Deep Learning on Lie Groups for Skeleton-based Action Recognition

In recent years, skeleton-based action recognition has become a popular 3D classification problem. State-of-the-art methods typically first represent each motion sequence as a high-dimensional trajectory on a Lie group with an additional dynamic time warping, and then shallowly learn favorable Lie group features. In this paper we incorporate the Lie group structure into a deep network architecture to learn more appropriate Lie group features for 3D action recognition. Within the network structure, we design rotation mapping layers to transform the input Lie group features into desirable ones, which are aligned better in the temporal domain. To reduce the high feature dimensionality, the architecture is equipped with rotation pooling layers for the elements on the Lie group. Furthermore, we propose a logarithm mapping layer to map the resulting manifold data into a tangent space that facilitates the application of regular output layers for the final classification. Evaluations of the proposed network for standard 3D human action recognition datasets clearly demonstrate its superiority over existing shallow Lie group feature learning methods as well as most conventional deep learning methods.Comment: Accepted to CVPR 201

Toxicity of Pb and of Pb/Cd combination on the springtail Folsomia candida in natural soils: Reproduction, growth and bioaccumulation as indicators

The toxicity of Pb and Cd+Pb was assessed on the Collembola F. candida in two cultivated soils (SV and AU) with low organic matter (OM) content and circumneutral to basic pH, and an acid forested soil (EPC) with high OM content. Collembola reproduction and growth as well as metal content in Collembola body, in soil, exchangeable fraction and soil solutions, pH and DOC were investigated. Pb and Cd+Pb were the highest in exchangeable fraction and soil solution of the acidic soils. Soil solution pH decreased after metal spiking in every soil due to metal adsorption, which was similar for Cd and the highest in AU for Pb. With increasing Pb and Cd+Pb, the most important reproduction decrease was in EPC soil. The LOEC for reproduction after metal addition was 2400 (Pb) and 200/2400 (Cd/Pb), 1200 and 100/1200, 300 and 100/1200 μg g−1 for AU, SV and EPC, respectively. The highest and the lowest Pb toxicity was observed for EPC and AU bulk soil, respectively. The metal in Collembola increased with increasing soil concentration, except in AU, but the decreasing BFsolution with increasing concentrations indicates a limited metal transfer to Collembola or an increased metal removal. Loading high Pb concentrations decreases Cd absorption by the Collembola, but the reverse was not true. The highest Pb toxicity in EPC can be explained by pH and OM content. Because of metal complexation, OM might have a protective role but its ingestion by Collembola lead to higher toxicity. Metal bioavailability in Collembola differs from soil solution indicating that soil solution is not sufficient to evaluate toxicity in soil organisms. The toxicity as a whole decreased when metals were combined, except for Pb in AU, due to adsorption competition between Cd and Pb on clay particles and OM sites in AU and EPC soils, respectively

Admissible closures of polynomial time computable arithmetic

We propose two admissible closures $${\mathbb{A}({\sf PTCA})}$$ and $${\mathbb{A}({\sf PHCA})}$$ of Ferreira's system PTCA of polynomial time computable arithmetic and of full bounded arithmetic (or polynomial hierarchy computable arithmetic) PHCA. The main results obtained are: (i) $${\mathbb{A}({\sf PTCA})}$$ is conservative over PTCA with respect to $${\forall\exists\Sigma^b_1}$$ sentences, and (ii) $${\mathbb{A}({\sf PHCA})}$$ is conservative over full bounded arithmetic PHCA for $${\forall\exists\Sigma^b_{\infty}}$$ sentences. This yields that (i) the $${\Sigma^b_1}$$ definable functions of $${\mathbb{A}({\sf PTCA})}$$ are the polytime functions, and (ii) the $${\Sigma^b_{\infty}}$$ definable functions of $${\mathbb{A}({\sf PHCA})}$$ are the functions in the polynomial time hierarch

Evidence of Springwater Acidification in the Vosges Mountains (North-East of France): Influence of Bedrock Buffering Capacity

Investigations on springwater acidity were carried out in the Vosges mountains (north-eastern France). Acid or poorly buffered spring and streamwaters were detected in the same area. The proportion of acid springwaters (pH < 5.6) is about 20% among 220 springs. The springwater pH on granite are equally spread between 5.0 and 6.8 whereas on sandstone a majority of springs is in the range 5.6 to 6.2. As a whole, but mainly on sandstone, from the 1960's to 1990's, the shape of the pH distributions shifts toward greater acidity. In the sandstone area, trends in pH, alkalinity, total hardness (corresponding to divalent cations), sulfate and nitrate were considered over the 30 yr period (1963-1996) in relation to the bedrock chemical composition. Kendall seasonal tau coefficients indicate that decreasing trends were significant for the first three parameters. Linear regression on the smoothed mean value revealed 18 and 90% decrease for pH and alkalinity respectively, for springwaters draining poor-base cation sandstone whereas only 8 and 30% decrease respectively, was observed on clay-enriched sandstone. On silica-enriched sandstone, alkalinity began to decrease in the early 70's as well as pH. Loss of alkalinity only occurred in the early 80's for springs draining clay enriched sandstone. This can be interpreted as a titration process by acid atmospheric inputs of the buffering capacity of weathering and exchange processes in the soils and the catchment bedrock. The nitrate presents an increasing step in the early seventies but possibly as a result of change in analytical technics and/or increase in atmospheric inputs mainly resulting from increase in fertiliser inputs in agricultural areas or in car traffic. Surprisingly no change in sulfate was noticed in any groups of springs probably as a result of the adsorption/mobilisation in the soils. These long-term trends in spring waters (1963-1996) confirmed the soil and streamwater acidification trends already mentioned in this region, in relation to acid atmospheric inputs since no climate nor forestry practice changes have been detected over the period. Moreover, in spite of acid atmospheric input reductions, no recovery can presently be detected

Mapping, Localization and Path Planning for Image-based Navigation using Visual Features and Map

Building on progress in feature representations for image retrieval, image-based localization has seen a surge of research interest. Image-based localization has the advantage of being inexpensive and efficient, often avoiding the use of 3D metric maps altogether. That said, the need to maintain a large number of reference images as an effective support of localization in a scene, nonetheless calls for them to be organized in a map structure of some kind. The problem of localization often arises as part of a navigation process. We are, therefore, interested in summarizing the reference images as a set of landmarks, which meet the requirements for image-based navigation. A contribution of this paper is to formulate such a set of requirements for the two sub-tasks involved: map construction and self-localization. These requirements are then exploited for compact map representation and accurate self-localization, using the framework of a network flow problem. During this process, we formulate the map construction and self-localization problems as convex quadratic and second-order cone programs, respectively. We evaluate our methods on publicly available indoor and outdoor datasets, where they outperform existing methods significantly.Comment: CVPR 2019, for implementation see https://github.com/janinethom

Statistical Validation and Skill Assessment of Hyflux2 Model

The Joint Research Center (JRC) has developed extensive experience in tsunami early warning systems, using the JRC-SWAN finite difference code for wave propagation simulation and the JRC finite-volume HyFlux2 code for wave propagation and inundation modelling over the last years. Since 2011, NWP (Numerical Weather Prediction) atmospheric forcing terms have been included in the HyFlux2 code for simulating storm surge events. In the current work, the skill assessment of Hylfux2 is performed. A wide range of verification metrics has been utilised for both Hyflux2 model data sets namely NOF (raw forecasts with no adjustment) and YOF (post forecasts by applying an optimal type of offset). Investigating over typical metrics as bias, root mean square error (RMSE) and centred root mean square differences (CRMSD), inter-comparisons were possible versus another integrated storm surge forecast system namely KASSANDRA (KASS) of ISMAR-CNR. Referring to the ability of reproducing the variability of observations, inter-comparing over 10 common stations revealed that Hyflux2 YOF configuration although in the right direction, is not reaching the quality of KASS system for T+24-hour horizon. Hyflux2 normalised standard deviation manages to reach the 0.81 value compared to 0.97 value of KASS (with perfect score: 1.0). On the other hand, the most important message seems to be the one coming from the inter-comparison between CRMSD scores. Hylfux2 YOF forecasts appear to have a comparable CRMSD score (6.42 cm) to the score coming from KASS system (5.86 cm) for T+24 hours. Furthermore, there are stations (like Civitavecchia, Genova, Napoli and Palermo) over which Hyflux2 YOF forecasts score considerably better than KASS system, whereas the rest of YOF forecasts appear to have a lower (but still of high quality) correlation coefficient (0.80) score compared to the one coming from KASS system (0.89 cm) for T+24 hours. Another important area that special type of metrics was used (such as accuracy, frequency bias, hit rate, false alarm ratio, probability of false detection, success ratio, threat score, equitable threat score, true skill statistics, odds ratio and odds ratio skill score) has been the ability of Hyflux2 to provide useful (warning) forecast guidance in cases of high-intensity storm surge events. The selection of an optimal (95% percentile) threshold was made being high enough to be considered as extreme but also capable of providing enough cases for robust statistics. The main outcome of such an approach has revealed that 72% (T+72 hours) to 79% (T+12 hours) of all Hyflux2 forecasts were correct over central Mediterranean (CMEDI) for both NOF and YOF forecasts. The corresponding values for west Mediterranean (WMEDI) were reaching even higher values (80 - 81% to 88%) with similar skill values for both NOF and YOF configurations, but it should be stressed out that these results have considered a large number of correct negatives (referring to non-extremes events). Focussing over high-intensity events (that have been observed) Hylfux2 appears to have considerable forecasting limitations being able to capture only the 23% (T+72) to 34% (T+12) of events while missing more than 70% of the high-intensity events at T+48 hours. Such forecasting limitations become obvious during the in-depth analysis over two case study extreme events taken place over Ravenna (6 February 2015) and Venice (29 February 2016). The capabilities of both NOF & YOF forecasts based on ECMWF relatively low-resolution forcing terms to provide useful guidance in Ravenna case found to be limited even if both NOF & YOF managed to provide a relatively useful early warning for the extreme case of Venice. It appears that both NOF & YOF configurations (based on ECMWF forcing terms) have certain limitations to provide the best possible setup for detecting and simulating such high-impact events. On the other hand, HYflux2 YOF forecasts based on various COSMO model high-resolution forcing terms seem to do quite much better in capturing both events and providing useful (early) warning to the user. It seems that for such high-impact events higher-resolution forcing terms are necessary to correctly resolve the full extent and magnitude of the event. This higher resolution feature is most probably the reason why Hyflux2 based on COSMO model (run operationally by the Italian Air Force Weather Meteorological Service) high-resolution forcing terms provides much more useful guidance in cases of extreme events.JRC.E.1-Disaster Risk Managemen

Tropical Cyclones and Storm Surge Modelling Activities

The Global Disasters Alert and Coordination System (GDACS) automatically invokes ad hoc numerical models to analyse the level of the hazard of natural disasters like earthquakes, tsunamis, tropical cyclones, floods and volcanoes. The Tropical Cyclones (TCs) are among the most damaging events, due to strong winds, heavy rains and storm surge. In order to estimate the area and the population affected, all three types of the above physical impacts must be taken into account. GDACS includes all these dangerous effects, using various sources of data. The JRC set up an automatic routine that includes the TC information provided by the Joint Typhoon Warning Center (JTWC) and the National Oceanic and Atmospheric Administration (NOAA) into a single database, covering all TCs basins. This information is used in GDACS for the wind impact and as input for the JRC storm surge system. Recently the global numerical models and other TC models have notably improved their resolutions, therefore one of the first aim of this work is the assessment and implementation of new data sources for the wind, storm surge and rainfall impacts in GDACS. Moreover the TC modelling workflow has been revised in order to provide redundancy, transparency and efficiency while addressing issues of accuracy and incorporation of additional physical processes. The status of development is presented along with the outline of future steps.JRC.E.1-Disaster Risk Managemen