2022 IEEE 2nd International Conference on Computer Communication and Artificial Intelligence (CCAI)最新文献_第3页

Experimental Simulation and Comparative Analysis of an Access Control List at Different Deployment Locations 不同部署位置访问控制列表的实验仿真与对比分析

2022 IEEE 2nd International Conference on Computer Communication and Artificial Intelligence (CCAI) Pub Date : 2022-05-06 DOI: 10.1109/CCAI55564.2022.9807771

Yuanqing Cao, Lisina Ai

{"title":"Experimental Simulation and Comparative Analysis of an Access Control List at Different Deployment Locations","authors":"Yuanqing Cao, Lisina Ai","doi":"10.1109/CCAI55564.2022.9807771","DOIUrl":"https://doi.org/10.1109/CCAI55564.2022.9807771","url":null,"abstract":"An access control list is an important network security technology, and it is also a key point of computer network courses. Since access control lists are abstract and difficult to understand, their deployment locations are complex, diverse and hard to optimize and they are not easy to explain in experimental teaching. First, the basic working principle and classification standard of an access control list is introduced. Then, experimental cases are designed in the Cisco Packet Tracer simulation platform, the experimental results of a standard IP access control list and an extended IP access control list in different deployment locations are compared and analyzed, and the experimental steps and configuration commands are given. Finally, this paper summarizes the optimization methods for the deployment locations of a standard IP access control list and an extended IP access control list. The experimental teaching process shows that the comparative experimental analysis of an access control list in a virtual environment not only deepens students’ understanding and mastery of the working principle of access control lists and their deployment rules in different locations but also improves students’ skills in solving engineering practice problems by using access control lists.","PeriodicalId":340195,"journal":{"name":"2022 IEEE 2nd International Conference on Computer Communication and Artificial Intelligence (CCAI)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122311197","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

Classification and Feature Extraction of Lightning Electric Field Waveforms Based on Machine Learning 基于机器学习的雷电电场波形分类与特征提取

2022 IEEE 2nd International Conference on Computer Communication and Artificial Intelligence (CCAI) Pub Date : 2022-05-06 DOI: 10.1109/CCAI55564.2022.9807742

Xiaoyi Zhang, Cai-xia Wang, Y. Tian

{"title":"Classification and Feature Extraction of Lightning Electric Field Waveforms Based on Machine Learning","authors":"Xiaoyi Zhang, Cai-xia Wang, Y. Tian","doi":"10.1109/CCAI55564.2022.9807742","DOIUrl":"https://doi.org/10.1109/CCAI55564.2022.9807742","url":null,"abstract":"Forecasting and warning of thunderstorms is very important to reduce the threat and damage of lightning to humans. The basis and prerequisite for forecasting and warning is the rapid identification and classification of data observed at multiple stations, extraction of waveform feature parameters and transmission them back to the central station. Currently, machine learning is a popular method and technique to achieve image recognition, classification and feature extraction. In this paper, based on the observed data of lightning electric field and machine learning, an image recognition model is constructed using convolutional neural network (CNN), and the recognition rate of the image is improved by stepwise optimization. The feature parameters of lightning are extracted based on OpenCV image processing techniques for subsequent real-time lightning localization, and can also be used to verify the classification results of lightning waveforms. The results show that the recognition rate of the final classification model can reach more than 90%, and the required waveform features can be extracted. This work has important application value and practical significance for the prediction and warning of lightning process observation.","PeriodicalId":340195,"journal":{"name":"2022 IEEE 2nd International Conference on Computer Communication and Artificial Intelligence (CCAI)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127129532","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 Intelligent Classification Method of Seismic Information Text Based on BERT-BiLSTM Optimization Algorithm 基于BERT-BiLSTM优化算法的地震信息文本智能分类方法研究

2022 IEEE 2nd International Conference on Computer Communication and Artificial Intelligence (CCAI) Pub Date : 2022-05-06 DOI: 10.1109/CCAI55564.2022.9807785

Wang Zhonghao, L. Chenxi, Huan Meng, Liu Shuai

{"title":"Research on Intelligent Classification Method of Seismic Information Text Based on BERT-BiLSTM Optimization Algorithm","authors":"Wang Zhonghao, L. Chenxi, Huan Meng, Liu Shuai","doi":"10.1109/CCAI55564.2022.9807785","DOIUrl":"https://doi.org/10.1109/CCAI55564.2022.9807785","url":null,"abstract":"With the development of science and technology, it is possible to quickly obtain massive disaster information after the earthquake, but because the earthquake information not only has the characteristics of strong timeliness, but also is always in the process of dynamic change, it can quickly classify and analyze the earthquake information, which is of great significance for earthquake emergency decision-making. In this paper, an earthquake news text intelligent classification model based on the BERT-BiLSTM optimization algorithm is proposed. First, based on the BERT (Bidirectional Encoder Representation from Transformers) pre-trained model, the algorithm performs a sentence-level feature vector representation of the seismic news text, and enters the feature vector into the BiLSTM layer to extract the global features of the seismic news text, and then enters the SoftMax classifier for classification. Finally, the control experiment of earthquake news text data in Qinghai and Yunnan was passed. Experimental results show that the model is improved by 2 percentage points compared with the traditional Bert model method. Therefore, the intelligent classification model of earthquake information text proposed in this paper can effectively and accurately determine the category of earthquake news and help earthquake emergency rescue decision-making.","PeriodicalId":340195,"journal":{"name":"2022 IEEE 2nd International Conference on Computer Communication and Artificial Intelligence (CCAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129207491","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 and Application of Smart Government Approval Based on Blockchain 基于区块链的智能政务审批研究与应用

2022 IEEE 2nd International Conference on Computer Communication and Artificial Intelligence (CCAI) Pub Date : 2022-05-06 DOI: 10.1109/CCAI55564.2022.9807726

Chunyan Guo, Jie Sun

引用次数: 1

A Named Entity Recognition Model Based on Entity Trigger Reinforcement Learning 基于实体触发强化学习的命名实体识别模型

2022 IEEE 2nd International Conference on Computer Communication and Artificial Intelligence (CCAI) Pub Date : 2022-05-06 DOI: 10.1109/CCAI55564.2022.9807747

Ping Wang, Nong Si, Haopeng Tong

引用次数: 0

Actuator Energy Guaranteed Mobile Charging Scheme for Wireless Sensor and Actuator Networks 基于无线传感器和执行器网络的执行器能量保证移动充电方案

2022 IEEE 2nd International Conference on Computer Communication and Artificial Intelligence (CCAI) Pub Date : 2022-05-06 DOI: 10.1109/CCAI55564.2022.9807788

Fulong Xu, Hede Lu

{"title":"Actuator Energy Guaranteed Mobile Charging Scheme for Wireless Sensor and Actuator Networks","authors":"Fulong Xu, Hede Lu","doi":"10.1109/CCAI55564.2022.9807788","DOIUrl":"https://doi.org/10.1109/CCAI55564.2022.9807788","url":null,"abstract":"Wireless Sensor and Actuator Networks (WSANs) include not only sensor nodes, but also actuator nodes. Since actuators’ capabilities such as moving, communication and event handling require much more energy than sensors, both actuators and sensors are affected by energy and make WSANs encounter serious energy constraints. Although many energy replenishment studies have been proposed for Wireless sensor networks (WSNs), they cannot work well in WSANs. To solve the energy replenishment problem of WSANs, we first analyze the characteristics in WSANs, and then present an actuator energy guaranteed mobile charging scheme (AEG) for WSANs. AEG evaluates the actuator failure risk in the network, and provides charging service for actuators exclusively when there exists an actuator failure risk. Moreover, under the condition that energy safety of actuators is guaranteed, AEG replenishes energy for sensors preferentially, which could avoid sensor failures as much as possible. We evaluate the performance of AEG by simulation, and the results indicate that AEG could reduce sensor failures and achieve lower average charging delay than existing schemes on the basis of ensuring no actuator failure.","PeriodicalId":340195,"journal":{"name":"2022 IEEE 2nd International Conference on Computer Communication and Artificial Intelligence (CCAI)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130577238","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

Telemetry Parameter Interpretation in Image Form Through Federated Learning 基于联邦学习的图像形式遥测参数解释

2022 IEEE 2nd International Conference on Computer Communication and Artificial Intelligence (CCAI) Pub Date : 2022-05-06 DOI: 10.1109/CCAI55564.2022.9807781

Yanan Lu, Tianxiang Ou, Jianwen Cao

引用次数: 0

Optimized L2 Norm Loss for Adversarial Robustness 对抗鲁棒性的优化L2范数损失

2022 IEEE 2nd International Conference on Computer Communication and Artificial Intelligence (CCAI) Pub Date : 2022-05-06 DOI: 10.1109/CCAI55564.2022.9807767

Xuanyu Zhang, Shi-You Xu, Jun Hu, Zhiyuan Xie

{"title":"Optimized L2 Norm Loss for Adversarial Robustness","authors":"Xuanyu Zhang, Shi-You Xu, Jun Hu, Zhiyuan Xie","doi":"10.1109/CCAI55564.2022.9807767","DOIUrl":"https://doi.org/10.1109/CCAI55564.2022.9807767","url":null,"abstract":"Although adversarial training is the most common method to make models obtain better adversarial robustness, its drawback of leading to reduced accuracy has been plaguing the academic community. In recent years, many articles have pointed out that good Lipschitz continuity helps models obtain better robustness and standard accuracy, and argued that models that are both robust and accurate exist. However, many methods still perform less well with models even with the addition of Lipschitz continuity constraints. Therefore, we discuss the drawbacks of existing Lipschitz continuity metric in deep learning in terms of Lipschitz continuity, and propose a counteracting Lipschitz continuity metric that is more suitable for deep learning. We demonstrate theoretically and experimentally that Mixup can significantly enhance the local Lipschitz continuity of the model. Using this property, we generate a large number of mix confrontation samples using Target attack to fill the entire neighborhood space. Our method gives the model a smoother localization and significantly improves the adversarial robustness of the model beyond most existing adversarial training methods.","PeriodicalId":340195,"journal":{"name":"2022 IEEE 2nd International Conference on Computer Communication and Artificial Intelligence (CCAI)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123461192","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

Online Knowledge Distillation for Efficient Action Recognition 面向高效动作识别的在线知识精馏

2022 IEEE 2nd International Conference on Computer Communication and Artificial Intelligence (CCAI) Pub Date : 2022-05-06 DOI: 10.1109/CCAI55564.2022.9807753

Jiazheng Wang, Cunling Bian, Xian Zhou, Fan Lyu, Zhibin Niu, Wei Feng

引用次数: 1

The Semantic Framework of Library Intelligent Question Answering System Based on Exploratory Search Behavior 基于探索性搜索行为的图书馆智能问答系统语义框架

2022 IEEE 2nd International Conference on Computer Communication and Artificial Intelligence (CCAI) Pub Date : 2022-05-06 DOI: 10.1109/CCAI55564.2022.9807737

Yang Qian

{"title":"The Semantic Framework of Library Intelligent Question Answering System Based on Exploratory Search Behavior","authors":"Yang Qian","doi":"10.1109/CCAI55564.2022.9807737","DOIUrl":"https://doi.org/10.1109/CCAI55564.2022.9807737","url":null,"abstract":"Analyze consultation question characteristics, identify users’ exploratory search behavior stage and library element demand, and integrate interview skills into intelligent question answering system, which improve the accuracy of library intelligent question answering. Analyze virtual consulting archives data of the National Library of China from 2011 to 2020, label characteristic vocabulary in users’ consultation questions, use SPSS software to test correlation between research elements, and design semantic framework of library intelligence question answering system based on hypothesis test results. Through data analysis, this research concludes that there is a relationship between library elements orientation in user consultation questions and cognitive stage, and target resources discovery plays a crucial role in users’ cognitive stage. Therefore, applying natural language processing technology to analyze user consultation questions, extracting characteristic vocabulary related to library elements, users’ cognitive stage and target resources, so as to generate personalized intelligent consultation answers. Accordingly, design a semantic framework for intelligent question answering system based on user exploratory search behavior, which will improve the answering accuracy of intelligent question answering system.","PeriodicalId":340195,"journal":{"name":"2022 IEEE 2nd International Conference on Computer Communication and Artificial Intelligence (CCAI)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126087445","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