36 resultados para Decision analysis


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The purpose of this study was to analyze the evolution of Florida state level policy efforts and to assess the responding educational policy development and implementation at the local school district level. The focus of this study was the secondary language arts curriculum in Miami-Dade County Public Schools. Data was collected using document analysis as a source of meaning making out of the language sets proffered by agencies at each level. A matrix was created based on Klein's levels of curriculum decision-making and Functional Process Theory categories of policy formation. The matrix allowed the researcher to code and classify specific information in terms accountability/high-stakes testing; authority; outside influences; and operational/structural organization. Federal policy documents provided a background and impetus for much of what originated at the State level. The State then produced policy directives which were accepted by the District and specific policy directives and guidelines for practice. No evidence was found indicating the involvement of any other agencies in the development, transmission or implementation of the State level initiated policies. After analyzing the evolutionary process, it became clear that state policy directives were never challenged or discussed. Rather, they were accepted as standards to be met and as such, school districts complied. Policy implementation is shown to be a top-down phenomenon. No evidence was found indicating a dialogue between state and local systems, rather the state, as the source of authority, issued specifically worded policy directives and the district complied. Finally, this study recognizes that outside influences play an important role in shaping the education reform policy in the state of Florida. The federal government, through NCLB and other initiatives created a climate which led almost naturally to the creation of the Florida A+ Plan. Similarly, the concern of the business community, always interested in the production of competent workers, continued to support efforts at raising the minimum skill level of Florida high school graduates. Suggestions are made for future research including the examination of local school sites in order to assess the overall nature of the school experience rather than rely upon performance indicators mandated by state policy.

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In human society, people encounter various deontic conflicts every day. Deontic decisions are those that include moral, ethical, and normative aspects. Here, the concern is with deontic conflicts: decisions where all the alternatives lead to the violation of some norms. People think critically about these kinds of decisions. But, just ‘what’ they think about is not always clear. People use certain estimating factors/criteria to balance the tradeoffs when they encounter deontic conflicts. It is unclear what subjective factors people use to make a deontic decision. An elicitation approach called the Open Factor Conjoint System is proposed, which applies an online elicitation methodology which is a combination of two well-know research methodologies: repertory grid and conjoint analysis. This new methodology is extended to be a web based application. It seeks to elicit additional relevant (subjective) factors from people, which affect deontic decisions. The relative importance and utility values are used for the development of a decision model to predict people’s decisions. Fundamentally, this methodology was developed and intended to be applicable for a wide range of elicitation applications with minimal experimenter bias. Comparing with the traditional method, this online survey method reduces the limitation of time and space in data collection and this methodology can be applied in many fields. Two possible applications were addressed: robotic vehicles and the choice of medical treatment. In addition, this method can be applied to many research related disciplines in cross-cultural research due to its online ability with global capacity.

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Subtitle D of the Resource Conservation and Recovery Act (RCRA) requires a post closure period of 30 years for non hazardous wastes in landfills. Post closure care (PCC) activities under Subtitle D include leachate collection and treatment, groundwater monitoring, inspection and maintenance of the final cover, and monitoring to ensure that landfill gas does not migrate off site or into on site buildings. The decision to reduce PCC duration requires exploration of a performance based methodology to Florida landfills. PCC should be based on whether the landfill is a threat to human health or the environment. Historically no risk based procedure has been available to establish an early end to PCC. Landfill stability depends on a number of factors that include variables that relate to operations both before and after the closure of a landfill cell. Therefore, PCC decisions should be based on location specific factors, operational factors, design factors, post closure performance, end use, and risk analysis. The question of appropriate PCC period for Florida’s landfills requires in depth case studies focusing on the analysis of the performance data from closed landfills in Florida. Based on data availability, Davie Landfill was identified as case study site for a case by case analysis of landfill stability. The performance based PCC decision system developed by Geosyntec Consultants was used for the assessment of site conditions to project PCC needs. The available data for leachate and gas quantity and quality, ground water quality, and cap conditions were evaluated. The quality and quantity data for leachate and gas were analyzed to project the levels of pollutants in leachate and groundwater in reference to maximum contaminant level (MCL). In addition, the projected amount of gas quantity was estimated. A set of contaminants (including metals and organics) were identified as contaminants detected in groundwater for health risk assessment. These contaminants were selected based on their detection frequency and levels in leachate and ground water; and their historical and projected trends. During the evaluations a range of discrepancies and problems that related to the collection and documentation were encountered and possible solutions made. Based on the results of PCC performance integrated with risk assessment, projection of future PCC monitoring needs and sustainable waste management options were identified. According to these results, landfill gas monitoring can be terminated, leachate and groundwater monitoring for parameters above MCL and surveying of the cap integrity should be continued. The parameters which cause longer monitoring periods can be eliminated for the future sustainable landfills. As a conclusion, 30 year PCC period can be reduced for some of the landfill components based on their potential impacts to human health and environment (HH&E).

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This dissertation establishes a novel data-driven method to identify language network activation patterns in pediatric epilepsy through the use of the Principal Component Analysis (PCA) on functional magnetic resonance imaging (fMRI). A total of 122 subjects’ data sets from five different hospitals were included in the study through a web-based repository site designed here at FIU. Research was conducted to evaluate different classification and clustering techniques in identifying hidden activation patterns and their associations with meaningful clinical variables. The results were assessed through agreement analysis with the conventional methods of lateralization index (LI) and visual rating. What is unique in this approach is the new mechanism designed for projecting language network patterns in the PCA-based decisional space. Synthetic activation maps were randomly generated from real data sets to uniquely establish nonlinear decision functions (NDF) which are then used to classify any new fMRI activation map into typical or atypical. The best nonlinear classifier was obtained on a 4D space with a complexity (nonlinearity) degree of 7. Based on the significant association of language dominance and intensities with the top eigenvectors of the PCA decisional space, a new algorithm was deployed to delineate primary cluster members without intensity normalization. In this case, three distinct activations patterns (groups) were identified (averaged kappa with rating 0.65, with LI 0.76) and were characterized by the regions of: 1) the left inferior frontal Gyrus (IFG) and left superior temporal gyrus (STG), considered typical for the language task; 2) the IFG, left mesial frontal lobe, right cerebellum regions, representing a variant left dominant pattern by higher activation; and 3) the right homologues of the first pattern in Broca's and Wernicke's language areas. Interestingly, group 2 was found to reflect a different language compensation mechanism than reorganization. Its high intensity activation suggests a possible remote effect on the right hemisphere focus on traditionally left-lateralized functions. In retrospect, this data-driven method provides new insights into mechanisms for brain compensation/reorganization and neural plasticity in pediatric epilepsy.

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Accounting students become practitioners facing ethical decision-making challenges that can be subject to various interpretations; hence, the profession is concerned with the appropriateness of their decisions. Moral development of these students has implications for a profession under legal challenges, negative publicity, and government scrutiny. Accounting students moral development has been studied by examining their responses to moral questions in Rest's Defining Issues Test (DIT), their professional attitudes on Hall's Professionalism Scale Dimensions, and their ethical orientation-based professional commitment and ethical sensitivity. This study extended research in accounting ethics and moral development by examining students in a college where an ethics course is a requirement for graduation. Knowledge of differences in the moral development of accounting students may alert practitioners and educators to potential problems resulting from a lack of ethical understanding as measured by moral development levels. If student moral development levels differ by major, and accounting majors have lower levels than other students, the conclusion may be that this difference is a causative factor for the alleged acts of malfeasance in the profession that may result in malpractice suits. The current study compared 205 accounting, business, and nonbusiness students from a private university. In addition to academic major and completion of an ethics course, the other independent variable was academic level. Gender and age were tested as control variables and Rest's DIT score was the dependent variable. The primary analysis was a 2x3x3 ANOVA with post hoc tests for results with significant p-value of less than 0.05. The results of this study reveal that students who take an ethics course appear to have a higher level of moral development (p=0.013), as measured by the (DIT), than students at the same academic level who have not taken an ethics course. In addition, a statistically significant difference (p=0.034) exists between freshmen who took an ethics class and juniors who did not take an ethics class. For every analysis except one, the lower class year with an ethics class had a higher level of moral development than the higher class year without an ethics class. These results appear to show that ethics education in particular has a greater effect on the level of moral development than education in general. Findings based on the gender specific analyses appear to show that males and females respond differently to the effects of taking an ethics class. The male students do not appear to increase their moral development level after taking an ethics course (p=0.693) but male levels of moral development differ significantly (p=0.003) by major. Female levels of moral development appear to increase after taking an ethics course (p=0.002). However, they do not differ according to major (p=0.0 97). These findings indicate that accounting students should be required to have a class in ethics as part of their college curriculum. Students with an ethics class have a significantly higher level of moral development. The challenges facing the profession at the current time indicate that public confidence in the reports of client corporations has eroded and one way to restore this confidence could be to require ethics training of future accountants.

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This dissertation introduces a new approach for assessing the effects of pediatric epilepsy on the language connectome. Two novel data-driven network construction approaches are presented. These methods rely on connecting different brain regions using either extent or intensity of language related activations as identified by independent component analysis of fMRI data. An auditory description decision task (ADDT) paradigm was used to activate the language network for 29 patients and 30 controls recruited from three major pediatric hospitals. Empirical evaluations illustrated that pediatric epilepsy can cause, or is associated with, a network efficiency reduction. Patients showed a propensity to inefficiently employ the whole brain network to perform the ADDT language task; on the contrary, controls seemed to efficiently use smaller segregated network components to achieve the same task. To explain the causes of the decreased efficiency, graph theoretical analysis was carried out. The analysis revealed no substantial global network feature differences between the patient and control groups. It also showed that for both subject groups the language network exhibited small-world characteristics; however, the patient’s extent of activation network showed a tendency towards more random networks. It was also shown that the intensity of activation network displayed ipsilateral hub reorganization on the local level. The left hemispheric hubs displayed greater centrality values for patients, whereas the right hemispheric hubs displayed greater centrality values for controls. This hub hemispheric disparity was not correlated with a right atypical language laterality found in six patients. Finally it was shown that a multi-level unsupervised clustering scheme based on self-organizing maps, a type of artificial neural network, and k-means was able to fairly and blindly separate the subjects into their respective patient or control groups. The clustering was initiated using the local nodal centrality measurements only. Compared to the extent of activation network, the intensity of activation network clustering demonstrated better precision. This outcome supports the assertion that the local centrality differences presented by the intensity of activation network can be associated with focal epilepsy.