Statistics and Probability Commons^™

Bottleneck Analysis Of Cports, Sreekalyana Chakravarthy Kajuluri

Electrical & Computer Engineering Theses & Dissertations

CPortS is a transportation logistics simulation that models the flow of military cargo through a seaport and the interaction of the cargo with the port resources and infrastructure. It provides information about the seaport's capabilities, how the cargo has been handled, how many days the cargo took to clear a particular port area, and the overall throughput of the seaport. The model is highly data intensive since it models the huge traffic in a real seaport.

Bottlenecks reduce system performance. Systems that are traffic intensive or simulations of systems, which are data intensive, encounter bottlenecks, which reduce their performance. In …

Quantifying Initial Condition And Parametric Uncertainties In A Nonlinear Aeroelastic System With An Efficient Stochastic Algorithm, Daniel R. Millman

Theses and Dissertations

There is a growing interest in understanding how uncertainties in flight conditions and structural parameters affect the character of a limit cycle oscillation (LCO) response, leading to failure of an aeroelastic system. Uncertainty quantification of a stochastic system (parametric uncertainty) with stochastic inputs (initial condition uncertainty) has traditionally been analyzed with Monte Carlo simulations (MCS). Probability density functions (PDF) of the LCO response are obtained from the MCS to estimate the probability of failure. A candidate approach to efficiently estimate the PDF of an LCO response is the stochastic projection method. The objective of this research is to extend the …

An Investigation Of The Effects Of Correlation, Autocorrelation, And Sample Size In Classifier Fusion, Nathan J. Leap

Theses and Dissertations

This thesis extends the research found in Storm, Bauer, and Oxley, 2003. Data correlation effects and sample size effects on three classifier fusion techniques and one data fusion technique were investigated. Identification System Operating Characteristic Fusion (Haspert, 2000), the Receiver Operating Characteristic Within Fusion method (Oxley and Bauer, 2002), and a Probabilistic Neural Network were the three classifier fusion techniques; a Generalized Regression Neural Network was the data fusion technique. Correlation was injected into the data set both within a feature set (autocorrelation) and across feature sets for a variety of classification problems, and sample size was varied throughout. Total …

A Combinatorial Technique For Face Detection Based On Color And Statistical Analysis, Harishwaran Hariharan

Electrical & Computer Engineering Theses & Dissertations

Automatic detection of faces from video sequences is an important task in security applications. The number, location, size and orientation of human faces in a video frame are unpredictable and can vary from frame to frame. A face detection algorithm for color images in the presence of varying lighting conditions and complexity in background relying upon color and statistical analysis is presented in this thesis. The new method detects skin regions over the entire image and then classifies the skin regions as faces and non-faces. Segmentation of skin regions is performed by a novel color space merging procedure named Integrated …

Gaussian Mixture Reduction Of Tracking Multiple Maneuvering Targets In Clutter, Jason L. Williams

Theses and Dissertations

The problem of tracking multiple maneuvering targets in clutter naturally leads to a Gaussian mixture representation of the Provability Density Function (PDF) of the target state vector. State-of-the-art Multiple Hypothesis Tracking (MHT) techniques maintain the mean, covariance and probability weight corresponding to each hypothesis, yet they rely on ad hoc merging and pruning rules to control the growth of hypotheses.

Support For Statistical Analysis Of The Configurable Port Simulation (Cports), Saurav Mazumdar

Electrical & Computer Engineering Theses & Dissertations

The primary objective of this thesis is to provide support for statistical analysis of CPortS: a transportation logistics simulation, which models the movement of military traffic through seaports and the interaction of the traffic with port infrastructure. By any standards, CPortS is a very large, data intensive simulation. It provides capabilities for analyzing many important issues such as port clearance and throughput. CPortS was classically run in single run mode. Only a single replication of the simulation was performed and conclusions were drawn from the results obtained. Users and analysts of CPortS performed multiple runs only to see the effect …

Autoassociative-Heteroassociative Neural Network, Claudia V. Kropas-Hughes, Steven K. Rogers, Mark E. Oxley, Matthew Kabrisky

AFIT Patents

An efficient neural network computing technique capable of synthesizing two sets of output signal data from a single input signal data set. The method and device of the invention involves a unique integration of autoassociative and heteroassociative neural network mappings, the autoassociative neural network mapping enabling a quality metric for assessing the generalization or prediction accuracy of the heteroassociative neural network mapping.

Theater-Level Stochastic Air-To-Air Engagement Modeling Via Event Occurrence Networks Using Piecewise Polynomial Approximation, David R. Denhard

Theses and Dissertations

This dissertation investigates a stochastic network formulation termed an event occurrence network (EON). EONs are graphical representations of the superposition of several terminating counting processes. An EON arc represents the occurrence of an event from a group of (sequential) events before the occurrence of events from other event groupings. Events between groups occur independently, but events within a group occur sequentially. A set of arcs leaving a node is a set of competing events, which are probabilistically resolved by order relations. An important EON metric is the probability of being at a particular node or set of nodes at time …

Statistical Properties Of Maximum Likelihood Estimates For Accelerated Lifetime Data Under The Weibull Model, Mahmoud A. Yousef

Doctoral Dissertations

Pipe rehabilitation liners are often installed in host pipes that lie below the water table. As such, they are subjected to external hydrostatic pressure. The external pressure leads to early deformation in the liners, which could ultimately lead to its failing or buckling before its expected service lifetime is achieved. Experiments involving long term buckling behavior of liners are typically accelerated lifetime testing procedures. In an accelerated testing procedure a liner is subjected to a constant external hydrostatic pressure and observed until it fails or for a certain time, t whichever occurs first. Liners that do not fail at time …

Minimum Distance Estimation For Time Series Analysis With Little Data, Hakan Tekin

Theses and Dissertations

Minimum distance estimate is a statistical parameter estimate technique that selects model parameters that minimize a good-of-fit statistic. Minimum distance estimation has been demonstrated better standard approaches, including maximum likelihood estimators and least squares, in estimating statistical distribution parameters with very small data sets. This research applies minimum distance estimation to the task of making time series predictions with very few historical observations. In a Monte Carlo analysis, we test a variety of distance measures and report the results based on many different criteria. Our analysis tests the robustness of the approach by testing its ability to make predictions when …

Computer-Based Methods For Constructing Two-Level Fractional-Factorial Experimental Designs With A Requirement Set, Steven L. Forsythe

Theses and Dissertations

This dissertation developed four methodologies for computer-aided experimental design of two-level fractional factorial designs with requirement sets (DOE/RS). The requirement sets identify all the experimental factors and the appropriate interaction terms to be evaluated in the experiment. Taguchi graphs and similar manual methods provide techniques for solving the DOE/RS problem. Unfortunately, these methods are limited because they become difficult to use as the number of factors or interaction terms exceeds ten. This research showed that the DOE/RS problem belongs to a class of difficult-to-solve problems known as NP-Complete. It is the combinatorial nature of NP-Complete problems that causes them to …

Fluid Flow In Micro-Channels: A Stochastic Approach, Hilda Marino Black

Doctoral Dissertations

In this study free molecular flow in a micro-channel was modeled using a stochastic approach, namely the Kolmogorov forward equation in three dimensions. Model equations were discretized using Central Difference and Backward Difference methods and solved using the Jacobi method. Parameters were used that reflect the characteristic geometry of experimental work performed at the Louisiana Tech University Institute for Micromanufacturing.

The solution to the model equations provided the probability density function of the distance traveled by a particle in the micro-channel. From this distribution we obtained the distribution of the residence time of a particle in the micro-channel. Knowledge of …

Cramer-Rao Bound And Optimal Amplitude Estimator Of Superimposed Sinusoidal Signals With Unknown Frequencies, Shaohui Jia

Doctoral Dissertations

This dissertation addresses optimally estimating the amplitudes of superimposed sinusoidal signals with unknown frequencies. The Cramer-Rao Bound of estimating the amplitudes in white Gaussian noise is given, and the maximum likelihood estimator of the amplitudes in this case is shown to be asymptotically efficient at high signal to noise ratio but finite sample size. Applying the theoretical results to signal resolutions, it is shown that the optimal resolution of multiple signals using a finite sample is given by the maximum likelihood estimator of the amplitudes of signals.

Bottom-Up Design Of Artificial Neural Network For Single-Lead Electrocardiogram Beat And Rhythm Classification, Srikanth Thiagarajan

Doctoral Dissertations

Performance improvement in computerized Electrocardiogram (ECG) classification is vital to improve reliability in this life-saving technology. The non-linearly overlapping nature of the ECG classification task prevents the statistical and the syntactic procedures from reaching the maximum performance. A new approach, a neural network-based classification scheme, has been implemented in clinical ECG problems with much success. The focus, however, has been on narrow clinical problem domains and the implementations lacked engineering precision. An optimal utilization of frequency information was missing. This dissertation attempts to improve the accuracy of neural network-based single-lead (lead-II) ECG beat and rhythm classification. A bottom-up approach defined …

A New Sequential Goodness Of Fit Test For The Three-Parameter Gamma Distribution With Known Shape Based On Skewness And Kurtosis, Chil Ho Park

Theses and Dissertations

This research presents a new sequential goodness of fit test for the three-parameter gamma distribution with a known shape. The test is accomplished by employing two new tests, sample skewness and sample kurtosis, sequentially as test statistics. Unlike the typical goodness of fit test, using parameter estimation methods such as maximum likelihood estimation and minimum distance estimation, this test using the two test statistics above does not involve a substantial degree of computational complexity. Large Monte Carlo simulation has been used to determine critical values and overall significance levels for all combinations of the two tests, and to conduct extensive …

Optimum Preventive Maintenance Policies For The Amraam Missile, Scott J. Ruflin

Theses and Dissertations

The overall objective of this research effort was to formulate a preventive maintenance strategy for AMRAAM missiles subject to extended captive carry flight time. A preventive maintenance policy is only applicable if the item in question is aging, or deteriorating with time. Therefore, a supporting objective of this research is to characterize the aging process of the missile system through a non-parametric analysis of its Mean Residual Life (MRL) function. Three non-parametric, censored-data MRL function estimation techniques discussed in the literature are examined via a numerical example. All three estimation techniques provide MRL functions that exhibit greatly exaggerated decreasing trends …

Single Row Routing: Theoretical And Experimental Performance Evaluation, And New Heuristic Development, David A. Hysom

Computer Science Theses & Dissertations

The Single Row Routing Problem (SRRP) is an abstraction arising from real-world multilayer routing concerns. While NP-Complete, development of efficient SRRP routing heuristics are of vital concern to VLSI design. Previously, researchers have introduced various heuristics for SRRP; however, a comprehensive examination of SRRP behavior has been lacking.

We are particularly concerned with the street-congestion minimization constraint, which is agreed to be the constraint of greatest interest to industry. Several theorems stating lower bounds on street congestion are known. We show that these bounds are not tight in general, and argue they may be in error by at least 50% …

A Comparison Of Circular Error Probable Estimators For Small Samples, Charles E. Williams

Theses and Dissertations

Several previous studies investigated the performance of competing circular error probable (CEP) estimators for small samples. This estimation is important in ICBM analysis because, due to expense, there are a limited number of ICBM test launches. In the most recent previous study (1993), Tongue considered five CEP estimators in a simulation test, attempting to determine the behavior of these estimators for populations of various bias, ellipticity, correlation, and sample size. In this paper, we build on Tongue's findings in three ways: (1) The number of estimators compared is expanded to eight. (2) Different factors and factor levels are used. (3) …

Experiments In Aggregating Air Ordnance Effectiveness Data For The Tacwar Model, James E. Parker

Theses and Dissertations

An interactive MS Access&trademark; based application that aggregates the output of the SABSEL model for input into the TACWAR model is developed. The application was developed following efforts to create a functional approximation of the SABSEL data using neural networks, statistical networks, and traditional statistical techniques. These approximations were compared to a look-up table methodology on the basis of accuracy, (RMSE

Eigenvalue And Eigenvector Determination For Damped Gyroscopic Systems, D. P. Malone, Don L. Cronin, Timothy W. Randolph

Mechanical and Aerospace Engineering Faculty Research & Creative Works

No abstract provided.

A Monte Carlo Model Of Uncertainty In A Deterministic Hazardous Waste Transportation Risk Assessment, Michael A. Cowen

Masters Theses

This thesis is aimed at developing and applying advanced modeling tools in the prediction of risk to the general public from transportation of chemical waste on public highways. The modeling tools developed can then be used to compare alternative waste management scenarios. The application considered is related to the transport of hazardous waste generated by the United States Department of Energy (DOE) to current treatment, storage, and disposal facilities. DOE is currently considering four different scenarios.

The application considered can be more specifically defined as an analysis of the risk to the general public from transporting the 63 shipments of …

Review Of: Ike Jeanes, Forecast And Solution - A Trilogy For Everyone Grappling With The Nuclear (Pocahontas Press 1996), Drew Schaefer

RISK: Health, Safety & Environment (1990-2002)

Review of the book: Ike Jeanes, Forecast and Solution - A Trilogy for Everyone Grappling with the Nuclear (Pocahontas Press 1996). Addenda, appendix, figures, front matter, notes, references, tables. ISBN 0-936015-62-4 [800 pp. Cloth $32.00; paper $25.00. P.O. Drawer F, Blacksburg VA 24063-1020.]

Adaptive Integration Of Audio And Visual Information Using Discrete And Semi-Continuous Hidden Markov Models In Audiovisual Automatic Speech Recognition, Qin Su

Electrical & Computer Engineering Theses & Dissertations

An audiovisual semi-continuous hidden Markov model (HMM)-based Automatic Speech Recognition (ASR) system and an improved method of integrating audio and visual information in an audiovisual discrete HMM-based ASR system are investigated.

In the audiovisual discrete HMM, an adaptive integration formulation is employed, which incorporates the integration into the HMM at a pre-categorical stage. A visual weighting parameter is determined automatically, which allows the relative contribution of audio and visual information to be adjusted adaptively. Using an adaptive weight, the accuracy increased by 13% compared to the same model with no adaptive weight.

The semi-continuous HMM is a class of models …

A Robust Method Of Solving Nonlinear Boundary Value Problems Via Modified Compromise Programming, John L. Zornick

Theses and Dissertations

This study is an extension of Ng's previous work in which goal programming was used to determine an approximate solution to a boundary value problem. This approach follows the same basic approach developed by Ng in which the method of collocation was recast as a compromise programming model. Hence, instead of solving a system of simultaneous nonlinear equations, one seeks a compromise solution which minimizes (in a weighted residual sense) a vector norm of the differential equation residuals. A difference in this approach is that it makes use of a genetic algorithm as the optimizing engine as opposed to the …

Predicting Utility Bills For Air Combat Command A Study Of Forecasting Techniques, William L. Luthie

Engineering Management & Systems Engineering Theses & Dissertations

Many companies use forecasting techniques as a tool in managing their assets. Trends in such items as sales, population and inventory levels have all been determined at one time or another using forecasting, yet research indicates that these tools have not been utilized to predict utility budgets. This research was conducted to determine if such techniques could be applied to the specific task of predicting the utility bill at an Air Force base. Three quantitative models were chosen, the Moving Average, Exponential Smoothing and Regression, to determine their applicability to the task at hand. One base within Air Combat Command, …

Groundwater Model Parameter Estimation Using Response Surface Methodology, Richard M. Cotman

Theses and Dissertations

This thesis examined the use of response surface methodology (RSM) to estimate the parameters of a finite-element groundwater model. An existing two-dimensional, steady-state flow model of a fractured carbonate groundwater system in southwestern Ohio served as the calibration target data set. A Plackett-Burman screening design showed that only four of the ten hydraulic conductivity zones significantly contributed to the output of the finite-element model. Also, the effective porosity parameter did not significantly affect the model's output. Using only the four significant hydraulic conductivity parameters; four two-level, four-factor designed experiments were conducted to exploit the first-order response surface defined by a …

Estimation Of The Captive-Carry Survival Function For The Advanced Medium Range Air-To-Air Missile (Amraam), David R. Denhard

Theses and Dissertations

This thesis considers the problem of estimating the survival function of an item (probability that the item functions for a time greater than a given time t) from sampling data subject to partial right censoring (a portion of the items in the sampling data have not yet been observed to fail). Specifically the thesis describes several parametric and non-parametric statistical models that can be used when the sampling data is subject to partial right censoring. These models are applied to the case of estimating the captive-carry survival function of the AIM-120A Advanced Medium Range Air-to-Air Missile (AMRAAM).

Response Surface Methodology As A Sensitivity Tool In Decision Analysis, David A. Meyers

Theses and Dissertations

The purpose of this study is to evaluate response surface methodology as a sensitivity analysis tool in the area of decision analysis. The advent of low-cost personal computer software, such as DPLTM, has created an accessible tool with the ability to frame and solve influence diagrams for decision problems. This study provides a comparison of current sensitivity analysis techniques vs those made possible through response surface methodology (RSM). Sensitivity analysis alternatives are demonstrated on a decision problem concerning the evaluation of force structure options for the Department of Defense. Sensitivity analysis is performed on both one-way and two-way perturbations of …

A New Goodness-Of-Fit Test For The Gamma Distribution Based On Sample Spacings From Complete And Censored Samples, Huseyin Duman

Theses and Dissertations

This thesis studies a new goodness-of-fit test for the gamma distribution with known shape parameter. This test statistic, Z*, is based on spacings from complete or censored samples. The size of samples varied between 5 and 35. The critical value tables were generated for the Z* test statistic for complete and censored samples. The critical values were obtained for five different significance levels: 0.20 0.15, 0.10, 0.05, and 0.01. An extensive power study, containing 50,000 Monte Carlo runs was conducted using nine alternative distributions, H_a. It was observed that the Z* test statistic was more powerful against certain …

Comparing Traditional Statistical Models With Neural Network Models: The Case Of The Relation Of Human Performance Factors To The Outcomes Of Military Combat, William Oliver Hedgepeth

Engineering Management & Systems Engineering Theses & Dissertations

Statistics and neural networks are analytical methods used to learn about observed experience. Both the statistician and neural network researcher develop and analyze data sets, draw relevant conclusions, and validate the conclusions. They also share in the challenge of creating accurate predictions of future events with noisy data.

Both analytical methods are investigated. This is accomplished by examining the veridicality of both with real system data. The real system used in this project is a database of 400 years of historical military combat. The relationships among the variables represented in this database are recognized as being hypercomplex and nonlinear.

The …