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  • Open Access

    ARTICLE

    An Efficient Bar Code Image Recognition Algorithm for Sorting System

    Desheng Zheng1, *, Ziyong Ran1, Zhifeng Liu1, Liang Li2, Lulu Tian3

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1885-1895, 2020, DOI:10.32604/cmc.2020.010070

    Abstract In the sorting system of the production line, the object movement, fixed angle of view, light intensity and other reasons lead to obscure blurred images. It results in bar code recognition rate being low and real time being poor. Aiming at the above problems, a progressive bar code compressed recognition algorithm is proposed. First, assuming that the source image is not tilted, use the direct recognition method to quickly identify the compressed source image. Failure indicates that the compression ratio is improper or the image is skewed. Then, the source image is enhanced to identify the source image directly. Finally,… More >

  • Open Access

    ARTICLE

    Chinese Spirits Identification Model Based on Mid-Infrared Spectrum

    Wu Zeng1, Zhanxiong Huo1, *, Yuxuan Xie2, Yingxiang Jiang1, Kun Hu1

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1869-1883, 2020, DOI:10.32604/cmc.2020.010139

    Abstract Applying computer technology to the field of food safety, and how to identify liquor quickly and accurately, is of vital importance and has become a research focus. In this paper, sparse principal component analysis (SPCA) was applied to seek sparse factors of the mid-infrared (MIR) spectra of five famous vintage year Chinese spirits. The results showed while meeting the maximum explained variance, 23 sparse principal components (PCs) were selected as features in a support vector machine (SVM) model, which obtained a 97% classification accuracy. By comparison principal component analysis (PCA) selected 10 PCs as features but only achieved an 83%… More >

  • Open Access

    ARTICLE

    Predictive Control Algorithm for Urban Rail Train Brake Control System Based on T-S Fuzzy Model

    Xiaokan Wang1, 2, *, Qiong Wang2, Shuang Liang3

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1859-1867, 2020, DOI:10.32604/cmc.2020.011032

    Abstract Urban rail transit has the advantages of large traffic capacity, high punctuality and zero congestion, and it plays an increasingly important role in modern urban life. Braking system is an important system of urban rail train, which directly affects the performance and safety of train operation and impacts passenger comfort. The braking performance of urban rail trains is directly related to the improvement of train speed and transportation capacity. Also, urban rail transit has the characteristics of high speed, short station distance, frequent starting, and frequent braking. This makes the braking control system constitute a time-varying, time-delaying and nonlinear control… More >

  • Open Access

    ARTICLE

    Prophet_TD Routing Algorithm Based on Historical Throughput and Encounter Duration

    Jingjian Chen1, Gang Xu1, *, Fengqi Wei1, Liqiang He2

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1845-1858, 2020, DOI:10.32604/cmc.2020.010010

    Abstract Opportunistic networks are self-organizing networks that do not require a complete path between the source node and the destination node as it uses encounter opportunities brought by nodes movement to achieve network communication. Opportunistic networks routing algorithms are numerous and can be roughly divided into four categories based on different forwarding strategies. The Prophet routing algorithm is an important routing algorithm in opportunistic networks. It forwards messages based on the encounter probability between nodes, and has good innovation significance and optimization potential. However, the Prophet routing algorithm does not consider the impact of the historical throughput of the node on… More >

  • Open Access

    ARTICLE

    High Accuracy Network Cardinalities Estimation by Step Sampling Revision on GPU

    Jie Xu1, *, Qun Wang1, Yifan Wang1, Khan Asif2

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1819-1844, 2020, DOI:10.32604/cmc.2020.010727

    Abstract Host cardinality estimation is an important research field in network management and network security. The host cardinality estimation algorithm based on the linear estimator array is a common method. Existing algorithms do not take memory footprint into account when selecting the number of estimators used by each host. This paper analyzes the relationship between memory occupancy and estimation accuracy and compares the effects of different parameters on algorithm accuracy. The cardinality estimating algorithm is a kind of random algorithm, and there is a deviation between the estimated results and the actual cardinalities. The deviation is affected by some systematical factors,… More >

  • Open Access

    ARTICLE

    Privacy Protection for Medical Images Based on DenseNet and Coverless Steganography

    Yun Tan1, Jiaohua Qin1, *, Hao Tang2, Xuyu Xiang1, Ling Tan2, Neal N. Xiong3

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1797-1817, 2020, DOI:10.32604/cmc.2020.010802

    Abstract With the development of the internet of medical things (IoMT), the privacy protection problem has become more and more critical. In this paper, we propose a privacy protection scheme for medical images based on DenseNet and coverless steganography. For a given group of medical images of one patient, DenseNet is used to regroup the images based on feature similarity comparison. Then the mapping indexes can be constructed based on LBP feature and hash generation. After mapping the privacy information with the hash sequences, the corresponding mapped indexes of secret information will be packed together with the medical images group and… More >

  • Open Access

    ARTICLE

    Using Object Detection Network for Malware Detection and Identification in Network Traffic Packets

    Chunlai Du1, Shenghui Liu1, Lei Si2, Yanhui Guo2, *, Tong Jin1

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1785-1796, 2020, DOI:10.32604/cmc.2020.010091

    Abstract In recent years, the number of exposed vulnerabilities has grown rapidly and more and more attacks occurred to intrude on the target computers using these vulnerabilities such as different malware. Malware detection has attracted more attention and still faces severe challenges. As malware detection based traditional machine learning relies on exports’ experience to design efficient features to distinguish different malware, it causes bottleneck on feature engineer and is also time-consuming to find efficient features. Due to its promising ability in automatically proposing and selecting significant features, deep learning has gradually become a research hotspot. In this paper, aiming to detect… More >

  • Open Access

    ARTICLE

    Directional Modulation Based on a Quantum Genetic Algorithm for a Multiple-Reflection Model

    Yuwei Huang1, 2, Xiubo Chen1, 3, *, Kaiguo Yuan1, 3, Jianyi Zhang4, Biao Liu2

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1771-1783, 2020, DOI:10.32604/cmc.2020.09905

    Abstract Directional modulation is one of the hot topics in data security researches. To fulfill the requirements of communication security in wireless environment with multiple paths, this study takes into account the factors of reflections and antenna radiation pattern for directional modulation. Unlike other previous works, a novel multiple-reflection model, which is more realistic and complex than simplified two-ray reflection models, is proposed based on two reflectors. Another focus is a quantum genetic algorithm applied to optimize antenna excitation in a phased directional modulation antenna array. The quantum approach has strengths in convergence speed and the globe searching ability for the… More >

  • Open Access

    ARTICLE

    Adversarial Attacks on Content-Based Filtering Journal Recommender Systems

    Zhaoquan Gu1, Yinyin Cai1, Sheng Wang1, Mohan Li1, *, Jing Qiu1, Shen Su1, Xiaojiang Du1, Zhihong Tian1

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1755-1770, 2020, DOI:10.32604/cmc.2020.010739

    Abstract Recommender systems are very useful for people to explore what they really need. Academic papers are important achievements for researchers and they often have a great deal of choice to submit their papers. In order to improve the efficiency of selecting the most suitable journals for publishing their works, journal recommender systems (JRS) can automatically provide a small number of candidate journals based on key information such as the title and the abstract. However, users or journal owners may attack the system for their own purposes. In this paper, we discuss about the adversarial attacks against content-based filtering JRS. We… More >

  • Open Access

    ARTICLE

    Applying Feature-Weighted Gradient Decent K-Nearest Neighbor to Select Promising Projects for Scientific Funding

    Chuqing Zhang1, Jiangyuan Yao2, *, Guangwu Hu3, Thomas Schøtt4

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1741-1753, 2020, DOI:10.32604/cmc.2020.010306

    Abstract Due to its outstanding ability in processing large quantity and high-dimensional data, machine learning models have been used in many cases, such as pattern recognition, classification, spam filtering, data mining and forecasting. As an outstanding machine learning algorithm, K-Nearest Neighbor (KNN) has been widely used in different situations, yet in selecting qualified applicants for winning a funding is almost new. The major problem lies in how to accurately determine the importance of attributes. In this paper, we propose a Feature-weighted Gradient Decent K-Nearest Neighbor (FGDKNN) method to classify funding applicants in to two types: approved ones or not approved ones.… More >

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