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  • Open Access

    ARTICLE

    Tibetan Multi-Dialect Speech and Dialect Identity Recognition

    Yue Zhao1, Jianjian Yue1, Wei Song1,*, Xiaona Xu1, Xiali Li1, Licheng Wu1, Qiang Ji2

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1223-1235, 2019, DOI:10.32604/cmc.2019.05636

    Abstract Tibetan language has very limited resource for conventional automatic speech recognition so far. It lacks of enough data, sub-word unit, lexicons and word inventories for some dialects. And speech content recognition and dialect classification have been treated as two independent tasks and modeled respectively in most prior works. But the two tasks are highly correlated. In this paper, we present a multi-task WaveNet model to perform simultaneous Tibetan multi-dialect speech recognition and dialect identification. It avoids processing the pronunciation dictionary and word segmentation for new dialects, while, in the meantime, allows training speech recognition and dialect identification in a single… More >

  • Open Access

    ARTICLE

    Sentiment Analysis Method Based on Kmeans and Online Transfer Learning

    Shengting Wu1, Yuling Liu1,*, Jingwen Wang2, Qi Li1

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1207-1222, 2019, DOI:10.32604/cmc.2019.05835

    Abstract Sentiment analysis is a research hot spot in the field of natural language processing and content security. Traditional methods are often difficult to handle the problems of large difference in sample distribution and the data in the target domain is transmitted in a streaming fashion. This paper proposes a sentiment analysis method based on Kmeans and online transfer learning in the view of fact that most existing sentiment analysis methods are based on transfer learning and offline transfer learning. We first use the Kmeans clustering algorithm to process data from one or multiple source domains and select the data similar… More >

  • Open Access

    ARTICLE

    Three-Dimensional Numerical Analysis of Blast-Induced Damage Characteristics of the Intact and Jointed Rockmass

    Zhiliang Wang1,*, Youpeng Huang1, Feng Xiong1

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1189-1206, 2019, DOI:10.32604/cmc.2019.04972

    Abstract This article reports numerical results investigating the damage evolution and spatial distribution characteristics of intact and jointed rockmass subjected to blast loading. The behaviors of rock material are described by the Holmquist- Johnson-Cook (HJC) constitutive model incorporated in the finite element software LS-DYNA. Results indicate that the damage distribution shows a reverse S-shape attenuation with the increase of the distance from borehole, and a better goodness of fit with the Logistic function is observed. In the single-hole blasting of jointed rockmass, there are two types of regions around the intersection of borehole and joint in which the damage degree is… More >

  • Open Access

    ARTICLE

    YATA: Yet Another Proposal for Traffic Analysis and Anomaly Detection

    Yu Wang1,2,*, Yan Cao2, Liancheng Zhang2, Hongtao Zhang3, Roxana Ohriniuc4, Guodong Wang5, Ruosi Cheng6

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1171-1187, 2019, DOI:10.32604/cmc.2019.05575

    Abstract Network traffic anomaly detection has gained considerable attention over the years in many areas of great importance. Traditional methods used for detecting anomalies produce quantitative results derived from multi-source information. This makes it difficult for administrators to comprehend and deal with the underlying situations. This study proposes another method to yet determine traffic anomaly (YATA), based on the cloud model. YATA adopts forward and backward cloud transformation algorithms to fuse the quantitative value of acquisitions into the qualitative concept of anomaly degree. This method achieves rapid and direct perspective of network traffic. Experimental results with standard dataset indicate that using… More >

  • Open Access

    ARTICLE

    A Method of Obtaining Catchment Basins with Contour Lines for Foam Image Segmentation

    Yanpeng Wu1, Xiaoqi Peng1,*, Mohammad Nur2, Hengfu Yang1

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1155-1170, 2019, DOI:10.32604/cmc.2019.06123

    Abstract Foam image segmentation, represented by watershed algorithm, is wildly used in the extraction of bubble morphology features. H-minima transformation was proved to be effective in locating the catchment basins in the traditional watershed segmentation method. To further improve the accuracy of watershed segmentation, method of top-bottom-cap filters and method of morphological reconstruction were implied to marking the catchment basins. In this paper, instead of H-minima transformation, a method of contour lines is specially proposed to obtain the catchment basins for foam image segmentation by using top-bottom-cap filters and less morphological reconstruction. Experimental results in foam segmentation show that the proposed… More >

  • Open Access

    ARTICLE

    An Efficient Crossing-Line Crowd Counting Algorithm with Two-Stage Detection

    Zhenqiu Xiao1,*, Bin Yang2, Desy Tjahjadi3

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1141-1154, 2019, DOI:10.32604/cmc.2019.05638

    Abstract Crowd counting is a challenging task in crowded scenes due to heavy occlusions, appearance variations and perspective distortions. Current crowd counting methods typically operate on an image patch level with overlaps, then sum over the patches to get the final count. In this paper we describe a real-time pedestrian counting framework based on a two-stage human detection algorithm. Existing works with overhead cameras is mainly based on visual tracking, and their robustness is rather limited. On the other hand, some works, which focus on improving the performances, are too complicated to be realistic. By adopting a line sampling process, a… More >

  • 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 >

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