Titlebook: Nazi-Organized Recreation and Entertainment in the Third Reich; Julia Timpe Book 2017 The Editor(s) (if applicable) and The Author(s) 2017

離開浮于空中

書目名稱Nazi-Organized Recreation and Entertainment in the Third Reich影響因子(影響力)




書目名稱Nazi-Organized Recreation and Entertainment in the Third Reich影響因子(影響力)學(xué)科排名




書目名稱Nazi-Organized Recreation and Entertainment in the Third Reich網(wǎng)絡(luò)公開度




書目名稱Nazi-Organized Recreation and Entertainment in the Third Reich網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Nazi-Organized Recreation and Entertainment in the Third Reich被引頻次




書目名稱Nazi-Organized Recreation and Entertainment in the Third Reich被引頻次學(xué)科排名




書目名稱Nazi-Organized Recreation and Entertainment in the Third Reich年度引用




書目名稱Nazi-Organized Recreation and Entertainment in the Third Reich年度引用學(xué)科排名




書目名稱Nazi-Organized Recreation and Entertainment in the Third Reich讀者反饋




書目名稱Nazi-Organized Recreation and Entertainment in the Third Reich讀者反饋學(xué)科排名

雜色

Julia TimpePresents a comprehensive view of the activities of the Third Reich’s leisure organization.Argues that the Nazi regime’s ‘joy creation’ was more than instrumental manipulation.Makes an important contri

DOTE

PLUMP

Nazi-Organized Recreation and Entertainment in the Third Reich978-1-137-53193-3Series ISSN 2731-5711 Series E-ISSN 2731-572X

biosphere

規(guī)范要多

https://doi.org/10.1057/978-1-137-53193-3Nazism; Kraft durch Freude; Leisure; Second World War; Aryan

狗舍

sis application. This analysis application may become a performance bottleneck when monitoring several programs resulting in reduced monitoring quality or violated service level agreements of the monitored applications..We present an approach for elastic, distributed application-level monitoring for

Measured

Julia Timpe previously measured experiences by other consumers is beneficial. In this paper, we present the results of our evaluation of two machine learning approaches in combination with several learning strategies to predict the best service within this selection problem. The first approach focuses on the p

pulmonary-edema

Julia Timpe previously measured experiences by other consumers is beneficial. In this paper, we present the results of our evaluation of two machine learning approaches in combination with several learning strategies to predict the best service within this selection problem. The first approach focuses on the p

Arthropathy

Julia Timpe previously measured experiences by other consumers is beneficial. In this paper, we present the results of our evaluation of two machine learning approaches in combination with several learning strategies to predict the best service within this selection problem. The first approach focuses on the p