On developing efficient applications using conservative distributed simulation paradigm

This paper aims to present, using a set of guidelines, how to apply the conservative distributed simulation paradigm (CMB protocol) to develop efficient applications. Using these guidelines, even a user with little experience on distributed simulation and computer architecture can have good performance on distributed simulations using conservative synchronization protocols for parallel processes.The set of guidelines is focus on a specific application domain, the performance evaluation of computer systems, considering models with coarse granularity and few logical processes and running over two platforms: parallel (high performance communication environment) and distributed (low performance communication environment).

An Optimum-Path Forest framework for intrusion detection in computer networks

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

Continuous-time and discrete-time sliding mode control accomplished using a computer

A computer-based sliding mode control (SMC) is analysed. The control law is accomplished using a computer and A/D and D/A converters. Two SMC designs are presented. The first one is a continuous-time conventional SMC design, with a variable structure law, which does not take into consideration the sampling period. The second one is a discrete-time SMC design, with a smooth sliding law, which does not have a structure variable and takes into consideration the sampling period. Both techniques are applied to control an inverted pendulum system. The performance of both the continuous-time and discrete-time controllers are compared. Simulations and experimental results are shown and the effectiveness of the proposed techniques is analysed.

Optimum-Path Forest Classifier for Large Scale Biometric Applications

This paper addresses biometric identification using large databases, in particular, iris databases. In such applications, it is critical to have low response time, while maintaining an acceptable recognition rate. Thus, the trade-off between speed and accuracy must be evaluated for processing and recognition parts of an identification system. In this paper, a graph-based framework for pattern recognition, called Optimum-Path Forest (OPF), is utilized as a classifier in a pre-developed iris recognition system. The aim of this paper is to verify the effectiveness of OPF in the field of iris recognition, and its performance for various scale iris databases. The existing Gauss-Laguerre Wavelet based coding scheme is used for iris encoding. The performance of the OPF and two other - Hamming and Bayesian - classifiers, is compared using small, medium, and large-scale databases. Such a comparison shows that the OPF has faster response for large-scale databases, thus performing better than the more accurate, but slower, classifiers.

Line based camera calibration in machine vision dynamic applications

The problem of dynamic camera calibration considering moving objects in close range environments using straight lines as references is addressed. A mathematical model for the correspondence of a straight line in the object and image spaces is discussed. This model is based on the equivalence between the vector normal to the interpretation plane in the image space and the vector normal to the rotated interpretation plane in the object space. In order to solve the dynamic camera calibration, Kalman Filtering is applied; an iterative process based on the recursive property of the Kalman Filter is defined, using the sequentially estimated camera orientation parameters to feedback the feature extraction process in the image. For the dynamic case, e.g. an image sequence of a moving object, a state prediction and a covariance matrix for the next instant is obtained using the available estimates and the system model. Filtered state estimates can be computed from these predicted estimates using the Kalman Filtering approach and based on the system model parameters with good quality, for each instant of an image sequence. The proposed approach was tested with simulated and real data. Experiments with real data were carried out in a controlled environment, considering a sequence of images of a moving cube in a linear trajectory over a flat surface.

A linearly-tunable OTA-C sinusoidal oscillator for low-voltage applications

A low-voltage, low-power OTA-C sinusoidal oscillator based on a triode-MOSFET transconductor is here discussed. The classical quadrature model is employed and the transconductor inherent nonlinear characteristic with input voltage is used as the amplitude-stabilization element. An external bias VTUNE linearly adjusts the oscillation frequency. According to a standard 0.8μm CMOS n-well process, a prototype was integrated, with an effective area of 0.28mm2. Experimental data validate the theoretical analysis. For a single 1.8V-supply and 100mV≤VTUNE≤250mV, the oscillation frequency fo ranges from 0.50MHz to 1.125MHz, with a nearly constant gain KVCO=4.16KHz/mV. Maximum output amplitude is 374mVpp @1.12MHz. THD is -41dB @321mVpp. Maximum average consumption is 355μW.

Frequency-adjustable positive sequence detector for power conditioning applications

This paper proposes a novel and simple positive sequence detector (PSD), which is inherently self-adjustable to fundamental frequency deviations by means of a software-based PLL (Phase Locked Loop). Since the proposed positive sequence detector is not based on Fortescue's classical decomposition and no special input filtering is needed, its dynamic response may be as fast as one fundamental cycle. The digital PLL ensures that the positive sequence components can be calculated even under distorted waveform conditions and fundamental frequency deviations. For the purpose of validating the proposed models, the positive sequence detector has been implemented in a PC-based Power Quality Monitor and experimental results illustrate its good performance. The PSD algorithm has also been evaluated in the control loop of a Series Active Filter and simulation results demonstrate its effectiveness in a closed-loop system. Moreover, considering single-phase applications, this paper also proposes a general single-phase PLL and a Fundamental Wave Detector (FWD) immune to frequency variations and waveform distortions. © 2005 IEEE.

Effects in the population inversion of3H4 level in Tm, Tm-Tb and Tm-Eu doped germanate glasses for amplifiers applications

The population inversion of the Tm3+ in GLKZ glass involved in the 1470 nm emission (3H4 → 3F 4) as a function of Tb (or Eu) concentration was calculated by computational simulation for a CW laser pumping at 792 nm. These calculations were performed using the experimental Tm→Tb an Tm→Eu transfer rates and the spectroscopic parameters of the Tm (0.1 mol %) system. The result shows that 0.2 mol % (Tb3+) and 0.4 mol % of Eu3+ ions propitiate best population inversion of Tm3+ (0.1 mol %) maximizing the amplification coefficient of germanate (GLKZ) glass when operating as laser intensity amplification at 1470 nm. Besides the effective deactivation of the 3F4 level, the presence of Tb3+ or Eu 3+ ions introduce a depopulation of the 3H4 emitting level by means of a cross relaxation process with Tm3+ ions. In spite of this, the whole effect is verified to be benefic for using Tm-doped GLKZ glass codoped with Tb3+ or Eu3+ as a suitable material for confectioning optical amplifiers that operates in the S-band for telecommunication.

Recurrent neural network for induction motor speed estimation in industry applications

Many electronic drivers for the induction motor control are based on sensorless technologies. The proposal of this work Is to present an alternative approach of speed estimation, from transient to steady state, using artificial neural networks. The inputs of the network are the RMS voltage, current and speed estimated of the induction motor feedback to the input with a delay of n samples. Simulation results are also presented to validate the proposed approach. © 2006 IEEE.

Spatial clustering applied to health area

The significant volume of work accidents in the cities causes an expressive loss to society. The development of Spatial Data Mining technologies presents a new perspective for the extraction of knowledge from the correlation between conventional and spatial attributes. One of the most important techniques of the Spatial Data Mining is the Spatial Clustering, which clusters similar spatial objects to find a distribution of patterns, taking into account the geographical position of the objects. Applying this technique to the health area, will provide information that can contribute towards the planning of more adequate strategies for the prevention of work accidents. The original contribution of this work is to present an application of tools developed for Spatial Clustering which supply a set of graphic resources that have helped to discover knowledge and support for management in the work accidents area. © 2011 IEEE.

ENCORE: Enhanced Galileo code receiver for surveying applications

In this paper we describe the development of a low-cost high-accuracy Galileo Code receiver, user application software and positioning algorithms for land management applications, which have been implemented using a dedicated FPGA board and dual frequency Galileo E5/L1 Radio Frequency Front-End. The current situation of rural property surveying in Brazil is described and the use of code measurements from the new Galileo signals E5 AltBOC combined with E1 MBOC for use in land management applications is explored. We explain how such approach is expected to allow delivering an absolute positioning solution which could bridge the gap between receivers of high cost/complexity/accuracy based on carrier phase and receivers of lower cost/accuracy based on pseudorange observables. The system is presented together with a detailed description of main components: the Code Receiver and the Application Software. The work presented is part of an ongoing European-Brazilian consortium effort to explore the use of new Galileo for land management applications in Brazil and sponsored by the GNSS Supervisory Authority (GSA).

Computer techniques towards the automatic characterization of graphite particles in metallographic images of industrial materials

The automatic characterization of particles in metallographic images has been paramount, mainly because of the importance of quantifying such microstructures in order to assess the mechanical properties of materials common used in industry. This automated characterization may avoid problems related with fatigue and possible measurement errors. In this paper, computer techniques are used and assessed towards the accomplishment of this crucial industrial goal in an efficient and robust manner. Hence, the use of the most actively pursued machine learning classification techniques. In particularity, Support Vector Machine, Bayesian and Optimum-Path Forest based classifiers, and also the Otsu's method, which is commonly used in computer imaging to binarize automatically simply images and used here to demonstrated the need for more complex methods, are evaluated in the characterization of graphite particles in metallographic images. The statistical based analysis performed confirmed that these computer techniques are efficient solutions to accomplish the aimed characterization. Additionally, the Optimum-Path Forest based classifier demonstrated an overall superior performance, both in terms of accuracy and speed. © 2012 Elsevier Ltd. All rights reserved.

Simulation in NS-2 of DNP3 protocol encapsulated over TCP/IP in smart grid applications

In dealing with computer networks, these allow the flow of information through the resources of various equipment's. This work describes the implementation through the encapsulation of Protocol DNP3, usually employed in Smart Grid communication, in a simulator of discrete events. The NS-2 is a simulator in open source of network events, that facilitate the development of communication networks scenarios considering the protocols involved, in wireless or wired technologies. The objective of this work is to develop the DNP3 protocol encapsulation over a TCP/IP in the in the discrete event Simulator NS-2, allowing an analysis of behavior of a middle or large network sized in Smart Grid applications. © 2013 IEEE.