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<title>Interdisciplinary Engineering Dissertations</title>
<copyright>Copyright (c) 2013 Northeastern University All rights reserved.</copyright>
<link>http://iris.lib.neu.edu/interdisc_eng_diss</link>
<description>Recent documents in Interdisciplinary Engineering Dissertations</description>
<language>en-us</language>
<lastBuildDate>Sun, 27 Jan 2013 23:31:09 PST</lastBuildDate>
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<title>Understanding and improving novice drivers&apos; hazard perception skills</title>
<link>http://iris.lib.neu.edu/interdisc_eng_diss/3</link>
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<pubDate>Tue, 21 Aug 2012 06:41:52 PDT</pubDate>

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		<p>Road safety is always of great concern throughout the world. Many efforts have been made by research and laws to keep traffic accident rates low. A topic of interest for many years has been driving behaviors of novice drivers. The accident rate of novice drivers, especially newly licensed teens, is much higher when compared too more experienced drivers. An important reason may be that novice drivers are more likely to fail to identify hazardous situations. My research focuses on how to better prepare teen drivers for real-world driving by improving their hazard perception skills.</p> <p>Hazard perception skill may be a...
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	</description>



<author>Na Chen</author>


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<title>Characterization and analysis of sensor data using recurrence network analysis</title>
<link>http://iris.lib.neu.edu/interdisc_eng_diss/2</link>
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<pubDate>Mon, 20 Aug 2012 07:40:40 PDT</pubDate>

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		<p>For the past many decades, several concepts and measures for studying nonlinear sensor data have been proposed and investigated. There have been many attempts to understand behavior, reliability, and performance of sensor data. This dissertation presents novel methodologies for analyzing, classifying, and recognizing patterns of nonlinear sensor data based on recurrence network analysis.</p> <p>First, a comprehensive overview of recurrence theory and their quantification possibilities is presented. New measures of recurrence networks are defined by using the complex network properties. These measures are intended to recognize and classify patterns of sensor data using the feature extraction method. In this dissertation, we...
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<author>Sivarit Sultornsanee</author>


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<title>Nanoelectromechanical switching with single walled nanotubes</title>
<link>http://iris.lib.neu.edu/interdisc_eng_diss/1</link>
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<pubDate>Mon, 31 Oct 2011 10:45:57 PDT</pubDate>

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		<p>With the end of Moore's Law quickly approaching, there is a drive to find alternative technologies to traditional solid state devices. Static and dynamic power dissipation continues to increase in current CMOS architectures. The electromechanical switch has nearly zero off-state leakage current. Single walled nanotubes have demonstrated exceptional electrical and mechanical properties and are ideal candidates for the actuator in such switches. Presented here for the first time are vertically actuating switches that demonstrate an interesting phenomenon during the initial switching cycles. It was found that a finite length of the nanotube bundle would slip into the trench region. This...
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<author>Peter John Ryan</author>


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