42437646
Interleaving Functional and Performance Structural Analysis of Net Models
The design of parallel and distributed systems requires considering both functional and performance specifications and properties. The use of a single family of models to deal with both aspects, plus appropriate analysis techniques, are very important in practice. Petri Nets are one of the formal description techniques able to capture both functional and performance aspects. We illustrate here, after our research experience, how the interleaving of the functional and the performance analysis theories produces a synergetic situation, in which each contributes to the development of the other.
18072299
Petri nets and flexible manufacturing
The aim of this invited survey is to introduce Computer science/Petri nets specialists to the basic system level issues brought up by the development of Flexible Manufacturing and how Petri nets are used to aid the production engineers in their work. After some terminology concerning production engineering, the hierarchical decision and control level is briefly reviewed. Finally, the role and the presence of nets in CAE (Computer Aided Engineering) and in CAM (Computer Aided Manufacturing) for FMSs (Flexible Manufacturing Systems) are considered. From the design point of view, the use of nets have many advantages in modeling, qualitative analysis, performance evaluation and code generation. From the control of the plant perspective, scheduling on nets models, the coordination of the plant (global and partial) and the presence of nets in the local control level are discussed.
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.
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.
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.
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 ...
800062
Words avoiding repetitions in arithmetic progressions
Carpi constructed an infinite word over a 4-letter alphabet that avoids squares in all subsequences indexed by arithmetic progressions of odd difference. We show a connection between Carpi's construction and the paperfolding words. We extend Carpi's result by constructing uncountably many words that avoid squares in arithmetic progressions of odd difference. We also construct infinite words avoiding overlaps and infinite words avoiding all sufficiently large squares in arithmetic progressions of odd difference. We use these words to construct labelings of the 2-dimensional integer lattice such that any line through the lattice encounters a squarefree (resp. overlapfree) sequence of labels.
20448375
Heuristic Extraction of Rules in Pruned Artificial Neural Networks Models Used for Quantifying Highly Overlapping Chromatographic Peaks
The suitability of an approach for extracting heuristic rules from trained artificial neural networks (ANNs) pruned by a regularization method and with architectures designed by evolutionary computation for quantifying highly overlapping chromatographic peaks is demonstrated. The ANN input data are estimated by the Levenberg-Marquardt method in the form of a four-parameter Weibull curve associated with the profile of the chromatographic band. To test this approach, two N-methylcarbamate pesticides, carbofuran and propoxur, were quantified using a classic peroxyoxalate chemiluminescence reaction as a detection system for chromatographic analysis. Straightforward network topologies (one and two outputs models) allow the analytes to be quantified in concentration ratios ranging from 1:7 to 5:1 with an average standard error of prediction for the generalization test of 2.7 and 2.3% for carbofuran and propoxur, respectively. The reduced dimensions of the selected ANN architectures, especially those obtained after using heuristic rules, allowed simple quantification equations to be developed that transform the input variables into output variables. These equations can be easily interpreted from a chemical point of view to attain quantitative analytical information regarding the effect of both analytes on the characteristics of chromatographic bands, namely profile, dispersion, peak height, and residence time.
18278319
A two steps method: non linear regression and pruning neural network for analyzing multicomponent mixtures
This work deals with the use of pruning ANNs in conjunction with genetic algorithms for resolving nonlinear multicomponent systems based on oscillating chemical reactions. The singular analytical response provides by this chemical system after its perturbation was tted to a gaussian curve by least-square regression and the estimates were used as inputs to the ANNs. The proposed methodology was validated by the simultaneous determination of pyrogallol and gallic acid (two strong related phenol derivatives) in mixtures on the basis of their perturbation e ects on the classical Belousov-Zhabotinskii reaction. The trained network estimates concentrations of pyrogallol and gallic acid with a standard error of prediction for the testing set of ca. 4% and 5.7% respectively or 4.4%, 9% for di erent sets of train/test patterns. This result is much smaller than those provided by a classical parametric method such as non-linear regression.
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.