Big Data Analyses of Korea's Nation Branding on Google and Facebook

2020 ◽  
Vol 51 (1) ◽  
pp. 151-174
Author(s):  
Chung Joo Chung ◽  
Yunna Rhee ◽  
Heewon Cha
2021 ◽  
Author(s):  
Siyang Lu ◽  
Yihong Chen ◽  
Xiaolin Zhu ◽  
Ziyi Wang ◽  
Yangjun Ou ◽  
...  

2020 ◽  
Vol 48 (W1) ◽  
pp. W403-W414
Author(s):  
Fabrice P A David ◽  
Maria Litovchenko ◽  
Bart Deplancke ◽  
Vincent Gardeux

Abstract Single-cell omics enables researchers to dissect biological systems at a resolution that was unthinkable just 10 years ago. However, this analytical revolution also triggered new demands in ‘big data’ management, forcing researchers to stay up to speed with increasingly complex analytical processes and rapidly evolving methods. To render these processes and approaches more accessible, we developed the web-based, collaborative portal ASAP (Automated Single-cell Analysis Portal). Our primary goal is thereby to democratize single-cell omics data analyses (scRNA-seq and more recently scATAC-seq). By taking advantage of a Docker system to enhance reproducibility, and novel bioinformatics approaches that were recently developed for improving scalability, ASAP meets challenging requirements set by recent cell atlasing efforts such as the Human (HCA) and Fly (FCA) Cell Atlas Projects. Specifically, ASAP can now handle datasets containing millions of cells, integrating intuitive tools that allow researchers to collaborate on the same project synchronously. ASAP tools are versioned, and researchers can create unique access IDs for storing complete analyses that can be reproduced or completed by others. Finally, ASAP does not require any installation and provides a full and modular single-cell RNA-seq analysis pipeline. ASAP is freely available at https://asap.epfl.ch.


2019 ◽  
Vol 57 (1) ◽  
pp. 123-141
Author(s):  
Marija Jović ◽  
Edvard Tijan ◽  
Rebecca Marx ◽  
Berit Gebhard

As maritime transport produces a large amount of data from various sources and in different formats, authors have analysed current applications of Big Data by researching global applications and experiences and by studying journal and conference articles. Big Data innovations in maritime transport (both cargo and passenger) are demonstrated, mainly in the fields of seaport operations, weather routing, monitoring/tracking and security. After the analysis, the authors have concluded that Big Data analyses can provide deep understanding of causalities and correlations in maritime transport, thus improving decision making. However, there exist major challenges of an efficient data collection and processing in maritime transport, such as technology challenges, challenges due to competitive conditions etc. Finally, the authors provide a future perspective of Big Data usage in maritime transport.


Author(s):  
Toshiaki Onitsuka ◽  
Yoji Hirano ◽  
Kiyotaka Nemoto ◽  
Naoki Hashimoto ◽  
Itaru Kushima ◽  
...  

2018 ◽  
Vol 2018 (1) ◽  
Author(s):  
Antonio Gasparrini ◽  
Ana Maria Vicedo-Cabrera ◽  
Francesco Sera

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