Parallel group的問題，透過圖書和論文來找解法和答案更準確安心。 我們找到下列懶人包和總整理

Hither & Nigh

為了解決Parallel group的問題，作者 這樣論述：

Magic and mystery abound when a young girl discovers a secret, parallel New York City that may help her find her missing brother in this dazzling middle grade fantasy adventure for fans of Thirteen Witches and James Riley.Could lessons in magic make everything right again? Nell Batista has been i

n trouble one too many times. Now she’s down to her last chance--literally. Join the Last Chance Club or be expelled from school. The kids in the club are an odd group, but when their teacher starts giving lessons in magic, things quickly go completely off the weird scale. Nell doesn’t believe in it

at first; after all, she’s a smart city kid, and there has been nothing magical in her life since her brother, River, disappeared three years ago. But this magic is real--and powerful. As their skills grow, Nell and her new friends discover a parallel New York City called the Nigh. It’s a place as

delightful as it is scary, sizzling with magical energy, where statues can talk, magicians ride on giant dogs, and monsters roam Central Park. And it is all controlled by the terrifying Minister, who might hold the key to finding Nell’s missing brother. Just how far will Nell go to find him, and who

can she trust in a world topsy turvy with enchantment?

Parallel group進入發燒排行的影片

採用CUDA圖型處理器平行化改良5G軟體基地台之隨機存取通道流程

為了解決Parallel group的問題，作者王靖 這樣論述：

隨著5G逐漸於全球開始商轉，越來越多企業發現其中商機並相繼開發相關應用與服務，例如：無人機、物聯網、邊緣運算等，然而這些應用都需要基地台為其傳遞訊號才能正確運作，因此基地台本身的穩定與效能將是這一切的基礎。本論文即提出一改善方法以提升原基地台本身之運算效率使其能夠更穩定的提供服務。無線行動網路近年快速發展，於是有軟體化基地台（Software-defined Radio, SDR）的概念被提出並運行提供服務，此概念即透過編寫軟體程式提供傳統基地台之服務，以應付行動網路技術規格之快速發展與變遷。本論文在此基礎之上針對基地台中提供使用者註冊接入網路與使用者裝置同步服務的隨機存取通道（Random

Access Channel, RACH）流程，討論其傳統實作方法並提出一改善效率之方法與流程架構。本論文將研究使用圖型處理器（Graphics Processing Unit, GPU）加速平行RACH 流程上的運算，並修改運算流程與方法使之更適合運行於GPU。透過本論文提出的架構設計，基地台的模擬測試運算執行時間可調降至大約原本的10%～50%。本論文的架構亦提供彈性化設計，因此可一次處理多基地台接收之訊號，且由於本研究將所有運算拆開至不同運算單元上平行運算，所以即使需要處理的訊號增加，總處理時間也不會有太大的差異。藉此研究，軟體基地台運行時將能有更多閒餘的效能維持整體性之效能與穩定或是

提供更多服務應用。

Handbook of Nondestructive Evaluation 4.0

為了解決Parallel group的問題，作者 這樣論述：

Dr. Norbert Meyendorf retired in Fall 2018 as Deputy Director of the Center for Nondestructive Evaluation and Professor in the Aerospace Engineering Department at Iowa State University in Ames, Iowa. Before joining ISU in 2016 he was Branch Director at the Fraunhofer Institute for Nondestructive Tes

ting IZFP and later IKTS. Additionally, he was Director of the International University of Dayton / Fraunhofer Research Center at the School of Engineering at the University of Dayton, and Program Director of the Master Program ＂Nondestructive Testing, M. Sc. (NDT)＂ at the Dresden International Univ

ersity (DIU) between 2011 and 2015.Norbert Meyendorf continues to be active as Adjunct Professor for Micro- and Nano-NDE at the University of Dresden and the Department for Chemical, Materials and Bioengineering, University of Dayton. He is the author or co-author of more than 300 peer-reviewed jour

nal articles, contributions to edited proceedings, technical reports, and numerous oral presentations at international venues. He is Editor-in-Chief of the Journal of Nondestructive Evaluation and has edited several books and conference proceedings. Additionally, Meyendorf is the founder and chair o

f two expert committees of the German Society for Non-Destructive Testing (DGZfP); namely, ＂Structural Health Monitoring＂ and ＂Materials Diagnostics＂. Between 2016 and 2018 he reorganized and directed the American Society for Nondestructive Testing, Iowa SectionöDr. Nathan Ida is Distinguished Profe

ssor of Electrical and Computer Engineering at The University of Akron in Akron, Ohio where he has been since 1985. His current research interests are in the areas of electromagnetic nondestructive testing and evaluation of materials at low and microwave frequencies with particular emphasis on theor

etical issues, on all aspects of modeling and simulation and on related issues stemming from research in NDE. He received his B.Sc. in 1977 and M.S.E.E. in 1979 from the Ben-Gurion University in Israel, and his Ph.D. from Colorado State University in 1983. He has held visiting and/or adjunct positio

ns at various institutions including Nasa Glen Research Center, The Federal University of Santa Catarina, in Florianopolis, Brazil, McGill University in Montreal, Canada, Electricite De France, Paris, France, The University of Lille, Lille, France and Université Pierre et Marie Curie, Paris, France.

Dr. Ida has published extensively, in over 400 publications, on electromagnetic field computation, parallel and vector algorithms and computation, nondestructive testing of materials, surface impedance boundary conditions, and sensing. He has written 9 books, amongt them a textbook on engineering e

lectromagnetics, now in its fourth edition, and a textbook on sensing and actuation, now in its second edition. He is a Life Fellow of the Institute of Electric and Electronics Engineers (IEEE), a Fellow of the American Society of Nondestructive Testing (ASNT), a Fellow of the Applied Computational

Electromagnetics Society (ACES) and a Fellow of the Institute of Electronics and Technology (IET). Dr. Ida teaches Electromagnetics, Antenna Theory, Electromagnetic Compatibility, Sensing and Actuation as well as Computational Methods and Algorithms.Dr. Ripi Singh is a freelance innovation and strat

egy coach, specializing in preparing his clients for the upcoming Fourth Industrial Revolution. He boasts decades of experience in creating new technologies and products, and fostering a culture of innovation through academia, small business, and Fortune 500 companies in India, Germany, and the USA.

He holds a Masters Degree in Strategic Thinking from the Rensselaer Polytechnic Institute and has been recognized with the President of India Cash Prize for Research, the National Technical Education award, as well as with uninterrupted scholarships for 15 years from throughout high school in India

to his post-doctoral studies at Georgia Tech. Dr. Singh serves on the Council of the Connecticut Academy of Science and Engineering, the most prestigious body serving the needs of the state, as well as on the Advisory Boards of the Universities of Hartford and New Haven. He is also an instructor at

the Caltech Center for Technology and Management Education. His most notable roles as of late include serving on the US delegation on ISO 56000 for Innovation Management, and as Chair of the NDE 4.0 committee for the ASNT.Dr. Johannes Vrana, born in 1978, studied physics at the Technical University

of Munich, Germany and completed his PhD in 2008 at the Saarland University on the subject of thermographic testing. He then worked for Siemens Power and Gas in Orlando, USA as well as in Berlin and Munich, Germany, and was Chairman of the Siemens NDE Council. In addition to worldwide harmonization

of NDE specifications and the introduction of statistical tools, he was responsible for the development of automated NDE and the synthetic aperture focusing technique (SAFT). In 2015 he received an Honorable Mention for Ingenuity at the U.S. Excellence Awards and, in 2016, he received 4th prize for

Ingenuity at the Werner von Siemens Awards.In 2015 Dr. Vrana founded his own company. Vrana GmbH, based in Rimsting, Germany and specializing in NDE consulting and solutions, R&D, and software development. Moreover, he is chairman of the ICNDT (International Committee for NDT) Specialist Internatio

nal Group ＂NDE 4.0＂, of the ASNT (American Society for NDT) German Section, and of the DGZfP (German Society for NDT) subcommittees ＂Interfaces and Documentation for NDE 4.0＂ and ＂Automated Ultrasonic Testing＂. In 2019 he was awarded with the DGZfP application award for the implementation of SAFT in

to serial production of large rotor forgings.

以監督式機器學習探討電子病歷中非結構化資料對早期預測中風後功能復原後果之價值

為了解決Parallel group的問題，作者宋昇峯 這樣論述：

中風是導致成人殘障的重要原因，中風功能復原後果的精準預測，能協助病人及家屬及早準備後續照顧事宜，衛生政策制定者也能依此預測結果適切規劃人力與資源，以投入中風病人的急性後期與中長期照護。目前的中風功能復原後果預測模型皆是以結構化資料建立，甚至最新使用數據驅動方式發展的機器學習預測模型依然是以結構化資料為主。相對的，照顧病人所製作的大量敘述式病歷文字紀錄，即非結構化資料，反而甚少被使用。因此，本研究的目的，即是使用監督式機器學習來探討非結構化臨床文字紀錄於急性缺血性中風後之初期預測功能復原後果之應用價值。在6176位2007年10月至2019年12月間因急性缺血性中風住院之病人中，共3847位病

人符合本研究之收案/排除條件。我們使用自然語言處理，萃取出住院初期之醫師紀錄及放射報告中之臨床文字紀錄，並且實驗了不同文字模型與機器學習演算法之組合，來建構中風功能復原後果的預測模型。實驗發現使用醫師紀錄時，操作特徵曲線下面積為0.782至0.805，而使用放射報告時，曲線下面積為0.718至0.730。使用醫師紀錄時，最好的組合為詞頻-倒文件頻加上羅吉斯迴歸，而使用放射報告時，最好之組合為基于轉換器的雙向編碼器表示技術加上支持向量機。這些基於純文字的機器學習預測模型並無法勝過傳統的風險模型，這些傳統模型的曲線下面積為0.811至0.841。然而，不管是以曲線下面積、重分類淨改善指標、或整合式

區辨改善指標來評估，臨床文字紀錄中的資訊的確可以增強傳統風險模型的預測效能。本研究之結論為，電子病歷中的非結構化文字經過自然語言處理後，不僅可以成為另類預測中風功能復原後果的工具，更可以增強傳統風險模型的預測效能。透過演算法來自動擷取並整合分析結構化與非結構化資料，將能提供醫師更好的決策支援。