Simplified approach to low-cost multiparameter monitoring based on low frequency polarization modulation

We experimentally revisit a technique of low-cost multiparameter monitor for optical performance monitoring based on low frequency polarization modulation. A simplified calibration procedure, which significantly reduces the mathematical complexity and processing effort is proposed. Validation is achieved by carrying out relative optical power, wavelength, and differential group delay measurements. (C) 2012 Wiley Periodicals, Inc. Microwave Opt Technol Lett 54:18201824, 2012; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.26956

Enhancing weak signal transmission through a feedforward network

The ability to transmit and amplify weak signals is fundamental to signal processing of artificial devices in engineering. Using a multilayer feedforward network of coupled double-well oscillators as well as Fitzhugh-Nagumo oscillators, we here investigate the conditions under which a weak signal received by the first layer can be transmitted through the network with or without amplitude attenuation. We find that the coupling strength and the nodes' states of the first layer act as two-state switches, which determine whether the transmission is significantly enhanced or exponentially decreased. We hope this finding is useful for designing artificial signal amplifiers.

Algebraic-graph method for identification of islanding in power system grids

In this paper, a new algebraic-graph method for identification of islanding in power system grids is proposed. The proposed method identifies all the possible cases of islanding, due to the loss of a equipment, by means of a factorization of the bus-branch incidence matrix. The main features of this new method include: (i) simple implementation, (ii) high speed, (iii) real-time adaptability, (iv) identification of all islanding cases and (v) identification of the buses that compose each island in case of island formation. The method was successfully tested on large-scale systems such as the reduced south Brazilian system (45 buses/72 branches) and the south-southeast Brazilian system (810 buses/1340 branches). (C) 2011 Elsevier Ltd. All rights reserved.

Experiments on through-wall imaging using ultra wideband radar

Through-wall imaging (TWI) may provide vital information on interior environment in cases when physically entering such environment would pose danger to the person involved. The concept of ultra wideband radar (UWB radar) is an emerging technology, which offers high spatial resolution, as opposed to narrow band radars. Thus, TWI applications using UWB radar have become a growing field of research with several applications in the civil and defense areas such as rescue and surveillance. For this study, a prototype system of UWB radar to TWI has been built. Analyses and result to several kinds of experiments have been presented, that is, detection and visualization of metallic targets behind wooden board wall and concrete blocks wall. The results are encouraging and show the advantages of using UWB radar for TWI. (C) 2011 Wiley Periodicals, Inc. Microwave Opt Technol Lett, 54:339-344, 2012; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.26543

Subdivision of Hysteresis Loss in Mn-Zn Ferrite Toroidal Cores

The hysteresis loss subdivision method proved to be a strong tool to help in the analysis of different energy dissipation mechanisms along the quasi-static hysteresis loop measured on electrical steels. This paper used the samemethod to discuss the mechanisms involving the energy loss dissipation in Mn-Zn ferrite toroidal cores. The samples, sintered under controlled atmosphere in industrial conditions, were measured under triangular waveform excitation at very low frequency (5 mHz) and peak flux densities varying from 0.05 T to 0.45 T. The results show a different behavior between the low inductions hysteresis loss (WLI) and the high induction hysteresis loss (WHI) which proves the existence of different energy dissipation mechanisms affecting these loss components.

Development of a slow-wave MEMS phase shifter on CMOS technology for millimeter wave frequencies

We propose a slow-wave MEMS phase shifter that can be fabricated using the CMOS back-end and an additional maskless post-process etch. The tunable phase shifter concept is formed by a conventional slow-wave transmission line. The metallic ribbons that form the patterned floating shield of this type of structure are released to allow motion when a control voltage is applied, which changes the characteristic impedance and the phase velocity. For this device a quality factor greater than 40 can be maintained, resulting in a figure of merit on the order of 0.7 dB/360 degrees and a total area smaller than 0.14 mm(2) for a 60-GHz working frequency. (C) 2011 Elsevier B.V. All rights reserved.

Java Cryptographic Library for Smartphones

A JME-compliant cryptographic library for mobile application development is introduced in this paper. The library allows cryptographic protocols implementation over elliptic curves with different security levels and offers symmetric and asymmetric bilinear pairings operations, as Tate, Weil, and Ate pairings.

GeoHealth: A Georeferenced System for Health Data Analysis in Primary Care

The Primary Care Information System (SIAB) concentrates basic healthcare information from all different regions of Brazil. The information is collected by primary care teams on a paper-based procedure that degrades the quality of information provided to the healthcare authorities and slows down the process of decision making. To overcome these problems we propose a new data gathering application that uses a mobile device connected to a 3G network and a GPS to be used by the primary care teams for collecting the families' data. A prototype was developed in which a digital version of one SIAB form is made available at the mobile device. The prototype was tested in a basic healthcare unit located in a suburb of Sao Paulo. The results obtained so far have shown that the proposed process is a better alternative for data collecting at primary care, both in terms of data quality and lower deployment time to health care authorities.

A novel strategy for building interoperable MPI environment in heterogeneous high performance systems

Breakthrough advances in microprocessor technology and efficient power management have altered the course of development of processors with the emergence of multi-core processor technology, in order to bring higher level of processing. The utilization of many-core technology has boosted computing power provided by cluster of workstations or SMPs, providing large computational power at an affordable cost using solely commodity components. Different implementations of message-passing libraries and system softwares (including Operating Systems) are installed in such cluster and multi-cluster computing systems. In order to guarantee correct execution of message-passing parallel applications in a computing environment other than that originally the parallel application was developed, review of the application code is needed. In this paper, a hybrid communication interfacing strategy is proposed, to execute a parallel application in a group of computing nodes belonging to different clusters or multi-clusters (computing systems may be running different operating systems and MPI implementations), interconnected with public or private IP addresses, and responding interchangeably to user execution requests. Experimental results demonstrate the feasibility of this proposed strategy and its effectiveness, through the execution of benchmarking parallel applications.

Characterization of Stability Region for General Autonomous Nonlinear Dynamical Systems

The existing characterization of stability regions was developed under the assumption that limit sets on the stability boundary are exclusively composed of hyperbolic equilibrium points and closed orbits. The characterizations derived in this technical note are a generalization of existing results in the theory of stability regions. A characterization of the stability boundary of general autonomous nonlinear dynamical systems is developed under the assumption that limit sets on the stability boundary are composed of a countable number of disjoint and indecomposable components, which can be equilibrium points, closed orbits, quasi-periodic solutions and even chaotic invariant sets.

An analytic method to compute the stress dependence on the dimensions and its influence in the characteristics of triple gate devices

Triple-gate devices are considered a promising solution for sub-20 nm era. Strain engineering has also been recognized as an alternative due to the increase in the carriers mobility it propitiates. The simulation of strained devices has the major drawback of the stress non-uniformity, which cannot be easily considered in a device TCAD simulation without the coupled process simulation that is time consuming and cumbersome task. However, it is mandatory to have accurate device simulation, with good correlation with experimental results of strained devices, allowing for in-depth physical insight as well as prediction on the stress impact on the device electrical characteristics. This work proposes the use of an analytic function, based on the literature, to describe accurately the strain dependence on both channel length and fin width in order to simulate adequately strained triple-gate devices. The maximum transconductance and the threshold voltage are used as the key parameters to compare simulated and experimental data. The results show the agreement of the proposed analytic function with the experimental results. Also, an analysis on the threshold voltage variation is carried out, showing that the stress affects the dependence of the threshold voltage on the temperature. (C) 2011 Elsevier Ltd. All rights reserved.

Network-based high level data classification

Traditional supervised data classification considers only physical features (e. g., distance or similarity) of the input data. Here, this type of learning is called low level classification. On the other hand, the human (animal) brain performs both low and high orders of learning and it has facility in identifying patterns according to the semantic meaning of the input data. Data classification that considers not only physical attributes but also the pattern formation is, here, referred to as high level classification. In this paper, we propose a hybrid classification technique that combines both types of learning. The low level term can be implemented by any classification technique, while the high level term is realized by the extraction of features of the underlying network constructed from the input data. Thus, the former classifies the test instances by their physical features or class topologies, while the latter measures the compliance of the test instances to the pattern formation of the data. Our study shows that the proposed technique not only can realize classification according to the pattern formation, but also is able to improve the performance of traditional classification techniques. Furthermore, as the class configuration's complexity increases, such as the mixture among different classes, a larger portion of the high level term is required to get correct classification. This feature confirms that the high level classification has a special importance in complex situations of classification. Finally, we show how the proposed technique can be employed in a real-world application, where it is capable of identifying variations and distortions of handwritten digit images. As a result, it supplies an improvement in the overall pattern recognition rate.

Stochastic competitive learning in complex networks

Competitive learning is an important machine learning approach which is widely employed in artificial neural networks. In this paper, we present a rigorous definition of a new type of competitive learning scheme realized on large-scale networks. The model consists of several particles walking within the network and competing with each other to occupy as many nodes as possible, while attempting to reject intruder particles. The particle's walking rule is composed of a stochastic combination of random and preferential movements. The model has been applied to solve community detection and data clustering problems. Computer simulations reveal that the proposed technique presents high precision of community and cluster detections, as well as low computational complexity. Moreover, we have developed an efficient method for estimating the most likely number of clusters by using an evaluator index that monitors the information generated by the competition process itself. We hope this paper will provide an alternative way to the study of competitive learning.

Cryptanalysis of an efficient three-party password-based key exchange scheme

Three-party password-authenticated key exchange (3PAKE) protocols allow entities to negotiate a secret session key with the aid of a trusted server with whom they share a human-memorable password. Recently, Lou and Huang proposed a simple 3PAKE protocol based on elliptic curve cryptography, which is claimed to be secure and to provide superior efficiency when compared with similar-purpose solutions. In this paper, however, we show that the solution is vulnerable to key-compromise impersonation and offline password guessing attacks from system insiders or outsiders, which indicates that the empirical approach used to evaluate the scheme's security is flawed. These results highlight the need of employing provable security approaches when designing and analyzing PAKE schemes. Copyright (c) 2011 John Wiley & Sons, Ltd.

A Chaotic Approach of Differential Evolution Optimization Applied to Loudspeaker Design Problem

Over the past few years, the field of global optimization has been very active, producing different kinds of deterministic and stochastic algorithms for optimization in the continuous domain. These days, the use of evolutionary algorithms (EAs) to solve optimization problems is a common practice due to their competitive performance on complex search spaces. EAs are well known for their ability to deal with nonlinear and complex optimization problems. Differential evolution (DE) algorithms are a family of evolutionary optimization techniques that use a rather greedy and less stochastic approach to problem solving, when compared to classical evolutionary algorithms. The main idea is to construct, at each generation, for each element of the population a mutant vector, which is constructed through a specific mutation operation based on adding differences between randomly selected elements of the population to another element. Due to its simple implementation, minimum mathematical processing and good optimization capability, DE has attracted attention. This paper proposes a new approach to solve electromagnetic design problems that combines the DE algorithm with a generator of chaos sequences. This approach is tested on the design of a loudspeaker model with 17 degrees of freedom, for showing its applicability to electromagnetic problems. The results show that the DE algorithm with chaotic sequences presents better, or at least similar, results when compared to the standard DE algorithm and other evolutionary algorithms available in the literature.