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2021 International Conference on Digital Society and Intelligent Systems (DSInS)最新文献

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Research on the Design and Construction of Sanya Smart Tourism Information Platform Based on Federated Migration Algorithm 基于联邦迁移算法的三亚智慧旅游信息平台设计与构建研究
2021 International Conference on Digital Society and Intelligent Systems (DSInS) Pub Date : 2021-12-03 DOI: 10.1109/dsins54396.2021.9670562
Kun Zhang, Jia Zhu, Xuebing Huang, Hai-feng Wang, Vaniushkina · Dina, Kaparova Kumushai, Zhe Zhao, Peng Zeng
{"title":"Research on the Design and Construction of Sanya Smart Tourism Information Platform Based on Federated Migration Algorithm","authors":"Kun Zhang, Jia Zhu, Xuebing Huang, Hai-feng Wang, Vaniushkina · Dina, Kaparova Kumushai, Zhe Zhao, Peng Zeng","doi":"10.1109/dsins54396.2021.9670562","DOIUrl":"https://doi.org/10.1109/dsins54396.2021.9670562","url":null,"abstract":"The article is a series of research results of the smart tourism construction research project in Asia. Through the preliminary research, it analyzes and studies the problems existing in the smart tourism construction of Sanya City, and gives the countermeasures and measures for the smart tourism construction of Sanya City from multiple angles. Suggestions and based on the federal migration algorithm, the Sanya smart tourism information platform was designed, and the comprehensive Sanya smart tourism construction was analyzed and researched.","PeriodicalId":243724,"journal":{"name":"2021 International Conference on Digital Society and Intelligent Systems (DSInS)","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116238522","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 of Offline Analysis System for Remote Sensing Data Service Based on Hive 基于Hive的遥感数据服务离线分析系统设计
2021 International Conference on Digital Society and Intelligent Systems (DSInS) Pub Date : 2021-12-03 DOI: 10.1109/dsins54396.2021.9670605
Hongkuo Zhang, Jiaxiang Zhang, Meng Tian, Baojun Qiao
{"title":"Design of Offline Analysis System for Remote Sensing Data Service Based on Hive","authors":"Hongkuo Zhang, Jiaxiang Zhang, Meng Tian, Baojun Qiao","doi":"10.1109/dsins54396.2021.9670605","DOIUrl":"https://doi.org/10.1109/dsins54396.2021.9670605","url":null,"abstract":"With the wide application of remote sensing data service platform, the platform accumulates more and more data, and the remote sensing users' demand for remote sensing data service becomes more and more diverse. Therefore, how to deal with remote sensing service data, make statistics and analyze its potential value, and meet the diverse needs of remote sensing users becomes particularly important. Based on big data technology, this paper firstly collects and stores remote sensing user behavior data and remote sensing service platform business data, then uses Hive to build offline data warehouse, performs dimensional modeling and hierarchical design of the data, and finally obtains relevant index data values by statistical analysis. Through the statistical analysis of remote sensing service data can not only provide data support for active service mode, but also provide support for the decision of remote sensing application department managers.","PeriodicalId":243724,"journal":{"name":"2021 International Conference on Digital Society and Intelligent Systems (DSInS)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127222670","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
Multilocation Watermarking Algorithm for Energy Big Data Based on Orthogonal Coding 基于正交编码的能源大数据多位置水印算法
2021 International Conference on Digital Society and Intelligent Systems (DSInS) Pub Date : 2021-12-03 DOI: 10.1109/dsins54396.2021.9670621
Zhenhua Yan, Xuwei Xia, Rui Ma, Dongge Zhu, Xiaolong Li
{"title":"Multilocation Watermarking Algorithm for Energy Big Data Based on Orthogonal Coding","authors":"Zhenhua Yan, Xuwei Xia, Rui Ma, Dongge Zhu, Xiaolong Li","doi":"10.1109/dsins54396.2021.9670621","DOIUrl":"https://doi.org/10.1109/dsins54396.2021.9670621","url":null,"abstract":"Grid energy data contains a large amount of user data. How to protect the privacy of user data is a hot issue in related fields today. In order to protect the privacy of energy big data and improve the correctness of watermark embedding, this paper proposes a multi-location watermark embedding algorithm based on orthogonal coding. Based on the analysis of the demand of big data privacy protection in energy internet, the demand response mechanism is calculated, and the multi-location watermarking is embedded in the energy big data text. Experimental results show that the watermark embedding algorithm is correct and the transmission delay is 4ms, which improves the performance of the watermark embedding algorithm.","PeriodicalId":243724,"journal":{"name":"2021 International Conference on Digital Society and Intelligent Systems (DSInS)","volume":"137 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122342048","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
Content-based brain tumor retrieval for MR images with joint deep and handcrafted visual features 基于内容的脑肿瘤联合深度和手工视觉特征MR图像检索
2021 International Conference on Digital Society and Intelligent Systems (DSInS) Pub Date : 2021-12-03 DOI: 10.1109/dsins54396.2021.9670565
Wei-Luen Huang, W. Zou, Erxi Fang, Nan Hu, Jiajun Wang
{"title":"Content-based brain tumor retrieval for MR images with joint deep and handcrafted visual features","authors":"Wei-Luen Huang, W. Zou, Erxi Fang, Nan Hu, Jiajun Wang","doi":"10.1109/dsins54396.2021.9670565","DOIUrl":"https://doi.org/10.1109/dsins54396.2021.9670565","url":null,"abstract":"A novel feature extraction framework is proposed to improve the performance of the brain tumor retrieval system. To extract information that radiologists pay attention to when diagnosing brain tumors, not only features describing the location and layout of the tumor in the brain but also those for texture variations of the tumor region and tumor-surrounding tissues are extracted. The gray level co-occurrence matrix (GLCM) and Fisher vector (FV) are calculated as handcrafted features for the augmented tumor regions. Two deep features are extracted respectively from the whole brain MR images and the augmented tumor regions by fine-tuning the Xception model. Then the handcrafted and deep features are fused together after implementing a feature selection procedure based on roulette wheel selection (RWS) method. Extensive experiments are conducted on the brain CE-MRI dataset. The results show that the proposed system can achieve average mAP of 98.17±0.88% and Prec@10 of 97.56±1.16%, which outperforms the state-of-the-art retrieval systems by a large margin on the same dataset.","PeriodicalId":243724,"journal":{"name":"2021 International Conference on Digital Society and Intelligent Systems (DSInS)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127721781","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
Overlapping Community Based Relationship Discovery Algorithm for Herbs 基于重叠社区的草本植物关系发现算法
2021 International Conference on Digital Society and Intelligent Systems (DSInS) Pub Date : 2021-12-03 DOI: 10.1109/dsins54396.2021.9670576
Xin Chen, Shaojie Qiao
{"title":"Overlapping Community Based Relationship Discovery Algorithm for Herbs","authors":"Xin Chen, Shaojie Qiao","doi":"10.1109/dsins54396.2021.9670576","DOIUrl":"https://doi.org/10.1109/dsins54396.2021.9670576","url":null,"abstract":"The relationships discovery of herbs is an active research focus in data mining of traditional Chinese medicine (TCM). The existing methods are difficult to effectively find herbs relationships in TCM network. TCM doctors often give prescriptions according to the characteristics of herbs to combination. In this study, we propose an overlapping community based herbs relationship discover algorithm, through calculating the similarity of the characteristics of herbs and discovering the relationship between nodes based on the relationship between neighboring nodes. By comparing the proposed algorithm with the state-of-the-art methods, we conduct experiments in real TCM networks, the results show that the proposed algorithm can effectively partition the communities than traditional methods and can find common herbal combinations. It is interesting to find that searching similar relationships between nodes in a TCM networks can benefit partitioning the network community structures.","PeriodicalId":243724,"journal":{"name":"2021 International Conference on Digital Society and Intelligent Systems (DSInS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130335906","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
Remote sensing image object detection based on rotatable bounding box 基于可旋转边界框的遥感图像目标检测
2021 International Conference on Digital Society and Intelligent Systems (DSInS) Pub Date : 2021-12-03 DOI: 10.1109/dsins54396.2021.9670625
W. Zhuang, Xiaona Tang, Guangyu Yang, Guangming Yuan, Haoyuan Yu
{"title":"Remote sensing image object detection based on rotatable bounding box","authors":"W. Zhuang, Xiaona Tang, Guangyu Yang, Guangming Yuan, Haoyuan Yu","doi":"10.1109/dsins54396.2021.9670625","DOIUrl":"https://doi.org/10.1109/dsins54396.2021.9670625","url":null,"abstract":"Remote sensing image object detection is widely used in military investigations, disaster relief and urban traffic management. However, unlike ordinary images, remote sensing images are acquired from aerial photography, resulting in a variety of directions where targets are arranged. This situation leads to the poor detection accuracy of general object detection algorithms on remote sensing images. To address the problem that existing object detection algorithms have difficulty in detecting targets in remote sensing images with high accuracy, an improved YOLOv5 algorithm (Rotate-YOLOv5) was proposed for detecting arbitrary-oriented object in remote sensing images. Firstly, YOLOv5m was chosen as the baseline to build the network model, four types of movable targets were selected from the public dataset DOTA: plane, small vehicle, large vehicle and ship. And the dataset images were cropped to a size of 1024×1024 and preprocessed with mosaic data enhancements. And the anchor box size was determined by the adaptive anchor box filtering method. The long-edge definition method based on circular smoothing labels was used to achieve the rotation of the bounding box. The effect of angular periodicity on training was addressed by converting the regression problem into a classification problem. Finally, the CIoU loss was used as the loss function of the bounding box to improve the detection accuracy on the basis of ensuring the detection speed. The results show that the proposed algorithm achieves an improvement of 13.4% in mean average precision over YOLOv5. This algorithm can improve the accuracy of remote sensing image object detection.","PeriodicalId":243724,"journal":{"name":"2021 International Conference on Digital Society and Intelligent Systems (DSInS)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131668387","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 on Big Data Analysis System of Green Food Traceability Based on Smart Radio and Television 基于智能广电的绿色食品溯源大数据分析系统研究
2021 International Conference on Digital Society and Intelligent Systems (DSInS) Pub Date : 2021-12-03 DOI: 10.1109/dsins54396.2021.9670592
Liyang Hou, Yang Li, Shuang-cheng Li, Yujiao Wang
{"title":"Research on Big Data Analysis System of Green Food Traceability Based on Smart Radio and Television","authors":"Liyang Hou, Yang Li, Shuang-cheng Li, Yujiao Wang","doi":"10.1109/dsins54396.2021.9670592","DOIUrl":"https://doi.org/10.1109/dsins54396.2021.9670592","url":null,"abstract":"By discussing farmers' behavior characteristics, behavior intention, key factors and formation motivation of traceability control, this study builds a green food traceability big data analysis system which farmers are willing to participate in and easy to operate, and realizes the quality control of green food source. Based on the smart radio and television all over urban and rural areas, green food traceability applies big data analysis technology to the whole process of agricultural products from production to consumption, providing a convenient way to create “green food brand” by digital means and promoting the application of big data analysis technology in agriculture.","PeriodicalId":243724,"journal":{"name":"2021 International Conference on Digital Society and Intelligent Systems (DSInS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121251569","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
Automated Detection of Breast Cancer Metastases 乳腺癌转移的自动检测
2021 International Conference on Digital Society and Intelligent Systems (DSInS) Pub Date : 2021-12-03 DOI: 10.1109/dsins54396.2021.9670569
Chen Yang, Minghan Zhao, Chenyu Zhu, Suiwei Xie, Yifei Chen
{"title":"Automated Detection of Breast Cancer Metastases","authors":"Chen Yang, Minghan Zhao, Chenyu Zhu, Suiwei Xie, Yifei Chen","doi":"10.1109/dsins54396.2021.9670569","DOIUrl":"https://doi.org/10.1109/dsins54396.2021.9670569","url":null,"abstract":"For women, breast cancer is the most commonly diagnosed cancer, which brings a heavy workload to pathologists. Because this diagnostic procedure is now prone to being time-consuming and sometimes misinterpreting. In order to solve these problems, techniques related to deep learning and machine learning have been applied to the diagnostic process of breast cancer. However, some problems have been found in application of these technologies, such as imbalanced data sets. This paper proposes a data augmentation technique based on generative adversarial networks (GAN) which can solve the problem of data imbalance, then uses ResNet to evaluate the impact of different data augmentation techniques on the experimental results.","PeriodicalId":243724,"journal":{"name":"2021 International Conference on Digital Society and Intelligent Systems (DSInS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131207152","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
Company Name Recognition Based on Hybrid Method 基于混合方法的公司名称识别
2021 International Conference on Digital Society and Intelligent Systems (DSInS) Pub Date : 2021-12-03 DOI: 10.1109/dsins54396.2021.9670584
Yuan Liu
{"title":"Company Name Recognition Based on Hybrid Method","authors":"Yuan Liu","doi":"10.1109/dsins54396.2021.9670584","DOIUrl":"https://doi.org/10.1109/dsins54396.2021.9670584","url":null,"abstract":"With the development of Internet, there is more and more information which needs to be progress based on language. Named Entity Recognition is a good method to promote models of machine learning to obtain the structure features and contextual constraint, thus understanding the whole sentence, while company name recognition is an important part among Named Entity Recognition. In this paper, a model based on BERT-BiLSTM-CRF and text match is put forward to realize company name recognition. The text match based on company name feature thesaurus can recognize abbreviations more efficiently, thus improving the accuracy and recall of company name recognition.","PeriodicalId":243724,"journal":{"name":"2021 International Conference on Digital Society and Intelligent Systems (DSInS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125780726","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 Selection Strategy for Network Security Defense Based on a Time Game Model 基于时间博弈模型的网络安全防御选择策略
2021 International Conference on Digital Society and Intelligent Systems (DSInS) Pub Date : 2021-12-03 DOI: 10.1109/DSInS54396.2021.9670626
Pengyu Sun, Hengwei Zhang, Junqiang Ma, Chenwei Li, Yan Mi, Jin-dong Wang
{"title":"A Selection Strategy for Network Security Defense Based on a Time Game Model","authors":"Pengyu Sun, Hengwei Zhang, Junqiang Ma, Chenwei Li, Yan Mi, Jin-dong Wang","doi":"10.1109/DSInS54396.2021.9670626","DOIUrl":"https://doi.org/10.1109/DSInS54396.2021.9670626","url":null,"abstract":"Current network assessment models often ignore the impact of attack-defense timing on network security, making it difficult to characterize the dynamic game of attack-defense effectively. To effectively manage the network security risks and reduce potential losses, in this article, we propose a selection strategy for network defense based on a time game model. By analyzing the attack-defense status by analogy with the SIR infectious disease model, construction of an optimal defense strategy model based on time game, and calculation of the Nash equilibrium of the the attacker and the defender under different strategies, we can determine an optimal defense strategy. With the Matlab simulation, this strategy is verified to be effective.","PeriodicalId":243724,"journal":{"name":"2021 International Conference on Digital Society and Intelligent Systems (DSInS)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125800936","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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