Huan Zhang¹, Kangfeng Zheng^{1, *}, Xiujuan Wang², Shoushan Luo¹, Bin Wu¹

CMC-Computers, Materials & Continua, Vol.62, No.2, pp. 763-786, 2020, DOI:10.32604/cmc.2020.06553

Abstract As a core component of the network, web applications have become one of the preferred targets for attackers because the static configuration of web applications simplifies the exploitation of vulnerabilities by attackers. Although the moving target defense (MTD) has been proposed to increase the attack difficulty for the attackers, there is no solo approach can cope with different attacks; in addition, it is impossible to implement all these approaches simultaneously due to the resource limitation. Thus, the selection of an optimal defense strategy based on MTD has become the focus of research. In general, the confrontation of two players in… More >

Haoxiang Sun^{1, *}, Changxing Chen¹, Yunfei Ling¹, Mu Yang¹

CMC-Computers, Materials & Continua, Vol.62, No.2, pp. 747-761, 2020, DOI:10.32604/cmc.2020.05625

Abstract In the process of spectrum perception, in order to realize accurate perception of the channel state, the method of multi-node cooperative perception can usually be used. However, the first problem to be considered is how to complete information fusion and obtain more accurate and reliable judgment results based on multi-node perception results. The ideas put forward in this paper are as follows: firstly, the perceived results of each node are obtained on the premise of limiting detection probability and false alarm probability. Then, on the one hand, the weighted fusion criterion of decision-making weight optimization of each node is realized… More >

Lili Pan¹, Cong Li^{1, *}, Samira Pouyanfar², Rongyu Chen¹, Yan Zhou¹

CMC-Computers, Materials & Continua, Vol.62, No.2, pp. 731-746, 2020, DOI:10.32604/cmc.2020.06508

Abstract With the development of deep learning and Convolutional Neural Networks (CNNs), the accuracy of automatic food recognition based on visual data have significantly improved. Some research studies have shown that the deeper the model is, the higher the accuracy is. However, very deep neural networks would be affected by the overfitting problem and also consume huge computing resources. In this paper, a new classification scheme is proposed for automatic food-ingredient recognition based on deep learning. We construct an up-to-date combinational convolutional neural network (CBNet) with a subnet merging technique. Firstly, two different neural networks are utilized for learning interested features.… More >

Yinghang Jiang¹, Qi Liu^2,3,*, Williams Dannah¹, Dandan Jin², Xiaodong Liu³, Mingxu Sun^4,*

CMC-Computers, Materials & Continua, Vol.62, No.2, pp. 713-729, 2020, DOI:10.32604/cmc.2020.04604

Abstract Hadoop is a well-known parallel computing system for distributed computing and large-scale data processes. “Straggling” tasks, however, have a serious impact on task allocation and scheduling in a Hadoop system. Speculative Execution (SE) is an efficient method of processing “Straggling” Tasks by monitoring real-time running status of tasks and then selectively backing up “Stragglers” in another node to increase the chance to complete the entire mission early. Present speculative execution strategies meet challenges on misjudgement of “Straggling” tasks and improper selection of backup nodes, which leads to inefficient implementation of speculative executive processes. This paper has proposed an Optimized Resource… More >

Jin Wang^{1, 2, 3}, Yu Gao², Chang Zhou², R. Simon Sherratt⁴, Lei Wang^{5, *}

CMC-Computers, Materials & Continua, Vol.62, No.2, pp. 695-711, 2020, DOI:10.32604/cmc.2020.08674

Abstract Wireless Sensor Networks (WSNs) are usually formed with many tiny sensors which are randomly deployed within sensing field for target monitoring. These sensors can transmit their monitored data to the sink in a multi-hop communication manner. However, the ‘hot spots’ problem will be caused since nodes near sink will consume more energy during forwarding. Recently, mobile sink based technology provides an alternative solution for the long-distance communication and sensor nodes only need to use single hop communication to the mobile sink during data transmission. Even though it is difficult to consider many network metrics such as sensor position, residual energy… More >

N. Shobha Rani^{1, *}, M. Chandrajith², B. R. Pushpa¹, B. J. Bipin Nair¹

CMC-Computers, Materials & Continua, Vol.62, No.2, pp. 679-694, 2020, DOI:10.32604/cmc.2020.08552

Abstract Assessing the age of an individual via bones serves as a fool proof method in true determination of individual skills. Several attempts are reported in the past for assessment of chronological age of an individual based on variety of discriminative features found in wrist radiograph images. The permutation and combination of these features realized satisfactory accuracies for a set of limited groups. In this paper, assessment of gender for individuals of chronological age between 1-17 years is performed using left hand wrist radiograph images. A fully automated approach is proposed for removal of noise persisted due to non-uniform illumination during… More >

Yasir Nawaz¹, Muhammad Shoaib Arif ¹, Mairaj Bibi^{2, *}, Javeria Nawaz Abbasi², Umer Javed³, Amna Nazeer²

CMC-Computers, Materials & Continua, Vol.62, No.2, pp. 657-677, 2020, DOI:10.32604/cmc.2020.08584

Abstract Present contribution is concerned with the construction and application of a numerical method for the fluid flow problem over a linearly stretching surface with the modification of standard Gradient descent Algorithm to solve the resulted difference equation. The flow problem is constructed using continuity, and Navier Stoke equations and these PDEs are further converted into boundary value problem by applying suitable similarity transformations. A central finite difference method is proposed that gives third-order accuracy using three grid points. The stability conditions of the present proposed method using a Gauss-Seidel iterative procedure is found using VonNeumann stability criteria and order of… More >

Yun Wang¹, Fazli Subhan², Shahaboddin Shamshirband^{3, 4, *}, Muhammad Zubair Asghar⁵, Ikram Ullah⁵, Ammara Habib⁵

CMC-Computers, Materials & Continua, Vol.62, No.2, pp. 631-655, 2020, DOI:10.32604/cmc.2020.07920

Abstract The feedback collection and analysis has remained an important subject matter for long. The traditional techniques for student feedback analysis are based on questionnaire-based data collection and analysis. However, the student expresses their feedback opinions on online social media sites, which need to be analyzed. This study aims at the development of fuzzy-based sentiment analysis system for analyzing student feedback and satisfaction by assigning proper sentiment score to opinion words and polarity shifters present in the input reviews. Our technique computes the sentiment score of student feedback reviews and then applies a fuzzy-logic module to analyze and quantify student’s satisfaction… More >

Behrouz Karami¹, Maziar Janghorban¹, Timon Rabczuk^{2, *}

CMC-Computers, Materials & Continua, Vol.62, No.2, pp. 607-629, 2020, DOI:10.32604/cmc.2020.08032

Abstract This study investigates the forced vibration of functionally graded hexagonal nano-size plates for the first time. A quasi-three-dimensional (3D) plate theory including stretching effect is used to model the anisotropic plate as a continuum one where smallscale effects are considered based on nonlocal strain gradient theory. Also, the plate is assumed on a Pasternak foundation in which normal and transverse shear loads are taken into account. The governing equations of motion are obtained via the Hamiltonian principles which are solved using analytical based methods by means of Navier’s approximation. The influences of the exponential factor, nonlocal parameter, strain gradient parameter,… More >

Noor Mualla¹, Essam H Houssein^{2, *}, M. R. Hassan¹

CMC-Computers, Materials & Continua, Vol.62, No.2, pp. 591-605, 2020, DOI:10.32604/cmc.2020.08580

Abstract Chronological age estimation using panoramic dental X-ray images is an essential task in forensic sciences. Various statistical approaches have proposed by considering the teeth and mandible. However, building automated dental age estimation based on machine learning techniques needs more research efforts. In this paper, an automated dental age estimation is proposed using transfer learning. In the proposed approach, features are extracted using two deep neural networks namely, AlexNet and ResNet. Several classifiers are proposed to perform the classification task including decision tree, k-nearest neighbor, linear discriminant, and support vector machine. The proposed approach is evaluated using a number of suitable… More >