No description available.

Many health technologies exhibit some form of learning effect, and this represents a barrier to rigorous assessment by randomised controlled trials. There is reluctance to evaluate while the technique is being learnt, yet unwillingness to admit uncertainty once it has been learnt. In principle, statistical description of a learning curve and subsequent adjustment of an evaluation to take account of learning effects should solve this problem. Exactly how the analyses should be performed has been unclear. This thesis has three components: Systematic review of health technology assessment literature: a systematic description of studies that directly assessed the learning curve effect of health technologies. Systematic search of non-health technology assessment literature: a systematic identification of 'novel' statistical techniques applied to learning curve data in other fields, such as psychology and manufacturing. Testing of statistical methods: testing of these statistical techniques in sets of data describing a variety of health technologies where learning curve effects are known to exist.

Chlorophyll fluorescence imaging has now become a versatile and standard tool in fundamental and applied plant research. This method captures time series images of the chlorophyll fluorescence emission of whole leaves or plants upon various illuminations, typically combination of actinic light and saturating flashes. Several conventional chlorophyll fluorescence parameters have been recognized that have physiological interpretation and are useful for, e.g., assessment of plant health status and early detection of biotic and abiotic stresses. Chlorophyll florescence imaging enabled us to probe the performance of plants by visualizing physiologically relevant fluorescence parameters reporting physiology and biochemistry of the plant leaves. Sometimes there is a need to find the most contrasting fluorescence features/parameters in order to quantify stress response at very early stage of the stress treatment. The conventional fluorescence utilizes well defined single image such as F0, Fp, Fm, Fs or arithmetic combinations of basic images such as Fv/Fm, PSII, NPQ, qP. Therefore, although conventional fluorescence parameters have physiological interpretation, they may not be representing highly contrasting image sets. In order to find the effect of stress treatments at very early stage, advanced statistical techniques, based on classifiers and feature selection methods, have been developed to select highly contrasting chlorophyll fluorescence images out of hundreds of captured images. We combined sets of highly performing images resulting in images with very high contrast, the so called combinatorial imaging. The application of advanced statistical methods on chlorophyll fluorescence imaging data allows us to succeed in tasks, where conventional approaches do not work. This thesis aims to explore the application of conventional chlorophyll fluorescence parameters as well as advanced statistical techniques of classifiers and feature selection methods for high-throughput screening. We demonstrate the applicability of the technique in discriminating three species of the same family Lamiaceae at a very early stage of their growth. Further, we show that chlorophyll fluorescence imaging can be used for measuring cold and drought tolerance of Arabidopsis thaliana and tomato plants, respectively, in a simulated high ? throughput screening.

Please read the abstract in the section 00front of this document / Dissertation (MSc)--University of Pretoria, 2006. / Geography, Geoinformatics and Meteorology / MSc / Unrestricted

This research identifies large-scale synoptic controls that are relevant for rapid intensification (RI) in the Atlantic basin. Spatial statistical analysis techniques were performed on NASA MERRA data from 1979–2009. Rotated principal component analysis (RPCA) was performed, looking for common patterns in the datasets. The RPC’s were grouped using hierarchical clustering techniques, allowing for finding events similar in synoptic structure. The clustered events, representing the total RI and non-RI composites, were averaged yielding composite maps for different scenarios. To verify the results, a permutation test was done to show which variables are good distinguishers of RI and non-RI cases. These variables were used as input in two prediction schemes: logistic regression and support vector machine classification. The prediction scheme was a slight improvement in forecasting RI when using the synoptic variables mid-level vorticity, vertical velocity, low-level potential temperature and specific humidity, as the most significant in predicting RI.

No description available.

The aim of this thesis is to develop a quantitative measure of postural defects known as lordosis and kyphosis. The measurement of these is an important part of their identification and treatment.

The aim of this thesis is to develop a quantitative measure of postural defects known as lordosis and kyphosis. The measurement of these is an important part of their identification and treatment.

Submitted by Miriam Rodrigues Silvestre null (miriam@fct.unesp.br) on 2016-04-12T19:42:55Z No. of bitstreams: 1 Tese_MRS.pdf: 22047618 bytes, checksum: 7c7834a117ebe81c7554b7808f8593b5 (MD5) / Approved for entry into archive by Ana Paula Grisoto (grisotoana@reitoria.unesp.br) on 2016-04-15T12:40:50Z (GMT) No. of bitstreams: 1 silvestre_mr_dr_prud_par.pdf: 1762323 bytes, checksum: 590891333b2addf8f715166f578950f5 (MD5) / Made available in DSpace on 2016-04-15T12:40:50Z (GMT). No. of bitstreams: 1 silvestre_mr_dr_prud_par.pdf: 1762323 bytes, checksum: 590891333b2addf8f715166f578950f5 (MD5) Previous issue date: 2016-03-08 / Essa tese aborda o uso da Estatística na Climatologia Geográfica, através da identificação das técnicas mais usuais e possíveis falhas em sua aplicação em análises geográficas do clima, bem como sugestões de alternativas para as diversas situações e necessidades, de acordo com as possibilidades. As fontes de informações utilizadas foram trabalhos apresentados no Simpósio Brasileiro de Climatologia Geográfica (SBCG) e artigos publicados na Revista Brasileira de Climatologia (RBClima). Entre os objetivos para os quais se aplicam técnicas estatísticas foram apresentadas técnicas para: preenchimento de falhas, análise exploratória de dados, escolha de anos padrão, análise de tendências em séries com modelos de regressão, testes para análise de tendência, rupturas e consistência de séries, correlação entre duas séries, modelos estatísticos para relacionar uma variável dependente com duas ou mais variáveis independentes, interpolação de dados no espaço, definição de regiões homogêneas, classificação climática e vulnerabilidade socioambiental. Concluiu-se que ainda há algumas aplicações incorretas das técnicas estatísticas e foram realizadas sugestões de outras técnicas que poderiam ser utilizadas. Espera-se que essa tese possa contribuir para a aplicação da Estatística e facilitar a interação entre o geógrafo e o estatístico no desenvolvimento de pesquisas na área de Climatologia Geográfica, bem como na Geografia do Clima. / This thesis discussed the use of Statistics in the Geographical Climatology, by identifying the most common technics and possible failures in its application in geographical climate analyzes and suggests alternatives to the different situations and needs, according to the possibilities. The sources of information used were papers presented at the Brazilian Symposium of Geographical Climatology (SBCG) and articles published in the Brazilian Journal of Climatology (RBClima). Among the objectives for which they apply statistical techniques, were discussed techniques for: gap filling, exploratory data analysis, pattern year choice, trend analysis in series with regression models, tests for trend analysis, ruptures and consistency of series, correlation between two series, statistical models to relate a dependent variable with two or more independent variables, data interpolation in space, definition of homogeneous regions, climatic classification and socio-environmental vulnerability. It was concluded that there is still some incorrect application of statistical techniques and were suggested that other techniques could be used. It is hoped that this thesis can contribute to the application of Statistics and facilitate interaction between the geographer and statistician in the development of research in the field of Geographical Climatology and Climate in Geography.

No / In this paper, we illustrate the ways in which Bayesian statistical techniques may be used to enhance chronological resolution when applied to a series of OSL sediment dates. Such application can achieve an optimal chronological model by incorporating stratigraphic and age information. The application to luminescence data is not straightforward owing to the sources of uncertainty in each date, and here we present one solution to overcoming these difficulties, and introduce the concept of "unshared systematic" errors. Using OSL sediment dates from the site of Old Scatness Broch, Shetland Isles, UK, many measured with a high degree of precision, we illustrate some of the ways in which Bayesian techniques may be applied, as a tool for assessing systematic errors when combined with independent chronological information, and to determine the optimum chronological information for specific events and contexts. We provide a detailed procedure for the application of Bayesian methods to OSL dates using the widely available radiocarbon calibration programme OxCal.