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1732 articles for “Predicting”
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Study of an Improved Quantum Particle Swarm Optimization-Based Framework for Neural Network Optimization in Modelling of Polymer Data
Abstract: The accurate forecasting of polymer viscosity at various physicochemical conditions has been quite critical due to the nonlinear interactions and interrelations between the variables. This paper suggests a better hybrid modelling framework, which involves the use of Artificial Neural Networks (ANN) and more advanced versions of Quantum Particle Swarm Optimization (QPSO) to better predict polymer viscosity. The input parameters taken are, namely, log (shear rate), polymer concentration, NaCl concentration, Ca …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 282–297 Read article
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Generative AI-Based Inverse Design of Sustainable Biodegradable Polymers with Target Mechanical and Thermal Properties
Abstract: The escalating global plastic pollution crisis has intensified the urgent need for sustainable biodegradable polymer alternatives that can match or exceed the performance of conventional petroleum-based plastics while minimizing environmental impact. However, traditional polymer discovery approaches are severely constrained by high experimental costs, protracted development cycles spanning years, and fundamental inability to simultaneously optimize multiple conflicting material properties such as mechanical strength, thermal stability, and degradation kinetics. This study presents …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1285–1295 Read article
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The Tapper Approach: An Integrated Framework for Land Degradation, Restoration, and Climate-Conflict Dynamics
Abstract: Land systems across the globe are increasingly exposed to multiple and interacting pressures, including land degradation, climate change, biodiversity loss, unsustainable land-use practices, rapid population growth, and socio-economic conflicts. These challenges not only reduce ecosystem productivity and resilience but also threaten food security, water availability, rural livelihoods, and long-term environmental sustainability. Despite the growing recognition of these interconnected issues, most existing conceptual and analytical frameworks continue to address them in …
Published in Research & Reviews : Journal of Ecology · Vol. 15, Issue 2, 2026 · pp. 24–30 Read article
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Generative AI for Designing Sustainable Polymer Composites for Renewable Energy Applications
Abstract: Sustainable polymer composites are increasingly required for renewable energy devices, yet conventional trial-and-error formulation cannot efficiently balance performance, processability, recyclability, and environmental constraints. This study proposes a generative artificial intelligence framework for designing polymer composites for photovoltaic encapsulation, dielectric energy storage, polymer electrolytes, and thermal-management systems. Public polymer-property and composite datasets were curated from open databases and published supplementary records. Chemical descriptors, molecular fingerprints, polymer embeddings, processing variables, and sustainability …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1232–1257 Read article
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Metamaterial-Based Thermal Shielding Structures for Reusable Hypersonic Space Transportation Systems
Abstract: The rapid development of reusable hypersonic space transportation systems has intensified the need for advanced thermal protection technologies capable of withstanding extreme aerodynamic heating conditions encountered during atmospheric re-entry and sustained hypersonic flight. Conventional thermal shielding materials often suffer from high structural weight, limited adaptability, thermal fatigue, and degradation under repeated thermal cycling. This study proposes a novel Metamaterial-Based Thermal Shielding Structure for Reusable Hypersonic Space Transportation Systems, integrating engineered …
Published in Journal of Aerospace Engineering & Technology · Vol. 16, Issue 2, 2026 Read article
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Passive Digital Phenotyping for Longitudinal Burnout and Occupational Mental Health Surveillance: A Transformer-Based Explainable Deep Learning Approach Using Smartphone Behavioral Streams
Abstract: Occupational burnout constitutes a pervasive yet chronically under-surveilled public health threat, its insidious temporal evolution rendering episodic self-report instruments structurally inadequate for early detection. This paper introduces BurnoutSense, a passive digital phenotyping framework that continuously harvests eight heterogeneous smartphone behavioral data streams encompassing application usage ecology, communication metadata, geospatial mobility, screen interaction dynamics, inferred sleep rhythmicity, keystroke kinematics, ambient noise exposure, and battery/charging cadence to construct individualized multivariate behavioral signatures …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 2, 2026 · pp. 44–53 Read article
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The Impact of Artificial Intelligence on the Sales and Marketing of Pharmaceutical Products
Abstract: The rapid development of computing and technology has permeated all branches of science, with artificial intelligence (AI) emerging as a pivotal field in computer science. AI has significantly influenced disciplines ranging from basic engineering to pharmaceuticals. In healthcare and medicinal chemistry, AI applications have become indispensable. Traditional drug discovery approaches are gradually being overtaken by computer-aided drug design. In recent years, artificial intelligence (AI) and machine learning (ML) have become …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 1, 2025 · pp. 10–18 Read article
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Mechanical Performance Assessment of Hybrid FRP Laminates with Carbon Fiber Core Using Experimental and Numerical Approaches
Abstract: The high strength-to-weight ratio, corrosion resistance and design flexibility of Fiber-reinforced polymer (FRP) composites have attracted considerable attention in aerospace, automotive and structural applications. This work presents an experimental and finite element study on the tensile and flexural behavior of epoxy-based hybrid FRP laminates. Five laminate configurations were manufactured, including a unidirectional carbon fiber laminate and four hybrid laminates, Kevlar–Carbon–Kevlar (K/C/K), Glass–Carbon–Glass (G/C/G), Kevlar–Carbon–Glass (K/C/G), and Glass–Carbon–Kevlar (G/C/K). For all …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Artificial Intelligence-Assisted Multi-Objective Optimization of Agricultural Biomass-Reinforced Polymer Composites
Abstract: Agricultural biomass can reduce the environmental burden of polymer composites, yet its heterogeneous structure creates competing effects on strength, moisture resistance, density, and process ability. This study developed an artificial intelligence-assisted framework for balanced composite formulation. Experimental data of agricultural biomass reinforced polymer composites were gathered, harmonized and validated using leakage-controlled validation. The mechanical and physical properties were predicted by artificial neural networks and conventional regression models. Explainable analysis gave …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 202–222 Read article
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Application of Artificial Neural Networks in Optimizing Polyhouse Roof Truss Design
Abstract: Polyhouses are specialised agricultural structures developed to maintain controlled environmental conditions for crop cultivation, thereby ensuring consistent productivity even under adverse climatic circumstances. The performance of these systems largely relies on the structural stability and cost efficiency of the roof truss, which must achieve an effective balance between strength, adaptability, and economy. In this research, an Artificial Neural Network (ANN)-based modelling framework is introduced to optimise the members of polyhouse …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 15–25 Read article
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THERMAL DISSIPATION SYSTEM APPLIED TO LED DEVICES
Abstract: A thermal dissipation system, based on an aluminum case LED lamp system encapsulated in a PCM device, has been used to reduce LED device temperature, improving thermal performance of the LED unit. Three heating rates have been tested, low (0.6ºC/s), medium (1.3ºC/s) and high (1.8ºC/s). The system has been tested in an experimental prototype at reduced scale, showing a maximum reduction of temperature from 177.5º C to 56º C for …
Published in Journal of Thermal Engineering and Applications · Vol. 8, Issue 3, 2021 · pp. 1–18 Read article
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Mathematical Modeling of Concentration Flux in Thermosensitive Biopolymer-assisted Drug Delivery
Abstract: A mathematical model of drug concentration flux across thermosensitive biopolymer with degradable cross-link was developed to predict the effect of the physical configuration and chemical composition of thermosensitive biopolymer on the kinetics of MK2 inhibitor peptide drug release. The overall goal of this research was to efficiently model the 3D drug release kinetics of a controlled drug from a double-shell spherical nanoparticle. The newly developed model would be used to …
Published in Journal of Thermal Engineering and Applications · Vol. 9, Issue 3, 2022 · pp. 9–15 Read article
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Implementation of Kalman Filter Using TDC and PLL for Object Detection and Tracking in Signal Processing
Abstract: The measurement uncertainty of GPS receivers is dependent on a wide range of external factors, including receiver clock precision, thermal noise, atmospheric influences, and minute variations in satellite positions. Estimating hidden states precisely and accurately in the face of uncertainty is one of the main problems facing tracking and control systems. Among the most significant and widely used estimate methods is the Kalman Filter. It uses imprecise and erratic measurements …
Published in Current Trends in Signal Processing · Vol. 13, Issue 2, 2023 · pp. 38–47 Read article
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Implementation of K-Means clustering algorithm with technical indicators to identify Profitable stocks
Abstract: In the ever-changing world of stock market trading, accurately predicting price movements is key to maximizing profits. Technical analysis, which looks at past price data to predict future trends, provides valuable insights for investors. This paper delves into using machine learning methods, particularly the K-Means clustering algorithm, along with moving average data, to categorize daily trading patterns. By breaking down the market into clusters and examining the main patterns within …
Published in Current Trends in Signal Processing · Vol. 13, Issue 3, 2023 · pp. 8–14 Read article
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The Application of Buckingham Pi Theorem to Monitor Procurement Service Delivery: A Case Study of Walnut Wood
Abstract: The aim of this research is to demonstrate the application of Buckingham theorem to monitor procurement delivery of Walnut wood. In this investigation, wood material of walnut wood density, constant area, diameter and velocity was used to monitor, predict and simulate the weight, delivery time and tensile strength on the truck. The walnut wood material was investigated in terms of delivery time, tensile strength and the effect on the truck …
Published in Emerging Trends in Chemical Engineering · Vol. 10, Issue 1, 2023 · pp. 54–63 Read article
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INFLUENCE OF CLIMATIC CHANGES ONTO THE PERFORMANCE OF ELECTRIC VEHICLES: APPLICATION TO DRIVING RANGE
Abstract: The paper has the goal of developing a methodological process to predict electric vehicle driving range under the influence of sudden temperature changes in intercity routes due to variable climatic conditions. The model is based on the combined effects of discharge rate and temperature changes on the performance of a lithium battery; the model predicts the driving range using the dynamic driving conditions to determine the Depth-Of-Discharge (DOD) at any …
Published in Journal of Automobile Engineering and Applications · Vol. 9, Issue 2, 2022 · pp. 43–58 Read article
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Simulation of a Renewable Energy Hybrid MicroHydro-Wind-PV-Solar System for Electric Generation
Abstract: This project is based on the development of a renewable energy hybrid tri-system made up of a photovoltaic device, a small wind turbine and a micro hydraulic turbine to generate electricity in places where these renewable energy resources are available. The system pursues the reduction of energy dependence on local electric network as well as the greenhouse gases emission. The project will be theoretically modelled and verified in a small …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 13, Issue 2, 2022 · pp. 37–50 Read article
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Forecasting of Factors Affecting Thermiston Work Productivity Estimation by Using Artificial Neural Network
Abstract: The research aims to find factors affecting of Thermiston work productivity and the derivation of an equation to predict the rates of Thermiston work productivity by using artificial neural network technology and compared with traditional methods. The Artificial Neural Network with multilayer by back-propagation error technique for modeling the productivity estimation is used, it is founded that the ANN are able to manage to, can predict the productivity for Thermiston …
Published in Journal of Construction Engineering, Technology & Management · Vol. 7, Issue 1, 2017 · pp. 10–21 Read article
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Participatory Risk Management Model for Construction Projects Using Expert Systems
Abstract: Construction involves processing of numerous interdependent risks. But risk management in the sector is still largely intuitive and mere system compliance. Meticulous efforts towards a system-based approach is lacking. These lapses emphasized the need for developing an easy to use participatory model for risk management at construction project sites. A model that would not only enhance the effectiveness of the risk management process but also generate essential knowledge that can …
Published in Journal of Construction Engineering, Technology & Management · Vol. 6, Issue 2, 2016 · pp. 17–24 Read article
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Applications of Artificial Neural Network in Construction Engineering and Management: An Academic Literature Review and Direction for Future Research
Abstract: One of the artificial intelligence topics is artificial neural network in whichdata processing system is the idea of the human brain.The cause of processing data is many processorsthat treat in parallel form in order to solve the problem.The applications of artificial neural network with neuron model and different network architecture can be used to estimate, predict and modelling of complex problems in construction management. In order to bridge the gap …
Published in Journal of Construction Engineering, Technology & Management · Vol. 6, Issue 1, 2016 · pp. 24–38 Read article