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588 articles for “computational modelling”
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The Significance and Applications of Parallel Computing in the Modern Era
Abstract: This article explores the advancements in parallel computing, focusing on its applications in various domains such as scientific simulations, big data analytics, artificial intelligence, and real-time processing. We discuss the architectural shifts from traditional single-core processors to multi-core and many-core systems, along with the role of graphics processing unit (GPU)-based computing and specialized hardware like tensor processing units (TPUs) and field programmable gate arrays (FPGAs). Furthermore, the article examines contemporary …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 1, 2025 · pp. 24–38 Read article
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A Comprehensive Study of Natural Language Processing Systems Using Modern Programming Languages: Techniques, Architectures, Experimental Evaluation, and Applications
Abstract: Natural Language Processing is a key field of study within artificial intelligence that focuses on enabling machines to understand and work with human language. This is because there is much digital text data everywhere. Natural Language Processing is what this study is about. It looks at new ways of doing Natural Language Processing. The old ways are like machine learning and the new ways are like learning. This study compares …
Published in Recent Trends in Programming languages · Vol. 13, Issue 1, 2026 Read article
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Effect of Welding Factors on Nugget Size of Polymer-Metal Composite Sheets Using Computational Methods
Abstract: Resistance spot welding (RSW) is a vital technique for joining materials in industries like automotive and aerospace. This study extends the application of RSW to polymer-metal composite sheets by developing 2D axisymmetric, thermo-electro-mechanical coupled model in ANSYS. The focus is on analyzing the temperature distribution, nugget formation, and parameter optimization in hybrid composite sheets, emphasizing the unique challenges posed by polymers' thermal and electrical properties. These properties differ significantly from …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 612–623 Read article
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Real-Time Cab Fare and ETA Prediction Using API Integration
Abstract: The exponential proliferation of ride-hailing platforms has necessitated the formulation of sophisticated and highly responsive predictive models for cab fare estimation and estimated time of arrival (ETA) computation. This work elucidates a robust framework leveraging real-time application programming interface (API) integration from Uber and Ola within a Flutter-based ecosystem to enhance predictive analytics. By assimilating real-time geospatial data, dynamic pricing algorithms, and latency-optimized API responses, this study investigates the empirical …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 08–15 Read article
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Strategic Solutions: How Mathematics Reshapes Industrial Landscapes
Abstract: One of the earliest and most fundamental fields of the physical sciences is mathematics. It has a significant impact on industrial enterprises' bottom lines and enhances their performance in the current data-driven market. One subfield of applied mathematics is industrial mathematics. It concentrates on issues that arise in the industry and seeks answers that are pertinent to the sector. The use of mathematical models and techniques to diverse industry difficulties …
Published in International Journal of Industrial and Product Design Engineering · Vol. 2, Issue 1, 2024 · pp. 16–23 Read article
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An Investigation of Model Predictive Control in Self-driving Vehicles
Abstract: Autonomous vehicles, which are often known as self-driving automobiles or driverless cars, are vehicles that can navigate and operate without human intervention. They require efficient controllers capable of handling complexities, with reduced computational costs, and should handle multiple inputs and outputs simultaneously. Model predictive control (MPC) possesses all these characteristics which means it can be utilized effectively for the same purpose. MPC for autonomous vehicles proposes various ways of achieving …
Published in Trends in Electrical Engineering · Vol. 14, Issue 1, 2024 · pp. 40–50 Read article
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Time Series Methods in Meteorology: A Review of Predictive Models and Applications
Abstract: The accurate prediction of time series data holds substantial significance in various fields, enabling informed decision-making and resource optimization. In this study, temperature variations over time are predicted using the Autoregressive Integrated Moving Average (ARIMA) model. Reliable temperature projections are more important now than ever because of climate change and its effects. For time series prediction problems, the ARIMA model—which is well-known for its ability to capture temporal dependencies in …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 13, Issue 2, 2024 · pp. 35–46 Read article
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Recent Trends in Fluid Mechanics with Emphasis on Aeroacoustics and Flow-Induced Noise Control
Abstract: Fluid mechanics continues to evolve rapidly due to increasing demands in aerospace, automotive, energy, and environmental engineering applications. Recent trends in this field highlight significant advancements in both theoretical understanding and practical implementations, particularly in complex flow phenomena. Among these, aeroacoustics and flow-induced noise control have emerged as critical research areas due to their direct impact on system performance, efficiency, and environmental sustainability. Aeroacoustics deals with the generation, propagation, and …
Published in Recent Trends in Fluid Mechanics · Vol. 13, Issue 1, 2026 · pp. 32–38 Read article
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Review On BIM-Based (Revit+Robot Software) Comparative Wind Load Analysis of High-Rise RCC Buildings in Zone-III, IV and V
Abstract: Wind load is one of the most critical factors influencing the design and serviceability of high-rise reinforced concrete (RCC) buildings. As building height increases, wind-induced effects such as storey drift, lateral displacement, and structural stiffness become dominant design considerations. Numerous studies have been conducted using conventional and advanced techniques such as Finite Element Method (FEM), Computational Fluid Dynamics (CFD), and Building Information Modelling (BIM). However, limited research focuses on comparative …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 2, 2026 Read article
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A Conceptual Framework for AI-Integrated Metabolomics in Predictive Health Systems for Resource-Constrained Environments
Abstract: The increasing prevalence of non-communicable diseases (NCDs) continues to place a significant strain on healthcare systems, particularly in low- and middle-income regions where access to early diagnostic infrastructure is limited. Conventional healthcare approaches remain largely reactive, often detecting diseases at advanced stages when treatment effectiveness is reduced. This challenge underscores the need for predictive, cost-effective, and data-driven healthcare solutions. This study presents a conceptual framework that integrates metabolomics with artificial …
Published in Emerging Trends in Metabolites · Vol. 3, Issue 2, 2026 Read article
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AI-Based Discovery of High-Performance Energy Storage Polymer Composites: A Comprehensive Review
Abstract: The accelerating global demand for high-performance energy storage systems has stimulated significant research into advanced polymer composites as next-generation electrolytes, electrode binders, and functional membranes for batteries, supercapacitors, and photovoltaic devices. However, the vast compositional and structural design space of polymer materials presents formidable challenges for conventional trial-and-error discovery strategies, which remain slow, costly, and biased by prior expert knowledge. Machine learning (ML) and artificial intelligence (AI) have emerged as …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1083–1097 Read article
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Intelligent Earth: AI As A Catalyst For Climate Action
Abstract: Artificial Intelligence (AI) is assuming an increasingly influential role in climate science, providing advanced tools capable of interpreting vast, complex, and multi-dimensional environmental datasets. Traditional climate modeling approaches, while grounded in physical principles, frequently struggle to deliver high-resolution, real-time, and region-specific forecasts because of heavy computational demands, incomplete observations, and uncertainties in representing small -- scale processes. Artificial intelligence (AI) techniques, especially machine learning and deep learning, provide strong substitutes …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 4, Issue 1, 2026 · pp. 48–52 Read article
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A Real-time Visualization Framework to Enhance Prompt Accuracy and Result Outcomes Based on the Number of Tokens
Abstract: In the rapidly evolving domain of artificial intelligence (AI), the efficacy of user-generated prompts has emerged as a critical factor influencing the quality of model-generated responses. Current methodologies for prompt evaluation predominantly rely on post-hoc analysis, which often leads to iterative prompting and increased computational overhead. Furthermore, the challenge of “prompt hallucinations,” where AI models produce irrelevant or nonsensical responses, persists as a significant impediment to effective AI utilization. The …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 45–53 Read article
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Integrated Perspectives on Fluid Mechanics and Energy Transport in Complex Flow Systems
Abstract: Fluid mechanics plays a central role in understanding the transport of mass, momentum, and energy in complex flow systems encountered in both natural and engineered environments. This review presents an integrated perspective on fluid behavior by combining fundamental principles with modern approaches to energy transport analysis. The study emphasizes the significance of conservation laws and their application to diverse flow regimes, including laminar, turbulent, compressible, and multiphase flows. Energy transport …
Published in Recent Trends in Fluid Mechanics · Vol. 13, Issue 1, 2026 · pp. 22–31 Read article
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Computational Fluid Dynamics and Composite Material Study on Scoop-Type Savonius Turbine for Train-Based Energy Generation
Abstract: This study investigates the feasibility of integrating a scoop-type savonius vertical-axis wind turbine (VAWT) on the rooftop of a moving train to generate renewable onboard power. The motivation stems from increasing demands for sustainable energy solutions and reducing reliance on fossil fuels, particularly in transportation. A two-blade savonius turbine, with dimensions of 0.4 m in diameter and 0.5 m in height, was modeled in PTC Creo Parametric 3.0 and analyzed …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 566–580 Read article
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Driver Drowsiness Detection System
Abstract: One of the main causes of road accidents worldwide in recent years is driver fatigue. Assessing a driver's mood, or how sleepy they are, is a clear approach to gauge their level of exhaustion. Therefore, detecting driver fatigue is very important to save lives and property. The creation of a prototype drowsiness detection system is the aim of this research. The system operates in real time, continuously capturing images and …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 16–21 Read article
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Implementing Blockchain to Enhance Security in the Pharmaceutical Industry and Combat Drug Counterfeiting
Abstract: Drug counterfeiting has emerged as a critical threat to public health, as it has enabled inferior and counterfeit drugs to flood many markets around the world thereby eroding trust in healthcare systems and patient safety. This paper seeks to address the glaring need for adequate security safeguards to curb the circulation of counterfeit drugs by proposing a blockchain model designed specifically for the pharmaceutical industries. In general, the idea of …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 1, 2025 · pp. 33–46 Read article
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Leveraging Large Language Models for Personalized Document Summarization and Question Answering: An Architecture for Stoner-Friendly Chatbots
Abstract: This study presents a detailed framework for developing personalized chatbots that utilize large language models (LLMs) to process and extract information from extensive documents while effectively responding to user inquiries. The proposed system is designed to mitigate information overload by employing advanced natural language processing techniques, leveraging technologies such as OpenAI, LangChain, and Streamlit. By integrating these tools, the framework enhances knowledge retrieval, simplifies document comprehension, and improves overall productivity. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 88–93 Read article
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Impact of Partially Observable Markov Decision Process in Next Generation Satellite for Remote Sensing
Abstract: The integration of Partially Observable Markov Decision Processes (POMDPs) in next- generation satellite systems represents a transformative advancement in remote sensing technology. This article explores how POMDP frameworks address the inherent uncertainties and incomplete observability challenges in satellite operations, including dynamic task scheduling, resource allocation, and adaptive sensing strategies. By modeling satellite decision-making under uncertainty, POMDPs enable autonomous systems to optimize mission objectives while managing constraints such as limited power, …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 2, 2025 · pp. 20–28 Read article
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AI-Based Preventive Healthcare Using Quantum Computing
Abstract: With its improved performance and capabilities, quantum machine learning (QML) is becoming a promising field, especially in the healthcare industry for tasks like early heart disease prediction. In this work, a Quantum Support Vector Classifier (QSVC) is proposed as the basic classifier for a bagging ensemble learning model. Shapley Additive explanations (SHAP) are used to evaluate the significance of each attribute in the predictions in order to improve explainability. Using …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 15, Issue 2, 2025 Read article