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2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)最新文献

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Flexible Photodetectors based on SiC nanowires network on PDMS 基于SiC纳米线网络的PDMS柔性光电探测器
2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) Pub Date : 2022-04-01 DOI: 10.1109/AEMCSE55572.2022.00033
Z. Li
{"title":"Flexible Photodetectors based on SiC nanowires network on PDMS","authors":"Z. Li","doi":"10.1109/AEMCSE55572.2022.00033","DOIUrl":"https://doi.org/10.1109/AEMCSE55572.2022.00033","url":null,"abstract":"At present, a variety of sensors have been widely used in many intelligent detection equipment. For more and more special signals and special environments, sensors can also be transparent, flexible, extensible, freely bendable or even foldable, easy to carry, and wearable. With the development of flexible matrix materials, on this basis, flexible sensors that meet the above-mentioned various trends and characteristics are produced. In this paper, we prepared the SiC nanowires network based on PDMS. The SiC nanowires network has excellent physical properties, corrosion durability and high stabilities. The PDMS substrate has high flexibility and excellent conductivity transmission efficiency characteristics. The samples were subjected to photodetection tests under UV light, and the experimental results show that the SiC nanowires network had a higher photocurrent under UV light illumination. Our results indicate that with proper device design, SiC nanowires networks based on PDMS are promising candidates for low-cost, high-performance photodetectors.","PeriodicalId":309096,"journal":{"name":"2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114985405","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 real-time calculation platform of ship air pollutant emission based on Flink 基于Flink的船舶大气污染物排放实时计算平台
2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) Pub Date : 2022-04-01 DOI: 10.1109/aemcse55572.2022.00157
Juan Zhang, P. Tang, Taizhi Lv
{"title":"A real-time calculation platform of ship air pollutant emission based on Flink","authors":"Juan Zhang, P. Tang, Taizhi Lv","doi":"10.1109/aemcse55572.2022.00157","DOIUrl":"https://doi.org/10.1109/aemcse55572.2022.00157","url":null,"abstract":"Water transportation is not only an important part of the modern transportation system, but also an important source of air pollution. The air pollution in inland rivers, ports and coastal areas caused by ships is becoming increasing serious. Real-time calculation and early-warning of air pollutant emissions from ships can provide a basis of rapid-decision-making for relevant departments. To realize a real-time monitoring of air pollutant emission, a real-time calculation platform of air pollutant emission is proposed. This platform uses dynamic power method to calculate the ship air pollution based on the automatic identification system (AIS) data. The calculation is implemented by the stream computing of Flink. By taking advantage of the dynamization of the AIS data and real-time performance of Flink, this platform can improve the estimation of the ship air pollutant emission. It provides the data supporting for the blue-sky defense war.","PeriodicalId":309096,"journal":{"name":"2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115408473","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
Quality control and traceability system based on block chain 基于区块链的质量控制和可追溯系统
2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) Pub Date : 2022-04-01 DOI: 10.1109/AEMCSE55572.2022.00064
Qiyuan Wang, Muhong Zheng, Xie Ma, Jun Huang
{"title":"Quality control and traceability system based on block chain","authors":"Qiyuan Wang, Muhong Zheng, Xie Ma, Jun Huang","doi":"10.1109/AEMCSE55572.2022.00064","DOIUrl":"https://doi.org/10.1109/AEMCSE55572.2022.00064","url":null,"abstract":"In the 21st century, block chain has shown great potential. The repeated occurrence of epidemic makes people pay more attention to product safety. One of the important technologies to realize product traceability and prevent the spread of epidemic is \"block chain\" technology. This article mainly expounds a kind of quality control and product traceability system, this system can effectively prevent the imperfect products into the market, and through the production information module of storage devices to store product information, convenient for the user through the consumer landing platform to read of production information module, realize the product traceability, both for the quality control is also convenient for consumers to products. It is easy to operate and reduce the spread of the epidemic.","PeriodicalId":309096,"journal":{"name":"2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)","volume":"471 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116518726","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
Multi-Station Collaborative Analysis of Impending Seismic Precursor Based on Graph Neural Networks 基于图神经网络的临震前兆多站协同分析
2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) Pub Date : 2022-04-01 DOI: 10.1109/AEMCSE55572.2022.00054
Leyuan Chen, Yongming Huang, Yong Lu, Wenbo Shi, Fajun Miao, Hongyu Li
{"title":"Multi-Station Collaborative Analysis of Impending Seismic Precursor Based on Graph Neural Networks","authors":"Leyuan Chen, Yongming Huang, Yong Lu, Wenbo Shi, Fajun Miao, Hongyu Li","doi":"10.1109/AEMCSE55572.2022.00054","DOIUrl":"https://doi.org/10.1109/AEMCSE55572.2022.00054","url":null,"abstract":"Multi-station collaborative analysis is an important part of impending seismic precursor analysis. However, most analysis methods rely on manual feature selection and visual observation, and data missing is another problem in analysis. This paper proposes a method based on graph neural networks (GNNs) to facilitate message passing of adjacent stations, which is helpful to perform collaborative analysis of geomagnetic signals in the region and reduce the impact of data missing problem. A vertex drop layer is introduced in model training process for data enhancement and attention mechanism is introduced in the graph readout layer to model the importance of each station. On AETA dataset containing missing data, anomalies are found before 79.41% earthquakes, and anomaly detection precision reached 69.09%. Synchronized anomalies between stations are found before two big earthquakes. Besides, attention analysis shows the model can estimate the importance of each station, and the difference of attention weights can be explained by the data quality of stations.","PeriodicalId":309096,"journal":{"name":"2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122450845","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 channel estimation method of reference signal based on 5g-v2x 一种基于5g-v2x的参考信号信道估计方法
2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) Pub Date : 2022-04-01 DOI: 10.1109/AEMCSE55572.2022.00012
Shenmin Zhang, Hu Liu, Shenglin Xu, Qingqing Liu
{"title":"A channel estimation method of reference signal based on 5g-v2x","authors":"Shenmin Zhang, Hu Liu, Shenglin Xu, Qingqing Liu","doi":"10.1109/AEMCSE55572.2022.00012","DOIUrl":"https://doi.org/10.1109/AEMCSE55572.2022.00012","url":null,"abstract":"Based on 5G-V2X (Vehicle to Everything) is one of the key research areas in wireless communication. Channel estimation is the key to physical layer communication. In V2X communication, there are Doppler frequency shifts, fast time-varying fading, and multipath. To be able to support transmission requirements with low latency and high reliability, this paper combines 3GPP standards to perform channel estimation for V2X terminals. The MMSE algorithm is used to estimate the channel at the DMRS to address the Doppler shift and fast time-varying fading of the V2X channel, and the two-dimensional interpolation algorithm is used to accurately estimate the V2X channel by iterative calculation of the delay expansion. The simulation results show that the overall performance of the algorithm in this paper is suitable for V2X engineering, the accuracy of the algorithm is high and the complexity is low.","PeriodicalId":309096,"journal":{"name":"2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)","volume":"2016 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128725765","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
Multi-Scale Local Feature Fusion Network for Facial Expression Recognition 人脸表情识别的多尺度局部特征融合网络
2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) Pub Date : 2022-04-01 DOI: 10.1109/aemcse55572.2022.00146
Xusong Luo, J. Xiao, Aimin Xiong, Hongbin Zhang
{"title":"Multi-Scale Local Feature Fusion Network for Facial Expression Recognition","authors":"Xusong Luo, J. Xiao, Aimin Xiong, Hongbin Zhang","doi":"10.1109/aemcse55572.2022.00146","DOIUrl":"https://doi.org/10.1109/aemcse55572.2022.00146","url":null,"abstract":"To solve the problem that facial expression recognition (FER) system in actual application scenariosis always interfered by complex background which lead to low accuracy, we designed a multi-scale local feature fusion network (MSLFnet) to improve the performance of FER in actual application scenarios. Middle-level facial features map are extracted from the backbone, and the middle-level local feature is generated by a patch-level local attention module, the network can obtain richer facial expressions. Experiments is carried out on the FER datasets RAF-DB and FER+ to verify the efficacy of the network. Experimental results show that the accuracy of the proposed network on RAF-DB and FER+ is 2.5% and 1% higher than original ResNet-18, proving the effectiveness of MSLFnet.","PeriodicalId":309096,"journal":{"name":"2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130314429","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 Guilin Tourism Network Attention Based on Baidu Index 基于百度指数的桂林旅游网络关注度研究
2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) Pub Date : 2022-04-01 DOI: 10.1109/aemcse55572.2022.00087
Xinling Du
{"title":"Research on Guilin Tourism Network Attention Based on Baidu Index","authors":"Xinling Du","doi":"10.1109/aemcse55572.2022.00087","DOIUrl":"https://doi.org/10.1109/aemcse55572.2022.00087","url":null,"abstract":"This article uses Python to collect the \"Baidu Index\" index provided by Baidu search engine to conduct an in-depth exploration of the network attention of Guilin Tourism from 2011 to 2020. The results show that the online attention of Guilin tourism before 2019 showed an overall upward trend, but due to the impact of the new crown epidemic, the online attention of Guilin in 2020 has dropped significantly. The monthly network attention of Guilin Tourism shows obvious seasonality. The areas with higher attention on the national Guilin tourism economic network are mainly East China and South China. In comparison, the Northeast and Northwest regions have relatively weak awareness of Guilin tourism on the Internet. Finally, it is found that GDP and per capita disposable income of urban residents have an impact on the attention of Guilin tourism network.","PeriodicalId":309096,"journal":{"name":"2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125672138","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
Fingertip detection based on Freeman chain code analysis 基于Freeman链码分析的指尖检测
2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) Pub Date : 2022-04-01 DOI: 10.1109/AEMCSE55572.2022.00132
Yihong Wang, Jiaming Wang
{"title":"Fingertip detection based on Freeman chain code analysis","authors":"Yihong Wang, Jiaming Wang","doi":"10.1109/AEMCSE55572.2022.00132","DOIUrl":"https://doi.org/10.1109/AEMCSE55572.2022.00132","url":null,"abstract":"In order to meet the requirements of real-time fingertip positioning and detection in some scenes, a fingertip detection method based on Freeman chain code analysis is proposed in this paper. Firstly, the image collected by the camera needs to be preprocessed. The edge information of the palm is obtained by median filtering, analyzing the skin color space, binarization and morphological processing. The Freeman chain code of the hand contour is obtained by contour tracking calculation. After the convex points of the chain code of the hand contour are repaired, the matching points are analyzed according to the chain code difference, so as to realize the function of fingertip detection. The test shows that the fingertip detection based on Freeman chain code can detect the fingertip position quickly and accurately, and has good detection performance.","PeriodicalId":309096,"journal":{"name":"2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121972846","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 Transformer-Based Longer Entity Attention Model for Chinese Named Entity Recognition in Aerospace 基于变换的航天中文命名实体识别长实体注意模型
2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) Pub Date : 2022-04-01 DOI: 10.1109/AEMCSE55572.2022.00077
Shuai Gong, Xiong Xiong, Yunfei Liu, Shengyang Li, Anqi Liu
{"title":"A Transformer-Based Longer Entity Attention Model for Chinese Named Entity Recognition in Aerospace","authors":"Shuai Gong, Xiong Xiong, Yunfei Liu, Shengyang Li, Anqi Liu","doi":"10.1109/AEMCSE55572.2022.00077","DOIUrl":"https://doi.org/10.1109/AEMCSE55572.2022.00077","url":null,"abstract":"Chinese aerospace knowledge includes many long entities, such as professional terms, equipment names, and cabinets. However, current Named Entity Recognition (NER) algorithms typically address these longer and shorter entities uniformly. In this paper, a Longer Entity Attention (LEA) model based on the transformer is proposed. After the transformer encoding layer, LEA integrates sentence tags, sets thresholds according to the length of entities, and processes the hidden layer features of entities larger than the defined threshold to enhance the ability of the model to recognize longer entities. In addition, we construct an Aerospace Chinese NER dataset (ACNE) containing rich entity categories and domain knowledge. Experimental results demonstrate that LEA outperforms previous state-of-the-art models on ACNE, and shows a significant improvement on longer entities in each threshold range on OntoNotes 5.0 and ACNE datasets.","PeriodicalId":309096,"journal":{"name":"2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132165309","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
Bridge Crack Detection Based on Image Segmentation 基于图像分割的桥梁裂纹检测
2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) Pub Date : 2022-04-01 DOI: 10.1109/AEMCSE55572.2022.00122
Suqin Wu, Aimin Xiong, Xusong Luo, Jing-Yu Lai
{"title":"Bridge Crack Detection Based on Image Segmentation","authors":"Suqin Wu, Aimin Xiong, Xusong Luo, Jing-Yu Lai","doi":"10.1109/AEMCSE55572.2022.00122","DOIUrl":"https://doi.org/10.1109/AEMCSE55572.2022.00122","url":null,"abstract":"The detection of bridge cracks is related to the life of the bridge. Manual detection is time-consuming and laborious. Contact sensors exposed to air are susceptible to weather damage. In practice, the bridge cracks with low contrast and blurred edge features is the difficulty of crack detection based on image segmentation. To this end, this paper proposes a deep learning based image segmentation detection network. In order to reduce the size of the network model, we modify the backbone network of Segnet. The feature extraction network is modified to the structure of mobilenet and improved. Cracks belong to small targets and easily missed in the detection process. In order to improve the detection accuracy of small targets, a multi-scale feature fusion operation is adopted in this paper. The network training uses public datasets. In some images, the contrast between the crack and the background is low, so this paper binarization is used to strengthen the crack structure. The experimental results verify the effectiveness of image segmentation.","PeriodicalId":309096,"journal":{"name":"2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)","volume":"6 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114483265","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
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