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182 articles for “driving behavior”
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Physics-Informed Neural Networks for Multiphysics Analysis of Biomedical Polymer Composite Systems
Abstract: Physics-Informed Neural Networks (PINNs) offer an effective model of solving coupled multiphysics equations in biomedical polymer composite systems, which are data-driven. In the given work, the PINN method is presented where equations of elasticity, mass diffusion, and heat transfer are integrated to model the complex processes that take place in composite biomaterials. The neural network loss is specified to include the governing partial different equations which enables both the system …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Design and Development of an Electromagnetic Propulsion Train
Abstract: The recent advancement of new transportation techniques led to the search for methods of propulsion that were superior to classical mechanical systems. Among these new moments, electromagnetic propulsion (EMP) has attracted attention because this technique allows for motion generation via electromagnetic force without using conventional wheel-based friction processing. The paper describes the conceptual design, principle of working and performance evaluation of a prototype model train to be propelled electromagnetically.The system, …
Published in Trends in Mechanical Engineering & Technology · Vol. 15, Issue 3, 2025 · pp. 19–24 Read article
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Thermo-Mechanical Behavior and Intelligent Optimization of Contact Temperature During Ultrasonic Vibration-Assisted Single-Pole Magnetic Abrasive Finishing of Zinc Alloy
Abstract: This study proposes a new integration of the experimental analysis, multi-physics finite element modelling (FEM) and machine learning (ML) optimisation of contact temperature (CT) in ultrasonic vibration-assisted single pole magnetic abrasive finishing (UV-SPMAF) of zinc alloy. The three gaps of the research are addressed: (i) The absence of a multi-physics FEM model that can couple electromagnetic, thermal and structural fields for UV-SPMAF of zinc; (ii) No quantified contribution of the …
Published in International Journal of Manufacturing and Production Engineering · Vol. 4, Issue 2, 2026 Read article
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The Evolution of Payments: Traditional Bill Methods Compared to Mobile Innovations
Abstract: "Mobile Payment Experiences in the Future" explores the transformative impact of emerging technologies: Artificial Intelligence (AI), 5G connectivity, and biometrics, on the evolution of mobile payment systems, moving beyond today's simple "tap and pay" solutions. As mobile payments become an essential component of global commerce, these innovations are set to redefine the payment landscape by enhancing transaction speed, security, and personalization. AI will enable real-time fraud detection, adaptive user verification, …
Published in International Journal of Mobile Computing Technology · Vol. 3, Issue 1, 2025 · pp. 17–27 Read article
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AI-Driven Innovation in Biomaterials: Predictive Modeling and Design for the Future
Abstract: The integration of artificial intelligence (AI) is revolutionizing the field of biomaterials, paving the way for innovative approaches in their development and production. This paper examines the connection between AI and biomaterials, emphasizing the substantial impact of predictive modeling on the evolution of the field. By examining recent research and cutting-edge uses, the document shows how AI-powered predictive modeling has revolutionized biomaterial design, marking a period of unparalleled precision and …
Published in Trends in Machine design · Vol. 11, Issue 3, 2024 · pp. 25–35 Read article
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Data-Driven Energy Forecasting for Smart Homes: Ensemble Learning from IoT Meters and Relevance for Polymer-Composite Based Smart Infrastructure
Abstract: Reliable estimation of household electricity demand is relevant in creating efficiency in energy usage, optimization of the loads, and intelligent demand-side management in intelligent grid systems. This paper introduces a varied machine learning model that approaches residential electric consumption prediction using an assortment of ensemble regression boosts, including Linear Regression, Lasso Regression, Decision Tree Regressor, Random Forest, and Gradient Boosting, to predict residential electricity consumption environments on a time-series arrested …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 29–64 Read article
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Autonomous 6G Physical Layer Architectures for Space-Air-Ground Integrated Networks
Abstract: The emergence of sixth generation (6G) wireless systems calls for a significant shift away from conventional deterministic communication models. As communication infrastructures evolve into Space- Air-Ground Integrated Networks (SAGIN), traditional physical layer (PHY) techniques struggle to operate effectively under the severe Doppler effects and long propagation delays associated with space environments. This paper examines the role of artificial intelligence embedded directly within the 6G transceiver architecture to enable ultra-reliable and …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 2, 2026 · pp. 21–31 Read article
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Integrating Atmospheric Science: Understanding Greenhouse Gases, Aerosols, and Air Quality Dynamics
Abstract: Atmospheric science investigates the Earth’s atmospheric systems to understand their composition, dynamics, and the implications for climate, weather, and air quality. This review explores five primary areas within the field: atmospheric composition, atmospheric modeling, remote sensing, air pollution, and boundary layer dynamics, highlighting critical challenges and advancements. Rising levels of greenhouse gases (GHGs), including carbon dioxide and methane, continue to drive global warming, while feedback mechanisms—like cloud interactions and surface …
Published in International Journal of Atmosphere · Vol. 1, Issue 1, 2024 · pp. 32–35 Read article
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Nutrition Induced Remodeling Dynamics of Cell Membranes: Implications for Performance, Health, and Welfare Issues in Food Animals
Abstract: Cell membranes represent dynamic structural and functional platforms that integrate nutritional signals with cellular metabolism, immune competence, and physiological adaptation in food animals. Beyond their classical role as selective barriers, membranes actively regulate nutrient transport, signal transduction, and bioenergetics through highly responsive lipid and protein networks. Dietary components, particularly fatty acids, vitamins, minerals, amino acids, and bioactive compounds, critically influence membrane composition, fluidity, and stability, thereby shaping cellular function and …
Published in International Journal of Membranes · Vol. 3, Issue 1, 2026 · pp. 25–37 Read article
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THE BURDEN OF EMPIRICAL THERAPY: ANALYZING THE PREDOMINANCE OF BROAD-SPECTRUM ANTIBIOTIC USAGE IN LOWER RESPIRATORY TRACT INFECTIONS
Abstract: Lower respiratory tract infections (LRTIs) remain one of the leading causes of morbidity and hospitalization worldwide, particularly among older adults, immunocompromised individuals, and patients with chronic respiratory disorders. These infections include conditions such as community-acquired pneumonia, hospital-acquired pneumonia, bronchitis, and acute infective exacerbations of chronic lung disease, all of which often require rapid clinical intervention. Because microbiological confirmation of the causative pathogen frequently takes 48–72 hours, clinicians generally initiate empirical …
Published in International Journal of Antibiotics · Vol. 3, Issue 2, 2026 Read article
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Develop a Data Science Approach for Optimizing Energy Consumption
Abstract: Optimizing energy consumption has become a critical challenge in the era of sustainability and increasing energy demand. Efficient energy management is essential to address environmental concerns, reduce costs, and ensure resource availability for future generations. This project leverages data science techniques to evaluate and improve energy consumption across diverse sectors, including residential, industrial, and commercial domains. By integrating advanced analytics, machine learning models, and real-time data processing, the project aims …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 31–44 Read article
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Motors Using a Deep Learning-Based Torque Control with Torque Ripple Reduction under Nonlinear Magnetic Conditions
Abstract: This research discusses a deep learning strategy for torque management to minimize the effect of torque ripple in a nonlinear electric motor. Nonlinear electric motor losses may include: magnetic saturation, harmonic flux losses and inverter losses. In many cases when the system parameters deviate and/or instability issues occur, the traditional method with a model-based approach or PI control may encounter challenges. In this case, the authors proposed a hybrid approach …
Published in International Journal of Advanced Control and System Engineering · Vol. 4, Issue 2, 2026 Read article
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Transforming Human Resources Leveraging AI Across the Associate Lifecycle for Strategic Success
Abstract: AI is taking the lead in changing the game in human resources by mitigating challenges and optimizing processes throughout the entire associate lifecycle. From pre-hire, AI helps with interview bias, enhances hire projections, and supports talent acquisition with predictive analytics. Once onboarded, AI helps with compensation benchmarking, automates performance feedback with the mitigation of bias, and analyzes associate sentiment through NLP and LLMs. In the middle of the life cycle, …
Published in Recent Trends in Programming languages · Vol. 12, Issue 1, 2025 · pp. 30–36 Read article
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Numerical Investigation of the Osmatic Flow Impact on the Load Recovery and Early Well Performance
Abstract: The complexity of shale system coupled with the mystery of low fracturing fluid recovery has puzzled many researchers. Field reports from hydraulic fracturing operations performed on shale formation have highlighted the low recovery of the fracturing fluid. The fate of the hydraulic fracturing fluid is still controversial issue. However, literature has attributed the low load recovery to either trapping into the natural or created micro-fracture or imbibition to the matrix. …
Published in Journal of Petroleum Engineering & Technology · Vol. 5, Issue 3, 2015 · pp. 52–64 Read article
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Digital Twin-Driven Structural Health Monitoring and Energy Management of IoT-Enabled Energy-Storing Polymer Composites Using Explainable Machine Learning
Abstract: Energy storing polymer composites are widely utilized in intelligent structural systems, because of their mechanical and electrochemical properties. But, under varying thermo-mechanical and environmental conditions, it is important to have accurate degradation monitoring for real-time industrial process is challenging. In this work, an explainable machine-learning framework for structural health monitoring and adaptive energy management of polymer composites with energy storage capacity is proposed in an IoT environment with the help …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Codal Validation and Optimization of Gantry Girders Under Variable Wheelbase and Impact Loads: A Review of Analytical, Numerical, and Codal Approaches
Abstract: Gantry girders serve as critical structural elements in industrial facilities such as steel plants, workshops, and heavy manufacturing units, where electric overhead traveling (EOT) cranes operate. The design of these girders is governed by stringent codal provisions to ensure safety under bending, shear, and deflection. However, discrepancies between codal predictions, analytical formulations, and finite element analysis (FEA) results, particularly under variable wheelbase and dynamic impact loads, have been widely reported. …
Published in Journal of Offshore Structure and Technology · Vol. 12, Issue 3, 2025 · pp. 23–29 Read article
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Fractality of Magnetospheric Dynamics: A Diffusion Entropy Approach
Abstract: There are several self-organization processes in physics such as second-order phase transitions and associated scale-invariant phenomena, structure formation in thermodynamic systems away from equilibrium, self-organization of solitons into vortices in magnetized plasma etc. Space plasmas often display very complex behavior which includes multiscale dynamics, spatio-temporal chaos and self-organized criticality. The study of self-organization in magnetospheric plasma and its relation with instabilities is a subject at the forefront of space research …
Published in Research & Reviews : Journal of Physics · Vol. 7, Issue 2, 2018 · pp. 44–53 Read article
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Prediction of Mechanical Properties for Advanced Engineering Applications utilizing Polymer Composite Materials by Machine Learning
Abstract: Polymer composites show great promise as engineering materials because of their mechanical performance, resistance to corrosion, lightweight nature, and adaptability in design. Aerospace, automotive, biomedical, maritime, and civil engineers all rely on mechanical property prediction to cut down on trial expenses, expedite product development, and optimize material selection. Speedy design optimization is not possible using traditional numerical and experimental methods due to the high costs associated with material characterisation, computational …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1258–1284 Read article
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Air Flow Analysis in Sensor-Based Aircraft Wings Design
Abstract: Airflow analysis, at its core, is an application of fluid mechanics principles to the specific study of air movement. Airflow analysis plays a crucial role in diverse fields, impacting everything from the comfort of our homes to the efficiency of jet engines. The pursuit of more efficient, safer, and more responsive aircraft wings is a constant driver of innovation in the aerospace industry. The quest for more efficient, safer, and …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 2, 2025 · pp. 29–39 Read article
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Task Scheduling in Cloud Computing using Hippopotamus Optimization Algorithm
Abstract: Cloud computing, which provides remote clients with on-demand services, has emerged as a crucial component of contemporary technology. It is still difficult to schedule tasks effectively in such diverse and dynamic situations. Motivated by the hippopotamus's balanced exploration and exploitation behavior, this research suggests a unique work scheduling method utilizing the hippopotamus optimization algorithm (HOA). In order to maximize resource usage and throughput while minimizing makespan and execution cost, the …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 2, 2026 · pp. 22–29 Read article