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Multi-stream fusion network for continuous gesture recognition based on sEMG

International Journal of Wireless and Mobile Computing 2024年第4期26卷 374-383页

作者： Li, Jun Zou, Chunlong Tang, Dalai Sun, Ying Fan, Hanwen Li, Boao Tang, Xinjie Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Hubei Wuhan China College of Mechanical Engineering Hubei University of Automotive Technology Hubei Shiyan China Inner Mongolia University of Finance and Economics Hohhot China Research Centre for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Hubei Wuhan China Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Hubei Wuhan China

Dynamic gesture recognition is an essential step in human-computer interaction. However, dynamic gesture recognition based on Surface Electromyography (sEMG) signals faces issues such as incomplete feature extraction and incomplete recognition of temporal information between continuous gestures. Therefore, this paper proposes a multi-stream fusion network (MSK-LCNN) for dynamic gesture recognition to improve accuracy. We combine CNN and LSTM models into a unified framework which extracts spatio-temporal information both globally and in depth, and combines feature fusion to retain essential information. This framework uses an attention mechanism (SKNet) to learn more intricate feature information. The gesture recognition accuracy of this method on our data set is 95.23%, and on the NinaPro DB1 data set, it is 91.45%, which outperforms other similar networks in recent years. Applying this algorithm to prosthetic hand control has achieved flexible and stable control of the prosthetic hand. © 2024 Inderscience Enterprises Ltd.

关键词： Gesture recognition

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Optimised design of cross-shaft parameters based on response surface optimisation model with MOGA

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International Journal of Wireless and Mobile Computing 2024年第2期26卷 198-206页

作者： Xiong, Sijie Xie, Yuanmin Zou, Chunlong Mao, Yanfeng Cao, Yongcheng Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Hubei Wuhan China Research Centre for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Hubei Wuhan China Precision Manufacturing Research Institute Wuhan University of Science and Technology Hubei Wuhan China Hubei University of Automotive Technology Hubei Shiyan China Technology Research and Development Hubei Jingmen Wusan Machinery Equipment Manufacturing Co. Ltd. Jingmen Hubei China

Cross-shaft is the core component of the cross-type universal coupling and has a vital transmission function. This paper proposes Sparse Grid and the Kriging interpolation to construct a response surface model to solve the problem of long design cycles, low reliability and high susceptibility to cross-shaft fatigue deformation. The critical dimensions of the cross-shaft are used as design variables, and the maximum equivalent force and deformation are reduced as the optimisation objective. Then experimental points are obtained by Sparse Grid Initialisation and then the response surface model is obtained with high accuracy by Kriging interpolation, and finally, the optimised design of the cross-shaft is completed using MOGA in this paper. Compared with the original structural solution, the maximum deformation of the cross-shaft is reduced by 0.4717 mm (22.35%), the maximum equivalent force is reduced by 130.35 Mpa (17.21%) and the mass increased by only 4.17%. © 2024 Inderscience Enterprises Ltd.

关键词： Multiobjective optimization

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Indoor object segmentation based on YOLACT++

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International Journal of Wireless and Mobile Computing 2023年第2期24卷 127-133页

作者： Sun, Ying Zhao, Zichen Tao, Bo Liu, Xin Yun, Juntong Liu, Ying Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Hubei Wuhan China Research Centre for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of science and Technology Hubei Wuhan China Precision Manufacturing Research Institute Wuhan University of Science and Technology Hubei Wuhan China

intelligent manufacturing originates from the research of artificial intelligence, which can not only reduce operating costs, but also improve product quality, and has become the way to cultivate new advantages in forging international competition in manufacturing. With the transformation of traditional manufacturing to intelligent manufacturing, the course of intelligent manufacturing should also be different from the traditional teaching mode, but through the survey, it has been found that the course of intelligent manufacturing still has a single teaching mode, insufficient innovative guidance for students and insufficient combination of theory and practice. In order to solve the issues mentioned above, the Project-Analysis-Evaluation (PAE) structure is proposed in this paper, and it is combined with constructivist theory and analysed through the study of indoor object instance segmentation detection. The YOLACT++ algorithm is pre-trained on SUNRGBD dataset and applied to indoor environment detection in this paper. © 2023 Inderscience Enterprises Ltd.

关键词： Operating costs

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Unveiling insights in source code defect prediction using ChatGPT: moving beyond predictive metrics 4

Unveiling insights in source code defect prediction using Ch...

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4th International Conference on Signal Processing and Computer Science, SPCS 2023

作者： Pan, Cong Gu, Ai Gao, Yan Key Laboratory of General Quality Technology Application for Intelligent Manufacturing Equipment China Electronic Product Reliability and Environmental Testing Research Institute Guangzhou511370 China

ISBN: (纸本)9781510672505

In the realm of software engineering, defect prediction stands as a vital and valuable research domain. With the emergence of powerful models like ChatGPT, the potential for enhancing software defect prediction becomes significant. Leveraging the GHPR defect prediction dataset, this study delves into the application of ChatGPT for source code-level defect prediction. Different prompt paradigms, including general-purpose prompts, prompts that emphasize minority class, prompts that include few-shot examples, prompts that include target explanations, and prompts using chain-of-thoughts (CoT), are investigated for their impact on predictive outcomes. Furthermore, a comparative analysis is conducted between specific defects predicted by ChatGPT and defects rectified by developers in the GHPR dataset. While direct application of ChatGPT in source code-level defect prediction shows results akin to random guessing, the study reveals that employing CoT prompts unveils a propensity for ChatGPT to identify a higher number of issues, proposing questions with heightened rationale. The findings emphasize the necessity to move beyond predictive metrics when utilizing ChatGPT for source code-based defect prediction, advocating for a more profound analytical approach. © 2023 SPIE.

关键词： Defects

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A Latent Diffusion Based Image Generation Method for Anomaly Detection 8th

A Latent Diffusion Based Image Generation Method for Anomaly...

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8th International Conference on Computing, Control and Industrial Engineering, CCIE 2024

作者： Wang, Liangliang Song, Lian Yang, Zhuo Li, Bingyao Liang, Peidong School of Computer Science and Artificial Intelligence Wuhan University of Technology Wuhan China Wuhan University of Technology Chongqing Research Institute Chongqing China Institute of Advanced Manufacturing Technology Quanzhou China Fujian Key Laboratory of Intelligent Operation and Maintenance Robot Technology Quanzhou China

ISBN: (纸本)9789819769360

The primary issue in visual anomaly detection is lack of sufficient samples, which makes it difficult for real-world applications unless an effective anomalous image generation algorithm is proposed. To this end, this paper formulates a latent diffusion model to generate a variety of anomalous images by adapting the initial latent tensors to the anomaly. Therefore, the diffusion process is speeded up via transferring the image synthesis in a low-dimensional space, with anomalous labels provided. The pseudo-anomaly images and pseudo-labels are then used for data augmentation for anomaly detection based on YOLO-v8, and quantitative and qualitative experiments on NEU-DET demonstrate the applicability and superiority of our approach on precision and diversity. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Anomaly detection Deep learning Diffusion model Image generation

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Experimental research on affecting factors of the cutting quality of sugarcane harvesters under complicated excitations

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International Journal of Agricultural and Biological Engineering 2024年第5期17卷 176-192页

作者： Hanning Mo Shaochun Ma Chen Qiu Zhimin Huang Shangping Li Guangxi Key Laboratory of the Advanced Microwave Manufacturing Technology Guangxi Academy of SciencesNanning 530007China School of Mechanical and Resource Engineering Wuzhou UniversityWuzhou 543000GuangxiChina State Key Laboratory of Intelligent Agricultural Power Equipment College of EngineeringChina Agricultural UniversityBeijing 100083China College of Electronic Information Guangxi Minzu UniversityNanning 530006China

The sugarcane field excitation,cutting forces and the engine excitation constitute complicated excitations acting on sugarcane *** this study,the sugarcane cutting mechanism under complicated excitations was *** dynamics and the mathematical models of sugarcane harvesters were established and *** on theoretical analysis,sugarcane cutting experiments were done on a self-built sugarcane harvester test platform(SHTP),designed as single-factor and the orthogonal *** of the sugarcane field excitation characterized by the sugarcane field excitation device(SFED)output frequency,the engine excitation characterized by the actuating engine output frequency,the cutter rotating speed,the sugarcane harvester travelling speed simulated through the sugarcane transporting speed of the SHTP and the cutter inclination angle on the cutting quality of sugarcane harvesters were *** of the axial cutter vibration on three-directional cutting forces and the sugarcane cutting quality(SCQ)as well as effects of three-directional cutting forces on the SCQ were further *** is shown that the sugarcane field excitation,the axial cutter vibration amplitude and frequency as well as the three-directional cutting forces have significantly negative monotonic correlated effects on the SCQ while the cutter rotating speed,the sugarcane harvester travelling speed and the cutter inclination angle have significantly positive monotonic correlated effects on the *** levels of effects on three-directional cutting forces and the SCQ form high to low are as follow,the axial cutter vibration,the sugarcane field excitation,the cutter rotating speed,the engine excitation,the cutter inclination angle,the sugarcane harvester travelling *** theoretical analysis results were verified through experiment and an optimal combination was obtained with the cutter rotating speed of 700 r/min,sugarcane harvester travelling speed of 0.6 m/s and

关键词： sugarcane harvester cutting quality complicated excitations experimental research theoretical analysis

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Graph-to-Text Generation Combining Directed and Undirected Structural Information in Knowledge Graphs∗ 5

Graph-to-Text Generation Combining Directed and Undirected S...

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5th International Conference on Natural Language Processing, ICNLP 2023

作者： Gong, Hongda Shan, Shimin Wei, Hongkui Dalian University of Technology Software School DaLian116620 China Beijing Institute of Electronic System Engineering State Key Laboratory of Intelligent Manufacturing System Technology Beijing100854 China

ISBN: (纸本)9798350302219

Graph-to-text generation task is transforms knowledge graphs into natural language. In current research, pretrained language models(PLMs) have shown better performance than structured graph encoders in the generation task. Currently, PLMs serialise knowledge graphs mostly by transforming them into undirected graph structures. The advantage of an undirected graph structure is that it provides a more comprehensive representation of the information in knowledge graph, but it is difficult to capture the dependencies between entities, so the information represented may not be accurate. Therefore, We use four types of positional embedding to obtain both the directed and undirected structure of the knowledge graph, so that we can more fully represent the information in knowledge graph, and the dependencies between entities. We then add a semantic aggregation module to the Transformer layer of PLMs, which is used to obtain a more comprehensive representation of the information in knowledge graph, as well as to capture the dependencies between entities. Thus, our approach combines the advantages of both directed and undirected structural information. In addition, our new approach is more capable of capturing generic knowledge and can show better results with small samples of data. © 2023 IEEE.

关键词： Knowledge graph

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Method for the multi-view estimation of fish mass using a two-stage neural network with edge-sensitive module

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International Journal of Agricultural and Biological Engineering 2024年第3期17卷 222-229页

作者： Zeyu Jiao Yingjie Cai Qi Zhang Zhenyu Zhong Guangdong Key Laboratory of Modern Control Technology Institute of Intelligent ManufacturingGuangdong Academy of SciencesGuangzhou 510070China Department of Electronic Engineering The Chinese University of Hong KongHong Kong 999077China College of Economics and Management Northwest A&F UniversityYangling 712100ShaanxiChina

The estimation of fish mass is one of the most basic and important tasks in *** the mass of fish at different growth stages is of great significance for feeding,monitoring the health status of fish,and making breeding plans to increase *** existing estimation methods for fish mass often stay in the 2D plane,and it is difficult to obtain the 3D information on fish,which will lead to the *** solve this problem,a multi-view method was proposed to obtain the 3D information of fish and predict the mass of fish through a two-stage neural network with an edge-sensitive *** the first stage,the side-and downward-view images of the fish and some 3D information,such as side area,top area,length,deflection angle,and pitch angle,were captured to estimate the size of the fish through two vertically placed *** the area of the fish at different views was estimated accurately through the pre-trained image segmentation neural network with an edgesensitive *** the second stage,a fully connected neural network was constructed to regress the fish mass based on the 3D information obtained in the previous *** experimental results indicate that the proposed method can accurately estimate the fish mass and outperform the existing estimation methods.

关键词： fish mass multi-view estimation two-stage neural network edge-sensitive module image segmentation

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Base position planning of mobile manipulators for assembly tasks in construction environments

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Advances in manufacturing 2023年第1期11卷 93-110页

作者： Dai-Jun Xie Ling-Dong Zeng Zhen Xu Shuai Guo Guo-Hua Cui Tao Song Shanghai Key Laboratory of Intelligent Manufacturing and Robotics School of Mechatronic Engineering and AutomationShanghai UniversityShanghai200444People’s Republic of China National Demonstration Center for Experimental Engineering Training Education Shanghai UniversityShanghai200444People’s Republic of China School of Mechanical and Automotive Engineering Shanghai University of Engineering ScienceShanghai201620People’s Republic of China Shanghai Collaborative Innovation Center of Intelligent Manufacturing Robot Technology for Large Components Shanghai201620People’s Republic of China

With good mobility and flexibility,mobile manipulators have shown broad applications in construction *** position(BP)planning,which refers to the robot autonomously determining its working station in the environment,is an important technique for mobile manipulators when performing the construction assembly task,especially in a large-scale construction ***,the BP planning process is tedious and time-consuming for a human worker to carry ***,to improve the efficiency of construction assembly tasks,a novel BP planning method is proposed in this paper,which can lead to appropriate BPs and minimize the number of BPs at the same ***,the feasible BP regions are generated based on the grid division and the variable workspace of the mobile ***,the positioning uncertainties of the mobile manipulator are considered in calculating the preferred BP areas using ***,a set coverage optimization model is established to obtain the minimum number of BPs using an optimization algorithm according to the greedy *** simulated experiment based on a 9-degree of free(DoF)mobile manipulator has been *** results illustrated that the time for BP planning was significantly reduced and the number of BPs was reduced by 63.41%compared to existing manual planning,which demonstrated the effectiveness of the proposed method.

关键词： Base position(BP)planning Mobile manipulators Variable workspace Positioning uncertainties Construction environments

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The Immense Impact of Reverse Edges on Large Hierarchical Networks

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Engineering 2024年第5期36卷 240-249页

作者： Haosen Cao Bin-Bin Hu Xiaoyu Mo Duxin Chen Jianxi Gao Ye Yuan Guanrong Chen Tamás Vicsek Xiaohong Guan Hai-Tao Zhang MOE Engineering Research Center of Autonomous Intelligent Unmanned Systems State Key Laboratory of Intelligent Manufacturing Equipment and TechnologySchool of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingapore 639798Singapore Jiangsu Key Laboratory of Networked Collective Intelligence School of MathematicsSoutheast UniversityNanjing 210096China Department of Computer Science Rensselaer Polytechnic InstituteTroyNY 12180USA Department of Electronic Engineering City University of Hong KongHong Kong 999077China Department of Biological Physics Eötvös UniversityBudapest 1117Hungary MOE Key Laboratory for Intelligent Networks and Network Security School of Automation Science and EngineeringXi’an Jiaotong UniversityXi’an 710049China

Hierarchical networks are frequently encountered in animal groups,gene networks,and artificial engineering systems such as multiple robots,unmanned vehicle systems,smart grids,wind farm networks,and so *** structure of a large directed hierarchical network is often strongly influenced by reverse edges from lower-to higher-level nodes,such as lagging birds’howl in a flock or the opinions of lowerlevel individuals feeding back to higher-level ones in a social *** study reveals that,for most large-scale real hierarchical networks,the majority of the reverse edges do not affect the synchronization process of the entire network;the synchronization process is influenced only by a small part of these reverse edges along specific *** surprisingly,a single effective reverse edge can slow down the synchronization of a huge hierarchical network by over 60%.The effect of such edges depends not on the network size but only on the average in-degree of the involved *** overwhelming majority of active reverse edges turn out to have some kind of“bunching”effect on the information flows of hierarchical networks,which slows down synchronization *** finding refines the current understanding of the role of reverse edges in many natural,social,and engineering hierarchical networks,which might be beneficial for precisely tuning the synchronization rhythms of these *** study also proposes an effective way to attack a hierarchical network by adding a malicious reverse edge to it and provides some guidance for protecting a network by screening out the specific small proportion of vulnerable nodes.

关键词： Synchronizability Large hierarchical networks Reverse edges Information flows Complex networks

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