Class of 2014 Abstract / Specific Aims: To identify the factors that affects the potency of pharmacists’ interventions. Methods: Literature search was based on keywords and Mesh terms in eight different databases. The inclusion criteria were evidence of pharmacist involvement in direct patient care, patient-related therapeutic outcomes, studies done in the United States, randomized controlled trials, studies with reported number of subjects in the intervention and control group and reported means and standard deviations of therapeutic outcomes. For the study selection and data extraction, two students independently reviewed each study and met to resolve any discrepancies. In addition, each study was assigned a potency score using the potency tool. Data extraction included: pharmacists’ interventions (technical, behavioral, educational, and affective), patient characteristics, and therapeutic outcomes. The standardized mean difference (SMD) was calculated; studies with SMD ≥ -0.3 formed the low impact group (controls) and studies with SMD  -0.8 formed the high impact group (cases). Main Results: The included randomized control trials (N=11) were conducted in a variety of settings from ambulatory clinics to hospital. The high impact group was favored in the educational category (ES=0.88, p=0.18) while the low impact group was favored in the behavioral category (ES=-0.19, p=0.81). In general, there was a difference between the high impact and low impact (ES=0.82, p=0.37) groups with the high impact group being favored. Conclusion: There is a difference between the low impact and high impact groups, but it is unclear which pharmacist interventions have a significant impact on therapeutic outcomes.

NR 20140805

The implementation of a general-purpose tetrahedral mesh phantom geometry library for the Monte Carlo radiation transport code EGSnrc is described. Recently, tetrahedral mesh geometries have been proposed as standard reference phantoms to advance the state of the art over rectilinear voxel phantoms. Prior to this work, EGSnrc already supported voxelized geometries, but not tetrahedral meshes. Other major radiation transport codes such as MCNP6, Geant4, and PHITS, are also capable of simulating the interaction of ionizing radiation with tetrahedral mesh phantoms. Tetrahedral mesh phantoms have a number of advantages over voxel phantoms including improved modelling fidelity and locally varying element resolution. In addition, CAD geometries can be converted into meshes, which can then be directly used in simulations. In this work, an EGSnrc tetrahedral mesh geometry library called EGS_Mesh is implemented. The implementation uses fast computational geometry algorithms from the literature and is accelerated using an octree spatial partitioning scheme. For a preliminary verification, results obtained using EGS_Mesh are compared to classical EGSnrc geometries and theoretical results (including a Fano test) and found to match within 0.1%. To demonstrate the capability of EGS_Mesh to simulate transport in complex mesh phantoms from the literature, results using the ICRP 145 reference human phantoms are compared to published results obtained using Geant4. The comparison has found agreement mostly within 5% of the Geant4 results, but with some differences up to 10%.

When choosing what IoT protocol to use today, there are lots of choices. If a mesh type network is chosen, Bluetooth mesh might be a possible candidate. Bluetooth mesh without correctly configured parameters can however suffer from congestion and packet loss if the network is very dense or consists of many nodes. This can be counteracted by choosing which nodes should be relays more carefully, as well as setting the re-transmission count and Time To Live (TTL) based on the current topology of the network. If the nodes in the network change position or are added/removed regularly, it is impossible to set the parameters optimal for all the possible network layouts. This is where a dynamic configuration comes in handy. In this master thesis a custom control model was created which implemented the K2 Pruning algorithm for relay selection, custom heartbeats for a dynamic TTL on each node, and a static re-transmission count for message originators and relays. A possible way to implement a dynamic re-transmission count is also discussed, as well as how the dynamic configuration could be autonomous without the need of physical interaction when reconfiguring the network. The implemented dynamic configuration tested on a physical system of 33 nodes was partly unsuccessful, but still provided improved Packet Delivery Ratio (PDR), reduced message delay, and useful knowledge for future implementations of a dynamic configuration. The K2 Pruning algorithm failed in choosing relays correct and quickly due to congestion during the neighbor information exchange needed to run the algorithm. Therefore, a different relay selection algorithm is suggested for future models or the refrain of acknowledged messages during the neighbor information exchange phase.

No description available.

The goal of this thesis is to realize some critical techniques required in the cognitive radio mesh network. Cognitive radio (CR) is a new technology introduced to improve the frequency efficiency of current wireless systems. A mesh network, which leverages the advantages of an infrastructure network and a pure ad-hoc network, is a network topology highly suitable for the CR networks. CR users need to adapt to their ambient wireless environment and automatically select their own effective transceiver mode. The thesis focuses on the realization of a physical layer protocol, dynamic frequency-selection algorithm, mesh network signalling method, and transmit-power control algorithm in CR mesh networks. A new dynamic frequency selection algorithm is introduced in CR network, including estimation of the primary users' traffic statistics as well as adaptation to the local background noise interference. Through continuous observation, analysis, and adaptation to the time-varying environment, CR is able to select the candidate frequency bands to satisfy a user's rate and power requirements without causing collision to the primary users in those bands. As a generic model, a Gaussian mixture model, is selected for characterizing the statistics of the traffic environment. The transmit-power control in the CR mesh network is based on an iterative water-filling algorithm, rooted in information theory. The iterative water-filling algorithm is modified to suit the requirement of CR mesh networks. It works well for setting a suitable transmit-power level, sub-channels, and sub-carriers for the nodes in a CR mesh network. To support current systems, experiments are presented on the wireless mesh network, which are based on the orthogonal frequency-division multiple-access (OFDMA) mode of the High-speed Unlicensed Wireless Metropolitan Area Network (Wireless HUMAN). In the mesh network, the multiple access control(MAC) layer signals including the distributed network configuration, network entry, and network scheduling signals, are introduced. They are transmitted through a control channel in a cooperative mechanism. The physical layer(PHY) of OFDMA is also discussed in the thesis. / Thesis / Master of Applied Science (MASc)

Triangle-mesh modeling, as one of the approaches for representing images based on nonuniform sampling, has become quite popular and beneficial in many applications. In this thesis, image representation using triangle-mesh models and its application in image scaling are studied. Consequently, two new methods, namely, the SEMMG and MIS methods are proposed, where each solves a different problem. In particular, the SEMMG method is proposed to address the problem of image representation by producing effective mesh models that are used for representing grayscale images, by minimizing squared error. The MIS method is proposed to address the image-scaling problem for grayscale images that are approximately piecewise-smooth, using triangle-mesh models. The SEMMG method, which is proposed for addressing the mesh-generation problem, is developed based on an earlier work, which uses a greedy-point-insertion (GPI) approach to generate a mesh model with explicit representation of discontinuities (ERD). After in-depth analyses of two existing methods for generating the ERD models, several weaknesses are identified and specifically addressed to improve the quality of the generated models, leading to the proposal of the SEMMG method. The performance of the SEMMG method is then evaluated by comparing the quality of the meshes it produces with those obtained by eight other competing methods, namely, the error-diffusion (ED) method of Yang, the modified Garland-Heckbert (MGH) method, the ERDED and ERDGPI methods of Tu and Adams, the Garcia-Vintimilla-Sappa (GVS) method, the hybrid wavelet triangulation (HWT) method of Phichet, the binary space partition (BSP) method of Sarkis, and the adaptive triangular meshes (ATM) method of Liu. For this evaluation, the error between the original and reconstructed images, obtained from each method under comparison, is measured in terms of the PSNR. Moreover, in the case of the competing methods whose implementations are available, the subjective quality is compared in addition to the PSNR. Evaluation results show that the reconstructed images obtained from the SEMMG method are better than those obtained by the competing methods in terms of both PSNR and subjective quality. More specifically, in the case of the methods with implementations, the results collected from 350 test cases show that the SEMMG method outperforms the ED, MGH, ERDED, and ERDGPI schemes in approximately 100%, 89%, 99%, and 85% of cases, respectively. Moreover, in the case of the methods without implementations, we show that the PSNR of the reconstructed images produced by the SEMMG method are on average 3.85, 0.75, 2, and 1.10 dB higher than those obtained by the GVS, HWT, BSP, and ATM methods, respectively. Furthermore, for a given PSNR, the SEMMG method is shown to produce much smaller meshes compared to those obtained by the GVS and BSP methods, with approximately 65% to 80% fewer vertices and 10% to 60% fewer triangles, respectively. Therefore, the SEMMG method is shown to be capable of producing triangular meshes of higher quality and smaller sizes (i.e., number of vertices or triangles) which can be effectively used for image representation. Besides the superior image approximations achieved with the SEMMG method, this work also makes contributions by addressing the problem of image scaling. For this purpose, the application of triangle-mesh mesh models in image scaling is studied. Some of the mesh-based image-scaling approaches proposed to date employ mesh models that are associated with an approximating function that is continuous everywhere, which inevitably yields edge blurring in the process of image scaling. Moreover, other mesh-based image-scaling approaches that employ approximating functions with discontinuities are often based on mesh simplification where the method starts with an extremely large initial mesh, leading to a very slow mesh generation with high memory cost. In this thesis, however, we propose a new mesh-based image-scaling (MIS) method which firstly employs an approximating function with selected discontinuities to better maintain the sharpness at the edges. Secondly, unlike most of the other discontinuity-preserving mesh-based methods, the proposed MIS method is not based on mesh simplification. Instead, our MIS method employs a mesh-refinement scheme, where it starts from a very simple mesh and iteratively refines the mesh to reach a desirable size. For developing the MIS method, the performance of our SEMMG method, which is proposed for image representation, is examined in the application of image scaling. Although the SEMMG method is not designed for solving the problem of image scaling, examining its performance in this application helps to better understand potential shortcomings of using a mesh generator in image scaling. Through this examination, several shortcomings are found and different techniques are devised to address them. By applying these techniques, a new effective mesh-generation method called MISMG is developed that can be used for image scaling. The MISMG method is then combined with a scaling transformation and a subdivision-based model-rasterization algorithm, yielding the proposed MIS method for scaling grayscale images that are approximately piecewise-smooth. The performance of our MIS method is then evaluated by comparing the quality of the scaled images it produces with those obtained from five well-known raster-based methods, namely, bilinear interpolation, bicubic interpolation of Keys, the directional cubic convolution interpolation (DCCI) method of Zhou et al., the new edge-directed image interpolation (NEDI) method of Li and Orchard, and the recent method of super-resolution using convolutional neural networks (SRCNN) by Dong et al.. Since our main goal is to produce scaled images of higher subjective quality with the least amount of edge blurring, the quality of the scaled images are first compared through a subjective evaluation followed by some objective evaluations. The results of the subjective evaluation show that the proposed MIS method was ranked best overall in almost 67\% of the cases, with the best average rank of 2 out of 6, among 380 collected rankings with 20 images and 19 participants. Moreover, visual inspections on the scaled images obtained with different methods show that the proposed MIS method produces scaled images of better quality with more accurate and sharper edges. Furthermore, in the case of the mesh-based image-scaling methods, where no implementation is available, the MIS method is conceptually compared, using theoretical analysis, to two mesh-based methods, namely, the subdivision-based image-representation (SBIR) method of Liao et al. and the curvilinear feature driven image-representation (CFDIR) method of Zhou et al.. / Graduate

In this thesis our primary interest is in developing adaptive solution methods for parabolic and elliptic partial differential equations. The convection-diffusion equation is used as a representative test problem. Investigations are made into adaptive temporal solvers implementing only a few changes to existing software. This includes a comparison of commercial code against some more academic releases. A novel way to select step sizes for an adaptive BDF2 code is introduced. A chapter is included introducing some functional analysis that is required to understand aspects of the finite element method and error estimation. Two error estimators are derived and proofs of their error bounds are covered. A new finite element package is written, implementing a rather interesting error estimator in one dimension to drive a rather standard refinement/coarsening type of adaptivity. This is compared to a commercially available partial differential equation solver and an investigation into the properties of the two inspires the development of a new method designed to very quickly and directly equidistribute the errors between elements. This new method is not really a refinement technique but doesn't quite fit the traditional description of a moving mesh either. We show that this method is far more effective at equidistribution of errors than a simple moving mesh method and the original simple adaptive method. A simple extension of the new method is proposed that would be a mesh reconstruction method. Finally the new code is extended to solve steady-state problems in two dimensions. The mesh refinement method from one dimension does not offer a simple extension, so the error estimator is used to supply an impression of the local topology of the error on each element. This in turn allows us to develop a new anisotropic refinement algorithm, which is more in tune with the nature of the error on the parent element. Whilst the benefits observed in one dimension are not directly transferred into the two-dimensional case, the obtained meshes seem to better capture the topology of the solution.

In the field of Computational Fluid Dynamics, several types of mesh adaptation strategies are used to enhance a mesh’s quality, thereby improving simulation speed and accuracy. Mesh smoothing (r-refinement) is a simple and effective technique, where nodes are repositioned to increase or decrease local mesh resolution. Mesh partitioning divides a mesh into sections, for use on distributed-memory parallel machines. As a more abstract form of modeling, graph theory can be used to simulate many real-world problems, and has applications in the fields of computer science, sociology, engineering and transportation, to name a few. One of the more important graph analysis tasks involves moving through the graph to evaluate and calculate nodal connectivity. The basic structures of meshes and graphs are the same, as both rely heavily on connectivity information, representing the relationships between constituent nodes and edges. This research examines the parallelization of these algorithms using commodity graphics hardware; a low-cost tool readily available to the computing community. Not only does this research look at the benefits of the fine-grained parallelism of an individual graphics processor, but the use of Message Passing Interface (MPI) on large-scale GPU-based supercomputers is also studied.

Yes / The development of the patchwise Partial Di erential Equation (PDE) framework a few years a- go has paved the way for the PDE method to be used in mesh signal processing. In this paper we, for the rst time, extend the use of the PDE method to progressive mesh compression and mesh denoising. We, meanwhile, upgrade the existing patchwise PDE method in patch merging, mesh partitioning, and boundary extraction to accommodate mesh signal processing. In our new method an arbitrary mesh model is partitioned into patches, each of which can be represented by a small set of coe cients of its PDE spectral solution. Since low- frequency components contribute more to the recon- structed mesh than high-frequency ones, we can achieve progressive mesh compression and mesh denoising by manipulating the frequency terms of the PDE solution. Experimental results demonstrate the feasibility of our method in both progressive mesh compression and mesh denoising.