Open Access. Powered by Scholars. Published by Universities.®

Computer Sciences Commons™

Open Access. Powered by Scholars. Published by Universities.®

Faculty Publications

Discipline
Institution
Keyword
Publication Year
File Type

Articles 391 - 420 of 663

Full-Text Articles in Computer Sciences

Integrating Trust Into The Cybercraft Initiative Via The Trust Vectors Model, Michael Stevens, Paul D. Williams, Gilbert L. Peterson, Stuart H. Kurkowski May 2008

Integrating Trust Into The Cybercraft Initiative Via The Trust Vectors Model, Michael Stevens, Paul D. Williams, Gilbert L. Peterson, Stuart H. Kurkowski

Faculty Publications

This research supports the hypothesis that the Trust Vector model can be modified to fit the CyberCraft Initiative, and that there are limits to the utility of historical data. This research proposed some modifications and expansions to the Trust Model Vector, and identified areas for future research.

Go to article

Accelerating Corpus Annotation Through Active Learning, George Busby, Marc Carmen, James Carroll, Robbie Haertel, Deryle W. Lonsdale, Peter Mcclanahan, Eric K. Ringger, Kevin Seppi Mar 2008

Accelerating Corpus Annotation Through Active Learning, George Busby, Marc Carmen, James Carroll, Robbie Haertel, Deryle W. Lonsdale, Peter Mcclanahan, Eric K. Ringger, Kevin Seppi

Faculty Publications

PDF of Powerpoint Presentation on accelerating corpus annotation through active learning. This presentation was given at the Conference of the American Association for Corpus Linguistics in 2008.

Go to article

Analysis Of Canonical Chinese Antonym Co-Occurrence, Eric K. Ringger, Guohui Liu, Shiping Liu, Xingfu Wang Mar 2008

Analysis Of Canonical Chinese Antonym Co-Occurrence, Eric K. Ringger, Guohui Liu, Shiping Liu, Xingfu Wang

Faculty Publications

PDF of Powerpoint Presentation on canonical Chinese antonym co-occurrence. This presentation was given at the Conference of the American Association for Corpus Linguistics in 2008.

Go to article

Compiling And Annotating A Syriac Corpus, George Busby, James Carroll, Marc Carmen, Carl Griffin, Robbie Haertel, Kristian Heal, Joshua Heaton, Deryle W. Lonsdale, Peter Mcclanahan, Eric K. Ringger, Kevin Seppi, David Taylor Mar 2008

Compiling And Annotating A Syriac Corpus, George Busby, James Carroll, Marc Carmen, Carl Griffin, Robbie Haertel, Kristian Heal, Joshua Heaton, Deryle W. Lonsdale, Peter Mcclanahan, Eric K. Ringger, Kevin Seppi, David Taylor

Faculty Publications

PDF of Powerpoint Presentation on compiling and annotating a Syriac corpus. This presentation was given at the Conference of the American Association for Corpus Linguistics in 2008.

Go to article

Multi-Class Classification Fusion Using Boosting For Identifying Steganography Methods, Benjamin M. Rodriguez, Gilbert L. Peterson Mar 2008

Multi-Class Classification Fusion Using Boosting For Identifying Steganography Methods, Benjamin M. Rodriguez, Gilbert L. Peterson

Faculty Publications

No abstract provided.

Go to article

Sub-Symbolic Re-Representation To Facilitate Learning Transfer, Dan A. Ventura Mar 2008

Sub-Symbolic Re-Representation To Facilitate Learning Transfer, Dan A. Ventura

Faculty Publications

We consider the issue of knowledge (re-)representation in the context of learning transfer and present a subsymbolic approach for effecting such transfer. Given a set of data, manifold learning is used to automatically organize the data into one or more representational transformations, which are then learned with a set of neural networks. The result is a set of neural filters that can be applied to new data as re-representation operators. Encouraging preliminary empirical results elucidate the approach and demonstrate its feasibility, suggesting possible implications for the broader field of creativity.

Go to article

The Importance Of Generalizability To Anomaly Detection, Gilbert L. Peterson, Brent T. Mcbride Mar 2008

The Importance Of Generalizability To Anomaly Detection, Gilbert L. Peterson, Brent T. Mcbride

Faculty Publications

In security-related areas there is concern over novel “zero-day” attacks that penetrate system defenses and wreak havoc. The best methods for countering these threats are recognizing “nonself” as in an Artificial Immune System or recognizing “self” through clustering. For either case, the concern remains that something that appears similar to self could be missed. Given this situation, one could incorrectly assume that a preference for a tighter fit to self over generalizability is important for false positive reduction in this type of learning problem. This article confirms that in anomaly detection as in other forms of classification a tight fit, …

Go to article

Ant Clustering With Locally Weighting Ant Perception And Diversified Memory, Gilbert L. Peterson, Christopher B. Mayer, Thomas L. Kubler Mar 2008

Ant Clustering With Locally Weighting Ant Perception And Diversified Memory, Gilbert L. Peterson, Christopher B. Mayer, Thomas L. Kubler

Faculty Publications

Ant clustering algorithms are a robust and flexible tool for clustering data that have produced some promising results. This paper introduces two improvements that can be incorporated into any ant clustering algorithm: kernel function similarity weights and a similarity memory model replacement scheme. A kernel function weights objects within an ant’s neighborhood according to the object distance and provides an alternate interpretation of the similarity of objects in an ant’s neighborhood. Ants can hill-climb the kernel gradients as they look for a suitable place to drop a carried object. The similarity memory model equips ants with a small memory consisting …

Go to article

Using Plsi-U To Detect Insider Threats By Datamining Email, James S. Okolica, Gilbert L. Peterson, Robert F. Mills Feb 2008

Using Plsi-U To Detect Insider Threats By Datamining Email, James S. Okolica, Gilbert L. Peterson, Robert F. Mills

Faculty Publications

Despite a technology bias that focuses on external electronic threats, insiders pose the greatest threat to an organisation. This paper discusses an approach to assist investigators in identifying potential insider threats. We discern employees' interests from e-mail using an extended version of PLSI. These interests are transformed into implicit and explicit social network graphs, which are used to locate potential insiders by identifying individuals who feel alienated from the organisation or have a hidden interest in a sensitive topic. By applying this technique to the Enron e-mail corpus, a small number of employees appear as potential insider threats.

Go to article

Adapting Adtrees For High Arity Features, Irene Langkilde-Geary, Robert Van Dam, Dan A. Ventura Jan 2008

Adapting Adtrees For High Arity Features, Irene Langkilde-Geary, Robert Van Dam, Dan A. Ventura

Faculty Publications

ADtrees, a data structure useful for caching sufficient statistics, have been successfully adapted to grow lazily when memory is limited and to update sequentially with an incrementally updated dataset. For low arity symbolic features, ADtrees trade a slight increase in query time for a reduction in overall tree size. Unfortunately, for high arity features, the same technique can often result in a very large increase in query time and a nearly negligible tree size reduction. In the dynamic (lazy) version of the tree, both query time and tree size can increase for some applications. Here we present two modifications to …

Go to article

Utilizing Phrase-Similarity Measures For Detecting And Clustering Informative Rss News Articles, Yiu-Kai D. Ng, Maria Soledad Pera Jan 2008

Utilizing Phrase-Similarity Measures For Detecting And Clustering Informative Rss News Articles, Yiu-Kai D. Ng, Maria Soledad Pera

Faculty Publications

As the number of RSS news feeds continue to increase over the Internet, it becomes necessary to minimize the workload of the user who is otherwise required to scan through huge numbers of news articles to find related articles of interest, which is a tedious and often an impossible task. In order to solve this problem, we present a novel approach, called InFRSS, which consists of a correlation-based phrase matching (CPM) model and a fuzzy compatibility clustering (FCC) model. CPM can detect RSS news articles containing phrases that are the same as well as semantically alike, and dictate the degrees …

Go to article

Network Formation Using Ant Colony Optimization -- A Systematic Review, Steven C. Oimoen, Gilbert L. Peterson, Kenneth M. Hopkinson Jan 2008

Network Formation Using Ant Colony Optimization -- A Systematic Review, Steven C. Oimoen, Gilbert L. Peterson, Kenneth M. Hopkinson

Faculty Publications

A significant area of research in the field of hybrid communications is the Network Design Problem (NDP) [1]. The NDP is an NP complete problem [1] that focuses on identifying the optimal network topology for transmitting commodities between nodes, under constraints such as bandwidth, limited compatible directed channels, and link and commodity costs. The NDP focuses on designing a flexible network while trying to achieve optimal flow or routing. If a link (or arc) is used, then an associated fixed cost of the edge is incurred. In addition, there is a cost for using the arc depending on the flow. …

Go to article

Learning Policies For Embodied Virtual Agents Through Demonstration, Jonathan Dinerstein, Parris K. Egbert, Dan A. Ventura Jan 2008

Learning Policies For Embodied Virtual Agents Through Demonstration, Jonathan Dinerstein, Parris K. Egbert, Dan A. Ventura

Faculty Publications

Although many powerful AI and machine learning techniques exist, it remains difficult to quickly create AI for embodied virtual agents that produces visually lifelike behavior. This is important for applications (e.g., games, simulators, interactive displays) where an agent must behave in a manner that appears human-like. We present a novel technique for learning reactive policies that mimic demonstrated human behavior. The user demonstrates the desired behavior by dictating the agent’s actions during an interactive animation. Later, when the agent is to behave autonomously, the recorded data is generalized to form a continuous state-to-action mapping. Combined with an appropriate animation algorithm …

Go to article

Sentiment Regression: Using Real-Valued Scores To Summarize Overall Document Sentiment, Adam Drake, Eric K. Ringger, Dan A. Ventura Jan 2008

Sentiment Regression: Using Real-Valued Scores To Summarize Overall Document Sentiment, Adam Drake, Eric K. Ringger, Dan A. Ventura

Faculty Publications

In this paper, we consider a sentiment regression problem: summarizing the overall sentiment of a review with a real-valued score. Empirical results on a set of labeled reviews show that real-valued sentiment modeling is feasible, as several algorithms improve upon baseline performance. We also analyze performance as the granularity of the classification problem moves from two-class (positive vs. negative) towards infinite-class (real-valued).

Go to article

A Reductio Ad Absurdum Experiment In Sufficiency For Evaluating (Computational) Creative Systems, Dan A. Ventura Jan 2008

A Reductio Ad Absurdum Experiment In Sufficiency For Evaluating (Computational) Creative Systems, Dan A. Ventura

Faculty Publications

We consider a combination of two recent proposals for characterizing computational creativity and explore the sufficiency of the resultant framework. We do this in the form of a gedanken experiment designed to expose the nature of the framework, what it has to say about computational creativity, how it might be improved and what questions this raises.

Go to article

Automatic Composition Of Themed Mood Pieces, Heather Chan, Dan A. Ventura Jan 2008

Automatic Composition Of Themed Mood Pieces, Heather Chan, Dan A. Ventura

Faculty Publications

Musical harmonization of a given melody is a nontrivial problem; slight variations in instrumentation, voicing, texture, and bass rhythm can lead to significant differences in the mood of the resulting piece. This study explores the possibility of automatic musical composition by using machine learning and statistical natural language processing to tailor a piece to a particular mood using an existing melody.

Go to article

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 Nov 2007

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 …

Go to article

Spilling: Expanding Hand Held Interaction To Touch Table Displays, Jeffrey Clement, Dan R. Olsen Jr., Aaron Pace Oct 2007

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 …

Go to article

A Data-Dependent Distance Measure For Transductive Instance-Based Learning, Jared Lundell, Dan A. Ventura Oct 2007

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.

Go to article

Adtrees For Sequential Data And N-Gram Counting, Robert Van Dam, Dan A. Ventura Oct 2007

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 …

Go to article

Robust Multi-Modal Biometric Fusion Via Multiple Svms, Jonathan Dinerstein, Sabra Dinerstein, Dan A. Ventura Oct 2007

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.

Go to article

Ecological Interfaces For Improving Mobile Robot Teleoperation, Michael A. Goodrich, Curtis W. Nielsen, Robert W. Ricks Oct 2007

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 …

Go to article

Psoda: Better Tasting And Less Filling Than Paup, Hyrum Carroll, Mark J. Clement, Mark Ebbert, Quinn O. Snell Oct 2007

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.

Go to article

Psodascript: Applying Advanced Language Constructs To Open-Source Phylogenetic Search, Hyrum Carroll, Mark J. Clement, Jonathan Krein, Quinn O. Snell, Adam R. Teichert Oct 2007

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.

Go to article

Using Parsimony To Guide Maximum Likelihood Searches, Hyrum Carroll, Mark J. Clement, Timothy O'Connor, Quinn O. Snell, Kenneth Sundberg Oct 2007

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.

Go to article

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 Sep 2007

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 …

Go to article

Parallel Pso Using Mapreduce, Andrew Mcnabb, Christopher K. Monson, Kevin Seppi Sep 2007

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 …

Go to article

A Utile Function Optimizer, James Carroll, Christopher K. Monson, Kevin Seppi Sep 2007

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 …

Go to article

Image-Based Color Schemes, Bryan S. Morse, Daniel Thornton, Qing Xia, John Uibel Sep 2007

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 …

Go to article

Using Author Topic To Detect Insider Threats From Email Traffic, James S. Okolica, Gilbert L. Peterson, Robert F. Mills Sep 2007

Using Author Topic To Detect Insider Threats From Email Traffic, James S. Okolica, Gilbert L. Peterson, Robert F. Mills

Faculty Publications

One means of preventing insider theft is by stopping potential insiders from becoming actual thieves. This article discusses an approach to assist managers in identifying potential insider threats. By using the Author Topic [Rosen-Zvi Michal, Griffiths Thomas, Steyvers Mark, Smyth Padhraic. The author-topic model for authors and documents. In: Proceedings of the 20th conference on uncertainty in artificial intelligence; 2004. p. 487–94.] clustering algorithm, we discern employees' interests from their daily emails. These interests then provide a means to create an implicit and an explicit social network graph. This approach locates potential insiders by finding individuals who either (1) feel …

Go to article

First Prev Next Last