Kerr metric is one of the most well-known and useful exact solutions of Einstein equations. We study various geometric properties of the Kerr spacetime in order to gain intuition for its spatial shape. In the review part we summarize basic features of the Kerr geometry, we write down Carter equations for geodesic motion in the Kerr spacetime, and we introduce kinematic characteristics of time-like and light-like congruences, such as expansion, shear and twist. In the second part of the thesis we calculate scalars for acceleration, expansion, shear and twist - and plot the corresponding "equipotential" surfaces - for several privi- leged congruences, namely the Carter observers, the static observers, the zero-angular- momentum observers, the principal null congruence and the recently found non-twisting null congruence(s). We also draw surfaces radially equidistant from the horizon and sur- faces spatially orthogonal to the PNC and to the twist-free congruences, as well as the surfaces of constant energy and redshift for the important time-like congruences. 1

The environmental and economic implications of the increase in Information and Communication Technology energy consumption have become a topic of research in energy efficiency. Most studies focus on the energy estimation and optimization of lower tiers of the hardware and software infrastructures. However, the software itself is an indirect driver of energy consumption, therefore, its energy implications can be to some extent controlled by the software design. Software design patterns belong to high-level software abstractions that represent solutions to common design problems. Since patterns define the structure and behavior of software components, their application may come at energy efficiency costs that are not obvious to the software developers. The existing body of knowledge on energy consumption of software design patterns contains a number of gaps, some of which are addressed within the scope of this thesis project. More specifically, we conducted a series of experiments on the estimation of energy consumption of Visitor and Observer/Listener patterns within the context of non-trivial data parsing in Python. Furthermore, we considered a Patternless alternative for the same task. Additionally, our measurements include runtime duration and memory consumption. The results show that the Visitor pattern led to the largest energy consumption, followed by Observer/Listener and finally the Patternless version. We found a strong relationship between runtime duration and energy consumption, thus coming to the conclusion that the longest-running pattern is the most energy-consuming one. The findings of the current study can be beneficial for Python software developers interested in the energy implications of software design patterns.

No / Model based control of automotive engines for fuel economy and pollution minimization depends on accuracy of models used. A number of mathematical models of automotive engine processes are available for this purpose but critical model parameters are difficult to obtain and generalize. This paper presents a novel method of online estimation of discharge coefficient of throttle body at the intake manifold of gasoline engines. The discharge coefficient is taken to be a varying parameter. Air mass flow across the throttle body is a critical variable in maintaining a closer to stoichiometric air fuel ratio; which is necessary to minimize the pollution contents in exhaust gases. The estimation method is based on sliding mode technique. A classical first Sliding mode observer is designed to estimate intake manifold pressure and the model uncertainty arising from the uncertain and time varying discharge coefficient is compensated by the discontinuity/switching signal of sliding mode observer. This discontinuity is used to compute coefficient of discharge as a time varying signal. The discharge coefficient is used to tune/correct the intake manifold model to engine measurements. The resulting model shows a very good agreement with engine measurements in steady as wells transient state. The stability of the observer is shown by Lyapunov direct method and the validity of the online estimation is successfully demonstrated by experimental results. OBD-II (On Board Diagnostic revision II) based sensor data acquisition from the ECU (Electronic Control Unit) of a production model vehicle is used. The devised algorithm is simple enough to be designed and implemented in a production environment. The online estimation of parameter can also be used for engine fault diagnosis work. (c) 2012 Elsevier B.V. All rights reserved.

<p>This thesis aims to design a controller to apply medication to patients with hypothyroidism, a disease that occurs due to the underacting thyroid gland. The body cannot produce sufficient thyroid hormones, which leads to an increase in the production of hormones in the pituitary gland. The thyroid malfunctioning could lead to other associated conditions like nausea, fatigue, heart conditions, higher cholesterol, and elevated blood pressure. Thus, it is essential to ensure that the levels of thyroid hormones, Triiodothyronine (T3) and Thyroxine (T4), are healthy. The production of these hormones is governed by the hypothalamus-pituitary-thyroid (HPT) axis, a part of the endocrine system. This illness cannot be cured but can be regulated entirely through medication. The standard practice to control hypothyroidism in patients is to prescribe a constant daily dosage of synthetic T4 (i.e., levothyroxine) and, in some cases, an additional dose of synthetic T3 (i.e., Liothyronine). In this thesis, simulation studies are performed where two patients with varying levels of hypothyroidism are prescribed constant doses of synthetic hormones. The medications initially help the patients but are unsuccessful in maintaining healthy ranges. Using model predictive control, an observer-controller-based compensator is proposed to prescribe varying medication doses as inputs based on the patient's requirement. The inputs are quantized to be practically implemented in a real patient scenario. This compensator successfully improves the patient's hormone levels toward healthy values and ensures that the hormone trajectories follow the body's circadian rhythm.  </p>

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