Web Services are software services that can be advertised by providers and deployed by customers using Web technologies. This concept is currently carried further to address Web service choreography. Choreography refers to the composition of individual services to services processes that can communicate and interact with another.We propose a formal ontology framework for these Web service processes that supports the description, matching, and composition through logic reasoning techniques. The Semantic Web, based on a description logic-based knowledge representation and reasoning framework, provides the foundations. Integrating aspects from modal logics and process calculi into this framework will prove essential.

It is well known that under noisy conditions we can hear speech much more clearly when we read the speaker's lips. This sug(cid:173) gests the utility of audio-visual information for the task of speech enhancement. We propose a method to exploit audio-visual cues to enable speech separation under non-stationary noise and with a single microphone. We revise and extend HMM-based speech enhancement techniques, in which signal and noise models are fac(cid:173) tori ally combined, to incorporate visual lip information and em(cid:173) ploy novel signal HMMs in which the dynamics of narrow-band and wide band components are factorial. We avoid the combina(cid:173) torial explosion in the factorial model by using a simple approxi(cid:173) mate inference technique to quickly estimate the clean signals in a mixture. We present a preliminary evaluation of this approach using a small-vocabulary audio-visual database, showing promising improvements in machine intelligibility for speech enhanced using audio and visual information.

Activity-dependent plasticity appears to play an important role in the modification of neurons and neural circuits that occurs during development and learning. Plasticity is also essential for the maintenance of stable patterns of activity in the face of variable environmental and internal conditions. Previous theoretical and experimental results suggest that neurons stabilize their activity by altering the number or characteristics of ion channels to regulate their intrinsic electrical properties. We present both experimental and modeling evidence to show that activity-dependent regulation of conductances, operating at the level of individual neurons, can also stabilize network activity. These results indicate that the stomatogastric ganglion of the crab can generate a characteristic rhythmic pattern of activity in two fundamentally different modes of operation. In one mode, the rhythm is strictly conditional on the presence of neuromodulatory afferents from adjacent ganglia. In the other, it is independent of neuromodulatory input but relies on newly developed intrinsic properties of the component neurons.

Our earlier article, “The Dynamics of Discrete-Time Computation, with Application to Recurrent Neural Networks and Finite State Machine Extraction” (Casey, 1996), contains a corollary that shows that finite dimensional recurrent neural networks with noise in their state variables that perform algorithmic computations can perform only finite state machine computations. The proof of the corollary is technically incorrect. The problem resulted from the fact that the proof of the theorem on which the corollary is based was more general than the statement of the theorem, and it was the contents of the proof rather than the statement that were used to prove the corollary. In this note, we state the theorem in the necessary generality and then give the corrected proof of the corollary.