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  • Description:Computationally Efficient Algorithm to Identify Matched ...Additionally, the algorithm is computationally efficient enough to be applied on large data sets. As an example the algorithm was used to identify the MMPs in the ∼300k NIH MLSMR set. The algorithm identified ∼5.3 million matched molecular pairs in the set. These pairs cover ∼ ...
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computationally efficient algorithm to identify matched Description

A COMPUTATIONALLY EFFICIENT AMBIGUITY

A COMPUTATIONALLY EFFICIENT AMBIGUITY RESOLUTION TECHNIQUE Ron Hatch, Tenny Sharpe, NavCom Technology, Inc. computationally efficient algorithm to identify matched It uses a very efficient algorithm to compute the residuals associated with each potential combination of computationally efficient algorithm to identify matched required to correctly identify the integer ambiguity values. The capability of the technique to rapidly identify theA Computationally Efficient Ground-Motion Selection computationally efficient algorithm to identify matchedA Computationally Efficient Ground-Motion Selection Algorithm for Matching a Target Response Spectrum Mean and Variance Nirmal Jayaram,a) Ting Lin,a) M.EERI, and Jack W. Baker,a) M.EERI Dynamic structural analysis often requires the selection of input groundA Computationally Efficient Ground-Motion Selection computationally efficient algorithm to identify matchedThe variance of the target response spectrum is usually ignored or accounted for in an ad hoc manner, which can bias the structural response estimates. This manuscript proposes a computationally efficient and theoretically consistent algorithm to select ground motions that match the target response spectrum mean and variance.

A Computationally Efficient Method for Probabilistic computationally efficient algorithm to identify matched

A Computationally Efficient Method for Probabilistic Parameter Threshold Analysis for Health Economic Evaluations computationally efficient algorithm to identify matched We propose algorithm 2 to obtain the parameter threshold value, computationally efficient algorithm to identify matched threshold analysis can help to identify the maximum price that a government might be willing to pay for a drug.A Computationally Efficient Method for Probabilistic computationally efficient algorithm to identify matchedA Computationally Efficient Method for Probabilistic Parameter Threshold Analysis for Health Economic Evaluations computationally efficient algorithm to identify matched We propose algorithm 2 to obtain the parameter threshold value, computationally efficient algorithm to identify matched threshold analysis can help to identify the maximum price that a government might be willing to pay for a drug.A computationally efficient method for automatic computationally efficient algorithm to identify matchedJan 23, 2008Not only is the algorithm shown to be computationally more efficient with registration time being reduced by a factor of 8, but also the algorithm is shown to offer 50% higher capture range allowing the initial patient displacement up to 15 mm (measured by mean target registration error).

A computationally efficient method for automatic computationally efficient algorithm to identify matched

Jan 23, 2008Not only is the algorithm shown to be computationally more efficient with registration time being reduced by a factor of 8, but also the algorithm is shown to offer 50% higher capture range allowing the initial patient displacement up to 15 mm (measured by mean target registration error).A computationally efficient nonparametric approach for computationally efficient algorithm to identify matchedJul 28, 2016In this paper we build on an approach proposed by Zou et al. (2014) for nonparametric changepoint detection. This approach defines the best segmentation for a data set as the one which minimises a penalised cost function, with the cost function defined in term of minus a non-parametric log-likelihood for data within each segment. Minimising this cost function is possible using dynamic computationally efficient algorithm to identify matchedAccelerated Simulation of Large Reaction Systems Using a computationally efficient algorithm to identify matchedOct 31, 2020Simulation of reaction systems has been employed along decades for a better understanding of such systems. However, the ever-growing gathering of biological data implied in larger and more complex models that are computationally challenging for current discrete-stochastic simulation methods. In this work, we propose a constraint-based algorithm to simulate such reaction

An Industrial-Strength Audio Search Algorithm

Feb 07, 2002Amena using Philips robust hashing algorithm [2-4]. Using the algorithm from Relatable, Neuros has included a sampling feature on their MP3 player which allows a user to collect a 30-second sample from the built-in radio, then later plug into an online server to identify the music [5,6]. Audible Magic uses the Muscle Fish algorithm to offer theAn algorithm for progressive multiple alignment of computationally efficient algorithm to identify matchedJul 26, 2005Dynamic programming algorithms guarantee to find the optimal alignment between two sequences. For more than a few sequences, exact algorithms become computationally impractical, and progressive algorithms iterating pairwise alignments are widely used. These heuristic methods have a serious drawback because pairwise algorithms do not differentiate insertions from deletions and Author Anthony J. De Groot, David B. HarrisPublish Year 1998Computationally efficient, robust algorithm for matched computationally efficient algorithm to identify matchedFeb 05, 2005Computationally efficient, robust algorithm for matched field processing Computationally efficient, robust algorithm for matched field processing Groot, Anthony; Harris, David 2005-02-05 00:00:00 CIRCUITS SYSTEMS SIGNAL PROCESSING VOL. 17, NO, 2, 1998, Pi'. 165-193 COMPUTATIONALLY EFFICIENT, ROBUST ALGORITHM FOR MATCHED FIELD PROCESSING*

COMPUTATIONALLY EFFICIENT MONTE CARLO

Journal of Computational Acoustics Vol. 02, No. 03, pp. 285-314 (1994) SPECIAL ISSUE BENCHMARKING MATCHED FIELD PROCESSING METHODS No Access COMPUTATIONALLY EFFICIENT MONTE CARLO ESTIMATION ALGORITHMS FOR MATCHED FIELD PROCESSING IN UNCERTAIN OCEAN ENVIRONMENTSCOMPUTATIONALLY EFFICIENT MONTE CARLO ESTIMATION computationally efficient algorithm to identify matchedJournal of Computational Acoustics Vol. 02, No. 03, pp. 285-314 (1994) SPECIAL ISSUE BENCHMARKING MATCHED FIELD PROCESSING METHODS No Access COMPUTATIONALLY EFFICIENT MONTE CARLO ESTIMATION ALGORITHMS FOR MATCHED FIELD PROCESSING IN UNCERTAIN OCEAN ENVIRONMENTSCited by 319Publish Year 2010Author Jameed Hussain, Ceara ReaComputationally Efficient Algorithm to Identify Matched computationally efficient algorithm to identify matchedComputationally Efficient Algorithm to Identify Matched Molecular Pairs (MMPs) in Large Data Sets March 2010 Journal of Chemical Information and Modeling 50(3):339-48

Cited by 90Publish Year 1994Author J. A. Shorey, L. W. Nolte, J. L. KrolikMatched Molecular Pair Analysis in Short Algorithms computationally efficient algorithm to identify matched

Jan 01, 2017The term Molecular Matched Pair (MMP) was coined in 2004 by Kenny and Sadowski , for a special case of QSAR; now a widely used concept throughout drug design processes.In the most common situation, MMP describes a pair of compounds that differ structurally at a single site through a well-defined transformation (see Fig. 1) that is associated with a relative change in a property value.Comprehensive assessment of computational algorithms in computationally efficient algorithm to identify matchedFeb 20, 2020The initiation and subsequent evolution of cancer are largely driven by a relatively small number of somatic mutations with critical functional impacts, so-called driver mutations. Identifying driver mutations in a patients tumor cells is a central task in the era of precision cancer medicine. Over the decade, many computational algorithms have been developed to predict the effects of computationally efficient algorithm to identify matchedComputationally Efficient Algorithm to Identify Matched computationally efficient algorithm to identify matchedAdditionally, the algorithm is computationally efficient enough to be applied on large data sets. As an example the algorithm was used to identify the MMPs in the 300k NIH MLSMR set. The algorithm identified 5.3 million matched molecular pairs in the set. These pairs cover 2.6 million unique molecular transformations.

Computationally Efficient Spatial Forecast Verification computationally efficient algorithm to identify matched

May 01, 2008Nevertheless, the procedure proposed here allows for a computationally efficient automated method for distinguishing between objects that are close or far apart from one field to another. As a result, the procedure may contribute to other approaches where an algorithm is needed to merge and match binary image objects.Computationally Efficient Spatial Forecast Verification computationally efficient algorithm to identify matchedMay 01, 2008Nevertheless, the procedure proposed here allows for a computationally efficient automated method for distinguishing between objects that are close or far apart from one field to another. As a result, the procedure may contribute to other approaches where an algorithm is needed to merge and match binary image objects.Computationally efficient, robust algorithm for matched computationally efficient algorithm to identify matchedFeb 05, 2005Computationally efficient, robust algorithm for matched field processing Computationally efficient, robust algorithm for matched field processing Groot, Anthony; Harris, David 2005-02-05 00:00:00 CIRCUITS SYSTEMS SIGNAL PROCESSING VOL. 17, NO, 2, 1998, Pi'. 165-193 COMPUTATIONALLY EFFICIENT, ROBUST ALGORITHM FOR MATCHED FIELD PROCESSING*

Computationally efficient, robust algorithm for matched computationally efficient algorithm to identify matched

Mar 01, 1998When either the search volume is large of the acoustic array is large, computational efficiency is an issue. We present an efficient MFP implementation for the conventional MFP algorithm and our robust algorithm. We show that parallel implementation of these algorithms Dynamically dimensioned search algorithm for computationally efficient algorithm to identify matched[1] A new global optimization algorithm, dynamically dimensioned search (DDS), is introduced for automatic calibration of watershed simulation models. DDS is designed for calibration problems with many parameters, requires no algorithm parameter tuning, and automatically scales the search to find good solutions within the maximum number of userspecified function (or model) evaluations.Efficient haplotype matching and storage using the computationally efficient algorithm to identify matchedTo identify where maximal matches start, we need to keep track of the start position of matches between neighboring prefixes. Formally, for define to be the smallest value j such that matches (note that I have dropped the k suffix of the ys here and in the following for ease of notation, since its value is implicitly k for the time being). If then set It can then be shown that the start of computationally efficient algorithm to identify matched

Efficient haplotype matching and storage using the computationally efficient algorithm to identify matched

To identify where maximal matches start, we need to keep track of the start position of matches between neighboring prefixes. Formally, for define to be the smallest value j such that matches (note that I have dropped the k suffix of the ys here and in the following for ease of notation, since its value is implicitly k for the time being). If then set It can then be shown that the start of computationally efficient algorithm to identify matchedGitHub - XiaofangJ/PhaseFinder A pipeline to computationally efficient algorithm to identify matched2. Mimic inversion in silico to create a database of inverted sequences usage PhaseFinder.py create [-h] -f -t -s -i optional arguments -h, --help show this help message and exit -f , --fasta input genome sequence file in fasta format -t , --tab table with inverted repeat coordinates -s , --flanksize base pairs of flanking DNA on both sides of the identified inverted repeats -i , --inv computationally efficient algorithm to identify matchedImage Matching with OpenCVs Template Matching by Comparison Matrix. During my research, I mostly encountered solutions that are based on features extracted from images to match between images, but thats computationally expensive for our case, as were interested in doing this for every pair of images. Therefore we are in need of a different approach. As described, the images that actually match, are close to being identical.

Matching Pursuit Algorithms - MATLAB & Simulink

Matching pursuit is a greedy algorithm that computes the best nonlinear approximation to a signal in a complete, redundant dictionary. Matching pursuit builds a Matching Pursuit Algorithms - MATLAB & SimulinkMatching pursuit is a greedy algorithm that computes the best nonlinear approximation to a signal in a complete, redundant dictionary. Matching pursuit builds a Matching Pursuit Algorithms - MATLAB & SimulinkMatching pursuit is a greedy algorithm that computes the best nonlinear approximation to a signal in a complete, redundant dictionary. Matching pursuit builds a

Search Algorithms for Block-Matching in Motion Estimation

With the realization that motion compensation is the most computationally intensive operation in the coding and transmitting of video streams, people started looking for more efficient algorithms. However, there is a trade-off between the efficiency of the algorithm and the quality of the prediction image.Search Algorithms for Block-Matching in Motion EstimationWith the realization that motion compensation is the most computationally intensive operation in the coding and transmitting of video streams, people started looking for more efficient algorithms. However, there is a trade-off between the efficiency of the algorithm and the quality of the prediction image.Some results are removed in response to a notice of local law requirement. For more information, please see here.

Some results are removed in response to a notice of local law requirement. For more information, please see here.Computationally efficient, robust algorithm for matched computationally efficient algorithm to identify matched

Feb 05, 2005Computationally efficient, robust algorithm for matched field processing Computationally efficient, robust algorithm for matched field processing Groot, Anthony; Harris, David 2005-02-05 00:00:00 CIRCUITS SYSTEMS SIGNAL PROCESSING VOL. 17, NO, 2, 1998, Pi'. 165-193 COMPUTATIONALLY EFFICIENT, ROBUST ALGORITHM FOR MATCHED FIELD PROCESSING* Some results are removed in response to a notice of local law requirement. For more information, please see here.Computationally efficient, robust algorithm for matched computationally efficient algorithm to identify matchedWhen either the search volume is large of the acoustic array is large, computational efficiency is an issue. We present an efficient MFP implementation for the conventional MFP algorithm and our robust algorithm. We show that parallel implementation of these algorithms may allow real-time performance.Topological surrogates for computationally efficient computationally efficient algorithm to identify matchedMay 30, 2020To address this need, this research was conducted to identify, for the first time, computationally efficient topological surrogates for hydraulic simulationbased optimization. The computational efficiency of surrogate optimization was measured in terms of solution quality (i.e., postearthquake serviceability) and computational runtime.

Topological surrogates for computationally efficient computationally efficient algorithm to identify matched

May 30, 2020To address this need, this research was conducted to identify, for the first time, computationally efficient topological surrogates for hydraulic simulationbased optimization. The computational efficiency of surrogate optimization was measured in terms of solution quality (i.e., postearthquake serviceability) and computational runtime.

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