This paper reports about the research work currently going on at DEIS, University of Bologna, on the use of computer vision for extraction of information from urban traffic images. Two algorithms are described: the fi...
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In this paper, we analyze quantitative measures associated with if-then type rules. Basic quantities are identified and many existing measures are examined using the basic quantities. The main objective is to provide ...
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A lack of adequate and flexible topology support in the popular message passing systems such as Parallel Virtual Machine was a major factor in the development of our Virtual Process Topology Environment. This parallel...
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A lack of adequate and flexible topology support in the popular message passing systems such as Parallel Virtual Machine was a major factor in the development of our Virtual Process Topology Environment. This parallel programming environment provides high level abstractions for interprocess communication, relieving the application developer of the cumbersome task of mapping logical neighbours to their task identifiers within message passing systems. The novel approach of separating topological specification from the APIs provided extreme flexibility to the developers of the applications using regular topologies. We believed that the task of supporting process topologies could be made even easier and, in this paper present our new method which uses recurrence relations to define topologies. Within the new environment, the recurrence relationships can be passed to the topology server which then is used in the generation of the topological specification.
Present day electromechanical product design requires multi disciplinary design teams who have to perform complex synthesis, analysis, and control tasks to ensure desirable functional and performance characteristics f...
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In modern circuit design, the Shannon decomposition of switching functions is widely used. On the other hand, in information theory of telecommunication, the Shannon entropy used as a measure to represent the informat...
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In modern circuit design, the Shannon decomposition of switching functions is widely used. On the other hand, in information theory of telecommunication, the Shannon entropy used as a measure to represent the information in numerical values, is a key notion. In this paper, we relate these two concepts, belonging to different areas, into an approach to the minimisation of exclusive-or sum-of-products (AND/EXOR) expressions for switching functions. The Shannon decomposition, and the closely related Davio decomposition for AND/EXOR expressions are interpreted in terms of basic concepts in the information theory. Thanks to that, we have proposed an entropy based strategy for minimization of AND/EXOR expressions. We have provided a comparison and an experimental verification of this strategy with some known heuristic minimization strategies using benchmarks. In some cases, our program Info-EXOR produces extremely better results. Moreover, the information theory interpretation of classical decomposition of switching functions offers a new point of view to the existing design styles.
DMSS (Discrete Metabolic Simulation System) is a framework for modelling and simulating metabolic pathways. Quantitative simulation of metabolic pathways is achieved using discrete-event techniques. The approach diffe...
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The problem of improving the performance and scalability of current monitoring systems, which generally follow a centralised and static management model is considered herein. Several alternative solutions based on Mob...
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The use of multirate generalized sampled-data hold functions for model reference adaptive control of linear multiple-input, multiple-output (MIMO) systems with unknown parameters, is investigated in this paper, for th...
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The use of multirate generalized sampled-data hold functions for model reference adaptive control of linear multiple-input, multiple-output (MIMO) systems with unknown parameters, is investigated in this paper, for the first time. Such a control scheme contains a multirate sampling mechanism with different sampling period to each system input and relies on two periodically varying modulating matrix functions. The proposed control strategy allows us to assign an arbitrary discrete-time transfer function matrix for the sampled closed-loop system and does not make assumptions on the plant other than controllability and observability of the continuous and the sampled system, and the knowledge of a set of structural indices, namely the locally minimum controllability indices of the continuous-time plant. The indirect adaptive control scheme presented here, estimates the unknown plant parameters (and hence the parameters of the desired modulating matrix functions) on line, from sequential data of the inputs and the outputs of the plant, which are recursively updated within the time limit imposed by a fundamental sampling period T0. The controller determination is reduced to the simple problem of solving a linear algebraic system of equations, whereas known indirect model reference adaptive control techniques require the solution of matrix polynomial Diophantine equations, whose solutions may become unstable. Moreover, persistency of excitation and, therefore, parameter convergence, of the continuous-time plant is provided without making assumptions either on the existence of specific convex sets in which the estimated parameters belong or on the coprimeness of the polynomials describing the ARMA model, or finally on the richness of the reference signals, as compared to known indirect model reference adaptive control schemes.
In this paper a combined algorithm for the control of non-triangular nonlinear systems with unmatched uncertainties will be presented. It relies on a combination of Dynamical Adaptive Backstepping (DAB) and Sliding Mo...
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