0000000000710283

AUTHOR

Ning Xiang

showing 2 related works from this author

A Bayesian direction-of-arrival model for an undetermined number of sources using a two-microphone array.

2014

Sound source localization using a two-microphone array is an active area of research, with considerable potential for use with video conferencing, mobile devices, and robotics. Based on the observed time-differences of arrival between sound signals, a probability distribution of the location of the sources is considered to estimate the actual source positions. However, these algorithms assume a given number of sound sources. This paper describes an updated research account on the solution presented in Escolano et al. [J. Acoust. Am. Soc. 132(3), 1257-1260 (2012)], where nested sampling is used to explore a probability distribution of the source position using a Laplacian mixture model, whic…

Microphone arrayAcoustics and UltrasonicsComputer scienceAcousticsBayesian probabilityDirection of arrivalSampling (statistics)DOAAcoustic source localizationMicrophone arraySpeech processingMixture modelBayesianSound source localizationArts and Humanities (miscellaneous)TEORIA DE LA SEÑAL Y COMUNICACIONESProbability distributionAlgorithmNested sampling algorithmThe Journal of the Acoustical Society of America
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Comparison of machine learning and logistic regression as predictive models for adverse maternal and neonatal outcomes of preeclampsia: A retrospecti…

2022

IntroductionPreeclampsia, one of the leading causes of maternal and fetal morbidity and mortality, demands accurate predictive models for the lack of effective treatment. Predictive models based on machine learning algorithms demonstrate promising potential, while there is a controversial discussion about whether machine learning methods should be recommended preferably, compared to traditional statistical models.MethodsWe employed both logistic regression and six machine learning methods as binary predictive models for a dataset containing 733 women diagnosed with preeclampsia. Participants were grouped by four different pregnancy outcomes. After the imputation of missing values, statistic…

mallintaminenlogistic regressionretrospective studyäitiyshuoltoadverse outcomesraskauspredictive modelsneonatalraskausmyrkytysmaternalregressioanalyysimachine learningkoneoppiminenpre-eklampsiapre-eclampsia (PE)ennustettavuussairaudetCardiology and Cardiovascular MedicineFrontiers in Cardiovascular Medicine
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