An analysis of pilot error-related aircraft accidents

A multidisciplinary team approach to pilot error-related U.S. air carrier jet aircraft accident investigation records successfully reclaimed hidden human error information not shown in statistical studies. New analytic techniques were developed and applied to the data to discover and identify multiple elements of commonality and shared characteristics within this group of accidents. Three techniques of analysis were used: Critical element analysis, which demonstrated the importance of a subjective qualitative approach to raw accident data and surfaced information heretofore unavailable. Cluster analysis, which was an exploratory research tool that will lead to increased understanding and improved organization of facts, the discovery of new meaning in large data sets, and the generation of explanatory hypotheses. Pattern recognition, by which accidents can be categorized by pattern conformity after critical element identification by cluster analysis

Branch-and-Bound Algorithms for the Test Cover Problem

In the test cover problem a set of items is given together with a collection of subsets of the items, called tests. A smallest subcollection of tests is to be selected such that for every pair of items there is a test in the selection that contains exactly one of the two items. This problem is NP-hard in general. It has important applications in biology, pharmacy, and the medical sciences, as well as in coding theory. We develop a variety of branch-and-bound algorithms to solve the problem to optimality. The variety is in the definition of the branching rules and the lower bounds to prune the search tree. Our algorithms are compared both theoretically and empirically