979 resultados para animal tracking and telemetry


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Most studies of language minority students' performance focus on students' characteristics. This study uses qualitative methodology to examine instead how educational policies and practices affect the tracking of language minority students who are classified as limited English proficient (LEP). The placement of LEP students in core courses (English, Math, Social Studies, and Science) is seen as resulting from the interaction between school context and student characteristics. The school context includes factors such as equity policy requirements, overcrowding, attitudes regarding immigrants' academic potential, tracking, and testing practices. Interaction among these factors frequently leads to placement in lower track courses. It was found that the absence of formal tracks could be misleading to immigrant students, particularly those with high aspirations who do not understand the implications of the informal tracking system. Findings are discussed in relation to current theoretical explanations for minority student performance. ^

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The main challenges of multimedia data retrieval lie in the effective mapping between low-level features and high-level concepts, and in the individual users' subjective perceptions of multimedia content. ^ The objectives of this dissertation are to develop an integrated multimedia indexing and retrieval framework with the aim to bridge the gap between semantic concepts and low-level features. To achieve this goal, a set of core techniques have been developed, including image segmentation, content-based image retrieval, object tracking, video indexing, and video event detection. These core techniques are integrated in a systematic way to enable the semantic search for images/videos, and can be tailored to solve the problems in other multimedia related domains. In image retrieval, two new methods of bridging the semantic gap are proposed: (1) for general content-based image retrieval, a stochastic mechanism is utilized to enable the long-term learning of high-level concepts from a set of training data, such as user access frequencies and access patterns of images. (2) In addition to whole-image retrieval, a novel multiple instance learning framework is proposed for object-based image retrieval, by which a user is allowed to more effectively search for images that contain multiple objects of interest. An enhanced image segmentation algorithm is developed to extract the object information from images. This segmentation algorithm is further used in video indexing and retrieval, by which a robust video shot/scene segmentation method is developed based on low-level visual feature comparison, object tracking, and audio analysis. Based on shot boundaries, a novel data mining framework is further proposed to detect events in soccer videos, while fully utilizing the multi-modality features and object information obtained through video shot/scene detection. ^ Another contribution of this dissertation is the potential of the above techniques to be tailored and applied to other multimedia applications. This is demonstrated by their utilization in traffic video surveillance applications. The enhanced image segmentation algorithm, coupled with an adaptive background learning algorithm, improves the performance of vehicle identification. A sophisticated object tracking algorithm is proposed to track individual vehicles, while the spatial and temporal relationships of vehicle objects are modeled by an abstract semantic model. ^

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In the Florida Everglades, tree islands are conspicuous heterogeneous elements in a complex wetland landscape. I investigated the effects of increased freshwater flow in southern Everglades seasonally flooded tree islands, and characterized biogeochemical interactions among tree islands and the marsh landscape matrix, specifically examining hydrologic flows of nitrogen (N), and landscape N sequestration capacity. I utilized ecological trajectories of key ecosystem variables to differentiate effects of increased sheetflow and hydroperiod. I utilized stable isotope analyses and nutrient content of tree island ecosystem components to test the hypothesis that key processes in tree island nitrogen cycling would favor ecosystem N sequestration. I combined estimates of tree island ecosystem N standing stocks and fluxes, soil and litter N transformation rates, and hydrologic inputs of N to quantify the net sequestration of N by a seasonally flooded tree island. ^ Results show that increased freshwater flow to seasonally flooded tree islands promoted ecosystem oligotrophy, whereas reduced flows allowed some plant species to cycle P less efficiently. As oligotrophy is a defining parameter of Everglades wetlands, and likely promotes belowground production and peat development, reintroducing freshwater flow from an upstream canal had a favorable effect on ecosystem dynamics of tree islands in the study area. Important factors influencing the stable isotopic composition of nitrogen and carbon were: (1) a contribution to soil N by soil invertebrates, animal excrement, and microbes, (2) a possible NO3 source from an upstream canal and an "open" ecosystem N cycle, and (3) greater availability of phosphorus in tree islands relative to the marsh landscape, suggesting that tree island N cycling favors N sequestration. Hydrologic sources of N were dominated by surface water loads of NO3- and NH 4+, and an important soil N transformation promoting the net loss of surface water DIN was nitrate immobilization associated with soils and surficial leaf litter. The net inorganic N sequestration capacity of a seasonally flooded tree island was 50 g yr-1 m -2. Thus, tree islands likely have an important function in landscape sequestration of inorganic N, and may reduce significant anthropogenic N loads to downstream coastal systems. ^