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270 articles for “election prediction”
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Multiphysics Optimization of Polymer–Metal Hybrid Electrode Geometry in Electrostatic Precipitators for Enhanced Particle Collection Efficiency
Abstract: Electrostatic precipitators (ESPs) remain one of the most effective technologies for controlling fine particulate emissions in industrial exhaust systems. However, their performance is strongly influenced by electrode geometry and material characteristics, which govern electric field distribution, corona stability, and particle migration behaviour. In this study, a comprehensive numerical investigation is carried out to optimize electrode geometry using a multiphysics modelling framework, while introducing a novel polymer–metal hybrid design to enhance …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 701–716 Read article
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DFT/Data Guided Predictive Modelling of Absorption Maxima in the OLED Rubrene Derivatives
Abstract: This study investigates the optical properties of rubrene derivatives to develop an accurate predictive model for absorption maxima using computational chemistry and chemoinformatic techniques. We benchmarked various quantum chemical methods, identifying that the M06-2X/aug-cc-pVDZ method in dichloromethane (DCM) provided the strongest correlation with experimental data. Key molecular descriptors such as band gap, ionization potential, and electrophilicity index were calculated and analyzed using principal component analysis (PCA) to identify significant factors …
Published in International Journal of Cheminformatics · Vol. 4, Issue 1, 2026 · pp. 41–56 Read article
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AI-Driven Lightning Strike Prediction Using Polymer-Integrated Sensor Platforms for Climate-Resilient Energy Systems in India
Abstract: Lightning strikes are a major climate-related threat to India, resulting in severe human injuries as well as regular damages to the power transmission network and renewable energy infrastructure. This research aims to introduce the concept of an AI-based lightning strike prediction and mitigation system with the integration of polymers for making climate-resilient energy infrastructure. Multidata are collected based on satellite images, climate variables, as well as surface-based sensing modules, and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 234–242 Read article
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Strength Assessment of RCC Beams Subjected to Corrosion
Abstract: The damage assessment of civil structural members is one of the most important and recently emerging fields in engineering. Deterioration of a structure may occur due to a host of factors such as poor workmanship, improper maintenance, atmospheric effects, accidents, natural calamities. Certain causes like environmental effects, natural calamities cannot be controlled. Therefore, durability of concrete structures especially those exposed to aggressive environments is of great concern. Many deterioration causes …
Published in Recent Trends in Civil Engineering & Technology · Vol. 2, Issue 1-3, 2012 · pp. 139–152 Read article
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Optimized Machine Learning Framework for Battery State Prediction in Smart Charging Systems
Abstract: Good estimation of battery states, including State-of-Charge (SoC), State-of-Health (SoH), and Remaining Useful Life (RUL), are important in managing energy wisely and controlling the adaptive charging. This work introduces a streamlined machine learning model based on the ability to use multi-dimensional sensor measurements in terms of voltage, current, temperature, and cycle number to forecast battery conditions with high accuracy. Decent preprocessing, such as noise elimination, feature scaling, and calculated features, …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 55–66 Read article
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Fabrication, Numerical Simulation and Compact Modeling of Ph-BTBT-C10 Organic Thin Film Transistor
Abstract: Flexible and cost-effective electronics have been necessitated by the advent of organic thin-film transistors (OTFTs). This study aims to study the performance of OTFT using a 2-decyl-7-phenyl-[1]benzothieno[3,2-b][1]benzothiophene (Ph-BTBT-C10) organic semiconductor. The paper also explore accurate device modeling for technology optimization and circuit design that supports device improvement. This research includes device fabrication, numerical simulation using TCAD, compact modeling, and parameter extraction. By combining temperature-dependent bandgap narrowing with existing theories, this …
Published in Journal of Polymer & Composites · Vol. 12, Issue 5, 2024 · pp. 1–18 Read article
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Degradation in Energy Yield of Solar Photovoltaic Power Plant due to Soiling Effect
Abstract: Renewable energy resources are the future of the world. Solar photovoltaic energy conversion is one such type of clean and sustainable energy resource. Solar photovoltaic power plant’s performance is directly dependent on the sun’s incoming solar radiation availability and its intensity. Solar energy conversion of photovoltaic power plants is limited by local climatic parameters such as temperature, wind, humidity, dust deposition, etc. and geographical factors of latitude, longitude, etc. Accumulation …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 8, Issue 1, 2017 · pp. 6–11 Read article
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Effects of a Single Dose Inhalation of Ipratropium Bromide, Salbutamol, Salmeterol, Beclomethasone, Budesonide in Stable Chronic Bronchitis: Comparative Study
Abstract: Chronic bronchitis usually treated with long acting bronchodilators and inhaled corticosteroids as monotherapy or in combination. The aim of this study is to assess the efficacy of single dose of β2-agonist (short and long acting), muscarinic antagonist and inhaled corticosteroids on the pulmonary function test in clinically stable chronic bronchitis patients. A total number of 93 (61 males and 32 females) patients who fulfilled the criteria of uncomplicated chronic bronchitis …
Published in Research and Reviews: A Journal of Medicine · Vol. 4, Issue 3, 2014 · pp. 12–17 Read article
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A New Approach for Cuk Converter for Solar/Wind Hybrid Standalone System
Abstract: The non-conventional energy such assolar photovoltaic system and wind turbine are naturalresources and provides sustainable green energy .Now,Electricity is the most requisite means for man. All theenergy resources are depleting day by day In thecurrent technology , This project could be effective toachieve good prediction accuracy in smart grid usingdifferent weather conditions. It also upgrades thesocioeconomic condition of rural lives. In this articlebasically The wind turbine and solar photovoltaic (PV)are …
Published in Trends in Mechanical Engineering & Technology · Vol. 12, Issue 3, 2022 · pp. 18–28 Read article
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Early Fault Diagnosis of Vehicle EGR System Based on Support Vector Machine Technique
Abstract: It has been a challenge to the automotive world to manufacture the smart vehicle components that contribute to the performance of vehicle operations to adhere due to strict vehicle emission norms. In this context, engine operations need to carry systematically, which helps to maintain the function of the vehicle emission system properly. Now a day’s electronic sensors are playing a vital role in smarter vehicle component operation. In-vehicle exhaust gas …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 9, Issue 3, 2021 · pp. 1–11 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 · pp. 90–100 Read article
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AI-Driven Predictive Maintenance Framework for Intelligent Vehicle Health Monitoring
Abstract: The accelerated development of smart and connected car systems made the necessity to find the accurate and real-time predictive maintenance solutions which would minimize the number of unexpected failures as well as increase the cars on-road safety. The current paper proposes an artificial intelligence-based hybrid predictive maintenance system that combines Long Short-Memory (LSTM) networks and the XGBoost predictor to provide a potent vehicle fault diagnosis, Remaining Useful Life (RUL) prediction, …
Published in Trends in Machine design · Vol. 13, Issue 1, 2026 · pp. 1–17 Read article
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A Hybrid Machine Learning Approach for Enhanced Patient Diagnosis and Health Outcome Prediction
Abstract: Rapid and accurate diagnosis is essential to present day practitioners of medicine, yet can be complicated by the enormous volume and complexity inherent in clinical data. To this end, we here propose a hybrid machine learning model in combination with Recursive Feature Elimination (RFE) and ensemble voting to enhance the diagnostic accuracy by integrating multiple models. Trained on real-world electronic health data, including lab results, demographics and medical history, the …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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Future of Electric Vehicles (A Review)
Abstract: This paper presents a review on the possible advancements & future of electric vehicles. In today's world, most of the vehicles as of now are running on fossil fuels. Fossil fuels are the main driver of global warming and unsustainable. Fossil fuels are non-renewable and contribute to climate change. In addition to this, fossil fuels also pose a threat to the planet by producing harmful toxic gases upon burning into …
Published in Journal of Automobile Engineering and Applications · Vol. 8, Issue 1, 2021 · pp. 23–30 Read article
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Structural and Electrical Properties of Low-Energy Ion Beam Kr-Irradiated In/Se Bilayer
Abstract: In the present work, In (~50 nm) over Se (~50 nm) thin films were deposited successively on an Si substrate by e-beam evaporation method under 2×10–5 mbar pressure. The In/Se bilayers were irradiated with low-energy ion beams of 350 keV Kr+1 with fluence of 3 × 1016 ions/cm2. The sample was subsequently characterized for phase formation using X-ray diffraction and thickness profile using Rutherford backscattering spectrometry analysis. In the pristine …
Published in Journal of Polymer & Composites · Vol. 11, Issue 1, 2023 · pp. 91–96 Read article
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Explainable Artificial Intelligence in Personalized Medicine: Emerging Clinical Perspectives
Abstract: The convergence of artificial intelligence (AI) and precision medicine has transformed contemporary healthcare by enabling data-driven clinical decision-making, individualized therapeutic interventions, and predictive diagnostics. However, despite remarkable advances in machine learning (ML) and deep learning (DL), the widespread adoption of AI in healthcare remains constrained by the “black-box” nature of many computational systems. Clinicians, regulatory agencies, and patients increasingly demand transparency, interpretability, and trustworthiness in AI-guided medical recommendations. Explainable Artificial …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 2, 2026 · pp. 13–29 Read article
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A Review on Advances in Polymer Composites and Nanocomposites: Design, Applications, and Life Cycle Assessment
Abstract: Materials based on polymer composites and nanocomposites have won the main status in several regions of industry by mare possessing excellent properties and broad range of application. This review focuses on the advancements in the design of fiber-reinforced polymers, structural composites, multifunctional composites, and biomimetic and eco-friendly composites. Emerging developments in biomedical composites, polymer foams, and smart composites are explored, highlighting their applications in medical, aerospace, automotive, and structural engineering. …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 244–251 Read article
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Particle Swarm Optimization Framework for Accurate Battery State-of-Charge and Remaining Useful Life Estimation
Abstract: Accurate estimation of the State of Charge (SOC) and State of Health (SOH) of a battery is key to safe and efficient management of batteries in electric vehicles and energy-storage systems. However, it is challenging due to high nonlinearity, varying operating conditions, measurement noise, and limited access to comprehensive electrochemical parameters. Traditional data-driven models often generalize poorly and require heavy tuning, which can produce unstable predictions. To address these problems, …
Published in Journal of Automobile Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 53–64 Read article
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Machine-Learning-Assisted Development of Polymer-Biochar Composite Adsorbents for the Removal of Heavy Metals from Gomti River Water
Abstract: Rapid urbanization, industrial discharge, and agricultural runoff pose a significant threat to freshwater sustainability and public health. Within these ecosystems, polymer pollutants—such as microplastics, nanoplastics, synthetic fibres, and additive residues—have emerged as persistent vectors capable of adsorbing and transporting toxic heavy metals. Because these polymeric contaminants dynamically interact with conventional aquatic parameters to alter pollutant mobility and ecological risk profiles, there is an urgent need to transition from passive environmental …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 72–95 Read article
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Multi-variable Analysis and Optimization of Electrical Discharge Machining Process Using a PCA-ANN Based Approach
Abstract: AbstractThe optimum selection of process parameters has played a crucial role in electrical discharge machining (EDM) for improving the material removal rate, reducing the tool wear rate and radial overcut. In this paper, optimum parameters while machining 202 stainless steel using copper electrode as a tool has been investigated. For optimization of process parameters along with multiple quality characteristics, principal component analysis coupled with artificial neural network method has been …
Published in Trends in Opto-electro & Optical Communication · Vol. 6, Issue 3, 2016 · pp. 39–45 Read article