Pub Date : 2021-07-01DOI: 10.1109/ICNISC54316.2021.00161
Wei Wang
With the rapid development of network technology, all sectors of society are gradually inseparable from the application of network system, universities are no exception. They have their own application system in enrollment, teaching, employment, general affairs and other departments, which undoubtedly brings great work pressure to the University Information Center. However, the original application service deployment mode is faced with the problems of low resource utilization, complex management and low implementation efficiency. Combined with the actual situation of colleges and universities, this paper proposes an application service deployment solution based on docker container technology.
{"title":"Application of Docker Container Technology in University Information Center","authors":"Wei Wang","doi":"10.1109/ICNISC54316.2021.00161","DOIUrl":"https://doi.org/10.1109/ICNISC54316.2021.00161","url":null,"abstract":"With the rapid development of network technology, all sectors of society are gradually inseparable from the application of network system, universities are no exception. They have their own application system in enrollment, teaching, employment, general affairs and other departments, which undoubtedly brings great work pressure to the University Information Center. However, the original application service deployment mode is faced with the problems of low resource utilization, complex management and low implementation efficiency. Combined with the actual situation of colleges and universities, this paper proposes an application service deployment solution based on docker container technology.","PeriodicalId":396802,"journal":{"name":"2021 7th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123890240","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 : 2021-07-01DOI: 10.1109/ICNISC54316.2021.00168
Zhu Yan, Zhenyu Sun, Peng Liu, Chongwen Wang, Naiwu Li
With the development of fuel cell electric vehicles (FCEVs), the number of FCEVs is increasing constantly. In China, the use of commercial vehicles is promoted vigorously. It is necessary to propose a method to evaluate the comprehensive performance of fuel cell commercial vehicles. During the application of cloud data, operation data of electric vehicles can be stored on the cloud to evaluate comprehensive performance. In this paper, a method based on operation data is proposed to evaluate the comprehensive performance of fuel cell commercial vehicles. 5 indicators, including fueling economy, refueling time, driving range, environmental adaptability and reliability, are analyzed and evaluated by the original data. To comprehensively score the performance of vehicles, a weighted score mechanism is proposed. The weights of 5 factors are decided by the analytic hierarchy process. Finally, 2 vehicles are evaluated using the proposed scoring system.
{"title":"A Comprehensive Performance Evaluation Method for Fuel Cell Commercial Vehicles","authors":"Zhu Yan, Zhenyu Sun, Peng Liu, Chongwen Wang, Naiwu Li","doi":"10.1109/ICNISC54316.2021.00168","DOIUrl":"https://doi.org/10.1109/ICNISC54316.2021.00168","url":null,"abstract":"With the development of fuel cell electric vehicles (FCEVs), the number of FCEVs is increasing constantly. In China, the use of commercial vehicles is promoted vigorously. It is necessary to propose a method to evaluate the comprehensive performance of fuel cell commercial vehicles. During the application of cloud data, operation data of electric vehicles can be stored on the cloud to evaluate comprehensive performance. In this paper, a method based on operation data is proposed to evaluate the comprehensive performance of fuel cell commercial vehicles. 5 indicators, including fueling economy, refueling time, driving range, environmental adaptability and reliability, are analyzed and evaluated by the original data. To comprehensively score the performance of vehicles, a weighted score mechanism is proposed. The weights of 5 factors are decided by the analytic hierarchy process. Finally, 2 vehicles are evaluated using the proposed scoring system.","PeriodicalId":396802,"journal":{"name":"2021 7th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122461630","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 : 2021-07-01DOI: 10.1109/ICNISC54316.2021.00093
Pinge Ai, Yuehua Zhu
This proposal is designed to exam Chinese visiting scholars' Canadian community engagement experience and explore how they interact with the Canadian people in their one-year Canadian University visit. The Canadian community activities the Chinese visiting scholars took part in, their behaviors, their dilemmas, and their perspectives on their Canadian visits will be explored.
{"title":"Chinese Visiting Scholars' Canadian Community Engagement","authors":"Pinge Ai, Yuehua Zhu","doi":"10.1109/ICNISC54316.2021.00093","DOIUrl":"https://doi.org/10.1109/ICNISC54316.2021.00093","url":null,"abstract":"This proposal is designed to exam Chinese visiting scholars' Canadian community engagement experience and explore how they interact with the Canadian people in their one-year Canadian University visit. The Canadian community activities the Chinese visiting scholars took part in, their behaviors, their dilemmas, and their perspectives on their Canadian visits will be explored.","PeriodicalId":396802,"journal":{"name":"2021 7th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132350453","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}
Suggesting personalized tags to the Pumped storage hydropower plants (PSHPs) towards purchase requirements forecasting plays a key role in achieving the smart power grids. However, current tag suggestion solutions only take single sequence into consideration, and predict single label for PSHPs, resulting in suboptimal forecasting accuracy. In this paper, we propose a novel Multi-Sequence Joint Regression (MSJR) model towards the task of PSHP tagging. In particular, MSJR exploits multi-sequence as input for collaborative perception purpose, and a multi-label regression module is built in the MSJR framework to predict tags describing the purchase requirements of PSHPs. Our encouraging experimental results on a real-world dataset, crawled from the ERP system of the State Grid Xin Yuan, validate the superiority of the our MSJR over several existing tagging suggestion methods.
{"title":"Profiling Pumped Storage Power Station via Multi-Sequence Joint Regression","authors":"Wancheng He, Xun Li, Kaitao Zhou, Junheng Huang, Shuang Tang","doi":"10.1109/ICNISC54316.2021.00106","DOIUrl":"https://doi.org/10.1109/ICNISC54316.2021.00106","url":null,"abstract":"Suggesting personalized tags to the Pumped storage hydropower plants (PSHPs) towards purchase requirements forecasting plays a key role in achieving the smart power grids. However, current tag suggestion solutions only take single sequence into consideration, and predict single label for PSHPs, resulting in suboptimal forecasting accuracy. In this paper, we propose a novel Multi-Sequence Joint Regression (MSJR) model towards the task of PSHP tagging. In particular, MSJR exploits multi-sequence as input for collaborative perception purpose, and a multi-label regression module is built in the MSJR framework to predict tags describing the purchase requirements of PSHPs. Our encouraging experimental results on a real-world dataset, crawled from the ERP system of the State Grid Xin Yuan, validate the superiority of the our MSJR over several existing tagging suggestion methods.","PeriodicalId":396802,"journal":{"name":"2021 7th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114056081","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 : 2021-07-01DOI: 10.1109/ICNISC54316.2021.00100
Qianrun Chen
Mobile crowd sensing (MCS) is a computing paradigm that recruits citizens to collect and contribute sensing data from surroundings using their smart device. The incentive mechanisms and task allocation methods are critical parts that affect whether the MSC campaigns could continue gaining sensing data. In this paper, we survey the literature over the period of 2018–2020 from the state-of-the-art of incentive mechanism and task allocation method design in MCS.
{"title":"Incentive Mechanism and Task Allocation Methods for Mobile Crowd Sensing: A Survey","authors":"Qianrun Chen","doi":"10.1109/ICNISC54316.2021.00100","DOIUrl":"https://doi.org/10.1109/ICNISC54316.2021.00100","url":null,"abstract":"Mobile crowd sensing (MCS) is a computing paradigm that recruits citizens to collect and contribute sensing data from surroundings using their smart device. The incentive mechanisms and task allocation methods are critical parts that affect whether the MSC campaigns could continue gaining sensing data. In this paper, we survey the literature over the period of 2018–2020 from the state-of-the-art of incentive mechanism and task allocation method design in MCS.","PeriodicalId":396802,"journal":{"name":"2021 7th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115069277","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 : 2021-07-01DOI: 10.1109/ICNISC54316.2021.00049
Xinghua Su, Sheng Zhan, Zhe Lv, Xiang Gao, Hang Su
For most steel materials, the conventional corrosion method can only observe the martensite structure after transformation. There are some problems in measuring austenite grain size, such as complex operation, difficult to ensure the corrosion quality and so on. Therefore, we use machine learning to identify the original austenite grain boundary according to the martensite structure of conventional corrosion. In this paper, image style transfer is realized by iterative method based on generating model, and austenite grain boundary recognition during martensitic transformation is realized by means of pre training network model vgg19. Firstly, the pre trained deep network vgg19 is used to extract the style and content features of martensite metallographic images. Then, the loss function of style and content is defined, and the gradient descent method is used to iterate step by step to optimize the total loss. Finally, the austenite image with clear grain boundary is obtained by texture segmentation.
{"title":"Automatic Image Recognition of Austenite Grain Boundary in Martensitic Metallography based on Image Style Transfer","authors":"Xinghua Su, Sheng Zhan, Zhe Lv, Xiang Gao, Hang Su","doi":"10.1109/ICNISC54316.2021.00049","DOIUrl":"https://doi.org/10.1109/ICNISC54316.2021.00049","url":null,"abstract":"For most steel materials, the conventional corrosion method can only observe the martensite structure after transformation. There are some problems in measuring austenite grain size, such as complex operation, difficult to ensure the corrosion quality and so on. Therefore, we use machine learning to identify the original austenite grain boundary according to the martensite structure of conventional corrosion. In this paper, image style transfer is realized by iterative method based on generating model, and austenite grain boundary recognition during martensitic transformation is realized by means of pre training network model vgg19. Firstly, the pre trained deep network vgg19 is used to extract the style and content features of martensite metallographic images. Then, the loss function of style and content is defined, and the gradient descent method is used to iterate step by step to optimize the total loss. Finally, the austenite image with clear grain boundary is obtained by texture segmentation.","PeriodicalId":396802,"journal":{"name":"2021 7th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"84 2-3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116592222","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 : 2021-07-01DOI: 10.1109/ICNISC54316.2021.00032
Maofan Wang
With the growth of national strength, China's infrastructure construction capacity is growing. Traffic signal light is the soul of traffic dispatching, which can improve traffic smoothness and ensure pedestrian safety. The complicated traffic network makes China all-round, but at the same time, it is also more urgent to have more intelligent and efficient dispatching capacity. The conventional traffic signal lights are isolated and static, but traffic is complex and random. Thus, the function of traffic dispatching can be achieved, and the dynamic and intelligent management of traffic can be realized.
{"title":"Traffic Signal Control Method Based on A3C Reinforcement Learning","authors":"Maofan Wang","doi":"10.1109/ICNISC54316.2021.00032","DOIUrl":"https://doi.org/10.1109/ICNISC54316.2021.00032","url":null,"abstract":"With the growth of national strength, China's infrastructure construction capacity is growing. Traffic signal light is the soul of traffic dispatching, which can improve traffic smoothness and ensure pedestrian safety. The complicated traffic network makes China all-round, but at the same time, it is also more urgent to have more intelligent and efficient dispatching capacity. The conventional traffic signal lights are isolated and static, but traffic is complex and random. Thus, the function of traffic dispatching can be achieved, and the dynamic and intelligent management of traffic can be realized.","PeriodicalId":396802,"journal":{"name":"2021 7th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115102588","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 : 2021-07-01DOI: 10.1109/ICNISC54316.2021.00132
Pei-hong Zhao, Ling Xu
Based on the non-stationary characteristics of the time-phase modulation signal, in this paper, Choi-Williams distribution time-domain filter method is put forward to solve the problem that the bad aggregation performance of time-domain analysis and poor detection performance of the system in the time-phase modulation signal analysis. First the best input parameter of the time-phase modulation signal is determined by the analyses of cyclo-stationarity and power spectral characteristics and the effect of the phase transition time, transition angle and other parameters on the power spectrum. Second the Choi-Williams transform method is used to get the relationship between the Choi-Williams time-frequency distribution and the phase mutation angle, the window function length, the carrier frequency and other parameters. Theoretical analysis and simulations show that: the time domain filtering based on Choi-Williams time-frequency distribution can convert the phase mutation characteristics of time-phase modulation signal into amplitude information by which we can detect TPM signal. The performance comparison is simulated between the detection method of this paper and the traditional filtering method, and the error rate of method in this paper is 1–2 dB lower than the traditional method.
{"title":"Research on Time Domain Filtering Based on Choi-Williams Distribution about Time-Phase Modulation","authors":"Pei-hong Zhao, Ling Xu","doi":"10.1109/ICNISC54316.2021.00132","DOIUrl":"https://doi.org/10.1109/ICNISC54316.2021.00132","url":null,"abstract":"Based on the non-stationary characteristics of the time-phase modulation signal, in this paper, Choi-Williams distribution time-domain filter method is put forward to solve the problem that the bad aggregation performance of time-domain analysis and poor detection performance of the system in the time-phase modulation signal analysis. First the best input parameter of the time-phase modulation signal is determined by the analyses of cyclo-stationarity and power spectral characteristics and the effect of the phase transition time, transition angle and other parameters on the power spectrum. Second the Choi-Williams transform method is used to get the relationship between the Choi-Williams time-frequency distribution and the phase mutation angle, the window function length, the carrier frequency and other parameters. Theoretical analysis and simulations show that: the time domain filtering based on Choi-Williams time-frequency distribution can convert the phase mutation characteristics of time-phase modulation signal into amplitude information by which we can detect TPM signal. The performance comparison is simulated between the detection method of this paper and the traditional filtering method, and the error rate of method in this paper is 1–2 dB lower than the traditional method.","PeriodicalId":396802,"journal":{"name":"2021 7th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115141496","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 : 2021-07-01DOI: 10.1109/ICNISC54316.2021.00133
Xueru Li, Fanwen Meng, Xuan Zheng
In order to realize the integrated function of sluice management and control, S7-1200 PLC is used as the master control unit and S7-200 smart is used as the slave control unit. The load, opening degree, water level and other data of the sluice are collected through the special instrument, and the data is transmitted to PLC for storage and processing through MODBUS-RTU protocol. MCGS human-computer interface is designed, and data exchange with PLC through Modbus-TCP protocol is implemented, and the efficiency and intelligence of the sluice operation are greatly improved.
{"title":"Automatic Control System of Sluice Based on PLC, MCGS and MODBUS Communication","authors":"Xueru Li, Fanwen Meng, Xuan Zheng","doi":"10.1109/ICNISC54316.2021.00133","DOIUrl":"https://doi.org/10.1109/ICNISC54316.2021.00133","url":null,"abstract":"In order to realize the integrated function of sluice management and control, S7-1200 PLC is used as the master control unit and S7-200 smart is used as the slave control unit. The load, opening degree, water level and other data of the sluice are collected through the special instrument, and the data is transmitted to PLC for storage and processing through MODBUS-RTU protocol. MCGS human-computer interface is designed, and data exchange with PLC through Modbus-TCP protocol is implemented, and the efficiency and intelligence of the sluice operation are greatly improved.","PeriodicalId":396802,"journal":{"name":"2021 7th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121640294","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 : 2021-07-01DOI: 10.1109/ICNISC54316.2021.00092
Xiaozhi Du, Yurong Duan, Wei Huang
Extracting architectural elements from Industry Foundation Classes (IFC) files plays an important role on indoor air quality assessment. However, the traditional methods may extract useless instances and miss some necessary information, which results in poor air quality assessment. To address the above issues, this paper proposes an attribute extraction method for air quality assessment from IFC files, called as IFC-AAE. First the instances of the IFC file are preprocessed to remove the redundancies. Next the entity instances related to air quality assessment are extracted and then classified based on floors. Finally, the attribute information of these entities is extracted according to their reference relationship. The experimental results show that the IFC-AAE method is superior than the previous methods. Compared with the IFC file analyzer, the IFC-AEE method generates fewer invalid data. Compared with the Map-based extract method, the IFC-AEE method has an improvement by 4.78% on the precision rate on average.
{"title":"Attribute Information Extracting Method for Air Quality Assessment of Buildings","authors":"Xiaozhi Du, Yurong Duan, Wei Huang","doi":"10.1109/ICNISC54316.2021.00092","DOIUrl":"https://doi.org/10.1109/ICNISC54316.2021.00092","url":null,"abstract":"Extracting architectural elements from Industry Foundation Classes (IFC) files plays an important role on indoor air quality assessment. However, the traditional methods may extract useless instances and miss some necessary information, which results in poor air quality assessment. To address the above issues, this paper proposes an attribute extraction method for air quality assessment from IFC files, called as IFC-AAE. First the instances of the IFC file are preprocessed to remove the redundancies. Next the entity instances related to air quality assessment are extracted and then classified based on floors. Finally, the attribute information of these entities is extracted according to their reference relationship. The experimental results show that the IFC-AAE method is superior than the previous methods. Compared with the IFC file analyzer, the IFC-AEE method generates fewer invalid data. Compared with the Map-based extract method, the IFC-AEE method has an improvement by 4.78% on the precision rate on average.","PeriodicalId":396802,"journal":{"name":"2021 7th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122542733","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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