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8th International Conference on intelligent computing and Signal Processing, ICSP 2023

作者： Wang, Xiaohua Yang, Jie Hu, Min Wu, Xia Hefei University of Technology Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer Science and Information Engineering Hefei China

ISBN: (纸本)9798350302455

Traditional image emotion recognition focuses only on the emotion information embedded in the subject or part of the image, while ignoring the global emotion information. In this paper, we propose a new network based on Vision Transformer: a global perception network, containing a main module and a background module. The main module enhances the weighting of objects by showing the interdependencies between modelled channels. The background module further searches for emotional information in the background. In addition, we employ multi-task learning and Adaptive Gradient Clipping to improve the network. Extensive experiments show that our proposed method outperforms the state-of-the-art methods for image sentiment analysis. © 2023 IEEE.

关键词： Image classification

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The positive mass theorem for asymptotically flat manifolds with isolated conical singularities

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Science China Mathematics 2024年

作者： Xianzhe Dai Yukai Sun Changliang Wang Department of Mathematics University of California Santa Barbara Key Laboratory of Pure and Applied Mathematics School of Mathematical SciencesPeking University School of Mathematical Sciences and Institute for Advanced Study Key Laboratory of Intelligent Computing and Applications (Ministry of Education)Tongji University

We prove the positive mass theorem for asymptotically flat(AF for short) manifolds with finitely many isolated conical singularities. We do not impose the spin condition. Instead, we use the conformal blow-up techniqu...

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Acoustic Word Embedding Model with Transformer Encoder and Multivariate Joint Loss

Acoustic Word Embedding Model with Transformer Encoder and M...

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intelligent computing and Wireless Optical Communications (ICWOC), International Conference on

作者： Yunyun Gao Qiang Zhang Lasheng Zhao Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian China

As a representation of speech information, acoustic word embedding can enable query-by-example keyword search with low-resource speech data. An acoustic word embedding model with Transformer encoder and multivariate joint loss is presented in this article. First of all, on the basis of BLSTM, the model can extract richer information by adding a Transformer encoder, which improves representation ability of the embedding vector. Then, the contrast loss is improved according to the multiple negative samples, and combined with the hinge loss with distance characteristics, the model generates a more compact vector representation and improves the identification of features. Finally, considering the unbalanced characteristics of samples, the anti-focal loss is introduced to form a multivariate joint loss together with the above two losses, so as to make the model performance better. The model has achieved certain results in word recognition tasks and has certain competitiveness compared with other acoustic word models.

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IABC: An iteratively automatic machine learning boosted hand-eye calibration method for laser displacement sensor

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Chinese Journal of Aeronautics 2023年第8期36卷 422-453页

作者： Helin LI Bin LIN Tianyi SUI Liang XU Chen ZHANG Shuai YAN Yang WANG Xinquan HAO Deyu LOU School of Mechanical Engineering Ministry of EducationTianjin UniversityTianjin 300350China International Institute for Innovative Design and Intelligent Manufacturing of Tianjin University Shaoxing 312000China Science and Technology of Advanced Functional Composite Laboratory Aerospace Research Institute of Materials and Processing TechnologyBeijing 100076China Key Laboratory of Advanced Ceramics and Machining Technology of Ministry of Education Tianjin UniversityTianjin 300072China

An on-machine measuring(OMM)system with a laser displacement sensor(LDS)is designed for measuring free-form surfaces of hypersonic aircraft’s *** improve the measurement accuracy of the OMM system,a novel Iteratively Automatic machine learning Boosted hand-eye Calibration(IABC)method is *** the hand-eye relationship and LDS measurement errors can be calibrated in one calibration process without any hardware changes via ***,a new objective function is derived,containing analytical parameters of the handeye relationship and LDS ***,a hybrid calibration model composed of two kernels is proposed to solve the objective *** kernel is the analytical kernel designed for solving analytical *** kernel is the automatic machine learning(AutoML)kernel designed to model LDS *** two kernels are connected with stepwise iterations to find the best calibration *** with traditional methods,hand-eye experiments show that IABC reduces the calibration RMSE by about 50%.Verification experiments show that IABC reduces the measurement deviations by about 25%-50%and RMSEs within 40%.Even when the training data are obviously less than the test data,IABC performs *** demonstrate that IABC is more accurate than traditional hand-eye methods.

关键词： Hand-Eye Calibration Laser Displacement Sensor Machine learning Measurement errors On-Machine Measurement

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Humanoid Robot Collaborative Lifting Integrating Executable Judgment

Humanoid Robot Collaborative Lifting Integrating Executable ...

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2022 IEEE International Symposium on Product Compliance Engineering - Asia, ISPCE-ASIA 2022

作者： Chang, Hua Yi, Pengfei Liu, Rui Dong, Jing Hou, Yaqing Zhou, Dongsheng The Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian University Dalian China Dalian University of Technology Dalian China

ISBN: (数字)9798350332483

ISBN: (纸本)9798350332483

Humanoid robot collaborative lifting can be used in a variety of scenarios that require repetitive lifting tasks. Most existing studies of humanoid robot collaboration often assume that objects can always be lifted, which may result in damage to both the robot and the object if objects are too heavy to lift. To avoid such situations as much as possible, a collaborative lifting approach integrating executable judgment is proposed. First, a target search and localization method is constructed using monocular vision and marker points to identify the task object. Then, an executable judgment strategy is designed to determine whether the object is overweight or not according to robot force analysis. Finally, a multi-robot joint control model is proposed based on collaborative communication to perform collaborative tasks with different loads based on the judgment results. Experiments on two humanoid robots for different types and weights of targets show the effectiveness of the proposed approach. © 2022 IEEE.

关键词： Anthropomorphic robots

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An asymmetrically substituted dithieno[3,2-b:2',3'-d]pyrrole organic small-molecule hole-transporting material for high-performance perovskite solar cells

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Chinese Journal of Chemical Engineering 2022年第5期35卷 51-57页

作者： Jingwen Jia Yue Zhang Liangsheng Duan Quanping Wu Yu Chen Song Xue Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical EngineeringTianjin University of TechnologyTianjin 300384China Tianjin Key Laboratory of Organic Solar Cells and Photochemical Conversion Department of Applied ChemistryTianjin University of TechnologyTianjin 300384China

Hole-transporting materials play a vital role in terms of the performance of perovskite solar cells(PSCs).The dithieno[3,2-b:2’,3’-d]pyrrole(DTP),an S,N-heterocyclic building block,has been proved to be desirable for molecular design of hole-transporting materials in *** developed an asymmetrically substituted DTP small-molecule(JW12)and a reference compound(JW11).The asymmetrical structure of JW12 leads to different absorption properties and electron *** device in a planar n-i-p architecture using JW12 shows a much higher PCE(18.07%)than that based on JW11(15.46%),which is also better than the device based on spiro-OMe TAD(17.47%).We hope our research can provide a new perspective in molecular design of organic HTMs for perovskite solar cells.

关键词： Hole-transporting materials DTP Perovskite Photovoltaic performance

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A theoretical and deep learning hybrid model for predicting surface roughness of diamond-turned polycrystalline materials

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International Journal of Extreme Manufacturing 2023年第3期5卷 620-644页

作者： Chunlei He Jiwang Yan Shuqi Wang Shuo Zhang Guang Chen Chengzu Ren Tianjin Key Laboratory of Equipment Design and Manufacturing Technology Department of Mechanical EngineeringTianjin UniversityTianjin 30054People’s Republic of China Department of Mechanical Engineering Keio UniversityYokohama 223-8522Japan Tianjin Key Laboratory of the Design and Intelligent Control of the Advanced Mechatronical System School of Mechanical EngineeringTianjin University of TechnologyTianjin 300384People’s Republic of China School of Mechanical Engineering Yanshan UniversityQinhuangdao 066004People’s Republic of China

Polycrystalline materials are extensively employed in *** surface roughness significantly affects the working *** defects,particularly grain boundaries,have a great impact on the achieved surface roughness of polycrystalline ***,it is difficult to establish a purely theoretical model for surface roughness with consideration of the grain boundary effect using conventional analytical *** this work,a theoretical and deep learning hybrid model for predicting the surface roughness of diamond-turned polycrystalline materials is *** kinematic–dynamic roughness component in relation to the tool profile duplication effect,work material plastic side flow,relative vibration between the diamond tool and workpiece,etc,is theoretically *** material-defect roughness component is modeled with a cascade forward neural *** the neural network,the ratio of maximum undeformed chip thickness to cutting edge radius RT S,work material properties(misorientation angle θ_(g) and grain size d_(g)),and spindle rotation speed n s are configured as input *** material-defect roughness component is set as the output *** validate the developed model,polycrystalline copper with a gradient distribution of grains prepared by friction stir processing is machined with various processing parameters and different diamond *** with the previously developed model,obvious improvement in the prediction accuracy is observed with this hybrid prediction *** on this model,the influences of different factors on the surface roughness of polycrystalline materials are *** influencing mechanism of the misorientation angle and grain size is quantitatively *** fracture modes,including transcrystalline and intercrystalline fractures at different RTS values,are ***,optimal processing parameters are obtained with a simulated annealing *** experiments are performed with

关键词： diamond turning material-defect roughness component polycrystalline copper neural network simulated annealing algorithm

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Impulsive Control of Heterogeneous Multi-agent Systems with Saturation Constraint and Time Delay

Impulsive Control of Heterogeneous Multi-agent Systems with ...

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2024 China Automation Congress, CAC 2024

作者： Jiao, Ranran Li, Bo Chen, Xiangyong Jiang, Xiaowei School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control Intelligent Automation of Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Finance Anhui University of Finance and Economics Bengbu China Key Laboratory of Complex systems and Intelligent Computing in Universities of Shandong Linyi University Linyi China

ISBN: (纸本)9798350368604

This paper addresses the problem of leader-following consensus in heterogeneous multi-agent systems (HMAS) with input saturation and communication delay. Given the practical differences between leader and follower dimensions, we design virtual leaders to address this problem by allowing actual leaders and followers to communicate with virtual leaders separately, thus enabling indirect communication between actual leaders and followers. Additionally, the control protocol proposed in this paper takes into account the effects of input saturation and time delay that exist in real communication. At last, a simulation example is presented to demonstrate the effectiveness of the designed control protocol. © 2024 IEEE.

关键词： Multi agent systems

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BContext2Name: Naming Functions in Stripped Binaries with Multi-Label Learning and Neural Networks 10

BContext2Name: Naming Functions in Stripped Binaries with Mu...

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10th IEEE International Conference on Cyber Security and Cloud computing and 9th IEEE International Conference on Edge computing and Scalable Cloud, CSCloud-EdgeCom 2023

作者： Xia, Bing Ge, Yunxiang Yang, Ruinan Yin, Jiabin Pang, Jianmin Tang, Chongjun Dept.ZhongYuan University of Technology Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China Dept.ZhongYuan University of Technology Henan Key Laboratory on Public Opinion Intelligent Analysis Zhengzhou China Dept.ZhongYuan University of Technology Zhengzhou China Dept.Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9798350312461

Conducting binary function naming helps reverse engineers understand the internal workings of the code and perform malicious code analysis without accessing the source code. However, the loss of debugging information poses the challenge of insufficient high-level semantic information description for stripping binary code function naming. Meanwhile, the existing binary function naming scheme has one function label for only one sample. The long-tail effect of function labels for a single sample makes the machine learning-based prediction models face the challenge. To obtain a function correlation label and improve the propensity score of uncommon tail labels, we propose a multi-label learning-based binary function naming model BContext2Name. This model automatically generates relevant labels for binary function naming by function context information with the help of PfastreXML model. The experimental results show that BContext2Name can enrich function labels and alleviate the long-tail effect that exists for a single sample class. To obtain high-level semantics of binary functions, we align pseudocode and basic blocks based on disassembly and decompilation, identify concrete or abstract values of API parameters by variable tracking, and construct API-enhanced control flow graphs. Finally, a seq2seq neural network translation model with attention mechanism is constructed between function multi-label learning and enhanced control flow graphs. Experiments on the dataset reveal that the F1 values of the BContext2Name model improve by 3.55% and 15.23% over the state-of-the-art XFL and Nero, respectively. This indicates that function multi-label learning can provide accurate labels for binary functions and can help reverse analysts understand the inner working mechanism of binary code. Code and data for this evaluation are available at https://***/CSecurityZhongYuan/BContext2Name. © 2023 IEEE.

关键词： Graphic methods

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Hierarchically Micro/Nanostructured Current Collectors Induced by Ultrafast Femtosecond Laser Strategy for High-Performance Lithium-ion Batteries

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Energy & Environmental Materials 2022年第3期5卷 969-976页

作者： Yaya Wang Zexu Zhao Jiang Zhong Tao Wang Lei Wang Hanjiao Xu Jinhui Cao Jinhao Li Guanhua Zhang Huilong Fei Jian Zhu State Key Laboratory for Chemo/Biosensing and Chemometrics College of Chemistry and Chemical EngineeringHunan Key Laboratory of TwoDimensional MaterialsEngineering Research Center of Advanced CatalysisMinistry of EducationHunan UniversityChangsha 410082China State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan Provincial Key Laboratory of Intelligent Laser ManufacturingHunan UniversityChangsha 410082China College of Mechanical and Vehicle Engineering Hunan UniversityChangsha 410082China

Commercial Cu and Al current collectors for lithium-ion batteries(LIBs)possess high electrical conductivity,suitable chemical and electrochemical ***,the relatively flat surface of traditional current collectors causes weak bonding strength and poor electrochemical contact between current collectors and electrode materials,resulting in potential detachment of active materials and rapid capacity degradation during extended ***,we report an ultrafast femtosecond laser strategy to manufacture hierarchical micro/nanostructures on commercial Al and Cu foils as current collectors for high-performance *** hierarchically micro/nanostructured current collectors(HMNCCs)with high surface area and roughness offer strong adhesion to active materials,fast electronic delivery of entire electrodes,significantly improving reversible capacities and cyclic stability of HMNCCs based ***,LiNi_(0.5)Co_(0.2)Mn_(0.3)O_(2)(NCM523)cathode with Al HMNCC generated a high reversible capacity after 200 cycles(25%higher than that of cathode with Al CC).Besides,graphite anode with Cu HMNCC also maintained prominent reversible capacity even after 600 ***,the full cell assembled by graphite anode with Cu HMNCC and NCM523 cathode with Al HMNCC achieved high reversible capacity and remarkable cycling stability under industrial-grade mass *** study provides promising candidate for achieving high-performance LIBs current collectors.

关键词： currentcollectors femtosecondlaserstrategy hierarchical micro/nanostructures high rate performance lithium-ion battery

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