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-19.2019.88
Jianfeng Liao, Qun Zhang, J. You
This paper deeply discusses the general situation, background and application of humancomputer interaction, and proposes a new exploration-one-hand gesture recognition in humancomputer interaction mode, and discusses the main research techniques in detail and comprehensively. The basic framework of vision-based gesture recognition system is studied. The various principles and methods of vision-based gesture positioning, gesture tracking, gesture segmentation and gesture recognition are analyzed. Based on the CamShift algorithm and the improved CamShift algorithm for gesture tracking, the CamShift algorithm cannot solve the large-area motion interference problem when solving complex dynamic changes. Therefore, it is proposed to add Kalman filter to estimate the next state. It proves that more effective gesture tracking is realized. This paper uses a more reasonable method to achieve the correct sense of input gestures through the visual channel by means of computer vision, digital image processing, pattern recognition and other theories and techniques. The response required to achieve natural human-computer interaction.
{"title":"Research on Human-Computer Interaction Technology based on Visual User Gesture Recognition","authors":"Jianfeng Liao, Qun Zhang, J. You","doi":"10.2991/ICMEIT-19.2019.88","DOIUrl":"https://doi.org/10.2991/ICMEIT-19.2019.88","url":null,"abstract":"This paper deeply discusses the general situation, background and application of humancomputer interaction, and proposes a new exploration-one-hand gesture recognition in humancomputer interaction mode, and discusses the main research techniques in detail and comprehensively. The basic framework of vision-based gesture recognition system is studied. The various principles and methods of vision-based gesture positioning, gesture tracking, gesture segmentation and gesture recognition are analyzed. Based on the CamShift algorithm and the improved CamShift algorithm for gesture tracking, the CamShift algorithm cannot solve the large-area motion interference problem when solving complex dynamic changes. Therefore, it is proposed to add Kalman filter to estimate the next state. It proves that more effective gesture tracking is realized. This paper uses a more reasonable method to achieve the correct sense of input gestures through the visual channel by means of computer vision, digital image processing, pattern recognition and other theories and techniques. The response required to achieve natural human-computer interaction.","PeriodicalId":223458,"journal":{"name":"Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)","volume":"34 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":"116633376","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-19.2019.148
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-19.2019.140
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}
Pub Date : 2019-04-01DOI: 10.2991/ICMEIT-19.2019.66
Z. Chen
With the progress of science and technology, intelligent robot system has been applied in service industry. The research and design of service-oriented autonomous mobile robots have attracted more and more attention from enterprises and businesses. In this paper, an intelligent tennis pickup robot based on swarm intelligence is designed around the collection of tennis on the tennis court. Firstly, the paper briefly describes the purpose of the path planning of the Ryukyu robot and the working characteristics of the visual processing. It analyzes the problems faced by the design of the autonomous ball-racing robot. Then, based on the rolling window theory, an autonomous mobile robot based on the visual sensor is proposed. Multi-objective path planning algorithm. The algorithm effectively reduces the time for the mobile croquet robot to perform tasks and improves its croquet efficiency.
{"title":"Visual Navigation and Path Planning of Ball Picking Robot based on Swarm Intelligence","authors":"Z. Chen","doi":"10.2991/ICMEIT-19.2019.66","DOIUrl":"https://doi.org/10.2991/ICMEIT-19.2019.66","url":null,"abstract":"With the progress of science and technology, intelligent robot system has been applied in service industry. The research and design of service-oriented autonomous mobile robots have attracted more and more attention from enterprises and businesses. In this paper, an intelligent tennis pickup robot based on swarm intelligence is designed around the collection of tennis on the tennis court. Firstly, the paper briefly describes the purpose of the path planning of the Ryukyu robot and the working characteristics of the visual processing. It analyzes the problems faced by the design of the autonomous ball-racing robot. Then, based on the rolling window theory, an autonomous mobile robot based on the visual sensor is proposed. Multi-objective path planning algorithm. The algorithm effectively reduces the time for the mobile croquet robot to perform tasks and improves its croquet efficiency.","PeriodicalId":223458,"journal":{"name":"Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)","volume":"23 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":"128370908","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}
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-19.2019.131
Wenzhong Xia
Aiming at the poor connection and overload of electrical lines on campus, it is easy to generate fires, and then propose a wireless monitoring system to build a campus electricity monitoring system. The solution can dynamically set the threshold of the smart socket to avoid overload and affect the circuit. At the same time, it conducts intensive management for the power consumption of various types of electrical equipment on campus, and briefly summarizes the hardware and software components of the wireless sensor network of the system. The experimental research shows that the system is easy to install and debug, guarantee the safety of electricity consumption, achieve the purpose of energy saving on campus, and has high application value.
{"title":"Research on Power Monitoring System of Campus Intelligent Network based on Wireless Sensor Network","authors":"Wenzhong Xia","doi":"10.2991/ICMEIT-19.2019.131","DOIUrl":"https://doi.org/10.2991/ICMEIT-19.2019.131","url":null,"abstract":"Aiming at the poor connection and overload of electrical lines on campus, it is easy to generate fires, and then propose a wireless monitoring system to build a campus electricity monitoring system. The solution can dynamically set the threshold of the smart socket to avoid overload and affect the circuit. At the same time, it conducts intensive management for the power consumption of various types of electrical equipment on campus, and briefly summarizes the hardware and software components of the wireless sensor network of the system. The experimental research shows that the system is easy to install and debug, guarantee the safety of electricity consumption, achieve the purpose of energy saving on campus, and has high application value.","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":"130481316","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-19.2019.124
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}
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