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 421 - 450 of 663

Full-Text Articles in Computer Sciences

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

Using Fuzzy-Word Correlation Factors To Compute Document Similarity Based On Phrase Matching, Jun Won Lee, Yiu-Kai D. Ng Aug 2007

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 …

Go to article

A Dynamic Attribute-Based Load Shedding Scheme For Data Stream Management Systems, Amit Ahuja, Yiu-Kai D. Ng Jul 2007

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 …

Go to article

An Artificial Immune System-Inspired Multiobjective Evolutionary Algorithm With Application To The Detection Of Distributed Computer Network Intrusions, Charles R. Haag, Gary B. Lamont, Paul D. L. Williams, Gilbert L. Peterson Jul 2007

An Artificial Immune System-Inspired Multiobjective Evolutionary Algorithm With Application To The Detection Of Distributed Computer Network Intrusions, Charles R. Haag, Gary B. Lamont, Paul D. L. Williams, Gilbert L. Peterson

Faculty Publications

Today's signature-based intrusion detection systems are reactive in nature and storage-limited. Their operation depends upon catching an instance of an intrusion or virus and encoding it into a signature that is stored in its anomaly database, providing a window of vulnerability to computer systems during this time. Further, the maximum size of an Internet Protocol-based message requires the database to be huge in order to maintain possible signature combinations. In order to tighten this response cycle within storage constraints, this paper presents an innovative Artificial Immune System-inspired Multiobjective Evolutionary Algorithm. This distributed intrusion detection system (IDS) is intended to measure …

Go to article

Genetic Evolution Of Hierarchical Behavior Structures, Brian G. Woolley, Gilbert L. Peterson Jul 2007

Genetic Evolution Of Hierarchical Behavior Structures, Brian G. Woolley, Gilbert L. Peterson

Faculty Publications

The development of coherent and dynamic behaviors for mobile robots is an exceedingly complex endeavor ruled by task objectives, environmental dynamics and the interactions within the behavior structure. This paper discusses the use of genetic programming techniques and the unified behavior framework to develop effective control hierarchies using interchangeable behaviors and arbitration components. Given the number of possible variations provided by the framework, evolutionary programming is used to evolve the overall behavior design. Competitive evolution of the behavior population incrementally develops feasible solutions for the domain through competitive ranking. By developing and implementing many simple behaviors independently and then evolving …

Go to article

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 Jun 2007

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 …

Go to article

Probabilistic Searching Using A Small Unmanned Aerial Vehicle, Steven R. Hansen, Timothy W. Mclain, Michael A. Goodrich May 2007

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 …

Go to article

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 May 2007

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 …

Go to article

Multi-Class Classification Averaging Fusion For Detecting Steganography, Benjamin M. Rodriguez, Gilbert L. Peterson, Sos S. Agaian Apr 2007

Multi-Class Classification Averaging Fusion For Detecting Steganography, Benjamin M. Rodriguez, Gilbert L. Peterson, Sos S. Agaian

Faculty Publications

Multiple classifier fusion has the capability of increasing classification accuracy over individual classifier systems. This paper focuses on the development of a multi-class classification fusion based on weighted averaging of posterior class probabilities. This fusion system is applied to the steganography fingerprint domain, in which the classifier identifies the statistical patterns in an image which distinguish one steganography algorithm from another. Specifically we focus on algorithms in which jpeg images provide the cover in order to communicate covertly. The embedding methods targeted are F5, JSteg, Model Based, OutGuess, and StegHide. The developed multi-class steganalvsis system consists of three levels: (1) …

Go to article

Steganalysis Feature Improvement Using Expectation Maximization, Benjamin M. Rodriguez, Gilbert L. Peterson, Sos S. Agaian Apr 2007

Steganalysis Feature Improvement Using Expectation Maximization, Benjamin M. Rodriguez, Gilbert L. Peterson, Sos S. Agaian

Faculty Publications

No abstract provided.

Go to article

Steganography Anomaly Detection Using Simple One Class Classification, Benjamin M. Rodriguez, Gilbert L. Peterson, Sos S. Agaian Apr 2007

Steganography Anomaly Detection Using Simple One Class Classification, Benjamin M. Rodriguez, Gilbert L. Peterson, Sos S. Agaian

Faculty Publications

No abstract provided.

Go to article

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 Mar 2007

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 …

Go to article

Interactive Image Repair With Assisted Structure And Texture Completion, Teryl Arnold, Bryan S. Morse Feb 2007

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; …

Go to article

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 Feb 2007

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 …

Go to article

Human–Robot Interaction: A Survey, Michael A. Goodrich, Alan C. Schultz Feb 2007

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 …

Go to article

Clustering Streaming Music Via The Temporal Similarity Of Timbre, Jacob Merrell, Bryan S. Morse, Dan A. Ventura Jan 2007

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.

Go to article

A Cognitive Robotics Approach To Comprehending Human Language And Behaviors, Deryle W. Lonsdale, D. Paul Benjamin, Damian Lyons Jan 2007

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.

Go to article

Generating Ontologies Via Language Components And Ontology Reuse, Deryle W. Lonsdale, Yihong Ding, David W. Embley, Martin Hepp, Li Xu Jan 2007

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 …

Go to article

Analogical Modeling: An Update, Deryle W. Lonsdale, David Eddington Jan 2007

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 …

Go to article

Cybercraft: Protecting Electronic Systems With Lightweight Agents, Daniel R. Karrels, Gilbert L. Peterson Jan 2007

Cybercraft: Protecting Electronic Systems With Lightweight Agents, Daniel R. Karrels, Gilbert L. Peterson

Faculty Publications

The United States military is seeking new and innovative methods for securing and maintaining its computing and network resources locally and world-wide. This document presents a work-in-progress research thrust toward building a system capable of meeting many of the US military’s network security and sustainment requirements. The system is based on a Distributed Multi-Agent System (DMAS), that is secure, small, and scalable to the large networks found in the military. It relies on a staged agent architecture capable of dynamic configuration to support changing mission environments. These agents are combined into Hierarchical Peer-to-Peer (HP2P) networks to provide scalable solutions. They …

Go to article

Eliminating Redundant And Less-Informative Rss News Articles Based On Word Similarity And A Fuzzy Equivalence Relation, Ian Garcia, Yiu-Kai D. Ng Nov 2006

Eliminating Redundant And Less-Informative Rss News Articles Based On Word Similarity And A Fuzzy Equivalence Relation, Ian Garcia, Yiu-Kai D. Ng

Faculty Publications

The Internet has marked this era as the information age. There is no precedent in the amazing amount of information, especially network news, that can be accessed by Internet users these days. As a result, the problem of seeking information in online news articles is not the lack of them but being overwhelmed by them. This brings huge challenges in processing online news feeds, e.g., how to determine which news article is important, how to determine the quality of each news article, and how to filter irrelevant and redundant information. In this paper, we propose a method for filtering redundant …

Go to article

An Improved Distance Heuristic Function For Directed Software Model Checking, Eric G. Mercer, Neha Rungta Nov 2006

An Improved Distance Heuristic Function For Directed Software Model Checking, Eric G. Mercer, Neha Rungta

Faculty Publications

State exploration in directed software model checking is guided using a heuristic function to move states near errors to the front of the search queue. Distance heuristic functions rank states based on the number of transitions needed to move the current program state into an error location. Lack of calling context information causes the heuristic function to underestimate the true distance to the error; however, inlining functions at call sites in the control flow graph to capture calling context leads to an exponential growth in the computation. This paper presents a new algorithm that implicitly inlines functions at call sites …

Go to article

Large Grain Size Stochastic Optimization Alignment, Hyrum Carroll, Mark J. Clement, Perry Ridge, Dan Sneddon, Quinn O. Snell Oct 2006

Large Grain Size Stochastic Optimization Alignment, Hyrum Carroll, Mark J. Clement, Perry Ridge, Dan Sneddon, Quinn O. Snell

Faculty Publications

DNA sequence alignment is a critical step in identifying homology between organisms. The most widely used alignment program, ClustalW, is known to suffer from the local minima problem, where suboptimal guide trees produce incorrect gap insertions. The optimization alignment approach, has been shown to be effective in combining alignment and phylogenetic search in order to avoid the problems associated with poor guide trees. The optimization alignment algorithm operates at a small grain size, aligning each tree found, wasting time producing multiple sequence alignments for suboptimal trees. This research develops and analyzes a large grain size algorithm for optimization alignment that …

Go to article

Effects Of Gap Open And Gap Extension Penalties, Hyrum Carroll, Mark J. Clement, Perry Ridge, Quinn O. Snell Oct 2006

Effects Of Gap Open And Gap Extension Penalties, Hyrum Carroll, Mark J. Clement, Perry Ridge, Quinn O. Snell

Faculty Publications

Fundamental to multiple sequence alignment algorithms is modeling insertions and deletions (gaps). The most prevalent model is to use gap open and gap extension penalties. While gap open and gap extension penalties are well understood conceptually, their effects on multiple sequence alignment, and consequently on phylogeny scores are not as well understood. We use exhaustive phylogeny searching to explore the effects of varying the gap open and gap extension penalties for three nuclear ribosomal data sets. Particular attention is given to optimal phylogeny scores for 200 alignments of a range of gap open and gap extension penalties and their respective …

Go to article

Pharmacogenomics: Analyzing Snps In The Cyp2d6 Gene Using Amino Acid Properties, Wesley A. Beckstead, Mark J. Clement, Mark Ebbert, David Mcclellan, Timothy O'Connor Oct 2006

Pharmacogenomics: Analyzing Snps In The Cyp2d6 Gene Using Amino Acid Properties, Wesley A. Beckstead, Mark J. Clement, Mark Ebbert, David Mcclellan, Timothy O'Connor

Faculty Publications

Each year people suffer from complications of adverse drug reactions, but with pharmacogenomics there is hope to prevent thousands of these people from suffering or dying needlessly. The CYP2D6 gene is responsible for metabolizing a large portion of these drugs. Because of the gene’s importance, various approaches have been taken to analyze CYP2D6 and single nucleotide polymorphisms (SNPs) throughout its sequence. This study introduces a novel method to analyze the effects of SNPs on encoded protein complexes by focusing on the biochemical properties of each nonsynonymous substitution using the program TreeSAAP. We apply this technique to SNPs found in the …

Go to article

Steganalysis Embedding Percentage Determination With Learning Vector Quantization, Benjamin M. Rodriguez, Gilbert L. Peterson, Kenneth W. Bauer, Sos S. Agaian Oct 2006

Steganalysis Embedding Percentage Determination With Learning Vector Quantization, Benjamin M. Rodriguez, Gilbert L. Peterson, Kenneth W. Bauer, Sos S. Agaian

Faculty Publications

Steganography (stego) is used primarily when the very existence of a communication signal is to be kept covert. Detecting the presence of stego is a very difficult problem which is made even more difficult when the embedding technique is not known. This article presents an investigation of the process and necessary considerations inherent in the development of a new method applied for the detection of hidden data within digital images. We demonstrate the effectiveness of learning vector quantization (LVQ) as a clustering technique which assists in discerning clean or non-stego images from anomalous or stego images. This comparison is conducted …

Go to article

Digital Roots Of Human Relations: Enabling Technologies For Family History And Genealogical Research, William A. Barrett Sep 2006

Digital Roots Of Human Relations: Enabling Technologies For Family History And Genealogical Research, William A. Barrett

Faculty Publications

Flowing out of a Computer Science research lab on the third floor of the Talmage Building is a wellspring of enabling technologies for family history and genealogical research. Here, computer science students, working under the direction of Dr. Tom Sederberg and Dr. Bill Barrett are creating software tools to help individuals with their family history research so that people everywhere can seek out their ancestors and perform vital ordinances in their behalf, as desired. These tools include visualization of an entire pedigree on a single (large) sheet of paper, the ability to automatically calculate if and how two or more …

Go to article

Fuzzy State Aggregation And Policy Hill Climbing For Stochastic Environments, Dean C. Wardell, Gilbert L. Peterson Sep 2006

Fuzzy State Aggregation And Policy Hill Climbing For Stochastic Environments, Dean C. Wardell, Gilbert L. Peterson

Faculty Publications

Reinforcement learning is one of the more attractive machine learning technologies, due to its unsupervised learning structure and ability to continually learn even as the operating environment changes. Additionally, by applying reinforcement learning to multiple cooperative software agents (a multi-agent system) not only allows each individual agent to learn from its own experience, but also opens up the opportunity for the individual agents to learn from the other agents in the system, thus accelerating the rate of learning. This research presents the novel use of fuzzy state aggregation, as the means of function approximation, combined with the fastest policy hill …

Go to article

A Constructive Incremental Learning Algorithm For Binary Classification Tasks, Christophe G. Giraud-Carrier, Tony R. Martinez Jul 2006

A Constructive Incremental Learning Algorithm For Binary Classification Tasks, Christophe G. Giraud-Carrier, Tony R. Martinez

Faculty Publications

This paper presents i-AA1*, a constructive, incremental learning algorithm for a special class of weightless, self-organizing networks. In i-AA1*, learning consists of adapting the nodes’ functions and the network’s overall topology as each new training pattern is presented. Provided the training data is consistent, computational complexity is low and prior factual knowledge may be used to “prime” the network and improve its predictive accuracy. Empirical generalization results on both toy problems and more realistic tasks demonstrate promise.

Go to article

First Prev Next Last