With the rapid development of wireless communication technology, the demands for higher communication rates are increasing. Higher communication rate corresponds to higher DoF. Interference alignment, which is an emerging interference management technique, is able to substantially increase the DoF of wireless communication systems. This thesis mainly studies the delay-based interference alignment technique. The key problem lies in the design of the transmission scheme and the appropriate allocation of the propagation delay, so as to achieve the desired DoF of different wireless networks. In addition, through delay-based interference alignment, the achievability of extreme points of the DoF region of different wireless networks can be proved.

Many microwave (RF) circuit designs require passive distributed sub-components with prescribed scattering parameters. These sub-components have typically been realised by cascading building-block configurations (eg. transmission lines of specific lengths, bends in transmission lines, coupled lines, and so on) of standard shape, and then adjusting the dimensions of selected prescribed features of these building-blocks. The problem with this approach is that the resulting sub-component may take up more "real-estate" on the overall circuit board than can be tolerated, may require tolerances that are too tight and hence be more costly than product developers can allow, can lead to less-than-best performance because we select the building-blocks (that we think are needed) ahead of time, and so on. The research in this thesis contributes to the shape synthesis approach of physical microstrip circuit design. The shape synthesis process is usually contrasted to traditional design by recognizing that it does not merely adjust the dimensions of a set of prescribed geometrical features on pre-selected shapes, but allows the electromagnetic physics to tell us what the sub-component layout needs to be (and it can be unconventional) in order to obtain the required performance. Existing shape synthesis techniques are based on the discrete- or continuous-pixelation method. Each of these approaches, however, have disadvantages (eg. too many degrees of freedom required to achieve the geometrical resolution necessary; the need for arbitrary decisions to fix material properties) that have prevented shape synthesis from being accepted for widespread use in design practice. In this thesis we develop, implement and apply a completely new shape synthesis approach, called the subtractive approach, that overcomes many of the above-mentioned disadvantages of pixelation-based methods It reduces the number of variables (degrees of freedom) needed in spite of the fact that the "design space" is significantly broadened by this approach. The latter is confirmed by the fact that it produces physical circuit geometries that we would not have come up with using traditional design methods. Examples are provided of the application of the new subtractive shape synthesis method. This new method involves continuous variables directly related to the physical circuit geometry, and thus could be used with surrogate modelling, unlike some existing shape synthesis procedures.

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The traditional approach to imaging system design places the sole burden of image formation on optical components. In contrast, a computational imaging system relies on a combination of optics and post-processing to produce the final image and/or output measurement. Therefore, the joint-optimization (JO) of the optical and the post-processing degrees of freedom plays a critical role in the design of computational imaging systems. The JO framework also allows us to incorporate task-specific performance measures to optimize an imaging system for a specific task. In this dissertation, we consider the design of computational imaging systems within a JO framework for two separate tasks: object reconstruction and iris-recognition. The goal of these design studies is to optimize the imaging system to overcome the performance degradations introduced by under-sampled image measurements. Within the JO framework, we engineer the optical point spread function (PSF) of the imager, representing the optical degrees of freedom, in conjunction with the post-processing algorithm parameters to maximize the task performance. For the object reconstruction task, the optimized imaging system achieves a 50% improvement in resolution and nearly 20% lower reconstruction root-mean-square-error (RMSE ) as compared to the un-optimized imaging system. For the iris-recognition task, the optimized imaging system achieves a 33% improvement in false rejection ratio (FRR) for a fixed alarm ratio (FAR) relative to the conventional imaging system. The effect of the performance measures like resolution, RMSE, FRR, and FAR on the optimal design highlights the crucial role of task-specific design metrics in the JO framework. We introduce a fundamental measure of task-specific performance known as task-specific information (TSI), an information-theoretic measure that quantifies the information content of an image measurement relevant to a specific task. A variety of source-models are derived to illustrate the application of a TSI-based analysis to conventional and compressive imaging (CI) systems for various tasks such as target detection and classification. A TSI-based design and optimization framework is also developed and applied to the design of CI systems for the task of target detection, it yields a six-fold performance improvement over the conventional imaging system at low signal-to-noise ratios.

Standard statistical decision-making tools, such as inference, confidence intervals and forecasting, are contingent on the assumption that the statistical model used in the analysis is the true model. In linear mixed-effect models, ignoring model uncertainty results in an underestimation of the residual variance, contributing to hypothesis tests that demonstrate larger than nominal Type-I errors and confidence intervals with smaller than nominal coverage probabilities. A novel utilization of the generalized degrees of freedom developed by Zhang et al. (2012) is used to adjust the estimate of the residual variance for model uncertainty. Additionally, the general global linear approximation is extended to linear mixed-effect models to adjust the standard errors of the parameter estimates for model uncertainty. Both of these methods use a perturbation method for estimation, where random noise is added to the response variable and, conditional on the observed responses, the corresponding estimate is calculated. A simulation study demonstrates that when the proposed methodologies are utilized, both the variance and standard errors are inflated for model uncertainty. However, when a data-driven strategy is employed, the proposed methodologies show limited usefulness. These methods are evaluated with a trial assessing the performance of cervical traction in the treatment of cervical radiculopathy.

Application of haptic devices expanded to fields like virtual manufacturing, virtual assembly or medical simulations. Advances in development of haptic devices have resulted in a wide distribution of assymetric 6/3-DOF haptic devices. However, current haptic rendering algorithms work correctly only for symmetric devices. This thesis analyzes 3-DOF and 6-DOF haptic rendering algorithms and proposes an algorithm for 6/3-DOF haptic rendering involving pseudo-haptics. The 6/3-DOF haptic rendering algorithm is implemented based on the previous analysis and tested in a user study.

Neste trabalho aborda-se o desenvolvimento de um elemento finito de membrana com graus de liberdade rotacionais e sua implementação a um sistema computacional em elementos finitos. O trabalho é baseado na formulação livre de BERGAN & NYGARD (1984) que produz um elemento simples e de bom desempenho. Aspectos fundamentais da formulação livre, do desenvolvimento do elemento e sua implementação ao sistema são apresentados. Resultados obtidos em alguns exemplos comprovam a eficiência do procedimento. / In this work the formulation of a membrane finite element with rotational degrees of freedom and its implementation to a finite element computational system is presented. The development is based on the free formulation of BERGAN & NYGARD (1984) that produce a simple and efficient element. Fundamental aspects of the free formulation, of the element evaluation and its implementation to the system are shown. The results obtained in some examples indicate the accuracy of the procedure.

Data arising from Cluster Randomized Trials (CRTs) and longitudinal studies are correlated and generalized estimating equations (GEE) are a popular analysis method for correlated data. Previous research has shown that analyses using GEE could result in liberal inference due to the use of the empirical sandwich covariance matrix estimator, which can yield negatively biased standard error estimates when the number of clusters or subjects is not large. Many techniques have been presented to correct this negative bias; However, use of these corrections can still result in biased standard error estimates and thus test sizes that are not consistently at their nominal level. Therefore, there is a need for an improved correction such that nominal type I error rates will consistently result. First, GEEs are becoming a popular choice for the analysis of data arising from CRTs. We study the use of recently developed corrections for empirical standard error estimation and the use of a combination of two popular corrections. In an extensive simulation study, we find that nominal type I error rates can be consistently attained when using an average of two popular corrections developed by Mancl and DeRouen (2001, Biometrics 57, 126-134) and Kauermann and Carroll (2001, Journal of the American Statistical Association 96, 1387-1396) (AVG MD KC). Use of this new correction was found to notably outperform the use of previously recommended corrections. Second, data arising from longitudinal studies are also commonly analyzed with GEE. We conduct a simulation study, finding two methods to attain nominal type I error rates more consistently than other methods in a variety of settings: First, a recently proposed method by Westgate and Burchett (2016, Statistics in Medicine 35, 3733-3744) that specifies both a covariance estimator and degrees of freedom, and second, AVG MD KC with degrees of freedom equaling the number of subjects minus the number of parameters in the marginal model. Finally, stepped wedge trials are an increasingly popular alternative to traditional parallel cluster randomized trials. Such trials often utilize a small number of clusters and numerous time intervals, and these components must be considered when choosing an analysis method. A generalized linear mixed model containing a random intercept and fixed time and intervention covariates is the most common analysis approach. However, the sole use of a random intercept applies assumptions that will be violated in practice. We show, using an extensive simulation study based on a motivating example and a more general design, alternative analysis methods are preferable for maintaining the validity of inference in small-sample stepped wedge trials with binary outcomes. First, we show the use of generalized estimating equations, with an appropriate bias correction and a degrees of freedom adjustment dependent on the study setting type, will result in nominal type I error rates. Second, we show the use of a cluster-level summary linear mixed model can also achieve nominal type I error rates for equal cluster size settings.

Although tremor is the most common movement disorder, there are few non-invasive treatment options. One of the obstacles to creating effective tremor suppression devices is our lack of understanding regarding where tremor originates (which muscles), how it propagates through the limb (to which degrees of freedom, DOF), and where it manifests most severely (which DOF). To investigate these questions, we created a simple, linear time-invariant model to simulate tremor, with tremorogenic muscle activity input (in the 15 major superficial muscles from the shoulder to the wrist) and joint displacement output (in the 7 major upper limb DOF). The model included excitation-contraction dynamics, musculoskeletal geometry (muscle moment arms) and the mechanical impedance (inertia, damping, and stiffness) of the limb. From our simulation results, we determined four principles of tremor propagation. First, the distribution of tremor depends strongly on musculoskeletal dynamics. Second, the spreading of tremor is due to inertial coupling (primarily) and musculoskeletal geometry (secondarily). Third, tremor spreads narrowly in the sense that most of the tremor caused by a muscle occurs in a small number of DOF. Lastly, assuming uniform distribution of tremorogenic activity among upper-limb muscles, tremor increases proximal-distally, and the contribution from muscles increases proximal-distally.

<p>This master thesis studies how much the cycle time, i.e. the time it takes for an industrial robot to perform a given task, can be reduced if an extra degree of freedom (DOF) is added to the robot system. The extra DOF consists of a linear track, which is supposed to be used in an optimal way. The problem has been studied using simulations in the robot simulation tool RobotStudio. </p><p>To be able to run an optimization in Matlab, with the RobotStudio simulation cycle time as the object function, communication between Matlab and RobotStudio has been set up with an interface written in Visual Basic. An algorithm has been developed to solve the problem. Two different optimization methods have been examined and compared. </p><p>The resulting algorithm has been applied to test cases. The results show that the cycle time in several cases can be reduced by 20-30 percent, if the movements along the track are optimized with the suggested method.</p>