Thesis (Ph. D.)--Johns Hopkins University, 1921. / Vita. Published also as Johns Hopkins University studies in historical and political science, series XLI, no. 1. Bibliography: p. 95-96.

Thèse. Univ. Grenoble. Droit. 1931. / Also available on microform.

Inaug.-diss.--Leipzig. / Vita.

Thesis (Ph. D.)--University of Wisconsin--Madison, 1962. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 428-446).

Thesis (M.A.)--University of Delaware, 2007. / Principal faculty advisor: Wendy Bellion, Dept. of Art History. Includes bibliographical references.

Thesis (M.A.)--University of Missouri-Columbia, 2007. / The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on April 2, 2008) Includes bibliographical references.

Inaug.-diss.--Bern. / Also pub. under title: "Kleine reichsbanknoten. Das deutsche banknotengesetz ..." Leipzig, C.L. Hirschfeld, 1908. "Verzeichnis der benützten literatur": 2 p. at end.

Thèse--Université de Genève. / Includes bibliographical references.

No description available.

Submitted by Cátia Araújo (catia.araujo@unipampa.edu.br) on 2017-01-24T13:09:07Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Proposta de aplicativo móvel para identificação de cédulas de real por pessoas com deficiência visual.pdf: 26957479 bytes, checksum: fbee16416d94008754e7d9c9e7919046 (MD5) / Approved for entry into archive by Cátia Araújo (catia.araujo@unipampa.edu.br) on 2017-01-24T13:13:05Z (GMT) No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Proposta de aplicativo móvel para identificação de cédulas de real por pessoas com deficiência visual.pdf: 26957479 bytes, checksum: fbee16416d94008754e7d9c9e7919046 (MD5) / Made available in DSpace on 2017-01-24T13:13:05Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Proposta de aplicativo móvel para identificação de cédulas de real por pessoas com deficiência visual.pdf: 26957479 bytes, checksum: fbee16416d94008754e7d9c9e7919046 (MD5) Previous issue date: 2015-05-07 / Pessoas com deficiência visual têm dificuldade em reconhecer as cédulas de Real. Estas cédulas possuem características diferentes (i.e marcações táteis e dimensões diferentes) que são insuficientes para identificação por pessoas cegas e com baixa visão. Esta pesquisa propõe a criação de um aplicativo móvel para ajudar pessoas com deficiência visual a identificar as notas de Real. A plataforma de desenvolvimento é Android porque apresenta recursos nativos de acessibilidade e é considerado o sistema operacional mais popular no mercado de smartphones. O método desenvolvido usa descritores para classificação das cédulas, o cálculo da distância mínima para a correspondência de pontos, análise de cor predominante na cédula e identificação do numeral presente nas cédulas da primeira família. A validação com usuários é realizada através da avaliação cooperativa e escala de Likert. Na comparação com outros aplicativos, o método proposto atinge alta confiabilidade em relação à identificação das notas. A taxa de sensitividade, especificidade e acurácia foram de 86%, 98% e 89%, respectivamente. / People with visual impairment have difficulty in recognizing the Brazilian Real banknotes. These banknotes have different characteristics (e.g. different tactile markings and dimensions) which are insufficient for identification by blind and low vision persons. This research proposes the creation of a mobile application to help the visually impaired people to identify the current Brazilian paper money. The development platform is Android because it has accessibility native features and is considered the most popular operating system in the smartphone market. The developed method uses descriptors for classification of banknotes, the calculation of the minimum distance to the correspondence points, the predominant color analysis on the banknotes and the numeral recognition which is present in the first family of Real. The validation with users is performed by cooperative assessment and Likert scale. In comparison with other applications, the proposed method achieves high reliability in relation to the identification of the banknotes. We report a sensitivity, specificity and accuracy rate of 86%, 98% and 89%, respectively.