121386022
On observability in timed continuous Petri net systems
Fluidification is a classical relaxation technique for approximated performance evaluation of discrete systems. In this paper we deal with T-timed fully continuous Petri Nets working under infinite servers semantics, what leads to (deterministic) piecewise linear differential systems. Switches among dynamic linear systems are triggered by internal events through minimum operators on marking variables. The observability problem consists of estimating the (initial) marking from a partial measure. This paper is devoted to observability concepts and criteria in this particular class of systems, not to the observers design. The concept of structural observability, regarding to the possibility of estimating the marking of places for any speed of the transitions is introduced and studied for the subclass of join-free Petri nets (JF). For non join-free Petri nets, conditions to compute suitable estimates will be established.
9463713
Structure Theory of Equal Conflict Systems
Abstract Equal conflict net systems are a weighted generalisation of the (extended) free choice subclass that keeps the total autonomy of choices. A substantial part of the analytical branch of the structure theory of free choice systems, including decomposition and duality, the rank theorem, characterisations of impartial sequences and prompt interfaces, and the existence of home states, is extended to the equal conflict case. In so doing, several familiar concepts and objects from the structure theory of place/transition net systems are revisited from a linear algebraic perspective, which is specially adequate to cope with weighted nets.
26560925
{SC}*ECS: A Class of Modular and Hierarchical Cooperating Systems
We introduce a new class of Place/Transition net systems, {SC}*ECS, a generalisation of Equal Conflict systems [13] and Deterministic Systems of Sequential Processes [7, 11, 9, 10, 6]. {SC}*ECS are modular and hierarchical by definition: An {SC}*ECS is made up of a set of {SC}*ECS modules that asynchronously communicate through buffers in a restricted way.
29997198
Liveness and Home States in Equal Conflict Systems
Structure theory is a branch of net theory devoted to investigate the relationship between the structure and the behaviour of net models. Many of its powerful results have been derived for some subclasses of ordinary (i.e. all weights one) Place/Transition net systems. Nevertheless, weights may be very convenient to properly model systems with bulk services and arrivals. They can be implemented by means of ordinary subnets, but then the original structure of the net becomes too complex, even in the simplest cases, to be amenable of some interesting structural analysis techniques.
45802256
A New Technique for Finding a Generating Family of Siphons, Traps and st-Components. Application to Colored Petri Nets
In this paper we propose a new solution to the problem of finding generating families of siphons (structural dead-locks in classical terminology), traps and st-components in Petri Nets. These families are obtained as solutions of some systems of linear inequalities. Their transformation into a system of linear equations allows to interpret the technique as follows: traps (siphons, st-components) of a net N are deduced from the support of psemiflows of a transformed net NΘ(NΣ,NΣΘ).
17241799
Basic Server Semantics and Performance Monotonicity of Continuous Petri Nets
Continuous Petri nets were introduced as an approximation to deal with the state explosion problem which can appear in discrete event models. When time is introduced, the flow through a fluidified transition can be defined in many ways. The most used in literature are constant and variable speed (David and Alla, Discrete, continuous and hybrid Petri nets, Springer-Verlag, 2005), which can be seen as some kind of finite and infinite server interpretations of the transitions behavior, and derived from stochastic (discrete) Petri nets (Silva and Recalde, Annu Rev Control 28(2):253–266, 2004). In this paper we will compare the results obtained with both relaxations for the broad class of mono-T-semiflow reducible nets, and prove that, under some frequently true conditions, infinite server semantics offers a throughput which is closer to the throughput of the discrete system in steady state. In the second part, it will be proved that the throughput of mono-T-semiflow reducible net systems is monotone with respect to the speed of the transitions and the initial marking of the net.
9142441
Understanding Users' Response To Ontology Based Systems In The Context Of An Enterprise Sponsored Virtual Community
This paper aims at presenting the preliminary results of a research work that seeks to understand the users’ response to semantic based technologies, in the context of enterprise sponsored virtual communities. The research follows a qualitative methodology based on an action research approach. It particularly focuses on the socio-cognitive processes that underlie users’ learning and acquisition methods when training and interacting with a new knowledge management approach based on semantically enabled technologies in a collaborative, and sometimes virtual, learning/working environment. The outcomes of this research are expected to provide an assessment framework for a deeper level understanding of the cognition process in what concerns the evolution of individual’s knowledge, opinions, beliefs, and thoughts about ontology based systems.
34650038
Estimation of Parameters of Kinetic Compartmental Models by Use of Computational Neural Networks
A novel methodological approach to the estimation of parameters involved in multicomponent kinetic determinations from real kinetic data by use of computational or artificial neural networks (ANNs) is proposed. The ANN input data used are also estimates obtained by using the Levenberg−Marquardt method in the form of an approximate nonlinear function that is the sum of the two expressions associated with the pseudo-first-order kinetics of the two mixture components. The performance of the optimized network architecture, 2:4s:2l, was tested at variable rate constant ratios. The reduced dimensions of the network input space obtained using the Kolmogorov−Sprecher theorem result in improved limits of precision in estimating parameters at near-unity rate constant ratios. Experiments with real kinetic data provided a relative standard error of prediction of 2.47% and 4.23% for the two mixture components. These errors are much smaller than those obtained with existing alternative methods, particularly at the low ...
25007978
Use of Pruned Computational Neural Networks for Processing the Response of Oscillating Chemical Reactions with a View to Analyzing Nonlinear Multicomponent Mixtures
The suitability of pruned computational neural networks (CNNs) for resolving nonlinear multicomponent systems involving synergistic effects by use of oscillating chemical reaction-based methods implemented using the analyte pulse perturbation technique is demonstrated. The CNN input data used for this purpose are estimates provided by the Levenberg-Marquardt method in the form of a three-parameter Gaussian curve associated with the singular profile obtained when the oscillating system is perturbed by an analyte mixture. The performance of the proposed method was assessed by applying it to the resolution of mixtures of pyrogallol and gallic acid based on their perturbating effect on a classical oscillating chemical system, viz. the Belousov-Zhabotinskyi reaction. A straightforward network topology (3:3:2, with 18 connections after pruning) allowed the resolution of mixtures of the two analytes in concentration ratios from 1:7 to 6:2 with a standard error of prediction for the testing set of 4.01 and 8.98% for pyrogallol and gallic acid, respectively. The reduced dimensions of the selected CNN architecture allowed a mathematical transformation of the input vector into the output one that can be easily implemented via software. Finally, the suitability of response surface analysis as an alternative to CNNs was also tested. The results were poor (relative errors were high), which confirms that properly selected pruned CNNs are effective tools for solving the analytical problem addressed in this work.