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Motorway incidents are frequent & varied in nature. Incident management on motorways is critical for both driver safety & road network operation. The expected duration of an incident is a key parameter in the decision-making process for control room operators, however, the actual duration for which an incident will impact the network is never known with true certainty. This paper presents a study which compares the ability of different machine learning algorithms to estimate the duration of motorway incidents on Ireland's M50 motorway, using an extensive historical incident database. Results show that the support vector machine has the best performance in most cases, but a different method may need to be used to improve accuracy in some situations. Results highlight the main challenges in accurately forecasting incident durations in real time & recommendations are made for improving prediction accuracy through systematic recording of various additional incident details. [ABSTRACT FROM AUTHOR]

As locations of a distinctively Catholic faith, Mass Rocks are important historical, ritual and counter-cultural sites that present a tangible connection to Ireland's rich heritage for contemporary society. Recent authors have begun to fill a gap in published literature yet few go beyond traditional assumptions. This paper offers a more contemporary approach to the study of Mass Rocks based on extensive field research in county Cork. It argues for the introduction of new and innovative classifications that expand the accepted archaeological definition and proposes a set of criteria for the more robust verification of potential sites. [ABSTRACT FROM AUTHOR]