Natural fiber reinforced unsaturated polyester composites - An approach on compression molding

This work has been performed at Tapetes Sao Carlos-Brazil with the cooperation of the DaimlerChrysler Research Center Team in Ulm - Germany. The objective of the present paper is to report the results obtained with natural fiber reinforced unsaturated polyester (UP) composites, concerning surface quality measurements. The fibers that have been chosen for this work were sisal and curaua. The samples were produced by compression molding technique and afterwards submitted to three different tests, namely: a) thermal aging; b) water absorption and c) artificial weathering. The surface parameters measured before and after the tests were gloss, haze, short and long-waviness. The results have shown that after the tests there is a high loss of gloss, a high increase in haze, and a high increase in short and long-waviness as well. Curaua reinforced composites had a slightly better behavior when compared with sisal reinforced composites. The effect of the presence of filler and the addition of thermoplastic polyester (TP) on the material behavior has not been evidently detected. This result shows that the conventional technology/methods applied to UP-Fiberglass systems cannot be transferred to natural fibers without any modification. The fiber-matrix interaction and its response to the presence of additives must be fully understood before a successful processing route can be developed for painted natural fibers reinforced UP. Copyright © 2001 Society of Automotive Engineers, Inc.

A Bayesian approach to estimate the accuracy of in-house ELISA assay to measure rabies antibodies from compulsory vaccinated dogs and cattle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A practical approach for biometric authentication based on smartcards

Cryptographic systems are safe. However, the management of cryptographic keys of these systems is a tough task. They are usually protected by the use of password-based authentication mechanisms, which is a weak link on conventional cryptographic systems, as the passwords can be easily copied or stolen. The usage of a biometric approach for releasing the keys is an alternative to the password-based mechanisms. But just like passwords, we need mechanisms to keep the biometrical signal safe. One approach for such mechanism is to use biometrical key cryptography. The cryptographic systems based on the use of biometric characteristics as keys are called biometrical cryptographic systems. This article presents the implementation of Fuzzy Vault, a biometrical cryptographic system written in Java, along with its performance evaluation. Fuzzy Vault was tested on a real application using smartcards.

A First approach on the new transmission system in northern Brazil

This article shows an analysis of the electrical parameters of a three-phase transmission line section using a relatively new design for steel towers characterized by 280 meters high. These main features, the height of the line conductors and distance between them, are intrinsically related to the longitudinal and transversal parameters of the line. By this means, an analysis was carried out in order to show the electrical variations between a transmission line using the new technology and a conventional 440-kV line through a wide range of frequencies and a variable soil resistivity. © 2012 The Institution of Engineering and Technology.

Distributed generators as providers of reactive power support - A market approach

Traditionally, ancillary services are supplied by large conventional generators. However, with the huge penetration of distributed generators (DGs) as a result of the growing interest in satisfying energy requirements, and considering the benefits that they can bring along to the electrical system and to the environment, it appears reasonable to assume that ancillary services could also be provided by DGs in an economical and efficient way. In this paper, a settlement procedure for a reactive power market for DGs in distribution systems is proposed. Attention is directed to wind turbines connected to the network through synchronous generators with permanent magnets and doubly-fed induction generators. The generation uncertainty of this kind of DG is reduced by running a multi-objective optimization algorithm in multiple probabilistic scenarios through the Monte Carlo method and by representing the active power generated by the DGs through Markov models. The objectives to be minimized are the payments of the distribution system operator to the DGs for reactive power, the curtailment of transactions committed in an active power market previously settled, the losses in the lines of the network, and a voltage profile index. The proposed methodology was tested using a modified IEEE 37-bus distribution test system. © 1969-2012 IEEE.

An approach to implement data fusion techniques in wireless sensor networks using genetic machine learning algorithms

Wireless Sensor Networks (WSNs) can be used to monitor hazardous and inaccessible areas. In these situations, the power supply (e.g. battery) of each node cannot be easily replaced. One solution to deal with the limited capacity of current power supplies is to deploy a large number of sensor nodes, since the lifetime and dependability of the network will increase through cooperation among nodes. Applications on WSN may also have other concerns, such as meeting temporal deadlines on message transmissions and maximizing the quality of information. Data fusion is a well-known technique that can be useful for the enhancement of data quality and for the maximization of WSN lifetime. In this paper, we propose an approach that allows the implementation of parallel data fusion techniques in IEEE 802.15.4 networks. One of the main advantages of the proposed approach is that it enables a trade-off between different user-defined metrics through the use of a genetic machine learning algorithm. Simulations and field experiments performed in different communication scenarios highlight significant improvements when compared with, for instance, the Gur Game approach or the implementation of conventional periodic communication techniques over IEEE 802.15.4 networks. © 2013 Elsevier B.V. All rights reserved.

A New Approach to Reducing Search Space and Increasing Efficiency in Simulation Optimization Problems via the Fuzzy-DEA-BCC

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

RNS derivation of N-point disk amplitudes from the revisited S-matrix approach

Recently, in [7] we proposed a revisited S-matrix approach to efficiently find the bosonic terms of the open superstring low energy effective lagrangian (OSLEEL). This approach allows to compute the alpha'(N) terms of the OSLEEL using open superstring n-point amplitudes in which n is considerably lower than (N + 2) (which is the order of the required amplitude to obtain those alpha'(N) terms by means of the conventional S-matrix approach). In this work we use our revisited S-matrix approach to examine the structure of the scattering amplitudes, arriving at a closed form for them. This is a RNS derivation of the formula first found by Mafra, Schlotterer and Stieberger [21], using the pure spinor formalism. We have succeeded doing this for the 5, 6 and 7-point amplitudes. In order to achieve these results we have done a careful analysis of the kinematical structure of the amplitudes, finding as a by-product a purely kinematical derivation of the BCJ relations (for N = 4, 5, 6 and 7). Also, following the spirit of the revisited S-matrix approach, we have found the alpha' expansions for these amplitudes up to alpha'(6) order in some cases, by only using the well known open superstring 4-point amplitude, cyclic symmetry and tree level unitarity: we have not needed to compute any numerical series or any integral involving polylogarithms, at any moment. (C) 2014 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/3.0/).

Surgical time and complications of total transvaginal (total-NOTES), single-port laparoscopic-assisted and conventional ovariohysterectomy in bitches

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

OntoSDM: an approach to improve quality on spatial data mining algorithms

The increase in new electronic devices had generated a considerable increase in obtaining spatial data information; hence these data are becoming more and more widely used. As well as for conventional data, spatial data need to be analyzed so interesting information can be retrieved from them. Therefore, data clustering techniques can be used to extract clusters of a set of spatial data. However, current approaches do not consider the implicit semantics that exist between a region and an object’s attributes. This paper presents an approach that enhances spatial data mining process, so they can use the semantic that exists within a region. A framework was developed, OntoSDM, which enables spatial data mining algorithms to communicate with ontologies in order to enhance the algorithm’s result. The experiments demonstrated a semantically improved result, generating more interesting clusters, therefore reducing manual analysis work of an expert.