The provision and pricing of parking are recognized as important tools for achieving transportation demand management (TDM) objectives. Much of the existing literature on the topic concentrates on downtown cores and calls for the application of maximum parking allowances to limit supplies. This thesis presents an analysis of existing suburban parking supplies in order to quantify parking maxima. The total number of spaces provided, footprint required to accommodate the spaces and the employment to which parking is providing are quantified. The totals are separated by different land use categories and quantities of employment are normalized to account for high trip-generating jobs such as retail. Parking supplies are examined as a function of traditional land use market theory and across primary land use categories. The results indicate that employment is a fairly weak indicator of parking supply, while weighted employment that considers the effects of retail is a much stronger indicator. On average, very high and very low land use densities have the lowest parking requirements per employee (0.39 spaces per employee) while moderate land use densities have the least diversity of land use, yet the highest supply of employee parking (4.01 spaces per employee). The methodology applied may be used to produce quantitative maxima to be incorporated into local parking bylaws that are recognized as potentially strong TDM tools. Further research that compares the observed parking supply patterns across a series of mid-sized cities is recommended to make stronger conclusions regarding the range of maximum values.

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Turbot (Psetta maxima) and flounder (Platichthys flesus) are two species of flatfish both having their nursery areas around the shores of Gotland in the Baltic Sea. The common brown shrimp (Crangon crangon) is a known predator on newly settled plaice (Pleuronectes platessa) in the North Sea area and is also found in the Baltic Sea. Experiments were carried out to see if the brown shrimp is predating on juvenile turbot and flounder, and if so on which sizes, and if the brown shrimp prefers any of the flatfish species, and also to see if there is a difference between day and night in density of the shrimp, i.e. when the fish might be subjected to predation. The results showed that predation decreased with size for both turbot and flounder. The brown shrimps prefer small flatfishes, size class <30 mm, without any species preference. The shrimp abundance was higher during the night at one out of three locations around Gotland. More data is, however, needed to conclude that it is more active during the night.

Tesis para optar al grado de Magíster en Economía / Las tasas máximas de interés existen al menos desde el año 2000 AC, pero, a pesar de sus potenciales efectos en el mercado de crédito, existen pocos estudios que exploren sus consecuencias económicas en los datos. Esta investigación busca contribuir a la literatura empírica que estudia las consecuencias económicas de este tipo de regulaciones, haciendo uso de micro-datos a nivel de bancos y un cambio regulatorio en Chile que permite aislar el efecto causal de una política de tasas máximas en el mercado de crédito. Se encuentra que una menor tasa máxima impacta negativa y significativamente el crédito emitido por los bancos (margen intensivo) y no tiene efectos en el número de deudores (margen extensivo). Este resultado puede ser interpretado como que los bancos prestan menos dinero a aquellos segmentos de mercado con una menor tasa máxima, o que prestan más dinero a aquellos segmentos de mercado con regulaciones menos estrictas. Determinar cuál de estas interpretaciones prevalece requiere un análisis empírico con datos más desagregados, a nivel de deudor, los que son confidenciales. Por otro lado, se encuentra que el efecto negativo de una menor tasa máxima es más pronunciado en aquellos bancos con mayor exposición a segmentos de mercado afectos al cambio regulatorio. Finalmente, se observa que este grupo de bancos exhibe menores indicadores de rentabilidad, menores ingresos por intereses y menores márgenes de intermediación.

<p> Mechanized mathematics systems, especially Theorem Provers (TP) and Computer Algebra Systems (CAS), can play a very helpful role in handling relational calculus. Computer Algebra Systems help to automate tedious symbolic computations. However, they lack the ability to make sophisticated derivations of logical formulas. Correspondingly, a Theorem Prover is powerful in deriving the truth-value of a logical formula. Nevertheless, it is not suitable for dealing with symbolic expressions.</p> <p> The main goal for our research is to investigate the automation of relational calculus using existing mechanized mathematics technologies. Particularly, we elaborated a heuristic that enables the assignment of tasks to PVS and Maxima to help perform relational calculus. As well we built a proof-of-concept tool that supports this calculus.</p> <p> To fulfill our objective, we adopted the following steps: 1. Investigated and evaluated the characteristics and capabilities of TPs and CASs. This step led us to select PVS and Maxima as the tools to be used by our system. 2. Explored a strategy that governs setting tasks to PVS and Maxima in order to perform relational calculus. Then, we propose a task assignment heuristic based on this strategy. 3. Designed and built a proof-of-concept tool that makes use of PVS and Maxima to help perform relational calculus. 4. Assessed our tool by using it to handle some illustrative examples of operations on concrete relations.</p> <p> In our work, relations are given by their characteristic predicates. We assume as well that predicates that are provided to our proof-of-concept tool are in a Disjunctive Normal Form. We adopt a linear notation for the representation of propositions, quantifications, and expressions. We fall short of providing a user interface, which makes the use of the tool that we built slightly difficult.</p> / Thesis / Master of Science (MSc)

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Submitted by isabela.moljf@hotmail.com (isabela.moljf@hotmail.com) on 2016-08-18T15:10:00Z No. of bitstreams: 1 brunosampaiodeoliveira.pdf: 1292975 bytes, checksum: ab81c43620a92db7b1c0c5cf34a64222 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2016-08-19T11:45:01Z (GMT) No. of bitstreams: 1 brunosampaiodeoliveira.pdf: 1292975 bytes, checksum: ab81c43620a92db7b1c0c5cf34a64222 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2016-08-19T11:45:31Z (GMT) No. of bitstreams: 1 brunosampaiodeoliveira.pdf: 1292975 bytes, checksum: ab81c43620a92db7b1c0c5cf34a64222 (MD5) / Made available in DSpace on 2016-08-19T11:45:31Z (GMT). No. of bitstreams: 1 brunosampaiodeoliveira.pdf: 1292975 bytes, checksum: ab81c43620a92db7b1c0c5cf34a64222 (MD5) Previous issue date: 2013-03-25 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / O objetivo deste trabalho é propor a implementação do software MAXIMA no ensino de sistemas de equações lineares 2 x 2 em turma do 8º ano do Ensino Fundamental e de sistemas de equações lineares 3 x 3 em turmas do 2º ano do Ensino Médio. Além de destacar a importância da utilização de recursos tecnológicos nos dias atuais, o autor sugere algumas atividades e formas de abordar o tema com a utilização do programa. / The objective of this work is to propose the implementation of software MAXIMA in teaching systems of linear equations 2 x 2 in the 8th grade class of elementary school and systems of linear equations in 3 x 3 classes of 2nd year of high school. In addition to highlighting the importance of using technological resources nowadays, the author suggests some activities and ways of approaching the topic using the program.

by Chun Gu. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1999. / Includes bibliographical references (leaves 69-71). / Abstract also in Chinese. / Chapter 1 --- Introduction --- p.3 / Chapter 2 --- Definitions --- p.7 / Chapter 3 --- Some Previous Work on OBDD --- p.13 / Chapter 3.1 --- The Work of Bryant --- p.13 / Chapter 3.2 --- Some Variations of the OBDD --- p.14 / Chapter 3.3 --- Previous Work on Variable Ordering of OBDD --- p.16 / Chapter 3.3.1 --- The FIH Heuristic --- p.16 / Chapter 3.3.2 --- The Dynamic Variable Ordering --- p.17 / Chapter 3.3.3 --- The Interleaving method --- p.19 / Chapter 4 --- Two Level Logic Function and OBDD --- p.21 / Chapter 5 --- DSCF Algorithm --- p.25 / Chapter 6 --- Thin Boolean Function --- p.33 / Chapter 6.1 --- The Structure and Properties of thin Boolean functions --- p.33 / Chapter 6.1.1 --- The construction of Thin OBDDs --- p.33 / Chapter 6.1.2 --- Properties of Thin Boolean Functions --- p.38 / Chapter 6.1.3 --- Thin Factored Functions --- p.49 / Chapter 6.2 --- The Revised DSCF Algorithm --- p.52 / Chapter 6.3 --- Experimental Results --- p.54 / Chapter 7 --- A Pattern Merging Algorithm --- p.59 / Chapter 7.1 --- Merging of Patterns --- p.60 / Chapter 7.2 --- The Algorithm --- p.62 / Chapter 7.3 --- Experiments and Conclusion --- p.65 / Chapter 8 --- Conclusions --- p.67

The classical mean-variance model treats the upside and downside equally as risks. This feature is undesirable, in the eyes of a profit-making investor. In this regard, the downside Lower Partial Moments (LPM) are more attractive as alternative risk measures, since they only penalize the downside. This thesis is mainly concerned with the issues related to downside risk measures. We consider two different environments, under which our investigations shall proceed. The first one is the world of Q-radial distributions. The Q-radial distributions generalize the normal distribution and uniform distribution, among many other useful classes of probability distributions. The second type of setting that we will investigate assumes that the distribution of the assets' returns is ambiguous, and the only available (and reliable) knowledge that we have is the first few moments of the distribution. In the first setting, we show that if the investment return rates follow a Q-radial distribution, then the LPM related Risk Adjusted Performance Measures (RAPM), such as the Sortino ratio, the Omega Statistic, the upside potential ratio, and the normalized LPM, are all equivalent to the ordinary Sharpe ratio, which is easy to compute and optimize. Conversely, if all normalized LPM's are equivalent to the Sharpe ratio, then the underlying distribution must be Q-radial. Therefore, this property characterizes the class of Q-radial distributions in which the Sharpe ratio is essentially the only risk adjusted performance measure. If the distribution is unspecified, and only the first few moments (first, second, and/or fourth) are known, we develop tight upper bounds on the lower partial moment E[(r -- X+m], where r &isin; reals and X is stochastic. Based on such tight bounds we then consider the corresponding robust portfolio selection problem, in which the distribution of the investment return is ambiguous, but its first few moments are assumed to be known. We show that if the first two moments are known and the risk measures are either the lower partial moments or the Conditional Value-at-Risk (CVaR), then the optimal portfolio is mean-variance efficient. Moreover, one can formulate the (adjustable) two-stage robust portfolio selection problem as a convex program with finite representations. If more than two moments are known, then the problem is NP-hard in general. In that case we consider approximative models instead. We then proceed to consider the problem of how to alleviate regrets in a decision problem when the parameters are ambiguous, or part of the information will only become known in a dynamic fashion. Since the models we consider in this thesis are mostly in the minimax format, we also consider a general minimax model and study a progressive finite representation approach, which can be used to prove the minimax theorem constructively without any fixed-point theorem or hyperplane separation theorems. / Chen, Li. / Adviser: Shuzhong Zhang. / Source: Dissertation Abstracts International, Volume: 70-06, Section: B, page: 3762. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves 106-111). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest dissertations and theses, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.

Li, Rui. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2003. / Includes bibliographical references (leaves 69-71). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Portfolio Selection Models --- p.1 / Chapter 1.1.1 --- Single Period Models --- p.2 / Chapter 1.1.2 --- Multi-Period Models --- p.4 / Chapter 1.1.3 --- Continuous-Time Model --- p.5 / Chapter 1.2 --- Description and Motivation of New Model --- p.6 / Chapter 1.3 --- Major Contributions --- p.7 / Chapter 1.4 --- Thesis Organization --- p.8 / Chapter 2 --- Formulation and General Methodology --- p.9 / Chapter 2.1 --- Formulation --- p.9 / Chapter 2.1.1 --- Dynamics --- p.10 / Chapter 2.1.2 --- General Form --- p.13 / Chapter 2.1.3 --- Assumptions --- p.13 / Chapter 2.2 --- Methodology --- p.15 / Chapter 2.2.1 --- Weighting Problem --- p.15 / Chapter 2.2.2 --- Search For Optimal Weighting Coefficient --- p.19 / Chapter 3 --- Model I: A Trade-off Between Risk and Return Is Given --- p.22 / Chapter 3.1 --- Problem Formulation --- p.22 / Chapter 3.2 --- Solution to the Parameterized Weighting Problem (PWP(γ)) --- p.23 / Chapter 3.2.1 --- "Construction of the Auxiliary Problem A(γ, λ)" --- p.24 / Chapter 3.2.2 --- Discussion on Parameter A --- p.29 / Chapter 3.3 --- Algorithm --- p.39 / Chapter 4 --- Model II: Expected Return Level Is Specified --- p.42 / Chapter 4.1 --- Problem Formulation --- p.42 / Chapter 4.2 --- Optimal Max-Min Solution --- p.44 / Chapter 4.3 --- Discussion on Parameter λ --- p.50 / Chapter 4.4 --- Algorithm --- p.55 / Chapter 5 --- Numerical Examples --- p.58 / Chapter 6 --- Conclusions --- p.67 / Bibliography --- p.71