Isotropic Multiple Scattering Processes on Hyperspheres

This paper presents several results about isotropic random walks and multiple scattering processes on hyperspheres ${\mathbb S}^{p-1}$. It allows one to derive the Fourier expansions on ${\mathbb S}^{p-1}$ of these processes. A result of unimodality for the multiconvolution of symmetrical probability density functions (pdf) on ${\mathbb S}^{p-1}$ is also introduced. Such processes are then studied in the case where the scattering distribution is von Mises Fisher (vMF). Asymptotic distributions for the multiconvolution of vMFs on ${\mathbb S}^{p-1}$ are obtained. Both Fourier expansion and asymptotic approximation allows us to compute estimation bounds for the parameters of Compound Cox Processes (CCP) on ${\mathbb S}^{p-1}$.Comment: 16 pages, 4 figure

Asymptotic regime for impropriety tests of complex random vectors

Impropriety testing for complex-valued vector has been considered lately due to potential applications ranging from digital communications to complex media imaging. This paper provides new results for such tests in the asymptotic regime, i.e. when the vector dimension and sample size grow commensurately to infinity. The studied tests are based on invariant statistics named impropriety coefficients. Limiting distributions for these statistics are derived, together with those of the Generalized Likelihood Ratio Test (GLRT) and Roy's test, in the Gaussian case. This characterization in the asymptotic regime allows also to identify a phase transition in Roy's test with potential application in detection of complex-valued low-rank subspace corrupted by proper noise in large datasets. Simulations illustrate the accuracy of the proposed asymptotic approximations.Comment: 11 pages, 8 figures, submitted to IEEE TS

Efficient Ultrasound Image Analysis Models with Sonographer Gaze Assisted Distillation.

Recent automated medical image analysis methods have attained state-of-the-art performance but have relied on memory and compute-intensive deep learning models. Reducing model size without significant loss in performance metrics is crucial for time and memory-efficient automated image-based decision-making. Traditional deep learning based image analysis only uses expert knowledge in the form of manual annotations. Recently, there has been interest in introducing other forms of expert knowledge into deep learning architecture design. This is the approach considered in the paper where we propose to combine ultrasound video with point-of-gaze tracked for expert sonographers as they scan to train memory-efficient ultrasound image analysis models. Specifically we develop teacher-student knowledge transfer models for the exemplar task of frame classification for the fetal abdomen, head, and femur. The best performing memory-efficient models attain performance within 5% of conventional models that are 1000× larger in size

Si3N4 emissivity and the unidentified infrared bands

Infrared spectroscopy of warm (about 150 to 750 K), dusty astronomical sources has revealed a structured emission spectrum which can be diagnostic of the composition, temperature, and in some cases, even size and shape of the grains giving rise to the observed emission. The identifications of silicate emission in oxygen rich objects and SiC in carbon rich object are two examples of this type of analysis. Cometary spectra at moderate resolution have similarly revealed silicate emission, tying together interstellar and interplanetary dust. However, Goebel has pointed out that some astronomical sources appear to contain a different type of dust which results in a qualitatively different spectral shape in the 8 to 13 micron region. The spectra shown make it appear unlikely that silicon nitride can be identified as the source of the 8 to 13 micron emission in either NGC 6572 or Nova Aql 1982. The similarity between the general wavelength and shape of the 10 micron emission from some silicates and that from the two forms of silicon nitride reported could allow a mix of cosmic grains which include some silicon nitride if only the 8 to 13 micron data are considered

Contrôle des erreurs pour la détection d'événements rares et faibles dans des champs de données massifs

National audienceIn this paper, we address the general issue of detecting rare and weak signatures in very noisy data. Multiple hypotheses testing approaches can be used to extract a list of components of the data that are likely to be contaminated by a source while controlling a global error criterion. However most of efficients methods available in the literature stand for independent tests, or require specific dependency hypotheses. Based on the work of Benjamini and Yekutieli [1], we show that under some classical positivity assumptions, the Benjamini-Hochberg procedure for False Discovery Rate (FDR) [2] control can be directly applied to the statistics produced by a very common tool in signal and image processing that introduces dependency: the matched filter.Nous nous intéressons à la détection d'événements rares et de faible intensité dans des données massives bruitées. Les approches par tests multiples d'hypothèses peuvent être utilisées pour extraire une liste d'échantillons susceptibles de contenir de l'information tout en contrôlant un critère d'erreurs de détection global. Dans la littérature, la plupart de ces approches ne sont valides que pour des tests indépendants, ou sous des hypothèses particulières de dépendance. Nous nous proposons de montrer, en étendant les travaux de Benjamini et Yekutieli [1], que sous certaines hypothèses, il est cependant possible d'appliquer la procédure de contrôle du taux de fausses découverte (FDR) de Benjamini-Hochberg [2] sur une statistique de filtrage adapté très utilisée en traitement du signal et des images

Critical Behavior and Lack of Self Averaging in the Dynamics of the Random Potts Model in Two Dimensions

We study the dynamics of the q-state random bond Potts ferromagnet on the square lattice at its critical point by Monte Carlo simulations with single spin-flip dynamics. We concentrate on q=3 and q=24 and find, in both cases, conventional, rather than activated, dynamics. We also look at the distribution of relaxation times among different samples, finding different results for the two q values. For q=3 the relative variance of the relaxation time tau at the critical point is finite. However, for q=24 this appears to diverge in the thermodynamic limit and it is ln(tau) which has a finite relative variance. We speculate that this difference occurs because the transition of the corresponding pure system is second order for q=3 but first order for q=24.Comment: 9 pages, 13 figures, final published versio

Nonparametric Bayesian extraction of object configurations in massive data

International audienceThis study presents an unsupervised method for detection of configurations of objects based on a point process in a nonparametric Bayesian framework. This is of interest as the model presented here has a number of parameters that increases with the number of objects detected. The marked point process yields a natural sparse representation of the object configuration, even in massive data fields. However, Bayesian methods can lead to the evaluation of some densities that raise computational issues, due to the huge number of detected objects. We have developed an iterative update of these densities when changes in the object configurations are made, which allows the computational cost to be reduced. The performance of the proposed algorithm is illustrated on synthetic data and very challenging quasi-real hyperspectral data for young galaxy detection

Prosody Predicts Contest Outcome in Non-Verbal Dialogs.

Non-verbal communication has important implications for inter-individual relationships and negotiation success. However, to what extent humans can spontaneously use rhythm and prosody as a sole communication tool is largely unknown. We analysed human ability to resolve a conflict without verbal dialogs, independently of semantics. We invited pairs of subjects to communicate non-verbally using whistle sounds. Along with the production of more whistles, participants unwittingly used a subtle prosodic feature to compete over a resource (ice-cream scoops). Winners can be identified by their propensity to accentuate the first whistles blown when replying to their partner, compared to the following whistles. Naive listeners correctly identified this prosodic feature as a key determinant of which whistler won the interaction. These results suggest that in the absence of other communication channels, individuals spontaneously use a subtle variation of sound accentuation (prosody), instead of merely producing exuberant sounds, to impose themselves in a conflict of interest. We discuss the biological and cultural bases of this ability and their link with verbal communication. Our results highlight the human ability to use non-verbal communication in a negotiation process

Error control for the detection of rare and weak signatures in massive data

International audienceIn this paper, we address the general issue of detecting rare and weak signatures in very noisy data. Multiple hypotheses testing approaches can be used to extract a list of components of the data that are likely to be contaminated by a source while controlling a global error criterion. However most of efficients methods available in the literature are derived for independent tests. Based on the work of Benjamini and Yekutieli [1], we show that under some classical positiv-ity assumptions, the Benjamini-Hochberg procedure for False Discovery Rate (FDR) control can be directly applied to the result produced by a very common tool in signal and image processing: the matched filter. This shows that despite the dependency structure between the components of the matched filter output, the Benjamini-Hochberg procedure still guarantee the FDR control. This is illustrated on both synthetic and real data

Large-q asymptotics of the random bond Potts model

We numerically examine the large-q asymptotics of the q-state random bond Potts model. Special attention is paid to the parametrisation of the critical line, which is determined by combining the loop representation of the transfer matrix with Zamolodchikov's c-theorem. Asymptotically the central charge seems to behave like c(q) = 1/2 log_2(q) + O(1). Very accurate values of the bulk magnetic exponent x_1 are then extracted by performing Monte Carlo simulations directly at the critical point. As q -> infinity, these seem to tend to a non-trivial limit, x_1 -> 0.192 +- 0.002.Comment: 9 pages, no figure