An analysis of Generalized Symmetrical Components in non sinusoidal three phase systems

This paper presents the study of the so called Generalized Symmetrical Components, proposed by Tenti et. al. to the analysis of unbalanced periodic non sinusoidal three phase systems. As a result, it was possible to establish a proper relationship between such of generalized symmetrical components and Fortescue symmetrical components to the harmonic frequencies that compose a generic periodic non sinusoidal three phase system. © 2011 IEEE.

Symmetrical components applied to electric power networks.

Includes bibliography.

Um estudo das componentes simétricas generalizadas em sistemas trifásicos não senoidais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Symmetristen komponenttien mallinnus

Tässä insinöörityössä suunniteltiin Helsingin ammattikorkeakoululle jakeluverkoissa tapahtuvien oikosulkujen symmetristen komponenttien laskutavan havainnollistamiseen sopiva sijaiskytkentä. Sijaiskytkennässä tärkeitä huomioitavia asioita olivat mm. jännitetaso, havainnollistavien muuntajien oikosulkukestoisuus, jatkokäyttö laboratoriotyönä ja yleinen havainnollistavuus. Työssä on aluksi perehdytty symmetristen komponenttien ja jakeluverkoissa tapahtuvien oikosulkujen teoriaan. Tämän jälkeen mitoitettiin tarvittavan kytkennän komponenttien jännite- ja virtakestoisuudet mahdolliset lisäkäytöt huomioiden. Näiden rajoitusten mukaan perusteella työtä ruvettiin toteuttamaan. Työssä tilattiin sähkön 40 V:n pääjännitetasolle alentava muuntaja syöttämään oikosulun kestävää muuntajaa, jolla simuloitiin jakeluverkon yleisimpiä vikatyyppejä. Jälkimmäiselle muuntajalle mitoitettiin ja hankittiin sisäistä impedanssia vastaava induktanssi. Tämän avulla rakennettiin kokonaisuus, jonka avulla voidaan simuloida kaikkia tapahtuvia oikosulkuja vastaavat sijaiskytkennät. Työhön jätettiin kehittämisvaraa ja muita laboratoriotyön rakentamismahdollisuuksia tulevien insinööritöiden tekijöille.

Modelagem de um motor de indução trifásico operando com tensões desequilibradas por meio de redes neurais artificiais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Principal components and generalized linear modeling in the correlation between hospital admissions and air pollution

OBJECTIVE To analyze the association between concentrations of air pollutants and admissions for respiratory causes in children. METHODS Ecological time series study. Daily figures for hospital admissions of children aged < 6, and daily concentrations of air pollutants (PM10, SO2, NO2, O3 and CO) were analyzed in the Região da Grande Vitória, ES, Southeastern Brazil, from January 2005 to December 2010. For statistical analysis, two techniques were combined: Poisson regression with generalized additive models and principal model component analysis. Those analysis techniques complemented each other and provided more significant estimates in the estimation of relative risk. The models were adjusted for temporal trend, seasonality, day of the week, meteorological factors and autocorrelation. In the final adjustment of the model, it was necessary to include models of the Autoregressive Moving Average Models (p, q) type in the residuals in order to eliminate the autocorrelation structures present in the components. RESULTS For every 10:49 μg/m3 increase (interquartile range) in levels of the pollutant PM10 there was a 3.0% increase in the relative risk estimated using the generalized additive model analysis of main components-seasonal autoregressive – while in the usual generalized additive model, the estimate was 2.0%. CONCLUSIONS Compared to the usual generalized additive model, in general, the proposed aspect of generalized additive model − principal component analysis, showed better results in estimating relative risk and quality of fit.

Determination of the components of the gyration tensor of quartz by oblique incidence transmission two-modulator generalized ellipsometry

The two independent components of the gyration tensor of quartz, g11 and g33, have been spectroscopically measured using a transmission two-modulator generalized ellipsometer. The method is used to determine the optical activity in crystals in directions other than the optic axis, where the linear birefringence is much larger than the optical activity.

Genetic heterogeneity of residual variance : estimation of variance components using double hierarchical generalized linear models

Background: The sensitivity to microenvironmental changes varies among animals and may be under genetic control. It is essential to take this element into account when aiming at breeding robust farm animals. Here, linear mixed models with genetic effects in the residual variance part of the model can be used. Such models have previously been fitted using EM and MCMC algorithms. Results: We propose the use of double hierarchical generalized linear models (DHGLM), where the squared residuals are assumed to be gamma distributed and the residual variance is fitted using a generalized linear model. The algorithm iterates between two sets of mixed model equations, one on the level of observations and one on the level of variances. The method was validated using simulations and also by re-analyzing a data set on pig litter size that was previously analyzed using a Bayesian approach. The pig litter size data contained 10,060 records from 4,149 sows. The DHGLM was implemented using the ASReml software and the algorithm converged within three minutes on a Linux server. The estimates were similar to those previously obtained using Bayesian methodology, especially the variance components in the residual variance part of the model. Conclusions: We have shown that variance components in the residual variance part of a linear mixed model can be estimated using a DHGLM approach. The method enables analyses of animal models with large numbers of observations. An important future development of the DHGLM methodology is to include the genetic correlation between the random effects in the mean and residual variance parts of the model as a parameter of the DHGLM.

Hyperspectral unmixing based on mixtures of Dirichlet components

This paper introduces a new unsupervised hyperspectral unmixing method conceived to linear but highly mixed hyperspectral data sets, in which the simplex of minimum volume, usually estimated by the purely geometrically based algorithms, is far way from the true simplex associated with the endmembers. The proposed method, an extension of our previous studies, resorts to the statistical framework. The abundance fraction prior is a mixture of Dirichlet densities, thus automatically enforcing the constraints on the abundance fractions imposed by the acquisition process, namely, nonnegativity and sum-to-one. A cyclic minimization algorithm is developed where the following are observed: 1) The number of Dirichlet modes is inferred based on the minimum description length principle; 2) a generalized expectation maximization algorithm is derived to infer the model parameters; and 3) a sequence of augmented Lagrangian-based optimizations is used to compute the signatures of the endmembers. Experiments on simulated and real data are presented to show the effectiveness of the proposed algorithm in unmixing problems beyond the reach of the geometrically based state-of-the-art competitors.

Identificació de components inclusius en alguns centres escolars d'educació infantil i primària de la comarca d'Osona

The present essay –which is a pilot study conceived to continue the research in depth in the future- is based in a comparative analysis of educational practice between five different primary and pre-school teaching centres in Osona and the educational practice in inclusive educational centres. The essay introduces the objectives of the research and the theoretical and conceptual framework in which it is based (chapter 1) in relation with the main themes and expressions which are the purpose of the study: comprensivity, inclusive school and inclusive practice. The theoretical framework is linked to the principal regulations applied in our context. The study describes the instruments and procedure analysis describes the instruments and procedure analysis which have been designed and used for a qualitative methodological approach, together with the data obtained from the analysis of five teaching centres (chapter 2). The results from the research show that the practice done in the analised schools are not totally comparable to the ones in the inclusive environment. Notwithsanding, there are some similar points, although not totally coincident, like the fact that either the analysed schools or the ones with an inclusive approach show availability and interest in improving integration of all the pupils in the school, also the teachers work together in some aspects like, evaluation of pupils with special needs, objectives and contents and activities fort he specific kind of pupils with special needs parents and the majority of the analyzed schools, like those fallowing inclusive educational approaches, try the pupils with special needs to develop their acquisition within the ordinary class with adapted material. I think, these verifications, some of them close to inclusive educational practice, could constitute a starting point to analyse our model, in order to offer a common curriculum that could respect the different styles and rhythms of acquisition of all the pupils, so that promoting a more flexible and open schooling. In conclusion, the results of this analysis, although dues to its limits, they can not be generalized, they can help to find the necessary changes to bet for a qualitative education in a school for everyone.

Generalized percolation in random directed networks

We develop a general theory for percolation in directed random networks with arbitrary two-point correlations and bidirectional edgesthat is, edges pointing in both directions simultaneously. These two ingredients alter the previously known scenario and open new views and perspectives on percolation phenomena. Equations for the percolation threshold and the sizes of the giant components are derived in the most general case. We also present simulation results for a particular example of uncorrelated network with bidirectional edges confirming the theoretical predictions.

Estimating parameters for generalized mass action models using constraint propagation.

As modern molecular biology moves towards the analysis of biological systems as opposed to their individual components, the need for appropriate mathematical and computational techniques for understanding the dynamics and structure of such systems is becoming more pressing. For example, the modeling of biochemical systems using ordinary differential equations (ODEs) based on high-throughput, time-dense profiles is becoming more common-place, which is necessitating the development of improved techniques to estimate model parameters from such data. Due to the high dimensionality of this estimation problem, straight-forward optimization strategies rarely produce correct parameter values, and hence current methods tend to utilize genetic/evolutionary algorithms to perform non-linear parameter fitting. Here, we describe a completely deterministic approach, which is based on interval analysis. This allows us to examine entire sets of parameters, and thus to exhaust the global search within a finite number of steps. In particular, we show how our method may be applied to a generic class of ODEs used for modeling biochemical systems called Generalized Mass Action Models (GMAs). In addition, we show that for GMAs our method is amenable to the technique in interval arithmetic called constraint propagation, which allows great improvement of its efficiency. To illustrate the applicability of our method we apply it to some networks of biochemical reactions appearing in the literature, showing in particular that, in addition to estimating system parameters in the absence of noise, our method may also be used to recover the topology of these networks.

PRPF mutations are associated with generalized defects in spliceosome formation and pre-mRNA splicing in patients with retinitis pigmentosa.

Proteins PRPF31, PRPF3 and PRPF8 (RP-PRPFs) are ubiquitously expressed components of the spliceosome, a macromolecular complex that processes nearly all pre-mRNAs. Although these spliceosomal proteins are conserved in eukaryotes and are essential for survival, heterozygous mutations in human RP-PRPF genes lead to retinitis pigmentosa, a hereditary disease restricted to the eye. Using cells from patients with 10 different mutations, we show that all clinically relevant RP-PRPF defects affect the stoichiometry of spliceosomal small nuclear RNAs (snRNAs), the protein composition of tri-small nuclear ribonucleoproteins and the kinetics of spliceosome assembly. These mutations cause inefficient splicing in vitro and affect constitutive splicing ex-vivo by impairing the removal of at least 9% of endogenously expressed introns. Alternative splicing choices are also affected when RP-PRPF defects are present. Furthermore, we show that the steady-state levels of snRNAs and processed pre-mRNAs are highest in the retina, indicating a particularly elevated splicing activity. Our results suggest a role for PRPFs defects in the etiology of PRPF-linked retinitis pigmentosa, which appears to be a truly systemic splicing disease. Although these mutations cause widespread and important splicing defects, they are likely tolerated by the majority of human tissues but are critical for retinal cell survival.

THE GENERALIZED MAXIMUM LIKELIHOOD METHOD APPLIED TO HIGH PRESSURE PHASE EQUILIBRIUM

The generalized maximum likelihood method was used to determine binary interaction parameters between carbon dioxide and components of orange essential oil. Vapor-liquid equilibrium was modeled with Peng-Robinson and Soave-Redlich-Kwong equations, using a methodology proposed in 1979 by Asselineau, Bogdanic and Vidal. Experimental vapor-liquid equilibrium data on binary mixtures formed with carbon dioxide and compounds usually found in orange essential oil were used to test the model. These systems were chosen to demonstrate that the maximum likelihood method produces binary interaction parameters for cubic equations of state capable of satisfactorily describing phase equilibrium, even for a binary such as ethanol/CO2. Results corroborate that the Peng-Robinson, as well as the Soave-Redlich-Kwong, equation can be used to describe phase equilibrium for the following systems: components of essential oil of orange/CO2.

Fabrication and characterization of micromachined rectangular waveguide components for use at millimeter-wave and terahertz frequencies

The fabrication and characterization of micromachined reduced-height air-filled rectangular waveguide components suitable for integration is reported in this paper. The lithographic technique used permits structures with heights of up to 100 μm to be successfully constructed in a repeatable manner. Waveguide S-parameter measurements at frequencies between 75-110 GHz using a vector network analyzer demonstrate low loss propagation in the TE10 mode reaching 0.2 dB per wavelength. Scanning electron microscope photographs of conventional and micromachined waveguides show that the fabrication technique can provide a superior surface finish than possible with commercially available components. In order to circumvent problems in efficiently coupling free-space propagating beams to the reduced-height G-band waveguides, as well as to characterize them using quasi-optical techniques, a novel integrated micromachined slotted horn antenna has been designed and fabricated, E-, H-, and D-plane far-field antenna pattern measurements at different frequencies using a quasi-optical setup show that the fabricated structures are optimized for 180-GHz operation with an E-plane half-power beamwidth of 32° elevated 35° above the substrate, a symmetrical H-plane pattern with a half-power beamwidth of 23° and a maximum D-plane cross-polar level of -33 dB. Far-field pattern simulations using HFSS show good agreement with experimental results.