Zoekresultaten

Impact of Dataset Characteristics on Optimal Model Selection

In the rapidly evolving field of Machine Learning , selecting the most appropriate model for a given dataset is crucial. Understanding the characteristics of a dataset can significantly influence the outcomes of predictive modeling efforts, making the study of the properties of the dataset an essential component of data science. This study investigates the possibilities of using simulated human data for personalized applications, specifically for testing clustering approaches. In particular, the study focuses on the relationship between dataset characteristics and the selection of the optimal classification model for clusters of datasets. The results of this study provide critical insights for researchers and practitioners in machine learning, emphasizing the importance of dataset characteristics and variability in building and selecting robust models for diverse data conditions. The use of human simulation data provide valuable insights but requires further refinement to capture the full variability of real-world conditions.

Adverse effects of anxiety on attentional control differ as a function of experience

Effects of reflex-based self-defence training on police performance in simulated high-pressure arrest situations

We investigated the effects of reflex-based self-defence training on police performance in simulated high-pressure arrest situations. Police officers received this training as well as a regular police arrest and self-defence skills training (control training) in a crossover design. Officers' performance was tested on several variables in six reality-based scenarios before and after each training intervention. Results showed improved performance after the reflex-based training, while there was no such effect of the regular police training. Improved performance could be attributed to better communication, situational awareness (scanning area, alertness), assertiveness, resolution, proportionality, control and converting primary responses into tactical movements. As officers trained complete violent situations (and not just physical skills), they learned to use their actions before physical contact for de-escalation but also for anticipation on possible attacks. Furthermore, they learned to respond against attacks with skills based on their primary reflexes. The results of this study seem to suggest that reflex-based self-defence training better prepares officers for performing in high-pressure arrest situations than the current form of police arrest and self-defence skills training. Practitioner Summary: Police officers' performance in high-pressure arrest situations improved after a reflex-based self-defence training, while there was no such effect of a regular police training. As officers learned to anticipate on possible attacks and to respond with skills based on their primary reflexes, they were better able to perform effectively.