Group Importance Sampling for Particle Filtering and MCMC

Bayesian methods and their implementations by means of sophisticated Monte Carlo techniques have become very popular in signal processing over the last years. Importance Sampling (IS) is a well-known Monte Carlo technique that approximates integrals involving a posterior distribution by means of weighted samples. In this work, we study the assignation of a single weighted sample which compresses the information contained in a population of weighted samples. Part of the theory that we present as Group Importance Sampling (GIS) has been employed implicitly in different works in the literature. The provided analysis yields several theoretical and practical consequences. For instance, we discuss the application of GIS into the Sequential Importance Resampling framework and show that Independent Multiple Try Metropolis schemes can be interpreted as a standard Metropolis-Hastings algorithm, following the GIS approach. We also introduce two novel Markov Chain Monte Carlo (MCMC) techniques based on GIS. The first one, named Group Metropolis Sampling method, produces a Markov chain of sets of weighted samples. All these sets are then employed for obtaining a unique global estimator. The second one is the Distributed Particle Metropolis-Hastings technique, where different parallel particle filters are jointly used to drive an MCMC algorithm. Different resampled trajectories are compared and then tested with a proper acceptance probability. The novel schemes are tested in different numerical experiments such as learning the hyperparameters of Gaussian Processes, two localization problems in a wireless sensor network (with synthetic and real data) and the tracking of vegetation parameters given satellite observations, where they are compared with several benchmark Monte Carlo techniques. Three illustrative Matlab demos are also provided.Comment: To appear in Digital Signal Processing. Related Matlab demos are provided at https://github.com/lukafree/GIS.gi

Fraction-like ratings from preferential voting

A method is given for resolving a matrix of preference scores into a well-specfied mixture of options. This is done in agreement with several desirable properties, including the continuity of the mixing proportions with respect to the preference scores and a condition of compatibility with the Condorcet-Smith majority principle. These properties are achieved by combining the classical rating method of Zermelo with a projection procedure introduced in previous papers of the same authors

Electric field inversion asymmetry: Rashba and Stark effects for holes in resonant tunneling devices

We report experimental evidence of excitonic spin-splitting, in addition to the conventional Zeeman effect, produced by a combination of the Rashba spin-orbit interaction, Stark shift and charge screening. The electric-field-induced modulation of the spin-splitting are studied during the charging and discharging processes of p-type GaAs/AlAs double barrier resonant tunneling diodes (RTD) under applied bias and magnetic field. The abrupt changes in the photoluminescence, with the applied bias, provide information of the charge accumulation effects on the device.Comment: 4 pages, 2 figure

Woodland caribou persistence and extirpation in relic populations on Lake Superior

Extended: The hypothesis was proposed that woodland caribou (Rangifer tarandus caribou) in North America had declined due to wolf predation and over-hunting rather than from a shortage of winter lichens (Bergerud, 1974). In 1974, two study areas were selected for testing: for the lichen hypothesis, we selected the Slate Islands in Lake Superior (36 km2), a closed canopy forest without terrestrial lichens, wolves, bears, or moose; for the predation hypothesis, we selected the nearby Pukaskwa National Park (PNP) where terrestrial lichens, wolves, bears, and moose were present. Both areas were monitored from 1974 to 2003 (30 years). The living and dead caribou on the Slates were estimated by the ‘King census’ strip transect (mean length 108±9.3 km, extremes 22-190, total 3026 km) and the Lincoln Index (mean tagged 45±3.6, extremes 15-78). The mean annual population on the Slate Islands based on the strip transects was 262±22 animals (extremes 104-606), or 7.3/km2 (29 years) and from the Lincoln Index 303±64 (extremes 181-482), or 8.4/km2 (23 years). These are the highest densities in North America and have persisted at least since 1949 (56 years). Mountain maple (Acer spicatum) interacted with caribou density creating a record in its age structure which corroborates persistence at relatively high density from c. 1930. The mean percentage of calves was 14.8±0.34% (20 years) in the fall and 14.1±1.95% (19 years) in late winter. The Slate Islands herd was regulated by the density dependent abundance of summer green foods and fall physical condition rather than density independent arboreal lichen availability and snow depths. Two wolves (1 wolf/150 caribou) crossed to the islands in 1993-94 and reduced two calf cohorts (3 and 4.9 per cent calves) while female adult survival declined from a mean of 82% to 71% and the population declined ≈100 animals. In PNP, caribou/moose/wolf populations were estimated by aerial surveys (in some years assisted by telemetry). The caribou population estimates ranged from 31 in 1979 to 9 in 2003 (Y=1267 - 0.628X, r=-0.783, n=21, P<0.01) and extirpation is forecast in 2018. Animals lived within 3 km of Lake Superior (Bergerud, 1985) with an original density of 0.06/km2, similar to many other woodland herds coexisting with wolves (Bergerud, 1992), and 100 times less than the density found on the Slate Islands. The mean moose population was 0.25±0.016/km2 and the wolf population averaged 8.5±0.65/1000 km2. Late winter calf percentages in PNP averaged 16.2±1.89 (25 years); the population was gradually reduced by winter wolf predation (Bergerud, 1989; 1996). The refuge habitat available is apparently insufficient for persistence in an area where the continuous distribution of woodland caribou is fragmented due to moose exceeding 0.10/km2 and thereby supporting wolf densities ≥6.5/1000 km2. A second experimental study was to introduce Slate Island caribou to areas with and without wolves. A release to Bowman Island, where wolves and moose were present, failed due to predation. Bowman Island is adjacent to St. Ignace Island where caribou had persisted into the late 1940s. A second release in 1989 to the mainland in Lake Superior Provincial Park of 39 animals has persisted (<10 animals) because the animals utilize off-shore islands but numbers are also declining. A third release to Montréal Island in 1984 doubled in numbers (up to 20 animals) until Lake Superior froze in 1994 and wolves reached the island. A fourth release was to Michipicoten Island (188 km2) in 1982 where wolves were absent and few lichens were available. This herd increased at λ= 1.18 (8 to ±200, 160 seen 2001) in 19 years. This was the island envisioned for the crucial test of the lichen/predation hypotheses (Bergerud, 1974: p.769). These studies strongly support the idea that ecosystems without predators are limited bottom–up by food and those with wolves top-down by predation; however the proposed crucial test which has been initiated on Michipicoten Island remains to be completed and there is a limited window of opportunity for unequivocal results

Photocatalytic activity of nitrogen-doped and undoped titanium dioxide sputtered thin films

In the present work titanium dioxide (TiO2) thin films were grown by d.c. reactive magnetron sputtering process, systematically varying the Ar/O2 ratio in the gas mixture, in order to study the influence of the oxygen partial pressure on the crystallographic structure and photocatalytic activity of the TiO2 thin films. After the sputtering process the TiO2 coatings were nitrided in a microwave (f= 2.45 GHz) Electron Cyclotron Resonance (ECR) plasma discharge in pure nitrogen, to compare the photocatalytic activity of undoped and nitrogen-doped TiO2 thin films. The crystal structure of the TiO2 grown samples was studied by x-ray diffraction (XRD) and the presence of the anatase phase in these films were corroborated by Raman spectroscopy. On the other hand, X-ray photoelectron spectroscopy (XPS) measurements carried out in the nitrogen-doped TiO2 samples, showed that the nitrogen was incorporated to the films with an average concentration of 18 at% of N. The UV-Vis optical spectroscopy allowed calculating the band gap. A narrowing of the optical band gap from 3.2 eV for the undoped films to 2.5 eV for the N-doped films was observed. Photocatalytic activity tests were done using a methylene blue (MB) dye solution. The irradiation of the films in the MB dye solution was carried out with an emission lamp in the UV and in the visible range for undoped and N-doped TiO2 films, respectively. The results showed that the N-doped TiO2 films had a higher photocalytic activity in the visible range, reaching a greater MB degradation in comparison with undoped samples, which were subjected to a higher energy radiation.Fil: Franco Arias, Lina Maria. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad del Valle; ColombiaFil: Zambrano, G.. Universidad del Valle; ColombiaFil: Gómez, M. E.. Universidad del Valle; ColombiaFil: Camps, E.. Instituto Nacional de Investigaciones Nucleares; MéxicoFil: Escobar Alarcón, L.. Instituto Nacional de Investigaciones Nucleares; Méxic

New technology in Museums: AR and VR video games are coming

Museums have gone through a modernization process which has seen the adoption of new technologies in what they offer visitors. Within the framework of the new critical museology, these organizations have been transformed into places of encounter and experience, the key tools in this change being socialization and play. Gamification are now intrinsic to collections and are a way of inviting visitors to share new museum experiences through the latest technology such as AR (Augmented Reality) and VR (Virtual Reality). In this way, the museum becomes a playground and a space for creativity (Borja-Villel et al., 2014). In this research, we focus on what we consider to be an important link between the three central aspects of museum change: sociability, gamificaction and virtualization; and the growing interest in museums for videogames. Our aim is to reach a better understanding of the AR and VR video games developed for museums and how these technologies can not only motivate visitors’ interest but also improve their learning skills. Our analysis focuses of literature published between 2015 to 2018 and follows the analytic structure established by Connolly et al. (2012) with additional features related to learning experience, platforms, and the use of technologies (VR and AR). The general aim is to map the interest of the research community in the field of museum-developed video games, more specifically those that use augmented and virtual reality

Measuring the dust content and formation in SN 1987A using detailed radiative transfer modelling

AbstractCore-collapse supernovae are expected to be efficient producers of dust, and recent Herschel and ALMA observations have revealed up to 1 M⊙ of cold dust in the inner ejecta of SN 1987A. The formation time scale, spatial distribution and clumpiness, and the importance of the different heating sources of the dust remain poorly understood. We have started a project to make detailed 3D dust radiative transfer models for SN 1987A, based on a combination of the latest observational constraints and input from 3D hydrodynamical models and dust formation models. Preliminary results seem to indicate the need for large, micron-sized dust grains, and a relatively large dust mass.</jats:p

Machine-learned cloud classes from satellite data for process-oriented climate model evaluation

Clouds play a key role in regulating climate change but are difficult to simulate within Earth system models (ESMs). Improving the representation of clouds is one of the key tasks towards more robust climate change projections. This study introduces a new machine-learning based framework relying on satellite observations to improve understanding of the representation of clouds and their relevant processes in climate models. The proposed method is capable of assigning distributions of established cloud types to coarse data. It facilitates a more objective evaluation of clouds in ESMs and improves the consistency of cloud process analysis. The method is built on satellite data from the MODIS instrument labelled by deep neural networks with cloud types defined by the World Meteorological Organization (WMO), using cloud type labels from CloudSat as ground truth. The method is applicable to datasets with information about physical cloud variables comparable to MODIS satellite data and at sufficiently high temporal resolution. We apply the method to alternative satellite data from the Cloud\_cci project (ESA Climate Change Initiative), coarse-grained to typical resolutions of climate models. The resulting cloud type distributions are physically consistent and the horizontal resolutions typical of ESMs are sufficient to apply our method. We recommend outputting crucial variables required by our method for future ESM data evaluation. This will enable the use of labelled satellite data for a more systematic evaluation of clouds in climate models.Comment: Main Paper 16 pages, 11 figures. Supporting material 7 Pages, 8 figures. This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl