International Conference on Signal Processing Systems最新文献_第4页

Multi-domain feature extraction method of motor imagery EEG signal based on DWT and CSP 基于DWT和CSP的运动意象脑电信号多域特征提取方法

International Conference on Signal Processing Systems Pub Date : 2022-05-01 DOI: 10.1117/12.2631559

Ning Li, Yongze Liu

引用次数: 0

Security transmission technology for satellite communication based on integer domain chaotic system 基于整数域混沌系统的卫星通信安全传输技术

International Conference on Signal Processing Systems Pub Date : 2022-05-01 DOI: 10.1117/12.2631557

Yijun Deng, Yuanxiang Chen, Jiahao Li, Chang Liu, Fan Lu, Bing Ma, Zhang Lu, Jingshuang Cheng, Jianguo Yu

引用次数: 0

Research on unmanned aerial vehicle application based on 5G communication technology 基于5G通信技术的无人机应用研究

International Conference on Signal Processing Systems Pub Date : 2022-05-01 DOI: 10.1117/12.2631465

Tao Jia, Chuncheng Wei, Jing Tang

引用次数: 1

Robust adaptive beamforming based on sampling covariance matrix reconstruction and steering vector estimation 基于采样协方差矩阵重构和转向矢量估计的鲁棒自适应波束形成

International Conference on Signal Processing Systems Pub Date : 2022-05-01 DOI: 10.1117/12.2631411

Jiang Shao, Peng Li, Jingwei Hu, Dengbo Sun, Renhong Xie, Yibin Rui

引用次数: 0

Design and application of intelligent IoT full scene simulation detection system for energy internet 能源互联网智能物联网全场景仿真检测系统设计与应用

International Conference on Signal Processing Systems Pub Date : 2022-05-01 DOI: 10.1117/12.2631439

Donglan Liu, Haotong Zhang, Yang Guo, Yingxian Chang, Yong Zhang, Xin Liu, L. Ma, Rui Wang

{"title":"Design and application of intelligent IoT full scene simulation detection system for energy internet","authors":"Donglan Liu, Haotong Zhang, Yang Guo, Yingxian Chang, Yong Zhang, Xin Liu, L. Ma, Rui Wang","doi":"10.1117/12.2631439","DOIUrl":"https://doi.org/10.1117/12.2631439","url":null,"abstract":"In the context of the strategic goal of building energy Internet, State Grid Corporation of China has established a crossdisciplinary joint construction and common Internet of Things management platform, which carries out standardized access and unified online control for equipment in transmission, power transformation, distribution and other fields. In order to improve the access debugging efficiency of the IoT management platform accessed by terminal devices, this paper designed a full-scene simulation detection system for the intelligent IoT system oriented to the energy Internet. By using the existing construction ideas of intelligent IoT system and following the complete architecture of \"cloud, tube, edge, terminal \", the construction method of the simulation and coordination platform of intelligent IoT system of \"information-physical coupling\" is realized. Advanced technologies such as micro-service and distribution are adopted to build a lightweight simulation test system. A small amount of server resources can be used to simulate and test whether the communication protocol of the side device supports the communication protocol requirements of the intelligent IoT management platform. The functions of reporting equipment data collection and issuing control commands are tested, so as to complete the simulation, verification and testing functions of the whole electric power industry chain intelligent IoT system covering both internal and external businesses, and provide technical support for the construction and promotion of the IoT management platform of State Grid Corporation of China. Combined with the whole scene simulation and detection system of the intelligent Internet of Things system, the operating state sensing monitoring scene of the power distribution area is built to verify the functions of data reporting of the fusion terminal and command issuing of the simulation and detection system.","PeriodicalId":415097,"journal":{"name":"International Conference on Signal Processing Systems","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130919872","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

Video methods for gait analysis in daily environment 日常环境中步态分析的视频方法

International Conference on Signal Processing Systems Pub Date : 2022-05-01 DOI: 10.1117/12.2631593

P. Zhang, Yang Zhang

{"title":"Video methods for gait analysis in daily environment","authors":"P. Zhang, Yang Zhang","doi":"10.1117/12.2631593","DOIUrl":"https://doi.org/10.1117/12.2631593","url":null,"abstract":"Gait is one of important features to assess elderly physical condition which is directly relative to health status. The changes or abnormalities in gait may reflect risks in health. Different kinds of gait analysis methods have been proposed, such as pressure sensors based method and wearable equipment based method. Recently, with the development of computer vision technologies, more automatic, effective and non-intrusive ways are demanded to measure gait at either nursing facility or at-home in daily environment. In this paper, we propose an automatic approach for non-cooperative persons for gait analysis using 3D camera. This approach applies a tracking based recognition method to identify the targets on captured videos. Then 3D skeleton based behavior analysis is performed to select skeleton series of walking from daily behaviors. Finally gait characteristics are defined and calculated on selected skeleton series of each identified person for gait ability evaluation. Evaluations have been performed on a real-world environment where people do not stop in front of the camera. The result shows that the accuracy of recognition and behavior analysis method reaches above 90% for multiple persons, which is better efficiency and comparable accuracy than the previous methods and our approach is suitable for gait analysis in daily environment.","PeriodicalId":415097,"journal":{"name":"International Conference on Signal Processing Systems","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117161005","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

Three-stage deep learning system for recognizing contaminated serial numbers in hard disk drive: a comparison study with two-stage deep learning model 硬盘驱动器污染序列号识别的三阶段深度学习系统:与两阶段深度学习模型的比较研究

International Conference on Signal Processing Systems Pub Date : 2022-05-01 DOI: 10.1117/12.2631377

C. Chousangsuntorn, T. Tongloy, S. Chuwongin, S. Boonsang

{"title":"Three-stage deep learning system for recognizing contaminated serial numbers in hard disk drive: a comparison study with two-stage deep learning model","authors":"C. Chousangsuntorn, T. Tongloy, S. Chuwongin, S. Boonsang","doi":"10.1117/12.2631377","DOIUrl":"https://doi.org/10.1117/12.2631377","url":null,"abstract":"The previous two-stage deep learning model for detecting and classifying misidentified serial numbers on the defect hard disk drive (HDD) slider was proposed by authors. We found that the threshold level adjusted during preprocessing process could limit the robustness of the two-stage model in large-scale manufacturing. Thus, we proposed a three-stage deep learning model comprised of 1) region of interest (ROI) detection and cropping, 2) character detection and cropping, and 3) character classification. Object detection algorithm and classification network used in this model are based on YOLO v.4 and EfficientNet-B0. The 1000 images captured by the digital camera were used for training (600 images) and validation (400 images) of the ROI detection model. The other 1000 captured images were used for testing the performance of the proposed three-stage model, then we compared them with those obtained from the previous two-stage model. The proposed three-stage model reaches F1 score = 0.997 and recovery rate up to 95.9%, while the two-stage model yields only 0.948 and 73%, respectively.","PeriodicalId":415097,"journal":{"name":"International Conference on Signal Processing Systems","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130623290","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

Bidirectional multi-lane vehicle counting approach based on trajectory features using MIMO radar 基于MIMO雷达轨迹特征的双向多车道车辆计数方法

International Conference on Signal Processing Systems Pub Date : 2022-05-01 DOI: 10.1117/12.2631434

Liquan Tan, Zhaocheng Yang

引用次数: 0

Microphysical characteristics of a precipitation affected by cold vortex based on disdrometer 冷涡影响下一次降水的微物理特征

International Conference on Signal Processing Systems Pub Date : 2022-05-01 DOI: 10.1117/12.2631587

Hong Wang, Jun Wang, Wenqing Wang, D. Zhang, Shuo Wang

引用次数: 0

Design and implementation of power Internet of Things device security detection system 电力物联网设备安全检测系统的设计与实现

International Conference on Signal Processing Systems Pub Date : 2022-05-01 DOI: 10.1117/12.2631451

Donglan Liu, Haotong Zhang, Yang Guo, Yingxian Chang, Yong Zhang, Fa-quan Zhang, Xin Liu, L. Ma

{"title":"Design and implementation of power Internet of Things device security detection system","authors":"Donglan Liu, Haotong Zhang, Yang Guo, Yingxian Chang, Yong Zhang, Fa-quan Zhang, Xin Liu, L. Ma","doi":"10.1117/12.2631451","DOIUrl":"https://doi.org/10.1117/12.2631451","url":null,"abstract":"Power Internet of Things (IoT) devices are increasingly being used in power systems. Due to the variety and complexity of devices, there is no mature solution for security detection. In order to solve this situation, this paper proposes a power Internet of Things device security detection system. Based on key technologies such as device fingerprint identification, network protocol identification and firmware security analysis, comprehensive security analysis is conducted on power Internet of Things devices from the perspectives of vulnerability, configuration security and firmware security. The automatic system design greatly improves the efficiency of users to carry out the detection work. Through the design and implementation of power Internet of Things equipment security detection system, users can quickly and efficiently carry out network access security detection of power Internet of Things equipment. Based on this, it is decided whether to allow the Internet of things devices or systems to access the power system network, avoiding security risks and hidden dangers caused by the Internet of things devices entering the network.","PeriodicalId":415097,"journal":{"name":"International Conference on Signal Processing Systems","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125881728","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