Search Results - parallel ((evaluation method) OR (extraction method)) algorithm*
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Parallel execution of diagonally implicit Runge-Kutta methods for solving IVPs.
Published 2009“…Diagonally Implicit Runge-Kutta (DIRK) methods are amongst the most useful and cost-effective methods for solving initial value problems but the dependency of the functions evaluations on the previous functions evaluations makes DIRK method not so favourable for parallel computers. …”
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Parallel Execution of Runge-Kutta Methods for Solving Ordinary Differential Equations
Published 2004“…The method used here is actually have been tailored made for the purpose of parallel machine where the subsequent functions evaluations do not depend on the previous function evaluations. …”
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Optimization of extractive Automatic Text Summarization using Decomposition-based Multi-objective Differential Evolution and parallelization
Published 2024“…Additionally, when the input size is tripled, the parallel multi-core MODE/D achieves a 7.9 speedup with 98.98% efficiency under static scheduling. …”
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Projecting named entity tags from a resource rich language to a resource poor language
Published 2012“…The method computes the string similarity between the English words and the list of available lexemes in a pre-built lexicon that approximates the best NE mapping.The algorithm has been effectively evaluated using our own terrorism tagged corpus; it achieved satisfactory results in terms of precision, recall, and F-measure.An evaluation of the selected open source NER tool for English is also presented.…”
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Projecting named entity tags from a resource rich language to a resource poor language
Published 2013“…Hence, these two corpora are treated as parallel corpora. The method computes the string similarity between the English words and the list of available lexemes in a pre-built lexicon that approximates the best NE mapping. …”
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Projecting named entity tags from a resource rich language to a resource poor language
Published 2013“…Hence, these two corpora are treated as parallel corpora. The method computes the string similarity between the English words and the list of available lexemes in a pre-built lexicon that approximates the best NE mapping. …”
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Projecting named entity tags from a resource rich language to a resource poor language
Published 2013“…Hence, these two corpora are treated as parallel corpora. The method computes the string similarity between the English words and the list of available lexemes in a pre-built lexicon that approximates the best NE mapping. …”
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Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems
Published 2014“…To implement the parallel algorithms a distributed parallel computing laboratory using easily available low cost computers is setup. …”
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Solving ordinary differential equations using block multistep method
Published 2011“…The parallelism across the system is considered for the implementation of the parallel block methods. …”
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Communication and computational cost on parallel algorithm of PDE elliptic type
Published 2009“…Due to this needs, this paper presents the parallel performance evaluations of algorithms that will be discussed in term of communication and computational cost.…”
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Book Section -
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Enhancing performance of XTS cryptography mode of operation using parallel design
Published 2009“…In addition, the parallel XTS mode was also simulated using Twofish and RC6 encryption algorithms. …”
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Online system identification development based on recursive weighted least square neural networks of nonlinear hammerstein and wiener models.
Published 2022“…Best Hammerstein parallel NN polynomial based model and series-parallel NN polynomial model are 88.75% and 93.9% respectively, for best Hammerstein parallel NN sigmoid based model and series-parallel NN sigmoid based model 78.26% and 95.95% respectively, and for best Hammerstein parallel NN hyperbolic tangent based model and series-parallel NN hyperbolic tangent based model 70.7% and 96.4% respectively. …”
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Parallel system for abnormal cell growth prediction based on fast numerical simulation
Published 2010“…The development of the prediction system is the combinations of the parallel algorithms, open source software on Linux environment and distributed multiprocessor system. …”
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Conference or Workshop Item -
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Image classification using two dimensional wavelet coefficients with parallel computing
Published 2020“…This research algorithm demonstrated a very promising result with Support Vector Machines, this algorithm produces a 90% of accuracies whereas the decision tree algorithm gets 100% accuracies. …”
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Final Year Project / Dissertation / Thesis -
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Simulating Electrohydrodynamic Ion-Drag Pumping on Distributed Parallel Computing Systems
Published 2017“…For that reason, a Data Parallel Algorithm for EHD model (DPA-EHD) is designed. …”
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Analysis of evolutionary computing performance via mapreduce parallel processing architecture / Ahmad Firdaus Ahmad Fadzil
Published 2014“…MR is an emerging parallel processing framework that hides the complex parallelization processes by employing the functional abstraction of "map and reduce" The Performance of the parallelized GA via MR and PSO via MR are evaluated using an analogous case study to find out the speedup and efficiency in order to measure the scalability of both proposed algorithms. …”
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A spark-based parallel fuzzy C median algorithm for web log big data
Published 2022“…Based on the Rand Index and SSE (sum of squared error), the parallel Fuzzy C median algorithm's performance is evaluated in the PySpark platform. …”
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Automated plant recognition system based on multi-objective parallel genetic algorithm and neural network
Published 2014“…To conclude, multi objective parallel genetic algorithm can automatically tune feed forward neural network to classify the dataset with a good classification rate.…”
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Improving parallel self-organizing map using heterogeneous uniform memory access / Muhammad Firdaus Mustapha
Published 2018“…Finally, this research designs and implements an enhanced parallel SOM architecture through combining two parallel methods which are network and data partitioning. …”
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