The city landscape of China is undoubtedly experiencing rapid transformation. With the fast rate of urbanization it seems plausible that people will live in a vertical city served by new kinds of transportation infrastructure around the year 2050. This project studied the values of the upper middle class of migrants living in a future Shanghai. Ideation and form development resulted in an aesthetic sculpture informed by the western brand and the eastern culture. This sculpture then inspired the development of a vehicle concept that can act as mobility solution as well as an icon of quality living in the future Chinese home.

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Solution-focused therapy is a postmodern strength-based counselling intervention which focuses on the discovery of client strengths, resources and abilities to empower clients to bring about positive change in their lives. My research employed a pragmatic case study (PCS) method to systematically study the self-efficacy experiences of four New Zealand adolescents throughout the solution-focused process. Each client participated in up to five counselling sessions. Following the PCS method my study began with a presentation of my guiding conception which detailed my theoretical approach and the ways in which solution-focused skills and techniques would be applied throughout the study. Case data included analysis of all client counselling sessions and final interviews which were video-recorded, as well as the consideration of a quantitative measurement in the form of the Outcome Rating Scale (ORS). Through analysis of outcome results and using three inductively derived themes to guide cross-case analysis, it was found that the solution-focused counselling process, assisted adolescents in discovering and developing their knowledge and awareness of their personal strengths and resources; encouraged adolescents to feel empowered to act upon these resources, therefore enhancing self-efficacy; and used the quality of the therapeutic relationship to give adolescents a sense of being a co-participator in the counselling process and as a result gave adolescents a ‘boost’ towards taking action, therefore increasing self-efficacy. Process and thematic results, supported by a brief quantitative measure, showed that all four clients made significant progress towards achieving their goals for counselling. Overall the results suggest that the solution-focused process contributed to positive therapeutic outcome and gains in self-efficacy. All four clients demonstrated the confidence to take action to bring about positive change in relation to their counselling goals, supporting enhanced self-efficacy.

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Variable Selection has always been a very important problem in statistics. We often meet situations where a huge data set is given and we want to find out the relationship between the response and the corresponding variables. With a huge number of variables, we often end up with a big model even if we delete those that are insignificant. There are two reasons why we are unsatisfied with a final model with too many variables. The first reason is the prediction accuracy. Though the prediction bias might be small under a big model, the variance is usually very high. The second reason is interpretation. With a large number of variables in the model, it's hard to determine a clear relationship and explain the effects of variables we are interested in. A lot of variable selection methods have been proposed. However, one disadvantage of variable selection is that different sizes of model require different tuning parameters in the analysis, which is hard to choose for non-statisticians. Xin and Zhu advocate variable ranking instead of variable selection. Once variables are ranked properly, we can make the selection by adopting a threshold rule. In this thesis, we try to rank the variables using Least Angle Regression (LARS). Some shrinkage methods like Lasso and LARS can shrink the coefficients to zero. The advantage of this kind of methods is that they can give a solution path which describes the order that variables enter the model. This provides an intuitive way to rank variables based on the path. However, Lasso can sometimes be difficult to apply to variable ranking directly. This is because that in a Lasso solution path, variables might enter the model and then get dropped. This dropping issue makes it hard to rank based on the order of entrance. However, LARS, which is a modified version of Lasso, doesn't have this problem. We'll make use of this property and rank variables using LARS solution path.

Optimal trade execution aims at balancing price impact and timing risk. With respect to the mathematical formulation of the optimization problem, we primarily focus on Mean Variance (MV) optimization, in which the two conflicting objectives are maximizing expected revenue (the flip side of trading impact) and minimizing variance of revenue (a measure of timing risk). We also consider the use of expected quadratic variation of the portfolio value process as an alternative measure of timing risk, which leads to Mean Quadratic Variation (MQV) optimization. We demonstrate that MV-optimal strategies are quite different from MQV-optimal strategies in many aspects. These differences are in stark contrast to the common belief that MQV-optimal strategies are similar to, or even the same as, MV-optimal strategies. These differences should be of interest to practitioners since we prove that the classic Almgren-Chriss strategies (industry standard) are MQV-optimal, in contrary to the common belief that they are MV-optimal. From a computational point of view, we extend theoretical results in the literature to prove that the mean variance efficient frontier computed using our method is indeed the complete Pareto-efficient frontier. First, we generalize the result in Li (2000) on the embedding technique and develop a post-processing algorithm that guarantees Pareto-optimality of numerically computed efficient frontier. Second, we extend the convergence result in Barles (1990) to viscosity solution of a system of nonlinear Hamilton Jacobi Bellman partial differential equations (HJB PDEs). On the numerical aspect, we combine the techniques of similarity reduction, non-standard interpolation, and careful grid construction to significantly improve the efficiency of our numerical methods for solving nonlinear HJB PDEs.

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Thesis (Ph.D.)--Tufts University, 1999. / Adviser: Mary Jane Schultz. Submitted to the Dept. of Chemistry. Includes bibliographical references (leaves 134-136). Access restricted to members of the Tufts University community. Also available via the World Wide Web;