International Conference on Mechatronics Engineering and Artificial Intelligence最新文献_第6页

Research on agile production technology for inducing maintenance of space application facilities 空间应用设施诱导维修的敏捷生产技术研究

International Conference on Mechatronics Engineering and Artificial Intelligence Pub Date : 2023-02-28 DOI: 10.1117/12.2673019

Yanan Zhang, Lu Zhang, Hongyong Fu, Dequan Yu, Ke Wang

引用次数: 0

Layer counting method of hard target penetration fuze based on geomagnetic signal detection 基于地磁信号探测的硬目标突防引信层数方法

International Conference on Mechatronics Engineering and Artificial Intelligence Pub Date : 2023-02-28 DOI: 10.1117/12.2671823

K. Jiang, Zichen Liu, Zhengyu He, Changsheng Li

{"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}

引用次数: 0

Lung cancer prediction and analysis by regression models 肺癌预测与回归模型分析

International Conference on Mechatronics Engineering and Artificial Intelligence Pub Date : 2023-02-28 DOI: 10.1117/12.2672648

X. Yu

引用次数: 0

The effect of input size on the accuracy of a convolutional neural network performing brain tumor detection 输入大小对卷积神经网络执行脑肿瘤检测精度的影响

International Conference on Mechatronics Engineering and Artificial Intelligence Pub Date : 2023-02-28 DOI: 10.1117/12.2672694

Zirui Zhao

{"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}

引用次数: 0

Mapping relationship between airworthiness and performance testing of military aircraft 军用飞机适航与性能试验的映射关系

International Conference on Mechatronics Engineering and Artificial Intelligence Pub Date : 2023-02-28 DOI: 10.1117/12.2671960

Guoxing Li, Yongling Guo, Guowang Zhang

引用次数: 0

Research on suppression of pressure shock in shipping hydraulic system 船舶液压系统压力冲击的抑制研究

International Conference on Mechatronics Engineering and Artificial Intelligence Pub Date : 2023-02-28 DOI: 10.1117/12.2671953

Qiwei Lai, Nei Wang, X. Mao, Z. Wu, Di Wu, Runlin Zhang, Jian Wu

引用次数: 0

Ion thrusters to Saturn 离子推进器到土星

International Conference on Mechatronics Engineering and Artificial Intelligence Pub Date : 2023-02-28 DOI: 10.1117/12.2672709

Siwei Li, Zibo Zhou

引用次数: 0

An improved YOLOv5 method for small object detection in high resolution images 一种改进的YOLOv5高分辨率图像小目标检测方法

International Conference on Mechatronics Engineering and Artificial Intelligence Pub Date : 2023-02-28 DOI: 10.1117/12.2673151

Dongni Ran, Xuhui Xiong, Lujunjie Gao

引用次数: 0

Prediction of survival probability of cancer using machine learning models 使用机器学习模型预测癌症的生存概率

International Conference on Mechatronics Engineering and Artificial Intelligence Pub Date : 2023-02-28 DOI: 10.1117/12.2672658

Mingxin Li

{"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}

引用次数: 0

Geometrical analysis of maneuverability of the AGV forklift for the narrow aisle 窄通道AGV叉车机动性能的几何分析

International Conference on Mechatronics Engineering and Artificial Intelligence Pub Date : 2023-02-28 DOI: 10.1117/12.2672181

A. Berdiev, G. Bahadirov, D. Zhang, Azamat Axmedov

引用次数: 0