Switching characteristics of diamond-based m-i-p+ diodes in power electronic applications

Modeling and numerical analysis of diamond m-i-p+ diode have been performed for static and transient analysis using TCAD Sentaurus platform. The simulation results are compared with experimental measurements. Prediction of transient turn-off characteristics of diamond m-i-p+ diode at high temperature is performed for the first time. It was found that unlike conventional Si diode, peak reverse current in diamond m-i-p+ diode reduces with increasing temperature while on-state voltage drop increases. © 2011 IEEE.

Metrical dental analysis on golden monkey (Rhinopithecus roxellana)

Dental variation in the Chinese golden monkey (Rhinopithecus roxellana) is here evaluated by univariate, bivariate, and multivariate analyses. Allometric analyses indicate that canines and P3s are positively, but other dimensions negatively scaled to mandible and maxilla, and to body size. With the exception of the mesiodistal dimensions of I-1 and M-3, and the buccolingual dimension of Pq, mandibular dental variables show similar scaling relative to body size. Analysis of residuals shows that males have significantly larger canine, P-3 and buccolingual dimensions of the postcanine teeth (M-2 and M-3) than females. A significant difference in shape between the sexes is found in the buccolingual dimension of the upper teeth, but not in the mandible. Unlike the situation in some other species, Female golden monkeys do nor exhibit relatively larger postcanine teeth than males, in fact, the reverse is true, especially for M(2)s and M(3)s. The fact that most of the dental variables show low negative allometry to body size might be related a cold environment that has led to the development of larger body size with I-educed energy loss. When the raw data are examined by Discriminant Function Analysis the sexes are clearly distinguishable.

Formant estimation of speech signals using subspace-based spectral analysis

The objective of this paper is to propose a signal processing scheme that employs subspace-based spectral analysis for the purpose of formant estimation of speech signals. Specifically, the scheme is based on decimative spectral estimation that uses Eigenanalysis and SVD (Singular Value Decomposition). The underlying model assumes a decomposition of the processed signal into complex damped sinusoids. In the case of formant tracking, the algorithm is applied on a small amount of the autocorrelation coefficients of a speech frame. The proposed scheme is evaluated on both artificial and real speech utterances from the TIMIT database. For the first case, comparative results to standard methods are provided which indicate that the proposed methodology successfully estimates formant trajectories.

Comparative analysis of carbonization drivers in China's megacities

This study investigates the key drivers affecting emission increases in terms of population growth, economic growth, industrial transformation, and energy use in six Chinese megacities: Beijing, Shanghai, Tianjin, Chongqing, Guangzhou, and Hong Kong. The six cities represent the most-developed regions in China and they have similar per capita carbon dioxide (CO 2) emissions as many developed countries. There is an urgent need to quantify the magnitude of each factor in driving the emissions changes in those cities so that a potential bottom-up climate mitigation policy design at the city and sectoral levels can be initiated. We adopt index decomposition analysis and present the results in both additive and multiplicative approaches to reveal the absolute and relative levels of each factor in driving emission changes during 1985-2007. Among all cities, economic effect and energy intensity effect have always been the two dominant factors contributing to the changes in carbon emissions. This study reveals that there are large variations in the ways driving forces contribute to emission levels in different cities and industrial sectors. © 2012 by Yale University.

Reliability analysis of deep excavation based on a semi-empirical approach

The design and construction of deep excavations in urban environment is often governed by serviceability limit state related to the risk of damage to adjacent buildings. In current practice, the assessment of excavation-induced building damage has focused on a deterministic approach. This paper presents a component/system reliability analysis framework to assess the probability that specified threshold design criteria for multiple serviceability limit states are exceeded. A recently developed Bayesian probabilistic framework is used to update the predictions of ground movements in the later stages of excavation based on the recorded deformation measurements. An example is presented to show how the serviceability performance for excavation problems can be assessed based on the component/system reliability analysis. © 2011 ASCE.