Thermal environment effects on wave dispersion behavior of inhomogeneous strain gradient nanobeams based on higher order refined beam theory

In this article, an analytical model for the wave propagation analysis of inhomogeneous functionally graded (FG) nanobeam in thermal environment is developed based on nonlocal strain gradient theory, in which the stress accounts for not only the nonlocal elastic stress field but also the strain gradients stress field. The nanobeam is modeled through a higher order shear deformable refined beam theory which has a trigonometric shear stress function. The temperature field supposed to have a nonlinear distribution across the nanobeam thickness. Temperature-dependent material properties of nanobeams are spatially graded based on Mori–Tanaka model. The governing equations of the temperature-dependent functionally graded (FG) nanobeam are derived using the Hamilton’s principle. Numerical examples show that the characteristics of the wave propagation of FG nanobeam are influenced by various parameters such as nonlocality parameter, length scale parameter, gradient index, and temperature changes.     

Innovation in artificial neural network learning: Learn-On-Demand methodology

The artificial neural networks represent the state of the art tool for forecasting and prediction. However, the technique relies heavily on the availability of adequate data for its training. There have been many attempts to overcome the problems associated with the acquisition of learning data. These include the use of simulation techniques, which prepare the data for pre-processing prior to learning. Nevertheless, these methods tend to undermine the specific nature of the application that is reflected in its data. Furthermore, it is evident that, in certain circumstances, the current learning methods, grouped under on-line and off-line, do not provide an effective learning solution and their advantages are mutually exclusive. With these problems in mind, this research proposes a method for rectifying these shortcomings. The solution focuses on the learning processes rather than data. The work offers a new learning mechanism, namely the “Learn-On-Demand” (LOD) methodology, which enables the ANN to learn where the lack of knowledge is evident. The proposed LOD methodology integrates into ANN's learning process. Having produced the algorithm for its implementation, the paper then produces the mathematical representation of the Learn-On-Demand methodology by integrating the new algorithm into existing methodologies. The need for this solution emerged out of a research in the field of construction, where Structured Systems Analysis and Design was sued as a platform for integrating a hybrid of AI techniques in order to develop an enhanced method of client briefing.     

A mathemathical model for the calculation of the concentration at the outlet of an ozone generator

A mathematical model was generated to predict the composition of the outlet gas of ozone generators. In order to make the modelling possible it was important to predict the occurrence time and the exact location of each individual discharge zone. This was done by connecting a specially constructed ozone generator, which would locate the discharge zones, to a nanosecond pulse generator which would impose regular occurrence times for discharge columns. The experimental and theoretical outlet concentrations of this ozone generator were compared. The result was an excellent match which justified the assumptions made in the model. The mathematical model was also used to study the effect of different factors affecting the production of ozone.     

基于传统板理论的智能圆形FGM薄板自由振动研究

基于传统板理论（CPT）对圆形功能梯度（FG）薄板的自由振动性能进行分析。这种板具有2个由压电（PZT4）材料构成的均布驱动器。对FG底层板的材料特性进行假定,考虑了材料体积分数的能量分布,将材料沿厚度方向进行分级,并采用二次方程模拟沿压电覆层厚度方向分布的电势场。采用运动微分方程来模拟板的固定端边界条件。介绍了详细的数学推导过程,并采用数值分析来研究FG板的梯度变化对结构自由振动的影响。其分析结果得到了三维有限元分析结果的证实。     

Optimal sensor array configuration in remote image formation.

Determination of optimal sensor configuration is an important issue in many remote imaging modalities, such as tomographic and interferometric imaging. In this paper, a statistical optimality criterion is defined and a search is performed over the space of candidate sensor locations to determine the configuration that optimizes the criterion over all candidates. To make the search process computationally feasible, a modified version of a previously proposed suboptimal backward greedy algorithm is used. A statistical framework is developed which allows for inclusion of several widely used image constraints. Computational complexity of the proposed algorithm is discussed and a fast implementation is described. Furthermore, upper bounds on the sum of the squared error of the proposed algorithm are derived. Connections of the method to the deterministic backward greedy algorithm for the subset selection problem are presented, and two application examples are described. Five compelling optimality criteria are considered, and their performance is investigated through numerical experiments for a tomographic imaging scenario. In all cases, it is verified that the configuration designed by the proposed algorithm performs better than wisely chosen alternatives.     

Controlled Preparation and Characterization of Nigella Sativa Electrospun Pad for Controlled Release

Silicon - Nigella sativa (NS) oil is an anti-inflammatory agent in the traditional medicine. In the present study, novel electrospun mats contained NS oil/polyacrylonitrile as a sustained release...     

Decentralized Hierarchical Coded Caching Over Heterogeneous Wireless Networks with Multi-level Popularity Content

Wireless Personal Communications - Decentralized hierarchical coded caching is studied with two layers of caches which users receive their demands through intermediate helpers from a main server....     

Hydrogen production employing Cu(BDC) metal–organic framework support in methanol steam reforming process within monolithic micro-reactors

Cu(BDC) metal–organic framework (MOF) was used as a support for the copper (Cu) catalyst applied in the methanol steam reforming (MSR) process at low temperatures (130–250 °C) with a feed WHSV = 9.2 h^?1 within the monolithic reactor. Also, the effects of diverse promoters were examined on the catalytic activities of the Cu/X–Cu(BDC) (X = Ce, Zn, Gd, Sm, La, Y, Pr) catalysts. Results showed that the Ce/Sm–Cu(BDC) supports exhibited highest activities, lowest reduction temperatures and largest specific surface areas, which caused highest distributions of the active copper metal nanoparticles on the supports. The reactor tests displayed that the activities of Cu/X–Cu(BDC) (X = Ce, Zn, Gd, Sm, La, Y, Pr) catalysts followed the order X = Ce > Sm > Y > La > Pr > Cu(BDC) > Zn > Gd. The highest activities of Ce and Sm containing catalysts were attributed to the presence of CeO₂ and Sm₂O₃ caused the oxygen vacancies on the catalyst surface which had positive effects on the methanol reforming process. The time-on-stream stability tests showed the highest resistance of the Cu/Ce–Cu(BDC) catalyst to the carbon formation during 32 h. Consequently, the Cu/Ce–Cu(BDC) with the highest stability, methanol conversion and carbon monoxide selectivity could be used in practical industrial applications.     

Optimal characterization of a microwave transistor using grey wolf algorithms

Analog Integrated Circuits and Signal Processing - Modern time microwave stages require low power consumption, low size, low-noise amplifier (LNA) designs with high-performance measures. These...     

Effect of baking in different ovens on the quality and structural characteristics of saltine crackers

The aim of the study was to evaluate the physical and microstructural characteristics of crackers baked in four different industrial baking ovens (indirect radiation-cyclotherm, indirect convection, hybrid and industrial tunnel-ITO). Indirect convection and cyclotherm ovens provide the highest (5685.43 ± 51 W m⁻²) and the lowest (4860 ± 38.87 W m⁻²) amount of heat flux, respectively. Despite the amount of heat flux, indirect convection led to crackers with the highest moisture (7.86% vs. 4.82% in clyclotherm) and specific volume, but the lowest hardness. Cyclotherm resulted in crackers with lower specific volume, surface area, porosity, smooth and regular surface. Conversely, the hybrid and ITO ovens showed closer heat flux, leading to crackers with similar moisture content, texture parameters, specific volume, browning and inner porosity. Overall results show the potential of baking using different ovens for modifying the quality parameters of the crackers.