2018 IEEE International Conference on Advanced Manufacturing (ICAM)最新文献_第9页

Abrasion resistance and color retention assessment of porous concrete modified by PVA emulsion/PP fiber 聚乙烯醇乳液/聚丙烯纤维改性多孔混凝土的耐磨性和保色性评价

2018 IEEE International Conference on Advanced Manufacturing (ICAM) Pub Date : 2018-11-01 DOI: 10.1109/AMCON.2018.8614912

Lei Yang, Yanlin Li, Lingchao Lu, Yongbo Huang, P. Zhao

引用次数: 1

Analysis and Design of Differential bevel gear 差动锥齿轮的分析与设计

2018 IEEE International Conference on Advanced Manufacturing (ICAM) Pub Date : 2018-11-01 DOI: 10.1109/AMCON.2018.8615103

Peixing Wang, Kuang-Lun Liu

引用次数: 2

Airflow Patterns in the Airway Passage of Nasal Obstruction Patients 鼻塞患者气道通道的气流模式

2018 IEEE International Conference on Advanced Manufacturing (ICAM) Pub Date : 2018-11-01 DOI: 10.1109/AMCON.2018.8615052

Yue-Lin Hsieh, Y. Hsieh, Zhao Han, Hui-fang Lin

引用次数: 0

Intelligent Management Design on Air Conditioning Nonlinear Group Load 空调非线性群负荷智能管理设计

2018 IEEE International Conference on Advanced Manufacturing (ICAM) Pub Date : 2018-11-01 DOI: 10.1109/AMCON.2018.8614851

Zhu Jian-hong, Meng Bang-bang, Gu Ju-ping, Hu Qiong, Chen Ze-yu

引用次数: 0

The Prototype of a Smart Underwater Surveillance System for Shrimp Farming 虾类养殖智能水下监控系统原型

2018 IEEE International Conference on Advanced Manufacturing (ICAM) Pub Date : 2018-11-01 DOI: 10.1109/AMCON.2018.8614976

Ing-Jer Huang, Chin-Chang Hung, Shiann-Rong Kuang, Yun-Nan Chang, Kuan-Yu Huang, Chang-Ru Tsai, Kai-Lin Feng

引用次数: 14

A Digital Evaluation System for Inclusions in Steel 钢中夹杂物的数字化评价系统

2018 IEEE International Conference on Advanced Manufacturing (ICAM) Pub Date : 2018-11-01 DOI: 10.1109/AMCON.2018.8615078

Chia-Sui Wang, Wesley Huang, M. Yeh, Jou-Wei Lin

引用次数: 0

Investigating Multiple Quality Objectives for Surface Roughness and Dimensional Accuracy of Carbon Steel Manufactured by Turn-Mill Multitasking Machining 车铣多任务加工碳钢表面粗糙度和尺寸精度的多重质量目标研究

2018 IEEE International Conference on Advanced Manufacturing (ICAM) Pub Date : 2018-11-01 DOI: 10.1109/AMCON.2018.8614911

Wei-Tai Huang, Ting-Yi Lee, J. Chou

{"title":"Investigating Multiple Quality Objectives for Surface Roughness and Dimensional Accuracy of Carbon Steel Manufactured by Turn-Mill Multitasking Machining","authors":"Wei-Tai Huang, Ting-Yi Lee, J. Chou","doi":"10.1109/AMCON.2018.8614911","DOIUrl":"https://doi.org/10.1109/AMCON.2018.8614911","url":null,"abstract":"This research in multiple quality objectives of the turning and milling multitasking machining is based on the Taguchi process and the fuzzy theory. These two methods can quickly find the best processing parameters to obtain the best surface roughness and dimensional accuracy and reduce the research cost and save research time. In this research, the Taguchi robust process $L9 (3^{4})$ orthogonal table was used to find the individual optimized process parameters. The control factors used were spindle speed (RPM), feed (mm/min), and C-axis brake pressure (kg/$cm^{2})$.), the axial cutting depth, and then taking the surface roughness and dimensional accuracy as the characteristic indicators, and then the respective signal-to-noise ratio (S/N) is grayed out according to the experimental sequence to generate normalization, and the gray correlation coefficient is obtained. Further, a Multiple Performance Characteristic Index (MPCI) is obtained. The research results clearly demonstrated that the overall results of the process optimum parameters obtained by using the measurement indicators of multiple quality characteristics prevail the results of the individual optimized process parameters.","PeriodicalId":438307,"journal":{"name":"2018 IEEE International Conference on Advanced Manufacturing (ICAM)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116288445","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: 4

A CNN-RNN Neural Network Join Long Short-Term Memory For Crowd Counting and Density Estimation 一种CNN-RNN神经网络结合长短期记忆的人群计数和密度估计

2018 IEEE International Conference on Advanced Manufacturing (ICAM) Pub Date : 2018-11-01 DOI: 10.1109/AMCON.2018.8614939

Jingnan Fu, Hongbo Yang, Ping Liu, Yuzhen Hu

{"title":"A CNN-RNN Neural Network Join Long Short-Term Memory For Crowd Counting and Density Estimation","authors":"Jingnan Fu, Hongbo Yang, Ping Liu, Yuzhen Hu","doi":"10.1109/AMCON.2018.8614939","DOIUrl":"https://doi.org/10.1109/AMCON.2018.8614939","url":null,"abstract":"Crowd counting and density estimation is a challenging task in the field of computer vision. Most of existing methods of this task are based on convolutional neural network (CNN), which have achieved good results in low-density scene. Usually, people who are far away from the camera appear to be denser and smaller, while those who are close to the camera are more sparse and larger, therefor, structure contains only CNN gives the poor performance in some high-density crowd scene because of the uneven distribution of the crowd through camera. To address this problem, this paper designs a CNN-RNN Crowd Counting Neural Network (CRCCNN), which introduces Long Short-Term Memory (LSTM) structure, we use CNN structure to extract the features of the whole image, and use the LSTM structure to extract the contextual information of crowd region. Since LSTM has a good memory of the input information of sequential samples, it can predict the crowd density very well even for the high density population. We perform our experiments on different datasets and compare with other existing methods, which achieve the outstanding results and demonstrate the effectiveness performance of CRCCNN.","PeriodicalId":438307,"journal":{"name":"2018 IEEE International Conference on Advanced Manufacturing (ICAM)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115002248","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

Diagnosis of heavy metal cross contamination in leaf of rice based on hyperspectral image: a greenhouse experiment 基于高光谱图像的水稻叶片重金属交叉污染诊断:温室试验

2018 IEEE International Conference on Advanced Manufacturing (ICAM) Pub Date : 2018-11-01 DOI: 10.1109/AMCON.2018.8614938

Shuangyin Zhang, Teng Fei, Yanhong Ran

引用次数: 4

Development of a fiber-laser-based frequency comb for precision dimensional metrology 用于精密尺寸测量的光纤激光频率梳的研制

2018 IEEE International Conference on Advanced Manufacturing (ICAM) Pub Date : 2018-11-01 DOI: 10.1109/AMCON.2018.8614857

Yuri Kanda, H. Matsukuma, Shaoqing Yang, Y. Shimizu, H. Inaba, W. Gao

引用次数: 0