Institution
Vienna University of Technology
Education•Vienna, Austria•
About: Vienna University of Technology is a education organization based out in Vienna, Austria. It is known for research contribution in the topics: Laser & Context (language use). The organization has 16723 authors who have published 49341 publications receiving 1302168 citations.
Papers published on a yearly basis
Papers
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TL;DR: This paper estimates the LSF from a large set of measurements collected in the DRIVEWAY'09 measurement campaign, which focuses on scenarios for intelligent transportation systems (ITSs) and shows that the distribution of these channel parameters follows a bimodal Gaussian mixture distribution.
Abstract: Vehicular communication channels are characterized by a nonstationary time-frequency-selective fading process due to rapid changes in the environment. The nonstationary fading process can be characterized by assuming local stationarity for a region with finite extent in time and frequency. For this finite region, the wide-sense stationarity and uncorrelated scattering assumption approximately holds, and we are able to calculate a time-frequency-dependent local scattering function (LSF). In this paper, we estimate the LSF from a large set of measurements collected in the DRIVEWAY'09 measurement campaign, which focuses on scenarios for intelligent transportation systems (ITSs). We then obtain the time-frequency-varying power delay profile (PDP) and the time-frequency-varying Doppler power spectral density (DSD) from the LSF. Based on the PDP and the DSD, we analyze the time-frequency-varying root-mean-square (RMS) delay spread and the RMS Doppler spread. We show that the distribution of these channel parameters follows a bimodal Gaussian mixture distribution. High RMS delay spread values are observed in situations with rich scattering, whereas high RMS Doppler spreads are obtained in drive-by scenarios.
192 citations
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TL;DR: This work demonstrates that heterologous genes driven by pathogen-inducible promoters can increase the biocontrol and systemic resistance-inducing properties of fungal biOControl agents, such as Trichoderma spp.
Abstract: Biocontrol agents generally do not perform well enough under field conditions to compete with chemical fungicides. We determined whether transgenic strain SJ3-4 of Trichoderma atroviride, which expresses the Aspergillus niger glucose oxidase-encoding gene, goxA, under a homologous chitinase (nag1) promoter had increased capabilities as a fungal biocontrol agent. The transgenic strain differed only slightly from the wild-type in sporulation or the growth rate. goxA expression occurred immediately after contact with the plant pathogen, and the glucose oxidase formed was secreted. SJ3-4 had significantly less N-acetylglucosaminidase and endochitinase activities than its nontransformed parent. Glucose oxidase-containing culture filtrates exhibited threefold-greater inhibition of germination of spores of Botrytis cinerea. The transgenic strain also more quickly overgrew and lysed the plant pathogens Rhizoctonia solani and Pythium ultimum. In planta, SJ3-4 had no detectable improved effect against low inoculum levels of these pathogens. Beans planted in heavily infested soil and treated with conidia of the transgenic Trichoderma strain germinated, but beans treated with wild-type spores did not germinate. SJ3-4 also was more effective in inducing systemic resistance in plants. Beans with SJ3-4 root protection were highly resistant to leaf lesions caused by the foliar pathogen B. cinerea. This work demonstrates that heterologous genes driven by pathogen-inducible promoters can increase the biocontrol and systemic resistance-inducing properties of fungal biocontrol agents, such as Trichoderma spp., and that these microbes can be used as vectors to provide plants with useful molecules (e.g., glucose oxidase) that can increase their resistance to pathogens.
192 citations
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TL;DR: In this article, the microstructure of joints between an Al-alloy and a zinc coated ferritic steel sheet manufactured by the so-called CMT joining method is investigated.
Abstract: The microstructure of joints between an Al-alloy and a zinc coated ferritic steel sheet manufactured by the so-called CMT joining method is investigated. The joint consists of a weld between the Al-alloy and Al 99.8 filler and a brazing of the filler to the zinc coated steel. The morphology, the structure and the defects of the intermetallic phases that developed at the interface between the steel and the Al 99.8 filler are characterised using scanning and transmission electron microscopy. The intermetallic phase seam is only about 2.3 μm thick and consists of trapezoidal nearly equiaxial Fe2Al5 grains surrounded by finger-like remains of the steel and mostly elliptical FeAl3 grains extending into the Al 99.8 filler material. Both the Fe2Al5 and the FeAl3 grains contain crystal defects.
192 citations
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TL;DR: In this article, the authors analyzed aerosol samples from three distinctly different continental sites: an urban site (Vienna), a savanna site in South Africa (Nylsvley Nature Reserve, NNR) and a free tropospheric continental background site (Sonnblick Observatory, SBO).
192 citations
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01 Jul 2015
TL;DR: MARVIN is presented, a system that combines static with dynamic analysis and which leverages machine learning techniques to assess the risk associated with unknown Android apps in the form of a malice score and which correctly classifies 98.24% of malicious apps with less than 0.04% false positives.
Abstract: Android dominates the smartphone operating system market and consequently has attracted the attention of malware authors and researchers alike Despite the considerable number of proposed malware analysis systems, comprehensive and practical malware analysis solutions are scarce and often short-lived Systems relying on static analysis alone struggle with increasingly popular obfuscation and dynamic code loading techniques, while purely dynamic analysis systems are prone to analysis evasion We present MARVIN, a system that combines static with dynamic analysis and which leverages machine learning techniques to assess the risk associated with unknown Android apps in the form of a malice score MARVIN performs static and dynamic analysis, both off-device, to represent properties and behavioral aspects of an app through a rich and comprehensive feature set In our evaluation on the largest Android malware classification data set to date, comprised of over 135,000 Android apps and 15,000 malware samples, MARVIN correctly classifies 9824% of malicious apps with less than 004% false positives We further estimate the necessary retraining interval to maintain the detection performance and demonstrate the long-term practicality of our approach
192 citations
Authors
Showing all 16934 results
Name | H-index | Papers | Citations |
---|---|---|---|
Krzysztof Matyjaszewski | 169 | 1431 | 128585 |
Wolfgang Wagner | 156 | 2342 | 123391 |
Marco Zanetti | 145 | 1439 | 104610 |
Sridhara Dasu | 140 | 1675 | 103185 |
Duncan Carlsmith | 138 | 1660 | 103642 |
Ulrich Heintz | 136 | 1688 | 99829 |
Matthew Herndon | 133 | 1732 | 97466 |
Frank Würthwein | 133 | 1584 | 94613 |
Alain Hervé | 132 | 1279 | 87763 |
Manfred Jeitler | 132 | 1278 | 89645 |
David Taylor | 131 | 2469 | 93220 |
Roberto Covarelli | 131 | 1516 | 89981 |
Patricia McBride | 129 | 1230 | 81787 |
David Smith | 129 | 2184 | 100917 |
Lindsey Gray | 129 | 1170 | 81317 |