Search Results - (( data selection method algorithm ) OR ( parallel visualization based algorithm ))
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1
High performance visualization of human tumor growth software
Published 2008“…The implementation of parallel algorithm based on parallel computing system is used to visualize the growth of human tumour. …”
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The visualization of three dimensional brain tumors' growth on distributed parallel computer systems
Published 2009“…The main objective of this study is to visualize the brain tumors’ growth in three-dimensional and implement the algorithm on distributed parallel computer systems. …”
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Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
Published 2009“…The development of this architecture is based on several programming language as it involves algorithm implementation on C, parallelization using Parallel Virtual Machine (PVM) and Java for web services development. …”
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4
Grid portal technology for web based education of parallel computing courses, applications and researches
Published 2009“…These courses will actively engage the students in exploring the concepts of the development the parallel algorithm in visualizing the grand challenge applications of mathematical problems. …”
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Parallel computation of maass cusp forms using mathematica
Published 2013“…Our parallel programme comprises of two important parts namely the pullback algorithm and also the Maass cusp form algorithm. …”
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6
Tumor growth prediction using parallel computing: numerical solutions based on multi-dimensional partial differential equation (PDE)
Published 2010“…The parallel algorithm for the simulation of human tumor growth is a new invention at the present time. …”
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Parallel system for abnormal cell growth prediction based on fast numerical simulation
Published 2010“…The processing large sparse matrixes are based on multiprocessor computer systems for abnormal growth visualization. …”
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8
Image based autonomous indoor parallel parking assist on omni-directional vehicle (ODV)
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Undergraduates Project Papers -
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Implementation of Parallel K-Means Algorithm to Estimate Adhesion Failure in Warm Mix Asphalt
Published 2020“…Therefore, the execution time of the image processing algorithm is also an essential aspect of quality. This manuscript proposes a parallel k means for image processing (PKIP) algorithm using multiprocessing and distributed computing to assess the adhesion failure in WMA and HMA samples subjected to three different moisture sensitivity tests (dry, one, and three freeze-thaw cycles) and fractured by indirect tensile test. …”
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Parallel batch self-organizing map on graphics processing unit using CUDA
Published 2018“…The most computationally expensive parts of its training algorithm (such as steps to compute distance between each data vector and neuron, and determining the Best Matching Unit based on minimum distance) are identified and mapped on GPU to be processed in parallel. …”
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Parallel batch self-organizing map on graphics processing unit using CUDA
Published 2018“…The most computationally expensive parts of its training algorithm (such as steps to compute distance between each data vector and neuron, and determining the Best Matching Unit based on minimum distance) are identified and mapped on GPU to be processed in parallel. …”
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Conjunctions in biological neural architectures for visual pose estimation / Tom´As Maul
Published 2006“…A highly parallel approach based on simple inter-map conjunctions, or correspondence distributions, is chosen and tested on synthetic and real patterns. …”
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Drone Based Image Processing For Precision Agriculture
Published 2019“…At first, the parallel K-means clustering algorithm was applied on the acquired image to segregate various components acquired using UAV. …”
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14
Active contour model on digital mammograms using low-cost parallel computing systems
Published 2009“…Results obtained imply that the PCS is prospective for image visualization purposes.…”
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15
Partitioning techniques and their parallelization for stiff system of ordinary differential equations
Published 2007“…The graphs of its performance and execution time, visualize the advantages of parallelizing.…”
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16
Multiple equations model selection algorithm with iterative estimation method
Published 2016“…Meanwhile, real data analysis using water quality index displays excellent accomplishments when compared to other selection procedures.Consequently, iterative feasible generalized least squares method is regarded as a more suitable estimation method in this automated selection.It can also be seen that simultaneous selections outperform the individual selections.This strategy by executing simultaneous selection with iterative estimation method is therefore proven to outclass in this analysis.…”
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Application of the bees algorithm to the selection features for manufacturing data
Published 2007“…Some of the features may contain irrelevant information caused by data redundancy or by noise. A “wrapper” feature selection method using the Bees Algorithm and Multilayer Perception (MLP) networks is described in this paper. …”
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18
Case Slicing Technique for Feature Selection
Published 2004“…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
Published 2020“…Results of the reviewed techniques show that attribute selection methods capable to resolve the limitations in ID3 algorithm and increase the performance of the method. …”
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