Computational Sciences and Engineering
Volume:1 Issue: 1, Spring 2021

In this study, our main goal is to study the exact traveling wave solutions of some recent nonlinear evolution equations, namely, modified generalized (3+1)-dimensional time-fractional Kadomtsev–Petviashvili (KP) and Kadomtsev-Petviashvili-Benjamin-Bona-Mahony (KP-BBM) equations of conformable type. We employed a consistent analytical method called the generalized Riccati equation mapping method, along with a conformable derivative to extract the multiple kinks, bi-symmetry soliton, bright and dark soliton solutions, periodic solutions, and singular solutions for suggested equations. The theoretical method is based on the Riccati equation and a number of empirical solutions have been proposed that do not exist in the literature. Furthermore, as the order of the fractional derivative approaches one, the exact solutions obtained by the current method are reduced to classical solutions. The obtained results show that the present technique is effective, easy to implement, and a strong tool for solving nonlinear fractional partial differential equations, and produces a very large number of solutions.

In this paper, the buckling response of single-walled carbon nanotube (SWCNT)-reinforced shape memory polymer nanocomposite beams is investigated through a computational multiscale approach. First, the Mori-Tanaka micromechanical model is used to extract the effective mechanical properties of SWCNT-polymer nanocomposites. The role of interfacial region between the nanotubes and polymer matrix in the elastic properties is taken into account in the analysis. Then, the buckling behavior of the nanocomposite beams is evaluated by the finite element method (FEM). The effects of nanotube content, interphase and temperature on the buckling response are investigated. It is observed that the addition of SWCNT into the polymeric materials increases the buckling capacity of the resulting nanocomposite beams. According to the results, the buckling characteristics of shape memory polymer nanocomposite beams are affected by the CNT/polymer interphase. The increase of temperature significantly decreases the buckling loads of nanocomposite beams due to the decrease of nanocomposite elastic modulus.

Day after day, the need for a high-performance CMOS OP-AMP is increasingly needed for use in electronic and communications applications as well as in the biomedical field. For this purpose, OP-AMP must operate at wide band-width and high voltage gain with low power consumption. To design a high-performance OP-AMP we must select a modern technology in order to harmonize the process parameters of MOSFET transistors with the technique of the proposed CMOS OP-AMP consisting of a group of these transistors. In this paper, 0.18µm TSMC technology with ±1.8V supply voltage CMOS-OP-AMP is used to design Two Stage OP-AMP. Simulation results are obtained using PSPICE (version 16.6.0) program. The results showed that the designed techniques are highly efficient in terms of high frequency, high gain and low consumption of power. The Invasive Weed Optimization (IWO) algorithm was used to improve the performance parameters of the Two-Stage CMOS OP-AMP, and it implemented with MATLAB program. The simulation results of the proposed OP-AMP based-on IWO algorithm showed the GBP is improved into 100%, the voltage gain increased around 17% , the power consumption decreased by 32% and CMRR increased by 20% .From the result we can say that the IWO is a powerful algorithm can be used to improve other designs.

Breast cancer is the most common cancer between women worldwide. Although it is the leading cause of cancer death of women in the world, it can be prevented if it is detected and diagnosed at the early stages. There are various ways of detecting breast cancer varying from mammography to some basic clinical tests and procedures. Automated 3-D breast ultrasound (ABUS) is one of the most advanced breast cancer detection systems which is used as a complementary modality to mammography for early detection of breast cancer. However, it is notable that screening mammograms is so difficult and time consuming for radiologists due to the large variety in shape, size, and texture of 3-D masses in these images. Hence, computer-aided detection (CADe) systems could be considered as a second interpreter in order to assist radiologists to increase accuracy and speed. In this paper, we assess different approaches that have been implemented to segment masses in ABUS images. These approaches vary from pure image processing methods to deep neural networks based on which limits, advantages and disadvantages over each other have been compared.

In this paper an approximate analytical method for solving a class of two-point boundary value problems for fourth order integro-differential equations is presented. The method is based upon the Laplace transform, perturbation technique and polynomial series. Theoretical considerations are discussed. Illustrative examples have been discussed to demonstrate the validity and applicability of the technique. The results show that the method is of high accuracy and efficient for solving integro-differential equations.

Finding analytical or numerical solutions of fractional differential equations is one of the bothersome and challenging issues among mathematicians and engineers, specifically in recent years. The objective of this paper is to solve linear and nonlinear fractional differential equations for instance first order linear fractional differential equation, Bernoulli, and Riccati fractional differential equations by using Lie Symmetry method, in accordance with M-fractional derivative. For each equation, some numerical examples are presented to illustrate the proposed approach.

In this paper, we consider the Euclidean continuous minimax location problem under uncertainty. We consider the single-facility and the multi-facility case with uncertain location of demand points and uncertain transportation costs. We study these two problems under two kinds of uncertainty, the interval and the ellipsoidal uncertainty. Equivalent formulations of robust counterparts of the single facility and multi facility Euclidean continuous minimax location problems under interval andellipsoidal uncertainty are given as conic optimizationproblems.