A matrix CFT at multiple large charges

We investigate matrix models in three dimensions where the global $\text{SU}(N)$ symmetry acts via the adjoint map. Analyzing their ground state which is homogeneous in space and can carry either a unique or multiple fixed charges, we show the existence of at least two distinct fixed points of the renormalization group (RG) flow. In particular, the one type of those fixed points manifests itself via tractable deviations in the large-charge expansion from the known predictions in the literature. We demonstrate most of the novel features using mainly the example of the $\text{SU}(4)$ matrix theory to compute the anomalous dimension of the lowest scalar operator with large global charge(s).Comment: 1+36 pages, 2 figures, minor clarifications added, version to be published in JHE

Legal structure and management of terminals: Focus on commercial issues and privatization

Most ports globally remain under public control, yet globalization and international logistic chains exercise pressure towards the dilution of the public control. This text presents briefly the institutional framework of ports and focuses on the operational and financial triggers to dilute public control. Then the key issues related to the market and the society are analyzed. This chapter concludes with a section on the bid process and the primal points discussed, negotiated and agreed in a concession procedure. --Port Management,Terminal Management,Privatization

Malware Classification based on Call Graph Clustering

Each day, anti-virus companies receive tens of thousands samples of potentially harmful executables. Many of the malicious samples are variations of previously encountered malware, created by their authors to evade pattern-based detection. Dealing with these large amounts of data requires robust, automatic detection approaches. This paper studies malware classification based on call graph clustering. By representing malware samples as call graphs, it is possible to abstract certain variations away, and enable the detection of structural similarities between samples. The ability to cluster similar samples together will make more generic detection techniques possible, thereby targeting the commonalities of the samples within a cluster. To compare call graphs mutually, we compute pairwise graph similarity scores via graph matchings which approximately minimize the graph edit distance. Next, to facilitate the discovery of similar malware samples, we employ several clustering algorithms, including k-medoids and DBSCAN. Clustering experiments are conducted on a collection of real malware samples, and the results are evaluated against manual classifications provided by human malware analysts. Experiments show that it is indeed possible to accurately detect malware families via call graph clustering. We anticipate that in the future, call graphs can be used to analyse the emergence of new malware families, and ultimately to automate implementation of generic detection schemes.Comment: This research has been supported by TEKES - the Finnish Funding Agency for Technology and Innovation as part of its ICT SHOK Future Internet research programme, grant 40212/0

Detecting a stochastic background of gravitational waves by correlating n detectors

We discuss the optimal detection strategy for a stochastic background of gravitational waves in the case n detectors are available. In literature so far, only two cases have been considered: 2- and n-point correlators. We generalize these analysises to m-point correlators (with m<n) built out of the n detector signals, obtaining the result that the optimal choice is to combine 2-point correlators. Correlating n detectors in this optimal way will improve the (suitably defined) signal-to-noise ratio with respect to the n=2 case by a factor equal to the fourth root of n(n-1)/2. Finally we give an estimation of how this could improve the sensitivity for a network of multi-mode spherical antennas.Comment: 12 pages, version accepted by Class. & Quant. Gra

On the Inefficiency of the Uniform Price Auction

We present our results on Uniform Price Auctions, one of the standard sealed-bid multi-unit auction formats, for selling multiple identical units of a single good to multi-demand bidders. Contrary to the truthful and economically efficient multi-unit Vickrey auction, the Uniform Price Auction encourages strategic bidding and is socially inefficient in general. The uniform pricing rule is, however, widely popular by its appeal to the natural anticipation, that identical items should be identically priced. In this work we study equilibria of the Uniform Price Auction for bidders with (symmetric) submodular valuation functions, over the number of units that they win. We investigate pure Nash equilibria of the auction in undominated strategies; we produce a characterization of these equilibria that allows us to prove that a fraction 1-1/e of the optimum social welfare is always recovered in undominated pure Nash equilibrium -- and this bound is essentially tight. Subsequently, we study the auction under the incomplete information setting and prove a bound of 4-2/k on the economic inefficiency of (mixed) Bayes Nash equilibria that are supported by undominated strategies.Comment: Additions and Improvements upon SAGT 2012 results (and minor corrections on the previous version

Gestural control of sonic swarms: Composing with grouped sound objects

This paper outlines an alternative controller designed to diffuse and manipulate a swarm of sounds in 3- dimensional space and discusses the compositional issues that emerge from its use. The system uses an algorithm from a nature-derived model describing the spatial behavior of a swarm. The movement of the swarm is mapped in the 3- dimensional space and a series of sound transformation functions for the sonic agents are implemented. The notion of causal relationships is explored regarding the spatial movement of the swarm and sound transformation of the agents by employing the physical controller as a performance, compositional and diffusion tool