Large margin filtering for signal sequence labeling

Signal Sequence Labeling consists in predicting a sequence of labels given an observed sequence of samples. A naive way is to filter the signal in order to reduce the noise and to apply a classification algorithm on the filtered samples. We propose in this paper to jointly learn the filter with the classifier leading to a large margin filtering for classification. This method allows to learn the optimal cutoff frequency and phase of the filter that may be different from zero. Two methods are proposed and tested on a toy dataset and on a real life BCI dataset from BCI Competition III.Comment: IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2010, Dallas : United States (2010

Mesures d'adaptation à la fonte des glaciers dans les Andes et dans l'Hindou Kouch-Himalaya

On assiste depuis plusieurs années à un recul des glaciers dans les hautes montagnes du monde accéléré par les changements climatiques. Dans certains de ces lieux reculés, des peuples habitent à proximité des glaciers et leur mode de vie se retrouve affecté par la situation. La cordillère des Andes en Amérique du Sud et les chaînes de montagnes Himalaya et Hindou Kouch en Asie du Sud-Est et Asie centrale abritent chacune une grande diversité de cultures et d’écosystèmes qui dépendent de la cryosphère. Au fil du temps, ces communautés ont développé une panoplie d’initiatives pour s’adapter aux conditions changeantes de leur environnement. Cependant, devant l’importance des changements observés récemment, un besoin se manifeste de trouver de nouvelles idées et d’améliorer les stratégies d’adaptation. Dans ce sens, les régions des Andes et de l’Hindou Kouch-Himalaya gagneraient à s’inspirer l’une l’autre à partir de leurs expériences respectives. Cet essai a pour objectif de contribuer au partage des leçons apprises dans chaque région en mettant en lumière des mesures d’adaptation qui présentent des caractéristiques avantageuses. D’abord, les chaînes de montagnes à l’étude sont décrites à partir du concept de socioécosystème qui souligne les interactions entre des composantes physiques, environnementales et humaines. Ensuite, la réponse de ces systèmes au recul des glaciers est détaillée dans le but d’entamer la réflexion sur les possibilités qu’ont les communautés locales de réduire les dommages subis et de saisir de nouvelles opportunités. Enfin, une évaluation superficielle d’un ensemble d’initiatives d’adaptation mises en place dans les deux régions est réalisée. À la suite de cet exercice, un tableau rassemble des mesures prometteuses desquelles les intervenants des Andes et de l’Hindou Kouch-Himalaya pourront s’inspirer dans la conception de projets et de stratégies d’adaptation. Un des motifs qui ressort de l’évaluation des mesures est le grand potentiel qu’offre l’approche de l’adaptation fondée sur les écosystèmes pour augmenter la résilience des communautés des montagnes. Ce cadre se base sur des principes qui assurent que les mesures soient conçues pour et par la population ciblée. L’essai fait aussi valoir l’utilité de réaliser des études de vulnérabilité pour bien cerner le besoin des communautés en amont d’un projet. De même, on remarque que dans les deux régions, des systèmes traditionnels de gestion des ressources naturelles déjà en place présentent plusieurs éléments qui les rapprochent du développement durable. L’essai conclut qu’une réactualisation de ces modes d’organisation à travers des interventions participatives pourrait être une avenue profitable pour les habitants des Andes et de l’Hindou Kouch-Himalaya. En solidifiant ces structures, la distribution équitable des retombées est favorisée et des initiatives innovantes peuvent émerger

Seafloor morphology and substrate mapping in the Gulf of St Lawrence, Canada, using machine learning approaches

Detailed maps of seafloor substrata and morphology can act as valuable proxies for predicting and understanding the distributions of benthic communities and are important for guiding conservation initiatives. High resolution acoustic remote sensing data can facilitate the production of detailed seafloor maps, but are cost-prohibitive to collect and not widely available. In the absence of targeted high resolution data, global bathymetric data of a lower resolution, combined with legacy seafloor sampling data, can provide an alternative for generating maps of seafloor substrate and morphology. Here we apply regression random forest to legacy data in the Gulf of St Lawrence, Canada, to generate a map of seabed sediment distribution. We further apply k-means clustering to a principal component analysis output to identify seafloor morphology classes from the GEBCO bathymetric grid. The morphology classification identified most morphological features but could not discriminate valleys and canyons. The random forest results were in line with previous sediment mapping work done in the area, but a large proportion of zero values skewed the explained variance. In both models, improvements may be possible with the introduction of more predictor variables. These models prove useful for generating regional seafloor maps that may be used for future management and conservation applications

Using the Bullet Cluster as a Gravitational Telescope to Study z~7 Lyman Break Galaxies

We use imaging obtained with the Hubble Space Telescope Wide Field Camera 3 to search for z_850 dropouts at z~7 and J_110 dropouts at z~9 lensed by the Bullet Cluster. In total we find 10 z_850 dropouts in our 8.27 arcmin^2 field. Using magnification maps from a combined weak and strong lensing mass reconstruction of the Bullet Cluster and correcting for estimated completeness levels, we calculate the surface density and luminosity function of our z_850 dropouts as a function of intrinsic (accounting for magnification) magnitude. We find results consistent with published blank field surveys, despite using much shallower data, and demonstrate the effectiveness of cluster surveys in the search for z~7 galaxies.Comment: 12 pages, 2 tables, 9 figures. Accepted for publication in ApJ. V3: two new figures, improved calculation of intrinsic counts, better organization, added references; main results did not change significantl

Leveraging 3D-HST Grism Redshifts to Quantify Photometric Redshift Performance

We present a study of photometric redshift accuracy in the 3D-HST photometric catalogs, using 3D-HST grism redshifts to quantify and dissect trends in redshift accuracy for galaxies brighter than JH IR > 24 with an unprecedented and representative high-redshift galaxy sample. We find an average scatter of 0.0197 ± 0.0003(1 + z) in the Skelton et al. photometric redshifts. Photometric redshift accuracy decreases with magnitude and redshift, but does not vary monotonically with color or stellar mass. The 1σ scatter lies between 0.01 and 0.03 (1 + z) for galaxies of all masses and colors below z JH IR 2), dusty star-forming galaxies for which the scatter increases to ~0.1 (1 + z). We find that photometric redshifts depend significantly on galaxy size; the largest galaxies at fixed magnitude have photo-zs with up to ~30% more scatter and ~5 times the outlier rate. Although the overall photometric redshift accuracy for quiescent galaxies is better than that for star-forming galaxies, scatter depends more strongly on magnitude and redshift than on galaxy type. We verify these trends using the redshift distributions of close pairs and extend the analysis to fainter objects, where photometric redshift errors further increase to ~0.046 (1 + z) at HF160W=26. We demonstrate that photometric redshift accuracy is strongly filter dependent and quantify the contribution of multiple filter combinations. We evaluate the widths of redshift probability distribution functions and find that error estimates are underestimated by a factor of ~1.1–1.6, but that uniformly broadening the distribution does not adequately account for fitting outliers. Finally, we suggest possible applications of these data in planning for current and future surveys and simulate photometric redshift performance in the Large Synoptic Survey Telescope, Dark Energy Survey (DES), and combined DES and Vista Hemisphere surveys

Spectroscopic Confirmation of Three z-Dropout Galaxies at z = 6.844 - 7.213: Demographics of Lyman-Alpha Emission in z ~ 7 Galaxies

We present the results of our ultra-deep Keck/DEIMOS spectroscopy of z-dropout galaxies in the SDF and GOODS-N. For 3 out of 11 objects, we detect an emission line at ~ 1um with a signal-to-noise ratio of ~ 10. The lines show asymmetric profiles with high weighted skewness values, consistent with being Lya, yielding redshifts of z=7.213, 6.965, and 6.844. Specifically, we confirm the z=7.213 object in two independent DEIMOS runs with different spectroscopic configurations. The z=6.965 object is a known Lya emitter, IOK-1, for which our improved spectrum at a higher resolution yields a robust skewness measurement. The three z-dropouts have Lya fluxes of 3 x 10^-17 erg s^-1 cm^-2 and rest-frame equivalent widths EW_0^Lya = 33-43A. Based on the largest spectroscopic sample of 43 z-dropouts that is the combination of our and previous data, we find that the fraction of Lya-emitting galaxies (EW_0^Lya > 25A) is low at z ~ 7; 17 +- 10% and 24 +- 12% for bright (Muv ~= -21) and faint (Muv ~= -19.5) galaxies, respectively. The fractions of Lya-emitting galaxies drop from z ~ 6 to 7 and the amplitude of the drop is larger for faint galaxies than for bright galaxies. These two pieces of evidence would indicate that the neutral hydrogen fraction of the IGM increases from z ~ 6 to 7, and that the reionization proceeds from high- to low-density environments, as suggested by an inside-out reionization model.Comment: 15 pages, 9 figures, accepted for publication in Ap

Constraints on Physical Properties of z~6 Galaxies Using Cosmological Hydrodynamic Simulations

We conduct a detailed comparison of broad-band spectral energy distributions of six z >= 5.5 galaxies against galaxies drawn from cosmological hydrodynamic simulations. We employ a new tool called SPOC, which constrains the physical properties of observed galaxies through a Bayesian likelihood comparison with model galaxies. For five out of six observed z>=5.5 objects, our simulated galaxies match the observations at least as well as simple star formation histories such as tau-models, with similar favored values obtained for the intrinsic physical parameters such as stellar mass and star formation rate, but with substantially smaller uncertainties. Our results are broadly insensitive to simulation choices for galactic outflows and dust reddening. Hence the existence of early galaxies as observed is broadly consistent with current hierarchical structure formation models. However, one of the six objects has photometry that is best fit by a bursty SFH unlike anything produced in our simulations, driven primarily by a high K-band flux. These findings illustrate how SPOC provides a robust tool for optimally utilizing hydrodynamic simulations (or any model that predicts galaxy SFHs) to constrain the physical properties of individual galaxies having only photometric data, as well as identify objects that challenge current models. (abridged)Comment: 22 pages, 11 figures, accepted by MNRAS. Added discussions of dust, numerical resolution; clarified conclusion