Yanan Zhang, Lu Zhang, Hongyong Fu, Dequan Yu, Ke Wang
Space application facilities have complex systems and high operation requirements, making induction maintenance applications difficult and time-consuming based on augmented reality technology. To solve this problem, this paper puts forward the agile manufacturing technology framework and key technologies of induced maintenance application combined with the product characteristics of space application facilities and verifies the application effect of this technology in the actual scene through practical cases. The realization of the agile production technology of induced maintenance effectively improves the efficiency of application production. It provides a new auxiliary solution for the astronauts to solve emergencies and sudden missions in orbit.
{"title":"Research on agile production technology for inducing maintenance of space application facilities","authors":"Yanan Zhang, Lu Zhang, Hongyong Fu, Dequan Yu, Ke Wang","doi":"10.1117/12.2673019","DOIUrl":"https://doi.org/10.1117/12.2673019","url":null,"abstract":"Space application facilities have complex systems and high operation requirements, making induction maintenance applications difficult and time-consuming based on augmented reality technology. To solve this problem, this paper puts forward the agile manufacturing technology framework and key technologies of induced maintenance application combined with the product characteristics of space application facilities and verifies the application effect of this technology in the actual scene through practical cases. The realization of the agile production technology of induced maintenance effectively improves the efficiency of application production. It provides a new auxiliary solution for the astronauts to solve emergencies and sudden missions in orbit.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"20 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":"131414926","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}
Hard target penetration weapon is a trump card weapon for attacking multi-layered structural targets such as underground fortifications and command posts. The key to achieve the efficient damage to targets is the precise layer counting of fuse penetration process. Considering the oscillation aliasing and identifying difficulty in the traditional overload layer counting, a method of penetration layer counting based on the geomagnetic characteristic signal is proposed. During the warhead penetration of the reinforced concrete multilayer structure such as multi-story buildings, due to the additional magnetic field generated by magnetized ferromagnets in the geomagnetic field, the magnetic induction intensity measured by the sensor will change with its position related to the floors, so the layer can be counted by detecting the layer penetrating signal. The multi-layer target plate and warhead models are established, and the principle of penetration process, signal characteristics and layer counting strategy under the multi-parameter condition are analyzed through the COMSOL, a finite element analysis software. The purpose of this paper is to break through the large error and identifying difficulty of characteristic signals in the traditional layer counting method with accelerometer, and to provide theoretical reference for the design and damage efficiency improvement of penetration weapons.
{"title":"Layer counting method of hard target penetration fuze based on geomagnetic signal detection","authors":"K. Jiang, Zichen Liu, Zhengyu He, Changsheng Li","doi":"10.1117/12.2671823","DOIUrl":"https://doi.org/10.1117/12.2671823","url":null,"abstract":"Hard target penetration weapon is a trump card weapon for attacking multi-layered structural targets such as underground fortifications and command posts. The key to achieve the efficient damage to targets is the precise layer counting of fuse penetration process. Considering the oscillation aliasing and identifying difficulty in the traditional overload layer counting, a method of penetration layer counting based on the geomagnetic characteristic signal is proposed. During the warhead penetration of the reinforced concrete multilayer structure such as multi-story buildings, due to the additional magnetic field generated by magnetized ferromagnets in the geomagnetic field, the magnetic induction intensity measured by the sensor will change with its position related to the floors, so the layer can be counted by detecting the layer penetrating signal. The multi-layer target plate and warhead models are established, and the principle of penetration process, signal characteristics and layer counting strategy under the multi-parameter condition are analyzed through the COMSOL, a finite element analysis software. The purpose of this paper is to break through the large error and identifying difficulty of characteristic signals in the traditional layer counting method with accelerometer, and to provide theoretical reference for the design and damage efficiency improvement of penetration weapons.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"104 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":"131650331","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}
This paper is an essay about based on machine learning methods for patients with cancer probability prediction research, based on the existing machine learning just write and some of the cancer related information, dedicated to the study that can according to patients' basic living conditions, living habits, body external factors such as the age to the patient's cancer probability prediction, The aim is to allow patients to enter their own data at home to predict the incidence of cancer, so as to reduce the number of patients who come to hospital with advanced cancer. The machine learning methods adopted in this paper are mainly logistic regression and multiple linear regression, and the confounding matrix is used to verify the results, and finally the cancer-related information is obtained.
{"title":"Lung cancer prediction and analysis by regression models","authors":"X. Yu","doi":"10.1117/12.2672648","DOIUrl":"https://doi.org/10.1117/12.2672648","url":null,"abstract":"This paper is an essay about based on machine learning methods for patients with cancer probability prediction research, based on the existing machine learning just write and some of the cancer related information, dedicated to the study that can according to patients' basic living conditions, living habits, body external factors such as the age to the patient's cancer probability prediction, The aim is to allow patients to enter their own data at home to predict the incidence of cancer, so as to reduce the number of patients who come to hospital with advanced cancer. The machine learning methods adopted in this paper are mainly logistic regression and multiple linear regression, and the confounding matrix is used to verify the results, and finally the cancer-related information is obtained.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"34 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":"114948182","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 brain tumor can negatively affect basic bodily functions and when malignant can result in low survival rates. Many studies were conducted to detect and classify brain tumors in MRI images using a convolutional neural network (CNN) and other techniques like image preprocessing and transfer learning. However, few studies have explored the effect of specific hyperparameters on the performance of such CNNs. This study aims to investigate how the input size affects the CNN’s accuracy in brain tumor detection. Brain MRI datasets were collected and split into training, validation, and test sets. Four models with identical architectures but different input sizes of 256px×256px×3, 224px×224px×3, 128px×128px×3, and 64px×64px×3 were built using TensorFlow Keras, trained on the training set with data augmentation, and evaluated using the test sets. Of these four models, the one with 64px as input size has the best performance, yielding the highest test accuracy, 99.16%, and lowest test loss, 0.0282, whereas the 224px model has the worst performance, with the lowest accuracy, 98.06%, and highest loss, 0.0976. Accordingly, it appears that larger input sizes do not necessarily result in higher accuracy of the CNN performing brain tumor detection. Future studies on this topic may consider using a smaller input size, not only maintaining high accuracy but also significantly reducing the required time to train and the space to save the model.
{"title":"The effect of input size on the accuracy of a convolutional neural network performing brain tumor detection","authors":"Zirui Zhao","doi":"10.1117/12.2672694","DOIUrl":"https://doi.org/10.1117/12.2672694","url":null,"abstract":"A brain tumor can negatively affect basic bodily functions and when malignant can result in low survival rates. Many studies were conducted to detect and classify brain tumors in MRI images using a convolutional neural network (CNN) and other techniques like image preprocessing and transfer learning. However, few studies have explored the effect of specific hyperparameters on the performance of such CNNs. This study aims to investigate how the input size affects the CNN’s accuracy in brain tumor detection. Brain MRI datasets were collected and split into training, validation, and test sets. Four models with identical architectures but different input sizes of 256px×256px×3, 224px×224px×3, 128px×128px×3, and 64px×64px×3 were built using TensorFlow Keras, trained on the training set with data augmentation, and evaluated using the test sets. Of these four models, the one with 64px as input size has the best performance, yielding the highest test accuracy, 99.16%, and lowest test loss, 0.0282, whereas the 224px model has the worst performance, with the lowest accuracy, 98.06%, and highest loss, 0.0976. Accordingly, it appears that larger input sizes do not necessarily result in higher accuracy of the CNN performing brain tumor detection. Future studies on this topic may consider using a smaller input size, not only maintaining high accuracy but also significantly reducing the required time to train and the space to save the model.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"82 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":"115753382","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}
With the great success of airworthiness in ensuring the safe operation of civil aviation products, military aircraft products have begun to gradually introduce the concept and method of airworthiness. Under the premise of focusing on the function and performance of military aircraft, the safety of products is pursued to the maximum extent. However, in the actual process, due to the huge difference between military products and civil products, in the process of promoting airworthiness, military aircraft products often have an unbalanced contradiction between airworthiness verification and performance verification. Based on this, this paper proposes a dual fusion scheme and process based on airworthiness and performance verification, designs the complex diversification mapping method of airworthiness verification and performance verification test subjects in detail, and describes the verification method of airworthiness clauses in performance verification process. The scheme and method have been applied in actual model tasks and achieved good results.
{"title":"Mapping relationship between airworthiness and performance testing of military aircraft","authors":"Guoxing Li, Yongling Guo, Guowang Zhang","doi":"10.1117/12.2671960","DOIUrl":"https://doi.org/10.1117/12.2671960","url":null,"abstract":"With the great success of airworthiness in ensuring the safe operation of civil aviation products, military aircraft products have begun to gradually introduce the concept and method of airworthiness. Under the premise of focusing on the function and performance of military aircraft, the safety of products is pursued to the maximum extent. However, in the actual process, due to the huge difference between military products and civil products, in the process of promoting airworthiness, military aircraft products often have an unbalanced contradiction between airworthiness verification and performance verification. Based on this, this paper proposes a dual fusion scheme and process based on airworthiness and performance verification, designs the complex diversification mapping method of airworthiness verification and performance verification test subjects in detail, and describes the verification method of airworthiness clauses in performance verification process. The scheme and method have been applied in actual model tasks and achieved good results.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"18 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":"115589327","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}
Qiwei Lai, Nei Wang, X. Mao, Z. Wu, Di Wu, Runlin Zhang, Jian Wu
The traditional valve control system is prone to pressure shock which is harmful to the efficiency and reliability of the hydraulic system. In view of this, simulation model of valve control system has been established based on AMESim to analyze the characteristics of pressure shock. Through designing a set of load-sensitive controlling system instead of valve control system, the self-adaptive control strategy has been implemented in the system. The results show that the self-adaptive control system can effectively improve the pressure shock for multiple users working in different condition.
{"title":"Research on suppression of pressure shock in shipping hydraulic system","authors":"Qiwei Lai, Nei Wang, X. Mao, Z. Wu, Di Wu, Runlin Zhang, Jian Wu","doi":"10.1117/12.2671953","DOIUrl":"https://doi.org/10.1117/12.2671953","url":null,"abstract":"The traditional valve control system is prone to pressure shock which is harmful to the efficiency and reliability of the hydraulic system. In view of this, simulation model of valve control system has been established based on AMESim to analyze the characteristics of pressure shock. Through designing a set of load-sensitive controlling system instead of valve control system, the self-adaptive control strategy has been implemented in the system. The results show that the self-adaptive control system can effectively improve the pressure shock for multiple users working in different condition.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"191 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":"122431392","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}
This paper analyzes a feasible spacecraft flight plan that uses gravitation assistance to transport the spacecraft from Earth to the circular orbit around Saturn (the spacecraft is in a circular orbit around the Earth, with an orbital period of 90 minutes and a total mass of 5000 kg, including fuel) by establishing a low thrust transfer orbit model and calculates the minimum amount of fuel required, which is 1878.73kg. There is also an attempt to evaluate different options for controlling the ion thrusters during the journey, and one of the schemes inspired by the Cassini Huygens spacecraft is proposed and considered optimal. Adopting this plan, the total journey time is calculated to be 14.2 years.
{"title":"Ion thrusters to Saturn","authors":"Siwei Li, Zibo Zhou","doi":"10.1117/12.2672709","DOIUrl":"https://doi.org/10.1117/12.2672709","url":null,"abstract":"This paper analyzes a feasible spacecraft flight plan that uses gravitation assistance to transport the spacecraft from Earth to the circular orbit around Saturn (the spacecraft is in a circular orbit around the Earth, with an orbital period of 90 minutes and a total mass of 5000 kg, including fuel) by establishing a low thrust transfer orbit model and calculates the minimum amount of fuel required, which is 1878.73kg. There is also an attempt to evaluate different options for controlling the ion thrusters during the journey, and one of the schemes inspired by the Cassini Huygens spacecraft is proposed and considered optimal. Adopting this plan, the total journey time is calculated to be 14.2 years.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"9 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":"128659132","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}
The dense small objects detection is a challenging task in the scenario of UAV aerial surveillance. This paper proposes an improved YOLOv5 detection method for the dense small objects in high resolution images. To augment the dataset, a 20% overlap crop is used for the UAV aerial photography training set. In order to detect the tiny objects in the aerial photos of UAV, a tiny detection head is added on the basis of YOLOv5. The SPP and CBAM modules are introduced in the head of the model, SPP for feature fusion at different scales and CBAM for adding attention to spatial and channel dimensions. Multiple experiments are conducted on the VisDrone 2019 dataset, the results show that the mAP of 12 classes detected by the model is 30.4%, and 3.1% higher than the original YOLOv5.
{"title":"An improved YOLOv5 method for small object detection in high resolution images","authors":"Dongni Ran, Xuhui Xiong, Lujunjie Gao","doi":"10.1117/12.2673151","DOIUrl":"https://doi.org/10.1117/12.2673151","url":null,"abstract":"The dense small objects detection is a challenging task in the scenario of UAV aerial surveillance. This paper proposes an improved YOLOv5 detection method for the dense small objects in high resolution images. To augment the dataset, a 20% overlap crop is used for the UAV aerial photography training set. In order to detect the tiny objects in the aerial photos of UAV, a tiny detection head is added on the basis of YOLOv5. The SPP and CBAM modules are introduced in the head of the model, SPP for feature fusion at different scales and CBAM for adding attention to spatial and channel dimensions. Multiple experiments are conducted on the VisDrone 2019 dataset, the results show that the mAP of 12 classes detected by the model is 30.4%, and 3.1% higher than the original YOLOv5.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"47 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":"122084517","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}
As one of the major diseases, cancer has always been a hidden danger to human health. There has been a considerably improvement in the therapy for patients all over the world, as research and technology advance, medical care becomes more effective. In this regard, the cure rate and survival probability have increased positively compared with the last century. However, the incidence rate of cancer has not been effectively controlled, and lung cancer and breast cancer are still more common. Predicting the probability that a cancer patient will survive at their initial appointment is extremely important according to this report. In this case, doctors can not only have a more detailed understanding of the situation of patients, but also make the allocation of medical resources more reasonable; Secondly, it can also promote the improvement of medical treatment in cancer. This article will first import the relevant data sets and analyze the variables contained. Then, the next step will use logistic regression analysis and linear regression analysis to predict the survival probability of patients. Furthermore, completed the judgement which variable has a greater impact by comparing the data that affect this probability. By comparing the accuracy of these regression analysis, the accuracy of logical regression (93.14%) is higher than that of linear regression (77.12%). In this case, logistic regression analysis will be more applicable. Finally, this paper compares the influence of related variables. According to the findings, a patient's probability of survival is determined by the amount of lymph nodes inside the system.
{"title":"Prediction of survival probability of cancer using machine learning models","authors":"Mingxin Li","doi":"10.1117/12.2672658","DOIUrl":"https://doi.org/10.1117/12.2672658","url":null,"abstract":"As one of the major diseases, cancer has always been a hidden danger to human health. There has been a considerably improvement in the therapy for patients all over the world, as research and technology advance, medical care becomes more effective. In this regard, the cure rate and survival probability have increased positively compared with the last century. However, the incidence rate of cancer has not been effectively controlled, and lung cancer and breast cancer are still more common. Predicting the probability that a cancer patient will survive at their initial appointment is extremely important according to this report. In this case, doctors can not only have a more detailed understanding of the situation of patients, but also make the allocation of medical resources more reasonable; Secondly, it can also promote the improvement of medical treatment in cancer. This article will first import the relevant data sets and analyze the variables contained. Then, the next step will use logistic regression analysis and linear regression analysis to predict the survival probability of patients. Furthermore, completed the judgement which variable has a greater impact by comparing the data that affect this probability. By comparing the accuracy of these regression analysis, the accuracy of logical regression (93.14%) is higher than that of linear regression (77.12%). In this case, logistic regression analysis will be more applicable. Finally, this paper compares the influence of related variables. According to the findings, a patient's probability of survival is determined by the amount of lymph nodes inside the system.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"14 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":"130722760","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. Berdiev, G. Bahadirov, D. Zhang, Azamat Axmedov
The geometric dimensions and manoeuvrability of a forklift in narrow aisles are important in industrial enterprises and warehouses. In this paper, the influence of the geometric dimensions of the AGV forklift and the transported load on the dimensions of the aisle width is studied. The difference between aisle widths and turning radii required for the movement of the forklifts is shown, which affects to the efficiency of industrial sectors and warehouses. At the same time, the turning radii of three and four-wheeled AGV forklifts were analyzed and represented mathematical expressions.
{"title":"Geometrical analysis of maneuverability of the AGV forklift for the narrow aisle","authors":"A. Berdiev, G. Bahadirov, D. Zhang, Azamat Axmedov","doi":"10.1117/12.2672181","DOIUrl":"https://doi.org/10.1117/12.2672181","url":null,"abstract":"The geometric dimensions and manoeuvrability of a forklift in narrow aisles are important in industrial enterprises and warehouses. In this paper, the influence of the geometric dimensions of the AGV forklift and the transported load on the dimensions of the aisle width is studied. The difference between aisle widths and turning radii required for the movement of the forklifts is shown, which affects to the efficiency of industrial sectors and warehouses. At the same time, the turning radii of three and four-wheeled AGV forklifts were analyzed and represented mathematical expressions.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"30 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":"129154515","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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