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The buffered work-pool approach for search-tree based optimization algorithms
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Data of simulation model for photovoltaic system's maximum power point tracking using sequential Monte Carlo algorithm
Published 2024“…This article outlines the input data and partial shading conditions employed in the replication model of Sequential Monte Carlo (SMC)-based tracking techniques for photovoltaic (PV) systems. …”
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A Low-Cost Closed-Loop Solar Tracking System Based on the Sun Position Algorithm
Published 2019“…In summary, even for a small-scale solar tracking system, the algorithm-based closed-loop dual-axis tracking system can increase overall system efficiency. …”
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Optimum Track to Track Fusion Using CMA-ES and LSTM Techniques
Published 2024“…The first method uses an offline technique based on a global optimizer called the CMA-ES algorithm and the second one uses LSTM in its different forms to learn the online adjustment of the fusion weights between the two tracks. …”
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A reduced model for phase-change problems with radiation using simplified PN approximations
Published 2025“…The integro-differential equation for the full radiative transfer is replaced by a set of differential equations which are independent of the angle variable and easy to solve using conventional computational methods. To solve the coupled equations, we implement a second-order implicit scheme for the time integration and a mixed finite element method for the space discretization. …”
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MLMRS-Net: Electroencephalography (EEG) motion artifacts removal using a multi-layer multi-resolution spatially pooled 1D signal reconstruction network
Published 2022“…Because the diagnosis of many neurological diseases is heavily reliant on clean EEG data, it is critical to eliminate motion artifacts from motion-corrupted EEG signals using reliable and robust algorithms. Although a few deep learning-based models have been proposed for the removal of ocular, muscle, and cardiac artifacts from EEG data to the best of our knowledge, there is no attempt has been made in removing motion artifacts from motion-corrupted EEG signals: In this paper, a novel 1D convolutional neural network (CNN) called multi-layer multi-resolution spatially pooled (MLMRS) network for signal reconstruction is proposed for EEG motion artifact removal. …”
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Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices
Published 2016Subjects: Get full text
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Brain Source Localization in the Presence of Leadfield Perturbations
Published 2015Get full text
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Monitoring Bone Density Using Microwave Tomography of Human Legs: A Numerical Feasibility Study
Published 2021“…This study was performed using an in-house finite-element method contrast source inversion algorithm (FEM-CSI). …”
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The Use of Microwave Tomography in Bone Healing Monitoring
Published 2019Get full text
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Design of an innovative and self-adaptive-smart algorithm to investigate the structural integrity of a rail track using Rayleigh waves emitted and sensed by a fully non-contact las...
Published 2020“…The functioning of the algorithm was successfully tested by carrying out extensive experiments on a real rail track in the presence of different types of surface and sub-surface defects on its head and web. …”
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Design of adaptive arrays based on element position perturbations
Published 1993“…The main advantage of using this technique over the other commonly used methods is that the amplitudes and phases of the array elements can be used mainly to steer the main beam towards the desired signal. …”
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Lagrangian tracking in stochastic fields with application to an ensemble of velocity fields in the Red Sea
Published 2018“…Lagrangian tracking of passive tracers in a stochastic velocity field within a sequential ensemble data assimilation framework is challenging due to the exponential growth in the number of particles. …”
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A Novel Internal Model Control Scheme for Adaptive Tracking of Nonlinear Dynamic Plants
Published 2006“…The U-model utilizes only past data for plant modelling and standard root solving algorithm for control law formulation. …”
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A kernelization algorithm for d-Hitting Set
Published 2010“…For 3-Hitting Set, an arbitrary instance is reduced into an equivalent one that contains at most 5k2+k elements. This kernelization is an improvement over previously known methods that guarantee cubic-order kernels. …”
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