The power of linear and affine logic lies in their ability to model state change. However, in a trustless, peer-to-peer setting, it is difficult to force principals to commit to state changes. We show how to solve the peer-to-peer affine commitment problem using a generalization of Bitcoin in which transactions deal in types rather than numbers. This has applications to proof-carrying authorization and mechanically executable contracts. Importantly, our system can be---and is---implemented on top of the existing Bitcoin network, so there is no need to recruit computing power to a new protocol.

We propose a new approach to programming multi-core, relaxed-memory architectures in imperative, portable programming languages. Our memory model is based on explicit, programmer-specified requirements for order of execution and the visibility of writes. The compiler then realizes those requirements in the most efficient manner it can. This is in contrast to existing memory models, which---if they allow programmer control over synchronization at all---are based on inferring the execution and visibility consequences of synchronization operations or annotations in the code.

Presents a model-based approach for visual tracking and eye-in-hand robotic visual servoing. Our approach uses active deformable models to track a rigid or a semi-rigid object in the manipulator's workspace. These deformable models approximate the contour of the object boundary, defined by a set of control points. During tracking, the control points are updated at frame rates by minimizing an energy function involving the relative position of model points, the image data, and the characteristics of figure pixels. When visual servoing is combined with the use of active deformable models, movement of the manipulator can compensate for translations and deformations of the object's image. Experimental results are presented.