Search
270 articles for “election prediction”
-
A Comprehensive Survey of Polymer Detection Techniques and Computer-Based Analysis Methods for Advanced Material Characterization
Abstract: Polymers are widely used in aerospace, automotive, biomedical, packaging, electronics, and manufacturing industries because of their lightweight nature, durability, and versatility. Accurate polymer identification and characterization are essential for quality control, recycling, performance assessment, and the development of advanced materials. Characterization helps determine important properties such as chemical composition, molecular structure, thermal stability, mechanical strength, and surface morphology, which influence material performance and application suitability. Traditional polymer detection methods include …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 921–929 Read article
-
Role of Artificial Intelligence in Health Care Decision Making: Balancing Innovation and Caution
Abstract: Healthcare is undergoing a transformation powered by artificial intelligence, which improves monitoring, diagnosis, and treatment capabilities. Among Artificial Intelligence (AI's) shortcomings is the dearth of an emotional relationship between individuals and medical personnel. Robotic surgery procedures pose the possibility of malfunctioning machinery and mistaken assumptions. So, the present systematic review focused on exploring the boon and bane of the role of AI in predicting various abnormalities in advance to improve …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 3, 2025 · pp. 24–35 Read article
-
Optimization Study by Response Surface Methodology and Artificial Neural Network on the Culture Parameters of Citric Acid Bioproduction from Sweet Potato Peels
Abstract: In the cause of this research work, two steps enzymatic hydrolysis of sweet potato peel was carried out respectively. The effect of α-amylase dose, reaction time, and reaction temperature and biomass weight on glucose concentration was investigated carefully. The response surface methodology (REM) predicted the highest reducing sugar concentration at liquefaction to be 74 g/L, at the following optimized conditions; temperature of 45°C, α-amylase dose 0.7 %v/v, biomass weight 22.345 …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 9, Issue 1, 2022 · pp. 30–38 Read article
-
Material-Integrated Energy Management: Role of Advanced Polymers and Composites in Smart Homes
Abstract: The article discusses the possibility of improving the performance as well as the sustainability of smart-home-based energy management systems (EMS) by applying advanced polymeric and composite materials. Smart homes today are placing greater requirements on lightweight, thermally stable, high durability, and electrically conducting compounds in such important aspects of the devices as batteries, substrate layers in solar panels, thermally resistant enclosures, and high efficiency thermal insulation on intelligent appliances. Such …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1361–1374 Read article
-
Molecular Pharmacokinetics and Structural Docking of Phenolic Acids for Targeting NF-κB Pathway Components in Inflammation and Fibrosis: A Computational Approach Toward Therapeutic Discovery
Abstract: Inflammation and Fibrosis are critical pathological processes associated with various chronic diseases, often mediated by the nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) signaling pathway. This study investigates the therapeutic potential of phenolic acids as modulators of the NF-κB pathway, aiming to identify novel ligands that can effectively interact with key components of this signaling cascade. A comprehensive computational approach was employed, utilizing molecular docking, pharmacological screening, and post-docking …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 3, Issue 1, 2025 · pp. 14–31 Read article
-
IoT-Based Battery Health Monitoring for Electric Vehicles Using Machine Learning
Abstract: With increasing utilization of the Electric Vehicles (EV)s in global scale, battery health management becomes a critical factor which has great impact on vehicle performance, safety and longevity. Battery materials, such as NMC LFP lithium-ion batteries and lithium-ion batteries, degrade over time from charging behaviour, heat stress, discharging voltage profiles and environmental limits. Conventional BMS only offer threshold based health diagnostics and cannot perform accurate degradation prediction. This work presents …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 4, Issue 1, 2026 · pp. 8–12 Read article
-
Artificial Intelligence Techniques for Smart Polymer Nanocomposite Materials and Industrial Applications
Abstract: Protecting sensitive material data, manufacturing processes, and intelligent monitoring platforms is essential for the fast development of innovative polymer nanocomposite systems in fields such as aerospace, medicine, electronics, automobiles, and energy. In order to safeguard, consistently enhance, and optimize distributed industrial systems that consist of polymer nanocomposite materials, this study presents an AI-driven cybersecurity and cloud computing architecture. The suggested solution employs artificial intelligence (AI), machine learning (ML), cloud computing, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1109–1134 Read article
-
Optimization of Roof angle for Sloping Roof Buildings under Extreme Wind Conditions
Abstract: A downburst that occurs during a thunderstorm is a strong downward current of wind which comes down with high speed from the cloud level and hits the ground. After hitting the ground it spreads radially outward in all directions. These are generally destructive in nature. There are evidences of downburst causing extensive damages to buildings, electrical installations etc. In India thunderstorms often occur during pre-monsoon and post-monsoon seasons particularly in …
Published in Journal of Construction Engineering, Technology & Management · Vol. 9, Issue 1, 2019 · pp. 1–5 Read article
-
Study and Prediction of Radiation Effects in Solar Power Plants using Neuro Fuzzy and Neural Network
Abstract: Neural and neuro-fuzzy frameworks are utilized, to figure temperature and sun powered radiation. The principle benefit of these frameworks is that they don't need any earlier information on the qualities of the information time-series to foresee their future qualities. These frameworks with various models have been prepared utilizing as information estimations of the above meteorological boundaries acquired from the National Observatory of Athens. In the wake of having reproduced a …
Published in Trends in Electrical Engineering · Vol. 12, Issue 1, 2022 · pp. 8–19 Read article
-
Generative AI-Driven Design Optimization of Lightweight Polymer Composites for Electric Vehicles
Abstract: Lightweight polymer composites are increasingly important for electric vehicles, where mass reduction must be achieved without compromising structural performance, thermal stability, manufacturability, or material reliability. This study develops a generative AI-driven inverse-design framework for identifying experimentally credible lightweight polymer-composite configurations under coupled EV-oriented constraints. Public experimental polymer-composite datasets were integrated through leakage-controlled preprocessing and group-aware validation. A multi-task neural surrogate predicted mechanical response, while a conditional variational autoencoder explored feasible …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
-
Integrated Optimization of Solar Photovoltaic Systems Using Taguchi Method and Computational Fluid Dynamics for Enhanced Efficiency
Abstract: The transition to renewable energy demands efficient and reliable photovoltaic (PV) systems to meet rising global energy needs. This study presents an integrated optimization framework combining the Taguchi method and Computational Fluid Dynamics (CFD) to improve the thermal and electrical performance of solar PV systems. A structured experimental design using an L9 orthogonal array evaluates the influence of three key parameters—material type, panel thickness, and cooling mechanism—on system efficiency. Analysis …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 3, 2025 · pp. 10–25 Read article
-
A Review of Semiconductor Solar PV Cell and Development of Solar Radiation Estimation Models
Abstract: Today’s life could not be imagined without energy (Power). It has become an integral part of day to day life. Traditionally, dependency was there on conventional sources of energy like coal, hydroelectric etc. But they are limited resources; also, they offer residue or pollution to the environment which is not desirable. These are the main reasons that the researchers inclined themselves towards the maximum exploration and make optimal use of …
Published in Journal of Semiconductor Devices and Circuits · Vol. 5, Issue 1, 2018 · pp. 20–26 Read article
-
Hybrid Quantum-Classical Reinforcement Learning Enabled Thermal-Aware Electronic Design Automation Framework for Energy-Efficient Next-Generation VLSI Systems Applications
Abstract: Modern Very Large-Scale Integration (VLSI) systems are becoming more complicated, which has increased need for sophisticated Electronic Design Automation (EDA) frameworks that can concurrently optimise thermal behaviour, power consumption, and performance. This study proposes a Hybrid Quantum-Classical Reinforcement Learning (HQCRL) Enabled Thermal-Aware EDA Framework for next-generation energy- efficient VLSI systems. The proposed framework integrates quantum-inspired optimization techniques with classical reinforcement learning algorithms to address the challenges of placement, routing, and …
Published in Journal of Electronic Design Technology · Vol. 17, Issue 2, 2026 · pp. 10–22 Read article
-
Investigation of Robotic Transverse Twin-Wire GMAW for Large-Scale Wire-Arc Additive Manufacturing Applications
Abstract: Bulk metal additive manufacturing using wire-arc processes has gained significant attention for fabricating large-scale engineering components due to their high deposition rate and material efficiency. In this study, the feasibility and performance of robotic transverse twin-wire gas metal arc welding (GMAW) for bulk wire-arc additive manufacturing (WAAM) is systematically assessed. The research focuses on understanding arc stability, weld bead characteristics, and process–product relationships under high-deposition conditions. Welding current signals from …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 4, Issue 1, 2026 · pp. 36–50 Read article
-
Sensorless Direct Power Control of Brushless DC Motor Drive using Unknown Input Speed Observer
Abstract: This paper proposes the speed control of brushless DC (BLDC) motor via direct power control (DPC) method as a novel and effective strategy in electrical drives applications. The DPC has some advantages rather than other control methods of BLDC motor including simpler control algorithm and faster dynamic response. In proposed BLDC motor drive based on DPC strategy, space vector modulation (SVM) voltage source inverter is employed. To enhance the drive …
Published in Journal of Control & Instrumentation · Vol. 6, Issue 3, 2015 · pp. 31–41 Read article
-
Smart Monitoring and Controlling of the Battery and Motor
Abstract: The demand for effective battery and motor monitoring and management to guarantee dependability, safety, and peak performance has increased due to the quick development of electric vehicles and smart industrial systems. The smart monitoring and control methods used in battery management systems and motor control systems are thoroughly reviewed in this paper. In addition to speed, torque, efficiency, and fault situations in motors, it emphasizes important characteristics like temperature, voltage, …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 4, Issue 1, 2026 · pp. 11–15 Read article
-
IoT-Based Motor Protection and Control System Using PLC and ESP8266
Abstract: Because of their straightforward design and affordable price, single-phase induction motors are frequently utilized in residential and small-scale industrial settings. However, conventional direct-on-line (DOL) control provides fixed-speed operation and offers limited protection against thermal overload and fault conditions. This article describes the design and implementation of an ESP8266 Node MCU-based PLC- based closed-loop motor control system with Internet of Things features. To increase operating flexibility and maintenance efficiency, the suggested …
Published in International Journal of Electrical Power and Machine Systems · Vol. 4, Issue 1, 2026 · pp. 54–62 Read article
-
A Review on Transforming Patient Pathways: The Impact of Pharmaceutical Software on Drug Manufacturing and Safety Monitoring
Abstract: The development, production, and safety monitoring of pharmaceuticals are being revolutionized by incorporating digital technologies. Throughout drug lifecycles, pharmaceutical software which includes cloud-based systems, automation, data analytics, and artificial intelligence (AI) has emerged behind efficiency and innovation. Real-time monitoring, predictive maintenance, and process optimization are made possible in manufacturing by software tools like Digital Twins, Manufacturing Execution Systems (MES), and Quality Management Systems (QMS). These technologies improve batch consistency, lower …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 1, 2026 · pp. 40–46 Read article
-
Role of Artificial Intelligence in Quantum Materials Research
Abstract: Quantum materials have emerged as a transformative class of advanced materials due to their extraordinary electronic, magnetic, optical, and topological properties governed by quantum mechanical phenomena. These materials are expected to revolutionize next-generation technologies such as quantum computing, spintronics, superconducting electronics, nanoelectronics, intelligent sensing systems, and energy-efficient devices. However, conventional methods for discovering and optimizing quantum materials are often expensive, time-consuming, and computationally intensive because of the enormous complexity of …
Published in Journal of Materials & Metallurgical Engineering · Vol. 16, Issue 2, 2026 · pp. 13–27 Read article
-
Simulation Studies on the Drain Characteristics of Microelectronic AlGaN/GaN HEMTs Corresponding to the 30 nm of AlGaN Nano-Layer
Abstract: AbstractIn this work, the simulation studies are performed on high electron mobility transistor (HEMT) structures using the SILVACO-ATLAS software tool. The drain characteristics of HEMT structures is investigated with respect to the Aluminium mole fraction, drain voltage, gate voltage, and gate length at 30 nm thickness of AlGaN nano-layer. The simulation studies on the effect of gate length to control the drain characteristics are a novelty of this work. The …
Published in Journal of Semiconductor Devices and Circuits · Vol. 4, Issue 1, 2017 · pp. 8–16 Read article