Nonlinear dynamic investigation of electrostatically actuated micro-electro-mechanical-system (MEMS) microcantilever structures is presented. The nonlinear analysis aims to better quantify, than the linear model, the ...
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Nonlinear dynamic investigation of electrostatically actuated micro-electro-mechanical-system (MEMS) microcantilever structures is presented. The nonlinear analysis aims to better quantify, than the linear model, the instability threshold associated with electrostatically actuated MEMS structures, where the pull-in voltage of the microcantilever is determined using a phase portrait analysis of the microsystem. The microcantilever is modeled as a lumped mass-spring system. The nonlinear electrostatic force is incorporated into the lumped microsystem through an equivalent area of the microcantilever for a given electrostatic potential. Electro-mechanical force balance plots are obtained for various electrostatic potentials from which the static equilibrium positions of the microcantilever are obtained and the respective conservative energy values are determined. Subsequently, phase portrait plots are obtained for the corresponding energy values from which the pull-in voltage is estimated for the microsystem. This pull-in voltage value is in good agreement with the previously published results for the same geometric and material parameters. The results obtained for linear electrostatic models are also presented for comparison.
Suppose we want to build a system that answers a natural language question by representing its semantics as a logical form and computing the answer given a structured database of facts. The core part of such a system ...
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Suppose we want to build a system that answers a natural language question by representing its semantics as a logical form and computing the answer given a structured database of facts. The core part of such a system is the semantic parser that maps questions to logical forms. Semantic parsers are typically trained from examples of questions annotated with their target logical forms, but this type of annotation is expensive. Our goal is to instead learn a semantic parser from question-answer pairs, where the logical form is modeled as a latent variable. We develop a new semantic formalism, dependency-based compositional semantics (DCS) and define a log-linear distribution over DCS logical forms. The model parameters are estimated using a simple procedure that alternates between beam search and numerical optimization. On two standard semantic parsing benchmarks, we show that our system obtains comparable accuracies to even state-of-the-art systems that do require annotated logical forms.
The association between two random variables is often of primary interest in statistical research. In this paper semiparametric models for the association between random vectors X and Y are considered which leave the ...
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The association between two random variables is often of primary interest in statistical research. In this paper semiparametric models for the association between random vectors X and Y are considered which leave the marginal distributions arbitrary. Given that the odds ratio function comprises the whole information about the association, the focus is on bilinearlog-odds ratio models and in particular on the odds ratio parameter vector theta. The covariance structure of the maximum likelihood estimator (theta) over cap of theta is of major importance for asymptotic inference. To this end different representations of the estimated covariance matrix are derived for conditional and unconditional sampling schemes and different asymptotic approaches depending on whether X and/or Y has finite or arbitrary support. The main result is the invariance of the estimated asymptotic covariance matrix of (theta) over cap with respect to all above approaches. As applications we compute the asymptotic power for tests of linear hypotheses about theta-with emphasis to logistic and linear regression models-which allows to determine the necessary sample size to achieve a wanted power. (C) 2012 Elsevier B.V. All rights reserved.
Multiple systems estimation (MSE) is becoming an increasingly common approach for exploratory study of underreported events in the field of quantitative human rights. In this context, it is used to estimate the number...
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Multiple systems estimation (MSE) is becoming an increasingly common approach for exploratory study of underreported events in the field of quantitative human rights. In this context, it is used to estimate the number of people who died as a result of political unrest when it is believed that many of those who died or disappeared were never reported. MSE relies upon several assumptions, each of which may be slightly or significantly violated in particular applications. This article outlines the evolution of the application of MSE to human rights research through the use of three case studies: Guatemala, Peru, and Colombia. Each of these cases presents distinct challenges to the MSE method. Motivated by these applications, we describe new methodology for assessing the impact of violated assumptions in MSE. Our approach uses simulations to explore the cumulative magnitude of errors introduced by violation of the model assumptions at each stage in the analysis.
The paper presents a simple loglinear macroeconomic model designed to discuss the essentials of Keynes' dynamic analysis in the General Theory and in the Treatise on Money. The model has a conventional static Aggr...
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The paper presents a simple loglinear macroeconomic model designed to discuss the essentials of Keynes' dynamic analysis in the General Theory and in the Treatise on Money. The model has a conventional static Aggregate DemandAggregate Supply block plus a three-dimensional dynamic system involving the money wage and the expected level and rate of change of the output price. It illustrates Keynes' ideas, in particular on the nature of unemployment and on the stabilizing nature of money (as opposed to real) wage stickiness. It also allows to reconcile with empirical observations Keynes' (false) conjecture on the negative correlation of money and real wages.
State-of-the-art speech recognisers are usually based on hidden Markov models (HMMs). They model a hidden symbol sequence with a Markov process, with the observations independent given that sequence. These assumptions...
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ISBN:
(纸本)9781479903566
State-of-the-art speech recognisers are usually based on hidden Markov models (HMMs). They model a hidden symbol sequence with a Markov process, with the observations independent given that sequence. These assumptions yield efficient algorithms, but limit the power of the model. An alternative model that allows a wide range of features, including word-and phone-level features, is a log-linear model. To handle, for example, word-level variable-length features, the original feature vectors must be segmented into words. Thus, decoding must find the optimal combination of segmentation of the utterance into words and word sequence. Features must therefore be extracted for each possible segment of audio. For many types of features, this becomes slow. In this paper, long-span features are derived from the likelihoods of word HMMs. Derivatives of the log-likelihoods, which break the Markov assumption, are appended. Previously, decoding with this model took cubic time in the length of the sequence, and longer for higher-order derivatives. This paper shows how to decode in quadratic time.
This article describes long-term changes in the occupational class structure and intergenerational social mobility in Hungary between 1865 and 1950, a period that has not been studied in previous mobility research. Th...
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This article describes long-term changes in the occupational class structure and intergenerational social mobility in Hungary between 1865 and 1950, a period that has not been studied in previous mobility research. The study's long time span and the fact that the Hungarian economy began to industrialize in the second half of the 19th century allows us to test several competing hypotheses about changes in social mobility. We use a large, individual-level, historical dataset with over 73,000 marriage records, representing all regions of present-day Hungary. Although the occupational structure remained predominantly agrarian, total mobility increased over the observed period, with an upward shift in the occupational distribution. log-multiplicative association models were used to compare relative mobility patterns of men across 17 mobility tables over five-year periods. Relative mobility increased, lending partial support to the modernization thesis. The increase of relative mobility can be attributed to decreasing diagonal association. Off-diagonal association, indicating class-based inequalities in mobility chances, increased during the first period of industrialization. The results call for a closer examination of the mechanisms causing changes in social mobility during industrialization. (C) 2013 International Sociological Association Research Committee 28 on Social Stratification and Mobility. Published by Elsevier Ltd. All rights reserved.
This study examines the relationship between size and effectiveness of 97 US federal government organizations in combination with relevant mediating variables. The dependent variable, actual goal attainment, is consid...
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This study examines the relationship between size and effectiveness of 97 US federal government organizations in combination with relevant mediating variables. The dependent variable, actual goal attainment, is considered as a measure of organizational effectiveness. The number of full-time employees and budget size, the independent variables, are considered as measures of organizational size. Mediating variables considered are goal ambiguity measures, the number of programs, the proportion of professionals in the organization, and institutional location (independent agencies versus agencies inside executive departments). The path analysis corroborates an inverted U-shaped relationship between the number of employees and organizational effectiveness. Furthermore, the relationship between budget size and organizational effectiveness is found to be negative and log-linear, and the relationship is partially mediated by target-specification ambiguity and timeline ambiguity.
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