Today, 3D models of cities are created from aerial images using a camera rig. Images, together with sensor data from the flights, are stored for further processing when building 3D models. However, there is a market demand for a more mobile solution of satisfactory quality. If the camera position can be calculated for each image, there is an existing algorithm available for the creation of 3D models. This master thesis project aims to investigate whether the iPhone 4 offers good enough image and sensor data quality from which 3D models can be created. Calculations on movements and rotations from sensor data forms the foundation of the image processing, and should refine the camera position estimations. The 3D models are built only from image processing since sensor data cannot be used due to poor data accuracy. Because of that, the scaling of the 3D models are unknown and a measurement is needed on the real objects to make scaling possible. Compared to a test algorithm that calculates 3D models from only images, already available at the SBD’s system, the quality of the 3D model in this master thesis project is almost the same or, in some respects, even better when compared with the human eye.

In this thesis, a grid-connected wind-energy converter system including a matrix converter is proposed. The matrix converter, as a power electronic converter, is used to interface the induction generator with the grid and control the wind turbine shaft speed. At a given wind velocity, the mechanical power available from a wind turbine is a function of its shaft speed. Through the matrix converter, the terminal voltage and frequency of the induction generator is controlled, based on a constant V/f strategy, to adjust the turbine shaft speed and accordingly, control the active power injected into the grid to track maximum power for all wind velocities. The power factor at the interface with the grid is also controlled by the matrix converter to either ensure purely active power injection into the grid for optimal utilization of the installed wind turbine capacity or assist in regulation of voltage at the point of connection. Furthermore, the reactive power requirements of the induction generator are satisfied by the matrix converter to avoid use of self-excitation capacitors. The thesis addresses two dynamic models: a comprehensive dynamic model for a matrix converter and an overall dynamical model for the proposed wind turbine system. The developed matrix converter dynamic model is valid for both steady-state and transient analyses, and includes all required functions, i.e., control of the output voltage, output frequency, and input displacement power factor. The model is in the qdo reference frame for the matrix converter input and output voltage and current fundamental components. The validity of this model is confirmed by comparing the results obtained from the developed model and a simplified fundamental-frequency equivalent circuit-based model. In developing the overall dynamic model of the proposed wind turbine system, individual models of the mechanical aerodynamic conversion, drive train, matrix converter, and squirrel-cage induction generator are developed and combined to enable steady-state and transient simulations of the overall system. In addition, the constraint constant V/f strategy is included in the final dynamic model. The model is intended to be useful for controller design purposes. The dynamic behavior of the model is investigated by simulating the response of the overall model to step changes in selected input variables. Moreover, a linearized model of the system is developed at a typical operating point, and stability, controllability, and observability of the system are investigated. Two control design methods are adopted for the design of the closed-loop controller: a state-feedback controller and an output feedback controller. The state-feedback controller is designed based on the Linear Quadratic method. An observer block is used to estimate the states in the state-feedback controller. Two other controllers based on transfer-function techniques and output feedback are developed for the wind turbine system. Finally, a maximum power point tracking method, referred to as mechanical speed-sensorless power signal feedback, is developed for the wind turbine system under study to control the matrix converter control variables in order to capture the maximum wind energy without measuring the wind velocity or the turbine shaft speed.

In markets with cyclical fluctuations, firms may have different dynamic decision rules facing upturns and downturns of industry cycles. This paper extends the dynamic factor demand model to consider industry cycles. Because investment behavior could be endogenous uncertainty involved on industry dynamics, the current industry dynamic models with state-of-the-art would not appropriately interpret industry dynamics. In order to solve the uncertain problem, we utilize the idea of transfer probability in Markov switching model to catch the industry cyclical behavior. Explicitly incorporating the Markov regime switching mechanism based on Nelson and Kim (2000), this paper measures the firm¡¦s dynamic adjustments when facing upturns and downturns of industry cycles. The empirical work is based on firm level data of Taiwan high-technology industries. The empirical results show that the expansionary strategy in labor and capital usage may not have positive impacts on output when considering uncertainty that may be casued by business cycles. To have correct prediction in cyclical fluctuation becomes important task for high-technology firms. However, the positive contribution of exogenous technology to output growth is so significant. This proves why every industry tries to impel technology in recent years. The industry dynamic model integrated with cyclical fluctuation and demand uncertainty allows us to examine how sharp changes in financial factors might affect investment behavior, technological nature and adjustment effects for industries in facing demand and investment shocks.

<p>In this work a particle filter (PF) that uses a one-dimensional dynamic model to estimate the position of vehicles traveling on a road is derived. The dynamic model used in the PF is a second order linear-Gaussian model. To be able to track targets traveling both on and off road two different multiple model filters are proposed. One of the filters is a modified version of the Efficient Interacting Multiple Model (E-IMM) and the other is a version of the Multiple Likelihood Models (MLM). Both of the filters uses two modes, one for the on road motion and one for the off road motion. The E-IMM filter and the MLM filter are compared to the standard PF to be able to see the performance gain in using multiple models. This result indicates that the multiple model filters have better performance, at least when the true mode switching probabilities are used.</p> / <p>Den här arbetet presenterar ett partikelfilter som använder sig av en endimensionell dynamisk modell för att skatta positionen på fordon som befinner sig på någon väg. Den dynamiska modellen som används i partikelfiltret är en andra ordningens linjär-gaussisk modell. För att kunna spåra fordon som befinner sig både på och utanför vägen så föreslås två olika multipla filter. Ena filtret är en modifierad</p><p>variant av Efficient Interacting Multiple Model (E-IMM) och den andra är en version a Multiple Likelihood Models (MLM). Båda filtren använder sig av två moder, en för rörelse på vägen och en för rörelse utanför vägen. E-IMM filtret och MLM filtret jämförs med ett standard partikelfilter för att kunna se förbättringen vid använding av multipla modeller. Resultatet visar att båda multipla modell filtren ger bättre resultat, i varje fall då rätt sannolikheter för modbyte används.</p>

Analysis of circular data becomes more and more popular in many fields of studies. In this report, I present two statistical analysis of circular data using von Mises distributions. Firstly, the maximization-expectation algorithm is reviewed and used to classify and estimate circular data from the mixture of von Mises distributions. Secondly, Forward Filtering Backward Smoothing method via particle filtering is reviewed and implemented when circular data appears in the dynamic state-space models. / text

This thesis presents improvements and extensions of a previously presented threat assessment algorithm. The algorithm uses Monte Carlo simulation to find threats in a road scene. It is shown that, by using a wider sample distribution and only apply the most likely samples from the Monte Carlo simulation, for the threat assessment, improved results are obtained. By using this method more realistic paths will be chosen by the simulated vehicles and more complex traffic situations will be adequately handled. An improvement of the dynamic model is also suggested, which improves the realism of the Monte Carlo simulations. Using the new dynamic model less false positive and more valid threats are detected. A systematic method to choose parameters in a stochastic space, using optimisation, is suggested. More realistic trajectories can be chosen, by applying this method on the parameters that represents the human behaviour, in the threat assessment algorithm. A new definition of obstacles in a road scene is suggested, dividing them into two groups, Hard and Soft obstacles. A change to the resampling step, in the Monte Carlo simulation, using the soft and hard obstacles is also suggested.

In this work a particle filter (PF) that uses a one-dimensional dynamic model to estimate the position of vehicles traveling on a road is derived. The dynamic model used in the PF is a second order linear-Gaussian model. To be able to track targets traveling both on and off road two different multiple model filters are proposed. One of the filters is a modified version of the Efficient Interacting Multiple Model (E-IMM) and the other is a version of the Multiple Likelihood Models (MLM). Both of the filters uses two modes, one for the on road motion and one for the off road motion. The E-IMM filter and the MLM filter are compared to the standard PF to be able to see the performance gain in using multiple models. This result indicates that the multiple model filters have better performance, at least when the true mode switching probabilities are used. / Den här arbetet presenterar ett partikelfilter som använder sig av en endimensionell dynamisk modell för att skatta positionen på fordon som befinner sig på någon väg. Den dynamiska modellen som används i partikelfiltret är en andra ordningens linjär-gaussisk modell. För att kunna spåra fordon som befinner sig både på och utanför vägen så föreslås två olika multipla filter. Ena filtret är en modifierad variant av Efficient Interacting Multiple Model (E-IMM) och den andra är en version a Multiple Likelihood Models (MLM). Båda filtren använder sig av två moder, en för rörelse på vägen och en för rörelse utanför vägen. E-IMM filtret och MLM filtret jämförs med ett standard partikelfilter för att kunna se förbättringen vid använding av multipla modeller. Resultatet visar att båda multipla modell filtren ger bättre resultat, i varje fall då rätt sannolikheter för modbyte används.

In this study, a demand oriented simultaneous equation macroeconometric model with a dynamic perspective is constructed in order to investigate the impact of workers&rsquo / remittances on output growth via their effects on key macro variables such as private consumption, investment and imports for Turkey. The study covers the period of 1964-2003 on an annual basis. Results of the analysis suggest that workers&rsquo / remittances affect output growth in a positive manner through the multiplier process. It is found that the highest induced growth rate by remittances to output growth belongs to the early 1970s especially the year of 1973, which corresponds to the date of first oil shock and also the end of labour migration to Europe. Thus, it is concluded that although workers&rsquo / remittances have been mostly used for consumption and imports as mentioned in most of the studies both for Turkey and other countries, remittances contributed to economic growth of Turkey positively through the multiplier process especially in the early 1970s.

Este trabalho apresenta um modelo de dinâmica de desenvolvimento distribuído de software, cujo objetivo é representar a realidade e os aspectos de ambientes de DDS (Desenvolvimento distribuído de software), a fim de torná-los observáveis e descritíveis qualitativa e quantitativamente. Um modelo preliminar foi elaborado a partir da revisão bibliográfica e de um caso de experimentação desenvolvido por LErario et al (2004). Para a construção e validação deste modelo, a metodologia de estudo de múltiplos casos foi aplicada em diversas organizações que desenvolvem software de maneira distribuída. Ao modelo preliminar foram adicionados estados e transições significantes para a dinâmica do desenvolvimento distribuído de software, originando então o M3DS (Modelo de Dinâmica de Desenvolvimento Distribuído de Software). Duas versões do M3DS são apresentadas. Uma versão construída sobre uma máquina de estados, cujo objetivo é representar apenas a transições entre os estados. Outra versão equivalente, porém mais formal, é apresentada no formato de redes de Petri, na qual é possível visualizar a dependência entre transições e mudanças de estado. Com este modelo, é possível compreender o funcionamento de um projeto distribuído e auxiliar na eficácia da gestão da rede de produção, além de auxiliar as demais entidades e pessoas envolvidas a obterem um posicionamento na rede mais preciso. O M3DS pode, também, auxiliar a detecção proativa de problemas originados a partir do desenvolvimento a distância. Os resultados apresentados neste trabalho respondem a questão de como as organizações desenvolvedoras de software produzem software de maneira distribuída. A riginalidade da pesquisa centra-se na construção de um modelo de dinâmica do desenvolvimento distribuído elaborado com os dados levantados a partir de seis estudos de casos. / This work presents a dynamic model of distributed development of software, whose objective is to represent the reality and the aspects of DDS environments, in order to turn them qualitatively and quantitatively observable. A preliminary model was elaborated from the bibliographical revision and an experimentation case developed by L\'Erario et al (2004). The construction and validation of this model used the methodology multiple cases study in several organizations that develop software in a distributed way. After this, states and transitions were added in the dynamics model of the distributed development of software creating the M3DS. (Dynamics Model of Distributed Development of Software). Two versions of M3DS are presented. A version built on a state machine whose objective is demonstrating the transitions among the states. Another version equivalent, however more formal, it is presented in the format of Petri nets. The second version makes possible to visualize the dependence between transitions and state changes. With this model it is possible to understand the operation of a distributed project, aiding in the effectiveness of the manager of the network production and people can obtain a precise positioning in network. Besides, M3DS can also aid the proactive detection of problems originated from the development at the distance. The results presented in this work answer the question: how the development software organizations produce software in a distributed way. The originality of the research is the construction of a model of dynamics of the distributed development elaborated from data of six cases studies.

Sob o regime de metas de inflação cabe à autoridade monetária balisar seus instrumentos de política de forma a manter a estabilidade do nível geral de preços. Neste aspecto, pelo caráter volátil dos índices de inflação cheia os bancos centrais de todo o mundo utilizam o conceito de núcleo da inflação para tentar capturar com maior acurácia a tendência subjacente da taxa de inflação. Muitas vezes os índices de preços ao consumidor estão altamente sujeitos a volatilidades decorrentes de fatores temporários e muitas vezes localizados. E já que o objetivo da autoridade monetária está em zelar pela estabilidade \"real\" (ou de fato) do nível geral de preços, mudanças temporárias ou localizadas não afetam as taxas de inflação no longo prazo e, consequentemente, não cabe à autoridade monetária responder a tais mudanças, pois isso poderia gerar uma volatilidade desnecessária à política monetária com consequência sobre as flutuações da atividade econômica no período. Dessa forma, Bancos Centrais do mundo inteiro fazem uso de núcleos de inflação. Este trabalho aplica uma nova metodologia de cálculo de núcleo para a inflação brasileira, utilizando o modelo de fatores dinâmicos generalizados. Esta abordagem permite diferenciar fatores localizados (idiossincráticos) dos choques comuns (generalizados) em um grande conjunto de dados. Usamos o IPCA em seu nível mais desagregado e geramos o choque comum entre este conjunto. E a este choque chamamos de núcleo da inflação. Sua eficiência em termos de antecedência à inflação cheia no curto prazo foi testada por meio de uma cointegração, VEC, tais resultados foram comparados com o desempenho do núcleo por Exclusão, mostrando uma maior eficiência do núcleo aqui encontrado. / Under the inflation target system lies to the monetary authority the evaluation of the best tools to keep general price stability. In this context, due to the volatile character of the inflation, central banks around the world use the concept of the inflation core in attempt to capture in a more accurately way the prices trends. Several times, consumer prices indexes are subjected to very volatile prices, due to temporary or localized factors. As the vigilance of the monetary authority relies on the real stability of the general prices level, temporary or localized changes doesn\'t affect the inflation indexes in the long run and, therefore, it\'s not an issue to the central bank to respond to this variations, this could indeed create an unnecessary volatility to the monetary politics with consequences to the economic activity in the period. This way, central banks around the world calculate and use inflation core. This paper applies a new methodology to calculate the inflation core to the Brazilian inflation, using the generalized dynamic factor model. With this approach it\'s possible to differentiate the localized factors from the common (generalized) shocks in a great data set. We use IPCA on its more disaggregated level and create a common shock in the data set, and we name this shock the inflation core. We test the advance of this core to the inflation in the short run using a VEC, and compare with the results of the Exclusion core, we show that your core by using dynamic factor model is more effcient then Exclusion core.