The paper demonstrates how existing theory to assess spatial clustering based on second-moment properties of a labelled point process can be adapted to matched case-control studies. The null hypothesis that cases are a random sample from the superposition of cases and controls is replaced by the hypothesis that each case is a random sample from the set consisting of itself and its k matched controls. We compare the proposed test with other tests of spatial clustering, and describe an application to data on childhood diabetes in Yorkshire, England.

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A description of the application of microcomputers to the governing of hydro turbines for electricity generation on the UK public electricity supply system is presented. Experience has been gained using experimental equipment fitted to operational generating plant and a dramatic improvement in response to system frequency disturbances has been demonstrated.