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Rodger, J.A. (2015) Discovery of Medical Big Data Analytics: Improving the Prediction of Traumatic Brain Injury Survival Rates by Data Mining Patient Informatics Processing Software Hybrid Hadoop Hive. Informatics in Medicine Unlocked, 1, 17-26.
https://doi.org/10.1016/j.imu.2016.01.002

has been cited by the following article:

• TITLE: Secure and Performant Handling CIM-Based Data Streams in Control Room Software Interaction for Multi Vendor Solutions

  AUTHORS: Benjamin Requardt, Sebastian Wende-von Berg, Martin Braun

  KEYWORDS: Common Information Model (CIM), Grid Control Room Software, Electrical Grid

  JOURNAL NAME: Intelligent Information Management, Vol.12 No.1, January 17, 2020

  ABSTRACT: Due to the increasing share of renewable energy, new requirements are placed on control room software. Such software is often exclusive to the supplier, but other suppliers could offer new and better methods. For security reasons, external applications often have no direct data access to control room software. Such software can provide information about the power grid via a periodic file transfer in CIM (Common Information Model) format. These files are often very large, containing complete records, delivering information not always relevant to the external applications. Extracting the relevant information required by external applications can be time-consuming, thus presenting a problem for time-critical applications. This paper presents a method allowing different applications to efficiently access the relevant data from the massive data stream contained in the CIM files. This method has been tested with a distribution system operator and clearly increases performance, allowing different applications to access the relevant data.