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  • Open Access

    ARTICLE

    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 - 19 October 2020

    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

    ARTICLE

    The Genetic Algorithm and Binary Search Technique in the Program Path Coverage for Improving Software Testing Using Big Data

    Aysh Alhroob1,*, Wael Alzyadat2, Ayad Tareq Imam1, Ghaith M. Jaradat3

    Intelligent Automation & Soft Computing, Vol.26, No.4, pp. 725-733, 2020, DOI:10.32604/iasc.2020.010106

    Abstract Software program testing is the procedure of exercising a software component with a selected set of test cases as a way to discover defects and assess quality. Using software testing automation, especially the generating of testing data increases the effectiveness and efficiency of software testing as a whole. Instead of creating testing data from scratch, Big Data (BD) offers an important source of testing data. Although it is a good source, there is a need to select a proper set of testing data for the sake of selecting an optimal sub-domain input values from the… More >

  • Open Access

    ARTICLE

    Research on the Development of Project Cost Informatization in the Era of Big Data

    Huiyu Long1, Yan Ma1, Xiang Mao1, Xinyuerong Sun2,*

    Journal on Big Data, Vol.2, No.2, pp. 63-70, 2020, DOI:10.32604/jbd.2020.011214 - 18 September 2020

    Abstract Under the background of big data, Informatization plays an important role in the development of the engineering cost industry. The rapid development of the industry and the increasing complexity of construction projects require higher standards of informatization. The current information processing methods and models have been difficultly to meet new requirements. Based on this, this study deeply analyzes the key factors that impede the informatization of engineering cost development, and tries to find corresponding solutions through theoretical analysis and empirical research to break these constraints. This will play a guiding role in the development of More >

  • Open Access

    ARTICLE

    Big Data Audit of Banks Based on Fuzzy Set Theory to Evaluate Risk Level

    Yilin Bi1, Yuxin Ouyang1, Guang Sun1, Peng Guo1, 2, Jianjun Zhang3, Yijun Ai1, *

    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 >

  • Open Access

    ARTICLE

    Enhanced Schemes for Data Fragmentation, Allocation, and Replication in Distributed Database Systems

    Masood Niazi Torshiz1,∗, Azadeh Salehi Esfaji1,†, Haleh Amintoosi2,‡

    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 >

  • Open Access

    ARTICLE

    A Model to Create Organizational Value with Big Data Analytics

    Ali Mirarab1,∗, Seyedeh Leili Mirtaheri2,†, Seyed Amir Asghari3,‡

    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 >

  • Open Access

    ARTICLE

    Design and Analysis of a Rural Accurate Poverty Alleviation Platform Based on Big Data

    Fan Bingxu*

    Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 549-555, 2020, DOI:10.32604/iasc.2020.013932

    Abstract Poverty alleviation has always been the focus of China's work. According to the survey, the poverty population in rural areas has been reduced to a large extent, and the unemployed have had the lowest historical record in history. Big data technology is a new technology that has slowly emerged in recent years. The use of big data technology to create a visual platform for rural poverty alleviation is a relatively new idea at this stage. And we use the Map-reducebased big data missing value filling algorithm, which is designed to solve the data loss phenomenon More >

  • Open Access

    EDITORIAL

    Guest Editorial: Special Section on Big Data & Analytics Architecture

    Arun Kumar Sangaiah1,*, Ford Lumban Gaol2, Krishn K. Mishra3

    Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 515-517, 2020, DOI:10.32604/iasc.2020.013928

    Abstract This article has no abstract. More >

  • Open Access

    ARTICLE

    Case Study: Spark GPU-Enabled Framework to Control COVID-19 Spread Using Cell-Phone Spatio-Temporal Data

    Hussein Shahata Abdallah1, *, Mohamed H. Khafagy1, Fatma A. Omara2

    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1303-1320, 2020, DOI:10.32604/cmc.2020.011313 - 20 August 2020

    Abstract Nowadays, the world is fighting a dangerous form of Coronavirus that represents an emerging pandemic. Since its early appearance in China Wuhan city, many countries undertook several strict regulations including lockdowns and social distancing measures. Unfortunately, these procedures have badly impacted the world economy. Detecting and isolating positive/probable virus infected cases using a tree tracking mechanism constitutes a backbone for containing and resisting such fast spreading disease. For helping this hard effort, this research presents an innovative case study based on big data processing techniques to build a complete tracking system able to identify the… More >

  • Open Access

    ARTICLE

    Word Embedding Based Knowledge Representation with Extracting Relationship Between Scientific Terminologies

    Mucheol Kim*, Junho Kim, Mincheol Shin

    Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 141-147, 2020, DOI:10.31209/2019.100000135

    Abstract With the trends of big data era, many people want to acquire the reliable and refined information from web environments. However, it is difficult to find appropriate information because the volume and complexity of web information is increasing rapidly. So many researchers are focused on text mining and personalized recommendation for extracting users’ interests. The proposed approach extracted semantic relationship between scientific terminologies with word embedding approach. We aggregated science data in BT for supporting users’ wellness. In our experiments, query expansion is performed with relationship between scientific terminologies with user’s intention. More >

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