Background: Airlines occupy an increasingly important place in the economy of many countries. Because air disasters may cause substantial losses, comprehensive surveys of the psychophysiological mechanism of flying are needed; however, relatively few studies have focused on pilots. The default mode network (DMN) is an important intrinsic connectivity network involved in a range of functions related to flying. This study aimed to examine functional properties of the DMN in pilots. Method: Resting-state functional magnetic resonance imaging data from 26 pilots and 24 controls were collected. Independent component analysis, a data-driven approach, was combined with functional connectivity analysis to investigate functional properties of the DMN in pilots. Results: The pilot group exhibited increased functional integration in the precuneus/posterior cingulate cortex (PCC) and left middle occipital gyrus. Subsequent functional connectivity analysis identified enhanced functional connection between the precuneus/PCC and medial superior frontal gyrus. Conclusion: The pilot group exhibited increased functional connections within the DMN. These findings highlight the importance of the DMN in the neurophysiological mechanism of flying.
In the present paper, as continuous work about linguistics truth-valued LIA and its properties (CESA2006), the lattice value propositional logic system whose valuation field look as linguistic truth value LIA (briefly, L-LIA) is focused. Firstly, some properties about linguistic truth value LIA are discussed. On the other hand, some concepts about linguistic truth value lattice-valued propositional logic system ℓP(X) is established, whose truth value domain is a linguistic truth-valued lattice implication algebra, and the semantic problems of ℓP(X) are investigated.
Air transportation networks play important roles in human mobility. In this paper, from the perspective of multilayer network mechanism, the dynamics of the Chinese air transportation network are extensively investigated. A multilayer-based passengers re-scheduling model is introduced, and a multilayer cooperation (MC) approach is proposed to improve the efficiency of network traffic under random failures. We use two metrics: the success rate and the extra transfer number, to evaluate the efficiency of re-scheduling. It is found that a higher success rate of passengers re-scheduling can be obtained by MC, and MC is stronger for resisting the instability of the capacity of links. Furthermore, the explosion of the number of extra transfer can be well restrained by MC. Our work will highlight a better understanding of the dynamics and robustness of the Chinese air transportation network.
This paper presents the intelligent landing control system that overcome wind disturbance problem of a civil aviation aircraft during the landing phase when subjected to severe winds and failures such as stuck control surfaces. The controller architecture uses a dual fuzzy neural network (DFNN) controller, which is capable of implementing fuzzy inference in general and neural network mechanism in particular. A systematic method for mapping an existing rule base into a set of dual fuzzy neural network weights has also been presented. However, in order to utilize this method to initialize the dual fuzzy neural network weights, such a rule base obtained from domain experts or from experimental data through systematic, knowledge acquisition methods has been proposed. It uses one neural network as on-line learning and does not need a priori training. Simulations show that it improved the performance of conventional automatic landing system (ALS) and guide the aircraft to a safe landing.
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