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Finite Element Model-Based Weight-Over Process Philosophy for Bridge Loading Capacity Evaluation and Rating Factor Estimation
Published 2021-01-01“…This article presents the weight-over process (WOP), a novel computer-aided approach to bridge loading capacity evaluation based on tonnage and rating factor estimation. …”
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THEORETICAL STUDIES OF THE LEACHING PROCESS OF THE MUDDING ELEMENT IN THE GRAVEL PACKAGE OF THE WELL FILTER USING THE UNIT FOR REVERSE-REAGENT REGENERATION
Published 2018-01-01“…With the aid of the developed computer program, the operation of the unit for reverse-reagent filter regeneration is considered on behalf of a water well using two different reagents: hydrochloric acid and sodium dithionite. …”
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Management and prediction of river flood utilizing optimization approach of artificial intelligence evolutionary algorithms
Published 2025-07-01“…These evolutionary algorithms simulate natural processes like selection, mutation, and crossover to optimize flood predictions and management strategies, improving adaptability in dynamic environments. …”
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Structural Similarity-Guided Siamese U-Net Model for Detecting Changes in Snow Water Equivalent
Published 2025-05-01“…Snow water equivalent (SWE), the amount of water generated when a snowpack melts, has been used to study the impacts of climate change on the cryosphere processes and snow cover dynamics during the winter season. …”
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A Circuit-Model-Navigated Design Process and Efficiency Estimation for Short-Circuited Self-Excited EBG Resonator Antenna
Published 2016-01-01“…The paper presents a circuit model for the computationally efficient design of a planar Short-Circuited Self-Excited EBG Resonator Antenna (SC SE-EBG-RA). …”
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Fabrication of a 77 GHz Rotman Lens on a High Resistivity Silicon Wafer Using Lift-Off Process
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Power Quality 24 h Verification in Smart Load Scheduling Based on Differentiate, Deep, and Assembly Statistics in NWP Processing
Published 2025-01-01“…AI statistics allow processing entire 24 h forecast series, replacing related real-valued quantities available in learning stage, to compute final PQ targets at the corresponding prediction times. …”
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Quantifying Dynamic Oil Immersion in a Spiral Bevel Gear via Image Processing for Improved Churning Loss Prediction
Published 2025-05-01“…To quantify the practical immersion depth, a computational fluid dynamics (CFD) approach integrated with image processing techniques is utilized to determine the dynamic immersion depth and the associated churning power loss. …”
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