This thesis describes the development of an objective motor score (OMS) of Parkinson's disease that utilizes the Quantitative Motor Assessment Tool (QMAT) developed through efforts by the Intel Corporation and the Kinetics Foundation. Parkinson's disease (PD) is a movement disorder which is a member of a group of neurodegenerative diseases marked by the depletion or impairment of dopamine-producing cells in the brain. Since PD is chronic and degenerative, treatments are intended to either improve the quality of life for sufferers by superficially treating symptoms or slow and ultimately reverse the progression of the disease. No blood test or biomarker exists, so current assessment of the disease relies on a subjective tool called the Unified Parkinson's disease rating scale (UPDRS) which is a coarse scale that requires costly clinical administration and is subject to rater bias. The objective motor score described in this thesis exhibits excellent clinimetric properties, having demonstrated usability, validity, reliability, and responsiveness. It was calibrated to the motor section of the UPDRS, but in addition to high correlation with the motor UPDRS, it demonstrated an excellent ability to track deep brain stimulation treatment levels and to detect improvement in motor function of subjects due to dopaminergic treatment. With an excellent intraclass correlation coefficient, the OMS is a reliable measure and due to the objective nature of the test, it does not suffer from rater bias. Though these results come from the development phase, they suggest that confirmatory studies will firmly establish the excellent properties of the OMS. While further studies are in motion to improve upon the sensitivity of the OMS by exploring metrics of voice recordings and paced tapping tests, the OMS presented here is a complete and usable tool for assessing the severity of PD-related symptoms. In conjunction with the QMAT, it is ready to be used in clinical trials, clinical practice, and even in the homes of patients who suffer from PD. This makes it an invaluable tool that could begin to replace the UPDRS for use in PD research, reducing costs and confounding factors in studies as well as extending their capabilities into the home.

Skin cancer is a major medical problem. If not detected early enough, skin cancer like melanoma can turn fatal. As a result, early detection of skin cancer, like other types of cancer, is key for survival. In recent times, deep learning methods have been explored to create improved skin lesion diagnosis tools. In some cases, the accuracy of these methods has reached dermatologist level of accuracy. For this thesis, a full-fledged cloud-based diagnosis system powered by convolutional neural networks (CNNs) with near dermatologist level accuracy has been designed and implemented in part to increase early detection of skin cancer. A large range of client devices can connect to the system to upload digital lesion images and request diagnosis results from the diagnosis pipeline. The diagnosis is handled by a two-stage CNN pipeline hosted on a server where a preliminary CNN performs quality check on user requests, and a diagnosis CNN that outputs lesion predictions. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2018. / FAU Electronic Theses and Dissertations Collection

abstract: The research objective is fully differential op-amp with common mode feedback, which are applied in filter, band gap, Analog Digital Converter (ADC) and so on as a fundamental component in analog circuit. Having modeled various defect and analyzed corresponding probability, defect library could be built after reduced defect simulation.Based on the resolution of microscope scan tool, all these defects are categorized into four groups of defects by both function and location, bias circuit defect, first stage amplifier defect, output stage defect and common mode feedback defect, separately. Each fault result is attributed to one of these four region defects.Therefore, analog testing algorithm and automotive tool could be generated to assist testing engineers to meet the demand of large numbers of chips. / Dissertation/Thesis / M.S. Electrical Engineering 2014

Made available in DSpace on 2016-06-02T19:51:24Z (GMT). No. of bitstreams: 1 177.pdf: 1113978 bytes, checksum: 4d3ce8e1960eb30e36b74487b1cde791 (MD5) Previous issue date: 2003-02-05 / Universidade Federal de Minas Gerais / Companies need to know their environment, their strengths and their weaknesses in relation to competitors, so that they get benefits, consolidating themselves in this environment. In great companies, there are best conditions to perform self-knowledge studies and market studies internally, or still hiring agencies which make such studies. This is more difficult to happen in small or medium companies. In that way, studies with the purpose of producing a diagnosis for a company or for an industrial segment become important, mainly for small or medium companies, not only for the involved companies, but also for the scientific community, that can focus their research efforts in subjects that are of interest for the companies as for the scientific community. The objectives of this dissertation are to propose a methodology for diagnosing problems and needs in the productive area of small-medium sized industrial companies and its application in two different industrial segments: make-to-order foundries of the interior of São Paulo state and footwear manufacturers of Birigui-SP. The methodology consists in a survey (evaluation research), using questionnaires and interviews. The survey and the use of the inductive method of research make possible a visualization of the situation faced by the industrial segment in study. The application of the proposed methodology was able to show many production characteristics of the segments: make-to-order foundries of the interior of São Paulo state and footwear manufacturers of Birigui-SP. / As empresas necessitam conhecer o ambiente em que estão inseridas, seus pontos fortes e suas fraquezas com relação aos seus concorrentes, de modo que elas venham a se beneficiar e com isso se firmar neste ambiente. No caso de grandes empresas, há melhores condições para se realizar internamente estudos de autoconhecimento e estudos de mercados, ou ainda contratar agências que façam tais estudos, o que é mais difícil ocorrer em empresas de menor porte. Dessa forma, estudos com a finalidade de produzir diagnósticos de uma empresa ou de um segmento industrial tornam-se importantes, principalmente para empresas menores, não apenas para as empresas envolvidas, mas também para a comunidade científica, que podem direcionar seus esforços em questões que sejam de interesse tanto para as empresas quanto para a comunidade científica. Este trabalho tem por objetivos propor uma metodologia para diagnóstico de problemas e necessidades da área produtiva em pequenas e médias empresas industriais e aplicá-la em dois segmentos industriais distintos: fundições de mercado (que operam sob encomenda) do interior do estado de São Paulo e fabricantes de calçados de Birigui-SP. A metodologia consiste em uma pesquisa do tipo survey (pesquisa de avaliação), utilizando-se de questionários e entrevistas com empresas, que em conjunto com o método indutivo de pesquisa possibilitam uma visão da situação enfrentada pelo segmento industrial em estudo (uma fotografia do setor no período em que o estudo é realizado). Esta metodologia pode ser adaptada para ser aplicada em segmentos industriais diversos; isso foi feito para os segmentos de fundição de mercado do interior do estado de São Paulo e de fabricantes de calçados da cidade de Birigui-SP. As informações coletadas permitiram caracterizar os problemas da área produtiva destes dois segmentos e tirar várias conclusões sobre as relações das variáveis utilizadas no estudo.