International Business Machines Corporation

Xiaowan Lu

Xin Zheng

Xin Peng Liu

Zhen Zhang

Jing Zhao

Wen Sun

Guan Jun Liu

Ji Dong Li

Ting Xie

Hai He

A method, a system and a computer program product for hybrid computing system management are proposed. In the method, workload information associated with a set of application server instances running in a first computing system is obtained by a server controller in response to a scaling request for changing the number of instances in the set of application server instances from a request controller. The set of application server instances serves at least one application running in a second computing system. A scaling decision indicating whether to change the number of instances in the set of application server instances is determined by a predictor based on the workload information from the server controller. The second computing system is enabled by the request controller to handle requests associated with the at least one application for the set of application server instances based on the scaling decision.

Hybrid computing system management

Aspects of the invention include receiving performance data comprising video data and audio data associated with a performance by a performer, wherein the video data comprises audience video data for the performance, determining a performer skill score based on a feature vector generated by a performance skill machine learning model, the feature vector comprising a plurality of features extracted from the performance data, parsing the performance data into a plurality of performance segments, analyzing the performance data to determine a performer emotion of the performer for each performance segment, determining an audience emotion based on the audience video data for one or more audience members for each of the performance segments, comparing the audience emotion to the performer emotion for each performance segment to determine an emotion accuracy score, and determining a final score for the performance based on the performer skill score and the emotion accuracy score.

Intelligent performance rating

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Beijing, China

Xiaowan Lu