A clustering technique for the identification of piecewise affine systems

We propose a new technique for the identification of discrete-time hybrid systems in the piecewise affine (PWA) form. This problem can be formulated as the reconstruction of a possibly discontinuous PWA map with a multi-dimensional domain. In order to achieve our goal, we provide an algorithm that exploits the combined use of clustering, linear identification, and pattern recognition techniques. This allows to identify both the affine submodels and the polyhedral partition of the domain on which each submodel is valid avoiding gridding procedures. Moreover, the clustering step (used for classifying the datapoints) is performed in a suitably defined feature space which allows also to reconstruct different submodels that share the same coefficients but are defined on different regions. Measures of confidence on the samples are introduced and exploited in order to improve the performance of both the clustering and the final linear regression procedure.     

Tree-Based Credal Networks for Classification

Bayesian networks are models for uncertain reasoning which are achieving a growing importance also for the data mining task of classification. Credal networks extend Bayesian nets to sets of distributions, or credal sets. This paper extends a state-of-the-art Bayesian net for classification, called tree-augmented naive Bayes classifier, to credal sets originated from probability intervals. This extension is a basis to address the fundamental problem of prior ignorance about the distribution that generates the data, which is a commonplace in data mining applications. This issue is often neglected, but addressing it properly is a key to ultimately draw reliable conclusions from the inferred models. In this paper we formalize the new model, develop an exact linear-time classification algorithm, and evaluate the credal net-based classifier on a number of real data sets. The empirical analysis shows that the new classifier is good and reliable, and raises a problem of excessive caution that is discussed in the paper. Overall, given the favorable trade-off between expressiveness and efficient computation, the newly proposed classifier appears to be a good candidate for the wide-scale application of reliable classifiers based on credal networks, to real and complex tasks.     

Visual routines for real-time monitoring of vehicle behavior

Low-cost, purely visual modules are presented, which are able to reliably perform real-time computation of kinematic quantities relevant for the navigation of commercial vehicles moving along highways or motorways. Taking as input a video stream of b/w images coming from a standard camera mounted aboard the vehicle, the modules return instantaneous measurements for the speed of the vehicle, its lateral position in the lane, and the distance from the preceding vehicle. The modules, which are designed to work in real-time on standard PC platforms, have been tested under typical working conditions. Preliminary results are reported and discussed. Received: 10 March 1997 / Accepted: 24 November 1997     

Quattor: Tools and Techniques for the Configuration,Installation and Management of Large-Scale Grid Computing Fabrics

This paper describes the quattor tool suite, a new system for the installation, configuration, and management of operating systems and application software for computing fabrics. At present Unix derivatives such as Linux and Solaris are supported. Quattor is a powerful, portable and modular open source solution that has been shown to scale to thousands of computing nodes and offers a significant reduction in management costs for large computing fabrics. The quattor tool suite includes innovations compared to existing solutions which make it very useful for computing fabrics integrated into grid environments. Evaluations of the tool suite in current large scale computing environments are presented.     

The hyper-cube framework for ant colony optimization.

Ant colony optimization is a metaheuristic approach belonging to the class of model-based search algorithms. In this paper, we propose a new framework for implementing ant colony optimization algorithms called the hyper-cube framework for ant colony optimization. In contrast to the usual way of implementing ant colony optimization algorithms, this framework limits the pheromone values to the interval [0,1]. This is obtained by introducing changes in the pheromone value update rule. These changes can in general be applied to any pheromone value update rule used in ant colony optimization. We discuss the benefits coming with this new framework. The benefits are twofold. On the theoretical side, the new framework allows us to prove that in Ant System, the ancestor of all ant colony optimization algorithms, the average quality of the solutions produced increases in expectation over time when applied to unconstrained problems. On the practical side, the new framework automatically handles the scaling of the objective function values. We experimentally show that this leads on average to a more robust behavior of ant colony optimization algorithms.     

Specification and Verification of Agent Interaction using Social Integrity Constraints

In this paper we propose a logic-based social approach to the specification and verification of agent interaction. We firstly introduce integrity constraints about social acts (called Social Integrity Constraints) as a formalism to express interaction protocols and to give a social semantics to the behavior of agents, focusing on communicative acts. Then, we discuss several possible kinds of verification of agent interaction, and we show how social integrity constraints can be used to verify some properties in this respect. We focus our attention on static verification of compliance of agent specifications to interaction protocols, and on run-time verification, based on agents' observable behavior. We adopt as a running example the NetBill security transaction protocol for the selling and delivery of information goods.     

A Logical Model for Agent Communication Languages

The current ACL proposals show some shortcomings with respect to the definition of their semantics. Our paper aims at tackling those issues by defining an ACL semantics as a specification of the analytical effects of agent communicative acts. We analyze agent communication in terms of concepts taken from Speech Act Theory, as several researchers have already done, but move away from the mainstream view of artificial agent research, as we define communicative acts in terms of changes at the level of social relationship between agents. We take commitment to be a primitive concept underlying the social dimension of multiagent systems, and define a basic artificial institution whose aim is to provide agents with the means to affect the commitment network that binds them to each other.     

On state equations of two‐level quantum systems in a thermal environment

The state equations of open two‐level quantum systems, which form the building blocks of quantum cellular neural networks, are studied in arbitrary representations. It is shown that the dissipation matrix, that under the usual assumptions is diagonal in the energy representation, such remains if and only if the coupling between the states induced by an external field is real and infinitesimal. Copyright © 2004 John Wiley & Sons, Ltd.     

Qualitative Ordinal Scales: The Concept of Ordinal Range

Many practical problems of quality control involve the use of ordinal scales. Questionnaires planned to collect judgments on qualitative or linguistic scales, whose levels are terms such as “good,” “bad,” “medium,” etc., are extensively used both in evaluating service quality and in visual controls for manufacturing industry. In an ordinal environment, the concept of distance between two generic levels of the same scale is not defined. Therefore, a population (universe) of judgments cannot be described using “traditional” statistical distributions since they are based on the notion of distance. The concept of “distribution shape” cannot be defined as well. In this article, we introduce a new statistical entity, the so-called ordinal distribution, to describe a population of judgments expressed on an ordinal scale. We also discuss which of the traditional location and dispersion measures can be used in this context and we briefly analyze some of their properties. A new dispersion measure, the ordinal range, as an extension of the cardinal range to ordinal scales, is then proposed. A practical application in the field of quality is developed throughout the article.     

Energetic ion loss detector on the Alcator C-Mod tokamak

A scintillator-based energetic ion loss detector has been successfully commissioned on the Alcator C-Mod tokamak. This probe is located just below the outer midplane, where it captures ions of energies up to 2 MeV resulting from ion cyclotron resonance heating. After passing through a collimating aperture, ions impact different regions of the scintillator according to their gyroradius (energy) and pitch angle. The probe geometry and installation location are determined based on modeling of expected lost ions. The resulting probe is compact and resembles a standard plasma facing tile. Four separate fiber optic cables view different regions of the scintillator to provide phase space resolution. Evolving loss levels are measured during ion cyclotron resonance heating, including variation dependent upon individual antennae.