Establishment of a Cross-European Field Site Network in the ALARM Project for Assessing Large-Scale Changes in Biodiversity

The field site network (FSN) plays a central role in conducting joint research within all Assessing Large-scale Risks for biodiversity with tested Methods (ALARM) modules and provides a mechanism for integrating research on different topics in ALARM on the same site for measuring multiple impacts on biodiversity. The network covers most European climates and biogeographic regions, from Mediterranean through central European and boreal to subarctic. The project links databases with the European-wide field site network FSN, including geographic information system (GIS)-based information to characterise the test location for ALARM researchers for joint on-site research. Maps are provided in a standardised way and merged with other site-specific information. The application of GIS for these field sites and the information management promotes the use of the FSN for research and to disseminate the results. We conclude that ALARM FSN sites together with other research sites in Europe jointly could be used as a future backbone for research proposals

Data-mining chess databases

This is a report on the data-mining of two chess databases, the objective being to compare their sub-7-man content with perfect play as documented in Nalimov endgame tables. Van der Heijden’s ENDGAME STUDY DATABASE IV is a definitive collection of 76,132 studies in which White should have an essentially unique route to the stipulated goal. Chessbase’s BIG DATABASE 2010 holds some 4.5 million games. Insight gained into both database content and data-mining has led to some delightful surprises and created a further agenda.

Neural network feature maps for Chinese phonemes

It has been shown through a number of experiments that neural networks can be used for a phonetic typewriter. Algorithms can be looked on as producing self-organizing feature maps which correspond to phonemes. In the Chinese language the utterance of a Chinese character consists of a very simple string of Chinese phonemes. With this as a starting point, a neural network feature map for Chinese phonemes can be built up. In this paper, feature map structures for Chinese phonemes are discussed and tested. This research on a Chinese phonetic feature map is important both for Chinese speech recognition and for building a Chinese phonetic typewriter.

Using self-organising feature maps for the control of artificial organisms

Variations on the standard Kohonen feature map can enable an ordering of the map state space by using only a limited subset of the complete input vector. Also it is possible to employ merely a local adaptation procedure to order the map, rather than having to rely on global variables and objectives. Such variations have been included as part of a hybrid learning system (HLS) which has arisen out of a genetic-based classifier system. In the paper a description of the modified feature map is given, which constitutes the HLSs long term memory, and results in the control of a simple maze running task are presented, thereby demonstrating the value of goal related feedback within the overall network.

Implications for DNA identification arising from an analysis of Australian forensic databases

Previous analyses of Australian samples have suggested that populations of the same broad racial group (Caucasian, Asian, Aboriginal) tend to be genetically similar across states. This suggests that a single national Australian database for each such group may be feasible, which would greatly facilitate casework. We have investigated samples drawn from each of these groups in different Australian states, and have quantified the genetic homogeneity across states within each racial group in terms of the "coancestry coefficient" F(ST). In accord with earlier results, we find that F(ST) values, as estimated from these data, are very small for Caucasians and Asians, usually <0.5%. We find that "declared" Aborigines (which includes many with partly Aboriginal genetic heritage) are also genetically similar across states, although they display some differentiation from a "pure" Aboriginal population (almost entirely of Aboriginal genetic heritage).

Quantifying chaos: a tale of two maps

In many applications, there is a desire to determine if the dynamics of interest are chaotic or not. Since positive Lyapunov exponents are a signature for chaos, they are often used to determine this. Reliable estimates of Lyapunov exponents should demonstrate evidence of convergence; but literature abounds in which this evidence lacks. This paper presents two maps through which it highlights the importance of providing evidence of convergence of Lyapunov exponent estimates. The results suggest cautious conclusions when confronted with real data. Moreover, the maps are interesting in their own right.