[pt] A reconstrução de curvas e superfícies a partir de pontos esparsos é um problema que tem recebido bastante atenção ultimamente. A não-estruturação dos pontos (ou seja, desconhecimento das relações de vizinhança e proximidade) e a presença de ruído são dois fatores que tornam este problema complexo. Para resolver este problema, várias técnicas podem ser utilizadas, como triangulação de Delaunay, reconstrução de iso-superfícies através de Marching Cubes e algoritmos baseados em avanço de fronteira. O algoritmo proposto consiste de quatro etapas principais: a primeira etapa é a clusterização dos pontos de amostragem de acordo com sua localização espacial. A clusterização fornece uma estrutura espacial para os pontos, e consiste em dividir o espaço em células retangulares de mesma dimensão, classificando as células em cheias (caso possuam pontos de amostragem em seu interior) ou vazias (caso não possuam pontos de amostragem em seu interior). A estrutura de dados gerada nesta etapa permite também obter o conjunto dos pontos de amostragem de cada uma das células. A segunda etapa é o processamento dos pontos através de projeções MLS. A etapa de pré- processameno visa reduzir ruído dos pontos de amostragem, bem como adequar a densidade de pontos ao nível de detalhe esperado, adicionando ou removendo pontos do conjunto inicial. A terceira etapa parte do conjunto das células que possuem pontos de amostragem em seu interior (células cheias) e faz a esqueletonização deste conjunto de células, obtendo, assim, uma aproximação digital para a curva a ser reconstruída. Este esqueleto é encontrado através do afinamento topológico das células que possuem pontos. A implementação do algoritmo de afinamento é feita de modo que o número de pontos em cada célula seja levado em consideração, removendo primeiro sempre as células com menor número de pontos. Na quarta etapa, a reconstrução da curva é finalmente realizada. Para tal, parte-se do esqueleto obtido na terceira etapa e constrói-se uma curva linear por partes, onde cada vértice é obtido a partir da projeção MLS do ponto médio de cada célula do esqueleto. / [en] Curve and surface reconstruction from sparse data has been recognized as an important problem in computer graphics. Non structured data points (i.e., a set of points with no knowledge of connectivity and proximity) together with the existence of noise make this problem quite difficult. In order to solve it, several techniques have been proposed, such as, some of them are based on Delaunay triangulation, other are based on implicit surface reconstruction or on the advancing front techniques. Our algorithm consists basically in four steps. In the first step, a clustering procedure is performed in order to group the sample points according to their spatial location. This procedure obtains an spatial structure for the points by subdividing uniformly the plane in rectangular cells, and classifying them into two categories: empty (when the cell contains no point inside) or not empty (otherwise). At this stage, a data structure is built in such way that it is possible to query the set of sample points that belong to a given rectangular cell. The second step processes the point through the Moving Least Squares method. Its objective is not only to reduce the noise on the data, but also to adapt the number of point to the desired level, by adding or removing points from the initial set. The third step builds the skeleton of the set of cells that have sample point on its interior. Such skeleton is in fact a digital approximation for the curve that will be reconstructed. It is obtained by the use of a topological thinning algorithm, and its implementation is done in such a way that the number of points in each cell is considered, for example, the cells with less number of points are not considered for the thinning. In the last step, the curve is finally reconstructed To do so, the skeleton obtained in the third step is used to construct a piecewise-linear approximation for the curve, where each vertex is obtained from the MLS projection on the middle point of the skeleton rectangular cell.

Au cours de ces dernières années, les technologies mobiles ont créé des conditions de marché très concurrentielles. Face à cette nouvelle conjoncture, les banques ont lancé la banque mobile, une innovation technologique en milieu bancaire comme une nouvelle opportunité à saisir. Cette étude pose une question liée au cœur des principaux problèmes rencontrés dans le domaine bancaire : qui investit le plus dans les TIC, et qui vise à développer des relations à long terme avec ses clients. Afin de produire une valeur ajoutée sur les investissements technologiques, il devient important pour les banques d’assurer l’adoption de ces services par leurs clients dans un premier temps et d’assurer la survie de ces services (la continuité de l’utilisation) par le développement des relations durables et rentables avec les clients dans un deuxième temps. Ceci signifie que la compréhension des comportements des clients nécessite deux phases : la phase « adoption » et la phase « post-adoption ». La thèse vise, d’une part, à explorer les facteurs influençant l’adoption de la banque mobile par les clients et, d’autre part, à formuler un cadre explicatif de l’effet de ces facteurs pour établir et améliorer des relations entre les banques et leurs clients. L’analyse des données recueillies par questionnaire administré en face à face auprès de 282 répondants, identifie trois segments de clients : non utilisateurs, utilisateurs et adopteurs. L'analyse explicative réalisée par la méthode PLS relève le rôle important joué par quatre facteurs : l’utilité perçue, le risque perçu, la sécurité perçue et l’effort attendu dans les deux phases. / In recent years, mobile technologies have created very competitive market conditions. Facing this new environment, banks have launched mobile banking, a technological innovation in banking sector, as a new opportunity to seize. This study raises a question related to the heart of the main problems in banking: who invests the most in ICT, and who aims to develop long-term relationships with its clients. To produce added value on technological investments, it becomes important for banks to ensure the adoption of these services by their clients at first time and ensure the survival of these services (continuity of use) through the development of sustainable and profitable customer relationships in a second time. This means that the understanding of customer behavior requires two phases: the "adoption" phase and the "post-adoption" phase. The thesis aims, first, to explore the factors influencing the adoption of mobile banking by customers and, second, to formulate an explanatory framework of the effect of these factors to establish and improve relations between banks and their customers.The analysis of data collected by questionnaires administered face to face with 282 respondents identifies three customer segments: non-users, users and adopters. The explanatory analysis by the PLS method highlights the important role played by four factors: perceived usefulness, perceived risk, perceived safety and the expected effort in the two phases.

Crying is infants utilize to express their emotional state. It provides the parents and the nurses a criterion to understand infants’ physiology state. Many researchers have analyzed infants’ crying sounds to diagnose specific diseases or define the reasons for crying. This thesis presents an automatic crying level assessment system to classify infants’ crying sounds that have been recorded under realistic conditions in the Neonatal Intensive Care Unit (NICU) as whimpering or vigorous crying. To analyze the crying signal, Welch’s method and Linear Predictive Coding (LPC) are used to extract spectral features; the average and the standard deviation of the frequency signal and the maximum power spectral density are the other spectral features which are used in classification. For classification, three state-of-the-art classifiers, namely K-nearest Neighbors, Random Forests, and Least Squares Support Vector Machine are tested in this work, and the experimental result achieves the highest accuracy in classifying whimper and vigorous crying using the clean dataset is 90%, which is sampled with 10 seconds before scoring and 5 seconds after scoring and uses K-nearest neighbors as the classifier.

Rhythmic motion is ubiquitous in nature and technology. Various motions of organisms like the heart beating and walking require stable periodic execution. The stability of the rhythmic execution of human movement can be altered by neurological or orthopedic impairment. In robotics, successful development of legged robots heavily depends on the stability of the controlled limit-cycle. An accurate measure of the stability of rhythmic execution is critical to the diagnosis of several performed tasks like walking in human locomotion. Floquet multipliers have been widely used to assess the stability of a periodic motion. The conventional approach to extract the Floquet multipliers from actual data depends on the least squares method. We devise a new way to measure the Floquet multipliers with reduced bias and estimate orbital stability more accurately. We show that the conventional measure of the orbital stability has bias in the presence of noise, which is inevitable in every experiment and observation. Compared with previous method, the new method substantially reduces the bias, providing acceptable estimate of the orbital stability with fewer cycles even with different noise distributions or higher or lower noise levels. The new method can provide an unbiased estimate of orbital stability within a reasonably small number of cycles. This is important for experiments with human subjects or clinical evaluation of patients that require effective assessment of locomotor stability in planning rehabilitation programs. / Graduate / 2018-11-22

South Florida continues to become increasingly developed and urbanized. My exploratory study examines connections between land use and water quality. The main objectives of the project were to develop an understanding of how land use has affected water quality in Miami-Dade canals, and an economic optimization model to estimate the costs of best management practices necessary to improve water quality. Results indicate Miami-Dade County land use and water quality are correlated. Through statistical factor and cluster analysis, it is apparent that agricultural areas are associated with higher concentrations of nitrogen, while urban areas commonly have higher levels of phosphorous than agricultural areas. The economic optimization model shows that urban areas can improve water quality by lowering fertilizer inputs. Agricultural areas can also implement methods to improve water quality although it may be more expensive than urban areas. It is important to keep solutions in mind when looking towards future water quality improvements in South Florida.

As a solution to mid-air haptic actuation with strong and continuous tactile force, Magnetic Rendering is presented as an intuitive haptic display method applying an electromagnet array to produce a magnetic field in mid-air where the force field can be felt as magnetic repulsive force exerted on the hand through the attached magnet discs. The magnetic field is generated by a specifically designed electromagnet array driven by direct current. By attaching small magnet discs on the hand, the tactile sensation can be perceived by the user. This method can provide a strong tactile force on multiple points covering user’s hand and avoid cumbersome attachments with wires, thus it is suitable for a co-located visual and haptic display. In my work, the detailed design of the electromagnet array for haptic rendering purposes is introduced, which is modelled and tested using Finite Element Method simulations. The model is characterized mathematically, and three methods for controlling the magnetic field are applied accordingly: direct control, system identification and adaptive control. The performance of the simulated model is evaluated in terms of magnetic field distribution, force strength, operation distance and force stiffness. The control algorithms are implemented and tested on a 3-by-3 and a 15-by-15 model, respectively. Simulations are performed on a 15-by-15 model to generate a haptic human face, which results in a smooth force field and accurate force exertion on the control points.

This thesis is focused on analysis of the factors that influence the yields of the wheat. This thesis is divided into three parts. The first part opens the problem of wheat cultivation. The second one concerns the methodologies of creating the econometrics models and the third one solves the problem as a whole. Considering a large data file I have a need to reduce it by the factor analysis. I estimate relevant econometric model by application different econometrics methods. This model will show the influences of technological, soil and climatic factors on the yields of wheat. At the end I confront the observed variables with predicted ones by the graininess of soil, climate and the year of the crops.

Today’s power systems are based on a centralised system and distribution networks that are considered as passive terminations of transmission networks. The high penetration of Distributed Generation (DG) at the distribution network level has created many challenges for this structure. New tools and simulation approaches are required to address the subject and to quantify the dynamic characteristics of the system. A distribution network or part of it with DG, Active Distribution Network Cell (ADNC), can no longer be considered as passive. An equivalent dynamic model of ADNC is therefore extremely important, as it enables power system operators to quickly estimate the impact of disturbances on the power system’s dynamic behaviour. A dynamic equivalent model works by reducing both the complexity of the distribution network and the computation time required to run a full dynamic simulation. It offers a simple and low-order representation of the system without compromising distribution network dynamic characteristics and behaviour as seen by the external grid. This research aims to develop a dynamic equivalent model for ADNC. It focuses on the development of an equivalent model by exploiting system identification theory, i.e. the grey-box approach. The first part of the thesis gives a comprehensive overview and background of the dynamic equivalent techniques for power systems. The research was inspired by previous work on system identification theory. It further demonstrates the theoretical concept of system identification, system load modelling and the modelling of major types of DG. An equivalent model is developed, guided by the assumed structure of the system. The problem of equivalent model development is then formulated under a system identification framework, and the parameter estimation methodology is proposed. The validation results of the effectiveness and accuracy of the developed model are presented. This includes the estimation of the parameter model using a clustering algorithm to improve the computational performance and the analysis of transformer impedance effects on the ADNC responses. The evaluation of probability density function, eigenvalue analysis and parameter sensitivity analysis for the model parameters are also presented. Typical model parameters for different network topologies and configurations are identified. Finally, the developed equivalent model is used for a large power system application. The accuracy and robustness of the developed equivalent model are demonstrated under small and large disturbance studies for various types of fault and different fault locations.

This thesis describes the design and implementation of genetic algorithm for approximation of non-linear mathematical functions using the least squares method. One objective of this work is to theoretically describe the basics of genetic algorithms. The second objective is to create a program that would be potentially used to approximate empirically measured data by the scientific institutions. Besides the theoretical description of the given subject, the text part of the work mainly deals with the design of the genetic algorithm and the whole application solving the given problem. Specific part of the assignment is that the developed application has to support approximation of points by various mathematical non-linear functions in several different intervals, and then it has to insure, that resulting functions are continuous throughout all the intervals. Described functionality is not offered by any available software.

The thesis focuses on theoretical and empirical analysis of economic growth and its implications for economic and social development of the Least Developed Countries (LDCs). The thesis proceeds from the assumption that economic growth is the necessary (but not sufficient) condition for economic, social and human development of societies and nations. In context of the LDCs, this assumption can be modified: it is assumed that it has been the low average rate of growth in the long-run that is associated with the complex social and economic issues of LDCs. The primary objective of the thesis is to verify this association within the LDCs, then to investigate factors that have been the major determinants for economic growth in (African) LDCs. From the perspective of theory the thesis is grounded in theories and models of economic growth that are crucial for researching factors of growth and its implications for development. The thesis focuses also on in-depth analysis of the LDCs both from the classification and statistical perspectives. The latter one is based on comparisons with selected groups of states within the World economy.