H.M. Lee¹, H.S. Park^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.29, No.1, pp. 29-44, 2008, DOI:10.3970/cmes.2008.029.029

Abstract This paper presents a computational model to estimate deformed shapes of beam structures using 3D coordinate information from terrestrial laser scanning (TLS). The model is composed of five components: 1) formulation of polynomial shape function, 2) application of boundary condition, 3) inducement of compatibility condition, 4) application of the least square method and 5) evaluation of error vector and determination of reasonable polynomial shape function. In the proposed model, the optimal degree of polynomial function is selected based on the complexity of beam structures, instead of using a specific degree of polynomial function. The chosen polynomial function for estimation is… More >

Daiki Shiozawa¹, Shiro Kubo², Takahide Sakagami², Masaaki Takagi²

CMES-Computer Modeling in Engineering & Sciences, Vol.11, No.1, pp. 27-36, 2006, DOI:10.3970/cmes.2006.011.027

Abstract The passive electric potential CT (computed tomography) method using piezoelectric film was applied to the identification of plural through cracks. The use of piezoelectric material made it possible to obtain electric potential field without applying electric current. For identification of cracks an inverse analysis scheme based on the least residual method was applied, in which square sum of residuals is evaluated between the measured electric potential distributions and those computed by using the finite element method. Akaike information criterion (AIC) was used to estimate the number of cracks. Numerical simulations were carried out on the identification of plural cracks and… More >

Liang Kou¹, Yiqi Shi², Liguo Zhang¹, Duo Liu^1,*, Qing Yang³

CMC-Computers, Materials & Continua, Vol.58, No.2, pp. 545-565, 2019, DOI:10.32604/cmc.2019.03760

Abstract With the development of computer hardware technology and network technology, the Internet of Things as the extension and expansion of traditional computing network has played an increasingly important role in all professions and trades and has had a tremendous impact on people lifestyle. The information perception of the Internet of Things plays a key role as a link between the computer world and the real world. However, there are potential security threats in the Perceptual Layer Network applied for information perception because Perceptual Layer Network consists of a large number of sensor nodes with weak computing power, limited power supply,… More >

Xiangyan Tang^1,2, Liang Wang³, Jieren Cheng^1,2,4,*, Jing Chen², Victor S. Sheng⁵

CMC-Computers, Materials & Continua, Vol.58, No.2, pp. 463-491, 2019, DOI:10.32604/cmc.2019.03816

Abstract The accuracy of predicting the Producer Price Index (PPI) plays an indispensable role in government economic work. However, it is difficult to forecast the PPI. In our research, we first propose an unprecedented hybrid model based on fuzzy information granulation that integrates the GA-SVR and ARIMA (Autoregressive Integrated Moving Average Model) models. The fuzzy-information-granulation-based GA-SVR-ARIMA hybrid model is intended to deal with the problem of imprecision in PPI estimation. The proposed model adopts the fuzzy information-granulation algorithm to pre-classification-process monthly training samples of the PPI, and produced three different sequences of fuzzy information granules, whose Support Vector Regression (SVR) machine… More >

Kehua Yang^1,2,*, Tian Tan¹, Wei Zhang¹

CMC-Computers, Materials & Continua, Vol.57, No.2, pp. 269-281, 2018, DOI:10.32604/cmc.2018.03696

Abstract Dempster-Shafer (D-S) evidence theory is a key technology for integrating uncertain information from multiple sources. However, the combination rules can be paradoxical when the evidence seriously conflict with each other. In the paper, we propose a novel combination algorithm based on unsupervised Density-Based Spatial Clustering of Applications with Noise (DBSCAN) density clustering. In the proposed mechanism, firstly, the original evidence sets are preprocessed by DBSCAN density clustering, and a successfully focal element similarity criteria is used to mine the potential information between the evidence, and make a correct measure of the conflict evidence. Then, two different discount factors are adopted… More >

Lingling Xia¹, Bo Song^2,3, Zhengjun Jing⁴, Yurong Song^5,*, Liang Zhang¹

CMC-Computers, Materials & Continua, Vol.57, No.1, pp. 123-144, 2018, DOI:10.32604/cmc.2018.03738

Abstract Considering dynamical disease spreading network consisting of moving individuals, a new double-layer network is constructed, one where the information dissemination process takes place and the other where the dynamics of disease spreading evolves. On the basis of Markov chains theory, a new model characterizing the coupled dynamics between information dissemination and disease spreading in populations of moving agents is established and corresponding state probability equations are formulated to describe the probability in each state of every node at each moment. Monte Carlo simulations are performed to characterize the interaction process between information and disease spreading and investigate factors that influence… More >

Jun Shi¹, Zhujun Zhang², Yangyang Li^1,*, Rui Wang¹, Hao Shi¹, Xile Li³

CMC-Computers, Materials & Continua, Vol.57, No.1, pp. 69-80, 2018, DOI:10.32604/cmc.2018.03688

Abstract The electromagnetic waves emitted from devices can be a source of information leakage and can cause electromagnetic compatibility (EMC) problems. Electromagnetic radiation signals from computer displays can be a security risk if they are intercepted and reconstructed. In addition, the leaks may reveal the hardware information of the computer, which is more important for some attackers, protectors and security inspection workers. In this paper, we propose a statistical distribution based algorithm (SD algorithm) to extracted eigenvalues from electromagnetic radiate video signals, and then classified computers by using classifier based on Bayesian and SVM. We can identify computers automatically and accurately… 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 >

Junjia Chen¹, Wei Lu^1,2,*, Yuileong Yeung¹, Yingjie Xue¹, Xianjin Liu¹, Cong Lin^1,3, Yue Zhang⁴

CMC-Computers, Materials & Continua, Vol.55, No.2, pp. 201-211, 2018, DOI:10.3970/cmc.2018.01781

Abstract In recent years, binary image steganography has developed so rapidly that the research of binary image steganalysis becomes more important for information security. In most state-of-the-art binary image steganographic schemes, they always find out the flippable pixels to minimize the embedding distortions. For this reason, the stego images generated by the previous schemes maintain visual quality and it is hard for steganalyzer to capture the embedding trace in spacial domain. However, the distortion maps can be calculated for cover and stego images and the difference between them is significant. In this paper, a novel binary image steganalytic scheme is proposed,… More >

Qili Zhou¹, Yongbin Qiu¹, Li Li^1,*, Jianfeng Lu¹, Wenqiang Yuan¹, Xiaoqing Feng², Xiaoyang Mao³

CMC-Computers, Materials & Continua, Vol.55, No.1, pp. 151-163, 2018, DOI:10.3970/cmc.2018.055.151

Abstract Steganography technology has been widely used in data transmission with secret information. However, the existing steganography has the disadvantages of low hidden information capacity, poor visual effect of cover images, and is hard to guarantee security. To solve these problems, steganography using reversible texture synthesis based on seeded region growing and LSB is proposed. Secret information is embedded in the process of synthesizing texture image from the existing natural texture. Firstly, we refine the visual effect. Abnormality of synthetic texture cannot be fully prevented if no approach of controlling visual effect is applied in the process of generating synthetic texture.… More >