Wear of graphite anodes during electrolysis of add sulphate solutions

Graphite electrodes were prepared by mixing calcined coke and coal tar pitch. They were pressed under 250 kg cm^–2 and heat treated up to 2800° C. Rectangles measuring 70 mm x 40 mm x 8 mm were anodically polarized under galvanostatic and potentiostatic conditions. Electrolyses were conducted at 10–50 mA cm^–2 for periods ranging from 10–120 hours in Na₂SO₄ solutions acidified with sulphuric acid to various pH values. The wear of graphite anodes increased with decreasing bath temperature, increasing acid concentration, decreasing pH of the electrolyte and increasing current density. A model is suggested which assumes that corrosion takes place via the formation of a lamellar crystal compound with the formula (C ₈ ⁰ O)(OH)₃HSO ₄ ^– ·2H₂SO₄.The compound is unstable at higher temperatures when corrosion is effected by oxidation of graphite by atomic oxygen. The formation of the carbon ions was found to be a necessary precondition for the formation of the complex.     

Metal recovery in a pilot-scale rotating cylindrical wiper-blade electrode system

The performance of an experimental pilot-scale electrochemical reactor using a rotating cylindrical electrode equipped with wiper blades is described. Data obtained from monopolar depositing and bipolar stripping—depositing of copper from dilute aqueous electrolytes are presented and certain economic aspects of metal recovery are discussed.     

A quadratic spline approximation using detail multi-layer for soft shadow generation in augmented reality

Implementation of shadows is crucial to enhancement of images in AR environments. Without shadows, virtual objects would look floating over the scene resulting in unrealistic rendering of AR environments. Casting hard shadows would provide only spatial information while soft shadows help improve realism of AR environments. Several algorithms have been proposed to render realistic shadows which often incurred high computational costs. Little attention has been directed towards the balanced trade-off between shadow quality and computational costs. In this study, two approaches are proposed: Quadratic Spline Interpolation (QSI) to soften the outline of the shadow and Detail Multi-Layer (DML) technique to optimize the volume of computations for the generation of soft shadows based on real light sources. QSI estimates boarder hard shadow samples while DML involves three main phases: real light sources estimation, soft shadow production and reduction of the complexity of 3-Dimensional objects’ shadows. To be more precise, a reflective hemisphere is used to capture real light and to create an environment map. The Median Cut algorithm is implemented to locate the direction of real light sources on the environment map. Subsequently, the original hard shadows are retrieved and a sample of multilayer hard shadows is produced where each layer has its unique size and colour. These layers overlap to produce soft shadows based on the real light sources’ directions. Finally, the Level of Details (LOD) algorithm is implemented to increase the efficiency of soft shadows by decreasing the complexity of vertex transformations. The proposed technique is tested using three samples of multilayer hard shadows with varying numbers of light sources generated from the Median Cut algorithm. The experimental results show that the proposed technique successfully produces realistic soft shadows at low computational costs.     

Morphological characteristics of copper deposition on stainless steel cathodes

The results of a metallographic study of cathodic copper deposition on 316 stainless steel are presented. In magnetically assisted d.c. electrolysis, characteristic screen-type deposition patterns are observed. Simultaneous hydrogen evolution causes tunnel-type deposits at 30–45° to the horizontal.Nomenclature B _z magnetic flux density, vertical field lines pointing downwards - C electrolyte concentration - CVD cell voltage drop - i _c cathode current density - s cathode-anode separation distance - T temperature - t _e length of electrolysis time     

Crystallization and melting behavior of blends comprising poly(3‐hydroxy butyrate‐co‐3‐hydroxy valerate) and poly(ethylene oxide)

Blends of poly(3‐hydroxy butyrate‐co‐3‐hydroxy valerate) (PHBV) and poly(ethylene oxide) (PEO) were prepared by casting from chloroform solutions. Crystallization kinetics and melting behavior of blends have been studied by differential scanning calorimetry and optical polarizing microscopy. Experimental results reveal that the constituents are miscible in the amorphous state. They form separated crystal structures in the solid state. Crystallization behavior of the blends was studied under isothermal and nonisothermal conditions. Owing to the large difference in melting temperatures, the constituents crystallize consecutively in blends; however, the process is affected by the respective second component. PHBV crystallizes from the amorphous mixture of the constituents, at temperatures where the PEO remains in the molten state. PEO, on the other hand, is surrounded during its crystallization process by crystalline PHBV regions. The degree of crystallinity in the blends stays constant for PHBV and decreases slightly for PEO, with ascending PHBV content. The rate of crystallization of PHBV decreases in blends as compared to the neat polymer. The opposite behavior is observed for PEO. Nonisothermal crystallization is discussed in terms of a quasi‐isothermal approach. Qualitatively, the results show the same tendencies as under isothermal conditions. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 101: 2776–2783, 2006     

(BaTiO3)1-x + (Co0.5Ni0.5Nb0.06Fe1.94O4)x nanocomposites: Structure,morphology, magnetic and dielectric properties

Two phase-based nanocomposites consisting of dielectric barium titanate (BaTiO₃ or BTO) and magnetic spinel ferrite Co_0.5Ni_0.5Nb_0.06Fe_1.94O₄ (CNNFO) have been synthesized through solid state route. Series of (BaTiO₃)_1-x + (Co_0.5Ni_0.5Nb_0.06Fe_1.94O₄)_x nanocomposites with x content of 0.00, 0.25, 0.50, 0.75, and 1.00 were considered. The structure has been examined via X-rays diffraction (XRD) and indicated the occurrence of both perovskite BTO and spinel CNNFO phases in various nanocomposites. A phase transition from tetragonal BTO structure to cubic structure occurs with inclusion of CNNFO phase. The average crystallites size of BTO phase decreases, whereas that for the CNNFO phase increases with increasing x in various nanocomposites. The morphological observations revealed that the porosity is highly reduced, and the connectivity between grains is enhanced with increasing x content. The optical properties have been investigated by UV−vis diffuse reflectance spectroscopy. The deduced band gap energy (E_g) value is found to reduce with increasing the content of spinel ferrite phase. The magnetic as well as the dielectric properties were also investigated. The analysis showed that CNNFO ferrite phase greatly affects the magnetic properties and dielectric response of BTO material. The obtained findings can be useful to enhance the performances of magneto-dielectric composite-based systems.     

On ℤ2ℤ2[u]-additive codes

In this paper, a new class of additive codes which is referred to as ?₂ ?₂[u]-additive codes is introduced. This is a generalization towards another direction of recently introduced ?₂ ?₄-additive codes [J. Borges, C. Fernández-Córdoba, J. Pujol, J. Rif´a, and M. Villanueva, ?₂ ?₄-linear codes: Generator matrices and duality, Designs Codes Cryptogr. 54(2) (2010), pp. 167–179]. ?₂ ?₄-additive codes have shown to provide a promising class of codes with their algebraic structure and applications such as steganography. The standard generator matrices are established and by introducing orthogonality the parity-check matrices are also obtained. A MacWilliams-type identity that relates the weight enumerator of a code with its dual is proved. Furthermore, a Gray map that maps these codes to binary codes is defined and some examples of optimal codes which are the binary Gray images of ?₂ ?₂[u]-additive codes are presented.     

Implementation and performance evaluation of a scheduling algorithm for divisible load parallel applications in a cloud computing environment

Cloud computing is an emerging technology in which information technology resources are virtualized to users in a set of computing resources on a pay‐per‐use basis. It is seen as an effective infrastructure for high performance applications. Divisible load applications occur in many scientific and engineering applications. However, dividing an application and deploying it in a cloud computing environment face challenges to obtain an optimal performance due to the overheads introduced by the cloud virtualization and the supporting cloud middleware. Therefore, we provide results of series of extensive experiments in scheduling divisible load application in a Cloud environment to decrease the overall application execution time considering the cloud networking and computing capacities presented to the application's user. We experiment with real applications within the Amazon cloud computing environment. Our extensive experiments analyze the reasons of the discrepancies between a theoretical model and the reality and propose adequate solutions. These discrepancies are due to three factors: the network behavior, the application behavior and the cloud computing virtualization. Our results show that applying the algorithm result in a maximum ratio of 1.41 of the measured normalized makespan versus the ideal makespan for application in which the communication to computation ratio is big. They show that the algorithm is effective for those applications in a heterogeneous setting reaching a ratio of 1.28 for large data sets. For application following the ensemble clustering model in which the computation to communication ratio is big and variable, we obtained a maximum ratio of 4.7 for large data set and a ratio of 2.11 for small data set. Applying the algorithm also results in an important speedup. These results are revealing for the type of applications we consider under experiments. The experiments also reveal the impact of the choice of the platforms provided by Amazon on the performance of the applications under study. Considering the emergence of cloud computing for high performance applications, the results in this paper can be widely adopted by cloud computing developers. Copyright © 2014 John Wiley & Sons, Ltd.     

Robust face recognition against expressions and partial occlusions

Facial features under variant-expressions and partial occlusions could have degrading effect on overall face recognition performance. As a solution, we suggest that the contribution of these features on final classification should be determined. In order to represent facial features contribution according to their variations, we propose a feature selection process that describes facial features as local independent component analysis(ICA) features. These local features are acquired using locally lateral subspace(LLS) strategy.Then, through linear discriminant analysis(LDA) we investigate the intraclass and interclass representation of each local ICA feature and express each feature s contribution via a weighting process. Using these weights, we define the contribution of each feature at local classifier level. In order to recognize faces under single sample constraint, we implement LLS strategy on locally linear embedding(LLE) along with the proposed feature selection. Additionally, we highlight the efficiency of the implementation of LLS strategy. The overall accuracy achieved by our approach on datasets with different facial expressions and partial occlusions such as AR, JAFFE,FERET and CK+ is 90.70%. We present together in this paper survey results on face recognition performance and physiological feature selection performed by human subjects.