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Pages
- Title
- CONTEXTUALIZING OBSERVATIONAL DATA FOR MODELING HUMAN PERFORMANCE.
- Creator
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Trinh, Viet, Gonzalez, Avelino, University of Central Florida
- Abstract / Description
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This research focuses on the ability to contextualize observed human behaviors in efforts to automate the process of tactical human performance modeling through learning from observations. This effort to contextualize human behavior is aimed at minimizing the role and involvement of the knowledge engineers required in building intelligent Context-based Reasoning (CxBR) agents. More specifically, the goal is to automatically discover the context in which a human actor is situated when...
Show moreThis research focuses on the ability to contextualize observed human behaviors in efforts to automate the process of tactical human performance modeling through learning from observations. This effort to contextualize human behavior is aimed at minimizing the role and involvement of the knowledge engineers required in building intelligent Context-based Reasoning (CxBR) agents. More specifically, the goal is to automatically discover the context in which a human actor is situated when performing a mission to facilitate the learning of such CxBR models. This research is derived from the contextualization problem left behind in Fernlund's research on using the Genetic Context Learner (GenCL) to model CxBR agents from observed human performance [Fernlund, 2004]. To accomplish the process of context discovery, this research proposes two contextualization algorithms: Contextualized Fuzzy ART (CFA) and Context Partitioning and Clustering (COPAC). The former is a more naive approach utilizing the well known Fuzzy ART strategy while the latter is a robust algorithm developed on the principles of CxBR. Using Fernlund's original five drivers, the CFA and COPAC algorithms were tested and evaluated on their ability to effectively contextualize each driver's individualized set of behaviors into well-formed and meaningful context bases as well as generating high-fidelity agents through the integration with Fernlund's GenCL algorithm. The resultant set of agents was able to capture and generalized each driver's individualized behaviors.
Show less - Date Issued
- 2009
- Identifier
- CFE0002563, ucf:48253
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0002563
- Title
- AN ADAPTIVE MODULAR REDUNDANCY TECHNIQUE TO SELF-REGULATE AVAILABILITY, AREA, AND ENERGY CONSUMPTION IN MISSION-CRITICAL APPLICATIONS.
- Creator
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Al-Haddad, Rawad, DeMara, Ronald, University of Central Florida
- Abstract / Description
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As reconfigurable devices' capacities and the complexity of applications that use them increase, the need for self-reliance of deployed systems becomes increasingly prominent. A Sustainable Modular Adaptive Redundancy Technique (SMART) composed of a dual-layered organic system is proposed, analyzed, implemented, and experimentally evaluated. SMART relies upon a variety of self-regulating properties to control availability, energy consumption, and area used, in dynamically-changing...
Show moreAs reconfigurable devices' capacities and the complexity of applications that use them increase, the need for self-reliance of deployed systems becomes increasingly prominent. A Sustainable Modular Adaptive Redundancy Technique (SMART) composed of a dual-layered organic system is proposed, analyzed, implemented, and experimentally evaluated. SMART relies upon a variety of self-regulating properties to control availability, energy consumption, and area used, in dynamically-changing environments that require high degree of adaptation. The hardware layer is implemented on a Xilinx Virtex-4 Field Programmable Gate Array (FPGA) to provide self-repair using a novel approach called a Reconfigurable Adaptive Redundancy System (RARS). The software layer supervises the organic activities within the FPGA and extends the self-healing capabilities through application-independent, intrinsic, evolutionary repair techniques to leverage the benefits of dynamic Partial Reconfiguration (PR). A SMART prototype is evaluated using a Sobel edge detection application. This prototype is shown to provide sustainability for stressful occurrences of transient and permanent fault injection procedures while still reducing energy consumption and area requirements. An Organic Genetic Algorithm (OGA) technique is shown capable of consistently repairing hard faults while maintaining correct edge detector outputs, by exploiting spatial redundancy in the reconfigurable hardware. A Monte Carlo driven Continuous Markov Time Chains (CTMC) simulation is conducted to compare SMART's availability to industry-standard Triple Modular Technique (TMR) techniques. Based on nine use cases, parameterized with realistic fault and repair rates acquired from publically available sources, the results indicate that availability is significantly enhanced by the adoption of fast repair techniques targeting aging-related hard-faults. Under harsh environments, SMART is shown to improve system availability from 36.02% with lengthy repair techniques to 98.84% with fast ones. This value increases to "five nines" (99.9998%) under relatively more favorable conditions. Lastly, SMART is compared to twenty eight standard TMR benchmarks that are generated by the widely-accepted BL-TMR tools. Results show that in seven out of nine use cases, SMART is the recommended technique, with power savings ranging from 22% to 29%, and area savings ranging from 17% to 24%, while still maintaining the same level of availability.
Show less - Date Issued
- 2011
- Identifier
- CFE0003993, ucf:48660
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0003993
- Title
- Optimal distribution network reconfiguration using meta-heuristic algorithms.
- Creator
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Asrari, Arash, Wu, Thomas, Lotfifard, Saeed, Haralambous, Michael, Atia, George, Pazour, Jennifer, University of Central Florida
- Abstract / Description
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Finding optimal configuration of power distribution systems topology is an NP-hard combinatorial optimization problem. It becomes more complex when time varying nature of loads in large-scale distribution systems is taken into account. In the second chapter of this dissertation, a systematic approach is proposed to tackle the computational burden of the procedure. To solve the optimization problem, a novel adaptive fuzzy based parallel genetic algorithm (GA) is proposed that employs the...
Show moreFinding optimal configuration of power distribution systems topology is an NP-hard combinatorial optimization problem. It becomes more complex when time varying nature of loads in large-scale distribution systems is taken into account. In the second chapter of this dissertation, a systematic approach is proposed to tackle the computational burden of the procedure. To solve the optimization problem, a novel adaptive fuzzy based parallel genetic algorithm (GA) is proposed that employs the concept of parallel computing in identifying the optimal configuration of the network. The integration of fuzzy logic into GA enhances the efficiency of the parallel GA by adaptively modifying the migration rates between different processors during the optimization process. A computationally efficient graph encoding method based on Dandelion coding strategy is developed which automatically generates radial topologies and prevents the construction of infeasible radial networks during the optimization process. The main shortcoming of the proposed algorithm in Chapter 2 is that it identifies only one single solution. It means that the system operator will not have any option but relying on the found solution. That is why a novel hybrid optimization algorithm is proposed in the third chapter of this dissertation that determines Pareto frontiers, as candidate solutions, for multi-objective distribution network reconfiguration problem. Implementing this model, the system operator will have more flexibility in choosing the best configuration among the alternative solutions. The proposed hybrid optimization algorithm combines the concept of fuzzy Pareto dominance (FPD) with shuffled frog leaping algorithm (SFLA) to recognize non-dominated suboptimal solutions identified by SFLA. The local search step of SFLA is also customized for power systems applications so that it automatically creates and analyzes only the feasible and radial configurations in its optimization procedure which significantly increases the convergence speed of the algorithm. In the fourth chapter, the problem of optimal network reconfiguration is solved for the case in which the system operator is going to employ an optimization algorithm that is automatically modifying its parameters during the optimization process. Defining three fuzzy functions, the probability of crossover and mutation will be adaptively tuned as the algorithm proceeds and the premature convergence will be avoided while the convergence speed of identifying the optimal configuration will not decrease. This modified genetic algorithm is considered a step towards making the parallel GA, presented in the second chapter of this dissertation, more robust in avoiding from getting stuck in local optimums. In the fifth chapter, the concentration will be on finding a potential smart grid solution to more high-quality suboptimal configurations of distribution networks. This chapter is considered an improvement for the third chapter of this dissertation for two reasons: (1) A fuzzy logic is used in the partitioning step of SFLA to improve the proposed optimization algorithm and to yield more accurate classification of frogs. (2) The problem of system reconfiguration is solved considering the presence of distributed generation (DG) units in the network. In order to study the new paradigm of integrating smart grids into power systems, it will be analyzed how the quality of suboptimal solutions can be affected when DG units are continuously added to the distribution network.The heuristic optimization algorithm which is proposed in Chapter 3 and is improved in Chapter 5 is implemented on a smaller case study in Chapter 6 to demonstrate that the identified solution through the optimization process is the same with the optimal solution found by an exhaustive search.
Show less - Date Issued
- 2015
- Identifier
- CFE0005575, ucf:50238
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005575
- Title
- Integrated Data Fusion and Mining (IDFM) Technique for Monitoring Water Quality in Large and Small Lakes.
- Creator
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Vannah, Benjamin, Chang, Ni-bin, Wanielista, Martin, Wang, Dingbao, University of Central Florida
- Abstract / Description
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Monitoring water quality on a near-real-time basis to address water resources management and public health concerns in coupled natural systems and the built environment is by no means an easy task. Furthermore, this emerging societal challenge will continue to grow, due to the ever-increasing anthropogenic impacts upon surface waters. For example, urban growth and agricultural operations have led to an influx of nutrients into surface waters stimulating harmful algal bloom formation, and...
Show moreMonitoring water quality on a near-real-time basis to address water resources management and public health concerns in coupled natural systems and the built environment is by no means an easy task. Furthermore, this emerging societal challenge will continue to grow, due to the ever-increasing anthropogenic impacts upon surface waters. For example, urban growth and agricultural operations have led to an influx of nutrients into surface waters stimulating harmful algal bloom formation, and stormwater runoff from urban areas contributes to the accumulation of total organic carbon (TOC) in surface waters. TOC in surface waters is a known precursor of disinfection byproducts in drinking water treatment, and microcystin is a potent hepatotoxin produced by the bacteria Microcystis, which can form expansive algal blooms in eutrophied lakes. Due to the ecological impacts and human health hazards posed by TOC and microcystin, it is imperative that municipal decision makers and water treatment plant operators are equipped with a rapid and economical means to track and measure these substances.Remote sensing is an emergent solution for monitoring and measuring changes to the earth's environment. This technology allows for large regions anywhere on the globe to be observed on a frequent basis. This study demonstrates the prototype of a near-real-time early warning system using Integrated Data Fusion and Mining (IDFM) techniques with the aid of both multispectral (Landsat and MODIS) and hyperspectral (MERIS) satellite sensors to determine spatiotemporal distributions of TOC and microcystin. Landsat satellite imageries have high spatial resolution, but such application suffers from a long overpass interval of 16 days. On the other hand, free coarse resolution sensors with daily revisit times, such as MODIS, are incapable of providing detailed water quality information because of low spatial resolution. This issue can be resolved by using data or sensor fusion techniques, an instrumental part of IDFM, in which the high spatial resolution of Landsat and the high temporal resolution of MODIS imageries are fused and analyzed by a suite of regression models to optimally produce synthetic images with both high spatial and temporal resolutions. The same techniques are applied to the hyperspectral sensor MERIS with the aid of the MODIS ocean color bands to generate fused images with enhanced spatial, temporal, and spectral properties. The performance of the data mining models derived using fused hyperspectral and fused multispectral data are quantified using four statistical indices. The second task compared traditional two-band models against more powerful data mining models for TOC and microcystin prediction. The use of IDFM is illustrated for monitoring microcystin concentrations in Lake Erie (large lake), and it is applied for TOC monitoring in Harsha Lake (small lake). Analysis confirmed that data mining methods excelled beyond two-band models at accurately estimating TOC and microcystin concentrations in lakes, and the more detailed spectral reflectance data offered by hyperspectral sensors produced a noticeable increase in accuracy for the retrieval of water quality parameters.
Show less - Date Issued
- 2013
- Identifier
- CFE0005066, ucf:49979
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005066
- Title
- Structural and Functional Studies of Glycine Riboswitches and Development of Fab Chaperone Assisted RNA Crystallography.
- Creator
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Sherman, Eileen, Ye, Jingdong, Kolpashchikov, Dmitry, Koculi, Eda, Harper, James, Self, William, University of Central Florida
- Abstract / Description
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The glycine riboswitch is a structured RNA found upstream of genes in mRNA transcripts in many bacteria, functioning as a biofeedback gene regulator. Upon binding glycine, a complete RNA transcript including gene sequences is transcribed, effectively turning on gene expression. In an effort to understand the intricacies of its functioning, many mutants of the riboswitch were made and characterized during Ph. D. work, resulting in discovery of a P0 duplex/kink-turn motif involving a few...
Show moreThe glycine riboswitch is a structured RNA found upstream of genes in mRNA transcripts in many bacteria, functioning as a biofeedback gene regulator. Upon binding glycine, a complete RNA transcript including gene sequences is transcribed, effectively turning on gene expression. In an effort to understand the intricacies of its functioning, many mutants of the riboswitch were made and characterized during Ph. D. work, resulting in discovery of a P0 duplex/kink-turn motif involving a few nucleotides upstream of the established glycine riboswitch sequence which changed its ligand binding characteristics (Chapter 1). Previously, the two aptamers of the riboswitch were thought to cooperatively bind glycine, but with the inclusion of this leader sequence which forms a kink turn motif with the linker between the two aptamers, glycine binding in one aptamer no longer requires glycine binding in the other. Furthermore, the Kd from three species tested are now a similar, lower value of about 5 (&)#181;M, indicating authenticity of this new consensus sequence. Glycine binding and interaptamer interaction both enhanced one another in trans aptamer assays. Another discovery from this was a shortened construct including all of aptamer II but only part of aptamer I in which a few specific nucleotides prevented glycine binding in aptamer II (Chapter 2). This may provide insight into the nature of interaptamer interactions in the full switch; addition of an oligonucleotide complimentary to these nucleotides restored glycine binding ability to aptamer II. With future development, this could also be a useful molecular biology tool, using two signals, glycine and an oligonucleotide, to allow gene expression.To precisely understand how any macromolecule functions, a 3D structure, obtainable by x-ray crystallography, is vital. A new technique to accomplish that for RNA, precedented in the protein world, is Fab chaperoned crystallography, which has advantages compared to RNA alone. A phage displayed library of Fabs with reduced codon diversity designed for RNA was created, the YSGR Min library (Chapter 3). Its Fabs had specificities and affinities equal to or greater than previous libraries which were originally created for phage displayed selection against proteins. Fab chaperoned RNA crystallography is currently in progress for the glycine riboswitch; the best resolution thus far is 5.3 (&)#197; (Chapter 4). In addition to providing molecular insight into its gene regulation mechanism, a structure of the glycine riboswitch could be applied for use in structure based drug design of novel antibiotics targeting the riboswitch to disrupt important downstream carbon cycle genes in pathogenic bacteria.
Show less - Date Issued
- 2014
- Identifier
- CFE0005549, ucf:50285
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005549
- Title
- Investigation of Novel Fin Structures Enhancing Micro Heat Sink Thermal Performance.
- Creator
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Ismayilov, Fuad, Peles, Yoav, Kassab, Alain, Putnam, Shawn, Akturk, Ali, University of Central Florida
- Abstract / Description
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Operating temperature in electronics applications is continuously increasing. Therefore, for the past few decades, high heat flux removing micro heat sinks are investigated in terms of heat transfer effectiveness. This study generally concentrates on improving the passive heat transfer techniques. Micro heat sinks used in experiments are fabricated using MEMS techniques. Resistance temperature detectors, RTDs, were used for temperature measurements. The experimental data was obtained for...
Show moreOperating temperature in electronics applications is continuously increasing. Therefore, for the past few decades, high heat flux removing micro heat sinks are investigated in terms of heat transfer effectiveness. This study generally concentrates on improving the passive heat transfer techniques. Micro heat sinks used in experiments are fabricated using MEMS techniques. Resistance temperature detectors, RTDs, were used for temperature measurements. The experimental data was obtained for single and two phase flow regions; however, only single phase flow results were considered in numerical simulations. Numerical validations were performed on the micro heat sinks, including cylinder and hydrofoil shaped pin fins. Following the validation phase, optimization has been performed to further improve the hydraulic and thermal performance. DOE study showed that the chord length and leading edge size of the hydrofoil pin fin are significant contributors to the thermal performance. The ranges of geometrical variables were identified and fed into multi-objective optimization cycles implementing the multi-objective genetic algorithm. The optimization objectives were to minimize pumping requirements while enhancing the local and global heat transfer effectiveness over the surface of the heater in single phase flow environment. A broad range of geometries were obtained with an acceptable tradeoff between thermal and hydraulic performance for low Reynolds number. Additionally, tandem geometries were investigated and showed that higher heat transfer effectiveness could be obtained with acceptable pumping power requirements. The importance of such optimization studies before the experimental testing is highlighted, and novel geometries are presented for further experimental investigations. Thermal performance improvement of 28% was obtained via implementing proposed geometries with only a 12% pressure drop increase. Local heat transfer optimization, aiming to decrease the local temperatures were also performed using doublet pin fin configurations. Results showed that tandem hydrofoils could control the flow with minimum pressure drops while reaching the desired low local temperatures.
Show less - Date Issued
- 2019
- Identifier
- CFE0007821, ucf:52828
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007821
- Title
- Genetic Engineering as Literary Praxis: A Study in Contemporary Literature.
- Creator
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Evans, Taylor, Campbell, James, Oliver, Kathleen, Murphy, Patrick, University of Central Florida
- Abstract / Description
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This thesis considers the understudied issue of genetic engineering as it has been deployed in the literature of the late 20th century. With reference to the concept of the enlightened gender hybridity of Cyborg theory and an eye to ecocritical implications, I read four texts: Joan Slonczewski's 1986 science fiction novel A Door Into Ocean, Octavia Butler's science fiction trilogy Lilith's Brood (-) originally released between 1987 and 1989 as Xenogenesis (-) Simon Mawer's 1997 literary novel...
Show moreThis thesis considers the understudied issue of genetic engineering as it has been deployed in the literature of the late 20th century. With reference to the concept of the enlightened gender hybridity of Cyborg theory and an eye to ecocritical implications, I read four texts: Joan Slonczewski's 1986 science fiction novel A Door Into Ocean, Octavia Butler's science fiction trilogy Lilith's Brood (-) originally released between 1987 and 1989 as Xenogenesis (-) Simon Mawer's 1997 literary novel Mendel's Dwarf, and the first two books in Margaret Atwood's speculative fiction MaddAddam series: 2003's Oryx and Crake and 2009's The Year Of the Flood. I argue that the inclusion of genetic engineering has changed as the technology moves from science fiction to science fact, moving from the fantastic to the mundane. Throughout its recent literary history, genetic engineering has played a role in complicating questions of sexuality, paternity, and the division between nature and culture. It has also come to represent a nexus of potential cultural change, one which stands to fulfill the dramatic hybridity Haraway rhapsodized in her (")Cyborg Manifesto(") while also containing the potential to disrupt the ecocritical conversation by destroying what we used to understand as nature. Despite their four different takes on the issue, each of the texts I read offers a complex vision of utopian hopes and apocalyptic fears. They agree that, for better or for worse, genetic engineering is forever changing both our world and ourselves.
Show less - Date Issued
- 2012
- Identifier
- CFE0004373, ucf:49438
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004373
- Title
- Adaptive Architectural Strategies for Resilient Energy-Aware Computing.
- Creator
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Ashraf, Rizwan, DeMara, Ronald, Lin, Mingjie, Wang, Jun, Jha, Sumit, Johnson, Mark, University of Central Florida
- Abstract / Description
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Reconfigurable logic or Field-Programmable Gate Array (FPGA) devices have the ability to dynamically adapt the computational circuit based on user-specified or operating-condition requirements. Such hardware platforms are utilized in this dissertation to develop adaptive techniques for achieving reliable and sustainable operation while autonomously meeting these requirements. In particular, the properties of resource uniformity and in-field reconfiguration via on-chip processors are exploited...
Show moreReconfigurable logic or Field-Programmable Gate Array (FPGA) devices have the ability to dynamically adapt the computational circuit based on user-specified or operating-condition requirements. Such hardware platforms are utilized in this dissertation to develop adaptive techniques for achieving reliable and sustainable operation while autonomously meeting these requirements. In particular, the properties of resource uniformity and in-field reconfiguration via on-chip processors are exploited to implement Evolvable Hardware (EHW). EHW utilize genetic algorithms to realize logic circuits at runtime, as directed by the objective function. However, the size of problems solved using EHW as compared with traditional approaches has been limited to relatively compact circuits. This is due to the increase in complexity of the genetic algorithm with increase in circuit size. To address this research challenge of scalability, the Netlist-Driven Evolutionary Refurbishment (NDER) technique was designed and implemented herein to enable on-the-fly permanent fault mitigation in FPGA circuits. NDER has been shown to achieve refurbishment of relatively large sized benchmark circuits as compared to related works. Additionally, Design Diversity (DD) techniques which are used to aid such evolutionary refurbishment techniques are also proposed and the efficacy of various DD techniques is quantified and evaluated.Similarly, there exists a growing need for adaptable logic datapaths in custom-designed nanometer-scale ICs, for ensuring operational reliability in the presence of Process, Voltage, and Temperature (PVT) and, transistor-aging variations owing to decreased feature sizes for electronic devices. Without such adaptability, excessive design guardbands are required to maintain the desired integration and performance levels. To address these challenges, the circuit-level technique of Self-Recovery Enabled Logic (SREL) was designed herein. At design-time, vulnerable portions of the circuit identified using conventional Electronic Design Automation tools are replicated to provide post-fabrication adaptability via intelligent techniques. In-situ timing sensors are utilized in a feedback loop to activate suitable datapaths based on current conditions that optimize performance and energy consumption. Primarily, SREL is able to mitigate the timing degradations caused due to transistor aging effects in sub-micron devices by reducing the stress induced on active elements by utilizing power-gating. As a result, fewer guardbands need to be included to achieve comparable performance levels which leads to considerable energy savings over the operational lifetime.The need for energy-efficient operation in current computing systems has given rise to Near-Threshold Computing as opposed to the conventional approach of operating devices at nominal voltage. In particular, the goal of exascale computing initiative in High Performance Computing (HPC) is to achieve 1 EFLOPS under the power budget of 20MW. However, it comes at the cost of increased reliability concerns, such as the increase in performance variations and soft errors. This has given rise to increased resiliency requirements for HPC applications in terms of ensuring functionality within given error thresholds while operating at lower voltages. My dissertation research devised techniques and tools to quantify the effects of radiation-induced transient faults in distributed applications on large-scale systems. A combination of compiler-level code transformation and instrumentation are employed for runtime monitoring to assess the speed and depth of application state corruption as a result of fault injection. Finally, fault propagation models are derived for each HPC application that can be used to estimate the number of corrupted memory locations at runtime. Additionally, the tradeoffs between performance and vulnerability and the causal relations between compiler optimization and application vulnerability are investigated.
Show less - Date Issued
- 2015
- Identifier
- CFE0006206, ucf:52889
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006206
