In this report, various deduplication methods are described in order to assist Vet-AI with the removal of redundant clinical codes from their database system. Their system currently operates whereby clinicians enter codes for diagnoses, leaving open the possibility that multiple clinicians assign the same code to disparate diagnoses. It is also possible that two new entries in the database may be the same diagnosis, with synonymous terminology used. By formulating this as a graph problem, we sought to reduce redundancies by identifying the most probable duplicated codes. A probabilistic model was used, where the probability that two codes are duplicates is a function of a suitable similarity measure (e.g. the Hamming distance). A heuristic method for graph edge pruning is also outlined, based on the application of principles of logical consistency.

This report addresses anti-social behaviour at green spaces in Wales. Using the data available, this report investigates classifying sites and site users. This classification is used to understand specific anti-social behaviours with agent-based modelling. Regression modelling is also used to calculate a site user’s impact on anti-social behaviour, and the scaling behaviour of associated quantities of interest as the number of site visitors increased was examined. Each area of research provides a different lens to understand what is happening at sites across Wales.

This report addresses anti-social behaviour at green spaces in Wales. Using the data available, this report investigates classifying sites and site users. This classification is used to understand specific anti-social behaviours with agent-based modelling. Regression modelling is also used to calculate a site user’s impact on anti-social behaviour, and the scaling behaviour of associated quantities of interest as the number of site visitors increased was examined. Each area of research provides a different lens to understand what is happening at sites across Wales.