<?xml version="1.0" encoding="UTF-8"?>
<feed xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns="http://www.w3.org/2005/Atom">
<title>Session 4: Other fields of application</title>
<link href="http://hdl.handle.net/10256/635" rel="alternate"/>
<subtitle/>
<id>http://hdl.handle.net/10256/635</id>
<updated>2013-05-23T14:16:01Z</updated>
<dc:date>2013-05-23T14:16:01Z</dc:date>
<entry>
<title>Grain size analyses in tin-lead glazes based on 2d-sections</title>
<link href="http://hdl.handle.net/10256/691" rel="alternate"/>
<author>
<name>Schwedt, A.</name>
</author>
<author>
<name>Buxeda i Garrigós, Jaume</name>
</author>
<author>
<name>Madrid Fernández, Marisol</name>
</author>
<id>http://hdl.handle.net/10256/691</id>
<updated>2012-11-30T07:34:04Z</updated>
<published>2005-10-01T00:00:00Z</published>
<summary type="text">Grain size analyses in tin-lead glazes based on 2d-sections
Schwedt, A.; Buxeda i Garrigós, Jaume; Madrid Fernández, Marisol
Mateu i Figueras, Glòria; Barceló i Vidal, Carles
A problem in the archaeometric classification of Catalan Renaissance pottery is the fact, that&#13;
the clay supply of the pottery workshops was centrally organized by guilds, and therefore&#13;
usually all potters of a single production centre produced chemically similar ceramics.&#13;
However, analysing the glazes of the ware usually a large number of inclusions in the glaze is&#13;
found, which reveal technological differences between single workshops. These inclusions&#13;
have been used by the potters in order to opacify the transparent glaze and to achieve a white&#13;
background for further decoration.&#13;
In order to distinguish different technological preparation procedures of the single workshops,&#13;
at a Scanning Electron Microscope the chemical composition of those inclusions as well as&#13;
their size in the two-dimensional cut is recorded. Based on the latter, a frequency distribution&#13;
of the apparent diameters is estimated for each sample and type of inclusion.&#13;
Following an approach by S.D. Wicksell (1925), it is principally possible to transform the&#13;
distributions of the apparent 2D-diameters back to those of the true three-dimensional bodies.&#13;
The applicability of this approach and its practical problems are examined using different&#13;
ways of kernel density estimation and Monte-Carlo tests of the methodology. Finally, it is&#13;
tested in how far the obtained frequency distributions can be used to classify the pottery
</summary>
<dc:date>2005-10-01T00:00:00Z</dc:date>
</entry>
<entry>
<title>Interpretation of wind components as compositional variables</title>
<link href="http://hdl.handle.net/10256/690" rel="alternate"/>
<author>
<name>Buenestado Caballero, Pablo</name>
</author>
<author>
<name>Jarauta Bragulat, Eusebio</name>
</author>
<author>
<name>Hervada i Sala, Carme</name>
</author>
<id>http://hdl.handle.net/10256/690</id>
<updated>2012-06-28T12:30:36Z</updated>
<published>2005-10-01T00:00:00Z</published>
<summary type="text">Interpretation of wind components as compositional variables
Buenestado Caballero, Pablo; Jarauta Bragulat, Eusebio; Hervada i Sala, Carme
Mateu i Figueras, Glòria; Barceló i Vidal, Carles
The classical statistical study of the wind speed in the atmospheric surface layer is made&#13;
generally from the analysis of the three habitual components that perform the wind data,&#13;
that is, the component W-E, the component S-N and the vertical component,&#13;
considering these components independent.&#13;
When the goal of the study of these data is the Aeolian energy, so is when wind is&#13;
studied from an energetic point of view and the squares of wind components can be&#13;
considered as compositional variables. To do so, each component has to be divided by&#13;
the module of the corresponding vector.&#13;
In this work the theoretical analysis of the components of the wind as compositional&#13;
data is presented and also the conclusions that can be obtained from the point of view of&#13;
the practical applications as well as those that can be derived from the application of&#13;
this technique in different conditions of weather
</summary>
<dc:date>2005-10-01T00:00:00Z</dc:date>
</entry>
<entry>
<title>Compositional analysis of archaeological glasses</title>
<link href="http://hdl.handle.net/10256/688" rel="alternate"/>
<author>
<name>Baxter, M.J.</name>
</author>
<author>
<name>Beardah, C.C.</name>
</author>
<author>
<name>Freestone, I.C.</name>
</author>
<id>http://hdl.handle.net/10256/688</id>
<updated>2012-06-28T12:30:36Z</updated>
<published>2005-10-01T00:00:00Z</published>
<summary type="text">Compositional analysis of archaeological glasses
Baxter, M.J.; Beardah, C.C.; Freestone, I.C.
Mateu i Figueras, Glòria; Barceló i Vidal, Carles
At CoDaWork'03 we presented work on the analysis of archaeological glass composi-&#13;
tional data. Such data typically consist of geochemical compositions involving 10-12&#13;
variables and approximates completely compositional data if the main component, sil-&#13;
ica, is included. We suggested that what has been termed `crude' principal component&#13;
analysis (PCA) of standardized data often identi ed interpretable pattern in the data&#13;
more readily than analyses based on log-ratio transformed data (LRA). The funda-&#13;
mental problem is that, in LRA, minor oxides with high relative variation, that may&#13;
not be structure carrying, can dominate an analysis and obscure pattern associated&#13;
with variables present at higher absolute levels. We investigate this further using sub-&#13;
compositional data relating to archaeological glasses found on Israeli sites. A simple&#13;
model for glass-making is that it is based on a `recipe' consisting of two `ingredients',&#13;
sand and a source of soda. Our analysis focuses on the sub-composition of components&#13;
associated with the sand source. A `crude' PCA of standardized data shows two clear&#13;
compositional groups that can be interpreted in terms of di erent recipes being used at&#13;
di erent periods, re&#13;
ected in absolute di erences in the composition. LRA analysis can&#13;
be undertaken either by normalizing the data or de ning a `residual'. In either case,&#13;
after some `tuning', these groups are recovered. The results from the normalized LRA&#13;
are di erently interpreted as showing that the source of sand used to make the glass&#13;
di ered. These results are complementary. One relates to the recipe used. The other&#13;
relates to the composition (and presumed sources) of one of the ingredients. It seems&#13;
to be axiomatic in some expositions of LRA that statistical analysis of compositional&#13;
data should focus on relative variation via the use of ratios. Our analysis suggests that&#13;
absolute di erences can also be informative
</summary>
<dc:date>2005-10-01T00:00:00Z</dc:date>
</entry>
</feed>
