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Faculty Publications

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Articles 601 - 630 of 663

Full-Text Articles in Computer Sciences

Model Predictive Satisficing Fuzzy Logic Control, Richard L. Frost, Michael A. Goodrich, Wynn C. Stirling Jun 1999

Model Predictive Satisficing Fuzzy Logic Control, Richard L. Frost, Michael A. Goodrich, Wynn C. Stirling

Faculty Publications

Model-predictive control, which is an alternative to conventional optimal control, provides controller solutions to many constrained and nonlinear control problems. However, even when a good model is available, it may be necessary for an expert to specify the relationship between local model predictions and global system performance. We present a satisficing fuzzy logic controller that is based on a receding control horizon, but which employs a fuzzy description of system consequences via model predictions. This controller considers the gains and losses associated with each control action, is compatible with robust design objectives, and permits flexible defuzzifier design. We demonstrate the …

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Multiscale Image Registration Using Scale Trace Correlation, Bruce B. Hansen, Bryan S. Morse Jun 1999

Multiscale Image Registration Using Scale Trace Correlation, Bruce B. Hansen, Bryan S. Morse

Faculty Publications

This paper presents a method for registering images at different magnifications (scales) by treating the problem not only as one of scaling the image coordinates but also as one inherently involving multiresolution information. While some existing methods for multiresolution registration do consider the way the resolution (scale) affects the image, they often consider the image one scale at a time, using geometric properties within that scale. Others use multiscale information, usually to produce more robust results, but only to register same-magnification images (e.g., stereo). A scale trace is the set of values that a single pixel takes on as magnification …

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Toboggan-Based Intelligent Scissors With A Four-Parameter Edge Model, William A. Barrett, Eric N. Mortensen Jun 1999

Toboggan-Based Intelligent Scissors With A Four-Parameter Edge Model, William A. Barrett, Eric N. Mortensen

Faculty Publications

Intelligent Scissors is an interactive image segmentation tool that allows a user to select piece-wise globally optimal contour segments that correspond to a desired object boundary. We present a new and faster method of computing the optimal path by over-segmenting the image using tobogganing and then imposing a weighted planar graph on top of the resulting region boundaries. The resulting region-based graph is many times smaller than the previous pixel-based graph, thus providing faster graph searches and immediate user interaction. Further, tobogganing provides an new systematic and predictable framework for computing edge model parameters, allowing subpixel localization as well as …

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Performance Surface Prediction For Wan-Based Clusters, Mark J. Clement, J. Kelly Flanagan, Glenn M. Judd, Bryan S. Morse, Joy L. Peterson Jan 1999

Performance Surface Prediction For Wan-Based Clusters, Mark J. Clement, J. Kelly Flanagan, Glenn M. Judd, Bryan S. Morse, Joy L. Peterson

Faculty Publications

The last five years have been a period of exponential growth in the number of machines connected to the Internet and the speed at which these machines communicate. The infrastructure is now in place to consider a nationwide cluster of workstations as a viable parallel processing platform. In order to achieve acceptable performance on this kind of a machine, performance prediction tools must provide information on where to place computational objects. Incorrect object placement can result in poor performance and congestion in the network. This research develops a new paradigm for predicting performance in the Wide Area Network (WAN) based …

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A Work Minimization Approach To Image Morphing, Peisheng Gao, Thomas W. Sederberg Dec 1998

A Work Minimization Approach To Image Morphing, Peisheng Gao, Thomas W. Sederberg

Faculty Publications

An algorithm is presented for morphing two images, often with little or no user interaction. For two similar images (such as different faces against a neutral background) the algorithm generally can create a pleasing morph completely automatically. The algorithm seeks the minimum work to deform one image into the other, where work is a function of the amount of warping and recoloration. A hierarchical method for finding a minimal work solution is invoked. Anchor point constraints are satisfied by imposing penalties on deformations that disobey these constraints. Good results can be obtained in less than ten seconds for 256 x …

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A Theory Of Satisficing Decisions And Control, Richard L. Frost, Michael A. Goodrich, Wynn C. Stirling Nov 1998

A Theory Of Satisficing Decisions And Control, Richard L. Frost, Michael A. Goodrich, Wynn C. Stirling

Faculty Publications

The existence of an optimal control policy and the techniques for finding it are grounded fundamentally in a global perspective. These techniques can be of limited value when the global behavior of the system is difficult to characterize, as it may be when the system is nonlinear, when the input is constrained, or when only partial information is available regarding system dynamics or the environment. Satisficing control theory is an alternative approach that is compatible with the limited rationality associated with such systems. This theory is extended by the introduction of the notion of strong satisficing to provide a systematic …

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Isophote-Based Interpolation, Bryan S. Morse, Duane Schwartzwald Oct 1998

Isophote-Based Interpolation, Bryan S. Morse, Duane Schwartzwald

Faculty Publications

Standard methods for image interpolation are based on smoothly fitting the image intensity surface. Recent edge-directed interpolation methods add limited geometric information (edge maps) to build more accurate and visually appealing interpolations at key contours in the image. This paper presents a method for geometry-based interpolation that smoothly fits the isophote (intensity level curve) contours at all points in the image rather than just at selected contours. By using level set methods for curve evolution, no explicit extraction or representation of these contours is required (unlike earlier edge-directed methods). The method uses existing interpolation techniques as an initial approximation and …

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Analysis Of The Interpolation Error Between Multiresolution Images, Bryan S. Morse Oct 1998

Analysis Of The Interpolation Error Between Multiresolution Images, Bryan S. Morse

Faculty Publications

Many rendering or image-analysis systems require calculation of versions of an image at lesser resolutions than the original. Because the filtering required to perform such calculations accurately cannot typically be done in real time, many systems use interpolation between images at precalculated resolutions. This discrete sampling of the scale component of multiresolution image spaces is analogous to spatial sampling in discrete images. This paper quantifies and bounds the error that can be introduced during such interpolation as a function of the scale-space sampling rate used. A method is presented that uses the diffusion equation to relate spatial derivatives to scale …

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Parallel Linear Congruential Generators With Prime Moduli, Michael Mascagni Jun 1998

Parallel Linear Congruential Generators With Prime Moduli, Michael Mascagni

Faculty Publications

Linear congruential generators (LCGs) remain the most popular method of pseudorandom number generation on digital computers. Ease of implementation has favored implementing LCGs with power-of-two moduli. However, prime modulus LCGs are superior in quality to power-of-two modulus LCGs, and the use of a Mersenne prime minimizes the computational cost of generation. When implemented for parallel computation, quality becomes an even more compelling issue. We use a full-period exponential sum as the measure of stream independence and present a method for producing provably independent streams of LCGs in parallel by utilizing an explicit parameterization of all of the primitive elements module …

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Constructing High Order Perceptrons With Genetic Algorithms, Timothy L. Andersen, Tony R. Martinez May 1998

Constructing High Order Perceptrons With Genetic Algorithms, Timothy L. Andersen, Tony R. Martinez

Faculty Publications

Constructive induction, which is defined to be the process of constructing new and useful features from existing ones, has been extensively studied in the literature. Since the number of possible high order features for any given learning problem is exponential in the number of input attributes (where the order of a feature is defined to be the number of attributes of which it is composed), the main problem faced by constructive induction is in selecting which features to use out of this exponentially large set of potential features. For any feature set chosen the desirable characteristics are minimality and generalization …

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Optimal Control Using A Neural/Evolutionary Hybrid System, Tony R. Martinez, Dan A. Ventura May 1998

Optimal Control Using A Neural/Evolutionary Hybrid System, Tony R. Martinez, Dan A. Ventura

Faculty Publications

One of the biggest hurdles to developing neurocontrollers is the difficulty in establishing good training data for the neural network. We propose a hybrid approach to the development of neurocontrollers that employs both evolutionary computation (EC) and neural networks (NN). EC is used to discover appropriate control actions for specific plant states. The survivors of the evolutionary process are used to construct a training set for the NN. The NN leams the training set, is able to generalize to new plant states, and is then used for neurocontrol. Thus the EC/NN approach combines the broad, parallel search of EC with …

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Quantum Associative Memory With Exponential Capacity, Tony R. Martinez, Dan A. Ventura May 1998

Quantum Associative Memory With Exponential Capacity, Tony R. Martinez, Dan A. Ventura

Faculty Publications

Quantum computation uses microscopic quantum level effects to perrform computational tasks and has produced results that in some cases are exponentially faster than their classical counterparts by taking advantage of quantum parallelism. The unique characteristics of quantum theory may also be used to create a quantum associative memory with a capacity exponential in the number of neurons. This paper covers necessary high-level quantum mechanical ideas and introduces a simple quantum associative memory. Further, it provides discussion, empirical results and directions for future work.

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Resources For Undergraduate User Interface Implementation Courses, Charles J. Welty Ms Apr 1998

Resources For Undergraduate User Interface Implementation Courses, Charles J. Welty Ms

Faculty Publications

It has been estimated that 48% of the code and 50% of the implementation time required in new applications are directly related to the user interface (Myers and Rosson, 1992). Our research shows that most undergraduate courses that consider graphical user interfaces (GUIs) have no implementation component. Most undergraduate programs (85%) that include GUI implementation are offered at the Doctoral II Carnegie classification or above. Appropriate Web and print references and other materials given in this paper will help faculty at smaller institutions offer such courses.

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Breakpoint Skeletal Representation And Compression Of Document Images, William A. Barrett, Bryan S. Morse, Eric N. Mortensen Mar 1998

Breakpoint Skeletal Representation And Compression Of Document Images, William A. Barrett, Bryan S. Morse, Eric N. Mortensen

Faculty Publications

We present a new method for representation and (lossy) compression of bitonal document images. The technique extracts a skeletal medial axis from each object using a true Euclidean distance map of the image and then finds piecewise linear breakpoints in the skeleton to create a breakpoint skeletal representation, bps, (Fig. 1). The bps is encoded for each object as a set of triples {, <Δx2,Δy2,Δr2>, . . . <Δxn,Δyn,Δrn>} where contains the coordinate and distance (radius, r1) of the initial breakpoint from the closest point on the perimeter of the object and <Δxi,Δyi,Δri> represents the difference in location and radius between …

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Electro-Deposition Of Polymer Chains On An Adsorbing Wall: Density Profiles And Wall Coverage, Grace M. Foo, Ras B. Pandey Dec 1997

Electro-Deposition Of Polymer Chains On An Adsorbing Wall: Density Profiles And Wall Coverage, Grace M. Foo, Ras B. Pandey

Faculty Publications

Growth of polymer density in an electro-deposition model of polymer chains on an impenetrable wall is studied on a two dimensional discrete lattice using a Monte Carlo simulation. Polymer-polymer repulsion and polymer-wall attraction for the adsorbing wall (along with the neutral and repulsive interactions) are considered in an external field. Effects of the field strength (B), temperature (T), and chain length (L-c) on the density profile of the polymer chains and wall coverage are investigated. The spatial density profile shows onset of oscillation near the wall at a characteristic field (B-c) which depends on chain length and temperature, In low …

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Bias And The Probability Of Generalization, Tony R. Martinez, D. Randall Wilson Dec 1997

Bias And The Probability Of Generalization, Tony R. Martinez, D. Randall Wilson

Faculty Publications

In order to be useful, a learning algorithm must be able to generalize well when faced with inputs not previously presented to the system. A bias is necessary for any generalization, and as shown by several researchers in recent years, no bias can lead to strictly better generalization than any other when summed over all possible functions or applications. This paper provides examples to illustrate this fact, but also explains how a bias or learning algorithm can be “better” than another in practice when the probability of the occurrence of functions is taken into account. It shows how domain knowledge …

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Dynamic Correlations In Porous Media, J.C. Lee Feb 1997

Dynamic Correlations In Porous Media, J.C. Lee

Faculty Publications

When binary liquid mixtures are infused into various random porous media, past experiment have shown that different media affect the dynamic correlations of concentration fluctuations in different ways. Vycor glasses of relatively small pore size and dilute gels allow the exponential bulk mode to remain in the final ensemble average, but Vycor glasses of vary large pore size do not. We take this to mean that the relaxation time of the bulk mode is spatialIy homogeneous in the two former media but heterogeneous in the latter media. Thus we search for a heterogeneous dynamic mode with an Ising model. We …

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Improved Heterogeneous Distance Functions, Tony R. Martinez, D. Randall Wilson Jan 1997

Improved Heterogeneous Distance Functions, Tony R. Martinez, D. Randall Wilson

Faculty Publications

Instance-based learning techniques typically handle continuous and linear input values well, but often do not handle nominal input attributes appropriately. The Value Difference Metric (VDM) was designed to find reasonable distance values between nominal attribute values, but it largely ignores continuous attributes, requiring discretization to map continuous values into nominal values. This paper proposes three new heterogeneous distance functions, called the Heterogeneous Value Difference Metric (HVDM), the Interpolated Value Difference Metric (IVDM), and the Windowed Value Difference Metric (WVDM). These new distance functions are designed to handle applications with nominal attributes, continuous attributes, or both. In experiments on 48 applications …

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Faster Ray Tracing Using Adaptive Grids, Thomas W. Sederberg, Krysztof S. Klimaszewski Jan 1997

Faster Ray Tracing Using Adaptive Grids, Thomas W. Sederberg, Krysztof S. Klimaszewski

Faculty Publications

A new hybrid approach is presented which outperforms the regular grid technique in scenes with highly irregular object distributions by a factor of hundreds, and combined with an area interpolator, by a factor of thousands. Much has been said about scene independence of different acceleration techniques and the alleged superiority of one approach over another. Several theoretical and practical studies conducted in the past have led to the same conclusion: a space partitioning method that allows the fastest rendering of one scene often fails with another. Specialization may be the answer. This has always been pursued, consciously or not, in …

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A Fertility Channel Model For Post-Correction Of Continuous Speech Recognition, Eric K. Ringger, James F. Allen Oct 1996

A Fertility Channel Model For Post-Correction Of Continuous Speech Recognition, Eric K. Ringger, James F. Allen

Faculty Publications

We have implemented a post-processor called SPEECHPP to correct word-level errors committed by an arbitrary speech recognizer. Applying a noisy-channel model, SPEECHPP uses a Viterbi beam-search that employs language and channel models. Previous work demonstrated that a simple word-for-word channel model was sufficient to yield substantial incieases in word accuracy. This paper demonstrates that some improvements in word accuracy result from augmenting the channel model with an account of word fertility in the channel. This work further demonstrates that a modern continuous speech recognizer can be used in "black-box" fashion for robustly recognizing speech for which the recognizer was not …

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Procedurally Rational Decision-Making And Control, Richard L. Frost, Michael A. Goodrich, Wynn C. Stirling Oct 1996

Procedurally Rational Decision-Making And Control, Richard L. Frost, Michael A. Goodrich, Wynn C. Stirling

Faculty Publications

Substantive rationality requires a decision-maker to be a utility maximizer; under this paradigm, the decision is paramount, and not dependent on the computational process used to obtain it. Procedural rationality is dependent on the method used to make the decision; reasonableness of the procedure is paramount. Well-formed problems are amenable to substantive rationality; ill-formed problems are not, but are amenable to procedural rationality. To qualify as being procedurally rational, a methodology must possess a sound epistemological basis, it must be amenable to a formal design synthesis procedure, and it must be consistent with substantive rationality. Epistemic utility theory forms the …

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Robust Optimization Using Training Set Evolution, Tony R. Martinez, Dan A. Ventura Jun 1996

Robust Optimization Using Training Set Evolution, Tony R. Martinez, Dan A. Ventura

Faculty Publications

Training Set Evolution is an eclectic optimization technique that combines evolutionary computation (EC) with neural networks (NN). The synthesis of EC with NN provides both initial unsupervised random exploration of the solution space as well as supervised generalization on those initial solutions. An assimilation of a large amount of data obtained over many simulations provides encouraging empirical evidence for the robustness of Evolutionary Training Sets as an optimization technique for feedback and control problems.

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A Robust System For Natural Spoken Dialogue, Eric K. Ringger, James F. Allen, Bradford W. Miller, Teresa Sikorski Jun 1996

A Robust System For Natural Spoken Dialogue, Eric K. Ringger, James F. Allen, Bradford W. Miller, Teresa Sikorski

Faculty Publications

This paper describes a system that leads us to believe in the feasibility of constructing natural spoken dialogue systems in task-oriented domains. It specifically addresses the issue of robust interpretation of speech in the presence of recognition errors. Robustness is achieved by a combination of statistical error post-correction, syntactically- and semantically-driven robust parsing, and extensive use of the dialogue context. We present an evaluation of the system using time-to-completion and the quality of the final solution that suggests that most native speakers of English can use the system successfully with virtually no training.

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Heterogeneous Radial Basis Function Networks, Tony R. Martinez, D. Randall Wilson Jun 1996

Heterogeneous Radial Basis Function Networks, Tony R. Martinez, D. Randall Wilson

Faculty Publications

Radial Basis Function (RBF) networks typically use a distance function designed for numeric attributes, such as Euclidean or city-block distance. This paper presents a heterogeneous distance function which is appropriate for applications with symbolic attributes, numeric attributes, or both. Empirical results on 30 data sets indicate that the heterogeneous distance metric yields significantly improved generalization accuracy over Euclidean distance in most cases involving symbolic attributes.

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A Brief Introduction To Formal Methods, Paul E. Black, Kelly M. Hall, Michael D. Jones, Trent N. Larson, Phillip J. Windley May 1996

A Brief Introduction To Formal Methods, Paul E. Black, Kelly M. Hall, Michael D. Jones, Trent N. Larson, Phillip J. Windley

Faculty Publications

As hardware designs grow in size and complexity, current design methods are proving less adequate. Current methods for specification, design, and test are typically empirical or informal, that is, they are based on experience and argument. Formal methods are solidly based on mathematical logic systems and precise rules of inference. Formal methods offer a discipline which complements current methods so designers can successfully meet the demand for high performance systems. Formal methods covers a broad and diverse set of techniques aimed at improving computer correctness. This paper explains the role of specifications and implementation models in formal methods, and different …

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Error Correction Via A Post-Processor For Continuous Speech Recognition, Eric K. Ringger, James F. Allen May 1996

Error Correction Via A Post-Processor For Continuous Speech Recognition, Eric K. Ringger, James F. Allen

Faculty Publications

This paper presents a new technique for overcoming several types of speech recognition errors by post-processing the output of a continuous speech recognizer. The post-processor output contains fewer errors, thereby making interpretation by higher-level modules, such as a parser, in a speech understanding system more reliable. The primary advantage to the post-processing approach over existing approaches for overcoming SR errors lies in its abilityto introduce options that are not available in the SR module’s output. This work provides evidence for the claim that a modern continuous speech recognizer can be used successfully in “black-box” fashion for robustly interpreting spontaneous utterances …

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Compressing Semi-Structured Text Using Hierarchical Phrase Identifications, Dan R. Olsen Jr., Craig G. Nevill-Manning, Ian H. Witten Apr 1996

Compressing Semi-Structured Text Using Hierarchical Phrase Identifications, Dan R. Olsen Jr., Craig G. Nevill-Manning, Ian H. Witten

Faculty Publications

The structure of this paper is as follows. We begin by identifying some characteristics of semi-structured text that have special relevance to data compression. We then give a brief account of a particular large textual database, and describe a compression scheme that exploits its structure. In addition to providing compression, the system gives some insight into the structure of the database. Finally we show how the hierarchical grammar can be generalized, first manually and then automatically, to yield further improvements in compression performance.

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Dynamics Of Binary Liquids In Pores, J.C. Lee Dec 1995

Dynamics Of Binary Liquids In Pores, J.C. Lee

Faculty Publications

A computer simulation is performed to study the dynamics of binary liquids in the pores of Vycor glasses. The pores are modeled with glass walls that form randomly interconnected tunnels. When the relaxation is probed with a particular wavelength, the time autocorrelation function depends on whether or not there is a significant periodic or quasiperiodic structure in the distribution of the walls with that wavelength. If there is not, the relaxation may be fitted as the sum of an exponential term and a nonexponential activated term. If there is, the relaxation shows a long-lasting tail that can be fitted by …

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A Provably Convergent Dynamic Training Method For Multi-Layer Perceptron Networks, Timothy L. Andersen, Tony R. Martinez Sep 1995

A Provably Convergent Dynamic Training Method For Multi-Layer Perceptron Networks, Timothy L. Andersen, Tony R. Martinez

Faculty Publications

This paper presents a new method for training multi-layer perceptron networks called DMP1 (Dynamic Multilayer Perceptron 1). The method is based upon a divide and conquer approach which builds networks in the form of binary trees, dynamically allocating nodes and layers as needed. The individual nodes of the network are trained using a genetic algorithm. The method is capable of handling real-valued inputs and a proof is given concerning its convergence properties of the basic model. Simulation results show that DMP1 performs favorably in comparison with other learning algorithms.

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An Integrated Framework For Learning And Reasoning, Christophe G. Giraud-Carrier, Tony R. Martinez Aug 1995

An Integrated Framework For Learning And Reasoning, Christophe G. Giraud-Carrier, Tony R. Martinez

Faculty Publications

Learning and reasoning are both aspects of what is considered to be intelligence. Their studies within AI have been separated historically, learning being the topic of machine learning and neural networks, and reasoning falling under classical (or symbolic) AI. However, learning and reasoning are in many ways interdependent. This paper discusses the nature of some of these interdependencies and proposes a general framework called FLARE, that combines inductive learning using prior knowledge together with reasoning in a propositional setting. Several examples that test the framework are presented, including classical induction, many important reasoning protocols and two simple expert systems.

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