The Pros and Cons of Compressive Sensing for Wideband Signal Acquisition: Noise Folding vs. Dynamic Range

Compressive sensing (CS) exploits the sparsity present in many signals to reduce the number of measurements needed for digital acquisition. With this reduction would come, in theory, commensurate reductions in the size, weight, power consumption, and/or monetary cost of both signal sensors and any associated communication links. This paper examines the use of CS in the design of a wideband radio receiver in a noisy environment. We formulate the problem statement for such a receiver and establish a reasonable set of requirements that a receiver should meet to be practically useful. We then evaluate the performance of a CS-based receiver in two ways: via a theoretical analysis of its expected performance, with a particular emphasis on noise and dynamic range, and via simulations that compare the CS receiver against the performance expected from a conventional implementation. On the one hand, we show that CS-based systems that aim to reduce the number of acquired measurements are somewhat sensitive to signal noise, exhibiting a 3dB SNR loss per octave of subsampling, which parallels the classic noise-folding phenomenon. On the other hand, we demonstrate that since they sample at a lower rate, CS-based systems can potentially attain a significantly larger dynamic range. Hence, we conclude that while a CS-based system has inherent limitations that do impose some restrictions on its potential applications, it also has attributes that make it highly desirable in a number of important practical settings

THE EFFECT OF LIQUID COMPRESSIBILITY AND DOMAIN VOLUME ON THE COLLAPSE OF CYLINDRICAL VAPOR CAVITIES

The dynamics of slender vapor cavities is studied experimentally and with a compressible multi-material Euler equation solver. For the computational study, the cavity was approximated as an infinitely long cylinder. Compressibility is shown to be a controlling factor in the dynamics of the cavity collapse, both as a means to limit the amount of fluid mass accelerated and as a source of radiated energy. As a result, cavities reach an invariant collapse time for fluid domains large enough that acoustic waves traveling outward from the cavity wall are unable to return before collapse. The dynamics of the collapse are studied using an inviscid compressible hydrocode and are compared to those given by the incompressible cylindrical analogue of the Rayleigh-Plesset equation. The incompressible solution is known to depend on the size of the domain due to a logarithmic dependence in the governing equation, predicting a monotonically-increasing collapse time with increasing fluid domain size. Thus, for sufficiently large fluid domains, the analytic incompressible solution greatly over-predicts the cavity collapse time observed in the compressible calculation. Using the results of this study, a compressibility-limited collapse time can be predicted for a cylindrical bubble using the incompressible model, providing a rational upper limit for the effective domain size often used in slender-body approximation models. In the experimental study, supercavitating projectiles with a mass of 55 g, and cavitator radii of 3 and 6 mm were fired vertically into a shallow hydroballistics tank at velocities between 194 and 434 m/s. Cavity morphology and dynamics are extracted from high-speed video footage with two image processing techniques. Resulting cavity radial flow histories are compared to a model adapted from Bergmann et al. (2009). The model uses the volume of the hydroballistics tank as the upper limit for the amount of fluid available for cavity expansion and collapse. It accurately predicts cavity radial dynamics where local three-dimensionality (e.g. surface seal and axial flow) does not dominate the flow. The resulting model is capable of predicting gross cavity behavior and collapse mode. For cavities where the collapse is primarily radial, the model accurately predicts the time and location of collapse. These predictions could facilitate estimates of cavity collapse loading on adjacent structures

IUNR Campus-Tag der Biodiversität : erste "Volkszählung der Biodiversität" auf dem Campus Grüental der ZHAW Wädenswil

Jagen, fangen, pflücken, bestimmen, auflisten – das war die Devise am IUNR Campus-Tag Biodiversität, der am 6. Juni 2019 erstmals stattfand. Und zwar alles, was auf dem Gelände des Campus Grüental der ZHAW in Wädenswil an Pflanzen und Tieren an diesem Tag zu finden war. Die rund 80 Teilnehmenden, je zur Hälfte UI-Studierende und IUNR-Mitarbeitende, hatten die Qual der Wahl zwischen 11 verschiedenen Artengruppen, bei denen sie mitmachen konnten

Ideal and Real Treatment Planning Processes for People With Serious Mental Illness in Public Mental Health Care

Treatment planning processes are a fundamental component of evidence-based practice in mental health for people with serious mental illness (SMI), who often present with complex concerns and require an interdisciplinary treatment team. It is unclear how well treatment planning practices in usual care settings for SMI adhere to best practices guidelines. In this study, we used qualitative methods to increase understanding of typical treatment planning practices. Twelve mental health providers completed a participatory dialogue focused on discussing perceptions of ideal and real treatment planning processes. Content analysis of the transcription from the dialogue was used to identify major themes and subthemes. Analysis revealed 6 primary themes with 23 subthemes. Providers described the ideal treatment planning process as dynamic and collaborative, including thorough assessment and inclusion of all stakeholders including the consumer, providers, and family members. Real treatment planning was described as directed by institutional and regulatory needs, resulting in treatment plans that were not personalized and not communicated to frontline staff or the consumer. These results indicate that providers have a strong understanding of evidence-based principles of treatment decision-making. However, actual treatment planning processes rarely live up to those principles. Providers identified several obstacles to enacting best practices. Although many obstacles were system-level, providers themselves also contributed to the gap between ideal and real treatment planning. Additional training and education may help to close this gap. Consumer self-advocacy is also important, given that providers often see themselves as lacking agency to make changes

Research Methods in Psychology (PSYC 362) Posters: Manipulated Arousal and the Threat-Focus Effect on Memory

Students taking Research Methods in Psychology are tasked with generating a novel research question, designing a study to answer that question, and analyzing and interpreting data within the context of their original hypotheses. These posters represent the culmination of this semester-long project

The Impact of DRGs on Social Workers in a University-Affiliated, Teaching Hospital System

The impact of DRGs on social workers in four social work departments located in one Northeast State was assessed by interviews with all social work staff and administrators. The impact of DRGs was determined to be substantial. Implications for social work education and practice are considered

Exascale Deep Learning for Climate Analytics

We extract pixel-level masks of extreme weather patterns using variants of Tiramisu and DeepLabv3+ neural networks. We describe improvements to the software frameworks, input pipeline, and the network training algorithms necessary to efficiently scale deep learning on the Piz Daint and Summit systems. The Tiramisu network scales to 5300 P100 GPUs with a sustained throughput of 21.0 PF/s and parallel efficiency of 79.0%. DeepLabv3+ scales up to 27360 V100 GPUs with a sustained throughput of 325.8 PF/s and a parallel efficiency of 90.7% in single precision. By taking advantage of the FP16 Tensor Cores, a half-precision version of the DeepLabv3+ network achieves a peak and sustained throughput of 1.13 EF/s and 999.0 PF/s respectively.Comment: 12 pages, 5 tables, 4, figures, Super Computing Conference November 11-16, 2018, Dallas, TX, US