Ma Ning^1,*, Jianhe Guan¹, Pingzeng Liu², Ziqing Zhang³, Gregory M. P. O’Hare⁴

CMC-Computers, Materials & Continua, Vol.58, No.1, pp. 215-227, 2019, DOI:10.32604/cmc.2019.03763

Abstract With the rapid development of China’s economy, the scale of the city has been continuously expanding, industrial enterprises have been increasing, the discharge of multiple pollutants has reached the top of the world, and the environmental problems become more and more serious. The air pollution problem is particularly prominent. Air quality has become a daily concern for people. In order to control air pollution, it is necessary to grasp the air quality situation in an all-round way. It is necessary to evaluate air quality. Accurate results of air quality evaluation can help people know more about air quality. In this… More >

Wenjun Yang¹, Pingping Dong^1,2,*, Wensheng Tang¹, Xiaoping Lou¹, Hangjun Zhou³, Kai Gao⁴, Haodong Wang⁵

CMC-Computers, Materials & Continua, Vol.57, No.2, pp. 205-222, 2018, DOI:10.32604/cmc.2018.03726

Abstract Multipath TCP (MPTCP) is the most significant extension of TCP that enables transmission via multiple paths concurrently to improve the resource usage and throughput of long flows. However, due to the concurrent multiple transfer (CMT) in short flow trans-mission, the congestion window (cwnd) of each MPTCP subflow is too small and it may lead to timeout when a single lost packet cannot be recovered through fast retransmission. As a result, MPTCP has even worse performance for short flows compared to regular TCP. In this paper, we take the first step to analyze the main reason why MPTCP has the diminished… More >

Chuanlong Li^1,2,*, Yumeng Jiang³, Marta Cheslyar¹

CMC-Computers, Materials & Continua, Vol.56, No.2, pp. 313-324, 2018, DOI: 10.3970/cmc.2018.03950

Abstract Deep neural network has proven to be very effective in computer vision fields. Deep convolutional network can learn the most suitable features of certain images without specific measure functions and outperform lots of traditional image processing methods. Generative adversarial network (GAN) is becoming one of the highlights among these deep neural networks. GAN is capable of generating realistic images which are imperceptible to the human vision system so that the generated images can be directly used as intermediate medium for many tasks. One promising application of using GAN generated images would be image concealing which requires the embedded image looks… More >

Shuaiwei Zhang¹, Xiaoyuan Yang^1,*, Weidong Zhong¹, Yujuan Sun²

CMC-Computers, Materials & Continua, Vol.56, No.2, pp. 325-338, 2018, DOI:10.3970/cmc.2018.03611

Abstract As one of the typical method for side channel attack, DPA has become a serious trouble for the security of encryption algorithm implementation. The potential capability of DPA attack induces researchers making a lot of efforts in this area, which significantly improved the attack efficiency of DPA. However, most of these efforts were made based on the hypothesis that the gathered power consumption data from the target device were stable and low noise. If large deviation happens in part of the power consumption data sample, the efficiency of DPA attack will be reduced rapidly. In this work, a highly efficient… More >

Xintao Duan^1,*, Haoxian Song¹, Chuan Qin², Muhammad Khurram Khan³

CMC-Computers, Materials & Continua, Vol.55, No.3, pp. 483-493, 2018, DOI: 10.3970/cmc.2018.01798

Abstract In this paper, we propose a novel coverless image steganographic scheme based on a generative model. In our scheme, the secret image is first fed to the generative model database, to generate a meaning-normal and independent image different from the secret image. The generated image is then transmitted to the receiver and fed to the generative model database to generate another image visually the same as the secret image. Thus, we only need to transmit the meaning-normal image which is not related to the secret image, and we can achieve the same effect as the transmission of the secret image.… More >

Xuewen Zhang¹, Zhonghao Li¹, Gongshen Liu^1,*, Jiajun Xu¹, Tiankai Xie², Jan Pan Nees¹

CMC-Computers, Materials & Continua, Vol.55, No.3, pp. 405-417, 2018, DOI: 10.3970/cmc.2018.02527

Abstract As a main distributed computing system, Spark has been used to solve problems with more and more complex tasks. However, the native scheduling strategy of Spark assumes it works on a homogenized cluster, which is not so effective when it comes to heterogeneous cluster. The aim of this study is looking for a more effective strategy to schedule tasks and adding it to the source code of Spark. After investigating Spark scheduling principles and mechanisms, we developed a stratifying algorithm and a node scheduling algorithm is proposed in this paper to optimize the native scheduling strategy of Spark. In this… More >

Surkay D. Akbarov^1,2, Hatam H. Guliyev³, Yusif M. Sevdimaliyev⁴, Nazmiye Yahnioglu^5,*

CMC-Computers, Materials & Continua, Vol.55, No.2, pp. 359-380, 2018, DOI:10.3970/cmc.2018.00173

Abstract The paper deals with a development of the discrete-analytical method for the solution of the dynamical problems of a hollow sphere with inhomogeneous initial stresses. The examinations are made with respect to the problem on the natural vibration of the hollow sphere the initial stresses in which is caused by internal and external uniformly distributed pressure. The initial stresses in the sphere are determined within the scope of the exact equations of elastostatics. It is assumed that after appearing this static initial stresses the sphere gets a dynamical excitation and mechanical behavior of the sphere caused by this excitation is… More >

Ran Wang¹, Xuegang Yuan^1,2, Hongwu Zhang¹, Jing Zhang³, Na Lv^2,*

CMC-Computers, Materials & Continua, Vol.55, No.2, pp. 345-357, 2018, DOI:10.3970/cmc.2018.00233

Abstract In this paper, a nonlinear wave equation with variable coefficients is studied, interestingly, this equation can be used to describe the travelling waves propagating along the circular rod composed of a general compressible hyperelastic material with variable cross-sections and variable material densities. With the aid of Lou’s direct method1, the nonlinear wave equation with variable coefficients is reduced and two sets of symmetry transformations and exact solutions of the nonlinear wave equation are obtained. The corresponding numerical examples of exact solutions are presented by using different coefficients. Particularly, while the variable coefficients are taken as some special constants, the nonlinear… More >

Ya Tu¹, Yun Lin¹, Jin Wang^2,3,*, Jeong-Uk Kim⁴

CMC-Computers, Materials & Continua, Vol.55, No.2, pp. 243-254, 2018, DOI:10.3970/cmc.2018.01755

Abstract Deep Learning (DL) is such a powerful tool that we have seen tremendous success in areas such as Computer Vision, Speech Recognition, and Natural Language Pro-cessing. Since Automated Modulation Classification (AMC) is an important part in Cognitive Radio Networks, we try to explore its potential in solving signal modula-tion recognition problem. It cannot be overlooked that DL model is a complex mod-el, thus making them prone to over-fitting. DL model requires many training data to combat with over-fitting, but adding high quality labels to training data manually is not always cheap and accessible, especially in real-time system, which may counter… More >

Qi Cui^1,2,*, Suzanne McIntosh³, Huiyu Sun³

CMC-Computers, Materials & Continua, Vol.55, No.2, pp. 229-241, 2018, DOI:10.3970/cmc.2018.01693

Abstract Currently, some photorealistic computer graphics are very similar to photographic images. Photorealistic computer generated graphics can be forged as photographic images, causing serious security problems. The aim of this work is to use a deep neural network to detect photographic images (PI) versus computer generated graphics (CG). In existing approaches, image feature classification is computationally intensive and fails to achieve real-time analysis. This paper presents an effective approach to automatically identify PI and CG based on deep convolutional neural networks (DCNNs). Compared with some existing methods, the proposed method achieves real-time forensic tasks by deepening the network structure. Experimental results… More >