Physical Sciences and Mathematics Commons^™

An Estimation Theory Approach To Detection And Ranging Of Obscured Targets In 3-D Ladar Data, Charles R. Burris

Theses and Dissertations

The purpose of this research is to develop an algorithm to detect obscured images in 3-D LADAR data. The real data used for this research was gathered using a FLASH LADAR system under development at AFRL/SNJM. The system transmits light with a wavelength of 1.55 micrometers and produces 20 128 X 128 temporally resolved images from the return pulse separated by less than 2 nanoseconds in time. New algorithms for estimating the range to a target in 3-D FLASH LADAR data were developed. Results from processing real data are presented and compared to the traditional correlation receiver for extracting ranges …

Toward The Static Detection Of Deadlock In Java Software, Jose E. Fadul

Theses and Dissertations

Concurrency is the source of many real-world software reliability and security problems. Concurrency defects are difficult to detect because they defy conventional software testing techniques due to their non-local and non-deterministic nature. We focus on one important aspect of this problem: static detection of the possibility of deadlock - a situation in which two or more processes are prevented from continuing while each waits for resources to be freed by the continuation of the other. This thesis proposes a flow-insensitive interprocedural static analysis that detects the possibility that a program can deadlock at runtime. Our analysis proceeds in two steps. …

Crosscutting Score: An Indicator Metric For Aspect Orientation, Subhajit Datta

Research Collection School Of Computing and Information Systems

Aspect Oriented Programming (AOP) provides powerful techniques for modeling and implementing enterprise software systems. To leverage its full potential, AOP needs to be perceived in the context of existing methodologies such as Object Oriented Programming (OOP). This paper addresses an important question for AOP practitioners - how to decide whether a component is best modeled as a class or an aspect? Towards that end, we present an indicator metric, the Crosscutting Score and a method for its calculation and interpretation. We will illustrate our approach through a sample calculation.

Optimization Of A Multi-Echelon Repair System Via Generalized Pattern Search With Ranking And Selection: A Computational Study, Derek D. Tharaldson

Theses and Dissertations

With increasing developments in computer technology and available software, simulation is becoming a widely used tool to model, analyze, and improve a real world system or process. However, simulation in itself is not an optimization approach. Common optimization procedures require either an explicit mathematical formulation or numerous function evaluations at improving iterative points. Mathematical formulation is generally impossible for problems where simulation is relevant, which are characteristically the types of problems that arise in practical applications. Further complicating matters is the variability in the simulation response which can cause problems in iterative techniques using the simulation model as a function …

A Monocular Vision Based Approach To Flocking, Brian Kirchner

Theses and Dissertations

Flocking is seen in nature as a means for self protection, more efficient foraging, and other search behaviors. Although much research has been done regarding the application of this principle to autonomous vehicles, the majority of the research has relied on GPS information, broadcast communication, an omniscient central controller, or some other form of "global" knowledge. This approach, while effective, has serious drawbacks, especially regarding stealth, reliability, and biological grounding. This research effort uses three Pioneer P2-AT8 robots to achieve flocking behavior without the use of global knowledge. The sensory inputs are limited to two cameras, offset such that the …

Gpnn: Power Studies And Applications Of A Neural Network Method For Detecting Gene-Gene Interactions In Studies Of Human Disease, Alison A. Motsinger, Stephen L. Lee, George Mellick, Marylyn D. Ritchie

Dartmouth Scholarship

The identification and characterization of genes that influence the risk of common, complex multifactorial disease primarily through interactions with other genes and environmental factors remains a statistical and computational challenge in genetic epidemiology. We have previously introduced a genetic programming optimized neural network (GPNN) as a method for optimizing the architecture of a neural network to improve the identification of gene combinations associated with disease risk. The goal of this study was to evaluate the power of GPNN for identifying high-order gene-gene interactions. We were also interested in applying GPNN to a real data analysis in Parkinson's disease.

The Evolution Of Equation-Solving: Linear, Quadratic, And Cubic, Annabelle Louise Porter

Theses Digitization Project

This paper is intended as a professional developmental tool to help secondary algebra teachers understand the concepts underlying the algorithms we use, how these algorithms developed, and why they work. It uses a historical perspective to highlight many of the concepts underlying modern equation solving.

The Convergence Of V-Cycle Multigrid Algorithms For Axisymmetric Laplace And Maxwell Equations, Jay Gopalakrishnan, Joseph E. Pasciak

Mathematics and Statistics Faculty Publications and Presentations

We investigate some simple finite element discretizations for the axisymmetric Laplace equation and the azimuthal component of the axisymmetric Maxwell equations as well as multigrid algorithms for these discretizations. Our analysis is targeted at simple model problems and our main result is that the standard V-cycle with point smoothing converges at a rate independent of the number of unknowns. This is contrary to suggestions in the existing literature that line relaxations and semicoarsening are needed in multigrid algorithms to overcome difficulties caused by the singularities in the axisymmetric Maxwell problems. Our multigrid analysis proceeds by applying the well known regularity …

Hybrid Committee Classifier For A Computerized Colonic Polyp Detection System, Jiang Li, Jianhua Yao, Nicholas Petrick, Ronald M. Summers, Amy K. Hara, Joseph M. Reinhardt (Ed.), Josien P.W. Pluim (Ed.)

Electrical & Computer Engineering Faculty Publications

We present a hybrid committee classifier for computer-aided detection (CAD) of colonic polyps in CT colonography (CTC). The classifier involved an ensemble of support vector machines (SVM) and neural networks (NN) for classification, a progressive search algorithm for selecting a set of features used by the SVMs and a floating search algorithm for selecting features used by the NNs. A total of 102 quantitative features were calculated for each polyp candidate found by a prototype CAD system. 3 features were selected for each of 7 SVM classifiers which were then combined to form a committee of SVMs classifier. Similarly, features …

Unsymmetrical And Symmetrical Sparse Iterative Algorithm With Multiple Right-Hand-Sides Strategies, D. T. Nguyen, A. P. Honrao, G. Hou, O. Akan, O. Baysal

Civil & Environmental Engineering Faculty Publications

Unified unsymmetrical and symmetrical iterative solvers for handling multiple right-hand-side vectors are examined in this work. Efficient computer implementation strategies (to reduce computational time and in-core memory requirements) are proposed. In-core, out-of-core, linear, multiple right hand side (RHS) vectors, non-linear, symmetrical, and unsymmetrical capabilities of the developed software are demonstrated by solving variety of problems selected form different engineering disciplines. Results indicate that the developed algorithm and software is reliable and efficient.

Using Citation Data To Improve Retrieval From Medline, Elmer V Bernstam, Jorge R Herskovic, Yindalon Aphinyanaphongs, Constantin F Aliferis, Madurai G Sriram, William R Hersh

Faculty, Staff and Student Publications

OBJECTIVE: To determine whether algorithms developed for the World Wide Web can be applied to the biomedical literature in order to identify articles that are important as well as relevant. DESIGN AND MEASUREMENTS A direct comparison of eight algorithms: simple PubMed queries, clinical queries (sensitive and specific versions), vector cosine comparison, citation count, journal impact factor, PageRank, and machine learning based on polynomial support vector machines. The objective was to prioritize important articles, defined as being included in a pre-existing bibliography of important literature in surgical oncology. RESULTS Citation-based algorithms were more effective than noncitation-based algorithms at identifying important articles. …

Lattice Quantum Algorithm For The Schrodinger Wave Equation In 2+1 Dimensions With A Demonstration By Modeling Soliton Instabilities, Jeffrey Yepez, George Vahala, Linda L. Vahala

Electrical & Computer Engineering Faculty Publications

A lattice-based quantum algorithm is presented to model the non-linear Schrödinger-like equations in 2 + 1 dimensions. In this lattice-based model, using only 2 qubits per node, a sequence of unitary collide (qubit-qubit interaction) and stream (qubit translation) operators locally evolve a discrete field of probability amplitudes that in the long-wavelength limit accurately approximates a non-relativistic scalar wave function. The collision operator locally entangles pairs of qubits followed by a streaming operator that spreads the entanglement throughout the two dimensional lattice. The quantum algorithmic scheme employs a non-linear potential that is proportional to the moduli square of the wave function. …

Principal Component Analysis For Predicting Transcription-Factor Binding Motifs From Array-Derived Data, Yunlong Liu, Matthew P Vincenti, Hiroki Yokota

Dartmouth Scholarship

The responses to interleukin 1 (IL-1) in human chondrocytes constitute a complex regulatory mechanism, where multiple transcription factors interact combinatorially to transcription-factor binding motifs (TFBMs). In order to select a critical set of TFBMs from genomic DNA information and an array-derived data, an efficient algorithm to solve a combinatorial optimization problem is required. Although computational approaches based on evolutionary algorithms are commonly employed, an analytical algorithm would be useful to predict TFBMs at nearly no computational cost and evaluate varying modelling conditions. Singular value decomposition (SVD) is a powerful method to derive primary components of a given matrix. Applying SVD …

Using Genetic Algorithms To Map First-Principles Results To Model Hamiltonians: Application To The Generalized Ising Model For Alloys, Gus L. W. Hart, Volker Blum, Michael J. Walorski, Alex Zunger

Faculty Publications

The cluster expansion method provides a standard framework to map first-principles generated energies for a few selected configurations of a binary alloy onto a finite set of pair and many-body interactions between the alloyed elements. These interactions describe the energetics of all possible configurations of the same alloy, which can hence be readily used to identify ground state structures and, through statistical mechanics solutions, find finite-temperature properties. In practice, the biggest challenge is to identify the types of interactions which are most important for a given alloy out of the many possibilities. We describe a genetic algorithm which automates this …

Boosted Decision Trees For Word Recognition In Handwritten Document Retrieval, Nicholas Howe, Toni M. Rath, R. Manmatha

Computer Science: Faculty Publications

Recognition and retrieval of historical handwritten material is an unsolved problem. We propose a novel approach to recognizing and retrieving handwritten manuscripts, based upon word image classification as a key step. Decision trees with normalized pixels as features form the basis of a highly accurate AdaBoost classifier, trained on a corpus of word images that have been resized and sampled at a pyramid of resolutions. To stem problems from the highly skewed distribution of class frequencies, word classes with very few training samples are augmented with stochastically altered versions of the originals. This increases recognition performance substantially. On a standard …

Hot Event Detection And Summarization By Graph Modeling And Matching, Yuxin Peng, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

This paper proposes a new approach for hot event detection and summarization of news videos. The approach is mainly based on two graph algorithms: optimal matching (OM) and normalized cut (NC). Initially, OM is employed to measure the visual similarity between all pairs of events under the one-to-one mapping constraint among video shots. Then, news events are represented as a complete weighted graph and NC is carried out to globally and optimally partition the graph into event clusters. Finally, based on the cluster size and globality of events, hot events can be automatically detected and selected as the summaries of …

Live Data Views: Programming Pervasive Applications That Use “Timely” And “Dynamic” Data, Jay Black, Paul Castro, Archan Misra, Jerome White

Research Collection School Of Computing and Information Systems

In the absence of generic programming abstractions for dynamic data in most enterprise programming environments, individual applications treat data streams as a special case requiring custom programming. With the growing number of live data sources such as RSS feeds, messaging and presence servers, multimedia streams, and sensor data. a general-purpose client-server programming model is needed to easily incorporate live data into applications. In this paper, we present Live Data Views, a programming abstraction that represents live data as a time-windowed view over a set of data streams. Live Data Views allow applications to create and retrieve stateful abstractions of dynamic …

Some Nonparametric And Semiparametric Methods For Discriminant Analysis., Anil Kumar Ghosh Dr.

Doctoral Theses

Discriminant analysis (see e.g., Devijver and Kittler, 1982; Duda, Hart and Stork, 2000; Hastle, Tibahirani and Friedman, 2001) deals with the separation of different groups of obaervationa and allocation of a new oboervation to one of the previously delined grouga. In a J-class discriminant analysis problem, we usually hae a training sample of the form {(xk, ck) : k = 1,2,...,N}, where xk = (Ik1,Ik2,...J) is a d-dimensional measarement vector, and ca € {1,2,...,J} is its class label. On the basis of thia training sample, one aims to form a decision rule d(x) : Rd + (1,2,...,J} for clasifying the …

Quadratic Regression Analysis For Gene Discovery And Pattern Recognition For Non-Cyclic Short Time-Course Microarray Experiments, Hua Liu, Sergey Tarima, Aaron S. Borders, Thomas V. Getchell, Marilyn L. Getchell, Arnold J. Stromberg

Statistics Faculty Publications

BACKGROUND: Cluster analyses are used to analyze microarray time-course data for gene discovery and pattern recognition. However, in general, these methods do not take advantage of the fact that time is a continuous variable, and existing clustering methods often group biologically unrelated genes together.

RESULTS: We propose a quadratic regression method for identification of differentially expressed genes and classification of genes based on their temporal expression profiles for non-cyclic short time-course microarray data. This method treats time as a continuous variable, therefore preserves actual time information. We applied this method to a microarray time-course study of gene expression at short …

Hydrogeophysical Investigation At Luxor, Southern Egypt, Ahmed Ismail, Neil Lennart Anderson, J. David Rogers

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Over the past 35 years, the exposed stone foundations of the ancient Egyptian monuments at Luxor have deteriorated at an alarmingly accelerated rate. Accelerated deterioration is attributable to three principal factors: 1) excavation and exposure of foundation stone; 2) construction of the Aswan High Dam; and 3) changes in the regional groundwater regime. In an effort to better elucidate the hydrostratigraphy in the Luxor study area that extends from the River Nile to the boundaries of the Nile Valley and covers about 70 km², a geophysical/hydrological investigation was conducted. Forty Schlumberger vertical electrical soundings (VES), two approximately 6 …

Cryptographic And Combinatorial Properties Of Boolean Functions And S-Boxes., Kishan Chand Gupta Dr.

Doctoral Theses

In this thesis we study combinatorial aspects of Boolean functions and S-boxes with impor- tant cryptographic properties and construct new functions possesing such properties. These have possible applications in the design of private key (symmetric key) cryptosystems.Symmetric key cryptosystems are broadly divided into two classes.1. Stream Ciphers,2. Block Ciphers.Some recent proposals of stream ciphers are SNOW [37], SCREAM [52], TURING (98], MUGI (117), HBB (102], RABBIT (9), HELIX (38] and some proposals of block ciphers are DES, AES, RC6 [97), MARS (12], SERPENT (6], TWOFISH (104].In stream cipher cryptography a pseudorandom sequence of bits of length cqual to the message …

An Efficient Scheme For Authenticating Public Keys In Sensor Networks, Wenliang Du, Ronghua Wang, Peng Ning

Electrical Engineering and Computer Science - All Scholarship

With the advance of technology, Public Key Cryptography (PKC) will sooner or later be widely used in wireless sensor networks. Recently, it has been shown that the performance of some public key algorithms, such as Elliptic Curve Cryptography (ECC), is already close to being practical on sensor nodes. However, the energy consumption of PKC is still expensive, especially compared to symmetric-key algorithms. To maximize the lifetime of batteries, we should minimize the use of PKC whenever possible in sensor networks. This paper investigates how to replace one of the important PKC operations–the public key authentication–with symmetric key operations that are …

Using Incomplete Citation Data For Medline Results Ranking, Jorge R Herskovic, Elmer V Bernstam

Faculty, Staff and Student Publications

Information overload is a significant problem for modern medicine. Searching MEDLINE for common topics often retrieves more relevant documents than users can review. Therefore, we must identify documents that are not only relevant, but also important. Our system ranks articles using citation counts and the PageRank algorithm, incorporating data from the Science Citation Index. However, citation data is usually incomplete. Therefore, we explore the relationship between the quantity of citation information available to the system and the quality of the result ranking. Specifically, we test the ability of citation count and PageRank to identify "important articles" as defined by experts …

Analysis Of Oligonucleotide Array Experiments With Repeated Measures Using Mixed Models, Hao Li, Constance L. Wood, Thomas V. Getchell, Marilyn L. Getchell, Arnold J. Stromberg

Statistics Faculty Publications

BACKGROUND: Two or more factor mixed factorial experiments are becoming increasingly common in microarray data analysis. In this case study, the two factors are presence (Patients with Alzheimer's disease) or absence (Control) of the disease, and brain regions including olfactory bulb (OB) or cerebellum (CER). In the design considered in this manuscript, OB and CER are repeated measurements from the same subject and, hence, are correlated. It is critical to identify sources of variability in the analysis of oligonucleotide array experiments with repeated measures and correlations among data points have to be considered. In addition, multiple testing problems are more …

Two-Loop Bethe Logarithms For Higher Excited S Levels, Ulrich D. Jentschura

Physics Faculty Research & Creative Works

Processes mediated by two virtual low-energy photons contribute quite significantly to the energy of hydrogenic S states. The corresponding level shift is of the order of ( α / π )² ( Z α )⁶ m_ec² and may be ascribed to a two-loop generalization of the Bethe logarithm. For 1 S and 2 S states, the correction has recently been evaluated by Pachucki and Jentschura [Phys. Rev. Lett. 91, 113005 (2003)]. Here, we generalize the approach to higher excited S states, which in contrast to the 1 S and 2 S states can decay to …

Integrated Coverage And Connectivity Configuration For Energy Conservation In Sensor Networks, Guoliang Xing, Xiaorui Wang, Yuanfang Zhang, Chenyang Lu, Robert Pless, Christopher Gill

All Computer Science and Engineering Research

An effective approach for energy conservation in wireless sensor networks is scheduling sleep intervals for extraneous nodes, while the remaining nodes stay active to provide continuous service. For the sensor network to operate successfully, the active nodes must maintain both sensing coverage and network connectivity. Fur-thermore, the network must be able to configure itself to any feasible degrees of coverage and connectivity in order to support different applications and environments with diverse requirements. This paper presents the design and analysis of novel protocols that can dynamically configure a network to achieve guaranteed degrees of coverage and connectivity. This work differs …

Pattern Search Ranking And Selection Algorithms For Mixed-Variable Optimization Of Stochastic Systems, Todd A. Sriver

Theses and Dissertations

A new class of algorithms is introduced and analyzed for bound and linearly constrained optimization problems with stochastic objective functions and a mixture of design variable types. The generalized pattern search (GPS) class of algorithms is extended to a new problem setting in which objective function evaluations require sampling from a model of a stochastic system. The approach combines GPS with ranking and selection (R&S) statistical procedures to select new iterates. The derivative-free algorithms require only black-box simulation responses and are applicable over domains with mixed variables (continuous, discrete numeric, and discrete categorical) to include bound and linear constraints on …

Some Statistical Contributions To The Analysis Of Human Genome Diversity And Evolution., Analabha Basu Dr.

Doctoral Theses

The work embodied in this thesis pertains to human population genetics. In particular, the overarching goals of this thesis are to contribute to the understanding of genomic diversity of human populations and to the development of statistical methods for making inferences in genome diversity studies. With these two goals in mind, we have carried out a detailed statistical analysis of genomic data on a large number of ethnic populations of India, generated in the laboratory of the Anthropology & Human Genetics Unit, Indian Statistical Institute, Kolkata. Additionally, wherever relevant, we have compared our data with those collated from the published …

A Subgroup Algorithm To Identify Cross-Rotation Peaks Consistent With Non-Crystallographic Symmetry, Ryan H. Lilien, Chris Bailey-Kellogg, Amy C. Anderson, Bruce R. Donald

Dartmouth Scholarship

Molecular replacement (MR) often plays a prominent role in determining initial phase angles for structure determination by X-ray crystallography. In this paper, an efficient quaternion-based algorithm is presented for analyzing peaks from a cross-rotation function in order to identify model orientations consistent with proper non-crystallographic symmetry (NCS) and to generate proper NCS-consistent orientations missing from the list of cross-rotation peaks. The algorithm, CRANS, analyzes the rotation differences between each pair of cross-rotation peaks to identify finite subgroups. Sets of rotation differences satisfying the subgroup axioms correspond to orientations compatible with the correct proper NCS. The CRANS algorithm was first …

Heuristic Continuous Base Flow Separation, Jozsef Szilagyi

School of Natural Resources: Faculty Publications

No abstract provided.