Matching Items (18)

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This Cannot Be Forest Bathing

Description

This Cannot Be Forest Bathing is a collection of poems that deals with how we see ourselves in the greater picture. Reflecting on one’s experiences and trying to project the

This Cannot Be Forest Bathing is a collection of poems that deals with how we see ourselves in the greater picture. Reflecting on one’s experiences and trying to project the future is challenging for a young person, and these poems are my way of accepting that life, and the future, are both ever-changing. The practice of “forest bathing,” known as shinrin-yoku in Japan, means to ‘take in the forest.’ This form of meditation and self-cleansing is associated with a form of therapy. Shinrin-yoku utilizes techniques or treatments that focus on bettering physical and mental health through nature. During a “forest bath,” the participant is able to relax through being outside; in calmness, one is able to think clearly. For my collection, I wanted to emphasize this self-reflection as a dark meditation instead of a stereotypically peaceful endeavor. The title is a manifestation of disbelief, as I realized ‘I am with nature, in a moment of rest, and should be enjoying myself, but I am lost and feel trapped instead of being found. I still think about who I am as an individual, my anxieties, and of the future.’ As I am usually inspired by nature, all of my works were written either in connection to, or physically within the outside world. I find closure and relief through writing, and I hope that my poetry connects people together in our dark moments, reminding the reader that they are not alone. In youth, we are lost but never alone, even in the most tumultuous of times.

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Agent

Created

Date Created
  • 2019-12

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Uncertainty, Speculation and Leverage in Stock Market Mechanisms: An Analysis from 1987 to the Present

Description

This paper seeks to emphasize how the presence of uncertainty, speculation and leverage work in concert within the stock market to exacerbate crashes in a cyclical market. It analyzes three

This paper seeks to emphasize how the presence of uncertainty, speculation and leverage work in concert within the stock market to exacerbate crashes in a cyclical market. It analyzes three major stock market events: the crash of Oct. 19, 1987, “Black Monday;” the dotcom bust, from 1999 to 2002; and the subprime mortgage crisis, from 2007 to 2010. Within each event period I define determinants or measurements of uncertainty, speculation. Analysis of how these three concepts functioned during boom and bust will highlight how their presence can amplify the magnitude of a crash. This paper postulates that the amount of leverage during a crash determines how long-term its effects will be. This theory is fortified by extensive research and interviews with experts in the stock market who had a front row view of the discussed crises.

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Created

Date Created
  • 2019-05

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Three essays on consumer behavior under uncertainty

Description

It is well understood that decisions made under uncertainty differ from those made without risk in important and significant ways. Yet, there is very little research into how uncertainty manifests

It is well understood that decisions made under uncertainty differ from those made without risk in important and significant ways. Yet, there is very little research into how uncertainty manifests itself in the most ubiquitous of decision-making environments: Consumers' day-to-day decisions over where to shop, and what to buy for their daily grocery needs. Facing a choice between stores that either offer relatively stable "everyday low prices" (EDLP) or variable prices that reflect aggressive promotion strategies (HILO), consumers have to choose stores under price-uncertainty. I find that consumers' attitudes toward risk are critically important in determining store-choice, and that heterogeneity in risk attitudes explains the co-existence of EDLP and HILO stores - an equilibrium that was previously explained in somewhat unsatisfying ways. After choosing a store, consumers face another source of risk. While knowing the quality or taste of established brands, consumers have very little information about new products. Consequently, consumers tend to choose smaller package sizes for new products, which limits their exposure to the risk that the product does not meet their prior expectations. While the observation that consumers purchase small amounts of new products is not new, I show how this practice is fully consistent with optimal purchase decision-making by utility-maximizing consumers. I then use this insight to explain how manufacturers of consumer packaged goods (CPGs) respond to higher production costs. Because consumers base their purchase decisions in part on package size, manufacturers can use package size as a competitive tool in order to raise margins in the face of higher production costs. While others have argued that manufacturers reduce package sizes as a means of raising unit-prices (prices per unit of volume) in a hidden way, I show that the more important effect is a competitive one: Changes in package size can soften price competition, so manufacturers need not rely on fooling consumers in order to pass-through cost increases through changes in package size. The broader implications of consumer behavior under risk are dramatic. First, risk perceptions affect consumers' store choice and product choice patterns in ways that can be exploited by both retailers and manufacturers. Second, strategic considerations prevent manufacturers from manipulating package size in ways that seem designed to trick consumers. Third, many services are also offered as packages, and also involve uncertainty, so the effects identified here are likely to be pervasive throughout the consumer economy.

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Created

Date Created
  • 2014

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Product design optimization under epistemic uncertainty

Description

This dissertation is to address product design optimization including reliability-based design optimization (RBDO) and robust design with epistemic uncertainty. It is divided into four major components as outlined below. Firstly,

This dissertation is to address product design optimization including reliability-based design optimization (RBDO) and robust design with epistemic uncertainty. It is divided into four major components as outlined below. Firstly, a comprehensive study of uncertainties is performed, in which sources of uncertainty are listed, categorized and the impacts are discussed. Epistemic uncertainty is of interest, which is due to lack of knowledge and can be reduced by taking more observations. In particular, the strategies to address epistemic uncertainties due to implicit constraint function are discussed. Secondly, a sequential sampling strategy to improve RBDO under implicit constraint function is developed. In modern engineering design, an RBDO task is often performed by a computer simulation program, which can be treated as a black box, as its analytical function is implicit. An efficient sampling strategy on learning the probabilistic constraint function under the design optimization framework is presented. The method is a sequential experimentation around the approximate most probable point (MPP) at each step of optimization process. It is compared with the methods of MPP-based sampling, lifted surrogate function, and non-sequential random sampling. Thirdly, a particle splitting-based reliability analysis approach is developed in design optimization. In reliability analysis, traditional simulation methods such as Monte Carlo simulation may provide accurate results, but are often accompanied with high computational cost. To increase the efficiency, particle splitting is integrated into RBDO. It is an improvement of subset simulation with multiple particles to enhance the diversity and stability of simulation samples. This method is further extended to address problems with multiple probabilistic constraints and compared with the MPP-based methods. Finally, a reliability-based robust design optimization (RBRDO) framework is provided to integrate the consideration of design reliability and design robustness simultaneously. The quality loss objective in robust design, considered together with the production cost in RBDO, are used formulate a multi-objective optimization problem. With the epistemic uncertainty from implicit performance function, the sequential sampling strategy is extended to RBRDO, and a combined metamodel is proposed to tackle both controllable variables and uncontrollable variables. The solution is a Pareto frontier, compared with a single optimal solution in RBDO.

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Created

Date Created
  • 2012

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Toward an Uncertain Modeling of Hypersonic Aerodynamic Forces

Description

The focus of this investigation is on the development of a surrogate model of hypersonic aerodynamic forces on structures to reduce the computational effort involved in the determination of the

The focus of this investigation is on the development of a surrogate model of hypersonic aerodynamic forces on structures to reduce the computational effort involved in the determination of the structural response. The application is more precisely focused on uncertain structures. Then, following an uncertainty management strategy, the surrogate may exhibit an error with respect to Computational Fluid Dynamics (CFD) reference data as long as that error does not significantly affect the uncertainty band of the structural response. Moreover, this error will be treated as an epistemic uncertainty introduced in the model thereby generating an uncertain surrogate. Given this second step, the aerodynamic surrogate is limited to those exhibiting simple analytic forms with parameters that can be identified from CFD data.

The first phase of the investigation focuses on the selection of an appropriate form for the surrogate for the 1-dimensional flow over a flat clamped-clamped. Following piston theory, the model search started with purely local models, linear and nonlinear of the local slope. A second set of models was considered that involve also the local displacement, curvature, and integral of displacement and an improvement was observed that can be attributed to a global effect of the pressure distribution. Various ways to involve such a global effect were next investigated eventually leading to a two-level composite model based on the sum of a local component represented as a cubic polynomial of the downwash and a global component represented by an auto-regressive moving average (ARMA) model driven nonlinearly by the local downwash. This composite model is applicable to both steady pressure distributions with the downwash equal to the slope and to unsteady cases with the downwash as partial derivative with time in addition to steady.

The second part of the investigation focused on the introduction of the epistemic uncertainty in the aerodynamic surrogate and it was recognized that it could be achieved by randomizing the coefficients of the local and/or the auto-regressive components of the model. In fact, the combination of the two effects provided an applicable strategy.

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Created

Date Created
  • 2017

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Addressment of uncertainty and variability in attributional environmental life cycle assessment

Description

'Attributional' Life Cycle Assessment (LCA) quantitatively tracks the potential environmental impacts of international value chains, in retrospective, while ensuring that burden shifting is avoided. Despite the growing popularity of LCA

'Attributional' Life Cycle Assessment (LCA) quantitatively tracks the potential environmental impacts of international value chains, in retrospective, while ensuring that burden shifting is avoided. Despite the growing popularity of LCA as a decision-support tool, there are numerous concerns relating to uncertainty and variability in LCA that affects its reliability and credibility. It is pertinent that some part of future research in LCA be guided towards increasing reliability and credibility for decision-making, while utilizing the LCA framework established by ISO 14040.

In this dissertation, I have synthesized the present state of knowledge and application of uncertainty and variability in ‘attributional’ LCA, and contribute to its quantitative assessment.

Firstly, the present state of addressment of uncertainty and variability in LCA is consolidated and reviewed. It is evident that sources of uncertainty and variability exist in the following areas: ISO standards, supplementary guides, software tools, life cycle inventory (LCI) databases, all four methodological phases of LCA, and use of LCA information. One source of uncertainty and variability, each, is identified, selected, quantified, and its implications discussed.

The use of surrogate LCI data in lieu of missing dataset(s) or data-gaps is a source of uncertainty. Despite the widespread use of surrogate data, there has been no effort to (1) establish any form of guidance for the appropriate selection of surrogate data and, (2) estimate the uncertainty associated with the choice and use of surrogate data. A formal expert elicitation-based methodology to select the most appropriate surrogates and to quantify the associated uncertainty was proposed and implemented.

Product-evolution in a non-uniform manner is a source of temporal variability that is presently not considered in LCA modeling. The resulting use of outdated LCA information will lead to misguided decisions affecting the issue at concern and eventually the environment. In order to demonstrate product-evolution within the scope of ISO 14044, and given that variability cannot be reduced, the sources of product-evolution were identified, generalized, analyzed and their implications (individual and coupled) on LCA results are quantified.

Finally, recommendations were provided for the advancement of robustness of 'attributional' LCA, with respect to uncertainty and variability.

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Created

Date Created
  • 2016

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Effects of Structural Uncertainty on the Dynamic Response of Nearly-Straight Pipes Conveying Fluid: Modeling and Numerical Validation

Description

This investigation is focused on the consideration of structural uncertainties in nearly-straight pipes conveying fluid and on the effects of these uncertainties on the dynamic response and stability of those

This investigation is focused on the consideration of structural uncertainties in nearly-straight pipes conveying fluid and on the effects of these uncertainties on the dynamic response and stability of those pipes. Of interest more specifically are the structural uncertainties which affect directly the fluid flow and its feedback on the structural response, e.g., uncertainties on/variations of the inner cross-section and curvature of the pipe. Owing to the complexity of introducing such uncertainties directly in finite element models, it is desired to proceed directly at the level of modal models by randomizing simultaneously the appropriate mass, stiffness, and damping matrices. The maximum entropy framework is adopted to carry out the stochastic modeling of these matrices with appropriate symmetry constraints guaranteeing that the nature, e.g., divergence or flutter, of the bifurcation is preserved when introducing uncertainty.

To support the formulation of this stochastic ROM, a series of finite element computations are first carried out for pipes with straight centerline but inner radius varying randomly along the pipe. The results of this numerical discovery effort demonstrate that the dominant effects originate from the variations of the exit flow speed, induced by the change in inner cross-section at the pipe end, with the uncertainty on the cross-section at other locations playing a secondary role. Relying on these observations, the stochastic reduced order model is constructed to model separately the uncertainty in inner cross-section at the pipe end and at other locations. Then, the fluid related mass, damping, and stiffness matrices of this stochastic reduced order model (ROM) are all determined from a single random matrix and a random variable. The predictions from this stochastic ROM are found to closely match the corresponding results obtained with the randomized finite element model. It is finally demonstrated that this stochastic ROM can easily be extended to account for the small effects due to uncertainty in pipe curvature.

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Created

Date Created
  • 2017

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Incorporating social network variables into relational turbulence theory: popping the dyadic bubble

Description

Relational turbulence theory (RTT) has primarily explored the effects of relational uncertainty and partner interdependence on relational outcomes. While robust, the theory fails to account for uncertainties and perceived interdependence

Relational turbulence theory (RTT) has primarily explored the effects of relational uncertainty and partner interdependence on relational outcomes. While robust, the theory fails to account for uncertainties and perceived interdependence stemming from extra-dyadic factors (such as partners’ social networks). Thus, this dissertation had two primary goals. First, scales indexing measures of social network-based relational uncertainty (i.e., network uncertainty) and social network interdependence are tested for convergent and divergent validity. Second, measurements of network uncertainty and interdependence are tested alongside measures featured in RTT to explore predictive validity. Results confirmed both measurements and demonstrated numerous significant relationships for turbulence variables. Discussions of theoretical applications and future directions are offered.

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Created

Date Created
  • 2018

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Policy Innovation for an Uncertain Future: Regulating Drone Use in Southern California Cities

Description

Over the past six years, the use of drones for recreational and commercial purposes has increased dramatically. There are currently over one million registered drones in the United States, and

Over the past six years, the use of drones for recreational and commercial purposes has increased dramatically. There are currently over one million registered drones in the United States, and this number is expected to increase in the foreseeable future. For now, drones are a local phenomenon. The operational limitations prevent them from long range activity and federal policies prevent them from operating beyond the visual line of sight of the controller. The localized nature of drone operation makes them a particularly salient issue at the local regulatory level. At this level, cities must contend with the uncertainty of drone operation and a complex regulatory environment. Within a single metropolitan region, there are cities that may attempt to restrict the use of drones through various local ordinances while neighboring cities may have not even considered, let alone adopted, any type of regulation. The reasons behind these policy choices are not clear.

In an effort to understand the factors involved in the decisions to adopt a local drone use policy, this dissertation leverages qualitative methods to analyze the policy process leading to local decisions. The study capitalizes on rich contextual data gathered from a variety of sources for select cities in Orange and Los Angeles Counties. Specifically, this study builds a conceptual framework from policy innovation literature and applies it in the form of content analysis. This initial effort is used to identify the catalysts for policy discussion and the specific innovation mechanisms that support or detract from the decision to adopt a local drone use ordinance. Then, qualitative comparative analysis is used to determine which configuration of factors, identified during the content analysis, contribute to the causal path of policy adoption. Among other things, the results highlight the role that uncertainty plays in the policy process. Cities that adopt a drone use ordinance have low levels of uncertainty, high numbers of registered drone users, and at least two neighboring cities that also have drone use policies. This dissertation makes a modest contribution to policy innovation research, highlights how a configurational analysis technique can be applied to policy adoption decisions, and contains several recommendations for regulating drone use at the local level.

Contributors

Agent

Created

Date Created
  • 2019