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Broadcast News in the Digital Age: A Guide to Storytelling, Producing and Performing Online and on TV

為了解決Emcee的問題，作者Sidlow, Faith,Stephens, Kim 這樣論述：

Faith Sidlow is an award-winning broadcast journalist with three decades of experience in television and radio news. She is an associate professor of broadcast journalism at California State University, Fresno, where she teaches broadcast and multimedia journalism. Faith worked as a reporter, anchor

and producer for the Fresno NBC affiliate for 28 years. Her early broadcast career included radio reporter and board operator at KPBS-FM; San Diego reporter for KNX News Radio, Los Angeles; and research intern for CBS News in London. Kim Stephens is an Edward R. Murrow and Emmy(R) award-winning jou

rnalist and college professor. She’s worked as a news anchor, producer, reporter, weather anchor, telethon host, and community event emcee at KERO, WBIR, HGTV, WVLT, KNTV, KMPH. Kim is also an adjunct professor teaching broadcast news writing, on-air performance and broadcast reporting and productio

n at California State University, Fresno.

Emcee進入發燒排行的影片

通過引力波數據分析來搜索緻密星

為了解決Emcee的問題，作者黃國彰 這樣論述：

The detection of the gravitational-wave is a novel way to explore the universe. Along with increasing sensitivity of the detectors, it is possible that LIGO/VIRGO/KAGRA will observe more compact stars in the future. The compact stars include black holes, neutron stars, exotic stars etc. More and mo

re gravitational-wave events can help people to figure out the properties of compact stars. In this thesis, we try to search the dark stars from the O1/O2 events, and performed the parameter estimation with tidal signature. When the properties of the one source is similar with the black hole, but it

has the tidal deformability and match the dark matter EoSs. We can suppose this source that could be a dark star. However, we compare the tidal/non-tidal Bayes factor for the gravitational-wave events, only GW170817 has the tidal deformability. In addition, we propose three scenarios of the compact

hybrid stars, and explore their M-R and M-Λ relations. We try to explain this GW190425 event through three scenarios of the hybrid stars. We find the free parameter region of the hybrid stars through the inference results of GW190425.

Broadcast News in the Digital Age: A Guide to Storytelling, Producing and Performing Online and on TV

為了解決Emcee的問題，作者Sidlow, Faith,Stephens, Kim 這樣論述：

Faith Sidlow is an award-winning broadcast journalist with three decades of experience in television and radio news. She is an associate professor of broadcast journalism at California State University, Fresno, where she teaches broadcast and multimedia journalism. Faith worked as a reporter, anchor

and producer for the Fresno NBC affiliate for 28 years. Her early broadcast career included radio reporter and board operator at KPBS-FM; San Diego reporter for KNX News Radio, Los Angeles; and research intern for CBS News in London. Kim Stephens is an Edward R. Murrow and Emmy(R) award-winning jou

rnalist and college professor. She’s worked as a news anchor, producer, reporter, weather anchor, telethon host, and community event emcee at KERO, WBIR, HGTV, WVLT, KNTV, KMPH. Kim is also an adjunct professor teaching broadcast news writing, on-air performance and broadcast reporting and productio

n at California State University, Fresno.

Universal Gravitational Wave Parameter Estimation by Deep Learning

為了解決Emcee的問題，作者郭瀚翔 這樣論述：

As the improvement of gravitational wave detectors, gravitationalwave events become more and more popular which opens a new win-dow of astronomy. In 2017, a binary neutron star event, GW170817,has been detected through the gravitational wave and also the electro-magnetic signal. After that, people

start to consider an efficient wayto detect the GW and extract its dynamics parameters. In this thesis,we construct a Bayesian inference based on deep learning machine,CVAE, for the parameter estimation of binary black hole coalescence.This machine can obtain the inference of 5-dimensional parameter

s ofthe GW event within one second, where the parameters are two com-ponent mass m1 , m2 , luminosity distance dL , and time and phase ofcoalescence (tc , φ0 ). Since the noise of real detectors varies from timeto time, in contract to previous CVAE envelopments, we train ourmachine not only by strai

n data but also the corresponding amplitudespectrum density, which is used to characterize the noise background.We find our machine can obtain the compatible result in comparisonto traditional PE algorithm even with the noise drift, which meansthe noise background varies event by event. Finally, we

apply ourmachine to the LIGO/Virgo third observing run (O3) events to testthe performance of our machine against real data.