examinations and the characteristics of the models. This paper also presents the lessons learned from the organizer’s point of view. It discusses the enhancements required for future editions of the Model Checking Contest event at the Petri Nets conference.

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-plication in the supply chain management domain. The methodology, which is based on queueing Petri nets, pro-vides a basis for performance analysis and capacity plan-ning. We study a deployment of the SPECjms2007 stan-dard benchmark on a leading commercial middleware platform. A detailed system model is built in a step

pages 156–175, 2013. [2] Johannes Buchmann, Denise Demirel, and Jeroen van de Graaf. Towards a publicly-verifiable mix-net providing everlasting privacy. In Financial Cryptog-raphy, pages 197–204, 2013. [3] Denise Demirel, Jeroen van de Graaf, and Roberto Araùjo. Improving helios

This article gives theoretical insights into the performance of K-SVD, a dictionary learning algorithm that has gained significant popularity in practical applications. The particular question studied here is when a dictionary Φ ∈ Rd×K can be recovered as local minimum of the minimisation criterion underlying K-SVD from a set of N training signals yn = Φxn. A theoretical analysis of the problem leads to two types of identifiability results assuming the training signals are generated from a tight frame with coefficients drawn from a random symmetric distribution. First asymptotic results showing, that in expectation the generating dictionary can be recovered exactly as a local minimum of the K-SVD criterion if the coefficient distribution exhibits sufficient decay. This decay can be characterised by the coherence of the dictionary and the `1-norm of the coefficients. Based on the asymptotic results it is further demonstrated that given a finite number of training samples N, such that N / logN = O(K3d), except with probability O(N−Kd) there is a local minimum of the K-SVD criterion within distance O(KN−1/4) to the generating dictionary. Index Terms dictionary learning, sparse coding, K-SVD, finite sample size, sampling complexity, dictionary identification, minimisation criterion, sparse representation 1

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Abstract. Soil respiration – RS, the flux of CO2 from the soil to the atmosphere – is probably the least well constrained component of the terrestrial carbon cycle. Here we introduce the SRDB database, a near-universal compendium of pub-lished RS data, and make it available to the scientific com

Bug found in FPU. Intel offers to replace faulty chips. Estimated loss: 475M US$ Esploded 37secs after launch. Cause: uncaught overflow ex-ception. Software “glitch ” found in anti-lock braking system. 185,000 cars recalled. Why verify? “Testing can only show the presence of errors, not their absence. ” [Edgar Dijkstra]

on the selected platforms. In this paper, we present a systematic approach for evaluating and predicting the performance and scalability of J2EE applications based on modeling and simulation. The approach helps to identify and eliminate bottlenecks in the application design and ensure that systems are designed

is conceptually similar to binary search, but it returns a set instead of a single number. Intuitively, starting with {c 1 , …, c n }, it might check {c 1 , …, c n/2 }: if that half of the changes is sufficient to pass the Test, then {c 1+n/2 , …, c n } can be discarded. When no more subsets of size n/2 can