Kyong Pil Jang¹, Je kuk Son², Seung Hee Kwon^1,3

CMC-Computers, Materials & Continua, Vol.38, No.3, pp. 155-173, 2013, DOI:10.3970/cmc.2013.038.155

Abstract In a precast shell pier cap, cracking at the interface between the precast shell and the cast-in-place concrete may happen due to differences between the drying shrinkage of the inner and the outer concrete. The objective of this study is to establish a prediction method for interfacial cracking that will consider the real mechanism of differential drying shrinkage and creep. The main parameters used in the analysis were determined from experiments for a concrete mix that is applied to the manufacturing of pier caps. The variation of internal relative humidity over time was first calculated based on the nonlinear moisture… More >

Walter Gerstle¹, Stewart Silling², David Read³, Vinod Tewary⁴, Richard Lehoucq⁵

CMC-Computers, Materials & Continua, Vol.8, No.2, pp. 75-92, 2008, DOI:10.3970/cmc.2008.008.075

Abstract A theoretical framework, based upon the peridynamic model, is presented for analytical and computational simulation of electromigration. The framework allows four coupled physical processes to be modeled simultaneously: mechanical deformation, heat transfer, electrical potential distribution, and vacancy diffusion. The dynamics of void and crack formation, and hillock and whisker growth can potentially be modeled. The framework can potentially be applied at several modeling scales: atomistic, crystallite, multiple crystallite, and macro. The conceptual simplicity of the model promises to permit many phenomena observed in microchips, including electromigration, thermo-mechanical crack formation, and fatigue crack formation, to be analyzed in a systematic and… More >

J. Oh¹, N. Katsube², F.W. Brust³

CMC-Computers, Materials & Continua, Vol.6, No.3, pp. 129-158, 2007, DOI:10.3970/cmc.2007.006.129

Abstract In this paper, intergranular cavity growth in regimes, where both surface diffusion and deformation enhanced grain boundary diffusion are important, is studied. In order to continuously simulate the cavity shape evolution and cavity growth rate, a fully-coupled numerical method is proposed. Based on the fully-coupled numerical method, a gradual cavity shape change is predicted and this leads to the adverse effect on the cavity growth rate. As the portion of the cavity volume growth due to jacking and viscoplastic deformation in the total cavity volume growth increases, spherical cavity evolves to V-shaped cavity. The obtained numerical results are physically more… More >

Hefei Ling¹, Jia Wu¹, Ping Li^1,*, Jialie Shen²

CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1041-1054, 2019, DOI:10.32604/cmc.2019.05605

Abstract Gait recognition is a complicated task due to the existence of co-factors like carrying conditions, clothing, viewpoints, and surfaces which change the appearance of gait more or less. Among those co-factors, clothing analysis is the most challenging one in the area. Conventional methods which are proposed for clothing invariant gait recognition show the body parts and the underlying relationships from them are important for gait recognition. Fortunately, attention mechanism shows dramatic performance for highlighting discriminative regions. Meanwhile, latent semantic analysis is known for the ability of capturing latent semantic variables to represent the underlying attributes and capturing the relationships from… More >

Chunfang Yang^1,*, Jie Wang¹, Chengliang Lin¹, Huiqin Chen², Wenjuan Wang¹

CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 633-644, 2019, DOI:10.32604/cmc.2019.06154

Abstract For the case of that only a single stego image of LSB (Least Significant Bit) matching steganography is available, the existing steganalysis algorithms cannot effectively locate the modified pixels. Therefore, an algorithm is proposed to locate the modified pixels of LSB matching based on spatial and wavelet filter fusion. Firstly, the validity of using the residuals obtained by spatial and wavelet filtering to locate the modified pixels of LSB matching is analyzed. It is pointed out that both of these two kinds of residuals can be used to identify the modified pixels of LSB matching with success rate higher than… More >

Chak Fong Cheang^1,*, Yiqin Wang¹, Zhiping Cai², Gen Xu¹

CMC-Computers, Materials & Continua, Vol.57, No.2, pp. 297-306, 2018, DOI:10.32604/cmc.2018.03808

Abstract Cloud computing provides easy and on-demand access to computing resources in a configurable pool. The flexibility of the cloud environment attracts more and more network services to be deployed on the cloud using groups of virtual machines (VMs), instead of being restricted on a single physical server. When more and more network services are deployed on the cloud, the detection of the intrusion likes Distributed Denial-of-Service (DDoS) attack becomes much more challenging than that on the traditional servers because even a single network service now is possibly provided by groups of VMs across the cloud system. In this paper, we… 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 >

Xi Kan¹, Yonghong Zhang^2,*, Linglong Zhu², Liming Xiao², Jiangeng Wang³, Wei Tian⁴, Haowen Tan⁵

CMC-Computers, Materials & Continua, Vol.57, No.1, pp. 49-68, 2018, DOI:10.32604/cmc.2018.02376

Abstract Snow cover plays an important role in meteorological and hydrological researches. However, the accuracies of currently available snow cover products are significantly lower in mountainous areas than in plains, due to the serious snow/cloud confusion problem caused by high altitude and complex topography. Aiming at this problem, an improved snow cover mapping approach for mountainous areas was proposed and applied in Qinghai-Tibetan Plateau. In this work, a deep learning framework named Stacked Denoising Auto-Encoders (SDAE) was employed to fuse the MODIS multispectral images and various geographic datasets, which are then classified into three categories: Snow, cloud and snow-free land. Moreover,… More >

Rui Wang¹, Miaomiao Shen^1,*, Yanping Li¹, Samuel Gomes²

CMC-Computers, Materials & Continua, Vol.57, No.1, pp. 25-48, 2018, DOI:10.32604/cmc.2018.02408

Abstract Recently, sparse representation classification (SRC) and fisher discrimination dictionary learning (FDDL) methods have emerged as important methods for vehicle classification. In this paper, inspired by recent breakthroughs of discrimination dictionary learning approach and multi-task joint covariate selection, we focus on the problem of vehicle classification in real-world applications by formulating it as a multi-task joint sparse representation model based on fisher discrimination dictionary learning to merge the strength of multiple features among multiple sensors. To improve the classification accuracy in complex scenes, we develop a new method, called multi-task joint sparse representation classification based on fisher discrimination dictionary learning, for… More >

Jixin Liu^1,*, Ning Sun^1,2, Xiaofei Li¹, Guang Han¹, Haigen Yang¹, Quansen Sun³

CMC-Computers, Materials & Continua, Vol.55, No.3, pp. 435-446, 2018, DOI: 10.3970/cmc.2018.02177

Abstract Rare bird has long been considered an important in the field of airport security, biological conservation, environmental monitoring, and so on. With the development and popularization of IOT-based video surveillance, all day and weather unattended bird monitoring becomes possible. However, the current mainstream bird recognition methods are mostly based on deep learning. These will be appropriate for big data applications, but the training sample size for rare bird is usually very short. Therefore, this paper presents a new sparse recognition model via improved part detection and our previous dictionary learning. There are two achievements in our work: (1) after the… More >