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2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI)最新文献

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Design of Automatic Navigation Trash Bucke 自动导航垃圾桶的设计
2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI) Pub Date : 2020-06-01 DOI: 10.1109/IWECAI50956.2020.00044
Bin Shu, Zhiyuan Zhu, Zhicheng Han, Jing Guo
{"title":"Design of Automatic Navigation Trash Bucke","authors":"Bin Shu, Zhiyuan Zhu, Zhicheng Han, Jing Guo","doi":"10.1109/IWECAI50956.2020.00044","DOIUrl":"https://doi.org/10.1109/IWECAI50956.2020.00044","url":null,"abstract":"Automatic navigation trash can adopts image processing technology, infrared scanning technology, omni-directional information acquisition, so that the trash can avoid obstacles in time during operation, trash can wheels use track, this kind of effective climbing low staircase can be realized, navigation positioning function is SLAM technology, voice speech is realized by ISD8004 series chip, speed control function is realized by friction nano-power generation. This paper describes a kind of automatic navigation trash can by the above technology.","PeriodicalId":364789,"journal":{"name":"2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128529095","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
[Copyright notice] (版权)
2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI) Pub Date : 2020-06-01 DOI: 10.1109/iwecai50956.2020.00003
{"title":"[Copyright notice]","authors":"","doi":"10.1109/iwecai50956.2020.00003","DOIUrl":"https://doi.org/10.1109/iwecai50956.2020.00003","url":null,"abstract":"","PeriodicalId":364789,"journal":{"name":"2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134323095","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
Research on Fast Location Method of Network Fault Based on Big Data 基于大数据的网络故障快速定位方法研究
2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI) Pub Date : 2020-06-01 DOI: 10.1109/IWECAI50956.2020.00024
Jun-Wei Huang, B. Jin, H. Meng, Dongling Xiao
{"title":"Research on Fast Location Method of Network Fault Based on Big Data","authors":"Jun-Wei Huang, B. Jin, H. Meng, Dongling Xiao","doi":"10.1109/IWECAI50956.2020.00024","DOIUrl":"https://doi.org/10.1109/IWECAI50956.2020.00024","url":null,"abstract":"The stable and reliable operation of the power grid information system is the fundamental to ensure the safe production and optimal management of the power grid. In this paper, by obtaining the performance parameters of the system between load and response time, resource consumption, and introducing time, external time and other parameters for big data analysis, the performance trend analysis of throughput, error and response time is given, and the current situation and history of the system are analyzed Historical data comparison and performance bottleneck analysis can improve the level of information mining, quickly and accurately realize the location of network fault components and fault type and cause identification","PeriodicalId":364789,"journal":{"name":"2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132710771","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
Research on Extraction of Human Information Entity Relationship Based on Improved Capsule Network 基于改进胶囊网络的人体信息实体关系提取研究
2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI) Pub Date : 2020-06-01 DOI: 10.1109/IWECAI50956.2020.00015
Lige Yang, Liping Zheng, Lijuan Zheng
{"title":"Research on Extraction of Human Information Entity Relationship Based on Improved Capsule Network","authors":"Lige Yang, Liping Zheng, Lijuan Zheng","doi":"10.1109/IWECAI50956.2020.00015","DOIUrl":"https://doi.org/10.1109/IWECAI50956.2020.00015","url":null,"abstract":"Entity relation extraction is to learn the implicit semantic relations among entities from multiple entities of a single sentence. Extracting entity relationships from unstructured text information is a key step in building large-scale knowledge map, optimizing personalized search, machine translation and intelligent Q & A. At present, the more popular depth model of entity relationship extraction has a better effect on the relationship extraction of single entity pair, but the evaluation index data of the model is not high when it is extended to the situation of single sentence multi entity pair and document level complex semantics. In this paper, an improved capsule network model based on dynamic routing rules is introduced, and it is applied to the relationship extraction of multi entity pairs of unstructured human information in the field of literature. The capsule network uses the route iteration method to connect the capsules between different hidden layers, which makes the capsule network establish the position relationship between different features in the routing process. Therefore, the capsule network is more robust to the position and angle changes of the target than other neural networks, so as to avoid the loss of information. In the experiment, we use the improved capsule network model, transformer and CNN model to extract the entity relationship of human information. The experimental results show that the improved capsule network model can achieve high accuracy, recall rate and F1 value in the multi entity pair relation extraction of small language database in the field of literature.","PeriodicalId":364789,"journal":{"name":"2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124818820","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 of Training Platform for IOT Based on Cloud Services 基于云服务的物联网培训平台设计
2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI) Pub Date : 2020-06-01 DOI: 10.1109/IWECAI50956.2020.00029
Xiaoxu Zeng, Hongbo Li, Zhiyuan Zhu, Ming Tang, Chuyan Zhang, Jing Guo
{"title":"Design of Training Platform for IOT Based on Cloud Services","authors":"Xiaoxu Zeng, Hongbo Li, Zhiyuan Zhu, Ming Tang, Chuyan Zhang, Jing Guo","doi":"10.1109/IWECAI50956.2020.00029","DOIUrl":"https://doi.org/10.1109/IWECAI50956.2020.00029","url":null,"abstract":"With continuous innovation of technology and rapid development and wide application of new technologies, such as Internet of Things (IOT), cloud computing, big data, artificial intelligence, the demand for innovative talents familiar with new technologies has increased sharply. This has brought challenges and opportunities to university personnel training. In particular, technical talents based on IOT, intelligent control, embedded systems, and big data are in shortage. In recent years, many colleges and universities have set up new majors such as IOT, big data, and artificial intelligence. However, there are still many problems such as single teaching mode and weak practice links during the personnel training. Therefore, a practical training platform for IOT based on cloud services is established. The platform realizes the combination of class learning and web-based learning. It also implements the real-time monitoring and comments in the web-link-web experiment process. It is of great theoretical value and practical value to enhance the experimental effects of the IOT and implement personalized learning recommendations. The main functions include experimental teaching management, real-time monitoring in the experimental process, evaluation of experimental learning status, and other functions. Training platform for IOT based on cloud services develop on the basis of end-to-end communication module based on the cloud services, develop a networked web-link-web training platform. Through the construction of this platform, we can achieve the goal of training high-quality, mastering new high-tech talents, and making education modernization, intellectualization, and informatization.","PeriodicalId":364789,"journal":{"name":"2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125528423","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
Path Planning Obstacle Avoidance Algorithm Based on Wheeled Robot 基于轮式机器人的路径规划避障算法
2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI) Pub Date : 2020-06-01 DOI: 10.1109/IWECAI50956.2020.00019
Lin Yao, Xu Yuanyuan, Xu Shaoyu, L. Yurong, Jiang Hongyu
{"title":"Path Planning Obstacle Avoidance Algorithm Based on Wheeled Robot","authors":"Lin Yao, Xu Yuanyuan, Xu Shaoyu, L. Yurong, Jiang Hongyu","doi":"10.1109/IWECAI50956.2020.00019","DOIUrl":"https://doi.org/10.1109/IWECAI50956.2020.00019","url":null,"abstract":"There are many obstacles and movements in the indoor environment. Indoor robots need to cope with the changing environment. This paper studies the obstacle avoidance problem of wheeled robots moving in an unknown environment. Firstly, the dynamic path planning algorithm for robot autonomous obstacle avoidance is studied, and the algorithm is implemented in C# language. Then use the Unity3D game engine to simulate the algorithm. The innovations of this algorithm are as follows: 1. Vectorize the path of the robot; 2. Summarize the motion state of the obstacle and the robot into six cases. During the movement process, the obstacle movement state is continuously judged, and the speed and direction of the obstacle are analyzed. The judgment result must belong to six situations. The experiment proves that the algorithm can solve the obstacle avoidance problem when encountering obstacles of different speeds and sizes, and has stronger applicability.","PeriodicalId":364789,"journal":{"name":"2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125157235","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: 2
Positioning System Based on Lidar Fusion 基于激光雷达融合的定位系统
2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI) Pub Date : 2020-06-01 DOI: 10.1109/IWECAI50956.2020.00013
Junchang Zhou, Changjun He, Jie Fang
{"title":"Positioning System Based on Lidar Fusion","authors":"Junchang Zhou, Changjun He, Jie Fang","doi":"10.1109/IWECAI50956.2020.00013","DOIUrl":"https://doi.org/10.1109/IWECAI50956.2020.00013","url":null,"abstract":"Aiming at the problems of slow positioning speed and information loss in the process of autonomous navigation of robots, we propose the adaptive Monte Carlo Localization (AMCL) algorithm based on lidar data fusion under the Robot Operating System (ROS) development system, realizing the robot for faster positioning and navigation.","PeriodicalId":364789,"journal":{"name":"2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123855151","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
Unsupervised Deep Learning for Text Steganalysis 文本隐写分析的无监督深度学习
2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI) Pub Date : 2020-06-01 DOI: 10.1109/IWECAI50956.2020.00030
Y. Xu
{"title":"Unsupervised Deep Learning for Text Steganalysis","authors":"Y. Xu","doi":"10.1109/IWECAI50956.2020.00030","DOIUrl":"https://doi.org/10.1109/IWECAI50956.2020.00030","url":null,"abstract":"Text steganography aims to embed hidden messages in text information while the goal of text steganalysis is to identify the existence of hidden information or further uncover the embedded message from the text. Steganalysis has received significant attention recently for the security and privacy purpose. In this paper, we develop unsupervised learning approaches for text steganalysis. In particular, two detection models based on deep learning have been proposed to detect hidden information that may be embedded in text from a global and a local perspective. Extensive studies have been carried out on the Chinese poetry text steganography datasets. It is seen that the proposed models show strong empirical performance in steganographic text detection.","PeriodicalId":364789,"journal":{"name":"2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134476379","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: 2
Air Target Combat Intention Identification Based on IE-DSBN 基于IE-DSBN的空中目标作战意图识别
2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI) Pub Date : 2020-06-01 DOI: 10.1109/IWECAI50956.2020.00014
Yu-Heng Xu, Siyi Cheng, Hubiao Zhang, Zhenkun Chen
{"title":"Air Target Combat Intention Identification Based on IE-DSBN","authors":"Yu-Heng Xu, Siyi Cheng, Hubiao Zhang, Zhenkun Chen","doi":"10.1109/IWECAI50956.2020.00014","DOIUrl":"https://doi.org/10.1109/IWECAI50956.2020.00014","url":null,"abstract":"Air target combat intention identification is a key step in modern air combat. Effective identification can improve the effectiveness of target threat assessment and assist commanders to make decisions. In order to optimize the operational intention recognition algorithm based on the dynamic sequence bayesian network, the information entropy theory is introduced in this paper to objectively allocate the attribute weight by analyzing the amount of useful information provided by different participating attributes. In the hypothetical air combat scenario, this model can effectively realize the combat intention identification.","PeriodicalId":364789,"journal":{"name":"2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129149768","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
An Intelligent Alarm Method for Optical Fiber Network Based on Backtracking Single Alarm Information 基于单告警信息回溯的光纤网络智能报警方法
2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI) Pub Date : 2020-06-01 DOI: 10.1109/IWECAI50956.2020.00018
Haisu Zhang, Yibo Liu, Long Wang
{"title":"An Intelligent Alarm Method for Optical Fiber Network Based on Backtracking Single Alarm Information","authors":"Haisu Zhang, Yibo Liu, Long Wang","doi":"10.1109/IWECAI50956.2020.00018","DOIUrl":"https://doi.org/10.1109/IWECAI50956.2020.00018","url":null,"abstract":"Optical fiber transmission network has gradually become the mainstream communication transmission medium and the development of artificial intel-ligence provides new ideas for the prediction of fiber transmission network failures. Different from traditional method which using the alarm infor-mation only for troubleshooting after a fault has occurred, this paper applies the real-time and serialized characteristics of alarm information to predict fault, achieving that a single alarm message can be used to indicate the pres-ence or absence of a fault. The specific steps of this paper are as follows, first extracting the alarm feature by collecting the alarm information and malfunction information from optical fiber network, then building a smart alarm learner by using the machine learning algorithm, finally achieving the goal to predict the probability of a failure occurring in the future. This meth-od can be integrated into the optical fiber transmission network operation, and lay the foundation for further research on Intelligent alarm.","PeriodicalId":364789,"journal":{"name":"2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125589909","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
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