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Sökning: LAR1:uu > Licentiatavhandling

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  • Aalto, Aino-Maija (författare)
  • The (in)effectiveness of financial incentive on fertility behaviour : Childcare –a safety net for children?
  • 2017
  • Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • Is childcare a safety net for vulnerable children? This paper investigates the role of childcare for the health outcomes of children whose parents are unemployed. Exploiting time variation in childcare access resulting from a reform requiring Swedish municipalities to provide childcare also for children with unemployed parents, we estimate causal effects on health, as measured by register data on hospitalizations. We find that access to childcare reduced hospitalizations for infections among toddlers, especially among boys. Among children in preschool age access to childcare caused a temporary increase in hospitalization for infections the year they got access to childcare.
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  • Abd-Elrady, Emad (författare)
  • Harmonic signal modeling based on the Wiener model structure
  • 2002
  • Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • The estimation of frequencies and corresponding harmonic overtones is a problem of great importance in many situations. Applications can, for example, be found in supervision of electrical power transmission lines, in seismology and in acoustics. Generally, a periodic function with an unknown fundamental frequency in cascade with a parameterized and unknown nonlinear function can be used as a signal model for an arbitrary periodic signal. The main objective of the proposed modeling technique is to estimate the fundamental frequency of the periodic function in addition to the parameters of the nonlinear function.The thesis is divided into four parts. In the first part, a general introduction to the harmonic signal modeling problem and different approaches to solve the problem are given. Also, an outline of the thesis and future research topics are introduced.In the second part, a previously suggested recursive prediction error method (RPEM) for harmonic signal modeling is studied by numerical examples to explore the ability of the algorithm to converge to the true parameter vector. Also, the algorithm is modified to increase its ability to track the fundamental frequency variations.A modified algorithm is introduced in the third part to give the algorithm of the second part a more stable performance. The modifications in the RPEM are obtained by introducing an interval in the nonlinear block with fixed static gain. The modifications that result in the convergence analysis are, however, substantial and allows a complete treatment of the local convergence properties of the algorithm. Moreover, the Cramér–Rao bound (CRB) is derived for the modified algorithm and numerical simulations indicate that the method gives good results especially for moderate signal to noise ratios (SNR).In the fourth part, the idea is to give the algorithm of the third part the ability to estimate the driving frequency and the parameters of the nonlinear output function parameterized also in a number of adaptively estimated grid points. Allowing the algorithm to automatically adapt the grid points as well as the parameters of the nonlinear block, reduces the modeling errors and gives the algorithm more freedom to choose the suitable grid points. Numerical simulations indicate that the algorithm converges to the true parameter vector and gives better performance than the fixed grid point technique. Also, the CRB is derived for the adaptive grid point technique.
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  • Abdalmoaty, Mohamed, 1986- (författare)
  • Learning Stochastic Nonlinear Dynamical Systems Using Non-stationary Linear Predictors
  • 2017
  • Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • The estimation problem of stochastic nonlinear parametric models is recognized to be very challenging due to the intractability of the likelihood function. Recently, several methods have been developed to approximate the maximum likelihood estimator and the optimal mean-square error predictor using Monte Carlo methods. Albeit asymptotically optimal, these methods come with several computational challenges and fundamental limitations.The contributions of this thesis can be divided into two main parts. In the first part, approximate solutions to the maximum likelihood problem are explored. Both analytical and numerical approaches, based on the expectation-maximization algorithm and the quasi-Newton algorithm, are considered. While analytic approximations are difficult to analyze, asymptotic guarantees can be established for methods based on Monte Carlo approximations. Yet, Monte Carlo methods come with their own computational difficulties; sampling in high-dimensional spaces requires an efficient proposal distribution to reduce the number of required samples to a reasonable value.In the second part, relatively simple prediction error method estimators are proposed. They are based on non-stationary one-step ahead predictors which are linear in the observed outputs, but are nonlinear in the (assumed known) input. These predictors rely only on the first two moments of the model and the computation of the likelihood function is not required. Consequently, the resulting estimators are defined via analytically tractable objective functions in several relevant cases. It is shown that, under mild assumptions, the estimators are consistent and asymptotically normal. In cases where the first two moments are analytically intractable due to the complexity of the model, it is possible to resort to vanilla Monte Carlo approximations. Several numerical examples demonstrate a good performance of the suggested estimators in several cases that are usually considered challenging.
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  • Abrahamsson, Johan (författare)
  • Kinetic Energy Storage and Magnetic Bearings, for vehicular applications
  • 2011
  • Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • One of the main challenges in order to make electric cars competitive with gaspowered cars is in the improvement of the electric power system. Although many of the energy sources currently used in electric vehicles have sufficiently high specific energy, their applicability is limited due to low specific power. It would therefore be advantageous to create a driveline with the main energy storage separated from a smaller energy buffer, designed to have high power capabilities and to withstand frequent and deep discharge cycles. It has been found that rotating kinetic energy storage in flywheels is very well suited for this type of application. The work presented in this thesis and the included papers span a number of topcis Introductory overview - This section explains the concept of the modern flywheel, and investigates some of its properties. It illustrates the concepts with a number of examples, relevant for the usage of flywheels in vehicular applications. Experimental set-up - The construction of a complete electric driveline is ongoing within the division for Electricity at Uppsala University. An optimized electric machine has been constructed and connected with a programmable load, as well as with a DC power source through power electronics controlled by PWM. As a part of this system, an experimental set-up of an active magnetic bearing for two degrees-of-freedom has been constructed. The work with this device is described in detail and some preliminary results are presented. Self-bearing machine - The electric machine developed for the existing driveline is coreless, double wound and with a double rotor. In order to achieve magnetic bearing functionality in this device for all DOF, a novel Lorentz force self-bearing machine is suggested. The design is analyzed analytically and numerically.
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