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Title: Investigating Simulation-Based Pattern Recognition Training For Behavior Cue Detection.
Creator: Maraj, Crystal, Lackey, Stephanie, Kincaid, John, Shumaker, Randall, Keebler, Joseph, University of Central Florida
Abstract / Description: The U.S. military uses pattern recognition training to observe anomalies in human behavior. An examination of the pattern recognition training literature for Warfighters reveals a gap in training to discern patterns of human behavior in live environments. Additionally, the current state of warfare is evolving and requires operations to change. As a result, pattern recognition training must accommodate new practices to improve performance. A technique used to improve memory for identifying...
Show moreThe U.S. military uses pattern recognition training to observe anomalies in human behavior. An examination of the pattern recognition training literature for Warfighters reveals a gap in training to discern patterns of human behavior in live environments. Additionally, the current state of warfare is evolving and requires operations to change. As a result, pattern recognition training must accommodate new practices to improve performance. A technique used to improve memory for identifying patterns in the environment is Kim's game. Kim's game establishes patterns to identify inanimate objects, of which information retains in memory for later recall. The paper discusses the fundamental principles of Kim's game applied to virtual Simulation-Based Training. The virtual version of Kim's game contains customized scenarios for training behavior cue analysis. Virtual agents display kinesic cues that exhibit aggressive (i.e., slap hands and clench fist) and nervous behaviors including wring hands and check six. This research takes a novel approach by animating the kinesics cues in the virtual version of Kim's game for pattern recognition training. Detection accuracy, response time, and false positive detection serve as the performance data for analysis. Additional survey data collected include engagement, flow, and simulator sickness. All collected data was compared to a control condition to examine its effectiveness of behavior cue detection. A series of one-way between subjects design ANOVA's were conducted to examine the differences between Kim's game and control on post-test performance. Although, the results from this experiment showed no significance in post-test performance, the percent change in post-test performance provide further insight into the results of the Kim's game and control strategies. Specifically, participants in the control condition performed better than the Kim's game group on detection accuracy and response time. However, the Kim's game group outperformed the control group on false positive detection. Further, this experiment explored the differences in Engagement, Flow, and Simulator Sickness after the practice scenario between Kim's game group and the control group. The results found no significant difference in Engagement, partial significance for Flow, and significant difference for Simulator Sickness between the Kim's game and control group after the practice scenario. Next, a series of Spearman's rank correlations were conducted to assess the relationships between Engagement, Flow, Simulator Sickness, and post-test performance, as well as examine the relationship between working memory and training performance; resulting in meaningful correlations to explain the relationships and identifying new concepts to explain unrelated variables. Finally, the role of Engagement, Flow, and Simulator Sickness as a predictor of post-test performance was examined using a series of multiple linear regressions. The results highlighted Simulator Sickness as a significant predictor of post-test performance. Overall, the results from this experiment proposes to expand the body of pattern recognition training literature by identifying strategies that enhance behavior cue detection training. Furthermore, it provides recommendations to training and education communities for improving behavior cue analysis. ?
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Date Issued: 2015
Identifier: CFE0005659, ucf:50166
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005659

Title: Objectively Defining Scenario Complexity: Towards Automated, Adaptive Scenario-Based Training.
Creator: Dunn, Robert, Sivo, Stephen, Hoffman, Bobby, Hartshorne, Richard, Bowers, Clint, University of Central Florida
Abstract / Description: Effective Scenario-Based Training (SBT) is sequenced in an efficient trajectory from novice to mastery and is well-grounded in pedagogically sound instructional strategies and learning theory. Adaptive, automated SBT attempts to sequence scenarios according to the performance of the student and implement the sequence without human agency. The source of these scenarios may take the form of a matrix constructed by Instructional Systems Designers (ISD), software engineers or trainers. The domain...
Show moreEffective Scenario-Based Training (SBT) is sequenced in an efficient trajectory from novice to mastery and is well-grounded in pedagogically sound instructional strategies and learning theory. Adaptive, automated SBT attempts to sequence scenarios according to the performance of the student and implement the sequence without human agency. The source of these scenarios may take the form of a matrix constructed by Instructional Systems Designers (ISD), software engineers or trainers. The domain being instructed may contain procedures or concepts that are easily differentiated thus allowing quick and accurate determination of difficulty. In this instance, the sequencing of the SBT is relatively simple. However, in complex, domain-integrated instructional environments accurate and efficient sequencing may be extremely difficult as ISD, software engineers and trainers, without an objective means to calculate a scenario's complexity must rely on subjectivity. In the Military, where time, fiscal and manpower constraints may lead to ineffective, inefficient and, perhaps, negative training SBT is a growing alternative to live training due to the significant cost avoidance demonstrated by such systems as the United States Marine Corps' (USMC) Abrams Main Battle Tank (M1A1) Advanced Gunnery Training System (AGTS). Even as the practice of simulation training grows, leadership such as the Government Accountability Office asserts that little has been done to demonstrate simulator impact on trainee proficiency. The M1A1 AGTS instructional sub system, the Improved Crew Training Program (ICTP), employs an automated matrix intended to increase Tank Commander (TC) and Gunner (GNR) team proficiency. This matrix is intended to guide the team along a trajectory of ever-increasing scenario difficulty. However, as designed, the sequencing of the matrix is based on subjective evaluation of difficulty, not on empirical or objective calculations of complexity. Without effective, automated SBT that adapts to the performance of the trainee, gaps in combat readiness and fiscal responsibility could grow large.In 2010, the author developed an algorithm intended to computationally define scenario complexity (Dunne, Schatz, Fiore, Martin (&) Nicholson, 2010) and conducted a proof of concept study to determine the algorithm's effectiveness (Dunne, Schatz, Fiore, Nicholson (&) Fowlkes, 2010). Based on results of that study, and follow-on analysis, revisions were made to that Scenario Complexity (SC) algorithm. The purpose of this research was to examine the efficacy of the revised SC algorithm to enable Educators and Trainers, ISDs, and software engineers to objectively and computationally define SC. The research process included a period of instruction for Subject Matter Experts (SME) to receive instruction on how to identify the base variables that comprise SC. Using this knowledge SMEs then determined the values of the scenarios base variables. Once calculated, these values were ranked and compared to the ICTP matrix sequence.Results indicate that the SMEs were very consistent in their ratings of the items across scenario base variables. Due to the highly proceduralized process underlying advanced gunnery skills, this high degree of agreement was expected. However, the significant lack of correlation to the matrix sequencing is alarming and while a recent study has shown the AGTS to increase TC and GNR team proficiency (PM TRASYS, 2014a), this research's findings suggests that redesign of the ICTP matrix is in order.
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Date Issued: 2014
Identifier: CFE0005789, ucf:50062
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005789

Title: The effect of Curriculum Organization on the acquisition of Abstract Declarative Knowledge in Computer Based Instructions.
Creator: Al-Foraih, Saleh, Williams, Kent, Proctor, Michael, Rabelo, Luis, Ozkaptan, Halim, University of Central Florida
Abstract / Description: ABSTRACTThe United States of America has dropped behind many countries in terms of theScience and Engineering university degrees awarded since the beginning of the nineties.Multiple studies have been conducted to determine the cause of this decline in degreesawarded, and try to reverse the trend in US education. The goal of these studies was todetermine the proper instructional methods that facilitate the knowledge acquisitionprocess for the student. It has been determined that not one method...
Show moreABSTRACTThe United States of America has dropped behind many countries in terms of theScience and Engineering university degrees awarded since the beginning of the nineties.Multiple studies have been conducted to determine the cause of this decline in degreesawarded, and try to reverse the trend in US education. The goal of these studies was todetermine the proper instructional methods that facilitate the knowledge acquisitionprocess for the student. It has been determined that not one method works for all types ofcurriculum, for example methods that have been found to work effectively in curriculumthat teaches procedures and physical systems often fail in curriculum that teaches abstractand conceptual content. The purpose of this study is to design an instructional methodthat facilitates teaching of abstract knowledge, and to demonstrate its effectivenessthrough empirical research.An experiment including 72 undergraduate students was conducted to determinethe best method of acquiring abstract knowledge. All students were presented with thesame abstract knowledge but presented in different types of organization. Theseorganization types consisted of hierarchy referred as Bottom Up, Top Down, andUnorganized. Another factor that was also introduced is Graphing, which is a method thatis believe to improve the learning process. The experiment was completed in 8 weeks anddata was gathered and analyzed.The results strongly suggest that abstract knowledge acquisition is greatlyimproved when the knowledge is presented in a Bottom Up hierarchical fashion. On theother hand, neither Graphing nor the Top Down or Unorganized conditions affectlearning in these novice students.
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Date Issued: 2013
Identifier: CFE0004644, ucf:49893
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0004644

Title: Training for Decision Making in Complex Environments: Instructional Methods and Individual Differences.
Creator: Ray, Jessica, Mouloua, Mustapha, Sims, Valerie, Hancock, Peter, Spain, Randall, Durlach, Paula, University of Central Florida
Abstract / Description: Increased technology reliance along with today's global fast paced society has produced increasingly complex, dynamic operating environments in disciplines as diverse as the military, healthcare, and transportation. These complex human machine systems often place additional cognitive and metacognitive demands on the operator. Thus, there is a crucial need to develop training tools for all levels of operators in these dynamic systems. The current study was designed to empirically test the...
Show moreIncreased technology reliance along with today's global fast paced society has produced increasingly complex, dynamic operating environments in disciplines as diverse as the military, healthcare, and transportation. These complex human machine systems often place additional cognitive and metacognitive demands on the operator. Thus, there is a crucial need to develop training tools for all levels of operators in these dynamic systems. The current study was designed to empirically test the effects of four training methods on performance and mental model accuracy in a microworld simulation game. It was hypothesized that process-focused guidance targeting metacognitive level processes as well as combined process and problem focused guidance would result in better performance and mental model accuracy than problem- focused guidance alone or unguided training approaches. Additionally, it was expected that individual differences in prior decision making ability, metacognitive awareness, working memory span, and fluid intelligence would moderate the relationship between the type of instructional guidance and outcomes. Results supported the development of decision-making skills through process-focused instructional guidance, particularly for initially low performing or more novice individuals. Results highlight the importance of individual learner experience prior to training. Similarly, this research aims to expand the literature by providing support for process-focused training as a method to support non-expert decision making skills. While further research needs are outlined, the current research represents an important step forward in both the theoretical literature providing support for instruction designed to support domain general decision making skills in non-experts. Practical implications regarding improved guidance for future instructional and training systems design, personnel selection, operator and system performance evaluation, and safety are also discussed.
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Date Issued: 2013
Identifier: CFE0004738, ucf:49836
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0004738

Title: Electronic properties and atomic scale microscopy of two dimensional materials: graphene and molybdenum disulfide.
Creator: Katoch, Jyoti, Ishigami, Marsahir, Mucciolo, Eduardo, Del Barco, Enrique, Coffey, Kevin, University of Central Florida
Abstract / Description: Novel two dimensional nanoscale materials like graphene and metal dichalcogenides (MX2) have attracted the attention of the scientific community, due to their rich physics and wide range of potential applications.It has been shown that novel graphene based transparent conductors and radiofrequency transistors are competitive with the existing technologies. Graphene's properties are influenced sensitively by adsorbates and substrates. As such not surprisingly, physical properties of graphene...
Show moreNovel two dimensional nanoscale materials like graphene and metal dichalcogenides (MX2) have attracted the attention of the scientific community, due to their rich physics and wide range of potential applications.It has been shown that novel graphene based transparent conductors and radiofrequency transistors are competitive with the existing technologies. Graphene's properties are influenced sensitively by adsorbates and substrates. As such not surprisingly, physical properties of graphene are found to have a large variability, which cannot be controlled at the synthesis level, reducing the utility of graphene. As a part of my doctorate dissertation, I have developed atomic hydrogen as a novel technique to count the scatterers responsible for limiting the carrier mobility of graphene field effect transistors on silicon oxide (SiO2) and identified that charged impurities to be the most dominant scatterer. This result enables systematic reduction of the detrimental variability in device performance of graphene. Such sensitivity to substrates also gives an opportunity for engineering device properties of graphene using substrate interaction and atomic scale vacancies. Stacking graphene on hexagonal boron-nitride (h-BN) gives rise to nanoscale periodic potential, which influences its electronic graphene. Using state-of-the-art atomic-resolution scanning probe microscope, I correlated the observed transport properties to the substrate induced extrinsic potentials. Finally in efforts to exploit graphene's sensitivity to discover new sensor technologies, I have explored noncovalentfunctionalization of graphene using peptides.Molybdenum disulfide (MoS2) exhibits thickness dependent bandgap. Transistors fabricated from single layer MoS2 have shown a high on/off ratio. It is expected that ad-atom engineering can be used to induce on demand a metal-semiconductor transition in MoS2. In this direction, I have explored controlled/reversible fluorination and hydrogenation of monolayer MoS2 to potentially derive a full range of integrated circuit technology. The in-depth characterization of the samples is carried out by Raman/photoluminescence spectroscopy and scanning tunneling microscopy.
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Date Issued: 2014
Identifier: CFE0005190, ucf:50614
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005190

Title: Lyapunov-Based Robust and Adaptive Control Design for nonlinear Uncertain Systems.
Creator: Zhang, Kun, Behal, Aman, Haralambous, Michael, Xu, Yunjun, Boloni, Ladislau, Marzocca, Piergiovanni, University of Central Florida
Abstract / Description: The control of systems with uncertain nonlinear dynamics is an important field of control scienceattracting decades of focus. In this dissertation, four different control strategies are presentedusing sliding mode control, adaptive control, dynamic compensation, and neural network for a nonlinear aeroelastic system with bounded uncertainties and external disturbance. In Chapter 2, partial state feedback adaptive control designs are proposed for two different aeroelastic systems operating in...
Show moreThe control of systems with uncertain nonlinear dynamics is an important field of control scienceattracting decades of focus. In this dissertation, four different control strategies are presentedusing sliding mode control, adaptive control, dynamic compensation, and neural network for a nonlinear aeroelastic system with bounded uncertainties and external disturbance. In Chapter 2, partial state feedback adaptive control designs are proposed for two different aeroelastic systems operating in unsteady flow. In Chapter 3, a continuous robust control design is proposed for a class of single input and single output system with uncertainties. An aeroelastic system with a trailingedge flap as its control input will be considered as the plant for demonstration of effectiveness of the controller. The controller is proved to be robust by both athematical proof and simulation results. In Chapter 3, a robust output feedback control strategy is discussed for the vibration suppression of an aeroelastic system operating in an unsteady incompressible flowfield. The aeroelastic system is actuated using a combination of leading-edge (LE) and trailing-edge (TE) flaps in the presence of different kinds of gust disturbances. In Chapter 5, a neural-network based model-free controller is designed for an aeroelastic system operating at supersonic speed. The controller is shown to be able to effectively asymptotically stabilize the system via both a Lyapunov-based stability proof and numerical simulation results.
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Date Issued: 2015
Identifier: CFE0005748, ucf:50110
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005748

Title: A Faith-Based Primary Diabetes Prevention Intervention for At-Risk Puerto Rican Adults: A Feasibility Study.
Creator: Torres-Thomas, Sylvia, Chase, Susan, Covelli, Maureen, Gonzalez, Laura, Yan, Xin, Miller, Ann, University of Central Florida
Abstract / Description: Diabetes is a serious health threat that disproportionately affects Hispanics of Puerto Rican heritage. Current evidence supports diabetes prevention programs to change health behaviors in people who are at risk and thus prevent the development of type 2 diabetes. However, few interventions exist for Hispanics, and even fewer have been designed for Puerto Rican adults. A literature review of community-based diabetes prevention programs involving at-risk Hispanics was conducted using a...
Show moreDiabetes is a serious health threat that disproportionately affects Hispanics of Puerto Rican heritage. Current evidence supports diabetes prevention programs to change health behaviors in people who are at risk and thus prevent the development of type 2 diabetes. However, few interventions exist for Hispanics, and even fewer have been designed for Puerto Rican adults. A literature review of community-based diabetes prevention programs involving at-risk Hispanics was conducted using a cultural sensitivity framework to determine the state of the science and identify gaps in knowledge regarding diabetes prevention for Puerto Ricans. An integrated theoretical framework was developed using constructs from the extended parallel process model (perceived severity and susceptibility) and social cognitive theory (self-efficacy) to design program components aimed to educate and motivate positive dietary behavior change in Puerto Rican adults. The two key components were a diabetes health threat message and dietary skill building exercises that incorporated spirituality and relevant faith practices, and were culturally-tailored for Puerto Ricans. A pretest-posttest, concurrent mixed methods design was used to test the impact and evaluate feasibility of a diabetes health threat message and skill-building exercises in a sample of Puerto Rican adults. A total of 24 participants enrolled in the study and attended six-weekly meetings that included baseline data collection, a health threat message, dietary skill building exercises, focus group interviews, posttest data collection, and an end-of-study potluck gathering. All of the study participants were Puerto Rican and a majority were female (70.8%), with a mean age of 55.5 years (SD 13.71). Most had a family history of diabetes (n = 21, 87.5%) and believed they were at-risk for the disease (n = 16, 66.7%). Using Wilcoxon matched-pairs signed rank test, significant increases or improvements were found in perceptions of diabetes severity (p (<) .01), dietary self-efficacy (p = .002), and dietary patterns (p = .02) at posttest in comparison to baseline. Spearman's rank correlations found moderate to strong relationships between the following variables: perceived severity and weight (rs = -.44, p = .03), dietary self-efficacy and dietary patterns (rs = .43, p = .04), dietary self-efficacy and fasting blood glucose levels (rs = - .45, p = .03), and American acculturation and weight (rs = .51, p = .02). The qualitative themes that emerged contributed to our understanding of participants' perspective relative to the health threat message, dietary skill building exercises, and the importance of cultural relevance and spirituality. The data support feasibility of this faith-based intervention that had an attendance rate of 58% and no loss of sample due to attrition. Diabetes prevention interventions for at-risk Puerto Ricans adults that incorporate a faith-based, culturally-tailored health threat message and dietary skill building exercises may help educate those who are at-risk and motivate lifestyle behavior change to prevent the development of diabetes. Further faith-based, culturally-tailored diabetes prevention research is indicated for Puerto Rican adults.
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Date Issued: 2015
Identifier: CFE0005725, ucf:50124
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005725

Title: LEARNING GEOMETRY-FREE FACE RE-LIGHTING.
Creator: Moore, Thomas, Foroosh, Hassan, University of Central Florida
Abstract / Description: The accurate modeling of the variability of illumination in a class of images is a fundamental problem that occurs in many areas of computer vision and graphics. For instance, in computer vision there is the problem of facial recognition. Simply, one would hope to be able to identify a known face under any illumination. On the other hand, in graphics one could imagine a system that, given an image, the illumination model could be identified and then used to create new images. In this thesis...
Show moreThe accurate modeling of the variability of illumination in a class of images is a fundamental problem that occurs in many areas of computer vision and graphics. For instance, in computer vision there is the problem of facial recognition. Simply, one would hope to be able to identify a known face under any illumination. On the other hand, in graphics one could imagine a system that, given an image, the illumination model could be identified and then used to create new images. In this thesis we describe a method for learning the illumination model for a class of images. Once the model is learnt it is then used to render new images of the same class under the new illumination. Results are shown for both synthetic and real images. The key contribution of this work is that images of known objects can be re-illuminated using small patches of image data and relatively simple kernel regression models. Additionally, our approach does not require any knowledge of the geometry of the class of objects under consideration making it relatively straightforward to implement. As part of this work we will examine existing geometric and image-based re-lighting techniques; give a detailed description of our geometry-free face re-lighting process; present non-linear regression and basis selection with respect to image synthesis; discuss system limitations; and look at possible extensions and future work.
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Date Issued: 2007
Identifier: CFE0001893, ucf:47394
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0001893

Title: A MULTI-LAYER FPGA FRAMEWORK SUPPORTING AUTONOMOUS RUNTIME PARTIAL RECONFIGURATION.
Creator: Tan, Heng, DeMara, Ronald, University of Central Florida
Abstract / Description: Partial reconfiguration is a unique capability provided by several Field Programmable Gate Array (FPGA) vendors recently, which involves altering part of the programmed design within an SRAM-based FPGA at run-time. In this dissertation, a Multilayer Runtime Reconfiguration Architecture (MRRA) is developed, evaluated, and refined for Autonomous Runtime Partial Reconfiguration of FPGA devices. Under the proposed MRRA paradigm, FPGA configurations can be manipulated at runtime using on-chip...
Show morePartial reconfiguration is a unique capability provided by several Field Programmable Gate Array (FPGA) vendors recently, which involves altering part of the programmed design within an SRAM-based FPGA at run-time. In this dissertation, a Multilayer Runtime Reconfiguration Architecture (MRRA) is developed, evaluated, and refined for Autonomous Runtime Partial Reconfiguration of FPGA devices. Under the proposed MRRA paradigm, FPGA configurations can be manipulated at runtime using on-chip resources. Operations are partitioned into Logic, Translation, and Reconfiguration layers along with a standardized set of Application Programming Interfaces (APIs). At each level, resource details are encapsulated and managed for efficiency and portability during operation. An MRRA mapping theory is developed to link the general logic function and area allocation information to the device related physical configuration level data by using mathematical data structure and physical constraints. In certain scenarios, configuration bit stream data can be read and modified directly for fast operations, relying on the use of similar logic functions and common interconnection resources for communication. A corresponding logic control flow is also developed to make the entire process autonomous. Several prototype MRRA systems are developed on a Xilinx Virtex II Pro platform. The Virtex II Pro on-chip PowerPC core and block RAM are employed to manage control operations while multiple physical interfaces establish and supplement autonomous reconfiguration capabilities. Area, speed and power optimization techniques are developed based on the developed Xilinx prototype. Evaluations and analysis of these prototype and techniques are performed on a number of benchmark and hashing algorithm case studies. The results indicate that based on a variety of test benches, up to 70% reduction in the resource utilization, up to 50% improvement in power consumption, and up to 10 times increase in run-time performance are achieved using the developed architecture and approaches compared with Xilinx baseline reconfiguration flow. Finally, a Genetic Algorithm (GA) for a FPGA fault tolerance case study is evaluated as a ultimate high-level application running on this architecture. It demonstrated that this is a hardware and software infrastructure that enables an FPGA to dynamically reconfigure itself efficiently under the control of a soft microprocessor core that is instantiated within the FPGA fabric. Such a system contributes to the observed benefits of intelligent control, fast reconfiguration, and low overhead.
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Date Issued: 2007
Identifier: CFE0001933, ucf:47448
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0001933

Title: The Ability to Critically Evaluate Research Literature in Speech-Language Pathology.
Creator: Gregorio, David, Carnaby, Giselle, Hoffman Ruddy, Bari, Crary, Michael, University of Central Florida
Abstract / Description: Research in Speech-Language Pathology provides the basis for understanding how and to what degree therapeutic techniques and interventions affect the health and quality of life of individuals with communication disorders. Across numerous fields of healthcare, research serves just as important a function and is used to guide the practices of professionals across the public health sector. Several disciplines, including chiropracty, nursing, and physical therapy, rely on the implementation of...
Show moreResearch in Speech-Language Pathology provides the basis for understanding how and to what degree therapeutic techniques and interventions affect the health and quality of life of individuals with communication disorders. Across numerous fields of healthcare, research serves just as important a function and is used to guide the practices of professionals across the public health sector. Several disciplines, including chiropracty, nursing, and physical therapy, rely on the implementation of Evidence-Based Practice (EBP) to ensure that the process of rehabilitation and the techniques employed therein are carried out though the synthesis of best clinical judgment, empirical evidence, and patient values. The field of Speech-Language Pathology also uses EBP as the foundation of intervention and rehabilitation. Research has shown, however, that clinicians in a variety of settings encounter barriers to the implementation of EBP. Such reported barriers include lack of access to current research literature, lack of time with which to review the literature, and difficulty determining the quality of research available. General aims of the present study were: (1) to explore speech pathologists' self-reported patterns of access and use of techniques presented in the current research literature, (2) to investigate their self-rated knowledge of and ability to critically evaluate the research literature, and (3) to examine their knowledge and ability through use of a problem-based survey design. 325 certified Speech-Language Pathologists (SLPs) were administered a brief web-based survey to collect information that might provide insight related to these research questions. Results of the study indicated that, on average, participants access the research literature and utilize techniques found therein with moderate frequency. Findings also reveal that self-rated capacity and research knowledge were significantly greater for respondents who had acquired their PhD and for those who had previously conducted formal research. Significant results were also found when evaluating differences among respondent's place of work by median change in self-rated research capacity. Furthermore, positive correlations were found between research knowledge and self-rated capacity and research knowledge and research evaluation. These findings call attention to the process through which research methodology is taught in higher education. The findings may also suggest that a more effective and functional model of instruction in this area is critical to the clinical implementation of EBP.
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Date Issued: 2017
Identifier: CFE0006597, ucf:51269
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006597

Title: Designing a Virtual Embedded Scenario-Based Military Simulation Training Program using Educational and Design Instructional Strategies.
Creator: Cook, Christina, Hopp, Carolyn, Gunter, Glenda, Hewitt, Randall, Vitale, Thomas, University of Central Florida
Abstract / Description: The purpose of this dissertation in practice was to develop and implement a new training program for designers of military intelligence simulation scenarios used to train soldiers. The use of education and design instructional strategies assisted in the ability for designers to gain mastery skills in creating realistic, high-fidelity scenarios that are applied in the training process. The use of simulation scenarios to train adult learners has increased significantly with improvements in...
Show moreThe purpose of this dissertation in practice was to develop and implement a new training program for designers of military intelligence simulation scenarios used to train soldiers. The use of education and design instructional strategies assisted in the ability for designers to gain mastery skills in creating realistic, high-fidelity scenarios that are applied in the training process. The use of simulation scenarios to train adult learners has increased significantly with improvements in technology and its fidelity to engage learners in a realistic way. Despite these advances, the lack of effective design, implementation and analysis of military simulation training programs in the military intelligence community has led to a decrease in simulation utilization, as in the case of the organization examined in this problem of practice. The current training program's increasing difficulties with consistent use by military intelligence simulation scenario designers were discovered in the results of a gap analysis conducted in 2014, prompting this design. This simulation design aimed to examine: (1) a research-based design methodology to match training requirements for the designers, (2) formative assessment of performance and (3) a research-based evaluation framework to determine the effectiveness of the new training program. For the organization's training program, a Simulation-Based Embedded Training (SBET) solution using scenarios was conceived based on research grounded in cognitive theory and instructional design considerations for simulations. As a structured framework for how to design and implement an effective and sustained training program, the educational instructional design model, ADDIE, was used. This model allowed for continual flexibility in each phase to evaluate and implement changes iteratively. The instructional model and its techniques were used with fidelity, specifically for training the designers of the simulation system. Industries will continue to increase the use of simulation as advances in technologies offer more realistic, safe, and complex training environments.A detailed strategy was provided specific to the organization using a research-based instructional approach integrated into program requirements set forth by the government. This proposed solution, supported by research in the application of instructional strategies, is specific to this organization; however, the training program design differs from other high-fidelity military simulator training programs through its use of dispersed training to the simulation scenario designers using realistic scenarios to mimic the tasks that the designers themselves must create. The difference in the solution in this dissertation in practice is: 1) that the simulation scenarios are designed without the help of subject matter experts by using the embedded instructional strategies and 2) the design is to the fidelity of realism required for military intelligence training exercises.
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Date Issued: 2018
Identifier: CFE0006990, ucf:51617
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006990

Title: Virtual Interactions with Real-Agents for Sustainable Natural Resource Management.
Creator: Pierce, Tyler, Madani Larijani, Kaveh, Wang, Dingbao, Jacques, Peter, University of Central Florida
Abstract / Description: Common pool resource management systems are complex to manage due to the absence of a clear understanding of the effects of users' behavioral characteristics. Non-cooperative decision making based on individual rationality (as opposed to group rationality) and a tendency to free ride due to lack of trust and information about other users' behavior creates externalities and can lead to tragedy of the commons without intervention by a regulator. Nevertheless, even regulatory institutions often...
Show moreCommon pool resource management systems are complex to manage due to the absence of a clear understanding of the effects of users' behavioral characteristics. Non-cooperative decision making based on individual rationality (as opposed to group rationality) and a tendency to free ride due to lack of trust and information about other users' behavior creates externalities and can lead to tragedy of the commons without intervention by a regulator. Nevertheless, even regulatory institutions often fail to sustain natural common pool resources in the absence of clear understanding of the responses of multiple heterogeneous decision makers to different regulation schemes. While modeling can help with our understanding of complex coupled human-natural systems, past research has not been able to realistically simulate these systems for two major limitations: 1) lack of computational capacity and proper mathematical models for solving distributed systems with self-optimizing agents; and 2) lack of enough information about users' characteristics in common pool resource systems due to absence of reliable monitoring information. Recently, different studies have tried to address the first limitation by developing agent-based models, which can be appropriately handled with today's computational capacity. While these models are more realistic than the social planner's models which have been traditionally used in the field, they normally rely on different heuristics for characterizing users' behavior and incorporating heterogeneity. This work is a step-forward in addressing the second limitation, suggesting an efficient method for collecting information on diverse behavioral characteristics of real agents for incorporation in distributed agent-based models. Gaming in interactive virtual environments is suggested as a reliable method for understanding different variables that promote sustainable resource use through observation of decision making and behavior of the resource system beneficiaries under various institutional frameworks and policies. A review of educational or "serious" games for environmental management was undertaken to determine an appropriate game for collecting information on real-agents and also to investigate the state of environmental management games and their potential as an educational tool. A web-based groundwater sharing simulation game(-)Irrigania(-)was selected to analyze the behavior of real agents under different common pool resource management institutions. Participants included graduate and undergraduate students from the University of Central Florida and Lund University. Information was collected on participants' resource use, behavior and mindset under different institutional settings through observation and discussion with participants. Preliminary use of water resources gaming suggests communication, cooperation, information disclosure, trust, credibility and social learning between beneficiaries as factors promoting a shift towards sustainable resource use. Additionally, Irrigania was determined to be an effective tool for complementing traditional lecture-based teaching of complex concepts related to sustainable natural resource management. The different behavioral groups identified in the study can be used for improved simulation of multi-agent groundwater management systems.
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Date Issued: 2013
Identifier: CFE0005045, ucf:49953
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005045

Title: The Impact of the Community Partnership Schools Model Community School on Graduation and Attendance Rates in One Florida High School.
Creator: Ellis, Amy, Johnson, Jerry, Doherty, Walter, Williams-Fjeldhe, Karri, Castor Dentel, Karen, University of Central Florida
Abstract / Description: The purpose of this quantitative study was to identify and describe the nature and extent of the relationships, if any, that existed between a Community Partnership Schools(TM) (CPS) model community school and the outcomes of graduation and attendance rates at one public high school in Florida. An evaluation study utilizing an interrupted time series (ITS) design addressed this problem by identifying and describing the relationship between the CPS model and the key outcome measures using...
Show moreThe purpose of this quantitative study was to identify and describe the nature and extent of the relationships, if any, that existed between a Community Partnership Schools(TM) (CPS) model community school and the outcomes of graduation and attendance rates at one public high school in Florida. An evaluation study utilizing an interrupted time series (ITS) design addressed this problem by identifying and describing the relationship between the CPS model and the key outcome measures using visual analysis and descriptive statistics. Graduation and attendance rates for seven years before the CPS model was introduced (2003-2010) and seven years after the CPS model was introduced (2010-2017) at the CPS school were compared to the graduation and attendance rates for the same time frames of five other matched comparison high schools that had not implemented a CPS model community school. Findings of this study, though mixed, suggest the Community Partnership Schools(TM) model may have provided a positive environment for improvement in key measures at the targeted CPS high school. Though no definitive conclusions were reached, this study alongside other evaluations of the Community Partnership Schools(TM) model may be helpful in informing decision makers regarding the potential positive influence of the CPS model on such measures as graduation and attendance rates.
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Date Issued: 2019
Identifier: CFE0007452, ucf:52698
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0007452

Title: Spatial and Temporal Compressive Sensing for Vibration-based Monitoring: Fundamental Studies with Beam Vibrations.
Creator: Ganesan, Vaahini, Das, Tuhin, Kauffman, Jeffrey L., Raghavan, Seetha, University of Central Florida
Abstract / Description: Vibration data from mechanical systems carry important information that is useful for characterization and diagnosis. Standard approaches rely on continually streaming data at a fixed sampling frequency. For applications involving continuous monitoring, such as Structural Health Monitoring (SHM), such approaches result in high data volume and require powering sensors for prolonged duration. Furthermore, adequate spatial resolution, typically involves instrumenting structures with a large...
Show moreVibration data from mechanical systems carry important information that is useful for characterization and diagnosis. Standard approaches rely on continually streaming data at a fixed sampling frequency. For applications involving continuous monitoring, such as Structural Health Monitoring (SHM), such approaches result in high data volume and require powering sensors for prolonged duration. Furthermore, adequate spatial resolution, typically involves instrumenting structures with a large array of sensors. This research shows that applying Compressive Sensing (CS) can significantly reduce both the volume of data and number of sensors in vibration monitoring applications. Random sampling and the inherent sparsity of vibration signals in the frequency domain enables this reduction. Additionally, by exploiting the sparsity of mode shapes, CS can also enable efficient spatial reconstruction using fewer spatially distributed sensors than a traditional approach. CS can thereby reduce the cost and power requirement of sensing as well as streamline data storage and processing in monitoring applications. In well-instrumented structures, CS can enable continuous monitoring in case of sensor or computational failures. The scope of this research was to establish CS as a viable method for SHM with application to beam vibrations. Finite element based simulations demonstrated CS-based frequency recovery from free vibration response of simply supported, fixed-fixed and cantilever beams. Specifically, CS was used to detect shift in natural frequencies of vibration due to structural change using considerably less data than required by traditional sampling. Experimental results using a cantilever beam provided further insight into this approach. In the experimental study, impulse response of the beam was used to recover natural frequencies of vibration with CS. It was shown that CS could discern changes in natural frequencies under modified beam parameters. When the basis functions were modified to accommodate the effect of damping, the performance of CS-based recovery further improved. Effect of noise in CS-based frequency recovery was also studied. In addition to incorporating damping, formulating noise-handling as a part of the CS algorithm for beam vibrations facilitated detecting shift in frequencies from even fewer samples. In the spatial domain, CS was primarily developed to focus on image processing applications, where the signals and basis functions are very different from those required for mechanical beam vibrations. Therefore, it mandated reformulation of the CS problem that would handle related challenges and enable the reconstruction of spatial beam response using very few sensor data. Specifically, this research addresses CS-based reconstruction of deflection shape of beams with fixed boundary conditions. Presence of a fixed end makes hyperbolic terms indispensable in the basis, which in turn causes numerical inconsistencies. Two approaches are discussed to mitigate this problem. The first approach is to restrict the hyperbolic terms in the basis to lower frequencies to ensure well conditioning. The second, a more systematic approach, is to generate an augmented basis function that will combine harmonic and hyperbolic terms. At higher frequencies, the combined hyperbolic terms will limit each other's magnitude, thus ensuring boundedness. This research thus lays the foundation for formulating the CS problem for the field of mechanical vibrations. It presents fundamental studies and discusses open-ended challenges while implementing CS to this field that will pave way for further research.
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Date Issued: 2017
Identifier: CFE0007120, ucf:51954
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0007120

Title: SYNTHESIS AND CHARACTERIZATION OF STABLE AND METASTABLE PHASES IN Ni- AND Fe-BASED ALLOY SYSTEMS BY MECHANICAL ALLOYING.
Creator: Al-Joubori, Ahmed, Challapalli, Suryanarayana, Vaidyanathan, Raj, Gou, Jihua, Bai, Yuanli, Lin, Kuo-Chi, University of Central Florida
Abstract / Description: Mechanical Alloying (MA) is a process that involves repeated cold welding, fracturing and rewelding of powder particles in a high-energy ball mill and has been used extensively to synthesize both stable (equilibrium) and metastable phases in a number of alloy systems. This is due to its ability to achieve many effects simultaneously, viz., reduction in grain size, introduction of a variety of crystal defects, disordering of the lattice, and modifying the crystal structures of materials; all...
Show moreMechanical Alloying (MA) is a process that involves repeated cold welding, fracturing and rewelding of powder particles in a high-energy ball mill and has been used extensively to synthesize both stable (equilibrium) and metastable phases in a number of alloy systems. This is due to its ability to achieve many effects simultaneously, viz., reduction in grain size, introduction of a variety of crystal defects, disordering of the lattice, and modifying the crystal structures of materials; all these allowing alloying and phase transformations to occur in powders. In this Dissertation, we have synthesized a number of different alloy phases in Ni- and Fe-based alloy systems using MA.The as-received, blended, and milled powders were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), and transmission electron microscopy techniques to obtain information about the overall microstructure and chemical compositions. The NiX2 (X = Ge and Si) phases were synthesized in the Ni-Ge and Ni-Si systems. MA of Ni-Ge powder blends was investigated to study phase evolution as a function of milling time. On milling the powders for 5 h, the equilibrium NiGe phase started to form, and its amount in the powder increased with increasing milling time. On milling for about 60 h, the equilibrium intermetallic NiGe and Ge powder particles reacted to form the metastable NiGe2 phase. However, on milling for a longer time (75 h), the metastable phase transformed back to the equilibrium NiGe phase.Synthesis of the NiSi2 intermetallic phase depended on the Si content in the initial powder blend. For example, while in the Ni-60 at.% Si powder blend, only the NiSi phase was present homogeneously, the powder blend of the Ni-67 at.% Si composition contained the NiSi phase along with a small amount of unreacted Si. But in the Ni-75 at.% Si and Ni-80 at% compositions, the NiSi phase that had formed earlier (after 2 h of milling) and the remaining free Si powder reacted to form the equilibrium intermetallic NiSi2 phase. This constitution in the milled powder has been attributed to a partial loss of Si content during MA. Formation of Ni(Si) solid solutions with a solubility of about 18.2 at.% and 20.6 at.% for the Ni-75 at.% Si and Ni-80 at.% Si powder blends, respectively, was also achieved in the early stages of MA.In the Fe-C system, we were able to synthesize ferrite, cementite, and mixtures of the two phases. We were able to obtain the Fe-C solid solution phase (ferrite) with a BCC structure and the cementite phase with an orthorhombic structure in the eutectoid Fe-0.8 wt. % C composition, while a homogeneous cementite phase had formed at the higher carbon content of Fe-7.0 wt. % C after 30 h of milling time.In the case of the Fe-18Cr-xNi (x = 8, 12, and 20) system, the current investigation showed that the phase constitution depended significantly on the Ni content in the powder blend. Whereas mostly the martensite or the ferrite and austenite phase mixture was present at lower Ni contents, a completely homogeneous austenite phase was present in the alloy with 20% Ni.
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Date Issued: 2016
Identifier: CFE0006244, ucf:51059
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006244

Title: SketChart: A Pen-Based Tool for Chart Generation and Interaction.
Creator: Vargas Gonzalez, Andres, Laviola II, Joseph, Foroosh, Hassan, Hua, Kien, University of Central Florida
Abstract / Description: It has been shown that representing data with the right visualization increases the understanding of qualitative and quantitative information encoded in documents. However, current tools for generating such visualizations involve the use of traditional WIMP techniques, which perhaps makes free interaction and direct manipulation of the content harder. In this thesis, we present a pen-based prototype for data visualization using 10 different types of bar based charts. The prototype lets users...
Show moreIt has been shown that representing data with the right visualization increases the understanding of qualitative and quantitative information encoded in documents. However, current tools for generating such visualizations involve the use of traditional WIMP techniques, which perhaps makes free interaction and direct manipulation of the content harder. In this thesis, we present a pen-based prototype for data visualization using 10 different types of bar based charts. The prototype lets users sketch a chart and interact with the information once the drawing is identified. The prototype's user interface consists of an area to sketch and touch based elements that will be displayed depending on the context and nature of the outline. Brainstorming and live presentations can benefit from the prototype due to the ability to visualize and manipulate data in real time. We also perform a short, informal user study to measure effectiveness of the tool while recognizing sketches and users acceptance while interacting with the system. Results show SketChart strengths and weaknesses and areas for improvement.
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Date Issued: 2014
Identifier: CFE0005434, ucf:50405
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005434

Title: SCALING OF SPECTRA OF CANTOR-TYPE MEASURES AND SOME NUMBER THEORETIC CONSIDERATIONS.
Creator: Kraus, Isabelle, Dutkay, Dorin, University of Central Florida
Abstract / Description: We investigate some relations between number theory and spectral measures related to the harmonic analysis of a Cantor set. Specifically, we explore ways to determine when an odd natural number m generates a complete or incomplete Fourier basis for a Cantor-type measure with scale g.
Date Issued: 2017
Identifier: CFH2000169, ucf:45948
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFH2000169

Title: EVOLVING MODELS FROM OBSERVED HUMAN PERFORMANCE.
Creator: Fernlund, Hans Karl Gustav, Gonzalez, Avelino J., University of Central Florida
Abstract / Description: To create a realistic environment, many simulations require simulated agents with human behavior patterns. Manually creating such agents with realistic behavior is often a tedious and time-consuming task. This dissertation describes a new approach that automatically builds human behavior models for simulated agents by observing human performance. The research described in this dissertation synergistically combines Context-Based Reasoning, a paradigm especially developed to model tactical...
Show moreTo create a realistic environment, many simulations require simulated agents with human behavior patterns. Manually creating such agents with realistic behavior is often a tedious and time-consuming task. This dissertation describes a new approach that automatically builds human behavior models for simulated agents by observing human performance. The research described in this dissertation synergistically combines Context-Based Reasoning, a paradigm especially developed to model tactical human performance within simulated agents, with Genetic Programming, a machine learning algorithm to construct the behavior knowledge in accordance to the paradigm. This synergistic combination of well-documented AI methodologies has resulted in a new algorithm that effectively and automatically builds simulated agents with human behavior. This algorithm was tested extensively with five different simulated agents created by observing the performance of five humans driving an automobile simulator. The agents show not only the ability/capability to automatically learn and generalize the behavior of the human observed, but they also capture some of the personal behavior patterns observed among the five humans. Furthermore, the agents exhibited a performance that was at least as good as agents developed manually by a knowledgeable engineer.
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Date Issued: 2004
Identifier: CFE0000013, ucf:46068
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0000013

Title: IMAGE-BASED MATERIAL EDITING.
Creator: Khan, Erum, Reinhard, Erik, University of Central Florida
Abstract / Description: Photo editing software allows digital images to be blurred, warped or re-colored at the touch of a button. However, it is not currently possible to change the material appearance of an object except by painstakingly painting over the appropriate pixels. Here we present a set of methods for automatically replacing one material with another, completely different material, starting with only a single high dynamic range image, and an alpha matte specifying the object. Our approach exploits the...
Show morePhoto editing software allows digital images to be blurred, warped or re-colored at the touch of a button. However, it is not currently possible to change the material appearance of an object except by painstakingly painting over the appropriate pixels. Here we present a set of methods for automatically replacing one material with another, completely different material, starting with only a single high dynamic range image, and an alpha matte specifying the object. Our approach exploits the fact that human vision is surprisingly tolerant of certain (sometimes enormous) physical inaccuracies. Thus, it may be possible to produce a visually compelling illusion of material transformations, without fully reconstructing the lighting or geometry. We employ a range of algorithms depending on the target material. First, an approximate depth map is derived from the image intensities using bilateral filters. The resulting surface normals are then used to map data onto the surface of the object to specify its material appearance. To create transparent or translucent materials, the mapped data are derived from the object's background. To create textured materials, the mapped data are a texture map. The surface normals can also be used to apply arbitrary bidirectional reflectance distribution functions to the surface, allowing us to simulate a wide range of materials. To facilitate the process of material editing, we generate the HDR image with a novel algorithm, that is robust against noise in individual exposures. This ensures that any noise, which would possibly have affected the shape recovery of the objects adversely, will be removed. We also present an algorithm to automatically generate alpha mattes. This algorithm requires as input two images--one where the object is in focus, and one where the background is in focus--and then automatically produces an approximate matte, indicating which pixels belong to the object. The result is then improved by a second algorithm to generate an accurate alpha matte, which can be given as input to our material editing techniques.
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Date Issued: 2006
Identifier: CFE0001462, ucf:47065
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0001462

Title: PREDICTION AND ALLOCATION OF LIVE TO VIRTUAL COMMUNICATION BRIDGING RESOURCES.
Creator: lackey, stephanie, Malone, Linda, University of Central Florida
Abstract / Description: This document summarizes a research effort focused on improving live-to-virtual (L-V) communication systems. The purpose of this work is to address a significant challenge facing the tactical communications training community through the development of the Live-to-Virtual Relay Radio Prediction Algorithm and implementation of the algorithm into an Integrated Live-to-Virtual Communications Server prototype device. The motivation for the work and the challenges of integrating live and virtual...
Show moreThis document summarizes a research effort focused on improving live-to-virtual (L-V) communication systems. The purpose of this work is to address a significant challenge facing the tactical communications training community through the development of the Live-to-Virtual Relay Radio Prediction Algorithm and implementation of the algorithm into an Integrated Live-to-Virtual Communications Server prototype device. The motivation for the work and the challenges of integrating live and virtual communications are presented. Details surrounding the formulation of the prediction algorithm and a description of the prototype system, hardware, and software architectures are shared. Experimental results from discrete event simulation analysis and prototype functionality testing accompany recommendations for future investigation. If the methods and technologies summarized are implemented, an estimated equipment savings of 25%-53% and an estimated cost savings of $150,000.00 - $630,000.00 per site are anticipated. Thus, a solution to a critical tactical communications training problem is presented through the research discussed.
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Date Issued: 2006
Identifier: CFE0001401, ucf:47072
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0001401

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