Existing lane line detection algorithm for identification of a straight line in good condition, to solve the problem of curve, however, failed to find a good strategy, especially in large curvature of curve, the visual field to extract the lane line produces by the two become one, resulting in a wrong calculation, in the case of real vehicle test, bend by camera height, visual field, etc. The indoor robot car is used as the carrier for the test, and a turning strategy is proposed to recognize the lane line at the corner, and the lane line detection algorithm based on sliding window is improved to make it less affected by the environment. The algorithm is simple and efficient, which is suitable for the indoor robot car visual line inspection. The experimental results show that the lane detection algorithm proposed in this paper improves the passing rate and stability of the robot car under large area rate curves.
{"title":"Research on lane detection algorithm for large curvature curve","authors":"Shihe Tian, Zhian Zhang, X. Huang","doi":"10.1117/12.2672222","DOIUrl":"https://doi.org/10.1117/12.2672222","url":null,"abstract":"Existing lane line detection algorithm for identification of a straight line in good condition, to solve the problem of curve, however, failed to find a good strategy, especially in large curvature of curve, the visual field to extract the lane line produces by the two become one, resulting in a wrong calculation, in the case of real vehicle test, bend by camera height, visual field, etc. The indoor robot car is used as the carrier for the test, and a turning strategy is proposed to recognize the lane line at the corner, and the lane line detection algorithm based on sliding window is improved to make it less affected by the environment. The algorithm is simple and efficient, which is suitable for the indoor robot car visual line inspection. The experimental results show that the lane detection algorithm proposed in this paper improves the passing rate and stability of the robot car under large area rate curves.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131579515","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}
Qingqing Li, Qing-zhong Hu, Yun Qin, Like Tao, Jinyong Xu
Based on the stable operation of the intelligent production line for molten salt electrolysis of rare earth oxides, Flink technology is used to monitor the information of equipment, materials and relevant operators in the electrolysis process online, centralize processing and analysis, alert abnormal information in time, use big data analysis technology to make the production elements controllable and in an optimal state, solve the problems of unstable product quality, unstable power consumption and unstable material ratio in the refining of rare earth metals (alloys) that exist in the manual operation of the whole industry, and realize the centralization, digitalization, remoteness and intelligence of rare earth metal smelting.
{"title":"Research on the digital application of molten salt electrolysis based on distributed clusters","authors":"Qingqing Li, Qing-zhong Hu, Yun Qin, Like Tao, Jinyong Xu","doi":"10.1117/12.2671968","DOIUrl":"https://doi.org/10.1117/12.2671968","url":null,"abstract":"Based on the stable operation of the intelligent production line for molten salt electrolysis of rare earth oxides, Flink technology is used to monitor the information of equipment, materials and relevant operators in the electrolysis process online, centralize processing and analysis, alert abnormal information in time, use big data analysis technology to make the production elements controllable and in an optimal state, solve the problems of unstable product quality, unstable power consumption and unstable material ratio in the refining of rare earth metals (alloys) that exist in the manual operation of the whole industry, and realize the centralization, digitalization, remoteness and intelligence of rare earth metal smelting.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123259919","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}
Firstly, this paper introduces the importance of welding specialty in colleges and universities and the application direction of welding technology, then analyzes the problems existing in welding training courses in colleges and universities, and finally puts forward the application of virtual reality technology to change the current situation of welding training. Based on the in-depth study of virtual reality technology, the author decided to design and develop a welding training simulation platform based on Web3D. The overall design framework of the platform is B/S combined with MVC design pattern, and the realization of each functional module is based on ASP.NET technology. The virtual reality part uses Unity 3D and 3DMAX software to complete modeling and animation interaction. The construction of this platform aims at improving the practical teaching effect of welding specialty and cultivating students' welding technical ability on the basis of safety, environmental protection and cost saving.
{"title":"Design and implementation of welding training simulation platform based on virtual reality technology","authors":"Wei Wang","doi":"10.1117/12.2671859","DOIUrl":"https://doi.org/10.1117/12.2671859","url":null,"abstract":"Firstly, this paper introduces the importance of welding specialty in colleges and universities and the application direction of welding technology, then analyzes the problems existing in welding training courses in colleges and universities, and finally puts forward the application of virtual reality technology to change the current situation of welding training. Based on the in-depth study of virtual reality technology, the author decided to design and develop a welding training simulation platform based on Web3D. The overall design framework of the platform is B/S combined with MVC design pattern, and the realization of each functional module is based on ASP.NET technology. The virtual reality part uses Unity 3D and 3DMAX software to complete modeling and animation interaction. The construction of this platform aims at improving the practical teaching effect of welding specialty and cultivating students' welding technical ability on the basis of safety, environmental protection and cost saving.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126569766","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}
One of the most common malignancies worldwide is breast cancer. Early screening and diagnosis are important to the reduction of mortality rates of patients. In order to improve the performance and accuracy of breast cancer image screening, researchers have made significant progress in Computer-aided diagnosis (CAD) systems built on convolutional neural networks (CNN). In this research, several recent CNN models of breast cancer diagnosis are discussed and explained, and multiple public datasets of breast cancer images are introduced. The detailed performances of the models are presented and compared. The limitations and potential improvements of current CNN-based CAD are discussed. Convolution neural network-based CAD are still facing challenges of shortage of public dataset and the problem of implementation in the clinical scenario. Conclusively, using a convolutional neural network to diagnose breast cancer is still at its early stage, and further developments are required to apply convolutional neural network-based cancer diagnosis to clinical practices.
{"title":"Recent trend analysis of convolutional neural network-based breast cancer diagnosis","authors":"Mingzhe Liu","doi":"10.1117/12.2672660","DOIUrl":"https://doi.org/10.1117/12.2672660","url":null,"abstract":"One of the most common malignancies worldwide is breast cancer. Early screening and diagnosis are important to the reduction of mortality rates of patients. In order to improve the performance and accuracy of breast cancer image screening, researchers have made significant progress in Computer-aided diagnosis (CAD) systems built on convolutional neural networks (CNN). In this research, several recent CNN models of breast cancer diagnosis are discussed and explained, and multiple public datasets of breast cancer images are introduced. The detailed performances of the models are presented and compared. The limitations and potential improvements of current CNN-based CAD are discussed. Convolution neural network-based CAD are still facing challenges of shortage of public dataset and the problem of implementation in the clinical scenario. Conclusively, using a convolutional neural network to diagnose breast cancer is still at its early stage, and further developments are required to apply convolutional neural network-based cancer diagnosis to clinical practices.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123893522","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}
Font generation is a challenging problem. To address the existing problems of poor font style conversion models, which have missing structure, blurred glyphs and require paired datasets, this paper proposes a Chinese font style migration algorithm based on the improved CycleGan. The model introduces deformable convolution in the encoder part of the generator, which can learn the font features adaptively. A skip connection module, which fuses global and local features, was added to the model, and the features in the encoder are projected to the decoder using this module to avoid the structural error problem by reducing the information loss of the decoder. Meanwhile, using the attention mechanism, we can quickly and efficiently obtain the key information of the target region. On this basis, we can further complete the local and global feature fusion. According to the research results, this method can better achieve font generation in practice, so it has high application value.
{"title":"Chinese font generation based on deep learning","authors":"Xuexin Li, Yichen Ma, Di Shen","doi":"10.1117/12.2671957","DOIUrl":"https://doi.org/10.1117/12.2671957","url":null,"abstract":"Font generation is a challenging problem. To address the existing problems of poor font style conversion models, which have missing structure, blurred glyphs and require paired datasets, this paper proposes a Chinese font style migration algorithm based on the improved CycleGan. The model introduces deformable convolution in the encoder part of the generator, which can learn the font features adaptively. A skip connection module, which fuses global and local features, was added to the model, and the features in the encoder are projected to the decoder using this module to avoid the structural error problem by reducing the information loss of the decoder. Meanwhile, using the attention mechanism, we can quickly and efficiently obtain the key information of the target region. On this basis, we can further complete the local and global feature fusion. According to the research results, this method can better achieve font generation in practice, so it has high application value.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115439536","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}
In order to exclude differences in the perception of vibration by different testers and to help the relevant authorities to plan maintenance and determine the timing of line repairs, the vehicle jitter threshold was analysed to make it one of the predictors of sustained vehicle jitter and to exclude to a certain extent the interference of the testers' physical sensations. According to the acceleration signal collected by the test, spectrum analysis and ride and comfort index calculation. When it is close to the threshold and the trend continues to increase, i.e. ride index is greater than 1.6-1.8, comfort index is greater than 0.7-0.9, lateral main frequency 6-9Hz, vertical main frequency 6-9Hz and 12-15Hz, the vehicle and line should be checked in advance and targeted management, if close to the threshold but the trend of change is gentle, the means of governance can be temporarily not taken, but need to strengthen the monitoring, collection of various types of monitoring indicators exceed the threshold and there is a continuous trend of increase, it is recommended that the vehicles and lines are inspected.
{"title":"Research on vehicle vibration threshold based on big data mining","authors":"Puchao Li, Dongyu Li, Mian Wang","doi":"10.1117/12.2671809","DOIUrl":"https://doi.org/10.1117/12.2671809","url":null,"abstract":"In order to exclude differences in the perception of vibration by different testers and to help the relevant authorities to plan maintenance and determine the timing of line repairs, the vehicle jitter threshold was analysed to make it one of the predictors of sustained vehicle jitter and to exclude to a certain extent the interference of the testers' physical sensations. According to the acceleration signal collected by the test, spectrum analysis and ride and comfort index calculation. When it is close to the threshold and the trend continues to increase, i.e. ride index is greater than 1.6-1.8, comfort index is greater than 0.7-0.9, lateral main frequency 6-9Hz, vertical main frequency 6-9Hz and 12-15Hz, the vehicle and line should be checked in advance and targeted management, if close to the threshold but the trend of change is gentle, the means of governance can be temporarily not taken, but need to strengthen the monitoring, collection of various types of monitoring indicators exceed the threshold and there is a continuous trend of increase, it is recommended that the vehicles and lines are inspected.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"45 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122892281","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}
A multi-objective optimization method for electromagnetic actuator with permanent magnet is presented in this paper. The OLS-RBF neural network is improved by introducing gradient descent operator, and the coupling relationship between optimization objective and optimization factor of electromagnetic actuator with permanent magnet is fitted. NSGA-II algorithm is used to solve the multi-objective optimization of the approximate model obtained by fitting, and its effectiveness and feasibility are verified by simulation.
{"title":"Multi-objective optimization design of single-stage electromagnetic needle selector with permanent magnet","authors":"Tao Wang, Zhen Mao, Cheng Ju","doi":"10.1117/12.2672266","DOIUrl":"https://doi.org/10.1117/12.2672266","url":null,"abstract":"A multi-objective optimization method for electromagnetic actuator with permanent magnet is presented in this paper. The OLS-RBF neural network is improved by introducing gradient descent operator, and the coupling relationship between optimization objective and optimization factor of electromagnetic actuator with permanent magnet is fitted. NSGA-II algorithm is used to solve the multi-objective optimization of the approximate model obtained by fitting, and its effectiveness and feasibility are verified by simulation.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"4571 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128347177","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}
According to statistics from the World Health Organization, Colorectal Cancer (CRC) is the third most commonly diagnosed cancer in the world. The detection of CRC in an early stage is crucial for on-time and proper treatment, which may significantly increase the patient's survival rate. Although computers are not qualified to replace human experts at the moment, having a referential result from CRC auto-detection and saving the time of manual diagnosis is still very meaningful. This paper compares the performances of two different neural networks classifying CRC based on a set of histology images. The labeled dataset is publicly available on the Tensorflow website, and the two neural networks are tested on the same dataset separately. The first type of neural network in this study is Convolutional Neural Network (CNN), and the second type is a Deep Neural Network (DNN). As the dataset splits into training, testing, and validation sets, the loss, accuracy, and training time are recorded by the end of each epoch. The study result shows that the CNN method is better than the DNN method in terms of CRC image classification. It takes a long time but has better performance.
{"title":"Colorectal cancer classification based on histology images: comparison between DNN and CNN","authors":"Jue Han, Deshang Kong","doi":"10.1117/12.2672689","DOIUrl":"https://doi.org/10.1117/12.2672689","url":null,"abstract":"According to statistics from the World Health Organization, Colorectal Cancer (CRC) is the third most commonly diagnosed cancer in the world. The detection of CRC in an early stage is crucial for on-time and proper treatment, which may significantly increase the patient's survival rate. Although computers are not qualified to replace human experts at the moment, having a referential result from CRC auto-detection and saving the time of manual diagnosis is still very meaningful. This paper compares the performances of two different neural networks classifying CRC based on a set of histology images. The labeled dataset is publicly available on the Tensorflow website, and the two neural networks are tested on the same dataset separately. The first type of neural network in this study is Convolutional Neural Network (CNN), and the second type is a Deep Neural Network (DNN). As the dataset splits into training, testing, and validation sets, the loss, accuracy, and training time are recorded by the end of each epoch. The study result shows that the CNN method is better than the DNN method in terms of CRC image classification. It takes a long time but has better performance.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122967252","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}
Xiaohua Wu, Weiming Shao, Yunhong Zheng, Pingfan Li
The lighting control system in the market still has many problems, such as complex wiring, insufficient intelligence of the operating system, weak anti-interference ability and so on. This design uses wireless communication technology to solve the above problems. Firstly, a wireless communication network based on ZigBee module is constructed. Collect environmental information through various sensors and upload it to ZigBee terminal for intelligent logic judgment. The terminal can upload the received sensor data to the network to realize remote monitoring. In addition, the design of lowpower single live switch of RCC switching power supply is divided into open power supply and closed power supply. This design scheme can effectively take power and control the load. The controller adopts polysilicon solar charging scheme to effectively supply power to the main circuit.
{"title":"Intelligent lighting system with single live wire based on ZigBee","authors":"Xiaohua Wu, Weiming Shao, Yunhong Zheng, Pingfan Li","doi":"10.1117/12.2672997","DOIUrl":"https://doi.org/10.1117/12.2672997","url":null,"abstract":"The lighting control system in the market still has many problems, such as complex wiring, insufficient intelligence of the operating system, weak anti-interference ability and so on. This design uses wireless communication technology to solve the above problems. Firstly, a wireless communication network based on ZigBee module is constructed. Collect environmental information through various sensors and upload it to ZigBee terminal for intelligent logic judgment. The terminal can upload the received sensor data to the network to realize remote monitoring. In addition, the design of lowpower single live switch of RCC switching power supply is divided into open power supply and closed power supply. This design scheme can effectively take power and control the load. The controller adopts polysilicon solar charging scheme to effectively supply power to the main circuit.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127016425","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}
Qiugen Pei, Zewu Peng, Qiang Chen, Yuhong Shen, Huaquan Su
In view of the poor recognition effect of power equipment fault features in China, a method for building power equipment fault feature model based on unified semantic expression is proposed. The power equipment fault information is identified by combining the unified semantic expression principle. And the phase space reconstruction algorithm is constructed according to the feature semantics of the identified fault information. The power equipment fault feature model is optimized based on the reconstruction results. Finally, it is verified by experiments, the power equipment fault feature model based on unified semantic expression can quickly identify the semantic features of fault information in the process of practical application, and effectively improve the recognition effect.
{"title":"Construction of power equipment fault feature model based on unified semantic expression","authors":"Qiugen Pei, Zewu Peng, Qiang Chen, Yuhong Shen, Huaquan Su","doi":"10.1117/12.2671876","DOIUrl":"https://doi.org/10.1117/12.2671876","url":null,"abstract":"In view of the poor recognition effect of power equipment fault features in China, a method for building power equipment fault feature model based on unified semantic expression is proposed. The power equipment fault information is identified by combining the unified semantic expression principle. And the phase space reconstruction algorithm is constructed according to the feature semantics of the identified fault information. The power equipment fault feature model is optimized based on the reconstruction results. Finally, it is verified by experiments, the power equipment fault feature model based on unified semantic expression can quickly identify the semantic features of fault information in the process of practical application, and effectively improve the recognition effect.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127200846","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}
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