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Standization Trends in Local Regions Ningxia Hui Autonomous Region Utilizes Standardization to Promote Economic Development
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《China Standardization》 2008年第1期26-27,共2页
In China, 10 ethnic minorities with a combined population of over 20 million people are followers of Islam. In Ningxia Hui Autonomous Region, the population is nearly 6 million, a-mong which the Islamic population is ... In China, 10 ethnic minorities with a combined population of over 20 million people are followers of Islam. In Ningxia Hui Autonomous Region, the population is nearly 6 million, a-mong which the Islamic population is about 2 million. In China as a whole, more than 20 million people enjoy eating food prepared according to Islamic guidelines, known as hal'al food. 展开更多
关键词 than more Standization Trends in local Regions Ningxia Hui Autonomous Region Utilizes Standardization to Promote Economic Development over high
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Avoiding experimental bias by systematic antibody validation
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作者 Sara B.Jager Christian Bjerggaard Vaegter 《Neural Regeneration Research》 SCIE CAS CSCD 2016年第7期1079-1080,共2页
Antibodies are valued reagents in most modern laboratories and indispensable for many experiments.They can be utilized in a wide range of experimental setups designed to elucidate various scientific questions.In our l... Antibodies are valued reagents in most modern laboratories and indispensable for many experiments.They can be utilized in a wide range of experimental setups designed to elucidate various scientific questions.In our laboratory,antibodies are used to investigate protein localization,quantity and phosphorylation state, 展开更多
关键词 indispensable questions furthermore utilized elucidate localization validation laboratories necessity giving
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Bayesian localization in an uncertain ocean environment 被引量:8
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作者 LI Qianqian LI Zhenglin ZHANG Renhe 《Chinese Journal of Acoustics》 CSCD 2016年第1期71-83,共13页
In order to improve the ability to localize a source in an uncertain acoustic environment,a Bayesian approach,referred to here as Bayesian localization is used by including the environment in the parameter search spac... In order to improve the ability to localize a source in an uncertain acoustic environment,a Bayesian approach,referred to here as Bayesian localization is used by including the environment in the parameter search space.Genetic algorithms are used for the parameter optimization.This method integrates the a posterior probability density(PPD) over environmental parameters to obtain a sequence of marginal probability distributions over source range and depth,from which the most-probable source location and localization uncertainties can be extracted.Considering that the seabed density and attenuation are less sensitive to the objective function of matched field processing,we utilize the empirical relationship to invert those parameters indirectly.The broadband signals recorded by a vertical line array in a Yellow Sea experiment in 2000 are processed and analyzed.It was found that,the Bayesian localization method that incorporates the environmental variability into the processor,made it robust to the uncertainty in the ocean environment.In addition,using the empirical relationship could enhance the localization accuracy. 展开更多
关键词 Bayesian localization uncertain ocean processed processor utilize matched dimensionality posteriori
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Three-dimensional sound source localization using distributed microphone arrays 被引量:3
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作者 KE Wei ZHANG Ming ZHANG Tiecheng 《Chinese Journal of Acoustics》 CSCD 2017年第2期231-244,共14页
To improve the performance of sound source localization based on distributed microphone arrays in noisy and reverberant environments,a sound source localization method was proposed.This method exploited the inherent s... To improve the performance of sound source localization based on distributed microphone arrays in noisy and reverberant environments,a sound source localization method was proposed.This method exploited the inherent spatial sparsity to convert the localization problem into a sparse recovery problem based on the compressive sensing(CS) theory.In this method two-step discrete cosine transform(DCT)-based feature extraction was utilized to cover both short-time and long-time properties of the signal and reduce the dimensions of the sparse model.Moreover,an online dictionary learning(DL) method was used to dynamically adjust the dictionary for matching the changes of audio signals,and then the sparse solution could better represent location estimations.In addition,we proposed an improved approximate l_0norm minimization algorithm to enhance reconstruction performance for sparse signals in low signal-noise ratio(SNR).The effectiveness of the proposed scheme is demonstrated by simulation results where the locations of multiple sources can be obtained in the noisy and reverberant conditions. 展开更多
关键词 localization sparse dictionary minimization noisy dynamically matching approximate utilized audio
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