检索结果-内蒙古大学图书馆

SSRN 2024年

作者： Tao, Youliang Nie, Zhongquan Zhang, Xuefeng Pan, Deng Wang, Han College of Aeronautics and Astronautics Taiyuan University of Technology Taiyuan030024 China Key Lab of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi Province College of Electronic Information and Optical Engineering Taiyuan University of Technology Taiyuan030024 China Institute of New Carbon Materials College of Materials Science and Engineering Taiyuan University of Technology Taiyuan030024 China Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui University 111 Jiu Long Road Hefei230601 China

Carbon-based nanomaterials with excellent electrical and optical properties are highly sought after for a plethora of hybrid applications ranging from advanced opto-electronic components to sustainable energy storage devices. In this contribution, we examine in detail the dependence of electrical conductivity and ultrafast optical nonlinearity of graphene oxide (GO) films on their degrees of reduction, as well as the link between the two properties. The GO films are first synthesized through the vacuum filtration method and then reduced partially controllably by the femtosecond laser direct writing with varying power doses. Subsequently, the 4-point probe measurements of the reduced GO (r-GO) films are demonstrated to exhibit superior resistivity and electrical conductivity compared with the pristine GO counterpart. It was found that the conductivity of the film increases and then decreases with increasing ablation laser power (P), GO was completely reduced at P = 100 mW with resistivity and electrical conductivity of 1.09 × 10-3Ω·m and 9.19 × 102s/m, respectively. GO was over reduced at P = 120 mW with resistivity and electrical conductivity being 3.72 × 10-3Ω·m and 2.69 × 102s/m, respectively. We further test the ultrafast optical nonlinearity (ONL) of the as-prepared pristine and reduced GO with the femtosecond Z-scan technique. The results show that the behavior of ONL is reversed whenever GO is reduced in a controlled manner. More interestingly, the higher the ablation laser power is, the stronger the optical nonlinearity of r-GO is. In particular, the nonlinear absorption and refraction coefficients of the r-GO films reach up to 3.26 × 10-8 m/W and -1.12 × 10-13 m2/W when P = 120 mW. The nonlinear absorption and refraction coefficients reach 1.9 × 10-8 m/W and -3 × 10-13 m2/W, respectively, for P = 70 mW. The GO/r-GO films endowing tunable electro-optical responses are potential building blocks for wide-ranging applications in microelectronic circuits, optoele

关键词： Femtosecond lasers

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Spatial non-locality induced non-markovian EIT in a single giant atom

arXiv

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arXiv 2021年

作者： Zhu, Y.T. Wu, R.B. Xue, S. Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China Department of Automation Tsinghua University Beijing100084 China Beijing National Research Center for Information Science and Technology Beijing100084 China

In recent experiments, electromagnetically induced transparency (EIT) were observed with giant atoms, but nothing unconventional were found from the transmission spectra. In this letter, we show that unconventional EIT does exist in giant atoms, and indicate why it has not been observed so far. Different from these existing works, this letter presents a consistent theory including a real space method and a time delayed master equation for observing unconventional EIT. We discover that this phenomenon is a quantum effect which cannot be correctly described in a semi-classical way as those in recent works. Our theory shows that it can be observed when the time delay between two neighboring coupling points is comparable to the relaxation time of the atom, which is crucial for a future experimental observation. This new phenomenon results from inherent non-locality of the giant atom, which physically forces propagating fields to be standing waves in space and the atom exhibiting retardations in time. Our theory establishes a framework for application of nonlocal systems to quantum information processing. Copyright © 2021, The Authors. All rights reserved.

关键词： Atoms

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An IMU Error Correction Method Based on Multithreshold ZV Detection and SRCKF

An IMU Error Correction Method Based on Multithreshold ZV De...

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Cyber-Physical Social Intelligence (ICCSI), International Conference on

作者： Jialiang Luo Shichao Chen Yisheng Lv Wenqiao Sun Fan Yang Ruijie Xu The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences School of Information Engineering China University of Geosciences Beijing China The State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences The Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited Beijing China The State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China Transportation and Economics Research Institute and the Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited China The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences College of Rail Transit Shan Dong JiaoTong University Jinan China Department of Aeronautical and Aviation Engineering The Hong Kong Polytechnic University Hong Kong China

With the rapid development and widespread application of Inertial Measurement Units (IMUs), IMU-based human localization has become critically important in environments lacking Global Navigation Satellite systems (GNSS) signals. Methods such as UWB/WIFI and other anchor-based localization have been employed to enhance the positioning accuracy. However, these methods are susceptible to the environmental interference and increased costs. In contrast, SINS-based localization methods eliminate reliance on the external data. However, this method can suffer from drift errors due to cumulative integration errors. Inertial navigation error correction techniques like Zero Detection Update technology (ZUPT) provide potential solutions to address drift errors. This paper proposes an error correction method based on the multithreshold zero-velocity detection and Square Root Cubature Kalman Filter (SRCKF) updates. Compared to the single fixed threshold detection, the multi-threshold zero-velocity detection reduces the likelihood of missed zero velocity detection and false alarms, providing accurate time intervals for error correction. Experimental results demonstrate that the SRCKF-based algorithm reduces position deviation to approximately 0.3146 meters, corresponding to an error ratio of1.14%. The proposed method enables cost-effective and accurate pedestrian localization, driving advancements in the field.

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An Improved Chimp Optimization Algorithm for Short-term Hydrothermal Scheduling

IAENG International Journal of Computer Science

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IAENG International Journal of Computer science 2022年第3期49卷 666页

作者： Chen, Gonggui Wang, Shumin He, Yongsheng Shang, Wanfeng Long, Hongyu Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing University of Posts and Telecommunications Chongqing400065 China Chongqing University of Posts and Telecommunications Chongqing400065 China State Grid Chongqing Electric Power Company Chongqing400015 China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen Shenzhen518055 China Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing400065 China

The short-term hydrothermal scheduling (STHS) is a complex non-linear, non-convex and high-dimensional mathematical optimization problem. Due to the fact that the original chimp optimization algorithm (ChOA) is likely to fall into local optimum and has the disadvantage of low population diversity, an improved chimp optimization algorithm (IChOA) is proposed to solve the STHS problem. Firstly, Logistic-Tent chaotic mapping is employed to initialize the population and increase the population diversity. Then a new nonlinear convergence factor is introduced to make the optimization search process more applicable to STHS problems. Next, particle swarm algorithm (PSO) and gravitational search algorithm (GSA) are combined to enhance the shortcoming and balance the global search ability and local exploration ability of ChOA. Moreover, Cauchy mutation and opposition-based learning strategy are supplemented as perturbation interference when the optimal position is not updated to improve the ability to leap out of the local optimum. Finally, a graded optimization strategy is adopted for the constraint handing of dynamic reservoir balance and thermal power balance. Three standard hydrothermal power systems are utilized to verify the practicability and validity of the proposed method. Results of simulations reveal that IChOA has significant competitive advantages in addressing the STHS problem. © 2022, IAENG International Journal of Computer science. All Rights Reserved.

关键词： Particle swarm optimization (PSO)

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Non-Stoichiometric Protic Ionic Liquids for Efficient Carbon Dioxide Capture and Subsequent Conversion Under Mild Conditions

SSRN

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SSRN 2024年

作者： Wang, Litian Chen, Jie Wang, Shuai Zhou, Tongyao Li, Dan Li, Cuiping Qian, Lirong Xiong, Yang Miao, Lin Xie, Zhiyong Tianjin Key Laboratory of Film Electronic and Communication Devices School of Integrated Circuit Science and Engineering Tianjin University of Technology Tianjin300384 China School of Integrated Circuit Science and Engineering Tianjin University of Technology Tianjin300384 China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China China Tianjin Bohua Yongli Chemical Industry CO. Ltd Tianjin30045 China

Protic ionic liquids (PILs) have emerged as innovative solvents with significant potential for CO2 capture and transformation, presenting a sustainable alternative to conventional methods which often involve energy-intensive processes or environmentally detrimental chemicals. Herein, a novel strategy for CO2 capture and conversion at mild conditions using non-stoichiometric protic ionic liquids (NPILs) was demonstrated for the first time. These NPILs, employed as sorbents, solvents, and catalysts, were composed of imidazole (Im) and 1,8-diazabicyclo [5.4.0] undec-7-ene (DBU) in various ratios. Correlations between the mole ratio of DBU/Im and physicochemical properties such as viscosity, conductivity, thermal stability, and the distribution of neutral and ionic species were systematically investigated. Effects of the absorption temperature and CO2 partial pressure on the absorption capacity were also studied. Different absorption mechanisms, including carbonate and carbamate pathways, were analyzed using FT-IR and NMR spectroscopy. Moreover, the fixed CO2 could be catalytically converted to quinazoline-2,4(1H,3H)-diones under exceptionally mild reaction conditions (1atm, 50 °C, metal-free process). A plausible reaction mechanism involving simultaneous CO2 activation and substrate activation for the transformation of CO2 into quinazoline-2,4(1H,3H)-diones was verified through NMR spectra. It is believed that the new insights into the CO2 mechanism will facilitate the rationaldesign of functional ionic liquids for CO2 capture, utilization, and storage in the future. © 2024, The Authors. All rights reserved.

关键词： Carbon dioxide

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Robust sampled-data control for Itô stochastic Markovian jump systems with state delay

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International Journal of Robust and Nonlinear control 2018年第15期28卷

作者： Guoliang Chen Jian Sun Jianwei Xia School of Automation Beijing Institute of Technology Beijing China Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China School of Mathematics Science Liaocheng University Liaocheng China

In this paper, the problem of robust sampled-data control for Itô stochastic Markovian jump systems (Itô SMJSs) with state delay is investigated. Using parameters-dependent Lyapunov functionals and some stochastic equations, we give stochastic sufficient stability criteria for polytopic uncertain Itô SMJSs. As a corollary, stochastic sufficient stability criteria are given for nominal Itô SMJSs. For this two cases of Itô SMJSs, based on the obtained stochastic stability criteria, their time-independent sampled-data controllers are designed, respectively. Then, for designing a time-dependent sampled-data controller for Itô SMJSs, a parameters-dependent time-scheduled Lyapunov functional is developed. New stochastic sufficient stability criteria are obtained for polytopic uncertain Itô SMJSs and nominal Itô SMJSs. Furthermore, their time-dependent sampled-data controllers are designed, respectively. Lastly, a numerical example is provided to illustrate the effectiveness of the proposed method.

关键词： Itô stochastic Markovian jump systems parameters-dependent time-scheduled Lyapunov functional robust sampled-data control stability

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On the role of shape features in metaphor generation for abstract images

On the role of shape features in metaphor generation for abs...

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International Symposium on Soft Computing and intelligent systems (SCIS)

作者： Asuka Terai Natsuki Yamamura Junichi Chikazoe Takaaki Yoshimoto Norihiro Sadato Koji Jimura Dept. of Complex and Intelligent Systems Future University Hakodate Hokkaido Japan Research and Development Dept Araya Inc Tokyo Japan Res. Org. of Science and Technology Ritsumeikan University Kyoto Japan Dept. of System Neuroscience National Institute for Physiological Sciences Aichi Japan Dept. of Informatics Gunma University Gunma Japan

In this study, we examined the role of shape features on metaphor generation for abstract images based on a simulation with a retrained convolutional neural network (CNN), which is in turn based on a pretrained CNN model (AlexNet). A computational experiment was conducted using three types of object recognition models, including a pretrained object recognition model (AlexNet) and recognition models that were retrained to recognize more or fewer shape features using edge-detected or blurred images from the ILSVRC-2012 dataset. A psychological experiment was conducted to collect metaphors that were used to explain the abstract images. The simulation results of the models for the abstract images were compared to examine how well they predicted the concepts used in the metaphors generated for the abstract images. The results of the computational experiment suggest that the model retrained to recognize fewer shape features performed best at predicting the generated metaphors. However, for some abstract images, the model retrained to recognize more shape features performed better. These results suggest that the role of shape features on metaphor generation differs depending on the types of abstract images.

关键词： Shape Image color analysis Image edge detection Computational modeling Simulation Psychology Predictive models

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Compound Fault Diagnosis of Planetary Gearbox Using Capsule Network with Multi-Scale Convolutional Neural Network

Compound Fault Diagnosis of Planetary Gearbox Using Capsule ...

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Prognostics and system Health Management Conference (PHM)

作者： Guoyan Li Jingbin Zhang Guoliang Lu School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China Key Laboratory of Advance Transducers and Intelligent Control System Ministry of Education Taiyuan University of Technology Taiyuan China Key Laboratory of High-efficiency and Clean Mechanical Manufacture of MOE National Demonstration Center for Experimental Mechanical Engineering Education School of Mechanical Engineering Shandong University Jinan China

ISBN: (数字)9798350360585

ISBN: (纸本)9798350360592

Capsule network is an innovative deep learning-based model that uses neuron vectors as inputs and outputs of the network. It can achieve independent output of multiple classification labels, and solve the problem of decoupling recognition of compound fault components in planetary gearboxes. However, the single-scale feature extraction cannot fully explore multi-scale feature information in compound fault signals. This study proposes a capsule network combined with multi-scale convolutional feature fusion to diagnose the compound fault of planetary gearbox. The multi-scale features are extracted from STFT images of vibration signals using convolutional layers with different kernel sizes; secondly, a capsule network is designed to classify and identify the fault components by using the dynamic routing algorithm. The experiments are conducted to assess the performance of the proposed method, and the results indicates that it can effectively decoupling identify the compound faults with strong anti-interference and stability.

关键词： Fault diagnosis Vibrations Convolution Heuristic algorithms Feature extraction Stability analysis Vectors

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A Novel Sensitization Mechanism of Stress-Electric-Coupled Biosensor Originated in Magnetostrictive Effect

SSRN

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SSRN 2022年

作者： Sang, Shengbo Ge, Yang Ji, Jianglong Yuan, Zhongyun Dong, Xiushan Zhou, Chuangang Xiao, Pengli Tan, Qiuyun Zhao, Dong MicroNano System Research Center Key Lab of Advanced Transducers and Intelligent Control System The Ministry of Education College of Information and Computer Taiyuan University of Technology Taiyuan030024 China School of Electrical Engineering College of Engineering Science Hanyang University Seoul04763 Korea Republic of Shanxi Bethune Hospital Taiyuan030024 China Six-dimensional Artificial Intelligence Biomedical Research Institute Taiyuan030024 China

The stress-electric coupling based on receptor functionalization provides a new paradigm for the development of biosensor. However, the gravity factor of sensitive element usually shows difficult to be avoided due to its suppression to biosensor sensitivity. Herein, a magnetic-sensitization biosensing system with multi-physical field coupling of stress, magnetism and electricity was proposed to highly detect biomolecules. The gravitational interference of sensitive membrane was conquered by doping the TbDyFe with magnetostrictive effect into polydimethylsiloxane (PDMS) and applying magnetic field, showing great contributions to magnetic sensitization. The magnetic sensitization of the biosensor was proved by the collaboration of experiment and simulation. The detections of urine protein and urine sugar associated with kidney disease were realized with limits of detection (LOD) of 0.21 ng/mL and 0.45 nM by using the magnetic-sensitization biosensor. The prepared biosensor exhibited the high specificity, selectivity, stability and repeatability. Especially, the HSA and glucose in real samples can be accurately detect, showing good practicability of the prepared biosensor. This study provides a way to improve the sensitivity of the mechanical biosensor. © 2022, The Authors. All rights reserved.

关键词： Silicones

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Sources of atmospheric glyoxal and methylglyoxal in Beijing and its impact on wintertime secondary organic aerosol formation

Sources of atmospheric glyoxal and methylglyoxal in Beijing ...

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第二十四届大气污染防治技术研讨会

作者： Xionghui Qiu Shuxiao Wang Qi Ying Lei Duan Jia Xing Jingyuan Cao Di Wu Xiaoxiao Li Chengzhi Xing Xiao Yan Cheng Liu Jiming Hao MOE Key Laboratory of Resources and Environmental System Optimization College of Environmental Science and Engineering North China Electric Power University State Key Joint Laboratory of Environmental Simulation and Pollution Control School of Environment Tsinghua University State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Zachry Department of Civil Engineering Texas A&M University College Station School of Earth and Space Sciences University of Science and Technology of China National Engineering Research Center of Urban Environmental Pollution Control Beijing Municipal Research Institute of Environmental Protection Department of Precision Machinery and Precision Instrumentation University of Science and Technology of China

Atmospheric glyoxal(GLY) and methylglyoxal(MGLY) are key precursors of secondary organic aerosol(SOA). However, anthropogenic emissions of GLY and MGLY and their contribution to surface GLY and MGLY concentrations, as well as the secondary organic aerosol(SOA) formation, are not well quantified. By developing an emission inventory of anthropogenic GLY and MGLY and improving Community Multiscale Air Quality Model(CMAQ) with SOA formation from irreversible surface uptake of GLY and MGLY, as well as a precursor-origin resolved technique, we quantified the source contributions of GLY and MGLY and their impact on wintertime SOA formation in Beijing, China. The total emissions of GLY and MGLY in Beijing in 2017 are 1.1×10～4 kmol and 7.0×10～3 kmol, respectively. Anthropogenic primary emissions are found to be the dominant contributor to GLY and MGLY concentrations(～74% for GLY and ～63% for MGLY). Anthropogenic primary emissions of GLY and MGLY contributes to 30% of GLY/MGLY SOA daily average concentration and accounts for up to 45% of nighttime GLY/MGLY SOA. The study suggests that the anthropogenic GLY and MGLY emissions, mainly from gasoline vehicles and cooking, are important for SOA formation and shall be strictly controlled in Chinese megacities.

关键词： SOA Sources of atmospheric glyoxal and methylglyoxal in Beijing and its impact on wintertime secondary organic aerosol formation

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