Novel pearl millet couscous process for West African markets using a low-cost single-screw extruder

Traditional West African pearl millet couscous products are popular; however, their preparation is laborious, time-consuming and energy-demanding, involving agglomeration, steaming, drying and sieving steps. In this study, a process was developed to produce millet couscous using a high pressure, high temperature and low-cost single-screw extruder. The innovation was to directly process the cooked low-moisture extrudate to a couscous product by drying and milling to the appropriate particle size (ranging between 1 and 2 mm). Throughput for the traditional process as prepared for commercial sale is 50 kg per day, but with the same amount of labour, the extrusion process yields ~350 kg per day. A consumer sensory study held in Niamey (Niger) showed that the extruded millet couscous was comparable to traditional couscous, though this was dependent on selection of the proper millet variety. This novel extrusion process could stimulate small- to medium-scale manufacturing of couscous and couscous-type products in West Africa.     

UV-curable acrylic resins for production of glass laminates

Glass laminates have been readily obtained by photocuring at ambient temperature of an acrylic adhesive consisting either of a liquid resin or a solid thermoplastic polymer. The light-induced polymerization process was followed by real-time infrared spectroscopy. Close to 100% conversion was reached within a few seconds of exposure, by taking as the photoinitiator an α-hydroxy alkylphenone or an aryl phosphine oxide. A liquid formulation containing an aliphatic polyurethane–acrylate oligomer, acrylic acid, and butyl acrylate gives the best performance in terms of reactivity, adhesion, impact resistance, and transparency. The impact resistance was further increased by introducing a polycarbonate core between the two glass plates. The solid thermoplastic polymer was obtained either by casting from a solution containing an aliphatic polyurethane, an acrylate oligomer, and the photoinitiator or by mixing these compounds in the molten state and further extrusion. The glass assembly was heated above the softening temperature (80°C) under a 1 MPa pressure and cured by a 1 min exposure to UV radiation to give a strongly adhesive laminate showing good transparency and long term weatherability. © 1995 John Wiley & Sons, Inc.     

Multilevel assessment method for reliable design of composite structures

This work aims at demonstrating the interest of a new methodology for the design and optimization of composite materials and structures. Coupling reliability methods and homogenization techniques allow the consideration of probabilistic design variables at different scales. The main advantage of such an original micromechanics-based approach is to extend the scope of solutions for engineering composite materials to reach or to respect a given reliability level. This approach is illustrated on a civil engineering case including reinforced fiber composites. Modifications of microstructural components properties, manufacturing process, and geometry are investigated to provide new alternatives for design and guidelines for quality control.     

Estimation of nonlinear systems via a Chebyshev approximation approach

This paper proposes to decompose the nonlinear dynamic of a chaotic system with Chebyshev polynomials to improve performances of its estimator. More widely than synchronization of chaotic systems, this algorithm is compared to other nonlinear stochastic estimator such as Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF). Chebyshev polynomials orthogonality properties is used to fit a polynomial to a nonlinear function. This polynomial is then used in an Exact Polynomial Kalman Filter (ExPKF) to run real time state estimation. The ExPKF offers mean square error optimality because it can estimate exact statistics of transformed variables through the polynomial function. Analytical expressions of those statistics are derived so as to lower ExPKF algorithm computation complexity and allow real time applications. Simulations under the Additive White Gaussian Noise (AWGN) hypothesis, show relevant performances of this algorithm compared to classical nonlinear estimators.     

Toward effective service composition for real-time SOA-based systems

Many application domains are increasingly leveraging service-oriented architecture (SOA) techniques to facilitate rapid system deployment. Many of these applications are time-critical and, hence, real-time assurance is an essential step in the service composition process. However, there are gaps in existing service composition techniques for real-time systems. First, admission control is an essential technique to assure the time bound for service execution, but most of the service composition techniques for real-time systems do not take admission control into account. A service may be selected for a workflow during the composition phase, but then during the grounding phase, the concrete service may not be able to admit the workload. Thus, the entire composition process may have to be repeated. Second, communication time is an important factor in real-time SOA, but most of the existing works do not consider how to obtain the communication latencies between services during the composition phase. It is clear that maintaining a full table of communication latencies for all pairs of services is infeasible. Obtaining communication latencies between candidate services during the composition phase can also be costly, since many candidate services may not be used for grounding. Thus, some mechanism is needed for estimating the communication latency for composite services. In this paper, we propose a three-phase composition approach to address the above issues. In this approach, we first use a highly efficient but moderately accurate algorithm to eliminate most of the candidate compositions based on estimated communication latencies and assured service response latency. Then, a more accurate timing prediction is performed on a small number of selected compositions in the second phase based on confirmed admission and actual communication latency. In the third phase, specific concrete services are selected for grounding, and admissions are actually performed. The approach is scalable and can effectively achieve service composition for satisfying real-time requirements. Experimental studies show that the three-phase approach does improve the effectiveness and time for service composition in SOA real-time systems. In order to support the new composition approach, it is necessary to effectively specify the needed information. In this paper, we also present the specification model for timing-related information and the extension of OWL-S to support this specification model.     

A compact split step Padé scheme for higher-order nonlinear Schrödinger equation (HNLS) with power law nonlinearity and fourth order dispersion

In this paper we propose a compact split step Padé scheme (CSSPS) to solve the scalar higher-order nonlinear Schrödinger equation (HNLS) with higher-order linear and nonlinear effects such as the third and fourth order dispersion effects, Kerr dispersion, stimulated Raman scattering and power law nonlinearity. The stability of this method has been proved. It has been shown as well that the CSSPS method gives the same results as classical numerical methods like the split step Fourier method and Crank–Nicholson (CN) method but it presents many advantages over theme. It is more efficient. This proposed scheme is well suited to higher-order dispersion effects and readily generalized for nonlinear and dispersion managed fibers. We tested this scheme for the case of the quintic nonlinearity and confirmed that this effect has no significant role on the propagation of single solitons.     

Blind spatial unmixing of multispectral images: New methods combining sparse component analysis,clustering and non-negativity constraints

Remote sensing has become an unavoidable tool for better managing our environment, generally by realizing maps of land cover using classification techniques. Traditional classification techniques assign only one class (e.g., water, soil, grass) to each pixel of remote sensing images. However, the area covered by one pixel contains more than one surface component and results in the mixture of these surface components. In such situations, classical classification is not acceptable for many major applications, such as environmental monitoring, agriculture, mineral exploration and mining, etc. Most methods proposed for treating this problem have been developed for hyperspectral images. On the contrary, there are very few automatic techniques suited to multispectral images. In this paper, we propose new unsupervised spatial methods (called 2D-Corr-NLS and 2D-Corr-NMF) in order to unmix each pixel of a multispectral image for better recognizing the surface components constituting the observed scene. These methods are related to the blind source separation (BSS) problem, and are based on sparse component analysis (SCA), clustering and non-negativity constraints. Our approach consists in first identifying the mixing matrix involved in this BSS problem, by using the first stage of a spatial correlation-based SCA method with very limited source sparsity constraints, combined with clustering. Non-negative least squares (NLS) or non-negative matrix factorization (NMF) methods are then used to extract spatial sources. An important advantage of our proposed methods is their applicability to the possibly globally underdetermined, but locally (over)determined BSS model in multispectral remote sensing images. Experiments based on realistic synthetic mixtures and real multispectral images collected by the Landsat ETM+ and the Formosat-2 sensors are performed to evaluate the performance of the proposed approach. We also show that our methods significantly outperform the sequential maximum angle convex cone (SMACC) method.     

Application of top seeding in the melt processing of Nd<Subscript>123</Subscript> thick films on YSZ substrates: I buffer layer optimization

A new concept of a buffer layer in superconducting thick film technology was tested. The idea is based on increasing the NdBa₂Cu₃O_x melt viscosity at the processing temperature near the substrate by using higher ratios of Nd₄Ba₂Cu₂O_z solid phase in the first screen printed pass which is considered as a buffer layer. Different compositions, thicknesses and thermal schedules were used to optimise the buffer layer. The optimised buffer layer was employed in the fabrication of NdBa₂Cu₃O_y thick films on yttria stabilized zirconia (YSZ) substrates using the top seeding melt growth (TSMG) technique. Using the buffer layer was effective in preventing a large amount of liquid (BaCuO₂-CuO) from severe interaction with the substrate during the prolonged time in the TSMG technique. Consequently, a large superconducting single domain was obtained. Thick films were melt processed in 0.1% O₂ in Ar atmosphere to suppress the Nd_{1 + x}Ba_{2 − x}Cu₃O_y (Nd_123SS) solid solution formation. The produced thick films have high transition temperature (T_C) and improved microstructures.     

Influence of secondary source technologies and energy management strategies on Energy Storage System sizing for fuel cell electric vehicles

Fuel cell electric vehicles (FCEVs) have some limitation which make them less competitor to thermal ones and delay their commercialization. The most important problems as the range, the durability and the cost depend directly on the energy storage problematic issues. In this context, this work presents an optimal sizing methodology for an Energy Storage System (ESS) composed by a fuel cell and an assistant source to supply a lightweight vehicle with 700 km driving range. Firstly, a comparative study between single and hybrid source is carried out to show the benefits of hybridization according to the range in terms of weight, cost and fuel consumption. Moreover, in order to improve the hybrid source characteristics, three technologies of the secondary source are tested and evaluated to be chosen for hybridization with fuel cell system purposes. Furthermore, the influence of three Energy Management Strategies (EMSs) on ESS sizing is studied where an optimal strategy provides the most favorable dimensions of the hybrid system. Simulation results give us the best technology needed for hybridization and allow us adopting the optimal management strategy to design the hybrid source. Finally, in order to show the influence of the driving cycles on the ESS design, a comparison study using the New European Driving Cycle “NEDC” and the Assessment and Reliability of Transport Emission Models Inventory Systems (ARTEMIS) confirms that there is a slow influence of the driving cycle on the ESS sizes.