Probabilistic logic with independence

This paper investigates probabilistic logics endowed with independence relations. We review propositional probabilistic languages without and with independence. We then consider graph-theoretic representations for propositional probabilistic logic with independence; complexity is analyzed, algorithms are derived, and examples are discussed. Finally, we examine a restricted first-order probabilistic logic that generalizes relational Bayesian networks. (c) 2007 Elsevier Inc. All rights reserved.

Approximate algorithms for credal networks with binary variables

This paper presents a family of algorithms for approximate inference in credal networks (that is, models based on directed acyclic graphs and set-valued probabilities) that contain only binary variables. Such networks can represent incomplete or vague beliefs, lack of data, and disagreements among experts; they can also encode models based on belief functions and possibilistic measures. All algorithms for approximate inference in this paper rely on exact inferences in credal networks based on polytrees with binary variables, as these inferences have polynomial complexity. We are inspired by approximate algorithms for Bayesian networks; thus the Loopy 2U algorithm resembles Loopy Belief Propagation, while the Iterated Partial Evaluation and Structured Variational 2U algorithms are, respectively, based on Localized Partial Evaluation and variational techniques. (C) 2007 Elsevier Inc. All rights reserved.

Sequential decision making with partially ordered preferences

This paper presents new insights and novel algorithms for strategy selection in sequential decision making with partially ordered preferences; that is, where some strategies may be incomparable with respect to expected utility. We assume that incomparability amongst strategies is caused by indeterminacy/imprecision in probability values. We investigate six criteria for consequentialist strategy selection: Gamma-Maximin, Gamma-Maximax, Gamma-Maximix, Interval Dominance, Maximality and E-admissibility. We focus on the popular decision tree and influence diagram representations. Algorithms resort to linear/multilinear programming; we describe implementation and experiments. (C) 2010 Elsevier B.V. All rights reserved.

Characterization of mixed waste of granite and LD slag

This study focuses on the technical feasibility of the utilization of waste from the cutting of granite to adjust the chemical composition of slag from steelworks LD, targeting the addition of clinker Portland cement. For this, chemical characterization of the waste, its mixture and fusion was performed, obtaining a CaO/SiO(2) relationship of around 0.9 to 1.2 for the steelworks slag. We selected samples of the waste, mixed, melted and cooled in water and in the oven. Samples cooled in water, after examining with X-ray difractrograms, had been predominantly amorphous. For samples cooled in the furnace, which had vitreous, there was the presence of mineralogical phases Akermanita and Gehlenita, which is considered as the ideal stage for the mineral water activity of the slag. The adjustment of the chemical composition of the slag from steel works by the addition of waste granite was efficient, transforming the waste into a product that is the same as blast furnace slag and can be used in the manufacture of cement.

Linear viscoelasticity of styrenic block copolymers-clay nanocomposites

In this work, the rheological behavior of block copolymers with different morphologies (lamellar, cylindrical, spherical, and disordered) and their clay-containing nanocomposites was studied using small amplitude oscillatory shear. The copolymers studied were one asymmetric starblock styrene-butadiene-styrene copolymer and four styrene-ethylene/butylenes-styrene copolymers with different molecular architectures, one of them being modified with maleic anhydride. The nanocomposites of those copolymers were prepared by adding organophilic clay using three different preparation techniques: melt mixing, solution casting, and a hybrid melt mixing-solution technique. The nanocomposites were characterized by X-ray diffraction and transmission electron microscopy, and their viscoelastic properties were evaluated and compared to the ones of the pure copolymers. The influence of copolymer morphology and presence of clay on the storage modulus (G`) curves was studied by the evaluation of the changes in the low frequency slope of log G` x log omega (omega: frequency) curves upon variation of temperature and clay addition. This slope may be related to the degree of liquid- or solid-like behavior of a material. It was observed that at temperatures corresponding to the ordered state, the rheological behavior of the nanocomposites depended mainly on the viscoelasticity of each type of ordered phase and the variation of the slope due to the addition of clay was small. For temperatures corresponding to the disordered state, however, the rheological behavior of the copolymer nanocomposites was dictated mostly by the degree of clay dispersion: When the clay was well dispersed, a strong solid-like behavior corresponding to large G` slope variations was observed.

Dodigen 213-N as corrosion inhibitor for ASTM 1010 mild steel in 10% HCL

This article describes a study of the behavior of a mixture of amines and amides, commercially known as Dodigen 213-N (D-213 N), as a corrosion inhibitor for ASTM 1010 mild steel in 10% w/w HCl solution. The concentration range used was 1 x 10(-5) M to 8 x 10(-4) M. The weight loss and electrochemical techniques used were corrosion potential measurement, anodic and cathodic polarization curves, and electrochemical impedance spectroscopy (EIS). The solution temperature was 50 +/- A 1 A degrees C and it was naturally aerated. The corrosion potential values shifted to slightly more positive values, thus indicating mixed inhibitor behavior. The anodic and cathodic polarization curves showed that D-213 N is an effective corrosion inhibitor, since both the anodic and the cathodic reactions were polarized in comparison with those obtained without inhibitor. For all concentrations the cathodic polarization curves were more polarized than the anodic ones. The inhibition efficiency was in the range 75-98%, calculated from values of weight loss and corrosion current density, i (corr), obtained by extrapolation of Tafel cathodic linear region.

Minimizing total tardiness in a stochastic single machine scheduling problem using approximate dynamic programming

This paper addresses the non-preemptive single machine scheduling problem to minimize total tardiness. We are interested in the online version of this problem, where orders arrive at the system at random times. Jobs have to be scheduled without knowledge of what jobs will come afterwards. The processing times and the due dates become known when the order is placed. The order release date occurs only at the beginning of periodic intervals. A customized approximate dynamic programming method is introduced for this problem. The authors also present numerical experiments that assess the reliability of the new approach and show that it performs better than a myopic policy.

AUTOMATIC CORONARY WALL SEGMENTATION IN INTRAVASCULAR ULTRASOUND IMAGES USING BINARY MORPHOLOGICAL RECONSTRUCTION

Intravascular ultrasound (IVUS) image segmentation can provide more detailed vessel and plaque information, resulting in better diagnostics, evaluation and therapy planning. A novel automatic segmentation proposal is described herein; the method relies on a binary morphological object reconstruction to segment the coronary wall in IVUS images. First, a preprocessing followed by a feature extraction block are performed, allowing for the desired information to be extracted. Afterward, binary versions of the desired objects are reconstructed, and their contours are extracted to segment the image. The effectiveness is demonstrated by segmenting 1300 images, in which the outcomes had a strong correlation to their corresponding gold standard. Moreover, the results were also corroborated statistically by having as high as 92.72% and 91.9% of true positive area fraction for the lumen and media adventitia border, respectively. In addition, this approach can be adapted easily and applied to other related modalities, such as intravascular optical coherence tomography and intravascular magnetic resonance imaging. (E-mail: matheuscardosomg@hotmail.com) (C) 2011 World Federation for Ultrasound in Medicine & Biology.

On the Filtering Problem for Continuous-Time Markov Jump Linear Systems with no Observation of the Markov Chain

We consider in this paper the optimal stationary dynamic linear filtering problem for continuous-time linear systems subject to Markovian jumps in the parameters (LSMJP) and additive noise (Wiener process). It is assumed that only an output of the system is available and therefore the values of the jump parameter are not accessible. It is a well known fact that in this setting the optimal nonlinear filter is infinite dimensional, which makes the linear filtering a natural numerically, treatable choice. The goal is to design a dynamic linear filter such that the closed loop system is mean square stable and minimizes the stationary expected value of the mean square estimation error. It is shown that an explicit analytical solution to this optimal filtering problem is obtained from the stationary solution associated to a certain Riccati equation. It is also shown that the problem can be formulated using a linear matrix inequalities (LMI) approach, which can be extended to consider convex polytopic uncertainties on the parameters of the possible modes of operation of the system and on the transition rate matrix of the Markov process. As far as the authors are aware of this is the first time that this stationary filtering problem (exact and robust versions) for LSMJP with no knowledge of the Markov jump parameters is considered in the literature. Finally, we illustrate the results with an example.

Discrete-time mean variance optimal control of linear systems with Markovian jumps and multiplicative noise

In this article, we consider the stochastic optimal control problem of discrete-time linear systems subject to Markov jumps and multiplicative noise under three kinds of performance criterions related to the final value of the expectation and variance of the output. In the first problem it is desired to minimise the final variance of the output subject to a restriction on its final expectation, in the second one it is desired to maximise the final expectation of the output subject to a restriction on its final variance, and in the third one it is considered a performance criterion composed by a linear combination of the final variance and expectation of the output of the system. We present explicit sufficient conditions for the existence of an optimal control strategy for these problems, generalising previous results in the literature. We conclude this article presenting a numerical example of an asset liabilities management model for pension funds with regime switching.

Non-linear modal analysis for beams subjected to axial loads: Analytical and finite-element solutions

A rigorous derivation of non-linear equations governing the dynamics of an axially loaded beam is given with a clear focus to develop robust low-dimensional models. Two important loading scenarios were considered, where a structure is subjected to a uniformly distributed axial and a thrust force. These loads are to mimic the main forces acting on an offshore riser, for which an analytical methodology has been developed and applied. In particular, non-linear normal modes (NNMs) and non-linear multi-modes (NMMs) have been constructed by using the method of multiple scales. This is to effectively analyse the transversal vibration responses by monitoring the modal responses and mode interactions. The developed analytical models have been crosschecked against the results from FEM simulation. The FEM model having 26 elements and 77 degrees-of-freedom gave similar results as the low-dimensional (one degree-of-freedom) non-linear oscillator, which was developed by constructing a so-called invariant manifold. The comparisons of the dynamical responses were made in terms of time histories, phase portraits and mode shapes. (C) 2008 Elsevier Ltd. All rights reserved.

Magnetic suspension of the rotor of a ventricular assist device of mixed flow type

This work presents results of preliminary studies concerning application of magnetic bearing in a ventricular assist device (VAD) being developed by Dante Pazzanese Institute of Cardiology-IDPC (Sao Paulo, Brazil). The VAD-IDPC has a novel architecture that distinguishes from other known VADs. In this, the rotor has a conical geometry with spiral impellers, showing characteristics that are intermediate between a centrifugal VAD and an axial VAD. The effectiveness of this new type of blood pumping principle was showed by tests and by using it in heart surgery for external blood circulation. However, the developed VAD uses a combination of ball bearings and mechanical seals, limiting the life for some 10 h, making impossible its long-term use or its use as an implantable VAD. As a part of development of an implantable VAD, this work aims at the replacement of ball bearings by a magnetic bearing. The most important magnetic bearing principles are studied and the magnetic bearing developed by Escola Politecnica of Sao Paulo University (EPUSP-MB) is elected because of its very simple architecture. Besides presenting the principle of the EPUSP-MB, this work presents one possible alternative for applying the EPUSP-MB in the IDPC-VAD.

Linear minimum mean square filter for discrete-time linear systems with Markov jumps and multiplicative noises

In this paper we obtain the linear minimum mean square estimator (LMMSE) for discrete-time linear systems subject to state and measurement multiplicative noises and Markov jumps on the parameters. It is assumed that the Markov chain is not available. By using geometric arguments we obtain a Kalman type filter conveniently implementable in a recurrence form. The stationary case is also studied and a proof for the convergence of the error covariance matrix of the LMMSE to a stationary value under the assumption of mean square stability of the system and ergodicity of the associated Markov chain is obtained. It is shown that there exists a unique positive semi-definite solution for the stationary Riccati-like filter equation and, moreover, this solution is the limit of the error covariance matrix of the LMMSE. The advantage of this scheme is that it is very easy to implement and all calculations can be performed offline. (c) 2011 Elsevier Ltd. All rights reserved.

Metal separation from mixed types of batteries using selective precipitation and liquid-liquid extraction techniques

The purpose of this paper is to study metal separation from a sample composed of a mixture of the main types of spent household batteries, using a hydrometallurgical route, comparing selective precipitation and liquid-liquid extraction separation techniques. The preparation of the solution consisted of: grinding the waste of mixed batteries, reduction and volatile metals elimination using electric furnace and acid leaching. From this solution two different routes were studied: selective precipitation with sodium hydroxide and liquid-liquid extraction using Cyanex 272 [bis(2,4,4-trimethylpentyl) phosphoric acid] as extracting agent. The best results were obtained from liquid-liquid extraction in which Zn had a 99% extraction rate at pH 2.5. More than 95% Fe was extracted at pH 7.0, the same pH at which more than 90% Ce was extracted. About 88% Mn, Cr and Co was extracted at this pH. At pH 3.0, more than 85% Ni was extracted, and at pH 3.5 more than 80% of Cd and La was extracted. (C) 2010 Elsevier Ltd. All rights reserved.

Formulating Mixed Models for Experiments, Including Longitudinal Experiments

Mixed models have become important in analyzing the results of experiments, particularly those that require more complicated models (e.g., those that involve longitudinal data). This article describes a method for deriving the terms in a mixed model. Our approach extends an earlier method by Brien and Bailey to explicitly identify terms for which autocorrelation and smooth trend arising from longitudinal observations need to be incorporated in the model. At the same time we retain the principle that the model used should include, at least, all the terms that are justified by the randomization. This is done by dividing the factors into sets, called tiers, based on the randomization and determining the crossing and nesting relationships between factors. The method is applied to formulate mixed models for a wide range of examples. We also describe the mixed model analysis of data from a three-phase experiment to investigate the effect of time of refinement on Eucalyptus pulp from four different sources. Cubic smoothing splines are used to describe differences in the trend over time and unstructured covariance matrices between times are found to be necessary.