Abstract
Today's dynamic industrial process simulation problems require systematically new methodologies and sophisticated computational tools. Such processes involve frequently discontinuities, environment structures changes and entities with high functional levels. Furthermore, there are cases where we must integrate intelligent techniques and negotiation protocols. These characteristics are crucial in distributed problems that require resource balance, low cost distribution plans, and stock optimization. In order to analyse the application of a distributed object-oriented simulation system we selected, as a case study, a gas distribution network in which we find all the referred characteristics. This paper presents a brief description of the simulation scenario, the overall system's structure, the intelligent negotiation protocol used by system's objects and the concurrent programming techniques to implement it.

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

Abstract
A two-level data transformation consists of a type-level transformation of a data format coupled with value-level transformations of data instances corresponding to that format. Examples of two-level data transformations include XML schema evolution coupled with document migration, and data mappings used for interoperability and persistence. We provide a formal treatment of two-level data transformations that is type-safe in the sense that the well-formedness of the value-level transformations with respect to the type-level transformation is guarded by a strong type system. We rely on various techniques for generic functional programming to implement the formalization in Haskell. The formalization addresses various two-level transformation scenarios, covering fully automated as well as user-driven transformations, and allowing transformations that are information-preserving or not. In each case, two-level transformations are disciplined by one-step transformation rules and type-level transformations induce value-level transformations. We demonstrate an example hierarchical-relational mapping and subsequent migration of relational data induced by hierarchical format evolution.

Abstract
This paper presents a distributed algorithm to simultaneously compute the diameter, radius and node eccentricity in all nodes of a synchronous network. Such topological information may be useful as input to configure other algorithms. Previous approaches have been modular, progressing in sequential phases using building blocks such as BFS tree construction, thus incurring longer executions than strictly required. We present an algorithm that, by timely propagation of available estimations, achieves a faster convergence to the correct values. We show local criteria for detecting convergence in each node. The algorithm avoids the creation of BFS trees and simply manipulates sets of node ids and hop counts. For the worst scenario of variable start times, each node i with eccentricity ecc(i) can compute: the node eccentricity in diam(G)+ecc(i)+2 rounds; the diameter in 2 diam(G)+ecc(i)+ 2 rounds; and the radius in diam(G) + ecc(i) + 2 radius(G) rounds.