The traditional mobile radio channel has always suffered from the detrimental effects of multipath fading. The use of multiple antennae at both ends of the wireless channel has proven to be very effective in combatting fading and enhancing the channel's spectral efficiency. To exploit the benefits offered by Multi-Input Multi-Output (MIMO) systems, both the transmitter and the receiver have to be optimally designed. In this thesis, we are concerned with the problem of receiver design for MIMO systems in a spatial multiplexing scheme. The MIMO detection problem is an NP-hard combinatorial optimization problem. Solving this problem to optimality requires an exponential search over the space of all possible transmitted symbols in order to find the closest point in a Euclidean sense to the received symbols; a procedure that is infeasible for large systems. We introduce a new heuristic algorithm for the detection of a MIMO wireless system based on the Ant Colony Optimization (ACO) metaheuristic. The new algorithm, AntMIMO, has a simple architecture and achieves near maximum likelihood performance in polynomial time.

Neurovascular models have played an important role in understanding neuronal function or medical conditions. In the past few decades, only small volumes of neurovascular data have been available. However, huge data sets are becoming available with high throughput instruments like the Knife-Edge Scanning Microscope (KESM). Therefore, fast and robust tracing methods become necessary for tracing such large data sets. However, most tracing methods are not effective in handling complex structures such as branches. Some methods can solve this issue, but they are not computationally efficient (i.e., slow). Motivated by the issue of speed and robustness, I introduce an effective and efficient fiber tracing algorithm for 2D and 3D data. In 2D tracing, I have implemented a Moving Window (MW) method which leads to a mathematical simplification and noise robustness in determining the trace direction. Moreover, it provides enhanced handling of branch points. During tracing, a Cubic Tangential Trace Spline (CTTS) is used as an accurate and fast nonlinear interpolation approach. For 3D tracing, I have designed a method based on local maximum intensity projection (MIP). MIP can utilize any existing 2D tracing algorithms for use in 3D tracing. It can also significantly reduce the search space. However, most neurovascular data are too complex to directly use MIP on a large scale. Therefore, we use MIP within a limited cube to get unambiguous projections, and repeat the MIP-based approach over the entire data set. For processing large amounts of data, we have to automate the tracing algorithms. Since the automated algorithms may not be 100 percent correct, validation is needed. I validated my approach by comparing the traced results to human labeled ground truth showing that the result of my approach is very similar to the ground truth. However, this validation is limited to small-scale real-world data due to the limitation of the manual labeling. Therefore, for large-scale data, I validated my approach using a model-based generator. The result suggests that my approach can also be used for large-scale real-world data. The main contributions of this research are as follows. My 2D tracing algorithm is fast enough to analyze, with linear processing time based on fiber length, large volumes of biological data and is good at handling branches. The new local MIP approach for 3D tracing provides significant performance improvement and it allows the reuse of any existing 2D tracing methods. The model-based generator enables tracing algorithms to be validated for large-scale real-world data. My approach is widely applicable for rapid and accurate tracing of large amounts of biomedical data.

In this thesis, we study two optimization problems which have a lot of important applications in diverse domains: Line Cover Problem (LCP) in Computational Geometry and Maximum Genus Embedding (MGE) in Topological Graph Theory. We study LCP whose decision version is known NP-Complete from the perspective of Parameterized Complexity, as well as classical techniques in Algorithm Design. In particular, we provide an exact algorithm in time O(n^3 2n) based on Dynamic Programming and initiate a dual problem of LCP in terms of Linear Programming Duality. We study the dual problem by applying approximation and kernelization, obtaining an approximation algorithm with ratio k - 1 and a kernel of size O(k^4). Then we survey related geometric properties on LCP. Finally we propose a Parameterized Algorithm to solve LCP with running time O*(k^k/1:35^k). We explore connections between the maximum genus of a graph and its cycle space consisting of fundamental cycles only. We revisit a known incorrect approach of finding a maximum genus embedding via computing a maximum pairing of intersected fundamental cycles with respect to an arbitrary spanning tree. We investigate the reason it failed and conclude it confused the concept of deficiency. Also, we characterize the upper-embeddablity of a graph in terms of maximum pairings of intersected fundamental cycles, i.e. a graph is upper-embeddable if and only if the number of maximum pairings of intersected fundamental cycles for any spanning tree is the same. Finally, we present a lower and an upper bound of the maximum number of vertex-disjoint cycles in a general graph, beta(G) - 2gammaM(G) and beta(G) - gammaM(G), only depending on maximum genus and cycle rank.

First, we study a Poisson model a polluted random screen. In this model, the defects on random screen are assumed Poisson-distribution and overlapped. The transmittance effects of overlapping defects are multiplicative. We can compute the autocorrelation function of the screen is obtained by defects' density, radius, and transmittance. Using the autocorrelation function, we then restore the telescope astronomy images. These image signals are generally degraded by their propagation through the random scattering in atmosphere. To restore the images, we estimate the three key parameters by three methods. They are expectation- maximization (EM) method and two Maximum-Entropy (ME) methods according to two different definitions. The restoration are successful and demonstrated in this thesis.

Reproduction de : Thèse de doctorat : Programmation et systèmes : Toulouse, INPT : 2005. / Titre provenant de l'écran-titre. Bibliogr. 38 réf.

Stretching exercises are commonly used as an integral part of a pre-exercise warm-up training sessions despite even early laboratory studies having demonstrated that some degree of mechanical weakness takes place following the stretching of muscle tissue. This study compared the effects of four treatments (n = 12 each) [10 minutes of quiet sitting, without stretching (NS); two minutes warm up on an arm ergometer at 25 watts resistance (WU); 10 second-hold static stretching (each) of the shoulder, chest and arm muscle groups (ST10); and two sets of 20 second-hold static stretching (each) of the shoulder, chest and upper-arm muscle groups (ST20)] on a 1-RM bench press in 48 subjects who were matched for their pre-test 1-RM bench press values. The mean 1-RM bench press values following ST10 (45.0 ± 9.9 kg) and WU (48.9 ± 10.5 kg) treatments were significantly (p ? 0.05) higher at the post-test than at the pre-test 1-RM (43.9 ± 10.1 kg and 43.9 ± 10. kg, respectively). The mean 1-RM values following the ST20 treatment was significantly lower (41.9 ± 10.0 kg) than at pre-test (43.9 ± 10.1 kg). However, multiple comparisons and Analysis of Variance (ANOVA) statistical procedures demonstrated that there was no significant difference from pre- to post-test between the four groups. These findings suggest that the use of stretching activities prior to events requiring maximal force production may not be obligatory or may even be contraindicated since the effects of stretching are then to decrease the amount of force that can be produced via the natural elastic components of the muscle and tendons and via the stretch reflex.

Abstract Stretching exercises are commonly used as an integral part of a pre-exercise warm-up training sessions despite even early laboratory studies having demonstrated that some degree of mechanical weakness takes place following the stretching of muscle tissue. This study compared the effects of four treatments (n = 12 each) [10 minutes of quiet sitting, without stretching (NS); two minutes warm up on an arm ergometer at 25 watts resistance (WU); 10 second-hold static stretching (each) of the shoulder, chest and arm muscle groups (ST10); and two sets of 20 second-hold static stretching (each) of the shoulder, chest and upper-arm muscle groups (ST20)] on a 1-RM bench press in 48 subjects who were matched for their pre-test 1-RM bench press values. The mean 1-RM bench press values following ST10 (45.0 ± 9.9 kg) and WU (48.9 ± 10.5 kg) treatments were significantly (p ? 0.05) higher at the post-test than at the pre-test 1-RM (43.9 ± 10.1 kg and 43.9 ± 10. kg, respectively). The mean 1-RM values following the ST20 treatment was significantly lower (41.9 ± 10.0 kg) than at pre-test (43.9 ± 10.1 kg). However, multiple comparisons and Analysis of Variance (ANOVA) statistical procedures demonstrated that there was no significant difference from pre- to post-test between the four groups. These findings suggest that the use of stretching activities prior to events requiring maximal force production may not be obligatory or may even be contraindicated since the effects of stretching are then to decrease the amount of force that can be produced via the natural elastic components of the muscle and tendons and via the stretch reflex.

Rigid-body registration is an important research area with major applications in computer-assisted and image-guided surgery. In these surgeries, often the relationship between the preoperative and intraoperative images taken from a patient must be established. This relationship is computed through a registration process, which finds a set of transformation parameters that maps some point fiducials measured on a patient anatomy to a preoperative model. Due to point measurement error caused by medical measurement instruments, the estimated registration parameters are imperfect and this reduces the accuracy of the performed registrations. Medical measurement instruments often perturb the collected points from the patient anatomy by heterogeneous noise. If the noise characteristics are known, they can be incorporated in the registration algorithm in order to more reliably and accurately estimate the registration parameters and their variances. Current techniques employed in rigid-body registration are primarily based on the well-known Iterative Closest Points (ICP) algorithm. Such techniques are susceptible to the existence of noise in the data sets, and are also very sensitive to the initial alignment errors. Also, the literature offers no analytical solution on how to estimate the accuracy of the performed registrations in the presence of heterogenous noise. In an effort to alleviate these problems, we propose and validate various novel registration techniques based on the Unscented Kalman Filter (UKF) algorithm. This filter is generally employed for analyzing nonlinear systems corrupted by additive heterogenous Gaussian noise. First, we propose a new registration algorithm to fit two data sets in the presence of arbitrary Gaussian noise, when the corresponding points between the two data sets are assumed to be known. Next, we extend this algorithm to perform surface-based registration, where point correspondences are not available, but the data sets are roughly aligned. A solution to multi-body point and surface-based registration problem is then proposed based on the UKF algorithm. The outputs of the proposed UKF registration algorithms are then utilized to estimate the accuracy of the performed registration. For the first time, novel derivations are presented that can estimate the distribution of registration error at a target in the presence of an arbitrary Gaussian noise. / Thesis (Ph.D, Electrical & Computer Engineering) -- Queen's University, 2008-09-28 07:25:38.229

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Denna uppsats presenterar en undersökning av Vårdförbundets medlemmars inställning till nätjournal. Syftet med denna uppsats är att undersöka relationen mellan medlemmarnas inställning till nätjournal som reform och hur medlemmarna tror att nätjournal kommer påverka patienten samt deras eget arbete. En modell, som tagits fram genom explorativ och konfirmativ faktoranalys, presenterar relationen mellan medlemmarnas inställning till nätjournal som reform och hur medlemmarna tror att nätjournal kommer påverka patienten samt deras eget arbete i en strukturell ekvationsmodell. Undersökningen presenterar relationen utifrån medlemmarnas länstillhörighet. Länen är grupperade efter andel som ställer sig negativa till nätjournal som reform och fyra grupperingar kan urskiljas i en klusteranalys. Resultatet från undersökningen visar att det finns ett samband mellan inställning till nätjournal som reform och hur medlemmarna tror att nätjournal kommer påverka patienten samt deras eget arbete. Starkast relation till inställning till nätjournal som reform, i samtliga grupper, har frågor som berör patienten och hur denna påverkas av nätjournal. Skillnaderna mellan länsgrupperingarna kan urskiljas i fem enskilda frågor; ”Ditt sätt att skriva i journalen förändras av Journal på nätet?”, ”Patienter tar skada av den information de får via sin journalåtkomst?”, ”Obehöriga kommer att kunna ta del av patientuppgifter genom Journal på nätet?”, ”Journal på nätet ger en mer informerad patient?” och ”Patienters följsamhet till behandling ökar med tillgången till Journal på nätet?”.