6 resultados para first-priority relation graph
em Digital Commons at Florida International University
Resumo:
In community college nursing programs the high rate of attrition was a major concern to faculty and administrators. Since first semester attrition could lead to permanent loss of students and low retention in nursing programs, it was important to identify at-risk students early and develop proactive approaches to assist them to be successful. The goal of nursing programs was to graduate students who were eligible to take the national council licensing examination (RN). This was especially important during a time of critical shortage in the nursing workforce. ^ This study took place at a large, multi-campus community college, and used Tinto's (1975) Student Integration Model of persistence as the framework. A correlational study was conducted to determine whether the independent variables, past academic achievement, English proficiency, achievement tendency, weekly hours of employment and financial resources, could discriminate between the two grade groups, pass and not pass. Establishing the relationship between the selected variables and successful course completion might be used to reduce attrition and improve retention. Three research instruments were used to collect data. A Demographic Information form developed by the researcher was used to obtain academic data, the research questionnaire Measure of Achieving Tendency measured achievement motivation, and the Test of Adult Basic Education (TABE), Form 8, Level A, Tests 1, 4, and 5 measured the level of English proficiency. The Department of Nursing academic policy, requiring a minimum course grade of “C” or better was used to determine the final course outcome. A stepwise discriminant analysis procedure indicated that college language level and pre-semester grade point average were significant predictors of final course outcome. ^ Based on the findings of the study recommendations focused on assessing students' English proficiency prior to admission into the nursing program, an intensive remediation plan in language comprehension for at-risk students, and the selection of alternate textbooks and readings that more closely matched the English proficiency level of the students. A pilot study should be conducted to investigate the benefit of raising the admission grade point average. ^
Resumo:
Optimization of adaptive traffic signal timing is one of the most complex problems in traffic control systems. This dissertation presents a new method that applies the parallel genetic algorithm (PGA) to optimize adaptive traffic signal control in the presence of transit signal priority (TSP). The method can optimize the phase plan, cycle length, and green splits at isolated intersections with consideration for the performance of both the transit and the general vehicles. Unlike the simple genetic algorithm (GA), PGA can provide better and faster solutions needed for real-time optimization of adaptive traffic signal control. ^ An important component in the proposed method involves the development of a microscopic delay estimation model that was designed specifically to optimize adaptive traffic signal with TSP. Macroscopic delay models such as the Highway Capacity Manual (HCM) delay model are unable to accurately consider the effect of phase combination and phase sequence in delay calculations. In addition, because the number of phases and the phase sequence of adaptive traffic signal may vary from cycle to cycle, the phase splits cannot be optimized when the phase sequence is also a decision variable. A "flex-phase" concept was introduced in the proposed microscopic delay estimation model to overcome these limitations. ^ The performance of PGA was first evaluated against the simple GA. The results show that PGA achieved both faster convergence and lower delay for both under- or over-saturated traffic conditions. A VISSIM simulation testbed was then developed to evaluate the performance of the proposed PGA-based adaptive traffic signal control with TSP. The simulation results show that the PGA-based optimizer for adaptive TSP outperformed the fully actuated NEMA control in all test cases. The results also show that the PGA-based optimizer was able to produce TSP timing plans that benefit the transit vehicles while minimizing the impact of TSP on the general vehicles. The VISSIM testbed developed in this research provides a powerful tool to design and evaluate different TSP strategies under both actuated and adaptive signal control. ^
Resumo:
This study investigated Microteaching Lesson Study (MLS) and three possible MLS mentor interaction structures during the debriefing sessions in relation to elementary preservice teacher development of knowledge for teaching. One hundred three elementary preservice teachers enrolled in five different sections of a mathematics methods course at a southern urban university were part of the study. This included 72 participants who completed MLS across three different mentor interaction structures as part of their course requirements and 31 elementary preservice teachers who did not complete MLS as part of their methods course and served as a comparison group for a portion of the study. A sequential mixed-methods research design was used to analyze the relationship between MLS mentor interaction structure and growth in preservice teachers' mathematics teacher knowledge. Data sources included pre and post assessments, group developed lesson plans and final reports, a feedback survey with Likert-type and open-ended questions, and transcripts of audio-recorded debriefing sessions. The pre and post assessments were analyzed using Analysis of Variance (ANOVA) and descriptive statistics were used to analyze the Likert-type feedback survey questions. Group MLS lesson plans, final reports, and transcripts of debriefing sessions along with the open-ended questions from the feedback survey were coded in a three-step process as described by Miles and Huberman (1994). In alignment with findings from M. Fernandez (2005, 2010), elementary preservice teachers participating in MLS grew in content knowledge related to MLS topics taught by one another. Results from the analysis of pre and post content knowledge assessments revealed that participants grew in their understanding of the mathematics topics taught during MLS irrespective of their mentor interaction structure and when compared to the participants who did not complete MLS in their methods course. Findings from the analysis of lesson plans for growth in pedagogical content knowledge revealed the most growth in this area occurred for participants assigned to the interaction structure in which the MLS mentor participated in the first two debriefing sessions. Analysis of the transcripts of the discourse during the debriefing sessions and the feedback surveys support the finding that the elementary preservice teachers assigned to the interaction structure in which the MLS mentor participated in the first and second debriefing sessions benefited more from the MLS experience when compared to elementary preservice teachers assigned to the other two interaction structures (MLS mentor participated in only the first debriefing session and MLS mentor participated in only the last debriefing session).
Resumo:
As the nursing profession faces a shortage of nurses, workplace initiatives focused on retaining employees are critical to the United States healthcare industry (Sochalski, 2002). The purpose of this research was to determine whether self-reported intent to stay on the job was related to perceptions of workplace empowerment using Kanter's (1977) theory of organizational empowerment as a framework. ^ The sample consisted of 206 Florida registered nurses. Four self-report scales and a demographic questionnaire were administered by mail. The Conditions for Work Effectiveness Questionnaire (CWEQ; Chandler, 1987), Job Activity Scale (JAS; Laschinger, Kutzscher, & Sabiston, 1993), Organizational Relationships Scale (ORS; Laschinger, Sabiston, & Kutzscher, 1993) and an intent to stay instrument (Kim, Price, Mueller & Watson, 1996) were used to measure perceived access to empowerment structures, perceived formal power, perceived informal power, and intent to stay, respectively. The data were analyzed using descriptive statistics, correlational analysis, and hierarchical regression. ^ Twenty-eight percent of the variance of intent to stay was explained by perceived access to empowerment structures, perceived formal power, and perceived informal power when holding age, gender, education, overall nursing experience, and number of years on current job constant. Perceived access to empowerment structures (CWEQ total score) was the best predictor of self-reported intent to stay for this sample. Of the four components of perceived access to work empowerment structures, perceived access to opportunity and resources were the best predictors of nurses' intent to stay on the job. ^ This study was the first step in establishing the relationship between Kanter's full model and intent to remain on the job, which is a stepping stone for the development of effective retention strategies based on a workplace empowerment model. This knowledge is particularly important in today's healthcare industry where healthcare administrators and human resource development practitioners are ideally positioned to implement organizational strategies to enhance access to work empowerment structures and potentially reduce turnover and mitigate the effects of nursing shortage. ^
Resumo:
The first part of this paper deals with an extension of Dirac's Theorem to directed graphs. It is related to a result often referred to as the Ghouila-Houri Theorem. Here we show that the requirement of being strongly connected in the hypothesis of the Ghouila-Houri Theorem is redundant. The Second part of the paper shows that a condition on the number of edges for a graph to be hamiltonian implies Ore's condition on the degrees of the vertices.
Resumo:
Carbon capture and storage (CCS) can contribute significantly to addressing the global greenhouse gas (GHG) emissions problem. Despite widespread political support, CCS remains unknown to the general public. Public perception researchers have found that, when asked, the public is relatively unfamiliar with CCS yet many individuals voice specific safety concerns regarding the technology. We believe this leads many stakeholders conflate CCS with the better-known and more visible technology hydraulic fracturing (fracking). We support this with content analysis of media coverage, web analytics, and public lobbying records. Furthermore, we present results from a survey of United States residents. This first-of-its-kind survey assessed participants’ knowledge, opinions and support of CCS and fracking technologies. The survey showed that participants had more knowledge of fracking than CCS, and that knowledge of fracking made participants less willing to support CCS projects. Additionally, it showed that participants viewed the two technologies as having similar risks and similar risk intensities. In the CCS stakeholder literature, judgment and decision-making (JDM) frameworks are noticeably absent, and public perception is not discussed using any cognitive biases as a way of understanding or explaining irrational decisions, yet these survey results show evidence of both anchoring bias and the ambiguity effect. Public acceptance of CCS is essential for a national low-carbon future plan. In conclusion, we propose changes in communications and incentives as programs to increase support of CCS.