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1
Parallel Algorithm for Hardware Implementation of Inverse Halftoning
Published 2005“…A Parallel algorithm and its hardware implementation of Inverse Halftone operation is proposed in this paper. …”
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Parallel algorithm for hardware implementation of inverse halftoning
Published 2005“…A parallel algorithm and its hardware implementation are proposed for an inverse halftone operation. …”
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Sensitivity analysis and genetic algorithm-based shear capacity model for basalt FRC one-way slabs reinforced with BFRP bars
Published 2023“…Finally, a design equation that can predict the shear capacity of one-way BFRC-BFRP slabs was proposed based on genetic algorithm. The proposed model showed the best prediction accuracy compared to the available design codes and guidelines with a mean of predicted to experimental shear capacities (V<sub>pred</sub>/V<sub>exp</sub>) ratio of 0.97 and a coefficient of variation of 17.91%.…”
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A Parallel Algorithm for Inverse Halftoning and its Hardware Implementation
Published 2020“…The LUT method for inverse halftoning is parallelized by dividing the single Look-Up Table of LUT method for inverse halftoning into many smaller Look-up Tables (sLUTs). In the parallel algorithm up-to four pixels can be fetched from the halftone image concurrently and go to their separate smaller Look-Up Tables (sLUT) from where each template fetches its inverse halftone value independent to other pixels. …”
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A Parallel Neural Networks Algorithm for the Clique Partitioning Problem
Published 2002“…A parallel simulator, based on PVM, was implemented for the proposed algorithm on a Linux Cluster. …”
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Block constrained pressure residual preconditioning for two-phase flow in porous media by mixed hybrid finite elements
Published 2023“…Therefore, we designed a dedicated two-stage strategy, inspired by the CPR algorithm, where a block preconditioner is used for the pressure part with the aim at exploiting the inner $$2\times 2$$ 2 × 2 structure. …”
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On the Optimization of Band Gaps in Periodic Waveguides
Published 2025“…<h3 dir="ltr">Purpose</h3><p dir="ltr">This work applies a computational framework for vibration attenuation in periodic structures by combining the established wave and finite element (WFE) method with nature-inspired optimization algorithms. …”
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Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices
Published 2016Get full text
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Predicting Compression Modes and Split Decisions for HEVC Video Coding Using Machine Learning Techniques
Published 2017Get full text
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Real-Time Implementation of High Performance Control Scheme for Grid-Tied PV System for Power Quality Enhancement Based on MPPC-SVM Optimized by PSO Algorithm
Published 2018“…In addition, it can be implemented in a low-cost control platform due to its simplicity. …”
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Multi-Objective Optimisation of Injection Moulding Process for Dashboard Using Genetic Algorithm and Type-2 Fuzzy Neural Network
Published 2024“…It is worth noting that the injection moulding process does not incorporate a type-2 fuzzy neural network (T2FNN). However, in this particular investigation, T2FNN was employed to replicate the mechanical stress model associated with dashboard injection moulding. …”
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Design of adaptive arrays based on element position perturbations
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Large language models for code completion: A systematic literature review
Published 2024“…Different techniques can achieve code completion, and recent research has focused on Deep Learning methods, particularly Large Language Models (LLMs) utilizing Transformer algorithms. …”
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Implementation of trust region methods in optimization. (c1998)
Published 1998Get 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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Adaptive bias simulated evolution algorithm for placement
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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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