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Berry-Esseen bounds for self-normalized sums of locally dependent random variables

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Science China Mathematics 2024年第11期67卷 2629-2652页

作者： Zhuo-song Zhang Department of Statistics and Data Science Southern University of Science and Technology

The Berry-Esseen bound provides an upper bound on the Kolmogorov distance between a random variable and the normal *** this paper,we establish Berry-Esseen bounds with optimal rates for self-normalized sums of locally dependent random variables,assuming only a second-moment *** proof leverages Stein's method and introduces a novel randomized concentration inequality,which may also be of independent interest for other *** main results have applied to self-normalized sums of m-dependent random variables and graph dependency models.

关键词： Berry-Esseen bounds self-normalized sums localdependence $m$-dependence graph dependency

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Effect of nano-carbon black content on wetting phenomenon of molten steel and alumina-carbon ceramic filter substrates

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Journal of Iron and Steel Research International 2024年第8期31卷 1900-1913页

作者： Jin-wen song Wen Yan Zhe Chen Ying Liu Shao-song Hong The State Key Laboratory of Refractories and Metallurgy Wuhan University of Science and TechnologyWuhan 430081HubeiChina National-provincial Joint Engineering Research Center of High Temperature Materials and Lining Technology Wuhan University of Science and TechnologyWuhan 430081HubeiChina Jiangsu Sheng Nai New Materials Co. Ltd.Taizhou 225503JiangsuChina

The effect of nano-carbon black content(O,8 and 12 wt.%)on the wettability of molten steel on Al_(2)O_(3)-C substrates was investigated by the sessile drop wetting method at 1500℃ under argon *** the beginning of the wetting experiment,the contact angle decreased with the increase in nano-carbon black *** the wetting experiment progressed,FeAl_(2)0_(4) layer and sheet Al_(2)O_(3) layer were found at the interface between the molten steel and the Al_(2)O_(3)-C substrates with O and 8 wt.% nano-carbon black content,and the contact angle deceased with *** the content of nano-carbon black was 12 wt.%,a large number of nano-Al_(2)O_(3) whiskers were observed,which made the contact angle between the molten steel and Al_(2)O_(3)-C substrate become *** on the scanning electron microscope and energy dispersive spectrometry results,the formation mechanism of FeAl2O4 layer and Al_(2)O_(3) layer and the interfacial reaction mechanism were proposed.

关键词： Contact angle Nano-carbon black Al_(2)O_(3)-C substrate Molten steel Interfacial reaction

Spiking neural networks in intelligent control systems:a perspective

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Science China(Information Sciences) 2024年第7期67卷 324-326页

作者： Anguo ZHANG Yongduan song School of Artificial Intelligence Anhui University School of Automation Chongqing University

Artificial intelligence (AI) has undergone substantial advancements in recent years, prompting an era of innovation in various domains. Among the groundbreaking contributions, neural networks stand at the forefront, powering applications ranging from computer vision and natural language processing to intelligent control systems [1, 2].

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基于S-R和分解定理的无网格法在功能梯度板中的应用

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上海大学学报（自然科学版） 2022年第4期28卷 702-714页

作者：宋彦琦石博康李向上中国矿业大学(北京)力学与建筑工程学院北京100083

为了研究功能梯度板的非线性变形问题,以S-R和分解定理为基础,从虚功率原理出发,结合更新拖带坐标系法、无网格Galerkin法,推导出用于求解三维几何非线性问题的离散方程.利用MATLAB编写无网格法程序,对功能梯度板的非线性弯曲问题进行求... 详细信息

为了研究功能梯度板的非线性变形问题,以S-R和分解定理为基础,从虚功率原理出发,结合更新拖带坐标系法、无网格Galerkin法,推导出用于求解三维几何非线性问题的离散方程.利用MATLAB编写无网格法程序,对功能梯度板的非线性弯曲问题进行求解,并研究板的体积分数指数和宽厚比对板弯曲的影响.将计算结果与已有成果进行了比较,验证了三维S-R无网格法求解功能梯度板大变形问题的合理性.

关键词： S-R和分解定理几何非线性问题无网格Galerkin法功能梯度板

Genome-wide SNP markers provided insights into the reproductive strategy and genetic diversity of the green tide causative species Ulva prolifera in China

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Journal of Oceanology and Limnology 2024年第2期42卷 533-543页

作者： song SUN Weiwei MA Nan WANG song FENG Yan SUN CAS Key Laboratory of Marine Ecology and Environmental Sciences Institute of OceanologyChinese Academy of SciencesQingdao 266071China Laboratory for Marine Ecology and Environmental Science Laoshan LaboratoryQingdao 266237China Jiaozhou Bay Marine Ecosystem Research Station Chinese Academy of SciencesQingdao 266071China University of Chinese Academy of Sciences Beijing 100049China

Ulva prolifera is the causative species of the annually occurring large-scale green tides in China since *** specific biological features on reproductivity strategies,as well as intra-species genetic diversity,are still largely unknown,especially at the genome level,despite their importance in understanding the formation and outbreak of massive green *** the present study,the restriction site-associated DNA genotyping approach(2b-RAD)was adopted to identify the genome-wide single-nucleotide polymorphisms(SNPs)of 54 individual thalli including samples collected from Subei Shoal in 2019 and Qingdao coast from 2019 to *** genotype results revealed that most of the thalli in 2019 and 2020 were haploid gametophytes,while only half of the thalli were gametophytes in 2021,indicating flexibility in the reproductive strategies for the formation of the green tides among different years and the dominance of asexual and vegetative reproductive mode for the floating ***,population analysis was conducted,and it revealed a very low genetic diversity among samples from Subei Shoal and the Qingdao coast in the same year and a higher divergence among samples in different *** results showed the efficiency of 2b-RAD in the exploration of SNPs in *** and provided the first genome-wide scale evidence for the origin of the large-scale green tides on the Qingdao *** study improved our understanding of the reproductive strategy and genetic diversity of the green tide causative species and will help further reveal the biological causes of the green tide in China.

关键词： green tide Ulva prolifera 2b-RAD single-nucleotide polymorphism(SNP) reproductive strategy genetic diversity

Experimental study on combustion characteristics of supersonic combustor based on alternating-wedge strut

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Chinese Journal of Aeronautics 2024年第5期37卷 214-227页

作者： Jie LI Wenyan song Yuhang WANG School of Power Energy Northwestern Polytechnical UniversityXi’an 710129China

Acetone Planar Lase-Induced Fluorescence(PLIF)and OH-PLIF were employed to capture the fuel distribution and OH distribution downstream for the supersonic combustor based on the alternating-wedge *** combustion establishment process and combustion mode in the combustor under different fuel injection methods and different equivalence ratios were *** with the kerosene-PLIF and OH-PLIF results in the cavity combustor,a comparative analysis was conducted to understand the combustion characteristics and combustion modes between the alternating-wedge strut-based combustor and the cavity-based *** results show that the combustor is in weak combustion mode in the case of low equivalence ratio,and the combustor is in intensive combustion mode in the case of high equivalence *** lower limit of the equivalence ratio of the combustor to maintain the intensive combustion mode varies based on different fuel injection *** OH distribution under reacting condition has a strong correlation with the fuel distribution under non-reacting *** OH fluorescence signal near the injector is weaker when the fuel distribution is more *** injector position located at the base of the strut rear has better mixing performance,enabling the combustor to be in intensive combustion mode at a lower equivalence *** combustion reaction in the alternating-wedge strut-based combustor is not necessarily dominated by mass transfer due to the mixing enhancement and premixed zone downstream of strut,while the combustion reaction process in the cavity-based combustor is mainly influenced by mass transfer.

关键词： Supersonic combustor Alternating-wedge strut Cavity PLIF Fuel injection Fuel distribution Combustion characteristics Combustion mode

A credible traffic prediction method based on self-supervised causal discovery

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Science China(Information Sciences) 2024年第5期67卷 244-258页

作者： Dan WANG Yingjie LIU Bin song State Key Laboratory of Integrated Services Networks Xidian University

Next-generation wireless network aims to support low-latency, high-speed data transmission services by incorporating artificial intelligence(AI) technologies. To fulfill this promise, AI-based network traffic prediction is essential for pre-allocating resources, such as bandwidth and computing power. This can help reduce network congestion and improve the quality of service(QoS) for users. Most studies achieve future traffic prediction by exploiting deep learning and reinforcement learning, to mine spatio-temporal correlated variables. Nevertheless, the prediction results obtained only by the spatio-temporal correlated variables cannot reflect real traffic changes. This phenomenon prevents the true prediction variables from being inferred, making the prediction algorithm perform poorly. Inspired by causal science, we propose a novel network traffic prediction method based on self-supervised spatio-temporal causal discovery(SSTCD). We first introduce the Granger causal discovery algorithm to build a causal graph among prediction variables and obtain spatio-temporal causality in the observed data, which reflects the real reasons affecting traffic ***, a graph neural network(GNN) is adopted to incorporate causality for traffic prediction. Furthermore,we propose a self-supervised method to implement causal discovery to to address the challenge of lacking ground-truth causal graphs in the observed data. Experimental results demonstrate the effectiveness of the SSTCD method.

关键词： wireless network traffic prediction causal discovery self-supervised

Achieving Given Precision Within Prescribed Time yet With Guaranteed Transient Behavior via Output Based Event-Triggered Control

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IEEE/CAA Journal of Automatica Sinica 2024年第10期11卷 2059-2067页

作者： Zeqiang Li Yujuan Wang Yongduan song International Joint Laboratory on Safety and Control of Autonomous Unmanned Systems School of AutomationChongqing UniversityChongqing 400044China IEEE

It is interesting yet nontrivial to achieve given control precision within user-assignable time for uncertain nonlinear *** underlying problem becomes even more challenging if the transient behavior also needs to be accommodated and only system output is available for *** key design innovations are proposed to circumvent the aforementioned technical difficulties,including the employment of state estimation filters with event-triggered mechanism,the construction of a novel performance scaling function and an error *** contrast to most existing performance based works where the stability is contingent on initial conditions and the maximum allowable steady-state tracking precision can only be guaranteed at some unknown(theoretically infinite)time,in this work the output of the system is ensured to synchronize with the desired trajectory with arbitrarily pre-assignable convergence rate and arbitrarily pre-specified precision within prescribed time,using output only with lower cost of sensing and *** addition,all the closed-loop signals are ensured to be globally uniformly bounded under the proposed control *** merits of the designed control scheme are confirmed by numerical simulation on a ship model.

关键词： Adaptive control nonlinear systems output feedback prescribed performance

FSCIL-EACA: Few-Shot Class-Incremental Learning Network Based on Embedding Augmentation and Classifier Adaptation for Image Classification

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Chinese Journal of Electronics 2024年第1期33卷 139-152页

作者： Ruru ZHANG Haihong E Meina song School of Computer Science Beijing University of Posts and Telecommunications Education Department Information Network Engineering Research Center Beijing University of Posts and Telecommunications

The ability to learn incrementally is critical to the long-term operation of AI systems. Benefiting from the power of few-shot class-incremental learning(FSCIL), deep learning models can continuously recognize new classes with only a few samples. The difficulty is that limited instances of new classes will lead to overfitting and exacerbate the catastrophic forgetting of the old classes. Most previous works alleviate the above problems by imposing strong constraints on the model structure or parameters, but ignoring embedding network transferability and classifier adaptation(CA), failing to guarantee the efficient utilization of visual features and establishing relationships between old and new classes. In this paper, we propose a simple and novel approach from two perspectives: embedding bias and classifier bias. The method learns an embedding augmented(EA) network with cross-class transfer and class-specific discriminative abilities based on self-supervised learning and modulated attention to alleviate embedding bias. Based on the adaptive incremental classifier learning scheme to realize incremental learning capability,guiding the adaptive update of prototypes and feature embeddings to alleviate classifier bias. We conduct extensive experiments on two popular natural image datasets and two medical datasets. The experiments show that our method is significantly better than the baseline and achieves state-of-the-art results.

关键词： Training Adaptation models Visualization Image recognition Prototypes Self-supervised learning Power capacitors