Jieren Cheng^{1, 2}, Yifu Liu^{1, *}, Xiangyan Tang¹, Victor S. Sheng³, Mengyang Li¹, Junqi Li¹

CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1317-1333, 2020, DOI:10.32604/cmc.2020.06177

Abstract Distributed Denial-of-Service (DDoS) has caused great damage to the network in the big data environment. Existing methods are characterized by low computational efficiency, high false alarm rate and high false alarm rate. In this paper, we propose a DDoS attack detection method based on network flow grayscale matrix feature via multiscale convolutional neural network (CNN). According to the different characteristics of the attack flow and the normal flow in the IP protocol, the seven-tuple is defined to describe the network flow characteristics and converted into a grayscale feature by binary. Based on the network flow grayscale matrix feature (GMF), the… More >

Bingji Lan¹, Kanghao Yan^{1, *}

CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1303-1315, 2020, DOI:10.32604/cmc.2020.06584

Abstract In order to study the wind-induced vibration control effect of the viscous damper on the large-scale substation frame, this paper takes the large-scale 1000 kV substation frame of western Inner Mongolia as an example. The time-history sample of pulsating wind load is simulated by harmonic superposition method based on Matlab software. 6 kinds of viscous damper arrangement schemes have been designed, and SAP2000 finite element software is used for fine modeling and input wind speed time history load for nonlinear time history analysis. The displacement and acceleration of a typical node are the indicators of wind vibration control. The wind-induced… More >

Yaochan Zhu^{1, 2, *}, Hua Qiu¹, Håkan Hallberg³

CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1289-1302, 2020, DOI:10.32604/cmc.2020.06281

Abstract Based on multiphase field conception and integrated with the idea of vectorvalued phase field, a phase field model for typical allotropic transformation of solid solution is proposed. The model takes the non-uniform distribution of grain boundaries of parent phase and crystal orientation into account in proper way, as being illustrated by the simulation of austenite to ferrite transformation in low carbon steel. It is found that the misorientation dependent grain boundary mobility shows strong influence on the formation of ferrite morphology comparing with the weak effect exerted by misorientation dependent grain boundary energy. The evolution of various types of grain… More >

Bo Zhang¹, Haowen Wang^{1, #}, Longquan Jiang¹, Shuhan Yuan², Meizi Li^{1, *}

CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1273-1288, 2020, DOI:10.32604/cmc.2020.07269

Abstract Deep learning models have been shown to have great advantages in answer selection tasks. The existing models, which employ encoder-decoder recurrent neural network (RNN), have been demonstrated to be effective. However, the traditional RNN-based models still suffer from limitations such as 1) high-dimensional data representation in natural language processing and 2) biased attentive weights for subsequent words in traditional time series models. In this study, a new answer selection model is proposed based on the Bidirectional Long Short-Term Memory (Bi-LSTM) and attention mechanism. The proposed model is able to generate the more effective question-answer pair representation. Experiments on a question… More >

Yuwei Chen^{1, 2}, Yuling Chen^{1, *}, Yu Yang^{1, 2}, Xinda Hao², Ning Wang²

CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1259-1271, 2020, DOI:10.32604/cmc.2020.06723

Abstract Local binary pattern (LBP) is one of the most advanced image classification recognition operators and is commonly used in texture detection area. Research indicates that LBP also has a good application prospect in steganalysis. However, the existing LBP-based steganalysis algorithms are only capable to detect the least significant bit (LSB) and the least significant bit matching (LSBM) algorithms. To solve this problem, this paper proposes a steganalysis model called msdeLTP, which is based on multi-scale local ternary patterns (LTP) and derivative filters. The main characteristics of the msdeLTP are as follows: First, to reduce the interference of image content on… More >

Tingting Yang¹, Shuwen Jia¹, Hao Ma^{2, *}

CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1249-1258, 2020, DOI:10.32604/cmc.2020.05777

Abstract Underwater imaging is widely used in ocean, river and lake exploration, but it is affected by properties of water and the optics. In order to solve the lower-resolution underwater image formed by the influence of water and light, the image super-resolution reconstruction technique is applied to the underwater image processing. This paper addresses the problem of generating super-resolution underwater images by convolutional neural network framework technology. We research the degradation model of underwater images, and analyze the lower-resolution factors of underwater images in different situations, and compare different traditional super-resolution image reconstruction algorithms. We further show that the algorithm of… More >

Yi Shen¹, Victor S. Sheng^{1, 2, *}, Lei Wang¹, Jie Duan¹, Xuefeng Xi¹, Dengyong Zhang³, Ziming Cui¹

CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1233-1247, 2020, DOI:10.32604/cmc.2020.07450

Abstract Accurate segmentation of CT images of liver tumors is an important adjunct for the liver diagnosis and treatment of liver diseases. In recent years, due to the great improvement of hard device, many deep learning based methods have been proposed for automatic liver segmentation. Among them, there are the plain neural network headed by FCN and the residual neural network headed by Resnet, both of which have many variations. They have achieved certain achievements in medical image segmentation. In this paper, we firstly select five representative structures, i.e., FCN, U-Net, Segnet, Resnet and Densenet, to investigate their performance on liver… More >

Shang Li¹, Hongli Zhang^{1, *}, Lin Ye¹, Shen Su², Xiaoding Guo¹, Haining Yu^{1, 3}, Binxing Fang¹

CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1217-1231, 2020, DOI:10.32604/cmc.2020.06787

Abstract The task of prison term prediction is to predict the term of penalty based on textual fact description for a certain type of criminal case. Recent advances in deep learning frameworks inspire us to propose a two-step method to address this problem. To obtain a better understanding and more specific representation of the legal texts, we summarize a judgment model according to relevant law articles and then apply it in the extraction of case feature from judgment documents. By formalizing prison term prediction as a regression problem, we adopt the linear regression model and the neural network model to train… More >

Yun Tan^{1, #}, Ling Tan^{2, #}, Xuyu Xiang^{1, *}, Hao Tang^{2, *}, Jiaohua Qin¹, Wenyan Pan¹

CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1201-1215, 2020, DOI:10.32604/cmc.2020.07127

Abstract Aortic dissection (AD) is a kind of acute and rapidly progressing cardiovascular disease. In this work, we build a CTA image library with 88 CT cases, 43 cases of aortic dissection and 45 cases of health. An aortic dissection detection method based on CTA images is proposed. ROI is extracted based on binarization and morphology opening operation. The deep learning networks (InceptionV3, ResNet50, and DenseNet) are applied after the preprocessing of the datasets. Recall, F1-score, Matthews correlation coefficient (MCC) and other performance indexes are investigated. It is shown that the deep learning methods have much better performance than the traditional… More >

Jian Liu¹, Wantao Wang¹, Jie Chen^{2, *}, Guozhong Sun³, Alan Yang⁴

CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1187-1200, 2020, DOI:10.32604/cmc.2020.05883

Abstract Classification of skin lesions is a complex identification challenge. Due to the wide variety of skin lesions, doctors need to spend a lot of time and effort to judge the lesion image which zoomed through the dermatoscopy. The diagnosis which the algorithm of identifying pathological images assists doctors gets more and more attention. With the development of deep learning, the field of image recognition has made longterm progress. The effect of recognizing images through convolutional neural network models is better than traditional image recognition technology. In this work, we try to classify seven kinds of lesion images by various models… More >