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testing algorithm » cosine algorithm (Expand Search)
code algorithm » cosine algorithm (Expand Search), rd algorithm (Expand Search), colony algorithm (Expand Search)
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A Quasi-Oppositional Method for Output Tracking Control by Swarm-Based MPID Controller on AC/HVDC Interconnected Systems With Virtual Inertia Emulation
Published 2021“…The proposed analysis is established considering the most highly cited, well-known tested and newly expanded swarm-based optimization algorithms (SBOAs), such as Grasshopper Optimization Algorithm (GOA), Grey Wolf Optimization (GWO), Artificial Fish Swarm Algorithm (AFSA), Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO). …”
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84
Metallic coating thickness assessment over nonmagnetic metals using eddy current technology
Published 2019Get full text
doctoralThesis -
85
A comparative study of regression testing methods. (c1996)
Published 1996Get full text
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masterThesis -
86
Oversampling techniques for imbalanced data in regression
Published 2024“…For such high-dimension data our approach outperforms the Synthetic Minority Oversampling Technique for Regression (SMOTER) algorithm for the IMDB-WIKI and AgeDB image datasets. …”
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87
Dynamic adaptation for video streaming over mobile devices. (c2013)
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masterThesis -
88
A Modified PWM Strategy With an Improved ANN Based MPPT Algorithm for Solar PV Fed NPC Inverter Driven Induction Motor Drives
Published 2023“…Apart from that, a robust artificial neutral network (ANN) based incremental conductance maximum power point tracking (MPPT) algorithm is also introduced to control the dc-link voltage of the PV fed NPC inverter driven IMD system. …”
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89
Multi-Robot Map Exploration Based on Multiple Rapidly-Exploring Randomized Trees
Published 2017Get full text
doctoralThesis -
90
Impact Of Multidisciplinary Maternal Resuscitation Training Program on Improving the Front-Line Care Provider’s Readiness to Manage Maternal Cardiac Arrest: A Pre-test/Post-test St...
Published 2024“…The sample size consisted of three groups of front-line multidisciplinary obstetric maternal resuscitation teams (physicians, midwives, and nurses) divided into a pre-test group (N=30) and post-test group (N=30). The multidisciplinary resuscitation teams were observed during the cardiac arrest mock drills both before and after conducting the multidisciplinary resuscitation simulation-based training program and the introduction of the maternal resuscitation algorithm pathway against seven KPIs. …”
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Methods for system-on-chip test design, scheduling and optimization. (c2006)
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masterThesis -
93
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94
Parallel Algorithm for Hardware Implementation of Inverse Halftoning
Published 2005“…The algorithm is based on Lookup Tables from which the inverse halftone value of a pixel is directly determined using a pattern of pixels. …”
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Parallel algorithm for hardware implementation of inverse halftoning
Published 2005“…The algorithm is based on lookup tables from which the inverse halftone value of a pixel is directly determined using a pattern of pixels. …”
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Optimization of Commercially Off the Shelf (COTS) Electric Propulsion System for Low Speed Fuel Cell UAV
Published 2013Get full text
doctoralThesis -
97
An Evolutionary Meta-Heuristic for State Justification in Sequential Automatic Test Pattern Generation
Published 2001“…Sequential circuit test generation using deterministic, fault-oriented algorithms is highly complex and time consuming. …”
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98
An evolutionary meta-heuristic for state justification insequential automatic test pattern generation
Published 2001“…Sequential circuit test generation using deterministic, fault-oriented algorithms is highly complex and time consuming. …”
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99
A method for efficient NoC test scheduling using deterministic routing
Published 2017“…This paper presents a method for NoCs test scheduling using simulated annealing. The method uses a deterministic routing algorithm that minimizes test time while avoiding blocking. …”
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conferenceObject -
100
An Iterative Heuristic for State Justi�cation in Sequential Automatic Test Pattern Generation
Published 2001“…State justifcation is one of the most time-consuming tasks in sequential Automatic Test Pattern Generation (ATPG). For states that are difficult to justify, deterministic algorithms take significant CPU time without much success most of the time. …”
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