Yizhi Liu, Rutian Qing, Jianxun Liu^*, Zhuhua Liao, Yijiang Zhao, Hong Ouyang

Journal of Cyber Security, Vol.2, No.3, pp. 131-140, 2020, DOI:10.32604/jcs.2020.010625 - 14 September 2020

Abstract Road network extraction is vital to both vehicle navigation and road planning. Existing approaches focus on mining urban trunk roads from GPS trajectories of floating cars. However, path extraction, which plays an important role in earthquake relief and village tour, is always ignored. Addressing this issue, we propose a novel approach of extracting campus’ road network from walking GPS trajectories. It consists of data preprocessing and road centerline generation. The patrolling GPS trajectories, collected at Hunan University of Science and Technology, were used as the experimental data. The experimental evaluation results show that our approach More >

Yilin Bi¹, Yuxin Ouyang¹, Guang Sun¹, Peng Guo^{1, 2}, Jianjun Zhang³, Yijun Ai^{1, *}

Journal on Big Data, Vol.2, No.1, pp. 9-18, 2020, DOI:10.32604/jbd.2020.01002 - 07 September 2020

Abstract The arrival of big data era has brought new opportunities and challenges to the development of various industries in China. The explosive growth of commercial bank data has brought great pressure on internal audit. The key audit of key products limited to key business areas can no longer meet the needs. It is difficult to find abnormal and exceptional risks only by sampling analysis and static analysis. Exploring the organic integration and business processing methods between big data and bank internal audit, Internal audit work can protect the stable and sustainable development of banks under… More >

Yifu Sheng¹, Weida Chen, Huan Wen¹, Haijun Lin¹, Jianjun Zhang^{1, *}

Journal on Big Data, Vol.2, No.1, pp. 1-8, 2020, DOI:10.32604/jbd.2020.01001 - 07 September 2020

Abstract Water resources are one of the basic resources for human survival, and water protection has been becoming a major problem for countries around the world. However, most of the traditional water quality monitoring research work is still concerned with the collection of water quality indicators, and ignored the analysis of water quality monitoring data and its value. In this paper, by adopting Laravel and AdminTE framework, we introduced how to design and implement a water quality data visualization platform based on Baidu ECharts. Through the deployed water quality sensor, the collected water quality indicator data More >

Ning Chen¹, Naernaer Xialihaer^2,3, Weiliang Kong³, Jiping Ren^2,3,*

Journal of New Media, Vol.2, No.3, pp. 99-109, 2020, DOI:10.32604/jnm.2020.09889 - 04 September 2020

Abstract This paper analyzes the energy consumption situation in Beijing, based on the comparison of common energy consumption prediction methods. Here we use multiple linear regression analysis, grey prediction, BP neural net-work prediction, grey BP neural network prediction combined method, LSTM long-term and short-term memory network model prediction method. Firstly, before constructing the model, the whole model is explained theoretically. The advantages and disadvantages of each model are analyzed before the modeling, and the corresponding advantages and disadvantages of these models are pointed out. Finally, these models are used to construct the Beijing energy forecasting model, More >

Yulan Zheng^∗

Computer Systems Science and Engineering, Vol.35, No.4, pp. 293-298, 2020, DOI:10.32604/csse.2020.35.293

Abstract With the development of e-commerce, more and more enterprises attach importance to precision marketing for network channels. This study adopted the decision tree algorithm in data mining to achieve precision marketing. Firstly, precision marketing and C4.5 decision tree algorithm were briefly introduced. Then e-commerce enterprise A was taken as an example. The data from January to June 2018 were collected. Four attributes including age, income, occupation and educational background were selected for calculation and decision tree was established to extract classification rules.The results showed that the consumers of the products of the company were high-income More >

Jing-Hua Zhao^1,†, Da-Lin Zeng^2,*, Ting-Wei Zhou^1,‡, Ze-Chao Zhu^1,§

Computer Systems Science and Engineering, Vol.35, No.3, pp. 151-172, 2020, DOI:10.32604/csse.2020.35.151

Abstract Given the government subsidies for new energy vehicles, this study is conducted to study the closed-loop supply chain comprising individual manufacturers, individual retailers and individual third-party recyclers. In this paper, combine the reality of new energy vehicles with the relevant research of game theory, and establish an no government subsidy model (Model N), a government subsidized consumer model (Model C), a government subsidized manufacturer model (Model M), a government subsidized third party recycler model (Model T), and a government subsidized retailer model (Model R) for quantitative research. Then, numerical examples are used to simulate the More >

Bing Xu^1,∗, Darong Huang^2,†, Bo Mi^3,‡

Computer Systems Science and Engineering, Vol.35, No.2, pp. 113-121, 2020, DOI:10.32604/csse.2020.35.113

Abstract In this paper, according to the information classification algorithm in data mining, data in the network payment system of e-commerce is mined, forming an effective evaluation of the security of the network payment system. Firstly, the method of network security risk prediction is discussed. Secondly, according to the characteristics of network payment system, the system security index system is analyzed in detail, and the specific application process of the C4.5 Classification Algorithm in security evaluation is discussed. Finally, the data mining process is designed in detail and the corresponding code established. In this paper, data More >

Masood Niazi Torshiz^1,∗, Azadeh Salehi Esfaji^1,†, Haleh Amintoosi^2,‡

Computer Systems Science and Engineering, Vol.35, No.2, pp. 99-112, 2020, DOI:10.32604/csse.2020.35.099

Abstract With the growth of information technology and computer networks, there is a vital need for optimal design of distributed databases with the aim of performance improvement in terms of minimizing the round-trip response time and query transmission and processing costs. To address this issue, new fragmentation, data allocation, and replication techniques are required. In this paper, we propose enhanced vertical fragmentation, allocation, and replication schemes to improve the performance of distributed database systems. The proposed fragmentation scheme clusters highly-bonded attributes (i.e., normally accessed together) into a single fragment in order to minimize the query processing More >

Ali Mirarab^1,∗, Seyedeh Leili Mirtaheri^2,†, Seyed Amir Asghari^3,‡

Computer Systems Science and Engineering, Vol.35, No.2, pp. 69-79, 2020, DOI:10.32604/csse.2020.35.069

Abstract Value creation is a major factor not only in the sustainability of organizations but also in the maximization of profit, customer retention, business goals fulfillment, and revenue. When the value is intended to be created from Big Data scenarios, value creation entails being understood over a broader range of complexity. A question that arises here is how organizations can use this massive quantity of data and create business value? The present study seeks to provide a model for creating organizational value using Big Data Analytics (BDA). To this end, after reviewing the related literature and… More >

Swathypriyadharsini P^1,∗, K.Premalatha^2,†

Computer Systems Science and Engineering, Vol.35, No.1, pp. 39-50, 2020, DOI:10.32604/csse.2020.35.039

Abstract Microarrays have reformed biotechnological research in the past decade. Deciphering the hidden patterns in gene expression data proffers a prodigious preference to strengthen the understanding of functional genomics. The complexity of biological networks with larger volume of genes also increases the challenges of comprehending and interpretation of the resulting mass of data. Clustering addresses these challenges, which is essential in the data mining process to reveal natural structures and identify interesting patterns in the underlying data. The clustering of gene expression data has been proven to be useful in making known the natural structure inherent… More >