3rd Edition of “Introduction to Discrete Event Systems”

The Third Edition of “Introduction to Discrete Event Systems” was published in November 2021. The book, originally published in 1999, is a comprehensive introduction to the field of discrete event systems, offering a breadth of coverage that makes the material accessible to readers of varied backgrounds. The book emphasizes a unified modeling framework that transcends specific application areas, linking the following topics in a coherent manner: language and automata theory, supervisory control, Petri net theory, Markov chains and queueing theory, discrete-event simulation, and concurrent estimation techniques. The third edition is a “superset” of the second one, with new material based on the teaching of discrete event systems courses by the two co-authors at Boston University and at the University of Michigan. They reflect active research trends and new topics in discrete event systems since the publication of the second edition, as more thorough coverage of existing topics.

More info: https://link.springer.com/book/10.1007/978-3-030-72274-6#about

NEXTCAR Self-Driving car in action

Congestion Maps Platform Made Public

$900k NSF Grant to Predict Heart Disease, Diabetes Using Machine Learning

Researchers from the College of Engineering and Boston Medical Center (BMC) will use a three-year, $900,000 grant from the National Science Foundation to develop and pilot a health informatics system to predict patients at risk of heart disease or diabetes, and enable early intervention and personalized treatment. Click here to read more.

Robotics and AI Event

The Center for Information and Systems Engineering (CISE) partnered with Greg Woolf, CEO of Coalesce.Info and moderator of The Cognitive Computing Group of Boston, to host a community evening focused on Robotics & AI research at Boston University, on February 28, 2017.

Click here to read more.

BBC News – Tomorrow’s cities

Real-time alterations to the red-and-green cycle can cut congestion time by up to 50% and make a city drive much more agreeable, says Prof Christos Cassandras, a smart cities expert from Boston University, who helped develop the system.

“We have all been in the situation where we keep getting stuck behind red light after red light, so imagine if we can control the traffic lights or even the car to alert drivers that if they accelerate a little bit they will make that green light,” he says.

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