The study describes how cointegration-based techniques can be employed in order to construct profitable trading strategies that exploit mispricing events between similar securities. Particularly, the Johansen Maximum Likelihood Estimation and the Kalman filter approaches are applied to the universe of 200 most liquid ETF stocks traded on NYSE and NASDAQ. The results show that the strategies are quite sensitive to transaction costs, but are still able to maintain profitability even after accounting for a conservative level of transaction costs. While the Kalman filter produces better results on daily data, the 15-minute timeframe is dominated by portfolios constructed by the Johansen cointegration test. Both strategies achieve significantly higher risk-adjusted returns on the intraday timeframe. The study also reveals a performance decline of both strategies in the period of 2013-2015 and outlines possible interpretation of such event.

O controle de plantas daninhas é uma importante preocupação para a agricultura tendo em vista as perdas de produtividade que estas causam ao competir com a cultura por água, luz e nutrientes. O uso de herbicida é a forma de manejo mais empregada em todo o mundo para o controle destas plantas. Entretanto, o uso frequente de um dado herbicida, além de causar diversos impactos ambientais, pode levar à diminuição da eficiência do próprio herbicida ao promover a seleção de plantas que são resistentes a este herbicida. Com o crescente número de novos casos de biótipos resistentes aos herbicidas, conter a evolução da resistência tornou-se uma necessidade para a agricultura convencional. Assim, grande esforço tem sido despendido para compreender este fenômeno e tentar contornar este problema. Neste sentido, os modelos computacionais se apresentam como importantes ferramentas para investigar os efeitos dos diversos fatores, em particular das estratégias de aplicação dos herbicidas, que influenciam na dinâmica da evolução da resistência. Com esta motivação, este trabalho tem como objetivo propor e estudar algumas estratégias de aplicação de herbicidas, ou ditos simplesmente controladores, que sejam implementáveis e que diminuam os impactos ambientais considerando a evolução da resistência. Para isto, assumimos que existe um herbicida, denominado neste trabalho por herbicida recomendado, que é o preferível dentre os disponíveis por produzir uma boa relação entre os benefícios produtivos e os malefícios aos ecossistemas. Para projetar os controladores, assumimos que é possível obter informações sobre a identificação visual da resistência em campo, feitas por um agente quando o número de indivíduos resistentes ultrapassa um certo limiar, assim como informações sobre a quantidade de plantas daninhas na área, feita possivelmente empregando técnicas de sensoriamento remoto. Então, para definir os controladores, empregamos diretamente a identificação visual da resistência e estimativas para o banco de sementes e para a fração dos genótipos do banco, geradas por um filtro de Kalman a partir de informações sobre a quantidade de plantas na área. Os controladores foram avaliados em relação à preservação da eficiência do herbicida recomendado, produtividade, impacto ambiental e propagação da resistência. Concluímos destes estudos que o controlador sugerido pode apresentar melhores resultados que os obtidos por controladores ditos convencionais, que se baseiam apenas na informação de identificação da resistência em campo. / Weed control is a major concern in agriculture as it causes significant loss of productivity by competition for water, sunlight and nutrients. The use of herbicides is the most common practice in the world to control them. However, the frequent use of a particular herbicide, besides causing many environmental impacts, may lead to loss of efficiency by promoting herbicide resistance via selection of resistant individuals. Considering the increasing number of herbicide resistant biotic, restraining resistance evolution is becoming a necessity for the conventional agriculture. This motivates a great deal of research effort to understand the involved phenomena and eventually to circumvent the problem. To this end, computational models are of great aid to understand the impact of many different aspects involved in this problem, in particular, to understand how different herbicide strategies usage lead to different resistance evolution dynamics. In this thesis we propose and study some strategies for herbicide application, which we refer to as controllers. We seek for controllers that can be implemented in real word crops growing, while decreasing environmental impacts and restrain resistance evolution. We assume that there exists one herbicide of choice for a given crop, meaning that it is preferred in terms of environmental impact and efficiency. To define the controllers, we assume that it is possible to obtain visual information on resistance, meaning that we observe when the proportion of resistant individuals is above a threshold. Also, we assume noisy observation of the number of adult weed individuals, possibly made by remote sensing. So, the controller directly employs the visual identification information and an estimate for the number of resistant seeds in the seed bank, generated by the Kalman filter using information on the number of adult weed. This strategy was evaluated in terms of herbicide efficiency preservation, crop production, environmental impact and resistance proliferation. We conclude that the proposed control strategies performed better than other strategies, called conventional strategies that are based only on the visual identification information.

Motorradfahrer gehören zu den am meisten gefährdeten Verkehrsteilnehmern im Straßenverkehr. Häufig ist die Unfallursache ein Kontrollverlust auf Landstraßen, der durch Ausnutzung des physikalischen Potenzials in Form von größeren Schräglagenwinkeln vermieden werden könnte. Gleichzeitig sind in der Realität gefahrene Schräglagen über eine größere Gruppe von Fahrern und eine längere Strecke unbekannt, was vor allem auf die erforderliche spezielle Messtechnik zurückzuführen ist. Der Schwerpunkt liegt daher auf der Entwicklung eines kostengünstigen Messverfahrens zur Messung der Schräglagenwinkel von Motorrädern. Smartphones zeichnen sich in der Regel durch integrierte Inertialsensoren aus, die für die Erfassung der Fahrdynamik von Motorrädern geeignet sind. Mit Hilfe einer auf die Anforderungen zugeschnittenen Smartphone-App zur Erfassung von Messdaten auf dem Motorrad werden die Daten der Sensoren aufgezeichnet. Anschließend werden mittels einer Offline-Auswertung die Drehwinkel zwischen dem Smartphone und dem Motorrad-Koordinatensystem bestimmt, die inertialen Messdaten transformiert und der Schräglagenwinkel berechnet. Ein wesentlicher Bestandteil ist die Validierung der entwickelten Messkette durch einen Vergleich der Ergebnisse mit einem hochpräzisen Messsystem. Dieser wurde auf verschiedenen Strecken zur Bestimmung der Datenqualität durchgeführt. Als Machbarkeitsstudie diente eine Probandenstudie, die die Praxistauglichkeit der Messkette bestätigte. Die Studienergebnisse werden zusätzlich auszugsweise dargestellt und diskutiert. Die erfolgreiche Validierung auf verschiedenen Strecken, die Praxistauglichkeit der Datenerfassung und die Genauigkeit des Messsystems ermutigen dazu, die Smartphone-App auf ein größeres Panel von Testpersonen auszurollen und damit Daten über ein größeres Fahrerkollektiv zu erheben.:Introduction, State of Research, Methods, Measurement Chain Verification, Results and Discussion, Conclusion / Motorcyclists are among the most vulnerable road users in road traffic. Often, the cause of accidents is a loss of control on rural roads which could be averted by making use of the physical potential in terms of larger lean angles. At the same time, in reality driven lean angles over a larger group of riders and a longer route are unknown which is mainly due to the special measuring technology required. The focus is therefore on the development of a low-cost measurement method for measuring the lean angles of motorcycles. Smartphones are usually characterized by integrated inertial sensors, which are suitable for the acquisition of motorcycle driving dynamics. Employing a smartphone app tailored to the requirements for collecting measurement data on the motorcycle, the data of the sensors are recorded. During the offline evaluation, the rotation angles between the smartphone and the motorcycle coordinate system are determined, the inertial measurement data are transformed and the roll angle is calculated. An essential part is the alignment of the developed measurement chain with a high-precision measurement system. This was carried out on different routes and thus the data quality was determined. As a feasibility study, a test person study with several participants was carried out, which confirmed the practical suitability of the measurement chain. Hence, the study outcomes are briefly shown and discussed. The successful validation on different routes, the practical suitability of the data acquisition and the accuracy of the measurement system encourage to roll out the smartphone app to a larger panel of test persons and thus to collect data on a larger driver collective.:Introduction, State of Research, Methods, Measurement Chain Verification, Results and Discussion, Conclusion

Conventional coastal ocean models solve the shallow water equations, which describe the conservation of mass and momentum when the horizontal length scale is much greater than the vertical length scale. In this case vertical pressure gradients in the momentum equations are nearly hydrostatic. The outputs of coastal ocean models are thus sensitive to the bottom stress terms defined through the formulation of Manning’s n coefficients. This thesis considers the Bayesian inference problem of the Manning’s n coefficient in the context of storm surge based on the coastal ocean ADCIRC model. In the first part if the thesis, we apply an ensemble-based Kalman filter, the singular evolutive interpolated Kalman (SEIK) filter to estimate both a constant Manning’s n coefficient and a 2-D parameterized Manning’s coefficient on one ideal and one of more realistic domain using observation system simulation experiments (OSSEs). We study the sensitivity of the system to the ensemble size. we also access the benefits from using an inflation factor on the filter performance. To study the limitation of the Guassian restricted assumption on the SEIK filter, we also implemented in the second part of this thesis a Markov Chain Monte Carlo (MCMC) method based on a Generalized Polynomial chaos (gPc) approach for the estimation of the 1-D and 2-D Mannning’s n coefficient. The gPc is used to build a surrogate model that imitate the ADCIRC model in order to make the computational cost of implementing the MCMC with the ADCIRC model reasonable. We evaluate the performance of the MCMC-gPc approach and study its robustness to different OSSEs scenario. we also compare its estimates with those resulting from SEIK in term of parameter estimates and full distributions. we present a full analysis of the solution of these two methods, of the contexts of their algorithms, and make recommendation for fully realistic application.

In this work, we propose three control strategies from different perspectives to solve the alignment problem for different optical wireless communication (OWC) systems. • Experimental modeling based strategy: we model and analyze the vibration effects on the stationary OWC system (e.g. urban free-space optical (FSO) communication system in our case). The proposed Bifurcated-Gaussian (B-G) distribution model of the receiver optical power is derived under different vibra- tion levels and link distances using the nonlinear iteration method. Besides, the UFSO channel under the effects of both vibration and atmospheric turbulence is also explored under three atmospheric turbulence conditions. Our proposed B-G distribution model helps to easily evaluate the link performance of UFSO systems and paves the way for constructing completed auxiliary control subsys- tems for robust UFSO links. • Extremum seeking control based strategy: we propose an extremum seeking control (ESC) based strategy for the mobile OWC system. Our proposed ap- proach consists of coarse alignment and fine alignment. The coarse alignment using feedback proportional-derivative (PD) control is responsible for tracking and following the receiver. For fine alignment, the perturbation-based extremum seeking control (ESC) is adopted for a continuous search for the optimal posi- tion, where the received optical power is maximum in the presence of distur- bance. The proposed approach is simple, effective, and easy to implement. • Time scale theory based strategy: we design a time scale based Kalman filter for the intermittent OWC system. First, the algorithm of Kalman filter on time scales is presented, followed by several numerical examples for interpretation and analysis. The design of Kalman filter on time scales for our simulated vibrating OWC system is then discussed, whose results are analyzed thoroughly and further validated by a reference system. The proposed strategy has great potential for solving the problem of observer design in the case of intermittent received signals (non-uniform measurements) and paves the way for further controller design. The three proposed control strategies directly or indirectly solve the beam align- ment problem for optical communication systems, supporting the development of robust optical communication link.

In this paper, a computer vision system for counting people standing in line is presented. In this application, common techniques such as Adaptive Background Subtraction (ABS), blob tracking with Kalman filter, and occlusion resistive techniques are used to detect and track people. Additionally, a novel method using Dual Adaptive Background Subtractors (DABS) is implemented for dynamically determining the line region in a real-world crowded scene, and also as an alternative target acquisition to regular ABS. The DABS technique acts as a temporal bandpass filter for motion, helping identify people standing in line while in the presence of other moving people. This is achieved by using two ABS with different temporal adaptiveness. Unlike other computer vision papers which perform tests in highly controlled environments, the DABS technique is tested in a crowded Starbucks© at the Cal Poly student union. For any length of people standing in line, result shows that DABS has a lower mean error by one or more people when compared to ABS. Even in challenging crowded scenes where the line can reach 19 people in length, DABS achieves a Normalized RMS Error of 43%.

The diploma thesis deals with putting the pendulum into upright position and its stabilization on a real system. The opening chapter describes the limiting various implementation inverse pendulums, the use of major laboratory tasks in industry, and the selection of appropriate methods for stabilization. The real system was properly identified and parameterized. The mathematical model of the inverse pendulum was derived using the Lagrange method of the second type, the nonlinear system was converted into a status description and linearized for the needs of the state controller design. The system was simulated in the Matlab Simulink environment. The LQR controller was chosen as the regulator stabilizing in upright cases. A Kalman controller in discrete form was prepared for the filter signal and estimation of residual states. The energy method was chosen for the upright pendulums. The proposed methods were tested and implemented in simulation and on a real system.

Tahle práce se zabývá monitorováním venkovních vysokonapěťových vedeních, což mohou být vedení od 70kV do 400kV. Senzory jsou umístěny na vodiči a hlavní myšlenkou je vyhodnotit mechanické chování vodičů, a to od nízkých frekvencí (zlomky Hz) až po vysoké frekvence (desítky Hz). Tahle práce se zabývala pohyby o nízkých frekvencích a vysokých amplitudách a popsala možnosti sestavení těchto pohybů na základě měření ze senzorů. Konkrétně se jedná o pohyby v případě silného větru, zkratu, opadávání ledu nebo dalších. Všechno tohle pomáhá operátorů dělat rozhodnutí ohledně provozování sítí. Vývoj zahrnuje přidání/kombinaci nových senzorů, popsání matematického algoritmu potřebného k sestavení pohybu na základě toho co bylo změřeno, ať už se jedná o hodnoty získané simulací, laboratorním testem nebo reálným měřením na vedení.

The goal of this thesis is to deal with comparison of algorithms in the field of sensorless control of permanent magnet synchronous motor. It is focused mainly on deterministic methods of estimation, verification of their dynamic responses and the influence of parasitic effects. Implementation of selected algortihms on DSP in fractional arithmetic with verification by Processor-in-the-loop method is described in second part. The last part describes use of algorithms on real drive.

This thesis is concerned with attitude estimation of small flying robots using low cost, small-sized inertial and magnetic sensors. A quaternion-based extended Kalman filter is used, which adaptively compensates external acceleration. External acceleration is the main source of estimation error. If external acceleration is detected, the accelerometer measurement covariance matrix of the Kalman filter is adjusted. The proposed algorithms are verified through experiments. Selected algorithm is implemented on STM32F4DISCOVERY development board.