The problem of non-Darcian-Bènard double diffusive magneto-Marangoni convection is considered in a horizontal infinite two layer system. The system consists of a two-component fluid layer placed above a porous layer, saturated with the same fluid with a constant heat sources/sink in both the layers, in the presence of a vertical magnetic field. The lower porous layer is bounded by rigid boundary, while the upper boundary of the fluid region is free with the presence of Marangoni effects. The system of ordinary differential equations obtained after normal mode analysis is solved in a closed form for the eigenvalue and the Thermal Marangoni Number (TMN) for two cases of Thermal Boundary Combinations (TBC); these are type (i) Adiabatic-Adiabatic and type (ii) Adiabatic-Isothermal. The corresponding two TMNs are obtained and the impacts of the porous parameter, solute Marangoni number, modified internal Rayleigh numbers, viscosity ratio, and the diffusivity ratios on the non-Darcian-Bènard double diffusive magneto - Marangoni convection are studied in detail.
The increasing availability of computing power in the past two decades has been use to develop new techniques for optimizing solution of estimation problem. Today's computational capacity and the widespread availability of computers have enabled development of new generation of intelligent computing techniques, such as our interest algorithm, this paper presents one of new class of stochastic search algorithm (known as Canonical Genetic' Algorithm ‘CGA’) for optimizing the maximum likelihood function strategy is composed of three main steps: recombination, mutation, and selection. The experimental design is based on simulating the CGA with different values of are compared with those of moment method. Based on MSE value obtained from bot
... Show MoreGreen synthesis methods have emerged as favorable techniques for the synthesis of nano-oxides due to their simplicity, cost-effectiveness, eco-friendliness, and non-toxicity. In this study, Nickel oxide nanoparticles (NiO-NPs) were synthesized using the aqueous extract of Laurus nobilis leaves as a natural capping agent. The synthesized NiO-NPs were employed as an adsorbent for the removal of Biebrich Scarlet (BS) dye from aqueous solution using adsorption technique. Comprehensive characterization of NiO-NPs was performed using various techniques such as atomic force microscopy (AFM), Fourier transform infrared (FTIR), X-ray diffraction (XRD), Brunauer-Emmett and Teller (BET) analysis, and scanning electron microscopy (SEM). Additionally, o
... Show MoreThe purpose of this investigation is to determine and analyze the fluid inertia of electroosmotic flow on the Cu-water nanofluids by peristaltic transport. Fluid flow properties and heat transfer characteristics are studied for aqueous ionic nanofluids through a vertical microtube of a constant radius. Streamlines are plotted for the governing fluid flow.
Within this work, to promote the efficiency of organic-based solar cells, a series of novel A-π-D type small molecules were scrutinised. The acceptors which we designed had a moiety of N, N-dimethylaniline as the donor and catechol moiety as the acceptor linked through various conjugated π-linkers. We performed DFT (B3LYP) as well as TD-DFT (CAM-B3LYP) computations using 6-31G (d,p) for scrutinising the impact of various π-linkers upon optoelectronic characteristics, stability, and rate of charge transport. In comparison with the reference molecule, various π-linkers led to a smaller HOMO–LUMO energy gap. Compared to the reference molecule, there was a considerable red shift in the molecules under study (A1–A4). Therefore, based on
... Show MoreSocial media and news agencies are major sources for tracking news and events. With these sources' massive amounts of data, it is easy to spread false or misleading information. Given the great dangers of fake news to societies, previous studies have given great attention to detecting it and limiting its impact. As such, this work aims to use modern deep learning techniques to detect Arabic fake news. In the proposed system, the attention model is adapted with bidirectional long-short-term memory (Bi-LSTM) to identify the most informative words in the sentence. Then, a multi-layer perceptron (MLP) is applied to classify news articles as fake or real. The experiments are conducted on a newly launched Arabic dataset called the Ara
... Show MoreThis study presents a practical method for solving fractional order delay variational problems. The fractional derivative is given in the Caputo sense. The suggested approach is based on the Laplace transform and the shifted Legendre polynomials by approximating the candidate function by the shifted Legendre series with unknown coefficients yet to be determined. The proposed method converts the fractional order delay variational problem into a set of (n + 1) algebraic equations, where the solution to the resultant equation provides us the unknown coefficients of the terminated series that have been utilized to approximate the solution to the considered variational problem. Illustrative examples are given to show that the recommended appro
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