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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
Pub Date : 2021-06-01 DOI: 10.1109/ICCEA53728.2021.00052
Weiyi Wang, Dawei Zuo, Meizheng Zhu
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.
为了增强专题地图的美感,提高地图配色的智能化水平,本文根据专题地图的实际需求,结合鹅群优化算法,设计了一种专题地图配色的智能设计优化算法。其基本思路是:以地图类型和用户期望为指导,根据色彩心理学和Munsell的色彩和谐理论,选择初始颜色作为种群中的粒子,然后使用鹅群优化算法更新种群,并使用Munsell Spencer的色彩和谐理论和美丽公式作为适应度函数进行评价和优化,从而得到地图配色方案。最后,通过实验对算法进行了验证。
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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
Pub Date : 2021-06-01 DOI: 10.1109/ICCEA53728.2021.00008
Ning Jia, Xiaoyi Gong, Qiao Zhang
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.
近年来,风格迁移的应用越来越广泛。传统的基于深度学习的风格迁移网络往往存在图像失真、细节信息丢失、部分内容消失、迁移错误等问题。本文提出的基于深度学习的风格迁移网络就是为了解决这些问题。该方法利用图像边缘信息融合和语义分割技术对迁移前后的图像结构进行约束,使转换后的图像保持结构的一致性和完整性。我们已经验证了该方法可以在大多数场景下成功地抑制图像转换失真,并且可以产生良好的效果。
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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
Pub Date : 2021-06-01 DOI: 10.1109/ICCEA53728.2021.00040
Feng Zhang, Haihu Li, Haibing Li, Cheng Luo
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.
提出了一种海洋观测平台多源数据的时间同步方法,实现了海洋观测平台多源传感器数据在时间维度上的融合。在该方法中,使用计时器生成一个独立运行的高分辨率本地时钟系统。结合GNSS接收机产生的通用时间和脉冲每秒信号,将本地时钟系统与通用时间同步,输出稳定、可靠、可持续、高分辨率的传感器时间。该方法已在海试中得到应用,取得了良好的效果。
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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
Pub Date : 2021-06-01 DOI: 10.1109/ICCEA53728.2021.00053
Xilin Zhang, Jiaqi Wang, Zhenhong Wan, Zuying Luo
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.
教师用语言来指导课堂教学活动。教师言语的意向自动分类有助于课堂教学过程的定量分析和评价。利用真实中学语文和数学课堂教学中的教师言语构建语料库,训练深度卷积神经网络(CNN)对教师言语进行分类,识别教师主导的教学活动、提问活动和课堂管理活动三种类型。实验数据表明:(1)与经典浅层网络分类算法SVM相比,CNN的分类准确率提高了10%,达到95.5%,能够满足课堂教学过程自动分析的准确率要求;(2)利用CNN分类算法对课堂教学行为进行分类和统计分析,可以为课堂分析和研究提供有用的思路。
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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
Pub Date : 2021-06-01 DOI: 10.1109/ICCEA53728.2021.00067
Zhiqiang Fan, Jiang Cao, Lanlan Gao, Mengyuan Zou, Zhiang Xu
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.
为了促进大型复杂系统的架构开发,我们提出了一种架构工程方法,并定义了架构工程的七个核心(即机会、利益相关者、需求、架构、团队、工作和工作方式),这些都是在开发架构过程中必须考虑的。每个内核都有五到六种不同的状态,这些状态可以指示架构开发的进度和健康状况。为了进一步提高所定义的7个内核及其36个状态在架构开发中的实用性,根据我们在实践中的工程经验,提出了一个参考指南,其中包含100多个项目,有助于检查内核状态并推动它们向前发展。利用参考指南,对一个复杂的业务信息系统进行了应用程序的体系结构开发。结果表明,所提出的指南可以有效地帮助建筑工程师确定和推动建筑发展的状态。架构开发可以清晰、及时、顺利地进行。此外,所有的团队成员都能很好地合作。
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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
Pub Date : 2021-06-01 DOI: 10.1109/ICCEA53728.2021.00016
H. Tian, Yanlong Li
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.
为解决患者信息集中、篡改、存储不完整、隐私等问题,提出了一种基于区块链“双链”的医疗防伪溯源系统。该系统解决了单链应用可扩展性差、吞吐量低的问题,将可追溯信息和消费者信息分开存储,利用区块链的去中心化特性和智能合约的链上代码,实现了不可信环境下的访问控制,有效保护了消费者隐私数据。该系统是在超级账本(Hyperledger)的Fabric区块链平台上开发的。系统环境配备了四个组织:制药企业、经销商、医院和消费者。链码采用Java语言开发,客户端程序采用Node.js编写,查询请求采用链码中的药品追溯功能发起。最终,通过证书认证的用户账号可以实现对网页中药品信息的查询。区块链的数据难以篡改,时间戳和交易追溯可以很好地应用到药品防伪追溯系统中,使得系统的追溯功能更加完善,消费者可以获得包括药品生产信息、物流信息、使用信息在内的所有追溯信息。
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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
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
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.
知识图谱技术近年来发展迅速,广泛应用于智能语义搜索、智能深度问答、移动个人助理等各种场景。然而,电力营销服务面临着服务响应效率低、客户体验差、在线服务实时性差等诸多问题。因此,有必要设计一个电力营销知识图谱平台,整合电力营销领域分散的知识点,促进知识利用,改善内部和外部服务,增强主动感知和服务功能/能力。本文在建立Neo4j动力营销图谱数据库的基础上,进一步将规则、字典和模型相结合进行知识提取,构建了具有知识管理应用和提取服务功能的知识图谱平台应用架构。期望从用户表达的多元化问题中准确识别出查询的主体,并从电力营销知识图谱中找到答案。
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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
Pub Date : 2021-06-01 DOI: 10.1109/ICCEA53728.2021.00107
Zhiwei Liu
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.
随着高校数字化校园的发展,校园网络安全系统也面临着一定的问题。如何构建完善的网络安全体系,防范潜在风险,帮助高校做好防范,在发生网络安全事件时及时防范至关重要。针对校园网接入互联网,开展网络安全实打实的网络攻防,发现安全隐患和漏洞,可以有效提高网络安全防护能力,培养安全人才。在此背景下,本文探讨了基于实际网络攻防的校园网安全体系建设方案,并介绍了相关技术。
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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
Pub Date : 2021-06-01 DOI: 10.1109/ICCEA53728.2021.00095
Yongbing Xiao, Supeng Liang, J. Peng, Zhijie Huang, Yan Wang, Jing Wang
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.
在文本挖掘任务中,分布式表示通常用作输入特征。以往的研究已经显示了它在编码语义方面的潜力。通常,存在静态和动态两种表示方法,即它们分别是与上下文无关的和与上下文相关的。许多研究表明,基于上下文的表示显著提高了自然语言处理领域的性能。因此,在本文中,我们利用情境化表征来识别生物医学实体,并在实体层面评估BC2GM和bc5cdr -疾病数据集的结果。结果表明,我们获得的f1分数分别为75.16%和75.97%,比无上下文表示分别提高了2.54%和3.96%。结果表明,基于情境化表示的实体识别方法具有较好的应用前景。
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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
Pub Date : 2021-06-01 DOI: 10.1109/ICCEA53728.2021.00101
Yang Liu, Wei Zhong, Wenzheng Wang, Qingxing Cao, Kaiwen Luo
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%.
为了识别禁止交通标志,本文在分析禁止交通标志颜色占用情况的基础上,提出了一种基于梯度直方图(HOG)和支持向量机(SVM)特征的禁止交通标志识别方法。该识别方法主要分为三个步骤:第一步是图像预处理,实现图像的尺寸归一化处理、灰度处理和Gamma校正;第二步是HOG特征提取;第三步是基于支持向量机的禁止交通标志识别。在禁止交通标志分类器的设计与实现中,利用线性变换后的禁止交通标志图像训练来训练42个二元分类器,然后基于这42个分类器构建并实现禁止交通标志分类器。最后,利用自建数据集对禁止交通标志识别方法进行测试分析,总体识别准确率为90.2%。
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引用次数: 1
期刊
2021 International Conference on Computer Engineering and Application (ICCEA)
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