published_or_final_version / Psychology / Master / Master of Philosophy

Planning theory and practice in the United States has been dominated by a paradigm of growth; however, since the 1980s, many cities have faced prolonged population decline, prompting questions about how shrinkage is engaged as planners attempt to provide for health, safety, and welfare. This investigation surveys and compares lines of thought being used to make decisions regarding these properties, with particular emphasis on planners located within cities having dissimilar experiences of “shrinking.” Principally, it is focused on vacant and abandoned lots, which are the most immediately visible symptom of population decline and offer the greatest opportunity to reimagine urban form-and-function relationships. The investigation begins with a literature review of the causes and effects of shrinking as well as an investigation into historical research and contemporary thought on vacant land in the United States. Current reasoning supporting decisions about vacant and abandoned lots is identified through a national survey of planning professionals in fifteen cities with either stable-to-growing or shrinking populations. These are augmented by selected follow-up interviews. Both stratified sampling and matching were used to achieve a range of city characteristics and control for them across growth orientation. This approach is new in that while case studies of one or two shrinking cities have been undertaken, there has not been a national survey focused on shrinking cities and vacancy. The goal is to understand regional trends, tools, and obstacles to progress. The results indicate a range in which methods and techniques predicated on the dominant and normative growth paradigm have been both adopted or adapted for use in shrinking cities. Results suggest that concepts regarding quality of life, intentions for the future, and community goals have been reprioritized and redefined in shrinking cities. Finally, results indicate ways in which ideas regarding the built environment and the discontinuities of the urban fabric are being reconceptualized in the face of massive economic and demographic upheaval. / text

With its multiple dining halls, close proximity to restaurants, and diesel vehicle fleet, the University of Texas at Austin (UT) has both the supply of raw materials to implement a waste vegetable oil to biodiesel recycling program and the capacity to use it. At face value, implementing a large-scale recycling program provides a source of cheap, low emissions fuel. However, the feasibility of such a program is contingent on its economic cost and environmental impact relative to alternative fuel sources. Thus, this research estimated the greenhouse gas (GHG) inventories and the unit cost associated with 1 megajoule worth of recycled biodiesel derived from three production processes –Alkali Catalyzed, Acid Catalyzed, and Supercritical Methanol–using environmental life cycle assessment and life cycle costing. These GHG inventories and unit costs were then compared to the conventional diesel and oilseed biodiesel sources that make up UT’s current fuel portfolio. This analysis suggested that implementing a recycling program using a Supercritical Methanol biodiesel conversion process would have the lowest combined GHG impact and unit cost, although as an emerging technology, it poses a high investment risk. In general, these findings are encouraging to the success and impact of a large-scale recycling program. / text

There is increasing evidence supporting the Affect Infusion Model (AIM), which accounts for the role of affect processing in social judgments. Based on the AIM, the study examined the role of mood states in making risky decisions. Forty female Chinese adults from Hong Kong were recruited for this study. A mood induction procedure was applied before they engaged in the experimental task. On random assignment, each subject was induced either a positive (Happy group), or negative mood (Sad group). Results revealed successful mood induction and no significant interaction effects between the groups across pre-and post-tests. The findings did not support the hypothesis based on the AIM, nor the hypotheses advocating for the opposite of the AIM – Mood Maintenance Hypothesis (MMH) and Mood Repair Hypothesis (MRH). It suggested further studies to examine the possible curvilinear relationship between mood and risky decision making, which will highlight the influence of mood on our decision making when risk taking is involved. / published_or_final_version / Clinical Psychology / Master / Master of Social Sciences

The general problem we consider in this thesis is the following: we have to analyze a stream of data (records, packets, events ...) by successively applying to each piece of data a set of ``rules'. Rules are best viewed as lightweight parallel processes synchronizing on each arrival of a new piece of data. In many applications, such as signature-based intrusion detection, only a few rules are concerned with each new piece of data. But all other rules have to be executed anyway just to conclude that they can ignore it. Our goal is to make it possible to avoid this useless work completely. To do so, we perform a static analysis of the code of each rule and we build a decision tree that we apply to each piece of data before executing the rule. The decision tree tells us whether executing the rule or not will change anything to the global analysis results. The decision trees are built at compile time, but their evaluation at each cycle (i.e., for each piece of data) entails an overhead. Thus we organize the set of all computed decision trees in a way that makes their evaluation as fast as possible. The two main original contributions of this thesis are the following. Firstly, we propose a method to organize the set of decision trees and the set of active rules in such a way that deciding which rules to execute can be made optimally in O(r_u), where r_u is the number of useful rules. This time complexity is thus independent of the actual (total) number of active rules. This method is based on the use of a global decision tree that integrates all individual decision trees built from the code of the rules. Secondly, as such a global tree may quickly become much too large if usual data structures are used, we introduce a novel kind of data structure called sequential tree that allows us to keep global decision trees much smaller in many situations where the individual trees share few common conditions. (When many conditions are shared by individual trees the global tree remains small.) To assess our contribution, we first modify the implementation of ASAX, a generic system for data stream analysis based on the rule paradigm presented above. Then we compare the efficiency of the optimized system with respect to its original implementation, using the MIT Lincoln Laboratory Evaluation Dataset and a classical set of intrusion detection rules. Impressive speed-ups are obtained. Finally, our optimized implementation has been used by Nicolas Vanderavero, in his PhD thesis, for the design of stateful honeytanks (i.e., low-interaction honeypots). It makes it possible to simulate tens of thousands hosts on a single computer, with a high level of realism.

Investigate the use of partial relations for multicriteria reverse auctions. At first, a theoretical framework is introduced. Then, an extension of traditional multicriteria tools is considered. This is referred to as the Butterfly model. Finally, the concept of Bidding Niches partitions is formalized and tested.

<p>Successful concept decisions are crucial for product development organisations. Failure in theconcept decision-making process means costly rework, requiring resources that could havebeen spent on innovative work with new products instead. This licentiate thesis tackles theconcept decision-making process and how to improve it. The research presented here is thefirst part of a research project, with an action research approach, that will develop newsupporting working procedures for concept decision making and thereby contribute to moresuccessful products.Empirical studies were conducted in Swedish industrial practice, particularly focusing oneorganisation, and it was found that concept decisions are not made at a certain point in time.Instead, many decisions and activities, on several organisational levels, were adding up to theconcept decisions in the investigated organisations. The concept decision-making process wasfound to be a web of interconnected activities, with many decisions integrated and embedded in the process. Itwas also found that both formal and informal factors influence the concept decision-makingprocess and main factors were identified as: Project and product request, Supporting structures androutines, Individual competence and driving forces, Teamwork and company culture and Contextualcircumstances. These factors represent different perspectives, meaning on what level theyinfluence concept decision making: individual, team, project, organisation, and context, and in orderto create improvements in the concept decision-making process all levels have to beconsidered. The knowledge of the different perspectives has implications for howimprovements should be designed.Larger product developing companies do often have internally defined formal workingprocedures that prescribe how to develop products within the company. The thesis discusseshow the internal working procedures relate to academic theory and to practice. It wasconcluded that internal formal working procedures has not been discussed in a sufficient wayin earlier engineering design research. Furthermore, means for improving the concept decisionmakingprocess are discussed, and it was concluded, based on interviews with practitioners,that the strongest pragmatic means for improvement were developing mindset and applyingmethods. Mindset addresses the awareness, attitude and approach needed for management (andco-workers) working in early product development phases. Methods mainly addresses the needfor having relevant supporting working procedures in general and templates for evaluationalternative solutions in particular. Finally, recommendations for future design of a template forevaluation alternative solutions are presented.</p>

<p>Forecasting, cost management and pricing policies are topics which have beenwidely investigated over time. Due to a lack of scientific research about therelationships between each of those subjects, these methods have beeninvestigated in combination with their outcomes. The purpose of this work was todevelop a framework which can be used by managers who want to make adecision in either of the subjects mentioned before. By the use of a qualitative, interpretive research design, a literature review was performed which led to some interesting findings. Generally, it can be said that the methods are not related directly, although the outcomes are linked and can often be used as a criterion for the decision making process for the other methods.</p>

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