Finding the direction of disturbance propagation in a chemical process using transfer entropy

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Dynamic test input generation for multiple-fault isolation

Recent work is Causal Reasoning has provided practical techniques for multiple fault diagnosis. These techniques provide a hypothesis/measurement diagnosis cycle. Using probabilistic methods, they choose the best measurements to make, then update fault hypotheses in response. For many applications such as computers and spacecraft, few measurement points may be accessible, or values may change quickly as the system under diagnosis operates. In these cases, a hypothesis/measurement cycle is insufficient. A technique is presented for a hypothesis/test-input/measurement diagnosis cycle. In contrast to generating tests a priori for determining device functionality, it dynamically generates tests in response to current knowledge about fault probabilities. It is shown how the mathematics previously used for measurement specification can be applied to the test input generation process. An example from an efficient implementation called Multi-Purpose Causal (MPC) is presented

Combining causal model and focus group discussions experiences learned from a socio-anthropological research on the differing perceptions of caretakers and health professionals on children's health (Bolivia/Peru)

The paper discusses the utility of constructing causal models in focus groups. This was experienced as a complement to an in-depth ethnographic research on the differing perceptions of caretakers and health professionals on child's growth and development in Peru and Bolivia. The rational, advantages, difficulties and necessary adaptations of combining the two techniques are discussed on the basis of concrete examples. Authors conclude that the building of a causal model in a focus group session can be useful in comparing lay etiologies of diseases as perceived by different categories of caretakers and health professionals and in identifying specific health risks faced by children. Causal model building in a focus group can help renew discussions and participants'interest but its use is only justified when the study concerns the perception of the causality of a given phenomenon