A Poincar\'e Covariant Noncommutative Spacetime?

We interpret, in the realm of relativistic quantum field theory, the tangential operator given by Coleman, Mandula as an appropriate coordinate operator. The investigation shows that the operator generates a Snyder-like noncommutative spacetime with a minimal length that is given by the mass. By using this operator to define a noncommutative spacetime, we obtain a Poincar\'e invariant noncommutative spacetime and in addition solve the soccer-ball problem. Moreover, from recent progress in deformation theory we extract the idea how to obtain, in a physical and mathematical well-defined manner, an emerging noncommutative spacetime. This is done by a strict deformation quantization known as Rieffel deformation (or warped convolutions). The result is a noncommutative spacetime combining a Snyder and a Moyal-Weyl type of noncommutativity that in addition behaves covariant under transformations of the \textbf{whole} Poincar\'e group

Industrial growth and the quality of institutions : what do (transition) economies have to gain from the Rule of Law?

The authors empirically test the link between industrial growth and indicators of institutional quality. They find significant evidence that institutional quality affects inindustrial growth in 27 Asian and Latin American countries. Their results suggest that the development of the legal and regulatory framework works its way to industrial growth through both investment and total factor productivity. The implications for policymakers in transition economies: Institution building should complement privatization, public and private investment in education, research and development, and measures to promote foreign direct investment. Specifically, policymakers should try to reduce corruption, eliminate bureacratic barriers, and improve the legal environment and contract enforcement. Special attention should also be given to measures to deepen financial intermediation, improve the financial sector infrastructure, and increase the efficiency of financial transactions.Governance Indicators,Environmental Economics&Policies,Achieving Shared Growth,Economic Theory&Research,Trade and Regional Integration

A comparison of linear and non-linear calibrations for speaker recognition

In recent work on both generative and discriminative score to log-likelihood-ratio calibration, it was shown that linear transforms give good accuracy only for a limited range of operating points. Moreover, these methods required tailoring of the calibration training objective functions in order to target the desired region of best accuracy. Here, we generalize the linear recipes to non-linear ones. We experiment with a non-linear, non-parametric, discriminative PAV solution, as well as parametric, generative, maximum-likelihood solutions that use Gaussian, Student's T and normal-inverse-Gaussian score distributions. Experiments on NIST SRE'12 scores suggest that the non-linear methods provide wider ranges of optimal accuracy and can be trained without having to resort to objective function tailoring.Comment: accepted for Odyssey 2014: The Speaker and Language Recognition Worksho

Evaluation of the Immigrant Citizens Survey (ICS)

This evaluation undertakes a critical appraisal of the "Immigrant Citizens Survey (ICS)". The survey was funded under the European Integration Fund and jointly coordinated by the King Baudouin Foundation (KBF) and the Migration Policy Group (MPG). The survey was implemented in cooperation with research, polling and launch partners in the 7 countries covered by the survey. The survey was implemented in 2011 and 2012 and launched in May 2012

Using the High Productivity Language Chapel to Target GPGPU Architectures

It has been widely shown that GPGPU architectures offer large performance gains compared to their traditional CPU counterparts for many applications. The downside to these architectures is that the current programming models present numerous challenges to the programmer: lower-level languages, explicit data movement, loss of portability, and challenges in performance optimization. In this paper, we present novel methods and compiler transformations that increase productivity by enabling users to easily program GPGPU architectures using the high productivity programming language Chapel. Rather than resorting to different parallel libraries or annotations for a given parallel platform, we leverage a language that has been designed from first principles to address the challenge of programming for parallelism and locality. This also has the advantage of being portable across distinct classes of parallel architectures, including desktop multicores, distributed memory clusters, large-scale shared memory, and now CPU-GPU hybrids. We present experimental results from the Parboil benchmark suite which demonstrate that codes written in Chapel achieve performance comparable to the original versions implemented in CUDA.NSF CCF 0702260Cray Inc. Cray-SRA-2010-016962010-2011 Nvidia Research Fellowshipunpublishednot peer reviewe