Renewable thermoplastic multiphase systems from dimer fatty acids,with mineral microfillers

Renewable thermoplastic blends based on polyurethane (TPU) and polyamide (DAPA) obtained from dimers of fatty acids were reinforced with mineral microfillers, surface coated calcium carbonate (CaCO₃) or high aspect ratio talc (HAR), to prepare different micro‐biocomposites systems. The influence of the nature of the filler, the aspect ratio and the filler content (5, 10, and 15 wt %), for different TPU/DAPA ratios (20/80, 50/50, and 80/20 wt %/wt %), were specifically investigated. Differential scanning calorimetry (DSC) and thermogravimetric analyses were conducted to investigate the thermal properties. DSC analyses showed that the addition of CaCO₃ had no influence on the glass transition and the melting temperature of the corresponding composites. Moreover, the morphology and the mechanical properties in the solid state of the different multiphase systems were investigated. SEM observations after tensile tests showed that the best matrix/filler interactions were obtained in the case of the 20/80‐based systems. Uniaxial tensile tests have shown that the addition of HAR or CaCO₃ fillers led to a clear increase of the Young modulus. Micromechanical models based on a two‐phase composite approach, including Mori–Tanaka and Davies models were used to describe the dependence of the elastic modulus on the volume fraction of HAR or CaCO₃ fillers. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 43055.     

Feedback stabilization for high order feedforward nonlinear time-delay systems

This paper investigates the problem of global strong stabilization by state feedback, for a family of high order feedforward nonlinear time-delay systems. The uncertain nonlinearities are assumed to satisfy a polynomial growth assumption with an input or delayed input dependent rate. With the help of the appropriate Lyapunov–Krasovskii functionals, and a rescaling transformation with a gain to be tuned online by a dynamic equation, we propose a dynamic low gain state feedback control scheme. A simulation example is given to demonstrate the effectiveness of the proposed design procedure.     

EDUCA: A web 2.0 authoring tool for developing adaptive and intelligent tutoring systems using a Kohonen network

This paper presents a Web 2.0 Learning Environment, for a systematic creation of adaptive and intelligent tutoring systems. Authoring contents is made by a community of users including teachers and students. The tutoring systems adapt the contents according to the best learning style using self-organizing maps (SOMs). The SOM was trained for classifying Felder–Silverman learning styles. The most important advantage of these unsupervised neural networks is that they do not require an external teacher for presenting a training set. The approach was implemented under an authoring tool that allows the production of personalized learning material to be used under collaborative and mobile learning environments. The tutoring systems together with the neural network can also be exported to mobile devices. We present different results to the approach working under the authoring tool.     

Markerless tracking of complex human motions from multiple views

We present a method for markerless tracking of complex human motions from multiple camera views. In the absence of markers, the task of recovering the pose of a person during such motions is challenging and requires strong image features and robust tracking. We propose a solution which integrates multiple image cues such as edges, color information and volumetric reconstruction. We show that a combination of multiple image cues helps the tracker to overcome ambiguous situations such as limbs touching or strong occlusions of body parts. Following a model-based approach, we match an articulated body model built from superellipsoids against these image cues. Stochastic Meta Descent (SMD) optimization is used to find the pose which best matches the images. Stochastic sampling makes SMD robust against local minima and lowers the computational costs as a small set of predicted image features is sufficient for optimization. The power of SMD is demonstrated by comparing it to the commonly used Levenberg–Marquardt method. Results are shown for several challenging sequences showing complex motions and full articulation, with tracking of 24 degrees of freedom in ≈1 frame per second.     

Contracting Optimally an Interval Matrix without Loosing Any Positive Semi-Definite Matrix Is a Tractable Problem

In this paper, we show that the problem of computing the smallest interval submatrix of a given interval matrix [A] which contains all symmetric positive semi-definite (PSD) matrices of [A], is a linear matrix inequality (LMI) problem, a convex optimization problem over the cone of positive semidefinite matrices, that can be solved in polynomial time. From a constraint viewpoint, this problem corresponds to projecting the global constraint PSD (A) over its domain [A]. Projecting such a global constraint, in a constraint propagation process, makes it possible to avoid the decomposition of the PSD constraint into primitive constraints and thus increases the efficiency and the accuracy of the resolution.D. Henrion acknowledges support of grant No. 102/02/0709 of the Grant Agency of the Czech Republic, and project No. ME 698/2003 of the Ministry of Education of the Czech Republic.     

Regional aboveground forest biomass using airborne and spaceborne LiDAR in Québec

Aboveground dry biomass was estimated for the 1.3 M km² forested area south of the treeline in the eastern Canadian province of Québec by combining data from an airborne and spaceborne LiDAR, a Landsat ETM+ land cover map, a Shuttle Radar Topographic Mission (SRTM) digital elevation model, ground inventory plots, and vegetation zone maps. Plot-level biomass was calculated using allometric relationships between tree attributes and biomass. A small footprint portable laser profiler then flew over these inventory plots to develop a generic airborne LiDAR-based biomass equation (R² = 0.65, n = 207). The same airborne LiDAR system flew along four portions of orbits of the ICESat Geoscience Laser Altimeter System (GLAS). A square-root transformed equation was developed to predict airborne profiling LiDAR estimates of aboveground dry biomass from GLAS waveform parameters combined with an SRTM slope index (R² = 0.59, n = 1325).Using the 104,044 quality-filtered GLAS pulses obtained during autumn 2003 from 97 orbits over the study area, we then predicted aboveground dry biomass for the main vegetation areas of Québec as well as for the entire Province south of the treeline. Including cover type covariances both within and between GLAS orbits increased standard errors of the estimates by two to five times at the vegetation zone level and as much as threefold at the provincial level. Aboveground biomass for the whole study area averaged 39.0 ± 2.2 (standard error) Mg ha^? 1 and totalled 4.9 ± 0.3 Pg. Biomass distributions were 12.6% northern hardwoods, 12.6% northern mixedwood, 38.4% commercial boreal, 13% non-commercial boreal, 14.2% taiga, and 9.2% treed tundra. Non-commercial forests represented 36% of the estimated aboveground biomass, thus highlighting the importance of remote northern forests to C sequestration. This study has shown that space-based forest inventories of northern forests could be an efficient way of estimating the amount, distribution, and uncertainty of aboveground biomass and carbon stocks at large spatial scales.