Graphics Processor Unit Based Parallelization of Optimized Baseline Wander Filtering Algorithms for Long-term Electrocardiography

Long-term electrocardiogram (ECG) often suffers from relevant noise. Baseline wander in particular is pronounced in ECG recordings using dry or esophageal electrodes, which are dedicated for prolonged registration. While analog high-pass filters introduce phase distortions, reliable offline filtering of the baseline wander implies a computational burden that has to be put in relation to the increase in signal-to-baseline ratio (SBR). Here we present a graphics processor unit (GPU) based parallelization method to speed up offline baseline wander filter algorithms, namely the wavelet, finite, and infinite impulse response, moving mean, and moving median filter. Individual filter parameters were optimized with respect to the SBR increase based on ECGs from the Physionet database superimposed to auto-regressive modeled, real baseline wander. A Monte-Carlo simulation showed that for low input SBR the moving median filter outperforms any other method but negatively affects ECG wave detection. In contrast, the infinite impulse response filter is preferred in case of high input SBR. However, the parallelized wavelet filter is processed 500 and 4 times faster than these two algorithms on the GPU, respectively, and offers superior baseline wander suppression in low SBR situations. Using a signal segment of 64 mega samples that is filtered as entire unit, wavelet filtering of a 7-day high-resolution ECG is computed within less than 3 seconds. Taking the high filtering speed into account, the GPU wavelet filter is the most efficient method to remove baseline wander present in long-term ECGs, with which computational burden can be strongly reduced.

Taking Root in the Silicon Forest: High-technology Firms as Surrogate Universities in Portland, Oregon

Most case studies of successful high-technology industry regions highlight the role of research universities in fostering regional economic development. The Portland, Oregon, region managed to root a thriving high-tech industry in the absence of this critical factor. In this article, I present a case study of the evolution of Portland's high-tech industry and propose that high-tech firms can act as surrogate universities that attract and develop labor, create knowledge, and function as incubators for startups. I conclude that planners working to develop high-tech industries in regions without major research universities should attract R&D-intensive firms, maintain information on key busineses and entrepreneurial ventures, support an innovation milieu, and set realistic goals.

Liulin silicon semiconductor spectrometers as cosmic ray monitors at the high mountain observatories Jungfraujoch and Lomnický stit

Currently, most cosmic ray data are obtained by detectors on satellites, aircraft, high-altitude balloons and ground (neutron monitors). In our work, we examined whether Liulin semiconductor spectrometers (simple silicon planar diode detectors with spectrometric properties) located at high mountain observatories could contribute new information to the monitoring of cosmic rays by analyzing data from selected solar events between 2005 and 2013. The decision thresholds and detection limits of these detectors placed at Jungfraujoch (Switzerland; 3475 m a.s.l.; vertical cut-off rigidity 4.5 GV) and Lomnicky stıt (Slovakia; 2633 m a.s.l.; vertical cut-off rigidity 3.84 GV) highmountain observatories were determined. The data showed that only the strongest variations of the cosmic ray flux in this period were detectable. The main limitation in the performance of these detectors is their small sensitive volume and low sensitivity of the PIN photodiode to neutrons.