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    <title>SMARTech Collection: School of Computer Science Undergraduate Research Option Theses</title>
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    <title>Using First Order Inductive Learning as an Alternative to a Simulator in a Game Artificial Intelligence</title>
    <link>http://smartech.gatech.edu/handle/1853/28284</link>
    <description>Title: Using First Order Inductive Learning as an Alternative to a Simulator in a Game Artificial Intelligence
&lt;br/&gt;
&lt;br/&gt;Authors: Long, Kathryn Anna
&lt;br/&gt;
&lt;br/&gt;Abstract: Currently many game artificial intelligences attempt to determine their next moves by using a simulator to predict the effect of actions in the world. However, writing such a simulator is time-consuming, and the simulator must be changed substantially whenever a detail in the game design is modified. As such, this research project set out to determine if a version of the first order inductive learning algorithm could be used to learn rules that could then be used in place of a simulator. By eliminating the need to write a simulator for each game by hand, the entire Darmok 2 project could more easily adapt to additional real-time strategy games. Over time, Darmok 2 would also be able to provide better competition for human players by training the artificial intelligences to play against the style of a specific player. Most importantly, Darmok 2 might also be able to create a general solution for creating game artificial intelligences, which could save game development companies a substantial amount of money, time, and effort.</description>
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    <title>Distributed Feature Extraction Using Cloud Computing Resources</title>
    <link>http://smartech.gatech.edu/handle/1853/28138</link>
    <description>Title: Distributed Feature Extraction Using Cloud Computing Resources
&lt;br/&gt;
&lt;br/&gt;Authors: Dalton, Steven
&lt;br/&gt;
&lt;br/&gt;Abstract: The need to expand the computational resources in a massive surveillance network is clear but traditional means of purchasing new equipment for short-term tasks every year is wasteful. In this work I will provide evidence in support of utilizing a cloud computing infrastructure to perform computationally intensive feature extraction tasks on data streams. Efficient off-loading of computational tasks to cloud resources will require a minimization of the time needed to expand the cloud resources, an efficient model of communication and a study of the interplay between the in-network computational resources and remote resources in the cloud. This report provides strong evidence that the use of cloud computing resources in a near real-time distributed sensor network surveillance system, ASAP, is feasible. A face detection web service operating on an Amazon EC2 instance is shown to provide processing of 10-15 frames per second.</description>
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    <title>Performance Information Sharing Middleware</title>
    <link>http://smartech.gatech.edu/handle/1853/21821</link>
    <description>Title: Performance Information Sharing Middleware
&lt;br/&gt;
&lt;br/&gt;Authors: Reiss, Charles
&lt;br/&gt;
&lt;br/&gt;Abstract: This thesis presents a design for distributed monitoring system designed to enable monitoring-informed optimizationsin distributed applications. Microbenchmarks and an evaluation  in a scientific-computing scenario are presented.&#xD;
The monitoring system is intended to assist when application requirements cannot be easily expressed in a form suitable for existing autonomic computing approaches.&#xD;
The design embeds awareness of the application's topology into the monitoring system so queries can reference a node's place in the application without embedding extra assumptions about the overall layout of the application. Through integration with dynamic code generation, users may make potentially application-specific metadata available and use such data within dynamically deployed filters and transformation functions. Evaluations demonstrate that this approach can provide timely and useful information with low overhead.</description>
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    <title>Evaluating the effectiveness of using touch sensor capacitors as an input device for a wrist watch computer</title>
    <link>http://smartech.gatech.edu/handle/1853/19947</link>
    <description>Title: Evaluating the effectiveness of using touch sensor capacitors as an input device for a wrist watch computer
&lt;br/&gt;
&lt;br/&gt;Authors: Wilson, Gregory
&lt;br/&gt;
&lt;br/&gt;Abstract: On the go computing is becoming more important for users who wish to access information from anywhere. Wearable computers are an optimal solution to achieving this feat because it allows for easy accessibility and quick use. There are many challenges that arise with small computers worn on the body. One of the most common issues is the interaction between the computer and the user and more specifically how the user enters input. In this paper we research a potential effective way to interact with a wrist watch by mounting touch sensors on the watch band.</description>
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