New surgical approaches for total hip arthroplasty (THA) are being developed to reduce muscle damage sustained during surgery, in the hope to allow better muscle functioning afterwards. The goal of this study was to compare the muscle sparing anterior (ANT) approach to a traditional lateral (LAT) approach with three-dimensional motion analysis. Kinematics and kinetics were obtained with an infrared camera system and force plates. It was hypothesized that (1) the ANT group would have closer to normal range of motion, moments and powers, compared to the LAT group, and that (2) the ANT group would have higher peak hip abduction moment than the LAT group. Forty patients undergoing unilateral THA for osteoarthritis between the ages of 50 and 75 (20 ANT, 20 LAT) were asked to perform three trials of walking, stair ascent and stair descent. Patients were assessed between six to twelve months postoperatively. Twenty age- and weight-matched control participants (CON) provided normative data. Results indicated that both THA groups had gait anomalies compared to the CON group. Both THA groups had reduced hip abduction moment during walking (CON vs. ANT: p<0.001; CON vs. LAT: p=0.011), and the ANT group had a significantly lower hip abduction moment compared to the LAT group (p=0.008). Similar results were observed during stair descent, where the ANT group had reduced peak hip abduction moment compared to the CON group (p<0.001) and the LAT group (p=0.014). This indicates that the anterior approach did not allow better gait and stair climbing ability after THA. It is therefore thought that other variables, such as preoperative gait adaptations, trauma from the surgery, or postoperative protection mechanisms to avoid loading the prosthetic hip, are factors that might be more important than surgical approach in determining the mechanics of THA patients after surgery.

New surgical approaches for total hip arthroplasty (THA) are being developed to reduce muscle damage sustained during surgery, in the hope to allow better muscle functioning afterwards. The goal of this study was to compare the muscle sparing anterior (ANT) approach to a traditional lateral (LAT) approach with three-dimensional motion analysis. Kinematics and kinetics were obtained with an infrared camera system and force plates. It was hypothesized that (1) the ANT group would have closer to normal range of motion, moments and powers, compared to the LAT group, and that (2) the ANT group would have higher peak hip abduction moment than the LAT group. Forty patients undergoing unilateral THA for osteoarthritis between the ages of 50 and 75 (20 ANT, 20 LAT) were asked to perform three trials of walking, stair ascent and stair descent. Patients were assessed between six to twelve months postoperatively. Twenty age- and weight-matched control participants (CON) provided normative data. Results indicated that both THA groups had gait anomalies compared to the CON group. Both THA groups had reduced hip abduction moment during walking (CON vs. ANT: p<0.001; CON vs. LAT: p=0.011), and the ANT group had a significantly lower hip abduction moment compared to the LAT group (p=0.008). Similar results were observed during stair descent, where the ANT group had reduced peak hip abduction moment compared to the CON group (p<0.001) and the LAT group (p=0.014). This indicates that the anterior approach did not allow better gait and stair climbing ability after THA. It is therefore thought that other variables, such as preoperative gait adaptations, trauma from the surgery, or postoperative protection mechanisms to avoid loading the prosthetic hip, are factors that might be more important than surgical approach in determining the mechanics of THA patients after surgery.

One of the most essential objectives in WSNs is to determine the spatial coordinates of a source or a sensor node having information. In this study, the problem of range measurement-based localization of a signal source or a sensor is revisited. The main challenge of the problem results from the non-convexity associated with range measurements calculated using the distances from the set of nodes with known positions to a xed sen- sor node. Such measurements corresponding to certain distances are non-convex in two and three dimensions. Attempts recently proposed in the literature to eliminate the non- convexity approach the problem as a non-convex geometric minimization problem, using techniques to handle the non-convexity. This study proposes a new fuzzy range-free sensor localization method. The method suggests using some notions of Euclidean geometry to convert the problem into a convex geometric problem. The convex equivalent problem is built using convex fuzzy sets, thus avoiding multiple stable local minima issues, then a gradient based localization algorithm is chosen to solve the problem. Next, the proposed algorithm is simulated considering various scenarios, including the number of available source nodes, fuzzi cation level, and area coverage. The results are compared with an algorithm having similar fuzzy logic settings. Also, the behaviour of both algorithms with noisy measurements are discussed. Finally, future extensions of the algorithm are suggested, along with some guidelines.

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A helicopter rotor in descent flight encounters its own wake, resulting in a doughnut-shaped ring around the rotor disk, known as the Vortex Ring State (VRS). Flight in VRS condition can be dangerous as it may cause uncommanded drop in descent rate, loss of control effectiveness, power settling, excessive thrust and torque fluctuations, and vibration. As simple momentum theory is no longer valid for a rotor in VRS, modeling of rotor inflow in VRS continues to challenge researchers, especially for flight simulation applications. In this dissertation, a simplified inflow model, called the ring vortex model, is developed for a helicopter rotor operating in descent condition. By creating a series of vortex rings near the rotor disk, the ring vortex model addresses the strong flow interaction between the rotor wake and the surrounding airflow in descent flight. In addition, the total mass flow parameter in the existing inflow models is augmented to create a steady state transition between the helicopter and the windmill branches. With the ring vortex model, rotor inflow can now be adequately predicted over a wide range of descent rates. Validations of the ring vortex model for helicopter rotors are conducted extensively in axial and inclined descent. Effects from blade taper, blade twist, and rotor thrust are also investigated with further application of the finite-state inflow model. The ring vortex model is applied to a single main-rotor helicopter. The main effort is to establish VRS boundary based on heave stability criterion. In addition, two important phenomena observed in the descent flight tests are addressed in the dynamic simulation, including uncommanded drop in descent rate and loss of collective control effectiveness. The ring vortex model is further applied to a side-by-side rotor configuration. Lateral thrust asymmetry on the side-by-side rotor configuration can be reproduced through uneven distribution of vortex rings at the two rotors. Two important issues are investigated, including the impact of vortex rings on lateral thrust deficit and on lateral AFCS limit.

We develop a neuro-fuzzy network technique to extract TSK-type fuzzy rules from a given set of input-output data for classification problems. Fuzzy clusters are generated incrementally from the training data set, and similar clusters are merged dynamically together through input-similarity, output-similarity, and output-variance tests. The associated membership functions are defined with statistical means and deviations. Each cluster corresponds to a fuzzy IF-THEN rule, and the obtained rules can be further refined by a fuzzy neural network with a hybrid learning algorithm which combines a recursive SVD-based least squares estimator and the gradient descent method. The proposed technique has several advantages. The information about input and output data subspaces is considered simultaneously for cluster generation and merging. Membership functions match closely with and describe properly the real distribution of the training data points. Redundant clusters are combined and the sensitivity to the input order of training data is reduced. Besides, generation of the whole set of clusters from the scratch can be avoided when new training data are considered.

The selection and learning of kernel functions is a very important but rarely studied problem in the field of support vector learning. However, the kernel function of a support vector regression has great influence on its performance. The kernel function projects the dataset from the original data space into the feature space, and therefore the problems which can not be done in low dimensions could be done in a higher dimension through the transform of the kernel function. In this paper, there are two main contributions. Firstly, we introduce the gradient descent method to the learning of kernel functions. Using the gradient descent method, we can conduct learning rules of the parameters which indicate the shape and distribution of the kernel functions. Therefore, we can obtain better kernel functions by training their parameters with respect to the risk minimization principle. Secondly, In order to reduce the number of support vectors, we use the orthogonal least squares method. By choosing the representative support vectors, we may remove the less important support vectors in the support vector regression model. The experimental results have shown that our approach can derive better kernel functions than others and has better generalization ability. Also, the number of support vectors can be effectively reduced.

One of the most essential objectives in WSNs is to determine the spatial coordinates of a source or a sensor node having information. In this study, the problem of range measurement-based localization of a signal source or a sensor is revisited. The main challenge of the problem results from the non-convexity associated with range measurements calculated using the distances from the set of nodes with known positions to a xed sen- sor node. Such measurements corresponding to certain distances are non-convex in two and three dimensions. Attempts recently proposed in the literature to eliminate the non- convexity approach the problem as a non-convex geometric minimization problem, using techniques to handle the non-convexity. This study proposes a new fuzzy range-free sensor localization method. The method suggests using some notions of Euclidean geometry to convert the problem into a convex geometric problem. The convex equivalent problem is built using convex fuzzy sets, thus avoiding multiple stable local minima issues, then a gradient based localization algorithm is chosen to solve the problem. Next, the proposed algorithm is simulated considering various scenarios, including the number of available source nodes, fuzzi cation level, and area coverage. The results are compared with an algorithm having similar fuzzy logic settings. Also, the behaviour of both algorithms with noisy measurements are discussed. Finally, future extensions of the algorithm are suggested, along with some guidelines.

This paper purposes to answer some questions pertaining to perceptions of Metis identity (individual and collective, subjective and objective) as the Canadian public's conceptualizations of the Metis have been changed during the 80s and 90s by the works of Canadians historians and by popular media. These changes have been stimulated by the politics of Metis participation in: The Constitution Act, 1982; The First Ministers' Conferences [FM'Cs], 1983-1987; The Charlottetown Accord, 1992 Questions asked are (1) who are the modern-day Metis; (2) how do the Metis define themselves, conceptually and legally; (3) how does the Canadian public, in general, define the Metis? The results of the Lethbridge Area Metis Survey (Chapter Three) are valid for the local area but it is possible that they may be generalized. / vi, 103 leaves : ill. ; 28 cm.

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