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  • Open Access


    Design of a Web Crawler for Water Quality Monitoring Data and Data Visualization

    Ziwen Yu1, Jianjun Zhang1,*, Wenwu Tan1, Ziyi Xiong1, Peilun Li1, Liangqing Meng2, Haijun Lin1, Guang Sun3, Peng Guo4

    Journal on Big Data, Vol.4, No.2, pp. 135-143, 2022, DOI:10.32604/jbd.2022.031024

    Abstract Many countries are paying more and more attention to the protection of water resources at present, and how to protect water resources has received extensive attention from society. Water quality monitoring is the key work to water resources protection. How to efficiently collect and analyze water quality monitoring data is an important aspect of water resources protection. In this paper, python programming tools and regular expressions were used to design a web crawler for the acquisition of water quality monitoring data from Global Freshwater Quality Database (GEMStat) sites, and the multi-thread parallelism was added to More >

  • Open Access


    Filter and Embedded Feature Selection Methods to Meet Big Data Visualization Challenges

    Kamal A. ElDahshan, AbdAllah A. AlHabshy, Luay Thamer Mohammed*

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 817-839, 2023, DOI:10.32604/cmc.2023.032287

    Abstract This study focuses on meeting the challenges of big data visualization by using of data reduction methods based the feature selection methods. To reduce the volume of big data and minimize model training time (Tt) while maintaining data quality. We contributed to meeting the challenges of big data visualization using the embedded method based “Select from model (SFM)” method by using “Random forest Importance algorithm (RFI)” and comparing it with the filter method by using “Select percentile (SP)” method based chi square “Chi2” tool for selecting the most important features, which are then fed into… More >

  • Open Access


    Machine Learning and Artificial Neural Network for Predicting Heart Failure Risk

    Polin Rahman1, Ahmed Rifat1, MD. IftehadAmjad Chy1, Mohammad Monirujjaman Khan1,*, Mehedi Masud2, Sultan Aljahdali2

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 757-775, 2023, DOI:10.32604/csse.2023.021469

    Abstract Heart failure is now widely spread throughout the world. Heart disease affects approximately 48% of the population. It is too expensive and also difficult to cure the disease. This research paper represents machine learning models to predict heart failure. The fundamental concept is to compare the correctness of various Machine Learning (ML) algorithms and boost algorithms to improve models’ accuracy for prediction. Some supervised algorithms like K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Decision Trees (DT), Random Forest (RF), Logistic Regression (LR) are considered to achieve the best results. Some boosting algorithms like Extreme Gradient… More >

  • Open Access


    Design and Implementation of Log Data Analysis Management System Based on Hadoop

    Dunhong Yao1,2,3,*, Yu Chen4

    Journal of Information Hiding and Privacy Protection, Vol.2, No.2, pp. 59-65, 2020, DOI:10.32604/jihpp.2020.010223

    Abstract With the rapid development of the Internet, many enterprises have launched their network platforms. When users browse, search, and click the products of these platforms, most platforms will keep records of these network behaviors, these records are often heterogeneous, and it is called log data. To effectively to analyze and manage these heterogeneous log data, so that enterprises can grasp the behavior characteristics of their platform users in time, to realize targeted recommendation of users, increase the sales volume of enterprises’ products, and accelerate the development of enterprises. Firstly, we follow the process of big… More >

  • Open Access


    A Survey of Time Series Data Visualization Methods

    Wangdong Jiang1, Jie Wu1,*, Guang Sun1,2, Yuxin Ouyang3, Jing Li3, Shuang Zhou2

    Journal of Quantum Computing, Vol.2, No.2, pp. 105-117, 2020, DOI:10.32604/jqc.2020.07242

    Abstract In the era of big data, the general public is more likely to access big data, but they wouldn’t like to analyze the data. Therefore, the traditional data visualization with certain professionalism is not easy to be accepted by the general public living in the fast pace. Under this background, a new general visualization method for dynamic time series data emerges as the times require. Time series data visualization organizes abstract and hard-to-understand data into a form that is easily understood by the public. This method integrates data visualization into short videos, which is more More >

  • Open Access


    Visualization Research and Application of Water Quality Monitoring Data Based on ECharts

    Yifu Sheng1, Weida Chen, Huan Wen1, Haijun Lin1, Jianjun Zhang1, *

    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 More >

  • Open Access


    COVID-19 Public Opinion and Emotion Monitoring System Based on Time Series Thermal New Word Mining

    Yixian Zhang1, Jieren Cheng2, *, Yifan Yang2, Haocheng Li2, Xinyi Zheng2, Xi Chen2, Boyi Liu3, Tenglong Ren4, Naixue Xiong5

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1415-1434, 2020, DOI:10.32604/cmc.2020.011316

    Abstract With the spread and development of new epidemics, it is of great reference value to identify the changing trends of epidemics in public emotions. We designed and implemented the COVID-19 public opinion monitoring system based on time series thermal new word mining. A new word structure discovery scheme based on the timing explosion of network topics and a Chinese sentiment analysis method for the COVID-19 public opinion environment are proposed. Establish a “Scrapy-Redis-Bloomfilter” distributed crawler framework to collect data. The system can judge the positive and negative emotions of the reviewer based on the comments, More >

  • Open Access


    On Visualization Analysis of Stock Data

    Yue Cai1, Zeying Song1, Guang Sun1, *, 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 More >

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