Recently, some distributed stream computing platforms, such as Storm and Spark streaming, have been developed for processing massive datastreams. However, these platforms lack support for higher-level declarative lan...
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ISBN:
(纸本)9781450332866
Recently, some distributed stream computing platforms, such as Storm and Spark streaming, have been developed for processing massive datastreams. However, these platforms lack support for higher-level declarative languages and provide only programming interfaces. Moreover, the users should be well versed of the syntax and programming constructs of each language in these platforms. In this paper, we are going to demonstrate our PipeFlow system. In the PipeFlow system, the user can write a stream-processing script (i.e., query) using a higher-level dataflow language. This script can be translated into different stream-processing programs that run in the corresponding engines. In this case, the user is only willing to know a single language, thus, he/she can write one stream-processing script and expects to execute this script on different engines.
Tactical decisions profoundly characterize team sports like soccer or basketball. Analyses of matches and training sessions (e.g., mileage or pass completion rate of a player) become more and more important for those ...
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ISBN:
(纸本)9781450332866
Tactical decisions profoundly characterize team sports like soccer or basketball. Analyses of matches and training sessions (e.g., mileage or pass completion rate of a player) become more and more important for those tactical decisions. Most of the analyses are video-based, resulting in high operating expenses. Additionally, a highly specialized system with a huge amount of system resources like processors and memory is needed. Typically, analysts present the results of the video data analysis in time-outs (e.g., in the half-time break of a soccer match). However, coaches often desire to view statistics in real-time during the *** this paper, we demonstrate Herakles, a system for live sport analysis using streaming sensor data and a Peer-to-Peer network of conventional and low-cost private machines. Since sensor data is typically of high volume and velocity, Herakles uses OdysseusP2P, a distributed datastream management system, for processing these streams in real-time. Since the results of the data stream processing are intended for coaches, the front-end of Herakles is an application for mobile devices like smartphones or tablets. With Herakles, a coach is able to view individual sport statistics during the game at the sideline to make immediate tactical decisions.
An architecture and learning methods for deep neural networks that increase a number of layers and adjust their synaptic weights in an online mode are proposed in the article. The system's architecture is based on...
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ISBN:
(纸本)9781509030071
An architecture and learning methods for deep neural networks that increase a number of layers and adjust their synaptic weights in an online mode are proposed in the article. The system's architecture is based on nodes of a special type (extended neo-fuzzy neurons) which possess enhanced approximating properties. A main feature of the proposed network is a learning process for each node that is performed sequentially in an online mode.
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