Digital Commons Network^™

Analysis Of Music Genre Clustering Algorithms, Samuel Walter Stern

Theses and Dissertations

Classification and clustering of music genres has become an increasingly prevalent focusin recent years, prompting a push for research into relevant algorithms. The most successful algorithms have typically applied the Naive Bayes or k-Nearest Neighbors algorithms, or used Neural Networks to perform classification. This thesis seeks to investigate the use of unsupervised clustering algorithms such as K-Means or Hierarchical clustering, and establish their usefulness in comparison to or conjunction with established methods.

Algorithmic Robot Design: Label Maps, Procrustean Graphs, And The Boundary Of Non-Destructiveness, Shervin Ghasemlou

Theses and Dissertations

This dissertation is focused on the problem of algorithmic robot design. The process of designing a robot or a team of robots that can reliably accomplish a task in an environment requires several key elements. How the problem is formulated can play a big role in the design process. The ability of the model to correctly reflect the environment, the events, and different pieces of the problem is crucial. Another key element is the ability of the model to show the relationship between different designs of a single system. These two elements can enable design algorithms to navigate through the …

Evaluating And Improving The Efficiency Of Software And Algorithms For Sequence Data Analysis, Hugh L. Eaves

Theses and Dissertations

With the ever-growing size of sequence data sets, data processing and analysis are an increasingly large portion of the time and money spent on nucleic acid sequencing projects. Correspondingly, the performance of the software and algorithms used to perform that analysis has a direct effect on the time and expense involved. Although the analytical methods are widely varied, certain types of software and algorithms are applicable to a number of areas. Targeting improvements to these common elements has the potential for wide reaching rewards. This dissertation research consisted of several projects to characterize and improve upon the efficiency of several …

Quasinovo: Algorithms For De Novo Peptide Sequencing, James Paul Cleveland

Theses and Dissertations

High-throughput proteomics analysis involves the rapid identification and characterization of large sets of proteins in complex biological samples. Tandem mass spectrometry (MS/MS) has become the leading approach for the experimental identification of proteins. Accurate analysis of the data produced is a computationally challenging process that relies on a complex understanding of molecular dynamics, signal processing, and pattern classification. In this work we address these modeling and classification problems, and introduce an additional data-driven evolutionary information source into the analysis pipeline.

The particular problem being solved is peptide sequencing via MS/MS. The objective in solving this problem is to decipher the …

Blind Deconvolution Through Polarization Diversity Of Long Exposure Imagery, Steven P. James

Theses and Dissertations

The purpose of the algorithm developed in this thesis was to create a post processing method that could resolve objects at low signal levels using polarization diversity and no knowledge of the atmospheric seeing conditions. The process uses a two-channel system, one unpolarized image and one linearly polarized image, in a GEM algorithm to reconstruct the object. Previous work done by Strong showed that a two-channel system using polarization diversity on short exposure imagery could produce images up to twice the diffraction limit. In this research, long exposure images were simulated and a simple Kolmogorov model used. This allowed for …

Range Estimation Algorithm Comparison In 3-D Flash Ladar Data, Steven P. Jordan

Theses and Dissertations

Range estimation algorithms have been applied to Laser Detection and Ranging (LADAR) data to test for accuracy and precision. Data was acquired from Matlab® simulations and an experiment using the Advanced Scientific Concepts 3-D flash LADAR camera. Simulated LADAR data was based on a Gaussian pulse shape model with Poisson noise added. Simulations were performed to test range estimation algorithm performance with respect to waveform position within the range gate. The effectiveness of each algorithm is presented in terms of its average root mean square error and standard deviation in 1000 trials. The measured data experiment examined the effectiveness of …

Algorithms For White-Box Obfuscation Using Randomized Subcircuit Selection And Replacement, Kenneth E. Norman

Theses and Dissertations

Software protection remains an active research area with the goal of preventing adversarial software exploitation such as reverse engineering, tampering, and piracy. Heuristic obfuscation techniques lack strong theoretical underpinnings while current theoretical research highlights the impossibility of creating general, efficient, and information theoretically secure obfuscators. In this research, we consider a bridge between these two worlds by examining obfuscators based on the Random Program Model (RPM). Such a model envisions the use of program encryption techniques which change the black-box (semantic) and white-box (structural) representations of underlying programs. In this thesis we explore the possibilities for white-box transformation. Under an …

Type Ii Quantum Computing Algorithm For Computational Fluid Dynamics, James A. Scoville

Theses and Dissertations

An algorithm is presented to simulate fluid dynamics on a three qubit type II quantum computer: a lattice of small quantum computers that communicate classical information. The algorithm presented is called a three qubit factorized quantum lattice gas algorithm. It is modeled after classical lattice gas algorithms which move virtual particles along an imaginary lattice and change the particles’ momentums using collision rules when they meet at a lattice node. Instead of moving particles, the quantum algorithm presented here moves probabilities, which interact via a unitary collision operator. Probabilities are determined using ensemble measurement and are moved with classical communications …

Multiframe Shift Estimation, Stephen A. Bruckart

Theses and Dissertations

The purpose of this research was to develop a fundamental framework for a new approach to multiframe translational shift estimation in image processing. This thesis sought to create a new multiframe shift estimator, to theoretically prove and experimentally test key properties of it, and to quantify its performance according to several metrics. The new estimator was modeled successfully and was proven to be an unbiased estimator under certain common image noise conditions. Furthermore its performance was shown to be superior to the cross correlation shift estimator, a robust estimator widely used in similar image processing cases, according to several criteria. …

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. …

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 …

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 …

Translation And Rotation Invariant Multiscale Image Registration, Jennifer L. Manfra

Theses and Dissertations

The most recent research involved registering images in the presence of translations and rotations using one iteration of the redundant discrete wavelet transform. We extend this work by creating a new multiscale transform to register two images with translation or rotation differences, independent of scale differences between the images. Our two-dimensional multiscale transform uses an innovative combination of lowpass filtering and the continuous wavelet transform to mimic the two-dimensional redundant discrete wavelet transform. This allows us to obtain multiple subbands at various scales while maintaining the desirable properties of the redundant discrete wavelet transform. Whereas the discrete wavelet transform produces …

An Efficient Gps Position Determination Algorithm, Carlos R. Colon

Theses and Dissertations

The use of detect, or closed-form solutions of the trilateration equations used to obtain the position fix in GPS receivers is investigated. The paper is concerned with the development of an efficient new position determination algorithm that uses the closed-form solution of the trilateration equations and works in the presence of pseudorange measurement noise and for an arbitrary number of satellites. in addition, an initial position guess is not required and good estimation performance is achieved even under high GDOP conditions. A two step GPS position determination algorithm which 1) entails the solution of a linear regression problem and, 2) …

Automatic Target Cueing Of Hyperspectral Image Data, Terry A. Wilson

Theses and Dissertations

Modern imaging sensors produce vast amounts data, overwhelming human analysts. One such sensor is the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) hyperspectral sensor. The AVIRIS sensor simultaneously collects data in 224 spectral bands that range from 0.4µm to 2.5µm in approximately 10nm increments, producing 224 images, each representing a single spectral band. Autonomous systems are required that can fuse "important" spectral bands and then classify regions of interest if all of this data is to be exploited. This dissertation presents a comprehensive solution that consists of a new physiologically motivated fusion algorithm and a novel Bayes optimal self-architecting classifier …

Representations, Approximations, And Algorithms For Mathematical Speech Processing, Laura R. Suzuki

Theses and Dissertations

Representing speech signals such that specific characteristics of speech are included is essential in many Air Force and DoD signal processing applications. A mathematical construct called a frame is presented which captures the important time-varying characteristic of speech. Roughly speaking, frames generalize the idea of an orthogonal basis in a Hilbert space, Specific spaces applicable to speech are L₂(R) and the Hardy spaces H_p(D) for p> 1 where D is the unit disk in the complex plane. Results are given for representations in the Hardy spaces involving Carleson's inequalities (and its extensions), …

New Algorithms For Moving-Bank Multiple Model Adaptive Estimation, Juan R. Vasquez

Theses and Dissertations

The focus of this research is to provide methods for generating precise parameter estimates in the face of potentially significant parameter variations such as system component failures. The standard Multiple Model Adaptive Estimation (MMAE) algorithm uses a bank of Kalman filters, each based on a different model of the system. A new moving-bank MMAE algorithm is developed based on exploitation of the density data available from the MMAE. The methods used to exploit this information include various measures of the density data and a decision-making logic used to move, expand, and contract the MMAE bank of filters. Parameter discretization within …

Concept Vectors: A Synthesis Of Concept Mapping And Matrices For Knowledge Representation In Intelligent Tutoring Systems, Mark L. Dyson

Theses and Dissertations

A review of the literature relating to intelligent tutoring systems (ITS) reveals that the bulk of research to date is focused on the student, and on methods for representing the knowledge itself. From student models to learning schemas to presentation methods, comparatively little attention has been paid to the problem of educators attempting to build viable lesson plans for use in an ITS environment--yet when this problem is addressed in the literature, it is recognized as a potentially daunting one. This thesis addresses the problem of ITS lesson plan development by proposing a practical, computable approach for knowledge engineering that …

Applications Of Unsupervised Clustering Algorithms To Aircraft Identification Using High Range Resolution Radar, Dzung Tri Pham

Theses and Dissertations

Identification of aircraft from high range resolution (HRR) radar range profiles requires a database of information capturing the variability of the individual range profiles as a function of viewing aspect. This database can be a collection of individual signatures or a collection of average signatures distributed over the region of viewing aspect of interest. An efficient database is one which captures the intrinsic variability of the HRR signatures without either excessive redundancy typical of single-signature databases, or without the loss of information common when averaging arbitrary groups of signatures. The identification of 'natural' clustering of similar HRR signatures provides a …

A Single Chip Low Power Implementation Of An Asynchronous Fft Algorithm For Space Applications, Bruce W. Hunt

Theses and Dissertations

A fully asynchronous fixed point FFT processor is introduced for low power space applications. The architecture is based on an algorithm developed by Suter and Stevens specifically for a low power implementation. The novelty of this architecture lies in its high localization of components and pipelining with no need to share a global memory. High throughput is attained using large numbers of small, local components working in parallel. A derivation of the algorithm from the discrete Fourier transform is presented followed by a discussion of circuit design parameters specifically, those relevant to space applications. The generic architecture is explained with …

Modeling And Simulation Support For Parallel Algorithms In A High-Speed Network, Dustin E. Yates

Theses and Dissertations

This thesis investigates the ability of a simulation model to compare and contrast parallel processing algorithms in a high-speed network. The model extends existing modeling, analysis, and comparison of parallel algorithms by providing graphics based components that facilitate the measurement of system resources. Simulation components are based on the Myrinet local area network standard. The models provide seven different topologies to contrast the performance of five variations of Fast Fourier Transform (FFT) algorithms. Furthermore, the models were implemented using a commercially developed product that facilitates the testing of additional topologies and the investigation of hardware variations. Accurate comparisons are statistically …

A Numerical Study Of High-Speed Missile Configurations Using A Block- Structured Parallel Algorithm, Douglas C. Blake

Theses and Dissertations

A numerical analysis of the aerodynamic phenomena associated with the high-speed flight of a sharp-nosed, four-finned, high-fineness ratio missile using a block-structured, parallel computer algorithm is presented. The algorithm, PANS-3EM, utilizes a second-order-accurate, shock-capturing, Total Variation Diminishing scheme and incorporates a Baldwin-Lomax turbulence model. PANS-3EM allows for extreme flexibility in the choice of computational domain decomposition and computing machine of implementation. Developmental work consists of conceptualization and verification of the algorithm as well as parallel performance and scalability studies conducted on a variety of computing platforms. Using PANS-3EM, the aerodynamic characteristics of the missile are investigated. Drag and pitching moment …