2018 10th International Conference on Modelling, Identification and Control (ICMIC)最新文献

A Passivity-Based Control Strategy for Three-Phase Current Source Inverter Based on Interconnection and Damping Assignment 基于互联和阻尼分配的三相电流源逆变器无源控制策略

2018 10th International Conference on Modelling, Identification and Control (ICMIC) Pub Date : 2018-07-02 DOI: 10.1109/ICMIC.2018.8530001

Pengwei Li, Jing Wang, Jing Bai

引用次数: 2

Neural Network Based Switching State Selection for Direct Power Control of Three Phase PWM-Rectifier 基于神经网络的三相pwm整流器直接功率控制开关状态选择

2018 10th International Conference on Modelling, Identification and Control (ICMIC) Pub Date : 2018-07-02 DOI: 10.1109/ICMIC.2018.8529997

A. Fekik, H. Denoun, Mohamed Lamine Hamida, A. Azar, M. Atig, Q. Zhu

引用次数: 13

A Recommendation System Based on Extreme Gradient Boosting Classifier 基于极端梯度增强分类器的推荐系统

2018 10th International Conference on Modelling, Identification and Control (ICMIC) Pub Date : 2018-07-02 DOI: 10.1109/ICMIC.2018.8529885

A. Xu, B. J. Liu, C. Gu

引用次数: 7

Automatic Segmentation and 3D Reconstruction of Spine Based on FCN and Marching Cubes in CT Volumes 基于CT体FCN和Marching Cubes的脊柱自动分割与三维重建

2018 10th International Conference on Modelling, Identification and Control (ICMIC) Pub Date : 2018-07-01 DOI: 10.1109/ICMIC.2018.8529993

Lingyu Fang, Jiwei Liu, Jianfei Liu, R. Mao

{"title":"Automatic Segmentation and 3D Reconstruction of Spine Based on FCN and Marching Cubes in CT Volumes","authors":"Lingyu Fang, Jiwei Liu, Jianfei Liu, R. Mao","doi":"10.1109/ICMIC.2018.8529993","DOIUrl":"https://doi.org/10.1109/ICMIC.2018.8529993","url":null,"abstract":"The spine is of great significance in the course of radiotherapy. The accurate location of the spine can provide reference for the determination of the tumor target area and the endanger organ in the radiotherapy plan. However, for some low-resolution areas of CT images, traditional methods cannot achieve a good segmentation effect. Due to the lack of data marked by doctors, there are few studies on the use of deep learning methods for segmentation of the spine. We use threshold segmentation and manual labeling methods to make our own data sets. This article combines the Fully Convolutional Neural Network (FCN) and the Marching Cubes (MC) algorithms to automatically segment and reconstruct the spine in the CT images. And we improved the network structure of FCN because FCN finally lost many details in one step down sampling. In the study, we used data from 40 patients, of which 30 were for training and 10 for testing. The final segmentation accuracy of the improved network is over 93%. The experimental results show that this method has a good segmentation effect and can better restore the shape of the spine and ribs. This preliminary result showed that our spine segmentation method had a great potential to reduce human efforts in labeling CT images in radiation therapy.","PeriodicalId":262938,"journal":{"name":"2018 10th International Conference on Modelling, Identification and Control (ICMIC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122519544","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: 5

Mathematical Prediction Model of Cutting Forces and Intuitive Representation Based on Experimental Study of High-Speed Milling of Ti6A14V 基于高速铣削Ti6A14V试验研究的切削力数学预测模型及直观表示

2018 10th International Conference on Modelling, Identification and Control (ICMIC) Pub Date : 2018-07-01 DOI: 10.1109/ICMIC.2018.8529972

Maohua Du, Jianfei Zhang

{"title":"Mathematical Prediction Model of Cutting Forces and Intuitive Representation Based on Experimental Study of High-Speed Milling of Ti6A14V","authors":"Maohua Du, Jianfei Zhang","doi":"10.1109/ICMIC.2018.8529972","DOIUrl":"https://doi.org/10.1109/ICMIC.2018.8529972","url":null,"abstract":"Cutting forces in high speed machining of titanium alloy Ti6A14V are generally measured by experiments and the experimental cost is very high. In this work we dealt with the experimental data of cutting forces using the Second Order Response Surface (SORS) method, and then established SORS prediction model of cutting forces within the normally used ranges of the cutting parameters, i.e. milling speed 130mlmin $leq v_{c}leq 160$ m/min, feed rate 0.04mm/tooth $leq f_{z}, leq 0.07$ mm/tooth, and axial depth of cut O.lmm $leq a_{p}leq 0.4$ mm. The analysis of variance (ANOVA) and F-test prove the effectiveness of the model only with the average percentage error of 5.02 % • The advantage of the SORS method lies in that the established SORS prediction model can be used to provide a basis for predicting and evaluating the milling forces without doing more machining experiments in the investigated parameters range in practice. Also, the method of modeling can intuition ally reflect the change trends of the forces through the three dimensional (3D) SORS graphs. Thus it is a new thinking and more applicable way of predicting cutting forces.","PeriodicalId":262938,"journal":{"name":"2018 10th International Conference on Modelling, Identification and Control (ICMIC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124471019","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

Cloud Service Selection Based on Chaos Quantum Immune Algorithm 基于混沌量子免疫算法的云服务选择

2018 10th International Conference on Modelling, Identification and Control (ICMIC) Pub Date : 2018-07-01 DOI: 10.1109/ICMIC.2018.8529860

Chao Zhou, Ping Pan, Ping Yang, Liang Huang

引用次数: 2

Research on the Application of Bat Algorithm in the Medium and Long Term Optimization of Reservoir Operation Bat算法在水库调度中长期优化中的应用研究

2018 10th International Conference on Modelling, Identification and Control (ICMIC) Pub Date : 2018-07-01 DOI: 10.1109/ICMIC.2018.8529894

W. Jingyi, Zhang Zhi, L. Wenwu, Daniel Eliote Mbanze

引用次数: 1

Research on Control and Planning of Soft-Wing UAV for Haze Removal 软翼无人机除霾控制与规划研究

2018 10th International Conference on Modelling, Identification and Control (ICMIC) Pub Date : 2018-07-01 DOI: 10.1109/ICMIC.2018.8529970

Wei Huang, Liying Yang, Yuqing He, Bingbing Li

引用次数: 1

Multivariable Feedback Control Design for Hypersonic Vehicles Based on Stochastic Robustness Analysis 基于随机鲁棒性分析的高超声速飞行器多变量反馈控制设计

2018 10th International Conference on Modelling, Identification and Control (ICMIC) Pub Date : 2018-07-01 DOI: 10.1109/ICMIC.2018.8529998

Xiaomeng Yin, Lei Liu, Yongji Wang

引用次数: 0

Computer-Aided Diagnosis of Pulmonary Nodules on CT Scan Images 肺结节CT扫描图像的计算机辅助诊断

2018 10th International Conference on Modelling, Identification and Control (ICMIC) Pub Date : 2018-07-01 DOI: 10.1109/ICMIC.2018.8529939

A. Jia, Second B. Jiwei Liu, Third C. Yu Gu

{"title":"Computer-Aided Diagnosis of Pulmonary Nodules on CT Scan Images","authors":"A. Jia, Second B. Jiwei Liu, Third C. Yu Gu","doi":"10.1109/ICMIC.2018.8529939","DOIUrl":"https://doi.org/10.1109/ICMIC.2018.8529939","url":null,"abstract":"Lung cancer has become the leading cause of cancer death with the increasing morbidity and mortality all over the world. Early detection, early diagnosis, and early treatment are of great significance to increase the survival rate of lung cancer patients. Computer-aided Diagnosis (CAD) based on computed tomography (CT) is an important technique for early diagnosis of lung lesions. This paper proposes a four-step approach for segmentation and classification of pulmonary nodules on CT scan images. A lung parenchyma segmentation method is performed which overcomes the shortcoming of pleural nodule omission of simple thresholding segmentation method. Then, a modified U-net fully convolutional network is constructed to segment suspected pulmonary nodules. Followed that, gray-level, shape, interior morphological, external morphological, texture and spatial features of pulmonary nodules are extracted. Last, an ensemble model of Random Forest (RF) and eXtreme Gradient Boosting (XGBoost) classifiers are employed to classify the suspected pulmonary nodules and the Area Under Receiver Operating Characteristic (ROC) Curve (AUC) is 0.93. Results confirm the feasibility and efficiency of the proposed approach. Taking both segmentation and classification of pulmonary nodules into account, we have thus created a doctor-assisted CAD approach for diagnosis of pulmonary nodules.","PeriodicalId":262938,"journal":{"name":"2018 10th International Conference on Modelling, Identification and Control (ICMIC)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127293117","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: 9