networking and security systems, is imperative. Traditional methods of predicting software maintainability have limitations, particularly in balancing …
Published in International Journal of Information Security Engineering · Vol. 2, Issue 2, 2024 · pp. 36–48 Read article
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Support Vector Machine Inspired Load Forecasting of a State University in Haryana
Abstract: Estimating the possible environmental impact and determining probable capital requirements are made easier with a solid grasp of electricity demand. Beginning in the middle of the 20th century, demand forecasting for electric power networks was studied theoretically. Prior to that, the study of demand forecasting had not developed because of the small scale of power networks. With the use of statistical prediction techniques, plans for the electric power industry have …
Published in Trends in Electrical Engineering · Vol. 15, Issue 2, 2025 · pp. 33–40 Read article
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Advanced Lithium-Ion Battery Prognostics: A Comprehensive Review of Machine Learning Approaches for Remaining Useful Life Prediction
Abstract: The lithium-ion battery (LIB), as one of the main sources for portable power systems, has been increasingly popular owing to its widespread applications in electric vehicles, consumer electronics, aerospace and renewable energy. Despite their advantages in high energy density and long cycle life, LIBs suffer from degradation over time of aging and cycling, resulting in loss of performance, safety issues, and economic bottlenecks. Predicting their Remaining Useful Life (RUL) is …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 2, 2025 · pp. 12–27 Read article
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Fracture Mechanics-based Assessment of Welded Joints in Structural Steel Components
Abstract: In many engineering applications, connection by welding are essential to the structural integrity of steel components. However, because of the intricate interplay between material qualities, welding techniques, and structural stress conditions, evaluating the dependability and safety of these welded connections continues to be a difficult challenge. A systematic framework that evaluates the behavior of cracks and faults in welded joints is provided by fracture mechanics, which also offers insights into …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 1, Issue 2, 2023 · pp. 16–22 Read article
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Advancements in Battery Storage Technology for Renewable Energy Systems: Improving Reliability and Efficiency of Sustainable Energy
Abstract: Advances in battery storage technology are critical to improved reliability and efficiency of renewable energy systems, underpinning a sustainable energy future. Innovations exist in many different kinds of battery technologies- being developed and tested, and the leading contenders include innovations such as lithium-ion and sodium-ion, and much newer entrants like the solid-state and lithium-sulfur batteries. These developments respond to growing needs for sustainable solutions towards better integration of intermittent renewable …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 17, Issue 2, 2026 Read article
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Optimizing Airline Efficiency Using Big Data and Predictive Analytics
Abstract: Recent technological advancements have resulted in the generation of vast volumes of data across industries, including the airline sector, supporting operational control and service quality. Big Data Analytics (BDA) enables organizations to analyze large and complex datasets to derive actionable insights that support informed decision – making and superior operational performance. This review paper systematically analyzes twenty relevant research studies to explore the application of Big Data Analytics (BDA) within …
Published in Journal of Advanced Database Management & Systems · Vol. 13, Issue 1, 2026 Read article
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Cloud-based Application Development and Optimization
Abstract: As cloud computing powers today’s applications, optimizing cloud-based development is crucial to achieve performance, cost effectiveness, and scalability. This research focuses on enhancing the design, deployment, and maintenance of cloud applications, tackling challenges in resource management, scalability, and resilience. We specifically explore dynamic resource allocation algorithms that use predictive analytics for auto-scaling based on workload variations, aiming to cut costs while preserving high performance. The study also investigates cross-cloud optimization …
Published in Journal of Open Source Developments · Vol. 12, Issue 1, 2025 · pp. 37–42 Read article
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A Study to Assess the Risk Factors Associated with Sudden Death in Population on Hemodialysis
Abstract: Background: Patients with chronic kidney disease (CKD) receiving maintenance hemodialysis (HD) experience disproportionately high mortality, with sudden death remaining a leading cause. Multiple clinical, biochemical, and care-related factors influence outcomes, yet comprehensive risk stratification models and the role of dialysis timing and early nephrology care remain inadequately explored in resource-limited settings. Objectives: This study aimed to (i) identify clinical and biochemical risk factors associated with mortality in HD patients, (ii) …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 16, Issue 1, 2026 · pp. 14–19 Read article
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Photosynthetic Living Plant–Integrated Cybernetic Sensors for Autonomous Environmental Intelligence
Abstract: The increasing demand for sustainable and autonomous environmental monitoring systems has motivated the development of biologically integrated sensing technologies that combine living organisms with advanced cybernetic intelligence. This study proposes a novel framework of Photosynthetic Living Plant–Integrated Cybernetic Sensors for Autonomous Environmental Intelligence, where living plants act as self-sustaining sensing platforms capable of continuously monitoring environmental conditions without external energy sources. By integrating bioelectrical signal acquisition modules, flexible nanomaterial electrodes, …
Published in Recent Trends in Sensor Research & Technology · Vol. 13, Issue 2, 2026 Read article
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A Study on the Use of AI and Sensors in Aerospace
Abstract: The synergistic combination of modern sensors including artificial intelligence (AI) has significantly changed the aeronautics industry's ongoing quest for increased safety, efficiency, and autonomy. The examination of the critical role these technologies play throughout the whole aerospace lifecycle from design and production to flight operations and maintenance is examined in this research. The eyes and ears of contemporary aircraft, sensors give an unparalleled amount and quality of real-time data about …
Published in Journal of Aerospace Engineering & Technology · Vol. 16, Issue 1, 2026 Read article
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Data-driven Approaches to Mineral Resource Management Using AI: A Brief Review
Abstract: The role of Artificial Intelligence (AI) in the mineral resource sector has become increasingly significant over the past few years, as industries seek to optimize and modernize their operations. AI encompasses a variety of technologies and techniques, such as machine learning, deep learning, and expert systems, that are now widely used in mineral exploration, resource estimation, and mine management. These AI-driven approaches have brought about a transformative shift, enhancing efficiency, …
Published in International Journal of Minerals · Vol. 2, Issue 1, 2025 · pp. 25–29 Read article
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Smart Framework for Personal Fuel Expense Tracking and Carbon Emission Assessment
Abstract: This study presents a smart system that is intended to assist individuals and administrators in tracking their fuel costs and keeping an eye on their daily carbon emissions. It makes it simpler to make decisions by examining fuel consumption and its effects on the environment. The technology gathers real-time emissions data from vehicles equipped with Internet of Things devices. It can predict future trends of emissions by utilizing AI-based predictive …
Published in Journal of Thermal Engineering and Applications · Vol. 11, Issue 3, 2024 · pp. 36–44 Read article
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Feature Extraction and Analysis of Bearing Faults: A Review
Abstract: One of the most important steps in identifying bearing problems is feature extraction. In order to provide a more meaningful dataset, it entails locating and extracting pertinent features from raw bearing vibration signals. Tasks involving categorization and prediction can then make use of these attributes. In many practical applications, such as monitoring rotating machinery or electronic components, the raw signals collected (e.g., vibration, current, temperature) are often complex, high-dimensional, and …
Published in Trends in Mechanical Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 20–28 Read article