A supervised classification method for temporal series, even multivariate, is presented. It is based on boosting very simple classifiers: clauses with one literal in the body. The background predicates are based on temporal intervals. Two types of predicates are used: i) relative predicates, such as “increases” and “stays”, and ii) region predicates, such as “always” and “sometime”, which opera...

A supervised classification method for temporal series, even multivariate, is presented. It is based on boosting very simple classifiers: clauses with one literal in the body. The background predicates are based on temporal intervals. Two types of predicates are used: i) relative predicates, such as “increases” and “stays”, and ii) region predicates, such as “always” and “sometime”, which opera...

There has been very little research in distributed predicate detection for faulty, asynchronous environments. In this paper we deene a class of predicates called set decreasing predicates which can be detected in such an environment. We introduce a set of failure detectors called innnitely often accurate detectors which are implementable in asynchronous systems. Based on these failure detectors...