Cuban-American Women's Anglophone Novels of the 1990s

My dissertation examines twelve Anglophone novels written by Cuban-American women published in the 1990s, a period during which Isabel Alvarez-Borland and others have observed a Cuban-American Literary Boom. The twelve novels that constitute my corpus belong to nine authors: Teresa Bevin, Havana Split (1998); Cristina García, Dreaming in Cuban (1992) and The Agüero Sisters (1997); Margarita Engle, Singing to Cuba (1993) and Skywriting (1995); Ivonne Lamazares, The Sugar Island (2000); Tina Matlock, Guava and Cheese (2000); Himilce Novas, Mangos, Bananas, and Coconuts: A Cuban Love Story (1996); Achy Obejas, Memory Mambo (1996); Beatriz Rivera, Midnight Sandwiches at the Mariposa Express (1997) and Playing with Light (2000); and Ana Veciana-Suárez, The Chin Kiss King (1997). A combination of known and lesser-known writers, this group includes all the novels written during the decade I selected with the exception of the entertaining mass-market detective thrillers by Cristina García-Aguilera. Chapter 1 defines the contours of this boom by discussing first the unifying motifs and preoccupations that speak to the hyphenated identity that represents contemporary Cuban-American narrative written in English by women and then by establishing three common themes that explore questions of self-identity and nationality shared by the Cuban-American characters in the novels in my corpus: the mother-daughter relationship, the voyage to Cuba, and the obsession with family history. Each theme is developed in the three chapters that follow (Chapters 2-4) and four novels are discussed in each. The analyses of these three themes brings to the fore aspects of identity confusion between various generations as depicted by the mothers and daughters portrayed in these texts, the centrality of the voyage back to the island and its effect on identity formation, and the intersections between individual and family memory, which often are enlightened by the use of concepts such as postmemory and collective memory. The 1990s is a period of particular importance to Cubans on and off the island and this dissertation is but one example of the central -and I believe representative--preoccupations and achievements of some of the Cuban-Americans writing in this significant period at the end of the 20th century

Sensitivity in Multiobjective Programming by Differential Equations Methods. The Case of Homogeneous Functions

Proceedings of the Second International Conference on Multi-Objective Programming and Goal Programming, Torremolinos, Spain, May 16-18, 1996.The purpose of this paper is to characterize for convex multiobjective programming, the situations in which the sensitivity with respect to the right side vector of the constraints can be obtained as a solution of a dual program.Publicad

Leveraging Existing Technology: Developing a Trusted Digital Repository for the U.S. Geological Survey

As Federal Government agencies in the United States pivot to increase access to scientific data (Sheehan, 2016), the U.S. Geological Survey (USGS) has made substantial progress (Kriesberg et al., 2017). USGS authors are required to make federally funded data publicly available in an approved data repository (USGS, 2016b). This type of public data product, known as a USGS data release, serves as a method for publishing reviewed and approved data. In this paper, we present major milestones in the approach the USGS took to transition an existing technology platform to a Trusted Digital Repository. We describe both the technical and the non-technical actions that contributed to a successful outcome.We highlight how initial workflows revealed patterns that were later automated, and the ways in which assessments and user feedback influenced design and implementation. The paper concludes with lessons learned, such as the importance of a community of practice, application programming interface (API)-driven technologies, iterative development, and user-centered design. This paper is intended to offer a potential roadmap for organizations pursuing similar goals. &nbsp

Analysis of Production and Location Decisions by Means of Multi-Criteria Analysis

During the last few years economists and operations researchers have paid much attention to multi-criteria analysis as a tool in modern decision-making. The basic feature of multi-criteria analysis is the fact that a wide variety of relevant decision aspects can be taken into account without a necessity to translate all these aspects in monetary terms. This article will give a brief survey of these new methods in both a quantitative and in a qualitative sense. After this survey the relevance of multi-criteria analysis for entrepreneurial decisions in the field of production and investments will be exposed. The analysis will be illustrated by means of two examples of entrepreneurial decision-problems, which have been solved by means of multi-criteria analysis

GA-ANN Short-Term Electricity Load Forecasting

This paper presents a methodology for short-term load forecasting based on genetic algorithm feature selection and artificial neural network modeling. A feed forward artificial neural network is used to model the 24-h ahead load based on past consumption, weather and stock index data. A genetic algorithm is used in order to find the best subset of variables for modeling. Three data sets of different geographical locations, encompassing areas of different dimensions with distinct load profiles are used in order to evaluate the methodology. The developed approach was found to generate models achieving a minimum mean average percentage error under 2 %. The feature selection algorithm was able to significantly reduce the number of used features and increase the accuracy of the models

A Mathematical Basis for Satisficing Decision Making

This paper presents an analysis of the satisficing decisionmaking process in a simple organization under multiple objectives. The role of aspiration levels or reference objective levels is stressed and a conceptual model of this behavior is presented. A specification or rather modification of the mathematical concept of a value (utility) function that describes the satisficing behavior is given; the modified value function, called the achievement scalarizing function, should not be only order preserving but also order approximating in a certain sense. It is shown that the notions of reference objective levels and achievement scalarizing functions form a mathematical basis not only for satisficing decision making but also for Pareto optimization; this basis is an alternative to or even stronger than the approaches based on weighting coefficients or typical value functions. This mathematical basis, which can also be considered as a generalization of the goal programming approach in multiobjective optimization, results in pragmatic approaches to many problems of multiobjective analysis, including the problem of interactive assessment of solutions to economic models for policy analysis and planning purposes

Randomly generated polytopes for testing mathematical programming algorithms

Randomly generated polytopes are used frequently to test and compare algorithms for a variety of mathematical programming problems. These polytopes are constructed by generating linear inequality constraints with coefficients drawn independently from a distribution such as the uniform or the normal. It is noted that this class of 'random' polytopes has a special property: the angles between the hyperplanes, though dependent on the specific distribution used, tend to be equal when the dimension of the space increases. Obviously this structure of 'random' polytopes may bias test results

Profitability as a business goal: the multicriteria approach to the ranking of the five largest Croatian banks

Background: The ranking of commercial banks is usually based on using a single criterion, the size of assets or income. A multicriteria approach allows a more complex analysis of their business efficiency. Objectives: This paper proposes the ranking of banks based on six financial criteria using a multicriteria approach implementing a goal programming model. The criteria are classified into three basic groups: profitability, credit risk and solvency. Methods/Approach: Business performance is evaluated using a score for each bank, calculated as the weighted sum of relative values of individual indicators. Results: In the process of solving the corresponding goal programming problem, the weights are calculated. It is assumed that the goal of each bank is the highest profitability. Because of the market competition among banks, the weights of indicators depend on the performance of each bank. This method is applied to the five biggest Croatian banks (ZABA, PBZ, ERSTE, RBA and HYPO). Conclusion: For the observed period (2010), the highest priority is given to profitability and then to credit risk. The ranking is achieved by using a multicriteria model