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42nd Chinese control Conference, CCC 2023

作者： Gu, Xiao Liu, Jian Yuan, Ye Zhao, Peng Xin, Kuankuan Fang, Tao Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China Shanghai Engineering Research Centre of Intelligent Control and Management Shanghai200240 China Institute of Machine Intelligence University of Shanghai for Science and Technology Shanghai200093 China Queensland Brain Institute The University of Queensland BrisbaneQLD4072 Australia

ISBN: (纸本)9789887581543

The self-organized criticality is a fundamental property for organisms to perform normal functional activities. Extensive large-scale biological neural network researches have found the existence of self-organized criticality through avalanche phenomenon, which is typical characteristic of self-organized criticality. However, such research method is not suitable for small-scale biological neural network, because number of neurons in small-scale biological neural network is not large enough to support the emergence of avalanche phenomenon. It has been demonstrated that branching parameter can also be used to describe the propagation of activity in the neural network. Here, in this paper, the C. elegans neural network composed of 302 neurons is selected to investigate the existence of self-organized criticality using branching parameter. Based on the obtained connectome of C. elegans, a directed graph model is constructed to simulate the gradient potential of neurons and the activity of C. elegans, then, the existence of self-organized criticality in the neural network of C. elegans is proved by using branching parameter method. Meanwhile, the result is further confirmed by analyzing the calcium activity data of C. elegans obtained from biological experiments. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Calcium

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Metric Learning with Distillation for Overcoming Catastrophic Forgetting 16th

Metric Learning with Distillation for Overcoming Catastrop...

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16th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2021

作者： Yu, Piaoyao He, Juanjuan Min, Qilang Zhu, Qi College of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan China

ISBN: (纸本)9789811912528

In incremental learning, reducing catastrophic forgetting always adds additional weights to the classification layer when a new task comes. Moreover, it focuses on prediction accuracy, ignores mislabeling differences, and causes the learned features to be scattered. This paper removes the softmax and integrates depth metric learning to compute image embeddings, which doesn’t need to add extra weights or additional space for new classes. The distances of the data mapped in the old and new task spaces are calculated separately. Then, the distillation of depth metric learning is used to make the two distances as similar as possible to improve the performance of the old knowledge. The experimental results on Cifar10 and Tiny-ImageNet show that the proposed method can effectively alleviate catastrophic forgetting and enhance the effectiveness of incremental learning. © 2022, Springer Nature Singapore Pte Ltd.

关键词： Distillation

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In-plane shear failure behavior and mechanical properties of SiC/SiC Composites 3

In-plane shear failure behavior and mechanical properties of...

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2024 3rd International Conference on Applied Mechanics and Advanced Materials, ICAMAM 2024

作者： Li, Tianshan Yu, Guoqiang Zhou, Shihao Zheng, Zhikang Gao, Xiguang Song, Yingdong Key Laboratory of Aero-Engine Thermal Environment and Structure Ministry of Industry and Information Technology College of Energy and Power Engineering Nanjing University of Aeronautics and Astronautics Nanjing210016 China Jiangsu Province Key Laboratory of Aerospace Power System College of Energy and Power Engineering Nanjing University of Aeronautics and Astronautics Nanjing210016 China State Key Laboratory of Mechanics and Control of Mechanical Structures Nanjing University of Aeronautics and Astronautics Nanjing210016 China

Fiber-reinforced ceramic matrix composites, especially SiC/SiC composites, have the characteristics of lightweight, high strength, high-temperature resistance, etc., which are ideal structural candidates for aerospace vehicle components, in-plane shear performance is one of the important indicators to characterize the mechanical properties of materials and component assessment, this paper designs and processes the in-plane shear test pieces and test devices and methods to study the shear mechanical behavior under the mechanical properties and failure behavior of SiC/SiC ceramic-based fiber bundle composites are studied under shear mechanical behavior. The results show that matrix cracking and fiber fracture are the main failure modes, and there are two obvious phases in the specimen shear force-displacement curves, and fiber fracture is the main cause of strain in the specimen. © Published under licence by IOP Publishing Ltd.

关键词： Ceramic matrix composites

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Image Dehazing Network Based on Multi-scale Feature Extraction 4th

Image Dehazing Network Based on Multi-scale Feature Extracti...

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4th International Conference on Smart Vehicular Technology, Transportation, Communication and Applications, VTCA 2021

作者： Feng, Ting Zhang, Fuquan Yu, Zhaochai Li, Zuoyong Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou350121 China College of Mathematics and Computer Science Fuzhou University Fuzhou350108 China

ISBN: (纸本)9789811640384

To remove image haze and make haze image scene clear, we proposed an image dehazing network based on multi-scale feature extraction (MSFNet) in this paper. The MSFNet first directly performs feature extraction on hazy images with three different resolutions to obtain fine feature maps and concatenates them with the rough feature maps extracted in the downsampling process for fusing and obtaining richer image information. Then, the fused feature maps are put into a network module composed of ResNeXt building blocks for network learning. Next, the feature maps extracted by upsampling are sequentially concatenated with the feature maps learned by the ResNeXt module for obtaining the residual image. Finally, the learned residual image is added to the input hazy image to obtain the image dehazing result. The experimental results on the SOTS dataset show that the MSFNet improves effectiveness of image dehazing. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Feature extraction

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An Enhanced Particle Swarm Algorithm Based on Fitness Landscape information

An Enhanced Particle Swarm Algorithm Based on Fitness Landsc...

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Congress on Evolutionary Computation

作者： Zhenya Diao Fei Yu Jian Guan Meitong Liu Key Lab of Intelligent Optimization and Information Processing School of Physics and Information Engineering Minnan Normal University Zhangzhou China Key Laboratory of Light Field Manipulation and System Integration Applications in Fujian Province Key Lab of Intelligent Optimization and Information Processing School of Physics and Information Engineering Minnan Normal University Zhangzhou China

ISBN: (数字)9798350308365

ISBN: (纸本)9798350308372

In the original Particle Swarm Optimization (PSO), the selection of parameters significantly impacts the search capability of PSO. The paper introduces an innovative algorithm called Fitness Landscape-based PSO (FLPSO) to address the impact of parameter selection on the search capability of PSO. The algorithm focuses on acquiring fitness landscape information and analyzing the population state to intelligently select appropriate parameters in each generation. FLPSO defines four primary states: exploration, exploitation, convergence, and escaping state. In the convergence state, an elite learning strategy is incorporated to help the algorithm escape potential local optima by targeting the global best particle. To validate the efficacy of FLPSO, the paper conducted experiments on 30 different characteristic test functions from CEC2017. FLPSO was compared with six existing algorithms: PSO, PSO-TVAC, APSO, AWPSO, RPSO and ASRPPSO. The experimental results showed significant improvements in FLPSO, providing promising evidence for its effectiveness.

关键词： Sociology Particle swarm optimization Statistics Convergence

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Adaptive Neural Consensus Tracking control for Nonlinear Multiagent systems with Dead Zone and Sensor Faults 42

Adaptive Neural Consensus Tracking Control for Nonlinear Mul...

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42nd Chinese control Conference, CCC 2023

作者： Huang, Chengjie Chen, Ci Liu, Zhi Li, Zhenni Guangdong University of Technology Guangzhou510006 China Guangdong Key Laboratory of IoT Information Technology Guangzhou510006 China 111 Center for Intelligent Batch Manufacturing Based on IoT Technology Guangzhou510006 China Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing Guangzhou510006 China Key Laboratory of Intelligent Information Processing and System Integration of IoT Ministry of Education Guangzhou510006 China Key Laboratory of Intelligent Detection and the Internet of Things in Manufacturing Ministry of Education Guangzhou510006 China

ISBN: (纸本)9789887581543

In this paper, an adaptive neural tracking control design is investigated for uncertain multiagent systems (MASs) with actuator dead zone and sensor faults. The adaptive control technique based on neural networks is employed to handle the uncertainty in the systems, which, however, results in a bounded tracking error from most existing works. To achieve the asymptotic tracking performance, we proposed a direct adaptive strategy via the tuning function method. Technically, a Lyapunov function with a series of smooth functions is designed, which benefits proposing of an asymptotic controller. Then, under the framework of direct adaptive control, an inverse compensation scheme, as well as a fault-tolerant mechanism, are considered for disposing of the actuator dead zone and sensor failures. As a result, user-preset tracking performance is achieved and the system error in the MASs converges to a predefined range. An example in the simulation section illustrates the effectiveness of the proposed method. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Multi agent systems

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Modulating surface cation vacancies of nickel-cobalt oxides as efficient catalysts for lithium-oxygen batteries

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Journal of Materials Science & Technology 2023年第8期139卷 147-155页

作者： Yuan Yang Linna Dai Jianwei Qiu Zhibiao Hu Peng Wang Yongtao Zhao Huanhuan Guo Pengchao Si Rui Song Center for Robotics School of Control Science and EngineeringShandong UniversityJinan 250061China Research Center for Carbon Nanomaterials Key Laboratory for Liquid-Solid Structural Evolution and Processing of Materials(Ministry of Education)School of Materials Science and EngineeringShandong UniversityJinan 250061China School of Mechanical Electrical and Information EngineeringShandong UniversityWeihai 264209China College of Chemistry and Chemical Engineering Xingtai UniversityXingtai 054001China

Rechargeable lithium-oxygen batteries(LOBs)have received incremental attention owing to their high energy density and applicability to mobile devices and electric ***,the lack of robust,low-cost,and environmentally benign bifunctional catalysts is a major impediment to the commercial *** introduction of vacancies is one of the effective strategies to enhance the performance of cathode catalysts for lithium-oxygen batteries,but the preparation is *** this work,needle-like microsphere cathode catalysts of nickel-cobalt oxide containing cationic vacancies are constructed by controlling the annealing *** is demonstrated that the presence of cationic vacancies can modulate the electronic structure of the catalyst,reduce the energy barrier for the oxygen electrode re-action,meanwhile enhance the bifunctional catalytic ***,the nickel-cobalt oxide-based LOB with cationic vacancies exhibits large specific capacity(12,205 mAh g^(-1)at 200 mA g^(-1))and good *** work provides worthwhile insight into the formation and catalytic enhancement mech-anism of transition metal oxide catalysts with cationic vacancies,and to some extent,the creation of efficient and low-cost oxygen electrocatalysts for LOBs.

关键词： Li-O_(2)batteries Metal oxides Cation vacancies Catalytic kinetic

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Lead-free perovskite Cs_(2)AgBiBr_(6)photodetector detecting NIR light driven by titanium nitride plasmonic hot holes

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Photonics Research 2024年第3期12卷 522-533页

作者： ZIJIAN LIU YUYING XI WENBO ZENG TING JI WENYAN WANG SITONG GUO LINLIN SHI RONG WEN YANXIA CUI GUOHUI LI College of Physics College of Electronic Information and Optical EngineeringKey Laboratory of Advanced Transducers and Intelligent Control System of Ministry of EducationTaiyuan University of TechnologyTaiyuan 030024China Shanxi-Zheda Institute of Advanced Materials and Chemical Engineering Taiyuan 030032China

Lead-free perovskite Cs_(2)AgBiBr_(6)manifests great potential in developing high-performance,environmentally friendly,solution-processable photodetectors(PDs).However,due to the relatively large energy bandgap,the spectrum responses of Cs_(2)AgBiBr_(6)PDs are limited to the ultraviolet and visible region with wavelengths shorter than 560 *** this work,a broadband Cs_(2)AgBiBr_(6)PD covering the ultraviolet,visible,and near infrared(NIR)range is demonstrated by incorporating titanium nitride(TiN)nanoparticles that are prepared with the assistance of self-assembled polystyrene sphere *** addition,an atomically thick Al2O3layer is introduced at the interface between the Cs_(2)AgBiBr_(6)film and TiN nanoparticles to alleviate the dark current deterioration caused by nanoparticle *** a result,beyond the spectrum range where Cs_(2)AgBiBr_(6)absorbs light,the external quantum efficiency(EQE)of the TiN nanoparticle incorporated Cs_(2)AgBiBr_(6)PD is enhanced significantly compared with that of the control,displaying enhancement factors as high as 2000 over a broadband NIR wavelength *** demonstrated enhancement in EQE arises from the photocurrent contribution of plasmonic hot holes injected from TiN nanoparticles into Cs_(2)AgBiBr_(6).This work promotes the development of broadband solution-processable perovskite PDs,providing a promising strategy for realizing photodetection in the NIR region.

关键词： perovskite titanium ultraviolet

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Optimization for Pickup Vehicle Scheduling in Steel Logistics Park Based on Enhanced SPEA2

Optimization for Pickup Vehicle Scheduling in Steel Logistic...

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2023 China Automation Congress, CAC 2023

作者： Xu, Hongjie Wang, Jinlong Xu, Zhezhuang Chen, Boyu Zhang, Qingdong College of Electrical Engineering and Automation Fuzhou University Key Laboratory of Industrial Automation Control Technology and Information Processing Education Department of Fujian Province Fuzhou350000 China Sansteel Minguang Co. Ltd. Sanming353000 China

ISBN: (纸本)9798350303759

Pickup vehicle scheduling in the steel logistics park is a critical issue in determining the outbound effciency of steel products. Steel products are distributed in the yards of the steel logistics park with mixed storage, and the optional yards for each pickup operation are not unique, which greatly increases the scheduling complexity. To overcome this challenge, in this paper, we propose a pickup vehicle scheduling problem with mixed steel storage (PVSP-MSS) to optimize makespan of pickup vehicle and makespan of steel logistics park simultaneously. The optimization problem is described as a multi-objective problem, and an enhanced Strength Pareto Evolutionary Algorithm 2 (ESPEA) is proposed to solve the problem with high efficiency. Experiments are executed based on data collected from a real steel logistics park. The results confirm that ESPEA can significantly reduce both makespan of each pickup vehicle and makespan of steel logistics park. © 2023 IEEE.

关键词： Pickups

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Isoform Function Prediction Based on Heterogeneous Graph Attention Networks

Isoform Function Prediction Based on Heterogeneous Graph Att...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Guo, Kuo Li, Yifan Chen, Hao Shen, Hong-Bin Yang, Yang Shanghai Jiao Tong University Key Lab. of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Department of Computer Science and Engineering Shanghai200240 China Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Institute of Image Processing and Pattern Recognition Shanghai200240 China Carnegie Mellon University School of Computer Science Computational Biology Department PittsburghPA15213 United States

ISBN: (纸本)9798350337488

Isoforms refer to different mRNA molecules transcribed from the same gene, which can be translated into proteins with varying structures and functions. Predicting the functions of isoforms is an essential topic in bioinformatics as it can provide valuable insights into the intricate mechanisms of gene regulation and biological processes. Conventionally, gene function labels are standardized in Gene Ontology (GO) terms. However, traditional methods for predicting isoform function are largely limited by the absence of isoform-specific labels, sparse annotations, and the vast number of GO terms. To address these issues, we propose HANIso, a deep learning-based method for isoform function prediction. HANIso leverages a pretrained protein language model to extract features from protein sequences. It also integrates heterogeneous information, such as isoform sequence features, GO annotations, and isoform interaction data, using a Heterogeneous Graph Attention Network (HAN). This allows the model to learn the importance of different sources of information and their semantic relationships through the attention mechanism. Our method can predict function labels at both the gene level and isoform level. We conduct experiments on two species datasets, and the results demonstrate that our method outperforms existing methods on both AUROC and AUPRC. HANIso has the potential to overcome the limitations of traditional methods and provide a more accurate and comprehensive understanding of isoform function. © 2023 IEEE.

关键词： alternative splicing gene ontology heterogeneous graph attention network isoform function prediction protein language model

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