Muhammad Yahya Saeed¹, Muhammad Awais¹, Muhammad Younas¹, Muhammad Arif Shah^2,*, Atif Khan³, M. Irfan Uddin⁴, Marwan Mahmoud⁵

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2409-2423, 2021, DOI:10.32604/cmc.2021.014330

Abstract Text Summarization is an essential area in text mining, which has procedures for text extraction. In natural language processing, text summarization maps the documents to a representative set of descriptive words. Therefore, the objective of text extraction is to attain reduced expressive contents from the text documents. Text summarization has two main areas such as abstractive, and extractive summarization. Extractive text summarization has further two approaches, in which the first approach applies the sentence score algorithm, and the second approach follows the word embedding principles. All such text extractions have limitations in providing the basic theme of the underlying documents.… More >

Miaomiao Yang, Wentao Ma, Yongbin Ge^*

CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.1, pp. 25-54, 2021, DOI:10.32604/cmes.2021.012575

Abstract In this paper, Chebyshev interpolation nodes and barycentric Lagrange interpolation basis function are used to deduce the scheme for solving the Helmholtz equation. First of all, the interpolation basis function is applied to treat the spatial variables and their partial derivatives, and the collocation method for solving the second order differential equations is established. Secondly, the differential equations on a given test node. Finally, based on three kinds of test nodes, numerical experiments show that the present scheme can not only calculate the high wave numbers problems, but also calculate the variable wave numbers problems. In addition, the algorithm has… More >

Muhammad Saqib¹, Hanifa Hanif^{1, 2}, T. Abdeljawad^{3, 4, 5}, Ilyas Khan^{6, *}, Sharidan Shafie¹, Kottakkaran Sooppy Nisar⁷

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 1959-1973, 2020, DOI:10.32604/cmc.2020.011339

Abstract The idea of fractional derivatives is applied to several problems of viscoelastic fluid. However, most of these problems (fluid problems), were studied analytically using different integral transform techniques, as most of these problems are linear. The idea of the above fractional derivatives is rarely applied to fluid problems governed by nonlinear partial differential equations. Most importantly, in the nonlinear problems, either the fractional models are developed by artificial replacement of the classical derivatives with fractional derivatives or simple classical problems (without developing the fractional model even using artificial replacement) are solved. These problems were mostly solved for steady-state fluid problems.… More >

Alberto Fernández Oliva¹, Francisco Maciá Pérez², José Vicente Berná-Martinez^2,*, Miguel Abreu Ortega³

Computer Systems Science and Engineering, Vol.34, No.3, pp. 131-144, 2019, DOI:10.32604/csse.2019.34.131

Abstract This study presents a method for the detection of outliers based on the Variable Precision Rough Set Model (VPRSM). The basis of this model is the generalisation of the standard concept of a set inclusion relation on which the Rough Set Basic Model (RSBM) is based. The primary contribution of this study is the improvement in detection quality, which is achieved due to the generalisation allowed by the classification system that allows a certain degree of uncertainty. From this method, a computationally efficient algorithm is proposed. The experiments performed with a real scenario and a comparison of the results with… More >

Wenxuan Wang^*, Xiaoyi Wang

CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 985-1000, 2020, DOI:10.32604/cmes.2020.09006

Abstract The importance analysis method represents a powerful tool for quantifying the impact of input uncertainty on the output uncertainty. When an input variable is described by a specific interval rather than a certain probability distribution, the interval importance measure of input interval variable can be calculated by the traditional non-probabilistic importance analysis methods. Generally, the non-probabilistic importance analysis methods involve the Monte Carlo simulation (MCS) and the optimization-based methods, which both have high computational cost. In order to overcome this problem, this study proposes an interval important analytical method avoids the time-consuming optimization process. First, the original performance function is… More >

Yiming Huang^{1, *}, Hang Lei¹, Xiaoyu Li^{1, *}, Qingsheng Zhu², Wanghao Ren³, Xusheng Liu^{2, 4}

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 445-458, 2020, DOI:10.32604/cmc.2020.010390

Abstract In recent years, an increasing number of studies about quantum machine learning not only provide powerful tools for quantum chemistry and quantum physics but also improve the classical learning algorithm. The hybrid quantum-classical framework, which is constructed by a variational quantum circuit (VQC) and an optimizer, plays a key role in the latest quantum machine learning studies. Nevertheless, in these hybridframework-based quantum machine learning models, the VQC is mainly constructed with a fixed structure and this structure causes inflexibility problems. There are also few studies focused on comparing the performance of quantum generative models with different loss functions. In this… More >

Tao Shang^{1, *}, Ran Liu¹, Jianwei Liu¹, Yafei Hou²

CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1629-1645, 2020, DOI:10.32604/cmc.2020.09820

Abstract Establishing entanglement is an essential task of quantum communication technology. Beyond entanglement, quantum discord, as a measure of quantum correlation, is a necessary prerequisite to the success of entanglement distribution. To realize efficient quantum communication based on quantum discord, in this paper, we consider the practical advantages of continuous variables and propose a feasible continuous-variable quantum network coding scheme based on quantum discord. By means of entanglement distribution by separable states, it can achieve quantum entanglement distribution from sources to targets in a butterfly network. Compared with the representative discrete-variable quantum network coding schemes, the proposed continuous-variable quantum network coding… More >

Chao Mei, Qifu Wang^*, Chen Yu, Zhaohui Xia

CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.1, pp. 179-202, 2020, DOI:10.32604/cmes.2020.09948

Abstract This paper presents a topology optimization method for variable stiffness composite panels with varying fiber orientation and curvilinear fiber path. Non-uniform rational B-Splines (NURBS) based Isogeometric analysis (IGA) is utilized for the numerical computation of the general minimum compliance problem. The sensitivity analysis of the structure compliance function for the density and bi-layer orientation is conducted. The bi-layer fiber paths in the design domain are generated using streamline method and updated by divided pieces reselection method after the optimization process. Several common examples are tested to demonstrate the effectiveness of the method. The results show that the proposed method can… More >

Rashmi Gupta¹, Manju Khari¹, Vipul Gupta¹, Elena Verdú², Xing Wu³, Enrique Herrera-Viedma⁴, Rubén González Crespo^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.123, No.3, pp. 1175-1192, 2020, DOI:10.32604/cmes.2020.010092

Abstract The images capture in a bad environment usually loses its fidelity and contrast. As the light rays travel towards its destination they get scattered several times due to the tiny particles of fog and pollutants in the environment, therefore the energy gets lost due to multiple scattering till it arrives its destination, and this degrades the images. So the images taken in bad weather appear in bad quality. Therefore, single image haze removal is quite a bit tough task. Significant research has been done in the haze removal algorithm but in all the techniques, the coefficient of scattering is taken… More >

Gökçe Yıldız¹, Gültekin Tınaztepe^{2, *}, Mehmet Sezer¹

CMES-Computer Modeling in Engineering & Sciences, Vol.123, No.3, pp. 973-993, 2020, DOI:10.32604/cmes.2020.09329

Abstract In this article, we approximate the solution of high order linear Fredholm integro-differential equations with a variable coefficient under the initial-boundary conditions by Bell polynomials. Using collocation points and treating the solution as a linear combination of Bell polynomials, the problem is reduced to linear system of equations whose unknown variables are Bell coefficients. The solution to this algebraic system determines the approximate solution. Error estimation of approximate solution is done. Some examples are provided to illustrate the performance of the method. The numerical results are compared with the collocation method based on Legendre polynomials and the other two methods… More >