Yan Chang^1,*, Shibin Zhang¹, Lili Yan¹, Guihua Han¹, Haiquan Song¹, Yan Zhang¹, Xueyang Li¹, Qirun Wang²

CMC-Computers, Materials & Continua, Vol.59, No.3, pp. 1005-1014, 2019, DOI:10.32604/cmc.2019.06297

Abstract Quantum authorization management (QAM) is the quantum scheme for privilege management infrastructure (PMI) problem. Privilege management (authorization management) includes authentication and authorization. Authentication is to verify a user’s identity. Authorization is the process of verifying that a authenticated user has the authority to perform a operation, which is more fine-grained. In most classical schemes, the authority management center (AMC) manages the resources permissions for all network nodes within the jurisdiction. However, the existence of AMC may be the weakest link of the whole scheme. In this paper, a protocol for QAM without AMC is proposed based on entanglement swapping. In… More >

Xiang Li¹, Mei-E Fang^1,2,*, QIan Qi²

CMES-Computer Modeling in Engineering & Sciences, Vol.120, No.1, pp. 45-62, 2019, DOI:10.32604/cmes.2019.05659

Abstract In this article, we adopt the C-type spline of degree 2 to model and blend basic shapes including conics and circle arcs. The C-type spline belongs to the ωB-spline category of splines that are capable of blending polynomial, trigonometric and hyperbolic functions. Commonly used basic shapes can be exactly represented by these types of splines. We derive explicit formulas for the convenience of modeling the basic curves. The entire blending curve is C¹-continuous. In comparison with the existing best blending method by rational G² splines, which are rational splines of degree 3, the proposed method allows simpler representation and blending… More >

Liqiang Lin¹, Xianqiao Wang², Xiaowei Zeng^1,3

CMES-Computer Modeling in Engineering & Sciences, Vol.98, No.2, pp. 203-220, 2014, DOI:10.3970/cmes.2014.098.203

Abstract The Voronoi tessellation is employed to describe cellular patterns and to simulate cell division and cell remodeling in epithelial tissue. First, Halton sequence is utilized to generate the random generators of Voronoi cell points. The centroidal Voronoi cell center is obtained by probabilistic Lloyd's method and polygonal structure of cell distribution is modeled. Based on the polygonal shape of cells, the instantaneous mechanism of cell division is applied to simulate the cell proliferation and remodeling. Four kinds of single-cell division algorithms are designed with the consideration of cleavage angle. From these simulations, we find that cell topological structure varies case… More >

Chein-Shan Liu¹

CMES-Computer Modeling in Engineering & Sciences, Vol.80, No.1, pp. 57-86, 2011, DOI:10.3970/cmes.2011.080.057

Abstract Based-on the ordinary differential equations defined on an invariant manifold, we propose a theoretical procedure to derive a Relaxed Steepest Descent Method (RSDM) for numerically solving an ill-posed system of linear equations when the data are polluted by random noise. The invariant manifold is defined in terms of a squared-residual-norm and a fictitious time-like variable, and in the final stage we can derive an iterative algorithm including a parameter, which is known as the relaxation parameter. Through a Hopf bifurcation, this parameter indeed plays a major role to switch the situation of slow convergence to a new situation with faster… 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 >

Daojian Zeng^1,3, Yuan Dai^1,3, Feng Li^1,3, R. Simon Sherratt², Jin Wang^3,*

CMC-Computers, Materials & Continua, Vol.55, No.1, pp. 121-136, 2018, DOI:10.3970/cmc.2018.055.121

Abstract Recently, many researchers have concentrated on using neural networks to learn features for Distant Supervised Relation Extraction (DSRE). These approaches generally use a softmax classifier with cross-entropy loss, which inevitably brings the noise of artificial class NA into classification process. To address the shortcoming, the classifier with ranking loss is employed to DSRE. Uniformly randomly selecting a relation or heuristically selecting the highest score among all incorrect relations are two common methods for generating a negative class in the ranking loss function. However, the majority of the generated negative class can be easily discriminated from positive class and will contribute… More >

Wenyan Liu¹, Xiangyang Luo^1,*, Yimin Liu¹, Jianqiang Liu², Minghao Liu¹, Yun Q. Shi³

CMC-Computers, Materials & Continua, Vol.55, No.1, pp. 71-93, 2018, DOI:10.3970/cmc.2018.055.071

Abstract Precise localization techniques for indoor Wi-Fi access points (APs) have important application in the security inspection. However, due to the interference of environment factors such as multipath propagation and NLOS (Non-Line-of-Sight), the existing methods for localization indoor Wi-Fi access points based on RSS ranging tend to have lower accuracy as the RSS (Received Signal Strength) is difficult to accurately measure. Therefore, the localization algorithm of indoor Wi-Fi access points based on the signal strength relative relationship and region division is proposed in this paper. The algorithm hierarchically divide the room where the target Wi-Fi AP is located, on the region… More >