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270 articles for “election prediction”
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Real-Time Air Quality Prediction Using IoT-Integrated Polymer Sensors and Recurrent Neural Networks
Abstract: Real-time air quality monitoring remains a critical challenge in urban environments, where traditional sensor infrastructures often suffer from limited responsiveness, poor scalability, and high deployment costs. The increasing prevalence of NO₂ pollution, a key contributor to respiratory and cardiovascular ailments, demands advanced sensing platforms capable of both accurate detection and predictive inference. Existing methods either rely on rigid electronic sensors lacking adaptability or on statistical forecasting models that fail to …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 332–347 Read article
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Harmonic Compensation in Grid Interconnected DG Units by Closed Loop Control
Abstract: This paper deals with improvement of power quality problem namely harmonic problem using distributed generation as their source of electricity. The harmonics occur in such a system because of the nature of loads connected. There are many power quality problems; out of which harmonics normally caused by nonlinear loads like variable frequency drives, fluorescent lightning, office computers etc. have adverse effects on the power quality. Also, harmonic detection and prediction …
Published in Journal of Power Electronics and Power Systems · Vol. 7, Issue 1, 2017 · pp. 9–17 Read article
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Enhance Thermal and Conductive Properties through Graph Neural Network-Based Machine Learning-Driven Advanced Polymer Material Design
Abstract: Advanced polymer materials are widely used in modern engineering and manufacturing because of their lightweight nature, flexibility, durability, and adaptability to different applications. However, designing polymer materials with enhanced thermal and electrical properties remains a challenging task. The performance of polymers is influenced by a complex combination of molecular structures, filler materials, processing parameters, and nanoscale interactions. Conventional optimization methods often require extensive experimental trials and computational resources, making it …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 386–407 Read article
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Heat Transfer by Arc Welding for A Similar Material Joint
Abstract: Electric arc welding (EAW) is a traditional fabrication process used in wider domestic, commercial and industrial application. Welding is a joining of two materials with the application of heat at the molecular level with the application of heat and pressure. Many materials used for welding application for different joining process. Maraging steel is special steel used for production of different air-craft components. Maraging material is used for heavy tools, producing …
Published in Journal of Materials & Metallurgical Engineering · Vol. 15, Issue 2, 2025 · pp. 1–13 Read article
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Prediction of Air Quality Index (AQI)
Abstract: AbstractGrowing economy of a country has its pros and cons. Swift development of industries on an extensive scale has led to immense growth in air pollution. It happens to be elementary root of maladies and early deaths around the world. The UN responsible agency for international public health has estimated that outside atmosphere consisting of air pollution takes about three million people’s lives every year. Therefore, contamination amount in air …
Published in Journal of Electronic Design Technology · Vol. 11, Issue 2, 2020 · pp. 28–34 Read article
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Analysis and Modeling of Acoustic Noise in the Switched Reluctance Motors with Finite Element Method
Abstract: Due to high importance of noise in switched reluctance motor (SRM), a coupled electromagnetic-structure simulation model is created for this motor using ANSYS finite element (FE) package. Since the main reason for producing noise and vibration in the SRM is the radial force applied to the stator pole, the radial force waveform is predicted using the 2D FE transient analysis in the developed electromagnetic model. Determination of the frequency modes …
Published in Trends in Electrical Engineering · Vol. 5, Issue 3, 2015 · pp. 17–22 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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Simulation and Analysis of Battery Pack Using the Multi Scale Multi-Domain Battery Model
Abstract: The creation of sophisticated simulation models has been made necessary by the need for reliable and effective battery packs in energy storage systems and electric vehicles. This study focuses on the simulation and analysis of battery packs using a multi-scale multi-domain battery model. The model enables a thorough knowledge of battery pack behavior across a range of operating situations by integrating the electricity, thermal, and mechanical domains. Multi-scale modeling bridges …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 2, Issue 2, 2024 · pp. 31–46 Read article
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Green AI-Enabled Opto-Electronic Communication Systems for Carbon-Neutral Digital Networks
Abstract: The rapid expansion of digital communication infrastructure, driven by cloud computing, Internet of Things (IoT), 6G networks, and artificial intelligence applications, has significantly increased the energy consumption and carbon footprint of modern communication systems. Conventional optical communication networks often rely on static resource allocation and energy-intensive signal processing mechanisms, resulting in inefficient utilization of network resources and elevated operational costs. This study proposes a Green Artificial Intelligence (Green AI)-Enabled Opto-Electronic …
Published in Trends in Opto-electro & Optical Communication · Vol. 16, Issue 2, 2026 Read article
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Rapid Forecasting of Short-run Electric Power Demand Profiles of India Using the Statistical Method of Z Scores
Abstract: Power demand profile prediction for a region or nation is a critical part of the energy system design and operational planning process. A simplified method based on non-dimensionalizing power demand data from previous years using Z scores calculated from the mean and standard deviation of the profiles is developed in this study to forecast monthly demand profiles at time resolution of 1 hour for future years. The Z score range …
Published in Research & Reviews : Journal of Statistics · Vol. 14, Issue 1, 2025 · pp. 38–48 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 · pp. 1–18 Read article
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Investigations On Use of Poly(3,4-Ethylenedioxythiophene): Poly (Styrene Sulfonic Acid) (PEDOT: PSS) Conductive Polymers for Design of Improved EEG Based Brain Computer Interface for Seizure Control and Analysis
Abstract: This research explores the application of Poly(3,4-ethylenedioxythiophene):poly(styrene sulfonic acid) (PEDOT:PSS) conductive polymers in the design of an enhanced Electroencephalography (EEG)-based Brain-Computer Interface (BCI) for seizure control and analysis. PEDOT: PSS, known for its high conductivity, flexibility, and biocompatibility, is employed to improve the efficiency and sensitivity of EEG electrodes, addressing challenges such as signal noise, skin-electrode impedance, and user comfort. The study evaluates the material’s properties, including its electrical conductivity, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 223–241 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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Comparative Study of Geopolymer Paste Prepared from Different Activators
Abstract: The present paper explores the comparative study of the geopolymer paste resulting from different alkali activations. In this experimental study, four series of geopolymer pastes differing in the alkali activation were manufactured by activating low calcium fly ash. These activators were subjected to a certain temperature of 35 °C for duration of 24 h. After casting of the specimens, activated by those activators, they were subjected to 85 °C for …
Published in Recent Trends in Civil Engineering & Technology · Vol. 2, Issue 1-3, 2012 · pp. 9–18 Read article
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Using Machine Learning to Guess Photochemical Reaction Pathways
Abstract: Photochemical reactions are crucial to many activities in the fields of energy conversion, environmental cleanup, and synthetic chemistry. However, predicting their causes and results effectively is still very hard since they entail excited electronic states, nonadiabatic transitions, and complicated potential energy surfaces. Machine learning (ML) has been a powerful technique to go along with classic quantum chemistry methods in the last few years. It offers better prediction capability and lower …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 3, Issue 2, 2025 · pp. 01–12 Read article
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Analysis of Pull-in Voltage with Respect to Changes in Dielectric Material and their Thickness
Abstract: Micro Electromechanical Systems (MEMS) actuators experience pull-in effect in their actuation range. MEMS actuating elements are thin parallel plate capacitor electrodes separated with air gap. Parallel plate electrostatic micro actuators are known to have the pull-in effect, where electrostatic attractive force exceeds the mechanical restoring force of the suspending spring, and that the movable plate spontaneously pulled into physical contact with the opposite electrode. In our model the effect of …
Published in Recent Trends in Electronics Communication Systems · Vol. 2, Issue 1, 2015 · pp. 1–5 Read article
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Mathematical Modelling of Semiconductor Device Physics: An Analytical Approach
Abstract: Semiconductor device physics forms the foundation of modern electronic and optoelectronic technologies. Mathematical modelling provides a rigorous framework for understanding, predicting, and optimizing the behavior of semiconductor devices by linking physical principles with device-level performance. This work presents an analytical approach to the mathematical modelling of semiconductor devices, emphasizing the derivation and interpretation of governing equations that describe charge transport and electrostatic behavior. The model is based on fundamental physical …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 1, 2026 · pp. 36–42 Read article
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MedVerse AI: An Intelligent Digital Health Platform for Patient-Centric Healthcare and Proactive Disease Prediction
Abstract: The rapid digitization of healthcare has led to an unprecedented growth in medical data, ranging from diagnostic images and laboratory reports to electronic health records and clinical notes. Despite this abundance, patients and healthcare providers often struggle to extract meaningful insights due to data complexity and fragmentation. MedVerse AI proposes an intelligent digital health platform that unifies medical image analysis, clinical report interpretation, real-time interaction, and predictive disease analytics into …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 2, 2026 · pp. 1–7 Read article
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Time Series Forecasting of Electricity Consumption: A Comparative Analysis of ARIMA and SARIMA Models
Abstract: Accurate electricity demand forecasting plays a vital role in energy planning, efficient power system operation, and sustainable resource management. This study conducts a comparative evaluation of the Autoregressive Integrated Moving Average (ARIMA) and Seasonal Autoregressive Integrated Moving Average (SARIMA) models using ten years of monthly electricity consumption data collected from a national electricity regulatory authority. The performance of both models is assessed using forecasting accuracy metrics, including Mean Absolute Error …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 2, 2026 · pp. 43–53 Read article
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Microstructural Design and Functional Properties of Polycrystalline Materials
Abstract: Polycrystalline materials, composed of an aggregate of crystallites or grains, are foundational to modern engineering applications due to their versatile functional properties. The microstructural design—encompassing grain size, shape, orientation, phase distribution, and grain boundary characteristics—plays a pivotal role in determining mechanical, thermal, electrical, and magnetic behavior. This abstract explores the intricate relationship between microstructure and functionality, emphasizing how tailored processing techniques such as thermomechanical treatments, sintering, and additive manufacturing can …
Published in International Journal of Crystalline Materials · Vol. 2, Issue 2, 2025 · pp. 16–20 Read article