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    A Novel CACNA1A Nonsense Variant [c.4054C>T (p.Arg1352⁎)] Causing Episodic Ataxia Type 2 by Sean Lance, Stuart Mossman, Gemma Poke

    Published 2018-01-01
    “…Episodic ataxia is a heterogenous group of uncommon neurological disorders characterised by recurrent episodes of vertigo, dysarthria, and ataxia for which a variety of different genetic variations have been implicated. Episodic ataxia type two (EA2) is the most common and also has the largest number of identified causative genetic variants. …”
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    How Environmental Uncertainty Moderates the Effect of Relative Advantage and Perceived Credibility on the Adoption of Mobile Health Services by Chinese Organizations in the Big Data Era by Xing Chen, Xing Zhang

    Published 2016-01-01
    “…Despite the importance of adoption of mobile health services by an organization on the diffusion of mobile technology in the big data era, it has received minimal attention in literature. …”
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    Complex Power System Status Monitoring and Evaluation Using Big Data Platform and Machine Learning Algorithms: A Review and a Case Study by Yuanjun Guo, Zhile Yang, Shengzhong Feng, Jinxing Hu

    Published 2018-01-01
    “…Efficient and valuable strategies provided by large amount of available data are urgently needed for a sustainable electricity system that includes smart grid technologies and very complex power system situations. Big Data technologies including Big Data management and utilization based on increasingly collected data from every component of the power grid are crucial for the successful deployment and monitoring of the system. …”
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    Dynamic Prediction Research of Silicon Content in Hot Metal Driven by Big Data in Blast Furnace Smelting Process under Hadoop Cloud Platform by Yang Han, Jie Li, Xiao-Lei Yang, Wei-Xing Liu, Yu-Zhu Zhang

    Published 2018-01-01
    “…In order to explore a dynamic prediction model with good generalization performance of the content of [Si] in molten iron, an improved SVM algorithm is proposed to enhance its practicability in the big data sample set of the smelting process. Firstly, we propose a parallelization scheme to design an SVM solution algorithm based on the MapReduce model under a Hadoop platform to improve the solution speed of the SVM on big data sample sets. …”
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    Boruta-grid-search least square support vector machine for NO2 pollution prediction using big data analytics and IoT emission sensors by Habeeb Balogun, Hafiz Alaka, Christian Nnaemeka Egwim

    Published 2025-01-01
    “…Design/methodology/approach – This research installed and used data from 14 IoT emission sensors to develop machine learning predictive models for NO2 pollution concentration. The authors used big data analytics infrastructure to retrieve the large volume of data collected in tens of seconds for over 5 months. …”
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