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2021 International Conference on Computer Engineering and Application (ICCEA)最新文献

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Thematic Map Color Matching Design Based On Geese Swarm Optimization Algorithm 基于鹅群优化算法的专题地图色彩匹配设计
2021 International Conference on Computer Engineering and Application (ICCEA) Pub Date : 2021-06-01 DOI: 10.1109/ICCEA53728.2021.00052
Weiyi Wang, Dawei Zuo, Meizheng Zhu
{"title":"Thematic Map Color Matching Design Based On Geese Swarm Optimization Algorithm","authors":"Weiyi Wang, Dawei Zuo, Meizheng Zhu","doi":"10.1109/ICCEA53728.2021.00052","DOIUrl":"https://doi.org/10.1109/ICCEA53728.2021.00052","url":null,"abstract":"In order to enhance the beauty of thematic map and improve the intelligent level of map color matching, this paper designs an intelligent design optimization algorithm of thematic map color based on the actual needs of thematic map and geese swarm optimization algorithm. The basic idea is: guided by map types and user expectations, according to color psychology and Munsell’s color harmony theory, the initial color is selected as the particles in the population, and then the geese swarm optimization algorithm is used to update the population, and the Munsell Spencer’s color harmony theory and beauty formula are used as fitness functions for evaluation and optimization, so as to get the map color scheme. Finally, the algorithm is demonstrated by experiments.","PeriodicalId":325790,"journal":{"name":"2021 International Conference on Computer Engineering and Application (ICCEA)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117190413","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}
引用次数: 0
Improvement of Style Transfer Algorithm based on Neural Network 基于神经网络的风格迁移算法改进
2021 International Conference on Computer Engineering and Application (ICCEA) Pub Date : 2021-06-01 DOI: 10.1109/ICCEA53728.2021.00008
Ning Jia, Xiaoyi Gong, Qiao Zhang
{"title":"Improvement of Style Transfer Algorithm based on Neural Network","authors":"Ning Jia, Xiaoyi Gong, Qiao Zhang","doi":"10.1109/ICCEA53728.2021.00008","DOIUrl":"https://doi.org/10.1109/ICCEA53728.2021.00008","url":null,"abstract":"In recent years, the application of style transfer has become more and more widespread. Traditional deep learning-based style transfer networks often have problems such as image distortion, loss of detailed information, partial content disappearance, and transfer errors. The style transfer network based on deep learning that we propose in this article is aimed at dealing with these problems. Our method uses image edge information fusion and semantic segmentation technology to constrain the image structure before and after the migration, so that the converted image maintains structural consistency and integrity. We have verified that this method can successfully suppress image conversion distortion in most scenarios, and can generate good results.","PeriodicalId":325790,"journal":{"name":"2021 International Conference on Computer Engineering and Application (ICCEA)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121402058","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}
引用次数: 1
A time synchronization method of multi-source data for ocean-based observation platform 海洋观测平台多源数据时间同步方法
2021 International Conference on Computer Engineering and Application (ICCEA) Pub Date : 2021-06-01 DOI: 10.1109/ICCEA53728.2021.00040
Feng Zhang, Haihu Li, Haibing Li, Cheng Luo
{"title":"A time synchronization method of multi-source data for ocean-based observation platform","authors":"Feng Zhang, Haihu Li, Haibing Li, Cheng Luo","doi":"10.1109/ICCEA53728.2021.00040","DOIUrl":"https://doi.org/10.1109/ICCEA53728.2021.00040","url":null,"abstract":"In this paper, a time synchronization method of multi-source data of ocean-based observation platform is proposed, which realizes the fusion of multi-source sensor data of ocean-based observation platform in time dimension. In this method, a timer is used to generate a high resolution local clock system which operates independently. Combined with the universal time and pulse-per-second signal generated by the GNSS receiver, the local clock system and universal time are synchronized to output a stable, reliable, sustainable and high resolution sensor time. This method has been applied in the sea trial and achieved good results.","PeriodicalId":325790,"journal":{"name":"2021 International Conference on Computer Engineering and Application (ICCEA)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121993544","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}
引用次数: 0
Classification of Classroom Teachers’ Speech Intention Based on Deep Learning 基于深度学习的课堂教师言语意图分类
2021 International Conference on Computer Engineering and Application (ICCEA) Pub Date : 2021-06-01 DOI: 10.1109/ICCEA53728.2021.00053
Xilin Zhang, Jiaqi Wang, Zhenhong Wan, Zuying Luo
{"title":"Classification of Classroom Teachers’ Speech Intention Based on Deep Learning","authors":"Xilin Zhang, Jiaqi Wang, Zhenhong Wan, Zuying Luo","doi":"10.1109/ICCEA53728.2021.00053","DOIUrl":"https://doi.org/10.1109/ICCEA53728.2021.00053","url":null,"abstract":"Teachers use language to guide classroom teaching activities. The automatic classification of teacher speech according to intention is helpful for the quantitative analysis and evaluation of classroom teaching process. Teachers’ speech in real classroom teaching of middle school Chinese and mathematics is used to construct a corpus, and deep convolutional neural network (CNN) is trained to classify teachers’ speech and identify three kinds of teacher-led teaching activities, including teaching, questioning and classroom management. The experimental data show that:(1) compared with the classical shallow network classification algorithm SVM, the classification accuracy of CNN is increased by 10% to 95.5%, which can meet the requirements for accuracy of automatic analysis of classroom teaching process; (2) Classifying and statistical analysis of classroom teaching behaviors by using CNN classification algorithm can provide useful ideas for classroom analysis and research.","PeriodicalId":325790,"journal":{"name":"2021 International Conference on Computer Engineering and Application (ICCEA)","volume":"761 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123281128","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}
引用次数: 0
A Checking Method of Architecture Engineering Kernel States for Large-scale and Complex Information System 大型复杂信息系统的体系结构工程核状态检测方法
2021 International Conference on Computer Engineering and Application (ICCEA) Pub Date : 2021-06-01 DOI: 10.1109/ICCEA53728.2021.00067
Zhiqiang Fan, Jiang Cao, Lanlan Gao, Mengyuan Zou, Zhiang Xu
{"title":"A Checking Method of Architecture Engineering Kernel States for Large-scale and Complex Information System","authors":"Zhiqiang Fan, Jiang Cao, Lanlan Gao, Mengyuan Zou, Zhiang Xu","doi":"10.1109/ICCEA53728.2021.00067","DOIUrl":"https://doi.org/10.1109/ICCEA53728.2021.00067","url":null,"abstract":"To facilitate architecture development of largescale and complex systems, we have proposed an architecture engineering methodology and defined seven kernels of architecture engineering (i.e., opportunity, Stakeholder, Need, Architecture, Team, Work and Way-of-Working) which must be considered during the process of developing an architecture. Each kernel has five or six different states that can indicate the progress and health of architecture development. To further improve practicability of the defined seven kernels and their 36 states in architecture development, a reference guide is suggested based on our engineering experience in practice, which contains more than 100 items helping to check kernel states and move them forward. Using the reference guide, we conducted an application of architecture development of a complex business information system. Results show that the proposed guide can be effectively used to help architecture engineers to determine and push on the state of architecture development. Architecture development can be proceeded clearly, timely and smoothly. Moreover, all the team members can work well together.","PeriodicalId":325790,"journal":{"name":"2021 International Conference on Computer Engineering and Application (ICCEA)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131765725","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}
引用次数: 0
Pharmaceutical anti-counterfeiting traceability system based on block chain double chain 基于区块链双链的药品防伪溯源系统
2021 International Conference on Computer Engineering and Application (ICCEA) Pub Date : 2021-06-01 DOI: 10.1109/ICCEA53728.2021.00016
H. Tian, Yanlong Li
{"title":"Pharmaceutical anti-counterfeiting traceability system based on block chain double chain","authors":"H. Tian, Yanlong Li","doi":"10.1109/ICCEA53728.2021.00016","DOIUrl":"https://doi.org/10.1109/ICCEA53728.2021.00016","url":null,"abstract":"In order to solve the problems of centralization, tampering, incomplete storage and privacy of patient information, a medical anti-counterfeiting traceability system based on block chain “double chain” is proposed. The system solves the problem of poor expansibility and low throughput in single chain applications, stores traceability information and consumer information separately, and realizes access control in untrusted environment by using the decentralization characteristic of block chain and the on-chain code of intelligent contract, which effectively protects consumer privacy data. The system is developed on the Fabric block chain platform of super account book (Hyperledger). The system environment is equipped with four organizations: pharmaceutical manufacturer, dealer, hospital and consumer. The chain code is developed by Java language, the client program is written by using Node.js, and the query request is initiated with the drug traceability function in the chain code. Ultimately, the certificate-certified user account can achieve drug information in the web page query. The data of block chain is difficult to tamper with, time stamp and transaction traceability can be well applied to the pharmaceutical anti-counterfeiting traceability system, which makes the traceability function of the system more perfect, and consumers can get all traceability information including drug production information, logistics information and use information.","PeriodicalId":325790,"journal":{"name":"2021 International Conference on Computer Engineering and Application (ICCEA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131793420","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}
引用次数: 0
Design and Implementation of Knowledge Graph Platform of Power Marketing 电力营销知识图谱平台的设计与实现
2021 International Conference on Computer Engineering and Application (ICCEA) Pub Date : 2021-06-01 DOI: 10.1109/ICCEA53728.2021.00065
Wei Meng, Dongning Zhang, Tengxuan Guo, Zhenguo Zong, Yijuan Liu, Yanmei Wang, Jing Li, Weiyi Zhu
{"title":"Design and Implementation of Knowledge Graph Platform of Power Marketing","authors":"Wei Meng, Dongning Zhang, Tengxuan Guo, Zhenguo Zong, Yijuan Liu, Yanmei Wang, Jing Li, Weiyi Zhu","doi":"10.1109/ICCEA53728.2021.00065","DOIUrl":"https://doi.org/10.1109/ICCEA53728.2021.00065","url":null,"abstract":"Knowledge graph technology has developed rapidly in recent years, and it is widely used in various scenarios, such as intelligent semantic search, intelligent in-depth question answering and mobile personal assistants. However, power marketing services face many problems such as low service response efficiency, poor customer experience and a lack of real-time online services. Thus, it is necessary to design a power marketing knowledge graph platform that can integrate scattered knowledge points in the power marketing field, promote knowledge utilization, improve internal and external service, and strengthen active perception and service functions/capabilities. Based on the establishment of the Neo4j power marketing graph database, this paper further combined rules, dictionaries and models to extract knowledge, and builds an application architecture of knowledge graph platform with knowledge management applications and extraction service functions. It expected to accurately identify the subject of the inquiry from the diversified questions expressed by users, and the answer can be found from the power marketing knowledge graph.","PeriodicalId":325790,"journal":{"name":"2021 International Conference on Computer Engineering and Application (ICCEA)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131803609","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}
引用次数: 2
The construction of campus network security system based on the actual network offensive and defensive environment 校园网安全体系的构建基于实际的网络攻防环境
2021 International Conference on Computer Engineering and Application (ICCEA) Pub Date : 2021-06-01 DOI: 10.1109/ICCEA53728.2021.00107
Zhiwei Liu
{"title":"The construction of campus network security system based on the actual network offensive and defensive environment","authors":"Zhiwei Liu","doi":"10.1109/ICCEA53728.2021.00107","DOIUrl":"https://doi.org/10.1109/ICCEA53728.2021.00107","url":null,"abstract":"With the development of digital campuses in universities, campus network security systems are also facing certain problems. How to build a complete network security system, prevent potential risks, and help colleges and universities take precautions, and timely prevention in the event of a network security incident is crucial. Aiming at the campus network connected to the Internet, carrying out network security real network attack and defense, discovering security risks and loopholes, can effectively improve network security protection capabilities and train security personnel. In this context, this article explores the campus network security system construction plan based on the actual network attack and defense, and introduces related technologies.","PeriodicalId":325790,"journal":{"name":"2021 International Conference on Computer Engineering and Application (ICCEA)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128163469","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}
引用次数: 0
Using Contextualized Representations For Biomedical Entity Recognition 在生物医学实体识别中使用情境化表示
2021 International Conference on Computer Engineering and Application (ICCEA) Pub Date : 2021-06-01 DOI: 10.1109/ICCEA53728.2021.00095
Yongbing Xiao, Supeng Liang, J. Peng, Zhijie Huang, Yan Wang, Jing Wang
{"title":"Using Contextualized Representations For Biomedical Entity Recognition","authors":"Yongbing Xiao, Supeng Liang, J. Peng, Zhijie Huang, Yan Wang, Jing Wang","doi":"10.1109/ICCEA53728.2021.00095","DOIUrl":"https://doi.org/10.1109/ICCEA53728.2021.00095","url":null,"abstract":"Distributed representations are usually used as input features in text mining tasks. Previous works have shown its potential in encoding semantics. Generally, there existing two representation methods namely static and dynamic, which means they are context-free and context-dependent respectively. Many works have demonstrated that context based representations significantly improved performance in natural language processing field. Therefore, in this paper, we utilize contextualized representations to recognize biomedical entities and evaluate the results at entity-level on BC2GM and BC5CDR-disease datasets. Results show that we obtain a F1-score of 75.16% and 75.97%, which improving 2.54% and 3.96% respectively compared with context-free representations. It indicates that the method based on contextualized representations is promising for entity recognition tasks.","PeriodicalId":325790,"journal":{"name":"2021 International Conference on Computer Engineering and Application (ICCEA)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128687605","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}
引用次数: 0
A Method for Recognizing Prohibition Traffic Sign Based on HOG-SVM 基于HOG-SVM的禁止交通标志识别方法
2021 International Conference on Computer Engineering and Application (ICCEA) Pub Date : 2021-06-01 DOI: 10.1109/ICCEA53728.2021.00101
Yang Liu, Wei Zhong, Wenzheng Wang, Qingxing Cao, Kaiwen Luo
{"title":"A Method for Recognizing Prohibition Traffic Sign Based on HOG-SVM","authors":"Yang Liu, Wei Zhong, Wenzheng Wang, Qingxing Cao, Kaiwen Luo","doi":"10.1109/ICCEA53728.2021.00101","DOIUrl":"https://doi.org/10.1109/ICCEA53728.2021.00101","url":null,"abstract":"In order to recognize prohibition traffic signs, based on the analysis of the color occupancy of prohibition traffic signs, this paper proposes a method to recognize the prohibition traffic signs based on the feature of Histogram of Oriented Gradient (HOG) and Support Vector Machine (SVM). The recognition method is mainly divided into three steps: the first step is image preprocessing, which realizes the size normalization processing, grayscale processing and Gamma correction of the image; the second step is the feature extraction of HOG; the third step is the recognition of prohibition traffic signs based on SVM. In the design and implementation of the prohibition traffic sign classifier, the prohibition traffic sign image training after linear transformation is used to train 42 binary classifiers, and then based on these 42 classifiers, the prohibition traffic sign classifier is constructed and implemented. Finally, the self-built data set was used to test and analyze the prohibition traffic sign recognition method, and the overall recognition accuracy rate was 90.2%.","PeriodicalId":325790,"journal":{"name":"2021 International Conference on Computer Engineering and Application (ICCEA)","volume":"2017 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125649351","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}
引用次数: 1
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