A dynamic model is developed and presented that predicts the voltage response for a Severinghaus electrode-based point-of-care pCO2 sensor. Eight partial differential equations are derived to describe the diffusion and reaction phenomena in the sensor. The model is able to predict the potential response versus time behaviour from different CO2 concentrations in the calibration fluid and control fluids. The two most influential and uncertain parameters in the model are determined to be the forward rate constant for benzoquinone consumption at the gold surface ( k_(f_Au ) ), and the partition coefficient for CO2 between the membrane and the electrolyte (κ_(〖CO〗_(2_m ) )). These parameters were adjusted heuristically to obtain a good fit (within 2 mV) between the dynamic voltage response data and the model predictions during a critical 4 second period. The model predictions are sufficient for design sensitivity studies, however an improved fit might be possible using a formal least-squares parameter estimation approach, or if additional parameters were estimated. Several design parameters are varied to study the influence of the electrolyte concentration and the sensor geometry on the voltage response. The most influential design parameter studied is the amount of water present in the electrolyte during sensor operation. This can be affected by the amount of water evaporated during manufacturing and storage, and by the amount of water present when the sensor “wets up” again during operation. The amount of water picked up by the sensor in turn is affected by design parameters such as component/membrane dimensions and thicknesses. The initial buffer concentration in the electrolyte is the second most influential parameter. The resulting model can be used to perform “what if” analyses in order to understand the impact of design decisions on the sensor performance, and to potentially improve the sensor from performance and manufacturing cost perspectives. / Thesis (Master, Chemical Engineering) -- Queen's University, 2014-02-06 15:00:47.555

Elastic deformation has wide applications in medical simulations, therefore when it comes to designing physical behavior of objects for realistic training applications, determining material parameters so that objects behave in a desired way becomes a crucial. In this work we consider the problem of elasticity parameter estimation for deformable bodies, which is important for accurate medical simulations. Our work has two major steps: the first step is the data acquisition and preparation, and the second step is the parameter estimation. The experimental setup for data acquisition consists of depth and force sensors. Surface deformations are acquired as a series of images along with the corresponding applied forces. The contact point of the force sensor on the surface is found visually and the corresponding applied forces are acquired directly from the force sensor. A complete mesh deformation which is obtained from a surface tracking method is employed along with force measurements in the elasticity parameter estimation method. Our approach to estimate the physical material properties is based on an inverse linear finite element method. We have experimented with two approaches to optimize the elasticity parameters: a linear iterative method and a force-displacement error minimization method. The two methods were tested on the simulation data, and the second method was tested on three deformable objects. The results are presented for the data captured by two different depth sensors. The result is a set of two parameters, the Young's modulus and the Poisson's ratio, which represents the stiffness of the object under test.

This thesis studies implementation-related issues in OFDM-based digital receivers, using the IEEE 802.11a WLAN standard as a specific wireless technology, where the data rate ranges from 6 Mbps to 54 Mbps. Our goal is to expose and exploit the possibility of scaling of the receiver computational complexity in relation to variable data rate requirements. To facilitate such computational scalability, we propose and evaluate the use of the polar coordinates during data processing in the frequency domain. We also evaluate the impact of various fixed-point precision settings during data processing in both the time domain and the frequency domain. We have found that for the 6-Mbps and 54-Mbps data rates the appropriate fixed-point word length should be 15 bits and 20 bits, respectively. While evaluating different fixed-point precision settings, we found that simulations times were prohibitively long. To address this issue, we also propose an alternative 5-step simulation procedure that significantly reduces the simulation time needed to evaluate any given fixed-point setting option. / Graduate

This thesis uses data-driven techniques to analyse and assess both point and probability forecasts within a prequential framework. Point forecasts are assessed using recursive residuals. Examination of the properties of the recursive residual found them to be unique to this residual. Recursive residuals for the hidden state of HMM are also defined by taking the difference between the one step ahead forecast and the forecast's filtered update. The quality of forecasts generated from different models can be assessed by comparing the information content in their corresponding residuals. When faced with model to correct this misspecification it is shown how this residual can be modelled to correct this misspecification, thereby improving forecasts. It is also shown how the residual content can be used to judge the predictive sufficiency of alternative forecasting methods. Using the theory of probability forecasting, the technique of forecasting assessment by calibration is extended to HMM's to assess how well the one step ahead forecast is explained by its filtered update. A test statistic to test the empirical calibration of the forecasts is also defined and applied to the real world problem of CpG island detection in Human DNA sequences. The distribution of the test statistic is investigated using a prequential frame of reference and is found to be N(0.1). Calibration of HMMs is also examined using smoothed predictions and cross- validation forecasts. A test statistic is defined for this scenario and the its distribution is examined using a cross- validation frame of reference. A prequential estimation algorithm for HMMs is also developed.

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vi, 99 leaves : ill. ; 26 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Thesis (Ph.D.)--University of Adelaide, Dept. of Pure Mathematics, 1974

Thesis (Ph. D.)--Oregon State University, 1988. / Typescript (photocopy). Includes bibliographical references (leaves 71-74). Also available on the World Wide Web.

Thesis (Ph.D.) -- University of Adelaide, Department of Pure Mathematics, 1974.

Thesis (doctoral)--Universität, Paderborn, 2007. / Includes bibliographical references (p. [231]-235) and index.