Supporting public availability and accessibility with Elvin: experiences and reflections.

We provide a retrospective account of how a generic event notification service called Elvin and a suite of simple client applications: CoffeeBiff, Tickertape and Tickerchat, came to be used within our organisation to support awareness and interaction. After overviewing Elvin and its clients, we outline various experiences from data collated across two studies where Elvin and its clients have been used to augment the workaday world to support interaction, to make digital actions visible, to make physical actions available beyond the location of action, and to support content and socially based information filtering. We suggest there are both functional and technical reasons for why Elvin works for enabling awareness and interaction. Functionally, it provides a way to produce, gather and redistribute information from everyday activities (via Elvin) and to give that information a perceptible form (via the various clients) that can be publicly available and accessible as a resource for awareness. The integration of lightweight chat facilities with these information sources enables awareness to easily flow into interaction, starting to re-connect bodies to actions, and starting to approximate the easy flow of interaction that happens when we are co-located. Technically, the conceptual simplicity of the Elvin notification, the wide availability of its APIs, and the generic functionality of its clients, especially Tickertape, have made the use of the service appealing to developers and users for a wide range of uses

New modification of the hestenes-stiefel with strong wolfe line search

. The method of the nonlinear conjugate gradient is widely used in solving large-scale unconstrained optimization since been proven in solving optimization problems without using large memory storage. In this paper, we proposed a new modification of the Hestenes-Stiefel conjugate gradient parameter that fulfils the condition of sufficient descent using a strong Wolfe-Powell line search. Besides, the conjugate gradient method with the proposed conjugate gradient also guarantees low computation of iteration and CPU time by comparing with other classical conjugate gradient parameters. Numerical results have shown that the conjugate gradient method with the proposed conjugate gradient parameter performed better than the conjugate gradient method with other classical conjugate gradient parameters

Pushbroom Stereo for High-Speed Navigation in Cluttered Environments

We present a novel stereo vision algorithm that is capable of obstacle detection on a mobile-CPU processor at 120 frames per second. Our system performs a subset of standard block-matching stereo processing, searching only for obstacles at a single depth. By using an onboard IMU and state-estimator, we can recover the position of obstacles at all other depths, building and updating a full depth-map at framerate. Here, we describe both the algorithm and our implementation on a high-speed, small UAV, flying at over 20 MPH (9 m/s) close to obstacles. The system requires no external sensing or computation and is, to the best of our knowledge, the first high-framerate stereo detection system running onboard a small UAV