Hybrid fault diagnosis scheme implementation for power distribution systems automation

Power distribution automation and control are import-ant tools in the current restructured electricity markets. Unfortunately, due to its stochastic nature, distribution systems faults are hardly avoidable. This paper proposes a novel fault diagnosis scheme for power distribution systems, composed by three different processes: fault detection and classification, fault location, and fault section determination. The fault detection and classification technique is wavelet based. The fault-location technique is impedance based and uses local voltage and current fundamental phasors. The fault section determination method is artificial neural network based and uses the local current and voltage signals to estimate the faulted section. The proposed hybrid scheme was validated through Alternate Transient Program/Electromagentic Transients Program simulations and was implemented as embedded software. It is currently used as a fault diagnosis tool in a Southern Brazilian power distribution company.

An EFG method for the nonlinear analysis of plates undergoing arbitrarily large deformations

The applicability of a meshfree approximation method, namely the EFG method, on fully geometrically exact analysis of plates is investigated. Based on a unified nonlinear theory of plates, which allows for arbitrarily large rotations and displacements, a Galerkin approximation via MLS functions is settled. A hybrid method of analysis is proposed, where the solution is obtained by the independent approximation of the generalized internal displacement fields and the generalized boundary tractions. A consistent linearization procedure is performed, resulting in a semi-definite generalized tangent stiffness matrix which, for hyperelastic materials and conservative loadings, is always symmetric (even for configurations far from the generalized equilibrium trajectory). Besides the total Lagrangian formulation, an updated version is also presented, which enables the treatment of rotations beyond the parameterization limit. An extension of the arc-length method that includes the generalized domain displacement fields, the generalized boundary tractions and the load parameter in the constraint equation of the hyper-ellipsis is proposed to solve the resulting nonlinear problem. Extending the hybrid-displacement formulation, a multi-region decomposition is proposed to handle complex geometries. A criterium for the classification of the equilibrium`s stability, based on the Bordered-Hessian matrix analysis, is suggested. Several numerical examples are presented, illustrating the effectiveness of the method. Differently from the standard finite element methods (FEM), the resulting solutions are (arbitrary) smooth generalized displacement and stress fields. (c) 2007 Elsevier Ltd. All rights reserved.

Computational Method to Determine Reflected Ultrasonic Signals From Arbitrary-Geometry Targets

A computational method based on the impulse response and on the discrete representation computational concept is proposed for the determination of the echo responses from arbitrary-geometry targets. It is supposed that each point of the transducer aperture can be considered as a source radiating hemispherical waves to the reflector. The local interaction with each of the hemispherical waves at the reflector surface can be modeled as a plane wave impinging on a planar surface, using the respective reflection coefficient. The method is valid for all field regions and can be performed for any excitation waveform radiated from an arbitrary acoustic aperture. The effects of target geometry, position, and material on both the amplitude and the shape of the echo response are studied. The model is compared with experimental results obtained using broadband transducers together with plane and cylindrical concave rectangular reflectors (aluminum, brass, and acrylic), as well as a circular cavity placed on a plane surface, in a water medium. The method can predict the measured echoes accurately. This paper shows an improved approach of the method, considering the reflection coefficient for all incident hemispherical waves arriving at each point of the target surface.

Local search multiuser detection

In this work, a wide analysis of local search multiuser detection (LS-MUD) for direct sequence/code division multiple access (DS/CDMA) systems under multipath channels is carried out considering the performance-complexity trade-off. It is verified the robustness of the LS-MUD to variations in loading, E(b)/N(0), near-far effect, number of fingers of the Rake receiver and errors in the channel coefficients estimates. A compared analysis of the bit error rate (BER) and complexity trade-off is accomplished among LS, genetic algorithm (GA) and particle swarm optimization (PSO). Based on the deterministic behavior of the LS algorithm, it is also proposed simplifications over the cost function calculation, obtaining more efficient algorithms (simplified and combined LS-MUD versions) and creating new perspectives for the MUD implementation. The computational complexity is expressed in terms of the number of operations in order to converge. Our conclusion pointed out that the simplified LS (s-LS) method is always more efficient, independent of the system conditions, achieving a better performance with a lower complexity than the others heuristics detectors. Associated to this, the deterministic strategy and absence of input parameters made the s-LS algorithm the most appropriate for the MUD problem. (C) 2008 Elsevier GmbH. All rights reserved.

XAS characterization of the RuO(2)-Ta(2)O(5) system local (crystal) structure

The influence of the preparation method on the structural properties of the RuO(2)-Ta(2)O(5) system was investigated. Both thin films on Ti substrates and powder samples of nominal composition Ti/RuO(2)-Ta(2)O(5) (Ru:Ta = 100:0, 90:10, 80:20, 30:70, and 0:100 at.%) were prepared through thermal decomposition of polymeric precursors (DPP). The thin films and powder samples were investigated using X-ray absorption spectroscopy (XAS). XANES analyses showed that Ru and Ta are present in the Ru(IV) and Ta(V) oxidation states. EXAFS signals of all the samples were analyzed, to obtain the average bond length (r), coordination number, and the Debye-Waller factor (sigma(2)) for each Ru-O, Ru-Ru, Ta-O nearest-neighbor. The first shell Ru-O distance was found at 1.91-1.92 angstrom with coordination number of 1.8-2.1, and at 2.01-2.02 angstrom with coordination number of 3.9-4.1. The Ta-O distance obtained for all the samples and in both modes (transmission and fluorescence) had significantly different values from the theoretical ones. The results revealed that the local structure around both the Ru and Ta sites are similar, and that they consist of distorted M-O(6) octahedra (where M = Ru or Ta). (C) 2010 Elsevier B.V. All rights reserved.

Decline in homicide rates in Sao Paulo, Brasil: a descriptive analysis

Objective. To describe homicide mortality in the municipality of Sao Paulo according to type of weapon, sex, race or skin color, age, and areas of socioeconomic inequalities, between 1996 and 2008. Method. For this ecological time-series study, data about deaths in the municipality of Sao Paulo were collected from the municipal program for improvement of mortality information, using International Classification of Diseases, 10th revision (ICD-10) codes. Homicide mortality rates (HMR) were calculated for the overall population and specifically for each sex, race or skin color, age range, type of weapon, and occurrence in social deprivation/affluence areas. HMR were adjusted for age using the direct method. The percentage age of variation in HMR was calculated for the study period. For areas of socioeconomic inequalities, the relative risk of death from homicide was calculated. Results. HMR fell 73.7% between 2001 and 2008. A reduction in HMR was observed in all groups, especially males (-74.5%), young men between 15 and 24 years of age (-78.0%), and residents in areas of extreme socioeconomic deprivation (-79.3%). The reduction occurred mostly in firearm homicide rates (-74.1%). The relative risk of death from homicide in areas of extreme socioeconomic deprivation, as compared to areas with some degree of socioeconomic deprivation, was 2.77 in 1996, 3.9 in 2001, and 2.13 in 2008. In areas of high socioeconomic deprivation, the relative risk was 2.07 in 1996 and 1.96 in 2008. Conclusions. To understand the reduction in homicide rates in the municipality of Sao Paulo, it is important to take into consideration macrodeterminants that affect the entire municipality and all population subgroups, as well as micro/local determinants that have special impact on homicides committed with firearms and on subgroups such as the young, males, and residents of areas of high socioeconomic deprivation.

Hyperplane navigation: A method to set individual scores in fMRI group datasets

Recent studies have demonstrated that spatial patterns of fMRI BOLD activity distribution over the brain may be used to classify different groups or mental states. These studies are based on the application of advanced pattern recognition approaches and multivariate statistical classifiers. Most published articles in this field are focused on improving the accuracy rates and many approaches have been proposed to accomplish this task. Nevertheless, a point inherent to most machine learning methods (and still relatively unexplored in neuroimaging) is how the discriminative information can be used to characterize groups and their differences. In this work, we introduce the Maximum Uncertainty Linear Discrimination Analysis (MLDA) and show how it can be applied to infer groups` patterns by discriminant hyperplane navigation. In addition, we show that it naturally defines a behavioral score, i.e., an index quantifying the distance between the states of a subject from predefined groups. We validate and illustrate this approach using a motor block design fMRI experiment data with 35 subjects. (C) 2008 Elsevier Inc. All rights reserved.

Classification System of Raman Spectra using Cluster Analysis to Diagnose Coronary Artery Lesions

The traditional methods employed to detect atherosclerotic lesions allow for the identification of lesions; however, they do not provide specific characterization of the lesion`s biochemistry. Currently, Raman spectroscopy techniques are widely used as a characterization method for unknown substances, which makes this technique very important for detecting atherosclerotic lesions. The spectral interpretation is based on the analysis of frequency peaks present in the signal; however, spectra obtained from the same substance can show peaks slightly different and these differences make difficult the creation of an automatic method for spectral signal analysis. This paper presents a signal analysis method based on a clustering technique that allows for the classification of spectra as well as the inference of a diagnosis about the arterial wall condition. The objective is to develop a computational tool that is able to create clusters of spectra according to the arterial wall state and, after data collection, to allow for the classification of a specific spectrum into its correct cluster.

Characterization of a Local Renin-Angiotensin System in Rat Gingival Tissue

Background: The systemic renin-angiotensin system (RAS) promotes the plasmatic production of angiotensin (Ang) II, which acts through interaction with specific receptors. There is growing evidence that local systems in various tissues and organs are capable of generating angiotensins independently of circulating RAS. The aims of this study were to investigate the expression and localization of RAS components in rat gingival tissue and evaluate the in vitro production of Ang II and other peptides catalyzed by rat gingival tissue homogenates incubated with different Ang II precursors. Methods: Reverse transcription - polymerase chain reaction assessed mRNA expression. Immunohistochemical analysis aimed to detect and localize renin. A standardized fluorimetric method with tripeptide hippuryl-histidyl-leucine was used to measure tissue angiotensin-converting enzyme (ACE) activity, whereas high performance liquid chromatography showed products formed after the incubation of tissue homogenates with Ang I or tetradecapeptide renin substrate (TDP). Results: mRNA for renin, angiotensinogen, ACE, and Ang II receptors (AT(1a), AT(1b), and AT(2)) was detected in gingival tissue; cultured gingival fibroblasts expressed renin, angiotensinogen, and AT(1a) receptor. Renin was present in the vascular endothelium and was intensely expressed in the epithelial basal layer of periodontally affected gingival tissue. ACE activity was detected (4.95 +/- 0.89 nmol histidyl-leucine/g/minute). When Ang I was used as substrate, Ang 1-9 (0.576 +/- 0.128 nmol/mg/minute), Ang II (0.066 +/- 0.008 nmol/mg/minute), and Ang 1-7 (0.111 +/- 0.017 nmol/mg/minute) were formed, whereas these same peptides (0.139 +/- 0.031, 0.206 +/- 0.046, and 0.039 +/- 0.007 nmol/mg/minute, respectively) and Ang 1 (0.973 +/- 0.139 nmol/mg/minute) were formed when TDP was the substrate. Conclusion: Local RAS exists in rat gingival tissue and is capable of generating Ang II and other vasoactive peptides in vitro. J Periodontol 2009;80:130-139.

Outcome Analysis of Immediate and Delayed Conservative Breast Surgery Reconstruction With Mastopexy and Reduction Mammaplasty Techniques

Background: Bilateral mammaplasty or mastopexy is frequently used for oncoplastic objectives. However, little information has been available regarding outcome following immediate and delayed reconstruction. Method: Patients were divided into Group I (immediate reconstruction) and Group II (delayed reconstruction). Retrospective review was performed to compare complications, length of hospital stay, revision surgeries, and satisfaction. The associations between the complications with potential risk factors (timing, age, body mass index, smoking, and comorbid medical conditions) were analyzed. Results: There were a total of 144 patients with a mean follow-up of 47 months. Of the 106 patients in Group I, complications occurred in 24 (22.6%), skin necrosis was observed in 7.5%, fat necrosis in 5.6%, and 6.6% patients developed local recurrence. Mean period of hospitalization was 1.89 days. Of the 38 patients of the Group II, complications occurred in 12 (31.5%), skin necrosis was observed in 7 (18.4%), fat necrosis in 4 (10.5%), and 5.2% patients developed local recurrence. Mean period of hospitalization was 1.35 days. Increased length of hospital stay greater than 1 day (P < 0.001) and the number of revision surgeries (P = 0.043) were associated with the timing of the reconstruction. In univariate analysis, no difference between groups was found with respect to complication incidence (P = 0.275); however, after adjusting for other risk factors, the probability of complications tend to be higher for Group II (OR = 2.65; 95% confidence interval - 1.01-7.00; P = 0.049). Conclusions: On the basis of the results of our study, the probability of complications tends to be higher for delayed reconstructions, and it is demonstrated that obesity and smoking are risk factors for complications. Ultimately, these data may facilitate the provision of individualized risk information for shared medical decision-making.

Genetic algorithm inversion of the average 1D crustal structure using local and regional earthquakes

Knowing the best 1D model of the crustal and upper mantle structure is useful not only for routine hypocenter determination, but also for linearized joint inversions of hypocenters and 3D crustal structure, where a good choice of the initial model can be very important. Here, we tested the combination of a simple GA inversion with the widely used HYPO71 program to find the best three-layer model (upper crust, lower crust, and upper mantle) by minimizing the overall P- and S-arrival residuals, using local and regional earthquakes in two areas of the Brazilian shield. Results from the Tocantins Province (Central Brazil) and the southern border of the Sao Francisco craton (SE Brazil) indicated an average crustal thickness of 38 and 43 km, respectively, consistent with previous estimates from receiver functions and seismic refraction lines. The GA + HYPO71 inversion produced correct Vp/Vs ratios (1.73 and 1.71, respectively), as expected from Wadati diagrams. Tests with synthetic data showed that the method is robust for the crustal thickness, Pn velocity, and Vp/Vs ratio when using events with distance up to about 400 km, despite the small number of events available (7 and 22, respectively). The velocities of the upper and lower crusts, however, are less well constrained. Interestingly, in the Tocantins Province, the GA + HYPO71 inversion showed a secondary solution (local minimum) for the average crustal thickness, besides the global minimum solution, which was caused by the existence of two distinct domains in the Central Brazil with very different crustal thicknesses. (C) 2010 Elsevier Ltd. All rights reserved.

A Survey on Graphical Methods for Classification Predictive Performance Evaluation

Predictive performance evaluation is a fundamental issue in design, development, and deployment of classification systems. As predictive performance evaluation is a multidimensional problem, single scalar summaries such as error rate, although quite convenient due to its simplicity, can seldom evaluate all the aspects that a complete and reliable evaluation must consider. Due to this, various graphical performance evaluation methods are increasingly drawing the attention of machine learning, data mining, and pattern recognition communities. The main advantage of these types of methods resides in their ability to depict the trade-offs between evaluation aspects in a multidimensional space rather than reducing these aspects to an arbitrarily chosen (and often biased) single scalar measure. Furthermore, to appropriately select a suitable graphical method for a given task, it is crucial to identify its strengths and weaknesses. This paper surveys various graphical methods often used for predictive performance evaluation. By presenting these methods in the same framework, we hope this paper may shed some light on deciding which methods are more suitable to use in different situations.

Texture analysis and classification using deterministic tourist walk

In this paper, we present a study on a deterministic partially self-avoiding walk (tourist walk), which provides a novel method for texture feature extraction. The method is able to explore an image on all scales simultaneously. Experiments were conducted using different dynamics concerning the tourist walk. A new strategy, based on histograms. to extract information from its joint probability distribution is presented. The promising results are discussed and compared to the best-known methods for texture description reported in the literature. (C) 2009 Elsevier Ltd. All rights reserved.

Shape classification using complex network and Multi-scale Fractal Dimension

Shape provides one of the most relevant information about an object. This makes shape one of the most important visual attributes used to characterize objects. This paper introduces a novel approach for shape characterization, which combines modeling shape into a complex network and the analysis of its complexity in a dynamic evolution context. Descriptors computed through this approach show to be efficient in shape characterization, incorporating many characteristics, such as scale and rotation invariant. Experiments using two different shape databases (an artificial shapes database and a leaf shape database) are presented in order to evaluate the method. and its results are compared to traditional shape analysis methods found in literature. (C) 2009 Published by Elsevier B.V.

Concentric characterization and classification of complex network nodes: Application to an institutional collaboration network

Differently from theoretical scale-free networks, most real networks present multi-scale behavior, with nodes structured in different types of functional groups and communities. While the majority of approaches for classification of nodes in a complex network has relied on local measurements of the topology/connectivity around each node, valuable information about node functionality can be obtained by concentric (or hierarchical) measurements. This paper extends previous methodologies based on concentric measurements, by studying the possibility of using agglomerative clustering methods, in order to obtain a set of functional groups of nodes, considering particular institutional collaboration network nodes, including various known communities (departments of the University of Sao Paulo). Among the interesting obtained findings, we emphasize the scale-free nature of the network obtained, as well as identification of different patterns of authorship emerging from different areas (e.g. human and exact sciences). Another interesting result concerns the relatively uniform distribution of hubs along concentric levels, contrariwise to the non-uniform pattern found in theoretical scale-free networks such as the BA model. (C) 2008 Elsevier B.V. All rights reserved.