Multifractality in the random parameter model for multivariate time series

The Random Parameter model was proposed to explain the structure of the covariance matrix in problems where most, but not all, of the eigenvalues of the covariance matrix can be explained by Random Matrix Theory. In this article, we explore the scaling properties of the model, as observed in the multifractal structure of the simulated time series. We use the Wavelet Transform Modulus Maxima technique to obtain the multifractal spectrum dependence with the parameters of the model. The model shows a scaling structure compatible with the stylized facts for a reasonable choice of the parameter values. (C) 2009 Elsevier B.V. All rights reserved.

Bayesian updating rules in continuous opinion dynamics models

Here, I investigate the use of Bayesian updating rules applied to modeling how social agents change their minds in the case of continuous opinion models. Given another agent statement about the continuous value of a variable, we will see that interesting dynamics emerge when an agent assigns a likelihood to that value that is a mixture of a Gaussian and a uniform distribution. This represents the idea that the other agent might have no idea about what is being talked about. The effect of updating only the first moments of the distribution will be studied, and we will see that this generates results similar to those of the bounded confidence models. On also updating the second moment, several different opinions always survive in the long run, as agents become more stubborn with time. However, depending on the probability of error and initial uncertainty, those opinions might be clustered around a central value.

Improvements on ICA mixture models for image pre-processing and segmentation

Today several different unsupervised classification algorithms are commonly used to cluster similar patterns in a data set based only on its statistical properties. Specially in image data applications, self-organizing methods for unsupervised classification have been successfully applied for clustering pixels or group of pixels in order to perform segmentation tasks. The first important contribution of this paper refers to the development of a self-organizing method for data classification, named Enhanced Independent Component Analysis Mixture Model (EICAMM), which was built by proposing some modifications in the Independent Component Analysis Mixture Model (ICAMM). Such improvements were proposed by considering some of the model limitations as well as by analyzing how it should be improved in order to become more efficient. Moreover, a pre-processing methodology was also proposed, which is based on combining the Sparse Code Shrinkage (SCS) for image denoising and the Sobel edge detector. In the experiments of this work, the EICAMM and other self-organizing models were applied for segmenting images in their original and pre-processed versions. A comparative analysis showed satisfactory and competitive image segmentation results obtained by the proposals presented herein. (C) 2008 Published by Elsevier B.V.

The production of school numbers (1871-1931): contributions to a critical approach to statistical sources in History of Education

This article intends to contribute to the reflection on the Educational Statistics as being source for the researches on History of Education. The main concern was to reveal the way Educational Statistics related to the period from 1871 to 1931 were produced, in central government. Official reports - from the General Statistics Directory - and Statistics yearbooks released by that department were analyzed and, on this analysis, recommendations and definitions to perform the works were sought. By rending problematic to the documental issues on Educational Statistics and their usual interpretations, the intention was to reduce the ignorance about the origin of the school numbers, which are occasionally used in current researches without the convenient critical exam.

Morphological analysis of pitting corrosion in AISI 310S austenitic stainless steel after salt spray exposition

This paper aims to study evolution of increase, distribution and classification of pits in 310S austenitic stainless steels obtained in the state as-received and heat-treated under different exposure times in saline. This work applicability has been based on a technique development for morphologic characterization of localized corrosion associated with description aspects of shapes, size and population-specific parameters. Methodology has been consisted in the following steps: specimens preparation, corrosion tests via salt spray in different conditions, microstructural analysis, pits profiles analysis and images analysis, digital processing and image analysis in order to characterize the pits distribution, morphology and size. Results obtained in digital processing and profiles image analysis have been subjected to statistical analysis using median as parameter in the alloy as received and treated. The alloy as received displays the following morphology: hemispheric pits> transition region A> transition region B> irregular> conic. The pits amount in the treated alloy at each exposure time is: transition region B> hemispherical> transition region A> conic> irregular.

STATISTICAL EVALUATION OF MATURE LANDFILL LEACHATE TREATMENT BY HOMOGENEOUS CATALYTIC OZONATION

This study presents the results of a mature landfill leachate treated by a homogeneous catalytic ozonation process with ions Fe(2+) and Fe(3+) at acidic pH. Quality assessments were performed using Taguchi`s method (L(8) design). Strong synergism was observed statistically between molecular ozone and ferric ions, pointing to their catalytic effect on (center dot)OH generation. The achievement of better organic matter depollution rates requires an ozone flow of 5 L h(-1) (590 mg h(-1) O(3)) and a ferric ion concentration of 5 mg L(-1).

The cultural adaptation and validation of the ""Burn Specific Health Scale-Revised"" (BSHS-R): Version for Brazilian burn victims

Background: The Burns Specific Health Scale-Revised (BSHS-R) is of easy application, can be self-administered, and it is considered a good scale to evaluate various important life aspects of burn victims. Objectives: To translate and culturally adapt the BSHS-R into the Brazilian-Portuguese language and to evaluate the internal consistency and convergent validity of the translated BSHS-R. Methods: The cultural adaptation of the BSHS-R included translation and back-translation, discussions with professionals and patients to ensure conceptual equivalence, semantic evaluation, and pre-test of the instrument. The Final Brazilian-Portuguese Version (FBPV) of the BSHS-R was tested on a group of 115 burn patients for internal consistency and validity of construct (using the Rosenberg Self-Esteem Scale (RSES) and the Beck Depression Inventory (BDI)). Results: All values of Cronbach`s alpha were greater than. 8, demonstrating that the internal consistency of the FBPV was very high. Self-esteem was highly correlated with affect and body image (r = .59, p < .001), and with interpersonal relationships (T = .51, p < .001). Correlations between the domains of the FBPV and the BDI were all negative but larger in magnitude than the correlations with RSES. Depression was highly correlated with affect and body image (r = -77, p < .001), and with interpersonal relationships (r = -67, p < .001). Conclusions: The results showed that the adapted version of the BSHS-R into Brazilian-Portuguese fulfills the validity and reliability criteria required from an instrument of health status assessment for burn patients. (C) 2008 Elsevier Ltd and ISBI. All rights reserved.

Automatic tuning method for the design of supplementary damping controllers for flexible alternating current transmission system devices

The design of supplementary damping controllers to mitigate the effects of electromechanical oscillations in power systems is a highly complex and time-consuming process, which requires a significant amount of knowledge from the part of the designer. In this study, the authors propose an automatic technique that takes the burden of tuning the controller parameters away from the power engineer and places it on the computer. Unlike other approaches that do the same based on robust control theories or evolutionary computing techniques, our proposed procedure uses an optimisation algorithm that works over a formulation of the classical tuning problem in terms of bilinear matrix inequalities. Using this formulation, it is possible to apply linear matrix inequality solvers to find a solution to the tuning problem via an iterative process, with the advantage that these solvers are widely available and have well-known convergence properties. The proposed algorithm is applied to tune the parameters of supplementary controllers for thyristor controlled series capacitors placed in the New England/New York benchmark test system, aiming at the improvement of the damping factor of inter-area modes, under several different operating conditions. The results of the linear analysis are validated by non-linear simulation and demonstrate the effectiveness of the proposed procedure.

Roughness and surface material effects on nucleate boiling heat transfer from cylindrical surfaces to refrigerants R-134a and R-123

This paper presents results of an experimental investigation carried out to determine the effects of the surface roughness of different materials on nucleate boiling heat transfer of refrigerants R-134a and R-123. Experiments have been performed over cylindrical surfaces of copper, brass and stainless steel. Surfaces have been treated by different methods in order to obtain an average roughness, Ra, varying from 0.03 mu m to 10.5 mu m. Boiling curves at different reduced pressures have been raised as part of the investigation. The obtained results have shown significant effects of the surface material, with brass being the best performing and stainless steel the worst. Polished surfaces seem to present slightly better performance than the sand paper roughened. Boiling on very rough surfaces presents a peculiar behavior characterized by good thermal performance at low heat fluxes, the performance deteriorating at high heat fluxes with respect to smoother surfaces. (C) 2008 Elsevier Inc. All rights reserved.

Electrochemical treatment of tannery wastewater using DSA (R) electrodes

In this work we studied the electrochemical treatment of a tannery wastewater using dimensionally stable anodes (DSA (R)) containing tin, iridium, ruthenium, and titanium. The electrodes were prepared by thermal decomposition of the polymeric precursors. The electrolyses were performed under galvanostatic conditions, at room temperature. Effects of the oxide composition, current density, and effluent conductivity were investigated, and the current efficiency was calculated as a function of the time for the performed electrolyses. Results showed that all the studied electrodes led to a decrease in the content of both total phenolic compounds and total organic carbon (TOC), as well as lower absorbance in the UV-vis region. Toxicity tests using Daphnia similis demonstrated that the electrochemical treatment reduced the wastewater toxicity. The use of DSA (R) type electrodes in the electrochemical treatment of tannery wastewater proved to be useful since it can promote a decrease in total phenolic compounds, TOC, absorbance, and toxicity. (C) 2007 Elsevier B.V. All rights reserved.

Exploring the potential of functionally graded materials concept for the development of fiber cement

In this study we establish the concept of functionally graded fiber cement. We discuss the use of statistical mixture designs to choose formulations and present ideas for the production of functionally graded fiber cement components for Hatschek machines. The feasibility of producing functionally graded fiber cement by grading PVA fiber content has been experimentally evaluated. Thermogravimetric analysis (TG) was employed to assess fiber distribution profiles and four-point bending tests were applied to evaluate the mechanical performance of both conventional and graded composites. The results show that grading PVA fiber content is an effective way to produce functionally graded fiber cement, which allows for a reduction of the total fiber volume without a significant reduction on modulus of rupture of composite. TG tests were found adequate to assess the fiber content at different points in functionally graded fiber cements. (C) 2009 Elsevier Ltd. All rights reserved.

Adaptive Approach for a Maximum Entropy Algorithm in Ecological Niche Modeling

This paper presents an Adaptive Maximum Entropy (AME) approach for modeling biological species. The Maximum Entropy algorithm (MaxEnt) is one of the most used methods in modeling biological species geographical distribution. The approach presented here is an alternative to the classical algorithm. Instead of using the same set features in the training, the AME approach tries to insert or to remove a single feature at each iteration. The aim is to reach the convergence faster without affect the performance of the generated models. The preliminary experiments were well performed. They showed an increasing on performance both in accuracy and in execution time. Comparisons with other algorithms are beyond the scope of this paper. Some important researches are proposed as future works.

Synaptic compensation on Hopfield network: implications for memory rehabilitation

The discrete-time neural network proposed by Hopfield can be used for storing and recognizing binary patterns. Here, we investigate how the performance of this network on pattern recognition task is altered when neurons are removed and the weights of the synapses corresponding to these deleted neurons are divided among the remaining synapses. Five distinct ways of distributing such weights are evaluated. We speculate how this numerical work about synaptic compensation may help to guide experimental studies on memory rehabilitation interventions.

Resource use pattern analysis for predicting resource availability in opportunistic grids

This work presents a method for predicting resource availability in opportunistic grids by means of use pattern analysis (UPA), a technique based on non-supervised learning methods. This prediction method is based on the assumption of the existence of several classes of computational resource use patterns, which can be used to predict the resource availability. Trace-driven simulations validate this basic assumptions, which also provide the parameter settings for the accurate learning of resource use patterns. Experiments made with an implementation of the UPA method show the feasibility of its use in the scheduling of grid tasks with very little overhead. The experiments also demonstrate the method`s superiority over other predictive and non-predictive methods. An adaptative prediction method is suggested to deal with the lack of training data at initialization. Further adaptative behaviour is motivated by experiments which show that, in some special environments, reliable resource use patterns may not always be detected. Copyright (C) 2009 John Wiley & Sons, Ltd.

Experimental and theoretical study of transport properties in uniaxially pressed (Bi, Pb)(2)Sr(2)Ca(2)Cu(3)O(10+delta) ceramic samples

Experimental and theoretical studies on the magnetic field dependence of the electrical resistance R(B(a)) and the transport noise (TN) in polycrystalline high-T(c) superconductors subjected to different uniaxial compacting pressures were conducted. X-ray diffraction rocking curves were performed in different surfaces of the samples in order to investigated the degree of texture The results indicated an improvement of the degree of texture with increasing the uniaxial compacting pressure In theoretical simulations of the data, the polycrystalline superconductors were described as a series-parallel array of Josephson devices The intergranular magnetic field is described within the framework of the intragranular flux-trapping model and the distribution of the grain-boundary angles is assumed to follow the Rayleigh statistical function The proposed model describes well the experimental magnetoresistance R(B(a)) data We have found that the behavior of the R(B(a)) curves changes appreciably when different uniaxially compacting pressures are applied to the sample and such a changes are reproduced by the model when different grain-boundary angles distributions are used In addition, changes in the R(B(a)) dependence have their counterparts in the experimental transport noise signals (C) 2009 Elsevier B.V. All rights reserved