Pro-social themes like empathy and wellbeing are gaining popularity within games to contrast the medium's stigmatised explorations of themes like violence, often to catalyse reflection or even change players' beliefs surrounding complex scenarios. These abstract themes can be classified as a game's "values": elements that are "useful or important" to game designers and their audience. Exploration of values in games was spearheaded by Values at Play, which described how values manifest in games and advocated for their explicit consideration within games and their discourse. Frameworks such as empathy, ethical, and anti-oppressive design all discuss similar values, but present ontological diversity that makes it difficult to collate games and frameworks under the values-conscious design umbrella. Such frameworks also often focus on design approaches and small-scale prototypes but pay less attention to how values influence aspects like publication and play. As such, the present research examines values within each stage of a game's lifecycle: design, development, publication, interaction, and reportage. Doing so provides an understanding of values in multiple game contexts. This provides new perspectives that form the basis of a taxonomy for values in games, which is then presented alongside practical questions for values-conscious designers, publishers, and players to guide its use.

A systematic review of the literature on statistical and machine learning schemes for identifying symptoms of developmental stuttering from audio recordings is reported. Twenty-seven papers met the quality standards that were set. Comparison of results across studies was not possible because training and testing data, model architecture and feature inputs varied across studies. The limitations that were identified for comparison across studies included: no indication of application for the work, data were selected for training and testing models in ways that could lead to biases, studies used different datasets and attempted to locate different symptom types, feature inputs were reported in different ways and there was no standard way of reporting performance statistics. Recommendations were made about how these problems can be addressed in future work on this topic.

REPROOF analytically and experimentally quantifies a Jam Resistant BBC based Uncoordinated Frequency Division Multiplexing (FDM) system that does not require any shared secret.