Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (21,887)
  • Open Access

    ARTICLE

    Reversible Data Hiding Based on Run-Level Coding in H.264/AVC Video Streams

    Yi Chen1, Hongxia Wang2, *, Xuyun Zhang3

    CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 911-922, 2020, DOI:10.32604/cmc.2020.08027

    Abstract This paper presents a reversible data hiding (RDH) method, which is designed by combining histogram modification (HM) with run-level coding in H.264/advanced video coding (AVC). In this scheme, the run-level is changed for embedding data into H.264/AVC video sequences. In order to guarantee the reversibility of the proposed scheme, the last nonzero quantized discrete cosine transform (DCT) coefficients in embeddable 4×4 blocks are shifted by the technology of histogram modification. The proposed scheme is realized after quantization and before entropy coding of H.264/AVC compression standard. Therefore, the embedded information can be correctly extracted at the decoding side. Peak-signal-noise-to-ratio (PSNR) and… More >

  • Open Access

    ARTICLE

    Within-Project and Cross-Project Software Defect Prediction Based on Improved Transfer Naive Bayes Algorithm

    Kun Zhu1, Nana Zhang1, Shi Ying1, *, Xu Wang2

    CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 891-910, 2020, DOI:10.32604/cmc.2020.08096

    Abstract With the continuous expansion of software scale, software update and maintenance have become more and more important. However, frequent software code updates will make the software more likely to introduce new defects. So how to predict the defects quickly and accurately on the software change has become an important problem for software developers. Current defect prediction methods often cannot reflect the feature information of the defect comprehensively, and the detection effect is not ideal enough. Therefore, we propose a novel defect prediction model named ITNB (Improved Transfer Naive Bayes) based on improved transfer Naive Bayesian algorithm in this paper, which… More >

  • Open Access

    ARTICLE

    A Novel Quantum-Behaved Particle Swarm Optimization Algorithm

    Tao Wu1, Lei Xie1, Xi Chen2, Amir Homayoon Ashrafzadeh3, Shu Zhang4, *

    CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 873-890, 2020, DOI:10.32604/cmc.2020.07478

    Abstract The efficient management of ambulance routing for emergency requests is vital to save lives when a disaster occurs. Quantum-behaved Particle Swarm Optimization (QPSO) algorithm is a kind of metaheuristic algorithms applied to deal with the problem of scheduling. This paper analyzed the motion pattern of particles in a square potential well, given the position equation of the particles by solving the Schrödinger equation and proposed the Binary Correlation QPSO Algorithm Based on Square Potential Well (BCQSPSO). In this novel algorithm, the intrinsic cognitive link between particles’ experience information and group sharing information was created by using normal Copula function. After… More >

  • Open Access

    ARTICLE

    A Temporal Multi-Tenant RBAC Model for Collaborative Cloud Services

    Zhengtao Liu1, *, Yi Ying1, Yaqin Peng1, Jinyue Xia2

    CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 861-871, 2020, DOI:10.32604/cmc.2020.07142

    Abstract Multi-tenant collaboration brings the challenge to access control in cloud computing environment. Based on the multi-tenant role-based access control (MTRBAC) model, a Temporal MT-RBAC (TMT-RBAC) model for collaborative cloud services is proposed. It adds the time constraint between trusted tenants, including usable role time constraint based on both calendar and interval time. Analysis shows that the new model strengthens the presentation ability of MT-RBAC model, achieves the finergrained access control, reduces the management costs and enhances the security of multitenant collaboration in cloud computing environment. More >

  • Open Access

    ARTICLE

    Post-Quantum Blockchain over Lattice

    Xiao Zhang1, 2, 3, Faguo Wu1, 2, 3, Wang Yao1, 2, 3, *, Wenhua Wang4, Zhiming Zheng1, 2, 3

    CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 845-859, 2020, DOI:10.32604/cmc.2020.08008

    Abstract Blockchain is an emerging decentralized architecture and distributed computing paradigm underlying Bitcoin and other cryptocurrencies, and has recently attracted intensive attention from governments, financial institutions, high-tech enterprises, and the capital markets. Its cryptographic security relies on asymmetric cryptography, such as ECC, RSA. However, with the surprising development of quantum technology, asymmetric cryptography schemes mentioned above would become vulnerable. Recently, lattice-based cryptography scheme was proposed to be secure against attacks in the quantum era. In 2018, with the aid of Bonsai Trees technology, Yin et al. [Yin, Wen, Li et al. (2018)] proposed a lattice-based authentication method which can extend a… More >

  • Open Access

    ARTICLE

    Laboratory Model Tests and DEM Simulations of Unloading- Induced Tunnel Failure Mechanism

    Abierdi1, Yuzhou Xiang2, Haiyi Zhong2, Xin Gu2, Hanlong Liu2, 3, Wengang Zhang2, 3, *

    CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 825-844, 2020, DOI:10.32604/cmc.2020.07946

    Abstract Tunnel excavation is a complicated loading-unloading-reloading process characterized by decreased radial stresses and increased axial stresses. An approach that considers only loading, is generally used in tunnel model testing. However, this approach is incapable of characterizing the unloading effects induced by excavation on surrounding rocks and hence presents radial and tangential stress paths during the failure process that are different from the actual stress state of tunnels. This paper carried out a comparative analysis using laboratory model testing and particle flow code (PFC2D)-based numerical simulation, and shed light upon the crack propagation process and, microscopic stress and force chain variations… More >

  • Open Access

    ARTICLE

    Molecular Dynamics Simulations for Anisotropic Thermal Conductivity of Borophene

    Yue Jia1, Chun Li1, *, Jinwu Jiang2, Ning Wei3, Yang Chen4, Yongjie Jessica Zhang5

    CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 813-823, 2020, DOI:10.32604/cmc.2020.07801

    Abstract The present work carries out molecular dynamics simulations to compute the thermal conductivity of the borophene nanoribbon and the borophene nanotube using the Muller-Plathe approach. We investigate the thermal conductivity of the armchair and zigzag borophenes, and show the strong anisotropic thermal conductivity property of borophene. We compare results of the borophene nanoribbon and the borophene nanotube, and find the thermal conductivity of the borophene is orientation dependent. The thermal conductivity of the borophene does not vary as changing the width of the borophene nanoribbon and the perimeter of the borophene nanotube. In addition, the thermal conductivity of the borophene… More >

  • Open Access

    ARTICLE

    Energy Efficiency in Internet of Things: An Overview

    Wuxiong Zhang1, 2, Weidong Fang1, 2, *, Qianqian Zhao1, 2, Xiaohong Ji3, Guoqing Jia3

    CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 787-811, 2020, DOI:10.32604/cmc.2020.07620

    Abstract Energy efficiency is very important for the Internet of Things (IoT), especially for front-end sensed terminal or node. It not only embodies the node’s life, but also reflects the lifetime of the network. Meanwhile, it is also a key indicator of green communications. Unfortunately, there is no article on systematic analysis and review for energy efficiency evaluation in IoT. In this paper, we systemically analyze the architecture of IoT, and point out its energy distribution, Furthermore, we summarized the energy consumption model in IoT, analyzed the pros and cons of improving energy efficiency, presented a state of the art the… More >

  • Open Access

    ARTICLE

    OTT Messages Modeling and Classification Based on Recurrent Neural Networks

    Guangyong Yang1, Jianqiu Zeng1, Mengke Yang2, *, Yifei Wei3, Xiangqing Wang3, Zulfiqar Hussain Pathan4

    CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 769-785, 2020, DOI:10.32604/cmc.2020.07528

    Abstract A vast amount of information has been produced in recent years, which brings a huge challenge to information management. The better usage of big data is of important theoretical and practical significance for effectively addressing and managing messages. In this paper, we propose a nine-rectangle-grid information model according to the information value and privacy, and then present information use policies based on the rough set theory. Recurrent neural networks were employed to classify OTT messages. The content of user interest is effectively incorporated into the classification process during the annotation of OTT messages, ending with a reliable trained classification model.… More >

  • Open Access

    ARTICLE

    Improvement of Stochastic Competitive Learning for Social Network

    Wenzheng Li1, Yijun Gu1, *

    CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 755-768, 2020, DOI:10.32604/cmc.2020.07984

    Abstract As an unsupervised learning method, stochastic competitive learning is commonly used for community detection in social network analysis. Compared with the traditional community detection algorithms, it has the advantage of realizing the timeseries community detection by simulating the community formation process. In order to improve the accuracy and solve the problem that several parameters in stochastic competitive learning need to be pre-set, the author improves the algorithms and realizes improved stochastic competitive learning by particle position initialization, parameter optimization and particle domination ability self-adaptive. The experiment result shows that each improved method improves the accuracy of the algorithm, and the… More >

Displaying 15081-15090 on page 1509 of 21887. Per Page