SAS has become an increasingly important public-health problem in recent years. It can abversely affect neurocognitive, cardiovascular, respiratory diseases and can also cause behavior disorder. Moreover, up to 90¢H of these cases are obstructive sleep apnea (OSA). Therefore, it is important that how to diagnose, detect and treat OSA. The respiratory disturbance index is one parameter of estimating OSA. Polysomnography can monitor the OSA with relatively fewer invasive techniques. However, polysomnography-based sleep studies are expensive and time-consuming because they require overnight evaluation in sleep laboratories with dedicated systems and attending personnel. Based on the digital oximetry, this work introduces the estimating respiratory disturbance index. In particular, via signal processing, feature parameters and artificial intelligence, this thesis describes an off-line SpO2-based RDI estimating system.

The southern pine beetle (SPB) (Dendroctonus frontalis Zimm.) is one of the most destructive forest insect pests in the southeastern United States and has historically had a large impact on the forests of North Carolina. Many characteristics of a forest can contribute to SPB susceptibility including stand density, growth rate, age, soil type, and position on the landscape. This work was undertaken in an effort to assist and improve on the current federal SPB hazard modeling being conducted for North Carolina by the USDA Forest Service – Forest Health Protection's Forest Health Technology Enterprise Team (FHTET). In our study, predictive SPB susceptibility models were developed for each physiographic region in North Carolina using two variables not currently included in the FHTET modeling, mean stand age and the in-stand percentage of sawtimber-sized pines. These variables were obtained from USDA Forest Service – Forest Inventory and Analysis (FIA) data and North Carolina Forest Service historical SPB records creating a dataset of both infested and non-infested stands and the models were developed using the CART® classification tree approach. Two model-derived age classes (older than and younger than 22 years) were identified on the landscape using current Landsat 5 Thematic Mapper (TM) imagery chronosequences of disturbance index (DI) â transformed scenes to identify stand-replacing disturbances, resulting in a kappa statistic of 0.6364 for the younger than 22 year age class and 0.7778 for the older than 22 years age class. A kappa value of 1 is ideal. The CART® modeling effort produced valid models in all three physiographic regions of North Carolina, though the complexity of the piedmont model makes it impractical for use in the field. The dependent variable in the classification tree was presence or absence of SPB outbreak and the test sample error percentages were similar across regions, with errors ranging between 23.76 - 34.95 percent. Overall prediction success, based on the software's internal cross-validation procedure, was likewise comparable across the regions with 72.28 - 89.56 percent correctly predicted. Based on our modeling, stand age and percent sawtimber should be included in future FHTET SPB hazard modeling efforts for the coastal plain and mountains, respectively. Age classes can be reasonably estimated using Landsat or other multispectral imagery. / Master of Science

A study was conducted to determine what impact high white-tailed deer (Odocoileus virginianus) densities were having on the native grasslands of a tallgrass: aspen forest tract embedded within an agro-urban setting. Due to excessive spring moisture, row-crops were unavailable the first year. Using microhistological fecal analysis to determine dietary composition, deer were assessed to be placing the site’s favoured native plant species at risk of extirpation. Measuring woody stem abundance and height along and near the prairie: forest ecotone, deer were found to restructure woody growth but not directly influence encroachment rates. Indirectly, however, deer facilitated forest encroachment and prairie degradation through seed dispersal, nitrogen deposition, gap-dynamics, and trampling. Comparing dietary composition to nutritional data, deer grazed to maximize fitness, selecting foods high in IVDMD, minimizing energy expenditure, and optimizing CP. High crop CP was offset by intensively grazing particular native plants. ADF was an effective nutritional marker, not AIA.

A study was conducted to determine what impact high white-tailed deer (Odocoileus virginianus) densities were having on the native grasslands of a tallgrass: aspen forest tract embedded within an agro-urban setting. Due to excessive spring moisture, row-crops were unavailable the first year. Using microhistological fecal analysis to determine dietary composition, deer were assessed to be placing the site’s favoured native plant species at risk of extirpation. Measuring woody stem abundance and height along and near the prairie: forest ecotone, deer were found to restructure woody growth but not directly influence encroachment rates. Indirectly, however, deer facilitated forest encroachment and prairie degradation through seed dispersal, nitrogen deposition, gap-dynamics, and trampling. Comparing dietary composition to nutritional data, deer grazed to maximize fitness, selecting foods high in IVDMD, minimizing energy expenditure, and optimizing CP. High crop CP was offset by intensively grazing particular native plants. ADF was an effective nutritional marker, not AIA.