Abstract
Parallel logic programming systems are sophisticated examples of symbolic computing systems. They address problems such as dynamic memory allocation, scheduling irregular execution patterns, and managing different types of implicit parallelism. Most parallel logic programming systems have been developed for bus-based shared-memory architectures. The complexity of parallel logic programming systems and the large amount of data they process raises the question of whether logic programming systems can still obtain good performance on scalable architectures, such as distributed shared-memory systems. In this work we use execution-driven simulation to investigate the access patterns and caching behaviour exhibited by a parallel logic programming system, Andorra-I. We show that the system obtains reasonable performance, but that it does not scale well. By studying the behaviour of the major data structures in Andorra-I in detail, we conclude that this result is largely a consequence of the scheduling and work manipulation implementation used in the system. We also show that the Andorra-I's data structures exhibit widely-varying memory access patterns and caching behaviour, which not only depend on the number of processors, but also on the amount and type of parallelism available in the application program. Some of these data structures clearly favour invalidate-based cache coherence protocols, while others favour update-based protocols. Since most of Andorra-I's data structures are common to other parallel logic programming systems, we believe that these systems can greatly benefit from flexible coherence schemes where either the compiler can specify the protocol to be used for each data structure or the protocol can adapt to varying memory access patterns.

Abstract
We report the experimental observation of up-conversion in an integrated silica-on-silicon waveguide. Blue light at 455 nm and 475 nm was observed. In addition to the strong blue emission near infrared (similar to 800 nm), visible (648 nm) and UV (366 nm) lines were also detected. We investigated the excitation mechanisms by using different pumping wavelengths. (C) 1997 Elsevier Science B.V.

Abstract

Abstract
Load distribution is a well known critical problem in every distributed system. From operating systems to agent oriented applications it is not difficult to find cases where processing nodes are overloaded when, at the same time, other peers present low levels of activity. In agent oriented applications, where the appeal to cooperation is almost a constant event, these unbalanced situations may generate serious cases of contention, deadlock or simply large idle times. The implementation of load distribution strategies in a distributed system may help significantly to improve its overall performance and reduce effectively such undesirable situations. In order to study the effects of different load distribution policies in agent based applications a generic load distribution simulation system was design and implemented. The system allows the specification of multiorganisational distributed systems with dynamic load patterns. Its main characteristics and functionalities are presented in this paper.

Abstract
This paper presents and discusses the design and the development of a pattern recognition agent based on neural networks. This agent is part of an intelligent navigation system, providing it with the necessary vision abilities so that it can be placed on a strange environment in order to explore and recognise its structures and specificities. Although similar, the properties of the recognised objects change through time and according to each specific environment. The flexibility required by such recognition process was implemented by several pattern recognition agents. Each agent is based on a neural network and can be trained on-line by a parallel training algorithm to allow an effective real time utilisation.

Abstract
The control of fermentation is very important in order to ensure a sustained level of wine quality year after year. Usually wine fermentation is carried out at a constant temperature. This fact is due mainly to traditional reasons. Nevertheless the results year after year and from region to region may be very different due to large variations in must characteristics. A more complex control is needed to overcome this fluctuations. Recent works have introduced some innovation but still have some empirical characteristics and can not control the duration of fermentation. In order to predict the behaviour of the fermentation, a reasonably accurate mathematical model is required. Unfortunately mathematical models for wine fermentation are scarce, particularly for wine batch fermentation. In this work we develop a mathematical fermentation model and an industrial tank thermal model. A new control strategy is proposed: Relative density control instead of temperature control. A reference model is developed and we try to tune a PID controller to the process. The need of more complex controllers such as predictive controllers is addressed.