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  • Open Access

    ARTICLE

    Analyzing Dynamic Change in Social Network Based on Distribution-Free Multivariate Process Control Method

    Yan Liu1,*, Lian Liu1, Yu Yan2, Hao Feng1, Shichang Ding3

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1123-1139, 2019, DOI:10.32604/cmc.2019.05619

    Abstract Social organizations can be represented by social network because it can mathematically quantify and represent complex interrelated organizational behavior. Exploring the change in dynamic social network is essential for the situation awareness of the corresponding social organization. Social network usually evolves gradually and slightly, which is hard to be noticed. The statistical process control techniques in industry field have been used to distinguish the statistically significant change of social network. But the original method is narrowed due to some limitation on measures. This paper presents a generic framework to address the change detection problem in dynamic social network and introduces… More >

  • Open Access

    ARTICLE

    Data Based Violated Behavior Analysis of Taxi Driver in Metropolis in China

    Jiao Yao1, Yiling Ni1, Jing Zhao2, Huiwei Niu1, Shanyong Liu1, Yuhui Zheng3, Jin Wang4,5,*

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1109-1122, 2019, DOI:10.32604/cmc.2019.06252

    Abstract Violation probability of taxi drivers in metropolis is far more than that of normal drivers because they are labor-intensive, overconfident of self-driving skill, and always searching potential customers, sometimes even picking up or dropping off passengers randomly. In this paper, four types of violated behavior of taxi drivers in metropolis were first summarized, based on which corresponding scale table was initial designed with social statistical method. Furthermore, with certain samples, relative item analysis, exploratory factor analysis, validity analysis and reliability analysis were conducted to verify validity of the initial scale table, based on which some improvements were made, and we… More >

  • Open Access

    ARTICLE

    An Adaptive Superpixel Tracker Using Multiple Features

    Jingjing Liu1,2, Bin Zhang3, Xu Cheng4, Ying Chen5, Li Zhao1,*

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1097-1108, 2019, DOI:10.32604/cmc.2019.05968

    Abstract Visual tracking is a challenging issue in the field of computer vision due to the objects’ intricate appearance variation. To adapt the change of the appearance, multiple channel features which could provide more information are used. However, the low level feature could not represent the structure of the object. In this paper, a superpixel-based adaptive tracking algorithm by using color histogram and haar-like feature is proposed, whose feature is classified into the middle level. Based on the superpixel representation of video frames, the haar-like feature is extracted at the superpixel level as the local feature, and the color histogram feature… More >

  • Open Access

    ARTICLE

    Researching the Link Between the Geometric and Rènyi Discord for Special Canonical Initial States Based on Neural Network Method

    Xiaoyu Li1, Qinsheng Zhu2,*, Qingyu Meng2, Caishu You1, Mingzheng Zhu1, Yong Hu2, Yiming Huang1,3, Hao Wu2, Desheng Zheng4

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1087-1095, 2019, DOI:10.32604/cmc.2019.06060

    Abstract Quantum correlation which is different to the entanglement and classical correlation plays important role in quantum information field. In our setup, neural network method is adopted to simulate the link between the Rènyi discord (α = 2) and the geometric discord (Bures distance) for special canonical initial states in order to show the consistency of physical results for different quantification methods. Our results are useful for studying the differences and commonalities of different quantizing methods of quantum correlation. More >

  • Open Access

    ARTICLE

    Few-Shot Learning with Generative Adversarial Networks Based on WOA13 Data

    Xin Li1,2, Yanchun Liang1,2, Minghao Zhao1,2, Chong Wang1,2,3, Yu Jiang1,2,*

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1073-1085, 2019, DOI:10.32604/cmc.2019.05929

    Abstract In recent years, extreme weather events accompanying the global warming have occurred frequently, which brought significant impact on national economic and social development. The ocean is an important member of the climate system and plays an important role in the occurrence of climate anomalies. With continuous improvement of sensor technology, we use sensors to acquire the ocean data for the study on resource detection and disaster prevention, etc. However, the data acquired by the sensor is not enough to be used directly by researchers, so we use the Generative Adversarial Network (GAN) to enhance the ocean data. We use GAN… More >

  • Open Access

    ARTICLE

    Attention-Aware Network with Latent Semantic Analysis for Clothing Invariant Gait Recognition

    Hefei Ling1, Jia Wu1, Ping Li1,*, Jialie Shen2

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1041-1054, 2019, DOI:10.32604/cmc.2019.05605

    Abstract Gait recognition is a complicated task due to the existence of co-factors like carrying conditions, clothing, viewpoints, and surfaces which change the appearance of gait more or less. Among those co-factors, clothing analysis is the most challenging one in the area. Conventional methods which are proposed for clothing invariant gait recognition show the body parts and the underlying relationships from them are important for gait recognition. Fortunately, attention mechanism shows dramatic performance for highlighting discriminative regions. Meanwhile, latent semantic analysis is known for the ability of capturing latent semantic variables to represent the underlying attributes and capturing the relationships from… More >

  • Open Access

    ARTICLE

    Non-Contact Real-Time Heart Rate Measurement Algorithm Based on PPG-Standard Deviation

    Jiancheng Zou1,*, Tianshu Chen1, Xin Yang2

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1029-1040, 2019, DOI:10.32604/cmc.2019.05793

    Abstract Heart rate is an important physiological parameter for clinical diagnosis, it can infer the health of the human body. Thus, efficient and accurate heart rate measurement is important for disease diagnosis and health monitoring. There are two ways to measure heart rate. One is contact type and the other is non-contact. Contact measurement methods include pulse cutting, electrocardiogram, etc. Because of the inconvenience of this method, a non-contact heart rate method has been proposed. Traditional non-contact measurement method based on image is collecting RGB three-channel signals in continuous video and selecting the average value of the green channel pixels as… More >

  • Open Access

    ARTICLE

    Research on Public Opinion Propagation Model in Social Network Based on Blockchain

    Gengxin Sun1,*, Sheng Bin1, Meng Jiang2, Ning Cao3, Zhiyong Zheng4, Hongyan Zhao5, Dongbo Wang6, Lina Xu7

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1015-1027, 2019, DOI:10.32604/cmc.2019.05644

    Abstract With the emergence and development of blockchain technology, a new type of social networks based on blockchain had emerged. In these social networks high quality content creators, filters and propagators can all be reasonably motivated. Due to the transparency and traceability brought by blockchain technology, the public opinion propagation in such social networks presents new characteristics and laws. Based on the theory of network propagation and blockchain, a new public opinion propagation model for this kind of social network based on blockchain technology is proposed in this paper. The model considers the effect of incentive mechanism produced by reasonably quantifying… More >

  • Open Access

    ARTICLE

    A Recommendation System Based on Fusing Boosting Model and DNN Model

    Aziguli Wulam1,2, Yingshuai Wang1,2, Dezheng Zhang1,2,*, Jingyue Sang3, Alan Yang4

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1003-1013, 2019, DOI:10.32604/cmc.2019.07704

    Abstract In recent years, the models combining traditional machine learning with the deep learning are applied in many commodity recommendation practices. It has been proved better performance by the means of the neural network. Feature engineering has been the key to the success of many click rate estimation model. As we know, neural networks are able to extract high-order features automatically, and traditional linear models are able to extract low-order features. However, they are not necessarily efficient in learning all types of features. In traditional machine learning, gradient boosting decision tree is a typical representative of the tree model, which can… More >

  • Open Access

    ARTICLE

    Research on Sensor Network Coverage Enhancement Based on Non-Cooperative Games

    Chaofan Duan1, Jing Feng1,*, Haotian Chang1, Jianping Pan2, Liming Duan1

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 989-1002, 2019, DOI:10.32604/cmc.2019.06033

    Abstract Coverage is an important issue for resources rational allocation, cognitive tasks completion in sensor networks. The mobility, communicability and learning ability of smart sensors have received much attention in the past decade. Based on the deep study of game theory, a mobile sensor non-cooperative game model is established for the sensor network deployment and a local information-based topology control (LITC) algorithm for coverage enhancement is proposed. We both consider revenue of the monitoring events and neighboring sensors to avoid nodes aggregation when formulating the utility function. We then prove that the non-cooperative game is an exact potential game in which… More >

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