KEYWORDS: Information security, Information fusion, Standards development, Research management, Reliability, Human-machine interfaces, Control systems, Code division multiplexing
Recently, with the continuous improvement of living standards and the rapid development of civil aviation industry, more and more people choose convenient and efficient aircraft as a means of travel, and the number of flights increases rapidly. However, in the process of flight operation, it is inevitable to encounter complicated weather, other airspace user activities or air resource flow restrictions, which seriously affect the flight normality and passenger satisfaction. In order to solve such problems, people also put forward higher requirements for flight time resource management. In this paper, based on the collaborative decision-making mechanism, this paper carries out flight plan adjustment through the early predictions, assessment analysis, dynamic update and so on, implementation of passengers, airlines and flights running related units and efficient coordination, make the flight security requirements and Air traffic control, integrated airport security ability to achieve the optimal matching, to ensure flight safety, stable, orderly, and maintain flight release order, Improve the normal rate of flight clearance.
Accurate segmentation of infant brain magnetic resonance images is crucial for studying brain development. However, infant images even within a narrow age-range differ drastically in size and contrast. Here, we investigated whether deep-learning based methods evaluated in iSeg-2017 can be generalized to accurately segment brain data acquired from other cohorts with different acquisition and ages. ISeg-2017 and UNC infant datasets were used to investigate three methods: SemiDenseNet, HyperDenseNet, and 3D-DenseSeg. Results demonstrate that HyperDenseNet has better segmentation performance and generalizability. Moreover, we built a joint segmentation-registration method by applying HyperDenseNet for segmentation. Results show that the joint method produced better performance compared with only registration or segmentation.
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