Collection of microseismic intensity data: a model for Turkey

2021 ◽  
Vol 14 (5) ◽  
Author(s):  
Shaghayegh Karimzadeh ◽  
Aysegul Askan
Keyword(s):  
Intensity Data

Direct phase determination in electron crystallography: small organic molecules

1992 ◽  
Vol 50 (2) ◽  
pp. 1166-1167
Author(s):  
Douglas L. Dorset
Keyword(s):  
Organic Molecules ◽  
Data Sets ◽  
Temperature Structure ◽  
3D Analysis ◽  
Intensity Data ◽  
Electron Crystallography ◽  
Phase Determination ◽  
Measured Intensity ◽  
3D Data

The quantitative use of electron diffraction intensity data for the determination of crystal structures represents the pioneering achievement in the electron crystallography of organic molecules, an effort largely begun by B. K. Vainshtein and his co-workers. However, despite numerous representative structure analyses yielding results consistent with X-ray determination, this entire effort was viewed with considerable mistrust by many crystallographers. This was no doubt due to the rather high crystallographic R-factors reported for some structures and, more importantly, the failure to convince many skeptics that the measured intensity data were adequate for ab initio structure determinations.We have recently demonstrated the utility of these data sets for structure analyses by direct phase determination based on the probabilistic estimate of three- and four-phase structure invariant sums. Examples include the structure of diketopiperazine using Vainshtein's 3D data, a similar 3D analysis of the room temperature structure of thiourea, and a zonal determination of the urea structure, the latter also based on data collected by the Moscow group.

GRAPHICAL DISPLAY OF THREE-DIMENSIONAL (3-D) INTENSITY DATA FROM SINGLE-CRYSTAL REFLECTIONS

1986 ◽  
Vol 47 (C5) ◽  
pp. C5-183-C5-187
Author(s):  
M. U. PILOTTI ◽  
G. J. McINTYRE
Keyword(s):  
Single Crystal ◽  
Three Dimensional ◽  
Graphical Display ◽  
Intensity Data

scholarly journals Macroseismic intensity data of the 22 April 2013 Tenk (Hungary) earthquake

2014 ◽  
Vol 49 (3) ◽  
pp. 283-294
Author(s):  
Gyöngyvér Szanyi ◽  
Zoltán Gráczer ◽  
Erzsébet Győri
Keyword(s):  
Macroseismic Intensity ◽  
Intensity Data

Use of TALP with laboratory powder diffraction data from 2D detectors

2013 ◽  
Vol 28 (S2) ◽  
pp. S481-S490
Author(s):  
Oriol Vallcorba ◽  
Anna Crespi ◽  
Jordi Rius ◽  
Carles Miravitlles
Keyword(s):  
Organic Compounds ◽  
Structural Study ◽  
Powder Diffraction ◽  
Diffraction Data ◽  
Powder Pattern ◽  
Experimental Setup ◽  
Intensity Data ◽  
Powder Diffraction Data ◽  
X Ray ◽  
Molecular Compounds

The viability of the direct-space strategy TALP (Vallcorba et al., 2012b) to solve crystal structures of molecular compounds from laboratory powder diffraction data is shown. The procedure exploits the accurate metric refined from a ‘Bragg-Brentano’ powder pattern to extract later the intensity data from a second ‘texture-free’ powder pattern with the DAJUST software (Vallcorba et al., 2012a). The experimental setup for collecting this second pattern consists of a circularly collimated X-ray beam and a 2D detector. The sample is placed between two thin Mylar® foils, which reduces or even eliminates preferred orientation. With the combination of the DAJUST and TALP software a preliminary but rigorous structural study of organic compounds can be carried out at the laboratory level. In addition, the time-consuming filling of capillaries with diameters thinner than 0.3mm is avoided.

scholarly journals AIS and VBD Data Fusion for Marine Fishing Intensity Mapping and Analysis in the Northern Part of the South China Sea

2021 ◽  
Vol 10 (5) ◽  
pp. 277
Author(s):  
Xiaoen Li ◽  
Yang Xiao ◽  
Fenzhen Su ◽  
Wenzhou Wu ◽  
Liang Zhou
Keyword(s):  
South China Sea ◽  
South China ◽  
Coastal Area ◽  
Data Sources ◽  
Intensity Data ◽  
Marine Fishery ◽  
Fishing Vessels ◽  
Intensity Information ◽  
Marine Fishery Resources ◽  
Marine Fishing

For the sustainable development of marine fishery resources, it is essential to comprehensively, accurately, and objectively obtain the spatial characteristics and evolution law of fishing intensity. However, previous studies have focused more on the use of single data sources, such as AIS (Automatic Information System) and VBD (VIIRS boat detection), to obtain fishing intensity information and, as such, have encountered some problems, such as insufficient comprehensive data coverage for ships, non-uniform spatial distribution of data signal acquisition, and insufficient accuracy in obtaining fishing intensity information. The development of big data and remote sensing Earth observation technology has provided abundant data sources and technical support for the acquisition of fishing intensity data for marine fisheries. Based on this situation, this paper proposes a framework that integrates the data of fishing vessels from two sources (AIS, with high space-time granularity, and VBD, with short revisit cycle and high sensitivity), in order to obtain such information based on closely matching and fusing the vector point data of ship positions. With the help of this framework and the strategy of indirectly representing fishing intensity by data point density after fusion, the spatial characteristics and rules of fishing intensity in typical seasons (February, April, September, and November) in the northern South China Sea in 2018 were systematically analyzed and investigated. The results revealed the following: (1) Matching and fusing AIS and VBD data can provide a better perspective to produce robust and accurate marine fishery intensity data. The two types of data have a low proximity match rate (approximately 1.89% and 6.73% of their respective inputs) and the matching success for fishing vessels in the data was 49.42%. (2) Single AIS data can be used for nearshore (50 to 70 km) marine fishery analysis research, while VBD data reflect the objective marine fishing in space, showing obvious complementarity with AIS. (3) The fishing intensity grid data obtained from the integrated data show that high-intensity fishing in the study area was concentrated in the coastal area of Maoming City, Guangdong (0–50 km); the coastal area of Guangxi Beihai (10–70 km); around Hainan Island in Zhangzhou (10–30 km); and the Sanya nearshore area (0–50 km). However, it did not decay with increasing offshore distance, such as at the Trans-Vietnamese boundary in the Beibu Gulf, near the China–Vietnam Common Fisheries Area (50 km) and high-intensity fishing areas. (4) The obtained fishing intensity data (AIS, VBD, and AIS + VBD) were quantitatively analyzed, showing that the CV (Coefficient of Variation) of the average for each month (after fusing the two types of data) was 0.995, indicating that the distribution of the combined data was better than that before fusion (before fusion: AIS = 0.879, VBD = 1.642). Therefore, the integration of AIS and VBD can meet the need for a more effective, comprehensive, and accurate fishing intensity analysis in marine fishery resources.

Fusion of range and intensity data in a scanning sensor

1992 ◽  
Author(s):  
Andrzej M. Hanczak
Keyword(s):  
Intensity Data

Sizing of soft spheroidal particles by multiangle scattered light intensity data: application of neural networks

2004 ◽  
Vol 89 (1-4) ◽  
pp. 279-289 ◽  
Author(s):  
Vladimir V. Berdnik ◽  
Robert D. Mukhamedyarov ◽  
Valery A. Loiko
Keyword(s):  
Neural Networks ◽  
Light Intensity ◽  
Scattered Light ◽  
Scattered Light Intensity ◽  
Intensity Data ◽  
Data Application

scholarly journals Discriminating among distinct source models of the 1908 Messina Straits earthquake by modelling intensity data through full wavefield seismograms

2014 ◽  
Vol 198 (1) ◽  
pp. 164-173 ◽  
Author(s):  
Vincenzo Convertito ◽  
Nicola Alessandro Pino
Keyword(s):  
Intensity Data ◽  
Distinct Source ◽  
Source Models

Recovering Phase Information from Intensity Data(Nobel Lecture)

1986 ◽  
Vol 25 (7) ◽  
pp. 614-629 ◽  
Author(s):  
Jerome Karle
Keyword(s):  
Intensity Data ◽  
Phase Information ◽  
Nobel Lecture
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