Wen Tian¹, Xiaopeng Ji^1,*, Weiwei Liu¹, Guangjie Liu¹, Rong Lin^1,2, Jiangtao Zhai³, Yuewei Dai³

CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 193-211, 2019, DOI:10.32604/cmc.2019.05290

Abstract Cyber-physical system (CPS) is an advanced system that integrats physical processes, computation and communication resources. The security of cyber-physical systems has become an active research area in recent years. In this paper, we focus on defensive strategies against network attacks in CPS. We introduce both low- and highinteraction honeypots into CPS as a security management tool deliberately designed to be probed, attacked and compromised. In addition, an analysis resource constraint is introduced for the purpose of optimizing defensive strategies against network attacks in CPS. We study the offensive and defensive interactions of CPS and model the offensive and defensive process… More >

Filipe L. A. Ribeiro^1,*, Andre R. Barbosa², Luis C. Neves³

CMES-Computer Modeling in Engineering & Sciences, Vol.120, No.3, pp. 657-676, 2019, DOI:10.32604/cmes.2019.06296

Abstract Although pre-Northridge earthquake steel moment resisting frame buildings have been shown to be susceptible to brittle connection failures, they still represent a large fraction of the existing steel buildings in the United States of America. In this study, the performance of the 3- and 9-story Los Angeles pre-Northridge SAC buildings are analyzed considering ductile and brittle beam-column connection failures, and their uncertainty. This paper contributes to understanding the influence of uncertainty associated with connections brittle fracture on building interstory deformation capacity and its impact on bias and variability of fragility functions and loss assessment. The results show that considering brittle… More >

Yaohui Li^1,2, Yizhong Wu^1,3, Zhengdong Huang¹

CMES-Computer Modeling in Engineering & Sciences, Vol.97, No.4, pp. 323-357, 2014, DOI:10.3970/cmes.2014.097.323

Abstract Kriging model, which provides an exact interpolation and minimizes the error estimates, is a highly-precise global approximation model in contrast with other traditional response surfaces. Therefore, sequential exploratory experimental design (SEED) with Kriging model is crucial for globally approximating a complex black-box function. However, the more sampling points are, the longer time it would take to update the Kriging model during sequential exploratory design. This paper, therefore, proposes a new construction method called incremental Kriging method (IKM) to improve the constructing efficiency with just a little and controllable loss of accuracy for Kriging model. The IKM, based on the matrix… More >

A.E. Martínez-Castro¹, I.H. Faris¹, R. Gallego¹

CMES-Computer Modeling in Engineering & Sciences, Vol.87, No.3, pp. 177-206, 2012, DOI:10.3970/cmes.2012.087.177

Abstract In this paper, the identification of hidden defects inside a three-dimen -sional layer is set as an Identification Inverse Problem. This problem is solved by minimizing a cost functional which is linearized with respect to the volume defects, leading to a procedure that requires only computations at the host domain free of defects. The cost functional is stated as the misfit between experimental and computed displacements and spherical and/or ellipsoidal cavities are the defects to locate. The identification of these cavities is based on the measured displacements at a set of points due to time-harmonic point loads at an array… More >

G. Veble^1,2,3

CMES-Computer Modeling in Engineering & Sciences, Vol.36, No.3, pp. 243-260, 2008, DOI:10.3970/cmes.2008.036.243

Abstract A simple cost function is proposed that depends on the inviscid pressure distribution around an airfoil and that, when minimized, results in airfoils that promote laminar flow. Additional constraints specify the design point of the airfoil. The method allows for straightforward inclusion of multiple design points. The resulting airfoils are quantitatively similar to those already successfully used in practice. More >

Satya N. Atluri¹, Shengping Shen¹

CMES-Computer Modeling in Engineering & Sciences, Vol.3, No.1, pp. 11-52, 2002, DOI:10.3970/cmes.2002.003.011

Abstract A comparison study of the efficiency and accuracy of a variety of meshless trial and test functions is presented in this paper, based on the general concept of the meshless local Petrov-Galerkin (MLPG) method. 5 types of trial functions, and 6 types of test functions are explored. Different test functions result in different MLPG methods, and six such MLPG methods are presented in this paper. In all these six MLPG methods, absolutely no meshes are needed either for the interpolation of the trial and test functions, or for the integration of the weak-form; while other meshless methods require background cells.… More >

A. P. Chassiakos, C. I. Samaras, D. D. Theodorakopoulos¹

CMES-Computer Modeling in Engineering & Sciences, Vol.1, No.4, pp. 9-18, 2000, DOI:10.3970/cmes.2000.001.461

Abstract Time and cost to complete a project is an important tradeoff problem in project planning and control. Existing methods have not provided an accepted solution in terms of both accuracy and efficiency. In an attempt to improve the solution process, a method is presented for developing optimal project time-cost curves based on CPM analysis. Using activity succession information, project paths are developed and duration is calculated. Following that, duration is reduced in an optimal way employing integer programming. Two alternative formulations are proposed which lead to corresponding algorithms, a progressive duration reduction and a direct reduction to the desired level.… More >

Daojian Zeng^1,2, Yao Xiao^1,2, Jin Wang^2,*, Yuan Dai^1,2, Arun Kumar Sangaiah³

CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1251-1261, 2019, DOI:10.32604/cmc.2019.06100

Abstract Recently, many researchers have concentrated on distant supervision relation extraction (DSRE). DSRE has solved the problem of the lack of data for supervised learning, however, the data automatically labeled by DSRE has a serious problem, which is class imbalance. The data from the majority class obviously dominates the dataset, in this case, most neural network classifiers will have a strong bias towards the majority class, so they cannot correctly classify the minority class. Studies have shown that the degree of separability between classes greatly determines the performance of imbalanced data. Therefore, in this paper we propose a novel model, which… More >