A Novel Approach to Accurately Determine the tq Parameter of Thyristors

International audienceThe continued use of high-voltage thyristor devices in industry and their increased use in high-voltage dc transmission systems call for more attention to the properties of these devices. One of the important thyristor parameters is their turn-off time tq, which can be a limiting factor when applying thyristors at elevated switching frequencies. Hence, the accurate measurement of tq and its variation versus the operating conditions remains a crucial task for thyristor converters operating at elevated switching frequencies. In this paper, a proper test circuit for measuring this parameter with a high level of accuracy has been designed and built. Owing to the test circuit specificity, the variation effects of several electrical and physical constraints, such as the forward current IF , the reverse applied voltage VR, the operating temperature To, and the ramp rate of the forward reapplied voltage dVD/dt, on the tq parameter of thyristors are also studied and analyzed based on the physics of semiconductor devices and associated simulations

CATSCALE: A stochastic multidimensional scaling methodology for the spatial analysis of sorting data and the study of stimulus categorization

Sorting tasks have provided researchers with valuable alternatives to traditional paired-comparison similarity judgments. They are particularly well-suited to studies involving large stimulus sets where exhaustive paired-comparison judgments become infeasible, especially in psychological studies investigating stimulus categorization. This paper presents a new stochastic multidimensional scaling procedure called CATSCALE for the analysis of three-way sorting data (as typically collected in categorization studies). We briefly present a review of the role of sorting tasks, especially in categorization studies, as well as a description of several traditional modes of analysis. The CATSCALE model and maximum likelihood based estimation procedure are described. An application of CATSCALE is presented with respect to a behavioral accounting study examining auditor's categorization processes with respect to various types of errors found in typical financial statements.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/31400/1/0000315.pd

Multiclus: A new method for simultaneously performing multidimensional scaling and cluster analysis

This paper develops a maximum likelihood based method for simultaneously performing multidimensional scaling and cluster analysis on two-way dominance or profile data. This MULTICLUS procedure utilizes mixtures of multivariate conditional normal distributions to estimate a joint space of stimulus coordinates and K vectors, one for each cluster or group, in a T -dimensional space. The conditional mixture, maximum likelihood method is introduced together with an E-M algorithm for parameter estimation. A Monte Carlo analysis is presented to investigate the performance of the algorithm as a number of data, parameter, and error factors are experimentally manipulated. Finally, a consumer psychology application is discussed involving consumer expertise/experience with microcomputers.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45747/1/11336_2005_Article_BF02294590.pd

A new clustering methodology for the analysis of sorted or categorized stimuli

This paper introduces a new stochastic clustering methodology devised for the analysis of categorized or sorted data. The methodology reveals consumers' common category knowledge as well as individual differences in using this knowledge for classifying brands in a designated product class. A small study involving the categorization of 28 brands of U.S. automobiles is presented where the results of the proposed methodology are compared with those obtained from KMEANS clustering. Finally, directions for future research are discussed.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47082/1/11002_2004_Article_BF00554131.pd

Infant acute myocarditis mimicking acute myocardial infarction

Myocarditis is an inflammatory disease of the myocardium with heterogeneous clinical manifestations and progression. In clinical practice, although there are many methods of diagnosis of acute myocarditis, the diagnosis remains an embarrassing dilemma for clinicians. The authors report the case of 9-month-old infant who was brought to the Pediatric Emergency Department with sudden onset dyspnea. Examination disclosed heart failure and resuscitation was undertaken. The electrocardiogram showed an ST segment elevation in the anterolateral leads with a mirror image. Cardiac enzyme tests revealed a significant elevation of troponin and creatine phosphokinase levels. A diagnosis of acute myocardial infarction was made, and heparin therapy was prescribed. The infant died on the third day after admission with cardiogenic shock. The autopsy showed dilatation of the ventricles and massive edema of the lungs. Histological examinations of myocardium samples revealed the presence of a marked lymphocytic infiltrate dissociating myocardiocytes. Death was attributed to acute myocarditis. The authors call attention to the difficulties of differential diagnosis between acute myocarditis and acute myocardial infarction especially in children, and to the important therapeutic implications of a correct diagnosi

Infant acute myocarditis mimicking acute myocardial infarction

Myocarditis is an inflammatory disease of the myocardium with heterogeneous clinical manifestations and progression. In clinical practice, although there are many methods of diagnosis of acute myocarditis, the diagnosis remains an embarrassing dilemma for clinicians. The authors report the case of 9-month-old infant who was brought to the Pediatric Emergency Department with sudden onset dyspnea. Examination disclosed heart failure and resuscitation was undertaken. The electrocardiogram showed an ST segment elevation in the anterolateral leads with a mirror image. Cardiac enzyme tests revealed a significant elevation of troponin and creatine phosphokinase levels. A diagnosis of acute myocardial infarction was made, and heparin therapy was prescribed. The infant died on the third day after admission with cardiogenic shock. The autopsy showed dilatation of the ventricles and massive edema of the lungs. Histological examinations of myocardium samples revealed the presence of a marked lymphocytic infiltrate dissociating myocardiocytes. Death was attributed to acute myocarditis. The authors call attention to the difficulties of differential diagnosis between acute myocarditis and acute myocardial infarction especially in children, and to the important therapeutic implications of a correct diagnosi

Simultaneous multidimensional unfolding and cluster analysis: An investigation of strategic groups

This paper develops a maximum likelihood based methodology for simultaneously performing multidimensional unfolding and cluster analysis on two-way dominance or profile data. This new procedure utilizes mixtures of multivariate conditional normal distributions to estimate a joint space of stimulus coordinates and K ideal points, one for each cluster or group, in a T -dimensional space. The conditional mixture, maximum likelihood methodology is introduced together with an E-M algorithm utilized for parameter estimation. A marketing strategy application is provided with an analysis of PIMS data for a set of firms drawn from the same competitive industry to determine strategic groups, while simultaneously depicting strategy-performance relationships.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47056/1/11002_2004_Article_BF00436033.pd

A maximum likelihood method for latent class regression involving a censored dependent variable

The standard tobit or censored regression model is typically utilized for regression analysis when the dependent variable is censored. This model is generalized by developing a conditional mixture, maximum likelihood method for latent class censored regression. The proposed method simultaneously estimates separate regression functions and subject membership in K latent classes or groups given a censored dependent variable for a cross-section of subjects. Maximum likelihood estimates are obtained using an EM algorithm. The proposed method is illustrated via a consumer psychology application.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45751/1/11336_2005_Article_BF02294647.pd

A stochastic multidimensional scaling procedure for the spatial representation of three-mode, three-way pick any/ J data

This paper presents a new stochastic multidimensional scaling procedure for the analysis of three-mode, three-way pick any/ J data. The method provides either a vector or ideal-point model to represent the structure in such data, as well as “floating” model specifications (e.g., different vectors or ideal points for different choice settings), and various reparameterization options that allow the coordinates of ideal points, vectors, or stimuli to be functions of specified background variables. A maximum likelihood procedure is utilized to estimate a joint space of row and column objects, as well as a set of weights depicting the third mode of the data. An algorithm using a conjugate gradient method with automatic restarts is developed to estimate the parameters of the models. A series of Monte Carlo analyses are carried out to investigate the performance of the algorithm under diverse data and model specification conditions, examine the statistical properties of the associated test statistic, and test the robustness of the procedure to departures from the independence assumptions. Finally, a consumer psychology application assessing the impact of situational influences on consumers' choice behavior is discussed.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45749/1/11336_2005_Article_BF02294486.pd

A stochastic multidimensional scaling procedure for the empirical determination of convex indifference curves for preference/choice analysis

The vast majority of existing multidimensional scaling (MDS) procedures devised for the analysis of paired comparison preference/choice judgments are typically based on either scalar product (i.e., vector) or unfolding (i.e., ideal-point) models. Such methods tend to ignore many of the essential components of microeconomic theory including convex indifference curves, constrained utility maximization, demand functions, et cetera. This paper presents a new stochastic MDS procedure called MICROSCALE that attempts to operationalize many of these traditional microeconomic concepts. First, we briefly review several existing MDS models that operate on paired comparisons data, noting the particular nature of the utility functions implied by each class of models. These utility assumptions are then directly contrasted to those of microeconomic theory. The new maximum likelihood based procedure, MICROSCALE, is presented, as well as the technical details of the estimation procedure. The results of a Monte Carlo analysis investigating the performance of the algorithm as a number of model, data, and error factors are experimentally manipulated are provided. Finally, an illustration in consumer psychology concerning a convenience sample of thirty consumers providing paired comparisons judgments for some fourteen brands of over-the-counter analgesics is discussed.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45748/1/11336_2005_Article_BF02294463.pd