Pub Date : 2020-06-01DOI: 10.1109/IWECAI50956.2020.00044
Bin Shu, Zhiyuan Zhu, Zhicheng Han, Jing Guo
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.
{"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}
Pub Date : 2020-06-01DOI: 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}
Pub Date : 2020-06-01DOI: 10.1109/IWECAI50956.2020.00024
Jun-Wei Huang, B. Jin, H. Meng, Dongling Xiao
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
{"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}
Pub Date : 2020-06-01DOI: 10.1109/IWECAI50956.2020.00015
Lige Yang, Liping Zheng, Lijuan Zheng
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.
{"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}
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.
{"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}
Pub Date : 2020-06-01DOI: 10.1109/IWECAI50956.2020.00019
Lin Yao, Xu Yuanyuan, Xu Shaoyu, L. Yurong, Jiang Hongyu
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.
{"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}
Pub Date : 2020-06-01DOI: 10.1109/IWECAI50956.2020.00013
Junchang Zhou, Changjun He, Jie Fang
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.
{"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}
Pub Date : 2020-06-01DOI: 10.1109/IWECAI50956.2020.00030
Y. Xu
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.
{"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}
Research on multi-antenna system gain cooperative communication and multiple-input multiple-output (MIMO) systems in modern wireless communication networks, the noise introduced by each of the multiple wireless ad-hoc network relay nodes and the signal from the interference source received by the relay node and the sink node affect the signal to noise ratio of the system, an integrated relay-and-forward amplifying base station platform for air-ground integration and a more realistic method for solving air-ground relay beamforming vectors based on the convexity optimization method are proposed, and the sink node uses maximum ratio combining (MRC) diversity for signal reception. The simulation results show that the wireless ad-hoc network relay node under the air-ground combination is in the relay cooperative forwarding and amplifying beamforming vector design. When the correlated interference noise is introduced, the final sink node receives the corresponding covariance matrix. The optimal beamforming signal in the network transmission bit error rate (BER) decreases significantly as the signal-to-noise ratio (SNR) increases; The experiment results showed that very intuitive and significant to extend the communication distance of wireless ad-hoc network nodes.
{"title":"The Air-Ground Integrated MIMO Cooperative Relay Beamforming Wireless Ad-Hoc Network Technology Research That Based on Maximum Ratio Combining","authors":"Zhifang Wang, Junguo Dong, Jianguo Yu, Zhen Yu, Shangjing Lin, Kaile Li","doi":"10.1109/IWECAI50956.2020.00010","DOIUrl":"https://doi.org/10.1109/IWECAI50956.2020.00010","url":null,"abstract":"Research on multi-antenna system gain cooperative communication and multiple-input multiple-output (MIMO) systems in modern wireless communication networks, the noise introduced by each of the multiple wireless ad-hoc network relay nodes and the signal from the interference source received by the relay node and the sink node affect the signal to noise ratio of the system, an integrated relay-and-forward amplifying base station platform for air-ground integration and a more realistic method for solving air-ground relay beamforming vectors based on the convexity optimization method are proposed, and the sink node uses maximum ratio combining (MRC) diversity for signal reception. The simulation results show that the wireless ad-hoc network relay node under the air-ground combination is in the relay cooperative forwarding and amplifying beamforming vector design. When the correlated interference noise is introduced, the final sink node receives the corresponding covariance matrix. The optimal beamforming signal in the network transmission bit error rate (BER) decreases significantly as the signal-to-noise ratio (SNR) increases; The experiment results showed that very intuitive and significant to extend the communication distance of wireless ad-hoc network nodes.","PeriodicalId":364789,"journal":{"name":"2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI)","volume":"94 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":"114833508","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}
Pub Date : 2020-06-01DOI: 10.1109/IWECAI50956.2020.00035
Pei Lv, Min Fu, Y. Zhuo, Hang-sheng Zhao, Jianzhao Zhang
Dynamic spectrum access is an important step in the spectrum resource sharing process. However, in the case of unknown spectrum access environment and dynamic model, it is difficult to achieve global optimal resource allocation. Considering the signal-to-noise ratio (SINR) limits of the primary network (PN) and the secondary network (SN), this paper presents a dynamic spectrum access method based on the relationship between the transmission rate of a secondary user (SU) and the relative SINR, which enables the SU to obtain and update the environment information through the Q-function, adopt an optimal strategy to maximize the network performance and utilize user collaborative learning mechanism to overcome local optimum problems. The simulation results show that the number of iterations required for the proposed algorithm to achieve convergence is reduced by up to 65%, the average performance index of the system is improved by up to 35% and the proposed algorithm can also ensure the fairness among SUs compared with traditional access method.
{"title":"A Dynamic Spectrum Access Method Based on Q-Learning","authors":"Pei Lv, Min Fu, Y. Zhuo, Hang-sheng Zhao, Jianzhao Zhang","doi":"10.1109/IWECAI50956.2020.00035","DOIUrl":"https://doi.org/10.1109/IWECAI50956.2020.00035","url":null,"abstract":"Dynamic spectrum access is an important step in the spectrum resource sharing process. However, in the case of unknown spectrum access environment and dynamic model, it is difficult to achieve global optimal resource allocation. Considering the signal-to-noise ratio (SINR) limits of the primary network (PN) and the secondary network (SN), this paper presents a dynamic spectrum access method based on the relationship between the transmission rate of a secondary user (SU) and the relative SINR, which enables the SU to obtain and update the environment information through the Q-function, adopt an optimal strategy to maximize the network performance and utilize user collaborative learning mechanism to overcome local optimum problems. The simulation results show that the number of iterations required for the proposed algorithm to achieve convergence is reduced by up to 65%, the average performance index of the system is improved by up to 35% and the proposed algorithm can also ensure the fairness among SUs compared with traditional access method.","PeriodicalId":364789,"journal":{"name":"2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI)","volume":"48 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":"127287900","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}
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