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- Title
- LEADERSHIP ORIENTATIONS OFCOMMUNITY COLLEGE PRESIDENTS AND THE ADMINISTRATORS WHO REPORT TO THEM: A FRAME ANALYSIS.
- Creator
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McArdle, Michele, Taylor, Rosemarye, University of Central Florida
- Abstract / Description
-
Presidents of Community Colleges and the administrators who reported directly to them were the subjects for this study based on the Four Frame Leadership Theory of Bolman and Deal (1990b). The Leadership Orientation (Self) Survey (LOS) was mailed to 169 community college presidents and administrators in the presidents' direct report teams. The final usable response rate of 69.82% to the survey fell within the acceptable range for education as defined by Boser and Green (1997). In addition...
Show morePresidents of Community Colleges and the administrators who reported directly to them were the subjects for this study based on the Four Frame Leadership Theory of Bolman and Deal (1990b). The Leadership Orientation (Self) Survey (LOS) was mailed to 169 community college presidents and administrators in the presidents' direct report teams. The final usable response rate of 69.82% to the survey fell within the acceptable range for education as defined by Boser and Green (1997). In addition, the subjects were asked to write about the most difficult challenge they had faced in their current position and how they handled that challenge. The purpose of this study was to determine (a) the usage of leadership frames from both groups; presidents and their administrative teams, (b) if gender or years of experience in their current positions were factors in leadership frame usage in each group, and (c) if there was a relationship between a president's frame usage and the frame usage of the members of the direct report team. The major findings were: 1. The presidents and administrators displayed the highest mean scores for the human resource frame with the mean scores of the three remaining frames (structural, political, and symbolic) clustering as a second unit of responses. In the narrative segment of the survey, the most frequently rated central theme among the presidents and the direct reports was the political frame. 2. The results from statistical analysis of the responses from both groups (presidents and the administrators who directly reported to them) did not show any statistically significant difference among frame use based on gender or number of years of experience in their positions. 3. The correlation coefficients did not indicate that there was a relationship in either direction regarding leadership style between the two groups (presidents and administrators). A phenomenological analysis of the scenario statements from these two groups indicated that presidents who used the political frame as a central theme tended to have administrators who also used the political frame as one or as a pair of central themes. Presidents who used the symbolic frame as a central theme tended to have administrators who used all four frames as central themes in their narratives. 4. A fourth finding was the discrepancy in the ability of the leaders to use multiple frames as demonstrated in the results from the quantitative and qualitative findings. The quantitative data suggested that these leaders were practicing the techniques of multi-framing more than one-half of the time. Contrary to this finding, the qualitative data showed that 5 of 30 scenario statements showed paired frames being used as central frames. 5. One additional finding based on the qualitative statements by presidents and their administrators revealed much thought and intentional practice in the leaders' ability to build teams.
Show less - Date Issued
- 2008
- Identifier
- CFE0002301, ucf:47872
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0002301
- Title
- Leaning Robust Sequence Features via Dynamic Temporal Pattern Discovery.
- Creator
-
Hu, Hao, Wang, Liqiang, Zhang, Shaojie, Liu, Fei, Qi, GuoJun, Zhou, Qun, University of Central Florida
- Abstract / Description
-
As a major type of data, time series possess invaluable latent knowledge for describing the real world and human society. In order to improve the ability of intelligent systems for understanding the world and people, it is critical to design sophisticated machine learning algorithms for extracting robust time series features from such latent knowledge. Motivated by the successful applications of deep learning in computer vision, more and more machine learning researchers put their attentions...
Show moreAs a major type of data, time series possess invaluable latent knowledge for describing the real world and human society. In order to improve the ability of intelligent systems for understanding the world and people, it is critical to design sophisticated machine learning algorithms for extracting robust time series features from such latent knowledge. Motivated by the successful applications of deep learning in computer vision, more and more machine learning researchers put their attentions on the topic of applying deep learning techniques to time series data. However, directly employing current deep models in most time series domains could be problematic. A major reason is that temporal pattern types that current deep models are aiming at are very limited, which cannot meet the requirement of modeling different underlying patterns of data coming from various sources. In this study we address this problem by designing different network structures explicitly based on specific domain knowledge such that we can extract features via most salient temporal patterns. More specifically, we mainly focus on two types of temporal patterns: order patterns and frequency patterns. For order patterns, which are usually related to brain and human activities, we design a hashing-based neural network layer to globally encode the ordinal pattern information into the resultant features. It is further generalized into a specially designed Recurrent Neural Networks (RNN) cell which can learn order patterns in an online fashion. On the other hand, we believe audio-related data such as music and speech can benefit from modeling frequency patterns. Thus, we do so by developing two types of RNN cells. The first type tries to directly learn the long-term dependencies on frequency domain rather than time domain. The second one aims to dynamically filter out the ``noise" frequencies based on temporal contexts. By proposing various deep models based on different domain knowledge and evaluating them on extensive time series tasks, we hope this work can provide inspirations for others and increase the community's interests on the problem of applying deep learning techniques to more time series tasks.
Show less - Date Issued
- 2019
- Identifier
- CFE0007470, ucf:52679
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007470
- Title
- A qualitative analysis of key concepts in Islam from the perspective of imams.
- Creator
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Dobiyanski, Chandler, Matusitz, Jonathan, Yu, Nan, Barfield, Rufus, University of Central Florida
- Abstract / Description
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The continuous occurrence of terrorist attacks in the name of Islam has shown this ideology and its tenets are at least somewhat connected to jihadists committing attacks in its name. This ideology in terms of 13 themes was investigated by the researcher in 58 sermons outlined in the tables in the appendix. These themes include: brotherhood, death, freedom, human rights, justice and equality, love, oppression, peace and treaty, self-defense, sin, submission, terrorism and truth vs. lies. The...
Show moreThe continuous occurrence of terrorist attacks in the name of Islam has shown this ideology and its tenets are at least somewhat connected to jihadists committing attacks in its name. This ideology in terms of 13 themes was investigated by the researcher in 58 sermons outlined in the tables in the appendix. These themes include: brotherhood, death, freedom, human rights, justice and equality, love, oppression, peace and treaty, self-defense, sin, submission, terrorism and truth vs. lies. The researcher used a sample of 10 sermons from U.S.- born imams and 10 sermons from foreign-born imams as the basis for the analysis for the theories and themes. Conducting a thematic analysis of U.S.-born and foreign-born imams' sermons, the researcher uncovered their true interpretations of these themes. Following this, the researcher investigated the imams' speech codes.The researcher found that imams who were born in the United States focused more on religious speech codes compared to the international imams who focused more prominently on cultural speech codes. In terms of social codes, foreign-born imams seem to be more focused on relationships, while those born in the United States focuses more on religious conduct. In terms of religious codes, foreign-born imams seem to have a checklist of requirements in how to act, including referencing believers vs. disbelievers and historical aspects of the codes, while those born in the United States focused on more codes that referred to everyday activities, people and the kind of conduct that a Muslim should have. In terms of cultural codes, foreign-born imams seem to have an immediate need to physically defend against outside forces. This is compared to the United States-born imams, who discuss how to better oneself, how cultural aspects are a distraction and how Muslim converts are more inspirational than the Muslim-born since the converts actively rejected their cultural norms in favor of Islam.
Show less - Date Issued
- 2018
- Identifier
- CFE0007324, ucf:52145
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007324
- Title
- Business Closure in the North American Theme Park Industry: An Analysis of Causes.
- Creator
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Kaak, Kelly, Milman, Ady, Breiter Terry, Deborah, Mendez, Jesse, Schuckert, Markus, University of Central Florida
- Abstract / Description
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Prior to this study, no analysis had focused on the 31% failure rate recorded among theme parks opened in North American between the years 1955 and 2009. This study's purpose was to identify the causes of closures among the 23 failed theme parks and inform the industry of what can be learned from these business failures. Business failure analysis typically stresses the impact of financial ratios and the accuracy of certain negative numbers to predict impending failure, but such studies avoid...
Show morePrior to this study, no analysis had focused on the 31% failure rate recorded among theme parks opened in North American between the years 1955 and 2009. This study's purpose was to identify the causes of closures among the 23 failed theme parks and inform the industry of what can be learned from these business failures. Business failure analysis typically stresses the impact of financial ratios and the accuracy of certain negative numbers to predict impending failure, but such studies avoid examining the underlying causes that lead to poor financial performance in the first place. To focus on this question, this study adopted an events approach to discover the actual event causes that preceded failure and business closure. This study tabulated the frequency of event occurrences among two samples: failed/closed theme parks and a comparable sample of surviving theme parks. Event occurrences were more common among the failed/closed sample than among the surviving theme parks sample. A detailed analysis revealed that six of the 21 events measured were more common among the failed/closed theme park sample: declaring bankruptcy; excessive debt or general unprofitability; low customer satisfaction, defined as not offering enough to do in the park and/or inadequate capacity; development pressures; limited space for expansion; and a location in a regional geographic market. Theme parks failed more frequently due to involuntary event causes than due to voluntary closures. And, in contrast to previous studies, the occurrences of internal environmental events associated with business failure were not significantly different from the occurrences of external environmental events associated with failure. These findings identified events that have preceded failure or closure in theme parks and can provide insights to operators and industry decision makers on how best to prevent or better manage such business closures in the future.
Show less - Date Issued
- 2018
- Identifier
- CFE0007026, ucf:52030
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007026
- Title
- A Comprehensive Assessment of Vehicle-to-Grid Systems and Their Impact to the Sustainability of Current Energy and Water Nexus.
- Creator
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Zhao, Yang, Tatari, Omer, Oloufa, Amr, Mayo, Talea, Zheng, Qipeng, University of Central Florida
- Abstract / Description
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This dissertation aims to explore the feasibility of incorporating electric vehicles into the electric power grid and develop a comprehensive assessment framework to predict and evaluate the life cycle environmental, economic and social impact of the integration of Vehicle-to-Grid systems and the transportation-water-energy nexus. Based on the fact that electric vehicles of different classes have been widely adopted by both fleet operators and individual car owners, the following questions...
Show moreThis dissertation aims to explore the feasibility of incorporating electric vehicles into the electric power grid and develop a comprehensive assessment framework to predict and evaluate the life cycle environmental, economic and social impact of the integration of Vehicle-to-Grid systems and the transportation-water-energy nexus. Based on the fact that electric vehicles of different classes have been widely adopted by both fleet operators and individual car owners, the following questions are investigated: 1. Will the life cycle environmental impacts due to vehicle operation be reduced? 2. Will the implementation of Vehicle-to-Grid systems bring environmental and economic benefits? 3. Will there be any form of air emission impact if large amounts of electric vehicles are adopted in a short time? 4. What is the role of the Vehicle-to-Grid system in the transportation-water-energy nexus? To answer these questions: First, the life cycle environmental impacts of medium-duty trucks in commercial delivery fleets are analyzed. Second, the operation mechanism of Vehicle-to-Grid technologies in association with charging and discharging of electric vehicles is researched. Third, the feasible Vehicle-to-Grid system is further studied taking into consideration the spatial and temporal variance as well as other uncertainties within the system. Then, a comparison of greenhouse gas emission mitigation of the Vehicle-to-Grid system and the additional emissions caused by electric vehicle charging through marginal electricity is analyzed. Finally, the impact of the Vehicle-to-Grid system in the transportation-water-energy nexus, and the underlying environmental, economic and social relationships are simulated through system dynamic modeling. The results provide holistic evaluations and spatial and temporal projections of electric vehicles, Vehicle-to-Grid systems, wind power integration, and the transportation-water-energy nexus.
Show less - Date Issued
- 2017
- Identifier
- CFE0007300, ucf:52153
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007300
- Title
- Bioarchaeological Investigations of The Red House Archaeological Site, Port of Spain, Trinidad: A Pre-Columbian, Mid-Late Ceramic Age Caribbean Population.
- Creator
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Meyers, Patrisha, Schultz, John, Williams, Lana, Toyne, J. Marla, Reid, Basil, University of Central Florida
- Abstract / Description
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In 2013 structural assessments associated with ongoing renovations of the Red House, Trinidad and Tobago's Parliament building, revealed human remains buried beneath the foundation. Excavations and radiocarbon dating indicate the remains are pre-Columbian with 14C dates ranging between approximately AD 125 and AD 1395. Due to the small overall sample size and the inability to attribute all individuals to a specific Amerindian period, the skeletal sample was considered as an aggregate. A...
Show moreIn 2013 structural assessments associated with ongoing renovations of the Red House, Trinidad and Tobago's Parliament building, revealed human remains buried beneath the foundation. Excavations and radiocarbon dating indicate the remains are pre-Columbian with 14C dates ranging between approximately AD 125 and AD 1395. Due to the small overall sample size and the inability to attribute all individuals to a specific Amerindian period, the skeletal sample was considered as an aggregate. A bioarchaeological assessment of excavated graves and associated human skeletal material was conducted to determine the demographic profile and the pathological conditions exhibited by the collective skeletal 'population.' Osteological analyses included determining the minimum number of individuals (MNI), assessing the biological profile (e.g. sex, age, ancestry and stature), evaluating pathological conditions, antemortem and perimortem trauma and describing the overall taphonomic modifications. In addition, dental wear patterns, artificial cranial modifications and musculoskeletal stress markers were noted. Finally, the mortuary treatment and context was compared to the limited information published on contemporary skeletal samples from islands in the Lesser Antilles and nearby coastal regions of South America. The sample consisted of an MNI of 60 individuals including 47 adults and 13 juveniles. The skeletal completeness of these individuals ranged from a single skeletal element to more than 90% complete. Sex assessment was possible for 23 individuals with 11 females (23%) and 17 males (35%). Multiple antemortem conditions indicate a total of 35 individuals (58%) who exhibited one or more pathological condition including dental pathology (e.g. LEHs, carious lesions, antemortem tooth loss, dental wear, abscesses and a possible apical cyst), healed antemortem trauma, non-specific generalized infections, osteoarthritis, spinal osteophystosis and Schmorl's nodes. Additional antemortem conditions include examples of artificial cranial modification in both sexes, and activity related humeral bilateral asymmetry. While not a representative population, the reconstruction of health, lifestyle and disease for these ancient peoples makes a significant contribution to the limited osteological research published on the Caribbean's pre-contact period.
Show less - Date Issued
- 2016
- Identifier
- CFE0006144, ucf:52863
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006144
- Title
- A CONTENT ANALYSIS OF JIHADIST MAGAZINES: THEORETICAL PERSPECTIVES.
- Creator
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Udani, Catalina M, Matusitz, Jonathan, Neuberger, Lindsay; Reynolds, Ted, University of Central Florida
- Abstract / Description
-
During its violent spread across the Middle East, the Islamic State of Iraq and Sham (ISIS) amassed both a local and international following in large part due to its usage of emergent media distribution. Beginning in 2014, ISIS's Ministry of Media published an English-language magazine, Dabiq, disseminating its issues through online platforms. Dabiq and its successor Rumiyah both serve as propagandistic recruitment material for ISIS's international community as well as broadcasting the...
Show moreDuring its violent spread across the Middle East, the Islamic State of Iraq and Sham (ISIS) amassed both a local and international following in large part due to its usage of emergent media distribution. Beginning in 2014, ISIS's Ministry of Media published an English-language magazine, Dabiq, disseminating its issues through online platforms. Dabiq and its successor Rumiyah both serve as propagandistic recruitment material for ISIS's international community as well as broadcasting the message of the jihadist movement to ISIS's enemies. This study analyzed ISIS's publications using a qualitative content analysis in order to identify jihadist recruitment strategies through the perspectives of agenda-setting theory, the diffusion of innovations, symbolic convergence theory, and speech codes theory. These communication theories characterize the roles that civilizational conflict, population demographics, narrative themes, and emergent media play in the diffusion of the jihadist movement. This study samples the textual content and imagery of issues of Dabiq and Rumiyah, using thematic analysis to procedurally code the data by recognizing shared characteristics and concepts. The fundamental goal of this study is to gain a greater understanding of the way ISIS, its members, and the jihadist movement communicate their intentions, with the hope of preventing further recruitment and radicalization. The two following research questions drive this study: (1) What themes are present in the ISIS publications of Dabiq and Rumiyah? (2) How do the themes of these publications vary over time?
Show less - Date Issued
- 2018
- Identifier
- CFH2000351, ucf:52905
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFH2000351
- Title
- Managing IO Resource for Co-running Data Intensive Applications in Virtual Clusters.
- Creator
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Huang, Dan, Wang, Jun, Zhou, Qun, Sun, Wei, Zhang, Shaojie, Wang, Liqiang, University of Central Florida
- Abstract / Description
-
Today Big Data computer platforms employ resource management systems such as Yarn, Torque, Mesos, and Google Borg to enable sharing the physical computing among many users or applications. Given virtualization and resource management systems, users are able to launch their applications on the same node with low mutual interference and management overhead on CPU and memory. However, there are still challenges to be addressed before these systems can be fully adopted to manage the IO resources...
Show moreToday Big Data computer platforms employ resource management systems such as Yarn, Torque, Mesos, and Google Borg to enable sharing the physical computing among many users or applications. Given virtualization and resource management systems, users are able to launch their applications on the same node with low mutual interference and management overhead on CPU and memory. However, there are still challenges to be addressed before these systems can be fully adopted to manage the IO resources in Big Data File Systems (BDFS) and shared network facilities. In this study, we mainly study on three IO management problems systematically, in terms of the proportional sharing of block IO in container-based virtualization, the network IO contention in MPI-based HPC applications and the data migration overhead in HPC workflows. To improve the proportional sharing, we develop a prototype system called BDFS-Container, by containerizing BDFS at Linux block IO level. Central to BDFS-Container, we propose and design a proactive IOPS throttling based mechanism named IOPS Regulator, which improves proportional IO sharing under the BDFS IO pattern by 74.4% on an average. In the aspect of network IO resource management, we exploit using virtual switches to facilitate network traffic manipulation and reduce mutual interference on the network for in-situ applications. In order to dynamically allocate the network bandwidth when it is needed, we adopt SARIMA-based techniques to analyze and predict MPI traffic issued from simulations. Third, to solve the data migration problem in small-medium sized HPC clusters, we propose to construct a sided IO path, named as SideIO, to explicitly direct analysis data to BDFS that co-locates computation with data. By experimenting with two real-world scientific workflows, SideIO completely avoids the most expensive data movement overhead and achieves up to 3x speedups compared with current solutions.
Show less - Date Issued
- 2018
- Identifier
- CFE0007195, ucf:52268
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007195
- Title
- Macrolinguistic Analysis of Discourse Production in people with Aphasia, individuals with Mild Cognitive Impairment, and Survivors of Traumatic Brain Injury.
- Creator
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Eaton, Stephanie, Kong, Anthony Pak Hin, Wilson, Lauren Bislick, Rosa-Lugo, Linda, University of Central Florida
- Abstract / Description
-
This study examined the macrolinguistic features of three genres (single picture description, sequential picture description, and story retell) of discourse samples collected from participants with acquired communication disorders (including two speakers with aphasia, two with mild cognitive impairment, and two with traumatic brain injury) and unimpaired controls (n=6). Comparisons were made to investigate group and genre differences. Standardized assessment scores of cognitive and linguistic...
Show moreThis study examined the macrolinguistic features of three genres (single picture description, sequential picture description, and story retell) of discourse samples collected from participants with acquired communication disorders (including two speakers with aphasia, two with mild cognitive impairment, and two with traumatic brain injury) and unimpaired controls (n=6). Comparisons were made to investigate group and genre differences. Standardized assessment scores of cognitive and linguistic evaluations were collected and correlated to features of macrolinguistic discourse analysis.Participants with acquired communication disorders performed best on the story retell discourse task compared to single picture description and sequential picture description. Significant measures for story retell task include lexical efficiency, time efficiency, and Main Concept score. No significant difference was found on performance between single-picture description task and sequential picture description for participants with acquired communication disorders. The Main Concept Analysis presented with the strongest correlation to macrolinguistic features of analysis. These preliminary findings suggest that main concept score is a predominant indicator of the overall informativeness and macrostructure of a speaker's discourse.
Show less - Date Issued
- 2019
- Identifier
- CFE0007799, ucf:52341
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007799
- Title
- Pooling correlation matrices corrected for selection bias: Implications for meta-analysis.
- Creator
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Matthews, Kenneth, Sivo, Stephen, Bai, Haiyan, Hahs-Vaughn, Debbie, Butler, Malcolm, University of Central Florida
- Abstract / Description
-
Selection effects systematically attenuate correlations and must be considered when performing meta-analyses. No research domain is immune to selection effects, evident whenever self-selection or attrition take place. In educational research, selection effects are unavoidable in studies of postsecondary admissions, placement testing, or teacher selection. While methods to correct for selection bias are well documented for univariate meta-analyses, they have gone unexamined in multivariate...
Show moreSelection effects systematically attenuate correlations and must be considered when performing meta-analyses. No research domain is immune to selection effects, evident whenever self-selection or attrition take place. In educational research, selection effects are unavoidable in studies of postsecondary admissions, placement testing, or teacher selection. While methods to correct for selection bias are well documented for univariate meta-analyses, they have gone unexamined in multivariate meta-analyses, which synthesize more than one correlation from each study (i.e., a correlation matrix). Multivariate meta-analyses of correlations provide opportunities to explore complex relationships and correcting for selection effects improves the summary effect estimates. I used Monte Carlo simulations to test two methods of correcting selection effects and evaluate a method for pooling the corrected matrices. First, I examined the performance of Thorndike's corrections (for both explicit and incidental selection) and Lawley's multivariate correction for selection on correlation matrices when explicit selection takes place on a single variable. Simulation conditions included a wide range of selection ratios, samples sizes, and population correlations. The results indicated that univariate and multivariate correction methods perform equivalently. I provide practical guidelines for choosing between the two methods. In a second Monte Carlo simulation, I examined the confidence interval coverage rates of a Robust Variance Estimation (RVE) procedure when it is used to pool correlation matrices corrected for selection effects under a random-effects model. The RVE procedure empirically estimates the standard errors of the corrected correlations and has the advantage of having no distributional assumptions. Simulation conditions included tau-squared ratio, within-study sample size, number of studies, and selection ratio. The results were mixed, with RVE performing well under higher selection ratios and larger unrestricted sample sizes. RVE performed consistently across values of tau-squared. I recommend applications of the results, especially for educational research, and opportunities for future research.
Show less - Date Issued
- 2019
- Identifier
- CFE0007680, ucf:52483
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007680
- Title
- detecting anomalies from big data system logs.
- Creator
-
Lu, Siyang, Wang, Liqiang, Zhang, Shaojie, Zhang, Wei, Wu, Dazhong, University of Central Florida
- Abstract / Description
-
Nowadays, big data systems (e.g., Hadoop and Spark) are being widely adopted by many domains for offering effective data solutions, such as manufacturing, healthcare, education, and media. A common problem about big data systems is called anomaly, e.g., a status deviated from normal execution, which decreases the performance of computation or kills running programs. It is becoming a necessity to detect anomalies and analyze their causes. An effective and economical approach is to analyze...
Show moreNowadays, big data systems (e.g., Hadoop and Spark) are being widely adopted by many domains for offering effective data solutions, such as manufacturing, healthcare, education, and media. A common problem about big data systems is called anomaly, e.g., a status deviated from normal execution, which decreases the performance of computation or kills running programs. It is becoming a necessity to detect anomalies and analyze their causes. An effective and economical approach is to analyze system logs. Big data systems produce numerous unstructured logs that contain buried valuable information. However manually detecting anomalies from system logs is a tedious and daunting task.This dissertation proposes four approaches that can accurately and automatically analyze anomalies from big data system logs without extra monitoring overhead. Moreover, to detect abnormal tasks in Spark logs and analyze root causes, we design a utility to conduct fault injection and collect logs from multiple compute nodes. (1) Our first method is a statistical-based approach that can locate those abnormal tasks and calculate the weights of factors for analyzing the root causes. In the experiment, four potential root causes are considered, i.e., CPU, memory, network, and disk I/O. The experimental results show that the proposed approach is accurate in detecting abnormal tasks as well as finding the root causes. (2) To give a more reasonable probability result and avoid ad-hoc factor weights calculating, we propose a neural network approach to analyze root causes of abnormal tasks. We leverage General Regression Neural Network (GRNN) to identify root causes for abnormal tasks. The likelihood of reported root causes is presented to users according to the weighted factors by GRNN. (3) To further improve anomaly detection by avoiding feature extraction, we propose a novel approach by leveraging Convolutional Neural Networks (CNN). Our proposed model can automatically learn event relationships in system logs and detect anomaly with high accuracy. Our deep neural network consists of logkey2vec embeddings, three 1D convolutional layers, a dropout layer, and max pooling. According to our experiment, our CNN-based approach has better accuracy compared to other approaches using Long Short-Term Memory (LSTM) and Multilayer Perceptron (MLP) on detecting anomaly in Hadoop DistributedFile System (HDFS) logs. (4) To analyze system logs more accurately, we extend our CNN-based approach with two attention schemes to detect anomalies in system logs. The proposed two attention schemes focus on different features from CNN's output. We evaluate our approaches with several benchmarks, and the attention-based CNN model shows the best performance among all state-of-the-art methods.
Show less - Date Issued
- 2019
- Identifier
- CFE0007673, ucf:52499
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007673
- Title
- Front-Line Registered Nurse Job Satisfaction and Predictors: A Meta-Analysis from 1980 - 2009.
- Creator
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Saber, Deborah Anne, Norris, Anne, Andrews, Diane, Byers, Jacqueline, Bowers, Clint, University of Central Florida
- Abstract / Description
-
Front-line registered nurses (RNs) make up the workforce that directly affect the care of patients in a variety of different healthcare settings. RN job satisfaction is important because it is tied to retention, organizational commitment, workforce safety, patient safety, and cost savings. The strongest predictors have been difficult to determine because workplaces differ, numerous tools to measure satisfaction exist, the workforce is diversified by generations and work positions, and ongoing...
Show moreFront-line registered nurses (RNs) make up the workforce that directly affect the care of patients in a variety of different healthcare settings. RN job satisfaction is important because it is tied to retention, organizational commitment, workforce safety, patient safety, and cost savings. The strongest predictors have been difficult to determine because workplaces differ, numerous tools to measure satisfaction exist, the workforce is diversified by generations and work positions, and ongoing policy changes directly impact the work of the front-line RN. The strength and stability of the workforce depends on an accurate understanding of the predictors of job satisfaction for the front-line RN. The purpose of this study was to comprehensively, quantitatively examine predictors of front-line RN job satisfaction from 1980-2009 to provide overarching conclusions based on empirical evidence. Of interest was: the (1) estimation of large, moderate, and small predictor summary effect sizes; (2) assessment of predictor differences among decades (i.e., 1980s, 1990s, and 2000s); (3) identification of causes for predictor differences among studies (i.e., moderators); and (4) investigation of predictor differences between generations (i.e., Baby Boomers, Generation X, and Millennials).A non-a priori meta-analysis approach was guided by inclusion and exclusion criteria to review published and unpublished studies from 1980(-)2009. The search process identified 48 published and 14 unpublished studies used for analysis. Within the studies that met inclusion criteria, 27 job satisfaction predictors met inclusion for analysis. Studies were coded for Study Characteristics (e.g., Year of Publication, Country of Study) that were needed for moderator analysis. Predictors were coded for data that were necessary to calculate predictor summary effect sizes (i.e., r, n). Coding quality was maximized with a coding reliability scheme that included the primary investigator (PI) and secondary coder. A random-effects model was used to guide the calculation of summary effect sizes for each job satisfaction predictor. Publication bias was examined using funnel plots and Rosenthal's Fail-safe N. An analysis of variance (ANOVA) was used to evaluate predictor differences among decades (i.e., 1980s, 1990s, and 2000s). Heterogeneity among studies was calculated (i.e., Q-statistic, I-squared, and Tau-squared) to guide the need for moderator analysis. Moderator analyses were conducted to evaluate Study Characteristics as sources of predictor differences among studies, and to investigate the influence of Age (i.e., generation) on predictor effect sizes.The largest effect sizes were found for three predictors: Task Significance (r=.61), Empowerment (r=.55), and Control (r=.52). Moderate effect sizes were found for 10 predictors (e.g., Autonomy: r=.44; Stress: r=-.43), and small effect sizes were found for nine predictors (e.g., Wages: r=.23; Staffing Adequacy: r=.19). Significant heterogeneity between studies was present in all of the 27 predictor analyses. Effect size differences were not found between decades or generations. Moderator analysis found that the sources of the difference between studies remain unexplained indicating that unknown moderators are present.Findings from this study indicate that the largest predictors of job satisfaction for the front-line RN may be different than previously thought. Heterogeneity between studies and unidentified moderators indicate that there are significant differences among studies and more research is needed to identify the source(s) of these differences. The findings from this study can be used at the organizational, state, and national level to guide leaders to focus efforts of workplace improvements that are based on predictors that are most meaningful to front-line RNs (i.e., Task Requirements, Empowerment, and Control). Future research is needed to determine contemporary predictors of job satisfaction for the front-line RN, and the causes of heterogeneity between studies. The findings from the current study provide the critical synthesis needed to guide educational and practice recommendations aimed at supporting job satisfaction of front-line RNs, thereby, maintaining this integral component of the healthcare workforce.
Show less - Date Issued
- 2012
- Identifier
- CFE0004592, ucf:49220
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004592
- Title
- Sustainable Transportation at the University of Central Florida: Evaluation of UCF Rideshare Program, Zimride.
- Creator
-
Defrancisco, Joseph, Radwan, Ahmed, Abdel-Aty, Mohamed, Harb, Rami, University of Central Florida
- Abstract / Description
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As the second-largest university in the United States, UCF has experienced the largest enrollment in its history. A more densely populated campus has in turn caused increased traffic congestion. Despite increased parking permit fees and newly constructed parking garages, traveling and parking on campus is unpredictable. In effort to reduce congestion on campus, a rideshare program was implemented in Summer 2010. Several universities across the nation have successfully used carpooling as a...
Show moreAs the second-largest university in the United States, UCF has experienced the largest enrollment in its history. A more densely populated campus has in turn caused increased traffic congestion. Despite increased parking permit fees and newly constructed parking garages, traveling and parking on campus is unpredictable. In effort to reduce congestion on campus, a rideshare program was implemented in Summer 2010. Several universities across the nation have successfully used carpooling as a viable alternative mode to manage traffic and parking demand. This thesis evaluates the UCF rideshare program, Zimride, using stated- and revealed-preference surveys. Preliminary results indicate most students prefer to commute to campus using their own car and without incentives there is no reason to change mode choice, regardless of associated costs(-)e.g. decal cost, parking time and frustration. Despite 70% of respondents considering themselves environmentally friendly and over 80% are aware of savings in money and productive by using alternative modes, 70% still use their car to commute to campus. Using Explanatory Factor Analysis (EFA) and Structural Equation Modeling (SEM), the observed variables were organized into three (3) latent variables based on the correlation among them. The SEM results of the revealed-preference survey indicate current travel behavior significantly influences attitudes towards carpooling and demographics have a significant effect on current travel behavior. It was also found that demographics influences attitudes towards carpooling at a non statistically significant level.
Show less - Date Issued
- 2012
- Identifier
- CFE0004226, ucf:48996
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004226
- Title
- Development of a Cognitive Work Analysis Framework Tutorial Using Systems Modeling Language.
- Creator
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Wells, Wilfred, Karwowski, Waldemar, Williams, Kent, Sala-Diakanda, Serge, Elshennawy, Ahmad, Ahram, Tareq, University of Central Florida
- Abstract / Description
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At the present time, most systems engineers do not have access to cognitivework analysis information or training in terms they can understand. This may lead to adisregard of the cognitive aspect of system design. The impact of this issue is systemrequirements that do not account for the cognitive strengths and limitations of users.Systems engineers cannot design effective decision support systems without definingcognitive work requirements. In order to improve system requirements, integration...
Show moreAt the present time, most systems engineers do not have access to cognitivework analysis information or training in terms they can understand. This may lead to adisregard of the cognitive aspect of system design. The impact of this issue is systemrequirements that do not account for the cognitive strengths and limitations of users.Systems engineers cannot design effective decision support systems without definingcognitive work requirements. In order to improve system requirements, integration ofcognitive work requirements into the systems engineering process has to be improved.One option to address this gap is the development of a Cognitive Work Analysis (CWA)framework using Systems Modeling Language (SysML). The study had two phases.The first involved aligning the CWA terminology with the SysML to produce a CWAframework using SysML. The second was the creation of an instruction using SysML toinform systems engineers of the process of integrating cognitive work requirements intothe systems engineering process. This methodology provides a structured framework todefine, manage, organize, and model cognitive work requirements. Additionally, itprovides a tool for systems engineers to use in system design which supports a user'scognitive functions, such as situational awareness, problem solving, and decisionmaking.
Show less - Date Issued
- 2011
- Identifier
- CFE0004177, ucf:49079
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004177
- Title
- BLACK WRITING INK ANALYSIS BY DIRECT INFUSION ELECTROSPRAY MASS SPECTROSCOPY.
- Creator
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Moody, Christopher, Sigman, Michael, University of Central Florida
- Abstract / Description
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An optimized method of extraction, an instrumental analysis method and data analysis was proposed for black writing inks based on direct infusion electrospray-mass spectrometry (ESI-MS). The sampling and analysis method is both minimally destructive and able to assess differences in inks from a reference collection of thirty ballpoint, gel, and rollerball inks. The methanol extracts of ink on paper samples were analyzed with three direct infusion (ESI-MS) methods. Each method varied scan...
Show moreAn optimized method of extraction, an instrumental analysis method and data analysis was proposed for black writing inks based on direct infusion electrospray-mass spectrometry (ESI-MS). The sampling and analysis method is both minimally destructive and able to assess differences in inks from a reference collection of thirty ballpoint, gel, and rollerball inks. The methanol extracts of ink on paper samples were analyzed with three direct infusion (ESI-MS) methods. Each method varied scan voltage negative and positive, ESI fragmentor applied voltage (+120V, +0V, and -120V), and mobile phase additive. Direct infusion ESI-MS analysis, followed by pair-wise comparisons of the observed ion data in binary form allowed inks to be distinguished from each other. The photobleaching of the dye Basic Violet 3 (BV3) in ink-on-paper samples was examined to determine the use of degradation products as a marker of the age of the writing sample. The extent of photobleaching of BV3 was determined using several illumination sources. Pair-wise comparison of observed ion data was able to distinguish 29 of 30 ink samples using the combined three instrumental methods. Out of 435 pair-wise comparisons 429 pairs could be discriminated from each other using the combined three methods. This is a 98.6% discrimination with the combined analysis scheme.
Show less - Date Issued
- 2010
- Identifier
- CFE0003563, ucf:48929
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0003563
- Title
- ESTIMATING DIET AND FOOD SELECTIVITY OF THE LOWER KEYS MARSH RABBIT USING STABLE ISOTOPE ANALYSIS.
- Creator
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Gordon, Matthew, Hoffman, Eric, University of Central Florida
- Abstract / Description
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Understanding the effect of food abundance on feeding behavior can benefit conservation efforts in many ways, such as to determine whether impacted environments need food supplementation, whether different locations of threatened species contain different food abundances, or whether reintroduction sites are missing key components of a species' diet. I studied the relationship between feeding behavior and food abundance in the Lower Keys marsh rabbit (Sylvilagus palustris hefneri), an...
Show moreUnderstanding the effect of food abundance on feeding behavior can benefit conservation efforts in many ways, such as to determine whether impacted environments need food supplementation, whether different locations of threatened species contain different food abundances, or whether reintroduction sites are missing key components of a species' diet. I studied the relationship between feeding behavior and food abundance in the Lower Keys marsh rabbit (Sylvilagus palustris hefneri), an endangered subspecies endemic to the lower Florida Keys. Specifically, my study set out to measure the relative abundance of the primary plants within the natural habitat of the Lower Keys marsh rabbit and estimate the proportion of each of these plants within the rabbit's diet. With this information, I tested the following hypotheses: first, the Lower Keys marsh rabbit selectively feeds on specific plants; second, that diet does not differ among sites; and third, that diet is not affected by food abundance. Using stable isotope analysis, I determined that two plants were prominent in the rabbit's diet: a shrub, Borrichia frutescens, and a grass, Spartina spartinae. These two species were prominent in the rabbit's diet in most patches, even where they were relatively rare, suggesting the rabbits are indeed selectively feeding on these species. In addition, although diet did differ among patches, selective feeding was apparent in all cases. Overall, this study determined that certain food types are important food sources for the federally endangered Lower Keys marsh rabbit and that these rabbits do not feed on plants based on plant abundance. This knowledge can be directly applied to reintroduction and restoration efforts for the Lower Keys marsh rabbit. More generally, the methods used in this study can be applied to other species of concern in order to address questions associated with diet requirements and foraging behavior.
Show less - Date Issued
- 2010
- Identifier
- CFE0003471, ucf:48952
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0003471
- Title
- Learning Hierarchical Representations for Video Analysis Using Deep Learning.
- Creator
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Yang, Yang, Shah, Mubarak, Sukthankar, Gita, Da Vitoria Lobo, Niels, Stanley, Kenneth, Sukthankar, Rahul, University of Central Florida
- Abstract / Description
-
With the exponential growth of the digital data, video content analysis (e.g., action, event recognition) has been drawing increasing attention from computer vision researchers. Effective modeling of the objects, scenes, and motions is critical for visual understanding. Recently there has been a growing interest in the bio-inspired deep learning models, which has shown impressive results in speech and object recognition. The deep learning models are formed by the composition of multiple non...
Show moreWith the exponential growth of the digital data, video content analysis (e.g., action, event recognition) has been drawing increasing attention from computer vision researchers. Effective modeling of the objects, scenes, and motions is critical for visual understanding. Recently there has been a growing interest in the bio-inspired deep learning models, which has shown impressive results in speech and object recognition. The deep learning models are formed by the composition of multiple non-linear transformations of the data, with the goal of yielding more abstract and ultimately more useful representations. The advantages of the deep models are three fold: 1) They learn the features directly from the raw signal in contrast to the hand-designed features. 2) The learning can be unsupervised, which is suitable for large data where labeling all the data is expensive and unpractical. 3) They learn a hierarchy of features one level at a time and the layerwise stacking of feature extraction, this often yields better representations.However, not many deep learning models have been proposed to solve the problems in video analysis, especially videos ``in a wild''. Most of them are either dealing with simple datasets, or limited to the low-level local spatial-temporal feature descriptors for action recognition. Moreover, as the learning algorithms are unsupervised, the learned features preserve generative properties rather than the discriminative ones which are more favorable in the classification tasks. In this context, the thesis makes two major contributions.First, we propose several formulations and extensions of deep learning methods which learn hierarchical representations for three challenging video analysis tasks, including complex event recognition, object detection in videos and measuring action similarity. The proposed methods are extensively demonstrated for each work on the state-of-the-art challenging datasets. Besides learning the low-level local features, higher level representations are further designed to be learned in the context of applications. The data-driven concept representations and sparse representation of the events are learned for complex event recognition; the representations for object body parts and structures are learned for object detection in videos; and the relational motion features and similarity metrics between video pairs are learned simultaneously for action verification.Second, in order to learn discriminative and compact features, we propose a new feature learning method using a deep neural network based on auto encoders. It differs from the existing unsupervised feature learning methods in two ways: first it optimizes both discriminative and generative properties of the features simultaneously, which gives our features a better discriminative ability. Second, our learned features are more compact, while the unsupervised feature learning methods usually learn a redundant set of over-complete features. Extensive experiments with quantitative and qualitative results on the tasks of human detection and action verification demonstrate the superiority of our proposed models.
Show less - Date Issued
- 2013
- Identifier
- CFE0004964, ucf:49593
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004964
- Title
- Real Estate Investment Trust Performance, Efficiency and Internationalization.
- Creator
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Harris, Joshua, Anderson, Randy, Schnitzlein, Charles, Turnbull, Geoffrey, Rottke, Nico, University of Central Florida
- Abstract / Description
-
Real Estate Investment Trusts (REITs) are firms that own and manage income producing commercial real estate for the benefit of their shareholders. The three studies in this dissertation explore topics relating to best practices of REIT management and portfolio composition. Managers and investors can use the findings herein to aide in analyzing a REIT's performance and determining optimal investment policies. Utilizing REIT from SNL Real Estate and CRSP, the first two studies examine the role...
Show moreReal Estate Investment Trusts (REITs) are firms that own and manage income producing commercial real estate for the benefit of their shareholders. The three studies in this dissertation explore topics relating to best practices of REIT management and portfolio composition. Managers and investors can use the findings herein to aide in analyzing a REIT's performance and determining optimal investment policies. Utilizing REIT from SNL Real Estate and CRSP, the first two studies examine the role of international diversification upon performance, technical efficiency, and scale efficiency. The third study utilizes REIT data to examine technical and scale efficiency over a 21 year window and investigates characteristics of the REITs that affect the levels of efficiency. CHAPTER 1 (-) PROFITABILITY OF REAL ESTATE INVESTMENT TRUST INTERNATIONALIZATIONReal Estate Investment Trusts (REITs) in the United States have grown extremely fast in terms of assets and market capitalization since the early 1990's. As with many industries, U.S. REITs began acquiring foreign properties as their size grew and they needed to seek new investment opportunities. This paper investigates the role of holding foreign assets upon the total return of U.S. based REITs from 1995 through 2010. We find that holding foreign properties in associated with negative relative performance when risk, size, and other common market factors are controlled for. Interestingly, the source of the negative performance is not related to the two largest areas for foreign investment, Europe and Canada. Instead, the negative performance is detected when a REIT begins acquiring properties in other global regions such as Latin America and Asia/Pacific. This paper has broad ramifications for REIT investors and managers alike.CHAPTER 2 (-) EFFECT OF INTERNATIONAL DIVERSIFICATION BY U.S. REAL ESTATE INVESTMENT TRUSTS ON COST EFFICIENCY AND SCALEAs U.S. based Real Estate Investment Trusts (REITs) have increased their degree and type of holdings overseas, there has yet to a study that has investigated such activity on the REIT's measures of cost efficiency and scale. Using data from 2010, Data Envelopment Analysis techniques are used to estimate measures of technical and scale efficiency that are then regressed against measures of international diversification and other controls to measure the impact of this global expansion. It is determined that REITs with foreign holdings are significantly larger than domestic REITs and are correspondingly 96% of foreign investing REITs are operating at decreasing returns to scale. Further almost every measure of foreign diversification is negative and significantly impacting scale efficiency. However, simply being a REIT with foreign holdings did positively and significantly associate with higher levels of technical efficiencies. Thus REITs that expand globally may have some advantages in operational efficiency but lose considerably in terms of scale efficiency by increasing their size as they move cross-border. ?CHAPTER 3 (-) THE EVOLUTION OF TECHNICAL EFFICIENCY AND ECONOMIES OF SCALE OF REAL ESTATE INVESTMENT TRUSTSData Envelopment Analysis (DEA) is used to measure technical and scale efficiency of 21 years of Real Estate Investment Trust (REIT) data. This is the longest, most complete dataset ever analyzed in the REIT efficiency literature and as such makes a significant contribution as prior efficiency studies' data windows end in the early 2000's at latest. Overall, REITs appear to continue to operate at decreasing returns to scale despite rapid growth in total assets. Further, there is some evidence of improving technical efficiency overtime; however the finding is not strong. In summation, it appears that REITs have not improved on a relative basis despite the rapid growth, a finding that suggests a potential of a high degree of firm competition in the REIT industry. Finally, firm characteristics such as debt utilization, management and advisory structure, and property type specialization are tested for their impact upon technical and scale efficiency.
Show less - Date Issued
- 2012
- Identifier
- CFE0004383, ucf:49399
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004383
- Title
- WHAT DO WE KNOW ABOUT INTERPERSONAL SKILLS? A META-ANALYTIC EXAMINATION OF ANTECEDENTS, OUTCOMES, AND THE EFFICACY OF TRAINING.
- Creator
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Klein, Cameron, Salas, Eduardo, University of Central Florida
- Abstract / Description
-
Despite extensive statements about the importance of possessing good interpersonal skills, little quantitative evidence has been brought forth to investigate these claims. At the same time, training in soft, or interpersonal, skills continues for organizational managers, customer service representatives, and members of formal work teams. Based on these considerations, the current research was guided by five broad questions. First, are gender and the Big Five personality variables important...
Show moreDespite extensive statements about the importance of possessing good interpersonal skills, little quantitative evidence has been brought forth to investigate these claims. At the same time, training in soft, or interpersonal, skills continues for organizational managers, customer service representatives, and members of formal work teams. Based on these considerations, the current research was guided by five broad questions. First, are gender and the Big Five personality variables important predictors in the use and effectiveness of interpersonal skills? Second, what is the relationship between various interpersonal skills and important personal and workplace outcomes? Third, given that training in interpersonal skills is prevalent in organizations today, does this training work? Further, and perhaps more importantly, under what conditions do these training interventions result in optimal outcomes? Lastly, does job complexity moderate the relationship between interpersonal skills and outcomes? To answer these questions, a series of meta-analytic investigations was conducted. The results of these analyses provided evidence for the existence of meaningful antecedents of interpersonal skills. In addition, relationships between interpersonal skills and outcomes were identified, with hypotheses in this area confirmed. The results of this research demonstrate the beneficial impact of interpersonal skills training for improving interpersonal skills. Finally, in line with predictions, job complexity was identified as a moderator of the relationship between interpersonal skills and outcomes. The current document concludes with recommendations both for researchers interested in furthering the science of interpersonal skills research, and for practitioners charged with improving the interpersonal skills of their workforce.
Show less - Date Issued
- 2009
- Identifier
- CFE0002642, ucf:48221
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0002642
- Title
- ULTRA-HIGH PERFORMANCE FIBER REINFORCED CONCRETE IN BRIDGE DECKAPPLICATIONS.
- Creator
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Xia, Jun, Mackie, Kevin, University of Central Florida
- Abstract / Description
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The research presented in this dissertation focuses on the material characterization of ultrahigh performance fiber reinforced concrete (UHP-FRC) at both the microscopic and macroscopic scales. The macroscopic mechanical properties of this material are highly related to the orientation of the steel fibers distributed within the matrix. However, the fiber orientation distribution has been confirmed to be anisotropic based on the flow-casting process. The orientation factor and probability...
Show moreThe research presented in this dissertation focuses on the material characterization of ultrahigh performance fiber reinforced concrete (UHP-FRC) at both the microscopic and macroscopic scales. The macroscopic mechanical properties of this material are highly related to the orientation of the steel fibers distributed within the matrix. However, the fiber orientation distribution has been confirmed to be anisotropic based on the flow-casting process. The orientation factor and probability density function (PDF) of the crossing fiber (fibers crossing a cutting plane) orientation was obtained based on theoretical derivations and numerical simulations with respect to different levels of anisotropy and cut planes oriented arbitrarily in space. The level of anisotropy can be calibrated based on image analysis on cut sections from hardened UHP-FRC prisms. Simplified equations provide a framework to predict the mechanical properties based on a single fiber-matrix interaction rule selected from existing theoretical models. Along with the investigation of the impacts from different curing methods and available post-cracking models, a versatile parameterized uniaxial stress-strain constitutive model was developed and calibrated. The constitutive model was implemented in a finite element analysis software program, and the program was utilized in the preliminary design of moveable bridge deck panels made of passively reinforced UHP-FRC. This deck system was among the several alternatives to replace the problematic steel grid decks currently in use. Based on experimental investigations of the deck panels, failure occurred largely in shear rather than flexure during bending tests. However, this shear failure is not abrupt and usually involves large deformation, large sectional rotation, and wide shear cracks before loss of load-carrying capacity. This particular shear failure mode observed was further investigated numerically and experimentally. Three-dimensional FEM models with the ability to reflect the interaction between rebar and concrete were created in a commercial FEM software to investigate the load transfer mechanism before and after bond failure. Small-scale passively reinforced prisms were tested to verify the conclusions drawn from simulation results. In an effort to improve the original design, several shear-strengthened deck panels were tested and evaluated for effectiveness. Finally, methods and equations to predict the ultimate shear capacity were calibrated. A two-dimensional frame element based complete moveable bridge finite element model was built for observation of bridge system performance. The model contained the option to substitute any available deck system based on a subset of pre-calibrated parameters specific to each deck type. These alternative deck systems include an aluminum bridge deck system and a glass fiber reinforced plastic (GFRP) deck system. All three alternatives and the original steel grid deck system were evaluated based on the global responses of the moveable bridge, and the advantages and disadvantages of adopting the UHP-FRC deck system are quantified.
Show less - Date Issued
- 2011
- Identifier
- CFE0003721, ucf:48803
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0003721
