Radio-wave propagation model for UHF band in different climatic conditions with dyadic green’s function

This article proposes a deterministic radio propagation model using dyadic Green's function to predict the value of the electric field. Dyadic is offered as an efficient mathematical tool which has symbolic simplicity and robustness, as well as taking account of the anisotropy of the medium. The proposed model is an important contribution for the UHF band because it considers climatic conditions by changing the constants of the medium. Most models and recommendations that include an approach for climatic conditions, are designed for satellite links, mainly Ku and Ka bands. The results obtained by simulation are compared and validated with data from a Digital Television Station measurement campaigns conducted in the Belém city in Amazon region during two seasons. The proposed model was able to provide satisfactory results by differentiating between the curves for dry and wet soil and these corroborate the measured data, (the RMS errors are between 2-5 dB in the case under study).

Microsatellite analysis supports clonal propagation and reduced divergence of Trypanosoma vivax from asymptomatic to fatally infected livestock in South America compared to West Africa

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A path- and label-cost propagation approach to speedup the training of the optimum-path forest classifier

In general, pattern recognition techniques require a high computational burden for learning the discriminating functions that are responsible to separate samples from distinct classes. As such, there are several studies that make effort to employ machine learning algorithms in the context of big data classification problems. The research on this area ranges from Graphics Processing Units-based implementations to mathematical optimizations, being the main drawback of the former approaches to be dependent on the graphic video card. Here, we propose an architecture-independent optimization approach for the optimum-path forest (OPF) classifier, that is designed using a theoretical formulation that relates the minimum spanning tree with the minimum spanning forest generated by the OPF over the training dataset. The experiments have shown that the approach proposed can be faster than the traditional one in five public datasets, being also as accurate as the original OPF. (C) 2014 Elsevier B. V. All rights reserved.

Prototype Fault Current Limiter Using Transformer and a Modular Device of YBCO Coated Conductor

A superconducting fault current limiter (SCFL) consisted of a transformer with low reactance connected to the power line and with the secondary winding short-circuited by a modular superconducting limiter device with 16 elements connected in series was constructed and tested. The designed coupling transformer has low dispersion reactance in order to limit the voltage drop in the power line within the range of 5 % to 10 %. The experimental results showed that an insertion of a 0.125 Omega resistance limited the peak current to a factor of 2.5 times of the unlimited current. The power dissipation reached 39 kW during 100 ms, with an energy density of 380 J/cm(3). Based on these results, the SCFL will be further tested in a 3 MVA (15 kV/380 V) generator for currents up to 10 kA.

Theoretical Analysis and Experimental Validation of the Scholte Wave Propagation in Immersed Plates for the Characterization of Viscous Fluids

This work reports the study of an attractive interfacial wave for application in ultrasonic NDE techniques for inspection and fluid characterization. This wave, called quasi-Scholte mode, is a kind of flexural wave in a plate in contact with a fluid which presents a good sensitivity to the fluid properties. In order to explore this feature, the phase velocity curve of quasi-Scholte mode is experimentally measured in a plate in contact with a viscous fluid, showing a good agreement with theory.

Fast fault section estimation in distribution control centers using adaptive genetic algorithm

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Development and test of resistive superconducting fault current limiter; acting time and its recovery conditions

Resistive-type of superconducting fault current limiters (RSFCL) have been developed for medium voltage class aiming to operate at 1 MVA power capacity and short time recovery (< 2 s). A RSFCL in form of superconducting modular device was designed and constructed using 50 m-length of YBCO coated conductor tapes for operation under 1 kV / 1 kA and acting time of 0.1 s. In order to increase the acting time the RSFCL was combined with an air-core reactor in parallel to increase the fault limiting time up to 1 s. The tests determined the electrical and thermal characteristics of the combined resistive/ inductive protection unit. The combined fault current limiter reached a limiting current of 583 A, corresponding to a limiting factor of 3.3 times within an acting time of up to 1 s.

Modeling the formation and propagation of desiccation cracks in soils

The problem of desiccation cracks in soils has received increasing attention in the last few years, in both experimental investigations and modeling. Experimental research has been mainly focused on the behavior of slurries subjected to drying in plates of different shapes, sizes and thickness. The main objectives of these studies were to learn about the process of crack formation under controlled environmental conditions, and also to better understand the effect of different factors (e.g. soil type, boundary conditions, soil thickness) on the morphology of the crack network. As for the numerical modeling, different approaches have been suggested lately to describe the behavior of drying cracks in soils. One aspect that it is still difficult to describe properly is the crack pattern observed in desiccated soils. This work presents a novel technique to model the behavior of drying soils. The crack patter observed in desiccation tests on circular plates are simulated with the main objective of predicting the effect of soil thickness on crack pattern. Good agreement between experimental results and model prediction are observed.

An Empirical Study of Fault Localization for End-User Programmers

End users develop more software than any other group of programmers, using software authoring devices such as e-mail filtering editors, by-demonstration macro builders, and spreadsheet environments. Despite this, there has been little research on finding ways to help these programmers with the dependability of their software. We have been addressing this problem in several ways, one of which includes supporting end-user debugging activities through fault localization techniques. This paper presents the results of an empirical study conducted in an end-user programming environment to examine the impact of two separate factors in fault localization techniques that affect technique effectiveness. Our results shed new insights into fault localization techniques for end-user programmers and the factors that affect them, with significant implications for the evaluation of those techniques.

Incorporating Varying Test Costs and Fault Severities into Test Case Prioritization

Test case prioritization techniques schedule test cases for regression testing in an order that increases their ability to meet some performance goal. One performance goal, rate offault detection, measures how quickly faults are detected within the testing process. In previous work we provided a metric, APFD, for measuring rate of fault detection, and techniques for prioritizing test cases to improve APFD, and reported the results of experiments using those techniques. This metric and these techniques, however, applied only in cases in which test costs and fault severity are uniform. In this paper, we present a new metric for assessing the rate of fault detection of prioritized test cases, that incorporates varying test case and fault costs. We present the results of a case study illustrating the application of the metric. This study raises several practical questions that might arise in applying test case prioritization; we discuss how practitioners could go about answering these questions.

Efficient Placement of Fault Indicators in an Actual Distribution System Using Evolutionary Computing

This paper proposes an evolutionary computing strategy to solve the problem of fault indicator (FI) placement in primary distribution feeders. More specifically, a genetic algorithm (GA) is employed to search for an efficient configuration of FIs, located at the best positions on the main feeder of a real-life distribution system. Thus, the problem is modeled as one of optimization, aimed at improving the distribution reliability indices, while, at the same time, finding the least expensive solution. Based on actual data, the results confirm the efficiency of the GA approach to the FI placement problem.

VEGETATIVE PROPAGATION OF ANGICO-VERMELHO Anadenanthera macrocarpa (Benth) Brenan) HALF-SIBS BY MINI-CUTTINGS

The objective of this work is to evaluate the efficiency of the mini-cuttings technique in the vegetative propagation of half-sibs of angico-vermelho (Anadenanthera macrocarpa(Benth) Brenan) regarding to the productive capacity and survival of mini-stumps, rooting of the apical and intermediate mini-cuttings treated with different doses of IBA (0, 2000, 4000 and 6000 mg L-1) as well as to determine the speed of rooting in the greenhouse. The mini-stumps were obtained from seedlings of the six progenies of Anadenanthera macrocarpa half-sibs. The mini-stumps presented productivity from 1,2 to 3,7 mini-cuttings/mini-stump/collection and survival of 84% to 98% after six harvests. The apical mini-cuttings were higher than the intermediate, more prone to root, but the IBA had no significant effect on the rooting of the progenies. The results of the rooting speed showed variation among the progenies.

In vitro propagation of Sacha inchi

The aim of this study was to perform an in vitro evaluation of the auxin: cytokinine ratio in different segments of the epicotyl and hypocotyl of Sacha inchi (Plukenetia Volubilis Linneo) seeds germinated in vitro. The segments apical (A), median (B) and basal (C) were introduced into semi-solid MS culture medium (2.0g L-1 Phytagel), supplemented with MS vitamins, sucrose (30.0g L-1) and submitted to three doses of auxin indolebutyric acid - IBA (0; 0.1; 0.5mg L-1), associated with four doses of the cytokinine benzylaminopurine - BAP (0; 0.1; 0.5; 1.0mg L-1), totaling 36 treatments. After nine weeks of in vitro cultivation, the apical segment ( A) presented shoot formation by direct organogenesis at the concentrations of 0.5 and 1.0 of BAP associated with 0.0 and 0.1 of IBA. It is feasible to use in vitro cultivation with the apical region of seeds germinated in vitro used as explants.

Signal propagation in Bayesian networks and its relationship with intrinsically multivariate predictive variables

A set of predictor variables is said to be intrinsically multivariate predictive (IMP) for a target variable if all properly contained subsets of the predictor set are poor predictors of the. target but the full set predicts the target with great accuracy. In a previous article, the main properties of IMP Boolean variables have been analytically described, including the introduction of the IMP score, a metric based on the coefficient of determination (CoD) as a measure of predictiveness with respect to the target variable. It was shown that the IMP score depends on four main properties: logic of connection, predictive power, covariance between predictors and marginal predictor probabilities (biases). This paper extends that work to a broader context, in an attempt to characterize properties of discrete Bayesian networks that contribute to the presence of variables (network nodes) with high IMP scores. We have found that there is a relationship between the IMP score of a node and its territory size, i.e., its position along a pathway with one source: nodes far from the source display larger IMP scores than those closer to the source, and longer pathways display larger maximum IMP scores. This appears to be a consequence of the fact that nodes with small territory have larger probability of having highly covariate predictors, which leads to smaller IMP scores. In addition, a larger number of XOR and NXOR predictive logic relationships has positive influence over the maximum IMP score found in the pathway. This work presents analytical results based on a simple structure network and an analysis involving random networks constructed by computational simulations. Finally, results from a real Bayesian network application are provided. (C) 2012 Elsevier Inc. All rights reserved.

EFFICIENT FAULT LOCATION IN UNDERGROUND DISTRIBUTION SYSTEMS THROUGH OPTIMUM-PATH FOREST

In this article we propose an efficient and accurate method for fault location in underground distribution systems by means of an Optimum-Path Forest (OPF) classifier. We applied the time domains reflectometry method for signal acquisition, which was further analyzed by OPF and several other well-known pattern recognition techniques. The results indicated that OPF and support vector machines outperformed artificial neural networks and a Bayesian classifier, but OPF was much more efficient than all classifiers for training, and the second fastest for classification.