Automated Derivation of Primitives for Movement Classification

We describe a new method for representing human movement compactly, in terms of a linear super-imposition of simpler movements termed primitives. This method is a part of a larger research project aimed at modeling motor control and imitation using the notion of perceptuo-motor primitives, a basis set of coupled perceptual and motor routines. In our model, the perceptual system is biased by the set of motor behaviors the agent can execute. Thus, an agent can automatically classify observed movements into its executable repertoire. In this paper, we describe a method for automatically deriving a set of primitives directly from human movement data.We used movement data gathered from a psychophysical experiment on human imitation to derive the primitives. The data were first filtered, then segmented, and principal component analysis was applied to the segments. The eigenvectors corresponding to a few of the highest eigenvalues provide us with a basis set of primitives. These are used, through superposition and sequencing, to reconstruct the training movements as well as novel ones. The validation of the method was performed on a humanoid simulation with physical dynamics. The effectiveness of the motion reconstruction was measured through an error metric. We also explored and evaluated a technique of clustering in the space of primitives for generating controllers for executing frequently used movements.     

Propene Adsorption on Gold Particles on TiO2(110)

The adsorption of propene on rutile TiO₂(110) and on gold islands dispersed on TiO₂(110) [Au/TiO₂(110)], both at 120 K, has been studied using temperature programmed desorption (TPD), X-ray photoelectron spectroscopy (XPS) and He⁺ low energy ion scattering spectroscopy (LEIS). Propene adsorbs on both TiO₂(110) and Au/TiO₂(110), with desorption peak temperatures at low coverage of 190 and 240 K, respectively. When only 16% of the TiO₂(110) surface is covered by gold islands [16% Au/TiO₂(110)], moderate propene doses populate both the 240 and 190 K TPD peaks, in that order. The 190 K peak, seen also without Au, is due to propene bound to bare Ti sites. The 240 K peak is attributed to propene adsorbed to Ti sites at the edges of gold islands. Tiny doses of propene to the 16% Au/TiO₂(110) surface give this a 240 K TPD peak but no 190 K feature, showing that the propene is mobile on TiO₂(110). A TPD feature at 150 K, which is more prominent at higher Au coverages and higher propene doses, is due to propene bound only to metallic Au islands. Propene desorption shows additional intensity at 265-310 K when the gold islands are only one atom thick, due to propene adsorbed on 2D Au islands or at Ti sites near their edges.     

High-yield γ-ray-induced polymerization of bis-2-acetoacetoxyethyl methacrylate copper. II.

The copper (II) acrylic monomer Cu(aaem)₂ (aaem = 2-acetoacetoxyethyl methacrylate) undergoes high-yield γ-ray copolymerization with dimethylacrylamide, styrene, and hydroxoethyl methacrylate in the presence of methylene bisacrylamide as crosslinking agent in dimethylformamide. The metalloorganic copolymers are fully characterized. Polymer-protected Cu(II) results in being extremely stable toward a number of reducing agents in different media. © 1997 John Wiley & Sons, Inc. J Appl Polym Sci 65: 2201–2207, 1997     

Drying Corn Grains Contained in a Vertical Channel with Constant Heat Flux on Walls

A previous report^{[ 1} Bathiébo , J. ; Daguenet , M. ; Zeghmati , B. ; M'Bow , C. Numerical study of natural convection drying of coffee grains contained in a vertical channel with constant heat flux on walls . International Journal of Ambient Energy 2003 , 24 ( 4 ), 171 – 188 .[Taylor & Francis Online] , [Google Scholar] ^] developed a numerical model to study the influence of thermal and mass Rayleigh numbers as well as Darcy and Lewis numbers on heat and mass transfer during the drying by natural convection of coffee grains which are treated as a porous medium. The code uses the Darcy-Brinkman momentum equation and the classical natural convection equations. In this work the numerical computer code has been validated by comparing experimental results obtained during the drying of a corn bed.     

Finite element modelling of an energy-storing prosthetic foot during the stance phase of transtibial amputee gait

Energy-storing prosthetic feet are designed to store energy during mid-stance motion and to recover it during late-stance motion. Gait analysis is the most commonly used method to characterize prosthetic foot behaviour during walking. In using this method, however, the foot is generally modelled as a rigid body. Therefore, it does not take into account the ability of the foot to deform. However, the way this deformation occurs is a key parameter of various foot properties under gait conditions. The purpose of this study is to combine finite element modelling and gait analysis in order to calculate the strain, stress and energy stored in the foot along the stance phase for self-selected and fast walking speeds. A finite element model, validated using mechanical testing, is used with boundary conditions collected experimentally from the gait analysis of a single transtibial amputee. The stress, strain and energy stored in the foot are assessed throughout the stance phase for two walking speed conditions: a self-selected walking speed (SSWS), and a fast walking speed (FWS). The first maximum in the strain energy occurs during heel loading and reaches 3J for SSWS and 7J for FWS at the end of the first double support phase. The second maximum appears at the end of the single support phase, reaching 15J for SSWS and 18J for FWS. Finite element modelling combined with gait analysis allows the calculation of parameters that are not obtainable using gait analysis alone. This modelling can be used in the process of prosthetic feet design to assess the behaviour of a prosthetic foot under specific gait conditions.