Linear quadratic Gaussian control of discrete-time Markov jump linear systems with horizon defined by stopping times

The linear quadratic Gaussian control of discrete-time Markov jump linear systems is addressed in this paper, first for state feedback, and also for dynamic output feedback using state estimation. in the model studied, the problem horizon is defined by a stopping time τ which represents either, the occurrence of a fix number N of failures or repairs (T N), or the occurrence of a crucial failure event (τ δ), after which the system paralyzed. From the constructive method used here a separation principle holds, and the solutions are given in terms of a Kalman filter and a state feedback sequence of controls. The control gains are obtained by recursions from a set of algebraic Riccati equations for the former case or by a coupled set of algebraic Riccati equation for the latter case. Copyright © 2005 IFAC.

Filtering for discrete-time Markov jump systems with network transmitted mode

This paper is concerned with ℋ 2 and ℋ ∞ filter design for discrete-time Markov jump systems. The usual assumption of mode-dependent design, where the current Markov mode is available to the filter at every instant of time is substituted by the case where that availability is subject to another Markov chain. In other words, the mode is transmitted to the filter through a network with given transmission failure probabilities. The problem is solved by modeling a system with N modes as another with 2N modes and cluster availability. We also treat the case where the transition probabilities are not exactly known and demonstrate our conditions for calculating an ℋ ∞ norm bound are less conservative than the available results in the current literature. Numerical examples show the applicability of the proposed results. ©2010 IEEE.

A Markov random field model for combining optimum-path forest classifiers using decision graphs and game strategy approach

The research on multiple classifiers systems includes the creation of an ensemble of classifiers and the proper combination of the decisions. In order to combine the decisions given by classifiers, methods related to fixed rules and decision templates are often used. Therefore, the influence and relationship between classifier decisions are often not considered in the combination schemes. In this paper we propose a framework to combine classifiers using a decision graph under a random field model and a game strategy approach to obtain the final decision. The results of combining Optimum-Path Forest (OPF) classifiers using the proposed model are reported, obtaining good performance in experiments using simulated and real data sets. The results encourage the combination of OPF ensembles and the framework to design multiple classifier systems. © 2011 Springer-Verlag.

H ∞ state feedback control of discrete-time Markov jump linear systems through linear matrix inequalities

This paper addresses the H ∞ state-feedback control design problem of discretetime Markov jump linear systems. First, under the assumption that the Markov parameter is measured, the main contribution is on the LMI characterization of all linear feedback controllers such that the closed loop output remains bounded by a given norm level. This results allows the robust controller design to deal with convex bounded parameter uncertainty, probability uncertainty and cluster availability of the Markov mode. For partly unknown transition probabilities, the proposed design problem is proved to be less conservative than one available in the current literature. An example is solved for illustration and comparisons. © 2011 IFAC.

Stochastic exponential stability of singular linear systems with Markov jump parameters

This paper deals with exponential stability of discrete-time singular systems with Markov jump parameters. We propose a set of coupled generalized Lyapunov equations (CGLE) that provides sufficient conditions to check this property for this class of systems. A method for solving the obtained CGLE is also presented, based on iterations of standard singular Lyapunov equations. We present also a numerical example to illustrate the effectiveness of the approach we are proposing.

Aplicacion de un proceso en cadena de Markov a la proyeccion de la mortalidad, por sexo y grupos de edades

Incluye Bibliografía

Assessment of force decay in orthodontic elastomeric chains: An in vitro study

Introduction: Elastomeric materials are considered important sources of orthodontic forces. Objective: To assess force degradation over time of four commercially available orthodontic elastomeric chains (Morelli, Ormco, TP and Unitek). Methods: The synthetic elastics were submerged in 37 oC synthetic saliva and stretched by a force of 150 g (15 mm - Morelli and TP; 16mm - Unitek and Ormco). With a dynamometer, the delivered force was evaluated at different intervals: 30 minutes, 7 days, 14 days and 21 days. The results were subjected to ANOVA and Tukey's test. Results: There was a force decay between 19% to 26.67% after 30 minutes, and 36.67% to 57% after 21 days of activation. Conclusions: TP elastomeric chains exhibited the smallest percentage of force decay, with greater stability at all time intervals tested. Meanwhile, the Unitek chains displayed the highest percentage of force degradation, and no statically significant difference was found in force decay between Ormco and Morelli elastomeric chains during the study period.

The expansion model of the major Chilean retail chains

Includes bibliography

Modelling polymers with side chains: MEH-PPV and P3HT

Modelling polymers with side chains is always a challenge once the degrees of freedom are very high. In this study, we present a successful methodology to model poly[2-methoxy-5-(2′-ethyl-hexyloxy)-p-phenylenevinylene] (MEH-PPV) and poly[3-hexylthiophene] (P3HT) in solutions, taking into account the influence of side chains on the polymer conformation. Molecular dynamics and semi-empirical quantum mechanical methods were used for structure optimisation and evaluation of optical properties. The methodology allows to describe structural and optical characteristics of the polymers in a satisfactory way, as well as to evaluate some usual simplifications adopted for modelling these systems. Effective conjugation lengths of 8-14.6 and 21 monomers were obtained for MEH-PPV and P3HT, respectively, in accordance with experimental findings. In addition, anti/syn conformations of these polymers could be predicted based on intrinsic interactions of the lateral branches. © 2013 Copyright Taylor and Francis Group, LLC.

OPF-MRF: Optimum-path forest and Markov random fields for contextual-based image classification

Some machine learning methods do not exploit contextual information in the process of discovering, describing and recognizing patterns. However, spatial/temporal neighboring samples are likely to have same behavior. Here, we propose an approach which unifies a supervised learning algorithm - namely Optimum-Path Forest - together with a Markov Random Field in order to build a prior model holding a spatial smoothness assumption, which takes into account the contextual information for classification purposes. We show its robustness for brain tissue classification over some images of the well-known dataset IBSR. © 2013 Springer-Verlag.

Latin America and the Caribbean in the World Economy 2013: A sluggish postcrisis, mega trade negotiations and value chains: scope for regional action

Incluye bibliografía.

Strengthening value chains as an industrial policy instrument. Methodology and experience of ECLAC in Central America

Foreword by Alicia Bárcena.

Upgrading value chains through professional and supporting services: Lessons from three agro-industry chains in El Salvador and Guatemala

Includes bibliography

Global value chains and world trade: Prospects and challenges for Latin America

Foreword by Alicia Bárcena.