Hazard and risk assessment from Hurricane Ivan (2004) in Grenada using Geographical Information Systems and remote sensing

Hurricanes are destructive storms with strong winds, intense storm surges, and heavy rainfall. The resulting impact from a hurricane can include structural damage to buildings and infrastructure, flooding, and ultimately loss of human life. This paper seeks to identify the impact of Hurricane Ivan on the aected population of Grenada, one of the Caribbean islands. Hurricane Ivan made landfall on 7th September 2004 and resulted in 80% of the population being adversely aected. The methods that were used to model these impacts involved performing hazard and risk assessments using GIS and remote sensing techniques. Spatial analyses were used to create a hazard and a risk map. Hazards were identied initially as those caused by storm surges, severe winds speeds, and flooding events related to Hurricane Ivan. These estimated hazards were then used to create a risk map. An innovative approach was adopted, including the use of hillshading to assess the damage caused by high wind speeds. This paper explains in detail the methodology used and the results produced.

A run-time configurable software architecture for self-managing systems

This paper describes a highly flexible component architecture, primarily designed for automotive control systems, that supports distributed dynamically- configurable context-aware behaviour. The architecture enforces a separation of design-time and run-time concerns, enabling almost all decisions concerning runtime composition and adaptation to be deferred beyond deployment. Dynamic context management contributes to flexibility. The architecture is extensible, and can embed potentially many different self-management decision technologies simultaneously. The mechanism that implements the run-time configuration has been designed to be very robust, automatically and silently handling problems arising from the evaluation of self- management logic and ensuring that in the worst case the dynamic aspects of the system collapse down to static behavior in totally predictable ways.