Data mining and simulation: a grey relationship demonstration

Fuzzy data has grown to be an important factor in data mining. Whenever uncertainty exists, simulation can be used as a model. Simulation is very flexible, although it can involve significant levels of computation. This article discusses fuzzy decision-making using the grey related analysis method. Fuzzy models are expected to better reflect decision-making uncertainty, at some cost in accuracy relative to crisp models. Monte Carlo simulation is used to incorporate experimental levels of uncertainty into the data and to measure the impact of fuzzy decision tree models using categorical data. Results are compared with decision tree models based on crisp continuous data.

An analysis of relational complexity in an air traffic control conflict detection task

Theoretical analyses of air traffic complexity were carried out using the Method for the Analysis of Relational Complexity. Twenty-two air traffic controllers examined static air traffic displays and were required to detect and resolve conflicts. Objective measures of performance included conflict detection time and accuracy. Subjective perceptions of mental workload were assessed by a complexity-sorting task and subjective ratings of the difficulty of different aspects of the task. A metric quantifying the complexity of pair-wise relations among aircraft was able to account for a substantial portion of the variance in the perceived complexity and difficulty of conflict detection problems, as well as reaction time. Other variables that influenced performance included the mean minimum separation between aircraft pairs and the amount of time that aircraft spent in conflict.

Isolation of polymorphic tetranucleotide microsatellite markers for the grey-headed robin (Poecilodryas albispecularis)

We isolated 12 polymorphic microsatellite markers for the grey-headed robin Poecilodryas albispecularis from genomic libraries enriched for (AAGG)n and (AACC)n repetitive elements and characterized them in 12 individuals. The number of alleles ranges from three to nine per locus with the observed heterozygosity ranging from 0.33 to 0.90. These markers will be useful for analysis of questions concerning population genetic structure and testing models of speciation.

MHC promoter polymorphism in grey wolves and domestic dogs

A functional immune system requires a tight control over major histocompatibility complex (MHC) gene transcription, as the abnormal MHC expression patterns of severe immunodeficiency and autoimmune diseases demonstrate. Although the regulation of MHC expression has been well documented in humans and mice, little is known in other species. In this study, we detail the level of polymorphism in wolf and dog MHC gene promoters. The promoter regions of the DRB, DQA and DQB locus were sequenced in 90 wolves and 90 dogs. The level of polymorphism was high in the DQB promoters, with variation found within functionally relevant regions, including binding sites for transcription factors. Clear associations between DQB promoters and exon 2 alleles were noted in wolves, indicating strong linkage disequilibrium in this region. Low levels of polymorphism were found within the DRB and DQA promoter regions. However, a variable site was identified within the T box, a TNF-alpha response element, of the DQA promoter. Furthermore, we identified a previously unrecognised 18-base-pair deletion within exon 1 of the DQB locus.