Mesoscopic approach for steady‐state free convection in a diamond array

The purpose of the present paper is testing an in‐house efficiency algorithm based on lattice Boltzmann method (LBM) and using it to resolve the obtained coupled nondimensional governing equations to analyze two‐dimensional free convection inside a cold outer cavity subjected to a heated cylindrical diamond array. Steady state or oscillatory results are obtained using the Bhatnagar‐Gross‐Krook collision model associated to the thermal LBM. Both the velocity and temperature fields are solved using the D2Q9 models. With different Rayleigh numbers (Ra), the tested free convection can either achieve to steady state or oscillatory. We extended our in house Fortran 90 code using curved boundary conditions and implemented them into a cavity with a diamond array. The numerical simulations were done using distinct Ra (10⁶ and 10 ⁷) and distances between the four neighboring circular cylinders aligned in a diamond array. The effects of several physical parameters, including Ra and position of the hot body array on flow and heat transfer characteristics are investigated. The obtained results are highlighted in the form of streamlines, isotherms, and velocities plots. We show in this paper the stability and the efficiency of the LBM to deal with a complex geometry and its ability to reach suitable convergence criteria for high Ra (10 ⁶ and 10 ⁷). The numerical results indicate that LBM can simulate numerical problems with a high Ra reaching a steady state where we can depict the change of the flow pattern and enhancement of the heat transfer in the presence of heated diamond array.     

Abundant non-toxic materials for thin film solar cells: Alternative to conventional materials

Presented are the results of a comparative analysis to identify abundant, non-toxic binary materials with potential applicability for photovoltaics. Materials other than the conventional Si, CdTe, and Cu(In,Ga)Se₂ (CIGS) are examined. The screening is based on the materials’ bulk properties and a set of environmental, physical, and chemical criteria. The screening process is detailed and the properties and applicability of the screened materials are discussed.     

Photocatalytic degradation of methyl orange dye by NiFe<Subscript>2</Subscript>O<Subscript>4</Subscript> nanoparticles under visible irradiation: effect of varying the synthesis temperature

Nanoparticles of nickel ferrites (NiFe₂O₄) were synthesized at different temperature of synthesis (25, 50 and 80 °C) through the chemical co-precipitation method. The synthesized powders were characterized using X-ray diffraction for crystallite size and lattice parameter calculation. It reveals the presence of cubic spinel structure of ferrites with crystallite size between 29 and 41 nm. Transmission electron microscopy and scanning electron microscopy showed uniform distribution of ferrite particles with some agglomeration. The Fourier-transform infrared spectroscopy showed absorption bonds, which were assigned to the vibration of tetrahedral and octahedral complexes. Raman spectroscopy is used to verify that we have synthesized ferrite spinels and determines their phonon modes. The thermal decomposition of the NiFe₂O₄ was investigated by TGA/DTA. The optical study UV–visible is used to calculate the band gap energy. Magnetic measurements of the samples were carried out by means of vibrating sample magnetometer and these studies reveal that the formed nickel ferrite exhibits ferromagnetic behavior. Photoluminescence showed three bands of luminescence located at 420, 440 and 535 nm. The photocatalytic properties of nickel ferrite (NiFe₂O₄) nanoparticles were evaluated by studying the photodecomposition of methyl orange as organic pollutant models and showed a good photocatalytic activity.     

“<Emphasis Type="SmallCaps">disassembly plan approach based on subassembly concept</Emphasis>”

A three-dimensional numerical model is established to study the temperature and fluid flow fields in the twin-wire gas metal arc welding (GMAW) process. The high-speed photography system is used to capture the images of the weld pool during the welding. Based on simulation and experimental results, the weld pool formation, convection, and stability in twin-wire GMAW process are investigated. Both “push-pull” and outward flow patterns exist in the twin-wire GMAW weld pool, which can contribute to decreasing the height of the bulge and increasing the width of the pool. The convection in the weld pool can proceed adequately, the arc force between the leading and trailing arcs is relatively balanced, surface tension normal force is uniform along the liquid channel, and the liquid channel is capillary stable, all of those contribute to the stability of the weld bead. The simulation results are in good agreement with those in the experiment.     

Novel Approach for Management of Automated IPv6 Network Simulation

Wireless Personal Communications - The complexity of network technologies and the variety of their equipment and settings make them difficult to evaluate, to simulate, and to deploy. IPv4 to IPv6...     

A comparative study on the performance of MIMO‐STBC subject to Weibull fading channels

In this paper, we investigate the analytical performance of the multiple‐input multiple‐output system (MIMO) with orthogonal space‐time block codes (STBCs) subject to Weibull fading channels (WFC). Space‐time block code technique provides an efficient pattern for wireless transmission over various fading channels using multiple transmit antennas. Two approximating methods of the sum of independent Weibull random variables are studied. For each approach, we derive accurate approximate expressions for several performance metrics of MIMO‐STBC system operating under independent and nonidentical WFC. The proposed approximations are expressed in terms of 2 generalized hypergeometric functions, namely, Fox's H and Meijer's G functions. All the derived approximate expressions prove high accuracy, while compared with the simulation results established via Monte Carlo method and Kolmogorov‐Smirnov test as well. Although the 2 approaches have approximately the same accuracy, the second method approximate expressions are much less complex than those of the first method.     

A New Method for Sentiment Analysis Using Contextual Auto-Encoders

Sentiment analysis, a hot research topic, presents new challenges for understanding users’ opinions and judgments expressed online. They aim to classify the subjective texts by assigning them a polarity label. In this paper, we introduce a novel machine learning framework using auto-encoders network to predict the sentiment polarity label at the word level and the sentence level. Inspired by the dimensionality reduction and the feature extraction capabilities of the auto-encoders, we propose a new model for distributed word vector representation “PMI-SA” using as input pointwise-mutual-information “PMI” word vectors. The resulted continuous word vectors are combined to represent a sentence. An unsupervised sentence embedding method, called Contextual Recursive Auto-Encoders “CoRAE”, is also developed for learning sentence representation. Indeed, CoRAE follows the basic idea of the recursive auto-encoders to deeply compose the vectors of words constituting the sentence, but without relying on any syntactic parse tree. The CoRAE model consists in combining recursively each word with its context words (neighbors’ words: previous and next) by considering the word order. A support vector machine classifier with fine-tuning technique is also used to show that our deep compositional representation model CoRAE improves significantly the accuracy of sentiment analysis task. Experimental results demonstrate that CoRAE remarkably outperforms several competitive baseline methods on two databases, namely, Sanders twitter corpus and Facebook comments corpus. The CoRAE model achieves an efficiency of 83.28% with the Facebook dataset and 97.57% with the Sanders dataset.     

Arabic stop consonants characterisation and classification using the normalized energy in frequency bands

In general, speech is made with sequences of consonants (fricatives, nasals and stops), vowels and glides. The classification of the stop consonants remains one of the most challenging problems in speech recognition. In this paper, we propose a new approach based on the normalized energy in frequency bands in the release and closure phases in order to characterize and classify the Arabic stop consonants (/b/, /d/, /t/, /k/ and /q/) and to recognize the CV syllable. Classification experiments were performed using decision algorithms on stop consonants C and CV syllables extracted from an Arabic corpus. The results yielded to an overall stop consonants classification of 90.27% and syllables CV recognition upper than 90% for all stops.