5 resultados para classification and regression tree

em Digital Commons at Florida International University


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This research is to establish new optimization methods for pattern recognition and classification of different white blood cells in actual patient data to enhance the process of diagnosis. Beckman-Coulter Corporation supplied flow cytometry data of numerous patients that are used as training sets to exploit the different physiological characteristics of the different samples provided. The methods of Support Vector Machines (SVM) and Artificial Neural Networks (ANN) were used as promising pattern classification techniques to identify different white blood cell samples and provide information to medical doctors in the form of diagnostic references for the specific disease states, leukemia. The obtained results prove that when a neural network classifier is well configured and trained with cross-validation, it can perform better than support vector classifiers alone for this type of data. Furthermore, a new unsupervised learning algorithm---Density based Adaptive Window Clustering algorithm (DAWC) was designed to process large volumes of data for finding location of high data cluster in real-time. It reduces the computational load to ∼O(N) number of computations, and thus making the algorithm more attractive and faster than current hierarchical algorithms.

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Eddy covariance (EC) estimates of carbon dioxide (CO2) fluxes and energy balance are examined to investigate the functional responses of a mature mangrove forest to a disturbance generated by Hurricane Wilma on October 24, 2005 in the Florida Everglades. At the EC site, high winds from the hurricane caused nearly 100% defoliation in the upper canopy and widespread tree mortality. Soil temperatures down to -50 cm increased, and air temperature lapse rates within the forest canopy switched from statically stable to statically unstable conditions following the disturbance. Unstable conditions allowed more efficient transport of water vapor and CO2 from the surface up to the upper canopy layer. Significant increases in latent heat fluxes (LE) and nighttime net ecosystem exchange (NEE) were also observed and sensible heat fluxes (H) as a proportion of net radiation decreased significantly in response to the disturbance. Many of these impacts persisted through much of the study period through 2009. However, local albedo and MODIS (Moderate Resolution Imaging Spectro-radiometer) data (the Enhanced Vegetation Index) indicated a substantial proportion of active leaf area recovered before the EC measurements began 1 year after the storm. Observed changes in the vertical distribution and the degree of clumping in newly emerged leaves may have affected the energy balance. Direct comparisons of daytime NEE values from before the storm and after our measurements resumed did not show substantial or consistent differences that could be attributed to the disturbance. Regression analyses on seasonal time scales were required to differentiate the storm's impact on monthly average daytime NEE from the changes caused by interannual variability in other environmental drivers. The effects of the storm were apparent on annual time scales, and CO2 uptake remained approximately 250 g C m-2 yr-1 lower in 2009 compared to the average annual values measured in 2004-2005. Dry season CO2 uptake was relatively more affected by the disturbance than wet season values. Complex leaf regeneration dynamics on damaged trees during ecosystem recovery are hypothesized to lead to the variable dry versus wet season impacts on daytime NEE. In contrast, nighttime CO2 release (i.e., nighttime respiration) was consistently and significantly greater, possibly as a result of the enhanced decomposition of litter and coarse woody debris generated by the storm, and this effect was most apparent in the wet seasons compared to the dry seasons. The largest pre- and post-storm differences in NEE coincided roughly with the delayed peak in cumulative mortality of stems in 2007-2008. Across the hurricane-impacted region, cumulative tree mortality rates were also closely correlated with declines in peat surface elevation. Mangrove forest-atmosphere interactions are interpreted with respect to the damage and recovery of stand dynamics and soil accretion processes following the hurricane.

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More than half of the original Everglades extent formed a patterned peat mosaic of elevated ridges, lower and more open sloughs, and tree islands aligned parallel to the dominant flow direction. This ecologically important landscape structure remained in a dynamic equilibrium for millennia prior to rapid degradation over the past century in response to human manipulation of the hydrologic system. Restoration of the patterned landscape structure is one of the primary objectives of the Everglades restoration effort. Recent research has revealed that three main drivers regulated feedbacks that initiated and maintained landscape structure: the spatial and temporal distribution of surface water depths, surface and subsurface flow, and phosphorus supply. Causes of recent degradation include but are not limited to perturbations to these historically important controls; shifts in mineral and sulfate supply may have also contributed to degradation. Restoring predrainage hydrologic conditions will likely preserve remaining landscape pattern structure, provided a sufficient supply of surface water with low nutrient and low total dissolved solids content exists to maintain a rainfall-driven water chemistry. However, because of hysteresis in landscape evolution trajectories, restoration of areas with a fully degraded landscape could require additional human intervention.

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Hydrologic modifications have negatively impacted the Florida Everglades in numerous significant ways. The compartmentalization of the once continuously flowing system into the Water Conservation Areas (WCAs) caused disruption of the slow natural flow of water south from Lake Okeechobee through the Everglades to Florida Bay. The ponding of water in the WCAs, the linking of water flow to controlled water levels, and the management of water levels for anthropogenic vs. ecological well-being has caused a reduction in the spatial heterogeneity of the Everglades leading to greater uniformity in topography and vegetation. These effects are noticeable as the degradation in structure of the Everglades Ridge and Slough environment and associated Tree Islands. In aquatic systems water flow is of fundamental importance in shaping the structure and function of the ecosystem. The organized patterns of parallel orientation of ridges, sloughs, and tear-drop shaped tree islands along historic flow paths attest to the importance of water movement in structuring this system. Our main objective was to operate and manage the LILA facility to provide a broad potential as a research platform for an integrated group of multidisciplinary, multi-agency scientists collaborating on multifunctional studies aimed primarily at determining the effects of CERP water management scenarios on the ecology of tree islands and ridge and slough habitats. We support Everglades water management, CERP, and the Long-Term Plan by defining hydrologic regimes that sustain healthy tree islands and ridge and slough ecosystems. Information gained through this project will help to reduce the uncertainty of predicting the tree island and ridge and slough ecosystem response to changes in hydrologic conditions. Additionally, we have developed the LILA site as a visual example of Everglades restoration programs in action.

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This report examines the interaction between hydrology and vegetation over a 10-year period, between 2001/02 and 2012 within six permanent tree island plots located on three tree islands, two plots each per tree island, established in 2001/02, along a hydrologic and productivity gradient. We hypothesize that: (H1) hydrologic differences within plots between census dates will result in marked differences in a) tree and sapling densities, b) tree basal area, and c) forest structure, i.e., canopy volume and height, and (H2) tree island growth, development, and succession is dependent on hydrologic fluxes, particularly during periods of prolonged droughts or below average hydroperiods.