Obstructive Sleep Apnea (OSA) is a common respiratory disorder during sleep. Apnea is cessation of airflow to the lungs, which lasts for at least 10 seconds accompanied by more than 4% drop of the blood's Oxygen saturation. Polysomnography during the entire night is the Gold Standard diagnostic method of OSA. It's high cost and inconvenience for patients persuaded researchers to seek alternative OSA detection methods. This thesis proposes a technique for assessment of OSA during wakefulness. We recorded tracheal breath sounds of 17 non-apneic individuals and 35 people with various degrees of OSA severity in supine and upright positions during nose and mouth breathing at medium flow rate. We calculated the power spectrum, Kurtosis, and Katz fractal dimensions of the recorded signals. Then, we reduced the number of characteristic features to two. We classified the participant into severe OSA and non-OSA groups as well as non-OSA or mild vs. moderate and severe OSA groups. The results showed more than 91 and 83% accuracy; for the two types of classification. Once veri ed on a larger population, the proposed method may be used as a simple and non-invasive screening tool for assessment of OSA during wakefulness.

Freezing rain is an especially hazardous type of adverse weather and is frequently observed in Churchill, Manitoba. The goals of this study were to assess the climatology of freezing rain in Churchill, assess the synoptic climatology of the Hudson Bay region using a multi-level synoptic classification scheme, assess the relationships between the synoptic climate and freezing rain events, and assess the trends in synoptic types and to discuss the implications of climate change in relation to the expected changes in freezing rain. For the years 1953 thru 2009, freezing rain was observed during 796 hours, an average of approximately 15 hours per year. A 34-type multi-level synoptic classification consisting of five NCEP/NCAR reanalysis datasets was constructed. Type-20 was associated with a majority of the freezing rain cases. More research is needed to understand how climate change may impact the timing, frequency and intensity of freezing rain in Churchill.

Larval development of Berthella californica, a pleurobranchoidean heterobranch from the Northeastern Pacific, is described using histological sectioning, SEM, TEM, and immunolabelling. Current phylogenetic hypotheses place the Pleurobranchoidea as sister to all nudibranchs, or as sister to only the anthobranch nudibranchs. Deciding between these alternatives is difficult due to extensive homoplasy among heterobranchs. Analysis of larval morphology may help resolve this issue by identifying additional phylogenetically informative characters. Larval development has been well documented for many nudibranchs, but there are few studies on pleurobranchoideans. Larvae of B. calfornica dissolve internal shell whorls, a trait uniquely shared with nudibranch larvae. Additionally, mantle fold tissue inflates and reflects dorsally during metamorphosis to form the notum, which also occurs in anthobranchs. B. californica possesses several unusual developmental traits, as revealed by a review of current knowledge of heterobranch development. Morphological characters of B. californica larvae support hypotheses of nudibranch paraphyly and the clade Pleuroanthobranchea.

The monophyly of the Geometrinae is examined by investigating the green wing pigment and morphology of the tympanal (hearing) organs. The green colour of Geometrinae is caused by a single pigment, here termed geoverdin, located in the scales. Analysis of this pigment indicates that it is neither a bile pigment nor a derivative of chlorophyll. A method developed for taxonomic comparison of lepidopteran pigments and based on a chromatographic profiling technique is presented. The morphology of geometrid tympanal organs is described and an apomorphy for the Geometrinae, the distinctive shape of the ansa, is proposed. The value of the taxonomic literature on the Geometrinae is assessed in terms of its ability to identify internal monophyletic groups. A taxonomic revision of the genus Oospila Warren is presented, in which the neotropical genera Auophylla Warren, Auophyllodes Prout, Halioscia Warren, Oospila Warren, Oospiloma Prout, Progonodes Warren and Racheolopha Warren are united into a single genus. Phylogenetic analysis is used to demonstrate the monophyly of the revised genus Oospila and to assess relationships between species groups within it. The revised genus Oospila is defined as a monophyletic group supported by two apomorphic characters: the form of the abdominal crests and the presence of an anellar complex produced by the fusion of the juxta and transtilla. Sixty-six species of Oospila are treated, of which three are described as new. One new subspecies is also described. Forty-eight species group names are synonymised, and 16 species are recombined with Oospila.

The objective of this research is to identify and analyze sexual characters in mammalian skeletons in order to develop new methods for sex determination of archaeological animal remains. The study begins with an examination of the evolutionary and developmental framework of sexual characters, and a review of the current methods used for sex classification of animal remains. The materials and methods used in this research have been designed to locate the tertiary sexual characters in the fox, dog, pig, deer, and sheep skeletons. Morphometric and osteometric analyses of 11 elements of the post-cranial skeleton (atlas, axis, glenoid, proximal humerus, distal humerus, proximal metacarpus, innominate, proximal femur, distal tibia, astragalus, proximal metatarsus) have been conducted. Shape and size differences of bones have been analyzed using the F- test of variance and canonical variates analysis for shape variables, and discriminant analysis and the two-sample t- test for metrical data, to determine significance. Eigenshape analysis, an outline-based form of morphometrics, has been implemented for comparing bone shapes. Score plots have been produced by comparing eigenshape scores to indicate shape trends formed by the male and female bone groups. Mean shapes, calculated by the eigenshape program, have been superimposed so that differences in bone morphology between the sexes can be identified. Two alternative methods are introduced in this study, the Mean Shape Method for identifying sexual dimorphic or tnmorphic (with castrates) bones, and the Table Test for sexing canid humeri. These methods have been tested in a blind test to check confidence of sex classification. The new methods have been applied to bone samples from archaeological sites: Silchester for dog remains, Star Carr for red deer remains, and Canterbury for sheep remains. The results suggest that dogs buried at Silchester were female individuals, that predominantly male deer were hunted at Star Can, and that castration of sheep was practiced at Canterbury. Overall, the alternative methods developed here can aid in identifying the sex of archaeological bones more effectively.

The principal aim of this study was to develop a classification model in disability sports. Using disability swimming as an example, methods of participant observation, interview, survey and document analysis were undertaken in three empirical studies to develop and clarify the classification model and three elements in swimming classification- (a) the classification process, (b) classifiers and (c) the classification system. First, the swimming classification process was identified as a social process. Members in the classification process socially interacted. The detailed classification process was described, interpreted and discussed. Several features in the classification process were identified. They included interaction among social actors, routinization, rules in the process, resources used by classifiers, power relations among social actors, allocation of rewards and sanctions in the classification process, and conflicts among social actors. Second, the role of classifiers as an agent of social control in disability swimming was examined. Resources used by medical and technical classifiers in the classification process to maintain their role and social order, and the socialization of classifiers in swimming were specifically explored. In addition, the important characteristics of swimming classifiers were identified in the study. Third, classification outcomes in disability swimming were monitored to evaluate the effectiveness of the classification system. Performance and impairment approaches were used in the study. Data of performances and types of impairment of Paralympic swimmers were analysed. The results revealed that the swimming classification system was generally fair but some classes needed to be fine-tuned. In this study elements of the classification model were clarified by integration of the results of the three empirical studies and the classification literature. It is suggested that researchers may use the concepts of the classification model for further investigationin disability sportc lassificationa nd disability sport committees may apply the model to systematicallye valuatet heir own classification systems, processes and classifiers.

An item may be said to reach a standard suitable for use if it has some prescribed attributes. Supposet hat a variable 2: measurest he standard and TE, qT. if an item has the desired attributes. The variable -T may be very expensive to measure and so, some cheaper to measure screening variables, X say, correlated to I may be used to classify items. The purpose of screen design is to determine CX, the region of X space, for which an item should be said to reach the standard. If the error probabilities of classifying an item based on X are very high it may be economical to measure IT. Chapter 2 deals with this idea in the context of a very simple two-stage set-up in which, at the first stage of the screen a univariate screening variable X is measured. Some items are sentenced as acceptable or unacceptable, and the remainder are passed on to the second stage at which T is determined. The optimal screen is found that minimises cost, where costs are given for misclassifying items and for measuring the variables. The variable T is assumed binary and the model for TIX is a probit regression model. In designing a two-stage screen, Chapter 3 considers: (a) a general stochastic structure for (1, X), (b) a general loss function set up for misclassification costs and (c) assumes no fixed form for the screen. Also in Chapter 3, we consider a scenario in which a statistical goal or constraint is imposed in addition to the decision-theoretic target of minimising expected cost. In Chapter 4 we consider a sequential screen that operates as follows. At each stage of a sequence a covariate is measured and items may be accepted as suitable, discarded or passed on to the next stage. At the final stage the performance variable T is measured. Returning to the simple one-stage screen based solely on measuring covariates, Chapter 5 poses the question of how many and which covariates to include as part of the screen.

No description available.

Text categorization (TC) is the task of automatically categorizing textual digital documents into pre-set categories by analyzing their contents. The purpose of this study is to develop an effective TC model to resolve the difficulty of automatic classification. In this study, two primary goals are intended. First, a Hidden Markov Model (HAM is proposed as a relatively new method for text categorization. HMM has been applied to a wide range of applications in text processing such as text segmentation and event tracking, information retrieval, and information extraction. Few, however, have applied HMM to TC. Second, the Library of Congress Classification (LCC) is adopted as a classification scheme for the HMM-based TC model for categorizing digital documents. LCC has been used only in a handful of experiments for the purpose of automatic classification. In the proposed framework, a general prototype for an HMM-based TC model is designed, and an experimental model based on the prototype is implemented so as to categorize digitalized documents into LCC. A sample of abstracts from the ProQuest Digital Dissertations database is used for the test-base. Dissertation abstracts, which are pre-classified by professional librarians, form an ideal test-base for evaluating the proposed model of automatic TC. For comparative purposes, a Naive Bayesian model, which has been extensively used in TC applications, is also implemented. Our experimental results show that the performance of our model surpasses that of the Naive Bayesian model as measured by comparing the automatic classification of abstracts to the manual classification performed by professionals.

Bogs and fens, which comprise > 90% of the landscape near the De Beers Victor diamond mine, 90 km west of Attawapiskat, ON, provide different hydrological functions in connecting water flow pathways to the regional drainage network. It is essential to define their distribution, area and arrangement to understand the impact of mine dewatering, which is expected to increase groundwater recharge. Classification was achieved by developing a technique that uses IKONOS satellite imagery coupled with LiDAR-derived DEM derivatives to identify peatland classes. A supervised maximum likelihood classification was performed on the 1 m resolution IKONOS Red/Green/Blue without the infrared (RGB) and with the infrared (IR_RGB) band to determine the overall accuracy prior to inclusion of the DEM derivatives. Confusion matrices indicated 62.9% and 65.8% overall accuracy for the RGB and IR_RGB, respectively. Terrain derivatives were computed from the DEM including slope, vertical distance to channel network (VDCN), deviation from mean elevation (DME), percentile (PER) and difference from mean elevation (DiME). These derivatives were computed at a local (15-cell grid size) and meso (250-cell grid size) scale to capture terrain morphology. The mesoscale 250-cell grid analysis produced the most accurate classifications for all derivatives. However, spectral confusion still occurred (regardless of scale) most frequently in the Fen Dense Conifer vs. Bog Dense Conifer classes and also in the Bog Lichen vs. Bog Lichen Conifer. Despite this confusion, by combining the larger scale LiDAR DEM derivatives and the IKONOS imagery it was found that the overall classification accuracy could be improved by 13%. Specifically, the DiME derivative combined with the multispectral IKONOS (IR_RGB) produced an overall accuracy of 76.5%, and increased to 83.7% when Bog Lichen and Bog Lichen Conifer were combined during a post hoc analysis. This classification revealed the landscape composition of the North Granny Creek subwatershed, which is divided into north and south. The north portion comprises 67.4% bog, 13.6% fen and 18.9% water class, while the south is 63.7% bog, 15.2% fen and 21.1% water class. These proportions provide insight into the hydrology of the landscape and are indicative of the storage and conveyance properties of the subwatershed based on the percentage of bog, fen, or open water.