Abstract
This paper provides a description of a new approach for steady state security evaluation, using fuzzy nearest prototype classifiers, The basic method has an off-line training phase, used to design the fast classifiers for on-line purposes, allowing more than the two traditional security classes. A battery of these fuzzy classifiers, valid for a specific configuration of the network, is adopted to produce a global evaluation for all relevant single Contingencies. An important feature of this approach is that it selects automatically the most appropriate number of security clusters for each selected contingency. Natural language-labeling is also used to produce standardized sentences about the security level of the system, improving in this way the communication process between the system and the operator. The paper is completed by an example on a realistic model of the Hellenic interconnected power system, where seven contingencies were simulated.

Abstract
This paper describes the 5dpo-2000 team, The paper will be divided into three main sections, corresponding to three main blocks: the Global Level, the Local Level and the Interface Level. These Levels, their subsystems and some implementation details will be described next.

Abstract
In this article we present a new approach to interaction modeling based on the concept of information resources. The approach is inspired by recent distributed cognition (DC) literature but develops a model that applies specifically to human-computer interaction (HCI) modeling. Of course, there are many approaches to modeling HCI, and the motivation of this article is not to offer yet another approach. Rather, our motivation is that the recent developments in DC are so obviously relevant to HCI modeling and design, yet the ideas have lacked visibility in the HCI community. By providing a model whose concepts are rooted in DC concepts, we hope to achieve this visibility. DC research identifies resources for action as central to the interaction between people and technologies, but it stops short of providing a definition of such resources at a level that could be used to analyze interaction. The resources model described in this article defines a limited number of resource types as abstract information structures that can be used to analyze interaction. We demonstrate how these abstract types can be represented differently in an interface. The resources model uses the concept of interaction strategy to describe the way in which different configurations of resources can differently shape users' actions. These 2 components of the resources model (information structures and interaction strategies), through the process of coordination and integration, provide a link among devices, representations, and actions that is not well articulated in the DC literature.

Abstract
In this article we discuss in detail two techniques for rule and case integration. Case-based learning is used when the rule language is exhausted. Initially, all the examples are used to induce a set of rules with satisfactory quality. The examples that are not covered by these rules are then handled as cases. The case-based approach used also combines rules and cases internally. Instead of only storing the cases as provided, it has a learning phase where, for each case, it constructs and stores a set of explanations with support and confidence above given thresholds. These explanations have different levels of generality and the maximally specific one corresponds to the case itself. The same case may have different explanations representing different perspectives of the case. Therefore, to classify a new case, it looks for relevant stored explanations applicable to the new case. The different possible views of the case given by the explanations correspond to considering different sets of conditions/features to analyze the case. In other words, they lead to different ways to compute similarity between known cases/explanations and the new case to be classified (as opposed to the commonly used fixed metric).

Abstract
In this paper we deal with the optimisation problem involved in determining the maximal margin separation hyperplane in support vector machines. We consider three different formulations, based on L-2 norm distance (the standard case), L-1 norm, and L-infinity norm. We consider separation in the original space of the data (i.e., there are no kernel transformations). For any of these cases, we focus on the following problem: having the optimal solution for a given training data set, one is given a new training example. The purpose is to use the information about the solution of the problem without the additional example in order to speed up the new optimisation problem. We also consider the case of reoptimisation after removing an example from the data set. We report results obtained for some standard benchmark problems.

Abstract
In this paper we present an experimental approach for QoS-aware and bandwidth-efficient transmission of multimedia sources over ATM networks. VBR video sources are statistically multiplexed at the application level and the UPC parameters of a single connection for the aggregate traffic are dynamically renegotiated with the network during the session lifetime. A statistical multiplexer computes the required bandwidth for the aggregate traffic and dynamically assigns bandwidth according to the performances requested and network resources availability. A dynamic UPC manager using feedback information sent by the network, may initiate a renegotiation of traffic parameters upon receiving a request from the statistical multiplexer. Performing the connection admission control procedures for the aggregate traffic, allows significant reductions in the value of the total peak rate when compared to the sum of peak rates of individual connections. It also reduces the burstiness of the flow submitted to the network, thus increasing the lifetime of each set of UPC parameters. © Springer-Verlag Berlin Heidelberg 2000.