Pub Date : 2019-11-01DOI: 10.1109/IICSPI48186.2019.9096054
Jun Zhu, Lu Yan, Siyuan Guo
Ship network security issues are becoming more and more important as the level of ship intelligence continues to increase. In this paper, the stochastic game model is used to establish the ship network security defense strategy selection method. The simulation results show that the proposed method can select the attack and defense strategy and effectively maintain the safe operation of the ship network.
{"title":"Research on Ship Network Security Based on Game Theory","authors":"Jun Zhu, Lu Yan, Siyuan Guo","doi":"10.1109/IICSPI48186.2019.9096054","DOIUrl":"https://doi.org/10.1109/IICSPI48186.2019.9096054","url":null,"abstract":"Ship network security issues are becoming more and more important as the level of ship intelligence continues to increase. In this paper, the stochastic game model is used to establish the ship network security defense strategy selection method. The simulation results show that the proposed method can select the attack and defense strategy and effectively maintain the safe operation of the ship network.","PeriodicalId":318693,"journal":{"name":"2019 2nd International Conference on Safety Produce Informatization (IICSPI)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134140237","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 : 2019-11-01DOI: 10.1109/IICSPI48186.2019.9095964
Chen Yan
The image will inevitably be mixed with noise or interference signals in the process of acquisition and storage. For this reason, independent component analysis (ICA) and genetic Bayesian regularized BP neural networks are combined to deal with image denoising problems. Firstly, the image to be processed is separated into independent noisy images by ICA method. Then the noisy image is predicted by the genetic Bayesian regularized BP neural network to obtain a clear image. Experiments show this method can improve the PSNR and correlation coefficient of the image.
{"title":"Image Denoising Method Based on ICA and BP Neural Network","authors":"Chen Yan","doi":"10.1109/IICSPI48186.2019.9095964","DOIUrl":"https://doi.org/10.1109/IICSPI48186.2019.9095964","url":null,"abstract":"The image will inevitably be mixed with noise or interference signals in the process of acquisition and storage. For this reason, independent component analysis (ICA) and genetic Bayesian regularized BP neural networks are combined to deal with image denoising problems. Firstly, the image to be processed is separated into independent noisy images by ICA method. Then the noisy image is predicted by the genetic Bayesian regularized BP neural network to obtain a clear image. Experiments show this method can improve the PSNR and correlation coefficient of the image.","PeriodicalId":318693,"journal":{"name":"2019 2nd International Conference on Safety Produce Informatization (IICSPI)","volume":"137 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134442731","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 : 2019-11-01DOI: 10.1109/IICSPI48186.2019.9095927
Lin Zhang
With the continuous expansion of the application field of Case-Based Reasoning (CBR) technology, it is increasingly difficult for programmers to acquire and express professional knowledge. Therefore, the demand for general case retrieval model based on Case-Based Reasoning is rising. This paper first gives a structured expression of professional knowledge, and combines the Case-Based Reasoning method with the scientific measurement of keyword weight (Term Frequency-Inverse Document Frequency, TF-IDF) to design the case organization, case retrieval and case retaining in CBR technology. It provides an effective method for general case retrieval model.
{"title":"The Research on General Case-Based Reasoning Method Based on TF-IDF","authors":"Lin Zhang","doi":"10.1109/IICSPI48186.2019.9095927","DOIUrl":"https://doi.org/10.1109/IICSPI48186.2019.9095927","url":null,"abstract":"With the continuous expansion of the application field of Case-Based Reasoning (CBR) technology, it is increasingly difficult for programmers to acquire and express professional knowledge. Therefore, the demand for general case retrieval model based on Case-Based Reasoning is rising. This paper first gives a structured expression of professional knowledge, and combines the Case-Based Reasoning method with the scientific measurement of keyword weight (Term Frequency-Inverse Document Frequency, TF-IDF) to design the case organization, case retrieval and case retaining in CBR technology. It provides an effective method for general case retrieval model.","PeriodicalId":318693,"journal":{"name":"2019 2nd International Conference on Safety Produce Informatization (IICSPI)","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134015097","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 : 2019-11-01DOI: 10.1109/IICSPI48186.2019.9095908
R. Xie, Xiao Liu, Jinpo Fan, Guozhen Shi
To protect the confidentiality, integrity and privacy of users' data in cloud storage, a hierarchical cloud storage scheme based on environment features is proposed. The scheme maps the relationship between user attributes, data encryption security requirements, operating environment and data security storage levels. The hierarchical cloud storage addressed twice is realized. Firstly, the starting address of storage area corresponding to user data is determined according to the data security requirement level. Secondly, the data address offset is calculated through the data attribute set and account information set, and finally the hierarchical cloud storage of data is realized. Experimental results show that users' security requirements are met and security is improved, providing a solution for the implementation of cloud storage.
{"title":"An on-demand cloud storage scheme based on context aware","authors":"R. Xie, Xiao Liu, Jinpo Fan, Guozhen Shi","doi":"10.1109/IICSPI48186.2019.9095908","DOIUrl":"https://doi.org/10.1109/IICSPI48186.2019.9095908","url":null,"abstract":"To protect the confidentiality, integrity and privacy of users' data in cloud storage, a hierarchical cloud storage scheme based on environment features is proposed. The scheme maps the relationship between user attributes, data encryption security requirements, operating environment and data security storage levels. The hierarchical cloud storage addressed twice is realized. Firstly, the starting address of storage area corresponding to user data is determined according to the data security requirement level. Secondly, the data address offset is calculated through the data attribute set and account information set, and finally the hierarchical cloud storage of data is realized. Experimental results show that users' security requirements are met and security is improved, providing a solution for the implementation of cloud storage.","PeriodicalId":318693,"journal":{"name":"2019 2nd International Conference on Safety Produce Informatization (IICSPI)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134270933","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 : 2019-11-01DOI: 10.1109/IICSPI48186.2019.9096013
Xuefei Zhang
Aiming at the characteristics of intensity inhomogeneity distribution in images, a variational level set image segmentation model combining global and local intensity information is proposed. Local region information is the key to accurately segmenting images. However, the conventional CV model does not utilize the local region information, and the LBF model is susceptible to the initial outline and noise. In this paper, we present a hybrid model driven by new global and local intensity information. A new evolutionary stop function is constructed by using the principle of LBF model, and it is combined with the CV model to obtain an active contour model containing local and global information. By testing various types of real images and synthetic images, the model not only can deal with image with intensity inhomogeneity, but also reduces sensitivity of the model to the initial contour and the iteration number is also decreased.
{"title":"A hybrid active contour model driven by global and local intensity information","authors":"Xuefei Zhang","doi":"10.1109/IICSPI48186.2019.9096013","DOIUrl":"https://doi.org/10.1109/IICSPI48186.2019.9096013","url":null,"abstract":"Aiming at the characteristics of intensity inhomogeneity distribution in images, a variational level set image segmentation model combining global and local intensity information is proposed. Local region information is the key to accurately segmenting images. However, the conventional CV model does not utilize the local region information, and the LBF model is susceptible to the initial outline and noise. In this paper, we present a hybrid model driven by new global and local intensity information. A new evolutionary stop function is constructed by using the principle of LBF model, and it is combined with the CV model to obtain an active contour model containing local and global information. By testing various types of real images and synthetic images, the model not only can deal with image with intensity inhomogeneity, but also reduces sensitivity of the model to the initial contour and the iteration number is also decreased.","PeriodicalId":318693,"journal":{"name":"2019 2nd International Conference on Safety Produce Informatization (IICSPI)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128854660","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 : 2019-11-01DOI: 10.1109/IICSPI48186.2019.9095902
Yuefan Xu, Minling Zhu, Yuefan Xu, Mingjie Liu
Aiming at the obstacle avoidance problem of UAV, a control method of UAV obstacle avoidance based on ultrasonic is proposed. The number of ultrasonic waves is increased to surround a circle based on the traditional ultrasonic obstacle avoidance scheme, and fused the information of multiple ultrasonic sensors, and according to the distance between the UAV and the obstacle and the channel value of the tele controller, the obstacle avoidance flight of the multi-rotor UAV is realized. The experimental results show that the system has the characteristics of low price, simple implementation and reliable security performance, and has a certain reference value.
{"title":"Design and Implementation of UAV Obstacle Avoidance System","authors":"Yuefan Xu, Minling Zhu, Yuefan Xu, Mingjie Liu","doi":"10.1109/IICSPI48186.2019.9095902","DOIUrl":"https://doi.org/10.1109/IICSPI48186.2019.9095902","url":null,"abstract":"Aiming at the obstacle avoidance problem of UAV, a control method of UAV obstacle avoidance based on ultrasonic is proposed. The number of ultrasonic waves is increased to surround a circle based on the traditional ultrasonic obstacle avoidance scheme, and fused the information of multiple ultrasonic sensors, and according to the distance between the UAV and the obstacle and the channel value of the tele controller, the obstacle avoidance flight of the multi-rotor UAV is realized. The experimental results show that the system has the characteristics of low price, simple implementation and reliable security performance, and has a certain reference value.","PeriodicalId":318693,"journal":{"name":"2019 2nd International Conference on Safety Produce Informatization (IICSPI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129007367","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 : 2019-11-01DOI: 10.1109/IICSPI48186.2019.9095913
J. Bao, Xinyi Li
Exploration on the time series data in unknown model pattern recognition has important research significance. This paper proposes an unknown pattern detection method for time-series data based on convolution neural network, which planifies the output results by transforming fully connection layer and softmax layer of the traditional convolutional neural network, and uses the coordinate point and Euclidean distance to determine whether the timing series data belongs to the known pattern or the unknown pattern. Experiments show that the method in this paper can effectively detect the time-series data of unknown patterns and has certain accuracy.
{"title":"An Unknown Pattern Detection Method for Time Series Data Based on Convolutional Neural Network","authors":"J. Bao, Xinyi Li","doi":"10.1109/IICSPI48186.2019.9095913","DOIUrl":"https://doi.org/10.1109/IICSPI48186.2019.9095913","url":null,"abstract":"Exploration on the time series data in unknown model pattern recognition has important research significance. This paper proposes an unknown pattern detection method for time-series data based on convolution neural network, which planifies the output results by transforming fully connection layer and softmax layer of the traditional convolutional neural network, and uses the coordinate point and Euclidean distance to determine whether the timing series data belongs to the known pattern or the unknown pattern. Experiments show that the method in this paper can effectively detect the time-series data of unknown patterns and has certain accuracy.","PeriodicalId":318693,"journal":{"name":"2019 2nd International Conference on Safety Produce Informatization (IICSPI)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128012863","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 : 2019-11-01DOI: 10.1109/IICSPI48186.2019.9095937
Li Shuo, Qin Liwen, Yuan Xiaoyong, Zhou Yangjun, Lik Shan
It is urgent to build an effective big data management platform for power distribution network in view of the problems of massive power data being hard to be fully explored and managed integrally. Based on the big data architecture of power, this paper constructs the multidimensional visualization platform of distribution network, and realizes the multi-function architecture of the platform by integrating the production decision-making system and data analysis technology of multi-source distribution network. Based on the geographic information system, a large-screen visualization display platform of distribution network production business is established. Rich charts and geographic information are used to realize the comprehensive display of distribution network production business, providing users with smooth data visualization interaction and assisting in the decision-making of distribution network production business. The construction of multi-dimensional visualization platform of distribution network based on big data architecture has important research significance and application value to comprehensively improve the intelligent construction of distribution network.
{"title":"Research on Guangxi Multi-dimensional Visualization Platform Construction of Distribution Network Based on Big Data Architecture","authors":"Li Shuo, Qin Liwen, Yuan Xiaoyong, Zhou Yangjun, Lik Shan","doi":"10.1109/IICSPI48186.2019.9095937","DOIUrl":"https://doi.org/10.1109/IICSPI48186.2019.9095937","url":null,"abstract":"It is urgent to build an effective big data management platform for power distribution network in view of the problems of massive power data being hard to be fully explored and managed integrally. Based on the big data architecture of power, this paper constructs the multidimensional visualization platform of distribution network, and realizes the multi-function architecture of the platform by integrating the production decision-making system and data analysis technology of multi-source distribution network. Based on the geographic information system, a large-screen visualization display platform of distribution network production business is established. Rich charts and geographic information are used to realize the comprehensive display of distribution network production business, providing users with smooth data visualization interaction and assisting in the decision-making of distribution network production business. The construction of multi-dimensional visualization platform of distribution network based on big data architecture has important research significance and application value to comprehensively improve the intelligent construction of distribution network.","PeriodicalId":318693,"journal":{"name":"2019 2nd International Conference on Safety Produce Informatization (IICSPI)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122989863","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 : 2019-11-01DOI: 10.1109/IICSPI48186.2019.9095870
Kai Tang, Xiaohua Luo, Lifeng Sun, Yuan Xu, Chao Fang
Data of safety production accidents show that people’s unsafe behavior is the major and direct cause of accidents. The unsafe behavior is mainly caused by the decline of physiological function, insufficient risk assessment, negative understanding, insufficient safety knowledge, wrong management orientation and blind complacency, which is difficult to supervise and control for human uncertainty. Safety Intellectualization, which combines and optimizes space, equipment, facilities, systems and services according to scenarios and business logic, utilizes data value of big data mining and intelligently recognizes and processes images and voices to support innovative management models and applications, and provides safety technology support for smart factories and intelligent manufacturing. Through continuous optimization of Artificial Intelligent model and network, the recognition accuracy of unsafe behavior can reach more than 91.2%, which has commercial application value.
{"title":"AI Empowers the Application of Industry Safety Intellectualization","authors":"Kai Tang, Xiaohua Luo, Lifeng Sun, Yuan Xu, Chao Fang","doi":"10.1109/IICSPI48186.2019.9095870","DOIUrl":"https://doi.org/10.1109/IICSPI48186.2019.9095870","url":null,"abstract":"Data of safety production accidents show that people’s unsafe behavior is the major and direct cause of accidents. The unsafe behavior is mainly caused by the decline of physiological function, insufficient risk assessment, negative understanding, insufficient safety knowledge, wrong management orientation and blind complacency, which is difficult to supervise and control for human uncertainty. Safety Intellectualization, which combines and optimizes space, equipment, facilities, systems and services according to scenarios and business logic, utilizes data value of big data mining and intelligently recognizes and processes images and voices to support innovative management models and applications, and provides safety technology support for smart factories and intelligent manufacturing. Through continuous optimization of Artificial Intelligent model and network, the recognition accuracy of unsafe behavior can reach more than 91.2%, which has commercial application value.","PeriodicalId":318693,"journal":{"name":"2019 2nd International Conference on Safety Produce Informatization (IICSPI)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115510079","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 : 2019-11-01DOI: 10.1109/iicspi48186.2019.9095891
{"title":"IICSPI 2019 Table of Contents","authors":"","doi":"10.1109/iicspi48186.2019.9095891","DOIUrl":"https://doi.org/10.1109/iicspi48186.2019.9095891","url":null,"abstract":"","PeriodicalId":318693,"journal":{"name":"2019 2nd International Conference on Safety Produce Informatization (IICSPI)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115579726","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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