Comparison of partial least squares regression and principal component regression for pelvic shape prediction.

This paper studied two different regression techniques for pelvic shape prediction, i.e., the partial least square regression (PLSR) and the principal component regression (PCR). Three different predictors such as surface landmarks, morphological parameters, or surface models of neighboring structures were used in a cross-validation study to predict the pelvic shape. Results obtained from applying these two different regression techniques were compared to the population mean model. In almost all the prediction experiments, both regression techniques unanimously generated better results than the population mean model, while the difference on prediction accuracy between these two regression methods is not statistically significant (α=0.01).

A Passive WiFi Source Localization System based on Fine-grained Power-based Trilateration

Indoor localization systems become more interesting for researchers because of the attractiveness of business cases in various application fields. A WiFi-based passive localization system can provide user location information to third-party providers of positioning services. However, indoor localization techniques are prone to multipath and Non-Line Of Sight (NLOS) propagation, which lead to significant performance degradation. To overcome these problems, we provide a passive localization system for WiFi targets with several improved algorithms for localization. Through Software Defined Radio (SDR) techniques, we extract Channel Impulse Response (CIR) information at the physical layer. CIR is later adopted to mitigate the multipath fading problem. We propose to use a Nonlinear Regression (NLR) method to relate the filtered power information to propagation distances, which significantly improves the ranging accuracy compared to the commonly used log-distance path loss model. To mitigate the influence of ranging errors, a new trilateration algorithm is designed as well by combining Weighted Centroid and Constrained Weighted Least Square (WC-CWLS) algorithms. Experiment results show that our algorithm is robust against ranging errors and outperforms the linear least square algorithm and weighted centroid algorithm.

A Bayesian approach to estimating the regression coefficients of a multinomial logit model

A Bayesian approach to estimation of the regression coefficients of a multinominal logit model with ordinal scale response categories is presented. A Monte Carlo method is used to construct the posterior distribution of the link function. The link function is treated as an arbitrary scalar function. Then the Gauss-Markov theorem is used to determine a function of the link which produces a random vector of coefficients. The posterior distribution of the random vector of coefficients is used to estimate the regression coefficients. The method described is referred to as a Bayesian generalized least square (BGLS) analysis. Two cases involving multinominal logit models are described. Case I involves a cumulative logit model and Case II involves a proportional-odds model. All inferences about the coefficients for both cases are described in terms of the posterior distribution of the regression coefficients. The results from the BGLS method are compared to maximum likelihood estimates of the regression coefficients. The BGLS method avoids the nonlinear problems encountered when estimating the regression coefficients of a generalized linear model. The method is not complex or computationally intensive. The BGLS method offers several advantages over Bayesian approaches. ^

Determinación de un modelo de geoide gravimétrico para Puerto Rico como sistema de referencia para las altitudes ortométricas

El geoide, definido como la superficie equipotencial que mejor se ajusta (en el sentido de los mínimos cuadrados) al nivel medio del mar en una determinada época, es la superficie que utilizamos como referencia para determinar las altitudes ortométricas. Si disponemos de una superficie equipotencial de referencia como dátum altimétrico preciso o geoide local, podemos entonces determinar las altitudes ortométricas de forma eficiente a partir de las altitudes elipsoidales proporcionadas por el Sistema Global de Navegación por Satélite (Global Navigation Satellite System, GNSS ). Como es sabido uno de los problemas no resueltos de la geodesia (quizás el más importante de los mismos en la actualidad) es la carencia de un dátum altimétrico global (Sjoberg, 2011) con las precisiones adecuadas. Al no existir un dátum altimétrico global que nos permita obtener los valores absolutos de la ondulación del geoide con la precisión requerida, es necesario emplear modelos geopotenciales como alternativa. Recientemente fue publicado el modelo EGM2008 en el que ha habido una notable mejoría de sus tres fuentes de datos, por lo que este modelo contiene coeficientes adicionales hasta el grado 2190 y orden 2159 y supone una sustancial mejora en la precisión (Pavlis et al., 2008). Cuando en una región determinada se dispone de valores de gravedad y Modelos Digitales del Terreno (MDT) de calidad, es posible obtener modelos de superficies geopotenciales más precisos y de mayor resolución que los modelos globales. Si bien es cierto que el Servicio Nacional Geodésico de los Estados Unidos de América (National Geodetic Survey, NGS) ha estado desarrollando modelos del geoide para la región de los Estados Unidos de América continentales y todos sus territorios desde la década de los noventa, también es cierto que las zonas de Puerto Rico y las Islas Vírgenes Estadounidenses han quedado un poco rezagadas al momento de poder aplicar y obtener resultados de mayor precisión con estos modelos regionales del geoide. En la actualidad, el modelo geopotencial regional vigente para la zona de Puerto Rico y las Islas Vírgenes Estadounidenses es el GEOID12A (Roman y Weston, 2012). Dada la necesidad y ante la incertidumbre de saber cuál sería el comportamiento de un modelo del geoide desarrollado única y exclusivamente con datos de gravedad locales, nos hemos dado a la tarea de desarrollar un modelo de geoide gravimétrico como sistema de referencia para las altitudes ortométricas. Para desarrollar un modelo del geoide gravimétrico en la isla de Puerto Rico, fue necesario implementar una metodología que nos permitiera analizar y validar los datos de gravedad terrestre existentes. Utilizando validación por altimetría con sistemas de información geográfica y validación matemática por colocación con el programa Gravsoft (Tscherning et al., 1994) en su modalidad en Python (Nielsen et al., 2012), fue posible validar 1673 datos de anomalías aire libre de un total de 1894 observaciones obtenidas de la base de datos del Bureau Gravimétrico Internacional (BGI). El aplicar estas metodologías nos permitió obtener una base de datos anomalías de la gravedad fiable la cual puede ser utilizada para una gran cantidad de aplicaciones en ciencia e ingeniería. Ante la poca densidad de datos de gravedad existentes, fue necesario emplear un método alternativo para densificar los valores de anomalías aire libre existentes. Empleando una metodología propuesta por Jekeli et al. (2009b) se procedió a determinar anomalías aire libre a partir de los datos de un MDT. Estas anomalías fueron ajustadas utilizando las anomalías aire libre validadas y tras aplicar un ajuste de mínimos cuadrados por zonas geográficas, fue posible obtener una malla de datos de anomalías aire libre uniforme a partir de un MDT. Tras realizar las correcciones topográficas, determinar el efecto indirecto de la topografía del terreno y la contribución del modelo geopotencial EGM2008, se obtuvo una malla de anomalías residuales. Estas anomalías residuales fueron utilizadas para determinar el geoide gravimétrico utilizando varias técnicas entre las que se encuentran la aproximación plana de la función de Stokes y las modificaciones al núcleo de Stokes, propuestas por Wong y Gore (1969), Vanicek y Kleusberg (1987) y Featherstone et al. (1998). Ya determinados los distintos modelos del geoide gravimétrico, fue necesario validar los mismos y para eso se utilizaron una serie de estaciones permanentes de la red de nivelación del Datum Vertical de Puerto Rico de 2002 (Puerto Rico Vertical Datum 2002, PRVD02 ), las cuales tenían publicados sus valores de altitud elipsoidal y elevación. Ante la ausencia de altitudes ortométricas en las estaciones permanentes de la red de nivelación, se utilizaron las elevaciones obtenidas a partir de nivelación de primer orden para determinar los valores de la ondulación del geoide geométrico (Roman et al., 2013). Tras establecer un total de 990 líneas base, se realizaron dos análisis para determinar la 'precisión' de los modelos del geoide. En el primer análisis, que consistió en analizar las diferencias entre los incrementos de la ondulación del geoide geométrico y los incrementos de la ondulación del geoide de los distintos modelos (modelos gravimétricos, EGM2008 y GEOID12A) en función de las distancias entre las estaciones de validación, se encontró que el modelo con la modificación del núcleo de Stokes propuesta por Wong y Gore presentó la mejor 'precisión' en un 91,1% de los tramos analizados. En un segundo análisis, en el que se consideraron las 990 líneas base, se determinaron las diferencias entre los incrementos de la ondulación del geoide geométrico y los incrementos de la ondulación del geoide de los distintos modelos (modelos gravimétricos, EGM2008 y GEOID12A), encontrando que el modelo que presenta la mayor 'precisión' también era el geoide con la modificación del núcleo de Stokes propuesta por Wong y Gore. En este análisis, el modelo del geoide gravimétrico de Wong y Gore presento una 'precisión' de 0,027 metros en comparación con la 'precisión' del modelo EGM2008 que fue de 0,031 metros mientras que la 'precisión' del modelo regional GEOID12A fue de 0,057 metros. Finalmente podemos decir que la metodología aquí presentada es una adecuada ya que fue posible obtener un modelo del geoide gravimétrico que presenta una mayor 'precisión' que los modelos geopotenciales disponibles, incluso superando la precisión del modelo geopotencial global EGM2008. ABSTRACT The geoid, defined as the equipotential surface that best fits (in the least squares sense) to the mean sea level at a particular time, is the surface used as a reference to determine the orthometric heights. If we have an equipotential reference surface or a precise local geoid, we can then determine the orthometric heights efficiently from the ellipsoidal heights, provided by the Global Navigation Satellite System (GNSS). One of the most common and important an unsolved problem in geodesy is the lack of a global altimetric datum (Sjoberg, 2011)) with the appropriate precision. In the absence of one which allows us to obtain the absolute values of the geoid undulation with the required precision, it is necessary to use alternative geopotential models. The EGM2008 was recently published, in which there has been a marked improvement of its three data sources, so this model contains additional coefficients of degree up to 2190 and order 2159, and there is a substantial improvement in accuracy (Pavlis et al., 2008). When a given region has gravity values and high quality digital terrain models (DTM), it is possible to obtain more accurate regional geopotential models, with a higher resolution and precision, than global geopotential models. It is true that the National Geodetic Survey of the United States of America (NGS) has been developing geoid models for the region of the continental United States of America and its territories from the nineties, but which is also true is that areas such as Puerto Rico and the U.S. Virgin Islands have lagged behind when to apply and get more accurate results with these regional geopotential models. Right now, the available geopotential model for Puerto Rico and the U.S. Virgin Islands is the GEOID12A (Roman y Weston, 2012). Given this need and given the uncertainty of knowing the behavior of a regional geoid model developed exclusively with data from local gravity, we have taken on the task of developing a gravimetric geoid model to use as a reference system for orthometric heights. To develop a gravimetric geoid model in the island of Puerto Rico, implementing a methodology that allows us to analyze and validate the existing terrestrial gravity data is a must. Using altimetry validation with GIS and mathematical validation by collocation with the Gravsoft suite programs (Tscherning et al., 1994) in its Python version (Nielsen et al., 2012), it was possible to validate 1673 observations with gravity anomalies values out of a total of 1894 observations obtained from the International Bureau Gravimetric (BGI ) database. Applying these methodologies allowed us to obtain a database of reliable gravity anomalies, which can be used for many applications in science and engineering. Given the low density of existing gravity data, it was necessary to employ an alternative method for densifying the existing gravity anomalies set. Employing the methodology proposed by Jekeli et al. (2009b) we proceeded to determine gravity anomaly data from a DTM. These anomalies were adjusted by using the validated free-air gravity anomalies and, after that, applying the best fit in the least-square sense by geographical area, it was possible to obtain a uniform grid of free-air anomalies obtained from a DTM. After applying the topographic corrections, determining the indirect effect of topography and the contribution of the global geopotential model EGM2008, a grid of residual anomalies was obtained. These residual anomalies were used to determine the gravimetric geoid by using various techniques, among which are the planar approximation of the Stokes function and the modifications of the Stokes kernel, proposed by Wong y Gore (1969), Vanicek y Kleusberg (1987) and Featherstone et al. (1998). After determining the different gravimetric geoid models, it was necessary to validate them by using a series of stations of the Puerto Rico Vertical Datum of 2002 (PRVD02) leveling network. These stations had published its values of ellipsoidal height and elevation, and in the absence of orthometric heights, we use the elevations obtained from first - order leveling to determine the geometric geoid undulation (Roman et al., 2013). After determine a total of 990 baselines, two analyzes were performed to determine the ' accuracy ' of the geoid models. The first analysis was to analyze the differences between the increments of the geometric geoid undulation with the increments of the geoid undulation of the different geoid models (gravimetric models, EGM2008 and GEOID12A) in function of the distance between the validation stations. Through this analysis, it was determined that the model with the modified Stokes kernel given by Wong and Gore had the best 'accuracy' in 91,1% for the analyzed baselines. In the second analysis, in which we considered the 990 baselines, we analyze the differences between the increments of the geometric geoid undulation with the increments of the geoid undulation of the different geoid models (gravimetric models, EGM2008 and GEOID12A) finding that the model with the highest 'accuracy' was also the model with modifying Stokes kernel given by Wong and Gore. In this analysis, the Wong and Gore gravimetric geoid model presented an 'accuracy' of 0,027 meters in comparison with the 'accuracy' of global geopotential model EGM2008, which gave us an 'accuracy' of 0,031 meters, while the 'accuracy ' of the GEOID12A regional model was 0,057 meters. Finally we can say that the methodology presented here is adequate as it was possible to obtain a gravimetric geoid model that has a greater 'accuracy' than the geopotential models available, even surpassing the accuracy of global geopotential model EGM2008.

GESTÃO DO CONHECIMENTO: UM ESTUDO SOBRE A RELAÇÃO ENTRE A LIDERANÇA TRANSFORMACIONAL, A CONVERSÃO DO CONHECIMENTO E A EFICÁCIA ORGANIZACIONAL

Este estudo teve como objetivo principal analisar a relação entre a Liderança Transformacional, a Conversão do Conhecimento e a Eficácia Organizacional. Foram considerados como pressupostos teóricos conceitos consolidados sobre os temas desta relação, além de recentes pesquisas já realizadas em outros países e contextos organizacionais. Com base nisto identificou-se potencial estudo de um modelo que relacionasse estes três conceitos. Para tal considera-se que as organizações que buscam atingir Vantagem Competitiva e incorporam a Knowledge-Based View possam conquistar diferenciação frente a seus concorrentes. Nesse contexto o conhecimento ganha maior destaque e papel protagonista nestas organizações. Dessa forma criar conhecimento através de seus colaboradores, passa a ser um dos desafios dessas organizações ao passo que sugere melhoria de seus indicadores Econômicos, Sociais, Sistêmicos e Políticos, o que se define por Eficácia Organizacional. Portanto os modos de conversão do conhecimento nas organizações, demonstram relevância, uma vez que se cria e se converte conhecimentos através da interação entre o conhecimento existente de seus colaboradores. Essa conversão do conhecimento ou modelo SECI possui quatro modos que são a Socialização, Externalização, Combinação e Internalização. Nessa perspectiva a liderança nas organizações apresenta-se como um elemento capaz de influenciar seus colaboradores, propiciando maior dinâmica ao modelo SECI de conversão do conhecimento. Se identifica então na liderança do tipo Transformacional, características que possam influenciar colaboradores e entende-se que esta relação entre a Liderança Transformacional e a Conversão do Conhecimento possa ter influência positiva nos indicadores da Eficácia Organizacional. Dessa forma esta pesquisa buscou analisar um modelo que explorasse essa relação entre a liderança do tipo Transformacional, a Conversão do Conhecimento (SECI) e a Eficácia Organizacional. Esta pesquisa teve o caráter quantitativo com coleta de dados através do método survey, obtendo um total de 230 respondentes válidos de diferentes organizações. O instrumento de coleta de dados foi composto por afirmativas relativas ao modelo de relação pesquisado com um total de 44 itens. O perfil de respondentes concentrou-se entre 30 e 39 anos de idade, com a predominância de organizações privadas e de departamentos de TI/Telecom, Docência e Recursos Humanos respectivamente. O tratamento dos dados foi através da Análise Fatorial Exploratória e Modelagem de Equações Estruturais via Partial Least Square Path Modeling (PLS-PM). Como resultado da análise desta pesquisa, as hipóteses puderam ser confirmadas, concluindo que a Liderança Transformacional apresenta influência positiva nos modos de Conversão do Conhecimento e que; a Conversão do Conhecimento influencia positivamente na Eficácia Organizacional. Ainda, concluiu-se que a percepção entre os respondentes não apresenta resultado diferente sobre o modelo desta pesquisa entre quem possui ou não função de liderança.

Sur les tests lisses d'ajustement dans le context des series chronologiques

La plupart des modèles en statistique classique repose sur une hypothèse sur la distribution des données ou sur une distribution sous-jacente aux données. La validité de cette hypothèse permet de faire de l’inférence, de construire des intervalles de confiance ou encore de tester la fiabilité du modèle. La problématique des tests d’ajustement vise à s’assurer de la conformité ou de la cohérence de l’hypothèse avec les données disponibles. Dans la présente thèse, nous proposons des tests d’ajustement à la loi normale dans le cadre des séries chronologiques univariées et vectorielles. Nous nous sommes limités à une classe de séries chronologiques linéaires, à savoir les modèles autorégressifs à moyenne mobile (ARMA ou VARMA dans le cas vectoriel). Dans un premier temps, au cas univarié, nous proposons une généralisation du travail de Ducharme et Lafaye de Micheaux (2004) dans le cas où la moyenne est inconnue et estimée. Nous avons estimé les paramètres par une méthode rarement utilisée dans la littérature et pourtant asymptotiquement efficace. En effet, nous avons rigoureusement montré que l’estimateur proposé par Brockwell et Davis (1991, section 10.8) converge presque sûrement vers la vraie valeur inconnue du paramètre. De plus, nous fournissons une preuve rigoureuse de l’inversibilité de la matrice des variances et des covariances de la statistique de test à partir de certaines propriétés d’algèbre linéaire. Le résultat s’applique aussi au cas où la moyenne est supposée connue et égale à zéro. Enfin, nous proposons une méthode de sélection de la dimension de la famille d’alternatives de type AIC, et nous étudions les propriétés asymptotiques de cette méthode. L’outil proposé ici est basé sur une famille spécifique de polynômes orthogonaux, à savoir les polynômes de Legendre. Dans un second temps, dans le cas vectoriel, nous proposons un test d’ajustement pour les modèles autorégressifs à moyenne mobile avec une paramétrisation structurée. La paramétrisation structurée permet de réduire le nombre élevé de paramètres dans ces modèles ou encore de tenir compte de certaines contraintes particulières. Ce projet inclut le cas standard d’absence de paramétrisation. Le test que nous proposons s’applique à une famille quelconque de fonctions orthogonales. Nous illustrons cela dans le cas particulier des polynômes de Legendre et d’Hermite. Dans le cas particulier des polynômes d’Hermite, nous montrons que le test obtenu est invariant aux transformations affines et qu’il est en fait une généralisation de nombreux tests existants dans la littérature. Ce projet peut être vu comme une généralisation du premier dans trois directions, notamment le passage de l’univarié au multivarié ; le choix d’une famille quelconque de fonctions orthogonales ; et enfin la possibilité de spécifier des relations ou des contraintes dans la formulation VARMA. Nous avons procédé dans chacun des projets à une étude de simulation afin d’évaluer le niveau et la puissance des tests proposés ainsi que de les comparer aux tests existants. De plus des applications aux données réelles sont fournies. Nous avons appliqué les tests à la prévision de la température moyenne annuelle du globe terrestre (univarié), ainsi qu’aux données relatives au marché du travail canadien (bivarié). Ces travaux ont été exposés à plusieurs congrès (voir par exemple Tagne, Duchesne et Lafaye de Micheaux (2013a, 2013b, 2014) pour plus de détails). Un article basé sur le premier projet est également soumis dans une revue avec comité de lecture (Voir Duchesne, Lafaye de Micheaux et Tagne (2016)).

Sur les tests lisses d'ajustement dans le context des series chronologiques

La plupart des modèles en statistique classique repose sur une hypothèse sur la distribution des données ou sur une distribution sous-jacente aux données. La validité de cette hypothèse permet de faire de l’inférence, de construire des intervalles de confiance ou encore de tester la fiabilité du modèle. La problématique des tests d’ajustement vise à s’assurer de la conformité ou de la cohérence de l’hypothèse avec les données disponibles. Dans la présente thèse, nous proposons des tests d’ajustement à la loi normale dans le cadre des séries chronologiques univariées et vectorielles. Nous nous sommes limités à une classe de séries chronologiques linéaires, à savoir les modèles autorégressifs à moyenne mobile (ARMA ou VARMA dans le cas vectoriel). Dans un premier temps, au cas univarié, nous proposons une généralisation du travail de Ducharme et Lafaye de Micheaux (2004) dans le cas où la moyenne est inconnue et estimée. Nous avons estimé les paramètres par une méthode rarement utilisée dans la littérature et pourtant asymptotiquement efficace. En effet, nous avons rigoureusement montré que l’estimateur proposé par Brockwell et Davis (1991, section 10.8) converge presque sûrement vers la vraie valeur inconnue du paramètre. De plus, nous fournissons une preuve rigoureuse de l’inversibilité de la matrice des variances et des covariances de la statistique de test à partir de certaines propriétés d’algèbre linéaire. Le résultat s’applique aussi au cas où la moyenne est supposée connue et égale à zéro. Enfin, nous proposons une méthode de sélection de la dimension de la famille d’alternatives de type AIC, et nous étudions les propriétés asymptotiques de cette méthode. L’outil proposé ici est basé sur une famille spécifique de polynômes orthogonaux, à savoir les polynômes de Legendre. Dans un second temps, dans le cas vectoriel, nous proposons un test d’ajustement pour les modèles autorégressifs à moyenne mobile avec une paramétrisation structurée. La paramétrisation structurée permet de réduire le nombre élevé de paramètres dans ces modèles ou encore de tenir compte de certaines contraintes particulières. Ce projet inclut le cas standard d’absence de paramétrisation. Le test que nous proposons s’applique à une famille quelconque de fonctions orthogonales. Nous illustrons cela dans le cas particulier des polynômes de Legendre et d’Hermite. Dans le cas particulier des polynômes d’Hermite, nous montrons que le test obtenu est invariant aux transformations affines et qu’il est en fait une généralisation de nombreux tests existants dans la littérature. Ce projet peut être vu comme une généralisation du premier dans trois directions, notamment le passage de l’univarié au multivarié ; le choix d’une famille quelconque de fonctions orthogonales ; et enfin la possibilité de spécifier des relations ou des contraintes dans la formulation VARMA. Nous avons procédé dans chacun des projets à une étude de simulation afin d’évaluer le niveau et la puissance des tests proposés ainsi que de les comparer aux tests existants. De plus des applications aux données réelles sont fournies. Nous avons appliqué les tests à la prévision de la température moyenne annuelle du globe terrestre (univarié), ainsi qu’aux données relatives au marché du travail canadien (bivarié). Ces travaux ont été exposés à plusieurs congrès (voir par exemple Tagne, Duchesne et Lafaye de Micheaux (2013a, 2013b, 2014) pour plus de détails). Un article basé sur le premier projet est également soumis dans une revue avec comité de lecture (Voir Duchesne, Lafaye de Micheaux et Tagne (2016)).

GESTÃO DO CONHECIMENTO: UM ESTUDO SOBRE A RELAÇÃO ENTRE A LIDERANÇA TRANSFORMACIONAL, A CONVERSÃO DO CONHECIMENTO E A EFICÁCIA ORGANIZACIONAL

Este estudo teve como objetivo principal analisar a relação entre a Liderança Transformacional, a Conversão do Conhecimento e a Eficácia Organizacional. Foram considerados como pressupostos teóricos conceitos consolidados sobre os temas desta relação, além de recentes pesquisas já realizadas em outros países e contextos organizacionais. Com base nisto identificou-se potencial estudo de um modelo que relacionasse estes três conceitos. Para tal considera-se que as organizações que buscam atingir Vantagem Competitiva e incorporam a Knowledge-Based View possam conquistar diferenciação frente a seus concorrentes. Nesse contexto o conhecimento ganha maior destaque e papel protagonista nestas organizações. Dessa forma criar conhecimento através de seus colaboradores, passa a ser um dos desafios dessas organizações ao passo que sugere melhoria de seus indicadores Econômicos, Sociais, Sistêmicos e Políticos, o que se define por Eficácia Organizacional. Portanto os modos de conversão do conhecimento nas organizações, demonstram relevância, uma vez que se cria e se converte conhecimentos através da interação entre o conhecimento existente de seus colaboradores. Essa conversão do conhecimento ou modelo SECI possui quatro modos que são a Socialização, Externalização, Combinação e Internalização. Nessa perspectiva a liderança nas organizações apresenta-se como um elemento capaz de influenciar seus colaboradores, propiciando maior dinâmica ao modelo SECI de conversão do conhecimento. Se identifica então na liderança do tipo Transformacional, características que possam influenciar colaboradores e entende-se que esta relação entre a Liderança Transformacional e a Conversão do Conhecimento possa ter influência positiva nos indicadores da Eficácia Organizacional. Dessa forma esta pesquisa buscou analisar um modelo que explorasse essa relação entre a liderança do tipo Transformacional, a Conversão do Conhecimento (SECI) e a Eficácia Organizacional. Esta pesquisa teve o caráter quantitativo com coleta de dados através do método survey, obtendo um total de 230 respondentes válidos de diferentes organizações. O instrumento de coleta de dados foi composto por afirmativas relativas ao modelo de relação pesquisado com um total de 44 itens. O perfil de respondentes concentrou-se entre 30 e 39 anos de idade, com a predominância de organizações privadas e de departamentos de TI/Telecom, Docência e Recursos Humanos respectivamente. O tratamento dos dados foi através da Análise Fatorial Exploratória e Modelagem de Equações Estruturais via Partial Least Square Path Modeling (PLS-PM). Como resultado da análise desta pesquisa, as hipóteses puderam ser confirmadas, concluindo que a Liderança Transformacional apresenta influência positiva nos modos de Conversão do Conhecimento e que; a Conversão do Conhecimento influencia positivamente na Eficácia Organizacional. Ainda, concluiu-se que a percepção entre os respondentes não apresenta resultado diferente sobre o modelo desta pesquisa entre quem possui ou não função de liderança.

Data analysis methods in optometry. Part 5: correlation

1. Pearson's correlation coefficient only tests whether the data fit a linear model. With large numbers of observations, quite small values of r become significant and the X variable may only account for a minute proportion of the variance in Y. Hence, the value of r squared should always be calculated and included in a discussion of the significance of r. 2. The use of r assumes that a bivariate normal distribution is present and this assumption should be examined prior to the study. If Pearson's r is not appropriate, then a non-parametric correlation coefficient such as Spearman's rs may be used. 3. A significant correlation should not be interpreted as indicating causation especially in observational studies in which there is a high probability that the two variables are correlated because of their mutual correlations with other variables. 4. In studies of measurement error, there are problems in using r as a test of reliability and the ‘intra-class correlation coefficient’ should be used as an alternative. A correlation test provides only limited information as to the relationship between two variables. Fitting a regression line to the data using the method known as ‘least square’ provides much more information and the methods of regression and their application in optometry will be discussed in the next article.

Consumer evaluations of brand extensions in emerging economies : evidences from China

This project explored how consumers in emerging economies evaluate brand extension by using China as a case. Two separate but related studies were conducted, and university students were used as respondents in both the studies. Study one or replication study tested Aaker and Keller's brand extension model in China. Assuming similar methods to Aaker and Keller's, six well-recognised brands were chosen as parent brand and each was extended to three product categories. Totally, 469 respondents completed the survey questionnaire. As each was to evaluate six extensions, this made the cases 2814. The data was analysed using Optimal Least Square regression approach and "residual centred" approach respectively. The result confirmed most of the findings observed in developed countries. Specifically, consumer's attitude towards the extension is primarily driven by the brand affect, the fit between the two product categories, the difficulty of making the extension and moderated via the interactions between the brand affect and the fit variables. Study two refined and extended Aaker and Keller's model by adding new variables and making methodological adjustments. The same stimuli and data analysis techniques as those in the replication were employed. 252 respondents participated in the survey and each evaluated six extensions, making cases 1512. In addition to re-verifying the findings of the replication and providing cross validation to these findings, the extended study found that the image consistency between the parent brand and the extension, the competition intensity of the extension product market were important in determining the success of the extension. Further, consumer differed in evaluating durable extensions and non-durable extensions. The thesis detailed the two studies above, and discussed the findings and their implications by relating to branding literature, to the general situation of the emerging economies as well as the reality of China. It also presented the limitations of the research and the future research directions.

Modeling height-diameter relationship in pinus pinaster ait. in the forest intervention zone of Lomba, NE-Portugal

In this work, the relationship between diameter at breast height (d) and total height (h) of individual-tree was modeled with the aim to establish provisory height-diameter (h-d) equations for maritime pine (Pinus pinaster Ait.) stands in the Lomba ZIF, Northeast Portugal. Using data collected locally, several local and generalized h-d equations from the literature were tested and adaptations were also considered. Model fitting was conducted by using usual nonlinear least squares (nls) methods. The best local and generalized models selected, were also tested as mixed models applying a first-order conditional expectation (FOCE) approximation procedure and maximum likelihood methods to estimate fixed and random effects. For the calibration of the mixed models and in order to be consistent with the fitting procedure, the FOCE method was also used to test different sampling designs. The results showed that the local h-d equations with two parameters performed better than the analogous models with three parameters. However a unique set of parameter values for the local model can not be used to all maritime pine stands in Lomba ZIF and thus, a generalized model including covariates from the stand, in addition to d, was necessary to obtain an adequate predictive performance. No evident superiority of the generalized mixed model in comparison to the generalized model with nonlinear least squares parameters estimates was observed. On the other hand, in the case of the local model, the predictive performance greatly improved when random effects were included. The results showed that the mixed model based in the local h-d equation selected is a viable alternative for estimating h if variables from the stand are not available. Moreover, it was observed that it is possible to obtain an adequate calibrated response using only 2 to 5 additional h-d measurements in quantile (or random) trees from the distribution of d in the plot (stand). Balancing sampling effort, accuracy and straightforwardness in practical applications, the generalized model from nls fit is recommended. Examples of applications of the selected generalized equation to the forest management are presented, namely how to use it to complete missing information from forest inventory and also showing how such an equation can be incorporated in a stand-level decision support system that aims to optimize the forest management for the maximization of wood volume production in Lomba ZIF maritime pine stands.

Ihwg-μnir: A Miniaturised Near-infrared Gas Sensor Based On Substrate-integrated Hollow Waveguides Coupled To A Micro-nir-spectrophotometer.

A miniaturised gas analyser is described and evaluated based on the use of a substrate-integrated hollow waveguide (iHWG) coupled to a microsized near-infrared spectrophotometer comprising a linear variable filter and an array of InGaAs detectors. This gas sensing system was applied to analyse surrogate samples of natural fuel gas containing methane, ethane, propane and butane, quantified by using multivariate regression models based on partial least square (PLS) algorithms and Savitzky-Golay 1(st) derivative data preprocessing. The external validation of the obtained models reveals root mean square errors of prediction of 0.37, 0.36, 0.67 and 0.37% (v/v), for methane, ethane, propane and butane, respectively. The developed sensing system provides particularly rapid response times upon composition changes of the gaseous sample (approximately 2 s) due the minute volume of the iHWG-based measurement cell. The sensing system developed in this study is fully portable with a hand-held sized analyser footprint, and thus ideally suited for field analysis. Last but not least, the obtained results corroborate the potential of NIR-iHWG analysers for monitoring the quality of natural gas and petrochemical gaseous products.

Classification Of Frankfurters By Ft-raman Spectroscopy And Chemometric Methods.

Frankfurters are widely consumed all over the world, and the production requires a wide range of meat and non-meat ingredients. Due to these characteristics, frankfurters are products that can be easily adulterated with lower value meats, and the presence of undeclared species. Adulterations are often still difficult to detect, due the fact that the adulterant components are usually very similar to the authentic product. In this work, FT-Raman spectroscopy was employed as a rapid technique for assessing the quality of frankfurters. Based on information provided by the Raman spectra, a multivariate classification model was developed to identify the frankfurter type. The aim was to study three types of frankfurters (chicken, turkey and mixed meat) according to their Raman spectra, based on the fatty vibrational bands. Classification model was built using partial least square discriminant analysis (PLS-DA) and the performance model was evaluated in terms of sensitivity, specificity, accuracy, efficiency and Matthews's correlation coefficient. The PLS-DA models give sensitivity and specificity values on the test set in the ranges of 88%-100%, showing good performance of the classification models. The work shows the Raman spectroscopy with chemometric tools can be used as an analytical tool in quality control of frankfurters.

Comparing Near-infrared Conventional Diffuse Reflectance Spectroscopy And Hyperspectral Imaging For Determination Of The Bulk Properties Of Solid Samples By Multivariate Regression: Determination Of Mooney Viscosity And Plasticity Indices Of Natural Rubber.

Conventional reflectance spectroscopy (NIRS) and hyperspectral imaging (HI) in the near-infrared region (1000-2500 nm) are evaluated and compared, using, as the case study, the determination of relevant properties related to the quality of natural rubber. Mooney viscosity (MV) and plasticity indices (PI) (PI0 - original plasticity, PI30 - plasticity after accelerated aging, and PRI - the plasticity retention index after accelerated aging) of rubber were determined using multivariate regression models. Two hundred and eighty six samples of rubber were measured using conventional and hyperspectral near-infrared imaging reflectance instruments in the range of 1000-2500 nm. The sample set was split into regression (n = 191) and external validation (n = 95) sub-sets. Three instruments were employed for data acquisition: a line scanning hyperspectral camera and two conventional FT-NIR spectrometers. Sample heterogeneity was evaluated using hyperspectral images obtained with a resolution of 150 × 150 μm and principal component analysis. The probed sample area (5 cm(2); 24,000 pixels) to achieve representativeness was found to be equivalent to the average of 6 spectra for a 1 cm diameter probing circular window of one FT-NIR instrument. The other spectrophotometer can probe the whole sample in only one measurement. The results show that the rubber properties can be determined with very similar accuracy and precision by Partial Least Square (PLS) regression models regardless of whether HI-NIR or conventional FT-NIR produce the spectral datasets. The best Root Mean Square Errors of Prediction (RMSEPs) of external validation for MV, PI0, PI30, and PRI were 4.3, 1.8, 3.4, and 5.3%, respectively. Though the quantitative results provided by the three instruments can be considered equivalent, the hyperspectral imaging instrument presents a number of advantages, being about 6 times faster than conventional bulk spectrometers, producing robust spectral data by ensuring sample representativeness, and minimizing the effect of the presence of contaminants.

Adsorption of amyloglucosidase from Aspergillus niger NRRL 3122 using ion exchange resin

Amyloglucosidase enzyme was produced by Aspergillus niger NRRL 3122 from solid-state fermentation, using deffated rice bran as substrate. The effects of process parameters (pH, temperature) in the equilibrium partition coefficient for the system amyloglucosidase - resin DEAE-cellulose were investigated, aiming at obtaining the optimum conditions for a subsequent purification process. The highest partition coefficients were obtained using 0.025M Tris-HCl buffer, pH 8.0 and 25ºC. The conditions that supplied the highest partition coefficient were specified, the isotherm that better described the amyloglucosidase process of adsorption obtained. It was observed that the adsorption could be well described by Langmuir equation and the values of Qm and Kd estimated at 133.0 U mL-1 and 15.4 U mL-1, respectively. From the adjustment of the kinetic curves using the fourth-order Runge-Kutta algorithm, the adsorption (k1) and desorption (k2) constants were obtained through optimization by the least square procedure, and the values calculated were 2.4x10-3 mL U-1 min-1 for k1 and 0.037 min-1 for k2 .