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Barrett, Rebecca L.Building in the Styles of Their Time: Fugman, Cramer and Uhlrich
Master of Arts in History, Cleveland State University, 2008, College of Liberal Arts and Social Sciences

The impetus for this project was an unsual promotional book by an obscure local architectural firm. Greater Cleveland Architecture by Godfrey Fugman and C. Frank Cramer presented a unique glimpse into the nearly forgotten firm. Its meticulously photographed, pristine images of buildings in their intended environment provided crucial visual primary source material for my work.

Investigating the firm of Cramer and Fugman (1887-1896) naturally led to its successor firm of Fugman and Uhlrich (1899-1903). Primary research was conducted working with building permits, newspapers and periodicals of the profession such as Inland Architect and Builder, Interstate Architect, and Ohio Builder and Architect, None of them is fully indexed. This research was compiled chronologically in a catalogue of works containing over 100 buildings by the firms. After biographic details and information about the state of the profession and the firms, discussion of the structures in the text was done in terms of building type.

While not of national repute, the architects were, nonetheless, very talented men who worked in the nationally popular styles during the Golden Era of Cleveland. Innovative in design, technology and use of material, active in the continuing development of their profession, they were important architects for Cleveland at turn of the 20th century.

Committee:

Marian Bleeke, PhD (Committee Chair); Thomas Donaldson, PhD (Committee Member); Elizabeth Lehfeldt, PhD (Committee Member)

Subjects:

Architecture; Art History

Keywords:

Cleveland architecture; Godfrey Fugman; C. Frank Cramer; Emile Uhlrich; Fugman; Cramer; Uhlrich

Lingg, Andrew JamesStatistical Methods for Image Change Detection with Uncertainty
Doctor of Philosophy (PhD), Wright State University, 2012, Engineering PhD
Sensors capable of collecting wide area motion imagery (WAMI), video synthetic aperture radar (SAR), and other high frame rate sensor modalities provide massive amounts of high-resolution data. Such data allows for the use of multiple images in exploitation tasks which may have traditionally used single images or single pairs of images. One such task is change detection. This dissertation presents new statistical methods for change detection that provide for the exploitation of multiple images per pass. Uncertainty in image registration can degrade change detection performance. Registration accuracy is analyzed, and the impact of registration uncertainty is propagated to the registered imagery. A statistical understanding of this uncertainty is incorporated into the sequential change detection algorithm to mitigate performance degradation due to registration errors. Theoretical results are verified through simulation experiments and with measured data sets.

Committee:

Brian Rigling, PhD (Advisor); Fred Garber, PhD (Committee Member); John Gallagher, PhD (Committee Member); Micheal Temple, PhD (Committee Member); William Pierson, PhD (Committee Member)

Subjects:

Computer Science; Electrical Engineering; Engineering; Statistics

Keywords:

Change Detection; Estimation; Registration; Sequential Analysis; Cramer-Rao Lower Bound; Compressive Sensing

Golub, FrankAn Estimation Technique for Spin Echo Electron Paramagnetic Resonance
Master of Science, The Ohio State University, 2013, Electrical and Computer Engineering
In spin echo electron paramagnetic resonance (SE-EPR) spectroscopy, traditional methods to estimate T2 relaxation time include fitting an exponential to the peaks or the integrated areas of multiple noisy echoes. These methods are suboptimal and result in lower estimation accuracy for a given acquisition time. Here, two data processing methods to estimate T2 for SE-EPR are proposed. The fi rst method fi nds the maximum likelihood estimate (MLE) of T2 via parametric modeling of the spin echo and joint least-squares fi tting of the collected data. The second method exploits the underlying rank-one structure in SE-EPR data via singular-value decomposition (SVD). The right singular vector corresponding to the largest singular value is then fi tted with an exponential to fi nd T2. This method bears strong similarity to a non-parametric MLE-based approach that does not assume a structure of an echo. The methods are validated using simulation and experimental data. The proposed methods provide 41-fold and 3-fold acquisition time savings over the traditional methods of fi tting echo peaks and areas, respectively. Interestingly, the results also indicate that the SVD-based approach generates mean squared error nearly identical to that produced by the MLE based on parametric modeling for a wide range of SNR.

Committee:

Lee Potter (Advisor); Bradley Clymer (Committee Member); Rizwan Ahmad (Committee Member)

Subjects:

Electrical Engineering; Medical Imaging

Keywords:

electron paramagnetic resonance; singular value decomposition; spin echo; maximum likelihood estimation; Cramer-Rao lower bound; EPR; SVD; MLE; CRLB; CRB; peak picking; echo integration;

Kapadia, SharvariCramer Rao Lower Bound and Maximum Likelihood Estimation for Multipath Propagation of GPS Signals
MS, University of Cincinnati, 2013, Engineering and Applied Science: Electrical Engineering
Multipath propagation refers to a phenomenon wherein a radio signal winds up taking two or more paths because the signal is reflected off buildings or other obstructions near the receiver, resulting in one or more secondary propagation paths. In a GPS receiver, multipath effect can cause a stationary receiver's output to indicate as if it were randomly jumping about or creeping. The presence of multipath generally causes errors in the phase or delay measurements, thereby degrading the navigation accuracy. The main attention of this thesis is on computation of Cramer Rao Lower Bound that expresses a lower bound on the variance of estimated signal parameters. Cramer Rao Bound is computed for amplitude, phase and time delay signal parameters by taking the diagonal components of the Fisher Information Matrix, which is a 66 matrix for a 2-path multipath model. The Fisher Information Matrix entries are computed by taking the expected value of the product of the partial derivatives of log-likelihood function with respect to the signal parameters. The next part of the thesis is estimation of the signal parameters from distorted received signal of the same 2-path model using Maximum Likelihood estimation theory. The values of estimated parameter variance computed from estimated signal parameters, are compared with the Cramer Rao Lower bound.

Committee:

H. Howard Fan, Ph.D. (Committee Chair); Eric T. Vinande, Ph.D. (Committee Member); Xuefu Zhou, Ph.D. (Committee Member)

Subjects:

Electrical Engineering

Keywords:

Cramer Rao bound;GPS signals;Multipath Propagation;Maximum Likelihood Estimation;Parameter Estimation;;

Moore, Linda JenniferImpact of Phase Information on Radar Automatic Target Recognition
Doctor of Philosophy (Ph.D.), University of Dayton, 2016, Electrical Engineering
Traditional synthetic aperture radar (SAR) systems tend to discard phase information of formed complex radar imagery prior to automatic target recognition (ATR). This practice has historically been driven by available hardware storage, processing capabilities, and data link capacity. Recent advances in high performance computing (HPC) have enabled extremely dense storage and processing solutions. Therefore, previous motives for discarding radar phase information in ATR applications have been mitigated. First, we characterize the value of phase in one-dimensional (1-D) radar range profiles and two dimensional (2-D) SAR imagery with respect to the ability to correctly estimate target features, which are currently employed in ATR algorithms for target discrimination. These features correspond to physical characteristics of a target through radio frequency (RF) scattering phenomenology. Physics-based electromagnetic scattering models developed from the geometrical theory of diffraction are utilized for the information analysis presented here. Information is quantified by the error of target parameter estimates from noisy radar signals when phase is either retained or discarded. Operating conditions (OCs) of signal-to-noise ratio, bandwidth, and aperture extent are considered. Second, we investigate the value of phase in 1-D radar returns with respect to the ability to correctly classify canonical targets. Classification performance is evaluated via three techniques, namely, naïve Bayes, logistic regression and a bound on Bayes error rate (BER). These classification techniques maintain varying assumptions on the observed data set, with the BER bound making no assumptions. In each case, phase information is demonstrated to improve radar target classification rates.

Committee:

Robert Penno (Committee Chair); Brian Rigling (Advisor)

Subjects:

Electrical Engineering

Keywords:

synthetic aperture radar; high range resolution; radar range profiles; phase information; target feature estimation; position accuracy; error variance; Cramer-Rao lower bound; operating conditions; automatic target recognition