Effect of bandgap narrowing on performance of modern power devices

The effect of the bandgap narrowing (BGN) on performance of power devices is investigated in detail in this paper. The analysis reveals that the change in the energy band structure caused by BGN can strongly affect the conductivity modulation of the bipolar devices resulting in a completely different performance. This is due to the modified injection efficiency under high-level injection conditions. Using a comprehensive analysis of the injection efficiency in a p-n junction, an analytical model for this phenomenon is developed. BGN model tuning has been proved to be essential in accurately predicting the performance of a lateral insulated-gate bipolar transistor (IGBT). Other devices such as p-i-n diodes or punch-through IGBTs are significantly affected by the BGN, while others, such as field-stop IGBTs or power MOSFETs, are only marginally affected. © 2013 IEEE.

Paraphrastic language models and combination with neural network language models

In natural languages multiple word sequences can represent the same underlying meaning. Only modelling the observed surface word sequence can result in poor context coverage, for example, when using n-gram language models (LM). To handle this issue, paraphrastic LMs were proposed in previous research and successfully applied to a US English conversational telephone speech transcription task. In order to exploit the complementary characteristics of paraphrastic LMs and neural network LMs (NNLM), the combination between the two is investigated in this paper. To investigate paraphrastic LMs' generalization ability to other languages, experiments are conducted on a Mandarin Chinese broadcast speech transcription task. Using a paraphrastic multi-level LM modelling both word and phrase sequences, significant error rate reductions of 0.9% absolute (9% relative) and 0.5% absolute (5% relative) were obtained over the baseline n-gram and NNLM systems respectively, after a combination with word and phrase level NNLMs. © 2013 IEEE.

Automatic construction and natural-language description of nonparametric regression models

Copyright © 2014, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. This paper presents the beginnings of an automatic statistician, focusing on regression problems. Our system explores an open-ended space of statistical models to discover a good explanation of a data set, and then produces a detailed report with figures and natural- language text. Our approach treats unknown regression functions non- parametrically using Gaussian processes, which has two important consequences. First, Gaussian processes can model functions in terms of high-level properties (e.g. smoothness, trends, periodicity, changepoints). Taken together with the compositional structure of our language of models this allows us to automatically describe functions in simple terms. Second, the use of flexible nonparametric models and a rich language for composing them in an open-ended manner also results in state- of-the-art extrapolation performance evaluated over 13 real time series data sets from various domains.

Unified form language: A domain-specific language for weak formulations of partial differential equations

We present the Unified Form Language (UFL), which is a domain-specific language for representing weak formulations of partial differential equations with a view to numerical approximation. Features of UFL include support for variational forms and functionals, automatic differentiation of forms and expressions, arbitrary function space hierarchies formultifield problems, general differential operators and flexible tensor algebra. With these features, UFL has been used to effortlessly express finite element methods for complex systems of partial differential equations in near-mathematical notation, resulting in compact, intuitive and readable programs. We present in this work the language and its construction. An implementation of UFL is freely available as an open-source software library. The library generates abstract syntax tree representations of variational problems, which are used by other software libraries to generate concrete low-level implementations. Some application examples are presented and libraries that support UFL are highlighted. © 2014 ACM.

Enduring Borderlands: the Marches of Ireland and Wales in the Early Modern Period

This joint chapter explores similarities and differences between two borderlands within the early modern ‘British’ state – the marches of Ireland and Wales. In some respects, the two regions were very different, most fundamentally because the Irish march remained militarised throughout the Tudor period, while Welsh society was markedly more peaceful. However, there was also much in common. In the later middle ages both marches were frontiers between the expanding Anglo-Normans and native Celtic society. The notion that the march separated ‘civility’ from ‘savagery’ was an enduring one: despite the efforts of the Tudors to impose centralisation and uniformity throughout its territories, there remained institutions, structures of power, and mentalities which ensured that both sets of marches were still in existence by the end of the 16th century. This chapter explores the reasons for the endurance of these borderlands, and indicates how political reforms of the 16th century caused the perception – and sometimes the very location – of the marches to alter.