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School of Interactive Computing Technical Report Series
School of Interactive Computing Technical Report Series
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ItemSAM: Steady Affine Motions(Georgia Institute of Technology, 2009-11-23) Rossignac, Jarek ; Vinacua, ÀlvarAn affine motion is a continuous map from time value t to an affinity A subscript t. It is a SAM (Steady Affine Motion), when A subscript t = A superscript t. Although the beauty of a motion is subjective, the above equation provides one mathematical characterization and includes the screw ("universal instantaneous") motion and the golden ("mirabilis") spiral. Although a real matrix, A superscript t, may not exist, we show that it does for a dense set of affinities A covering a significant range of rotations and shears around the identity and that it may be computed efficiently and robustly in two and three dimensions using closed form expressions. SAMs have remarkable properties. For example, the velocity of any point remains constant, both in the global (fixed) and local (moving) frames, which facilitates the exact computation of derived entities, such as the envelope surfaces used to define the boundary of a swept volume. We say that a pattern of features F subscript i is steady when there exists an affinity M such that F subscript i = M superscript i F subscript 0. Each M superscript i is a frame of a SAM and may be computed as A superscript (i/n), where A is the afiine relation F subscript n = A F subscript 0 between the first and the last feature. This option makes it possible to edit directly the feature count n or the cumulative transformation A.
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ItemVisualization of Exception Handling Constructs to Support Program Understanding(Georgia Institute of Technology, 2009) Shah, Hina ; Görg, Carsten ; Harrold, Mary JeanThis paper presents a new visualization technique for supporting the understanding of exception-handling constructs in Java programs. To understand the requirements for such a visualization, we surveyed a group of software developers, and used the results of that survey to guide the creation of the visualizations. The technique presents the exception-handling information using three views: the quantitative view, the flow view, and the contextual view. The quantitative view provides a high-level view that shows the throw-catch interactions in the program, along with relative numbers of these interactions, at the package level, the class level, and the method level. The flow view shows the type-throw-catch interactions, illustrating information such as which exception types reach particular throw statements, which catch statements handle particular throw statements, and which throw statements are not caught in the program. The contextual view shows, for particular type-throw-catch interactions, the packages, classes, and methods that contribute to that exception-handling construct. We implemented our technique in an Eclipse plugin called EnHanCe and conducted a usability and utility study with participants in industry.
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ItemCompositional Classification(Georgia Institute of Technology, 2008-03-25) Jones, JoshuaAn intelligent system must routinely deal with massive information processing complexity. The research discussed in this document is concerned with finding representations and processes to deal with a part of this complexity. At a high level, the proposed idea is that a synthesis between the symbolic reasoning of classic artificial intelligence research and the statistical inference mechanisms of machine learning provides answers to some of these issues of complexity. This research is specifically concerned with a subset of classification problems that we call ”compositional classification”, where both the class label and values produced at internal nodes in the classification structure entail verifiable predictions. This research specifies and evaluates a technique for compositional classification. This investigation will consist of (i) implementing a framework for the construction of supervised classification learning systems that codifies the technique, (ii) instantiating a number of learning systems for various specific classification problems using the framework, (iii) using a synthetic problem setting to systematically vary the problem characteristics and system parameters and assess the impact on performance, and (iv) formally analyzing the properties of the technique. A central problem addressed by this technique is how diverse techniques for representation, reasoning and learning that arise from differing viewpoints on intelligence can be reconciled to form a consistent and effective whole. For example, how can neural network backpropagation and knowledge-based diagnosis be combined to achieve an effective structural credit assignment technique for a hybrid knowledge representation?
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ItemComputer Science Construct Use, Learning, and Creative Credit in a Graphic Design Community(Georgia Institute of Technology, 2008-02) Dorn, Brian ; Tew, Allison Elliott ; Guzdial, MarkEnd-users, who are projected to outnumber professional programmers in the next decade, present a unique opportunity to understand how computer science knowledge is acquired in the real world. We conducted an analysis of projects created by end-user programmers to discern their adoption of introductory computing constructs. A variety of project sizes were represented in the data, ranging from fewer than 100 lines of source code to greater than 1500. Many introductory computing constructs were highly adopted, but some were relatively unused. As these variations in adoption could be indications of topic complexity, we compared our findings to previous work in the novice programming literature. Additionally, a data-driven analysis provided insight into user sharing and reuse practices. Many distinct approaches to copyright and code ownership concerns were found in the projects studied, and their potential impact on end-user learning was considered.
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ItemWhat Makes Teachers Change? Factors that Influence Post-secondary Teachers’ Adoption of New Computing Curricula(Georgia Institute of Technology, 2008) Ni, Lijun ; Guzdial, MarkThis study explores factors that influence teachers’ adoption of curriculum innovations in the context of one specific innovation—Contextualized Computing Curricula. From a teacher-oriented perspective, we propose a theoretical model to represent hypotheses regarding potential adoption factors with an emphasis on the knowledge, beliefs, and attitudes that teachers hold about curriculum, students and themselves. We conducted a pilot study to examine those proposed factors through three summer workshops in 2007. We use the results of the pilot study to extend and refine the proposed model. Our findings indicate that teacher excitement in the new course drives adoption, while systemic issues inhibit adoption. This model might potentially provide a basis for researchers to devise effective strategies for removing barriers that prevent teachers’ adoption, and thereby foster the dissemination of innovations emerging from the learning sciences community.
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ItemLocalization and 3D Reconstruction of Urban Scenes Using GPS(Georgia Institute of Technology, 2008) Kim, Kihwan ; Summet, Jay ; Starner, Thad ; Ashbrook, Daniel ; Kapade, Mrunal ; Essa, IrfanUsing off-the-shelf Global Positioning System (GPS) units, we reconstruct buildings in 3D by exploiting the reduction in signal to noise ratio (SNR) that occurs when the buildings obstruct the line-of-sight between the moving units and the orbiting satellites. We measure the size and height of skyscrapers as well as automatically constructing a density map representing the location of multiple buildings in an urban landscape. If deployed on a large scale, via a cellular service provider’s GPS-enabled mobile phones or GPS-tracked delivery vehicles, the system could provide an inexpensive means of continuously creating and updating 3D maps of urban environments.
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ItemArt or Circus? Characterizing User-Created Video on YouTube(Georgia Institute of Technology, 2008) Landry, Brian M. ; Guzdial, MarkVideo and networking technologies have advanced such that posting and viewing video online is practical. Everyday people now post video online to communicate asynchronously with remote audiences. This paper explores the forms in which people communicate on the popular video sharing website YouTube. It also examines whether end-user video creators on YouTube use plot-based storytelling as a communication strategy. We analyzed popular content on YouTube and found the majority of that content showcases everyday people engaging in uncommon activities. Furthermore, a small minority of popular video actually tells a story. Based on our findings, we propose the compostion gap as a means of conceptualizing the disparity between video content on You- Tube and professional content. We then discuss opportunities for designing technologies to support communication through performance-based video as well as story-based video.
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ItemAutomatic Landmark Detection for Topological Mapping Using Bayesian Surprise(Georgia Institute of Technology, 2008) Ranganathan, Ananth ; Dellaert, FrankTopological maps are graphical representations of the environment consisting of nodes that denote landmarks, and edges that represent the connectivity between the landmarks. Automatic detection of landmarks, usually special places in the environment such as gateways, in a general, sensor-independent manner has proven to be a difficult task. We present a landmark detection scheme based on the notion of “surprise” that addresses these issues. The surprise associated with a measurement is defined as the change in the current model upon updating it using the measurement. We demonstrate that surprise is large when sudden changes in the environment occur, and hence, is a good indicator of landmarks. We evaluate our landmark detector using appearance and laser measurements both qualitatively and quantitatively. Part of this evaluation is performed in the context of a topological mapping algorithm, thus demonstrating the practical applicability of the detector.
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ItemStatically Stable Assembly Sequence Generation for Many Identical Blocks(Georgia Institute of Technology, 2007-10-16) Wolff, Sebastien Jean ; Ebert-Uphoff, Imme ; Lipkin, HarveyThis work develops optimal assembly sequences for modular building blocks. The underlying concept is that an automated device could take a virtual shape such as a CAD file, and decide how to physically build the shape using simple, identical building blocks. The primary focus of this work is the development of methods for generating assembly sequences in a time-feasible manner that ensure static stability at each step of the assembly. This is accomplished by a multi-hierarchical rule-based approach, consisting of a set of low-level, mid-level and high-level assembly rules. Both high-level and mid-level assembly rules are primarily based on static considerations. The best performing rules are presented and their behavior is analyzed.
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ItemMeasuring Connection Strengths and Link Strengths in Discrete Bayesian Networks(Georgia Institute of Technology, 2007-01-29) Ebert-Uphoff, ImmeThis paper discusses measures for connection strength (strength between any two nodes) and link strength (strength along a specific edge) in Discrete Bayesian Networks. The typical application is to visualize the connections in a Bayesian Network learned from data to learn more about the inherent properties of the system (e.g. in earth sciences, biology or medicine). The paper focuses on measures based on mutual information and conditional mutual information. The goal is to provide an easy-toread document that gives clear reasoning for existing measures, provides some simple extensions (modified measures for different applications), discusses the limitations of the measures, provides enough interpretation to aid a scientist in selecting the most appropriate one and suggests some new uses for link strength.