Wetland-Archaeology in the Alpine Space. Overview and actual research issues.

First indications of prehistoric sites in lakes of Switzerland go back more than 200 years and in 1854 Ferdinand Keller (1800-1881) published his famous book The Celtic Pile Dwellings in Swiss Lakes. Since these times, large-scale rescue excavations as well as survey and research projects have extended our knowledge about Neolithic and Bronze Age settlements in lakes, bogs and rivers around the European Alps. In 2011 a representative choice of 111 sites out of nearly 1000 in six countries around the Alps (Austria, France, Germany, Italy, Slovenia and Switzerland) were recognized by the UNESCO World Heritage committee as serial World Heritage. The lecture will give a general overview on prehistoric lake dwellings around the Alps (distribution, types of lakes/bogs and environment of sites, chronology/cultural units in the time scale 5300 to 800 BC) and present examples of well-documented settlement structures. The intense use of dendrochronological dating allowed the building up of a well-fixed chronological framework. In some cases dendrochronology is the basis for year-by-year reconstructions of prehistoric village biographies and detailed insights in the life cycle of early agrarian settlements. Beside these local events the grouped repartition of lake dwelling remains on the time scale makes a more global correlation between Holocene lake levels and the preservation of archaeological layers likely.

A study of the time complexity of an Elitist Genetic Algorithm used for associating optical observations of MEO and GEO Space Debris

Currently several thousands of objects are being tracked in the MEO and GEO regions through optical means. The problem faced in this framework is that of Multiple Target Tracking (MTT). In this context both the correct associations among the observations, and the orbits of the objects have to be determined. The complexity of the MTT problem is defined by its dimension S. Where S stands for the number of ’fences’ used in the problem, each fence consists of a set of observations that all originate from dierent targets. For a dimension of S ˃ the MTT problem becomes NP-hard. As of now no algorithm exists that can solve an NP-hard problem in an optimal manner within a reasonable (polynomial) computation time. However, there are algorithms that can approximate the solution with a realistic computational e ort. To this end an Elitist Genetic Algorithm is implemented to approximately solve the S ˃ MTT problem in an e cient manner. Its complexity is studied and it is found that an approximate solution can be obtained in a polynomial time. With the advent of improved sensors and a heightened interest in the problem of space debris, it is expected that the number of tracked objects will grow by an order of magnitude in the near future. This research aims to provide a method that can treat the correlation and orbit determination problems simultaneously, and is able to e ciently process large data sets with minimal manual intervention.