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Effective use of data can help us expand our knowledge of fundamental issues, such as social and political instability, natural disasters, and climate change to improve decision-making and enhance our ability to predict, and even pre-empt, the next crisis.
Increased availability and more effective use of data to drive sustainable development has the potential to be the game-changing innovation of the next decade.
The best way to lower the costs and improve the quality of medical service is by the effective use of data.
The report claimed new technologies such as 3D printing and more effective use of data could contribute £74bn to the wider UK economy over the next two decades, as well as cutting the time consumers have to wait for a new car by a third.
The report listed several factors that hamper effective use of data, among them: the "absence of a work culture that focuses on results, lack of agreement on key indicators of performance, lack of incentives for data utilization, delays in the transmission of data to relevant levels".
They must create the appropriate systems and publicly accountable spaces to ensure measurable and effective use of data.
Similar(40)
This paper presents the general architecture of a multi-sensor geographic information system which allows for the effective use of sensor data and geographic information in fire incident management and fire development analysis.
Further development of data driven acquisition will not only increase the efficiency of data collection but also result in more effective use of the data that is generated during an analysis.
Based on this evidence we develop a typology of mobile phone data sources, types, and end-uses, and a decision-tree for mobile data use, designed to enable effective use of mobile data for disease disaster management.
Today, the most formidable tools to effectively manage unstructured data include natural language processing, ontologies and data mining, which together support the effective use of unstructured data.
In this paper, we introduce a simple unsupervised framework for pre-training hidden-unit conditional random fields (HUCRFs), i.e., learning initial parameter estimates for HUCRFs prior to supervised training.Our framework exploits the model structure of HUCRFs to make effective use of unlabeled data from the same domain or labeled data from a different domain.
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