Improved prediction of hiking speeds using a data driven approach.

Hikers and hillwalkers typically use the gradient in the direction of travel (walking slope) as the main variable in established methods for predicting walking time (via the walking speed) along a route. Research into fell-running has suggested further variables which may improve speed algorithms in this context; the gradient of the terrain (hill slope) and the level of terrain obstruction. Recent improvements in data availability, as well as widespread use of GPS tracking now make it possible to explore these variables in a walking speed model at a sufficient scale to test statistical significance.

A multi-agent-based, semantic-driven system for decision support in epidemic management.

Issues in epidemiology are truly multidisciplinary, requiring knowledge from diverse disciplines such as sociology, medicine, biology, geography and information science. Such inherent complexity has led to a challenge in developing decision support systems for epidemic information management, especially when data are from heterogeneous origins. In order to achieve a solution, an integrative framework is proposed.