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- Title
- RIGOROUS ANALYSIS OF AN EDGE-BASED NETWORK DISEASE MODEL.
- Creator
-
Mai, Sabrina, Shuai, Zhisheng, University of Central Florida
- Abstract / Description
-
Edge-based network disease models, in comparison to classic compartmental epidemiological models, better capture social factors affecting disease spread such as contact duration and social heterogeneity. We reason that there should exist infinitely many equilibria rather than only an endemic equilibrium and a disease-free equilibrium for the edge-based network disease model commonly used in the literature, as there do not exist any changes in demographic in the model. We modify the commonly...
Show moreEdge-based network disease models, in comparison to classic compartmental epidemiological models, better capture social factors affecting disease spread such as contact duration and social heterogeneity. We reason that there should exist infinitely many equilibria rather than only an endemic equilibrium and a disease-free equilibrium for the edge-based network disease model commonly used in the literature, as there do not exist any changes in demographic in the model. We modify the commonly used network model by relaxing some assumed conditions and factor in a dependency on initial conditions. We find that this modification still accounts for realistic dynamics of disease spread (such as the probability of contracting a disease based off your neighbors' susceptibility to the disease) based on the basic reproduction number. Specifically, if the basic reproduction number is below 1, then the infection dies out; while if the basic reproduction number is above 1, then there is possibility of an epidemic.
Show less - Date Issued
- 2019
- Identifier
- CFH2000537, ucf:45651
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFH2000537
- Title
- OLDER ADULTS AND ONLINE SOCIAL NETWORKING: RELATING ISSUES OF ATTITUDES, EXPERTISE, AND USE.
- Creator
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Hernandez, Elise, Smither, Janan, University of Central Florida
- Abstract / Description
-
The social transition to older adulthood can be challenging for elderly individuals and their families when isolation poses a threat to well-being. Technology is currently providing younger generations with an opportunity to stay in contact with social partners through the use of online social networking tools; it is unclear whether older adults are also taking advantage of this communication method. This study explored how older adults are experiencing online social networking. Specifically,...
Show moreThe social transition to older adulthood can be challenging for elderly individuals and their families when isolation poses a threat to well-being. Technology is currently providing younger generations with an opportunity to stay in contact with social partners through the use of online social networking tools; it is unclear whether older adults are also taking advantage of this communication method. This study explored how older adults are experiencing online social networking. Specifically, this research addressed how older adults' attitudes towards online social networking are related to their expertise in using computers and the internet for this purpose. A survey methodological approach was employed whereby older adults aged 65 and over were recruited from senior centers across the Central Florida area to fill out a series of questionnaires. The Computer Aversion, Attitudes, and Familiarity Index (CAAFI) was used to measure attitudes and expertise with computers. The Internet Technical Literacy and Social Awareness Scale was used to measure interest and expertise with the internet. The relationship between older adults' use of online social networking and their attitudes and expertise was also investigated. Finally, social connectedness, (measured using the Social Connectedness Scale) and subjective well-being (measured using the Satisfaction with Life Scale) were measured to explore whether older adults receive a psychosocial benefit from using online social networking. Findings showed expertise and attitudes scores were strongly correlated, and these scores were also predictive of online social networking use. The results of this study may help social service providers for elderly individuals begin to understand the many factors associated with using new forms of technology.
Show less - Date Issued
- 2011
- Identifier
- CFH0004078, ucf:44786
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFH0004078
- Title
- Stochastic-Based Computing with Emerging Spin-Based Device Technologies.
- Creator
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Bai, Yu, Lin, Mingjie, DeMara, Ronald, Wang, Jun, Jin, Yier, Dong, Yajie, University of Central Florida
- Abstract / Description
-
In this dissertation, analog and emerging device physics is explored to provide a technology plat- form to design new bio-inspired system and novel architecture. With CMOS approaching the nano-scaling, their physics limits in feature size. Therefore, their physical device characteristics will pose severe challenges to constructing robust digital circuitry. Unlike transistor defects due to fabrication imperfection, quantum-related switching uncertainties will seriously increase their sus-...
Show moreIn this dissertation, analog and emerging device physics is explored to provide a technology plat- form to design new bio-inspired system and novel architecture. With CMOS approaching the nano-scaling, their physics limits in feature size. Therefore, their physical device characteristics will pose severe challenges to constructing robust digital circuitry. Unlike transistor defects due to fabrication imperfection, quantum-related switching uncertainties will seriously increase their sus- ceptibility to noise, thus rendering the traditional thinking and logic design techniques inadequate. Therefore, the trend of current research objectives is to create a non-Boolean high-level compu- tational model and map it directly to the unique operational properties of new, power efficient, nanoscale devices.The focus of this research is based on two-fold: 1) Investigation of the physical hysteresis switching behaviors of domain wall device. We analyze phenomenon of domain wall device and identify hys- teresis behavior with current range. We proposed the Domain-Wall-Motion-based (DWM) NCL circuit that achieves approximately 30x and 8x improvements in energy efficiency and chip layout area, respectively, over its equivalent CMOS design, while maintaining similar delay performance for a one bit full adder. 2) Investigation of the physical stochastic switching behaviors of Mag- netic Tunnel Junction (MTJ) device. With analyzing of stochastic switching behaviors of MTJ, we proposed an innovative stochastic-based architecture for implementing artificial neural network (S-ANN) with both magnetic tunneling junction (MTJ) and domain wall motion (DWM) devices, which enables efficient computing at an ultra-low voltage. For a well-known pattern recognition task, our mixed-model HSPICE simulation results have shown that a 34-neuron S-ANN imple- mentation, when compared with its deterministic-based ANN counterparts implemented with dig- ital and analog CMOS circuits, achieves more than 1.5 ? 2 orders of magnitude lower energy consumption and 2 ? 2.5 orders of magnitude less hidden layer chip area.
Show less - Date Issued
- 2016
- Identifier
- CFE0006680, ucf:51921
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006680
- Title
- D-FENS: DNS Filtering (&) Extraction Network System for Malicious Domain Names.
- Creator
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Spaulding, Jeffrey, Mohaisen, Aziz, Leavens, Gary, Bassiouni, Mostafa, Fu, Xinwen, Posey, Clay, University of Central Florida
- Abstract / Description
-
While the DNS (Domain Name System) has become a cornerstone for the operation of the Internet, it has also fostered creative cases of maliciousness, including phishing, typosquatting, and botnet communication among others. To address this problem, this dissertation focuses on identifying and mitigating such malicious domain names through prior knowledge and machine learning. In the first part of this dissertation, we explore a method of registering domain names with deliberate typographical...
Show moreWhile the DNS (Domain Name System) has become a cornerstone for the operation of the Internet, it has also fostered creative cases of maliciousness, including phishing, typosquatting, and botnet communication among others. To address this problem, this dissertation focuses on identifying and mitigating such malicious domain names through prior knowledge and machine learning. In the first part of this dissertation, we explore a method of registering domain names with deliberate typographical mistakes (i.e., typosquatting) to masquerade as popular and well-established domain names. To understand the effectiveness of typosquatting, we conducted a user study which helped shed light on which techniques were more (")successful(") than others in deceiving users. While certain techniques fared better than others, they failed to take the context of the user into account. Therefore, in the second part of this dissertation we look at the possibility of an advanced attack which takes context into account when generating domain names. The main idea is determining the possibility for an adversary to improve their (")success(") rate of deceiving users with specifically-targeted malicious domain names. While these malicious domains typically target users, other types of domain names are generated by botnets for command (&) control (C2) communication. Therefore, in the third part of this dissertation we investigate domain generation algorithms (DGA) used by botnets and propose a method to identify DGA-based domain names. By analyzing DNS traffic for certain patterns of NXDomain (non-existent domain) query responses, we can accurately predict DGA-based domain names before they are registered. Given all of these approaches to malicious domain names, we ultimately propose a system called D-FENS (DNS Filtering (&) Extraction Network System). D-FENS uses machine learning and prior knowledge to accurately predict unreported malicious domain names in real-time, thereby preventing Internet devices from unknowingly connecting to a potentially malicious domain name.
Show less - Date Issued
- 2018
- Identifier
- CFE0007587, ucf:52540
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007587
- Title
- Virtual Router Approach for Wireless Ad Hoc Networks.
- Creator
-
Ho, Ai, Hua, Kien, Guha, Ratan, Moshell, Jack, Zou, Changchun, Wang, Ching, University of Central Florida
- Abstract / Description
-
Wireless networks have become increasingly popular in recent years. There are two variations of mobile wireless networks: infrastructure mobile networks and infrastructureless mobile networks. The latter are also known as mobile ad hoc network (MANET). MANETs have no fixed routers. Instead, mobile nodes function as relay nodes or routers, which discover and maintain communication connections between source nodes and destination nodes for various data transmission sessions. In other words, an...
Show moreWireless networks have become increasingly popular in recent years. There are two variations of mobile wireless networks: infrastructure mobile networks and infrastructureless mobile networks. The latter are also known as mobile ad hoc network (MANET). MANETs have no fixed routers. Instead, mobile nodes function as relay nodes or routers, which discover and maintain communication connections between source nodes and destination nodes for various data transmission sessions. In other words, an MANET is a self-organizing multi-hop wireless network in which all nodes within a given geographical area participate in the routing and data forwarding process. Such networks are scalable and self-healing. They support mobile applications where an infrastructure is either not available (e.g., rescue operations and underground networks) or not desirable (e.g., harsh industrial environments).In many ad hoc networks such as vehicular networks, links among nodes change constantly and rapidly due to high node speed. Maintaining communication links of an established communication path that extends between source and destination nodes is a significant challenge in mobile ad hoc networks due to movement of the mobile nodes. In particular, such communication links are often broken under a high mobility environment. Communication links can also be broken by obstacles such as buildings in a street environment that block radio signal. In a street environment, obstacles and fast moving nodes result in a very short window of communication between nodes on different streets. Although a new communication route can be established when a break in the communication path occurs, repeatedly reestablishing new routes incurs delay and substantial overhead. To address this limitation, we introduce the Virtual Router abstraction in this dissertation. A virtual router is a dynamically-created logical router that is associated with a particular geographical area. Its routing functionality is provided by the physical nodes (i.e., mobile devices) currently within the geographical region served by the virtual router. These physical nodes take turns in forwarding data packets for the virtual router. In this environment, data packets are transmitted from a source node to a destination node over a series of virtual routers. Since virtual routers do not move, this scheme is much less susceptible to node mobility. There can be two virtual router approaches: Static Virtual Router (SVR) and Dynamic Virtual Router (DVR). In SVR, the virtual routers are predetermined and shared by all communication sessions over time. This scheme requires each mobile node to have a map of the virtual routers, and use a global positioning system (GPS) to determine if the node is within the geographical region of a given router. DVR is different from SVR with the following distinctions: (1) virtual routers are dynamically created for each communication sessions as needed, and deprecated after their use; (2) mobile nodes do not need to have a GPS; and (3) mobile nodes do not need to know whereabouts of the virtual routers.In this dissertation, we apply Virtual Router approach to address mobility challenges in routing data. We first propose a data routing protocol that uses SVR to overcome the extreme fast topology change in a street environment. We then propose a routing protocol that does not require node locations by adapting a DVR approach. We also explore how the Virtual Router Approach can reduce the overhead associated with initial route or location requests used by many existing routing protocols to find a destination. An initial request for a destination is expensive because all the nodes need to be reached to locate the destination. We propose two broadcast protocols; one in an open terrain environment and the other in a street environment. Both broadcast protocols apply SVR. We provide simulation results to demonstrate the effectiveness of the proposed protocols in handling high mobility. They show Virtual Router approach can achieve several times better performance than traditional routing and broadcast approach based on physical routers (i.e., relay nodes).
Show less - Date Issued
- 2011
- Identifier
- CFE0004119, ucf:49090
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004119
- Title
- MOVING FROM A TEXTBOOK TO FACEBOOK: COLLEGE STUDENTS' MOTIVATIONS FOR USING SOCIAL NETWORKING SITES IN EDUCATION.
- Creator
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Halter, Heather, Brown, Tim, University of Central Florida
- Abstract / Description
-
This study examined college student motivations for using social networking sites for educational purposes. Motives were examined through the uses and gratifications approach. If we can determine student motivations for using social networking sites, perhaps we can determine a way to successfully implement social networking sites into the classroom. By adding the concept of satisfaction, we can also determine if students will use the sites again. If students are satisfied with educational...
Show moreThis study examined college student motivations for using social networking sites for educational purposes. Motives were examined through the uses and gratifications approach. If we can determine student motivations for using social networking sites, perhaps we can determine a way to successfully implement social networking sites into the classroom. By adding the concept of satisfaction, we can also determine if students will use the sites again. If students are satisfied with educational social networking site use, they will return to these sites for educational purposes again. Data was collected by giving a questionnaire to undergraduate students that assessed social networking site use, as well as motivations for and satisfaction with use. For general uses, students were motivated to use social networking sites for relationship maintenance, passing time, and information seeking purposes. Overall, students were satisfied with their use of the sites. For educational uses, students were motivated to use the sites for relationship maintenance and information seeking purposes. Overall, students are not satisfied with their use of these sites for educational purposes. Theoretical and practical implications of these findings are discussed.
Show less - Date Issued
- 2010
- Identifier
- CFE0003497, ucf:48984
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0003497
- Title
- EVOLUTION OF THE FOLK DEVIL: A SOCIAL NETWORK PERSPECTIVE OF THE HYBRID GANG LABEL.
- Creator
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Bolden, Christian, Huff-Corzine, Lin, University of Central Florida
- Abstract / Description
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In keeping abreast of current gang phenomena, this study seeks to comparatively examine structural processes and characteristics of gangs in chronic gang city, San Antonio, and an emerging gang city that would be more likely to have ÂÂÂÂ"hybridÂÂÂÂ" gangs, Orlando. Hybrid gangs have been identified...
Show moreIn keeping abreast of current gang phenomena, this study seeks to comparatively examine structural processes and characteristics of gangs in chronic gang city, San Antonio, and an emerging gang city that would be more likely to have ÂÂÂÂ"hybridÂÂÂÂ" gangs, Orlando. Hybrid gangs have been identified as having organizational processes that differ from traditional gangs; thus, this work will examine these processes that consist of a range of non-traditional phenomena, including cooperation between gangs, members switching gang affiliations, as well as gang initiations, and members leaving gangs. Additional characteristics uniquely associated with hybrid gangs consist of the notable presence of white, middle-class, and female gang members. Evidence suggests that the hybrid gang is more of a socially constructed moral panic than a reality. A limited number of recent studies have indicated that some gangs may better fit into a social network framework rather than a solid organizational analysis. When using the social network framework it becomes apparent that alleged hybrid behaviors are no different from regular gang behaviors regardless of geographic location. Claims about hybrid gangs serve to increase the idea of gang members as folk devils and cause undue concern of normal behaviors.
Show less - Date Issued
- 2010
- Identifier
- CFE0003239, ucf:48536
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0003239
- Title
- LEARNING FROM GEOMETRY IN LEARNING FOR TACTICAL AND STRATEGIC DECISION DOMAINS.
- Creator
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Gauci, Jason, Stanley, Kenneth, University of Central Florida
- Abstract / Description
-
Artificial neural networks (ANNs) are an abstraction of the low-level architecture of biological brains that are often applied in general problem solving and function approximation. Neuroevolution (NE), i.e. the evolution of ANNs, has proven effective at solving problems in a variety of domains. Information from the domain is input to the ANN, which outputs its desired actions. This dissertation presents a new NE algorithm called Hypercube-based NeuroEvolution of Augmenting Topologies ...
Show moreArtificial neural networks (ANNs) are an abstraction of the low-level architecture of biological brains that are often applied in general problem solving and function approximation. Neuroevolution (NE), i.e. the evolution of ANNs, has proven effective at solving problems in a variety of domains. Information from the domain is input to the ANN, which outputs its desired actions. This dissertation presents a new NE algorithm called Hypercube-based NeuroEvolution of Augmenting Topologies (HyperNEAT), based on a novel indirect encoding of ANNs. The key insight in HyperNEAT is to make the algorithm aware of the geometry in which the ANNs are embedded and thereby exploit such domain geometry to evolve ANNs more effectively. The dissertation focuses on applying HyperNEAT to tactical and strategic decision domains. These domains involve simultaneously considering short-term tactics while also balancing long-term strategies. Board games such as checkers and Go are canonical examples of such domains; however, they also include real-time strategy games and military scenarios. The dissertation details three proposed extensions to HyperNEAT designed to work in tactical and strategic decision domains. The first is an action selector ANN architecture that allows the ANN to indicate its judgements on every possible action all at once. The second technique is called substrate extrapolation. It allows learning basic concepts at a low resolution, and then increasing the resolution to learn more advanced concepts. The final extension is geometric game-tree pruning, whereby HyperNEAT can endow the ANN the ability to focus on specific areas of a domain (such as a checkers board) that deserve more inspection. The culminating contribution is to demonstrate the ability of HyperNEAT with these extensions to play Go, a most challenging game for artificial intelligence, by combining HyperNEAT with UCT.
Show less - Date Issued
- 2010
- Identifier
- CFE0003464, ucf:48962
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0003464
- Title
- Development of an Automated Method for Identification of Wet and Dry Channel Segments Using LiDAR Data and Fuzzy Logic Cluster Analysis.
- Creator
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Rowney, Chris, Wang, Dingbao, Medeiros, Stephen, Kibler, Kelly, University of Central Florida
- Abstract / Description
-
Research into the use of LiDAR data for purposes other than simple topographic elevation determination, such as urban land cover classification and the identification of forest biomass, has become prominent in recent years. In many cases, alternative analysis methodologies conducted using airborne LiDAR data are possible because the raw data collected during a survey can include information other than the classically used elevation and coordinate points, the X, Y, and Z of the plane. In...
Show moreResearch into the use of LiDAR data for purposes other than simple topographic elevation determination, such as urban land cover classification and the identification of forest biomass, has become prominent in recent years. In many cases, alternative analysis methodologies conducted using airborne LiDAR data are possible because the raw data collected during a survey can include information other than the classically used elevation and coordinate points, the X, Y, and Z of the plane. In particular, intensity return values for each point in a LiDAR grid have been found to provide a useful data set for wet and dry channel classification. LiDAR intensity return data are, in essence, a numeric representation of the characteristic light reflectivity of the object being scanned; the more reflective the object is, the higher the intensity return will be. Intensity data points are collected along the course of the channel network and within the perceived banks of the channel. Intensity data do not crisply reflect a perfectly wet or dry condition, but instead vary over a range such that each location can be viewed as partially wet and partially dry. It is advantageous to assess problems of this type using the methods of fuzzy logic. Specifically, the variance in LiDAR intensity return data is such that the use of fuzzy logic to identify intensity cluster centers, and thereby assign wet and dry condition identifiers based on fuzzy memberships, is a possibility. Membership within a fuzzy data set is characterized by a value representing the degree of membership. Typically, membership values range from 0 (representing non-membership) through 1 (representing full membership), with many observations found to be not at either extreme but instead at some intermediate value representing partial membership. The ultimate goal of this research was to design and develop an automated algorithm to identify wet and dry channel sections, given a previously identified channel network based on topographic elevation, using a combination of intensity return values from LiDAR data and fuzzy logic clustering methods, and to implement that algorithm in such a way as to produce reliable multi-class channel segments in ArcGIS. To enable control of calculations, limiting parameters were defined, specifically including the maximum allowable bank slope, and a filtering percentage to more accurately accommodate the study area.Alteration of the maximum allowable bank slope has been shown to affect the comparative quantity of high and low intensity centroids, but only in extreme bank slope conditions are the centroids changed enough to hamper results. However, interference from thick vegetation has been shown to lower intensity values in dry channel sections into the range of a wet channel. The addition of a filtering algorithm alleviates some of the interference, but not all. Overall results of the tool show an effective methodology where basic channel conditions are identified, but refinement of the tool could produce more accurate results.
Show less - Date Issued
- 2015
- Identifier
- CFE0006053, ucf:50975
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006053
- Title
- Stability and Control in Complex Networks of Dynamical Systems.
- Creator
-
Manaffam, Saeed, Vosoughi, Azadeh, Behal, Aman, Atia, George, Rahnavard, Nazanin, Javidi, Tara, Das, Tuhin, University of Central Florida
- Abstract / Description
-
Stability analysis of networked dynamical systems has been of interest in many disciplines such as biology and physics and chemistry with applications such as LASER cooling and plasma stability. These large networks are often modeled to have a completely random (Erd\"os-R\'enyi) or semi-random (Small-World) topologies. The former model is often used due to mathematical tractability while the latter has been shown to be a better model for most real life networks.The recent emergence of cyber...
Show moreStability analysis of networked dynamical systems has been of interest in many disciplines such as biology and physics and chemistry with applications such as LASER cooling and plasma stability. These large networks are often modeled to have a completely random (Erd\"os-R\'enyi) or semi-random (Small-World) topologies. The former model is often used due to mathematical tractability while the latter has been shown to be a better model for most real life networks.The recent emergence of cyber physical systems, and in particular the smart grid, has given rise to a number of engineering questions regarding the control and optimization of such networks. Some of the these questions are: \emph{How can the stability of a random network be characterized in probabilistic terms? Can the effects of network topology and system dynamics be separated? What does it take to control a large random network? Can decentralized (pinning) control be effective? If not, how large does the control network needs to be? How can decentralized or distributed controllers be designed? How the size of control network would scale with the size of networked system?}Motivated by these questions, we began by studying the probability of stability of synchronization in random networks of oscillators. We developed a stability condition separating the effects of topology and node dynamics and evaluated bounds on the probability of stability for both Erd\"os-R\'enyi (ER) and Small-World (SW) network topology models. We then turned our attention to the more realistic scenario where the dynamics of the nodes and couplings are mismatched. Utilizing the concept of $\varepsilon$-synchronization, we have studied the probability of synchronization and showed that the synchronization error, $\varepsilon$, can be arbitrarily reduced using linear controllers.We have also considered the decentralized approach of pinning control to ensure stability in such complex networks. In the pinning method, decentralized controllers are used to control a fraction of the nodes in the network. This is different from traditional decentralized approaches where all the nodes have their own controllers. While the problem of selecting the minimum number of pinning nodes is known to be NP-hard and grows exponentially with the number of nodes in the network we have devised a suboptimal algorithm to select the pinning nodes which converges linearly with network size. We have also analyzed the effectiveness of the pinning approach for the synchronization of oscillators in the networks with fast switching, where the network links disconnect and reconnect quickly relative to the node dynamics.To address the scaling problem in the design of distributed control networks, we have employed a random control network to stabilize a random plant network. Our results show that for an ER plant network, the control network needs to grow linearly with the size of the plant network.
Show less - Date Issued
- 2015
- Identifier
- CFE0005834, ucf:50902
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005834
- Title
- Modeling Network Worm Outbreaks.
- Creator
-
Foley, Evan, Shuai, Zhisheng, Kaup, David, Nevai, A, University of Central Florida
- Abstract / Description
-
Due to their convenience, computers have become a standard in society and therefore, need the utmost care. It is convenient and useful to model the behavior of digital virus outbreaks that occur, globally or locally. Compartmental models will be used to analyze the mannerisms and behaviors of computer malware. This paper will focus on a computer worm, a type of malware, spread within a business network. A mathematical model is proposed consisting of four compartments labeled as Susceptible,...
Show moreDue to their convenience, computers have become a standard in society and therefore, need the utmost care. It is convenient and useful to model the behavior of digital virus outbreaks that occur, globally or locally. Compartmental models will be used to analyze the mannerisms and behaviors of computer malware. This paper will focus on a computer worm, a type of malware, spread within a business network. A mathematical model is proposed consisting of four compartments labeled as Susceptible, Infectious, Treatment, and Antidotal. We shall show that allocating resources into treating infectious computers leads to a reduced peak of infections across the infection period, while pouring resources into treating susceptible computers decreases the total amount of infections throughout the infection period. This is assuming both methods are receiving resources without loss. This result reveals an interesting notion of balance between protecting computers and removing computers from infections, ultimately depending on the business executives' goals and/or preferences.
Show less - Date Issued
- 2015
- Identifier
- CFE0005948, ucf:50816
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005948
- Title
- Online Neuro-Adaptive Learning For Power System Dynamic State Estimation.
- Creator
-
Birari, Rahul, Zhou, Qun, Sun, Wei, Dimitrovski, Aleksandar, University of Central Florida
- Abstract / Description
-
With the increased penetration of renewable generation in the smart grid , it is crucial to have knowledge of rapid changes of system states. The information of real-time electro-mechanical dynamic states of generators are essential to ensuring reliability and detecting instability of the grid. The conventional SCADA based Dynamic State Estimation (DSE) was limited by the slow sampling rates (2-4 Hz). With the advent of PMU based synchro-phasor technology in tandem with Wide Area Monitoring...
Show moreWith the increased penetration of renewable generation in the smart grid , it is crucial to have knowledge of rapid changes of system states. The information of real-time electro-mechanical dynamic states of generators are essential to ensuring reliability and detecting instability of the grid. The conventional SCADA based Dynamic State Estimation (DSE) was limited by the slow sampling rates (2-4 Hz). With the advent of PMU based synchro-phasor technology in tandem with Wide Area Monitoring System (WAMS), it has become possible to avail rapid real-time measurements at the network nodes. These measurements can be exploited for better estimates of system dynamic states. In this research, we have proposed a novel Artificial Intelligence (AI) based real-time neuro-adaptive algorithm for rotor angle and speed estimation of synchronous generators. Generator swing equations and power flow models are incorporated in the online learning. The algorithm learns and adapts in real-time to achieve accurate estimates. Simulation is carried out on 68 bus 16 generator NETS-NYPS model. The neuro-adaptive algorithm is compared with classical Kalman Filter based DSE. Applicability and accuracy of the proposed method is demonstrated under the influence of noise and faulty conditions.
Show less - Date Issued
- 2017
- Identifier
- CFE0006858, ucf:51747
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006858
- Title
- Placement of Mode and Wavelength Converters for Throughput Enhancement in Optical Networks.
- Creator
-
Abdulrahman, Ruaa, Bassiouni, Mostafa, Chatterjee, Mainak, Zou, Changchun, University of Central Florida
- Abstract / Description
-
The success of recent experiments to transport data using combined wavelength division multiplexed (WDM) and mode-division multiplexed (MDM) transmission has generated optimism for the attainment of optical networks with unprecedented bandwidth capacity, exceeding the fundamental Shannon capacity limit attained by WDM alone. Optical mode converters and wavelength converters are devices that can be placed in future optical nodes (routers) to prevent or reduce the connection blocking rate and...
Show moreThe success of recent experiments to transport data using combined wavelength division multiplexed (WDM) and mode-division multiplexed (MDM) transmission has generated optimism for the attainment of optical networks with unprecedented bandwidth capacity, exceeding the fundamental Shannon capacity limit attained by WDM alone. Optical mode converters and wavelength converters are devices that can be placed in future optical nodes (routers) to prevent or reduce the connection blocking rate and consequently increase network throughput. In this thesis, the specific problem of the placement of mode converters (MC) and mode-wavelength converters (MWC) in combined mode and wavelength division multiplexing (MWDM) networks is investigated. Four previously proposed wavelength converter placement heuristics are extended to handle the placement of MC and MWC in MWDM networks. A simple but effective method for the placement of mode and wavelength converters in MWDM networks is proposed based on ranking the nodes with respect to the volume of received connection requests. The results of extensive simulation tests to evaluate the new method and compare its performance with the performance of the other four heuristics are presented. The thesis provides extensive comparison results among the five converter placement methods using different network topologies and under different network loads. The results demonstrate the effectiveness of the new proposed method in achieving lower blocking rates compared to the other more-complex converter placement heuristics.
Show less - Date Issued
- 2014
- Identifier
- CFE0005118, ucf:50756
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005118
- Title
- Measuring the evolving Internet ecosystem with exchange points.
- Creator
-
Ahmad, Mohammad Zubair, Guha, Ratan, Bassiouni, Mostafa, Chatterjee, Mainak, Jha, Sumit, Goldiez, Brian, University of Central Florida
- Abstract / Description
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The Internet ecosystem comprising of thousands of Autonomous Systems (ASes) now include Internet eXchange Points (IXPs) as another critical component in the infrastructure. Peering plays a significant part in driving the economic growth of ASes and is contributing to a variety of structural changes in the Internet. IXPs are a primary component of this peering ecosystem and are playing an increasing role not only in the topology evolution of the Internet but also inter-domain path routing. In...
Show moreThe Internet ecosystem comprising of thousands of Autonomous Systems (ASes) now include Internet eXchange Points (IXPs) as another critical component in the infrastructure. Peering plays a significant part in driving the economic growth of ASes and is contributing to a variety of structural changes in the Internet. IXPs are a primary component of this peering ecosystem and are playing an increasing role not only in the topology evolution of the Internet but also inter-domain path routing. In this dissertation we study and analyze the overall affects of peering and IXP infrastructure on the Internet. We observe IXP peering is enabling a quicker flattening of the Internet topology and leading to over-utilization of popular inter-AS links. Indiscriminate peering at these locations is leading to higher end-to-end path latencies for ASes peering at an exchange point, an effect magnified at the most popular worldwide IXPs. We first study the effects of recently discovered IXP links on the inter-AS routes using graph based approaches and find that it points towards the changing and flattening landscape in the evolution of the Internet's topology. We then study more IXP effects by using measurements to investigate the networks benefits of peering. We propose and implement a measurement framework which identifies default paths through IXPs and compares them with alternate paths isolating the IXP hop. Our system is running and recording default and alternate path latencies and made publicly available. We model the probability of an alternate path performing better than a default path through an IXP by identifying the underlying factors influencing the end-to end path latency. Our first-of-its-kind modeling study, which uses a combination of statistical and machine learning approaches, shows that path latencies depend on the popularity of the particular IXP, the size of the provider ASes of the networks peering at common locations and the relative position of the IXP hop along the path. An in-depth comparison of end-to-end path latencies reveal a significant percentage of alternate paths outperforming the default route through an IXP. This characteristic of higher path latencies is magnified in the popular continental exchanges as measured by us in a case study looking at the largest regional IXPs. We continue by studying another effect of peering which has numerous applications in overlay routing, Triangle Inequality Violations (TIVs). These TIVs in the Internet delay space are created due to peering and we compare their essential characteristics with overlay paths such as detour routes. They are identified and analyzed from existing measurement datasets but on a scale not carried out earlier. This implementation exhibits the effectiveness of GPUs in analyzing big data sets while the TIVs studied show that the a set of common inter-AS links create these TIVs. This result provides a new insight about the development of TIVs by analyzing a very large data set using GPGPUs.Overall our work presents numerous insights into the inner workings of the Internet's peering ecosystem. Our measurements show the effects of exchange points on the evolving Internet and exhibits their importance to Internet routing.
Show less - Date Issued
- 2013
- Identifier
- CFE0004802, ucf:49744
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004802
- Title
- Energy efficient routing towards a mobile sink using virtual coordinates in a wireless sensor network.
- Creator
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Rahmatizadeh, Rouhollah, Boloni, Ladislau, Turgut, Damla, Jha, Sumit, University of Central Florida
- Abstract / Description
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The existence of a coordinate system can often improve the routing in a wireless sensor network. While most coordinate systems correspond to the geometrical or geographical coordinates, in recent years researchers had proposed the use of virtual coordinates. Virtual coordinates depend only on the topology of the network as defined by the connectivity of the nodes, without requiring geographical information. The work in this thesis extends the use of virtual coordinates to scenarios where the...
Show moreThe existence of a coordinate system can often improve the routing in a wireless sensor network. While most coordinate systems correspond to the geometrical or geographical coordinates, in recent years researchers had proposed the use of virtual coordinates. Virtual coordinates depend only on the topology of the network as defined by the connectivity of the nodes, without requiring geographical information. The work in this thesis extends the use of virtual coordinates to scenarios where the wireless sensor network has a mobile sink. One reason to use a mobile sink is to distribute the energy consumption more evenly among the sensor nodes and thus extend the life-time of the network. We developed two algorithms, MS-DVCR and CU-DVCR which perform routing towards a mobile sink using virtual coordinates. In contrast to the baseline virtual coordinate routing MS-DVCR limits routing updates triggered by the sink movement to a local area around the sink. In contrast, CU-DVCR limits the route updates to a circular area on the boundary of the local area. We describe the design justification and the implementation of these algorithms. Using a set of experimental studies, we show that MS-DVCR and CU-DVCR achieve a lower energy consumption compared to the baseline virtual coordinate routing without any noticeable impact on routing performance. In addition, CU-DVCR provides a lower energy consumption than MS-DVCR for the case of a fast moving sink.
Show less - Date Issued
- 2014
- Identifier
- CFE0005402, ucf:50422
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005402
- Title
- Spectrum Map and its Application in Cognitive Radio Networks.
- Creator
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Debroy, Saptarshi, Chatterjee, Mainak, Bassiouni, Mostafa, Zou, Changchun, Jha, Sumit, Catbas, Necati, University of Central Florida
- Abstract / Description
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Recent measurements on radio spectrum usage have revealed the abundance of underutilizedbands of spectrum that belong to licensed users. This necessitated the paradigm shift from static to dynamic spectrum access. Cognitive radio based secondary networks thatutilize such unused spectrum holes in the licensed band, have been proposed as a possible solution to the spectrum crisis. The idea is to detect times when a particular licensed band is unused and use it for transmission without causing...
Show moreRecent measurements on radio spectrum usage have revealed the abundance of underutilizedbands of spectrum that belong to licensed users. This necessitated the paradigm shift from static to dynamic spectrum access. Cognitive radio based secondary networks thatutilize such unused spectrum holes in the licensed band, have been proposed as a possible solution to the spectrum crisis. The idea is to detect times when a particular licensed band is unused and use it for transmission without causing interference to the licensed user. We argue that prior knowledge about occupancy of such bands and the corresponding achievable performance metrics can potentially help secondary networks to devise effective strategiesto improve utilization.In this work, we use Shepard's method of interpolation to create a spectrum mapthat provides a spatial distribution of spectrum usage over a region of interest. It is achieved by intelligently fusing the spectrum usage reports shared by the secondary nodes at various locations. The obtained spectrum map is a continuous and differentiable 2-dimension distribution function in space. With the spectrum usage distribution known, we show how different radio spectrum and network performance metrics like channel capacity, secondary network throughput, spectral efficiency, and bit error rate can be estimated. We show the applicability of the spectrum map in solving the intra-cell channel allocation problem incentralized cognitive radio networks, such as IEEE 802.22. We propose a channel allocationscheme where the base station allocates interference free channels to the consumer premise equipments (CPE) using the spectrum map that it creates by fusing the spectrum usage information shared by some CPEs. The most suitable CPEs for information sharing arechosen on a dynamic basis using an iterative clustering algorithm. Next, we present a contention based media access control (MAC) protocol for distributed cognitive radio network. The unlicensed secondary users contend among themselves over a common control channel. Winners of the contention get to access the available channels ensuring high utilization and minimum collision with primary incumbent. Last, we propose a multi-channel, multi-hop routing protocol with secondary transmission power control. The spectrum map, created and maintained by a set of sensors, acts as the basis of finding the best route for every source destination pair. The proposed routing protocol ensures primary receiver protection and maximizes achievable link capacity.Through simulation experiments we show the correctness of the prediction model and how it can be used by secondary networks for strategic positioning of secondary transmitter-receiver pairs and selecting the best candidate channels. The simulation model mimics realistic distribution of TV stations for urban and non-urban areas. Results validate the nature and accuracy of estimation, prediction of performance metrics, and efficiency of the allocation process in an IEEE 802.22 network. Results for the proposed MAC protocol show high channel utilization with primary quality of service degradation within a tolerable limit. Performance evaluation of the proposed routing scheme reveals that it ensures primary receiver protection through secondary power control and maximizes route capacity.
Show less - Date Issued
- 2014
- Identifier
- CFE0005324, ucf:50515
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005324
- Title
- ALGORITHMS FOR DISCOVERING COMMUNITIES IN COMPLEX NETWORKS.
- Creator
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Balakrishnan, Hemant, Deo, Narsingh, University of Central Florida
- Abstract / Description
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It has been observed that real-world random networks like the WWW, Internet, social networks, citation networks, etc., organize themselves into closely-knit groups that are locally dense and globally sparse. These closely-knit groups are termed communities. Nodes within a community are similar in some aspect. For example in a WWW network, communities might consist of web pages that share similar contents. Mining these communities facilitates better understanding of their evolution and...
Show moreIt has been observed that real-world random networks like the WWW, Internet, social networks, citation networks, etc., organize themselves into closely-knit groups that are locally dense and globally sparse. These closely-knit groups are termed communities. Nodes within a community are similar in some aspect. For example in a WWW network, communities might consist of web pages that share similar contents. Mining these communities facilitates better understanding of their evolution and topology, and is of great theoretical and commercial significance. Community related research has focused on two main problems: community discovery and community identification. Community discovery is the problem of extracting all the communities in a given network, whereas community identification is the problem of identifying the community, to which, a given set of nodes belong. We make a comparative study of various existing community-discovery algorithms. We then propose a new algorithm based on bibliographic metrics, which addresses the drawbacks in existing approaches. Bibliographic metrics are used to study similarities between publications in a citation network. Our algorithm classifies nodes in the network based on the similarity of their neighborhoods. One of the drawbacks of the current community-discovery algorithms is their computational complexity. These algorithms do not scale up to the enormous size of the real-world networks. We propose a hash-table-based technique that helps us compute the bibliometric similarity between nodes in O(m ?) time. Here m is the number of edges in the graph and ?, the largest degree. Next, we investigate different centrality metrics. Centrality metrics are used to portray the importance of a node in the network. We propose an algorithm that utilizes centrality metrics of the nodes to compute the importance of the edges in the network. Removal of the edges in ascending order of their importance breaks the network into components, each of which represent a community. We compare the performance of the algorithm on synthetic networks with a known community structure using several centrality metrics. Performance was measured as the percentage of nodes that were correctly classified. As an illustration, we model the ucf.edu domain as a web graph and analyze the changes in its properties like densification power law, edge density, degree distribution, diameter, etc., over a five-year period. Our results show super-linear growth in the number of edges with time. We observe (and explain) that despite the increase in average degree of the nodes, the edge density decreases with time.
Show less - Date Issued
- 2006
- Identifier
- CFE0001473, ucf:47085
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0001473
- Title
- HURRICANE EVACUATION: ORIGIN, ROUTE AND DESTINATION.
- Creator
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Dixit, Vinayak, Radwan, Essam, University of Central Florida
- Abstract / Description
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Recent natural disasters have highlighted the need to evacuate people as quickly as possible. During hurricane Rita in 2005, people were stuck in queue buildups and large scale congestions, due to improper use of capacity, planning and inadequate response to vehicle breakdown, flooding and accidents. Every minute is precious in situation of such disaster scenarios. Understanding evacuation demand loading is an essential part of any evacuation planning. One of the factors often understood to...
Show moreRecent natural disasters have highlighted the need to evacuate people as quickly as possible. During hurricane Rita in 2005, people were stuck in queue buildups and large scale congestions, due to improper use of capacity, planning and inadequate response to vehicle breakdown, flooding and accidents. Every minute is precious in situation of such disaster scenarios. Understanding evacuation demand loading is an essential part of any evacuation planning. One of the factors often understood to effect evacuation, but not modeled has been the effect of a previous hurricane. This has also been termed as the 'Katrina Effect', where, due to the devastation caused by hurricane Katrina, large number of people decided to evacuate during Hurricane Rita, which hit Texas three weeks after Katrina hit Louisiana. An important aspect influencing the rate of evacuation loading is Evacuation Preparation Time also referred to as 'Mobilization time' in literature. A methodology to model the effect of a recent past hurricane on the mobilization times for evacuees in an evacuation has been presented utilizing simultaneous estimation techniques. The errors for the two simultaneously estimated models were significantly correlated, confirming the idea that a previous hurricane does significantly affect evacuation during a subsequent hurricane. The results show that the home ownership, number of individuals in the household, income levels, and level/risk of surge were significant in the model explaining the mobilization times for the households. Pet ownership and number of kids in the households, known to increase the mobilization times during isolated hurricanes, were not found to be significant in the model. Evacuation operations are marred by unexpected blockages, breakdown of vehicles and sudden flooding of transportation infrastructure. A fast and accurate simulation model to incorporate flexibility into the evacuation planning procedure is required to react to such situations. Presently evacuation guidelines are prepared by the local emergency management, by testing various scenarios utilizing micro-simulation, which is extremely time consuming and do not provide flexibility to evacuation plans. To gain computational speed there is a need to move away from the level of detail of a micro-simulation to more aggregated simulation models. The Cell Transmission Model which is a mesoscopic simulation model is considered, and compared with VISSIM a microscopic simulation model. It was observed that the Cell Transmission Model was significantly faster compared to VISSIM, and was found to be accurate. The Cell Transmission model has a nice linear structure, which is utilized to construct Linear Programming Problems to determine optimal strategies. Optimization models were developed to determine strategies for optimal scheduling of evacuation orders and optimal crossover locations for contraflow operations on freeways. A new strategy termed as 'Dynamic Crossovers Strategy' is proposed to alleviate congestion due to lane blockages (due to vehicle breakdowns, incidents etc.). This research finds that the strategy of implementing dynamic crossovers in the event of lane blockages does improve evacuation operations. The optimization model provides a framework within which optimal strategies are determined quickly, without the need to test multiple scenarios using simulation. Destination networks are the cause of the main bottlenecks for evacuation routes, such aspects of transportation networks are rarely studied as part of evacuation operations. This research studies destination networks from a macroscopic perspective. Various relationships between network level macroscopic variables (Average Flow, Average Density and Average speed) over the network were studied. Utilizing these relationships, a "Network Breathing Strategy" was proposed to improve dissipation of evacuating traffic into the destination networks. The network breathing strategy is a cyclic process of allowing vehicles to enter the network till the network reaches congestion, which is followed by closure of their entry into the network until the network reaches an acceptable state. After which entrance into the network is allowed again. The intuitive motivation behind this methodology is to ensure that the network does not remain in congested conditions. The term 'Network Breathing' was coined due to the analogy seen between this strategy to the process of breathing, where vehicles are inhaled by the network (vehicles allowed in) and dissipated by the network (vehicles are not allowed in). It is shown that the network breathing improves the dissipation of vehicle into the destination network. Evacuation operations can be divided into three main levels: at the origin (region at risk), routes and destination. This research encompasses all the three aspects and proposes a framework to assess the whole system in its entirety. At the Origin the demand dictates when to schedule evacuation orders, it also dictates the capacity required on different routes. These breakthroughs will provide a framework for a real time Decision Support System which will help emergency management official make decisions faster and on the fly.
Show less - Date Issued
- 2008
- Identifier
- CFE0002051, ucf:47589
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0002051
- Title
- MEDIUM ACCESS CONTROL PROTOCOLS AND ROUTING ALGORITHMS FOR WIRELESS SENSOR NETWORKS.
- Creator
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Bag, Anirban, Bassiouni, Mostafa, University of Central Florida
- Abstract / Description
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In recent years, the development of a large variety of mobile computing devices has led to wide scale deployment and use of wireless ad hoc and sensor networks. Wireless Sensor Networks consist of battery powered, tiny and cheap "motes", having sensing and wireless communication capabilities. Although wireless motes have limited battery power, communication and computation capabilities, the range of their application is vast. In the first part of the dissertation, we have addressed the...
Show moreIn recent years, the development of a large variety of mobile computing devices has led to wide scale deployment and use of wireless ad hoc and sensor networks. Wireless Sensor Networks consist of battery powered, tiny and cheap "motes", having sensing and wireless communication capabilities. Although wireless motes have limited battery power, communication and computation capabilities, the range of their application is vast. In the first part of the dissertation, we have addressed the specific application of Biomedical Sensor Networks. To solve the problem of data routing in these networks, we have proposed the Adaptive Least Temperature Routing (ALTR) algorithm that reduces the average temperature rise of the nodes in the in-vivo network while routing data efficiently. For delay sensitive biomedical applications, we proposed the Hotspot Preventing Routing (HPR) algorithm which avoids the formation of hotspots (regions having very high temperature) in the network. HPR forwards the packets using the shortest path, bypassing the regions of high temperature and thus significantly reduces the average packet delivery delay, making it suitable for real-time applications of in-vivo networks. We also proposed another routing algorithm suitable for being used in a network of id-less biomedical sensor nodes, namely Routing Algorithm for networks of homogeneous and Id-less biomedical sensor Nodes (RAIN). Finally we developed Biocomm, a cross-layer MAC and Routing protocol co-design for Biomedical Sensor Networks, which optimizes the overall performance of an in-vivo network through cross-layer interactions. We performed extensive simulations to show that the proposed Biocomm protocol performs much better than the other existing MAC and Routing protocols in terms of preventing the formation of hotspots, reducing energy consumption of nodes and preventing network congestion when used in an in-vivo network. In the second part of the dissertation, we have addressed the problems of habitat-monitoring sensor networks, broadcast algorithms for sensor networks and the congestion problem in sensor networks as well as one non-sensor network application, namely, on-chip communication networks. Specifically, we have proposed a variation of HPR algorithm, called Hotspot Preventing Adaptive Routing (HPAR) algorithm, for efficient data routing in Networks On-Chip catering to their specific hotspot prevention issues. A protocol similar to ALTR has been shown to perform well in a sensor network deployed for habitat monitoring. We developed a reliable, low overhead broadcast algorithm for sensor networks namely Topology Adaptive Gossip (TAG) algorithm. To reduce the congestion problem in Wireless Sensor Networks, we proposed a tunable cross-layer Congestion Reducing Medium Access Control (CRMAC) protocol that utilizes buffer status information from the Network layer to give prioritized medium access to congested nodes in the MAC layer and thus preventing congestion and packet drops. CRMAC can also be easily tuned to satisfy different application-specific performance requirements. With the help of extensive simulation results we have shown how CRMAC can be adapted to perform well in different applications of Sensor Network like Emergency Situation that requires a high network throughput and low packet delivery latency or Long-term Monitoring application requiring energy conservation.
Show less - Date Issued
- 2007
- Identifier
- CFE0001915, ucf:47480
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0001915
- Title
- NEURAL NETWORK TREES AND SIMULATION DATABASES: NEW APPROACHES FOR SIGNALIZED INTERSECTION CRASH CLASSIFICATION AND PREDICTION.
- Creator
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Nawathe, Piyush, Abdel-Aty, Mohamed, University of Central Florida
- Abstract / Description
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Intersection related crashes form a significant proportion of the crashes occurring on roadways. Many organizations such as the Federal Highway Administration (FHWA) and American Association of State Highway and Transportation Officials (AASHTO) are considering intersection safety improvement as one of their top priority areas. This study contributes to the area of safety of signalized intersections by identifying the traffic and geometric characteristics that affect the different types of...
Show moreIntersection related crashes form a significant proportion of the crashes occurring on roadways. Many organizations such as the Federal Highway Administration (FHWA) and American Association of State Highway and Transportation Officials (AASHTO) are considering intersection safety improvement as one of their top priority areas. This study contributes to the area of safety of signalized intersections by identifying the traffic and geometric characteristics that affect the different types of crashes. The first phase of this thesis was to classify the crashes occurring at signalized intersections into rear-end, angle, turn and sideswipe crash types based on the traffic and geometric properties of the intersections and the conditions at the time of the crashes. This was achieved by using an innovative approach developed in this thesis "Neural Network Trees". The first neural network model built in the Neural Network tree classified the crashes either into rear end and sideswipe or into angle and turn crashes. The next models further classified the crashes into their individual types. Two different neural network methods (MLP and PNN) were used in classification, and the neural network with a better performance was selected for each model. For these models, the significant variables were identified using the forward sequential selection method. Then a large simulation database was built that contained all possible combinations of intersections subjected to various crash conditions. The collision type of crashes was predicted for this simulation database and the output obtained was plotted along with the input variables to obtain a relationship between the input and output variables. For example, the analysis showed that the number of rear end and sideswipe crashes increase relative to the angle and turn crashes when there is an increase in the major and minor roadways' AADT and speed limits, surface conditions, total left turning lanes, channelized right turning lanes for the major roadway and the protected left turning lanes for the minor roadway, but decrease when the light conditions are dark. The next phase in this study was to predict the frequency of different types of crashes at signalized intersections by using the geometric and traffic characteristics of the intersections. A high accuracy in predicting the crash frequencies was obtained by using another innovative method where the intersections were first classified into two different types named the "safe" and "unsafe" intersections based on the total number of lanes at the intersections and then the frequency of crashes was predicted for each type of intersections separately. This method consisted of identifying the best neural network for each step of the analysis, selecting significant variables, using a different simulation database that contained all possible combinations of intersections and then plotting each input variable with the average output to obtain the pattern in which the frequency of crashes will vary based on the changes in the geometric and traffic characteristics of the intersections. The patterns indicated that an increase in the number of lanes of the major roadway, lanes of the minor roadway and the AADT on the major roadway leads to an increased crashes of all types, whereas an increase in protected left turning lanes on the major road increases the rear end and sideswipe crashes but decreases the angle, turning and overall crash frequencies. The analyses performed in this thesis were possible due to a diligent data collection effort. Traffic and geometric characteristics were obtained from multiple sources for 1562 signalized intersections in Brevard, Hillsborough, Miami-Dade, Seminole and Orange counties and the city of Orlando in Florida. The crash database for these intersections contained 27,044 crashes. This research sheds a light on the characteristics of different types of crashes. The method used in classifying crashes into their respective collision types provides a deeper insight on the characteristics of each type of crash and can be helpful in mitigating a particular type of crash at an intersection. The second analysis carried out has a three fold advantage. First, it identifies if an intersection can be considered safe for different crash types. Second, it accurately predicts the frequencies of total, rear end, angle, sideswipe and turn crashes. Lastly, it identifies the traffic and geometric characteristics of signalized intersections that affect each of these crash types. Thus the models developed in this thesis can be used to identify the specific problems at an intersection, and identify the factors that should be changed to improve its safety
Show less - Date Issued
- 2005
- Identifier
- CFE0000664, ucf:46524
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0000664
