Structural drilling using the high-frequency (sonic) rotary method

AbstractIn Slovenia, there is widespread use of structural drilling along with classical core drilling. Recently, however, the need has arisen for a highly effective core drilling method with the aid of which high-quality core might be obtained. In order to achieve this aim, one among several Slovenian companies dealing with geological surveying has decided to implement structural drilling using a high-frequency drilling method. The following article presents the theoretical foundations for such a high-frequency method, as well as the manner of its implementation. In the final part of the article, a practical comparison between the conventional and the high-frequency core drilling methods is also provided.

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Development of a high-frequency method for the measurement of velocity distribution function of the electrons. (USSR)

Vacuum ◽

10.1016/s0042-207x(77)80348-5 ◽

1977 ◽

Vol 27 (1) ◽

pp. 40

Keyword(s):

Distribution Function ◽

Velocity Distribution ◽

High Frequency ◽

Velocity Distribution Function ◽

Frequency Method

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PCDRN: Progressive Cascade Deep Residual Network for Pansharpening

Remote Sensing ◽

10.3390/rs12040676 ◽

2020 ◽

Vol 12 (4) ◽

pp. 676 ◽

Cited By ~ 1

Author(s):

Yong Yang ◽

Wei Tu ◽

Shuying Huang ◽

Hangyuan Lu

Keyword(s):

High Resolution ◽

Loss Function ◽

High Frequency ◽

Experimental Results ◽

Superior Performance ◽

Residual Network ◽

High Quality ◽

Convolution Approach ◽

Visual Assessments ◽

Coarse To Fine

Pansharpening is the process of fusing a low-resolution multispectral (LRMS) image with a high-resolution panchromatic (PAN) image. In the process of pansharpening, the LRMS image is often directly upsampled by a scale of 4, which may result in the loss of high-frequency details in the fused high-resolution multispectral (HRMS) image. To solve this problem, we put forward a novel progressive cascade deep residual network (PCDRN) with two residual subnetworks for pansharpening. The network adjusts the size of an MS image to the size of a PAN image twice and gradually fuses the LRMS image with the PAN image in a coarse-to-fine manner. To prevent an overly-smooth phenomenon and achieve high-quality fusion results, a multitask loss function is defined to train our network. Furthermore, to eliminate checkerboard artifacts in the fusion results, we employ a resize-convolution approach instead of transposed convolution for upsampling LRMS images. Experimental results on the Pléiades and WorldView-3 datasets prove that PCDRN exhibits superior performance compared to other popular pansharpening methods in terms of quantitative and visual assessments.

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Investigating Fatigue Strength of Vacuum Carburized 17CrNi6-6 Steel Using a Resonance High Frequency Method

Solid State Phenomena ◽

10.4028/www.scientific.net/ssp.225.45 ◽

2014 ◽

Vol 225 ◽

pp. 45-52 ◽

Cited By ~ 1

Author(s):

Piotr Kula ◽

Konrad Dybowski ◽

Sebastian Lipa ◽

Robert Pietrasik ◽

Radomir Atraszkiewicz ◽

...

Keyword(s):

High Pressure ◽

Fatigue Strength ◽

High Frequency ◽

Vacuum Carburizing ◽

Frequency Method ◽

Single Degree Of Freedom ◽

Bending Fatigue ◽

Single Degree ◽

Bending Fatigue Strength ◽

Frequency Changes

The bending fatigue strength of 17CrNi6-6 steel subjected to vacuum carburizing with high pressure gas hardening has been measured using a novel high-frequency technique. The test records the changes in resonance and consists of observing resonance frequency changes in a vibrating system with a single degree of freedom as a result of the forming of a fatigue crack. Moreover, a mechanism of fatigue nucleation and propagation in steel hardened by vacuum carburizing is presented.

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Hybrid GRE-High frequency method for analysis of scattering and radiation problems incorporating large and complex structures

2010 International Conference on Electromagnetics in Advanced Applications ◽

10.1109/iceaa.2010.5653742 ◽

2010 ◽

Cited By ~ 1

Author(s):

P. Janpugdee ◽

C.-F. Wang ◽

T.-T. Chia

Keyword(s):

High Frequency ◽

Complex Structures ◽

Frequency Method ◽

Scattering And Radiation

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Collocations of high frequency words in nursing research articles and The Academic Collocation List: Similarities and differences

ExELL ◽

10.2478/exell-2020-0011 ◽

2020 ◽

Vol 8 (1) ◽

pp. 1-13

Author(s):

Kaja Mandić ◽

Izabela Dankić

Keyword(s):

Nursing Students ◽

Foreign Language ◽

High Frequency ◽

Research Articles ◽

Teaching English ◽

Microsoft Excel ◽

High Quality ◽

Academic Fields ◽

Medical Library ◽

Similarities And Differences

AbstractThe main objective of this corpus-based study is to research the most frequent two-word collocations in the corpus of nursing scientific articles and compare this newly assembled list of nursing collocations with the Academic Collocation List (ACL). The nursing scientific articles corpus (NSAC) used in this study comprises 1,119,441 words from 262 articles of 10 high-quality journals from the Medical Library Association list which nursing students can freely access. The focus is on noun-noun and noun-adjective collocations. The selected articles were converted into txt files using the ABBYY Fine Reader. WordSmith Tools 7.0 and TermeX were used for noun and collocation extraction. The newly assembled Nursing Collocation List (NCL) and the ACL were compared using Microsoft Excel 2016. A total of 488 collocations were identified in the NSAC and the NCL contains 234 (47.9%) noun + noun and 254 (52.1%) adjective + noun collocation combinations. The most frequent two-word collocation is health care and it appeared 618 times in the NSAC. The ACL (2,469) and the NCL (488) share 123 two-word collocations. Although there are some correspondences between collocations in the two corpora, key nursing collocations with notably higher frequencies are identified in the NSAC (365). Despite the fact that the ACL is the most extensive collocation list across different academic fields and it certainly plays an important role in teaching English as a foreign language, this study suggests that it does not provide key nursing collocations for improvement of nursing collocation competence.

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