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321 articles for “Scaling Model”
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Assessing Flow Pattern of Sabarmati River Portion at Hirpura Barrage Site Gujarat, India Using HEC-RAS Hydrodynamic Models and Physical Models
Abstract: A barrage is proposed to be constructed across river Sabarmati, 60 km downstream of Daroi dam to create reservoir within the bank for recharging and meeting water demand of nearby areas. For analyzing the flow pattern and assessing the hydraulic parameters of Hipura barrage on Sabarmati river near Hirpura village of Mehsana District of Gujarat, a 3D physical model with geometrically similar scale 1:80 for river reach 3 km (1 …
Published in Journal of Water Resource Engineering and Management · Vol. 6, Issue 3, 2019 · pp. 46–51 Read article
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An Approach for Discrete-Time Systems Design Using MPSM Continued Fraction Expansion Technique
Abstract: AbstractThis paper presents a new method for the design of the high-order discrete-time systems to overcome the limitations and drawbacks of some of the existing methods. It uses the Multi Point Squared-Magnitude Continued Fraction Expansion (MPSMCFE) and factorization technique for obtaining both denominator and numerator of the reduced order models. The method is extended for the design of high order systems using the reduced order model in place of original …
Published in Journal of Instrumentation Technology & Innovations · Vol. 7, Issue 3, 2017 · pp. 11–15 Read article
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Remote Sensing and Atmospheric Modelling: Data, Processes, Integration and Future Directions
Abstract: Atmospheric modelling plays a central role in weather forecasting, climate projection, and air quality assessment; however, the availability, accuracy, and representativeness of atmospheric observations fundamentally constrain its reliability. Over the past two decades, rapid advances in remote sensing (RS) have transformed atmospheric observation by providing spatially continuous, multiscale measurements of key atmospheric variables, including aerosols, trace gases, clouds, precipitation, and atmospheric thermodynamic profiles. This review synthesises recent progress in integrating …
Published in International Journal of Atmosphere · Vol. 3, Issue 1, 2026 · pp. 54–67 Read article
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Integrating Digital Twins, Smart Materials, and Human Machine Collaboration for Sustainable Smart Manufacturing: Smart CNC & Industry 4.0 Applications
Abstract: The rapid evolution of Industry 4.0 and the emerging transition toward Industry 5.0 have been catalyzed by the convergence of intelligent digital technologies such as digital twins, cyber–physical systems (CPS), artificial intelligence (AI), the Internet of Things (IoT), and human-in-the-loop (HITL) frameworks. These technologies have transformed traditional manufacturing into adaptive, data-centric ecosystems capable of real-time optimization and predictive decision-making. In recent years, the fusion of computer numerical control (CNC) machines, …
Published in International Journal of Manufacturing and Production Engineering · Vol. 3, Issue 2, 2025 · pp. 1–8 Read article
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The Green Cost of Generative Ai: Environmental Sustainability Implications of Large-Scale Ai Systems
Abstract: Generative Artificial Intelligence (GenAI) has advanced rapidly in scale and complexity, enabling powerful capabilities in automated content creation, multimodal reasoning and real-time decision support across sectors. While these systems offer significant technological and economic benefits, their environmental implications are not fully examined. Large-scale GenAI models rely on high-performance computing infrastructure that consumes substantial energy and resources throughout their lifecycle, raising critical sustainability concerns. This paper offers a sustainability-oriented assessment of …
Published in International Journal of Sustainability · Vol. 3, Issue 1, 2026 · pp. 12–20 Read article
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Revolutionizing Low Carbon Concrete: Innovations at the Nexus of Computational Science, Data Analytics, and Sustainable Technologies
Abstract: Concrete production accounts for 7% of global CO2 emissions necessitating low carbon innovations to curb exponential demand threatening climate commitments. This research reviews sustainable construction literature integrating computational simulations, big data infrastructure monitoring and alternative process redesign. Analysis reveals 30-50% reductions achievable through combined use of industrial ecologies, smarter sensing coordinated with ML optimization and novel binders like alkali-activated geopolymers. Rigorous LCA quantification verifies environmental superiority over conventional formulations. Case …
Published in Journal of Construction Engineering, Technology & Management · Vol. 13, Issue 3, 2023 · pp. 16–23 Read article
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Experimental Investigation of Effect of Soil Structure Interaction on Buildings
Abstract: In the conventional analysis and design, buildings are generally considered to be fixed at their bases, but in actual practice, the support condition depends on the type of soil on which it is founded. The flexibility of the soil medium allows the movement of soil and foundation, which decreases in the overall stiffness of building frames and results in a subsequent increase in natural periods of the system. Thus, the …
Published in Journal of Structural Engineering and Management · Vol. 6, Issue 3, 2019 · pp. 32–45 Read article
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Analysis of new Floating Offshore Wind Turbine under drag force operation
Abstract: The goal of this paper is the study and analysis of a new type of floating offshore wind turbine (FOWT), which operates under drag force instead of lifting force as the conventional FOWT. We simulate the wind turbine operation modifying the pitch angle to faithfully reproduce the behavior when submitted to waves’ movement. The analysis of the wind turbine performance is developed in a model at laboratory scale to control …
Published in Journal of Offshore Structure and Technology · Vol. 11, Issue 1, 2024 · pp. 1–10 Read article
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Container transportation in marine terminals and marine transportation infrastructure on the increase in export market share
Abstract: In order to achieve important policy goals like increasing global competitiveness, diversifying import sources, opening up new markets, and forging strategic partnerships, maritime transportation is essential. It also has a significant impact on reducing the economic vulnerability of nations that rely on the sale of gas and oil by carefully choosing its clients and growing the export of petroleum products, petrochemicals, and gas. This study develops a two-objective mathematical planning …
Published in Journal of Petroleum Engineering & Technology · Vol. 14, Issue 1, 2024 · pp. 36–42 Read article
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AI – Driven Smart Laboratory for Synthetic Organic Chemistry – A Literature Review
Abstract: The traditional chemistry laboratory is often subjective, time consuming and skill intensive that may lead to inconsistencies in the desired results. The advent of Artificial Intelligence (AI) and its speedy incorporation into the field of chemistry is transforming traditional synthetic laboratories into intelligent, automated systems that combine hardware, software and AI into a unified framework. This paper presents a comprehensive overview of AI – driven laboratory setup for organic synthesis, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Quasar: Quantum-Accelerated Sustainable Anomaly Recognition in Climate Systems
Abstract: Accurate detection of climate anomalies is vital for disaster alleviation and policy making in a sustainable manner, but customary detection methods face the challenges of computational inefficiency and physical inconsistency. In this study, we propose a novel approach called Quantum-Optimized Fuzzy Physics-Informed Neural Networks (QFuzzy-PINNs), which integrates quantum computing, fuzzy logic, and physics-informed deep learning. As a first step, we employ quantum annealing for conventional optimization to adjust multiple Gaussian …
Published in International Journal of Climate Conditions · Vol. 2, Issue 2, 2025 · pp. 18–27 Read article
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POLYMER AND COMPOSITE-BASED GEOSYNTHETIC REINFORCEMENTS FOR SEISMIC STABILITY OF SOIL RETAINING STRUCTURES: MATERIALS, MECHANICS, AND PERFORMANCE REVIEW
Abstract: Geosynthetic materials based on polymer and composites have become important items for the structural performance and seismic resilience of the reinforced soil retaining systems. Mechanically stabilized earth walls in recent geotechnical engineering practice are increasingly based on enhanced polymeric reinforcements for enhanced tensile strength, durability, flexibility, and energy dissipation under dynamic loading. High-density polyethylene, polypropylene, polyester, and fiber-reinforced polymer composites are usually used. The present review focus on the recent …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Physics-Informed Machine Learning and Multiscale Modeling for Structure–Property Quantification of Polymer Composites
Abstract: The growing need for light-weight, high strength, and sustainable polymer composites has led to the development of smart methods that enable accurate structural-property quantification and material design. However, conventional methods have been predominantly data-based, thus ignoring physical constraints as well as multi-scale interactions involving fiber, matrix, interface, and process parameters, leading to lower accuracy and poor robustness and interpretability of the models. In this study, a Cat Swarm Optimization-Tuned Physics-Informed …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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A Novel Mathematical Exploration of Fractal Dynamics in Hyperbolic Spaces
Abstract: This research paper presents an original study on the behavior, generation, and properties of fractal structures within hyperbolic geometry. Unlike classical Euclidean fractals, hyperbolic fractals demonstrate accelerated boundary complexity and distinct scaling symmetries due to the curvature of the underlying space. The paper proposes new iterative models, analyzes geometric invariants, and explores potential applications in data visualization, network science, and theoretical physics. This research paper conducts an in-depth investigation into …
Published in Recent Trends in Mathematics · Vol. 3, Issue 1, 2026 · pp. 1–7 Read article
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Analysis of DIBL Effect in MOSFET Working
Abstract: AbstractOne of the most widely used electronic devices, particularly in digital integrated circuits, is the metal insulator semiconductor (MIS) transistor. Most of the existing transistors used in fabrication of integrated chips are with junctions. The device scaling is growing the channel length between junctions in devices are scaling gone down to 10 nm. Drain Induced Barrier Lowering (DIBL) effect is prominent as the feature size of MOS device keep diminishing. …
Published in Journal of Microelectronics and Solid State Devices · Vol. 5, Issue 3, 2018 · pp. 33–40 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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An Automation Detection for Sign Language Using AI
Abstract: Sign language recognition has attracted considerable interest because of its ability to facilitate communication between the deaf community and the public, thereby bridging communication divides. Traditional approaches to sign language recognition often face challenges in accurately interpreting the complex and nuanced gestures inherent in sign languages. However, recent advancements in deep learning techniques have shown promising results in improving the accuracy and robustness of sign language recognition systems. This study …
Published in Recent Trends in Programming languages · Vol. 11, Issue 1, 2024 · pp. 1–14 Read article
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Swarm Intelligence in Software Engineering: A Systematic Review of Crowd-Based Development Models
Abstract: The crowd-based software production model has emerged as a transformative paradigm, leveraging global collaboration, decentralized governance, and artificial intelligence (AI)-driven automation to develop software efficiently. Traditional software development models, characterized by centralized control and in-house teams, are increasingly giving way to distributed, community-driven efforts. Key advancements such as blockchain-based decentralized autonomous organizations (DAOs), AI-assisted coding and debugging, and edge computing applications are reshaping the landscape of software engineering. DAOs provide …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 2, 2025 · pp. 01–11 Read article
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Modelling and Simulation of Urban Smart Micro Grid Operation
Abstract: The project is aimed at the development of a new protocol that enhances the operation of urban micro grid operation. The new protocol improves the capacity of management as well as the energy efficiency of the smart grid as an entire system. The modelling considers the interconnectivity between sources of energy and consumption centers, the daily hourly power generation by the different sources, and the hourly energy demand profile. The …
Published in Journal of Nuclear Engineering & Technology · Vol. 11, Issue 3, 2021 · pp. 5–28 Read article
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Federated Learning Framework for Sustainable Multi-Scale Design of Recyclable Thermoplastic Graphene Composites in Smart Manufacturing Environments
Abstract: The growing demand for sustainable advanced materials has accelerated the development of recyclable thermoplastic graphene composites for next-generation smart manufacturing systems. The typical central optimization methods have challenges with data privacy, scalability, and poor collaboration between distributed manufacturing sites. By combining material informatics, edge intelligence and distributed artificial intelligence, this study introduces a Federated Learning (FL) framework to design recyclable thermoplastic graphene composites at multiple scales sustainably. The proposed framework …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article