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Title: Strategic Improvement: A Systems Approach using the Balanced Scorecard Methodology to Increase Federally Financed Research at the University of Central Florida.
Creator: Walters, Joseph, Rabelo, Luis, Ajayi, Richard, Calabrese, Mark, University of Central Florida
Abstract / Description: The University of Central Florida has many successful measures to reflect on as it celebrates its 50th year in 2013. It is the university with the 2nd largest student population in the U. S. and its overall ranking in the U.S. News (&) World Report has improved 4 years in a row. However, with respect to research, the federally funded research and development for the University of Central Florida (UCF) has remained flat. In addition, when compared to other schools, its portion of those federal...
Show moreThe University of Central Florida has many successful measures to reflect on as it celebrates its 50th year in 2013. It is the university with the 2nd largest student population in the U. S. and its overall ranking in the U.S. News (&) World Report has improved 4 years in a row. However, with respect to research, the federally funded research and development for the University of Central Florida (UCF) has remained flat. In addition, when compared to other schools, its portion of those federal research dollars is small. This thesis lays the groundwork for developing a model for improving the federally financed academic research and development. A systems approach using the balanced scorecard methodology was used to develop causal loop relationships between the many factors that influence the federal funding process. Measures are proposed that link back to the objectives and mission of the university. One particular measure found in the literature was refined to improve its integration into this model. The resulting work provides a framework with specific measures that can be incorporated at the university to improve their share of the federally financed research and development. Although developed for UCF this work could be applied to any university that desires to improve their standing in the federal financed academic research and development market.
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Date Issued: 2013
Identifier: CFE0005069, ucf:49955
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005069

Title: A Framework for the Development of a Model for Successful, Sustained Lean Implementation and Improvement.
Creator: Sisson, Julie, Elshennawy, Ahmad, Rabelo, Luis, Xanthopoulos, Petros, Porter, Robert, University of Central Florida
Abstract / Description: Lean is a business philosophy focused on shortening lead times by removing waste and concentrating on value-added processes. When implemented successfully, it not only allows for cost reduction while improving quality, but it can also position a company to achieve tremendous growth. The problem is that though many companies are attempting to implement lean, it is estimated that only 2-3% are achieving the desired level of success. The purpose of this research is to identify the key...
Show moreLean is a business philosophy focused on shortening lead times by removing waste and concentrating on value-added processes. When implemented successfully, it not only allows for cost reduction while improving quality, but it can also position a company to achieve tremendous growth. The problem is that though many companies are attempting to implement lean, it is estimated that only 2-3% are achieving the desired level of success. The purpose of this research is to identify the key interrelated components of successful lean transformation. To this end, a thorough literature review was conducted and the findings indicate six key constructs that can act as enablers or inhibitors to implementing and sustaining lean. A theoretical framework was developed that integrates these constructs and develops research propositions for each. A multiple-case study analysis then was used to test the framework on four companies that have achieved successful, sustained results from their lean implementation in order to validate the model. The resulting model provides companies who are planning to implement lean with tangible actions that can be taken to make their lean transformations more successful.
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Date Issued: 2014
Identifier: CFE0005262, ucf:50608
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005262

Title: A Framework for Safety Training Using Virtual Reality Software.
Creator: Riad, Rana, Rabelo, Luis, Lee, Gene, Ferreras, Ana, University of Central Florida
Abstract / Description: Safety training is a vital component to the well-being of individuals in all industries. With technology advancing at the current pace, conventional training methods are no longer the most effective way to communicate information. There is a strong need for safety training that incorporates new methods and forms of communication to obtain higher levels of comprehension. Virtual reality systems offer a highly customizable and interactive form of delivering information to users. This research...
Show moreSafety training is a vital component to the well-being of individuals in all industries. With technology advancing at the current pace, conventional training methods are no longer the most effective way to communicate information. There is a strong need for safety training that incorporates new methods and forms of communication to obtain higher levels of comprehension. Virtual reality systems offer a highly customizable and interactive form of delivering information to users. This research addresses major gaps in the field of safety training using virtual reality systems and provides a design framework for creating a virtual safety-training system. A model for the virtual environment is designed and developed and the process and justification is described. The environment and an applied use case for this model is developed and verified using a sample of trainees that would use the model. This exploratory framework provides a significant contribution to the field of safety education through virtual reality systems and can be expanded with further research.
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Date Issued: 2015
Identifier: CFE0005698, ucf:50152
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005698

Title: Comparative Analysis of The Effects Of Virtual Reality Active Video Game And Controller-Free Active Video Game Play On Physiological Response, Perceived Exertion, And Hedonic Experience.
Creator: Wooden, Shanon, McCauley, Pamela, Rabelo, Luis, Karwowski, Waldemar, Fukuda, David, University of Central Florida
Abstract / Description: Over 60% of US adults are overweight or obese. Sedentary lifestyles are considered major contributors to the high rates and increasing prevalence of obesity. Physical activity is a critical component in shifting from sedentary lifestyles. Studies indicate that less than half of U.S. adults meet the CDC/ACSM physical activity recommendations. Interactive video games can increase PA, but no study has yet assessed physiologic effort, hedonics, and perceived exertion for playing immersive virtual...
Show moreOver 60% of US adults are overweight or obese. Sedentary lifestyles are considered major contributors to the high rates and increasing prevalence of obesity. Physical activity is a critical component in shifting from sedentary lifestyles. Studies indicate that less than half of U.S. adults meet the CDC/ACSM physical activity recommendations. Interactive video games can increase PA, but no study has yet assessed physiologic effort, hedonics, and perceived exertion for playing immersive virtual reality (VR) and controller-free screen-based active video games (AVGs), compared to treadmill walking and resting. We ran 25 subjects (9 female, 16 male) in 10-minute sessions of five conditions. Head Mounted Display VR: Oculus (Fruit Ninja and Boxing), Screen-based AVG: Kinect (Fruit Ninja and Boxing), and Treadmill walking at 3 mph. One, six-condition (Rest, Treadmill 3.0, Kinect Boxing, Kinect Fruit Ninja, Oculus Boxing, Oculus Fruit Ninja) repeated-measures ANOVA was used to examine differences in HRmean. Three, five-condition (Treadmill 3.0, Kinect Boxing, Kinect Fruit Ninja, Oculus Boxing, Oculus Fruit Ninja) repeated-measures ANOVA were used to examine differences in HRpeak, ratings of perceived exertion (RPE) and Hedonics (Liking). Post hoc analyses using pairwise comparisons were used to further assess significant main effects of the condition. A Pearson's product-moment correlation was run to assess the relationship between activity condition HRmean and RPE VR Boxing elicited the greatest physiological effort, producing vigorous-intensity PA. There was no significant difference in average heart rate for the Treadmill, Kinect Fruit Ninja, Kinect Boxing, and VR Fruit Ninja. Thus, the Kinect and VR sport and casual games are comparable to treadmill walking PA levels and qualify as moderate-intensity activity. The VR Fruit Ninja, VR Boxing, Kinect Fruit Ninja were the most enjoyed activities. Despite having the highest Heart rate and the highest self-reported Rating of Perceived Exertion (RPE), VR Boxing was significantly more enjoyable than Treadmill Walking. There was no statistically significant correlation between Activity Condition HRmean and RPE.Both casual and sports VR and AVG activities are enjoyable activities for adults, stimulating moderate-to-vigorous activity through a traditionally sedentary medium. This research extends previous works in active video gaming effects on physiological cost, perceived exertion and hedonics and fills the gap relating virtual reality active video games. The significance of the research outcomes is that this analysis provides a scientifically validated approach to support the establishment of physical activity level goals and guidelines in the development of active video games as a response and/or remedy to address the sedentary lifestyles that are contributing to American and global obesity.
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Date Issued: 2018
Identifier: CFE0007383, ucf:52065
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0007383

Title: A Methodology on Weapon Combat Effectiveness Analytics using Big Data and Live, Virtual, or/and Constructive Simulations.
Creator: Jung, Won Il, Lee, Gene, Rabelo, Luis, Elshennawy, Ahmad, Ahmad, Ali, University of Central Florida
Abstract / Description: The Weapon Combat Effectiveness (WCE) analytics is very expensive, time-consuming, and dangerous in the real world because we have to create data from the real operations with a lot of people and weapons in the actual environment. The Modeling and Simulation (M(&)S) of many techniques is used for overcoming these limitations. Although the era of big data has emerged and achieved a great deal of success in a variety of fields, most WCE research using the Defense Modeling and Simulation (DM(&)S...
Show moreThe Weapon Combat Effectiveness (WCE) analytics is very expensive, time-consuming, and dangerous in the real world because we have to create data from the real operations with a lot of people and weapons in the actual environment. The Modeling and Simulation (M(&)S) of many techniques is used for overcoming these limitations. Although the era of big data has emerged and achieved a great deal of success in a variety of fields, most WCE research using the Defense Modeling and Simulation (DM(&)S) techniques were studied without the help of big data technologies and techniques. The existing research has not considered various factors affecting WCE. This is because current research has been restricted by only using constructive simulation, a single weapon system, and limited scenarios. Therefore, the WCE analytics using existing methodologies have also incorporated the same limitations, and therefore, cannot help but get biased results.To solve the above problem, this dissertation is to initially review and compose the basic knowledge for the new WCE analytics methodology using big data and DM(&)S to further serve as the stepping-stone of the future research for the interested researchers. Also, this dissertation presents the new methodology on WCE analytics using big data generated by Live, Virtual, or/and Constructive (LVC) simulations. This methodology can increase the fidelity of WCE analytics results by considering various factors. It can give opportunities for application of weapon acquisition, operations analytics and plan, and objective level development on each training factor for the weapon operators according to the selection of Measures of Effectiveness (MOEs) and Measures of Performance (MOPs), or impact factors, based on the analytics goal.
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Date Issued: 2018
Identifier: CFE0007025, ucf:52870
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0007025

Title: An Agile Roadmap for Live, Virtual and Constructive-Integrating Training Architecture (LVC-ITA): A Case Study Using a Component based Integrated Simulation Engine.
Creator: Park, Tae Woong, Lee, Gene, Rabelo, Luis, Elshennawy, Ahmad, Kincaid, John, University of Central Florida
Abstract / Description: Conducting seamless Live Virtual Constructive (LVC) simulation remains the most challenging issue of Modeling and Simulation (M(&)S). There is a lack of interoperability, limited reuse and loose integration between the Live, Virtual and/or Constructive assets across multiple Standard Simulation Architectures (SSAs). There have been various theoretical research endeavors about solving these problems but their solutions resulted in complex and inflexible integration, long user-usage time and...
Show moreConducting seamless Live Virtual Constructive (LVC) simulation remains the most challenging issue of Modeling and Simulation (M(&)S). There is a lack of interoperability, limited reuse and loose integration between the Live, Virtual and/or Constructive assets across multiple Standard Simulation Architectures (SSAs). There have been various theoretical research endeavors about solving these problems but their solutions resulted in complex and inflexible integration, long user-usage time and high cost for LVC simulation. The goal of this research is to provide an Agile Roadmap for the Live Virtual Constructive-Integrating Training Architecture (LVC-ITA) that will address the above problems and introduce interoperable LVC simulation. Therefore, this research describes how the newest M(&)S technologies can be utilized for LVC simulation interoperability and integration. Then, we will examine the optimal procedure to develop an agile roadmap for the LVC-ITA.In addition, this research illustrated a case study using an Adaptive distributed parallel Simulation environment for Interoperable and reusable Model (AddSIM) that is a component based integrated simulation engine. The agile roadmap of the LVC-ITA that reflects the lessons learned from the case study will contribute to guide M(&)S communities to an efficient path to increase interaction of M(&)S simulation across systems.
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Date Issued: 2015
Identifier: CFE0005682, ucf:52867
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005682

Title: An Integrated Design for Six Sigma-Based Framework To Align Strategy, New Process Development, and Customer Requirements In The Airlines Industry.
Creator: Alghamdi, Mohammed, Elshennawy, Ahmad, Rabelo, Luis, Lee, Gene, Ahmad, Ali, University of Central Florida
Abstract / Description: When organizations create new strategy maps, key new processes are often identified. This is important for organizations to stay competitive in the global marketplace. This document describes the development, implementation, and validation of a framework that properly aligns and links an organization's strategy and new process development. The proposed framework integrates the Balanced Scorecard management system (BSC) and the Design for Six Sigma (DFSS) methodology, leveraging their...
Show moreWhen organizations create new strategy maps, key new processes are often identified. This is important for organizations to stay competitive in the global marketplace. This document describes the development, implementation, and validation of a framework that properly aligns and links an organization's strategy and new process development. The proposed framework integrates the Balanced Scorecard management system (BSC) and the Design for Six Sigma (DFSS) methodology, leveraging their strengths, overcoming weaknesses, and identifying lessons learned to help bridge the gap between strategy development and execution. The critical-to-quality conceptual model is used as an integrative component for the framework. Literature search has resulted in little or no research into the development of similar frameworks. To demonstrate and evaluate the effectiveness of the framework in a real-world environment, a case study is carried out and implemented successfully. As the case study progressed, cycle time as a performance indicator was estimated and showed progression towards the targeted strategic objective. The developed framework helps decision-makers seamlessly transit from a strategic position to process development linking strategic objectives to the critical-to-quality features. This comprehensive framework can help move organizations from where they currently are to where they want to be, laying the background needed for customer satisfaction and breakthrough performance.
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Date Issued: 2016
Identifier: CFE0006246, ucf:51079
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006246

Title: Parallel Distributed Discrete Event Simulation Optimization Using Complexity and Deep Learning.
Creator: Cortes, Edwin, Rabelo, Luis, Lee, Gene, Kincaid, John, Elshennawy, Ahmad, University of Central Florida
Abstract / Description: Parallel distributed discrete event simulation (PDDES) is the execution of a discrete event simulation on a tightly or loosely coupled computer system with multiple processors. The discrete-event simulation model is decomposed into several logical processors (LPs) or simulation objects that can be executed concurrently using partitioning types such as spatial and temporal. PDDES is exceedingly important for the reduction of the simulation time, increase of model size, intellectual property...
Show moreParallel distributed discrete event simulation (PDDES) is the execution of a discrete event simulation on a tightly or loosely coupled computer system with multiple processors. The discrete-event simulation model is decomposed into several logical processors (LPs) or simulation objects that can be executed concurrently using partitioning types such as spatial and temporal. PDDES is exceedingly important for the reduction of the simulation time, increase of model size, intellectual property issue mitigation in multi-enterprise simulations, and the sharing of resources.One of the problems with PDDES is the time management to provide flow control over event processing, the process flow, and the coordination of different logical processors to take advantage of parallelism. Time Warp (TW), Breathing Time Buckets (BTB), and Breathing Time Warp (BTW) are three time management schemes studied by this research. For a particular PDDES problem, unfortunately, there is no clear methodology to decide a priori a time management scheme to achieve higher system and simulation performance.This dissertation shows a new approach for selecting the optimal time synchronization technique class that corresponds to a particular parallel distributed anddiscrete simulation with different levels of simulation logic complexity. Simulation complexities such as branching, parallelism, function calls, concurrency, iterations, mathematical computations, messaging frequency, event processing, and number of simulation objects interactions were given a weighted parameter value based on the cognitive weight approach. Deep belief neural networks were then used to perform deep learning from the simulation complexity parameters and their corresponding optimal time synchronization scheme value as measured by speedup performance.
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Date Issued: 2015
Identifier: CFE0006211, ucf:51114
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006211

Title: The effect of Baldrige performance excellence program on organization's innovation/dynamic capabilities.
Creator: Alomairy, Mohammed, Elshennawy, Ahmad, Rabelo, Luis, Xanthopoulos, Petros, Porter, Robert, University of Central Florida
Abstract / Description: This dissertation investigated the effect of Baldrige performance excellence program on organization's innovation/dynamic capabilities improvement. According to the literature, there is little or no practical method for building dynamic/innovation capabilities within organizations. The study hypothesizes that Baldrige performance excellence program helps organizations to systematically develop the required dynamic/innovation capabilities for innovation.Twenty-four organizations that had...
Show moreThis dissertation investigated the effect of Baldrige performance excellence program on organization's innovation/dynamic capabilities improvement. According to the literature, there is little or no practical method for building dynamic/innovation capabilities within organizations. The study hypothesizes that Baldrige performance excellence program helps organizations to systematically develop the required dynamic/innovation capabilities for innovation.Twenty-four organizations that had implemented Baldrige program over the past five years participated in this research study. Two types of data were measured/collected from these organizations; Performance excellence data and Innovation capabilities data. To avoid bias in the data collection, the two data were measured and collected at different time frames and using different tools and methods. The analysis confirmed positive correlation between Organizations' performance excellence improvement through Baldrige program and Innovation capabilities represented in the Six Building Blocks Innovation model used in this research study.The performance excellence data of the organizations were measured using three different assessment programs from Florida Sterling Council, the state approved version of the US National Malcolm Baldrige Quality Award Program. The three different assessment programs were designed to help organizations in various stages of their performance excellence journey. Challenge program; designed for new organizations that have no experience with Baldrige criteria and typically have low performance, requires a written application and a team of five experienced examiners to visit the organization and conduct thorough interviews with the all the employees. Governor Sterling Award (GSA) program; designed for more experienced organizations that want to further improve their performance using intensive assessment criteria, requires a written application and a team of eight experienced examiners to visit the organization and conduct intensive interviews with most of the the employees. And Governor Sustained program; designed for mature organizations that completed the GSA assessment in the past three years and want to continue sustain their performance, requires a written application and a team of three experienced examiners to visit the organization and conduct a thorough meetings and interviews with management level employees.ANOVA statistical tool was used to analyze the difference in performance among the organizations that participated in at least one of the three assessment programs. The result showed a statistical difference with challenge program being the control group. This confirms that organizations' can systematically improve their performance when implementing Baldrige performance excellence program.The innovation capabilities data of the participated organizations were measured/collected using a survey-based tool. The innovation capabilities survey covers six building blocks; Innovation Value, Innovation Behavior, Innovation Climate, Innovation Resources, Innovation Process, Innovation Success measures. The Overall innovation capabilities measured based on the average score of all the six innovation building blocks.ANOVA statistical tool was used to analyze the innovation capabilities of organizations from the three assessment programs. The result confirmed a statistical difference with challenge program being the control group. Regression analysis was also used to analyze the relationship between performance excellence and each of the six innovation building blocks. The outcome of the study shows a positive correlation between the implementation of Baldrige performance excellence and organizations' innovation capabilities. Which confirms that Baldrige performance excellence program can be used by organizations to systematically build the required dynamic/innovation capabilities for innovations.
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Date Issued: 2016
Identifier: CFE0006068, ucf:50964
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006068

Title: Body Mass Bias Mitigation for Females in Military Physical Readiness Testing through Load Carriage Implementation.
Creator: Yeaton, Aaron, McCauley, Pamela, Rabelo, Luis, Lee, Gene, Cummings, Nancy, University of Central Florida
Abstract / Description: The US Military requires specific fitness testing, known as the Physical Readiness Test (PRT), for its members to determine their overall fitness levels. The test currently being used has been shown to have bias towards heavier mass individuals of up to 20%. Prior research has been completed and several recommendations have been made to eliminate mass bias, but this has been conducted almost exclusively on males. There is very little data and research on military physical fitness testing for...
Show moreThe US Military requires specific fitness testing, known as the Physical Readiness Test (PRT), for its members to determine their overall fitness levels. The test currently being used has been shown to have bias towards heavier mass individuals of up to 20%. Prior research has been completed and several recommendations have been made to eliminate mass bias, but this has been conducted almost exclusively on males. There is very little data and research on military physical fitness testing for women besides combat specific evolution exercises. A possibility exists to eliminate the bias for females through implementing load carriage during PRT events. A specified load is to be placed on women while performing the PRT and compared to a non-loaded control test. The results should show if the load carriage devised has a beneficial effect on current testing methods through eliminating the mass bias for women.
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Date Issued: 2015
Identifier: CFE0006020, ucf:51009
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006020

Title: Weighting Policies for Robust Unsupervised Ensemble Learning.
Creator: Unlu, Ramazan, Xanthopoulos, Petros, Zheng, Qipeng, Rabelo, Luis, Yun, Hae-Bum, University of Central Florida
Abstract / Description: The unsupervised ensemble learning, or consensus clustering, consists of finding the optimal com- bination strategy of individual partitions that is robust in comparison to the selection of an algorithmic clustering pool. Despite its strong properties, this approach assigns the same weight to the contribution of each clustering to the final solution. We propose a weighting policy for this problem that is based on internal clustering quality measures and compare against other modern approaches...
Show moreThe unsupervised ensemble learning, or consensus clustering, consists of finding the optimal com- bination strategy of individual partitions that is robust in comparison to the selection of an algorithmic clustering pool. Despite its strong properties, this approach assigns the same weight to the contribution of each clustering to the final solution. We propose a weighting policy for this problem that is based on internal clustering quality measures and compare against other modern approaches. Results on publicly available datasets show that weights can significantly improve the accuracy performance while retaining the robust properties. Since the issue of determining an appropriate number of clusters, which is a primary input for many clustering methods is one of the significant challenges, we have used the same methodology to predict correct or the most suitable number of clusters as well. Among various methods, using internal validity indexes in conjunction with a suitable algorithm is one of the most popular way to determine the appropriate number of cluster. Thus, we use weighted consensus clustering along with four different indexes which are Silhouette (SH), Calinski-Harabasz (CH), Davies-Bouldin (DB), and Consensus (CI) indexes. Our experiment indicates that weighted consensus clustering together with chosen indexes is a useful method to determine right or the most appropriate number of clusters in comparison to individual clustering methods (e.g., k-means) and consensus clustering. Lastly, to decrease the variance of proposed weighted consensus clustering, we borrow the idea of Markowitz portfolio theory and implement its core idea to clustering domain. We aim to optimize the combination of individual clustering methods to minimize the variance of clustering accuracy. This is a new weighting policy to produce partition with a lower variance which might be crucial for a decision maker. Our study shows that using the idea of Markowitz portfolio theory will create a partition with a less variation in comparison to traditional consensus clustering and proposed weighted consensus clustering.
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Date Issued: 2017
Identifier: CFE0006813, ucf:51786
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006813

Title: Assessing the Effect of Social Networks on Employee Creativity in a Fast-Food Restaurant Environment.
Creator: Rabinowitz, Mitchell, Karwowski, Waldemar, Elshennawy, Ahmad, Rabelo, Luis, Williams, Kent, Beitsch, Owen, University of Central Florida
Abstract / Description: Creativity has been widely recognized as critical to the economic success of organizations for over 60 years. Today, it is considered to be the most highly prized (")commodity(") of businesses. As such, there have been numerous efforts to better understand creativity with the goal of increasing individual creativity and therefore improving the economic success of organizations. An emerging area of research on creativity recognizes creativity as a complex, social process that is dependent upon...
Show moreCreativity has been widely recognized as critical to the economic success of organizations for over 60 years. Today, it is considered to be the most highly prized (")commodity(") of businesses. As such, there have been numerous efforts to better understand creativity with the goal of increasing individual creativity and therefore improving the economic success of organizations. An emerging area of research on creativity recognizes creativity as a complex, social process that is dependent upon many factors, including those of an environmental nature. In support of this perspective, a growing amount of research has investigated the effect of social networks on individual creativity. This relationship is based on the premise that an individual's social network affects access to diverse information, which in turn, is critical for creativity. The previous studies on this relationship, however, have been conducted in a limited number of environments, most of which have been knowledge-intensive in nature. As such, this study was conducted in a fast-food restaurant environment to determine whether the relationship between social networks and creativity is the same as in other, previously studied environments.Data was collected for a sample of 247 employees of an organization consisting of seven fast-food franchise restaurants of a popular fast-food restaurant chain in the northeast region of the United States. An ordinary least squares regression model was developed to investigate the relationship between creativity and the commonly studied social network variables: number of weak ties, number of strong ties, clustering, and centrality. The social network variables accounted for 17.3% of the overall variance in creativity, establishing that a relationship does exist between social networks and creativity in the fast-food restaurant environment. This relationship, however, was not as expected. In contrast to expectations, weak ties were not found to be a significant, positive predictor of creativity. Also, strong ties were found to be a significant, positive predictor of creativity, where it was expected that this relationship would be in the negative direction. Centrality, however, was found to be a significant, positive predictor of creativity, as expected, while the results for clustering were inconclusive due to its high correlation with the other social network variables in the study.As such, it appears that the relationship between social networks and creativity may be different in the fast-food restaurant environment when compared to environments previously studied. It is possible that this difference is a result of the differences between high and low knowledge-intensive working environments. The lack of support for weak ties as a significant positive predictor of creativity in conjunction with limited opportunities for significant creative achievement suggests that access to diverse information may be less important for creativity in the fast-food restaurant environment than in other environments. The findings that strong ties and centrality are significant, positive predictors of creativity, however, appear to indicate that the ability to implement a creative idea, however minor it may be, is more important in the fast-food restaurant environment than the generation of that idea in the first place. Due to the limitations of this study, however, it is not possible to definitively conclude this notion without efforts to determine which factor afforded by positions rich in strong ties or high in centrality, the informational benefits or the organizational influence, is more important for creativity.
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Date Issued: 2016
Identifier: CFE0006846, ucf:51799
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006846

Title: A Systems Approach to Assessing, Interpreting and Applying Human Error Mishap Data to Mitigate Risk of Future Incidents in a Space Exploration Ground Processing Operations Environment.
Creator: Alexander, Tiffaney, McCauley, Pamela, Rabelo, Luis, Karwowski, Waldemar, Nunez, Jose, University of Central Florida
Abstract / Description: Research results have shown that more than half of aviation, aerospace and aeronautics mishaps/incidents are attributed to human error. Although many existing incident report systems have been beneficial for identifying engineering failures, most of them are not designed around a theoretical framework of human error, thus failing to address core issues and causes of the mishaps. Therefore, it is imperative to develop a human error assessment framework to identify these causes. This research...
Show moreResearch results have shown that more than half of aviation, aerospace and aeronautics mishaps/incidents are attributed to human error. Although many existing incident report systems have been beneficial for identifying engineering failures, most of them are not designed around a theoretical framework of human error, thus failing to address core issues and causes of the mishaps. Therefore, it is imperative to develop a human error assessment framework to identify these causes. This research focused on identifying causes of human error and leading contributors to historical Launch Vehicle Ground Processing Operations mishaps based on past mishaps, near mishaps, and close calls. Three hypotheses were discussed. The first hypothesis addressed the impact Human Factor Analysis and Classification System (HFACS) contributing factors (unsafe acts of operators, preconditions for unsafe acts, unsafe supervision, and/or organizational influences) have on human error events (i.e. mishaps, close calls, incident or accidents) in NASA Ground Processing Operations. The second hypothesis focused on determining if the HFACS framework conceptual model could be proven to be a viable analysis and classification system to help classify both latent and active underlying contributors and causes of human error in ground processing operations. Lastly, the third hypothesis focused on determining if the development of a model using the Human Error Assessment and Reduction Technique (HEART) could be used as a tool to help determine the probability of human error occurrence in ground processing operations. A model to analyze and classify contributing factors to mishaps or incidents, and generate predicted Human Error Probabilities (HEPs) of future occurrence was developed using the HEART and HFACS tools. The research methodology was applied (retrospectively) to six Ground Processing Operations (GPO) Scenarios and 30 years of Launch Vehicle Related Mishap Data. Surveys were used to provide Subject Matter Experts' (SMEs) subjective assessments of the impact Error Producing Conditions (EPC) had on specific tasks. In this research a Logistic Binary Regression model, which identified the four most significant contributing HFACS human error factors was generated. This model provided predicted probabilities of future occurrence of mishaps when these contributing factors are present. The results showed that the HEART and HFACS methods, when modified, can be used as an analysis tool to identify contributing factors, their impact on human error events, and predict the potential probability of future human error occurrence. This methodology and framework was validated through consistency and comparison to other related research. A contribution methodology for other space operations and similar complex operations to follow was provided from this research. Future research should involve broadening the scope to explore and identify other existing models of human error management systems to integrate into complex space systems beyond what was conducted in this research.
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Date Issued: 2016
Identifier: CFE0006829, ucf:51795
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006829

Title: Improved Multi-Task Learning Based on Local Rademacher Analysis.
Creator: Yousefi, Niloofar, Mollaghasemi, Mansooreh, Rabelo, Luis, Zheng, Qipeng, Anagnostopoulos, Georgios, Xanthopoulos, Petros, Georgiopoulos, Michael, University of Central Florida
Abstract / Description: Considering a single prediction task at a time is the most commonly paradigm in machine learning practice. This methodology, however, ignores the potentially relevant information that might be available in other related tasks in the same domain. This becomes even more critical where facing the lack of a sufficient amount of data in a prediction task of an individual subject may lead to deteriorated generalization performance. In such cases, learning multiple related tasks together might offer...
Show moreConsidering a single prediction task at a time is the most commonly paradigm in machine learning practice. This methodology, however, ignores the potentially relevant information that might be available in other related tasks in the same domain. This becomes even more critical where facing the lack of a sufficient amount of data in a prediction task of an individual subject may lead to deteriorated generalization performance. In such cases, learning multiple related tasks together might offer a better performance by allowing tasks to leverage information from each other. Multi-Task Learning (MTL) is a machine learning framework, which learns multiple related tasks simultaneously to overcome data scarcity limitations of Single Task Learning (STL), and therefore, it results in an improved performance. Although MTL has been actively investigated by the machine learning community, there are only a few studies examining the theoretical justification of this learning framework. The focus of previous studies is on providing learning guarantees in the form of generalization error bounds. The study of generalization bounds is considered as an important problem in machine learning, and, more specifically, in statistical learning theory. This importance is twofold: (1) generalization bounds provide an upper-tail confidence interval for the true risk of a learning algorithm the latter of which cannot be precisely calculated due to its dependency to some unknown distribution P from which the data are drawn, (2) this type of bounds can also be employed as model selection tools, which lead to identifying more accurate learning models. The generalization error bounds are typically expressed in terms of the empirical risk of the learning hypothesis along with a complexity measure of that hypothesis. Although different complexity measures can be used in deriving error bounds, Rademacher complexity has received considerable attention in recent years, due to its superiority to other complexity measures. In fact, Rademacher complexity can potentially lead to tighter error bounds compared to the ones obtained by other complexity measures. However, one shortcoming of the general notion of Rademacher complexity is that it provides a global complexity estimate of the learning hypothesis space, which does not take into consideration the fact that learning algorithms, by design, select functions belonging to a more favorable subset of this space and, therefore, they yield better performing models than the worst case. To overcome the limitation of global Rademacher complexity, a more nuanced notion of Rademacher complexity, the so-called local Rademacher complexity, has been considered, which leads to sharper learning bounds, and as such, compared to its global counterpart, guarantees faster convergence rates in terms of number of samples. Also, considering the fact that locally-derived bounds are expected to be tighter than globally-derived ones, they can motivate better (more accurate) model selection algorithms.While the previous MTL studies provide generalization bounds based on some other complexity measures, in this dissertation, we prove excess risk bounds for some popular kernel-based MTL hypothesis spaces based on the Local Rademacher Complexity (LRC) of those hypotheses. We show that these local bounds have faster convergence rates compared to the previous Global Rademacher Complexity (GRC)-based bounds. We then use our LRC-based MTL bounds to design a new kernel-based MTL model, which enjoys strong learning guarantees. Moreover, we develop an optimization algorithm to solve our new MTL formulation. Finally, we run simulations on experimental data that compare our MTL model to some classical Multi-Task Multiple Kernel Learning (MT-MKL) models designed based on the GRCs. Since the local Rademacher complexities are expected to be tighter than the global ones, our new model is also expected to exhibit better performance compared to the GRC-based models.
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Date Issued: 2017
Identifier: CFE0006827, ucf:51778
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006827

Title: Using Case-Based Reasoning for Simulation Modeling in Healthcare.
Creator: Alshareef, Khaled, Rabelo, Luis, Elshennawy, Ahmad, Lee, Gene, Rahal, Ahmad, University of Central Florida
Abstract / Description: The healthcare system is always defined as a complex system. At its core, it is a system composed of people and processes and requires performance of different tasks and duties. This complexity means that the healthcare system has many stakeholders with different interests, resulting in the emergence of many problems such as increasing healthcare costs, limited resources and low utilization, limited facilities and workforce, and poor quality of services.The use of simulation techniques to aid...
Show moreThe healthcare system is always defined as a complex system. At its core, it is a system composed of people and processes and requires performance of different tasks and duties. This complexity means that the healthcare system has many stakeholders with different interests, resulting in the emergence of many problems such as increasing healthcare costs, limited resources and low utilization, limited facilities and workforce, and poor quality of services.The use of simulation techniques to aid in solving healthcare problems is not new, but it has increased in recent years. This application faces many challenges, including a lack of real data, complicated healthcare decision making processes, low stakeholder involvement, and the working environment in the healthcare field.The objective of this research is to study the utilization of case-based reasoning in simulation modeling in the healthcare sector. This utilization would increase the involvement of stakeholders in the analysis process of the simulation modeling. This involvement would help in reducing the time needed to build the simulation model and facilitate the implementation of results and recommendations. The use of case-based reasoning will minimize the required efforts by automating the process of finding solutions. This automation uses the knowledge in the previously solved problems to develop new solutions. Thus, people could utilize the simulation modeling with little knowledge about simulation and the working environment in the healthcare field.In this study, a number of simulation cases from the healthcare field have been collected to develop the case-base. After that, an indexing system was created to store these cases in the case-base. This system defined a set of attributes for each simulation case. After that, two retrieval approaches were used as retrieval engines. These approaches are K nearest neighbors and induction tree. The validation procedure started by selecting a case study from the healthcare literature and implementing the proposed method in this study. Finally, healthcare experts were consulted to validate the results of this study.
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Date Issued: 2016
Identifier: CFE0006831, ucf:51769
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006831

Title: A Framework for Quantifying and Managing Overcrowding in Healthcare Facilities.
Creator: Albar, Abdulrahman, Elshennawy, Ahmad, Rabelo, Luis, Lee, Gene, Rahal, Ahmad, University of Central Florida
Abstract / Description: Emergency Departments (EDs) represent a crucial component of any healthcare infrastructure. In today's world, healthcare systems face growing challenges in delivering efficient and time-sensitive emergency care services to communities. Overcrowding within EDs represents one of the most significant challenges for healthcare quality that adversely impacts clinical outcomes, patient safety, and overall satisfaction. Research in this area has resulted in creating several ED crowding indices, such...
Show moreEmergency Departments (EDs) represent a crucial component of any healthcare infrastructure. In today's world, healthcare systems face growing challenges in delivering efficient and time-sensitive emergency care services to communities. Overcrowding within EDs represents one of the most significant challenges for healthcare quality that adversely impacts clinical outcomes, patient safety, and overall satisfaction. Research in this area has resulted in creating several ED crowding indices, such as National Emergency Department Overcrowding Scale (NEDOCS) and Emergency Department Work Index (EDWIN) that have been developed to provide measures aimed at mitigating overcrowding. Recently, efforts made by researchers to examine the validity and reproducibility of these indices have shown that they are not reliable in accurately assessing overcrowding in regions beyond their original design settings. The shortcomings of such indices stem from their reliance upon the perspective and feedback of only clinical staff and the exclusion of other stakeholders. These limited perspectives introduce bias in the results of ED overcrowding indices. This study starts with confirming the inaccuracy of such crowding indices through examining their validity within a new healthcare system. To overcome the shortcomings of previous indices, the study presents a novel framework for quantifying and managing overcrowding based on emulating human reasoning in overcrowding perception. The framework of the proposed study takes into consideration emergency operational and clinical factors such as patient demand, patient complexity, staffing level, clinician workload, and boarding status when defining the crowding level. The hierarchical fuzzy logic approach is utilized to accomplish the goals of this framework by combining a diverse pool of healthcare expert perspectives while addressing the complexity of the overcrowding issue. The innovative design of the developed framework reduces bias in the assessment of ED crowding by developing a knowledge-base from the perspectives of multiple experts, and allows for its implementation in a variety of healthcare settings. Statistical analysis of results indicate that the developed index outperform previous indices in reflecting expert subjective assessments of overcrowding.
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Date Issued: 2016
Identifier: CFE0006521, ucf:51378
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006521

Title: Fire safety and emergency evacuation training for occupants of building using 3D virtual simulation.
Creator: Bhide, Sayli, Rabelo, Luis, Lee, Gene, McCauley, Pamela, Ahmad, Ali, University of Central Florida
Abstract / Description: With advancement in technology, building structures are becoming bigger and more complex. Incidences of horrifying fires that occur in such complex structures resulting in loss of property as well as lives are recorded worldwide. Emergency evacuation training can play a crucial role in mitigating damage not only in cases of fire, explosion or chemical spill but also in cases of natural calamities like floods and hurricanes. Conventional safety training provided in industries mostly comprises...
Show moreWith advancement in technology, building structures are becoming bigger and more complex. Incidences of horrifying fires that occur in such complex structures resulting in loss of property as well as lives are recorded worldwide. Emergency evacuation training can play a crucial role in mitigating damage not only in cases of fire, explosion or chemical spill but also in cases of natural calamities like floods and hurricanes. Conventional safety training provided in industries mostly comprises of unidirectional flow of information. Due to this passive learning style, response of employees in real life emergency situations is known to be ineffective. The proposed research focuses on the development of virtual emergency evacuation safety training for residents, workers and employees. This research developed a 3 dimensional (3D) virtual fire safety and emergency evacuation training for building occupants. A 3D model of a real engineering college building in the University of Central Florida (UCF) was developed in a virtual world and participants could interact with various objects and scenarios in this virtual building on a standard desktop computer using keyboard and mouse. Expert interviews and literature review were utilized to develop contents of fire safety and emergency evacuation training. Also, a slide based fire safety and emergency evacuation training was developed based on same contents and made available through a website. An effort was made to develop both trainings- virtual and slide based to be comparable in terms of contents. A case study with two sets of experiments comprising of 143 participants from UCF community was conducted to understand factors such as fidelity, simulation sickness, engagement and effectiveness of 3D virtual and slide based fire safety and emergency evacuation training. Results of fidelity and simulation sickness validated use of 3D virtual training for training building residents on fire safety and emergency evacuation. Data analysis of knowledge tests allowed to compare short terms and long term effectiveness of 3D virtual training and slide based training. To further understand engagement, physiological measure- electroencephalograph (EEG) of 40 healthy participants was recorded in second set of experiments. Ratio of Beta and Alpha frequency bands was studied to understand attention paid by trainees in 3D virtual and slide based training.
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Date Issued: 2017
Identifier: CFE0006935, ucf:51647
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006935

Title: A Framework for Lean Transformation in Developing Countries: The Case of Saudi Arabian Industry.
Creator: Andejany, Murad, Elshennawy, Ahmad, Rabelo, Luis, Lee, Gene, Darwish, Mohammed, University of Central Florida
Abstract / Description: Lean is a dynamic, knowledge-driven, and customer focused philosophy that continuously eradicates waste and generates value, with a goal to improve a company's productivity, efficiency, and quality. Successful implementation of lean does not only offer cost reduction and improved quality and productivity, but also provides efficient guidance for organizations to attain significant and continued growth. Although its adoption by companies has proven successful in developed countries, there is...
Show moreLean is a dynamic, knowledge-driven, and customer focused philosophy that continuously eradicates waste and generates value, with a goal to improve a company's productivity, efficiency, and quality. Successful implementation of lean does not only offer cost reduction and improved quality and productivity, but also provides efficient guidance for organizations to attain significant and continued growth. Although its adoption by companies has proven successful in developed countries, there is no sufficient evidence of its successful implementation in developing countries such as Saudi Arabia. A review of the literature indicates that there is a need to study lean transformation in developing countries as part of a comprehensive approach to their survival in the global economy. The purpose of this research is to develop a framework for a successful lean transformation in developing countries. The framework was developed by conducting a thorough literature review analysis and interviewing key personnel in ten local and eight multinational Saudi Arabian companies. The framework reacted to general data about lean transformation in developing countries, assessed a lean transformation level, and constructed the Interpretive Structure Molding (ISM) for barriers to achieve a successful lean transformation. Expert opinions were used for validation of the main components of this study, which are assessment, barriers, ISM and framework. Similar to the literature findings which indicated that the level of successful lean transformation in developing countries is low, the assessment revealed that the lean transformation level in local companies in Saudi Arabia is between 30% and 40%, and in multinational companies the level is between 50% and 60%. Both local and multinational companies in the case of Saudi Arabian industry considered lack of suppliers' involvement, lack of cooperation from suppliers, lack of good quality suppliers, and slow response to market due to demand fluctuations as the root barriers that need to be addressed at the primary stages of lean transformation. The resulting framework provides clear phases with an estimated timeline for each phase, from the foundation phase to the excellence level phase. In addition, it involves executive leaders and a cross-functional team to mentor and assess the transformation after each phase. The framework comprises several methods and tools that can be considered critical success factors for lean transformation, which will enable companies in developing countries to move toward achieving a successful lean transformation and sustainability, as well as reaching higher and persistent levels of growth.
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Date Issued: 2017
Identifier: CFE0006713, ucf:51892
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006713

Title: A New Six Sigma Implementation Approach For Power Generation Gas Turbines Repair Process Development.
Creator: Ghunakikar, Somesh, Elshennawy, Ahmad, Rabelo, Luis, Thompson, William, Furterer, Sandra, University of Central Florida
Abstract / Description: Power Generation gas turbines used for heavy duty application mainly constitutes three modules; compressor, combustion and turbine. Typically, all these parts are designed by OEM companies for specific number of hours and cycles (also known as starts) before they become dysfunctional. In addition, Gas Turbine (GT) also have intended repair interval depending upon the type of part application and anticipated damages during service operation. Thus, GT parts need inspections and repair (overhaul...
Show morePower Generation gas turbines used for heavy duty application mainly constitutes three modules; compressor, combustion and turbine. Typically, all these parts are designed by OEM companies for specific number of hours and cycles (also known as starts) before they become dysfunctional. In addition, Gas Turbine (GT) also have intended repair interval depending upon the type of part application and anticipated damages during service operation. Thus, GT parts need inspections and repair (overhaul) after certain operating hours in order to recondition them so that they can be fit for reoperation to produce power. In this dissertation, a unique six sigma DFSS approach for development of GT parts overhaul is presented for total quality improvement. In this dissertation report, a unique six sigma DFSS approach is presented applicable to the development of repair processes for GT parts that can be used during overhauling of the parts. All six sigma phases of the proposed DFSS approach along with repair product development cycle are discussed. Various six sigma tools which yield significant benefits for the process users are also discussed. Importantly, a statistical probabilistic life analysis approach is proposed in order to verify the structural integrity of a repaired GT part. Finally a case study of GT axial compressor diaphragms (stators) to illustrate various phases and six sigma tools usage during each phase of the DFSS approach is discussed. The overall significant benefit of the proposed DFSS approach was to achieve total quality improvement to deliver final GT repair process, faster repair development cycle and end customer satisfaction.
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Date Issued: 2016
Identifier: CFE0006105, ucf:51199
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006105

Title: A Hybrid Simulation Framework of Consumer-to-Consumer Ecommerce Space.
Creator: Joledo, Oloruntomi, Rabelo, Luis, Lee, Gene, Elshennawy, Ahmad, Ajayi, Richard, University of Central Florida
Abstract / Description: In the past decade, ecommerce transformed the business models of many organizations. Information Technology leveled the playing field for new participants, who were capable of causing disruptive changes in every industry. (")Web 2.0(") or (")Social Web(") further redefined ways users enlist for services. It is now easy to be influenced to make choices of services based on recommendations of friends and popularity amongst peers. This research proposes a simulation framework to investigate how...
Show moreIn the past decade, ecommerce transformed the business models of many organizations. Information Technology leveled the playing field for new participants, who were capable of causing disruptive changes in every industry. (")Web 2.0(") or (")Social Web(") further redefined ways users enlist for services. It is now easy to be influenced to make choices of services based on recommendations of friends and popularity amongst peers. This research proposes a simulation framework to investigate how actions of stakeholders at this level of complexity affect system performance as well as the dynamics that exist between different models using concepts from the fields of operations engineering, engineering management, and multi-model simulation. Viewing this complex model from a systems perspective calls for the integration of different levels of behaviors. Complex interactions exist among stakeholders, the environment and available technology. The presence of continuous and discrete behaviors coupled with stochastic and deterministic behaviors present challenges for using standalone simulation tools to simulate the business model.We propose a framework that takes into account dynamic system complexity and risk from a hybrid paradigm. The SCOR model is employed to map the business processes and it is implemented using agent based simulation and system dynamics. By combining system dynamics at the strategy level with agent based models of consumer behaviors, an accurate yet efficient representation of the business model that makes for sound basis of decision making can be achieved to maximize stakeholders' utility.
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Date Issued: 2016
Identifier: CFE0006122, ucf:51171
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006122

System Dynamics (8)	+ -
Machine Learning (4)	+ -
Simulation (4)	+ -
DFSS (3)	+ -
HLA (3)	+ -

Healthcare (3)	+ -
Industrial Engineering (3)	+ -
SPEEDES (3)	+ -
Agent Based Simulation (2)	+ -
Balanced Scorecard (2)	+ -
Change Management (2)	+ -
Customer Satisfaction (2)	+ -
Data Mining (2)	+ -
Engineering Management (2)	+ -
Hybrid Simulation (2)	+ -
Internet of Things (2)	+ -
LVC simulation (2)	+ -
Leadership (2)	+ -
Live (2)	+ -
Performance Excellence (2)	+ -
RTI (2)	+ -
Real Options Analysis (2)	+ -
Stakeholders (2)	+ -
Supply Chain Management (2)	+ -
Virtual (2)	+ -
Virtual Reality (2)	+ -
genetic algorithms (2)	+ -
interoperability (2)	+ -
lean (2)	+ -
manufacturing (2)	+ -

University of Central Florida (68)	+ -
Rabelo, Luis (67)	+ -
Elshennawy, Ahmad (35)	+ -
Lee, Gene (29)	+ -
Xanthopoulos, Petros (11)	+ -

Karwowski, Waldemar (8)	+ -
Rahal, Ahmad (7)	+ -
Kincaid, John (6)	+ -
Zheng, Qipeng (6)	+ -
Ajayi, Richard (5)	+ -
Ahmad, Ali (4)	+ -
McCauley, Pamela (4)	+ -
Pazour, Jennifer (4)	+ -
Darwish, Mohammed (2)	+ -
Ferreras, Ana (2)	+ -
Mollaghasemi, Mansooreh (2)	+ -
O'Neal, Thomas (2)	+ -
Porter, Robert (2)	+ -
Sarmiento, Alfonso (2)	+ -
Thompson, William (2)	+ -
Williams, Kent (2)	+ -
Abboodi, Mohammed (1)	+ -
Al-Foraih, Saleh (1)	+ -
Al-Shamkhani, Maher T. (1)	+ -
Albar, Abdulrahman (1)	+ -
Aldarmaki, Alia (1)	+ -
Alexander, Tiffaney (1)	+ -
Alghamdi, Mohammed (1)	+ -
Ali, Abdulelah (1)	+ -
Almalki, Hamed (1)	+ -

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