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- UAV (3)
- Machine learning (2)
- Unmanned aerial vehicle (2)
- 3-D interface (1)
- ADtrees (1)
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- Active sampling (1)
- Ad hoc networks (1)
- Aerial imagery (1)
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- Analogical modeling (1)
- Augmented-virtuality (1)
- Automated ontology generation (1)
- Biometric fusion (1)
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- Cognitive psychology (1)
- Cognitive robotics (1)
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- Continuous optimization (1)
- Corpora data (1)
- Corpus annotation (1)
- DSSS (1)
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- Down syndrome (1)
- Exemplar-based approach (1)
- FHSS (1)
- Fuzzy-word correlation (1)
Articles 1 - 28 of 28
Full-Text Articles in Physical Sciences and Mathematics
Analyzing Gene Relationships For Down Syndrome With Labeled Transition Graphs, Hyrum Carroll, Mark J. Clement, Eric G. Mercer, Neha Rungta, Quinn O. Snell, Randall J. Roper
Analyzing Gene Relationships For Down Syndrome With Labeled Transition Graphs, Hyrum Carroll, Mark J. Clement, Eric G. Mercer, Neha Rungta, Quinn O. Snell, Randall J. Roper
Faculty Publications
The relationship between changes in gene expression and physical characteristics associated with Down syndrome is not well understood. Chromosome 21 genes interact with nonchromosome 21 genes to produce Down syndrome characteristics. This indirect influence, however, is difficult to empirically define due to the number, size, and complexity of the involved gene regulatory networks. This work links chromosome 21 genes to non-chromosome 21 genes known to interact in a Down syndrome phenotype through a reachability analysis of labeled transition graphs extracted from published gene regulatory network databases. The analysis provides new relations in a recently discovered link between a specific gene …
Spilling: Expanding Hand Held Interaction To Touch Table Displays, Jeffrey Clement, Dan R. Olsen Jr., Aaron Pace
Spilling: Expanding Hand Held Interaction To Touch Table Displays, Jeffrey Clement, Dan R. Olsen Jr., Aaron Pace
Faculty Publications
We envision a nomadic model of interaction where the personal computer fits in your pocket. Such a computer is extremely limited in screen space. A technique is described for “spilling” the display of a hand held computer onto a much larger table top display surface. Because our model of nomadic computing frequently involves the use of untrusted display services we restrict interactive input to the hand held. Navigation techniques such as scrolling or turning the display can be expressed through the table top. The orientation and position of the hand held on the table top is detected using three conductive …
Adtrees For Sequential Data And N-Gram Counting, Robert Van Dam, Dan A. Ventura
Adtrees For Sequential Data And N-Gram Counting, Robert Van Dam, Dan A. Ventura
Faculty Publications
We consider the problem of efficiently storing n-gram counts for large n over very large corpora. In such cases, the efficient storage of sufficient statistics can have a dramatic impact on system performance. One popular model for storing such data derived from tabular data sets with many attributes is the ADtree. Here, we adapt the ADtree to benefit from the sequential structure of corpora-type data. We demonstrate the usefulness of our approach on a portion of the well-known Wall Street Journal corpus from the Penn Treebank and show that our approach is exponentially more efficient than the naïve approach to …
Robust Multi-Modal Biometric Fusion Via Multiple Svms, Jonathan Dinerstein, Sabra Dinerstein, Dan A. Ventura
Robust Multi-Modal Biometric Fusion Via Multiple Svms, Jonathan Dinerstein, Sabra Dinerstein, Dan A. Ventura
Faculty Publications
Existing learning-based multi-modal biometric fusion techniques typically employ a single static Support Vector Machine (SVM). This type of fusion improves the accuracy of biometric classification, but it also has serious limitations because it is based on the assumptions that the set of biometric classifiers to be fused is local, static, and complete. We present a novel multi-SVM approach to multi-modal biometric fusion that addresses the limitations of existing fusion techniques and show empirically that our approach retains good classification accuracy even when some of the biometric modalities are unavailable.
A Data-Dependent Distance Measure For Transductive Instance-Based Learning, Jared Lundell, Dan A. Ventura
A Data-Dependent Distance Measure For Transductive Instance-Based Learning, Jared Lundell, Dan A. Ventura
Faculty Publications
We consider learning in a transductive setting using instance-based learning (k-NN) and present a method for constructing a data-dependent distance “metric” using both labeled training data as well as available unlabeled data (that is to be classified by the model). This new data-driven measure of distance is empirically studied in the context of various instance-based models and is shown to reduce error (compared to traditional models) under certain learning conditions. Generalizations and improvements are suggested.
Ecological Interfaces For Improving Mobile Robot Teleoperation, Michael A. Goodrich, Curtis W. Nielsen, Robert W. Ricks
Ecological Interfaces For Improving Mobile Robot Teleoperation, Michael A. Goodrich, Curtis W. Nielsen, Robert W. Ricks
Faculty Publications
Navigation is an essential element of many remote robot operations including search and rescue, reconnaissance, and space exploration. Previous reports on using remote mobile robots suggest that navigation is difficult due to poor situation awareness. It has been recommended by experts in human–robot interaction that interfaces between humans and robots provide more spatial information and better situational context in order to improve an operator’s situation awareness. This paper presents an ecological interface paradigm that combines video, map, and robotpose information into a 3-D mixed-reality display. The ecological paradigm is validated in planar worlds by comparing it against the standard interface …
Psoda: Better Tasting And Less Filling Than Paup, Hyrum Carroll, Mark J. Clement, Mark Ebbert, Quinn O. Snell
Psoda: Better Tasting And Less Filling Than Paup, Hyrum Carroll, Mark J. Clement, Mark Ebbert, Quinn O. Snell
Faculty Publications
PSODA is an open-source phylogenetic search application that implements traditional parsimony and likelihood search techniques as well as advanced search algorithms. PSODA is compatible with PAUP and the search algorithms are competitive with those in PAUP. PSODA also adds a basic scripting language to the PAUP block, making it possible to easily create advanced meta-searches. Additionally, PSODA provides a user-friendly GUI with real-time graphing visualizations and phylogeny viewer, and a multiple sequence alignment algorithm PSODA is freely available from the PSODA web site: http://csl.cs.byu.edu/psoda.
Psodascript: Applying Advanced Language Constructs To Open-Source Phylogenetic Search, Hyrum Carroll, Mark J. Clement, Jonathan Krein, Quinn O. Snell, Adam R. Teichert
Psodascript: Applying Advanced Language Constructs To Open-Source Phylogenetic Search, Hyrum Carroll, Mark J. Clement, Jonathan Krein, Quinn O. Snell, Adam R. Teichert
Faculty Publications
Due to the immensity of phylogenetic tree space for large data sets, researches must rely on heuristic searches to infer reasonable phylogenies. By designing meta-searches which appropriately combine a variety of heuristics and parameter settings, researchers can significantly improve the performance of heuristic searches. Advanced language constructs in the open-source PSODA project—including variables, mathematical and logical expressions, conditional statements, and user-defined commands—give researchers a better framework for the exploration and exploitation of phylogenetic meta-search algorithms. PSODA’s approach to scripting meta-search algorithms is unique among open-source packages and addresses several limitations of other phylogenetic applications.
Using Parsimony To Guide Maximum Likelihood Searches, Hyrum Carroll, Mark J. Clement, Timothy O'Connor, Quinn O. Snell, Kenneth Sundberg
Using Parsimony To Guide Maximum Likelihood Searches, Hyrum Carroll, Mark J. Clement, Timothy O'Connor, Quinn O. Snell, Kenneth Sundberg
Faculty Publications
The performance of maximum likelihood searches can be boosted by using the most parsimonious tree as a starting point for the search. The time spent in performing the parsimony search to find this starting tree is insignificant compared to the time spent in the maximum likelihood search, leading to an overall gain in search time. These parsimony boosted maximum likelihood searches lead to topologies with scores statisitically similar to the unboosted searches, but in less time.
Using A Mini-Uav To Support Wilderness Search And Rescue: Practices For Human-Robot Teaming, Julie A. Adams, Brian G. Buss, Joseph L. Cooper, Michael A. Goodrich, Curtis Humphrey, Ron Zeeman
Using A Mini-Uav To Support Wilderness Search And Rescue: Practices For Human-Robot Teaming, Julie A. Adams, Brian G. Buss, Joseph L. Cooper, Michael A. Goodrich, Curtis Humphrey, Ron Zeeman
Faculty Publications
Wilderness Search and Rescue can benefit from aerial imagery of the search area. Mini Unmanned Aerial Vehicles can potentially provide such imagery, provided that the autonomy, search algorithms, and operator control unit are designed to support coordinated human-robot search teams. Using results from formal analyses of the WiSAR problem domain, we summarize and discuss information flow requirements for WiSAR with an eye toward the efficient use of mUAVs to support search. We then identify and discuss three different operational paradigms for performing field searches, and identify influences that affect which human-robot team paradigm is best. Since the likely location of …
Parallel Pso Using Mapreduce, Andrew Mcnabb, Christopher K. Monson, Kevin Seppi
Parallel Pso Using Mapreduce, Andrew Mcnabb, Christopher K. Monson, Kevin Seppi
Faculty Publications
In optimization problems involving large amounts of data, such as web content, commercial transaction information, or bioinformatics data, individual function evaluations may take minutes or even hours. Particle Swarm Optimization (PSO) must be parallelized for such functions. However, large-scale parallel programs must communicate efficiently, balance work across all processors, and address problems such as failed nodes. We present MapReduce Particle Swarm Optimization (MRPSO), a PSO implementation based on the MapReduce parallel programming model. We describe MapReduce and show how PSO can be naturally expressed in this model, without explicitly addressing any of the details of parallelization. We present a benchmark …
A Utile Function Optimizer, James Carroll, Christopher K. Monson, Kevin Seppi
A Utile Function Optimizer, James Carroll, Christopher K. Monson, Kevin Seppi
Faculty Publications
We recast the problem of unconstrained continuous evolutionary optimization as inference in a fixed graphical model. This approach allows us to address several pervasive issues in optimization, including the traditionally difficult problem of selecting an algorithm that is most appropriate for a given task. This is accomplished by placing a prior distribution over the expected class of functions, then employing inference and intuitively defined utilities and costs to transform the evolutionary optimization problem into one of active sampling. This allows us to pose an approach to optimization that is optimal for each expressly stated function class. The resulting solution methodology …
Hardness For Explicit State Software Model Checking Benchmarks, Eric G. Mercer, Neha Rungta
Hardness For Explicit State Software Model Checking Benchmarks, Eric G. Mercer, Neha Rungta
Faculty Publications
Directed model checking algorithms focus computation resources in the error-prone areas of concurrent systems. The algorithms depend on some empirical analysis to report their performance gains. Recent work characterizes the hardness of models used in the analysis as an estimated number of paths in the model that contain an error. This hardness metric is computed using a stateless random walk. We show that this is not a good hardness metric because models labeled hard with a stateless random walk metric have easily discoverable errors with a stateful randomized search. We present an analysis which shows that a hardness metric based …
Poisson Disk Point Sets By Hierarchical Dart Throwing, David Cline, Parris K. Egbert, Kenric B. White
Poisson Disk Point Sets By Hierarchical Dart Throwing, David Cline, Parris K. Egbert, Kenric B. White
Faculty Publications
Poisson disk point sets are “ideally” generated through a process of dart throwing. The naive dart throwing algorithm is extremely expensive if a maximal set is desired, however. In this paper we present a hierarchical dart throwing procedure which produces point sets that are equivalent to naive dart throwing, but is very fast. The procedure works by intelligently excluding areas known to be fully covered by existing samples. By excluding covered regions, the probability of accepting a thrown dart is greatly increased. Our algorithm is conceptually simple, performs dart throwing in O(N) time and memory, and produces a maximal point …
Image-Based Color Schemes, Bryan S. Morse, Daniel Thornton, Qing Xia, John Uibel
Image-Based Color Schemes, Bryan S. Morse, Daniel Thornton, Qing Xia, John Uibel
Faculty Publications
This paper presents a novel method for generating color schemes based on images intended to anchor color designs. This has wide applicability for web pages, printed materials, or other applications where images are used as a key part of the overall design. Unlike methods that are variants of color quantization and try to pixel-wise approximate the image, this method draws on graphic-design principles by emphasizing hue selection first, weighting effects of color by saturation, and considering the local spatial coherency in order to determine the overall visual impact of a color. Results demonstrate that the method generalizes to a wide …
Using Fuzzy-Word Correlation Factors To Compute Document Similarity Based On Phrase Matching, Jun Won Lee, Yiu-Kai D. Ng
Using Fuzzy-Word Correlation Factors To Compute Document Similarity Based On Phrase Matching, Jun Won Lee, Yiu-Kai D. Ng
Faculty Publications
One of the Web information Retrieval (IR) problems these days is to identify redundant information that exist in (replicated) Web documents. These documents can easily be found in several forms, such as documents in different versions, small documents combined with others to form a larger document, etc. As the Web is becoming more and more popular, the number of documents on the Web is increasing on a daily basis, and filtering redundant ones among this huge number of documents becomes a more difficult and an urgent task. As one of the solutions to this problem, we present a new method …
A Dynamic Attribute-Based Load Shedding Scheme For Data Stream Management Systems, Amit Ahuja, Yiu-Kai D. Ng
A Dynamic Attribute-Based Load Shedding Scheme For Data Stream Management Systems, Amit Ahuja, Yiu-Kai D. Ng
Faculty Publications
A data stream being transmitted over a network channel with capacity less than the data transmission rate of the data stream causes sequential network problems. In this paper, we present a new approach for shedding less-informative attribute data from a data stream to maintain a data transmission rate less than the network channel capacity. A scheme for shedding attributes and their data, instead of tuples, becomes imperative in data stream load shedding, since shedding a complete tuple would lead to shedding informative attribute data along with less-informative attribute data in the tuple. Our load shedding approach handles intra-stream, as well …
Active Learning For Part-Of-Speech Tagging: Accelerating Corpus Annotation, George Busby, Marc Carmen, James Carroll, Robbie Haertel, Deryle W. Lonsdale, Peter Mcclanahan, Eric K. Ringger, Kevin Seppi
Active Learning For Part-Of-Speech Tagging: Accelerating Corpus Annotation, George Busby, Marc Carmen, James Carroll, Robbie Haertel, Deryle W. Lonsdale, Peter Mcclanahan, Eric K. Ringger, Kevin Seppi
Faculty Publications
In the construction of a part-of-speech annotated corpus, we are constrained by a fixed budget. A fully annotated corpus is required, but we can afford to label only a subset. We train a Maximum Entropy Markov Model tagger from a labeled subset and automatically tag the remainder. This paper addresses the question of where to focus our manual tagging efforts in order to deliver an annotation of highest quality. In this context, we find that active learning is always helpful. We focus on Query by Uncertainty (QBU) and Query by Committee (QBC) and report on experiments with several baselines and …
Probabilistic Searching Using A Small Unmanned Aerial Vehicle, Steven R. Hansen, Timothy W. Mclain, Michael A. Goodrich
Probabilistic Searching Using A Small Unmanned Aerial Vehicle, Steven R. Hansen, Timothy W. Mclain, Michael A. Goodrich
Faculty Publications
Ground breaking concepts in optimal search theory were developed during World War II by the U.S. Navy. These concepts use an assumed detection model to calculate a detection probability rate and an optimal search allocation. Although this theory is useful in determining when and where search effort should be applied, it offers little guidance for the planning of search paths. This paper explains how search theory can be applied to path planning for an SUAV with a fixed CCD camera. Three search strategies are developed: greedy search, contour search, and composite search. In addition, the concepts of search efficiency and …
To Repair Or Not To Repair: Helping Ad Hoc Routing Protocols To Distinguish Mobility From Congestion, Qiuyi Duan, Roger Pack, Manoj Pandey, Lei Wang, Daniel Zappala
To Repair Or Not To Repair: Helping Ad Hoc Routing Protocols To Distinguish Mobility From Congestion, Qiuyi Duan, Roger Pack, Manoj Pandey, Lei Wang, Daniel Zappala
Faculty Publications
In this paper we consider the problem of distinguishing whether frame loss at the MAC layer has occurred due to mobility or congestion. Most ad hoc routing protocols make the faulty assumption that all frame loss means the destination node has moved, resulting in significant overhead as they initiate the repair of routes that have not been broken. We design a mobility detection algorithm, MDA, that properly detects the cause of a lost frame, then coordinates with the routing protocol so that it reacts properly. This approach dramatically reduces routing protocol overhead and significantly increases application throughput. We use a …
Ria: An Rf Interference Avoidance Algorithm For Heterogeneous Wireless Networks, Daniel P. Delorey, Qiuyi Duan, Charles D. Knutson, Manoj Pandey, Lei Wang, Ryan W. Woodings, Daniel Zappala
Ria: An Rf Interference Avoidance Algorithm For Heterogeneous Wireless Networks, Daniel P. Delorey, Qiuyi Duan, Charles D. Knutson, Manoj Pandey, Lei Wang, Ryan W. Woodings, Daniel Zappala
Faculty Publications
Devices with multiple wireless interfaces are becoming increasingly popular. We envision that these devices will become the building block for future mesh networks, providing seamless connectivity across a range of heterogeneous devices. Although these devices typically implement frequency sharing, using either Direct Sequence Spread Spectrum (DSSS) or Frequency Hopping Spread Spectrum (FHSS), they may still interfere with one another. In this paper we provide a novel Radio Interference Avoidance (RIA) algorithm that solves the problem of interference between IEEE 802.11 and Bluetooth. We then extend this algorithm to other types of DSSS and FHSS combinations. Though the algorithm is limited …
Performance Evaluation Of Vision-Based Navigation And Landing On A Rotorcraft Unmanned Aerial Vehicle, David Hubbard, Timothy W. Mclain, Bryan S. Morse, Colin Theodore, Mark Tischler
Performance Evaluation Of Vision-Based Navigation And Landing On A Rotorcraft Unmanned Aerial Vehicle, David Hubbard, Timothy W. Mclain, Bryan S. Morse, Colin Theodore, Mark Tischler
Faculty Publications
A Rotorcraft UAV provides an ideal experimental platform for vision-based navigation. This paper describes the flight tests of the US Army PALACE project, which implements Moravec’s pseudo-normalized correlation tracking algorithm. The tracker uses the movement of the landing site in the camera, a laser range, and the aircraft attitude from an IMU to estimate the relative motion of the UAV. The position estimate functions as a GPS equivalent to enable the rotorcraft to maneuver without the aid of GPS. With GPS data as a baseline, tests were performed in simulation and in flight that measure the accuracy of the position …
Human–Robot Interaction: A Survey, Michael A. Goodrich, Alan C. Schultz
Human–Robot Interaction: A Survey, Michael A. Goodrich, Alan C. Schultz
Faculty Publications
Human–Robot Interaction (HRI) has recently received considerable attention in the academic community, in labs, in technology companies, and through the media. Because of this attention, it is desirable to present a survey of HRI to serve as a tutorial to people outside the field and to promote discussion of a unified vision of HRI within the field. The goal of this review is to present a unified treatment of HRI-related problems, to identify key themes, and discuss challenge problems that are likely to shape the field in the near future. Although the review follows a survey structure, the goal of …
Interactive Image Repair With Assisted Structure And Texture Completion, Teryl Arnold, Bryan S. Morse
Interactive Image Repair With Assisted Structure And Texture Completion, Teryl Arnold, Bryan S. Morse
Faculty Publications
Removing image defects in an undetectable manner has been studied for its many useful and varied applications. In many cases the desired result may be ambiguous from the image data alone and needs to be guided by a user’s knowledge of the intended result. This paper presents a framework for interactively incorporating user guidance into the filling-in process, more effectively using user input to fill in damaged regions in an image. This framework contains five main steps: first, the scratch or defect is detected; second, the edges outside the defect are detected; third, curves are fit to the detected edges; …
Clustering Streaming Music Via The Temporal Similarity Of Timbre, Jacob Merrell, Bryan S. Morse, Dan A. Ventura
Clustering Streaming Music Via The Temporal Similarity Of Timbre, Jacob Merrell, Bryan S. Morse, Dan A. Ventura
Faculty Publications
We consider the problem of measuring the similarity of streaming music content and present a method for modeling, on the fly, the temporal progression of a song’s timbre. Using a minimum distance classification scheme, we give an approach to classifying streaming music sources and present performance results for auto-associative song identification and for content-based clustering of streaming music. We discuss possible extensions to the approach and possible uses for such a system.
Generating Ontologies Via Language Components And Ontology Reuse, Deryle W. Lonsdale, Yihong Ding, David W. Embley, Martin Hepp, Li Xu
Generating Ontologies Via Language Components And Ontology Reuse, Deryle W. Lonsdale, Yihong Ding, David W. Embley, Martin Hepp, Li Xu
Faculty Publications
Realizing the Semantic Web involves creating ontologies, a tedious and costly challenge. Reuse can reduce the cost of ontology engineering. Semantic Web ontologies can provide useful input for ontology reuse. However, the automated reuse of such ontologies remains underexplored. This paper presents a generic architecture for automated ontology reuse. With our implementation of this architecture, we show the practicality of automating ontology generation through ontology reuse. We experimented with a large generic ontology as a basis for automatically generating domain ontologies that fit the scope of sample natural-language web pages. The results were encouraging, resulting in five lessons pertinent to …
Analogical Modeling: An Update, Deryle W. Lonsdale, David Eddington
Analogical Modeling: An Update, Deryle W. Lonsdale, David Eddington
Faculty Publications
Analogical modeling is a supervised exemplar-based approach that has been widely applied to predict linguistic behavior. The paradigm has been well documented in the linguistics and cognition literature, but is less well known to the machine learning community. This paper sets out some of the basics of the approach, including a simplified example of the fundamental algorithm’s operation. It then surveys some of the recent analogical modeling language applications, and sketches how the computational system has been enhanced lately to offer users increased flexibility and processing power. Some comparisons and contrasts are drawn between analogical modeling and other language modeling …
A Cognitive Robotics Approach To Comprehending Human Language And Behaviors, Deryle W. Lonsdale, D. Paul Benjamin, Damian Lyons
A Cognitive Robotics Approach To Comprehending Human Language And Behaviors, Deryle W. Lonsdale, D. Paul Benjamin, Damian Lyons
Faculty Publications
The ADAPT project is a collaboration of researchers in linguistics, robotics and artificial intelligence at three universities. We are building a complete robotic cognitive architecture for a mobile robot designed to interact with humans in a range of environments, and which uses natural language and models human behavior. This paper concentrates on the HRI aspects of ADAPT, and especially on how ADAPT models and interacts with humans.