Pub Date : 2021-06-01DOI: 10.1109/ICCEA53728.2021.00028
Zhang Xue, Li Yi, Zuo Jie, Liu Shiqian
A pedestrian fusion tracking method with complementary multimodal information is proposed, and a fusion decision tracking model with detection followed by fusion and then tracking is established. The detection module uses a modified CenterNet network with a richer feature information backbone network and a lightweight prediction module, and the scene data is collected to train multiple detectors for multiple modalities. A decision process based on the confidence of detection results and feature similarity is proposed to achieve the fusion of multimodal detection results, and the fused results are fed to the tracker to achieve continuous pedestrian tracking. The results show that the proposed fusion tracking model can complement each other’s multi-modal information and provide better and more robust tracking results than the single-modal tracker for continuous tracking in multiple scenes.
{"title":"Pedestrian fusion tracking method based on multimodal information com-plementation","authors":"Zhang Xue, Li Yi, Zuo Jie, Liu Shiqian","doi":"10.1109/ICCEA53728.2021.00028","DOIUrl":"https://doi.org/10.1109/ICCEA53728.2021.00028","url":null,"abstract":"A pedestrian fusion tracking method with complementary multimodal information is proposed, and a fusion decision tracking model with detection followed by fusion and then tracking is established. The detection module uses a modified CenterNet network with a richer feature information backbone network and a lightweight prediction module, and the scene data is collected to train multiple detectors for multiple modalities. A decision process based on the confidence of detection results and feature similarity is proposed to achieve the fusion of multimodal detection results, and the fused results are fed to the tracker to achieve continuous pedestrian tracking. The results show that the proposed fusion tracking model can complement each other’s multi-modal information and provide better and more robust tracking results than the single-modal tracker for continuous tracking in multiple scenes.","PeriodicalId":325790,"journal":{"name":"2021 International Conference on Computer Engineering and Application (ICCEA)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115988241","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 : 2021-06-01DOI: 10.1109/ICCEA53728.2021.00025
L. Zhiqiang, Peng Jianshan, Bi Yechuan, Liang Xiaowei
With the advent of the network era, network security has attracted more and more attention. As the key node in the network, network key devices play an important role in protecting the internal network and ensuring the network security. For the vulnerability of network key devices, security analysis has become an important concern of security personnel. Fuzzing is an automatic and effective vulnerability mining technology. In this paper, we propose the first coverage feedback fuzzy testing framework based on KVM PT technology for network key devices, aiming to solve the feasibility of applying fuzzy tools in network critical devices. At the same time, a fuzzy test agent technology based on firmware modification is proposed to help speed up the call of testcases. We evaluated the framework on Cisco ASA firewall, and trigger CVE-2018-0101, which proves the effectiveness of the framework.
{"title":"KVM PT Based Coverage Feedback Fuzzing for Network Key Devices","authors":"L. Zhiqiang, Peng Jianshan, Bi Yechuan, Liang Xiaowei","doi":"10.1109/ICCEA53728.2021.00025","DOIUrl":"https://doi.org/10.1109/ICCEA53728.2021.00025","url":null,"abstract":"With the advent of the network era, network security has attracted more and more attention. As the key node in the network, network key devices play an important role in protecting the internal network and ensuring the network security. For the vulnerability of network key devices, security analysis has become an important concern of security personnel. Fuzzing is an automatic and effective vulnerability mining technology. In this paper, we propose the first coverage feedback fuzzy testing framework based on KVM PT technology for network key devices, aiming to solve the feasibility of applying fuzzy tools in network critical devices. At the same time, a fuzzy test agent technology based on firmware modification is proposed to help speed up the call of testcases. We evaluated the framework on Cisco ASA firewall, and trigger CVE-2018-0101, which proves the effectiveness of the framework.","PeriodicalId":325790,"journal":{"name":"2021 International Conference on Computer Engineering and Application (ICCEA)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114814791","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 : 2021-06-01DOI: 10.1109/ICCEA53728.2021.00014
Yue Heng
Text generation is now a very mature task. Many methods have been applied to text generation and achieved good results. This paper uses the pre-trained model Unilm with adversarial training to generate news headlines from the Thucnews dataset. We fine tune the methods and parameters in the model and produced some results for reference or comparison
{"title":"A News Title Generation Method Based on UNILM Framework via Adversarial Training","authors":"Yue Heng","doi":"10.1109/ICCEA53728.2021.00014","DOIUrl":"https://doi.org/10.1109/ICCEA53728.2021.00014","url":null,"abstract":"Text generation is now a very mature task. Many methods have been applied to text generation and achieved good results. This paper uses the pre-trained model Unilm with adversarial training to generate news headlines from the Thucnews dataset. We fine tune the methods and parameters in the model and produced some results for reference or comparison","PeriodicalId":325790,"journal":{"name":"2021 International Conference on Computer Engineering and Application (ICCEA)","volume":"219 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121468474","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 : 2021-06-01DOI: 10.1109/ICCEA53728.2021.00029
Ziping Liu
In the fast-changing Internet era, the advantages of e-commerce over traditional shopping models are becoming more and more obvious, and convenient and fast online shopping patterns are attracting more and more users. At the same time, large-scale transactions and demand between e-commerce competition is becoming increasingly fierce, inter-enterprise competition on the one hand to promote the development of e-commerce, at the same time, but also accelerate the survival of e-commerce. Enterprise competition has intensified, customers to the enterprise, has become the most important resource, how to attract customers and retain customers has become the focus of the enterprise, which also makes customer loss become the concern of many enterprises. E-commerce companies in order to ensure their own healthy development in the fierce competition market, not only to make their products attractive, but also in-depth understanding of user preferences and satisfaction, the user’s behavior characteristics of in-depth exploration. E-commerce user behavior instability is greater, the churn rate is high, then, can we find customers in time before the loss, while helping the marketing department to target the loss of customer base and develop appropriate marketing programs is an important work of the enterprise marketing department.It is an important work in the daily operation and management of e-commerce enterprises to predict the loss of users more accurately, to implement targeted retention strategies for users who are at greater risk of loss, and to reduce the churn rate. In these areas, data mining can help businesses. In this paper, data mining technology is applied to business analysis to predict the loss of Tmall users within a certain period of time, so as to implement retention strategy and reduce the churn rate.
{"title":"Predictive analysis of the loss of online shopping users based on data mining","authors":"Ziping Liu","doi":"10.1109/ICCEA53728.2021.00029","DOIUrl":"https://doi.org/10.1109/ICCEA53728.2021.00029","url":null,"abstract":"In the fast-changing Internet era, the advantages of e-commerce over traditional shopping models are becoming more and more obvious, and convenient and fast online shopping patterns are attracting more and more users. At the same time, large-scale transactions and demand between e-commerce competition is becoming increasingly fierce, inter-enterprise competition on the one hand to promote the development of e-commerce, at the same time, but also accelerate the survival of e-commerce. Enterprise competition has intensified, customers to the enterprise, has become the most important resource, how to attract customers and retain customers has become the focus of the enterprise, which also makes customer loss become the concern of many enterprises. E-commerce companies in order to ensure their own healthy development in the fierce competition market, not only to make their products attractive, but also in-depth understanding of user preferences and satisfaction, the user’s behavior characteristics of in-depth exploration. E-commerce user behavior instability is greater, the churn rate is high, then, can we find customers in time before the loss, while helping the marketing department to target the loss of customer base and develop appropriate marketing programs is an important work of the enterprise marketing department.It is an important work in the daily operation and management of e-commerce enterprises to predict the loss of users more accurately, to implement targeted retention strategies for users who are at greater risk of loss, and to reduce the churn rate. In these areas, data mining can help businesses. In this paper, data mining technology is applied to business analysis to predict the loss of Tmall users within a certain period of time, so as to implement retention strategy and reduce the churn rate.","PeriodicalId":325790,"journal":{"name":"2021 International Conference on Computer Engineering and Application (ICCEA)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124847543","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 : 2021-06-01DOI: 10.1109/ICCEA53728.2021.00027
Jianwu Long, Jiangzhou Zhu, Xinyu Feng, Tong Li, Xinlei Song
In complex outdoor scenes, most applicable neural networks can only detect and identify smoke, but cannot accurately locate the source of its pollution. In response to this problem, this paper proposes a smoke pollution source location method based on LMBP neural network to improve the prediction and location results of outdoor smoke pollution sources. This paper first analyzes the related knowledge of artificial neural network (ANN) and Levenberg-Marquardt algorithm (LM algorithm). Then it studies the ANN-BP model based on gradient descent method and the ANN-LMBP model based on the LM algorithm. Finally, experimental simulations verify the feasibility of the ANN-LMBP model in the problem of smoke pollution source location and its strong generalization ability. The error between the latitude and longitude of the ANN-LMBP model proposed in this paper and the actual latitude and longitude in the actual scene are both within 200 meters, which is of great significance for studying the location of smoke pollution sources in complex scenes.
{"title":"Location Method of Smoke Pollution Source based on LMBP Neural Network","authors":"Jianwu Long, Jiangzhou Zhu, Xinyu Feng, Tong Li, Xinlei Song","doi":"10.1109/ICCEA53728.2021.00027","DOIUrl":"https://doi.org/10.1109/ICCEA53728.2021.00027","url":null,"abstract":"In complex outdoor scenes, most applicable neural networks can only detect and identify smoke, but cannot accurately locate the source of its pollution. In response to this problem, this paper proposes a smoke pollution source location method based on LMBP neural network to improve the prediction and location results of outdoor smoke pollution sources. This paper first analyzes the related knowledge of artificial neural network (ANN) and Levenberg-Marquardt algorithm (LM algorithm). Then it studies the ANN-BP model based on gradient descent method and the ANN-LMBP model based on the LM algorithm. Finally, experimental simulations verify the feasibility of the ANN-LMBP model in the problem of smoke pollution source location and its strong generalization ability. The error between the latitude and longitude of the ANN-LMBP model proposed in this paper and the actual latitude and longitude in the actual scene are both within 200 meters, which is of great significance for studying the location of smoke pollution sources in complex scenes.","PeriodicalId":325790,"journal":{"name":"2021 International Conference on Computer Engineering and Application (ICCEA)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124974177","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 : 2021-06-01DOI: 10.1109/ICCEA53728.2021.00037
Wei Wan, Z. Peng, Jinxia Wei, Jing Zhao, Chun Long, Guanyao Du
With the rapid development of big data and cloud computing, network security threats are also growing. More and more researchers pay attention to the study of intrusion detection algorithms. Traditional intrusion detection algorithms are often unable to detect attacks with high dimensional and imbalanced data as input training data. In order to solve the problem above, this paper proposes an integrated intrusion detection model based on deep neural network. Furthermore, model integration solves the problem of sample imbalance and improves the generalization ability of the model. In this paper, we firstly use Generative Adversarial Networks(GAN) model to sample dataset. Then, multiple deep neural network (DNN) classifiers are established and special screening of the classifiers was carried out. Afterwards, all DNN classifiers were integrated based on AdaBoost integration algorithm. During the training of DNN classifiers, the training samples are sampled through an antagonistic generation network, which reduce the impact of data imbalance on classification performance of DNN classifiers. Finally, by conducting experiments with KDD 99 and NS-KDD data sets, the good stability and high accuracy of proposed model are verified.
{"title":"An Effective Integrated Intrusion Detection Model Based on Deep Neural Network","authors":"Wei Wan, Z. Peng, Jinxia Wei, Jing Zhao, Chun Long, Guanyao Du","doi":"10.1109/ICCEA53728.2021.00037","DOIUrl":"https://doi.org/10.1109/ICCEA53728.2021.00037","url":null,"abstract":"With the rapid development of big data and cloud computing, network security threats are also growing. More and more researchers pay attention to the study of intrusion detection algorithms. Traditional intrusion detection algorithms are often unable to detect attacks with high dimensional and imbalanced data as input training data. In order to solve the problem above, this paper proposes an integrated intrusion detection model based on deep neural network. Furthermore, model integration solves the problem of sample imbalance and improves the generalization ability of the model. In this paper, we firstly use Generative Adversarial Networks(GAN) model to sample dataset. Then, multiple deep neural network (DNN) classifiers are established and special screening of the classifiers was carried out. Afterwards, all DNN classifiers were integrated based on AdaBoost integration algorithm. During the training of DNN classifiers, the training samples are sampled through an antagonistic generation network, which reduce the impact of data imbalance on classification performance of DNN classifiers. Finally, by conducting experiments with KDD 99 and NS-KDD data sets, the good stability and high accuracy of proposed model are verified.","PeriodicalId":325790,"journal":{"name":"2021 International Conference on Computer Engineering and Application (ICCEA)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126657011","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 : 2021-06-01DOI: 10.1109/iccea53728.2021.00003
{"title":"[Copyright notice]","authors":"","doi":"10.1109/iccea53728.2021.00003","DOIUrl":"https://doi.org/10.1109/iccea53728.2021.00003","url":null,"abstract":"","PeriodicalId":325790,"journal":{"name":"2021 International Conference on Computer Engineering and Application (ICCEA)","volume":"139 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134015424","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 : 2021-06-01DOI: 10.1109/ICCEA53728.2021.00092
Zhiyong Li, H. Lou, Wenting Han, Yang Fan
A method of aperture allocation for cylindrical array antennas for the integration of radar communication is proposed. Firstly, analyze the pattern of the cylindrical array and establish a shared aperture model on this basis; secondly, select the highest sidelobe level of the radar array and the communication channel capacity as the optimization target and transform the allocation of array element positions into multiple Target optimization problem; Finally, the improved genetic algorithm is used for optimization calculation, and related simulation experiments are completed. The simulation results prove that the maximum sidelobe level of the radar and the communication channel capacity can simultaneously meet the requirements of the working index and the antenna aperture is shared.
{"title":"Radar-Communication Integrated Conformal Array Antenna Sharing Design","authors":"Zhiyong Li, H. Lou, Wenting Han, Yang Fan","doi":"10.1109/ICCEA53728.2021.00092","DOIUrl":"https://doi.org/10.1109/ICCEA53728.2021.00092","url":null,"abstract":"A method of aperture allocation for cylindrical array antennas for the integration of radar communication is proposed. Firstly, analyze the pattern of the cylindrical array and establish a shared aperture model on this basis; secondly, select the highest sidelobe level of the radar array and the communication channel capacity as the optimization target and transform the allocation of array element positions into multiple Target optimization problem; Finally, the improved genetic algorithm is used for optimization calculation, and related simulation experiments are completed. The simulation results prove that the maximum sidelobe level of the radar and the communication channel capacity can simultaneously meet the requirements of the working index and the antenna aperture is shared.","PeriodicalId":325790,"journal":{"name":"2021 International Conference on Computer Engineering and Application (ICCEA)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134068753","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}
Aiming at the problem of multiple observation stations target tracking, a multiple observation stations target tracking based on the unscented Kalman filter (UKF) algorithm is studied. Firstly, the modeling principle of multiple observation stations target tracking is given. On this basis, the multiple observation stations target tracking based on the UKF algorithm is proposed. Finally, a simulation experiment was carried out through MATLAB. The simulation results show that compared with a single observation station, the UKF target tracking algorithm based on multiple observation stations has higher tracking accuracy.
{"title":"Research on multiple observation stations target tracking based on UKF algorithm","authors":"Lieping Zhang, Zhihao Li, Shenglan Zhang, Yanlin Yu, Yong Liang, Zuqiong Zhang","doi":"10.1109/ICCEA53728.2021.00051","DOIUrl":"https://doi.org/10.1109/ICCEA53728.2021.00051","url":null,"abstract":"Aiming at the problem of multiple observation stations target tracking, a multiple observation stations target tracking based on the unscented Kalman filter (UKF) algorithm is studied. Firstly, the modeling principle of multiple observation stations target tracking is given. On this basis, the multiple observation stations target tracking based on the UKF algorithm is proposed. Finally, a simulation experiment was carried out through MATLAB. The simulation results show that compared with a single observation station, the UKF target tracking algorithm based on multiple observation stations has higher tracking accuracy.","PeriodicalId":325790,"journal":{"name":"2021 International Conference on Computer Engineering and Application (ICCEA)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134046062","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 : 2021-06-01DOI: 10.1109/ICCEA53728.2021.00034
Yuan Liu, Baogang Geng, Yongdong Zhang, Z. Wang, Du Lu, Xuan Yao
Aiming at the problem that the stability of airship’s posture is destroyed by turbulent flow when the airship leaves the large factory building, the Computational Fluid Dynamics(CFD) numerical simulation and finite element simulation method are used to simulate the condition that airship transport process in lateral incoming flow. The results shows that the turbulent flow of large factory building causes the variation of surface wind load of airship in the transport process, and the equivalent force and moment acting on airship body center show a certain degree of fluctuations; In lateral incoming flow, compared with the case of restrained by mooring tower, the transfer mode without mooring tower will produce less overall displacement and less extreme value of force on mooring rope. The simulation results provide an effective reference for the safety of airship transport process.
{"title":"Numerical simulation of aerodynamic force and moored state in airship transport process","authors":"Yuan Liu, Baogang Geng, Yongdong Zhang, Z. Wang, Du Lu, Xuan Yao","doi":"10.1109/ICCEA53728.2021.00034","DOIUrl":"https://doi.org/10.1109/ICCEA53728.2021.00034","url":null,"abstract":"Aiming at the problem that the stability of airship’s posture is destroyed by turbulent flow when the airship leaves the large factory building, the Computational Fluid Dynamics(CFD) numerical simulation and finite element simulation method are used to simulate the condition that airship transport process in lateral incoming flow. The results shows that the turbulent flow of large factory building causes the variation of surface wind load of airship in the transport process, and the equivalent force and moment acting on airship body center show a certain degree of fluctuations; In lateral incoming flow, compared with the case of restrained by mooring tower, the transfer mode without mooring tower will produce less overall displacement and less extreme value of force on mooring rope. The simulation results provide an effective reference for the safety of airship transport process.","PeriodicalId":325790,"journal":{"name":"2021 International Conference on Computer Engineering and Application (ICCEA)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114942208","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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