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  • Open Access

    ARTICLE

    Message Authentication with a New Quantum Hash Function

    Yalan Wang1,2, Yuling Chen1,*, Haseeb Ahmad3, Zhanhong Wei4

    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 635-648, 2019, DOI:10.32604/cmc.2019.05251

    Abstract To ensure the security during the communication, we often adopt different ways to encrypt the messages to resist various attacks. However, with the computing power improving, the existing encryption and authentication schemes are being faced with big challenges. We take the message authentication as an example into a careful consideration. Then, we proposed a new message authentication scheme with the Advanced Encryption Standard as the encryption function and the new quantum Hash function as the authentication function. Firstly, the Advanced Encryption Standard algorithm is used to encrypt the result of the initial message cascading the corresponding Hash values, which ensures… More >

  • Open Access

    ARTICLE

    A Multi-Feature Weighting Based K-Means Algorithm for MOOC Learner Classification

    Yuqing Yang1,2, Dequn Zhou1,*, Xiaojiang Yang1,3,4

    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 625-633, 2019, DOI:10.32604/cmc.2019.05246

    Abstract Massive open online courses (MOOC) have recently gained worldwide attention in the field of education. The manner of MOOC provides a new option for learning various kinds of knowledge. A mass of data miming algorithms have been proposed to analyze the learner’s characteristics and classify the learners into different groups. However, most current algorithms mainly focus on the final grade of the learners, which may result in an improper classification. To overcome the shortages of the existing algorithms, a novel multi-feature weighting based K-means (MFWK-means) algorithm is proposed in this paper. Correlations between the widely used feature grade and other… More >

  • Open Access

    ARTICLE

    Analysis and Improvement of Steganography Protocol Based on Bell States in Noise Environment

    Zhiguo Qu1,*, Shengyao Wu2, Wenjie Liu1, Xiaojun Wang3

    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 607-624, 2019, DOI:10.32604/cmc.2019.02656

    Abstract In the field of quantum communication, quantum steganography is an important branch of quantum information hiding. In a realistic quantum communication system, quantum noises are unavoidable and will seriously impact the safety and reliability of the quantum steganographic system. Therefore, it is very important to analyze the influence of noise on the quantum steganography protocol and how to reduce the effect of noise. This paper takes the quantum steganography protocol proposed in 2010 as an example to analyze the effects of noises on information qubits and secret message qubits in the four primary quantum noise environments. The results show that… More >

  • Open Access

    ARTICLE

    A Noise-Resistant Superpixel Segmentation Algorithm for Hyperspectral Images

    Peng Fu1,2, Qianqian Xu1, Jieyu Zhang3, Leilei Geng4,*

    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 509-515, 2019, DOI:10.32604/cmc.2019.05250

    Abstract The superpixel segmentation has been widely applied in many computer vision and image process applications. In recent years, amount of superpixel segmentation algorithms have been proposed. However, most of the current algorithms are designed for natural images with little noise corrupted. In order to apply the superpixel algorithms to hyperspectral images which are always seriously polluted by noise, we propose a noise-resistant superpixel segmentation (NRSS) algorithm in this paper. In the proposed NRSS, the spectral signatures are first transformed into frequency domain to enhance the noise robustness; then the two widely spectral similarity measures-spectral angle mapper (SAM) and spectral information… More >

  • Open Access

    ARTICLE

    Maximum Data Generation Rate Routing Protocol Based on Data Flow Controlling Technology for Rechargeable Wireless Sensor Networks

    Demin Gao1, 2, *, Shuo Zhang1, Fuquan Zhang1, Xijian Fan1, Jinchi Zhang1,∗

    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 649-667, 2019, DOI:10.32604/cmc.2019.05195

    Abstract For rechargeable wireless sensor networks, limited energy storage capacity, dynamic energy supply, low and dynamic duty cycles cause that it is unpractical to maintain a fixed routing path for packets delivery permanently from a source to destination in a distributed scenario. Therefore, before data delivery, a sensor has to update its waking schedule continuously and share them to its neighbors, which lead to high energy expenditure for reestablishing path links frequently and low efficiency of energy utilization for collecting packets. In this work, we propose the maximum data generation rate routing protocol based on data flow controlling technology. For a… More >

  • Open Access

    ARTICLE

    Feedback LSTM Network Based on Attention for Image Description Generator

    Zhaowei Qu1,*, Bingyu Cao1, Xiaoru Wang1, Fu Li2, Peirong Xu1, Luhan Zhang1

    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 575-589, 2019, DOI:10.32604/cmc.2019.05569

    Abstract Images are complex multimedia data which contain rich semantic information. Most of current image description generator algorithms only generate plain description, with the lack of distinction between primary and secondary object, leading to insufficient high-level semantic and accuracy under public evaluation criteria. The major issue is the lack of effective network on high-level semantic sentences generation, which contains detailed description for motion and state of the principal object. To address the issue, this paper proposes the Attention-based Feedback Long Short-Term Memory Network (AFLN). Based on existing codec framework, there are two independent sub tasks in our method: attention-based feedback LSTM… More >

  • Open Access

    ARTICLE

    A Distributed ADMM Approach for Collaborative Regression Learning in Edge Computing

    Yangyang Li1, Xue Wang2, Weiwei Fang2,*, Feng Xue2, Hao Jin1, Yi Zhang1, Xianwei Li3

    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 493-508, 2019, DOI:10.32604/cmc.2019.05178

    Abstract With the recent proliferation of Internet-of-Things (IoT), enormous amount of data are produced by wireless sensors and connected devices at the edge of network. Conventional cloud computing raises serious concerns on communication latency, bandwidth cost, and data privacy. To address these issues, edge computing has been introduced as a new paradigm that allows computation and analysis to be performed in close proximity with data sources. In this paper, we study how to conduct regression analysis when the training samples are kept private at source devices. Specifically, we consider the lasso regression model that has been widely adopted for prediction and… More >

  • Open Access

    ARTICLE

    Waveband Selection with Equivalent Prediction Performance for FTIR/ATR Spectroscopic Analysis of COD in Sugar Refinery Waste Water

    Jun Xie1, Dapeng Sun1, Jiaxiang Cai2, Fuhong Cai1,*

    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 687-695, 2019, DOI:10.32604/cmc.2019.03658

    Abstract The level of chemical oxygen demand (COD) is an important index to evaluate whether sewage meets the discharge requirements, so corresponding tests should be carried out before discharge. Fourier transform infrared spectroscopy (FTIR) and attenuated total reflectance (ATR) can detect COD in sewage effectively, which has advantages over conventional chemical analysis methods. And the selection of characteristic bands was one of the key links in the application of FTIR/ATR spectroscopy. In this work, based on the moving window partial least-squares (MWPLS) regression to select a characteristic wavelength, a method of equivalent wavelength selection was proposed combining with paired t-test equivalent… More >

  • Open Access

    ARTICLE

    Novel Approach for Automatic Region of Interest and Seed Point Detection in CT Images Based on Temporal and Spatial Data

    Zhe Liu1, Charlie Maere1,*, Yuqing Song1

    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 669-686, 2019, DOI:10.32604/cmc.2019.04590

    Abstract Accurately finding the region of interest is a very vital step for segmenting organs in medical image processing. We propose a novel approach of automatically identifying region of interest in Computed Tomography Image (CT) images based on temporal and spatial data . Our method is a 3 stages approach, 1) We extract organ features from the CT images by adopting the Hounsfield filter. 2)We use these filtered features and introduce our novel approach of selecting observable feature candidates by calculating contours’ area and automatically detect a seed point. 3) We use a novel approach to track the growing region changes… More >

  • Open Access

    ARTICLE

    Dependency-Based Local Attention Approach to Neural Machine Translation

    Jing Qiu1, Yan Liu2, Yuhan Chai2, Yaqi Si2, Shen Su1, ∗, Le Wang1, ∗, Yue Wu3

    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 547-562, 2019, DOI:10.32604/cmc.2019.05892

    Abstract Recently dependency information has been used in different ways to improve neural machine translation. For example, add dependency labels to the hidden states of source words. Or the contiguous information of a source word would be found according to the dependency tree and then be learned independently and be added into Neural Machine Translation (NMT) model as a unit in various ways. However, these works are all limited to the use of dependency information to enrich the hidden states of source words. Since many works in Statistical Machine Translation (SMT) and NMT have proven the validity and potential of using… More >

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