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454 articles for “Prediction”
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A Study on Machine-Learning-Driven Insight into theThermal Behavior of Polymers and Composite Materials
Abstract: The thermal performance of polymeric and composite systems underpins their suitability for aerospace, electronics, and energy‑storage applications, yet reliable prediction of temperature‑dependent properties remains a formidable challenge. In this work we present a data‑driven framework that harnesses modern machine‑learning (ML) techniques to forecast key thermal metrics – glass‑transition temperature (Tg), melting point (Tm), thermal conductivity (k), and decomposition onset (Td) – from a chemically informed descriptor space. A curated database …
Published in International Journal of Polymer Science and Engineering · Vol. 12, Issue 1, 2026 · pp. 1–11 Read article
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Cognitive Metallurgy: A Study on Microstructure and Energy Efficiency in High-Temperature Alloying via Sensor Fusion and Deep Reinforcement Learning
Abstract: Background Traditional high-temperature metallurgical processes, such as continuous casting and specialty alloy synthesis, are characterized by high energy consumption, stochastic variability, and reliance on post-process defect inspection. The inability to precisely monitor, model, and predict the real-time thermal, chemical, and mechanical state of molten metal and cooling substrates results in significant material waste and inconsistent microstructural integrity. Methodology This study introduces a novel framework for Cognitive Metallurgy utilizing an integrated …
Published in International Journal of Metallurgy and Alloys · Vol. 11, Issue 2, 2025 · pp. 27–36 Read article
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Cloud Security Using Machine Learning: A Study
Abstract: The rapid adoption of cloud computing has revolutionized IT infrastructure, offering unprecedented scalability, flexibility, and cost efficiency. However, this paradigm shift introduces a new spectrum of sophisticated security challenges that traditional, signature-based security mechanisms often struggle to address effectively given the dynamic, multi-tenant, and distributed nature of cloud environments. This paper explores the critical role of Machine Learning (ML) as a potent paradigm for strengthening cloud infrastructure. ML emerges as …
Published in International Journal of Distributed Computing and Technology · Vol. 11, Issue 2, 2025 · pp. 21–30 Read article
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Coupled Dynamics in Fluid-Structure Interaction Systems: A Review of Analytical and Computational Models
Abstract: Abstract: Fluid-Structure Interaction (FSI) systems embody the complex, coupled behavior between deformable or flexible structures and surrounding fluid flows. This interaction is inherently nonlinear and dynamic, posing significant challenges in modelling, simulation, and analysis. Understanding and accurately predicting the behavior of FSI systems is critical across a broad spectrum of engineering applications, including aerospace structures undergoing aeroelastic effects, underwater vehicles interacting with fluid currents, biomedical devices, such as heart valves …
Published in International Journal of Structural Mechanics and Finite Elements · Vol. 11, Issue 2, 2025 · pp. 1–5 Read article
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Leveraging Artificial Intelligence for Traffic Flow Optimization: A Case Study Approach
Abstract: AbstractTraffic congestion poses a significant challenge in urban environments, contributing to economiclosses, increased fuel consumption, environmental pollution, and diminished quality of life. Traditionaltraffic management approaches, such as pre-timed traffic signals and manual interventions, often failto adapt dynamically to fluctuating traffic conditions. This study explores the integration of artificialintelligence (AI) in traffic management to optimize traffic flow and reduce congestion. By leveragingAI-driven predictive models, deep reinforcement learning, and real-time traffic data, …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 11, Issue 1, 2025 · pp. 37–42 Read article
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AI-Powered Traffic Management: Enhancing Urban Mobility and Efficiency
Abstract: AbstractUrban traffic congestion is a persistent challenge, resulting in economic setbacks, extended traveldurations, excessive fuel consumption, and environmental harm. The rapid urbanization and increasingnumber of vehicles have intensified this issue, highlighting the need for smarter and more efficienttraffic management solutions. With advancements in artificial intelligence (AI), innovative trafficcontrol strategies can be implemented to optimize urban mobility and alleviate congestion. This paperexplores AI-driven traffic management solutions, focusing on machine learning-based adaptive …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 11, Issue 1, 2025 · pp. 32–36 Read article
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A Sensor Integrated Tool for Cutting Force Monitoring in Gantry Milling to Improve Flatness and Surface Finish: Review Study
Abstract: AbstractPrecision machining of sector plates plays a vital role in the efficient functioning of Air Pre-Heaters(APH), which are integral components of thermal power plants. These plates are subjected to harshthermal cycles and mechanical loads, making dimensional accuracy critical. For optimal heatexchange performance and mechanical reliability, it is essential to maintain tight manufacturingtolerances – flatness within ±400 microns and thickness up to 13 mm. Deviation from theseparameters can lead to air …
Published in International Journal of Manufacturing and Materials Processing · Vol. 11, Issue 1, 2025 · pp. 25–45 Read article
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Ethical Issues and Implementation Challenges of Artificial Intelligence in ICU Care: A Critical Nursing Perspective
Abstract: Background: The integration of Artificial Intelligence (AI) in Intensive Care Units (ICUs) is rapidly advancing, with AI showing potential to improve patient outcomes by enhancing monitoring, predicting deterioration, and optimizing clinical decision-making. Despite its promise, the implementation of AI in critical care environments raises ethical and practical concerns. This study aims to evaluate the impact of AI on ICU outcomes and explore the associated ethical and implementation challenges. Objective:To assess …
Published in International Journal of Nursing Critical Care · Vol. 11, Issue 1, 2025 Read article
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Unsupervised Machine Learning:Revealing Hidden Data patterns
Abstract: Machine learning helps computers learn from data and make smart decisions. There are two main ways they do this: supervised and unsupervised learning. Supervised learning is like teaching a child with flashcards—you show the computer examples with the right answers, and it learns to recognize patterns. This helps it make predictions, like guessing whether an email is spam or estimating house prices. Unsupervised learning, on the other hand, is like …
Published in International Journal of Digital Communication and Analog Signals · Vol. 11, Issue 1, 2025 · pp. 38–47 Read article
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The Impact of CAM on Digital Twin Technology inManufacturing Systems
Abstract: The integration of Computer-Aided Manufacturing (CAM) and Digital Twin technology is revolutionizing the manufacturing landscape by bringing together the strengths of process automation, real-time monitoring, and predictive analytics. CAM, which has long been used to optimize machining processes, automate toolpath generation, and control production workflows, plays a vital role in improving manufacturing efficiency and precision. On the other hand, Digital Twin technology, which creates a virtual replica of physical systems, …
Published in International Journal of Computer Aided Manufacturing · Vol. 10, Issue 2, 2024 · pp. 6–10 Read article
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Kinetic Model for Production of Carbon(iv)oxide (CO2) from Brewers Spent Grain Using Anaerobic Digester
Abstract: In this research paper, investigation studies were carried out to determine which model best predicts the amount of using the linear, power, growth rate decay, and non-elementary rate models, the kinetics of the biogas produced under the impact of biodegradation were explored. Carbon(iv)oxide was produced as a fraction of the biogas acquired from the experimental conditions. Either of the linear, power, growth rate decay, and non-elementary rate models can be …
Published in International Journal of Energetic Materials · Vol. 10, Issue 1, 2024 · pp. 17–31 Read article
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Comparative Analysis of Air Quality Indices Across Five Eastern States of India Using ML Models and Pollutant Based Insights
Abstract: This paper presents a comparative study of Air Quality Index (AQI) levels in five eastern Indian states–Arunachal Pradesh, Assam, Meghalaya, Nagaland, and Tripura. Using historical data, the study explores the concentration of key pollutants, including PM2.5, PM10, NO2, SO2, CO, and Ozone, highlighting regional variations in air quality. Assam, with its higher levels of urbanization and industrial activity, shows elevated AQI levels, especially for pollutants like PM10 and NO2. In …
Published in International Journal of Distributed Computing and Technology · Vol. 11, Issue 1, 2025 · pp. 31–42 Read article
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Health Monitoring System for Fault Identification on Centrifugal Pump Using ML
Abstract: Centrifugal pumps are crucial equipment widely used in various industries, and their reliable operation is essential for maintaining production and preventing costly downtimes. This paper proposes a comprehensive health monitoring system for centrifugal pumps that combines model-driven and data- driven approaches, leveraging artificial intelligence (AI) and machine learning (ML) techniques. The system incorporates demand prediction using artificial neural networks and fault diagnosis employing different ML classifiers, such as decision trees …
Published in International Journal of Mechanics and Design · Vol. 10, Issue 2, 2024 · pp. 1–12 Read article
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Advances in Gender Classification from Facial Images Using CNNs: A Comprehensive Review
Abstract: Predicting age and gender from facial images is important for various uses, like social interactions, security, and customizing user experiences. Despite progress in facial recognition technology, getting accurate and reliable predictions is still a challenge. This paper reviews recent advancements in Convolutional Neural Networks (CNNs) for age and gender classification, comparing their effectiveness to traditional methods. CNNs excel in extracting features from images and have shown notable improvements in accuracy …
Published in International Journal of Digital Communication and Analog Signals · Vol. 10, Issue 2, 2024 · pp. 1–5 Read article
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Modeling Fly Ash and Alccofine Partial Replacement of Concrete Density for High Strength Development
Abstract: This paper monitor the development of density from concrete model partially replaced cement with alccofine and fly ash, the study were generated applying modeling techniques, this concept were adopted to detail the influence of other concrete properties that influenced the growth rate of concrete density generated from such model concrete. Linear influences were observed in all the figures, the study observed variations of growth rate in the study, these are …
Published in International Journal of Sustainable Building Technology · Vol. 3, Issue 1, 2020 · pp. 29–48 Read article
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Analysis of Sun Path and Effective Shading Co-efficient using ECOTECT Software for Coimbatore
Abstract: Sun path of location depends on its latitude which creates a major heat impact on the surface of a building. This paper analyses the sun path of Coimbatore (11°N, 77°E), and its shading coefficient results as predicted by the ECOTECT software and Solar Tool. These sun path graphical presentations and calculated predictions of the shading coefficient can give a clear idea to the Architect/Designer to propose shading design, which can …
Published in International Journal of Architecture and Infrastructure Planning · Vol. 6, Issue 1, 2020 · pp. 18–27 Read article
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Regression Models to Examine Water Quality Index of Akabuta Stream
Abstract: Research carried out in this article is aimed at establishing mathematical tools, models that be used to monitor and predict water quality index concentration of Akabuta stream. The models developed seemed to be useful in monitoring and predicting water quality index as coefficient of determination of station A. Keywords: akabuta, Akabuta community, regression model, stream, water quality index
Published in International Journal of Analytical and Applied Chemistry · Vol. 3, Issue 2, 2017 · pp. 27–31 Read article
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Mathematical Modelling of the Effect of Functional Parameters of Temperature on Biodegradation of Petroleum Hydrocarbons
Abstract: Mathematical model was developed to examine the effect of functional parameters of temperature on biodegradation of petroleum hydrocarbons. The developed model was related to Monod’s equation and the microbial growth rate was monitored, predicted and simulated with variation on the functional parameters. The result obtained revealed increase in the microbial growth rate with increase in the functional parameter values. The maximum specific microbial growth rate was constant as well as …
Published in International Journal of Analytical and Applied Chemistry · Vol. 7, Issue 2, 2021 · pp. 21–27 Read article
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Analysis of Vapour-Liquid Equilibrium Behaviour of Cryogenic Hydrogen-Deuterium Mixtures Using Cubic Equation of State-based Method
Abstract: A comparative analysis of the vapour liquid equilibrium behaviour of the cryogenic hydrogen-deuterium system calculated under the assumption of an ideal solution using pure component vapour pressure data versus that of a real solution using Peng-Robinson cubic equation of state has been presented in this work. It is found that assumption of ideal solution leads to over prediction of the relative volatilities by 14% to 57% depending on the mixture …
Published in International Journal of Chemical Separation Technology · Vol. 4, Issue 2, 2018 · pp. 1–13 Read article
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Distribution Parameter Concentration of Alkalinity and Total hardness in Stagnant Water Environment: The Concepts of Oil and Gas Emission Influence
Abstract: Model for predicting the distribution parameter concentration of alkalinity and total hardness in stagnant water environment upon the influence of oil and gasemission was investigated in this paper. The model was formulated from the basic principle of mass and momentum concept which was resolved to obtain an ordinary differential equation. A mathematical tool known as the least square method was applied to resolve the differential equation to obtain quadratic equation …
Published in International Journal of Chemical Separation Technology · Vol. 6, Issue 1, 2020 · pp. 14–22 Read article