Current Search:   Liu, Andrew (x)

View All Items

  • CSV Spreadsheet
(1 - 2 of 2)
Work and Family Conflict: A Comparative Analysis Among Staff Nurses, Nurse Managers, and Nurse Executives
Title
Work and Family Conflict: A Comparative Analysis Among Staff Nurses, Nurse Managers, and Nurse Executives.
Creator
Raffenaud, Amanda, Unruh, Lynn, Liu, Albert Xinliang, Fottler, Myron, Andrews, Diane, University of Central Florida
Abstract / Description
The nursing workforce increasingly faces issues that affect clinical and managerial practice. One such issue is work-family conflict (WFC) and family-work conflict (FWC). Nurses face role strain as they confront the pressures from often competing work-and-family roles. This study assessed WFC/FWC among varying nurse roles: staff nurses, managerial nurses, and nurse executives. A random sample of 5,000 nurses, generated from registered nurses practicing in the state of Florida, was surveyed...
Show moreThe nursing workforce increasingly faces issues that affect clinical and managerial practice. One such issue is work-family conflict (WFC) and family-work conflict (FWC). Nurses face role strain as they confront the pressures from often competing work-and-family roles. This study assessed WFC/FWC among varying nurse roles: staff nurses, managerial nurses, and nurse executives. A random sample of 5,000 nurses, generated from registered nurses practicing in the state of Florida, was surveyed for this research study. Nurses were surveyed on demographics, perceptions regarding the work environment, and perceptions of WFC/FWC. Descriptively, nurses experienced more work-family conflict than family-work conflict. Regression analyses and ANOVAs indicated that staff nurses experienced less work-family conflict than nursing managers (second most) and nursing executives (highest). None of the nurse roles experienced significant levels of FWC. White nurses, compared to non-white nurses, experienced less WFC and FWC. WFC increased with shift length but FWC was not significantly affected by it. Paid leave for childbirth was associated with lower FWC. This study holds significant implication for the nursing workforce. Nurse managers and executives showed significantly higher WFC than staff nurses. This may discourage a nurse from taking on leadership roles or lead to leaving them. In an era where nurse managers and leaders are needed, efforts must be taken to decrease WFC/FWC factors. Nonwhite nurses reported higher levels of both WFC and FWC. This may contribute to tension at the workplace and a difficult family life. Leaders must continue to create platforms for nurses of all races and ethnicities to voice their work and family needs, and to be supported when doing so. Nurses working shifts over 8 hours had higher WFC levels. Although 12-hour shifts have been popular among staff and management, their use should be reevaluated. Finally, paid leave for childbirth is a program worth supporting, as it was a factor in lower FWC.
Show less
Date Issued
2018
Identifier
CFE0007081, ucf:51997
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0007081
Stochastic Optimization for Integrated Energy System with Reliability Improvement Using Decomposition Algorithm
Title
Stochastic Optimization for Integrated Energy System with Reliability Improvement Using Decomposition Algorithm.
Creator
Huang, Yuping, Zheng, Qipeng, Xanthopoulos, Petros, Pazour, Jennifer, Liu, Andrew, University of Central Florida
Abstract / Description
As energy demands increase and energy resources change, the traditional energy system has beenupgraded and reconstructed for human society development and sustainability. Considerable studies have been conducted in energy expansion planning and electricity generation operations bymainly considering the integration of traditional fossil fuel generation with renewable generation.Because the energy market is full of uncertainty, we realize that these uncertainties have continuously challenged...
Show moreAs energy demands increase and energy resources change, the traditional energy system has beenupgraded and reconstructed for human society development and sustainability. Considerable studies have been conducted in energy expansion planning and electricity generation operations bymainly considering the integration of traditional fossil fuel generation with renewable generation.Because the energy market is full of uncertainty, we realize that these uncertainties have continuously challenged market design and operations, even a national energy policy. In fact, only a few considerations were given to the optimization of energy expansion and generation taking into account the variability and uncertainty of energy supply and demand in energy markets. This usually causes an energy system unreliable to cope with unexpected changes, such as a surge in fuel price, a sudden drop of demand, or a large renewable supply fluctuation. Thus, for an overall energy system, optimizing a long-term expansion planning and market operation in a stochastic environment are crucial to improve the system's reliability and robustness.As little consideration was paid to imposing risk measure on the power management system, this dissertation discusses applying risk-constrained stochastic programming to improve the efficiency,reliability and economics of energy expansion and electric power generation, respectively. Considering the supply-demand uncertainties affecting the energy system stability, three different optimization strategies are proposed to enhance the overall reliability and sustainability of an energy system. The first strategy is to optimize the regional energy expansion planning which focuses on capacity expansion of natural gas system, power generation system and renewable energy system, in addition to transmission network. With strong support of NG and electric facilities, the second strategy provides an optimal day-ahead scheduling for electric power generation system incorporating with non-generation resources, i.e. demand response and energy storage. Because of risk aversion, this generation scheduling enables a power system qualified with higher reliability and promotes non-generation resources in smart grid. To take advantage of power generation sources, the third strategy strengthens the change of the traditional energy reserve requirements to risk constraints but ensuring the same level of systems reliability In this way we can maximize the use of existing resources to accommodate internal or/and external changes in a power system.All problems are formulated by stochastic mixed integer programming, particularly consideringthe uncertainties from fuel price, renewable energy output and electricity demand over time. Taking the benefit of models structure, new decomposition strategies are proposed to decompose the stochastic unit commitment problems which are then solved by an enhanced Benders Decomposition algorithm. Compared to the classic Benders Decomposition, this proposed solution approachis able to increase convergence speed and thus reduce 25% of computation times on the same cases.
Show less
Date Issued
2014
Identifier
CFE0005506, ucf:50339
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0005506