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Computer Sciences

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Faculty Publications

2010

Articles 1 - 18 of 18

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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Electronic Image Stabilization Using Optical Flow With Inertial Fusion, Michael J. Smith, Alexander J. Boxerbaum, Gilbert L. Peterson, Roger D. Quinn Oct 2010

Electronic Image Stabilization Using Optical Flow With Inertial Fusion, Michael J. Smith, Alexander J. Boxerbaum, Gilbert L. Peterson, Roger D. Quinn

Faculty Publications

When a camera is affixed on a dynamic mobile robot, image stabilization is the first step towards more complex analysis on the video feed. This paper presents a novel electronic image stabilization (EIS) algorithm for highly dynamic mobile robotic platforms. The algorithm combines optical flow motion parameter estimation with angular rate data provided by a strapdown inertial measurement unit (IMU). A discrete Kalman filter in feedforward configuration is used for optimal fusion of the two data sources. Performance evaluations are conducted using a simulated video truth model (capturing the effects of image translation, rotation, blurring, and moving objects), and live …

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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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Sql Querie Recommendations: A Query Fragment-Based Approach, Jayad Akbarnejad, Magdalini Eirinaki, Suju Koshy, Duc On, Neoklis Polyzotis Sep 2010

Sql Querie Recommendations: A Query Fragment-Based Approach, Jayad Akbarnejad, Magdalini Eirinaki, Suju Koshy, Duc On, Neoklis Polyzotis

Faculty Publications

Relational database systems are becoming increasingly popular in the scientific community to support the interactive exploration of large volumes of data. In this scenario, users employ a query interface (typically, a web-based client) to issue a series of SQL queries that aim to analyze the data and mine it for interesting information. First-time users, however, may not have the necessary knowledge to know where to start their exploration. Other times, users may simply overlook queries that retrieve important information. In this work we describe a framework to assist non-expert users by providing personalized query recommendations. The querying behavior of the …

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Personal Vs. Social, Magdalini Eirinaki Sep 2010

Personal Vs. Social, Magdalini Eirinaki

Faculty Publications

The last few years we witnessed an impressive growth in social networks and in applications that add value to their amassed information. At the same time, the continuing expansion of mobile platforms and applications (e.g. iPhone), combined with the overwhelming supply of information and services, makes effective personalization and context-awareness much required features. One may consider "personal" and "social" data management as comprising two distinct directions with conflicting characteristics. However, it can be argued that they complement each other and that in future applications they will ultimately converge. This "personal vs. social" predicament presents a number of interesting topics that …

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Malware Type Recognition And Cyber Situational Awareness, Thomas Dube, Richard A. Raines, Gilbert L. Peterson, Kenneth W. Bauer, Michael R. Grimaila, Steven K. Rogers Aug 2010

Malware Type Recognition And Cyber Situational Awareness, Thomas Dube, Richard A. Raines, Gilbert L. Peterson, Kenneth W. Bauer, Michael R. Grimaila, Steven K. Rogers

Faculty Publications

Current technologies for computer network and host defense do not provide suitable information to support strategic and tactical decision making processes. Although pattern-based malware detection is an active research area, the additional context of the type of malware can improve cyber situational awareness. This additional context is an indicator of threat capability thus allowing organizations to assess information losses and focus response actions appropriately. Malware Type Recognition (MaTR) is a research initiative extending detection technologies to provide the additional context of malware types using only static heuristics. Test results with MaTR demonstrate over a 99% accurate detection rate and 59% …

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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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Simulating Windows-Based Cyber Attacks Using Live Virtual Machine Introspection, Dustyn A. Dodge, Barry E. Mullins, Gilbert L. Peterson, James S. Okolica Jul 2010

Simulating Windows-Based Cyber Attacks Using Live Virtual Machine Introspection, Dustyn A. Dodge, Barry E. Mullins, Gilbert L. Peterson, James S. Okolica

Faculty Publications

Static memory analysis has been proven a valuable technique for digital forensics. However, the memory capture technique halts the system causing the loss of important dynamic system data. As a result, live analysis techniques have emerged to complement static analysis. In this paper, a compiled memory analysis tool for virtualization (CMAT-V) is presented as a virtual machine introspection (VMI) utility to conduct live analysis during simulated cyber attacks. CMAT-V leverages static memory dump analysis techniques to provide live system state awareness. CMAT-V parses an arbitrary memory dump from a simulated guest operating system (OS) to extract user information, network usage, …

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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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Developing Cyberspace Data Understanding Using Crisp-Dm For Host-Based Ids Feature Mining, Joseph R. Erskine, Gilbert L. Peterson, Barry E. Mullins, Michael R. Grimaila Apr 2010

Developing Cyberspace Data Understanding Using Crisp-Dm For Host-Based Ids Feature Mining, Joseph R. Erskine, Gilbert L. Peterson, Barry E. Mullins, Michael R. Grimaila

Faculty Publications

Current intrusion detection systems (IDS) generate a large number of specific alerts, but typically do not provide actionable information. Compounding this problem is the fact that many alerts are false positive alerts. This paper applies the Cross Industry Standard Process for Data Mining (CRISP-DM) to develop an understanding of a host environment under attack. Data is generated by launching scans and exploits at a machine outfitted with a set of host-based forensic data collectors. Through knowledge discovery, features are selected to project human understanding of the attack process into the IDS model. By discovering relationships between the data collected and …

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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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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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An Fpga-Based System For Tracking Digital Information Transmitted Via Peer-To-Peer Protocols, Karl R. Schrader, Barry E. Mullins, Gilbert L. Peterson, Robert F. Mills Jan 2010

An Fpga-Based System For Tracking Digital Information Transmitted Via Peer-To-Peer Protocols, Karl R. Schrader, Barry E. Mullins, Gilbert L. Peterson, Robert F. Mills

Faculty Publications

This paper presents a Field Programmable Gate Array (FPGA)-based tool designed to process file transfers using the BitTorrent Peer-to-Peer (P2P) protocol and VoIP phone calls made using the Session Initiation Protocol (SIP). The tool searches selected control messages in real time and compares the unique identifier of the shared file or phone number against a list of known contraband files or phone numbers. Results show the FPGA tool processes P2P packets of interest 92% faster than a software-only configuration and is 97.6% accurate at capturing and processing messages at a traffic load of 89.6 Mbps.

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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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