Urban Detection From Hyperspectral Images Using Dimension-Reduction Model and Fusion of Multiple Segmentations Based on Stuctural and Textural Features

Ce mémoire de maîtrise présente une nouvelle approche non supervisée pour détecter et segmenter les régions urbaines dans les images hyperspectrales. La méthode proposée n ́ecessite trois étapes. Tout d’abord, afin de réduire le coût calculatoire de notre algorithme, une image couleur du contenu spectral est estimée. A cette fin, une étape de réduction de dimensionalité non-linéaire, basée sur deux critères complémentaires mais contradictoires de bonne visualisation; à savoir la précision et le contraste, est réalisée pour l’affichage couleur de chaque image hyperspectrale. Ensuite, pour discriminer les régions urbaines des régions non urbaines, la seconde étape consiste à extraire quelques caractéristiques discriminantes (et complémentaires) sur cette image hyperspectrale couleur. A cette fin, nous avons extrait une série de paramètres discriminants pour décrire les caractéristiques d’une zone urbaine, principalement composée d’objets manufacturés de formes simples g ́eométriques et régulières. Nous avons utilisé des caractéristiques texturales basées sur les niveaux de gris, la magnitude du gradient ou des paramètres issus de la matrice de co-occurrence combinés avec des caractéristiques structurelles basées sur l’orientation locale du gradient de l’image et la détection locale de segments de droites. Afin de réduire encore la complexité de calcul de notre approche et éviter le problème de la ”malédiction de la dimensionnalité” quand on décide de regrouper des données de dimensions élevées, nous avons décidé de classifier individuellement, dans la dernière étape, chaque caractéristique texturale ou structurelle avec une simple procédure de K-moyennes et ensuite de combiner ces segmentations grossières, obtenues à faible coût, avec un modèle efficace de fusion de cartes de segmentations. Les expérimentations données dans ce rapport montrent que cette stratégie est efficace visuellement et se compare favorablement aux autres méthodes de détection et segmentation de zones urbaines à partir d’images hyperspectrales.

Psychopathie chez les individus non incarcérés et coopération dans un dilemme du prisonnier itératif

Au niveau interpersonnel, la psychopathie implique un manque de considération d’autrui pouvant se manifester par la tromperie, la manipulation et l’exploitation. La présente thèse a investigué la relation entre les caractéristiques psychopathiques d'individus non incarcérés et la tendance à coopérer dans un jeu du dilemme du prisonnier itératif. Un total de 85 hommes ont été recrutés via une annonce qui ciblait des traits de personnalité correspondant à des caractéristiques psychopathiques exprimées de façon non péjorative. Plusieurs méthodes ont été employées pour rejoindre les participants : 46 ont participés en personne après avoir répondu à une invitation affichée dans un journal local ainsi que sur des babillards à proximité d'une université; 39 ont complété l'étude sur Internet après avoir été recrutés via un site web de petites annonces. Chaque participant a répondu à un questionnaire incluant l’Échelle Auto-rapportée de Psychopathie (Levenson, Kiehl, & Fitzpatrick, 1995) et l’Échelle Auto-rapportée des Indicateurs de Psychopathie de l’Enfance et de l’Adolescence (Seto, Khattar, Lalumière, & Quinsey, 1997). Ils ont également complété une simulation informatique du dilemme du prisonnier itératif comprenant 90 essais. La simulation informatique utilisée pour évaluer les participants en personne ainsi que la version accessible par Internet ont été conçues et programmées spécifiquement pour la présente thèse. La simulation informatique incluait trois stratégies souvent associées au dilemme du prisonnier itératif : donnant-donnant, donnant-donnant-généreux et gagne/reste-perd/change. Les analyses préliminaires ont montré que les participants vus en personne et ceux rejoints par Internet ne différaient pas en termes de variables sociodémographiques, des caractéristiques psychopathiques, de la désirabilité sociale et des réponses au dilemme du prisonnier. Une régression multiple standard a indiqué que les mesures psychopathiques ne pouvaient pas prédire le nombre total de choix coopératifs dans le jeu. Par contre, une corrélation négative a été trouvée entre les caractéristiques interpersonnelles et affectives de la psychopathie et la coopération dans le premier tiers du jeu. De plus, les participants qui présentaient davantage de caractéristiques psychopathiques interpersonnelles et affectives avaient plus souvent réussi à exploiter l'ordinateur en dénonçant alors que la simulation informatique coopérait. Des analyses multi-niveaux ont exploré la contribution de variables au niveau de la décision et au niveau de l'individu dans la prédiction du choix de coopérer ou de dénoncer lors de chaque essai du jeu; les interactions entre ces variables ont aussi été considérées. Les résultats ont montré que les variables au niveau de la décision influençaient généralement plus fortement les chances de coopérer que les variables au niveau de l'individu. Parmi les mesures de la psychopathie, seulement les caractéristiques interpersonnelles et affectives ont montré une association significative avec les chances de coopérer; les interactions avec le premier choix effectué dans le jeu et le premier tiers du jeu étaient significatives. Ainsi, si un participant avait coopéré au premier essai, la présence de caractéristiques psychopathiques interpersonnelles et affectives était associée à une diminution de ses chances de coopérer par la suite. Aussi, durant les 30 premiers essais du jeu, la présence de caractéristiques psychopathiques interpersonnelles et affectives était associée à une diminution des chances de coopérer. La stratégie adoptée par la simulation informatique n'avait pas d'influence sur le lien entre les caractéristiques psychopathiques et la probabilité de coopérer. Toutefois, le fait de jouer contre donnant-donnant était associé à de plus fortes chances de coopérer d'un essai à l'autre pour l'ensemble des participants. Globalement, les résultats suggèrent que les hommes non incarcérés présentant des caractéristiques psychopathiques ne seraient pas nécessairement portés à choisir systématiquement la non-coopération. En fait, les caractéristiques interpersonnelles et affectives de la psychopathie ont semblé se traduire par une tendance à faire bonne impression au départ, tenter rapidement d'exploiter autrui en dénonçant, puis finir par coopérer. Cette tendance comportementale est discutée, ainsi que la pertinence d'utiliser le dilemme du prisonnier itératif et les analyses multi-niveaux pour étudier le comportement interpersonnel des psychopathes.

Managing Quality Properties of Web Service Compositions

Web services from different partners can be combined to applications that realize a more complex business goal. Such applications built as Web service compositions define how interactions between Web services take place in order to implement the business logic. Web service compositions not only have to provide the desired functionality but also have to comply with certain Quality of Service (QoS) levels. Maximizing the users' satisfaction, also reflected as Quality of Experience (QoE), is a primary goal to be achieved in a Service-Oriented Architecture (SOA). Unfortunately, in a dynamic environment like SOA unforeseen situations might appear like services not being available or not responding in the desired time frame. In such situations, appropriate actions need to be triggered in order to avoid the violation of QoS and QoE constraints. In this thesis, proper solutions are developed to manage Web services and Web service compositions with regard to QoS and QoE requirements. The Business Process Rules Language (BPRules) was developed to manage Web service compositions when undesired QoS or QoE values are detected. BPRules provides a rich set of management actions that may be triggered for controlling the service composition and for improving its quality behavior. Regarding the quality properties, BPRules allows to distinguish between the QoS values as they are promised by the service providers, QoE values that were assigned by end-users, the monitored QoS as measured by our BPR framework, and the predicted QoS and QoE values. BPRules facilitates the specification of certain user groups characterized by different context properties and allows triggering a personalized, context-aware service selection tailored for the specified user groups. In a service market where a multitude of services with the same functionality and different quality values are available, the right services need to be selected for realizing the service composition. We developed new and efficient heuristic algorithms that are applied to choose high quality services for the composition. BPRules offers the possibility to integrate multiple service selection algorithms. The selection algorithms are applicable also for non-linear objective functions and constraints. The BPR framework includes new approaches for context-aware service selection and quality property predictions. We consider the location information of users and services as context dimension for the prediction of response time and throughput. The BPR framework combines all new features and contributions to a comprehensive management solution. Furthermore, it facilitates flexible monitoring of QoS properties without having to modify the description of the service composition. We show how the different modules of the BPR framework work together in order to execute the management rules. We evaluate how our selection algorithms outperform a genetic algorithm from related research. The evaluation reveals how context data can be used for a personalized prediction of response time and throughput.

Emotion recognition in multiple sclerosis

The effect of multiple sclerosis (MS) on the ability to identify emotional expressions in faces was investigated, and possible associations with patients’ characteristics were explored. 56 non-demented MS patients and 56 healthy subjects (HS) with similar demographic characteristics performed an emotion recognition task (ERT), the Benton Facial Recognition Test (BFRT), and answered the Hospital Anxiety and Depression Scale (HADS). Additionally, MS patients underwent a neurological examination and a comprehensive neuropsychological evaluation. The ERT consisted of 42 pictures of faces (depicting anger, disgust, fear, happiness, sadness, surprise and neutral expressions) from the NimStim set. An iViewX high-speed eye tracker was used to record eye movements during ERT. The fixation times were calculated for two regions of interest (i.e., eyes and rest of the face). No significant differences were found between MS and HC on ERT’s behavioral and oculomotor measures. Bivariate and multiple regression analyses revealed significant associations between ERT’s behavioral performance and demographic, clinical, psychopathological, and cognitive measures.

Bergmann's rule and body size in mammals

Aim: To describe the geographical pattern of mean body size of the non-volant mammals of the Nearctic and Neotropics and evaluate the influence of five environmental variables that are likely to affect body size gradients. Location: The Western Hemisphere. Methods: We calculated mean body size (average log mass) values in 110 × 110 km cells covering the continental Nearctic and Neotropics. We also generated cell averages for mean annual temperature, range in elevation, their interaction, actual evapotranspiration, and the global vegetation index and its coefficient of variation. Associations between mean body size and environmental variables were tested with simple correlations and ordinary least squares multiple regression, complemented with spatial autocorrelation analyses and split-line regression. We evaluated the relative support for each multiple-regression model using AIC. Results: Mean body size increases to the north in the Nearctic and is negatively correlated with temperature. In contrast, across the Neotropics mammals are largest in the tropical and subtropical lowlands and smaller in the Andes, generating a positive correlation with temperature. Finally, body size and temperature are nonlinearly related in both regions, and split-line linear regression found temperature thresholds marking clear shifts in these relationships (Nearctic 10.9 °C; Neotropics 12.6 °C). The increase in body sizes with decreasing temperature is strongest in the northern Nearctic, whereas a decrease in body size in mountains dominates the body size gradients in the warmer parts of both regions. Main conclusions: We confirm previous work finding strong broad-scale Bergmann trends in cold macroclimates but not in warmer areas. For the latter regions (i.e. the southern Nearctic and the Neotropics), our analyses also suggest that both local and broad-scale patterns of mammal body size variation are influenced in part by the strong mesoscale climatic gradients existing in mountainous areas. A likely explanation is that reduced habitat sizes in mountains limit the presence of larger-sized mammals.

Linear-wavelet models applied to the identification of a two-link manipulator

This paper shows that a wavelet network and a linear term can be advantageously combined for the purpose of non linear system identification. The theoretical foundation of this approach is laid by proving that radial wavelets are orthogonal to linear functions. A constructive procedure for building such nonlinear regression structures, termed linear-wavelet models, is described. For illustration, sim ulation data are used to identify a model for a two-link robotic manipulator. The results show that the introduction of wavelets does improve the prediction ability of a linear model.

Probabilistic wind power forecasts with an inverse power curve transformation and censored regression

Forecasting wind power is an important part of a successful integration of wind power into the power grid. Forecasts with lead times longer than 6 h are generally made by using statistical methods to post-process forecasts from numerical weather prediction systems. Two major problems that complicate this approach are the non-linear relationship between wind speed and power production and the limited range of power production between zero and nominal power of the turbine. In practice, these problems are often tackled by using non-linear non-parametric regression models. However, such an approach ignores valuable and readily available information: the power curve of the turbine's manufacturer. Much of the non-linearity can be directly accounted for by transforming the observed power production into wind speed via the inverse power curve so that simpler linear regression models can be used. Furthermore, the fact that the transformed power production has a limited range can be taken care of by employing censored regression models. In this study, we evaluate quantile forecasts from a range of methods: (i) using parametric and non-parametric models, (ii) with and without the proposed inverse power curve transformation and (iii) with and without censoring. The results show that with our inverse (power-to-wind) transformation, simpler linear regression models with censoring perform equally or better than non-linear models with or without the frequently used wind-to-power transformation.

Tests of sunspot number sequences: 3. Effects of regression procedures on the calibration of historic sunspot data

We use sunspot group observations from the Royal Greenwich Observatory (RGO) to investigate the effects of intercalibrating data from observers with different visual acuities. The tests are made by counting the number of groups RB above a variable cut-off threshold of observed total whole-spot area (uncorrected for foreshortening) to simulate what a lower acuity observer would have seen. The synthesised annual means of RB are then re-scaled to the full observed RGO group number RA using a variety of regression techniques. It is found that a very high correlation between RA and RB (rAB > 0.98) does not prevent large errors in the intercalibration (for example sunspot maximum values can be over 30 % too large even for such levels of rAB). In generating the backbone sunspot number (RBB), Svalgaard and Schatten (2015, this issue) force regression fits to pass through the scatter plot origin which generates unreliable fits (the residuals do not form a normal distribution) and causes sunspot cycle amplitudes to be exaggerated in the intercalibrated data. It is demonstrated that the use of Quantile-Quantile (“Q  Q”) plots to test for a normal distribution is a useful indicator of erroneous and misleading regression fits. Ordinary least squares linear fits, not forced to pass through the origin, are sometimes reliable (although the optimum method used is shown to be different when matching peak and average sunspot group numbers). However, other fits are only reliable if non-linear regression is used. From these results it is entirely possible that the inflation of solar cycle amplitudes in the backbone group sunspot number as one goes back in time, relative to related solar-terrestrial parameters, is entirely caused by the use of inappropriate and non-robust regression techniques to calibrate the sunspot data.

Influência dos intermediários de distribuição de produtos turísticos no processo de decisão do meio de hospedagem pelo consumidor

This study examines the complex hotel buyer decision process in front of the tourism distribution channels. Its objective is to describe the influence level of the tourism marketing intermediaries, mainly the travel agents and tour operators, over the hotel decision process by the buyer-tourist. The data collection process was done trough a survey with three hundred brazilian tourists hosted in nineteen hotels of Natal, capital of Rio Grande do Norte, Brazil. The data analysis was done using some multivariate statistic techniques as correlation analysis, multiple regression analysis, factor analysis and multiple discriminant analysis. The research characterizes the hotel services consumers profile and his trip, and identifying the distribution channels used by them. Furthermore, the research verifies the intermediaries influence exercised over hotel buyer decision process, looking for identify causality relations between the influence level and the buyer profile. Verifies that information about hotels available on internet reduces the probability that this influence can be practiced; however it was possible identifying those consumers considers this information complementary and non-substitutes than the information from intermediaries. The characteristics of the data do not allow indentifying the factors that constraint the intermediaries influence neither identifying discriminant functions of the specific distribution channel choice by consumers. The study concludes that consumers don t agree in have been influenced by intermediaries or don t know if they have, still considering important to consult them and internet doesn t substitute their function as information source

Fatores que influenciam a intenção de compra online: aplicação de um modelo adaptado de aceitação da tecnologia para o comércio eletrônico

This research aims to understand the factors that influence intention to online purchase of consumers, and to identify between these factors those that influence the users and the nonusers of electronic commerce. Thus, it is an applied, exploratory and descriptive research, developed in a quantitative model. Data collection was done through a questionnaire administered to a sample of 194 graduate students from the Centre for Applied Social Sciences of UFRN and data analysis was performed using descriptive statistics, confirmatory factorial analysis and simple and multiple linear regression analysis. The results of descriptive statistics revealed that respondents in general and users of electronic commerce have positive perceptions of ease of use, usefulness and social influence about buying online, and intend to make purchases on Internet over the next six months. As for the non-users of electronic commerce, they do not trust the Internet to transact business, have negative perceptions of risk and social influence over purchasing online, and does not intend to make purchases on Internet over the next six months. Through confirmatory factorial analysis six factors were set up: behavioral intention, perceived ease of use, perceived usefulness, perceived risk, trust and social influence. Through multiple regression analysis, was observed that all these factors influence online purchase intentions of respondents in general, that only the social influence does not influence the intention to continue buying on the Internet from users of electronic commerce, and that only trust and social influence affect the intention to purchase online from non-users of electronic commerce. Through simple regression analysis, was found that trust influences perceptions of ease of use, usefulness and risk of respondents in general and users of electronic commerce, and that trust does not influence the perceptions of risk of non-users of electronic commerce. Finally, it was also found that the perceived ease of use influences perceived usefulness of the three groups. Given this scenario, it was concluded that it is extremely important that organizations that work with online sales know the factors that influence consumers purchasing intentions in order to gain space in their market

The use of artificial neural networks in analysing the nutritional ecology of Chrysomya megacephala (F.) (Diptera: Calliphoridae), compared with a statistical model

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Generalização de um modelo linear de impedância eletroquímica

Em geral, a função de um modelo de impedância para processos de eletrodo simples é deduzida de um modelo elétrico equivalente, denominado circuito de Randles. Neste trabalho estudou-se a generalização dessa função, mediante a introdução de um parâmetro não-elétrico, relacionado com a flexibilidade do ângulo de fase e da magnitude. A função foi ajustada às medidas experimentais de impedância obtidas de um sistema constituído de uma liga Ti-10%Al (m/m) em solução de cloreto de sódio 0,9%, variando-se a amplitude de perturbação. Verificou-se que a função generalizada foi adequada para descrever a impedância do sistema analisado, reduzindo as distorções entre a curva experimental e a curva teórica. Além disso, os melhores resultados foram obtidos para sinais de perturbação do sistema com amplitude igual a 10 mV.

Genetic trends in the expected progeny difference of the asymptotic weight of Nelore females

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Assessing relationships between genetic evaluations using robust regression with an application to holsteins in Uruguay

Globalization of dairy cattle breeding has created a need for international sire proofs. Some early methods for converting proofs from one population to another are based on simple linear regression. An alternative robust regression method based on the t-distribution is presented, and maximum likelihood and Bayesian techniques for analysis are described, including the situation in which some proofs are missing. Procedures were used to investigate the relationship between Holstein sire proofs obtained by two Uruguayan genetic evaluation programs. The results suggest that conversion equations developed from data including only sires having proofs in both populations can lead to distorted results, relative to estimates obtained using techniques for incomplete data. There was evidence of non-normality of regression residuals, which constitutes an additional source of bias. A robust estimator may not solve all problems, but can provide simple conversion equations that are less sensitive to outlying proofs and to departures from assumptions.

Evaluation of clinical periodontal conditions in smokers and non-smokers

Given that tobacco smoking habit is a risk factor for periodontal diseases, the aim of this study was to compare clinical periodontal aspects between smokers and non-smokers. The clinical status were assessed in 55 patients, 29 smokers and 26 non-smokers, aged 30 to 50 years, with mean age of 40. The clinical parameters used were: probing depth (PD), plaque index (PI), gingival index (GI), clinical attachment level (CAL), gingival recession (GR) and gingival bleeding index (GBI) for arches (upper and lower ) and teeth (anterior and posterior). Tooth loss was also evaluated in both groups. Multiple regression analysis showed: tendency of greater probing depth and clinical attachment level means for smokers; greater amount of plaque in smokers in all regions; greater gingival index means for non-smokers with clinical significance (p<0.05) in all regions. Although, without statistical significance, the analysis showed greater gingival bleeding index means almost always for nonsmokers; similar gingival recession means in both groups and tendency of upper tooth loss in smokers and lower tooth loss in non-smokers. The findings of this study showed that clinical periodontal parameters may be different in smokers when compared to non-smokers and that masking of some periodontal signs can be a result of nicotine's vasoconstrictor effect.