This study suggests that healthy late preterm infants compared with healthy term infants face a greater risk for developmental delay and school-related problems up through the first 5 years of life.
Models of cyber-physical systems are inherently complex since they must represent hardware, software, and the physical environment. Formal verification of these models is often precluded by state explosion. Fortunately, many important properties may only depend upon a relatively small portion of the system being accurately modeled. This paper presents an automatic abstraction methodology that simplifies the model accordingly. Preliminary results on a fault-tolerant temperature sensor are encouraging.
Stochastic model checking is a technique for analyzing systems that possess probabilistic characteristics. However, its scalability is limited as probabilistic models of real-world applications typically have very large or infinite state space. This paper presents a new infinite state CTMC model checker, STAMINA, with improved scalability. It uses a novel state space approximation method to reduce large and possibly infinite state CTMC models to finite state representations that are amenable to existing stochastic model checkers. It is integrated with a new property-guided state expansion approach that improves the analysis accuracy. Demonstration of the tool on several benchmark examples shows promising results in terms of analysis efficiency and accuracy compared with a state-of-theart CTMC model checker that deploys a similar approximation method.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.