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- Title
- THE EFFECT OF FREE CHLORINE AND CHLORAMINES ON LEAD RELEASE IN A DISTRIBUTION SYSTEM.
- Creator
-
Vasquez, Ferdinand, Taylor, James, University of Central Florida
- Abstract / Description
-
Total lead release in drinking water in the presence of free chlorine and chloramine residuals was investigated in field, laboratory and fundamental investigations for finished waters produced from ground (GW), surface (SW), saline (RO) and blended (B) sources. Field investigations found more total lead was released in the presence of chloramines than in the presence of free chlorine for RO and blended finished waters; however, there were no statistical differences in total lead release to...
Show moreTotal lead release in drinking water in the presence of free chlorine and chloramine residuals was investigated in field, laboratory and fundamental investigations for finished waters produced from ground (GW), surface (SW), saline (RO) and blended (B) sources. Field investigations found more total lead was released in the presence of chloramines than in the presence of free chlorine for RO and blended finished waters; however, there were no statistical differences in total lead release to finished GW and SW. Laboratory measurements of finished waters oxidation-reduction potential (ORP) were equivalent by source and were not affected by the addition of more than 100 mg/L of sulfates or chlorides, but were significantly higher in the presence of free chlorine relative to chloramines. Development of Pourbaix diagrams revealed the PbO2 was the controlling solid phase at the higher ORP in the presence of free chlorine and Pb3(CO3)2(OH)2(s) (hydrocerussite) was the controlling solid phase in the presence of chloramines at the lower ORP, which mechanistically accounted for the observed release of total lead as PbO2 is much less soluble than hydrocerussite. The lack of differences in total lead release to finished GW and SW was attributed to differences in water quality and intermittent behavior of particulate release from controlling solid films.
Show less - Date Issued
- 2005
- Identifier
- CFE0000533, ucf:46427
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0000533
- Title
- DATA BANDWIDTH REDUCTION TECHNIQUES FOR DISTRIBUTED EMBEDDED SIMULATION USING CONCURRENT BEHAVIOR MODELS.
- Creator
-
Bahr, Hubert, DeMara, Ronald, University of Central Florida
- Abstract / Description
-
Maintaining coherence between the independent views of multiple participants at distributed locations is essential in an Embedded Simulation environment. Currently, the Distributed Interactive Simulation (DIS) protocol maintains coherence by broadcasting the entity state streams from each simulation station. In this dissertation, a novel alternative to DIS that replaces the transmitting sources with local sources is developed, validated, and assessed by analytical and experimental means. The...
Show moreMaintaining coherence between the independent views of multiple participants at distributed locations is essential in an Embedded Simulation environment. Currently, the Distributed Interactive Simulation (DIS) protocol maintains coherence by broadcasting the entity state streams from each simulation station. In this dissertation, a novel alternative to DIS that replaces the transmitting sources with local sources is developed, validated, and assessed by analytical and experimental means. The proposed Concurrent Model approach reduces the communication burden to transmission of only synchronization and model-update messages. Necessary and sufficient conditions for the correctness of Concurrent Models in a discrete event simulation environment are established by developing Behavioral Congruence ¨B(EL, ER) and Temporal Congruence ¨T(t, ER) functions. They indicate model discrepancies with respect to the simulation time t, and the local and remote entity state streams EL and ER, respectively. Performance benefits were quantified in terms of the bandwidth reduction ratio BR=N/I obtained from the comparison of the OneSAF Testbed Semi-Automated Forces (OTBSAF) simulator under DIS requiring a total of N bits and a testbed modified for the Concurrent Model approach which required I bits. In the experiments conducted, a range of 100 d BR d 294 was obtained representing two orders of magnitude reduction in simulation traffic. Investigation showed that the models rely heavily on the priority data structure of the discrete event simulation and that performance of the overall simulation can be enhanced by an additional 6% by improving the queue management. A low run-time overhead, self-adapting storage policy called the Smart Priority Queue (SPQ) was developed and evaluated within the Concurrent Model. The proposed SPQ policies employ a lowcomplexity linear queue for near head activities and a rapid-indexing variable binwidth calendar queue for distant events. The SPQ configuration is determined by monitoring queue access behavior using cost scoring factors and then applying heuristics to adjust the organization of the underlying data structures. Results indicate that optimizing storage to the spatial distribution of queue access can decrease HOLD operation cost between 25% and 250% over existing algorithms such as calendar queues. Taken together, these techniques provide an entity state generation mechanism capable of overcoming the challenges of Embedded Simulation in harsh mobile communications environments with restricted bandwidth, increased message latency, and extended message drop-outs.
Show less - Date Issued
- 2004
- Identifier
- CFE0000198, ucf:46166
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0000198
- Title
- EXAMINING SOCIAL LOAFING WITHIN VIRTUAL TEAMS: THE MODERATING INFLUENCE OF A TEAM'S COLLECTIVE ORIENTATION.
- Creator
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Cotter, Seth, Salas, Eduardo, University of Central Florida
- Abstract / Description
-
Social loafing is a growing concern for modern organizations. With advancement in computer technology, virtual tools are used more frequently to communicate, which may allow social loafing to occur in new and unfamiliar forms. The intent of this thesis is to examine social loafing through the use of virtual tools, and to analyze whether collective orientation has a moderating influence on the relationship between social loafing and virtuality. 30 teams, each containing four participants, were...
Show moreSocial loafing is a growing concern for modern organizations. With advancement in computer technology, virtual tools are used more frequently to communicate, which may allow social loafing to occur in new and unfamiliar forms. The intent of this thesis is to examine social loafing through the use of virtual tools, and to analyze whether collective orientation has a moderating influence on the relationship between social loafing and virtuality. 30 teams, each containing four participants, were randomly assigned to a condition of virtuality (i.e., instant messaging or videoconferencing). Participants then completed a computer simulation task in which social loafing, collective orientation of the team, and team performance were measured.
Show less - Date Issued
- 2013
- Identifier
- CFH0004376, ucf:45013
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFH0004376
- Title
- IMPACT OF CORROSION INHIBITOR BLENDED ORTHOPHOSPHATE ON WATER QUALITY IN WATER DISTRIBUTION SYSTEMS.
- Creator
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Alshehri, Abdulrahman, Taylor, James, University of Central Florida
- Abstract / Description
-
The impact of blended orthophosphate (BOP) inhibitor addition on the corrosion of iron, copper, and lead in drinking water distribution systems was studied under changing water quality environment. Release of iron, copper, and lead were monitored at varying inhibitor doses and changing blends of source waters (groundwater, surface water, and desalinated water). Solid corrosion products on pipe surfaces under BOP treatment were evaluated with surface characterization techniques. Performance of...
Show moreThe impact of blended orthophosphate (BOP) inhibitor addition on the corrosion of iron, copper, and lead in drinking water distribution systems was studied under changing water quality environment. Release of iron, copper, and lead were monitored at varying inhibitor doses and changing blends of source waters (groundwater, surface water, and desalinated water). Solid corrosion products on pipe surfaces under BOP treatment were evaluated with surface characterization techniques. Performance of the BOP inhibitor was compared to other corrosion control strategies. Iron scales for iron and galvanized steel coupons incubated in different blended waters in the presence of BOP inhibitor were analyzed by X-ray Photoelectron Spectroscopy (XPS) for surface composition. Identified iron corrosion products were ferric oxide (Fe2O3), magnetite (Fe3O4), and hydrated ferric oxide (FeOOH), in addition to ferric phosphate (FePO4) on coupons exposed to BOP inhibitor. Variations of water quality did not significantly affect the distribution of solid iron forms on surface films. Thermodynamic modeling indicated siderite (FeCO3) was the controlling solid phase of iron release. XPS indicated addition of BOP inhibitor produced a solid phosphate film in the iron scale which could inhibit iron release. Impact of BOP, orthophosphate, and pH adjustment on iron release in a distribution system was examined. Iron release was sensitive to water quality variations (alkalinity and chloride) associated with source and blends of finished water. Finished waters with high alkalinity content (between 149 and 164 mg/L as CaCO3) consistently mitigated iron release regardless of inhibitor use. Dissolved iron constituted about 10% of total iron release. Empirical models were developed that related water quality, inhibitor type and dose to iron release. The BOP inhibitor minimized total iron release followed closely by increasing pH (between 7.9 and 8.1), while orthophosphate dose did not affect iron release. Temperature (ranged from 21.2 to 25.3) had limited influence on iron release with BOP treatment. Monitoring copper release showed that dissolved copper was the dominant form in the effluent, at about 88%. BOP inhibitor doses of 0.5 to 2.0 mg/L proved beneficial in controlling copper concentrations to an average of below 0.5 mg/L. Control of copper release improved with increasing BOP dose, despite changes in alkalinity. Elevation of pH by 0.3 unit beyond pHs (between 7.9 and 8.1) resulted in noticeable decrease in copper concentrations of about 30%, but was more sensitive to higher alkalinity (146 to 151 mg/L as CaCO3) than BOP treatment. Developed empirical models confirmed the importance of BOP inhibitor dose, pH increase, and alkalinity content on copper release. Statistical comparison of the corrosion control strategies proved the advantage of BOP inhibitor, at all doses, over pH elevation in controlling copper release. The BOP inhibitor mitigated lead release below action level, and consistently outperformed pH elevation, in all water quality conditions. XPS analysis identified lead dioxide (PbO2), lead oxide (PbO), cerussite (PbCO3), and hydrocerussite (Pb3(CO3)2(OH)2) as the corrosion products in the scale of lead/tin coupons exposed to BOP inhibitor. XPS and Scanning Electron Microscopy (SEM) analysis suggested cerussite or hydrocerussite is the controlling solid phase of lead release. Thermodynamic models for cerussite and hydrocerussite grossly over predicted actual concentrations. Solubility and equilibrium relationships suggested the possibility of a lead orthophosphate solid that would describe the effectiveness of BOP inhibitor, although no lead-phosphate solid was detected by surface analysis. BOP inhibitor appeared to have mitigated lead release by forming a surface film between lead scale and the bulk water.
Show less - Date Issued
- 2008
- Identifier
- CFE0002229, ucf:47922
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0002229
- Title
- AN ARCHITECTURE FOR HIGH-PERFORMANCE PRIVACY-PRESERVING AND DISTRIBUTED DATA MINING.
- Creator
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Secretan, James, Georgiopoulos, Michael, University of Central Florida
- Abstract / Description
-
This dissertation discusses the development of an architecture and associated techniques to support Privacy Preserving and Distributed Data Mining. The field of Distributed Data Mining (DDM) attempts to solve the challenges inherent in coordinating data mining tasks with databases that are geographically distributed, through the application of parallel algorithms and grid computing concepts. The closely related field of Privacy Preserving Data Mining (PPDM) adds the dimension of privacy to...
Show moreThis dissertation discusses the development of an architecture and associated techniques to support Privacy Preserving and Distributed Data Mining. The field of Distributed Data Mining (DDM) attempts to solve the challenges inherent in coordinating data mining tasks with databases that are geographically distributed, through the application of parallel algorithms and grid computing concepts. The closely related field of Privacy Preserving Data Mining (PPDM) adds the dimension of privacy to the problem, trying to find ways that organizations can collaborate to mine their databases collectively, while at the same time preserving the privacy of their records. Developing data mining algorithms for DDM and PPDM environments can be difficult and there is little software to support it. In addition, because these tasks can be computationally demanding, taking hours of even days to complete data mining tasks, organizations should be able to take advantage of high-performance and parallel computing to accelerate these tasks. Unfortunately there is no such framework that is able to provide all of these services easily for a developer. In this dissertation such a framework is developed to support the creation and execution of DDM and PPDM applications, called APHID (Architecture for Private, High-performance Integrated Data mining). The architecture allows users to flexibly and seamlessly integrate cluster and grid resources into their DDM and PPDM applications. The architecture is scalable, and is split into highly de-coupled services to ensure flexibility and extensibility. This dissertation first develops a comprehensive example algorithm, a privacy-preserving Probabilistic Neural Network (PNN), which serves a basis for analysis of the difficulties of DDM/PPDM development. The privacy-preserving PNN is the first such PNN in the literature, and provides not only a practical algorithm ready for use in privacy-preserving applications, but also a template for other data intensive algorithms, and a starting point for analyzing APHID's architectural needs. After analyzing the difficulties in the PNN algorithm's development, as well as the shortcomings of researched systems, this dissertation presents the first concrete programming model joining high performance computing resources with a privacy preserving data mining process. Unlike many of the existing PPDM development models, the platform of services is language independent, allowing layers and algorithms to be implemented in popular languages (Java, C++, Python, etc.). An implementation of a PPDM algorithm is developed in Java utilizing the new framework. Performance results are presented, showing that APHID can enable highly simplified PPDM development while speeding up resource intensive parts of the algorithm.
Show less - Date Issued
- 2009
- Identifier
- CFE0002853, ucf:48076
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0002853
- Title
- SCHEDULING AND RESOURCE MANAGEMENT FOR COMPLEX SYSTEMS: FROM LARGE-SCALE DISTRIBUTED SYSTEMS TO VERY LARGE SENSOR NETWORKS.
- Creator
-
Yu, Chen, Marinescu, Dan, University of Central Florida
- Abstract / Description
-
In this dissertation, we focus on multiple levels of optimized resource management techniques. We first consider a classic resource management problem, namely the scheduling of data-intensive applications. We define the Divisible Load Scheduling (DLS) problem, outline the system model based on the assumption that data staging and all communication with the sites can be done in parallel, and introduce a set of optimal divisible load scheduling algorithms and the related fault-tolerant...
Show moreIn this dissertation, we focus on multiple levels of optimized resource management techniques. We first consider a classic resource management problem, namely the scheduling of data-intensive applications. We define the Divisible Load Scheduling (DLS) problem, outline the system model based on the assumption that data staging and all communication with the sites can be done in parallel, and introduce a set of optimal divisible load scheduling algorithms and the related fault-tolerant coordination algorithm. The DLS algorithms introduced in this dissertation exploit parallel communication, consider realistic scenarios regarding the time when heterogeneous computing systems are available, and generate optimal schedules. Performance studies show that these algorithms perform better than divisible load scheduling algorithms based upon sequential communication. We have developed a self-organization model for resource management in distributed systems consisting of a very large number of sites with excess computing capacity. This self-organization model is inspired by biological metaphors and uses the concept of varying energy levels to express activity and goal satisfaction. The model is applied to Pleiades, a service-oriented architecture based on resource virtualization. The self-organization model for complex computing and communication systems is applied to Very Large Sensor Networks (VLSNs). An algorithm for self-organization of anonymous sensor nodes called SFSN (Scale-free Sensor Networks) and an algorithm utilizing the Small-worlds principle called SWAS (Small-worlds of Anonymous Sensors) are introduced. The SFSN algorithm is designed for VLSNs consisting of a fairly large number of inexpensive sensors with limited resources. An important feature of the algorithm is the ability to interconnect sensors without an identity, or physical address used by traditional communication and coordination protocols. During the self-organization phase, the collision-free communication channels allowing a sensor to synchronously forward information to the members of its proximity set are established and the communication pattern is followed during the activity phases. Simulation study shows that the SFSN ensures the scalability, limits the amount of communication and the complexity of coordination. The SWAS algorithm is further improved from SFSN by applying the Small-worlds principle. It is unique in its ability to create a sensor network with a topology approximating small-world networks. Rather than creating shortcuts between pairs of diametrically positioned nodes in a logical ring, we end up with something resembling a double-stranded DNA. By exploiting Small-worlds principle we combine two desirable features of networks, namely high clustering and small path length.
Show less - Date Issued
- 2009
- Identifier
- CFE0002907, ucf:48004
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0002907
- Title
- EFFECTS OF ORTHOPHOSPHATE CORROSION INHIBITOR IN BLENDED WATER QUALITY ENVIRONMENTS.
- Creator
-
Stone, Erica, Duranceau, Steven, University of Central Florida
- Abstract / Description
-
This study evaluated the effects of orthophosphate (OP) inhibitor addition on iron, copper, and lead corrosion on coupons exposed to different blends of groundwater, surface water, and desalinated seawater. The effectiveness of OP inhibitor addition on iron, copper, and lead release was analyzed by statistical comparison between OP treated and untreated pilot distribution systems (PDS). Four different doses of OP inhibitor, ranging from zero (control) to 2 mg/L as P, were investigated and non...
Show moreThis study evaluated the effects of orthophosphate (OP) inhibitor addition on iron, copper, and lead corrosion on coupons exposed to different blends of groundwater, surface water, and desalinated seawater. The effectiveness of OP inhibitor addition on iron, copper, and lead release was analyzed by statistical comparison between OP treated and untreated pilot distribution systems (PDS). Four different doses of OP inhibitor, ranging from zero (control) to 2 mg/L as P, were investigated and non-linear empirical models were developed to predict iron, copper, and lead release from the water quality and OP doses. Surface characterization evaluations were conducted using X-ray Photoelectron Spectroscopy (XPS) analyses for each iron, galvanized steel, copper, and lead/tin coupon tested. Also, a theoretical thermodynamic model was developed and used to validate the controlling solid phases determined by XPS. A comparison of the effects of phosphate-based corrosion inhibitor addition on iron, copper, and lead release from the PDSs exposed to the different blends was also conducted. Three phosphate-based corrosion inhibitors were employed; blended orthophosphate (BOP), orthophosphate (OP), and zinc orthophosphate (ZOP). Non-linear empirical models were developed to predict iron, copper, and lead release from each PDS treated with different doses of inhibitor ranging from zero (control) to 2 mg/L as P. The predictive models were developed using water quality parameters as well as the inhibitor dose. Using these empirical models, simulation of the water quality of different blends with varying alkalinity and pH were used to compare the inhibitors performance for remaining in compliance for iron, copper and lead release. OP inhibitor addition was found to offer limited improvement of iron release for the OP dosages evaluated for the water blends evaluated compared to pH adjustment alone. Empirical models showed increased total phosphorus, pH, and alkalinity reduced iron release while increased silica, chloride, sulfate, and temperature contributed to iron release. Thermodynamic modeling suggested that FePO4 is the controlling solid that forms on iron and galvanized steel surfaces, regardless of blend, when OP inhibitor is added for corrosion control. While FePO4 does not offer much control of the iron release from the cast iron surfaces, it does offer protection of the galvanized steel surfaces reducing zinc release. OP inhibitor addition was found to reduce copper release for the OP dosages evaluated for the water blends evaluated compared to pH adjustment alone. Empirical models showed increases in total phosphorus, silica, and pH reduced copper release while increased alkalinity and chloride contributed to copper release. Thermodynamic modeling suggested that Cu3(PO4)2•2H2O is the controlling solid that forms on copper surfaces, regardless of blend, when OP inhibitor is added for corrosion control. OP inhibitor addition was found to reduce lead release for the OP dosages evaluated for the water blends evaluated compared to pH adjustment alone. Empirical models showed increased total phosphorus and pH reduced lead release while increased alkalinity, chloride, and temperature contributed to lead release. Thermodynamic modeling suggested that hydroxypyromorphite is the controlling solid that forms on lead surfaces, regardless of blend, when OP inhibitor is added for corrosion control. The comparison of phosphate-based inhibitors found increasing pH to reduce iron, copper, and lead metal release, while increasing alkalinity was shown to reduce iron release but increase copper and lead release. The ZOP inhibitor was not predicted by the empirical models to perform as well as BOP and OP at the low dose of 0.5 mg/L as P for iron control, and the OP inhibitor was not predicted to perform as well as BOP and ZOP at the low dose of 0.5 mg/L as P for lead control. The three inhibitors evaluated performed similarly for copper control. Therefore, BOP inhibitor showed the lowest metal release at the low dose of 0.5 mg/L as P for control of iron, copper, and lead corrosion.
Show less - Date Issued
- 2008
- Identifier
- CFE0002382, ucf:47760
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0002382
- Title
- REMOTE SENSING WITH COMPUTATIONAL INTELLIGENCE MODELLING FOR MONITORING THE ECOSYSTEM STATE AND HYDRAULIC PATTERN IN A CONSTRUCTED WETLAND.
- Creator
-
Mohiuddin, Golam, Chang, Ni-bin, Lee, Woo Hyoung, Wanielista, Martin, University of Central Florida
- Abstract / Description
-
Monitoring the heterogeneous aquatic environment such as the Stormwater Treatment Areas (STAs) located at the northeast of the Everglades is extremely important in understanding the land processes of the constructed wetland in its capacity to remove nutrient. Direct monitoring and measurements of ecosystem evolution and changing velocities at every single part of the STA are not always feasible. Integrated remote sensing, monitoring, and modeling technique can be a state-of-the-art tool to...
Show moreMonitoring the heterogeneous aquatic environment such as the Stormwater Treatment Areas (STAs) located at the northeast of the Everglades is extremely important in understanding the land processes of the constructed wetland in its capacity to remove nutrient. Direct monitoring and measurements of ecosystem evolution and changing velocities at every single part of the STA are not always feasible. Integrated remote sensing, monitoring, and modeling technique can be a state-of-the-art tool to estimate the spatial and temporal distributions of flow velocity regimes and ecological functioning in such dynamic aquatic environments. In this presentation, comparison between four computational intelligence models including Extreme Learning Machine (ELM), Genetic Programming (GP) and Artificial Neural Network (ANN) models were organized to holistically assess the flow velocity and direction as well as ecosystem states within a vegetative wetland area. First the local sensor network was established using Acoustic Doppler Velocimeter (ADV). Utilizing the local sensor data along with the help of external driving forces parameters, trained models of ELM, GP and ANN were developed, calibrated, validated, and compared to select the best computational capacity of velocity prediction over time. Besides, seasonal images collected by French satellite Pleiades have been analyzed to address the seasonality effect of plant species evolution and biomass changes in the constructed wetland. The key finding of this research is to characterize the interactions between geophysical and geochemical processes in this wetland system based on ground-based monitoring sensors and satellite images to discover insight of hydraulic residence time, plant species variation, and water quality and improve the overall understanding of possible nutrient removal in this constructed wetland.
Show less - Date Issued
- 2014
- Identifier
- CFE0005533, ucf:52864
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005533
- Title
- Decision-making for Vehicle Path Planning.
- Creator
-
Xu, Jun, Turgut, Damla, Zhang, Shaojie, Zhang, Wei, Hasan, Samiul, University of Central Florida
- Abstract / Description
-
This dissertation presents novel algorithms for vehicle path planning in scenarios where the environment changes. In these dynamic scenarios the path of the vehicle needs to adapt to changes in the real world. In these scenarios, higher performance paths can be achieved if we are able to predict the future state of the world, by learning the way it evolves from historical data. We are relying on recent advances in the field of deep learning and reinforcement learning to learn appropriate...
Show moreThis dissertation presents novel algorithms for vehicle path planning in scenarios where the environment changes. In these dynamic scenarios the path of the vehicle needs to adapt to changes in the real world. In these scenarios, higher performance paths can be achieved if we are able to predict the future state of the world, by learning the way it evolves from historical data. We are relying on recent advances in the field of deep learning and reinforcement learning to learn appropriate world models and path planning behaviors.There are many different practical applications that map to this model. In this dissertation we propose algorithms for two applications that are very different in domain but share important formal similarities: the scheduling of taxi services in a large city and tracking wild animals with an unmanned aerial vehicle.The first application models a centralized taxi dispatch center in a big city. It is a multivariate optimization problem for taxi time scheduling and path planning. The first goal here is to balance the taxi service demand and supply ratio in the city. The second goal is to minimize passenger waiting time and taxi idle driving distance. We design different learning models that capture taxi demand and destination distribution patterns from historical taxi data. The predictions are evaluated with real-world taxi trip records. The predicted taxi demand and destination is used to build a taxi dispatch model. The taxi assignment and re-balance is optimized by solving a Mixed Integer Programming (MIP) problem.The second application concerns animal monitoring using an unmanned aerial vehicle (UAV) to search and track wild animals in a large geographic area. We propose two different path planing approaches for the UAV. The first one is based on the UAV controller solving Markov decision process (MDP). The second algorithms relies on the past recorded animal appearances. We designed a learning model that captures animal appearance patterns and predicts the distribution of future animal appearances. We compare the proposed path planning approaches with traditional methods and evaluated them in terms of collected value of information (VoI), message delay and percentage of events collected.
Show less - Date Issued
- 2019
- Identifier
- CFE0007557, ucf:52606
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007557
- Title
- INNERVATION, DISTRIBUTION AND MORPHOLOGY OF CALCITONIN GENE RELATED PEPTIDE AND SUBSTANCE P IMMUNOREACTIVE AXONS IN THE WHOLE-MOUNT ATRIA OF FVB MICE.
- Creator
-
Li, Liang, Cheng, Zixi, University of Central Florida
- Abstract / Description
-
Degeneration of nociceptive afferent axons and terminals in the heart is associated with painless sudden cardiac death. However, innervation, distribution and morphological structures of sympathetic cardiac nociceptive afferent axons and terminals have not yet been fully characterized. The aim of the present study is to characterize the density, arrangement, and structural features of differentiated sympathetic afferent axons and terminals in whole-mount FVB mouse atria. FVB mice (3-6 months...
Show moreDegeneration of nociceptive afferent axons and terminals in the heart is associated with painless sudden cardiac death. However, innervation, distribution and morphological structures of sympathetic cardiac nociceptive afferent axons and terminals have not yet been fully characterized. The aim of the present study is to characterize the density, arrangement, and structural features of differentiated sympathetic afferent axons and terminals in whole-mount FVB mouse atria. FVB mice (3-6 months old) were perfused and the tissues were fixed. The right and left atria were processed with immunohistochemistry. Calcitonin gene-related peptide (CGRP) and substance P (SP) are two neuropeptides which have been widely used to label sympathetic nociceptive afferent axons in many tissues. CGRP (rabbit anti-CGRP) and SP (Goat anti-SP) primary antibodies were applied, followed by Alexa Fluor 594 and 660 conjugated secondary antibodies. Whole-mount preparations of right and left atria were examined using a laser scanning confocal microscope. We found that 1) CGRP immunoreactive (IR) axon bundles innervated the right and left atria including the auricle and entrance area of the superior vena cava, the inferior vena cava, left precaval vein and pulmonary veins. Large axon bundles entered the area from the major veins and bifurcated into smaller axon bundles and single axon fibers to form terminal end-nets and free endings in the epicardium at each region with a similar pattern. In the atrial muscle layer, varicose CGRP-IR axons had close contacts with muscle fibers. In addition, CGRP-IR axons terminated in the intrinsic cardiac ganglia (ICGs) with varicosities surrounding individual ganglionic principle neurons (PNs). In the aortic arch, the CGRP-IR fibers exhibited similar terminal structures to those seen in the atria. 2) SP-IR axons also projected to the right and left atria and aorta. Similar to CGRP-IR axons, these SP-IR axons also formed end-nets and free endings in these areas. In cardiac ganglia, SP-IR axons formed varicose endings around many individual PNs. However, a salient difference was found: There appeared to be fewer SP-IR axons and terminals than CGRP-IR axons and terminals in the atria. 3) None of the cardiac PNs in ICG were CGRP-IR or SP-IR. 4) Many SP-IR axon terminals around PNs within ICGs and atrial muscles were found to have colocalized expression of CGRP-IR. Collectively, our data for the first time documented the distribution patterns and morphology of sympathetic afferent axons and terminals in each region of the atria in the mouse model. This will provide a foundation for future analysis of the pathological changes of sympathetic afferent nerves in the atria in different disease models (e.g., diabetes, sleep apnea, and aging). This study was supported by NIH R01 HL-79636.
Show less - Date Issued
- 2010
- Identifier
- CFE0003536, ucf:48965
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0003536
- Title
- RULE-BASED DECISION SUPPORT SYSTEM FOR SENSOR DEPLOYMENT IN DRINKING WATER NETWORKS.
- Creator
-
Prapinpongsanone, Natthaphon, Chang, Ni-Bin, University of Central Florida
- Abstract / Description
-
Drinking water distribution systems are inherently vulnerable to malicious contaminant events with environmental health concerns such as total trihalomethanes (TTHMs), lead, and chlorine residual. In response to the needs for long-term monitoring, one of the most significant challenges currently facing the water industry is to investigate the sensor placement strategies with modern concepts of and approaches to risk management. This study develops a Rule-based Decision Support System (RBDSS)...
Show moreDrinking water distribution systems are inherently vulnerable to malicious contaminant events with environmental health concerns such as total trihalomethanes (TTHMs), lead, and chlorine residual. In response to the needs for long-term monitoring, one of the most significant challenges currently facing the water industry is to investigate the sensor placement strategies with modern concepts of and approaches to risk management. This study develops a Rule-based Decision Support System (RBDSS) to generate sensor deployment strategies with no computational burden as we oftentimes encountered via large-scale optimization analyses. Three rules were derived to address the efficacy and efficiency characteristics and they include: 1) intensity, 2) accessibility, and 3) complexity rules. To retrieve the information of population exposure, the well-calibrated EPANET model was applied for the purpose of demonstration of vulnerability assessment. Graph theory was applied to retrieve the implication of complexity rule eliminating the need to deal with temporal variability. In case study 1, implementation potential was assessed by using a small-scale drinking water network in rural Kentucky, the United States with the sensitivity analysis. The RBDSS was also applied to two networks, a small-scale and large-scale network, in "The Battle of the Water Sensor Network" (BWSN) in order to compare its performances with the other models. In case study 2, the RBDSS has been modified by implementing four objective indexes, the expected time of detection (Z1), the expected population affected prior to detection (Z2), the expected consumption of contaminant water prior to detection, and the detection likelihood (Z4), are being used to evaluate RBDSS's performance and compare to other models in Network 1 analysis in BWSN. Lastly, the implementation of weighted optimization is applied to the large water distribution analysis in case study 3, Network 2 in BWSN.
Show less - Date Issued
- 2011
- Identifier
- CFE0003704, ucf:48825
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0003704
- Title
- The Relationship Between Perceived Personal Fairness, Social Fairness, Hotel Cancellation Policies and Consumer Patronage.
- Creator
-
Smith, Scott, Parsa, Haragopal, Chen, Po-Ju, Nusair, Khaldoon, Robinson, Edward, Schwartz, Zvi, University of Central Florida
- Abstract / Description
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The objective of the study was to examine the relationships between the concepts of personal fairness and social fairness and hotel cancellation policies. These relationships will be explored using the framework of Prospect Theory in terms of consumer patronage (willingness-to-purchase and word-of-mouth).This study includes a brief history of the development of the lodging industry in the United States from inns and taverns to the modern hotel industry that is a critical sector of the...
Show moreThe objective of the study was to examine the relationships between the concepts of personal fairness and social fairness and hotel cancellation policies. These relationships will be explored using the framework of Prospect Theory in terms of consumer patronage (willingness-to-purchase and word-of-mouth).This study includes a brief history of the development of the lodging industry in the United States from inns and taverns to the modern hotel industry that is a critical sector of the hospitality and tourism economy. Current statistics are provided regarding the U.S. and Central Florida hotel industry in order to provide both a national and local economic perspective. The study also provides relevant statistics regarding U.S. domestic traveller information.The included literature review consists of concepts of mental accounting theory, economic utility theory, prospect theory, personal fairness, social fairness, and consumer patronage. The study also discusses how the lodging industry is unique in its implementation of reservation cancellation policies when compared against other industries. Research regarding merchandise return policies is also discussed here. The study was designed to investigate three separate components of both personal and social fairness. The first component investigated the effects of hotel rate price increases and discounts on personal fairness when compared against an existing reference price. The second component studied the perceptions of social fairness on three established hotel cancellation policies. The third component introduces a treatment of distributive and procedural fairness violations as a moderator to observe the effects on consumer patronage for the same three hotel cancellation policies. The data were collected from 415 hotel guests staying in Central Florida hotels near the Orlando international airport using an experimental method which provided different written scenarios regarding hotel pricing and three different hotel cancellation policies. The data was then analyzed using Analysis of Variance (ANOVA) and Tukey's Post Hoc test to provide results that allowed the comparison of effects on each in terms of consumer patronage. The study results indicated that that price increases against established reference prices had a significant negative effect on consumer patronage whereas discounts of the same magnitude had a significant effect only in the middle range. Included smaller and large discounts did not have a significant effect on consumer patronage outside of the middle range. The study results also indicated that there was significant difference in consumer patronage between an Open cancellation policy and a 48 Hour Cancellation Policy. There is a significant difference in consumer patronage when a No Refund policy is compared against both the Open Cancellation Policy and the 48 Hour Cancellation Policy. The study results also show that a violation of either Distributive Fairness or Procedural Fairness has a significant negative effect on consumer patronage for both an Open Cancellation policy and 48 Hour Cancellation Policy. However, when Distributive Fairness or Procedural Fairness violations are introduced as a moderator, there is no significant effect on a No Refund Cancellation Policy.The study and its ensuing results are of importance to the academic community in that it provides additional scholarly support to both Prospect Theory and the theory of mental accounting and the roles that each plays in consumer behavior. From an industry practitioner perspective, the current results provide insight into hotel consumer's attitudes regarding rate increases/ discounts and the implementation of the three different hotel cancelation policies. The results can be utilized to provide justification and guidance in altering or establishing hotel cancellation policies that hotel consumers consider to be fair.
Show less - Date Issued
- 2012
- Identifier
- CFE0004269, ucf:49508
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004269
- Title
- SCALABLE AND EFFICIENT OUTLIER DETECTION IN LARGE DISTRIBUTED DATA SETS WITH MIXED-TYPE ATTRIBUTES.
- Creator
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Koufakou, Anna, Georgiopoulos, Michael, University of Central Florida
- Abstract / Description
-
An important problem that appears often when analyzing data involves identifying irregular or abnormal data points called outliers. This problem broadly arises under two scenarios: when outliers are to be removed from the data before analysis, and when useful information or knowledge can be extracted by the outliers themselves. Outlier Detection in the context of the second scenario is a research field that has attracted significant attention in a broad range of useful applications. For...
Show moreAn important problem that appears often when analyzing data involves identifying irregular or abnormal data points called outliers. This problem broadly arises under two scenarios: when outliers are to be removed from the data before analysis, and when useful information or knowledge can be extracted by the outliers themselves. Outlier Detection in the context of the second scenario is a research field that has attracted significant attention in a broad range of useful applications. For example, in credit card transaction data, outliers might indicate potential fraud; in network traffic data, outliers might represent potential intrusion attempts. The basis of deciding if a data point is an outlier is often some measure or notion of dissimilarity between the data point under consideration and the rest. Traditional outlier detection methods assume numerical or ordinal data, and compute pair-wise distances between data points. However, the notion of distance or similarity for categorical data is more difficult to define. Moreover, the size of currently available data sets dictates the need for fast and scalable outlier detection methods, thus precluding distance computations. Additionally, these methods must be applicable to data which might be distributed among different locations. In this work, we propose novel strategies to efficiently deal with large distributed data containing mixed-type attributes. Specifically, we first propose a fast and scalable algorithm for categorical data (AVF), and its parallel version based on MapReduce (MR-AVF). We extend AVF and introduce a fast outlier detection algorithm for large distributed data with mixed-type attributes (ODMAD). Finally, we modify ODMAD in order to deal with very high-dimensional categorical data. Experiments with large real-world and synthetic data show that the proposed methods exhibit large performance gains and high scalability compared to the state-of-the-art, while achieving similar accuracy detection rates.
Show less - Date Issued
- 2009
- Identifier
- CFE0002734, ucf:48161
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0002734
- Title
- Saturn's Rings: Measuring Particle Size Distributions Using Cassini UVIS Occultation Data.
- Creator
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Becker, Tracy, Colwell, Joshua, Fernandez, Yan, Campins, Humberto, Showalter, Mark, Klemm, Richard, University of Central Florida
- Abstract / Description
-
Since its arrival to Saturn in 2004, the Cassini spacecraft has utilized its suite of sophisticated instruments to further our understanding of the Saturnian ring system. We analyze occultation data from Cassini's Ultraviolet Imaging Spectrograph (UVIS) in order to measure the particle size distribution and place limits on the minimum particle sizes in Saturn's rings.Throughout the ring system, particle accretion is countered by collisional and tidal disruption and Keplerian shear. Therefore,...
Show moreSince its arrival to Saturn in 2004, the Cassini spacecraft has utilized its suite of sophisticated instruments to further our understanding of the Saturnian ring system. We analyze occultation data from Cassini's Ultraviolet Imaging Spectrograph (UVIS) in order to measure the particle size distribution and place limits on the minimum particle sizes in Saturn's rings.Throughout the ring system, particle accretion is countered by collisional and tidal disruption and Keplerian shear. Therefore, the particle size distribution of the rings is continually evolving. The presence of sub-centimeter particles, which have short lifetimes due to these processes, is indicative of ongoing dynamics in the rings. Sub-centimeter-sized particles efficiently diffract light at ultraviolet wavelengths, and thus produce signatures of diffraction in the occultation data. The shape and intensity of the diffraction signatures are indicative of the sizes of the particles that produce them. The UVIS wavelength bandpass, 51.2 - 180 nm, contains the shortest wavelengths of the Cassini instruments, making it most sensitive to the smallest particles in the rings. We have developed a computational model that reconstructs the geometry of a UVIS observation and produces a synthetic diffraction signal for a given truncated power-law particle size distribution, which we compare with the observed signal. We implement this model for two sets of observations: (1) diffraction spikes at sharp ring edges during stellar occultations and (2) the light curve due to attenuated and diffracted sunlight by particles in Saturn's F ring during solar occultations. Near sharp ring edges, ring particles can diffract light such that there is a measurable increase in the signal of an unocculted star exterior to the ring. In Saturn's A ring, diffracted light can augment the stellar signal by up to 6% and can be detected tens of kilometers radially beyond the edge. The radial profile of the diffraction signal is dependent on the size distribution of the particle population near the ring edge. These diffraction signals are observed at sharp edges throughout Saturn's rings, although in this work we focus on diffraction at the outer edge of Saturn's A ring and at the edges of the Encke Gap. We find an overall steepening of the power-law size distribution and a decrease in the minimum particle size at the outer edge of the A ring when compared with the Encke Gap edges. This suggests that interparticle collisions caused by satellite perturbations in the region result in more shedding of regolith or fragmentation of particles in the outermost parts of the A ring. We rule out any significant population of sub-millimeter-sized particles in Saturn's A ring, placing a lower limitation of 1-mm on the minimum particle size in the ring.We also model the light curves produced as Saturn's F ring occults the Sun. We consider both the attenuated signal and the light diffracted by the particles in the ring during the occultation. Five of the eleven solar occultations analyzed show a clear signature of diffracted light that surpasses the unocculted solar signal. This includes a misaligned solar occultation that placed most of the solar disk outside of the instrument's field of view, reducing the solar signal by 97.5% and resulting in the serendipitous detection of diffracted light. We measure a large variation in the the size distribution of the particles that fill the broad, ~500 km region surrounding the F ring core. We find that smaller particles ((<) 50 micrometers) are present during solar occultations for which diffraction was detected, and place a lower limit on the minimum particle size of 100 micrometers for occultations during which diffraction was not detected. A comparison with images of the F ring observed by the Cassini Imaging Science Subsystem near the times of the occultations reveals that the detections of small particles in the UVIS data correspond with locations of collisional events in the F ring. This implies that collisions within the F ring core replenish the sub-millimeter-sized dust in the 500-km region that encompasses the F ring core.
Show less - Date Issued
- 2016
- Identifier
- CFE0006073, ucf:50940
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006073
- Title
- An Integrated Framework for Automated Data Collection and Processing for Discrete Event Simulation Models.
- Creator
-
Rodriguez, Carlos, Kincaid, John, Karwowski, Waldemar, O'Neal, Thomas, Kaup, David, Mouloua, Mustapha, University of Central Florida
- Abstract / Description
-
Discrete Events Simulation (DES) is a powerful tool of modeling and analysis used in different disciplines. DES models require data in order to determine the different parameters that drive the simulations. The literature about DES input data management indicates that the preparation of necessary input data is often a highly manual process, which causes inefficiencies, significant time consumption and a negative user experience.The focus of this research investigation is addressing the manual...
Show moreDiscrete Events Simulation (DES) is a powerful tool of modeling and analysis used in different disciplines. DES models require data in order to determine the different parameters that drive the simulations. The literature about DES input data management indicates that the preparation of necessary input data is often a highly manual process, which causes inefficiencies, significant time consumption and a negative user experience.The focus of this research investigation is addressing the manual data collection and processing (MDCAP) problem prevalent in DES projects. This research investigation presents an integrated framework to solve the MDCAP problem by classifying the data needed for DES projects into three generic classes. Such classification permits automating and streamlining the preparation of the data, allowing DES modelers to collect, update, visualize, fit, validate, tally and test data in real-time, by performing intuitive actions. In addition to the proposed theoretical framework, this project introduces an innovative user interface that was programmed based on the ideas of the proposed framework. The interface is called DESI, which stands for Discrete Event Simulation Inputs.The proposed integrated framework to automate DES input data preparation was evaluated against benchmark measures presented in the literature in order to show its positive impact in DES input data management. This research investigation demonstrates that the proposed framework, instantiated by the DESI interface, addresses current gaps in the field, reduces the time devoted to input data management within DES projects and advances the state-of-the-art in DES input data management automation.
Show less - Date Issued
- 2015
- Identifier
- CFE0005878, ucf:50861
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005878
- Title
- Data-driven Predictive Analytics For Distributed Smart Grid Control: Optimization of Energy Storage, Voltage and Demand Response.
- Creator
-
Valizadehhaghi, Hamed, Qu, Zhihua, Behal, Aman, Atia, George, Turgut, Damla, Pensky, Marianna, University of Central Florida
- Abstract / Description
-
The smart grid is expected to support an interconnected network of self-contained microgrids. Nonetheless, the distributed integration of renewable generation and demand response adds complexity to the control and optimization of smart grid. Forecasts are essential due to the existence of stochastic variations and uncertainty. Forecasting data are spatio-temporal which means that the data correspond to regular intervals, say every hour, and the analysis has to take account of spatial...
Show moreThe smart grid is expected to support an interconnected network of self-contained microgrids. Nonetheless, the distributed integration of renewable generation and demand response adds complexity to the control and optimization of smart grid. Forecasts are essential due to the existence of stochastic variations and uncertainty. Forecasting data are spatio-temporal which means that the data correspond to regular intervals, say every hour, and the analysis has to take account of spatial dependence among the distributed generators or locations. Hence, smart grid operations must take account of, and in fact benefit from the temporal dependence as well as the spatial dependence. This is particularly important considering the buffering effect of energy storage devices such as batteries, heating/cooling systems and electric vehicles. The data infrastructure of smart grid is the key to address these challenges, however, how to utilize stochastic modeling and forecasting tools for optimal and reliable planning, operation and control of smart grid remains an open issue.Utilities are seeking to become more proactive in decision-making, adjusting their strategies based on realistic predictive views into the future, thus allowing them to side-step problems and capitalize on the smart grid technologies, such as energy storage, that are now being deployed atscale. Predictive analytics, capable of managing intermittent loads, renewables, rapidly changing weather patterns and other grid conditions, represent the ultimate goal for smart grid capabilities.Within this framework, this dissertation develops high-performance analytics, such as predictive analytics, and ways of employing analytics to improve distributed and cooperative optimization software which proves to be the most significant value-add in the smart grid age, as new network management technologies prove reliable and fundamental. Proposed optimization and control approaches for active and reactive power control are robust to variations and offer a certain level of optimality by combining real-time control with hours-ahead network operation schemes. The main objective is managing spatial and temporal availability of the energy resources in different look-ahead time horizons. Stochastic distributed optimization is realized by integrating a distributed sub-gradient method with conditional ensemble predictions of the energy storage capacity and distributed generation. Hence, the obtained solutions can reflect on the system requirements for the upcoming times along with the instantaneous cooperation between distributed resources. As an important issue for smart grid, the conditional ensembles are studied for capturing wind, photovoltaic, and vehicle-to-grid availability variations. The following objectives are pursued:- Spatio-temporal adaptive modeling of data including electricity demand, electric vehicles and renewable energy (wind and solar power)- Predictive data analytics and forecasting- Distributed control- Integration of energy storage systemsFull distributional characterization and spatio-temporal modeling of data ensembles are utilized in order to retain the conditional and temporal interdependence between projection data and available capacity. Then, by imposing measures of the most likely ensembles, the distributed control method is carried out for cooperative optimization of the renewable generation and energy storage within the smart grid.
Show less - Date Issued
- 2016
- Identifier
- CFE0006408, ucf:51481
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006408
- Title
- From pet to pest? The potential global range and food web effects of a generalist carnivore.
- Creator
-
Bevan, Hannah, Jenkins, David, Noss, Reed, Campbell, Todd, University of Central Florida
- Abstract / Description
-
The Nile monitor lizard [Varanus niloticus (Linnaeus, 1766)] is a generalist carnivore, native to Sub-Saharan Africa and the Nile River but now established in North America as a result of the pet trade. Once introduced, they are a potential invasive threat to native wildlife. Here, I create ensemble species distribution models (SDMs) to predict the global distribution of this generalist carnivore given current and future climate conditions. I then quantify the monitor's potential effects on...
Show moreThe Nile monitor lizard [Varanus niloticus (Linnaeus, 1766)] is a generalist carnivore, native to Sub-Saharan Africa and the Nile River but now established in North America as a result of the pet trade. Once introduced, they are a potential invasive threat to native wildlife. Here, I create ensemble species distribution models (SDMs) to predict the global distribution of this generalist carnivore given current and future climate conditions. I then quantify the monitor's potential effects on 85 food webs representing (>)900 different species within the projected regions based on stomach content data. Climate, vegetation, and elevation data are used for 507 georeferenced observation points from the Nile monitor's native range to produce current and future (2070) ensemble SDMs. Explanatory variables are evaluated as ten alternative models organized in three subsets according to model assumptions. The true skill statistic (TSS), sensitivity, and specificity were used to assess model performance, and the best subset was averaged to represent an ensemble model. Food web impacts after the generalist predator's addition are determined by changes in nine metrics of food web structure. The most predictive (TSS scores ?0.87) ensemble SDM was based on the MARS and FDA algorithms using elevation and climate for current and future conditions. This model shows that, if introduced, Nile monitors will likely spread into many regions in the Americas, the Caribbean, Madagascar, Southeast Asia, and Australia. Assuming unabated carbon emissions by 2070, climate change will enhance that potential range. Adding Nile monitors to food webs generally increases overall trophic links, connectance, link density, and fraction of intermediate taxa, with decreases in the fraction of top and basal taxa. These results are consistent with a generalist predator that affects many species and is likely to affect food web stability. The potential Nile monitor range is vast and encompasses multiple biodiversity hotspots. Given many strong food web interactions by this generalist predator, vulnerable regions should actively prohibit/regulate Nile monitors as pets, enforce those restrictions, and promote exotic pet amnesty programs. Southern US states should especially act soon to prevent spread of the Nile monitor to the Neotropics from its current introduced population in Florida and as released pets.
Show less - Date Issued
- 2016
- Identifier
- CFE0006441, ucf:51446
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006441
- Title
- Network Partitioning in Distributed Agent-Based Models.
- Creator
-
Petkova, Antoniya, Deo, Narsingh, Hughes, Charles, Bassiouni, Mostafa, Shaykhian, Gholam, University of Central Florida
- Abstract / Description
-
Agent-Based Models (ABMs) are an emerging simulation paradigm for modeling complex systems, comprised of autonomous, possibly heterogeneous, interacting agents. The utility of ABMs lies in their ability to represent such complex systems as self-organizing networks of agents. Modeling and understanding the behavior of complex systems usually occurs at large and representative scales, and often obtaining and visualizing of simulation results in real-time is critical.The real-time requirement...
Show moreAgent-Based Models (ABMs) are an emerging simulation paradigm for modeling complex systems, comprised of autonomous, possibly heterogeneous, interacting agents. The utility of ABMs lies in their ability to represent such complex systems as self-organizing networks of agents. Modeling and understanding the behavior of complex systems usually occurs at large and representative scales, and often obtaining and visualizing of simulation results in real-time is critical.The real-time requirement necessitates the use of in-memory computing, as it is dif?cult and challenging to handle the latency and unpredictability of disk accesses. Combining this observation with the scale requirement emphasizes the need to use parallel and distributed computing platforms, such as MPI-enabled CPU clusters. Consequently, the agent population must be "partitioned" across different CPUs in a cluster. Further, the typically high volume of interactions among agents can quickly become a signi?cant bottleneck for real-time or large-scale simulations. The problem is exacerbated if the underlying ABM network is dynamic and the inter-process communication evolves over the course of the simulation. Therefore, it is critical to develop topology-aware partitioning mechanisms to support such large simulations.In this dissertation, we demonstrate that distributed agent-based model simulations bene?t from the use of graph partitioning algorithms that involve a local, neighborhood-based perspective. Such methods do not rely on global accesses to the network and thus are more scalable. In addition, we propose two partitioning schemes that consider the bottom-up individual-centric nature of agent-based modeling. The ?rst technique utilizes label-propagation community detection to partition the dynamic agent network of an ABM. We propose a latency-hiding, seamless integration of community detection in the dynamics of a distributed ABM. To achieve this integration, we exploit the similarity in the process flow patterns of a label-propagation community-detection algorithm and self-organizing ABMs.In the second partitioning scheme, we apply a combination of the Guided Local Search (GLS) and Fast Local Search (FLS) metaheuristics in the context of graph partitioning. The main driving principle of GLS is the dynamic modi?cation of the objective function to escape local optima. The algorithm augments the objective of a local search, thereby transforming the landscape structure and escaping a local optimum. FLS is a local search heuristic algorithm that is aimed at reducing the search space of the main search algorithm. It breaks down the space into sub-neighborhoods such that inactive sub-neighborhoods are removed from the search process. The combination of GLS and FLS allowed us to design a graph partitioning algorithm that is both scalable and sensitive to the inherent modularity of real-world networks.
Show less - Date Issued
- 2017
- Identifier
- CFE0006903, ucf:51706
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006903
- Title
- Theodore is Dying: Production of the Feature Film from Development Through Distribution.
- Creator
-
Pomeranz, Ryan, Stoeckl, Ula, Peterson, Lisa, Schlow, Stephen, University of Central Florida
- Abstract / Description
-
Theodore Is Dying is a feature length film written and directed by Ryan Ceri Pomeranz. It was undertaken as a partial fulfillment of the requirements to receive a Master of Fine Arts in Film and Digital Media from the Department of Film in the College of Arts and Humanities at the University of Central Florida. The film aims to explore both the immediate and the long-term effects of choices made by four people at specific moments of demarcation in their lives. Structurally, the film is...
Show moreTheodore Is Dying is a feature length film written and directed by Ryan Ceri Pomeranz. It was undertaken as a partial fulfillment of the requirements to receive a Master of Fine Arts in Film and Digital Media from the Department of Film in the College of Arts and Humanities at the University of Central Florida. The film aims to explore both the immediate and the long-term effects of choices made by four people at specific moments of demarcation in their lives. Structurally, the film is presented in an episodic and non- linear style that attempts to examine each protagonist's own set of conflicts, while simultaneously exposing how the choices they make affect one another. The film's production presented many unique challenges to our producing team, cast and crew such as shooting on location in Scranton, Pennsylvania over one thousand miles from home and figuring out where to allocate funds from our (")ultra-low(") budget. These challenges were met head on and often times acted as catalysts for rethinking the way that films at our budget level could be produced. As a result, the account of the making of Theodore Is Dying, from development through distribution, aims to contribute these ideas to the larger conversation about the role of Ultra-Low Budget Filmmaking in the modern filmmaking era.
Show less - Date Issued
- 2013
- Identifier
- CFE0004737, ucf:49846
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004737
- Title
- Transient and Distributed Algorithms to Improve Islanding Detection Capability of Inverter Based Distributed Generation.
- Creator
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Alhosani, Mohamed, Qu, Zhihua, Mikhael, Wasfy, Haralambous, Michael, Behal, Aman, Xu, Chengying, University of Central Florida
- Abstract / Description
-
Recently, a lot of research work has been dedicated toward enhancing performance, reliability and integrity of distributed energy resources that are integrated into distribution networks. The problem of islanding detection and islanding prevention (i.e. anti-islanding) has stimulated a lot of research due to its role in severely compromising the safety of working personnel and resulting in equipment damages. Various Islanding Detection Methods (IDMs) have been developed within the last ten...
Show moreRecently, a lot of research work has been dedicated toward enhancing performance, reliability and integrity of distributed energy resources that are integrated into distribution networks. The problem of islanding detection and islanding prevention (i.e. anti-islanding) has stimulated a lot of research due to its role in severely compromising the safety of working personnel and resulting in equipment damages. Various Islanding Detection Methods (IDMs) have been developed within the last ten years in anticipation of the tremendous increase in the penetration of Distributed Generation (DG) in distribution system. This work proposes new IDMs that rely on transient and distributed behaviors to improve integrity and performance of DGs while maintaining multi-DG islanding detection capability.In this thesis, the following questions have been addressed: How to utilize the transient behavior arising from an islanding condition to improve detectability and robust performance of IDMs in a distributive manner? How to reduce the negative stability impact of the well-known Sandia Frequency Shift (SFS) IDM while maintaining its islanding detection capability? How to incorporate the perturbations provided by each of DGs in such a way that the negative interference of different IDMs is minimized without the need of any type of communication among the different DGs?It is shown that the proposed techniques are local, scalable and robust against different loading conditions and topology changes. Also, the proposed techniques can successfully distinguish an islanding condition from other disturbances that may occur in power system networks. This work improves the efficiency, reliability and safety of integrated DGs, which presents a necessary advance toward making electric power grids a smart grid.
Show less - Date Issued
- 2013
- Identifier
- CFE0005295, ucf:50567
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005295
