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  • Open Access

    ARTICLE

    Reversible Data Hiding in Classification-Scrambling Encrypted-Image Based on Iterative Recovery

    Yuyu Chen1, Bangxu Yin2, Hongjie He2, Shu Yan2, Fan Chen2,*, Hengming Tai3

    CMC-Computers, Materials & Continua, Vol.56, No.2, pp. 299-312, 2018, DOI: 10.3970/cmc.2018.03179

    Abstract To improve the security and quality of decrypted images, this work proposes a reversible data hiding in encrypted image based on iterative recovery. The encrypted image is firstly generated by the pixel classification scrambling and bit-wise exclusive-OR (XOR), which improves the security of encrypted images. And then, a pixel-type-mark generation method based on block-compression is designed to reduce the extra burden of key management and transfer. At last, an iterative recovery strategy is proposed to optimize the marked decrypted image, which allows the original image to be obtained only using the encryption key. The proposed reversible data hiding scheme in… More >

  • Open Access

    ARTICLE

    Speech Resampling Detection Based on Inconsistency of Band Energy

    Zhifeng Wang1, Diqun Yan1,*, Rangding Wang1, Li Xiang1, Tingting Wu1

    CMC-Computers, Materials & Continua, Vol.56, No.2, pp. 247-259, 2018, DOI: 10.3970/cmc.2018.02902

    Abstract Speech resampling is a typical tempering behavior, which is often integrated into various speech forgeries, such as splicing, electronic disguising, quality faking and so on. By analyzing the principle of resampling, we found that, compared with natural speech, the inconsistency between the bandwidth of the resampled speech and its sampling ratio will be caused because the interpolation process in resampling is imperfect. Based on our observation, a new resampling detection algorithm based on the inconsistency of band energy is proposed. First, according to the sampling ratio of the suspected speech, a band-pass Butterworth filter is designed to filter out the… More >

  • Open Access

    ARTICLE

    Improved GNSS Cooperation Positioning Algorithm for Indoor Localization

    Taoyun Zhou1,2, Baowang Lian1, Siqing Yang2,*, Yi Zhang1, Yangyang Liu1,3

    CMC-Computers, Materials & Continua, Vol.56, No.2, pp. 225-245, 2018, DOI: 10.3970/cmc.2018.02671

    Abstract For situations such as indoor and underground parking lots in which satellite signals are obstructed, GNSS cooperative positioning can be used to achieve high-precision positioning with the assistance of cooperative nodes. Here we study the cooperative positioning of two static nodes, node 1 is placed on the roof of the building and the satellite observation is ideal, node 2 is placed on the indoor windowsill where the occlusion situation is more serious, we mainly study how to locate node 2 with the assistance of node 1. Firstly, the two cooperative nodes are located with pseudo-range single point positioning, and the… More >

  • Open Access

    ARTICLE

    Coverless Steganography for Digital Images Based on a Generative Model

    Xintao Duan1,*, Haoxian Song1, Chuan Qin2, Muhammad Khurram Khan3

    CMC-Computers, Materials & Continua, Vol.55, No.3, pp. 483-493, 2018, DOI: 10.3970/cmc.2018.01798

    Abstract In this paper, we propose a novel coverless image steganographic scheme based on a generative model. In our scheme, the secret image is first fed to the generative model database, to generate a meaning-normal and independent image different from the secret image. The generated image is then transmitted to the receiver and fed to the generative model database to generate another image visually the same as the secret image. Thus, we only need to transmit the meaning-normal image which is not related to the secret image, and we can achieve the same effect as the transmission of the secret image.… More >

  • Open Access

    ARTICLE

    A Spark Scheduling Strategy for Heterogeneous Cluster

    Xuewen Zhang1, Zhonghao Li1, Gongshen Liu1,*, Jiajun Xu1, Tiankai Xie2, Jan Pan Nees1

    CMC-Computers, Materials & Continua, Vol.55, No.3, pp. 405-417, 2018, DOI: 10.3970/cmc.2018.02527

    Abstract As a main distributed computing system, Spark has been used to solve problems with more and more complex tasks. However, the native scheduling strategy of Spark assumes it works on a homogenized cluster, which is not so effective when it comes to heterogeneous cluster. The aim of this study is looking for a more effective strategy to schedule tasks and adding it to the source code of Spark. After investigating Spark scheduling principles and mechanisms, we developed a stratifying algorithm and a node scheduling algorithm is proposed in this paper to optimize the native scheduling strategy of Spark. In this… More >

  • Open Access

    ARTICLE

    Controlled Cyclic Remote State Preparation of Arbitrary Qubit States

    Mingming Wang1,2,*, Chen Yang1, Reza Mousoli3

    CMC-Computers, Materials & Continua, Vol.55, No.2, pp. 321-329, 2018, DOI:10.3970/cmc.2018.02064

    Abstract Quantum secure communications could securely transmit quantum information by using quantum resource. Recently, novel applications such as bidirectional and asymmetric quantum protocols have been developed. In this paper, we propose a new method for generating entanglement which is highly useful for multiparty quantum communications such as teleportation and Remote State Preparation (RSP). As one of its applications, we propose a new type of quantum secure communications, i.e. cyclic RSP protocols. Starting from a four-party controlled cyclic RSP protocol of one-qubit states, we show that this cyclic protocol can be generalized to a multiparty controlled cyclic RSP protocol for preparation of… More >

  • Open Access

    ARTICLE

    Semi-Supervised Learning with Generative Adversarial Networks on Digital Signal Modulation Classification

    Ya Tu1, Yun Lin1, Jin Wang2,3,*, Jeong-Uk Kim4

    CMC-Computers, Materials & Continua, Vol.55, No.2, pp. 243-254, 2018, DOI:10.3970/cmc.2018.01755

    Abstract Deep Learning (DL) is such a powerful tool that we have seen tremendous success in areas such as Computer Vision, Speech Recognition, and Natural Language Pro-cessing. Since Automated Modulation Classification (AMC) is an important part in Cognitive Radio Networks, we try to explore its potential in solving signal modula-tion recognition problem. It cannot be overlooked that DL model is a complex mod-el, thus making them prone to over-fitting. DL model requires many training data to combat with over-fitting, but adding high quality labels to training data manually is not always cheap and accessible, especially in real-time system, which may counter… More >

  • Open Access

    ARTICLE

    Identifying Materials of Photographic Images and Photorealistic Computer Generated Graphics Based on Deep CNNs

    Qi Cui1,2,*, Suzanne McIntosh3, Huiyu Sun3

    CMC-Computers, Materials & Continua, Vol.55, No.2, pp. 229-241, 2018, DOI:10.3970/cmc.2018.01693

    Abstract Currently, some photorealistic computer graphics are very similar to photographic images. Photorealistic computer generated graphics can be forged as photographic images, causing serious security problems. The aim of this work is to use a deep neural network to detect photographic images (PI) versus computer generated graphics (CG). In existing approaches, image feature classification is computationally intensive and fails to achieve real-time analysis. This paper presents an effective approach to automatically identify PI and CG based on deep convolutional neural networks (DCNNs). Compared with some existing methods, the proposed method achieves real-time forensic tasks by deepening the network structure. Experimental results… More >

  • Open Access

    ARTICLE

    Adversarial Learning for Distant Supervised Relation Extraction

    Daojian Zeng1,3, Yuan Dai1,3, Feng Li1,3, R. Simon Sherratt2, Jin Wang3,*

    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 >

  • Open Access

    ARTICLE

    The Interface Stress Field in the Elastic System Consisting of the Hollow Cylinder and Surrounding Elastic Medium Under 3D Non-axisymmetric Forced Vibration

    Surkay D. Akbarov1, 2, *, Mahir A. Mehdiyev3

    CMC-Computers, Materials & Continua, Vol.54, No.1, pp. 61-81, 2018, DOI:10.3970/cmc.2018.054.061

    Abstract The paper develops and employs analytical-numerical solution method for the study of the time-harmonic dynamic stress field in the system consisting of the hollow cylinder and surrounding elastic medium under the non-axisymmetric forced vibration of this system. It is assumed that in the interior of the hollow cylinder the point-located with respect to the cylinder axis, non-axisymmetric with respect to the circumferential direction and uniformly distributed time-harmonic forces act. Corresponding boundary value problem is solved by employing of the exponential Fourier transformation with respect to the axial coordinate and by employing of the Fourier series expansion of these transformations. Numerical… More >

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