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

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Eye Movement Events Detection with KNN-GA and Prior Knowledge 基于KNN-GA和先验知识的眼动事件检测
2021 International Conference on Computer Engineering and Application (ICCEA) Pub Date : 2021-06-01 DOI: 10.1109/ICCEA53728.2021.00098
Zheng Zhong, Hongping Fang, Hanyuan Zhang, Shiqian Wu
{"title":"Eye Movement Events Detection with KNN-GA and Prior Knowledge","authors":"Zheng Zhong, Hongping Fang, Hanyuan Zhang, Shiqian Wu","doi":"10.1109/ICCEA53728.2021.00098","DOIUrl":"https://doi.org/10.1109/ICCEA53728.2021.00098","url":null,"abstract":"Aiming at the problems of difficulty in threshold adjustment and low detection accuracy and efficiency, an eye movement event detection method combining K-Nearest Neighbor and genetic algorithm (KNN-GA) and prior knowledge is proposed. Firstly, design the absolute amplitude feature of eye movement to describe the eye movement event characteristics of PSOs, and then the KNN is used to pre-detect eye movement events based on the minimum feature subset generated by genetic algorithm; After that, screening rules based on prior knowledge are ted to further adjust and optimize the pre-detection results. Experimental results show that this algorithm avoids threshold adjustment, and its execution efficiency is equivalent to simple IVT and NH, meanwhile the detection accuracy of fixation, saccade, and PSOs are increased by at least 3.4%, 4.7%, and 12.7%, respectively, and the detection performance is robust under different noise levels.","PeriodicalId":325790,"journal":{"name":"2021 International Conference on Computer Engineering and Application (ICCEA)","volume":"62 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":"124566259","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 Test on Acoustic Device for Actively Measuring Underwater Short Distance with High-Precision 水下短距离高精度主动测量声学装置的设计与试验
2021 International Conference on Computer Engineering and Application (ICCEA) Pub Date : 2021-06-01 DOI: 10.1109/ICCEA53728.2021.00079
Li Bo, Shan Shan
{"title":"Design and Test on Acoustic Device for Actively Measuring Underwater Short Distance with High-Precision","authors":"Li Bo, Shan Shan","doi":"10.1109/ICCEA53728.2021.00079","DOIUrl":"https://doi.org/10.1109/ICCEA53728.2021.00079","url":null,"abstract":"For short-distance ranging and positioning of moving targets in water, a design scheme was proposed for active ranging acoustic device based on DSP as the signal processor, and the design ideas of each hardware component were described. The experimental test results of the active ranging acoustic device sample in pool and lake prove that the system is compact in structure, flexible in operation, and has high-precision ranging capabilities, which can meet the needs for short-range ranging applications of moving targets in the water.","PeriodicalId":325790,"journal":{"name":"2021 International Conference on Computer Engineering and Application (ICCEA)","volume":"54 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":"114668324","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
Quad-rotor UAV Audio Recognition Based on Mel Spectrum with Binaural Representation and CNN 基于双耳表示Mel谱和CNN的四旋翼无人机音频识别
2021 International Conference on Computer Engineering and Application (ICCEA) Pub Date : 2021-06-01 DOI: 10.1109/ICCEA53728.2021.00063
Luo Jiqing, Fang Husheng, Yin Qin, Zhou Chunhua
{"title":"Quad-rotor UAV Audio Recognition Based on Mel Spectrum with Binaural Representation and CNN","authors":"Luo Jiqing, Fang Husheng, Yin Qin, Zhou Chunhua","doi":"10.1109/ICCEA53728.2021.00063","DOIUrl":"https://doi.org/10.1109/ICCEA53728.2021.00063","url":null,"abstract":"With the wide application of UAV in civil and military fields, more and more attention has been paid to the accurate detection for UAV. In this paper, the noise of UAV is taken as the research object, and the audio recognition technology based on Mel spectrum with binaural representation and CNN is used for multi-UAV recognition. Firstly, the noise of UAV, bird chirp, traffic noise and other environmental noises are collected, and the audio dataset of UAV audio is made after preprocessing. Secondly, the Mel spectrum with binaural representation is proposed for audio feature extracting, and one-dimensional audio is converted to four channel spectrum with rich feature. Finally, designed deep CNN is trained by spectrum map for UAV audio recognition. Experimental results show that the proposed method is superior and the average accuracy is 99.24%.","PeriodicalId":325790,"journal":{"name":"2021 International Conference on Computer Engineering and Application (ICCEA)","volume":"70 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":"127387074","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
Analysis of Block Chain Technology Applying in Digital Archives 区块链技术在数字档案中的应用分析
2021 International Conference on Computer Engineering and Application (ICCEA) Pub Date : 2021-06-01 DOI: 10.1109/ICCEA53728.2021.00057
Cui Xianghong
{"title":"Analysis of Block Chain Technology Applying in Digital Archives","authors":"Cui Xianghong","doi":"10.1109/ICCEA53728.2021.00057","DOIUrl":"https://doi.org/10.1109/ICCEA53728.2021.00057","url":null,"abstract":"After archives are digitized, the efficiency of their information value mining depends on the information technology used in the open sharing of digital archives. The article discusses the risks and technical requirements of open sharing of digital archives, and analyses the fit between block-chain technology and the open sharing needs of digital archives from seven dimensions, and proposes that block chain technology should be selected in digital archives based on the seven-dimensional needs. The application model of open sharing points out that the needs of “subject rights” and the “impossible triangle paradox” are the evolution direction of open sharing of digital archives based on block chain.","PeriodicalId":325790,"journal":{"name":"2021 International Conference on Computer Engineering and Application (ICCEA)","volume":"93 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":"129015628","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
Radar Signal Modulation Recognition Based on Bispectrum Features and Deep learning 基于双谱特征和深度学习的雷达信号调制识别
2021 International Conference on Computer Engineering and Application (ICCEA) Pub Date : 2021-06-01 DOI: 10.1109/ICCEA53728.2021.00020
Zeyu Dong, Fengrong Lv, T. Wan, Kaili Jiang, Xueli Fang, Lei Zhang
{"title":"Radar Signal Modulation Recognition Based on Bispectrum Features and Deep learning","authors":"Zeyu Dong, Fengrong Lv, T. Wan, Kaili Jiang, Xueli Fang, Lei Zhang","doi":"10.1109/ICCEA53728.2021.00020","DOIUrl":"https://doi.org/10.1109/ICCEA53728.2021.00020","url":null,"abstract":"Signal bispectral transformation can not only suppress the influence of Gaussian white noise on signal modulation recognition, but also retain the signal amplitude and phase information. It is also used to extract the non-linear characteristics. Compared with other high-order spectra, bispectrum has a simple processing flow. However, the direct use of all bispectrum as signal features will lead to two-dimensional template matching, causing lots of calculations. Converting two-dimensional bispectrum into one-dimensional sequence, for example, extracting slice information of bispectrum, or using integral bispectrum apparently reduce the amount of data to be processed while retaining part of the bispectrum information. We input the extracted bispectral transformation of radar signals into the neural network to realize modulation recognition. The simulations validate our conclusions that our proposed methods still have a high recognition probability while SNR is low.","PeriodicalId":325790,"journal":{"name":"2021 International Conference on Computer Engineering and Application (ICCEA)","volume":"167 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":"132036641","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: 3
Support vector machine prediction model based on fractional particle swarm algorithm 基于分数粒子群算法的支持向量机预测模型
2021 International Conference on Computer Engineering and Application (ICCEA) Pub Date : 2021-06-01 DOI: 10.1109/ICCEA53728.2021.00042
Jing Li, Chunna Zhao
{"title":"Support vector machine prediction model based on fractional particle swarm algorithm","authors":"Jing Li, Chunna Zhao","doi":"10.1109/ICCEA53728.2021.00042","DOIUrl":"https://doi.org/10.1109/ICCEA53728.2021.00042","url":null,"abstract":"The support vector machine algorithm is widely used to solve nonlinear classification problems with its good generalization ability. This paper mainly explores the parameter optimization problem of the algorithm in detail. The method is proposing an improved fractional particle swarm algorithm, that is, set a linear decrease strategy for the inertia weight, and randomly adopt the single point mutation operation of the genetic algorithm during the particle update process. The improved particle swarm algorithm is utilized to optimize the parameters of the support vector machine to build a heart disease prediction model. The new algorithm can effectively avoid falling into the local optimal solution. The convergence speed, stability, and accuracy of the algorithm have been significantly improved, and further improving the ability to find the global optimal solution. The simulation experiment also proved the improvement of the diagnostic efficiency and accuracy of the predictive model. It significantly reduces the diagnosis errors and makes the prediction results have certain practical significance.","PeriodicalId":325790,"journal":{"name":"2021 International Conference on Computer Engineering and Application (ICCEA)","volume":"179 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":"122940328","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
Automatic annotation algorithm based on sliding window moment feature matching 基于滑动窗口矩特征匹配的自动标注算法
2021 International Conference on Computer Engineering and Application (ICCEA) Pub Date : 2021-06-01 DOI: 10.1109/ICCEA53728.2021.00050
Huang Liang, Fengxiang Wang, Luo Bing, Deying Yu, Jiuhe Wang
{"title":"Automatic annotation algorithm based on sliding window moment feature matching","authors":"Huang Liang, Fengxiang Wang, Luo Bing, Deying Yu, Jiuhe Wang","doi":"10.1109/ICCEA53728.2021.00050","DOIUrl":"https://doi.org/10.1109/ICCEA53728.2021.00050","url":null,"abstract":"In the era of big data, detecting and identifying targets based on massive data sources is a very important task. At present, most of the labeling of large-scale image data relies on traditional manual labeling methods, which takes a long time and is inefficient. In order to efficiently construct large-scale maritime target image data sets, we propose an automatic annotation algorithms, namely: automatic annotation algorithm based on moment features. Experiments were conducted to verify the accuracy of the automatic annotation algorithm to annotate image data, and finally proved that the two image automatic annotation algorithms proposed by us can construct the marine target image data set more efficiently, and provide good data support for downstream tasks.","PeriodicalId":325790,"journal":{"name":"2021 International Conference on Computer Engineering and Application (ICCEA)","volume":"130 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":"132618943","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
Research and Application of Blockchain Technology in the Distribution of Unbalanced Funds in the Spot Market 区块链技术在现货市场非均衡资金分配中的研究与应用
2021 International Conference on Computer Engineering and Application (ICCEA) Pub Date : 2021-06-01 DOI: 10.1109/ICCEA53728.2021.00058
Lei Xie, Haijing Zhang, Xiaohui Liu, K. Guo, Hui Zhang, Linlin Yang, Xiaobin Sun, Suoyue Wang, Yan Feng, Jialu Zhang
{"title":"Research and Application of Blockchain Technology in the Distribution of Unbalanced Funds in the Spot Market","authors":"Lei Xie, Haijing Zhang, Xiaohui Liu, K. Guo, Hui Zhang, Linlin Yang, Xiaobin Sun, Suoyue Wang, Yan Feng, Jialu Zhang","doi":"10.1109/ICCEA53728.2021.00058","DOIUrl":"https://doi.org/10.1109/ICCEA53728.2021.00058","url":null,"abstract":"In the third power adjustment operation and trial settlement in May 2020, the spot pilot project in Shandong Province generated nearly 100 million yuan of “unbalanced funds” in just four days, which caused high attention in the “power transformation circle”. In October, Shandong Provincial Energy Bureau issued the Notice on Improving the Settlement Work of the Third Electric Power Spot Market Settlement Trial Operation in Shandong Province, announced the allocation results of unbalanced funds of the third power adjustment operation and trial settlement in May 2020, and the unbalanced funds of external electricity allocation accounted for 53.42%. This paper plans to carry out the following research contents: the first is to research the causes of the unbalanced funds, analyze the difficulties existing in the coordination between the “non-market units” and the spot market in Shandong Province, and put forward solutions. The second is to study the application requirements and technical route of block chain technology in the unbalanced capital allocation in the spot market, and build the unbalanced capital allocation algorithm model of a specific power generation enterprise, so as to provide technical endorsement for the unbalanced capital allocation of power generation enterprises. The third is to design a set of unbalanced fund allocation mechanism suitable for the spot market of Shandong Province, and put forward specific measures to promote and apply.","PeriodicalId":325790,"journal":{"name":"2021 International Conference on Computer Engineering and Application (ICCEA)","volume":"44 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":"115930176","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
Research on Security Strategy of Power Internet of Things Devices Based on Zero-Trust 基于零信任的电力物联网设备安全策略研究
2021 International Conference on Computer Engineering and Application (ICCEA) Pub Date : 2021-06-01 DOI: 10.1109/ICCEA53728.2021.00023
Kehe Wu, Jin Shi, Zhimin Guo, Zheng Zhang, Junfei Cai
{"title":"Research on Security Strategy of Power Internet of Things Devices Based on Zero-Trust","authors":"Kehe Wu, Jin Shi, Zhimin Guo, Zheng Zhang, Junfei Cai","doi":"10.1109/ICCEA53728.2021.00023","DOIUrl":"https://doi.org/10.1109/ICCEA53728.2021.00023","url":null,"abstract":"In order to guarantee the normal operation of the power Internet of things devices, the zero-trust idea was used for studying the security protection strategies of devices from four aspects: user authentication, equipment trust, application integrity and flow baselines. Firstly, device trust is constructed based on device portrait; then, verification of device application integrity based on MD5 message digest algorithm to achieve device application trustworthiness. Next, the terminal network traffic baselines are mined from OpenFlow, a southbound protocol in SDN. Finally, according to the dynamic user trust degree attribute access control model, the comprehensive user trust degree was obtained by weighting the direct trust degree. It obtained from user authentication and the trust degree of user access to terminal communication traffic. And according to the comprehensive trust degree, users are assigned the minimum authority to access the terminal to realize the security protection of the terminal. According to the comprehensive trust degree, the minimum permissions for users to access the terminal were assigned to achieve the security protection of the terminal. The research shows that the zero-trust mechanism is applied to the terminal security protection of power Internet of Things, which can improve the reliability of the safe operation of terminal equipment.","PeriodicalId":325790,"journal":{"name":"2021 International Conference on Computer Engineering and Application (ICCEA)","volume":"49 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":"123324352","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
Semantic map generation algorithm combined with YOLOv5 结合YOLOv5的语义图生成算法
2021 International Conference on Computer Engineering and Application (ICCEA) Pub Date : 2021-06-01 DOI: 10.1109/ICCEA53728.2021.00009
Qing Ju, F. Liu, Guangbin Li, Xiao Nan Wang
{"title":"Semantic map generation algorithm combined with YOLOv5","authors":"Qing Ju, F. Liu, Guangbin Li, Xiao Nan Wang","doi":"10.1109/ICCEA53728.2021.00009","DOIUrl":"https://doi.org/10.1109/ICCEA53728.2021.00009","url":null,"abstract":"Traditional visual SLAM algorithms have problems such as lack of semantic information, low accuracy and slow speed of 3D point cloud segmentation. This paper proposes a semantic map generation algorithm based on YOLOv5 and improved VCCS point cloud segmentation. Firstly, the ORB-SLAM2 algorithm is used to generate the original three-dimensional point cloud. The target is detected by YOLOv5 and the original point cloud is semantically annotated, and the objects in the point cloud are expressed in other colors. Then, the VCCS algorithm was used for over-segmentation to obtain supervoxel clustering. The improved VCCS algorithm was used to merge supervoxel clustering to improve the accuracy of segmentation results. Finally, a three-dimensional point cloud map with semantic information is established. Experiments show that the algorithm can generate semantic maps very well, and the accuracy and speed of 3D point cloud segmentation are greatly improved.","PeriodicalId":325790,"journal":{"name":"2021 International Conference on Computer Engineering and Application (ICCEA)","volume":"31 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":"124258477","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
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