Defence planning: The uncertainty factor

Failures to predict the course of future conflicts are historically even more numerous than failures to predict the weapons with which they would be fought. Defence has to do with a two-sided activity of conflict and confrontation and in that there is a built-in minimum 50 per cent failure rate. Lack of opportunity, for continuous or even frequent comparison of prediction with reality compounds the defence planner's difficulties. Political decisions on defence purport to be derived from military predictions among other factors, but for practical purposes, have to be regarded as a major element of unpredictability in their own right. Bred in this tradition, the defence planner puts a bold front on things, dreams up scenarios, and keeps his fingers crossed. Knowing that, if he has got them wrong, the ships, tanks and aircraft, will come in useful in the conflicts and confrontations ahead.     

Addressing the impact of trauma before diagnosing mental illness in child welfare

Congress set requirements for child welfare agencies to respond to emotional trauma associated with child maltreatment and removal. In meeting these requirements, agencies should develop policies that address child trauma. To assist in policy development, this study analyzes more than 14,000 clinical assessments from child welfare in Illinois. Based on the analysis, the study recommends child welfare agencies adopt policies requiring that (1) mental health screenings and assessments of all youth in child welfare include measures of traumatic events and trauma-related symptoms; (2) evidence-based, trauma-focused treatment begin when a youth in child welfare demonstrates a trauma-related symptom; and (3) a clinician not diagnose a youth in child welfare with a mental illness without first addressing the impact of trauma. The study also raises the issue of treatment reimbursement based on diagnosis.     

Quantification of symmetry for functional data with application to equine lameness classification

This paper presents a study on symmetry of repeated bi-phased data signals, in particular, on quantification of the deviation between the two parts of the signal. Three symmetry scores are defined using functional data techniques such as smoothing and registration. One score is related to the L ₂-distance between the two parts of the signal, whereas the other two are constructed to specifically measure differences in amplitude and phase. Moreover, symmetry scores based on functional principal component analysis (PCA) are examined. The scores are applied to acceleration signals from a study on equine gait. The scores turn out to be highly associated with lameness, and their applicability for lameness quantification and detection is investigated. Four classification approaches turn out to give similar results. The scores describing amplitude and phase variation turn out to outperform the PCA scores when it comes to the classification of lameness.