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This thesis presents a generalized Bayesian framework for a mobile robot to localize itself and a target, while building a map of the environment. The proposed technique builds upon the Bayesian Simultaneous Robot Localization and Mapping (SLAM) method, to allow the robot to localize itself and the environment using map features or landmarks in close proximity. The target feature is distinguished from the rest of features since the robot has to navigate to its location and thus needs to be observed from a long distance. The contribution of the proposed approach is on enabling the robot to track a target object or region, using a multi-stage technique. In the first stage, the target state is corrected sequentially to the robot correction in the Recursive Bayesian Estimation. In the second stage, with the target being closer, the target state is corrected simultaneously with the robot and the landmarks. The process allows the robot's state uncertainty to be propagated into the estimated target's state, bridging the gap between tracking only methods where the target is estimated assuming known observer state and SLAM methods where only landmarks are considered. When the robot is located far, the sequential stage is efficient in tracking the target position while maintaining an accurate robot state using close only features. Also, target belief is always maintained in comparison to temporary tracking methods such as image-tracking. When the robot is closer to the target and most of its field of view is covered by the target, it is shown that simultaneous correction needs to be used in order to minimize robot, target and map entropies in the absence of other landmarks. / M.S. / This thesis presents a generalized framework with the goal of allowing a robot to localize itself and a static target, while building a map of the environment. This map is used as in the Simultaneous Localization and Mapping (SLAM) framework to enhance robot accuracy and with close features. Target, here, is distinguished from the rest of features since the robot has to navigate to its location and thus needs to be continuously observed from a long distance. The contribution of the proposed approach is on enabling the robot to track a target object or region, using a multi-stage technique. In the first stage, the robot and close landmarks are estimated simultaneously and they are both corrected. Using the robot's uncertainty in its estimate, the target state is then estimated sequentially, considering known robot state. That decouples the target estimation from the rest of the process. In the second stage, with the target being closer, target, robot and landmarks are estimated simultaneously. When the robot is located far, the sequential stage is efficient in tracking the target position while maintaining an accurate robot state using close only features. When the robot is closer to the target and most of its field of view is covered by the target, it is shown that simultaneous correction needs to be used in order to minimize robot, target and map uncertainties in the absence of other landmarks.

Robots are widely used in domestic and commercial applications. These applications typically involve robots built for a specific the task, thus leading to efficiency in task completion. However, with the increase in completion efficiency comes an increase in the time required for completion of the whole system. Specific tasks create the need for many different robots, all with differing capabilities, causing an increase in development cost and time needed. This raises the issue of whether using an off the shelf system with minor modifications can accurately perform the same tasks. If so, more time can be spent on refining the process leading to completion of the task, resulting in less time spent developing the robot. Consequently, less cost in the life cycle of the system leads to less cost for the end user, thus allowing robots to be used for more applications. This thesis explores using a commercially available robot, Acroname Inc.'s Garcia, to perform mapping and localization tasks. As the robot travels it gathers data about the environment. This data is processed in Matlab and the result of the algorithm is a map. In the creation of the map, mathematical morphology is explored as a means to reduce noise. When the robot has located a corner, Matlab provides the robot with a position estimate correction. This correction allows the robot to better estimate its location resulting in a more accurate map. As the results of this thesis illustrate, with very minor modifications, the robot is capable of accurately performing mapping and localization tasks. The results demonstrate that an off the shelf system is capable of accurately performing tasks for which it was not specifically designed. / Master of Science

The goal of this research is to map processes of political idealization and how images are used and understood within the waterboarding blogs included in the case study. Chapter One is designed to provide basic information about the waterboarding issue and elements of this research more generally. The first chapter provides the following: information regarding the background facts of the waterboarding issue, research methods, research limitations, general descriptions of the blogs included in the case study, information about the general findings/data, and a brief explanation of why the blogs were chosen to be included in the case study. Chapter Two maps how elements of political idealization operate in the waterboarding blog case study. The first section of this chapter outlines Wendy Brown's theories connected to the process of political idealization. The second section maps the process of political idealization within the context of the waterboarding blog case study. The second section is broken into three additional sub-sections each representing a stage in the political idealization process. Chapter Three uses Aaron Barlow's outline of the emergence of the "Celebrity Journalist" as the premise to provide a partial explanation of why some political subjects are looking to virtual publics to supplement news media. The main purpose of Chapter Three is to map how images are used in the CODEPINK and Kaj Larsen video clip. / Master of Arts

The World Health Organization estimates that vector-borne diseases account for 17% of the global burden of all infectious diseases and has identified the mosquito as the most dangerous of all disease-transmitting insects, being responsible for several million deaths and hundreds of millions of cases each year. The study of mosquito genomics provides a deeper understanding of the molecular mechanisms involved in every aspect of vector biology, such as sex determination, host-parasite interaction, ecology, feeding behavior, immunity and evolutionary trends and can be used for the development of new strategies for vector control. We developed the first map of the mitotic chromosomes of the major vector for West Nile fever and lymphatic filariasis, Culex quinquefasciatus. The map was then successfully utilized for mapping of approximately 90% of available genetic markers to their precise positions on the chromosomes. Idiograms were integrated with 140 genetic supercontigs representing 26.5% of the genome. A linear regression analysis demonstrated good overall correlation between the positioning of markers on physical and genetic linkage maps. This will improve gene annotation and help in distinguishing potential haplotype scaffolds and regions of segmental duplications. It will also facilitate identification of epidemiologically important genes that can be used as targets for the vector control and provide a better framework for comparative genomics that will help understanding of the evolution of epidemiologically important traits. In another study, we confirmed the presence of the newly described species, Anopheles daciae, in regions of Russia using molecular data. Although sympatric with its sibling species, Anopheles messeae, five nucleotide substitutions in the internal transcribed spacer 2 of ribosomal DNA can be used to distinguish the morphologically similar species. Chromosome rearrangements have a significant impact on mosquito adaptation and speciation. Using sequencing data in combination with karyotyping, we demonstrated that significant differences in inversion frequencies distinguish An. messeae from An. daciae, suggesting that these inversions are actively involved in adaptation and speciation. It is essential to have reliable toolbox for correct identification of these species and to know their range for future possible malaria outbreaks prevention. / Ph. D. / The more you study, the more you know The more you know, the more you forget The more you forget, the less you know So why study? According to the World Health Organization, mosquitoes are one of the deadliest animals in the world. They spread disease to humans resulting in hundreds of millions of illnesses and several million deaths every year. Study of the mosquito genome can help us understand vector biology and speciation and can be used to develop new strategies for vector control. Culex quinquefasciatus, the southern house mosquito, is one of the major vectors for the West Nile virus in the U.S. and for lymphatic filariasis, a disabling and disfiguring disease, worldwide. The traditional methods of control are of limited effectiveness because of high insecticide resistance in many populations of the mosquito. To enhance our resources for the control strategies, we developed physical maps of the chromosomes for this mosquito and effectively integrated it with available genetic linkage map. This work will help to identify epidemiologically important genes that can be used as targets for the vector control. Malaria vectors, mosquitoes from the genus Anopheles, are known for their ecological plasticity, which can be partially explained by chromosome rearrangements called inversion. A global malaria eradication program significantly reduced the number of deaths related to malaria, especially in Europe and the U.S. However, malaria outbreaks can occur anywhere competent vectors occur. We studied Anopheles messeae, one of the major European malaria vectors and its closely related species, Anopheles danciae. We report for the first time the presence of An. daciae in Russia and demonstrate that its distribution overlaps with that of An. messeae. Using genetic sequence data in combination with chromosome structure, we demonstrated that significant differences in inversion frequencies reliably distinguish An. messeae from An. daciae. These inversions may be involved in adaptation and speciation of these two species. It is essential to have reliable toolbox for correct identification of these species and to know their range for future possible malaria outbreaks prevention.

<p>The different mapping techniques that are used increases the details on surfaces without increasing the number of polygons. Image Based Sculpting tools in the program Modo and Z-Brush is used to create folds and wrinkles from photographs of actual fabrics instead of trying to create these shapes by modeling them. This method makes it easier to achieve photorealistic renderings and produce as realistic fabric dynamics as possible when they are applied on objects.</p>

Although much progress has been made in the field of robotic mapping, many challenges remain including: efficient semantic segmentation using RGB-D sensors, map representations that include complex features (structures and objects), and interfaces for interactive annotation of maps. This thesis addresses how prior knowledge of semi-structured human environments can be leveraged to improve segmentation, mapping, and semantic annotation of maps. We present an organized connected component approach for segmenting RGB-D data into planes and clusters. These segments serve as input to our mapping approach that utilizes them as planar landmarks and object landmarks for Simultaneous Localization and Mapping (SLAM), providing necessary information for service robot tasks and improving data association and loop closure. These features are meaningful to humans, enabling annotation of mapped features to establish common ground and simplifying tasking. A modular, open-source software framework, the OmniMapper, is also presented that allows a number of different sensors and features to be combined to generate a combined map representation, and enabling easy addition of new feature types.

When information is abundant, it becomes increasingly difficult to fit nuggets of knowledge into a single coherent picture. Complex stories spaghetti into branches, side stories, and intertwining narratives; search engines, our most popular navigational tools, are limited in their capacity to explore such complex stories. We propose a methodology for creating structured summaries of information, which we call metro maps. Our proposed algorithm generates a concise structured set of documents that maximizes coverage of salient pieces of information. Most importantly, metro maps explicitly show the relations among retrieved pieces in a way that captures story development. The overarching theme of this work is formalizing characteristics of good maps, and providing efficient algorithms (with theoretical guarantees) to optimize them. Moreover, as information needs vary from person to person, we integrate user interaction into our framework, allowing users to alter the maps to better reflect their interests. Pilot user studies with real-world datasets demonstrate that the method is able to produce maps which help users acquire knowledge efficiently. We believe that metro maps could be powerful tools for any Web user, scientist, or intelligence analyst trying to process large amounts of data.

Thesis (M.S.)--Oregon State University, 2011. / Printout. Includes bibliographical references (leaves 44-50). Also available on the World Wide Web.

Illinois statewide infrastructure mapping provides basis for economic development of the state. As a part of infrastructure mapping, this study is focused on mapping healthcare and education services for Illinois. Over 4337 k-12 schools and 1331 hospitals and long term cares were used in analyzing healthcare and education services. Education service was measured as ratio of population to teacher and healthcare service as the ratio of population to bed. Both of these services were mapped using three mapping techniques including Choropleth mapping, Thiessen polygon, and Kernel Density Estimation. The mapping was also conducted at three scales including county, census tract, and ZIP code area. The obtained maps were compared by visual interpretation and statistical correlation analysis. Moreover, spatial pattern analysis of maps was conducted using global and local Moran's I, high/low clustering, and hotspot analysis methods. In addition, multivariate mapping was carried out to demonstrate the spatial distributions of multiple variables and their relationships. The results showed that both Choropleth mapping and Thiessen polygon methods resulted in the service levels that were homogeneous throughout the polygons and abruptly changed at the boundaries hence which ignored the cross boundary flow of people for healthcare and education services. In addition they do not reflect the distance decay of services. Kernel Density mapping quantified the continuous and variable healthcare and educational services and has the potential to provide more accurate estimates of healthcare and educational services. Moreover, the county scale maps are more reliable than the census tract and ZIP code area maps. In addition, multivariate map obtained by legend design that combined the values of multiple variables well demonstrated the spatial distributions of healthcare and education services along with per capita income and relationships between them. Overall, Morgan, Wayne, Mason, and Ford counties had higher services for both education and healthcare whereas Champaign, Johnson, and Perry had lower service levels of healthcare and education. Generally, cities and the areas close to cities have better healthcare and educational service than other areas because of higher per capita income. In addition to numbers of hospitals and schools, the healthcare and education service levels were also affected by populations and per capita income. Additionally, other factors may also have influence on the service levels but were not taken into account in this study because of limited time and data.