Proceedings of the 2020 2nd International Conference on Robotics, Intelligent Control and Artificial Intelligence最新文献

Research and development of fine management system for Oujiang Beikou bridge industrial workers 瓯江北口桥梁产业工人精细化管理系统的研究与开发

Proceedings of the 2020 2nd International Conference on Robotics, Intelligent Control and Artificial Intelligence Pub Date : 2020-10-17 DOI: 10.1145/3438872.3439223

Sanping Zhu, H. Ma, Y. Zou, Jianqiu Zhou, Y. Zheng

引用次数: 0

Automated Detection of Sleep Apnea Using Convolutional Neural Network from a single-channel ECG signal 利用卷积神经网络从单通道心电信号中自动检测睡眠呼吸暂停

Proceedings of the 2020 2nd International Conference on Robotics, Intelligent Control and Artificial Intelligence Pub Date : 2020-10-17 DOI: 10.1145/3438872.3439089

Qunxia Gao, Lijuan Shang, Yin Zhang

{"title":"Automated Detection of Sleep Apnea Using Convolutional Neural Network from a single-channel ECG signal","authors":"Qunxia Gao, Lijuan Shang, Yin Zhang","doi":"10.1145/3438872.3439089","DOIUrl":"https://doi.org/10.1145/3438872.3439089","url":null,"abstract":"Sleep apnea (SA) is the most common sleep disorder to lead some serious cardiovascular diseases and neurological if left it alone. In this paper, a convolutional neural network (CNN) model with four 1D convolutional layers, two fully connected layers and one classification layer is presented to detect automatically SA from a single-channel electrocardiogram (ECG) signal, each convolutional layer is followed by rectified linear units (ReLU) activation function, max pooling and dropout operations. 70 ECG recordings from the Apnea-ECG dataset are used for evaluating the model. RR interval, which is time interval from one R wave to the next R wave, and R-peaks amplitudes from a single-channel ECG signal are employed as the input of the CNN model. We performed our experiment on single-channel ECG signal dataset and have achieved the advanced performance with overall classification accuracy of 87.9% and 97.1% on the per-segment classification and per-recording classification respectively. This model can effectively be used to detect SA from a single-channel ECG signal.","PeriodicalId":199307,"journal":{"name":"Proceedings of the 2020 2nd International Conference on Robotics, Intelligent Control and Artificial Intelligence","volume":"73 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116236511","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: 1

An Extended Predictive Maintenance Model under Covariate Distribution Parameters with Uncertainty 具有不确定性协变量分布参数下的扩展预测维修模型

Proceedings of the 2020 2nd International Conference on Robotics, Intelligent Control and Artificial Intelligence Pub Date : 2020-10-17 DOI: 10.1145/3438872.3439075

Guoqiang Tong, Xinbo Qian

{"title":"An Extended Predictive Maintenance Model under Covariate Distribution Parameters with Uncertainty","authors":"Guoqiang Tong, Xinbo Qian","doi":"10.1145/3438872.3439075","DOIUrl":"https://doi.org/10.1145/3438872.3439075","url":null,"abstract":"Predictive maintenance is the latest maintenance strategy, and it has been widely used in many areas. For most applications, condition monitoring may not directly reflect the degree of degradation. Therefore, both condition monitoring and life data can be considered comprehensively to estimate the failure hazards as the degradation state. And proportional hazard model is one of the popular methods. The proportional hazard model considers condition monitoring data as internal covariates, and it is generally assumed that distribution parameters of the covariates are determined for the predictive maintenance model. However, the distribution parameters may be of uncertainty due to the influence of component operating conditions and sensor detection accuracy fluctuations in practical applications. Therefore, this paper proposes an extended predictive maintenance model under the covariate distribution parameters with uncertainty. For the model, the Bayesian updating method is utilized to update the time-fixed covariate distribution parameters. The Monte Carlo simulation method is used to estimate approximately the expected cost rate for the extended predictive maintenance model under various prognosis scenarios. For the simulation studies, the influence of uncertain distribution parameters for covariate is analyzed on the optimal predictive maintenance policy. The results show that the proposed model can reduce the expected maintenance cost.","PeriodicalId":199307,"journal":{"name":"Proceedings of the 2020 2nd International Conference on Robotics, Intelligent Control and Artificial Intelligence","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123027522","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: 1

Study on Compensating the Dead Zone Effect in High-Frequency Square Wave Injection Scheme 高频方波注入方案中补偿死区效应的研究

Proceedings of the 2020 2nd International Conference on Robotics, Intelligent Control and Artificial Intelligence Pub Date : 2020-10-17 DOI: 10.1145/3438872.3439115

Shengjie Zhang, Yu Feng

引用次数: 0

A Maximum Entropy Segmentation and Gabor Filtering Algorithm for Transformer Oil Conservator Oil Level Detectio 变压器油保护器油位检测的最大熵分割与Gabor滤波算法

Proceedings of the 2020 2nd International Conference on Robotics, Intelligent Control and Artificial Intelligence Pub Date : 2020-10-17 DOI: 10.1145/3438872.3439106

Yicen Liu, Yanling Mao, Tianbao Wu, Songhai Fan

引用次数: 0

Optimal Controller Placement in MEC-aided Software-defined UAV Networks Against Jamming Attack mec辅助软件定义无人机网络抗干扰最优控制器配置

Proceedings of the 2020 2nd International Conference on Robotics, Intelligent Control and Artificial Intelligence Pub Date : 2020-10-17 DOI: 10.1145/3438872.3439058

Zhiwei Li, Wenxin Qiao, Yu Lu, Hairui Lei

{"title":"Optimal Controller Placement in MEC-aided Software-defined UAV Networks Against Jamming Attack","authors":"Zhiwei Li, Wenxin Qiao, Yu Lu, Hairui Lei","doi":"10.1145/3438872.3439058","DOIUrl":"https://doi.org/10.1145/3438872.3439058","url":null,"abstract":"In this paper, we solve the problem of optimal placement of controllers in a software-defined UAV network assisted by mobile edge computing (MEC) under jamming attack. In order to solve the problem of the dynamic change of the quality of the wireless link caused by the maneuver of the jammer, we designed a bargaining game-based dynamic controller deployment algorithm. Specifically, we simplified the controller placement problem to a sequential decision-making problem. The controller can be deployed on the UAV or on a fixed base station on the ground. In our work, we first predict the position of the jammer at the next moment based on the current position and speed of the jammer. After that, we calculate the communication cost between nodes in the network accordingly. We first predict the position of the jammer at the next moment based on the current position and speed of the jammer. After that, we calculate the Signal to Interference plus Noise Ratio (SINR) between nodes in the network accordingly. Finally, we comprehensively consider time delay, communication cost and load balance, and use game theory to determine the number and location of controllers. The simulation results prove the effectiveness of the proposed method.","PeriodicalId":199307,"journal":{"name":"Proceedings of the 2020 2nd International Conference on Robotics, Intelligent Control and Artificial Intelligence","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121292467","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: 1

Transmission power adaptive congestion control algorithm based on Bayesian network 基于贝叶斯网络的传输功率自适应拥塞控制算法

Proceedings of the 2020 2nd International Conference on Robotics, Intelligent Control and Artificial Intelligence Pub Date : 2020-10-17 DOI: 10.1145/3438872.3439067

Yu Qiao, Xiaohui Hu, LeThanhMan Cao

引用次数: 0

Research and application of formability region diagram in sheet metal stamping 成形区域图在板料冲压成形中的研究与应用

Proceedings of the 2020 2nd International Conference on Robotics, Intelligent Control and Artificial Intelligence Pub Date : 2020-10-17 DOI: 10.1145/3438872.3439107

Gai Yan, Yanping Zheng

引用次数: 0

Research on Light Path Switching and Adjustment Mechanism of Ocular Surface and Fundus Photography for TCM Liver Disease Eye Diagnostic Instrument 中医肝病眼诊断仪眼表眼底摄影光路切换及调节机制研究

Proceedings of the 2020 2nd International Conference on Robotics, Intelligent Control and Artificial Intelligence Pub Date : 2020-10-17 DOI: 10.1145/3438872.3439099

Renhui Peng, Lubin Hang, Hua Zhang, Sulong Li, Pengcheng Zhang, Shisen Lin, Cheng Lu, Borui Wu

{"title":"Research on Light Path Switching and Adjustment Mechanism of Ocular Surface and Fundus Photography for TCM Liver Disease Eye Diagnostic Instrument","authors":"Renhui Peng, Lubin Hang, Hua Zhang, Sulong Li, Pengcheng Zhang, Shisen Lin, Cheng Lu, Borui Wu","doi":"10.1145/3438872.3439099","DOIUrl":"https://doi.org/10.1145/3438872.3439099","url":null,"abstract":"Design of intelligent eye diagnosis system for liver diseases according to traditional Chinese medicine theory, eye observation is an important diagnosis method, which can reflect liver disease syndromes through the image features of ocular surface and fundus. In view of the fact that, eye diagnosis of liver disease mostly relies on the experience of doctors and lack objective quantitative indicators in traditional medicine, a new wearable intelligent eye diagnosis system for liver diseases in traditional Chinese medicine is designed. Based on the near-infrared visible light dual light path, an internal focusing adjustment structure with fundus and ocular surface integrated photography system is constructed. The near-infrared light path completes the observation and focusing of the camera on the fundus and oscular surface to obtain photos. The internal focusing structure compensates the diopter of the human eye to obtain a clear fundus image. The system consists of automatic collection of eye pictures, intelligent generation of atlas and digital diagnosis equipment. The work in this paper lays foundation to established, and the intelligent diagnosis of eye disease syndrome is realized with the help of image processing technology.","PeriodicalId":199307,"journal":{"name":"Proceedings of the 2020 2nd International Conference on Robotics, Intelligent Control and Artificial Intelligence","volume":"258 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132491160","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

Design And Simulation Analysis Of A Single-ended Beam Thermopile Infrard Detector 单端束热电堆红外探测器的设计与仿真分析

Proceedings of the 2020 2nd International Conference on Robotics, Intelligent Control and Artificial Intelligence Pub Date : 2020-10-17 DOI: 10.1145/3438872.3439119

Zupeng Zhou, Yihua Wang, Lang Lu, Xufeng Liu, Huan Wei, Yanzhao Lv

引用次数: 0