This thesis examines the discourse of careers services in UK university websites. The notion of employability has been presented and promoted by powerful groups, such as governments, organisations, the media, employers, and higher education institutions, as the remedy to the social problem of unemployment. Careers services in UK universities were given the role of ‘expert’ professionals who are there to support and guide students towards developing their employability and skills. This study examined the ideas and messages reproduced and promoted by the careers services, which could affect the students’ understanding of the ‘job market’ and their role in it. The chosen methodology, that is corpus-based critical discourse analysis, combined qualitative and quantitative methods and tools for the analysis of 2.6 million words deriving from 58 UK universities’ websites, and more specifically the careers services sections. In general, this thesis highlights some of the problematic, common-sense ideas that are being promoted by these services and encourages the denaturalisation of the careers services’ discourse. The main argument is that the language used by the careers services in UK universities reproduces and promotes neoliberal ideology. The analysis shows that higher education students are encouraged to develop ‘job-hunting techniques’ and are presented as responsible for their own ‘survival’ in a ‘fiercely competitive job market’. The notion of employability is promoted as the main solution to this highly problematic ‘reality’. The services advertise that they ‘know’ what employers are looking for from prospective employees and claim that they can ‘help’ students with their job search. The close analysis of linguistic data reveals that these services act as the ‘enablers’ of the students’ self-beneficiary action. In addition, besides their role as careers counsellors, the services’ use of language demonstrates their involvement in the therapeutic field. Finally, the language used by post-1992 and Russell Group universities was found to be quite similar. There are, however, some differences that could be viewed as signs of competition between these two university ‘groups’ and a preference of the job market towards a particular ‘group’ of graduates from elite institutions.

We study the total utility of an agent in a model of narrow framing with constant elasticity of intertemporal substitution and relative risk aversion degree and with infinite time horizon. In a finite-state Markovian setting, we prove that the total utility uniquely exists when the agent derives nonnegative utility of gains and losses incurred by holding risky assets and that the total utility can be non-existent or non-unique otherwise. Moreover, we prove that the utility, when uniquely exists, can be computed by a recursive algorithm with any starting point. We then consider a portfolio selection problem with narrow framing and solve it by proving that the corresponding dynamic programming equation has a unique solution. Finally, we propose a new model of narrow framing in which the agent's total utility uniquely exists in general. Barberis and Huang (2009, J. Econ. Dynam. Control, vol. 33, no. 8, pp. 1555-1576) propose a preference model that allows for narrow framing, and this model has been successfully applied to explain individuals' attitudes toward timeless gambles and high equity premia in the market. To uniquely define the utility process in this preference model and to yield a unique solution when the model is applied to portfolio selection problems, one needs to impose some restrictions on the model parameters, which are too tight for many financial applications. We propose a modification of Barberis and Huang's model and show that the modified model admits a unique utility process and a unique solution in portfolio selection problems. Moreover, the modified model is more tractable than Barberis and Huang's when applied to portfolio selection and asset pricing.

We study production planning integrated with risk hedging in a continuous-time stochastic setting. The (cumulative) demand process is modeled as a sum of two components: the demand rate is a general function in a tradable financial asset (which follows another stochastic process), and the noise component follows an independent Brownian motion. There are two decisions: a production quantity decision at the beginning of the planning horizon, and a dynamic hedging strategy throughout the horizon. Thus, the total terminal wealth has two components: production payoff, and profit/loss from the hedging strategy. The production quantity and hedging strategy are jointly optimized under the mean-variance and the shortfall criteria. For each risk objective, we derive the optimal hedging strategy in closed form and express the associated minimum risk as a function of the production quantity, the latter is then further optimized. With both production and hedging (jointly) optimized, we provide a complete characterization of the efficient frontier. By quantifying the risk reduction contributed by the hedging strategy, we demonstrate its substantial improvement over a production-only decision. To derive the mean-variance hedging strategy, we use a numeraire-based approach, and the derived optimal strategy consists of a risk mitigation component and an investment component. For the shortfall hedging, a convex duality method is used, and the optimal strategy takes the form of a put option and a digital option, which combine to close the gap from the target left by production (only). Furthermore, we extend the models and results by allowing multiple products, with demand rates depending on multiple assets. We also make extension by allowing the asset price to follow various stochastic processes (other than the geometric Brownian motion).

This dissertation studies control and optimization approaches to obtain energy-efficient and reliable routing schemes for battery-powered systems in network settings. First, incorporating a non-ideal battery model, the lifetime maximization problem for static wireless sensor networks is investigated. Adopting an optimal control approach, it is shown that there exists a time-invariant optimal routing vector in a fixed topology network. Furthermore, under very mild conditions, this optimal policy is robust with respect to the battery model used. Then, the lifetime maximization problem is investigated for networks with a mobile source node. Redefining the network lifetime, two versions of the problem are studied: when there exist no prior knowledge about the source node’s motion dynamics vs. when source node’s trajectory is known in advance. For both cases, problems are formulated in the optimal control framework. For the former, the solution can be reduced to a sequence of nonlinear programming problems solved on line as the source node trajectory evolves. For the latter, an explicit off-line numerical solution is required. Second, the problem of routing for vehicles with limited energy through a network with inhomogeneous charging nodes is studied. The goal is to minimize the total elapsed time, including traveling and recharging time, for vehicles to reach their destinations. Adopting a game-theoretic approach, the problem is investigated from two different points of view: user-centric vs. system-centric. The former is first formulated as a mixed integer nonlinear programming problem. Then, by exploiting properties of an optimal solution, it is reduced to a lower dimensionality problem. For the latter, grouping vehicles into subflows and including the traffic congestion effects, a system-wide optimization problem is defined. Both problems are studied in a dynamic programming framework as well. Finally, the thesis quantifies the Price Of Anarchy (POA) in transportation net- works using actual traffic data. The goal is to compare the network performance under user-optimal vs. system-optimal policies. First, user equilibria flows and origin- destination demands are estimated for the Eastern Massachusetts transportation net- work using speed and capacity datasets. Then, obtaining socially-optimal flows by solving a system-centric problem, the POA is estimated.

Growing Narrative, Conviviality, and Security: Community and Gardening in the North Shore of Massachusetts is an ethnography of the Highlands neighborhood of Lynn, Massachusetts. In this thesis I argue that the efforts of this community to combat the ills of their neighborhood seen through the lens of a community garden rely on three key factors. The first is their reliance and sharing of a narrative that reminds fellow community members of the difficult points in their past, but with the message that there is always a possibility of a brighter future. The second aspect is the reliance on the shared moments of celebration that the neighborhood actively supports and engages, which instill the bonds of community in an otherwise disparate, and multicultural setting. Finally, the narrative and celebration of community would not be sustainable if the community did not also provide the structure for security upon which the neighborhood can continue to improve their communal and social wellbeing. The lessons learned from this community are useful to understand how a multiracial, multicultural urban site can turn around their violent past in order to create a livable space.

abstract: I study the problem of locating Relay nodes (RN) to improve the connectivity of a set of already deployed sensor nodes (SN) in a Wireless Sensor Network (WSN). This is known as the Relay Node Placement Problem (RNPP). In this problem, one or more nodes called Base Stations (BS) serve as the collection point of all the information captured by SNs. SNs have limited transmission range and hence signals are transmitted from the SNs to the BS through multi-hop routing. As a result, the WSN is said to be connected if there exists a path for from each SN to the BS through which signals can be hopped. The communication range of each node is modeled with a disk of known radius such that two nodes are said to communicate if their communication disks overlap. The goal is to locate a given number of RNs anywhere in the continuous space of the WSN to maximize the number of SNs connected (i.e., maximize the network connectivity). To solve this problem, I propose an integer programming based approach that iteratively approximates the Euclidean distance needed to enforce sensor communication. This is achieved through a cutting-plane approach with a polynomial-time separation algorithm that identies distance violations. I illustrate the use of my algorithm on large-scale instances of up to 75 nodes which can be solved in less than 60 minutes. The proposed method shows solutions times many times faster than an alternative nonlinear formulation. / Dissertation/Thesis / Masters Thesis Industrial Engineering 2019

abstract: As immigrants in the United States, Chinese small business entrepreneurs often encountered social and cultural barriers in the areas of finance, language, and employment in their new environment. This dissertation investigated how they utilized social capital to surmount the embedded disadvantages of an unequal market in their adopted country. The findings presented in this qualitative descriptive multi-case analysis, conducted in the greater metropolitan regions of Phoenix and Los Angeles, demonstrated the importance of social and transnational ties created in the United States within the local Chinese community as well as their social connections brought from China. Drawing upon the data from in-depth interviews and informal observations, this dissertation was guided by three research questions: (a) What barriers do immigrant small business owners encounter? (b) What social connections provide help for immigrant small business owners to overcome those barriers or intensify their disadvantaged situations? (c) How do social networks influence immigrant small business development? The findings revealed many provocative facts on how social capital stimulated Chinese immigrant small business owners. The influence of local and strong ties especially provided essential start-up funds, an affordable labor force. Those ties also provided authentication for business information provided by weak ties. Although the governments’ Small Business Administration empowers small business by various programs because it is an important social and economic element in the U.S. market, the Chinese community rarely utilized this support. Transnational connections played an important role in the relatively mature market found in Los Angeles, but indeed all respondents in both case studies exhibited great interest in utilizing transnational connections to explore business opportunities. Regional connections provided a powerful resource for Chinese small business to create business alliance and increase their market competitiveness. Social capital embeds in a complexity of political, economic, social and personal backgrounds. In summary, social capital was an essential resource for Chinese small business when they encountered the barriers in the local market. From the findings, this dissertation’s scholarly contribution adds to the field of social capital studies by combining the investigation of social capital, embeddedness, intersectionality and transnational connections in respect to study immigrant entrepreneurship. / Dissertation/Thesis / Doctoral Dissertation Justice Studies 2019

Several computational applications in stochastic operations research are presented, where, for each application, a computational engine is used to achieve results that are otherwise overly tedious by hand calculations, or in some cases mathematically intractable. Algorithms and code are developed and implemented with specific emphasis placed on achieving exact results and substantiated via Monte Carlo simulation. The code for each application is provided in the software language utilized and algorithms are available for coding in another environment. The topics include univariate and bivariate nonparametric random variate generation using a piecewise-linear cumulative distribution, deriving exact statistical process control chart constants for non-normal sampling, testing probability distribution conformance to Benford's law, and transient analysis of M/M/s queueing systems. The nonparametric random variate generation chapters provide the modeler with a method of generating univariate and bivariate samples when only observed data is available. The method is completely nonparametric and is capable of mimicking multimodal joint distributions. The algorithm is "black-box," where no decisions are required from the modeler in generating variates for simulation. The statistical process control chart constant chapter develops constants for select non-normal distributions, and provides tabulated results for researchers who have identified a given process as non-normal The constants derived are bias correction factors for the sample range and sample standard deviation. The Benford conformance testing chapter offers the Kolmogorov-Smirnov test as an alternative to the standard chi-square goodness-of-fit test when testing whether leading digits of a data set are distributed according to Benford's law. The alternative test has the advantage of being an exact test for all sample sizes, removing the usual sample size restriction involved with the chi-square goodness-of-fit test. The transient queueing analysis chapter develops and automates the construction of the sojourn time distribution for the nth customer in an M/M/s queue with k customers initially present at time 0 (k ≥ 0) without the usual limit on traffic intensity, rho < 1, providing an avenue to conduct transient analysis on various measures of performance for a given initial number of customers in the system. It also develops and automates the construction of the sojourn time joint probability distribution function for pairs of customers, allowing the calculation of the exact covariance between customer sojourn times.

With the growing interest in the Marcellus Shale and its natural gas deposits, there are opportunities to purchase and hold land for investment purposes. A robust decision tool is needed to help guide investors towards the most profitable properties. Artificial neural networks have many unique benefits that make them an ideal candidate for this purpose. The artificial neural networks created in this study had nine independent variables. Combinations of these nine variables were created to describe 300 theoretical properties available for purchase. Each of these properties were then evaluated by an expert in the field and given a score from one to five to rate its investment potential, which was the dependent variable. Sixteen different network architectures were used to create over 200 neural networks. However, none of these networks met the criteria established to determine success. This is likely due to the unreliability in the data used to train the network, evidenced by the expert’s inability to reproduce previously assigned scores.

Source: Dissertation Abstracts International, Volume: 34-08, Section: B, page: 3953. / Thesis (Ph.D.)--The Florida State University, 1973.