Aurora Costales¹, C. J. F. Solano², E. Francisco¹, A. Martín Pendás¹

CMC-Computers, Materials & Continua, Vol.38, No.2, pp. 105-128, 2013, DOI:10.3970/cmc.2013.038.105

Abstract An extension of our previously reported periodic cluster model (J. Phys. Chem. C 2008, 112, 6667-6676 ) to nanorings and nanobelts is presented. This new scheme allows for accurately calculating reasonably large nanostructures while preserving a very small number of optimization parameters. The model has been applied to a number of AlN semiconducting structures using ab initio pair potentials. Attention has been paid to the variation of the B1-B4 phase transition pressure as the the size of the structures is varied. More >

Chein-Shan Liu¹, Chih-Wen Chang², Jiang-Ren Chang^2,3

CMC-Computers, Materials & Continua, Vol.9, No.2, pp. 111-136, 2009, DOI:10.3970/cmc.2009.009.111

Abstract In this paper, we take the advantage of an analytical method to solve the advection-dispersion equation (ADE) for identifying the contamination problems. First, the Fourier series expansion technique is employed to calculate the concentration field C(x, t) at any time t< T. Then, we consider a direct regularization by adding an extra term αC(x,0) on the final condition to carry off a second kind Fredholm integral equation. The termwise separable property of the kernel function permits us to transform itinto a two-point boundary value problem. The uniform convergence and error estimate of the regularized solution C^α(x,t) are provided and a… More >

Ning Cao^1,2, Shengfang Li¹, Keyong Shen¹, Sheng Bin³, Gengxin Sun^3,*, Dongjie Zhu⁴, Xiuli Han⁵, Guangsheng Cao⁵, Abraham Campbell⁶

CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 227-241, 2019, DOI:10.32604/cmc.2019.06125

Abstract Monitoring, understanding and predicting Origin-destination (OD) flows in a city is an important problem for city planning and human activity. Taxi-GPS traces, acted as one kind of typical crowd sensed data, it can be used to mine the semantics of OD flows. In this paper, we firstly construct and analyze a complex network of OD flows based on large-scale GPS taxi traces of a city in China. The spatiotemporal analysis for the OD flows complex network showed that there were distinctive patterns in OD flows. Then based on a novel complex network model, a semantics mining method of OD flows… More >

Hefei Ling¹, Jia Wu¹, Ping Li^1,*, 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 >

Xiaodong Yan^1,2, Wei Song^1,2,*, Xiaobing Zhao^1,2, Anti Wang³

CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 707-719, 2019, DOI:10.32604/cmc.2019.05157

Abstract We apply the semi-supervised recursive autoencoders (RAE) model for the sentiment classification task of Tibetan short text, and we obtain a better classification effect. The input of the semi-supervised RAE model is the word vector. We crawled a large amount of Tibetan text from the Internet, got Tibetan word vectors by using Word2vec, and verified its validity through simple experiments. The values of parameter α and word vector dimension are important to the model effect. The experiment results indicate that when α is 0.3 and the word vector dimension is 60, the model works best. Our experiment also shows the… More >

Changting Shi^{1, *}

CMC-Computers, Materials & Continua, Vol.57, No.3, pp. 635-652, 2018, DOI:10.32604/cmc.2018.03754

Abstract In the last decade, IoT has been widely used in smart cities, autonomous driving and Industry 4.0, which lead to improve efficiency, reliability, security and economic benefits. However, with the rapid development of new technologies, such as cognitive communication, cloud computing, quantum computing and big data, the IoT security is being confronted with a series of new threats and challenges. IoT device identification via Radio Frequency Fingerprinting (RFF) extracting from radio signals is a physical-layer method for IoT security. In physical-layer, RFF is a unique characteristic of IoT device themselves, which can difficultly be tampered. Just as people’s unique fingerprinting,… More >

Suzhen Wang¹, Lu Zhang¹, Yanpiao Zhang¹, Jieli Sun¹, Chaoyi Pang², Gang Tian³, Ning Cao^4,*

CMC-Computers, Materials & Continua, Vol.57, No.3, pp. 603-619, 2018, DOI:10.32604/cmc.2018.03884

Abstract Natural language semantic construction improves natural language comprehension ability and analytical skills of the machine. It is the basis for realizing the information exchange in the intelligent cloud-computing environment. This paper proposes a natural language semantic construction method based on cloud database, mainly including two parts: natural language cloud database construction and natural language semantic construction. Natural Language cloud database is established on the CloudStack cloud-computing environment, which is composed by corpus, thesaurus, word vector library and ontology knowledge base. In this section, we concentrate on the pretreatment of corpus and the presentation of background knowledge ontology, and then put… More >

Huiyu Sun^1,*, Suzanne McIntosh¹

CMC-Computers, Materials & Continua, Vol.57, No.1, pp. 1-9, 2018, DOI:10.32604/cmc.2018.03684

Abstract The majority of big data analytics applied to transportation datasets suffer from being too domain-specific, that is, they draw conclusions for a dataset based on analytics on the same dataset. This makes models trained from one domain (e.g. taxi data) applies badly to a different domain (e.g. Uber data). To achieve accurate analyses on a new domain, substantial amounts of data must be available, which limits practical applications. To remedy this, we propose to use semi-supervised and active learning of big data to accomplish the domain adaptation task: Selectively choosing a small amount of datapoints from a new domain while… More >

Meijuan Wang^1,2,*, Jian Wang¹, Lihong Guo^1,3, Lein Harn⁴

CMC-Computers, Materials & Continua, Vol.55, No.3, pp. 465-482, 2018, DOI: 10.3970/cmc.2018.02568

Abstract In the era of big data, the conflict between data mining and data privacy protection is increasing day by day. Traditional information security focuses on protecting the security of attribute values without semantic association. The data privacy of big data is mainly reflected in the effective use of data without exposing the user’s sensitive information. Considering the semantic association, reasonable security access for privacy protect is required. Semi-structured and self-descriptive XML (eXtensible Markup Language) has become a common form of data organization for database management in big data environments. Based on the semantic integration nature of XML data, this paper… More >

Ya Tu¹, Yun Lin¹, Jin Wang^2,3,*, 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 >