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Pages
- Title
- Gamification of Visual Search in Real World Scenes.
- Creator
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Hess, Alyssa, Neider, Mark, Szalma, James, Bohil, Corey, Paulson, Daniel, University of Central Florida
- Abstract / Description
-
Gamification, or the application of game-like features in non-game contexts, has been growing in popularity over the last five years. Specifically, the successful gamification of applications (such as Waze, Foursquare, and Fitocracy) has begun a spike in gamification of more complex tasks, such as learning to use AutoCAD or Photoshop. However, much is unknown about the psychological mapping of gamification or how it translates to behavioral outcomes. This dissertation aims to compare three...
Show moreGamification, or the application of game-like features in non-game contexts, has been growing in popularity over the last five years. Specifically, the successful gamification of applications (such as Waze, Foursquare, and Fitocracy) has begun a spike in gamification of more complex tasks, such as learning to use AutoCAD or Photoshop. However, much is unknown about the psychological mapping of gamification or how it translates to behavioral outcomes. This dissertation aims to compare three distinct styles of gamification (avatars, points and feedback, and leaderboards) onto the three basic psychological needs (autonomy, competence, and relatedness). It will assess behavioral outcomes on a visual search task when gamification styles are used separately, compared against all three styles used in concert. The task chosen is a camouflage visual search task. This task was selected because it is both boring (as indicated by the Flow Short Scale) and difficult (as indicated by previous work). These features make it the ideal task to gamify. Results indicated that only in the full gamification condition was response time significantly faster than in the control condition, or no gamification. However, ANOVA evaluating differences in enjoyment, motivation, and stress indicated differences among the groups, suggesting that gamification may elicit psychological outcomes that may not necessarily manifest into behavioral outcomes. ANCOVA were used to evaluate group differences using relevant survey measures as covariates. These tests indicated differences among groups in all behavioral measures, though these differences were most pronounced in response time measures. Future directions involving gamification based on personality type, as well as suggestions on best practice for gamification in the future are discussed.
Show less - Date Issued
- 2017
- Identifier
- CFE0006601, ucf:51264
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006601
- Title
- FLORIDA PUBLIC SCHOOL ADMINISTRATORS' KNOWLEDGE OF LEGAL ISSUES RELATED TO SEARCH AND SEIZURE.
- Creator
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Slack, Catherine, Murray, Kenneth, University of Central Florida
- Abstract / Description
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School officials trying to deter drug use, combat crime, and shore up security are conducting searches that are landing school in legal trouble for violating students' constitutional rights. In 1993, West Virginia Supreme Court ruled that a strip search of a student suspected of stealing money was illegal (State of West Virginia ex rel Gilford v. Mark Anthony B., 1993). In another case, a federal appellate court held that a strip search of a student for suspected drug possession was...
Show moreSchool officials trying to deter drug use, combat crime, and shore up security are conducting searches that are landing school in legal trouble for violating students' constitutional rights. In 1993, West Virginia Supreme Court ruled that a strip search of a student suspected of stealing money was illegal (State of West Virginia ex rel Gilford v. Mark Anthony B., 1993). In another case, a federal appellate court held that a strip search of a student for suspected drug possession was reasonable, although no drugs were found (Cornfield v. Consolidated High School District No. 230, 1993). Improper searches of students, lockers and automobiles can result in hundreds of thousands of dollars in civil liability, costs and attorney fees. This study collected data on administrative knowledge in the area of search and seizure. The analyzed data served to (a) determine if administrators across the state of Florida have a general understanding of the laws regarding search and seizure; (b) identify demographic areas that demonstrate a lack of knowledge related to search and seizure; and (c) suggest improvements to current educational leadership courses of study, state-wide staff development offerings, and ideas for possible conference topics. The study involved responses from questionnaires received from 139 public school administrators in Florida (17% of the 810 randomly sampled elementary, middle, and high school principals). Analysis of data revealed that more than one-third of the respondents fell below the mean, with no significant difference between building levels or metropolitan statistical area.
Show less - Date Issued
- 2005
- Identifier
- CFE0000729, ucf:46625
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0000729
- Title
- EXPLORING TECHNIQUES FOR MEASUREMENT AND IMPROVEMENT OF DATA QUALITY WITH APPLICATION TO DETERMINATION OF THE LAST KNOWN POSITION (LKP) IN SEARCH AND RESCUE (SAR) DATA.
- Creator
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Wakchaure, Abhijit, Hua, Kien, University of Central Florida
- Abstract / Description
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There is a tremendous volume of data being generated in today's world. As organizations around the globe realize the increased importance of their data as being a valuable asset in gaining a competitive edge in a fast-paced and a dynamic business world, more and more attention is being paid to the quality of the data. Advances in the fields of data mining, predictive modeling, text mining, web mining, business intelligence, health care analytics, etc. all depend on clean, accurate data. That...
Show moreThere is a tremendous volume of data being generated in today's world. As organizations around the globe realize the increased importance of their data as being a valuable asset in gaining a competitive edge in a fast-paced and a dynamic business world, more and more attention is being paid to the quality of the data. Advances in the fields of data mining, predictive modeling, text mining, web mining, business intelligence, health care analytics, etc. all depend on clean, accurate data. That one cannot effectively mine data, which is dirty, comes as no surprise. This research is an exploratory study of different domain data sets, addressing the data quality issues specific to each domain, identifying the challenges faced and arriving at techniques or methodologies for measuring and improving the data quality. The primary focus of the research is on the SAR or Search and Rescue dataset, identifying key issues related to data quality therein and developing an algorithm for improving the data quality. SAR missions which are routinely conducted all over the world show a trend of increasing mission costs. Retrospective studies of historic SAR data not only allow for a detailed analysis and understanding of SAR incidents and patterns, but also form the basis for generating probability maps, analytical data models, etc., which allow for an efficient use of valuable SAR resources and their distribution. One of the challenges with regards to the SAR dataset is that the collection process is not perfect. Often, the LKP or the Last Known Position is not known or cannot be arrived at. The goal is to fully or partially geocode the LKP for as many data points as possible, identify those data points where the LKP cannot be geocoded at all, and further highlight the underlying data quality issues. The SAR Algorithm has been developed, which makes use of partial or incomplete information, cleans and validates the data, and further extracts address information from relevant fields to successfully geocode the data. The algorithm improves the geocoding accuracy and has been validated by a set of approaches.
Show less - Date Issued
- 2011
- Identifier
- CFE0004050, ucf:49142
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004050
- Title
- Techniques for boosting the performance in Content-Based Image Retrieval Systems.
- Creator
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Yu, Ning, Hua, Kien, Hughes, Charles, Dutton, Ronald, Wang, Chung-Ching, University of Central Florida
- Abstract / Description
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Content-Based Image Retrieval has been an active research area for decades. In a CBIR system, one or more images are used as query to search for similar images. The similarity is measured on the low level features, such as color, shape, edge, texture. First, each image is processed and visual features are extracted. Therefore each image becomes a point in the feature space. Then, if two images are close to each other in the feature space, they are considered similar. That is, the k nearest...
Show moreContent-Based Image Retrieval has been an active research area for decades. In a CBIR system, one or more images are used as query to search for similar images. The similarity is measured on the low level features, such as color, shape, edge, texture. First, each image is processed and visual features are extracted. Therefore each image becomes a point in the feature space. Then, if two images are close to each other in the feature space, they are considered similar. That is, the k nearest neighbors are considered the most similar images to the query image. In this K-Nearest Neighbor (k-NN) model, semantically similar images are assumed to be clustered together in a single neighborhood in the high-dimensional feature space. Unfortunately semantically similar images with different appearances are often clustered into distinct neighborhoods, which might scatter in the feature space. Hence, confinement of the search results to a single neighborhood is the latent reason of the low recall rate of typical nearest neighbor techniques. In this dissertation, a new image retrieval technique - the Query Decomposition (QD) model is introduced. QD facilitates retrieval of semantically similar images from multiple neighborhoods in the feature space and hence bridges the semantic gap between the images' low-level feature and the high-level semantic meaning. In the QD model, a query may be decomposed into multiple subqueries based on the user's relevance feedback to cover multiple image clusters which contain semantically similar images. The retrieval results are the k most similar images from multiple discontinuous relevant clusters. To apply the benefit from QD study, a mobile client-side relevance feedback study was conducted. With the proliferation of handheld devices, the demand of multimedia information retrieval on mobile devices has attracted more attention. A relevance feedback information retrieval process usually includes several rounds of query refinement. Each round incurs exchange of tens of images between the mobile device and the server. With limited wireless bandwidth, this process can incur substantial delay making the system unfriendly to use. The Relevance Feedback Support (RFS) structure that was designed in QD technique was adopted for Client-side Relevance Feedback (CRF). Since relevance feedback is done on client side, system response is instantaneous significantly enhancing system usability. Furthermore, since the server is not involved in relevance feedback processing, it is able to support thousands more users simultaneously. As the QD technique improves on the accuracy of CBIR systems, another study, which is called In-Memory relevance feedback is studied in this dissertation. In the study, we improved the efficiency of the CBIR systems. Current methods rely on searching the database, stored on disks, in each round of relevance feedback. This strategy incurs long delay making relevance feedback less friendly to the user, especially for very large databases. Thus, scalability is a limitation of existing solutions. The proposed in-memory relevance feedback technique substantially reduce the delay associated with feedback processing, and therefore improve system usability. A data-independent dimensionality-reduction technique is used to compress the metadata to build a small in-memory database to support relevance feedback operations with minimal disk accesses. The performance of this approach is compared with conventional relevance feedback techniques in terms of computation efficiency and retrieval accuracy. The results indicate that the new technique substantially reduces response time for user feedback while maintaining the quality of the retrieval. In the previous studies, the QD technique relies on a pre-defined Relevance SupportSupport structure. As the result and user experience indicated that the structure might confine the search range and affect the result. In this dissertation, a novel Multiple Direction Search framework for semi-automatic annotation propagation is studied. In this system, the user interacts with the system to provide example images and the corresponding annotations during the annotation propagation process. In each iteration, the example images are dynamically clustered and the corresponding annotations are propagated separately to each cluster: images in the local neighborhood are annotated. Furthermore, some of those images are returned to the user for further annotation. As the user marks more images, the annotation process goes into multiple directions in the feature space. The query movements can be treated as multiple path navigation. Each path could be further split based on the user's input. In this manner, the system provides accurate annotation assistance to the user - images with the same semantic meaning but different visual characteristics can be handled effectively. From comprehensive experiments on Corel and U. of Washington image databases, the proposed technique shows accuracy and efficiency on annotating image databases.
Show less - Date Issued
- 2011
- Identifier
- CFE0004182, ucf:49058
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004182
- Title
- Detecting Submerged Remains: Controlled Research Using Side-Scan Sonar to Detect Proxy Cadavers.
- Creator
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Healy, Carrie, Schultz, John, Dupras, Tosha, Walker, John, University of Central Florida
- Abstract / Description
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While side-scan sonar has become a valuable geophysical tool for forensic water searches, controlled research is paramount to determine the best practices for searches in aquatic environments as it provides a structured environment in which to investigate variables that influence the effectiveness of the technology and provides valuable experience for sonar operators. The purpose of this research is to conduct controlled research in order to evaluate the applicability of side-scan sonar to...
Show moreWhile side-scan sonar has become a valuable geophysical tool for forensic water searches, controlled research is paramount to determine the best practices for searches in aquatic environments as it provides a structured environment in which to investigate variables that influence the effectiveness of the technology and provides valuable experience for sonar operators. The purpose of this research is to conduct controlled research in order to evaluate the applicability of side-scan sonar to searches involving submerged firearms and proxy cadavers. In addition, the best practices for employing this technology in forensic searches in freshwater ponds and lakes in a humid, subtropical environment in Central Florida would be developed. Five street-level firearms were submerged in a pond, and two sets of three pig carcasses (Sus scrofa), utilized as proxies for human bodies, were staked to the bottom of a pond for this research. Transects were conducted over the firearms and the pig carcasses utilizing side-scan sonar. The first set of pig carcasses represented a child size (30-32 kg) and the second set a small adult size (51-54 kg). Results show that firearms were not detected due to the terrain and small size. However, this technology successfully located small to medium-sized proxy carcasses on a flat, sandy lake bottom when experienced operators were conducting the search. Conversely, vegetation obscured submerged bodies. While the smaller carcasses were difficult to detect throughout the data collection, medium-sized carcasses were easily discerned. Moreover, the medium-sized carcasses decomposed at the same rate as previous studies and were visible throughout each stage of decomposition. Finally, employing a 900 kHz frequency with a 20 m swath-width provided the best search parameters. Therefore, in the appropriate conditions,side-scan sonar is an effective tool for locating submerged bodies in freshwater lakes and ponds in a humid, subtropical environment.
Show less - Date Issued
- 2012
- Identifier
- CFE0004544, ucf:49257
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004544
- Title
- The Effect of Public Information Sources on Satisfaction with Patient Search for a Physician.
- Creator
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Loyal, Michael, Wan, Thomas, Fottler, Myron, Noblin, Alice, Golden, Adam, University of Central Florida
- Abstract / Description
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The purpose of this research study is to examine the effect of public information sources on an individual's satisfaction with the search process undertaken to select a physician. A quasi-experimental research design was adopted to randomly divide the medical staff of a large central Florida medical group into control and intervention groups of approximately 77 physicians each. The intervention involved insertion of the website address to online physician report cards on to each intervention...
Show moreThe purpose of this research study is to examine the effect of public information sources on an individual's satisfaction with the search process undertaken to select a physician. A quasi-experimental research design was adopted to randomly divide the medical staff of a large central Florida medical group into control and intervention groups of approximately 77 physicians each. The intervention involved insertion of the website address to online physician report cards on to each intervention group physician's profile in the physician directory on the medical group's website. After two months, data were collected consisting of all individuals who had scheduled first-time appointments with one of the medical group's physicians during the two-month intervention period. A random sample of patients was drawn from each group and sample members were mailed a 62-item questionnaire along with a cover letter, summary of the research and postage-paid reply envelope. A total of 706 questionnaires were mailed and 61 completed questionnaires were returned, an 8.64% response rate.Intent-to-treat analysis was conducted using independent-samples t-tests to compare the research study's continuous variables' mean scores for control and intervention group participants. The analysis revealed no significant difference in scores for control and intervention groups with the exceptions that the control group was somewhat more committed to conducting a search and selecting a new physician. The control group said the physician's communications skills influenced their satisfaction with the search and selection of a new physician quite a lot while the intervention group said physician communication skills somewhat influenced their satisfaction with search and selection.Results of the covariance structure analysis demonstrated that information use and level of commitment to search and select a new physician independently predict search satisfaction. As information use and search commitment increase, a patient's satisfaction with the search increases as well. Furthermore, as information use increases, the variety of information sources relied upon or used also increases. The findings support the alternative hypothesis that the positive or direct effect of physician report cards is demonstrated in the time and cost of patient search for a physician for both intervention and control groups. One other alternative hypothesis was partially supported, i.e., the effect of household income is confirmed in patient search and satisfaction in selecting a physician. The alternative hypotheses that proposed that physician report cards are more likely to be used to search for a medical specialist and that physician experience, office location and accepted insurance effect patient search and selection of a physician were not tested. Two other alternative hypotheses were rejected. The research findings also indicated that predictors of health care information search satisfaction vary based upon the environment and contextual factors in which the search is conducted.
Show less - Date Issued
- 2013
- Identifier
- CFE0005030, ucf:49992
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005030
- Title
- ALAYZING THE EFFECTS OF MODULARITY ON SEARCH SPACES.
- Creator
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Garibay, Ozlem, Wu, Annie, University of Central Florida
- Abstract / Description
-
We are continuously challenged by ever increasing problem complexity and the need to develop algorithms that can solve complex problems and solve them within a reasonable amount of time. Modularity is thought to reduce problem complexity by decomposing large problems into smaller and less complex subproblems. In practice, introducing modularity into evolutionary algorithm representations appears to improve search performance; however, how and why modularity improves performance is not well...
Show moreWe are continuously challenged by ever increasing problem complexity and the need to develop algorithms that can solve complex problems and solve them within a reasonable amount of time. Modularity is thought to reduce problem complexity by decomposing large problems into smaller and less complex subproblems. In practice, introducing modularity into evolutionary algorithm representations appears to improve search performance; however, how and why modularity improves performance is not well understood. In this thesis, we seek to better understand the effects of modularity on search. In particular, what are the effects of module creation on the search space structure and how do these structural changes affect performance? We define a theoretical and empirical framework to study modularity in evolutionary algorithms. Using this framework, we provide evidence of the following. First, not all types of modularity have an effect on search. We can have highly modular spaces that in essence are equivalent to simpler non-modular spaces. This is the case, because these spaces achieve higher degree of modularity without changing the fundamental structure of the search space. Second, for the cases when modularity actually has an effect on the fundamental structure of the search space, if left without guidance, it would only crowd and complicate the space structure resulting in a harder space for most search algorithms. Finally, we have the case when modularity not only has an effect in the search space structure, but most importantly, module creation can be guided by problem domain knowledge. When this knowledge can be used to estimate the value of a module in terms of its contribution toward building the solution, then modularity is extremely effective. It is in this last case that creating high value modules or low value modules has a direct and decisive impact on performance. The results presented in this thesis help to better understand, in a principled way, the effects of modularity on search. Better understanding the effects of modularity on search is a step forward in the larger issue of evolutionary search applied to increasingly complex problems.
Show less - Date Issued
- 2008
- Identifier
- CFE0002490, ucf:47680
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0002490
- Title
- Analysis of large-scale population genetic data using efficient algorithms and data structures.
- Creator
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Naseri, Ardalan, Zhang, Shaojie, Hughes, Charles, Yooseph, Shibu, Zhi, Degui, University of Central Florida
- Abstract / Description
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With the availability of genotyping data of very large samples, there is an increasing need for tools that can efficiently identify genetic relationships among all individuals in the sample. Modern biobanks cover genotypes up to 0.1%-1% of an entire large population. At this scale, genetic relatedness among samples is ubiquitous. However, current methods are not efficient for uncovering genetic relatedness at such a scale. We developed a new method, Random Projection for IBD Detection (RaPID)...
Show moreWith the availability of genotyping data of very large samples, there is an increasing need for tools that can efficiently identify genetic relationships among all individuals in the sample. Modern biobanks cover genotypes up to 0.1%-1% of an entire large population. At this scale, genetic relatedness among samples is ubiquitous. However, current methods are not efficient for uncovering genetic relatedness at such a scale. We developed a new method, Random Projection for IBD Detection (RaPID), for detecting Identical-by-Descent (IBD) segments, a fundamental concept in genetics in large panels. RaPID detects all IBD segments over a certain length in time linear to the sample size. We take advantage of an efficient population genotype index, Positional BWT (PBWT), by Richard Durbin. PBWT achieves linear time query of perfectly identical subsequences among all samples. However, the original PBWT is not tolerant to genotyping errors which often interrupt long IBD segments into short fragments. The key idea of RaPID is that the problem of approximate high-resolution matching over a long range can be mapped to the problem of exact matching of low-resolution subsampled sequences with high probability. PBWT provides an appropriate data structure for bi-allelic data. With the increasing sample sizes, more multi-allelic sites are expected to be observed. Hence, there is a necessity to handle multi-allelic genotype data. We also introduce a multi-allelic version of the original Positional Burrows-Wheeler Transform (mPBWT).The increasingly large cohorts of whole genome genotype data present an opportunity for searching genetically related people within a large cohort to an individual. At the same time, doing so efficiently presents a challenge. The PBWT algorithm offers constant time matching between one haplotype and an arbitrarily large panel at each position, but only for the maximal matches. We used the PBWT data structure to develop a method to search for all matches of a given query in a panel. The matches larger than a given length correspond to the all shared IBD segments of certain lengths between the query and other individuals in the panel. The time complexity of the proposed method is independent from the number of individuals in the panel. In order to achieve a time complexity independent from the number of haplotypes, additional data structures are introduced.Some regions of genome may be shared by multiple individuals rather than only a pair. Clusters of identical haplotypes could reveal information about the history of intermarriage, isolation of a population and also be medically important. We propose an efficient method to find clusters of identical segments among individuals in a large panel, called cPBWT, using PBWT data structure. The time complexity of finding all clusters of identical matches is linear to the sample size. Human genome harbors several runs of homozygous sites (ROHs) where identical haplotypes are inherited from each parent. We applied cPBWT on UK-Biobank and searched for clusters of ROH region that are shared among multiple. We discovered strong associations between ROH regions and some non-cancerous diseases, specifically auto-immune disorders.
Show less - Date Issued
- 2018
- Identifier
- CFE0007764, ucf:52393
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007764
- Title
- PHONEME-BASED VIDEO INDEXING USING PHONETIC DISPARITY SEARCH.
- Creator
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Leon-Barth, Carlos, DeMara, Ronald, University of Central Florida
- Abstract / Description
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This dissertation presents and evaluates a method to the video indexing problem by investigating a categorization method that transcribes audio content through Automatic Speech Recognition (ASR) combined with Dynamic Contextualization (DC), Phonetic Disparity Search (PDS) and Metaphone indexation. The suggested approach applies genome pattern matching algorithms with computational summarization to build a database infrastructure that provides an indexed summary of the original audio content....
Show moreThis dissertation presents and evaluates a method to the video indexing problem by investigating a categorization method that transcribes audio content through Automatic Speech Recognition (ASR) combined with Dynamic Contextualization (DC), Phonetic Disparity Search (PDS) and Metaphone indexation. The suggested approach applies genome pattern matching algorithms with computational summarization to build a database infrastructure that provides an indexed summary of the original audio content. PDS complements the contextual phoneme indexing approach by optimizing topic seek performance and accuracy in large video content structures. A prototype was established to translate news broadcast video into text and phonemes automatically by using ASR utterance conversions. Each phonetic utterance extraction was then categorized, converted to Metaphones, and stored in a repository with contextual topical information attached and indexed for posterior search analysis. Following the original design strategy, a custom parallel interface was built to measure the capabilities of dissimilar phonetic queries and provide an interface for result analysis. The postulated solution provides evidence of a superior topic matching when compared to traditional word and phoneme search methods. Experimental results demonstrate that PDS can be 3.7% better than the same phoneme query, Metaphone search proved to be 154.6% better than the same phoneme seek and 68.1 % better than the equivalent word search.
Show less - Date Issued
- 2010
- Identifier
- CFE0003480, ucf:48979
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0003480
- Title
- MongoDB Incidence Response.
- Creator
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Morales, Cory, Lang, Sheau-Dong, Zou, Changchun, Guha, Ratan, University of Central Florida
- Abstract / Description
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NoSQL (Not only SQL) databases have been gaining some popularity over the last few years. Such big companies as Expedia, Shutterfly, MetLife, and Forbes use NoSQL databases to manage data on different projects. These databases can contain a variety of information ranging from nonproprietary data to personally identifiable information like social security numbers. Databases run the risk of cyber intrusion at all times. This paper gives a brief explanation of NoSQL and thoroughly explains a...
Show moreNoSQL (Not only SQL) databases have been gaining some popularity over the last few years. Such big companies as Expedia, Shutterfly, MetLife, and Forbes use NoSQL databases to manage data on different projects. These databases can contain a variety of information ranging from nonproprietary data to personally identifiable information like social security numbers. Databases run the risk of cyber intrusion at all times. This paper gives a brief explanation of NoSQL and thoroughly explains a method of Incidence Response with MongoDB, a NoSQL database provider. This method involves an automated process with a new self-built software tool that analyzing MongoDB audit log's and generates an html page with indicators to show possible intrusions and activities on the instance of MongoDB. When dealing with NoSQL databases there is a lot more to consider than with the traditional RDMS's, and since there is not a lot of out of the box support forensics tools can be very helpful.
Show less - Date Issued
- 2016
- Identifier
- CFE0006538, ucf:51356
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006538
- Title
- Modeling Dense Storage Systems With Location Uncertainty.
- Creator
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Awwad, Mohamed, Pazour, Jennifer, Elshennawy, Ahmad, Thompson, William, Leon, Steven, University of Central Florida
- Abstract / Description
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This dissertation focuses on developing models to study the problem of searching and retrieving items in a dense storage environment. We consider a special storage configuration called an inverted T configuration, which has one horizontal and one vertical aisle. Inverted T configurations have fewer aisles than a traditional aisle-based storage environment. This increases the storage density; however, requires that some items to be moved out of the way to gain access to other more deeply...
Show moreThis dissertation focuses on developing models to study the problem of searching and retrieving items in a dense storage environment. We consider a special storage configuration called an inverted T configuration, which has one horizontal and one vertical aisle. Inverted T configurations have fewer aisles than a traditional aisle-based storage environment. This increases the storage density; however, requires that some items to be moved out of the way to gain access to other more deeply stored items. Such movement can result in item location uncertainty. When items are requested for retrieval in a dense storage environment with item location uncertainty, searching is required. Dense storage has a practical importance as it allows for the use of available space efficiently, which is especially important with the scarce and expensive space onboard of US Navy's ships that form a sea base. A sea base acts as a floating distribution center that provides ready issue material to forces ashore participating in various types of missions. The sea basing concept and the importance of a sea base's responsiveness is our main motivation to conduct this research.In chapter 2, we review three major bodies of literature: 1) sea based logistics, 2) dense storage and 3) search theory. Sea based logistics literature mostly focuses on the concept and the architecture of a sea base, with few papers developing mathematical models to solve operational problems of a sea base, including papers handling the logistical and sustainment aspects. Literature related to dense storage can be broken down into work dealing with a dense storage environment with an inverted T configuration and other papers dealing with other dense storage configurations. It was found that some of the dense storage literature was motivated by the same application, i.e. sea based logistics. Finally, we surveyed the vast search theory literature and classification of search environments. This research contributes to the intersection of these three bodies of literature. Specifically, this research, motivated by the application of sea basing, develops search heuristics for dense storage environments that require moving items out of the way during searching. In chapter 3, we present the problem statements. We study two single-searcher search problems. The first problem is searching for a single item in an inverted T dense storage environment. The second one is searching for one or more items in an inverted T storage environment with items stacked over each other in the vertical direction.In chapter 4, we present our first contribution. In this contribution we propose a search plan heuristic to search for a single item in an inverted T, k-deep dense storage system with the objective of decreasing the expected search time in such an environment. In this contribution, we define each storage environment entirely by the accessibility constant and the storeroom length. In addition, equations are derived to calculate each component of the search time equation that we propose: travel, put-back and repositioning. Two repositioning policies are studied. We find that a repositioning policy that uses the open aisle locations as temporary storage locations and requires put-back of these items while searching is recommended. This recommendation is because such a policy results in lower expected search time and lower variability than a policy that uses available space outside the storage area and handles put-back independently of the search process. Statistical analysis is used to analyze the numerical results of the first contribution and to analyze the performances of both repositioning polices. We derive the probability distribution of search times in a storeroom with small configurations in terms of the accessibility constant and length. It was found that this distribution can be approximated using a lognormal probability distribution with a certain mean and standard deviation. Knowing the probability distribution provides the decision makers with the full range of all possible probabilities of search times, which is useful for downstream planning operations.In chapter 5, we present the second contribution, in which we propose a search plan heuristic but for multiple items in an inverted T, k-deep storage system. Additionally, we consider stacking multiple items over each other. Stacking items over each other, increases the number of stored items and allows for the utilization of the vertical space. In this second contribution, we are using the repositioning policy that proved its superiority in the first contribution. This contribution investigates a more general and a much more challenging environment than the one studied in the first contribution. In the second environment, to gain access to some items, not only may other items need to be moved out of the way, but also the overall number of movements for items within the system will be highly affected by the number of items stacked over each other. In addition, the searcher is given a task that includes searching and retrieving a set of items, rather than just one item.For the second contribution, the performance of the search heuristic is analyzed through a Statistical Design of Experiments, and it was found that searching and retrieving multiple items instead of just a single item, would decrease the variability in search times for each storeroom configuration. Finally, in chapter 6, conclusions of this research and suggestions for future research directions are presented.
Show less - Date Issued
- 2015
- Identifier
- CFE0006256, ucf:51045
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006256
- Title
- Arrangement of Google Search Results and Imperial Ideology: Searching for Benghazi, Libya.
- Creator
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Stewart, Jacob, Pigg, Stacey, Rounsaville, Angela, Walls, Douglas, University of Central Florida
- Abstract / Description
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This project responds to an ongoing discussion in scholarship that identifies and analyzes the ideological functions of computer interfaces. In 1994, Cynthia Selfe and Richard Selfe claimed that interfaces are maps of cultural information and are therefore ideological (485). For Selfe and Selfe and other scholars, these interfaces carried a colonial ideology that resulted in Western dominance over other cultures. Since this early scholarship, our perspectives on interface have shifted with...
Show moreThis project responds to an ongoing discussion in scholarship that identifies and analyzes the ideological functions of computer interfaces. In 1994, Cynthia Selfe and Richard Selfe claimed that interfaces are maps of cultural information and are therefore ideological (485). For Selfe and Selfe and other scholars, these interfaces carried a colonial ideology that resulted in Western dominance over other cultures. Since this early scholarship, our perspectives on interface have shifted with changing technology; interfaces can no longer be treated as having persistent and predictable characteristics like texts. I argue that interfaces are interactions among dynamic information that is constantly being updated online. One of the most prominent ways users interact with information online is through the use of search engines such as Google. Interfaces like Google assist users in navigating dynamic cultural information. How this information is arranged in a Google search event has a profound impact on what meaning we make surrounding the search term.In this project, I argue that colonial ideologies are upheld in several Google search events for the term (")Benghazi, Libya.(") I claim that networked connection during Google search events leads to the creation and sustainment of a colonial ideology through patterns of arrangement. Finally, I offer a methodology for understanding how ideologies are created when search events occur. This methodology searches for patterns in connected information in order to understand how they create an ideological lens.
Show less - Date Issued
- 2014
- Identifier
- CFE0005267, ucf:50559
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005267
- Title
- THE CONSTITUTIONALITY OF WARRANTLESS CELL PHONE SEARCHES INCIDENT TO ARREST.
- Creator
-
Brown, Kylie, Bast, Carol, University of Central Florida
- Abstract / Description
-
As technology has developed, Americans have come to carry their most private information around with them in their pockets in digital form on their cell phones. A cell phone has immense storage capacity and can contain a wide variety of communicative information about its owner. In the past, there had been a disagreement among the lower courts as to whether police officers could search the contents of an arrestee's cell phone when making an arrest. The United States Supreme Court settled this...
Show moreAs technology has developed, Americans have come to carry their most private information around with them in their pockets in digital form on their cell phones. A cell phone has immense storage capacity and can contain a wide variety of communicative information about its owner. In the past, there had been a disagreement among the lower courts as to whether police officers could search the contents of an arrestee's cell phone when making an arrest. The United States Supreme Court settled this disagreement in Riley v. California; in that case, the Court held that the warrantless search of a cell phone incident to arrest violated the Fourth Amendment to the United States Constitution. This thesis discusses case law that preceded the United States Supreme Court case Riley v. California, that decision, and possible ramifications of that decision.
Show less - Date Issued
- 2014
- Identifier
- CFH0004698, ucf:45237
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFH0004698
- Title
- LEARNING TECHNIQUES FOR INFORMATION RETRIEVAL AND MINING IN HIGH-DIMENSIONAL DATABASES.
- Creator
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Cheng, Hao, Hua, Kien A., University of Central Florida
- Abstract / Description
-
The main focus of my research is to design effective learning techniques for information retrieval and mining in high-dimensional databases. There are two main aspects in the retrieval and mining research: accuracy and efficiency. The accuracy problem is how to return results which can better match the ground truth, and the efficiency problem is how to evaluate users' requests and execute learning algorithms as fast as possible. However, these problems are non-trivial because of the...
Show moreThe main focus of my research is to design effective learning techniques for information retrieval and mining in high-dimensional databases. There are two main aspects in the retrieval and mining research: accuracy and efficiency. The accuracy problem is how to return results which can better match the ground truth, and the efficiency problem is how to evaluate users' requests and execute learning algorithms as fast as possible. However, these problems are non-trivial because of the complexity of the high-level semantic concepts, the heterogeneous natures of the feature space, the high dimensionality of data representations and the size of the databases. My dissertation is dedicated to addressing these issues. Specifically, my work has five main contributions as follows. The first contribution is a novel manifold learning algorithm, Local and Global Structures Preserving Projection (LGSPP), which defines salient low-dimensional representations for the high-dimensional data. A small number of projection directions are sought in order to properly preserve the local and global structures for the original data. Specifically, two groups of points are extracted for each individual point in the dataset: the first group contains the nearest neighbors of the point, and the other set are a few sampled points far away from the point. These two point sets respectively characterize the local and global structures with regard to the data point. The objective of the embedding is to minimize the distances of the points in each local neighborhood and also to disperse the points far away from their respective remote points in the original space. In this way, the relationships between the data in the original space are well preserved with little distortions. The second contribution is a new constrained clustering algorithm. Conventionally, clustering is an unsupervised learning problem, which systematically partitions a dataset into a small set of clusters such that data in each cluster appear similar to each other compared with those in other clusters. In the proposal, the partial human knowledge is exploited to find better clustering results. Two kinds of constraints are integrated into the clustering algorithm. One is the must-link constraint, indicating that the involved two points belong to the same cluster. On the other hand, the cannot-link constraint denotes that two points are not within the same cluster. Given the input constraints, data points are arranged into small groups and a graph is constructed to preserve the semantic relations between these groups. The assignment procedure makes a best effort to assign each group to a feasible cluster without violating the constraints. The theoretical analysis reveals that the probability of data points being assigned to the true clusters is much higher by the new proposal, compared to conventional methods. In general, the new scheme can produce clusters which can better match the ground truth and respect the semantic relations between points inferred from the constraints. The third contribution is a unified framework for partition-based dimension reduction techniques, which allows efficient similarity retrieval in the high-dimensional data space. Recent similarity search techniques, such as Piecewise Aggregate Approximation (PAA), Segmented Means (SMEAN) and Mean-Standard deviation (MS), prove to be very effective in reducing data dimensionality by partitioning dimensions into subsets and extracting aggregate values from each dimension subset. These partition-based techniques have many advantages including very efficient multi-phased pruning while being simple to implement. They, however, are not adaptive to different characteristics of data in diverse applications. In this study, a unified framework for these partition-based techniques is proposed and the issue of dimension partitions is examined in this framework. An investigation of the relationships of query selectivity and the dimension partition schemes discovers indicators which can predict the performance of a partitioning setting. Accordingly, a greedy algorithm is designed to effectively determine a good partitioning of data dimensions so that the performance of the reduction technique is robust with regard to different datasets. The fourth contribution is an effective similarity search technique in the database of point sets. In the conventional model, an object corresponds to a single vector. In the proposed study, an object is represented by a set of points. In general, this new representation can be used in many real-world applications and carries much more local information, but the retrieval and learning problems become very challenging. The Hausdorff distance is the common distance function to measure the similarity between two point sets, however, this metric is sensitive to outliers in the data. To address this issue, a novel similarity function is defined to better capture the proximity of two objects, in which a one-to-one mapping is established between vectors of the two objects. The optimal mapping minimizes the sum of distances between each paired points. The overall distance of the optimal matching is robust and has high retrieval accuracy. The computation of the new distance function is formulated into the classical assignment problem. The lower-bounding techniques and early-stop mechanism are also proposed to significantly accelerate the expensive similarity search process. The classification problem over the point-set data is called Multiple Instance Learning (MIL) in the machine learning community in which a vector is an instance and an object is a bag of instances. The fifth contribution is to convert the MIL problem into a standard supervised learning in the conventional vector space. Specially, feature vectors of bags are grouped into clusters. Each object is then denoted as a bag of cluster labels, and common patterns of each category are discovered, each of which is further reconstructed into a bag of features. Accordingly, a bag is effectively mapped into a feature space defined by the distances from this bag to all the derived patterns. The standard supervised learning algorithms can be applied to classify objects into pre-defined categories. The results demonstrate that the proposal has better classification accuracy compared to other state-of-the-art techniques. In the future, I will continue to explore my research in large-scale data analysis algorithms, applications and system developments. Especially, I am interested in applications to analyze the massive volume of online data.
Show less - Date Issued
- 2009
- Identifier
- CFE0002882, ucf:48022
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0002882
- Title
- FINDERS KEEPERS: A COMPARATIVE STUDY INVESTIGATING TEACHING THE FLORIDA RESEARCH PROCESS FINDS MODEL THROUGH THREE DIFFERENT APPROACHES AT THE ELEMENTARY SCHOOL LEVEL.
- Creator
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Serrell, Karen, Beile, Penny, University of Central Florida
- Abstract / Description
-
The children's taunt "Finders Keepers, Losers Weepers" gives new credence to the information search process at the elementary school level. Children keep what they find, claim it as their own, and accept information without discernment or critique. This study examines the effectiveness of teaching information literacy skills through three different approaches. The first curricular approach uses direct instruction to teach children how to do research using the Florida Research Process...
Show moreThe children's taunt "Finders Keepers, Losers Weepers" gives new credence to the information search process at the elementary school level. Children keep what they find, claim it as their own, and accept information without discernment or critique. This study examines the effectiveness of teaching information literacy skills through three different approaches. The first curricular approach uses direct instruction to teach children how to do research using the Florida Research Process FINDS Model. The second approach pairs the FINDS Model with a unit of study that is related to classroom curriculum. The third approach examines the FINDS Model in conjunction with project learning, a constructivist model based on student interest. One hundred twenty- eight third grade students attending a public elementary school in Southwest Florida during the 2008-2009 school year participated in the study. A mixed-methods research approach was used to gather data. Quantitative data was collected with an information literacy pre and post test, and an anonymous media lessons' survey about student preferences. Qualitative data were gathered through a review of student work samples and student interviews. Statistically significant gains were found between the pre to post test scores for all three groups, however no statistically significant differences were found among groups. Although quantitative data did not reveal differences among the treatment groups, qualitative findings revealed that the group taught research skills through the connection to classroom curriculum approach performed better. Thus the findings of this study support existing research which proposes that the best practice for teaching research skills to young children is through a connection to classroom curriculum.
Show less - Date Issued
- 2009
- Identifier
- CFE0002957, ucf:47963
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0002957
- Title
- PERFORMANCE IMPLICATIONS OF ALTERNATIVE COLOR-CODESIN AIRPORT X-RAY BAGGAGE SCREENING.
- Creator
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Hilscher, Matthew, Jentsch, Florian, University of Central Florida
- Abstract / Description
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This research investigated both cognitive and affective influences of alternative color combinations in a search task paradigm. The effects of re-mapping the existing, comparatively arbitrarily color codes of baggage X-ray images, were explored. Alternative color-codes were evaluated for improving the economy of visual search in X-ray baggage screening. Using a 2 x 2 between-groups design, the perceptual aspects of color-codes varying in degree of visual agreeability (accordant or discordant)...
Show moreThis research investigated both cognitive and affective influences of alternative color combinations in a search task paradigm. The effects of re-mapping the existing, comparatively arbitrarily color codes of baggage X-ray images, were explored. Alternative color-codes were evaluated for improving the economy of visual search in X-ray baggage screening. Using a 2 x 2 between-groups design, the perceptual aspects of color-codes varying in degree of visual agreeability (accordant or discordant) and color contrast (high or low) were examined in terms of efficiency (reaction time) and effectiveness (detection accuracy). Three hypotheses were put forth; two postulated main effects for color contrast and for visual agreeability, and a third postulated an interaction. Additionally, for comparison purposes, a fifth group of participants was presented with a stimulus condition that represented the current industry standard for colorizing X-ray images. Out of 100 volunteers, data were usable for 95 participants who had been randomly assigned to one of five conditions. All participants were exposed to the same screening task. The screening task required participants to view 153 X-ray images in random order. Of these images, 36 contained a single threat item (knife, scissor, gun) among clutter. Analyses of variance revealed significant differences between conditions with respect to detection accuracy. Implications are that high-color contrast improves detection accuracy; specifically with respect to correct rejections, and that this effect on performance can be moderated by psycho-emotional mechanisms. Specifically, the impact of color-contrast was significantly more pronounced under conditions of accordant color combinations. Theoretical underpinnings and applications to other domains are discussed.
Show less - Date Issued
- 2005
- Identifier
- CFE0000345, ucf:52835
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0000345
- Title
- INFORMATION-SEEKING STRATEGIES OF DOCTORAL STUDENTS AND IMPLICATIONS FOR DESIGN OF THE GRADUATE SCHOOL WEB SPACE.
- Creator
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Winter, Debra, Applen, J. D., University of Central Florida
- Abstract / Description
-
This dissertation looks at the information-seeking practices of doctoral students in the context of their search for a doctoral program and considers the implications for design of the graduate school Web space. Of particular interest is the description of patterns of Web use and the practices related to students' preparation for interactions with technology, the nature of the interactions, and the thinking that occurs. An exploratory study that brings together hypertext theory,...
Show moreThis dissertation looks at the information-seeking practices of doctoral students in the context of their search for a doctoral program and considers the implications for design of the graduate school Web space. Of particular interest is the description of patterns of Web use and the practices related to students' preparation for interactions with technology, the nature of the interactions, and the thinking that occurs. An exploratory study that brings together hypertext theory, contextual, holistic approaches, and information behavior, this research includes a focus group of current undergraduate and graduate students to gather fresh details about information-seeking for a graduate program as a preliminary investigation in this area, eight interviews with current doctoral students admitted in Fall 2007 to capture the specific details of students' information-seeking experiences for a doctoral program by mapping the journeys, and an online survey of current doctoral students admitted in Fall 2007 as further investigation of information-seeking for a doctoral program. Doctoral students who participated in this study rely on the Web as the primary source of prior knowledge of graduate education and graduate school, as well as the source most used to build that knowledge during the information-seeking journey for a graduate program and to prepare them for the start of their graduate study. The eight maps of students' information-seeking journeys for a graduate program show how complex and wide-ranging these journeys are. Based on bits collected through their many Web encounters over six months to two years, students develop a "feeling" for the people who make up the graduate program, social interactions within this group and research subgroups, and what it would be like to be a student in the program, all contributing to students' decision making. Academic Web sites play a key role as support structures for students and have to do more than make the information available and findable; they must design in order to encourage and sustain engagement, or deep involvement. This study proposes several suggestions for academic Web design.
Show less - Date Issued
- 2009
- Identifier
- CFE0002557, ucf:47634
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0002557
- Title
- MONITORING SHALLOW CONTROLLED GRAVES CONTAINING SMALL CADAVERS USING GROUND PENETRATING RADAR.
- Creator
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Fletcher, Joanna, Schultz, John, University of Central Florida
- Abstract / Description
-
Ground-penetrating radar (GPR) can be a useful geophysical instrument in the search and detection of clandestine graves in a forensic context. Controlled research in the field of forensic archaeology has demonstrated the applicability of this technology and is vital for improving GPR search methods. The objectives of this research was to evaluate the applicability of GPR, using 250 MHz and 500 MHz antennae, to locate shallow graves containing small pig cadavers in various burial scenarios...
Show moreGround-penetrating radar (GPR) can be a useful geophysical instrument in the search and detection of clandestine graves in a forensic context. Controlled research in the field of forensic archaeology has demonstrated the applicability of this technology and is vital for improving GPR search methods. The objectives of this research was to evaluate the applicability of GPR, using 250 MHz and 500 MHz antennae, to locate shallow graves containing small pig cadavers in various burial scenarios over a 12 month period. Data was collected on a controlled grid containing six graves at 0.5 m in depth: five graves containing pig carcasses and one control grave. The five graves containing the pig carcasses were devised to test a number of common forensic burial scenarios. The reflection profile data was processed using the computer program REFLEXW. The results demonstrate that the additional grave items did not always increase the detection of the grave for this monitoring period. Further, the low demarcation of the grave containing disturbed backfill illustrated that the hyperbolic reflection features were the result of the pig carcasses and not the disturbed soil. In terms of antenna performance, the 250 MHz data initially provided a higher resolution within the first few months. However, over time the higher detail provided by the 500 MHz data consistently resulted in easily discernable reflections.
Show less - Date Issued
- 2011
- Identifier
- CFE0003592, ucf:48883
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0003592
- Title
- Evolution Through the Search for Novelty.
- Creator
-
Lehman, Joel, Stanley, Kenneth, Gonzalez, Avelino, Wiegand, Rudolf, Hoffman, Eric, University of Central Florida
- Abstract / Description
-
I present a new approach to evolutionary search called novelty search, wherein only behavioral novelty is rewarded, thereby abstracting evolution as a search for novel forms. This new approach contrasts with the traditional approach of rewarding progress towards the objective through an objective function. Although they are designed to light a path to the objective, objective functions can instead deceive search into converging to dead ends called local optima.As a significant problem in...
Show moreI present a new approach to evolutionary search called novelty search, wherein only behavioral novelty is rewarded, thereby abstracting evolution as a search for novel forms. This new approach contrasts with the traditional approach of rewarding progress towards the objective through an objective function. Although they are designed to light a path to the objective, objective functions can instead deceive search into converging to dead ends called local optima.As a significant problem in evolutionary computation, deception has inspired many techniques designed to mitigate it. However, nearly all such methods are still ultimately susceptible to deceptive local optima because they still measure progress with respect to the objective, which this dissertation will show is often a broken compass. Furthermore, although novelty search completely abandons the objective, it counterintuitively often outperforms methods that search directly for the objective in deceptive tasks and can induce evolutionary dynamics closer in spirit to natural evolution. The main contributions are to (1) introduce novelty search, an example of an effective search method that is not guided by actively measuring or encouraging objective progress; (2) validate novelty search by applying it to biped locomotion; (3) demonstrate novelty search's benefits for evolvability (i.e. the abilityof an organism to further evolve) in a variety of domains; (4) introduce an extension of novelty search called minimal criteria novelty search that brings a new abstraction of natural evolution to evolutionary computation (i.e. evolution as a search for many ways of meeting the minimal criteria of life); (5) present a second extension of novelty search called novelty search with local competition that abstracts evolution instead as a process driven towards diversity with competition playing a subservient role; and (6) evolve a diversity of functional virtual creatures in a single run as a culminating application of novelty search with local competition. Overall these contributions establish novelty search as an important new research direction for the field of evolutionary computation.
Show less - Date Issued
- 2012
- Identifier
- CFE0004398, ucf:49390
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004398
- Title
- NEW COMPUTATIONAL APPROACHES FOR MULTIPLE RNA ALIGNMENT AND RNA SEARCH.
- Creator
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DeBlasio, Daniel, Zhang, Shaojie, University of Central Florida
- Abstract / Description
-
In this thesis we explore the the theory and history behind RNA alignment. Normal sequence alignments as studied by computer scientists can be completed in $O(n^2)$ time in the naive case. The process involves taking two input sequences and finding the list of edits that can transform one sequence into the other. This process is applied to biology in many forms, such as the creation of multiple alignments and the search of genomic sequences. When you take into account the RNA sequence...
Show moreIn this thesis we explore the the theory and history behind RNA alignment. Normal sequence alignments as studied by computer scientists can be completed in $O(n^2)$ time in the naive case. The process involves taking two input sequences and finding the list of edits that can transform one sequence into the other. This process is applied to biology in many forms, such as the creation of multiple alignments and the search of genomic sequences. When you take into account the RNA sequence structure the problem becomes even harder. Multiple RNA structure alignment is particularly challenging because covarying mutations make sequence information alone insufficient. Existing tools for multiple RNA alignments first generate pair-wise RNA structure alignments and then build the multiple alignment using only the sequence information. Here we present PMFastR, an algorithm which iteratively uses a sequence-structure alignment procedure to build a multiple RNA structure alignment. PMFastR also has low memory consumption allowing for the alignment of large sequences such as 16S and 23S rRNA. Specifically, we reduce the memory consumption to $\sim O(band^2*m)$ where $band$ is the banding size. Other solutions are $\sim O(n^2*m)$ where $n$ and $m$ are the lengths of the target and query respectively. The algorithm also provides a method to utilize a multi-core environment. We present results on benchmark data sets from BRAliBase, which shows PMFastR outperforms other state-of-the-art programs. Furthermore, we regenerate 607 Rfam seed alignments and show that our automated process creates similar multiple alignments to the manually-curated Rfam seed alignments. While these methods can also be applied directly to genome sequence search, the abundance of new multiple species genome alignments presents a new area for exploration. Many multiple alignments of whole genomes are available and these alignments keep growing in size. These alignments can provide more information to the searcher than just a single sequence. Using the methodology from sequence-structure alignment we developed AlnAlign, which searches an entire genome alignment using RNA sequence structure. While programs have been readily available to align alignments, this is the first to our knowledge that is specifically designed for RNA sequences. This algorithm is presented only in theory and is yet to be tested.
Show less - Date Issued
- 2009
- Identifier
- CFE0002736, ucf:48166
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0002736
