Titlebook: Big Data – BigData 2020; 9th International Co Surya Nepal,Wenqi Cao,Liang-Jie Zhang Conference proceedings 2020 Springer Nature Switzerland

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Introduction to Kienböck’s Diseasehastic passengers’ destination distribution based on the observation that the distribution has obvious periodicity and randomicity. We validate our method based on extensive experiments, using AFC data and weather data in Shenzhen, China over two years. The evaluation results show that our approach

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The Free Calculus and the Elementary Ideals, friendly interface to consult aggregated information promptly. This work establishes a Semantic Data Model for each clinical trial to create a summary of key information in a machine-readable format, and to enrich each summary with semantic information. In addition, it allows the union of these mod

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Richard H. Crowell,Ralph H. Foxstatus from tissue sample gene expressions. We use genes selected based on the prior mutual information technique. First, we select the top 500 genes from candidate genes without considerations for overlap in the predictability of those genes. We then applied Recursive Feature Elimination (RFE) to s

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Civil Law and Civil Procedural Law,ction of travel. We apply and compare leading deep learning approaches including You Only Look Once version 3 (YOLOv3) and Single Shot Multi-Box Detector (SSD). This paper builds upon earlier work [.] which focused on data (video) from a single traffic junction in Melbourne. This work is based on a

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Scalable Reference Genome Assembly from Compressed Pan-Genome Index with Sparkexing pan-genomes and assembling a reference genome from the pan-genomic index. We experimentally show the scalability of the PanGenSpark with human pan-genomes in a distributed Spark cluster comprising 448 cores distributed to 26 computing nodes. Assembling a consensus genome of a pan-genome includ