The purpose of this thesis is to discuss Markoff Numbers, their associated binary quadratic forms, together with the units in the associated real quadratic field. Relations betweeen the Markoff Numbers, the explicit structure of the automorph group of the forms, generators of the Commutator Subgroup Γ’ of SL₂(Z) = Γ and the lengths of geodesies on certain Riemann Surfaces are conveyed. A conjecture combining these relations is formulated and expressed at the end of this paper. / Science, Faculty of / Mathematics, Department of / Graduate

This dissertation applies policy improvement and successive approximation or value iteration to a general class of Markov decision processes with discounted costs. In particular, a class of Markov decision processes, called piecewise-linear, is studied. Piecewise-linear processes are characterized by the property that the value function of a process observed for one period and then terminated is piecewise-linear if the terminal reward function is piecewise-linear. Partially observable Markov decision processes have this property. It is shown that there are e-optimal piecewise-linear value functions and piecewise-constant policies which are simple. Simple means that there are only finitely many pieces, each of which is defined on a convex polyhedral set. Algorithms based on policy improvement and successive approximation are developed to compute simple approximations to an optimal policy and the optimal value function. / Business, Sauder School of / Graduate

In this thesis, I introduce a promising framework for representing an air traffic flow (stream) and flow-management action operating under weather uncertainty. I propose to use a meshed queuing and Markov-chain model---specifically, a queuing model whose service-rates are modulated by an underlying Markov chain describing weather-impact evolution---to capture traffic management in an uncertain environment. Two techniques for characterizing flow-management performance using the model are developed, namely 1) a master-Markov-chain representation technique that yields accurate results but at relatively high computational cost, and 2) a jump-linear system-based approximation that has promising scalability. The model formulation and two analysis techniques are illustrated with numerous examples. Based on this initial study, I believe that the interfaced weather-impact and traffic-flow model analyzed here holds promise to inform strategic flow contingency management in NextGen.

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Understanding cell motion facilitates the understanding of many biological processes such as wound healing and cancer growth. Constructing mathematical models that replicate amoeboid cell motion can help us understand and make predictions about real-world cell movement. We review a force-based model of cell motion that considers a cell as a nucleus and several adhesion sites connected to the nucleus by springs. In this model, the cell moves as the adhesion sites attach to and detach from a substrate. This model is then reformulated as a random process that tracks the attachment characteristic (attached or detached) of each adhesion site, the location of each adhesion site, and the centroid of the attached sites. It is shown that this random process is a continuous-time jump-type Markov process and that the sub-process that counts the number of attached adhesion sites is also a Markov process with an attracting invariant distribution. Under certain hypotheses, we derive a formula for the velocity of the expected location of the centroid.

In this thesis a Markov chain model, which can be used for analysing students’ performance and their academic progress, is developed. Being able to evaluate students progress is useful for any educational system. It gives a better understanding of how students resonates and it can be used as support for important decisions and planning. Such a tool can be helpful for managers of the educational institution to establish a more optimal educational policy, which ensures better position in the educational market. To show that it is reasonable to use a Markov chain model for this purpose, a test for how well data fits such a model is created and used. The test shows that we cannot reject the hypothesis that the data can be fitted to a Markov chain model. / I detta examensarbete utvecklas en Markov-kedjemodell, som kan användas för att analysera studenters prestation och akademiska framsteg. Att kunna utvärdera studenters väg genom studierna är användbart för alla utbildningssystem. Det ger en bättre förståelse för hur studenter resonerar och det kan användas som stöd för viktiga beslut och planering. Ett sådant verktyg kan vara till hjälp för utbildningsinstitutionens chefer att upprätta en mer optimal utbildningspolitik, vilket säkerställer en bättre ställning på utbildningsmarknaden. För att visa att det är rimligt att använda en Markov-kedjemodell för detta ändamål skapas och används ett test för hur väl data passar en sådan modell. Testet visar att vi inte kan avvisa hypotesen att data kan passa en Markov-kedjemodell.

Thesis advisor: Zhijie Xiao / The first two chapters study the copula Markov model combined with nonstationarity. The last chapter proposes a new structural break test with good size and power. / Thesis (PhD) — Boston College, 2020. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Economics.

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