Big data driven decision making and multi-prior models collaboration for media restoration

2014 ◽  
Vol 75 (20) ◽  
pp. 12967-12982 ◽  
Author(s):  
Feng Jiang ◽  
Seungmin Rho ◽  
Bo-Wei Chen ◽  
Kun Li ◽  
Debin Zhao
Procedia CIRP ◽  
2019 ◽  
Vol 83 ◽  
pp. 814-818 ◽  
Author(s):  
Yongheng Zhang ◽  
Rui Zhang ◽  
Yizhong Wang ◽  
Hongfei Guo ◽  
Ray Y Zhong ◽  
...  

Smart Cities ◽  
2021 ◽  
Vol 4 (1) ◽  
pp. 286-313
Author(s):  
Ahmed M. Shahat Osman ◽  
Ahmed Elragal

Interest in smart cities (SCs) and big data analytics (BDA) has increased in recent years, revealing the bond between the two fields. An SC is characterized as a complex system of systems involving various stakeholders, from planners to citizens. Within the context of SCs, BDA offers potential as a data-driven decision-making enabler. Although there are abundant articles in the literature addressing BDA as a decision-making enabler in SCs, mainstream research addressing BDA and SCs focuses on either the technical aspects or smartening specific SC domains. A small fraction of these articles addresses the proposition of developing domain-independent BDA frameworks. This paper aims to answer the following research question: how can BDA be used as a data-driven decision-making enabler in SCs? Answering this requires us to also address the traits of domain-independent BDA frameworks in the SC context and the practical considerations in implementing a BDA framework for SCs' decision-making. This paper's main contribution is providing influential design considerations for BDA frameworks based on empirical foundations. These foundations are concluded through a use case of applying a BDA framework in an SC's healthcare setting. The results reveal the ability of the BDA framework to support data-driven decision making in an SC.


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