Iconic memory and short-term memory are not only crucial for perception and cognition,but also of great importance to mental health.Here,we first showed that both types of memory could be improved by improving limitin...Iconic memory and short-term memory are not only crucial for perception and cognition,but also of great importance to mental health.Here,we first showed that both types of memory could be improved by improving limiting processes in visual processing through perceptual learning.Normal adults were trained in a contrast detection task for ten days,with their higher-order aberrations(HOA)corrected in real-time.We found that the training improved not only their contrast sensitivity function(CSF),but also their iconic memory and baseline information maintenance for short-term memory,and the relationship between memory and CSF improvements could be well-predicted by an observer model.These results suggest that training the limiting component of a cognitive task with visual perceptual learning could improve visual cognition.They may also provide an empirical foundation for new therapies to treat people with poor sensory memory.展开更多
This paper proposes a deformation evolution and perceptual prediction methodology for additive manufacturing of lightweight composite driven by hybrid digital twins(HDT).In order to improve manufacturing quality of ir...This paper proposes a deformation evolution and perceptual prediction methodology for additive manufacturing of lightweight composite driven by hybrid digital twins(HDT).In order to improve manufacturing quality of irregular lightweight composite through boosting conceptual design in aeronautic and aerospace engineering,the HDT meaning hybridization of physical and digital domains,including deformation and energy efficiency can be built,where the essential parameters can be perceptually predicted in advance,by virtue of the fusion of physical sensors and digital information.The long short term memory(LSTM)can be employed to void vanishing gradient problem and improve predicting precision via Recurrent Neural Networks,thereby laying a foundation for the HDT.The diverse manufacturing requirements of different regions are integrated into the parameters designing phase by attaching region weights confirmed via empiricism and in-service simulation.The effects of slicing strategy and external support structures on manufacturing quality are considered from the perspective of improving dimensional accuracy.The manufacturing efficiency and comprehensive costs are accounted as consideration factors,which are perceptually predicted via LSTM.The designed manufacturing parameters through HDT were virtually examined by evaluating the deformation and equivalent stress distributions of fabricated lightweight component with composite material through AM process simulation.The physical experiments were conducted to verify the HDT-based pre-designing and optimization method of manufacturing parameters via fused deposition modeling(FDM).The energy consumption of actual manufacturing process was measured via digital power meter and applied to evaluate accuracy of perceptual prediction outcomes.The dimensional accuracy and distortion distribution of the manufactured lightweight prototype made with composite material were measured through the coordinate measuring machine(CMM)and 3D optical scanner.The proposed method demonstrates effec展开更多
基金This work was supported by the National Natural Science Foundation of China(31970975)the Natural Science Foundation for Distinguished Young Scholars of Zhejiang Province,China(LR22H120001)+2 种基金the Scientific Instrument Developing Project of the Chinese Academy of Sciences(ZDKYYQ20200005)the National Science and Technology Innovation 2030 Major Program(2022ZD0204801)the Project of State Key Laboratory of Ophthalmology,Optometry and Vision Science,Wenzhou Medical University(J02-20210203).
文摘Iconic memory and short-term memory are not only crucial for perception and cognition,but also of great importance to mental health.Here,we first showed that both types of memory could be improved by improving limiting processes in visual processing through perceptual learning.Normal adults were trained in a contrast detection task for ten days,with their higher-order aberrations(HOA)corrected in real-time.We found that the training improved not only their contrast sensitivity function(CSF),but also their iconic memory and baseline information maintenance for short-term memory,and the relationship between memory and CSF improvements could be well-predicted by an observer model.These results suggest that training the limiting component of a cognitive task with visual perceptual learning could improve visual cognition.They may also provide an empirical foundation for new therapies to treat people with poor sensory memory.
基金Supported by National Key Research and Development Project of China(Grant No.2022YFB3303303)Zhejiang Provincial Research and Development Project of China(Grant No.LGG22E050010)Key Open Fund of State Key Laboratory of Materials Processing and Die and Mould Technology of China(Grant No.P2024-001).
文摘This paper proposes a deformation evolution and perceptual prediction methodology for additive manufacturing of lightweight composite driven by hybrid digital twins(HDT).In order to improve manufacturing quality of irregular lightweight composite through boosting conceptual design in aeronautic and aerospace engineering,the HDT meaning hybridization of physical and digital domains,including deformation and energy efficiency can be built,where the essential parameters can be perceptually predicted in advance,by virtue of the fusion of physical sensors and digital information.The long short term memory(LSTM)can be employed to void vanishing gradient problem and improve predicting precision via Recurrent Neural Networks,thereby laying a foundation for the HDT.The diverse manufacturing requirements of different regions are integrated into the parameters designing phase by attaching region weights confirmed via empiricism and in-service simulation.The effects of slicing strategy and external support structures on manufacturing quality are considered from the perspective of improving dimensional accuracy.The manufacturing efficiency and comprehensive costs are accounted as consideration factors,which are perceptually predicted via LSTM.The designed manufacturing parameters through HDT were virtually examined by evaluating the deformation and equivalent stress distributions of fabricated lightweight component with composite material through AM process simulation.The physical experiments were conducted to verify the HDT-based pre-designing and optimization method of manufacturing parameters via fused deposition modeling(FDM).The energy consumption of actual manufacturing process was measured via digital power meter and applied to evaluate accuracy of perceptual prediction outcomes.The dimensional accuracy and distortion distribution of the manufactured lightweight prototype made with composite material were measured through the coordinate measuring machine(CMM)and 3D optical scanner.The proposed method demonstrates effec
