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

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 is transmitted to the big… More >

Mengling Zou¹, Zhengxuan Liu², Xianyi Chen^{3, *}

Journal on Big Data, Vol.1, No.3, pp. 151-158, 2019, DOI:10.32604/jbd.2019.09057

Abstract Image encryption (IE) is a very useful and popular technology to protect the privacy of users. Most algorithms usually encrypt the original image into an image similar to texture or noise, but texture and noise are an obvious visual indication that the image has been encrypted, which is more likely to cause the attacks of enemy. To overcome this shortcoming, many image encryption systems, which convert the original image into a carrier image with visual significance have been proposed. However, the generated cryptographic image still has texture features. In line with the idea of improving the visual quality of the… More >

Danping Dong^{1, *}, Yue Wu¹, Lizhi Xiong¹, Zhihua Xia¹

Journal on Big Data, Vol.1, No.3, pp. 145-150, 2019, DOI:10.32604/jbd.2019.08706

Abstract This paper proposes a strategy for machine learning in the ciphertext domain. The data to be trained in the linear regression equation is encrypted by SHE homomorphic encryption, and then trained in the ciphertext domain. At the same time, it is guaranteed that the error of the training results between the ciphertext domain and the plaintext domain is in a controllable range. After the training, the ciphertext can be decrypted and restored to the original plaintext training data. More >

Yue Cai¹, Zeying Song¹, Guang Sun^{1, *}, Jing Wang¹, Ziyi Guo¹, Yi Zuo¹, Xiaoping Fan¹, Jianjun Zhang², Lin Lang¹

Journal on Big Data, Vol.1, No.3, pp. 135-144, 2019, DOI:10.32604/jbd.2019.08274

Abstract Big data technology is changing with each passing day, generating massive amounts of data every day. These data have large capacity, many types, fast growth, and valuable features. The same is true for the stock investment market. The growth of the amount of stock data generated every day is difficult to predict. The price trend in the stock market is uncertain, and the valuable information hidden in the stock data is difficult to detect. For example, the price trend of stocks, profit trends, how to make a reasonable speculation on the price trend of stocks and profit trends is a… 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 >

Yuan Chen¹, Liangtao Duan¹, Weize Sun^{2, *}, Jingxin Xu³

Journal on Big Data, Vol.1, No.3, pp. 107-116, 2019, DOI:10.32604/jbd.2019.07294

Abstract In this work, we address the frequency estimation problem of a complex singletone embedded in the heavy-tailed noise. With the use of the linear prediction (LP) property and l₁-norm minimization, a robust frequency estimator is developed. Since the proposed method employs the weighted l₁-norm on the LP errors, it can be regarded as an extension of the l_p-generalized weighted linear predictor. Computer simulations are conducted in the environment of α-stable noise, indicating the superiority of the proposed algorithm, in terms of its robust to outliers and nearly optimal estimation performance. More >

Yong Chen^1,*, Weihua Lan¹, Chong Wang²

Journal on Big Data, Vol.1, No.2, pp. 47-54, 2019, DOI:10.32604/jbd.2019.06282

Abstract In order to solve information island problem of offshore oil and gas field production-related information system, including repetitive reporting and input of data, data isolation of central control system, inadequate follow-up analysis and development to support oil and gas field production management, and so on. Therefore, the introduction of MES (Manufacturing Execution System) production execution system in the manufacturing industry and downstream production of offshore oil has become an inevitable choice. This system utilizes the real-time database combined with relational database to collect the scattered structured data, such as the production process real-time data, production management documents and statistical tables… More >

Guang Sun¹, Huanxin Xiang², Shuanghu Li^1,*

Journal on Big Data, Vol.1, No.2, pp. 89-106, 2019, DOI:10.32604/jbd.2019.07235

Abstract Web crawlers are an important part of modern search engines. With the development of the times, data has exploded and humans have entered a “big data era”. For example, Wikipedia carries the knowledge from all over the world, records the real-time news that occurs every day, and provides users with a good database of data, but because of the large amount of data, it puts a lot of pressure on users to search. At present, single-threaded crawling data can no longer meet the requirements of text crawling. In order to improve the performance and program versatility of single-threaded crawlers, a… More >

Zimeng Xing¹, Lina Wang^1,*, Wenbo Xing², Yongjun Ren³, Tao Li⁴, Jinyue Xia⁵

Journal on Big Data, Vol.1, No.2, pp. 79-88, 2019, DOI:10.32604/jbd.2019.05806

Abstract In this paper, the research advances of ontology and its application are reviewed firstly. With the development of ontology technology, subject-oriented web information retrieval technology combining ontology has been becoming one of the hot scientific issues. The innovative method of the semantic web technology combined with the traditional information retrieval technology is put forward, and the related algorithm based on ontology for judging the relevancy with different topics is also represented, and has proved to be effective in given experiments. More >

Ran Ou^1,2, Fei Chen^1,2, Yongjun Ren^1,2,*, Yepeng Liu^1,2, Qirun Wang³

Journal on Big Data, Vol.1, No.2, pp. 71-77, 2019, DOI:10.32604/jbd.2019.06057

Abstract With the broad application of information technology in urban infrastructure, urban construction has entered the stage of a smart city, forming many electronic records in urban construction. These electronic records play a vital role in the maintenance of urban infrastructure. However, electronic records often change in the process of urban construction. How to preserve the electronic records of urban construction became a significant challenge. In response to this problem, this paper proposes the use of risk-based management techniques to ensure the digital continuity, authenticity, integrity, and availability of electronic records More >