Static timing analyzers need to know the minimum and maximum number of iterations associated with each loop in a real-time program so accurate timing predictions can be obtained. ...
Abstract-- In this paper a new method for training singlemodel and multi-model fuzzy classifiers incrementally and adaptively is proposed, which is called FLEXFIS-Class. The evolvi...
The desire to predict power generation at a given point in time is essential to power scheduling, energy trading, and availability modeling. The research conducted within is conce...
Statistical language models estimate the probability of a word occurring in a given context. The most common language models rely on a discrete enumeration of predictive contexts ...
John Blitzer, Kilian Q. Weinberger, Lawrence K. Sa...
This paper develops a methodology for analyzing and predicting the impact category of malicious code, particularly email worms. The current paper develops two frameworks to classi...
Insu Park, Raj Sharman, H. Raghav Rao, Shambhu J. ...