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All-optical logic gates based on hierarchical photonic crystal modulated photoluminescence of perovskite nanocrystals

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science China(Technological sciences) 2023年第9期66卷 2735-2742页

作者： WANG Yun ZHA YanFang YANG YunYi LIU CiHui DI YunSong CAO GuiYuan WEI ShiBiao CHEN ZhiHui GAN ZhiXing Center for Future Optoelectronic Functional Materials School of Computer and Electronic InformationSchool of Artificial IntelligenceNanjing Normal UniversityNanjing 210023China Centre for Translational Atomaterials School of ScienceSwinburne University of TechnologyHawthorn VIC 3122Australia Nanophotonics Research Center Shenzhen Key Laboratory of Micro-Scale Optical Information TechnologyShenzhen UniversityShenzhen 518060China Key Laboratory of Advanced Transducers and Intelligent Control Systems Ministry of Education and Shanxi ProvinceCollege of Electronic Information and Optical EngineeringTaiyuan University of TechnologyTaiyuan 030024China

Halide perovskites exhibit high performance in all sorts of optoelectronic and photonic areas, suggesting their huge potential in integrated photonic devices. However, until now, all optical logic gates based on perovskites are still rarely explored, hindering the development of all-optical networks and computing. Herein, a new concept of all-optical logic gates is proposed based on the modulation of photoluminescence(PL) from perovskite nanocrystals(PNCs). A hierarchical photonic crystal(Hie PhC) is developed by self-assembling polystyrene(PS) and SiO2nanoparticles, which exhibit a higher PL enhancement than that of a monolayer PhC. Moreover, the light-controlled PL is realized by taking advantage of the high thermal response of the PL from PNCs/Hie PhC on polyethylene(PE) substrate, assisted by a graphene layer for light-heat conversion. Consequently, optical diode and triode are achieved based on the modulated PL, which exhibit contrast ratios(CR) of 24.7 and 74.0 dB, ***-optical logic gates, including “AND”, “OR” and “NOT”, are realized based on the optical diode and triode.

关键词： perovskite nanocrystals photonic crystals all-optical logic gates modulation of photoluminescence

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Building Edge Detection technology from Remote Sensing Image Based on NSCT and Tensor Voting 8

Building Edge Detection Technology from Remote Sensing Image...

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2024 8th International Conference on Machine Vision and Information technology, CMVIT 2024

作者： Wu, Yingbin Zhao, Peng Zhou, Mingquan Geng, Shengling Zhang, Dan School of Computer Science Qinghai Normal University Qinghai Xining China School of Mathematics and Information Technology Yuncheng University Shanxi Yuncheng China State Key Laboratory of Tibetan Intelligent Information Processing and Application Qinghai Xining China

An edge detection technology based on the combination of non-downsampling contour wave transform (NSCT) and tensor voting is proposed, which aims to obtain more accurate and detailed edge information of buildings in remote sensing images. Firstly, NSCT is used for image decomposition to obtain the subband frequency information of different scales and angles. Then, position encoding is performed on these subband coefficients to obtain second-order symmetric tensors at the corresponding positions. Tensors of different scales and angles at the same position are weighted and summed to complete feature fusion. Finally, the edge features of the image are obtained based on tensor voting theory. The experimental results show that compared to common edge detection technologies, such as Canny, Fast Edge (Fast edge detection using structured forests) and HED (Holistically-Nested Edge Detection), our method can more accurately and intensively reflect the boundaries of buildings and the edge information of roofs, providing better support for the analysis of building types and architectural styles. Compared to the HED method, which is based on deep learning, our method improves PSNR and SSIM metrics by 0.98 and 0.03, respectively. © Published under licence by IOP Publishing Ltd.

关键词： Edge detection

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High Performance 3D ITZO DGTFTs and Their Application in Wearable Pulse Sensors

High Performance 3D ITZO DGTFTs and Their Application in Wea...

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2024 IEEE International Electron Devices Meeting, IEDM 2024

作者： Lin, Delang Chen, Rongsheng Tseng, Man Chun Yeung, Fion Sze Yan Kwok, Hoi Sing School of Microelectronics South China University of Technology Guangzhou China State Key Laboratory of Advanced Displays and Optoelectronics Technologies Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong

ISBN: (纸本)9798350365429

This work presents the development of InSnZnO (ITZO) three-dimensional (3D) channel dual-gate thin-film transistors (DGTFTs) prepared by magnetron sputtering. The employment of an n-octyltriethoxysilane protection layer, prepared via liquid-phase self-assembly, effectively mitigates plasma-induced damage to the ITZO channel layer during top gate dielectric sputtering. Moreover, the high-k ZrO2 top gate dielectric and 3D channel structure endow the ITZO DGTFTs with excellent transistor performance, high electrical stability, and flexible mechanical reliability. These attributes include a low threshold voltage of 0.2 V, a high mobility of 41.7 cm2V-1s-1, and a competitive top gate coupling coefficient of -2.24. Finally, the ultra-high top-gate voltage coupling effect allows the ITZO DGTFT-based wearable pulse sensor accurately recognizes pulse waveforms from various parts of the body, including the temples, and infers blood pressure changes. © 2024 IEEE.

关键词： Gate dielectrics

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Two-Stage Representation Refinement Based on Convex Combination for 3-D Human Poses Estimation

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第12期5卷 6500-6508页

作者： Chen, Luefeng Cao, Wei Zheng, Biao Wu, Min Pedrycz, Witold Hirota, Kaoru China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada Macau University of Science and Technology Institute of Systems Engineering Taipa999078 China Istinye University Research Center of Performance and Productivity Analysis Istanbul34010 Turkey Tokyo Institute of Technology Yokohama226-8502 Japan

In the human pose estimation task, on the one hand, 3-D pose always has difficulty in dividing different 2-D poses if the view is limited;on the other hand, it is hard to reduce the lifting ambiguity because of the lack of depth information, it is an important and challenging problem. Therefore, two-stage representation refinement based on the convex combination for 3-D human pose estimation is proposed, in which the two-stage method includes a dense-spatial-temporal convolutional network and a local-to-refine network. The former is applied to determine the features between each video frame;the latter is used to get the different scales of pose details. It aims to address the difficulty of estimating 3-D human pose from 2-D image sequences. In such a way, it can better use the relations between every frame in the sequence of the pose video to produce more accurate results. Finally, we combine the above network with a block called convex combination to help refine the 3-D pose location. We test the proposed approach on both Human3.6m and MPII datasets. The result confirms that our method can achieve better performance than improved CNN supervision, a simple yet effective baseline, and coarse-to-fine volumetric prediction. Besides, a robustness test experiment is carried out for the proposed method while the input is interrupted. The result verifies that our method shows better robustness. © 2024 IEEE.

关键词： Convolution

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An inverse design method for supercritical airfoil based on conditional generative models

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Chinese Journal of Aeronautics 2022年第3期35卷 62-74页

作者： Jing WANG Runze LI Cheng HE Haixin CHEN Ran CHENG Chen ZHAI Miao ZHANG Shanghai Aircraft Design and Research Institute Shanghai 200436China School of Aerospace Engineering Tsinghua UniversityBeijing 100084China Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation Department of Computer Science and EngineeringSouthern University of Science and TechnologyShenzhen 518055China

Inverse design has long been an efficient and powerful design tool in the aircraft *** this paper,a novel inverse design method for supercritical airfoils is proposed based on generative models in deep learning.A Conditional Variational Auto Encoder(CVAE)and an integrated generative network CVAE-GAN that combines the CVAE with the Wasserstein Generative Adversarial Networks(WGAN),are conducted as generative *** are used to generate target wall Mach distributions for the inverse design that matches specified features,such as locations of suction peak,shock and aft *** and quantitative results show that both adopted generative models can generate diverse and realistic wall Mach number distributions satisfying the given *** CVAE-GAN model outperforms the CVAE model and achieves better reconstruction accuracies for all the samples in the ***,a deep neural network for nonlinear mapping is adopted to obtain the airfoil shape corresponding to the target wall Mach number *** performances of the designed deep neural network are fully demonstrated and a smoothness measurement is proposed to quantify small oscillations in the airfoil surface,proving the authenticity and accuracy of the generated airfoil shapes.

关键词： Conditional Variational AutoEncoder(CVAE) Deep learning Generative Adversarial Networks(GAN) Generative models Inverse design Supercritical airfoil

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Fault Diagnostic Opportunities for Robot Servo Motors Using the Physics of Failure Analysis 14

Fault Diagnostic Opportunities for Robot Servo Motors Using ...

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14th International Conference on Reliability, Maintainability and Safety, ICRMS 2023

作者： Zhang, Bo Liang, Shan Wang, Kai Key Laboratory of Networked Control Systems Shenyang Institute of Automation Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China College of Computer Science and Technology University of Chemical Technology Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9798350329988

Joint robots are widely used in various industries, such as aviation, aerospace, and automotive manufacturing. The performance degradation of servo motors can significantly affect the overall performance of the robots because of the core component of joint robots, and therefore, it is critical to detect and address servo motor failures promptly. In this study, we analyze some common causes and mechanisms of performance degradation in robot servo motors using the physics of failure analysis. We also discuss strategies for detecting and diagnosing faults using these mechanisms before the servo motors fail completely. © 2023 IEEE.

关键词： Servomotors

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Segment-Adaptive Spread Spectrum Audio Watermarking Using NSGA-Ⅱ

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Chinese Journal of Electronics 2021年第4期30卷 727-735页

作者： SU Zhaopin ZHANG Guofu ZHOU Xianxian LI Wangwang Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology Ministry of Education School of Computer Science and Information Engineering Hefei University of Technology Intelligent Interconnected Systems Laboratory of Anhui Province Hefei University of Technology Anhui Province Key Laboratory of Industry Safety and Emergency Technology Hefei University of Technology

In the field of robust audio watermarking,how to seek a good trade-off between robustness and imperceptibility is challenging. The existing studies use the same embedding parameter for each part of the audio signal, which ignores that different parts may have different requirements for embedding parameters. In this work, the constraints on imperceptibility are first ***, we present a segment multi-objective optimization model of the scaling parameter under the constrained Signal-to-noise ratio(SNR) in Spread spectrum(SS)audio watermarking. Additionally, we adopt the Nondominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ) to solve the proposed model. Finally, we compare our algorithm(called SS-SNR-NSGA-Ⅱ) with the existing methods. The experimental results show that the proposed SS-SNRNSGA-Ⅱ not only provides flexible choices for different application demands but also achieves more and better trade-offs between imperceptibility and robustness.

关键词： Spread spectrum audio watermarking Scaling parameter Segment Constrained SNR NSGA-Ⅱ

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Efficient Nearest Neighbor Emotion Classification with BERT-whitening

Efficient Nearest Neighbor Emotion Classification with BERT-...

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2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022

作者： Yin, Wenbiao Shang, Lin State Key Laboratory for Novel Software Technology Department of Computer Science and Technology Nanjing University Nanjing China

Retrieval-based methods have been proven effective in many NLP tasks. Previous methods use representations from the pre-trained model for similarity search directly. However, the sentence representations from the pre-trained model like BERT perform poorly in retrieving semantically similar sentences, resulting in poor performance of the retrieval-based methods. In this paper, we propose KNN-EC, a simple and efficient non-parametric emotion classification (EC) method using nearest neighbor retrieval. We use BERT-whitening to get better sentence semantics, ensuring that nearest neighbor retrieval works. Meanwhile, BERT-whitening can also reduce memory storage of datastore and accelerate retrieval speed, solving the efficiency problem of the previous methods. KNN-EC average improves the pre-trained model by 1.17 F1-macro on two emotion classification datasets. © 2022 Association for Computational Linguistics.

关键词： Semantics

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Out-of-Distribution Fault Diagnosis of Industrial Cyber-Physical systems Based on Orthogonal Anchor Clustering With Adaptive Balance

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical systems 2025年 3卷 48-60页

作者： Liu, Ruonan Hu, Puyuan Zhao, Siheng Sun, Zhijian Han, Te Pang, Zhibo Zhang, Weidong Shanghai Jiao Tong University Department of Automation Shanghai200240 China National Key Laboratory of Marine Engine Science and Technology Shanghai201108 China Crossocean of Suzhou Technology Suzhou215121 China Beijing Institute of Technology Center for Energy and Environmental Policy Research School of Management Beijing100081 China ABB Corporate Research Sweden Department of Automation Technology Vasteras722 26 Sweden KTH Royal Institute of Technology Department of Intelligent Systems Stockholm114 28 Sweden Henan University Henan Key Laboratory of Big Data Analysis and Processing School of Computer and Information Engineering Kaifeng475001 China Shanghai Jiaotong University Department of Automation Shanghai200240 China

Given the critical role of rotating machinery in industrial cyber-physical systems (ICPS), ensuring their reliable operation is essential for the stability and safety of ICPS. Deep neural networks have demonstrated competitive results for intelligent fault diagnosis, which are usually trained via the historical data of all fault modes. However, in real engineering, it is usually difficult to collect samples and exhaust all failures during the training stage. As a result, out-of-distribution fault diagnosis (OOD-FD) becomes a more realistic problem that requires the methods to not only accurately diagnose the known faults, but also effectively recognize unknown ones. Therefore, a novel orthogonal anchor clustering with focal attention (FA-OAC) is proposed in this paper for OOD-FD. Firstly, an orthogonal anchor clustering (OAC) algorithm is proposed to fix the class center of each fault mode orthogonally and distinguish the known and unknown faults at the class level. Then, because the identifiability of different fault modes changes a lot in OOD-FD, the focal attention mechanism is applied to dynamically adjust the attention to different fault modes according to the distance loss of OAC, thus addressing the identifiability imbalance problem. To verify the effectiveness of the proposed method, different OOD-FD tasks are designed based on two rotating machinery datasets. The experimental results and comparison with state-of-the-art fault diagnosis methods have demonstrated that the proposed method has improved the OOD-FD performance greatly and therefore provides an effective tool in real engineering. © 2023 IEEE.

关键词： Rotating machinery

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Resilience assessment framework toward interdependent bus-rail transit network:Structure,critical components,and coupling mechanism

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Communications in Transportation Research 2023年第1期3卷 118-129页

作者： Bing Liu Xiaoyue Liu Yang Yang Xi Chen Xiaolei Ma School of Transportation Science and Engineering Beihang UniversityBeijing100191China Department of Civil&Environmental Engineering University of UtahSalt Lake CityUT84112USA School of Computer Science and Engineering Beihang UniversityBeijing100191China Key Laboratory of Intelligent Transportation Technology and System Ministry of EducationBeijing100191China

Understanding the interdependent nature of multimodal public transit networks(PTNs)is vital for ensuring the resilience and robustness of transportation ***,previous studies have predominantly focused on assessing the vulnerability and characteristics of single-mode PTNs,neglecting the impacts of heterogeneous disturbances and shifts in travel behavior within multimodal ***,this study introduces a novel resilience assessment framework that comprehensively analyzes the coupling mechanism,structural and functional characteristics of bus-rail transit networks(BRTNs).In this framework,a network performance metric is proposed by considering the passengers’travel behaviors under various ***,stations and subnetworks are classified using the k-means algorithm and resilience metric by simulating various disturbances occurring at each station or *** proposed framework is validated via a case study of a BRTN in Beijing,*** indicate that the rail transit network(RTN)plays a crucial role in maintaining network function and resisting external disturbances in the interdependent ***,the coupling interactions between the RTN and bus transit network(BTN)exhibit distinct characteristics under infrastructure component disruption and functional *** findings provide valuable insights into emergency management for PTNs and understanding the coupling relationship between BTN and RTN.

关键词： Complex network Bus-rail transit network Resilience analysis Interdependent coupling relationship Classification analysis

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