Jieren Cheng^1,2, Ruomeng Xu^1,*, Xiangyan Tang¹, Victor S. Sheng³, Canting Cai¹

CMC-Computers, Materials & Continua, Vol.55, No.1, pp. 95-119, 2018, DOI:10.3970/cmc.2018.055.095

Abstract Distributed denial-of-service (DDoS) is a rapidly growing problem with the fast development of the Internet. There are multitude DDoS detection approaches, however, three major problems about DDoS attack detection appear in the big data environment. Firstly, to shorten the respond time of the DDoS attack detector; secondly, to reduce the required compute resources; lastly, to achieve a high detection rate with low false alarm rate. In the paper, we propose an abnormal network flow feature sequence prediction approach which could fit to be used as a DDoS attack detector in the big data environment and solve aforementioned problems. We define… More >

Qiankai Nie¹, Xuba Xu¹, Bingwen Feng^1,*, Leo Yu Zhang²

CMC-Computers, Materials & Continua, Vol.55, No.1, pp. 59-70, 2018, DOI:10.3970/cmc.2018.055.059

Abstract In this paper, an effective intra prediction mode-based video strganography is proposed. Secret messages are embedded during the intra prediction of the video encoding without causing large embedding impact. The influence on the sum of absolute difference (SAD) in intra prediction modes (IPMs) reversion phenomenon is sharp when modifying IPMs. It inspires us to take the SAD prediction deviation (SPD) to define the distortion function. What is more, the mapping rule between IPMs and the codewords is introduced to further reduce the SPD values of each intra block. Syndrome-trellis code (STC) is used as the practical embedding implementation. Experimental results… More >

Ying Xiao^1,2, Haomiao Zhou¹, Xiaofan Gou^2,*

CMC-Computers, Materials & Continua, Vol.54, No.3, pp. 209-228, 2018, DOI:10.3970/cmc.2018.054.209

Abstract In order to predict the performance of magnetostrictive smart material and push its applications in engineering, it is necessary to build the constitutive relations for the magnetostrictive material Galfenol. For Galfenol rods under the action of the pre-stress and magnetic field along the axial direction, the one-dimensional nonlinear magneto-mechanical coupling constitutive model is proposed based on the elastic Gibbs free energy, where the Taylor expansion of the elastic Gibbs free energy is made to obtain the polynomial forms. And then the constitutive relations are derived by replacing the polynomial forms with the proper transcendental functions based on the microscopic magneto-mechanical… More >

G. Jayaprakash¹, M. P. Muthuraj^2,*

CMC-Computers, Materials & Continua, Vol.54, No.1, pp. 83-102, 2018, DOI:10.3970/cmc.2018.054.083

Abstract This paper discusses the applicability of relevance vector machine (RVM) based regression to predict the compressive strength of various self compacting concrete (SCC) mixes. Compressive strength data various SCC mixes has been consolidated by considering the effect of water cement ratio, water binder ratio and steel fibres. Relevance vector machine (RVM) is a machine learning technique that uses Bayesian inference to obtain parsimonious solutions for regression and classification. The RVM has an identical functional form to the support vector machine, but provides probabilistic classification and regression. RVM is based on a Bayesian formulation of a linear model with an appropriate… More >

Haolong Chen^1,2, Bo Yu¹, Huanlin Zhou^1*, Zeng Meng¹

CMC-Computers, Materials & Continua, Vol.53, No.4, pp. 271-290, 2017, DOI:10.3970/cmc.2017.053.271

Abstract The cuckoo search algorithm (CS) is improved by using the conjugate gradient method(CGM), and the CS-CGM is proposed. The unknown inner boundary shapes are generated randomly and evolved by Lévy flights and elimination mechanism in the CS and CS-CGM. The CS, CGM and CS-CGM are examined for the prediction of a pipe’s inner surface. The direct problem is two-dimensional transient heat conduction in functionally graded materials (FGMs). Firstly, the radial integration boundary element method (RIBEM) is applied to solve the direct problem. Then the three methods are compared to identify the pipe’s inner surfacewith the information of measured temperatures. Finally,… More >

Susom Dutta¹, A. Ramach,ra Murthy², Dookie Kim³, Pijush Samui⁴

CMC-Computers, Materials & Continua, Vol.53, No.2, pp. 157-174, 2017, DOI:10.3970/cmc.2017.053.167

Abstract In the present scenario, computational modeling has gained much importance for the prediction of the properties of concrete. This paper depicts that how computational intelligence can be applied for the prediction of compressive strength of Self Compacting Concrete (SCC). Three models, namely, Extreme Learning Machine (ELM), Adaptive Neuro Fuzzy Inference System (ANFIS) and Multi Adaptive Regression Spline (MARS) have been employed in the present study for the prediction of compressive strength of self compacting concrete. The contents of cement (c), sand (s), coarse aggregate (a), fly ash (f), water/powder (w/p) ratio and superplasticizer (sp) dosage have been taken as inputs… More >

K. Khanna^1,2, V.K. Gupta³, S.P. Nigam¹

CMC-Computers, Materials & Continua, Vol.48, No.3, pp. 147-161, 2015, DOI:10.3970/cmc.2015.048.147

Abstract A mathematical model is developed to describe the steady state creep in a rotating Al-SiC_p disc having a non-linear thickness profile and distribution of SiC particles along the radial direction. The model is used to investigate the effect of imposing three different kinds of radial temperature profiles viz. linear, parabolic and exponential with fixed values of inner and outer surface temperatures, on the creep stresses and strain rates. It is noticed that by increasing the temperature exponent (n_T), the radial stress (over the entire radius) and tangential stress (near the inner radius) increase in the disc. However, the tangential stress… More >

Q.W. Yang¹, S.G. Du^1,2

CMC-Computers, Materials & Continua, Vol.47, No.3, pp. 217-236, 2015, DOI:10.3970/cmc.2015.047.217

Abstract Size effect is a major issue in concrete structures and occurs in concrete in any loading conditions. In this study, size effect on concrete cubic compressive strength is modeled with a back-propagation neural network. The main advantage in using an artificial neural network (ANN) technique is that the network is built directly from experimental data without any simplifying assumptions via the self-organizing capabilities of the neural network. The proposed ANN model is verified by using 27 experimental data sets collected from the literature. For the large specimens, a modified ANN is developed in the paper to further improve the forecast… More >

W.Xu¹, A.M. Waas²

CMC-Computers, Materials & Continua, Vol.46, No.3, pp. 165-194, 2015, DOI:10.3970/cmc.2015.046.165

Abstract Plastic deformation and splitting are two important mechanisms of energy dissipation when metal tubes undergo axial crushing. Isotropic J2 plasticity theory combined with a failure criterion is used to model axial splitting and curling of metal tubes undergoing axial crush. The proposed material model is implemented within a finite element (FE) framework using the user material subroutine VUMAT option available in the commercial code ABAQUS. Experimental results from literature are used to validate the model. The predicted splitting and curling patterns as well as the load-displacement response agree well with the experimental observations. The present material model is also used… More >

Vishal Shreyans Shah¹, Henyl Rakesh Shah², Pijush Samui³, A. Ramachra Murthy⁴

CMC-Computers, Materials & Continua, Vol.44, No.2, pp. 73-84, 2014, DOI:10.3970/cmc.2014.044.073

Abstract This paper deals with the development of models for prediction of facture parameters, namely, fracture energy and ultimate load of high strength and ultra high strength concrete based on Minimax Probability Machine Regression (MPMR) and Extreme Learning Machine (ELM). MPMR is developed based on Minimax Probability Machine Classification (MPMC). ELM is the modified version of Single Hidden Layer Feed Foreword Network (SLFN). MPMR and ELM has been used as regression techniques. Mathematical models have been developed in the form of relation between several input variables such as beam dimensions, water cement ratio, compressive strength, split tensile strength, notch depth, and… More >