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Physical Sciences and Mathematics Commons™

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Computer Sciences

Brigham Young University

Series

2010

Articles 1 - 11 of 11

Full-Text Articles in Physical Sciences and Mathematics

Beyond Robot Fan-Out: Towards Multi-Operator Supervisory Control, Michael A. Goodrich, Yisong Guo, Jonathan M. Whetten Oct 2010

Beyond Robot Fan-Out: Towards Multi-Operator Supervisory Control, Michael A. Goodrich, Yisong Guo, Jonathan M. Whetten

Faculty Publications

This paper explores multi-operator supervisory control (MOSC) of multiple independent robots using two complementary approaches: a human factors experiment and an agent-based simulation. The experiment identifies two task and environment limitations on MOSC: task saturation and task diffusion. It also identifies the correlation between task specialization and performance, and the possible existence of untapped spare capacity that emerges when multiple operators coordinate. The presence of untapped spare capacity is explored using agent-based simulation, resulting in evidence which suggests that operators may be more effective when they operate at less than maximum capacity.

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Detailed Requirements For Robots In Autism Therapy, Alan Atherton, Bonnie Brinton, Mark Colton, Nicole Giullian, Michael A. Goodrich, Daniel Ricks Oct 2010

Detailed Requirements For Robots In Autism Therapy, Alan Atherton, Bonnie Brinton, Mark Colton, Nicole Giullian, Michael A. Goodrich, Daniel Ricks

Faculty Publications

Robot-based autism therapy is a rapidly developing area of research, with a wide variety of robots being developed for use in clinical settings. Specific, detailed requirements for robots and user interfaces are needed to provide guidelines for the creation of robots that more effectively assist therapists in autism therapy. This paper enumerates a set of requirements for a clinical humanoid robot and the associated human interface. The design of two humanoid robots and an intuitive and flexible user interface for use by therapists in the treatment of children with autism are described.

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Supporting Wilderness Search And Rescue With Integrated Intelligence: Autonomy And Information At The Right Time And The Right Place, Michael A. Goodrich, Lanny Lin, Bryan S. Morse, Michael Roscheck Jul 2010

Supporting Wilderness Search And Rescue With Integrated Intelligence: Autonomy And Information At The Right Time And The Right Place, Michael A. Goodrich, Lanny Lin, Bryan S. Morse, Michael Roscheck

Faculty Publications

Current practice in Wilderness Search and Rescue (WiSAR) is analogous to an intelligent system designed to gather and analyze information to find missing persons in remote areas. The system consists of multiple parts — various tools for information management (maps, GPS, etc) distributed across personnel with different skills and responsibilities. Introducing a camera-equipped mini-UAV into this task requires autonomy and information technology that itself is an integrated intelligent system to be used by a sub-team that must be integrated into the overall intelligent system. In this paper, we identify key elements of the integration challenges along two dimensions: (a) attributes …

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On The Use Of Cartographic Projections In Visualizing Phylogenetic Treespace, Mark J. Clement, Quinn O. Snell, Kenneth Sundberg Jun 2010

On The Use Of Cartographic Projections In Visualizing Phylogenetic Treespace, Mark J. Clement, Quinn O. Snell, Kenneth Sundberg

Faculty Publications

Phylogenetic analysis is becoming an increasingly important tool for biological research. Applications include epidemiological studies, drug development, and evolutionary analysis. Phylogenetic search is a known NP-Hard problem. The size of the data sets which can be analyzed is limited by the exponential growth in the number of trees that must be considered as the problem size increases. A better understanding of the problem space could lead to better methods, which in turn could lead to the feasible analysis of more data sets. We present a definition of phylogenetic tree space and a visualization of this space that shows significant exploitable …

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Parallel Active Learning: Eliminating Wait Time With Minimal Staleness, Paul Felt, Robbie Haertel, Eric K. Ringger, Kevin Seppi Jun 2010

Parallel Active Learning: Eliminating Wait Time With Minimal Staleness, Paul Felt, Robbie Haertel, Eric K. Ringger, Kevin Seppi

Faculty Publications

A practical concern for Active Learning (AL) is the amount of time human experts must wait for the next instance to label. We propose a method for eliminating this wait time independent of specific learning and scoring algorithms by making scores always available for all instances, using old (stale) scores when necessary. The time during which the expert is annotating is used to train models and score instances–in parallel–to maximize the recency of the scores. Our method can be seen as a parameterless, dynamic batch AL algorithm. We analyze the amount of staleness introduced by various AL schemes and then …

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Geodesic Graph Cut For Interactive Image Segmentation, Bryan S. Morse, Brian L. Price, Scott Cohen Jun 2010

Geodesic Graph Cut For Interactive Image Segmentation, Bryan S. Morse, Brian L. Price, Scott Cohen

Faculty Publications

Interactive segmentation is useful for selecting objects of interest in images and continues to be a topic of much study. Methods that grow regions from foreground/background seeds, such as the recent geodesic segmentation approach, avoid the boundary-length bias of graph-cut methods but have their own bias towards minimizing paths to the seeds, resulting in increased sensitivity to seed placement. The lack of edge modeling in geodesic or similar approaches limits their ability to precisely localize object boundaries, something at which graph-cut methods generally excel. This paper presents a method for combining geodesicdistance information with edge information in a graphcut optimization …

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Simultaneous Foreground, Background, And Alpha Estimation For Image Matting, Bryan S. Morse, Brian L. Price, Scott Cohen Jun 2010

Simultaneous Foreground, Background, And Alpha Estimation For Image Matting, Bryan S. Morse, Brian L. Price, Scott Cohen

Faculty Publications

Image matting is the process of extracting a soft segmentation of an object in an image as defined by the matting equation. Most current techniques focus largely on computing the alpha values of unknown pixels and treat computation of the foreground and background colors as an afterthought, if at all. However, for many applications, such as compositing an object into a new scene or deleting an object from the scene, the foreground and background colors are vital for an acceptable answer. We propose a method of solving for the foreground, background, and alpha of an unknown region in an image …

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Uav Video Coverage Quality Maps And Prioritized Indexing For Wilderness Search And Rescue, Cameron Engh, Michael A. Goodrich, Bryan S. Morse Mar 2010

Uav Video Coverage Quality Maps And Prioritized Indexing For Wilderness Search And Rescue, Cameron Engh, Michael A. Goodrich, Bryan S. Morse

Faculty Publications

Video-equipped mini unmanned aerial vehicles (mini-UAVs) are becoming increasingly popular for surveillance, remote sensing, law enforcement, and search and rescue operations, all of which rely on thorough coverage of a target observation area. However, coverage is not simply a matter of seeing the area (visibility) but of seeing it well enough to allow detection of targets of interest, a quality we here call “see-ability”. Video flashlights, mosaics, or other geospatial compositions of the video may help place the video in context and convey that an area was observed, but not necessarily how well or how often. This paper presents a …

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Evaluating Models Of Latent Document Semantics In The Presence Of Ocr Errors, Daniel D. Walker, William B. Lund, Eric K. Ringger Jan 2010

Evaluating Models Of Latent Document Semantics In The Presence Of Ocr Errors, Daniel D. Walker, William B. Lund, Eric K. Ringger

Faculty Publications

Models of latent document semantics such as the mixture of multinomials model and Latent Dirichlet Allocation have received substantial attention for their ability to discover topical semantics in large collections of text. In an effort to apply such models to noisy optical character recognition (OCR) text output, we endeavor to understand the effect that character-level noise can have on unsupervised topic modeling. We show the effects both with document-level topic analysis (document clustering) and with word-level topic analysis (LDA) on both synthetic and real-world OCR data. As expected, experimental results show that performance declines as word error rates increase. Common …

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Directable Weathering Of Concave Rock Using Curvature Estimation, Matthew Beardall, Joseph Butler, Mckay Farley, Michael D. Jones Jan 2010

Directable Weathering Of Concave Rock Using Curvature Estimation, Matthew Beardall, Joseph Butler, Mckay Farley, Michael D. Jones

Faculty Publications

We address the problem of directable weathering of exposed concave rock for use in computer-generated animation or games. Previous weathering models that admit concave surfaces are computationally inefficient and difficult to control. In nature, the spheroidal and cavernous weathering rates depend on the surface curvature. Spheroidal weathering is fastest in areas with large positive mean curvature and cavernous weathering is fastest in areas with large negative mean curvature. We simulate both processes using an approximation of mean curvature on a voxel grid. Both weathering rates are also influenced by rock durability. The user controls rock durability by editing a durability …

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Automatic Generation Of Music For Inducing Emotive Response, Tony R. Martinez, Kristine Monteith, Dan A. Ventura Jan 2010

Automatic Generation Of Music For Inducing Emotive Response, Tony R. Martinez, Kristine Monteith, Dan A. Ventura

Faculty Publications

We present a system that generates original music designed to match a target emotion. It creates n-gram models, Hidden Markov Models, and other statistical distributions based on musical selections from a corpus representing a given emotion and uses these models to probabilistically generate new musical selections with similar emotional content. This system produces unique and often remarkably musical selections that tend to match a target emotion, performing this task at a level that approaches human competency for the same task.

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