Investigating the impacts of training data set length (T) and the aggregation unit size (M) on the accuracy of the self-exciting point process (SEPP) hotspot method

This study examines the impacts of two variables; the training data lengths (T) and the aggregation unit sizes (M); on the accuracy of the self-exciting point process (SEPP) model during crime prediction. A case study of three crime types in the South Chicago area is presented, in which different combinations of values of T and M are used for 100 daily consecutive crime predictions. The results showed two important points regarding the SEPP model: first is that large values of T are likely to improve the accuracy of the SEPP model and second is that, a small aggregation unit, such as a 50m x 50m grid, is better in terms of capturing local repeat and near-repeat patterns of crimes

Runtime Distributions and Criteria for Restarts

Randomized algorithms sometimes employ a restart strategy. After a certain number of steps, the current computation is aborted and restarted with a new, independent random seed. In some cases, this results in an improved overall expected runtime. This work introduces properties of the underlying runtime distribution which determine whether restarts are advantageous. The most commonly used probability distributions admit the use of a scale and a location parameter. Location parameters shift the density function to the right, while scale parameters affect the spread of the distribution. It is shown that for all distributions scale parameters do not influence the usefulness of restarts and that location parameters only have a limited influence. This result simplifies the analysis of the usefulness of restarts. The most important runtime probability distributions are the log-normal, the Weibull, and the Pareto distribution. In this work, these distributions are analyzed for the usefulness of restarts. Secondly, a condition for the optimal restart time (if it exists) is provided. The log-normal, the Weibull, and the generalized Pareto distribution are analyzed in this respect. Moreover, it is shown that the optimal restart time is also not influenced by scale parameters and that the influence of location parameters is only linear

A dynamic microsimulation framework for generating synthetic spatiotemporal crime patterns

The significance of synthetic crime datasets in criminological research cannot be underestimated, as real crime datasets are usually unavailable in many policing jurisdictions, due to reasons such as privacy concerns and the lack of shareable data formats. This study introduces a dynamic microsimulation framework by which a specified spatiotemporal crime pattern can be synthesised. A case study presented compares a real crime dataset with the synthesised datasets, and found certain spatiotemporal similarities between them. The developed model has the potential for wider applications in criminology, given some identified areas of improvement

A Comparison of Intermittent and Continuous Exercise Bouts at Different Intensities on Appetite and Postprandial Metabolic Responses in Healthy Men

Exercise intensity affects many potential postprandial responses, but there is limited information on the influence of exercise modality. Therefore, the aim of this study was to investigate if the nature of exercise at two different intensities would affect gastric emptying rate (GER), appetite and metabolic responses following ingestion of a semi-solid meal. Twelve healthy men completed, in a random order, four 60-min cycles at 60% VO2peak (MOD), 40% VO2peak (LOW) and in a continuous (CON) or intermittent (INT) manner. INT consisted of 20 × 1-min exercise bouts with 2-min rest breaks. INT and CON were matched for total work output at each intensity. GER of the post-exercise meal was measured for 2 h using the 13C-breath method. Blood glucose, substrate utilisation and appetite ratings were measured at regular intervals throughout all trials and 24-h energy intake (EI) post-trials was assessed. GER-Delta over Baseline (DOB) was lower (p 0.05). 24-h post-trial EI was similar between LOW-CON vs. LOW-INT (p > 0.05), although MOD-INT vs. MOD-CON 3500 ± 1419 vs. 2556 ± 989 kCal: p < 0.001 was elevated. In summary, MOD-INT exercise delays GER without stimulating perceived appetite in the 2 h period after meal ingestion, although EI was greater in the 24-h post-trial