56,876 research outputs found
Accuracy of the Orientation Estimate Obtained Using Four Sensor Fusion Filters Applied to Recordings of Magneto-Inertial Sensors Moving at Three Rotation Rates
No full textMagneto-Inertial technology is a well-established alternative to optical motion capture for human motion analysis applications since it allows prolonged monitoring in free-living conditions. Magneto and Inertial Measurement Units (MIMUs) integrate a triaxial accelerometer, a triaxial gyroscope and a triaxial magnetometer in a single and lightweight device. The orientation of the body to which a MIMU is attached can be obtained by combining its sensor readings within a sensor fusion framework. Despite several sensor fusion implementations have been proposed, no well-established conclusion about the accuracy level achievable with MIMUs has been reached yet. The aim of this preliminary study was to perform a direct comparison among four popular sensor fusion algorithms applied to the recordings of MIMUs rotating at three different rotation rates, with the orientation provided by a stereophotogrammetric system used as a reference. A procedure for suboptimal determination of the parameter filter values was also proposed. The findings highlighted that all filters exhibited reasonable accuracy (rms errors < 6.4°). Moreover, in accordance with previous studies, every algorithm's accuracy worsened as the rotation rate increased. At the highest rotation rate, the algorithm from Sabatini (2011) showed the best performance with errors smaller than 4.1° rms
Economic Growth, Technological Progress and Social Capital: The Inverted U Hypothesis
No full textWe set up a theoretical framework to analyse the role of economic growth and technological progress in the erosion of social capital. Under certain conditions on parameters, the relationship between technological progress and social capital can take the shape of an inverted U curve. Furthermore, we show the circumstances that allow the economy to follow trajectories where the stock of social capital grows endogenously and unboundedly
Deriving site-specific species pools from large databases
No full textDefining the species pool of a community is crucial for many types of ecological analyses, providing a foundation to metacommunity, null modelling or dark diversity frameworks. It is a challenge to derive the species pool empirically from large and heterogeneous databases. Here, we propose a method to define a site-specific species pool (SSSP), i.e. the probabilistic set of species that may co-occur with the species of a target community. Using large databases with geo-referenced records that comprise full plant community surveys, our approach characterizes each site by its own species pool without requiring a pre-defined habitat classification. We calculate the probabilities of each species in the database to occur in the target community using Beals’ index of sociological favourability, and then build sample-based rarefaction curves from neighbouring records with similar species composition to estimate the asymptotic species pool size. A corresponding number of species is then selected among the species having the highest occurrence probability, thus defining both size and composition of the species pool. We tested the robustness of this approach by comparing SSSPs obtained with different spatial extents and dissimilarity thresholds, fitting different models to the rarefaction curves, and comparing the results obtained when using Beals co-occurrence probabilities or presence/absence data. As an example application, we calculated the SSSPs for all calcareous grassland records in the German Vegetation Reference Database, and show how our method could be used to 1) produce grain-dependent estimations of species richness across plots, 2) derive scalable maps of species richness and 3) define the full list of species composing the SSSP of each target site. By deriving the species pool exclusively from community characteristics, the SSSP framework presented here provides a robust approach to bridge biodiversity estimations across spatial scales
Gait phases determination using Markov models applied to the recordings of a shank-worn gyroscope
No full textProgressive sensorineural hearing loss, ataxia and anosmia as manifestation of superficial siderosis in post traumatic brain injury.
No full textA Dynamic Subfilter-scale Stress Model for Large Eddy Simulations Based on Physical Flow Scales
No full textWe propose a new definition of the length scale in an eddy-viscosity model for large-eddy simulations (LES). This formulation extends and generalizes a previous proposal [Piomelli, Rouhi and Geurts, Proc. ETMM10, 2014], in which the LES length scale was expressed in terms of the integral length-scale of turbulence determined by the flow characteristics and explicitly decoupled from the simulation grid; this approach was named Integral Length-Scale Approximation (ILSA). As in the original ILSA, the model coefficient was determined by the user, and required to maintain a desired contribution of the unresolved, subfilter scales (SFS) to the global transport. We propose a local formulation (local ILSA) in which the model coefficient is local in space, allowing a precise control over SFS activity as a function of location. This new formulation preserves the properties of the global model; application to channel flow and backward-facing step verifies its features and accuracy
Large-eddy simulation of a separated flow with a sub-filter scale model based on the integral length-scale
No full textA new sub-filter scale model for large-eddy simulations, which uses a length-scale proportional to the integral scale of the turbulence instead of the grid resolution to parametrize the modelled stresses, will be assessed in the prediction of the flow of a boundary-layer over a rough surface, which includes separation and reattachment
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