Hangjun Zhou^{1, *}, Guang Sun^{1, 2}, Sha Fu¹, Xiaoping Fan¹, Wangdong Jiang¹, Shuting Hu¹, Lingjiao Li¹

CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1091-1105, 2020, DOI:10.32604/cmc.2020.09834

Abstract Supply Chain Finance (SCF) is important for improving the effectiveness of supply chain capital operations and reducing the overall management cost of a supply chain. In recent years, with the deep integration of supply chain and Internet, Big Data, Artificial Intelligence, Internet of Things, Blockchain, etc., the efficiency of supply chain financial services can be greatly promoted through building more customized risk pricing models and conducting more rigorous investment decision-making processes. However, with the rapid development of new technologies, the SCF data has been massively increased and new financial fraud behaviors or patterns are becoming more covertly scattered among normal… More >

Wangdong Jiang¹, Taian Yang^{1, *}, Guang Sun^{1, 3}, Yucai Li¹, Yixuan Tang², Hongzhang Lv¹, Wenqian Xiang¹

Journal on Big Data, Vol.1, No.3, pp. 117-134, 2019, DOI:10.32604/jbd.2019.08454

Abstract In order to study deeply the prominent problems faced by China’s clean government work, and put forward effective coping strategies, this article analyzes the network information of anti-corruption related news events, which is based on big data technology. In this study, we take the news report from the website of the Communist Party of China (CPC) Central Commission for Discipline Inspection (CCDI) as the source of data. Firstly, the obtained text data is converted to word segmentation and stop words under preprocessing, and then the pre-processed data is improved by vectorization and text clustering, finally, after text clustering, the key… More >

Youqin Huang¹, Jiayong Li¹, Jiyang Fu^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.121, No.3, pp. 845-875, 2019, DOI:10.32604/cmes.2019.07653

Abstract In last few years, big data and deep learning technologies have been successfully applied in various fields of civil engineering with the great progress of machine learning techniques. However, until now, there has been no comprehensive review on its applications in civil engineering. To fill this gap, this paper reviews the application and development of artificial intelligence in civil engineering in recent years, including intelligent algorithms, big data and deep learning. Through the work of this paper, the research direction and difficulties of artificial intelligence in civil engineering for the past few years can be known. It is shown that… More >

Chuanrong Wu^{1, *}, Evgeniya Zapevalova¹, Yingwu Chen², Deming Zeng³, Francis Liu⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.116, No.1, pp. 89-107, 2018, DOI:10.31614/cmes.2018.04041

Abstract With market competition becoming fiercer, enterprises must update their products by constantly assimilating new big data knowledge and private knowledge to maintain their market shares at different time points in the big data environment. Typically, there is mutual influence between each knowledge transfer if the time interval is not too long. It is necessary to study the problem of continuous knowledge transfer in the big data environment. Based on research on one-time knowledge transfer, a model of continuous knowledge transfer is presented, which can consider the interaction between knowledge transfer and determine the optimal knowledge transfer time at different time… More >

Qianxin Wang^1,*, Allison Kealy², Shengjie Zhai³

CMES-Computer Modeling in Engineering & Sciences, Vol.119, No.2, pp. 245-247, 2019, DOI:10.32604/cmes.2019.06589

Abstract This article has no abstract. More >

Yaqiang Gong^1,2, Guangli Guo^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.119, No.2, pp. 395-408, 2019, DOI:10.32604/cmes.2019.03686

Abstract Although big data are widely used in various fields, its application is still rare in the study of mining subsidence prediction (MSP) caused by underground mining. Traditional research in MSP has the problem of oversimplifying geological mining conditions, ignoring the fluctuation of rock layers with space. In the context of geospatial big data, a data-intensive FLAC^3D (Fast Lagrangian Analysis of a Continua in 3 Dimensions) model is proposed in this paper based on borehole logs. In the modeling process, we developed a method to handle geospatial big data and were able to make full use of borehole logs. The effectiveness… More >

Guang Sun^1,2, Fenghua Li^1,*, Wangdong Jiang¹

Journal on Big Data, Vol.1, No.1, pp. 25-38, 2019, DOI:10.32604/jbd.2019.05800

Abstract Graphical methods are used for construction. Data analysis and visualization are an important area of applications of big data. At the same time, visual analysis is also an important method for big data analysis. Data visualization refers to data that is presented in a visual form, such as a chart or map, to help people understand the meaning of the data. Data visualization helps people extract meaning from data quickly and easily. Visualization can be used to fully demonstrate the patterns, trends, and dependencies of your data, which can be found in other displays. Big data visualization analysis combines the… More >

Guangyong Yang^1,*, Mengke Yang^2,*, Shafaq Salam³, Jianqiu Zeng⁴

Journal of Cyber Security, Vol.1, No.1, pp. 19-28, 2019, DOI:10.32604/jcs.2019.05947

Abstract Big data is becoming increasingly important because of the enormous information generation and storage in recent years. It has become a challenge to the data mining technique and management. Based on the characteristics of geometric explosion of information in the era of big data, this paper studies the possible approaches to balance the maximum value and privacy of information, and disposes the Nine-Cells information matrix, hierarchical classification. Furthermore, the paper uses the rough sets theory to proceed from the two dimensions of value and privacy, establishes information classification method, puts forward the countermeasures for information security. Taking spam messages for… More >

Pingshui Wang^1,*, Zecheng Wang¹, Qinjuan Ma¹

Journal of Information Hiding and Privacy Protection, Vol.1, No.1, pp. 35-42, 2019, DOI:10.32604/jihpp.2019.05942

Abstract The issue of privacy protection for mobile social networks is a frontier topic in the field of social network applications. The existing researches on user privacy protection in mobile social network mainly focus on privacy preserving data publishing and access control. There is little research on the association of user privacy information, so it is not easy to design personalized privacy protection strategy, but also increase the complexity of user privacy settings. Therefore, this paper concentrates on the association of user privacy information taking big data analysis tools, so as to provide data support for personalized privacy protection strategy design. More >

Hangjun Zhou¹, Jieyu Zhou^1,*, Guang Sun^2,3, Wangdong Jiang³, Chuntian Luo¹, Xiaoping Fan¹, Haowen Zhang¹, Haoran Zhang¹

Journal of Quantum Computing, Vol.1, No.2, pp. 65-80, 2019, DOI:10.32604/jqc.2019.07238

Abstract Due to the huge amount of increasing data, the requirements of people for electronic products such as mobile phones, tablets, and notebooks are constantly improving. The development and design of various software applications attach great importance to users’ experiences. The rationalized UI design should allow a user not only enjoy the visual design experience of the new product but also operating it more pleasingly. This process is to enhance the attractiveness and performance of the new product and thus to promote the active usage and consuming conduct of users. In this paper, an UI design optimization strategy for general APP… More >