No description available.

In this thesis we deal with problems connected to range searching, which is one of the central areas of computational geometry. The dominant problems in this area are halfspace range searching, simplex range searching and orthogonal range searching and research into these problems has spanned decades. For many range searching problems, the best possible data structures cannot offer fast (i.e., polylogarithmic) query times if we limit ourselves to near linear storage. Even worse, it is conjectured (and proved in some cases) that only very small improvements to these might be possible. This inefficiency has encouraged many researchers to seek alternatives through approximations. In this thesis we continue this line of research and focus on relative approximation of range counting problems. One important problem where it is possible to achieve significant speedup through approximation is halfspace range counting in 3D. Here we continue the previous research done and obtain the first optimal data structure for approximate halfspace range counting in 3D. Our data structure has the slight advantage of being Las Vegas (the result is always correct) in contrast to the previous methods that were Monte Carlo (the correctness holds with high probability). Another series of problems where approximation can provide us with substantial speedup comes from robust statistics. We recognize three problems here: approximate Tukey depth, regression depth and simplicial depth queries. In 2D, we obtain an optimal data structure capable of approximating the regression depth of a query hyperplane. We also offer a linear space data structure which can answer approximate Tukey depth queries efficiently in 3D. These data structures are obtained by applying our ideas for the approximate halfspace counting problem. Approximating the simplicial depth turns out to be much more difficult, however. Computing the simplicial depth of a given point is more computationally challenging than most other definitions of data depth. In 2D we obtain the first data structure which uses near linear space and can answer approximate simplicial depth queries in polylogarithmic time. As applications of this result, we provide two non-trivial methods to approximate the simplicial depth of a given point in higher dimension. Along the way, we establish a tight combinatorial relationship between the Tukey depth of any given point and its simplicial depth. Another problem investigated in this thesis is the dominance reporting problem, an important special case of orthogonal range reporting. In three dimensions, we solve this problem in the pointer machine model and the external memory model by offering the first optimal data structures in these models of computation. Also, in the RAM model and for points from an integer grid we reduce the space complexity of the fastest known data structure to optimal. Using known techniques in the literature, we can use our results to obtain solutions for the orthogonal range searching problem as well. The query complexity offered by our orthogonal range reporting data structures match the most efficient query complexities known in the literature but our space bounds are lower than the previous methods in the external memory model and RAM model where the input is a subset of an integer grid. The results also yield improved orthogonal range searching in higher dimensions (which shows the significance of the dominance reporting problem). Intersection searching is a generalization of range searching where we deal with more complicated geometric objects instead of points. We investigate the rectilinear disjoint polygon counting problem which is a specialized intersection counting problem. We provide a linear-size data structure capable of counting the number of disjoint rectilinear polygons intersecting any rectilinear polygon of constant size. The query time (as well as some other properties of our data structure) resembles the classical simplex range searching data structures.

In this thesis we deal with problems connected to range searching, which is one of the central areas of computational geometry. The dominant problems in this area are halfspace range searching, simplex range searching and orthogonal range searching and research into these problems has spanned decades. For many range searching problems, the best possible data structures cannot offer fast (i.e., polylogarithmic) query times if we limit ourselves to near linear storage. Even worse, it is conjectured (and proved in some cases) that only very small improvements to these might be possible. This inefficiency has encouraged many researchers to seek alternatives through approximations. In this thesis we continue this line of research and focus on relative approximation of range counting problems. One important problem where it is possible to achieve significant speedup through approximation is halfspace range counting in 3D. Here we continue the previous research done and obtain the first optimal data structure for approximate halfspace range counting in 3D. Our data structure has the slight advantage of being Las Vegas (the result is always correct) in contrast to the previous methods that were Monte Carlo (the correctness holds with high probability). Another series of problems where approximation can provide us with substantial speedup comes from robust statistics. We recognize three problems here: approximate Tukey depth, regression depth and simplicial depth queries. In 2D, we obtain an optimal data structure capable of approximating the regression depth of a query hyperplane. We also offer a linear space data structure which can answer approximate Tukey depth queries efficiently in 3D. These data structures are obtained by applying our ideas for the approximate halfspace counting problem. Approximating the simplicial depth turns out to be much more difficult, however. Computing the simplicial depth of a given point is more computationally challenging than most other definitions of data depth. In 2D we obtain the first data structure which uses near linear space and can answer approximate simplicial depth queries in polylogarithmic time. As applications of this result, we provide two non-trivial methods to approximate the simplicial depth of a given point in higher dimension. Along the way, we establish a tight combinatorial relationship between the Tukey depth of any given point and its simplicial depth. Another problem investigated in this thesis is the dominance reporting problem, an important special case of orthogonal range reporting. In three dimensions, we solve this problem in the pointer machine model and the external memory model by offering the first optimal data structures in these models of computation. Also, in the RAM model and for points from an integer grid we reduce the space complexity of the fastest known data structure to optimal. Using known techniques in the literature, we can use our results to obtain solutions for the orthogonal range searching problem as well. The query complexity offered by our orthogonal range reporting data structures match the most efficient query complexities known in the literature but our space bounds are lower than the previous methods in the external memory model and RAM model where the input is a subset of an integer grid. The results also yield improved orthogonal range searching in higher dimensions (which shows the significance of the dominance reporting problem). Intersection searching is a generalization of range searching where we deal with more complicated geometric objects instead of points. We investigate the rectilinear disjoint polygon counting problem which is a specialized intersection counting problem. We provide a linear-size data structure capable of counting the number of disjoint rectilinear polygons intersecting any rectilinear polygon of constant size. The query time (as well as some other properties of our data structure) resembles the classical simplex range searching data structures.

Space use and resource use of three species of macaws (Ara ararauna, A. chloropterus, and A. macao) were studied for a period of three years in the southeastern Peruvian Amazon. Basic information on wild macaw populations is lacking due to the logistical and behavioral challenges of working with these species in dense rainforest. Population declines world-wide have been attributed significantly to a reduction in food and nesting resources due to habitat loss. This research aims to obtain baseline data on macaws in a region with relatively intact rainforest. Specific objectives were to (1) quantify space use, describe the spatial and temporal variation in movement patterns, explore habitat selection and spatial pattern of resources during the non-breeding season, and (2) identify key nesting and foraging species and determine whether there is seasonal variation in diet, and explore how resources may be related to movements and competition. Individuals from each species were radio-tagged and monitored from 2004 to 2008 by ground, platform, and aerial tracking. Seasonal ranges were estimated using MCP and KDE methods. Diversity and niche measurements and selection were calculated for dietary items, nesting substrate, and habitat. The relationship between palm habitat distribution and A. ararauna movements was explored using landscape analysis techniques. All species had similar home range sizes during the breeding season, ranging from a mean of 1,540 ha to 2,541 ha. Non-breeding ranges were significantly larger for A. ararauna (117,849 ha). Greater than 200 species of plants were consumed, yet seasonal preferences vary. The increase in dietary breadth and decrease in overlap during dry season is unlikely related to food scarcity or competition. Key nesting and dietary species include Mauritia flexuosa, Dipterix micrantha, and Bertholletia excelsa. Palm habitat is a key resource for Ara ararauna and associated with long-distance movements. This research addresses a critical gap in our knowledge regarding macaw movements and resource use in Amazonian rainforest. Despite their mobility, their low fecundity and specialized nesting requirements can impact reproductive success and population growth if habitat loss continues on its current trajectory.

Habitat disturbances play a major role in wildlife distribution. Disturbances such as loss of breeding habitat and fragmentation are of particular concern for Neotropical migrant songbird populations. Additionally, different avian species respond differently to the surrounding environment at different spatial scales. Thus, multi-scale studies on bird abundance and reproductive success is necessary for evaluating the effects of habitat alterations. The golden-cheeked warbler (Dendroica chrysoparia) is a Neotropical migrant songbird that breeds exclusively in central Texas. In 1990, the U.S. Fish and Wildlife Service listed the golden-cheeked warbler as endangered, providing habitat loss among the list of justifications. Habitat requirements for this species are known to include mature juniper-oak (Juniperus-Quercus) woodlands; however, relationships between habitat characteristics and golden-cheeked warbler reproductive success remain unclear. Whereas the majority of golden-cheeked warbler research has focused on areas in the center of the breeding range, little is known about interactions between warblers and the environment at the edge of the range. Therefore, it is important to understand these relationships for successful golden-cheeked warbler management. I investigated relationships between golden-cheeked warbler reproductive success and habitat characteristics, including canopy closure and tree species composition, at the study site and territory scale. My study took place within Kickapoo Cavern State Park and surrounding private properties in Kinney and Edwards counties in the southwest corner of the golden-cheeked warbler breeding range. I derived habitat characteristics from satellite imagery from the US Geological Survey National Land Cover Dataset (NLCD) and from field sampling. The NLCD provided data on canopy closure and tree species composition at a 30 m resolution. Additionally, I used spherical densitometers and transect evaluations to ground-truth data and take more detailed measurements. I determined reproductive success by nest monitoring and the Vickery index when nests could not be found. I monitored 80 territories across six study sites in 2009 and 2010. Reproductive success was 39.5 percent in 2009 and 59.4 percent in 2010. I found statistically significant results at the study site scale, whereas golden-cheeked warbler abundance increased as the portion of woodland increased. Similarly, I found that golden-cheeked warbler reproductive success increased at the study site scale as canopy closure increased. I did not find correlations between reproductive success and canopy closure or tree species composition at the territory scale. Results suggest that golden-cheeked warblers utilize a wider variety of habitat composition than previously thought, and habitat composition as a whole may not be the driving factors influencing warbler reproductive success in this region.

No description available.

Black-faced Spoonbill (BFS), Platalea minor, numbers during the non-breeding season increased steadily from 1990 to 2004 in Taiwan. Numbers of the BFS in Taiwan accounted for more than 50% of the total population, with 96% of the BFS in southwestern Taiwan at the town of Chi-Ku and Tainan City. The percentage of adult BFS remained constant from 2000-2003. Relatively constant high survey counts, with similar ratios of adult to non-adult birds, suggested that the BFS has a healthy population. With the exception of avian botulism resulting in 73 BFS deaths in the 2002 winter, several other mortality factors were documented with no more than four birds lost in a year from 1849-2004. I counted numbers of BFS at the town of Chi-Ku and Tainan City almost daily during the winter months from September 1998 to May 2001. Although variable, overall population numbers increased sharply from September to October. From November to February, the BFS maintained a high, stable population-level. Migration began during March, and population numbers decreased from March to May. I used visual observations and radio-telemetry data to locate, count and monitor BFS during the day and night, respectively, and also to assess nocturnal habitat use. Information obtained through these methods showed that habitat use was not in direct proportion to its availability. Activity ranges obtained from radio tracking and visual observations showed an increase in activity range size by BFS just prior to migration with more of the study area used north of the core-roosting area. Sizes and weights of potential prey items were measured at fish ponds used by BFS. Available prey in fish ponds was dominated by fish prey less than 5 cm in length and at least 30 gm in size. Similar size classes of prey items were selected by a captive BFS. Biomass of prey in fish ponds around the primary roosting site declined sharply in the pre-migration stage (March-April), compared to the middle winter stage (November-February). I suggest that this low biomass of prey items may have stimulated the northward movement of BFS in the late stage of winter. In addition, the activity range expansion may have related to preparation for migration.

Thesis (M.S.)--University of Idaho, 2002. / Includes bibliographical references. The annotated bibliography portion is also available via the World Wide Web.

The motivation for this research was an improvement of the quality of the Earth’s gravity solutions from the GRACE mission data through an instrument-level study. The objective was a better understanding of the characteristics and sources of the highfrequency noise in the range of (0.02 ~ 0.1 Hz) in the dual one-way ranging (DOWR) and its effect on the gravity solution. For this purpose, the mathematical model of the DOWR observation was derived and the Allan variance was computed to establish an upper bound on the level of frequency instability of the ultra-stable oscillators (USO) to determine their contribution to the high-frequency noise. Because they are dominated by the high-frequency noise, the postfit residuals of the time derivative of the DOWR ranges were also examined to evaluate the contributions of various other factors such as system noise from the microwave signal receiver, external influences, and internal influences. The results indicate that the system noise is the dominant source of the excessive highfrequency noise. As one method of mitigation, a tighter bandwidth filter was applied to the DOWR processing, resulting in modest improvements in gravity solutions. / text

ITC/USA 2012 Conference Proceedings / The Forty-Eighth Annual International Telemetering Conference and Technical Exhibition / October 22-25, 2012 / Town and Country Resort & Convention Center, San Diego, California / The iNET program uses network technology and infrastructure to enhance traditional telemetry systems. The program's components were designed with an eye to existing and emerging technology and infrastructure, requiring the program to gather data about these systems. The methods used in this design effort can be used to characterize existing network infrastructure to determine what upgrades and changes are necessary to deploy a TmNS. This paper describes the methods used for characterizing a range network infrastructure and explores network capacity and policy issues effecting a TmNS deployment. This effort includes making estimates and taking measurements of network capacity, surveying and analyzing network routing/management policies, and proposes a system for evaluating networks for future TmNS deployments.