Pub Date : 2019-04-01DOI: 10.2991/ICMEIT-19.2019.148
Qiang Liu
In the process of our current technological development, computers still play an important role, if the computer breaks down, a lot of data will be lost, we use e-mail or U disk to transmit data information. When we come to the era of cloud computing, "cloud" can store the data we need and carry out related calculations, the advantage of the cloud is that it can be used anytime, anywhere, to ensure the safety and reliability of data. This paper systematically analyzes and summarizes the research status of cloud computing, divides the cloud computing architecture into three levels: core services, service management, user access interface and so on, and makes a close study on the aspects of low cost and reliability, and studies the key technical content and development direction of cloud computing.
{"title":"Research on the Architecture and Key Technologies of Cloud Computing","authors":"Qiang Liu","doi":"10.2991/ICMEIT-19.2019.148","DOIUrl":"https://doi.org/10.2991/ICMEIT-19.2019.148","url":null,"abstract":"In the process of our current technological development, computers still play an important role, if the computer breaks down, a lot of data will be lost, we use e-mail or U disk to transmit data information. When we come to the era of cloud computing, \"cloud\" can store the data we need and carry out related calculations, the advantage of the cloud is that it can be used anytime, anywhere, to ensure the safety and reliability of data. This paper systematically analyzes and summarizes the research status of cloud computing, divides the cloud computing architecture into three levels: core services, service management, user access interface and so on, and makes a close study on the aspects of low cost and reliability, and studies the key technical content and development direction of cloud computing.","PeriodicalId":223458,"journal":{"name":"Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115471214","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 : 2019-04-01DOI: 10.2991/ICMEIT-19.2019.118
Li Zhang
. The smooth implementation of automation management of computer software engineering projects has played an important role in promoting the faster development of computer software development and further promoting the development of computer software engineering. In the process of realizing automation management of project, data mining technology and method are introduced, and a computer aided quality function configuration model based on data mining is proposed. The data mining tool was developed, and the model for product user demand and process quality selection decomposition was established. At the same time, the data mining model of fuzzy clustering and grey theory algorithm was established, and related application examples were analyzed. At present, all methods of validity discrimination do not have absolute advantages, and all need to be adapted and selected for specific data sets.
{"title":"Research on Computer Software Engineering Project Automation Management based on Data Mining and Fuzzy Clustering","authors":"Li Zhang","doi":"10.2991/ICMEIT-19.2019.118","DOIUrl":"https://doi.org/10.2991/ICMEIT-19.2019.118","url":null,"abstract":". The smooth implementation of automation management of computer software engineering projects has played an important role in promoting the faster development of computer software development and further promoting the development of computer software engineering. In the process of realizing automation management of project, data mining technology and method are introduced, and a computer aided quality function configuration model based on data mining is proposed. The data mining tool was developed, and the model for product user demand and process quality selection decomposition was established. At the same time, the data mining model of fuzzy clustering and grey theory algorithm was established, and related application examples were analyzed. At present, all methods of validity discrimination do not have absolute advantages, and all need to be adapted and selected for specific data sets.","PeriodicalId":223458,"journal":{"name":"Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)","volume":"121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122075349","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 : 2019-04-01DOI: 10.2991/ICMEIT-19.2019.74
Ming Li, R. Hu, Hong Xu, Huimin Zhao, Xueri Li
Aiming at the problems of asymmetric information and long delay time and excessive use of network traffic and inaccurate recommendation in the traditional medical information recommendation algorithm, the improved adaptive scheduling algorithm and intelligent optimization recommendation algorithm are combined, it can completely solve the problems of time, traffic occupancy, stability and accuracy of medical information push. In this paper, an improved adaptive scheduling algorithm is proposed to solve the problems of time occupancy, traffic flow and connection stability of medical information recommendation. The proposed intelligent optimization recommendation algorithm solves the accuracy problem of medical information recommendation. Experimental results show that the proposed algorithm has the advantages of short delay time, low flow occupation, stable connection and high accuracy of push.
{"title":"Research on Intelligent Scheduling Optimization Selection Algorithm for Medical Information","authors":"Ming Li, R. Hu, Hong Xu, Huimin Zhao, Xueri Li","doi":"10.2991/ICMEIT-19.2019.74","DOIUrl":"https://doi.org/10.2991/ICMEIT-19.2019.74","url":null,"abstract":"Aiming at the problems of asymmetric information and long delay time and excessive use of network traffic and inaccurate recommendation in the traditional medical information recommendation algorithm, the improved adaptive scheduling algorithm and intelligent optimization recommendation algorithm are combined, it can completely solve the problems of time, traffic occupancy, stability and accuracy of medical information push. In this paper, an improved adaptive scheduling algorithm is proposed to solve the problems of time occupancy, traffic flow and connection stability of medical information recommendation. The proposed intelligent optimization recommendation algorithm solves the accuracy problem of medical information recommendation. Experimental results show that the proposed algorithm has the advantages of short delay time, low flow occupation, stable connection and high accuracy of push.","PeriodicalId":223458,"journal":{"name":"Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126162905","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 : 2019-04-01DOI: 10.2991/ICMEIT-19.2019.112
Ruixin Chen, Na Lin, Jin Su, Yanjun Shi
Human-computer interaction system is the medium for human and computer. The rationality and intelligence of its design directly affect the work efficiency and execution ability of relevant practitioners. Traditional human-computer interaction evaluation usually adopts expert evaluation method. This method is difficult to evaluate objectively because of people’s subjective cognitive differences. Therefore, this paper proposes an intelligent evaluation method for complex human-computer interaction system based on BP neural network model. First, the known evaluation indicators are classified and organized, and five key evaluation indicators are optimized according to importance and relevance. Then the index is quantified into the evaluation function according to the fuzzy analytic hierarchy process. Finally, the data obtained by the simulation test is used as the training set and test set of the BP neural network, and then the evaluation model of the humancomputer interaction system is obtained.
{"title":"BP Neural Network-based Model for Evaluating User Interfaces of Human-computer Interaction System","authors":"Ruixin Chen, Na Lin, Jin Su, Yanjun Shi","doi":"10.2991/ICMEIT-19.2019.112","DOIUrl":"https://doi.org/10.2991/ICMEIT-19.2019.112","url":null,"abstract":"Human-computer interaction system is the medium for human and computer. The rationality and intelligence of its design directly affect the work efficiency and execution ability of relevant practitioners. Traditional human-computer interaction evaluation usually adopts expert evaluation method. This method is difficult to evaluate objectively because of people’s subjective cognitive differences. Therefore, this paper proposes an intelligent evaluation method for complex human-computer interaction system based on BP neural network model. First, the known evaluation indicators are classified and organized, and five key evaluation indicators are optimized according to importance and relevance. Then the index is quantified into the evaluation function according to the fuzzy analytic hierarchy process. Finally, the data obtained by the simulation test is used as the training set and test set of the BP neural network, and then the evaluation model of the humancomputer interaction system is obtained.","PeriodicalId":223458,"journal":{"name":"Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126287768","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 : 2019-04-01DOI: 10.2991/ICMEIT-19.2019.124
Shanshan Guan, Yinong Zhang, Zhuojing Tian
In order to improve the recognition rate of human behavior by intelligent terminals, a network model for deep learning of human behavior recognition is proposed. Time series data is transformed into a deep network model by performing motion segmentation using a sliding window algorithm. Feature vectors are imported into the SoftMax classifier through end-to-end research, which identifies six daily behaviors such as walking, sitting, going upstairs, going downstairs, standing and lying down. By comparing the recognition effects of different models, it was found that the convolutional neural network introduced into Dropout achieved better recognition results in UCI HAR dataset.
{"title":"Research on Human Behavior Recognition based on Deep Neural Network","authors":"Shanshan Guan, Yinong Zhang, Zhuojing Tian","doi":"10.2991/ICMEIT-19.2019.124","DOIUrl":"https://doi.org/10.2991/ICMEIT-19.2019.124","url":null,"abstract":"In order to improve the recognition rate of human behavior by intelligent terminals, a network model for deep learning of human behavior recognition is proposed. Time series data is transformed into a deep network model by performing motion segmentation using a sliding window algorithm. Feature vectors are imported into the SoftMax classifier through end-to-end research, which identifies six daily behaviors such as walking, sitting, going upstairs, going downstairs, standing and lying down. By comparing the recognition effects of different models, it was found that the convolutional neural network introduced into Dropout achieved better recognition results in UCI HAR dataset.","PeriodicalId":223458,"journal":{"name":"Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126375138","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 : 2019-04-01DOI: 10.2991/ICMEIT-19.2019.37
Xintong Liu, Huaxiong Zhang
Characteristics of paper-cutting, paper-cutting gallery construction, etc. are analyzed aiming at existing problems of folk traditional paper-cutting art multimedia interactive platform. It is proposed that rotation invariant LBP (Local Binary Pattern) is combined with LSH algorithm to present a large-scale paper-cutting image fast retrieval method. Firstly, the background image is eliminated with OTSU, then the paper-cutting image rotation LBP feature. In addition, highdimensional data is mapped to low dimensional space, and a hash index was constructed by local sensitive hash algorithm to find the approximate KNN. Experimental result in the dataset shows that the improved algorithm has high accuracy on paper-cutting image retrieval, and it is significantly higher than traditional algorithm on retrieval speed.
{"title":"Paper-cutting Image Retrieval Technology based on LSH Improvement","authors":"Xintong Liu, Huaxiong Zhang","doi":"10.2991/ICMEIT-19.2019.37","DOIUrl":"https://doi.org/10.2991/ICMEIT-19.2019.37","url":null,"abstract":"Characteristics of paper-cutting, paper-cutting gallery construction, etc. are analyzed aiming at existing problems of folk traditional paper-cutting art multimedia interactive platform. It is proposed that rotation invariant LBP (Local Binary Pattern) is combined with LSH algorithm to present a large-scale paper-cutting image fast retrieval method. Firstly, the background image is eliminated with OTSU, then the paper-cutting image rotation LBP feature. In addition, highdimensional data is mapped to low dimensional space, and a hash index was constructed by local sensitive hash algorithm to find the approximate KNN. Experimental result in the dataset shows that the improved algorithm has high accuracy on paper-cutting image retrieval, and it is significantly higher than traditional algorithm on retrieval speed.","PeriodicalId":223458,"journal":{"name":"Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125759794","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 : 2019-04-01DOI: 10.2991/ICMEIT-19.2019.109
Wenjun Ji
Co-simulation technology plays a vital role in computer software engineering design and development. How to improve resource allocation and workflow coupling computational efficiency in complex simulation is a key point in software engineering management. Scientific workflow technology is the means of support to solve the above problems. This method can simplify the complicated operation process of software product developers' collection, calculation and analysis of large-scale scientific data, realize product process customization, deployment and execution, and effectively improve the problem-solving efficiency. Based on this, the thesis uses the scientific workflow concept to implement collaborative simulation calculation in computer software engineering to improve software design efficiency.
{"title":"Research on Computer Software Engineering based on Scientific Workflow","authors":"Wenjun Ji","doi":"10.2991/ICMEIT-19.2019.109","DOIUrl":"https://doi.org/10.2991/ICMEIT-19.2019.109","url":null,"abstract":"Co-simulation technology plays a vital role in computer software engineering design and development. How to improve resource allocation and workflow coupling computational efficiency in complex simulation is a key point in software engineering management. Scientific workflow technology is the means of support to solve the above problems. This method can simplify the complicated operation process of software product developers' collection, calculation and analysis of large-scale scientific data, realize product process customization, deployment and execution, and effectively improve the problem-solving efficiency. Based on this, the thesis uses the scientific workflow concept to implement collaborative simulation calculation in computer software engineering to improve software design efficiency.","PeriodicalId":223458,"journal":{"name":"Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130125520","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 : 2019-04-01DOI: 10.2991/ICMEIT-19.2019.9
Yixiang Jiang, Chengting Zhang, Wen Jin
With the rapid development of industrial control network, performance management and risk prevention based on network traffic data, especially abnormal traffic detection, have gradually attracted people's attention. However, the traditional flow detection method based on fixed baseline cannot adapt to the growing data and increasingly complex data types. It leads to inaccurate test results and false alarms, and also consumes a lot of manpower and resources. In this paper, a semisupervised learning method is proposed to realize the self-construction of baseline and the automatic detection of abnormal index data.
{"title":"Research on Baseline Technology of Industrial Control Network Security based on Semi-supervised Learning","authors":"Yixiang Jiang, Chengting Zhang, Wen Jin","doi":"10.2991/ICMEIT-19.2019.9","DOIUrl":"https://doi.org/10.2991/ICMEIT-19.2019.9","url":null,"abstract":"With the rapid development of industrial control network, performance management and risk prevention based on network traffic data, especially abnormal traffic detection, have gradually attracted people's attention. However, the traditional flow detection method based on fixed baseline cannot adapt to the growing data and increasingly complex data types. It leads to inaccurate test results and false alarms, and also consumes a lot of manpower and resources. In this paper, a semisupervised learning method is proposed to realize the self-construction of baseline and the automatic detection of abnormal index data.","PeriodicalId":223458,"journal":{"name":"Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)","volume":"234 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128070430","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 : 2019-04-01DOI: 10.2991/ICMEIT-19.2019.140
Chao Bu
Abstract. This paper first probes into the application of Data Envelopment Analysis in educational efficiency assessment. Based on this, it establishes the assessment index system of vocational college educational efficiency. It makes a case evaluation of certain colleges’ efficiency using Data Envelopment Analysis and ranks the effectively-running vocational colleges with the C2R model and C2GS2 model.
{"title":"Research on the Assessment of Vocational College Educational Efficiency based on Data Envelopment Analysis","authors":"Chao Bu","doi":"10.2991/ICMEIT-19.2019.140","DOIUrl":"https://doi.org/10.2991/ICMEIT-19.2019.140","url":null,"abstract":"Abstract. This paper first probes into the application of Data Envelopment Analysis in educational efficiency assessment. Based on this, it establishes the assessment index system of vocational college educational efficiency. It makes a case evaluation of certain colleges’ efficiency using Data Envelopment Analysis and ranks the effectively-running vocational colleges with the C2R model and C2GS2 model.","PeriodicalId":223458,"journal":{"name":"Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128235682","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}
This paper proposed a K-means measure to cluster stocks, and predicted the investment of strong profitability objects through comprehensive analysis of KDJ indicators. The paper analyzed the clustering hierarchy diagram, as well as the inter-cluster similarity structure diagram of different cluster numbers. It is found that the clusters can be effectively distinguished for each type of stock. The comprehensive prediction precision of KDJ are better than each single index. The feasibility and effectiveness of the suggested method are verified by the example of the constituents of the CSI 800 Index. The quantitative investment model established by the analytical method in this paper has better prediction effect.
{"title":"Research on Comprehensive Analysis Method of Stock KDJ Index based on K-means Clustering","authors":"Baoyu Ding, Ling Li, Yunliang Zhu, Hui Liu, Junfeng Bao, Zezhu Yang","doi":"10.2991/ICMEIT-19.2019.78","DOIUrl":"https://doi.org/10.2991/ICMEIT-19.2019.78","url":null,"abstract":"This paper proposed a K-means measure to cluster stocks, and predicted the investment of strong profitability objects through comprehensive analysis of KDJ indicators. The paper analyzed the clustering hierarchy diagram, as well as the inter-cluster similarity structure diagram of different cluster numbers. It is found that the clusters can be effectively distinguished for each type of stock. The comprehensive prediction precision of KDJ are better than each single index. The feasibility and effectiveness of the suggested method are verified by the example of the constituents of the CSI 800 Index. The quantitative investment model established by the analytical method in this paper has better prediction effect.","PeriodicalId":223458,"journal":{"name":"Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128921386","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：