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113 result(s) within Volume 6 of Journal of Big Data

Page 2 of 3

  1. Access to affordable healthcare is a nationwide concern that impacts a large majority of the United States population. Medicare is a Federal Government healthcare program that provides affordable health insura...

    Authors: Justin M. Johnson and Taghi M. Khoshgoftaar
    Citation: Journal of Big Data 2019 6:63
  2. The human brain is a complex system of neural tissue that varies significantly between individuals. Although the technology that delineates these neural pathways does not currently exist, medical imaging modal...

    Authors: Andrea Hart, Brianna Smith, Sean Smith, Elijah Sales, Jacqueline Hernandez-Camargo, Yarlin Mayor Garcia, Felix Zhan, Lori Griswold, Brian Dunkelberger, Michael R. Schwob, Sharang Chaudhry, Justin Zhan, Laxmi Gewali and Paul Oh
    Citation: Journal of Big Data 2019 6:61
  3. Deep convolutional neural networks have performed remarkably well on many Computer Vision tasks. However, these networks are heavily reliant on big data to avoid overfitting. Overfitting refers to the phenomen...

    Authors: Connor Shorten and Taghi M. Khoshgoftaar
    Citation: Journal of Big Data 2019 6:60
  4. Due to the increasing popularity of recent advanced features and context-awareness in smart mobile phones, the contextual data relevant to users’ diverse activities with their phones are recorded through the d...

    Authors: Iqbal H. Sarker, A. S. M. Kayes and Paul Watters
    Citation: Journal of Big Data 2019 6:57
  5. ‘Big data’ is massive amounts of information that can work wonders. It has become a topic of special interest for the past two decades because of a great potential that is hidden in it. Various public and priv...

    Authors: Sabyasachi Dash, Sushil Kumar Shakyawar, Mohit Sharma and Sandeep Kaushik
    Citation: Journal of Big Data 2019 6:54
  6. This paper presents our research on the development of navigation systems of autonomous drone for delivering items that uses a GNSS (Global Navigation Satellite System) and a compass as the main tools in drone...

    Authors: Aurello Patrik, Gaudi Utama, Alexander Agung Santoso Gunawan, Andry Chowanda, Jarot S. Suroso, Rizatus Shofiyanti and Widodo Budiharto
    Citation: Journal of Big Data 2019 6:53
  7. Adversarial attacks represent a serious evolving threat to the operation of deep neural networks. Recently, adversarial algorithms were developed to facilitate hallucination of deep neural networks for ordinar...

    Authors: Alaa E. Abdel-Hakim
    Citation: Journal of Big Data 2019 6:51
  8. Recently, big data streams have become ubiquitous due to the fact that a number of applications generate a huge amount of data at a great velocity. This made it difficult for existing data mining tools, techno...

    Authors: Taiwo Kolajo, Olawande Daramola and Ayodele Adebiyi
    Citation: Journal of Big Data 2019 6:47
  9. Data scientists need scalable methods to explore and clean big data before applying advanced data analysis and mining algorithms. In this paper, we propose the RSP-Explore method to enable data scientists to i...

    Authors: Salman Salloum, Joshua Zhexue Huang and Yulin He
    Citation: Journal of Big Data 2019 6:45
  10. Data validation is about verifying the correctness of data. When organisations update and refine their data transformations to meet evolving requirements, it is imperative to ensure that the new version of a w...

    Authors: Raya Rizk, Steve McKeever, Johan Petrini and Erik Zeitler
    Citation: Journal of Big Data 2019 6:41
  11. Big data architectures have been gaining momentum in recent years. For instance, Twitter uses stream processing frameworks like Apache Storm to analyse billions of tweets per minute and learn the trending topi...

    Authors: Marcello M. Bersani, Francesco Marconi, Damian A. Tamburri, Andrea Nodari and Pooyan Jamshidi
    Citation: Journal of Big Data 2019 6:40
  12. Pattern mining is a powerful tool for analysing big datasets. Temporal datasets include time as an additional parameter. This leads to complexity in algorithmic formulation, and it can be challenging to proces...

    Authors: Sofya S. Titarenko, Valeriy N. Titarenko, Georgios Aivaliotis and Jan Palczewski
    Citation: Journal of Big Data 2019 6:37
  13. We study the the spread and adoption of libraries within Python projects hosted in public software repositories on GitHub. By modelling the use of Git pull, merge, commit, and other actions as deliberate cogni...

    Authors: Rachel Krohn and Tim Weninger
    Citation: Journal of Big Data 2019 6:36
  14. The global popularity of social media platforms has given rise to unprecedented amounts of data, much of which reflects the thoughts, opinions and affective states of individual users. Systematic explorations ...

    Authors: Aamna Al Shehhi, Justin Thomas, Roy Welsch, Ian Grey and Zeyar Aung
    Citation: Journal of Big Data 2019 6:33
  15. We address the problem of detecting highly raised crowd density in situations such as indoor dance events. We propose a new method for estimating crowd density by anonymous, non-participatory, indoor Wi-Fi loc...

    Authors: Sonja Georgievska, Philip Rutten, Jan Amoraal, Elena Ranguelova, Rena Bakhshi, Ben L. de Vries, Michael Lees and Sander Klous
    Citation: Journal of Big Data 2019 6:31
  16. The purpose of this study is to examine existing deep learning techniques for addressing class imbalanced data. Effective classification with imbalanced data is an important area of research, as high class imb...

    Authors: Justin M. Johnson and Taghi M. Khoshgoftaar
    Citation: Journal of Big Data 2019 6:27
  17. Prevention of hospital readmissions has the potential of providing better quality of care to the patients and deliver significant cost savings. A review of existing readmission analysis frameworks based on dat...

    Authors: Piyush Jain, Ankur Agarwal, Ravi Behara and Christopher Baechle
    Citation: Journal of Big Data 2019 6:26
  18. Critical systems that produce big data streams can require human operators to monitor these event streams for changes of interest. Automated systems which oversee many tasks can still have a need for the ‘huma...

    Authors: Alexander V. Mantzaris, Thomas G. Walker, Cameron E. Taylor and Dustin Ehling
    Citation: Journal of Big Data 2019 6:24
  19. This study represents an efficient method for extracting product aspects from customer reviews and give solutions for inferring aspect ratings and aspect weights. Aspect ratings often reflect the user’s satisf...

    Authors: Tu Nguyen Thi Ngoc, Ha Nguyen Thi Thu and Viet Anh Nguyen
    Citation: Journal of Big Data 2019 6:22
  20. The Internet of Things (IoT) facilitates creation of smart spaces by converting existing environments into sensor-rich data-centric cyber-physical systems with an increasing degree of automation, giving rise t...

    Authors: Rustem Dautov, Salvatore Distefano and Rajkumaar Buyya
    Citation: Journal of Big Data 2019 6:19
  21. Deep Learning is an increasingly important subdomain of artificial intelligence, which benefits from training on Big Data. The size and complexity of the model combined with the size of the training dataset ma...

    Authors: Robert K. L. Kennedy, Taghi M. Khoshgoftaar, Flavio Villanustre and Timothy Humphrey
    Citation: Journal of Big Data 2019 6:16
  22. Currently, the data to be explored and exploited by computing systems increases at an exponential rate. The massive amount of data or so-called “Big Data” put pressure on existing technologies for providing sc...

    Authors: Somnath Mazumdar, Daniel Seybold, Kyriakos Kritikos and Yiannis Verginadis
    Citation: Journal of Big Data 2019 6:15
  23. Global environmental pollution caused by human activities has become a threat to public health. Children are especially susceptible to adverse environmental conditions owing to their unique physiological and b...

    Authors: Guang-jun Yu, Jian-lei Gu, Wen-bin Cui, Jian-ping Jiang, Yang Wang, Georgi Z. Genchev, Ting Lu and Hui Lu
    Citation: Journal of Big Data 2019 6:14

Annual Journal Metrics

  • 2022 Citation Impact
    8.1 - 2-year Impact Factor
    5.095 - SNIP (Source Normalized Impact per Paper)
    2.714 - SJR (SCImago Journal Rank)

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    56 days submission to first editorial decision for all manuscripts (Median)
    205 days submission to accept (Median)

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