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Fall 2012
Time perspective (TP) represents a person's tendency to focus more on the past, present or future and has been shown to predict measures of individual well-being (Boniwell, et al., 2010). This study examined the relationship between one’s time perspective and measures of hedonic and eudaimonic...
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Fall 2017
This thesis will discuss the charge dynamics of dangling bonds (DBs) on the hydrogen terminated Si(100) surface under the effects of temperature and perturbations from local electric fields. The experimental methods are then extended towards DB chains. Electronic time resolved imaging techniques...
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Spring 2021
Relativistic jets are an ubiquitous element of systems with accreting black holes. These jets carry away a large fraction of the accreted energy which later energizes their surrounding media. On the largest scales, the jets from supermassive black holes found in the center of galaxies provide a...
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Time Series and Machine Learning Approach for Forecasting the Demand for Small Equipment, Tools, and Consumables for Industrial Construction Projects
DownloadSpring 2024
The high consumption and utilization of demand for small equipment, tools, and consumables in construction projects underscores the necessity for effective procurement strategies. Accurate estimation of these consumables is crucial for moving toward project completion in a timely manner. With...
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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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