The Great Transition:Climate, disease and society in the late-medieval world

In the fourteenth century the Old World witnessed a series of profound and abrupt changes in the trajectory of long-established historical trends. Trans-continental networks of exchange fractured and an era of economic contraction and demographic decline dawned from which Latin Christendom would not begin to emerge until its voyages of discovery at the end of the fifteenth century. In a major new study of this 'Great Transition', assessment is made of the contributions of commercial recession, war, climate change,and eruption of the Black Death to a far-reaching reversal of fortunes which spared no part of Eurasia. A wealth of new historical, palaeoecological and biological evidence are synthesised, including estimates of national income, reconstructions of past climates. and genetic analysis of DNA extracted from the teeth of plague victims, to provide a fresh account of the creation, collapse and realignment of western Europe's late-medieval commercial economy.

Analysing spatio-temporal change by use of national historical Geographical Information Systems: Population change during and after the Great Irish Famine

Several countries have made large investments in building historical Geographical Information Systems (GIS) databases containing census and other quantitative statistics over long periods of time. Making good use of these databases requires approaches that explore spatial and temporal change.

An Extended Implementation of the Great Deluge Algorithm for Course Timetabling

Course Scheduling consists of assigning lecture events to a limited set of specific timeslots and rooms. The objective is to satisfy as many soft constraints as possible, while maintaining a feasible solution timetable. The most successful techniques to date require a compute-intensive examination of the solution neighbourhood to direct searches to an optimum solution. Although they may require fewer neighbourhood moves than more exhaustive techniques to gain comparable results, they can take considerably longer to achieve success. This paper introduces an extended version of the Great Deluge Algorithm for the Course Timetabling problem which, while avoiding the problem of getting trapped in local optima, uses simple Neighbourhood search heuristics to obtain solutions in a relatively short amount of time. The paper presents results based on a standard set of benchmark datasets, beating over half of the currently published best results with in some cases up to 60% of an improvement.