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Gearbox faults in wind turbines are one of the most important reasons for the failure of these machines which lead to the longest downtime and maintenance cost. While much attention has been given to detect faults in these mechanical devices, real-time fault diagnosis for streaming vibration data from turbine gearboxes still remains an outstanding problem. Moreover, monitoring gearboxes in a wind...
Big data analytics is the hottest new practice in Business Analytics today. However, recent industrial surveys find that big data analytics may fail to meet business expectations because of lack of business context and lack of expertise to connect the dots, inaccurate scope and batch-oriented Hadoop system. In this paper, we present IRIS - a goal-oriented big data analytics framework using Spark for...
Limited access to supervised information may forge scenarios in real-world data mining applications, where training and test data are interconnected by a covariate shift, i.e., having equal class conditional distribution with unequal covariate distribution. Traditional data mining techniques assume that both training and test data represent an identical distribution, therefore suffer in presence of...
In recent years, mass atrocities, terrorism, and political unrest have caused much human suffering. Thousands of innocent lives have been lost to these events. With the help of advanced technologies, we can now dream of a tool that uses machine learning and natural language processing (NLP) techniques to warn of such events. Detecting atrocities demands structured event data that contain metadata,...
Political event data have been widely used to study international politics. Previously, natural text processing and event generation required a lot of human efforts. Today we have high computing infrastructure with advance NLP metadata to leverage those tiresome efforts. TABARI -- an open source non distributed event-coding software -- was an early effort to generate events from a large corpus. It...
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