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60 articles for “Physics-informed modelling”
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Comparing and Analysis of Various Automated Model for Number Plate Detection
Abstract: In this paper, we analyze the results by comparing different methods to identify the number plate and it is more suitable for detecting the number plate involved in accuracy and image processing than any other model. This paper presents the usage of pictures for physical changes. The page refers to the different advances required to extract content from any picture record and makes a different book document, including information removed …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 9, Issue 2, 2021 · pp. 20–24 Read article
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Digital Twin Assisted Intelligent Prediction of Polymer Composite Degradation Under Environmental Exposure
Abstract: Polymer matrix composites (PMCs) deployed in aerospace, marine, automotive, and renewable-energy structures are continuously subjected to coupled environmental stressors — ultraviolet (UV) radiation, moisture ingress, thermal cycling, and mechanical loading — that progressively degrade their mechanical performance. Conventional accelerated ageing tests and empirical lifetime models are time-consuming, destructive, and poorly suited to in-service, asset-specific degradation forecasting. This paper proposes a Digital Twin (DT) assisted intelligent prediction framework that fuses a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Automation and Robotics for Quality Control in Manufacturing: A Review of Technologies and Applications
Abstract: Automation and robotics technologies have rapidly evolved, transforming modern manufacturing processes by improving productivity, quality, and operational efficiency. This review examines key advancements such as cloud robotics, machine vision, Industry 4.0 robotics, Building Information Modeling (BIM) combined with Computer Numerical Control (CNC), joystick-controlled automation, and intelligent manufacturing systems. These technologies utilize artificial intelligence (AI), machine learning (ML), digital twins, collaborative robots, programmable logic controllers (PLCs), and cyber-physical systems (CPS) to …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 3, 2025 · pp. 36–48 Read article
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A Review on Vaccine Epidemiology
Abstract: The Present Review outlines the basic information regarding vaccines, vaccine epidemiology, Objectives and Scope of Vaccine Epidemiology, Studies and Methods involved in Vaccine Epidemiology, models involved in Vaccination Programs in detailed manner which can be greatly helpful and gives a clear picture to the epidemiologist, policy makers, physicians, public health experts, immunization program managers and other experts of medicine who are involving with immunization services. The present article ends with …
Published in Research and Reviews : A Journal of Immunology · Vol. 12, Issue 3, 2022 · pp. 27–36 Read article
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Harnessing AI and NLP to Transform Pharma Education Personalization, Learning, and Skill Development
Abstract: Particularly with NLP technologies, it is revolutionizing pharmaceutical education, enhancing human creativity, personalizing learning, and improving student outcomes. AI models like those from Open AI’s Chat GPT are increasingly integrated into educational practices that offer a solution to issues, such as teacher shortages, resource limitations, and the inefficient use of traditional teaching methods. This paper explores the diverse ways through which AI and NLP technologies are transforming pharma education within …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 1, 2025 · pp. 7–13 Read article
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Comparative Analysis of AI-Based Approach vs. Traditional Methods in Climate Modeling
Abstract: Climate modeling helps to predict the future of climate variations and human interference with environment. The traditional General Circulation Models (GCMs) are based on physics-derived mathematical equations but are very expensive in terms of computation. There are alternative ways to perform climate modeling in recent years with the rise and improvement of Artificial Intelligence (AI) based approaches in term of predictability, efficiency, and classification of extreme events compared to conventional. …
Published in Current Trends in Information Technology · Vol. 15, Issue 3, 2025 · pp. 26–32 Read article
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Deep Learning for Earth Observation Using Satellite Imagery: A Comprehensive Review
Abstract: Earth observation (EO) satellites provide continuous, large-scale information about the Earth's land, oceans, atmosphere, vegetation, infrastructure, and environmental conditions. The rapid growth of multispectral, hyperspectral, synthetic aperture radar (SAR), thermal, and high- resolution satellite missions has generated large volumes of heterogeneous spatial and temporal data. Conventional image-processing and machine-learning techniques often require manually designed features and may have difficulty representing the complex spatial, spectral, temporal, and multimodal characteristics of satellite …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 15, Issue 2, 2026 Read article
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Cross-layer Solutions in WSN Routing: A Review
Abstract: WSN is a less infrastructure wireless network which is embedded with large number of Sensor Nodes (SN). Its ad-hoc manner of device distribution allows it to monitor conditions under physical and environmental scenarios. Typically, SNs in WSN are installed in a specified geographical location to monitor required information. Due to SNs’ self-configuring ability, the exploitation of target is simpler. Though, its functioning is limited with factors such as energy efficiency, …
Published in International Journal of Wireless Security and Networks · Vol. 1, Issue 2, 2023 · pp. 26–36 Read article
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Image-Based Quantitative Mapping of Structure Property Relationships in Polymer Composite Materials
Abstract: The performance of polymer composite materials is intrinsically governed by their microstructural architecture, which is shaped by manufacturing conditions and constituent interactions. Despite extensive experimental characterization efforts, establishing transparent and quantitative structure–property relationships from microstructural images remains a challenge. In this study, an explainable image-driven framework is developed to systematically correlate microstructural features with composite property indicators. Microstructure images are processed to identify voids, fibers, and filler phases, from which …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 188–196 Read article
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Role of Fluid Engineering in Biomedical and Healthcare Systems: A Comprehensive Review
Abstract: Fluid engineering — the study and application of fluid behavior, transport, and interaction — has become a cornerstone of modern biomedical and healthcare systems. This review synthesizes the multifaceted roles fluid engineering plays across diagnostics, therapeutics, biomedical devices, and physiological modeling. Micro-fluidics enables precise manipulation of microliter and nanoliter volumes, facilitating rapid point-of-care diagnostics, high-throughput screening, and the fabrication of uniform nano particles for targeted drug delivery. In cardiovascular medicine, …
Published in Trends in Mechanical Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 1–5 Read article
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Structure Property Correlation of Polymer Dielectrics Using Electrical Response Data
Abstract: Polymer dielectrics are foundational to insulation, capacitors, embedded passives, and flexible electronics, where performance is governed by the frequency-dependent electrical response rather than a single dielectric constant. This study presents a spectroscopy-aware structure–property correlation framework that transforms dielectric response data into physically interpretable spectral fingerprints and learns mappings from polymer descriptors to these fingerprints for prediction and interpretation. Broadband spectra are standardized on a log-frequency grid and parameterized using relaxation-informed …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 315–324 Read article
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The Molecular Structure of Chemical Compounds by using Quantitative Calculations in Chemistry
Abstract: Computational chemistry has its roots in the early attempts of theoretical physicists, beginning in 1928, to solve the Schrödinger equation using mechanical calculating machines. These calculations verified that the solutions of the Schrödinger equation quantitatively reproduced experimentally observed properties of simple systems such as the helium atom and the hydrogen molecule. These approximate solutions of larger systems and exact solutions of simple model problems allowed chemists and physicists to provide …
Published in Journal of Catalyst & Catalysis · Vol. 12, Issue 2, 2025 · pp. 01–08 Read article
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Advanced Digital Twin and AI Integration for Real-Time Optimization in Polymer Production
Abstract: The integration of Internet of Things (IoT) with Artificial Intelligence (AI) technologies opens up considerable avenues for reshaping polymer manufacturing by improving operational effectiveness, securing exceptional product standards, and advancing sustainability in the environment. This academic manuscript delineates an advanced framework that integrates IoT and AI with synergistic technologies, including blockchain, edge computing, and digital twin methodologies, to revolutionize polymer manufacturing processes. The proposed architecture utilizes IoT sensors for the …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 81–89 Read article
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Adaptive Drift Correction in Polymer-Based Wearable Biosensors via Data-Driven Signal Modeling
Abstract: Polymer-based wearable biosensors have emerged as a promising technology for continuous health monitoring due to their mechanical flexibility, biocompatibility, and suitability for long-term physiological interfacing. However, prolonged exposure to biofluids, environmental variability, and mechanical deformation introduces signal drift, which significantly degrades measurement accuracy and limits clinical reliability. This paper presents a data-driven methodology for compensating signal drift in polymer-based wearable biosensors using adaptive signal processing and machine learning techniques. The …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 131–139 Read article
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Design of a Raspberry-pi based Wireless Adapter for Projector
Abstract: Wired world is transforming to wireless and this transformation generates necessity to innovate and create the wireless means. This paper proposes a wireless adapter to convert the existing wired projector into a wireless projector without major changes to projector hardware. Based on a development of the wireless adapter, a new feature of wireless projection is possible by transferring the information without any physical medium by establishing a wireless network between …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 2, Issue 1, 2015 · pp. 9–15 Read article
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Sentiment Analysis of E-Commerce Reviews using Machine Learning
Abstract: In e-commerce, sentiment pertains to the emotional responses, opinions, or perceptions that customers have about their online shopping experiences, including factors like product quality, service, and various processes such as ordering, shipping, and customer support. Sentiment analysis, which involves machine learning techniques, plays a crucial role in deciphering these sentiments. By using sentiment analysis, companies can obtain valuable insights from customer feedback from diverse online sources, including social media, surveys, …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 3, 2024 · pp. 25–37 Read article
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Errors-in-Variables Model for Photovoltaic Cell
Abstract: AbstractThe contribution of solar energy to the world's total energy supply has grown significantly. Energy from the sun is the most abundant and freely available energy on the planet. So, the importance of modelling the photovoltaic cell also increased remarkably. Many models for photovoltaic cell had been proposed since the beginning of the solar energy exploitation. Electronic equivalent circuit models, first-principles models and empirical models are the different modelling techniques …
Published in Journal of Semiconductor Devices and Circuits · Vol. 6, Issue 3, 2019 · pp. 8–15 Read article
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Smart City for Sustainable Development- A Review
Abstract: Smart Cities will attempt to utilize innovation, data &information to further develop framework &administrations. Smart city includes flood of change wherever individuals of specific city get a wide range of fundamental administrations as drinkable water, disinfection, transportation, streets, streetlamps, office of training, data innovation, medical clinic, nursery, stopping &inns, rail routes, air terminal network, fire alleviation, including calamity the board , well strong waste administration plan, so that impeccable neatness …
Published in Trends in Transport Engineering and Applications · Vol. 9, Issue 1, 2022 Read article
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Intelligent Earth: AI As A Catalyst For Climate Action
Abstract: Artificial Intelligence (AI) is assuming an increasingly influential role in climate science, providing advanced tools capable of interpreting vast, complex, and multi-dimensional environmental datasets. Traditional climate modeling approaches, while grounded in physical principles, frequently struggle to deliver high-resolution, real-time, and region-specific forecasts because of heavy computational demands, incomplete observations, and uncertainties in representing small -- scale processes. Artificial intelligence (AI) techniques, especially machine learning and deep learning, provide strong substitutes …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 4, Issue 1, 2026 · pp. 48–52 Read article
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AI and Machine Learning Approaches for Estimating Depression Severity: Techniques, Trends, and Applications
Abstract: Depression is a very common mental health disorder that results in a disorder of a person’s behavior, emotions, and cognitive abilities. Depression can be caused by environmental factors or hereditary factors. The person suffering from depression might have symptoms of suicidal thoughts, altering food patterns as well as sleeping issues. Depression is a global issue that has impacted millions of people globally having more effect on women worldwide. The complexity …
Published in Journal of Electronic Design Technology · Vol. 15, Issue 3, 2024 · pp. 29–38 Read article