Titlebook: Leselust in Risikogruppen; Gruppenspezifische W Ursula Maria Stalder Book 2013 Springer Fachmedien Wiesbaden 2013 Heterogenit?t.Kausale Wir

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書目名稱Leselust in Risikogruppen影響因子(影響力)




書目名稱Leselust in Risikogruppen影響因子(影響力)學(xué)科排名




書目名稱Leselust in Risikogruppen網(wǎng)絡(luò)公開度




書目名稱Leselust in Risikogruppen網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Leselust in Risikogruppen被引頻次




書目名稱Leselust in Risikogruppen被引頻次學(xué)科排名




書目名稱Leselust in Risikogruppen年度引用




書目名稱Leselust in Risikogruppen年度引用學(xué)科排名




書目名稱Leselust in Risikogruppen讀者反饋




書目名稱Leselust in Risikogruppen讀者反饋學(xué)科排名

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Mercurial

Ursula Maria Stalderhe model predicts well the state of the object, including faulty ones. If the value of this metric is close to 0.5, then the model is not able to predict the class of faulty states and to identify critical situations in the operation of the object. To assess the technical condition of the object, a

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Ursula Maria Stalderhe model predicts well the state of the object, including faulty ones. If the value of this metric is close to 0.5, then the model is not able to predict the class of faulty states and to identify critical situations in the operation of the object. To assess the technical condition of the object, a

LAPSE

sinoatrial-node

Ursula Maria Stalder to specific topics, such as.Advances in intelligent data processing and its applications.Multi-criteria decision analysis methods.Knowledge engineering in large-scale systems.High-dimensional data analysis.Spatial data analysis and sparse estimation.Innovative technologies and applications in compu

FLIC

稱贊

Ursula Maria Staldern, however, situations that lead to uncertainty percentages may occur. It can be concluded that a lot of information has ambiguous and incomplete tendencies. However, this information, instead of being wholly discarded because it is considered totally inconclusive, can be analyzed and optimized deci

ACTIN

Ursula Maria Stalderculation without subjecting a plant to an invasive procedure. This enabled a deployment and implementation of noninvasive plant disease detection prior to visual symptoms that can be applied on other plants. With analyzed data, the IoT technology in this experiment has enabled the detection of NLB d