Large scale annotated corpora are prerequisite to developing high-performance semantic role labeling systems. Unfortunately, such corpora are expensive to produce, limited in size, and may not be representative. Our work aims to reduce the annotation effort involved in creating resources for semantic role labeling via semi-supervised learning. Our algorithm augments a small number of manually l...

Arjmand Samuel, Hammad Haseeb, Arif Ghafoor and Elisa Bertino Abstract Cyber Physical Systems (CPS) are complex systems that operate in a dynamic environment where security characteristics of contexts are unique, and uniform access to secure resources anywhere anytime to mobile entities poses daunting challenges. To capture context parameters such as location and time in an access control polic...

Based on a nonlinear hybrid dynamic systems approach a new paradigm for goal-oriented dynamic cooperation of multiple robots is investigated within the RoboCup scenario. The time dependent hybrid state of the whole system consists of discrete (roles, actions) and continuous (position, orientation, velocity) state variables of all mobile robots and objects involved. The evolution in time of the ...

In order to solve the system optimum dynamic traffic assignment problem, the whole link model with physical queue is used to formulate the single destination system optimum dynamic traffic assignment problem as a mixed linear program. A relationship between the cumulative curves and the wave speed presented by Newell (1993) is used to present a dynamic network model in considering spillback que...

We study a dynamic traffic assignment model, where agents base their instantaneous routing decisions on real-time delay predictions. formulate mathematically concise model and derive properties of the predictors that ensure prediction equilibrium exists. demonstrate versatility our framework by showing it subsumes well-known full information models, in addition to admitting further realistic as...