Modelling and analysing user views of telecommunications services

User views of calls are modelled by behaviour trees, which are synchronised to form a network of users. High level presentations of the models are given using process algebra and an explicit theory of features, including precedences. These precedences abstractly encapsulate the possible state spaces which result from different combinations of features. The high level presentation supports incremental development of features and testing and experimentation through animation. Interactions which are not detected during the experimentation phase may be found through static analysis of the high level presentation, through dynamic analysis of the under-lying low level transition system, and through verification of temporal properties through model-checking. In each case, interactions are resolved through manipulation of the feature precedences

The applications of deep neural networks to sdBV classification

With several new large-scale surveys on the horizon, including LSST, TESS, ZTF, and Evryscope, faster and more accurate analysis methods will be required to adequately process the enormous amount of data produced. Deep learning, used in industry for years now, allows for advanced feature detection in minimally prepared datasets at very high speeds; however, despite the advantages of this method, its application to astrophysics has not yet been extensively explored. This dearth may be due to a lack of training data available to researchers. Here we generate synthetic data loosely mimicking the properties of acoustic mode pulsating stars and we show that two separate paradigms of deep learning - the Artificial Neural Network And the Convolutional Neural Network - can both be used to classify this synthetic data effectively. And that additionally this classification can be performed at relatively high levels of accuracy with minimal time spent adjusting network hyperparameters.Comment: 12 pages, 10 figures, originally presented at sdOB

Update on celiac disease

Celiac disease is a chronic autoimmune process that is modulated by an environmental trigger, namely glladin; a part of gluten which is present in wheat, barley and rye, Celiac disease is clearly increasing in prevalence worldwide and with easier access to screening tools the notion that it is a disease of Western society is in increasingly being challenged, We have also seen a broader gamut of symptoms and disease conditions that are associated with celiac disease to the extent that the nomenclature of classic and non-classic manifestations seems redundant. The increased recognition in prevalence is poorly understood but seems to also reflect a true increase in incidence, These observations supported by constantly improving diagnostic techniques; including serologic, genetic testing and endoscopic moralities has frustratingly not been paralleled in any measure by any breakthrough in managementpeer-reviewe