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Neural Networks to Map Archaeological Lithic Artefacts

Jimenez-Puerto Joaquin, Gallello Gianni, Orozco Teresa

Inżynieria Mineralna

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2024

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Vol. 1, no. 1

361--367

EN

An analytical non-destructive strategy to chemically characterize lithic artefacts has been developed. Around 100 archaeological lithic materials found in Neolithic-Chalcolithic sites in the Mediterranean region of the Iberian Peninsula and nowadays stored in different museums of the Valencian Community (Spain), were studied. The materials belong to different typologies of rock (diabase, sillimanite, ophite and amphibolite) and were analysed employing portable energy dispersive X-ray fluorescence spectroscopy (pXRF) directly in the rock surface. The obtained data were processed through neural networks protocol, specifically the so-called Kohonen networks or Self Organised Maps (SOM), to map the geologic samples. This selforganized topological feature maps are suitable to deal with multidimensional representations and map them in a twodimensional space of neurons, following an unsupervised learning protocol. SOM is used to reduce multidimensional data onto lower-dimensional spaces and clustering procedures. As a result, SOM create spatially organized representations, which enhance the discovery of correlations between data. In this case the method has enabled the evaluation of elemental markers related to each rock type behaving as a fine hidden pattern detector and so understand the possible advantages and disadvantages of the analytical method employed to define provenance issues. The attribution suggested by statistics is mainly driven by the composition of rocks essential minerals which are linked to the different petrogenetic conditions. The results showed that in most of the cases the distribution and dispersion of the chemical profile depend of the kind of rock, and clearly suggest that a good way to identify stone tools raw material procurement is to look for elemental markers, being the prior step to create an approximation to ancient exchange networks and their evolution in a diachronic axis.

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Minero-Petrographic Features and Physico-Mechanical Properties of the Macigno Sandstone in the Vellano Area (Pistoia, Tuscany, Italy)

Lezzerini Marco, Aquino Andrea, Di Petta Claudio, Gallello Gianni, Pagnotta Stefano

Inżynieria Mineralna

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2024

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Vol. 1, no. 1

351--360

EN

The sandstones belonging to the terrigenous deposits of the Macigno Formation (Late Oligocene-Early Miocene) were widely used as building stones in Tuscany (Italy) for the wide distribution of their outcrops and the good qualities of the extracted stone. This research reports the petrographic and mineralogical data, and the physical and mechanical test values collected to evaluate the main technical properties of the Macigno sandstones from the Vellano area, with the purpose of comparing the quality of the stones extracted in this area with those from other quarries in north-western Tuscany. The results, obtained analysing 21 samples from the Vellano quarry and its surroundings, show that sandstones cropping out here are characterized by medium to medium-fine sand-sized grains made up of quartz, K-feldspar, plagioclases, phyllosilicates, lithic fragments, and accessory. Clayey materials and calcite are present as matrix and cement, respectively. The clay fraction is made up of mica-like minerals, chlorite, chlorite/smectite interlayers and, in some samples, corrensite and kaolinite. From the physical and mechanical point of view the analysed samples show low porosity and high flexural and compressive strengths. Compared to the other Macigno sandstone samples from north-western Tuscany, the best samples of Vellano stone show rather comparable mechanical resistance than those quarried at Matraia in Lucca province, which today is another active quarry of sure interest for the good quality of the extracted material.

3

Building Material Recognition and Feature Extraction Using Small CCD Sensor and Image Analysis and Clustering Techniques

Pagnotta Stefano, Filimon Danis Ionut, Gallello Gianni, Lezzerini Marco

Inżynieria Mineralna

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2024

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Vol. 1, no. 1

229-236

EN

Heritage Building material recognition is the process of classifying building materials based on their visual appearance. It is important in construction, urban planning, and archaeology. Image analysis is a common approach, starting with acquiring RGB images, then extracting features using techniques such as colour histograms and texture analysis, and clustering the materials into groups using algorithms like k-means. Finally, the materials are classified into categories using classifiers like decision trees, SVM, or neural networks. Image analysis is a useful tool for building material recognition, as it allows for accurate classification of building materials based on their visual characteristics.

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An Innovative Methodological Approach for the Study of Ancient Cistern Waterproofing Mortar of Sagunto Castle

Saez-Hernandez Roberto, Gallello Gianni, Ortega Ivan Fumado, Lezzerini Marco, Pagnotta Stefano, Cervera M. Luisa, Morales-Rubio Angel

Inżynieria Mineralna

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2024

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Vol. 1, no. 1

195--201

EN

In this work, we present the results of the chemical, mineralogical and colorimetric characterization of the waterproofing mortars from the ancient cisterns of the Sagunto Castle (Valencia, Spain). The fortress presents 2500 years of human occupation and, given the lack of natural water sources, collecting and storing rain water was mandatory ever since. Nowadays, several cisterns are found in the hill, and thus the application of analytical approaches can help in characterizing each layer within the cultural phases of the Castle’s history (Iberian, Punic, Roman, Islamic, Medieval, Modern or Contemporary). Mineralogical analyses were carried out employing X-ray diffractometry and mid-infrared attenuated total reflection spectroscopy, and, on the other hand, the portable energy dispersive X-ray fluorescence spectroscopy was employed to obtain the concentrations of major and minor chemical elements. Colour features of the samples were identified by smartphone photo processing to observe possible relation between colour and waterproofing mortar compounds. Last, Raman spectroscopy was employed to analyze the different phases present in the samples. Multivariate statistics were employed to identify different waterproofing mortar layers and develop hypotheses concerning different construction phases and compare their manufacturing processes. Analytical results allowed to find common patterns among different cisterns and mortar layers, and colorimetric analyses showed good potential as an additional fast, cheap and non-destructive source of information for studying these types of samples.