Abstract
Adaptation of system parameters is acknowledged as a requirement to scalable and dependable distributed systems. Unfortunately, adaptation cannot be effective when provided solely by individual system components as the correct decision is often tied to the composition itself and the system as a whole. In fact, proper adaption is a cross-cutting issue: Diagnostic and feedback operations must target multiple components and do it at different abstraction levels. We address this problem with the SERPENTINE middleware platform. By relying on the industry standard JMX as a service interface, it can monitor and operate on a wide range of distributed middleware and application components. By building on a JMX-enabled OSGi runtime, SERPENTINE is able to control the life-cycle of components themselves. The scriptable stateless server and cascading architecture allow for increased dependability and flexibility.

Abstract

Abstract

Abstract
This work present and demonstrated an applications of artificial neural network approach in optical sensing. The conventional matrix method used in simultaneous measurement of strain and temperature with optical Bragg gratings is compared with artificial neural network approach. The alternative method is proposed for reduced the error.

Abstract
Programming directly with diagrams offers potential advantages such as visual intuitions, identification of errors (debugging), and insight into the dynamics of the algorithm. the purpose of this paper is to put forward one particular graphical formalism, interaction nets, as a candidate for visual programming which has not only all the desired properties that one would expect, but also has other benefits as a language, for instance sharing computation.

Abstract