A lajosmizsei La Tène üvegkarperec-töredékekről

Valéria Kulcsár, supervisor of the rescue excavations carried out during the construction of Motorway M5 identified some Late Iron Age (LT D, closer to Roman Age) phenomena at the archaeological site Lajosmizse–Kossuth TSz, formerly Kónya-major in 1987–1988. One of the features, a dwelling house (feature No. 10) contained three fragments of dark blue glass bracelets from the La Tène Period which belong to the three-ribbed type, 6a or 6b according to Haevernick 1960. The classification of these fragmentary bracelets was unambiguous due to the traces of a zigzag line ornament on item KKJM 92.1.35, and the articulated middle ribs on items KKJM 92.1.35–36. Both regional and local researches have demonstrated that three-ribbed bracelets (Haevernick group 6) were widespread in Europe – especially in Austria – in a relatively broad time range (LT C1a–LT C2 or D), but they appeared in distinct phases and typologically different variants regarding each area. In Hungary, group 6 is one of the most frequent types of glass bracelets in the whole LT C and LT D. Unfortunately, the only known LT D examples originate from the archaeological site Velem–Szentvid, and due to the challenges in dating the objects all over Europe (e.g. the scarcity of closed find complexes), it is a question whether the bracelets from Lajosmizse can also be determined as LT D fragments like the settlement, or had survived and had been preserved from a previous period. In order to determine the base glass type and the colourants and create a Hungarian archaeometric database of Iron Age glass bracelets, the chemical composition of the artefacts was determined using a handheld X-ray fluorescence spectrometer and an electron microprobe (attached with EDS). The bracelets were made of soda type glass (~70 wt% SiO2 , 17–19 wt% Na2O, 2 wt% > K2O, 1 wt% > MgO and phosphorous at or below the detection limit of the EDS). Only item KKJM 92.1.36 showed a somewhat higher K2O concentration (~2 wt%) compared to the other two pieces, indicating that the bracelets were not produced from a single glass batch. Based on the base glass composition, the bracelets fit well to the rest of the pieces already known from Europe (e.g. from Austria, the Lower-Rhine region), independent from the typology. The SrO (0.04 wt%) and ZrO2 (0.002–0.003 wt%) as well as Al2O3 content (~2.4 wt%) confirms that bracelets were produced in the younger phase of the La Tène Period glass production, from around LT C1b. This does not serve as a clear evidence for the LT D dating, although it does not exclude that. The combination of cobalt and copper were identified as causing the dark blue colour, a phenomenon characteristic for La Tène glass bracelets. In spite of the fact that the two colourants were definitely applied intentionally, we assume that both derived from one mineral deposit (maybe from cobaltiferous alum deposits close to the primary glass production centres in the Mediterranean). The glass composition and/or colour of glass beads from the preceding period largely corresponds to the chemical composition of these bracelets, suggesting a close relation with older (Hallstatt) glass-making traditions. Despite the lack of exact answers for all the emerging questions, it is important to continue the survey focusing on the details and involving more bracelets in the dataset in the future

Concept of a neural system for real-time evaluation of spectroscopic measurements

A hardware implementation of a Backpropagation feedforward neural network has been designed. The tool was proposed for reflectometric measurements integrated together with photosensor arrays. The intelligent reflectometric sensor is being implemented in a multi-chip-module approach. A logarithmic input transformation is applied for easing the misalignment and parameter scatter correction. It also allows for easy ratio calculation by subtraction for normalization with the reference value. The neural network was designed for complexities up to 100 inputs, 30 hidden neurons and 5 outputs. The digital building blocks (neurons) utilize a logic approximation of the sigmoid nonlinearity and the possibility of weight scaling. These hardware solutions result in a simultaneous area reduction and speed gain, at the cost of slightly decreased performance. Simulations of the proposed neural system prove applicability for evaluation of optical measurements were performed for reflectometric and ellipsometric data thin porous layers. Hardware simulations showed good correspondence to the optimum-case neural software simulations