scholarly journals Impulsive Volcanic Plumes Generate Volcanic Lightning and Vent Discharges: A Statistical Analysis of Sakurajima Volcano in 2015

2021 ◽  
Author(s):  
Cassandra M. Smith ◽  
Damien Gaudin ◽  
Alexa R. Van Eaton ◽  
Sonja A. Behnke ◽  
Steven Reader ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Volcanic Plumes ◽  
Sakurajima Volcano ◽  
Volcanic Lightning

scholarly journals Physical properties of volcanic lightning: Constraints from magnetotelluric and video observations at Sakurajima volcano, Japan

2016 ◽  
Vol 444 ◽  
pp. 45-55 ◽  
Author(s):  
Koki Aizawa ◽  
Corrado Cimarelli ◽  
Miguel A. Alatorre-Ibargüengoitia ◽  
Akihiko Yokoo ◽  
Donald B. Dingwell ◽  
...  
Keyword(s):  
Physical Properties ◽  
Sakurajima Volcano ◽  
Video Observations ◽  
Volcanic Lightning

Correlating the electrification of volcanic plumes with ashfall textures at Sakurajima Volcano, Japan

2018 ◽  
Vol 492 ◽  
pp. 47-58 ◽  
Author(s):  
Cassandra M. Smith ◽  
Alexa R. Van Eaton ◽  
Sylvain Charbonnier ◽  
Stephen R. McNutt ◽  
Sonja A. Behnke ◽  
...  
Keyword(s):  
Volcanic Plumes ◽  
Sakurajima Volcano

scholarly journals Magnetotelluric pulses generated by volcanic lightning at Sakurajima volcano, Japan

2010 ◽  
Vol 37 (17) ◽  
pp. n/a-n/a ◽  
Author(s):  
Koki Aizawa ◽  
Akihiko Yokoo ◽  
Wataru Kanda ◽  
Yasuo Ogawa ◽  
Masato Iguchi
Keyword(s):  
Sakurajima Volcano ◽  
Volcanic Lightning

scholarly journals Multiparametric observation of volcanic lightning: Sakurajima Volcano, Japan

2016 ◽  
Vol 43 (9) ◽  
pp. 4221-4228 ◽  
Author(s):  
C. Cimarelli ◽  
M. A. Alatorre-Ibargüengoitia ◽  
K. Aizawa ◽  
A. Yokoo ◽  
A. Díaz-Marina ◽  
...  
Keyword(s):  
Sakurajima Volcano ◽  
Volcanic Lightning

Statistical analysis of classification

1966 ◽  
Vol 24 ◽  
pp. 188-189
Author(s):  
T. J. Deeming
Keyword(s):  
Multivariate Analysis ◽  
Statistical Analysis ◽  
Classification Scheme ◽  
Analytical Procedure ◽  
Narrow Band ◽  
Scientific Research ◽  
Maximum Amount ◽  
Amount Of Information

If we make a set of measurements, such as narrow-band or multicolour photo-electric measurements, which are designed to improve a scheme of classification, and in particular if they are designed to extend the number of dimensions of classification, i.e. the number of classification parameters, then some important problems of analytical procedure arise. First, it is important not to reproduce the errors of the classification scheme which we are trying to improve. Second, when trying to extend the number of dimensions of classification we have little or nothing with which to test the validity of the new parameters.Problems similar to these have occurred in other areas of scientific research (notably psychology and education) and the branch of Statistics called Multivariate Analysis has been developed to deal with them. The techniques of this subject are largely unknown to astronomers, but, if carefully applied, they should at the very least ensure that the astronomer gets the maximum amount of information out of his data and does not waste his time looking for information which is not there. More optimistically, these techniques are potentially capable of indicating the number of classification parameters necessary and giving specific formulas for computing them, as well as pinpointing those particular measurements which are most crucial for determining the classification parameters.

Quantitative parallel EELS spectrum imaging developed as a new tool in AEM

1992 ◽  
Vol 50 (2) ◽  
pp. 1202-1203
Author(s):  
Gianluigi Botton ◽  
Gilles L'espérance
Keyword(s):  
Statistical Analysis ◽  
Spatial Resolution ◽  
Personal Computer ◽  
Systematic Study ◽  
Present Author ◽  
Chemical Elements ◽  
Detection Limits ◽  
Research Groups ◽  
Quantitative Performance ◽  
Spectrum Imaging

As interest for parallel EELS spectrum imaging grows in laboratories equipped with commercial spectrometers, different approaches were used in recent years by a few research groups in the development of the technique of spectrum imaging as reported in the literature. Either by controlling, with a personal computer both the microsope and the spectrometer or using more powerful workstations interfaced to conventional multichannel analysers with commercially available programs to control the microscope and the spectrometer, spectrum images can now be obtained. Work on the limits of the technique, in terms of the quantitative performance was reported, however, by the present author where a systematic study of artifacts detection limits, statistical errors as a function of desired spatial resolution and range of chemical elements to be studied in a map was carried out The aim of the present paper is to show an application of quantitative parallel EELS spectrum imaging where statistical analysis is performed at each pixel and interpretation is carried out using criteria established from the statistical analysis and variations in composition are analyzed with the help of information retreived from t/γ maps so that artifacts are avoided.

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