2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)最新文献_第7页

Research on intelligent decision support system of ship’s hull plates curved forming by line heating 船舶船体板线加热弯曲成形智能决策支持系统研究

2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Pub Date : 2019-12-01 DOI: 10.1109/IAEAC47372.2019.8997638

Liang Qi, Wei Wang, Liang Dong, Liankai Chen, Chenwei Ge, Jing Huang, Ganmin Xue, Xuan Jia

引用次数: 0

Advanced Density Peak and K-means Clustering on Image Segmentation 基于密度峰值和k均值聚类的图像分割

2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Pub Date : 2019-12-01 DOI: 10.1109/IAEAC47372.2019.8997758

Yu Hui, Yanju Han

引用次数: 1

Design of Remote Meter Monitoring System Based on MCU Control 基于单片机控制的远程仪表监控系统设计

2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Pub Date : 2019-12-01 DOI: 10.1109/IAEAC47372.2019.8997889

Zhaoxing Meng, Ying Zhu, Haiqiang Lv, Xinjian Xu

引用次数: 0

Restore the Original data by Embedded data 通过嵌入数据恢复原始数据

2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Pub Date : 2019-12-01 DOI: 10.1109/IAEAC47372.2019.8997598

Jianyuan Cui, Gang Li, P. Zhou, Jia Qi Zhang

引用次数: 0

Research on Digital Forensics Framework for Malicious Behavior in Cloud 云环境下恶意行为的数字取证框架研究

2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Pub Date : 2019-12-01 DOI: 10.1109/IAEAC47372.2019.8997702

Guangxuan Chen, Di Wu, Guangxiao Chen, Panke Qin, Lei Zhang, Qiang Liu

{"title":"Research on Digital Forensics Framework for Malicious Behavior in Cloud","authors":"Guangxuan Chen, Di Wu, Guangxiao Chen, Panke Qin, Lei Zhang, Qiang Liu","doi":"10.1109/IAEAC47372.2019.8997702","DOIUrl":"https://doi.org/10.1109/IAEAC47372.2019.8997702","url":null,"abstract":"The difficult of detecting, response, tracing the malicious behavior in cloud has brought great challenges to the law enforcement in combating cybercrimes. This paper presents a malicious behavior oriented framework of detection, emergency response, traceability, and digital forensics in cloud environment. A cloud-based malicious behavior detection mechanism based on SDN is constructed, which implements full-traffic flow detection technology and malicious virtual machine detection based on memory analysis. The emergency response and traceability module can clarify the types of the malicious behavior and the impacts of the events, and locate the source of the event. The key nodes and paths of the infection topology or propagation path of the malicious behavior will be located security measure will be dispatched timely. The proposed IaaS service based forensics module realized the virtualization facility memory evidence extraction and analysis techniques, which can solve volatile data loss problems that often happened in traditional forensic methods.","PeriodicalId":164163,"journal":{"name":"2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124779361","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

Design Puncturing Polar Codes : The Odd-numbered Criterion 设计穿刺极性码:奇数准则

2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Pub Date : 2019-12-01 DOI: 10.1109/IAEAC47372.2019.8997843

Rujing Xiong, Honggui Deng, Hao-hao Zhao, Yuxin Feng

引用次数: 0

Pedestrian detection method based on self-learning 基于自学习的行人检测方法

2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Pub Date : 2019-12-01 DOI: 10.1109/IAEAC47372.2019.8997629

Tong Liu, Jianghua Cheng, Mingsheng Yang, Xiangyu Du, Xiaobing Luo, Liang Zhang

{"title":"Pedestrian detection method based on self-learning","authors":"Tong Liu, Jianghua Cheng, Mingsheng Yang, Xiangyu Du, Xiaobing Luo, Liang Zhang","doi":"10.1109/IAEAC47372.2019.8997629","DOIUrl":"https://doi.org/10.1109/IAEAC47372.2019.8997629","url":null,"abstract":"Vision-based pedestrian detection technology is widely used in security surveillance, such as transportation, prisons, and important places. Security monitoring requires pedestrian detection not only to be accurate and reliable, but also to meet the needs of real-time monitoring, and the false alarm rate is low. The existing pedestrian learning method based on deep learning has high reliability, but the timeliness cannot meet the monitoring requirements. Traditional pedestrian detection methods are time-sensitive, but false alarm rates tend to be higher. This paper proposes a self-learning pedestrian detection method, combined with motion detection, HOG feature extraction, and SVM classification for preliminary pedestrian detection. The false alarms caused during the pedestrian detection process are manually confirmed, and then the system automatically detects the false alarm image at a specific time. Self-learning, retraining the classifier, so as to continuously reduce the pedestrian detection false alarm rate and improve the pedestrian detection performance index through self-learning during the system operation, and the timeliness can meet the needs of video surveillance. Experiments show that the false alarm rate of this method is low, timeliness is high, and the recognition rate is also high.","PeriodicalId":164163,"journal":{"name":"2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128495889","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

Comprehensive Diagnosis and Analysis of Early Damp Defects On a Single Section of EHV 750kV Arrester 超高压750kV避雷器单段早期阻尼缺陷综合诊断与分析

2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Pub Date : 2019-12-01 DOI: 10.1109/IAEAC47372.2019.8997821

Yunxiao Bai, Libing Zhou, Huiting Yang, Wenhua Luo, Wentao Chen, Longxiang Yuan

{"title":"Comprehensive Diagnosis and Analysis of Early Damp Defects On a Single Section of EHV 750kV Arrester","authors":"Yunxiao Bai, Libing Zhou, Huiting Yang, Wenhua Luo, Wentao Chen, Longxiang Yuan","doi":"10.1109/IAEAC47372.2019.8997821","DOIUrl":"https://doi.org/10.1109/IAEAC47372.2019.8997821","url":null,"abstract":"With the extention of the arrester’s running time, there appears the situation that a single section of extrahigh voltage 750kV four series surge arrester may get damp and deteriorated.Once subjected to over-voltage intrusion, a serious situation may even lead to a single section of arrester’s explosion, which will bring a very negative impact to the system over-voltage protection.Through the on-line monitoring of the arrester, it is found that the leakage current of an ultrahigh voltage 750kV arrester became over-limited, we carried out full current and resistive current live detection for the whole arrester and blackout test for single section.We analyzed the data and disintegrated the single section. It is concluded that, for the extrahigh voltage 750kV four series surge arrester, especially for early hidden defects, in terms of live detection, it should be effective to combine the on-line monitoring of arrester, live detection, we should pay attention to data accumulation and development trend.In terms of blackout test, DC leakage test is still the most reliable way to diagnose the arrester defect. Therefore, we should strengthen the on-line monitoring and charge detection data accumulation,and also focus on the development trend and combine with the blackout plan to carry out the DC leakage test actively. In this way we can detect early latent fault of single-stage arrester in time, and provide over-voltage protection correctly.","PeriodicalId":164163,"journal":{"name":"2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129829338","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

An incremental Bayesian network structure learning algorithm based on local updating strategy 一种基于局部更新策略的增量贝叶斯网络结构学习算法

2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Pub Date : 2019-12-01 DOI: 10.1109/IAEAC47372.2019.8997724

Dan Liu, Jie Wu, Lin Liang, Xiaowan Li, Chunguang Luo, Guanghua Xu

引用次数: 0

Topology Optimization of Complex Network based on NSGA-II 基于NSGA-II的复杂网络拓扑优化

2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Pub Date : 2019-12-01 DOI: 10.1109/IAEAC47372.2019.8997597

Zhang Bin, Gan Zhi-chun, Chen-Hsing Wen, Hu Qiang-qiang, Hou Jian-feng

引用次数: 0