Jun Li^{1, 2}, Jieren Cheng^{2, *}, Naixue Xiong³, Lougao Zhan⁴, Yuan Zhang¹

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 723-741, 2020, DOI:10.32604/cmc.2020.011272 - 23 July 2020

Abstract Security and privacy issues have become a rapidly growing problem with the fast development of big data in public health. However, big data faces many ongoing serious challenges in the process of collection, storage, and use. Among them, data security and privacy problems have attracted extensive interest. In an effort to overcome this challenge, this article aims to present a distributed privacy preservation approach based on smart contracts and Intel Software Guard Extensions (SGX). First of all, we define SGX as a trusted edge computing node, design data access module, data protection module, and data… More >

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 - 10 June 2020

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 >

Erna Qi^1,∗, Min Deng²

Computer Systems Science and Engineering, Vol.34, No.4, pp. 237-248, 2019, DOI:10.32604/csse.2019.34.237

Abstract The application of computer technology, especially the emergence of some statistical software and graphic presentation technology, has enabled many areas of research that require a large amount of data analysis. This paper discusses the relationship between R&D investment and corporate financial performance, and further studies the effect of environmental regulations on this relationship through these technologies. The unbalanced panel data of listed companies from 2007 to 2016 were used as a sample, and then corresponding regression modelswere established through logical reasoning. Empirical analysis has found that there is an inverted U-shaped relationship between R&D investment… More >

Vengadeswaran^∗, Balasundaram

Computer Systems Science and Engineering, Vol.34, No.1, pp. 47-60, 2019, DOI:10.32604/csse.2019.34.047

Abstract The tremendous growth of data being generated today is making storage and computing a mammoth task. With its distributed processing capability Hadoop gives an efficient solution for such large data. Hadoop’s default data placement strategy places the data blocks randomly across the nodes without considering the execution parameters resulting in several lacunas such as increased execution time, query latency etc., Also, most of the data required for a task execution may not be locally available which creates data-locality problem. Hence we propose an innovative data placement strategy based on dependency of data blocks across the More >

Yu Zhang^1,2, Yan-Ge Wang¹, Yan-Ping Bai³, Yong-Zhen Li^1,4, Zhao-Yong Lv⁵, Hong-Wei Ding⁶

Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 561-572, 2019, DOI:10.31209/2019.100000111

Abstract Rockburst phenomenon is a kind of phenomenon that the rock is out and ejected because the mineral was dug out, and the original force balance was destroyed in the process of mineral exploitation. From 2007, GeoLab (abbreviation of State Key Laboratory in China for GeoMechanics and Deep Underground Engineering) had made a series of important achievements in rockburst. Up to now, GeoLab’s rockburst experiment data is reached 800T, and these data may occupy about 2PB hard disk space after analyzed. At this ratio, GeoLab need to buy a new hard disk to save all these… 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,… 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 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 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… More >