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.

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.

A calibration approach based on Takagi-Sugeno fuzzy inference system for digital electronic compasses

Recently, the development of industrial processes brought on the outbreak of technologically complex systems. This development generated the necessity of research relative to the mathematical techniques that have the capacity to deal with project complexities and validation. Fuzzy models have been receiving particular attention in the area of nonlinear systems identification and analysis due to it is capacity to approximate nonlinear behavior and deal with uncertainty. A fuzzy rule-based model suitable for the approximation of many systems and functions is the Takagi-Sugeno (TS) fuzzy model. IS fuzzy models are nonlinear systems described by a set of if then rules which gives local linear representations of an underlying system. Such models can approximate a wide class of nonlinear systems. In this paper a performance analysis of a system based on IS fuzzy inference system for the calibration of electronic compass devices is considered. The contribution of the evaluated IS fuzzy inference system is to reduce the error obtained in data acquisition from a digital electronic compass. For the reliable operation of the TS fuzzy inference system, adequate error measurements must be taken. The error noise must be filtered before the application of the IS fuzzy inference system. The proposed method demonstrated an effectiveness of 57% at reducing the total error based on considered tests. (C) 2011 Elsevier Ltd. All rights reserved.

Approximate controllability of second-order distributed implicit functional systems

In this paper we study the approximate controllability of control systems with states and controls in Hilbert spaces, and described by a second-order semilinear abstract functional differential equation with infinite delay. Initially we establish a characterization for the approximate controllability of a second-order abstract linear system and, in the last section, we compare the approximate controllability of a semilinear abstract functional system with the approximate controllability of the associated linear system. (C) 2008 Elsevier Ltd. All rights reserved.

Supporting content-based image retrieval and computer-aided diagnosis systems with association rule-based techniques

In this work, we take advantage of association rule mining to support two types of medical systems: the Content-based Image Retrieval (CBIR) systems and the Computer-Aided Diagnosis (CAD) systems. For content-based retrieval, association rules are employed to reduce the dimensionality of the feature vectors that represent the images and to improve the precision of the similarity queries. We refer to the association rule-based method to improve CBIR systems proposed here as Feature selection through Association Rules (FAR). To improve CAD systems, we propose the Image Diagnosis Enhancement through Association rules (IDEA) method. Association rules are employed to suggest a second opinion to the radiologist or a preliminary diagnosis of a new image. A second opinion automatically obtained can either accelerate the process of diagnosing or to strengthen a hypothesis, increasing the probability of a prescribed treatment be successful. Two new algorithms are proposed to support the IDEA method: to pre-process low-level features and to propose a preliminary diagnosis based on association rules. We performed several experiments to validate the proposed methods. The results indicate that association rules can be successfully applied to improve CBIR and CAD systems, empowering the arsenal of techniques to support medical image analysis in medical systems. (C) 2009 Elsevier B.V. All rights reserved.

An association rule-based method to support medical image diagnosis with efficiency

In this paper, we propose a method based on association rule-mining to enhance the diagnosis of medical images (mammograms). It combines low-level features automatically extracted from images and high-level knowledge from specialists to search for patterns. Our method analyzes medical images and automatically generates suggestions of diagnoses employing mining of association rules. The suggestions of diagnosis are used to accelerate the image analysis performed by specialists as well as to provide them an alternative to work on. The proposed method uses two new algorithms, PreSAGe and HiCARe. The PreSAGe algorithm combines, in a single step, feature selection and discretization, and reduces the mining complexity. Experiments performed on PreSAGe show that this algorithm is highly suitable to perform feature selection and discretization in medical images. HiCARe is a new associative classifier. The HiCARe algorithm has an important property that makes it unique: it assigns multiple keywords per image to suggest a diagnosis with high values of accuracy. Our method was applied to real datasets, and the results show high sensitivity (up to 95%) and accuracy (up to 92%), allowing us to claim that the use of association rules is a powerful means to assist in the diagnosing task.

Physical and sensory properties of regular and reduced-fat pound cakes with added amaranth flour

The sum of wheat flour and corn starch was replaced by 10, 20, or 30% whole amaranth flour in both conventional (C) and reduced fat (RF) pound cakes. and the effects on physical and sensory properties of the cakes were investigated. RF presented 33% fat reduction. The increasing amaranth levels darkened crust and crumb of cakes, which decreased color acceptability. Fresh amaranth-containing cakes had similar texture characteristics to (he controls, evaluated both instrumentally and sensorially. Sensory evaluation revealed that replacement by 30% amaranth flour decreased C cakes overall acceptability scores, clue to its lower specific volume and darker color. Amaranth flour levels had no significant effect on overall acceptability of RF cakes. Hence, the sum of wheat flour and corn starch could be successfully replaced by up to 20% amaranth flour in C and up to 30% in RF pound cakes without negatively affecting sensory quality in fresh cakes. Moisture losses for all the cakes were similar, approximate to 1% per day during storage. After six days of storage, both C and RF amaranth-containing cakes had higher hardness and chewiness values than control cakes. Further experiments involving sensory evaluation during storage are necessary to determine the exact limit of amaranth flour replacement.

Consistency in approximate entropy given by a volumetric estimate

Non-linear methods for estimating variability in time-series are currently of widespread use. Among such methods are approximate entropy (ApEn) and sample approximate entropy (SampEn). The applicability of ApEn and SampEn in analyzing data is evident and their use is increasing. However, consistency is a point of concern in these tools, i.e., the classification of the temporal organization of a data set might indicate a relative less ordered series in relation to another when the opposite is true. As highlighted by their proponents themselves, ApEn and SampEn might present incorrect results due to this lack of consistency. In this study, we present a method which gains consistency by using ApEn repeatedly in a wide range of combinations of window lengths and matching error tolerance. The tool is called volumetric approximate entropy, vApEn. We analyze nine artificially generated prototypical time-series with different degrees of temporal order (combinations of sine waves, logistic maps with different control parameter values, random noises). While ApEn/SampEn clearly fail to consistently identify the temporal order of the sequences, vApEn correctly do. In order to validate the tool we performed shuffled and surrogate data analysis. Statistical analysis confirmed the consistency of the method. (C) 2008 Elsevier Ltd. All rights reserved.

An integer linear programming approach for approximate string comparison

We introduce a problem called maximum common characters in blocks (MCCB), which arises in applications of approximate string comparison, particularly in the unification of possibly erroneous textual data coming from different sources. We show that this problem is NP-complete, but can nevertheless be solved satisfactorily using integer linear programming for instances of practical interest. Two integer linear formulations are proposed and compared in terms of their linear relaxations. We also compare the results of the approximate matching with other known measures such as the Levenshtein (edit) distance. (C) 2008 Elsevier B.V. All rights reserved.

D*D rho vertex from QCD sum rules

We calculate the form factors and the coupling constant in the D*D rho vertex in the framework of QCD sum rules. We evaluate the three-point correlation functions of the vertex considering D, rho and D* mesons off-shell. The form factors obtained are very different but give the same coupling constant: g(D*D rho) = 4.3 +/- 0.9 GeV(-1). (C) 2011 Elsevier B.V. All rights reserved.

QCD sum rules for the production of the X(3872) as a mixed molecule-charmonium state in B meson decay

We use QCD sum rules to calculate the branching ratio for the production of the meson X(3872) in the decay B -> X(3872)K, assumed to be a mixture between charmonium and exotic molecular vertical bar c (q) over bar vertical bar vertical bar q (c) over bar vertical bar states with J(PC) = 1(++). We find that in a small range for the values of the mixing angle, 5 degrees <= theta <= 13 degrees, we get the branching ratio B(B -> XK) = (1.00 +/- 0.68) x 10(-5), which is in agreement with the experimental upper limit. This result is compatible with the analysis of the mass and decay width of the mode J/psi(n pi) and the radiative decay mode J/psi gamma performed in the same approach. (C) 2011 Elsevier B.V. All rights reserved.

QCD sum rules study of the J(PC)=1(- -) charmonium Y mesons

We use QCD sum rules to test the nature of the recently observed mesons Y(4260), Y(4350) and Y(4660), assumed to be exotic four-quark (c (c) over barq (q) over bar) or (c (c) over bars (s) over bar) states with J(PC)= 1(--). We work at leading order in alpha(s), consider the contributions of higher dimension condensates and keep terms which are linear in the strange quark mass m(s). We find for the (c (c) over bars (s) over bar) state a mass in m(Y) = (4.65 +/- 0.10) GeV which is compatible with the experimental candidate Y (4660), while for the (c (c) over barq (q) over bar) state we find a mass in m(Y) = (4.49 +/- 0.11) GeV, which is still consistent with the mass of the experimental candidate Y(4350). With the tetraquark structure we are working we cannot explain the Y(4260) as a tetraquark state. We also consider molecular D(s0)(D) over bar (s)* and D(0)(D) over bar* states. For the D(s0)(D) over bar (s)* molecular state we get m(Ds0 (D) over bars*) = (4.42 +/- 0.10) GeV which is consistent, considering the errors, with the mass of the meson Y(4350) and for the D(0)(D) over bar* molecular state we get m(D0 (D) over bar*) = (4.27 +/- 0.10) GeV in excellent agreement with the mass of the meson Y(4260). (C) 2008 Elsevier B.V. All rights reserved.

QCD sum rules study of the meson Z(+)(4430)

We use QCD sum rules to study the recently observed meson Z(+)(4430), considered as a D*D-1 molecule with J(P) = 0(-). We consider the contributions of condensates up to dimension eight and work at leading order in alpha(s). We get m(Z) = (4.40 +/- 0.10) GeV in a very good agreement with the experimental value. We also make predictions for the analogous mesons Z(s) and Z(bb) considered as D-s*D-1 and B*B-1 molecules, respectively. For Z(s) we predict mZ(s) = (4.70 +/- 0.06) GeV, which is above the D-s* D-1 threshold, indicating that it is probably a very broad state and, therefore, difficult to observe experimentally. For Z(bb) we predict m(Zbb) = (10.74 +/- 0.12) GeV, in agreement with quark model predictions. (c) 2008 Elsevier B.V. All rights reserved.

rho D*D* vertex from QCD sum rules

We calculate the form factors and the coupling constant in the rho D*D* vertex in the framework of QCD sum rules. We evaluate the three point correlation functions of the vertex considering both rho and D* mesons off-shell. The form factors obtained are very different but give the same coupling constant: g rho D*D* = 6.60 +/- 0.31. This number is 50% larger than what we would expect from SU(4) estimates. (c) 2007 Elsevier B.V. All rights reserved.

Molecular Ordering of Layer-by-Layer Polyelectrolyte Films Studied by Sum-Frequency Vibrational Spectroscopy

The molecular arrangement in organic thin films is crucial for their increasing technological applications. Here, we use vibrational spectroscopy by sum-frequency generation (SFG) to study the ordering of polyelectrolyte layers adsorbed on silica for all steps of layer-by-layer (LbL) self-assembly. In situ measurements during adsorption and rinsing showed that the adsorbed polymer has a disordered conformation and confirmed surface charge overcompensation upon polyelectrolyte adsorption by probing the interfacial electric field. In dry films, the polymer chains acquired a net orientational ordering, which was affected, however, by the adsorption of subsequent layers. Such a detailed characterization may allow the control of LbL film structure and functionality with unprecedented power.