962 resultados para Systems identification
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A collection of Rhizobium leguminosarum bv. viciae strains isolated from ultramafic and contaminated soils in Italy and Germany, respectively, was analyzed for resistance to nickel and cobalt ions. These assays led to the identification of strain UPM1137, which is able to grow at high concentrations of nickel and cobalt. In order to identify genetic systems involved in the homeostasis to these metals, a random mutagenesis was carried out in UPM1137 by inserting a Tn5-derivative minitransposon. As a result 4313 transconjugants were obtained, being 39 of them (0.90%) unable to grow at 1.5 mM NiCl2. The identification of the transposon insertion site in these mutants showed that the disrupted genes encode proteins belonging to different functional categories, where the secreted and membrane proteins were the most numerous. The analysis of heavy metal resistance and phenotypes in symbiotic and free –living cells will define the contribution of these genes to metal homeostasis.
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Abstract:The aim of this paper is to review the literature on voting systems based on Condorcet and Borda. We compared and classified them. Also we referred to some strengths and weaknesses of voting systems and finally in a case study, we made use of the Borda voting system for collective decision making in the Salonga National Park in the Democratic Republic of Congo. Resumen: el objetivo de este trabajo es hacer una revisión bibliográfica de los sistemas de votación basados en Condorcet y Borda. Se ha comparado y clasificado los mismos. Así mismo se ha hecho referencia a algunas debilidades y fortalezas de los sistemas de votación y por último en un caso de estudio, se ha hecho uso del sistema de votación de Borda para la toma de decisión colectiva en el Parque Nacional de Salonga en la República Democrática del Congo.
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The location of ground faults in railway electric lines in 2 × 5 kV railway power supply systems is a difficult task. In both 1 × 25 kV and transmission power systems it is common practice to use distance protection relays to clear ground faults and localize their positions. However, in the particular case of this 2 × 25 kV system, due to the widespread use of autotransformers, the relation between the distance and the impedance seen by the distance protection relays is not linear and therefore the location is not accurate enough. This paper presents a simple and economical method to identify the subsection between autotransformers and the conductor (catenary or feeder) where the ground fault is happening. This method is based on the comparison of the angle between the current and the voltage of the positive terminal in each autotransformer. Consequently, after the identification of the subsection and the conductor with the ground defect, only the subsection where the ground fault is present will be quickly removed from service, with the minimum effect on rail traffic. This method has been validated through computer simulations and laboratory tests with positive results.
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Paper submitted to the 44th European Congress of the European Regional Science Association, Porto, 25-29 August 2004.
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Includes bibliographies (p. 27-29).
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"NCJ-104342."
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A new approach to identify multivariable Hammerstein systems is proposed in this paper. By using cardinal cubic spline functions to model the static nonlinearities, the proposed method is effective in modelling processes with hard and/or coupled nonlinearities. With an appropriate transformation, the nonlinear models are parameterized such that the nonlinear identification problem is converted into a linear one. The persistently exciting condition for the transformed input is derived to ensure the estimates are consistent with the true system. A simulation study is performed to demonstrate the effectiveness of the proposed method compared with the existing approaches based on polynomials. (C) 2006 Elsevier Ltd. All rights reserved.
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The aim of this work was to design and build an equipment which can detect ferrous and non-ferrous objects in conveyed commodities, discriminate between them and locate the object along the belt and on the width of the belt. The magnetic induction mechanism was used as a means of achieving the objectives of this research. In order to choose the appropriate geometry and size of the induction field source, the field distributions of different source geometries and sizes were studied in detail. From these investigations it was found the square loop geometry is the most appropriate as a field generating source for the purpose of this project. The phenomena of field distribution in the conductors was also investigated. An equipment was designed and built at the preliminary stages of thework based on a flux-gate magnetometer with the ability to detect only ferrous objects.The instrument was designed such that it could be used to detect ferrous objects in the coal conveyors of power stations. The advantages of employing this detector in the power industry over the present ferrous metal electromagnetic separators were also considered. The objectives of this project culminated in the design and construction of a ferrous and non-ferrous detector with the ability to discriminate between ferrous and non-ferrous metals and to locate the objects on the conveying system. An experimental study was carried out to test the performance of the equipment in the detection of ferrous and non-ferrous objects of a given size carried on the conveyor belt. The ability of the equipment to discriminate between the types of metals and to locate the object on the belt was also evaluated experimentally. The benefits which can be gained from the industrial implementations of the equipment were considered. Further topics which may be investigated as an extension of this work are given.
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This thesis is concerned with the measurement of the characteristics of nonlinear systems by crosscorrelation, using pseudorandom input signals based on m sequences. The systems are characterised by Volterra series, and analytical expressions relating the rth order Volterra kernel to r-dimensional crosscorrelation measurements are derived. It is shown that the two-dimensional crosscorrelation measurements are related to the corresponding second order kernel values by a set of equations which may be structured into a number of independent subsets. The m sequence properties determine how the maximum order of the subsets for off-diagonal values is related to the upper bound of the arguments for nonzero kernel values. The upper bound of the arguments is used as a performance index, and the performance of antisymmetric pseudorandom binary, ternary and quinary signals is investigated. The performance indices obtained above are small in relation to the periods of the corresponding signals. To achieve higher performance with ternary signals, a method is proposed for combining the estimates of the second order kernel values so that the effects of some of the undesirable nonzero values in the fourth order autocorrelation function of the input signal are removed. The identification of the dynamics of two-input, single-output systems with multiplicative nonlinearity is investigated. It is shown that the characteristics of such a system may be determined by crosscorrelation experiments using phase-shifted versions of a common signal as inputs. The effects of nonlinearities on the estimates of system weighting functions obtained by crosscorrelation are also investigated. Results obtained by correlation testing of an industrial process are presented, and the differences between theoretical and experimental results discussed for this case;
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Growth of complexity and functional importance of integrated navigation systems (INS) leads to high losses at the equipment refusals. The paper is devoted to the INS diagnosis system development, allowing identifying the cause of malfunction. The proposed solutions permit taking into account any changes in sensors dynamic and accuracy characteristics by means of the appropriate error models coefficients. Under actual conditions of INS operation, the determination of current values of the sensor models and estimation filter parameters rely on identification procedures. The results of full-scale experiments are given, which corroborate the expediency of INS error models parametric identification in bench test process.
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Electrocardiography (ECG) has been recently proposed as biometric trait for identification purposes. Intra-individual variations of ECG might affect identification performance. These variations are mainly due to Heart Rate Variability (HRV). In particular, HRV causes changes in the QT intervals along the ECG waveforms. This work is aimed at analysing the influence of seven QT interval correction methods (based on population models) on the performance of ECG-fiducial-based identification systems. In addition, we have also considered the influence of training set size, classifier, classifier ensemble as well as the number of consecutive heartbeats in a majority voting scheme. The ECG signals used in this study were collected from thirty-nine subjects within the Physionet open access database. Public domain software was used for fiducial points detection. Results suggested that QT correction is indeed required to improve the performance. However, there is no clear choice among the seven explored approaches for QT correction (identification rate between 0.97 and 0.99). MultiLayer Perceptron and Support Vector Machine seemed to have better generalization capabilities, in terms of classification performance, with respect to Decision Tree-based classifiers. No such strong influence of the training-set size and the number of consecutive heartbeats has been observed on the majority voting scheme.