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Institution

Brno University of Technology

EducationBrno, Czechia
About: Brno University of Technology is a education organization based out in Brno, Czechia. It is known for research contribution in the topics: Fracture mechanics & Filter (video). The organization has 6339 authors who have published 15226 publications receiving 194088 citations. The organization is also known as: Vysoké učení technické v Brně & BUT.


Papers
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Journal ArticleDOI
TL;DR: In this paper, the authors show how the application of novel image processing techniques to unique high-resolution white light eclipse images reveals the presence of a new class of structures, reminiscent of smoke rings, faint nested expanding loops, expanding bubbles, and twisted helical structures.
Abstract: White light images of the solar corona, taken during total solar eclipses, capture the complex dynamic relationship between the coronal plasma and the magnetic field. This relationship can be recorded on timescales of seconds to minutes, within a few solar radii above the solar surface. Rays, large-scale loops, and streamers, which are the brightest structures in these images, have shaped current models of the coronal magnetic field and solar wind flow. We show in this work how the application of novel image processing techniques to unique high-resolution white light eclipse images reveals the presence of a new class of structures, reminiscent of smoke rings, faint nested expanding loops, expanding bubbles, and twisted helical structures. These features are interpreted as snapshots of the dynamical evolution of instabilities developing at prominence-corona interfaces and propagating outward with the solar wind.

46 citations

Journal ArticleDOI
TL;DR: The design exploits a three-stage structure with a Reversed Miller Compensation Scheme, where the input stage is based on a non-tailed bulk-driven differential pair, and the resulting amplifier outperforms other ultra-low-voltage OTAs in terms of a DC voltage gain and power efficiency.
Abstract: A new solution for an ultra-low-voltage, ultra-low-power operational transconductance amplifier (OTA) is presented in the paper. The design exploits a three-stage structure with a Reversed Miller Compensation Scheme, where the input stage is based on a non-tailed bulk-driven differential pair. Optimization of the structure for very low supply voltage is discussed. The resulting amplifier outperforms other ultra-low-voltage OTAs in terms of a DC voltage gain and power efficiency, expressed by standard figures of merit. Experimental verification using a $0.18~\mu \text{m}$ CMOS technology, with supply voltage of 0.3-V, showed a dissipation power of 13 nW, a DC voltage gain of 98 dB, a gain-bandwidth product of 3.1 kHz and an average slew-rate of 9.1 V/ms at 30 pF load capacitance. The experimental results agree well with simulations.

46 citations

Journal ArticleDOI
TL;DR: In this article, the results of alkaline activation of fly ash and waste fine-grained brick body were tested for the compressive and flexural strengths, bulk density, and microstructure.

46 citations

Proceedings ArticleDOI
22 Feb 2009
TL;DR: A new hardware-based algorithm for packet classification based on problem decomposition and aimed at the highest network speeds is proposed, with a unique property of the algorithm is the constant time complexity in terms of external memory accesses.
Abstract: Packet classification is an important operation for applications such as routers, firewalls or intrusion detection systems. Many algorithms and hardware architectures for packet classification have been created, but none of them can compete with the speed of TCAMs in the worst case. We propose new hardware-based algorithm for packet classification. The solution is based on problem decomposition and is aimed at the highest network speeds. A unique property of the algorithm is the constant time complexity in terms of external memory accesses. The algorithm performs exactly two external memory accesses to classify a packet. Using FPGA and one commodity SRAM chip, a throughput of 150 million packets per second can be achieved. This makes throughput of 100 Gbps for the shortest packets. Further performance scaling is possible with more or faster SRAM chips.

46 citations

Journal ArticleDOI
TL;DR: In this paper, Spikes and Jie conclude that the previous assumption has as much merit as the use of viscosity measured in viscometers, and that the great progress of the last few years would not have been possible using the concepts and methods espoused in this article.
Abstract: Progress in the classical field of EHL has for decades been paralyzed by the assumption that shear thinning should be indistinguishable from the shear dependence of the viscosity of a liquid heated by viscous dissipation and that the parameters of this simple shear dependence can be obtained from the shape of a friction curve. In the last few years, by abandoning this assumption and employing real viscosity measured with viscometers, there has been revolutionary progress in predicting film thickness and friction. Now, Spikes and Jie conclude that the previous assumption has as much merit as the use of viscosity measured in viscometers. This suggestion may be popular among those who wish to ignore viscometer measurements in favor of extracting properties from friction curves. However, within the subject article, there are numerous misstatements of fact and misrepresentations by omission, and the recent progress using real viscosity is not acknowledged. The debate has degenerated into a friction curve fitting competition which is not helpful. The great progress of the last few years would not have been possible using the concepts and methods espoused in this article.

46 citations


Authors

Showing all 6383 results

NameH-indexPapersCitations
Georg Kresse111430244729
Patrik Schmuki10976352669
Michael Schmid8871530874
Robert M. Malina8869138277
Jiří Jaromír Klemeš6456514892
Alessandro Piccolo6228414332
René Kizek6167216554
George Danezis5920911516
Stevo Stević583749832
Edvin Lundgren5728610158
Franz Halberg5575015400
Vojtech Adam5561114442
Lukas Burget5325221375
Jan Cermak532389563
Hynek Hermansky5131714372
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202328
2022106
20211,053
20201,010
20191,214
20181,131