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A real-time multi-head mixed attention mechanism-based prediction method for tunnel boring machine disc cutter wear

Science China Technological Sciences 2025年第1期 290-311页

作者： Haodi WANG Chengjin QIN Honggan YU Zhinan ZHANG Guoqiang HUANG zhengyang liu Chengliang liu State Key Laboratory of Mechanical System and Vibration School of Mechanical EngineeringShanghai Jiao Tong University

In the process of hard rock tunnel excavation, workers often need to enter the tunnel boring machine(TBM)cutterhead at regular intervals to measure cutter wear. However, this method is time-consuming and labor-intensive. Existing cutter prediction models primarily rely on geological parameters to predict overall cutter wear before construction, making it challenging to monitor real-time wear at different locations of the cutter and obtain accurate geological parameters. To address these challenges, this paper proposes a multi-head mixed attention mechanism-based method for real-time wear prediction of TBM disc cutter. First, a method of cutter wear normalization to eliminate measurement noise is explored. Then, considering the complex correlation of TBM operating parameters in feature and time dimensions, a new multi-head mixed attention mechanism model is designed to establish the dependency between different features and different moments, to better establish the mapping model between operating parameters and cutter wear. Finally, the current cutter wear state can be calculated by accumulating the wear amount of all previous small excavation sections. The effectiveness of the method is verified by using field data from the Mumbai tunnel. The results demonstrate that the method is capable of real-time prediction of front cutter and edge cutter wear on the test set, achieving an average accuracy rate of 95.75%. Moreover, the method can update the cutter wear status after every meter of excavation, which has good real-time performance. In addition, the average accuracy of cutter wear prediction of the proposed method is 11.75%, 10.375%, 3.875%, 3.625%, 1.375%, 3.125%, 2.25%, and 0.75%higher than that of LSTM, CNN, LSTM-CNN, CACNN, SACNN, MMADNN, MTACNN, and MFACNN. In summary, this approach offers an accurate prediction of cutter wear state while reducing inspection time and costs and has high application value.

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Brexit and Its Impact on the US Stock Market

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Journal of Systems Science & Complexity 2021年第3期34卷 1044-1062页

作者： QIAO Kenan liu zhengyang HUANG Bai SUN Yuying WANG Shouyang Academy of Mathematics and Systems Science Chinese Academy of SciencesBeijing 100190China Center for Forecasting Science Chinese Academy of SciencesBeijing 100190China School of Economics and Management University of Chinese Academy of SciencesBeijing 100190China School of Statistics and Mathematics Central University of Finance and EconomicsBeijing 100081China

This paper firstly analyzes the Brexit’s impact on the US stock market using a novel interval methodology. The interval-valued dummy variables are proposed to measure the direction and magnitudes of the changes in the inter-day trend and the intra-day volatility of S&P500 returns simultaneously. It is found that both the trend and the volatility of S&P500 returns increased before the Brexit. Besides, the Brexit negatively affected S&P500 returns’ trend in the short term after the event,while its impact on market volatility was positive, which slowly decayed across time. Furthermore, a new interesting finding is that there are both short-term momentum effects(i.e., positive autocorrelation of trends) and volatility clustering in stock markets.

关键词： Brexit interval time series intra-day volatility S&P500 index

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Engineering the Active Sites of MOF-derived Catalysts:From Oxygen Activation to Activate Metal-Air Batteries

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Chinese Journal of Chemistry 2024年第20期42卷 2520-2535页

作者： Fanjiao Chen Xueqin Mu Jialing Zhou Shengchen Wang zhengyang liu Dingyang Zhou Suli liu Dingsheng Wang Zhihui Dai Schoolof Chemistry and Molecular Engineering Nanjing TechUniversityNanjingJiangsu 211816China Department of Chemistry Tsinghua UniversityBeijing 100084China

The electrochemical processes of oxygen reduction reaction(ORR)and oxygen evolution reaction(OER)play a crucial role in various energy storage and conversion ***,the inherently slow kinetics of reversible oxygen reactions present an urgent demand for the development of efficient oxygen ***,metal-organic framework(MOF)derivatives have attracted extensive attention in electrocatalysis research due to their unique porous structure,abundant active sites,and tunable structural ***,the optimization of the electronic structure of active sites in MOF derivatives has been proven as an effective strategy to enhance the catalytic *** this review,we provide an overview of the electronic structure optimization strategies for active sites in MOF derivatives as advanced catalysts in various O—O bond activation reactions,including the construction of synergistic effects between multiple sites,the development of heterogeneous interfaces,the utilization of metal support interactions,and the precise modulation of organic ligands surrounding catalytic active sites at the atomic ***,this review offers theoretical insights into the oxygen activation and catalytic mechanisms of MOF derivatives,as well as the identification of active ***,the potential challenges and prospects of MOF derivatives in electrocatalysis are *** review contributes to the understanding and advancement of efficient oxygen electrocatalysis in energy systems.

关键词： Metal-organic framework derivatives Electronic structure Active sites Oxygen reduction reaction Oxygen evolution reaction

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LRRC25 plays a key role in all-trans retinoic acid-induced granulocytic differentiation as a novel potential leukocyte differentiation antigen

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Protein & Cell 2018年第9期9卷 785-798页

作者： Weili liu Ting Li Pingzhang Wang Wanchang liu Fujun liu Xiaoning Mo zhengyang liu Quansheng Song Ping Lv Guorui Ruan Wenling Han Department of Immunology School of Basic Medical Sciences Key Laboratory of Medical Immunology (Ministry of Health) Peking University Health Science Center Beijing 100191 China Peking University Center for Human Disease Genomics Beijing 100191 China Institute of Hematology Peking University People's Hospital Beijing 100044 China

Leukocyte differentiation antigens （LDAs） play important roles in the immune system, by serving as surface markers and participating in multiple biological activities, such as recognizing pathogens, mediating membrane signals, interacting with other cells or systems, and regulating cell differentiation and activation. Data mining is a powerful tool used to identify novel LDAs from whole genome. LRRC25 （leucine rich repeat-containing 25） was predicted to have a role in the function of myeloid cells by a large-scale ＂omics＂ data analysis. Further experimental validation showed that LRRC25 is highly expressed in primary myeloid cells, such as granulocytes and monocytes, and lowly/intermediately expressed in B cells, but not in T cells and almost all NK cells. It was down-regulated in multiple acute myeloid leukemia （AML） cell lines and bone marrow cells of AML patients and up-regulated after all-trans retinoic acid （ATRA）-mediated granulocytic differentiation in AML cell lines and acute promyelocytic leukemia （APL; AML-M3, FAB classification） cells. Localization analysis showed that LRRC25 is a type I transmembrane molecule. Although ectopic LRRC25 did not promote spontaneous differentiation of NB4 cells, knockdown of LRRC25 by siRNA or shRNA and knockout of LRRC25 by the CRISPR-Cas9 system attenuated ATRA-induced termi- nal granulocytic differentiation, and restoration of LRRC25 in knockout cells could rescue ATRA-induced granulocytic differentiation. Therefore, LRRC25, a potential leukocyte differentiation antigen, is a key regulator of ATRA-induced granulocytic differentiation.

关键词： LRRC25 differentiation antigen granulocytic differentiation ATRA AML

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Research on Information Architecture Design of Short-Form Video Social Platforms Based on Cognitive Psychology

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Psychology Research 2024年第1期14卷 1-13页

作者： zhengyang liu Albert Young Choi Hanyang University ERICA AnsanSouth Korea

This study investigates how cognitive psychology principles can be integrated into the information architecture design of short-form video platforms,like TikTok,to enhance user experience,engagement,and *** a questionnaire,it explores TikTok users’habits and preferences,highlighting how social media fatigue(SMF)impacts their interaction with the *** paper offers strategies to optimize TikTok’s *** suggests refining the organizational system using principles like chunking,schema theory,and working memory ***,it proposes incorporating shopping features within TikTok’s interface to personalize product suggestions and enable monetization for influencers and content ***,the study underlines the need to consider gender differences and user preferences in improving TikTok’s sharing features,recommending streamlined and customizable sharing options,collaborative sharing,and a system to acknowledge sharing *** to strengthen social connections and increase sharing likelihood,this research provides insights into enhancing information architecture for short-form video platforms,contributing to their growth and success.

关键词： information architecture design short-form video social cognitive psychology user experience

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A real-time multi-head mixed attention mechanism-based prediction method for tunnel boring machine disc cutter wear

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Science China Technological Sciences 2024年

In the process of hard rock tunnel excavation, workers often need to enter the tunnel boring machine (TBM)cutterhead at regular intervals to measure cutter wear. However, this method is time-consuming and labor-intensive. Existing cutter prediction models primarily rely on geological parameters to predict overall cutter wear before construction, making it challenging to monitor real-time wear at different locations of the cutter and obtain accurate geological parameters. To address these challenges, this paper proposes a multi-head mixed attention mechanism-based method for real-time wear prediction of TBM disc cutter. First, a method of cutter wear normalization to eliminate measurement noise is explored. Then, considering the complex correlation of TBM operating parameters in feature and time dimensions, a new multi-head mixed attention mechanism model is designed to establish the dependency between different features and different moments, to better establish the mapping model between operating parameters and cutter wear. Finally, the current cutter wear state can be calculated by accumulating the wear amount of all previous small excavation sections. The effectiveness of the method is verified by using field data from the Mumbai tunnel. The results demonstrate that the method is capable of real-time prediction of front cutter and edge cutter wear on the test set, achieving an average accuracy rate of 95.75%. Moreover, the method can update the cutter wear status after every meter of excavation, which has good real-time performance. In addition, the average accuracy of cutter wear prediction of the proposed method is 11.75%, 10.375%, 3.875%, 3.625%, 1.375%, 3.125%, 2.25%, and 0.75%higher than that of LSTM, CNN, LSTM-CNN, CACNN, SACNN, MMADNN, MTACNN, and MFACNN. In summary, this approach offers an accurate prediction of cutter wear state while reducing inspection time and costs and has high application value.

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随机参数摄动下的高超声速飞行器姿态控制

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系统工程与电子技术 2024年第2期46卷 703-714页

作者：刘正洋周丽张瑞南京信息工程大学自动化学院江苏南京210044 江苏省大气环境与装备技术协同创新中心江苏南京210044

针对高超声速飞行器随机参数摄动的姿态控制问题,提出一种基于轨迹线性化和扩展卡尔曼滤波(extended Kalman filter,EKF)的预测滑模控制方法。首先,针对随机参数摄动的高超声速飞行器非线性模型,采用轨迹线性化方法建立线性时变误差调... 详细信息

针对高超声速飞行器随机参数摄动的姿态控制问题,提出一种基于轨迹线性化和扩展卡尔曼滤波(extended Kalman filter,EKF)的预测滑模控制方法。首先,针对随机参数摄动的高超声速飞行器非线性模型,采用轨迹线性化方法建立线性时变误差调节模型。通过分析参数误差的统计特性,将统计信息以参数协方差矩阵的形式进行表示,并设计EKF对受扰误差状态进行滤波。然后,采用预测滑模控制方法设计误差稳定调节器,使系统快速趋于稳定。所提方法对随机参数摄动和非线性干扰都具有强鲁棒性。仿真验证了所提方法的有效性。

关键词：高超声速飞行器随机参数摄动轨迹线性化扩展卡尔曼滤波预测滑模

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氯盐环境下钢筋强度时变模型

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公路工程 2015年第3期40卷 270-274页

作者：刘正洋湖南省交通科学研究院湖南长沙410015

为了研究氯盐环境下钢筋强度规律,主要开展了以下工作:1运用Fick第二扩散定律,在基于氯离子扩散系数时变性以及多参数影响的基础上,得到了钢筋初锈时间,建立了蚀坑面积时变模型,继而构建了锈蚀钢筋强度时变模型;2对钢筋强度时变模型的... 详细信息

为了研究氯盐环境下钢筋强度规律,主要开展了以下工作:1运用Fick第二扩散定律,在基于氯离子扩散系数时变性以及多参数影响的基础上,得到了钢筋初锈时间,建立了蚀坑面积时变模型,继而构建了锈蚀钢筋强度时变模型;2对钢筋强度时变模型的影响因素进行了敏感性分析,发现混凝土保护层对钢筋强度的影响最大:当混凝土保护层厚度由10 mm增加到25 mm时,钢筋强度较之前可提高63%,而临界氯离子浓度对钢筋强度的影响最小;3利用误差传递公式对局部锈蚀钢筋的强度进行了理论分析,得到均值、变异系数计算模型,同时将所得分布的均值与试验所得数据对比证明此强度时变模型可用于工程实际预测。

关键词：时变氯离子扩散系数锈蚀钢筋强度模型

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基于价值创造的企业会计人才评价:理论框架、关键概念与运行机制

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会计研究 2019年第5期 89-96页

作者：刘正阳刘正航财政部会计司 100820 中央民族大学经济学院 100081

2018年2月,中共中央办公厅、国务院办公厅印发《关于分类推进人才评价机制改革的指导意见》提出“以职业属性和岗位要求为基础,健全科学的人才分类评价体系,创新多元评价方式”。基于该文件,本文尝试从价值创造视角构建企业会计人才评... 详细信息

2018年2月,中共中央办公厅、国务院办公厅印发《关于分类推进人才评价机制改革的指导意见》提出“以职业属性和岗位要求为基础,健全科学的人才分类评价体系,创新多元评价方式”。基于该文件,本文尝试从价值创造视角构建企业会计人才评价的理论框架,并研究企业会计人才评价范围等问题;探讨企业会计人才评价的运行机制,重点分析企业会计人才评价的原则,初步构建了企业会计人才评价指标体系。

关键词：价值创造会计人才评价理论框架关键概念运行机制

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融合RRT^(*)与DWA算法的移动机器人动态路径规划

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系统仿真学报 2024年第4期36卷 957-968页

作者：张瑞周丽刘正洋南京信息工程大学江苏南京210000 江苏省大气环境与装备技术协同创新中心江苏南京210000 江苏省气象能源利用与控制工程技术研究中心江苏南京210000

为实现移动机器人在复杂动态障碍物环境中的避障,提出一种改进的快速随机扩展树(rapidly-exploring random tree,RRT^(*))与动态窗口法(dynamic window approach,DWA)相融合的动态路径规划方法。基于已知环境信息,利用改进RRT^(*)算法... 详细信息

为实现移动机器人在复杂动态障碍物环境中的避障,提出一种改进的快速随机扩展树(rapidly-exploring random tree,RRT^(*))与动态窗口法(dynamic window approach,DWA)相融合的动态路径规划方法。基于已知环境信息,利用改进RRT^(*)算法生成全局最优安全路径。通过消除RRT^(*)算法产生的危险节点,来确保全局路径的安全性;使用贪婪算法去除路径中的冗余节点,以缩短全局路径的长度。利用DWA算法跟踪改进RRT^(*)算法规划的最优路径。当全局路径上出现静态障碍物时,通过二次调整DWA算法评价函数的权重来避开障碍物并及时回归原路线;当环境中出现移动障碍物时,通过提前检测危险距离并转向加速的方式安全驶离该区域。仿真结果表明:该算法在复杂动态环境中运行时间短、路径成本小,与障碍物始终保持安全距离,确保在安全避开动态障碍物的同时,跟踪最优路径。

关键词：移动机器人路径规划改进RRT^(*)算法动态窗口法动态避障

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