Conference on Intelligent and Human-Computer Interaction Technology最新文献_第6页

Discrete element modelling of Camellia oleifera fresh fruit and its simulation 油茶鲜果离散元建模及其仿真

Conference on Intelligent and Human-Computer Interaction Technology Pub Date : 2022-10-07 DOI: 10.1117/12.2655202

Hefei Zhang, Xujie Li, Fengxin Yan

{"title":"Discrete element modelling of Camellia oleifera fresh fruit and its simulation","authors":"Hefei Zhang, Xujie Li, Fengxin Yan","doi":"10.1117/12.2655202","DOIUrl":"https://doi.org/10.1117/12.2655202","url":null,"abstract":"According to the problems such as the absence of an accurate model of Camellia oleifera fresh fruit, inaccurate simulation process of decladding, and experience-based development of decladding equipment, the study combined the feature of shape structure and material characteristics of Camellia oleifera fruit, and is based on the bonded-particle model of discrete element method (DEM). The spherical equation was used to establish the contour of Camellia fresh fruit, and the crack line structure model of shell was generated in meta-particle method. The flexible model of seed was constructed by the particle accumulation method, and the particle coordinate control program was compiled to construct the flexible composite DEM model of Camellia oleifera fruit. The load-displacement curve of compression in the simulation test of Camellia oleifera fruit is basically consistent with that of the physical experiment, and the accuracy of the DEM model of Camellia oleifera fruit is verified. The research results provide theoretical guidance for revealing the mechanism of Camellia oleifera fresh fruit decladding and optimizing technical parameters of decladding equipment.","PeriodicalId":312603,"journal":{"name":"Conference on Intelligent and Human-Computer Interaction Technology","volume":"220 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130494165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

The application of computer image processing in interface design 计算机图像处理在界面设计中的应用

Conference on Intelligent and Human-Computer Interaction Technology Pub Date : 2022-10-07 DOI: 10.1117/12.2655194

Xin Huang, Jingwen Luo

引用次数: 0

Rehabilitation exercise based on brain-machine interaction with wearable robot 基于可穿戴机器人脑机交互的康复训练

Conference on Intelligent and Human-Computer Interaction Technology Pub Date : 2022-10-07 DOI: 10.1117/12.2655692

Zhouhao Jiang, X. Cheng, Kunqiang Qing

{"title":"Rehabilitation exercise based on brain-machine interaction with wearable robot","authors":"Zhouhao Jiang, X. Cheng, Kunqiang Qing","doi":"10.1117/12.2655692","DOIUrl":"https://doi.org/10.1117/12.2655692","url":null,"abstract":"This study proposes deep learning called Convolutional Neural Network (CNN), which can enhance the classification performance of five different rehabilitation exercise scenarios based on brain-machine interaction (BMI). Also, it further presents the feasibility of helping stroke patients and healthy people to assist in rehabilitation exercise. This work designs a wearable hand robot and five different motor images (MI) for exercise guidance on the computer screen. A participant is also asked to set on a chair to acquire the cerebral response signals using the function near-infrared spectroscopy (fNIRS). Deep learning called convolutional neural network (CNN) is utilized to extract and classify the collected data and make commands to the wearable hand robot. The classification accuracy of the S_2 MI is the highest value for participant 1; the classification accuracy of the S_1 MI is the highest value for participant 2. Besides, the S_5 and S_3 MI showed the lowest classification accuracy for participant one and participant two, respectively. Propose a CNN framework with visual guidance to control wearable robots to reduce incorrect commands, and present a rehabilitation exercise feasibility to stroke patients and healthy people with less time.","PeriodicalId":312603,"journal":{"name":"Conference on Intelligent and Human-Computer Interaction Technology","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115091859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Motion control and planning of a two-dimensional flying machine 二维飞行器的运动控制与规划

Conference on Intelligent and Human-Computer Interaction Technology Pub Date : 2022-10-07 DOI: 10.1117/12.2655274

Jiaye Wang

引用次数: 0

KNN vs. DNN: auto chatbot KNN与DNN:自动聊天机器人

Conference on Intelligent and Human-Computer Interaction Technology Pub Date : 2022-10-07 DOI: 10.1117/12.2655749

Qiushi Xu

引用次数: 0

Multi-objective optimization design of assembly tolerance based on improved NSGA-II algorithm 基于改进NSGA-II算法的装配公差多目标优化设计

Conference on Intelligent and Human-Computer Interaction Technology Pub Date : 2022-10-07 DOI: 10.1117/12.2655688

Zhuo Li, Chenwei Feng, Chuanlin Li, Zhenzhe Zhong, Yu Sun

引用次数: 0