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Fall 2016
Anomaly detection in time series is one of the fundamental issues in data mining. It addresses various problems in different domains such as intrusion detection in computer networks, anomaly detection in healthcare sensory data, and fraud detection in securities. Though there has been extensive...
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Fall 2013
Time series discords, as introduced in by Keogh et al. [5] is described as the subsequence in the time series which is maximally different from the rest of the subsequences. Discovery of time series discords has been applied to several diverse domains including space shuttle telemetry, industry,...
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Fall 2021
Due to the growing penetration of renewable energy sources, accurate energy forecasts are required to support their effective integration. In this field, deep learning methods are currently demonstrating successful results, but there is still a room for improvement that may eventually lead to...
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Fall 2018
Time series has become prevalent in a broad range of real-world applications such as weather, health care, agricultural production, satellite image analysis, speech recognition, industrial process control, and others. This type of data comes as a collection of observations obtained...
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Spring 2012
Three sedimentary drilling cores from Lake Baikal were used to build a new composite magnetic susceptibility record for the Brunhes and upper Matuyama chrons. The developed age model, based on the constructing of the composite susceptibility signal and orbital tuning, shows a substantial...
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Time-Cost Trade-off (TCT) Analysis based Application Framework for Safety Centric Construction Acceleration Planning
DownloadFall 2021
The purpose of using a Time-Cost Trade-off (TCT) analysis is to account for foreseeable project safety concerns and hazards, speed up activity times, and reduce the overall duration of the project while keeping project cost within a certain budget limit. This type of acceleration planning is...
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1979
Abstract in English, French and German.