Titlebook: Heidelberger Gelehrtenlexikon 1803–1932; Dagmar Drüll Book 2019Latest edition Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Na

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Alexandr A. Borovkovnity distribution of such knowledge. The results show that in this case, under very general conditions, the network of associative knowledge is characterized by inverse power laws of degree, eigenvector, and betweenness centralities. These results agree with the empirically found properties of stude

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Getting Value from Predictive Maintenance,entation of predictive maintenance. Certain elements like machine data collection and analytics, work process and standards, and criticality analysis need to be evaluated, and in many cases even optimized, to drive predictive maintenance. Only by considering those requirements predictive maintenance can show the full potential.

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