Car-following strategy of intelligent connected vehicle using extended disturbance observer adjusted by reinforcement learning

Disturbance observer-based control method has achieved good results in the carfollowing scenario of intelligent and connected vehicle(ICV).However,the gain of conventional extended disturbance observer(EDO)-based control method is usually set manually rather than adjusted adaptively according to real time traffic conditions,thus declining the car-following performance.To solve this problem,a car-following strategy of ICV using EDO adjusted by reinforcement learning is proposed.Different from the conventional method,the gain of proposed strategy can be adjusted by reinforcement learning to improve its estimation accuracy.Since the“equivalent disturbance”can be compensated by EDO to a great extent,the disturbance rejection ability of the carfollowing method will be improved significantly.Both Lyapunov approach and numerical simulations are carried out to verify the effectiveness of the proposed method.

新时代延安红色教育资源数字化及其育人路径研究

红色教育资源具有教育人、激励人、塑造人等教育功能。新时代,充分挖掘延安红色资源时代价值,拓展延安红色教育资源数字化服务方式,实现延安红色教育资源在立德树人方面的育人功效具有十分重要的现实意义。文章首先分析延安红色资源内涵与特点,归纳总结了新时代延安红色教育资源数字化服务方式;然后以延安大学为例,提出新时代红色教育资源育人的主要路径:构建现代技术与红色资源思政教育一体化育人模式、打造新技术与沉浸体验式红色资源的育人新方式、建立“互联网+”红色资源育人共享平台。

Empowering fall webworm surveillance with mobile phone-based community monitoring: a case study in northern China

Recent advances in information and communication technologies, such as mobile Internet and smartphones, have created new paradigms for participatory environment monitoring. The ubiquitous mobile phones with capabilities such as a global positioning system,camera, and network access, offer opportunities to establish distributed monitoring networks that can perform a wide range of measurements for a landscape. This study examined the potential of mobile phone-based community monitoring of fall webworm(Hyphantria cunea Drury).We built a prototype of a participatory fall webworm monitoring system based on mobile devices that streamlined data collection, transmission, and visualization. We also assessed the accuracy and reliability of the data collected by the local community. The system performance was evaluated at the Ziya commune of Tianjin municipality in northern China, where fall webworm infestation has occurred. The local community provided data with accuracy comparable to expert measurements(Willmott's index of agreement>0.85). Measurements by the local community effectively complemented remote sensing images in both temporal and spatial resolution.

Optimal Overbooking Mechanism in Data Plan Sharing

For mobile devices users, the inconvenience caused by the fixed data plans becomes a popular issue. With the help of personal hotspot (pH), however, the smartphone users can share network connection with other users nearby. In this paper a data plan sharing platform with reservation mechanism is proposed. The users on this platform can sell their surplus data plan traffic to make profit. A Markov decision process model was formulated and analyzed for data plan sharing platform revenue management through overbooking mechanism. The results of experiment and simulation show that the platform revenue has a considerable growth using this model.

Synaptic transistor with multiple biological functions based on metal-organic frameworks combined with the LIF model of a spiking neural network to recognize temporal information

Spiking neural networks(SNNs)have immense potential due to their utilization of synaptic plasticity and ability to take advantage of temporal correlation and low power consumption.The leaky integration and firing(LIF)model and spike-timing-dependent plasticity(STDP)are the fundamental components of SNNs.Here,a neural device is first demonstrated by zeolitic imidazolate frameworks(ZIFs)as an essential part of the synaptic transistor to simulate SNNs.Significantly,three kinds of typical functions between neurons,the memory function achieved through the hippocampus,synaptic weight regulation and membrane potential triggered by ion migration,are effectively described through short-term memory/long-term memory(STM/LTM),long-term depression/long-term potentiation(LTD/LTP)and LIF,respectively.Furthermore,the update rule of iteration weight in the backpropagation based on the time interval between presynaptic and postsynaptic pulses is extracted and fitted from the STDP.In addition,the postsynaptic currents of the channel directly connect to the very large scale integration(VLSI)implementation of the LIF mode that can convert high-frequency information into spare pulses based on the threshold of membrane potential.The leaky integrator block,firing/detector block and frequency adaptation block instantaneously release the accumulated voltage to form pulses.Finally,we recode the steadystate visual evoked potentials(SSVEPs)belonging to the electroencephalogram(EEG)with filter characteristics of LIF.SNNs deeply fused by synaptic transistors are designed to recognize the 40 different frequencies of EEG and improve accuracy to 95.1%.This work represents an advanced contribution to brain-like chips and promotes the systematization and diversification of artificial intelligence.

Enhancing performance of tin-based perovskite solar cells via fused-ring electron acceptor

The performance of tin-based perovskite solar cells has been substantially hampered by voltage loss caused by energy level mismatch,charge recombination,energetic disorder,and other issues.Here,a fused-ring electron acceptor based on indacenodithiophene(IDIC)was for the first time introduced as a transition layer between a tin-based perovskite layer and a C 60 electron transport layer,leading to better matched energy levels in the device.In addition,coordination interactions between IDIC and perovskite improved the latter's crystallinity.The introduction of IDIC raised the power conversion efficiency from 8.98%to 11.5%and improved the device's stability.The decomposition mechanism of tin-based perovskite was also revealed by detecting the optical properties of perovskite microdomains through innovative integration of confocal laser scanning microscopy and photoluminescence spectroscopy.

锡基钙钛矿太阳能电池研究进展

有机-无机杂化钙钛矿具有优异的光吸收性能和较高的载流子迁移率等优点,相应的钙钛矿太阳能电池在经历短短11年的发展后,光电转换效率已接近单晶硅电池.同时,制备工艺简单、生产成本低等优势令钙钛矿太阳能电池具有极大的商业潜力.然而,存在于传统钙钛矿太阳能电池中铅的毒性仍是限制其大规模生产最重要的阻碍之一.低毒性的锡基钙钛矿继承了铅基钙钛矿绝大部分优异的光电性能,目前最高的光电转换效率已超过13%,但与铅基相比还有一定差距.本文首先介绍锡基钙钛矿的结构和性质,然后分别从添加剂和组分调控两个角度综述锡基钙钛矿太阳能电池近年来的重要研究进展,最后总结该领域存在的挑战和发展方向.