Improving acoustic vehicle classification by information fusion

We present an information fusion approach for ground vehicle classification based on the emitted acoustic signal. Many acoustic factors can contribute to the classification accuracy of working ground vehicles. Classification relying on a single feature set may lose some useful information if its underlying sound production model is not comprehensive. To improve classification accuracy, we consider an information fusion diagram, in which various aspects of an acoustic signature are taken into account and emphasized separately by two different feature extraction methods. The first set of features aims to represent internal sound production, and a number of harmonic components are extracted to characterize the factors related to the vehicle’s resonance. The second set of features is extracted based on a computationally effective discriminatory analysis, and a group of key frequency components are selected by mutual information, accounting for the sound production from the vehicle’s exterior parts. In correspondence with this structure, we further put forward a modifiedBayesian fusion algorithm, which takes advantage of matching each specific feature set with its favored classifier. To assess the proposed approach, experiments are carried out based on a data set containing acoustic signals from different types of vehicles. Results indicate that the fusion approach can effectively increase classification accuracy compared to that achieved using each individual features set alone. The Bayesian-based decision level fusion is found fusion is found to be improved than a feature level fusion approac

Physics searches at the LHC

With the LHC up and running, the focus of experimental and theoretical high energy physics will soon turn to an interpretation of LHC data in terms of the physics of electroweak symmetry breaking and the TeV scale. We present here a broad review of models for new TeV-scale physics and their LHC signatures. In addition, we discuss possible new physics signatures and describe how they can be linked to specific models of physics beyond the Standard Model. Finally, we illustrate how the LHC era could culminate in a detailed understanding of the underlying principles of TeV-scale physics.Comment: 184 pages, 55 figures, 14 tables, hundreds of references; scientific feedback is welcome and encouraged. v2: text, references and Overview Table added; feedback still welcom

Statistical Physics and Representations in Real and Artificial Neural Networks

This document presents the material of two lectures on statistical physics and neural representations, delivered by one of us (R.M.) at the Fundamental Problems in Statistical Physics XIV summer school in July 2017. In a first part, we consider the neural representations of space (maps) in the hippocampus. We introduce an extension of the Hopfield model, able to store multiple spatial maps as continuous, finite-dimensional attractors. The phase diagram and dynamical properties of the model are analyzed. We then show how spatial representations can be dynamically decoded using an effective Ising model capturing the correlation structure in the neural data, and compare applications to data obtained from hippocampal multi-electrode recordings and by (sub)sampling our attractor model. In a second part, we focus on the problem of learning data representations in machine learning, in particular with artificial neural networks. We start by introducing data representations through some illustrations. We then analyze two important algorithms, Principal Component Analysis and Restricted Boltzmann Machines, with tools from statistical physics

String breaking by dynamical fermions in three-dimensional lattice QCD

The first observation is made of hadronic string breaking due to dynamical fermions in zero temperature lattice QCD. The simulations are done for SU(2) color in three dimensions, with two flavors of staggered fermions. The results have clear implications for the large scale simulations that are being done to search (so far, without success) for string breaking in four-dimensional QCD. In particular, string breaking is readily observed using only Wilson loops to excite a static quark-antiquark pair. Improved actions on coarse lattices are used, providing an extremely efficient means to access the quark separations and propagation times at which string breaking occurs.Comment: Revised version to appear in Physical Review D, has additional discussion of the results, additional references, modified title, larger figure

Personality cannot be predicted from the power of resting state EEG

In the present study we asked whether it is possible to decode personality traits from resting state EEG data. EEG was recorded from a large sample of subjects (N = 309) who had answered questionnaires measuring personality trait scores of the 5 dimensions as well as the 10 subordinate aspects of the Big Five. Machine learning algorithms were used to build a classifier to predict each personality trait from power spectra of the resting state EEG data. The results indicate that the five dimensions as well as their subordinate aspects could not be predicted from the resting state EEG data. Finally, to demonstrate that this result is not due to systematic algorithmic or implementation mistakes the same methods were used to successfully classify whether the subject had eyes open or eyes closed and whether the subject was male or female. These results indicate that the extraction of personality traits from the power spectra of resting state EEG is extremely noisy, if possible at all.Comment: 14 pages, 4 figure

Top-down Holographic Glueball Decay Rates

We present new results on the decay patterns of scalar and tensor glueballs in the top-down holographic Witten-Sakai-Sugimoto model. This model, which has only one free dimensionless parameter, gives semi-quantitative predictions for the vector meson spectrum, their decay widths, and also a gluon condensate in agreement with SVZ sum rules. The holographic predictions for scalar glueball decay rates are compared with experimental data for the widely discussed gluon candidates f0(1500) and f0(1710).Comment: 9 pages, 2 figures, 2 tables; to appear in the Proceedings of the XIth Conference Quark Confinement and the Hadron Spectrum, St. Petersburg, September 8-12, 201

High-precision αs\alpha_s measurements from LHC to FCC-ee

This document provides a writeup of all contributions to the workshop on "High precision measurements of $\alpha_s$: From LHC to FCC-ee" held at CERN, Oct. 12--13, 2015. The workshop explored in depth the latest developments on the determination of the QCD coupling $\alpha_s$ from 15 methods where high precision measurements are (or will be) available. Those include low-energy observables: (i) lattice QCD, (ii) pion decay factor, (iii) quarkonia and (iv) $\tau$ decays, (v) soft parton-to-hadron fragmentation functions, as well as high-energy observables: (vi) global fits of parton distribution functions, (vii) hard parton-to-hadron fragmentation functions, (viii) jets in $e^\pm$p DIS and $\gamma$-p photoproduction, (ix) photon structure function in $\gamma$-$\gamma$, (x) event shapes and (xi) jet cross sections in $e^+e^-$ collisions, (xii) W boson and (xiii) Z boson decays, and (xiv) jets and (xv) top-quark cross sections in proton-(anti)proton collisions. The current status of the theoretical and experimental uncertainties associated to each extraction method, the improvements expected from LHC data in the coming years, and future perspectives achievable in $e^+e^-$ collisions at the Future Circular Collider (FCC-ee) with $\cal{O}$(1--100 ab$^{-1}$) integrated luminosities yielding 10$^{12}$ Z bosons and jets, and 10$^{8}$ W bosons and $\tau$ leptons, are thoroughly reviewed. The current uncertainty of the (preliminary) 2015 strong coupling world-average value, $\alpha_s(m_Z)$ = 0.1177 $\pm$ 0.0013, is about 1\%. Some participants believed this may be reduced by a factor of three in the near future by including novel high-precision observables, although this opinion was not universally shared. At the FCC-ee facility, a factor of ten reduction in the $\alpha_s$ uncertainty should be possible, mostly thanks to the huge Z and W data samples available.Comment: 135 pages, 56 figures. CERN-PH-TH-2015-299, CoEPP-MN-15-13. This document is dedicated to the memory of Guido Altarell

Application of the Maximum Entropy Method to the (2+1)d Four-Fermion Model

We investigate spectral functions extracted using the Maximum Entropy Method from correlators measured in lattice simulations of the (2+1)-dimensional four-fermion model. This model is particularly interesting because it has both a chirally broken phase with a rich spectrum of mesonic bound states and a symmetric phase where there are only resonances. In the broken phase we study the elementary fermion, pion, sigma and massive pseudoscalar meson; our results confirm the Goldstone nature of the pi and permit an estimate of the meson binding energy. We have, however, seen no signal of sigma -> pi pi decay as the chiral limit is approached. In the symmetric phase we observe a resonance of non-zero width in qualitative agreement with analytic expectations; in addition the ultra-violet behaviour of the spectral functions is consistent with the large non-perturbative anomalous dimension for fermion composite operators expected in this model.Comment: 25 pages, 13 figure