Evaluating forensic biology results given source level propositions

The evaluation of forensic evidence can occur at any level within the hierarchy of propositions depending on the question being asked and the amount and type of information that is taken into account within the evaluation. Commonly DNA evidence is reported given propositions that deal with the sub-source level in the hierarchy, which deals only with the possibility that a nominated individual is a source of DNA in a trace (or contributor to the DNA in the case of a mixed DNA trace). We explore the use of information obtained from examinations, presumptive and discriminating tests for body fluids, DNA concentrations and some case circumstances within a Bayesian network in order to provide assistance to the Courts that have to consider propositions at source level. We use a scenario in which the presence of blood is of interest as an exemplar and consider how DNA profiling results and the potential for laboratory error can be taken into account. We finish with examples of how the results of these reports could be presented in court using either numerical values or verbal descriptions of the results.

Using active learning for monitoring networks design: The example of wind power plants sites evaluation

Locating new wind farms is of crucial importance for energy policies of the next decade. To select the new location, an accurate picture of the wind fields is necessary. However, characterizing wind fields is a difficult task, since the phenomenon is highly nonlinear and related to complex topographical features. In this paper, we propose both a nonparametric model to estimate wind speed at different time instants and a procedure to discover underrepresented topographic conditions, where new measuring stations could be added. Compared to space filling techniques, this last approach privileges optimization of the output space, thus locating new potential measuring sites through the uncertainty of the model itself.