Continuity and Change on an Urban Houselot: Archaeological Excavation at the 22 West Street Backlot (18AP51) of the Annapolis National Historic District, Anne Arundel County, Maryland

Intensive archaeological investigation was undertaken on an urban backlot in Annapolis, Maryland. Fieldwork was conducted on behalf of Historic Annapolis Foundation for the property's owners, King and Cornwall, Inc. Supplemental documentary research, an evaluation of existing conditions on the property, and below-ground excavation of a 35 X 70 ft. urban backlot were conducted. While the project was not a Section 106 compliance effort, the field methods and rationale for the site's investigation are comparable to those of standard Phase II site evaluations. Historical documentation attested to the fact that the 22 West Street Backlot, located along the western most edge of the Historic District of Annapolis, Maryland, had seen development and occupation since the first quarter of the eighteenth century. A substantial brick structure was known to have occupied the property in a series of altered forms for much of that period. This structure served a variety of purposes over time: a private residence in the eighteenth century, a boarding house in the nineteenth century (known as the National Hotel), a duplex in the early twentieth century, half of which remained in use until the structure was entirely razed in the 1970s after destruction by fire. Recovery and analysis of site formation processes (i.e., both cultural and natural transformations of the buried remains) indicated that sections of the site were disturbed to a depth of six feet. In contrast to what initially seemed a poor prognosis for site integrity, other areas of the backlot revealed numerous intact historical features and deposits. Structural remains from the dwelling and its associated outbuildings, additions, and attendant trash deposits were recovered. What was initiated as a program of limited testing evolved into a larger-scale undertaking that made use of largely hand-excavated units in conjunction with machine-assisted stripping of areas demonstrated to contain from four to six-foot deep sterile layers of fill. The current investigations provided a window into a portion of the city and period in its history not documented archaeologically. Moreover, this project provided valuable insight into the archaeology of the homelot within a lightly industrialized, urban context. Evidence was recovered of shifts in the layout and arrangement of the houselot as well as changing relations between individuals and the workplace--all within an urban context--an issue defined elsewhere in the archaeological literature as a significant one. No further investigations are recommended for the site, however, further analysis and interpretation of materials recovered are ongoing. In the event that the site were to undergo development, monitoring of any construction activity is recommended.

Spectral Frame Analysis and Learning through Graph Structure

This dissertation investigates the connection between spectral analysis and frame theory. When considering the spectral properties of a frame, we present a few novel results relating to the spectral decomposition. We first show that scalable frames have the property that the inner product of the scaling coefficients and the eigenvectors must equal the inverse eigenvalues. From this, we prove a similar result when an approximate scaling is obtained. We then focus on the optimization problems inherent to the scalable frames by first showing that there is an equivalence between scaling a frame and optimization problems with a non-restrictive objective function. Various objective functions are considered, and an analysis of the solution type is presented. For linear objectives, we can encourage sparse scalings, and with barrier objective functions, we force dense solutions. We further consider frames in high dimensions, and derive various solution techniques. From here, we restrict ourselves to various frame classes, to add more specificity to the results. Using frames generated from distributions allows for the placement of probabilistic bounds on scalability. For discrete distributions (Bernoulli and Rademacher), we bound the probability of encountering an ONB, and for continuous symmetric distributions (Uniform and Gaussian), we show that symmetry is retained in the transformed domain. We also prove several hyperplane-separation results. With the theory developed, we discuss graph applications of the scalability framework. We make a connection with graph conditioning, and show the in-feasibility of the problem in the general case. After a modification, we show that any complete graph can be conditioned. We then present a modification of standard PCA (robust PCA) developed by Cand\`es, and give some background into Electron Energy-Loss Spectroscopy (EELS). We design a novel scheme for the processing of EELS through robust PCA and least-squares regression, and test this scheme on biological samples. Finally, we take the idea of robust PCA and apply the technique of kernel PCA to perform robust manifold learning. We derive the problem and present an algorithm for its solution. There is also discussion of the differences with RPCA that make theoretical guarantees difficult.