Remote-Controlled Ambidextrous Robot Hand Concept

In the development of robotic limbs, the side of members is of importance to define the shape of artificial limbs and the range of movements. It is mainly significant tbr biomedical applications concerning patients suffering arms or legs injuries, fn this paper, the concept of an ambidextrous design lbr robot hands is introduced. The fingers can curl in one xvay or another, to imitate either a right hand or a left hand. The advantages and inconveniences of different models have been investigated to optimise the range and the maximum force applied by fingers. Besides, a remote control interthce is integrated to the system, allowing both to send comrnands through internet and to display a video streaming of the ambidextrous hand as feedback. Therefore, a robotic prosthesis could be used for the first time in telerehabilitation. The main application areas targeted are physiotherapy alter strokes or management of phantom pains/br amputees by/earning to control the ambidextrous hand. A client application is also accessible on Facehook social network, making the robotic limb easily reachable for the patients. Additionally the ambidextrous hand can be used tbr robotics research as well as artistic performances.     

Efficient product sampling using hierarchical thresholding

We present an efficient method for importance sampling the product of multiple functions. Our algorithm computes a quick approximation of the product on the fly, based on hierarchical representations of the local maxima and averages of the individual terms. Samples are generated by exploiting the hierarchical properties of many low-discrepancy sequences, and thresholded against the estimated product. We evaluate direct illumination by sampling the triple product of environment map lighting, surface reflectance, and a visibility function estimated per pixel. Our results show considerable noise reduction compared to existing state-of-the-art methods using only the product of lighting and BRDF.     

Effect of thickness stretching and porosity on mechanical response of a functionally graded beams resting on elastic foundations

The novelty of this paper is the use of an efficient beam theory for bending, free vibration and buckling analysis of functionally graded material (FGM) beams on two-parameter elastic foundation. The present theory accounts for both shear deformation and thickness stretching effects by a parabolic variation of all displacements across the thickness, and satisfies the stress-free boundary conditions on the upper and lower surfaces of the beam without requiring any shear correction factor. Due to porosities, possibly occurring inside FGMs during fabrication, it is therefore necessary to consider the vibration, bending and buckling behaviors of beams having porosities in this work. The equation of motion for FGM beams is obtained through Hamilton’s principle. The closed form solutions are obtained by using Navier technique, and then fundamental frequencies are found by solving the results of eigenvalue problems. The validity of the present theory is investigated by comparing some of the present in literature. It can be concluded that the proposed theory is accurate and simple in solving the bending, free vibration and buckling behaviors of FGM sandwich beams.     

The role of microcrystalline structure on optical scattering characteristics of semi-crystalline thermoplastics and the accuracy of numerical input for IR-heating modeling

Infrared (IR) heating is widely used for thermoforming of thermoplastic polymers. The key benefit of radiation heating is that a significant amount of the radiative energy penetrates into the polymers thanks to their semi-transparency. For the case of heating unfilled semi-crystalline polymers, the relation between their microcrystalline structure and optical properties is the key to develop a predictive IR-heating model as microcrystalline structure introduces an optically heterogeneous medium. In this study, a relation between the microcrystalline structure of a polyethylene (PE) and its effect on the thermo-optical properties was experimentally analyzed considering a two-step analysis. At very first step, the relation was analyzed considering samples with identical thicknesses and different morphologies, characterized here in terms of degree of crystallinity (X_c (%)). Using Fourier Transform Infrared (FT-IR) spectroscopy and integrating sphere, optical characteristics of the PE samples were analyzed in near-infrared (NIR) and middle-infrared (MIR) spectral ranges. The analyses showed that a slight variation in X_c (%) has a great effect on the optical characteristics of PE, particularly the transmission characteristics in NIR range. The wavelength-dependent effect of X_c (%) on the transmission behaviors opened a discussion about the fact that the microcrystalline structures -in particular spherulites or their substructures such as lamellae- are responsible for optical scattering. Using the optical properties obtained from the two-step experimental analyses, two different thermo-optical properties were calculated, namely extinction and absorption coefficients, and used as a numerical input for the parametric numerical studies. The numerical studies were performed using an in-house developed radiation heat transfer algorithm -RAYHEAT-. Both the experimental and numerical analyses demonstrated the importance of the optical scattering regarding the identification of thermo-optical properties, used as a numerical input for radiation heat transfer models.     

Exact algorithms for a generalization of the order acceptance and scheduling problem in a single-machine environment

This paper studies a generalization of the order acceptance and scheduling problem in a single-machine environment where a pool consisting of firm planned orders as well as potential orders is available from which an over-demanded company can select. The capacity available for processing the accepted orders is limited and each order is characterized by a known processing time, delivery date, revenue and a weight representing a penalty per unit-time delay beyond the delivery date. We prove that the existence of a constant-factor approximation algorithm for this problem is unlikely. We propose two linear formulations that are solved using an IP solver and we devise two exact branch-and-bound procedures able to solve instances with up to 50 jobs within reasonable CPU times. We compare the efficiency and quality of the results obtained using the different solution approaches.     

Neural mass activity, bifurcations, and epilepsy

In this letter, we propose a general framework for studying neural mass models defined by ordinary differential equations. By studying the bifurcations of the solutions to these equations and their sensitivity to noise, we establish an important relation, similar to a dictionary, between their behaviors and normal and pathological, especially epileptic, cortical patterns of activity. We then apply this framework to the analysis of two models that feature most phenomena of interest, the Jansen and Rit model, and the slightly more complex model recently proposed by Wendling and Chauvel. This model-based approach allows us to test various neurophysiological hypotheses on the origin of pathological cortical behaviors and investigate the effect of medication. We also study the effects of the stochastic nature of the inputs, which gives us clues about the origins of such important phenomena as interictal spikes, interictal bursts, and fast onset activity that are of particular relevance in epilepsy.     

Satellite-based estimates of groundwater storage variations in large drainage basins with extensive floodplains

This study presents monthly estimates of groundwater anomalies in a large river basin dominated by extensive floodplains, the Negro River Basin, based on the synergistic analysis using multisatellite observations and hydrological models. For the period 2003-2004, changes in water stored in the aquifer is isolated from the total water storage measured by GRACE by removing contributions of both the surface reservoir, derived from satellite imagery and radar altimetry, and the root zone reservoir simulated by WGHM and LaD hydrological models. The groundwater anomalies show a realistic spatial pattern compared with the hydrogeological map of the basin, and similar temporal variations to local in situ groundwater observations and altimetry-derived level height measurements. Results highlight the potential of combining multiple satellite techniques with hydrological modeling to estimate the evolution of groundwater storage.     

Robust pose estimation and recognition using non-gaussian modeling of appearance subspaces

We present an original appearance model that generalizes the usual Gaussian visual subspace model to non-Gaussian and nonparametric distributions. It can be useful for the modeling and recognition of images under difficult conditions such as large occlusions and cluttered backgrounds. Inference under the model is efficiently solved using the mean shift algorithm