2021 International Conference on Information and Communication Technologies for Disaster Management (ICT-DM)最新文献

Ledger-based Points Transfer System in LPWAN: From Disaster Management Aspect 基于分类帐的LPWAN点传输系统:从灾害管理的角度

2021 International Conference on Information and Communication Technologies for Disaster Management (ICT-DM) Pub Date : 2021-12-03 DOI: 10.1109/ict-dm52643.2021.9664160

Xin Qi, Keping Yu, Toshio Sato, Kouichi Shibata, Eric Brigham, Takanori Tokutake, Rikiya Eguchi, Yusuke Maruyama, Zheng Wen, Kazuhiko Tamesue, Yutaka Katsuyama, Kazue Sako, Takuro Sato

引用次数: 1

Revisit Gaussian Embedding: An Effective Method for Scalable Knowledge Graph 高斯嵌入:一种有效的可扩展知识图方法

2021 International Conference on Information and Communication Technologies for Disaster Management (ICT-DM) Pub Date : 2021-12-03 DOI: 10.1109/ict-dm52643.2021.9664081

Wei He, Qiao Li, Wei Zhao

{"title":"Revisit Gaussian Embedding: An Effective Method for Scalable Knowledge Graph","authors":"Wei He, Qiao Li, Wei Zhao","doi":"10.1109/ict-dm52643.2021.9664081","DOIUrl":"https://doi.org/10.1109/ict-dm52643.2021.9664081","url":null,"abstract":"Knowledge Graph with Gaussian Embedding (KG2E) is designed to capture the uncertainties of knowledge and hence shows great potential on various applications such as information retrieval, crisis management and so on. However, it is computational expensive, and limited to a Mahalanobis distance which essentially views relations as translation operator. This paper describes the theory and implementation of a highly scalable and effective solver to simplify KG2E, through decomposition of the objective of into two parts: an adaptive margin and a distance metric. For the first part, we provide a sound theoretical guarantee for the equivalence between uncertainties and the adaptive margin. We show that, under certain assumptions, it enjoys a linear time complexity with the help of SVD. For the second part, we extend the distance metric to capture the complicated effect of relations, enhancing the model's flexibility. Compared to original KG2E, our methods boost the convergence as well as the performance (over 10% improvement on Hits@10). On four large-scale knowledge graph benchmarks, our methods also achieve better or comparable performance among the state-of-the-art models.","PeriodicalId":337000,"journal":{"name":"2021 International Conference on Information and Communication Technologies for Disaster Management (ICT-DM)","volume":"78 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":"129341372","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 Grid and Vehicle Density Prediction-Based Communication Scheme in Large-scale Urban Environments 基于网格和车辆密度预测的大尺度城市环境通信方案

2021 International Conference on Information and Communication Technologies for Disaster Management (ICT-DM) Pub Date : 2021-12-03 DOI: 10.1109/ict-dm52643.2021.9664107

Bingyi Liu, Yong Sheng, Xun Shao, Yusheng Ji

引用次数: 1

Exploration and Discussion on Operation Management System of Telecom Operators 电信运营商运营管理体系的探索与探讨

2021 International Conference on Information and Communication Technologies for Disaster Management (ICT-DM) Pub Date : 2021-12-03 DOI: 10.1109/ict-dm52643.2021.9664125

Runsha Dong, Xiao-dong Cao, Jinghui Li, Tianyi Wang, Chuntao Song, Shengli Guo, Lexi Xu, Xiaomeng Zhu, Chen Cheng

引用次数: 1

Automation Test Tool for the Page Load Time of Mobile Applications 移动应用程序页面加载时间的自动化测试工具

2021 International Conference on Information and Communication Technologies for Disaster Management (ICT-DM) Pub Date : 2021-12-03 DOI: 10.1109/ict-dm52643.2021.9664210

Wentao Zeng, Xiangyu Bai, Kexin Zhou

引用次数: 1

Information Delivery and Collection System Based on Locally Accessible System 基于本地可访问系统的信息传递与采集系统

2021 International Conference on Information and Communication Technologies for Disaster Management (ICT-DM) Pub Date : 2021-12-03 DOI: 10.1109/ict-dm52643.2021.9664068

B. Ojetunde, T. Sakano, Yoshinori Suzuki

{"title":"Information Delivery and Collection System Based on Locally Accessible System","authors":"B. Ojetunde, T. Sakano, Yoshinori Suzuki","doi":"10.1109/ict-dm52643.2021.9664068","DOIUrl":"https://doi.org/10.1109/ict-dm52643.2021.9664068","url":null,"abstract":"This paper proposes a disaster information collection and delivery approach using locally accessible cloud system (LACS) in an infrastructureless environment such as a disaster area. Specifically, LACS is deployed to each evacuation center in the aftermath of a large-scale disaster to quickly and locally restore communication network and essential services. Furthermore, in order to reduce the time taken to deliver and collect information in a disaster affected area, a movable LACS (i.e., a movable LACS is a LACS deployed in a vehicle) from the city office or local command center tour each evacuation center to collect/deliver information to/from the users. Our experimental results suggest that LACS is useful in collecting and delivery of urgent and important disaster information to users within the affected disaster areas. We estimate the time it will take a movable LACS to deliver/collect information from an evacuation center. According to the results, it takes an average of 34 seconds to 6 minutes to deliver information to the LACS server when the data capacity is increased from 1 GB to 10 GB. On the other hand, it takes an average of 3 minutes to 25 minutes to collect information when the data capacity is increased from 1 GB to 10 GB. In the future, we will consider implementation of our method in the quasi-real situations.","PeriodicalId":337000,"journal":{"name":"2021 International Conference on Information and Communication Technologies for Disaster Management (ICT-DM)","volume":"435 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":"123607109","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 VANET Network Coding Strategy in Expressway Scene 高速公路场景VANET网络编码策略研究

2021 International Conference on Information and Communication Technologies for Disaster Management (ICT-DM) Pub Date : 2021-12-03 DOI: 10.1109/ict-dm52643.2021.9664024

Hua Zhang, Xiangyu Bai, L. Yao

{"title":"Research on VANET Network Coding Strategy in Expressway Scene","authors":"Hua Zhang, Xiangyu Bai, L. Yao","doi":"10.1109/ict-dm52643.2021.9664024","DOIUrl":"https://doi.org/10.1109/ict-dm52643.2021.9664024","url":null,"abstract":"VANET is a real-time, intelligent transportation network featuring motion patterns limited by roads, diverse transmission data, and frequent topological changes. In the highway scene, the network coding and the roadside unit are introduced to assist the data transmission in order to solve such problems as single data transmission path and short communication link duration. When the vehicle node transmits data, it will first determine the type of vehicle node at this time, and select the best transmission path as the main path of the encoded data packet according to the relative position information of the vehicle nodes, the difference of the requested content storage nodes, and the vehicle density. The path acts as a secondary path for the transmission of encoded packets. Finally, the routing strategy proposed in this paper is implemented by the opportunistic network simulator ONE simulation. According to the experimental results, the routing strategy proposed in this paper can effectively improve the message delivery rate, reduce the average network delay and network overhead.","PeriodicalId":337000,"journal":{"name":"2021 International Conference on Information and Communication Technologies for Disaster Management (ICT-DM)","volume":"43 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":"115859192","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

Enhancing Detection of SSVEPs through Spatial Filtering: An Inter-Trial Distance Minimization Perspective 通过空间滤波增强ssvep的检测:试验间距离最小化视角

2021 International Conference on Information and Communication Technologies for Disaster Management (ICT-DM) Pub Date : 2021-12-03 DOI: 10.1109/ict-dm52643.2021.9664208

Zhenyu Wang, Xianfu Chen, Ruxue Li, Honglin Hu, Ting Zhou

{"title":"Enhancing Detection of SSVEPs through Spatial Filtering: An Inter-Trial Distance Minimization Perspective","authors":"Zhenyu Wang, Xianfu Chen, Ruxue Li, Honglin Hu, Ting Zhou","doi":"10.1109/ict-dm52643.2021.9664208","DOIUrl":"https://doi.org/10.1109/ict-dm52643.2021.9664208","url":null,"abstract":"The brain-computer interface (BCI) technology has a great potential in providing more intelligent robots control for future disaster management systems. However, before brain-controlled robots can finally be brought to reality, many practical problems need to be solved. One of them is to further improve the detection performance of existing BCI systems. In steady-state visual-evoked potential (SSVEP) based BCIs, the selection of spatial filters poses a direct impact on the detection accuracy and the information transfer rate that can be achieved. To derive the optimum spatial filters, a popular approach is to maximize the inter-trial correlation over the training set. The relevant algorithms include task-related component analysis (TRCA), correlated component analysis (CORCA), sum of squared correlation analysis (SSCOR), etc. In this paper, a new perspective for calculating the spatial filters is proposed and it is named inter-trial distance minimization analysis (ITDMA). Literally, different from the conventional methods, the proposed ITDMA algorithm derives the spatial filters through minimizing the inter-trial distance over the training set. The detection performance of ITDMA is tested on a public benchmark SSVEP dataset and results show that the proposed ITDMA algorithm outperforms the three benchmark algorithms. The validity of ITDMA is verified.","PeriodicalId":337000,"journal":{"name":"2021 International Conference on Information and Communication Technologies for Disaster Management (ICT-DM)","volume":"6 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":"131118941","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

Mobile and wireless communication networks [Table of contents] 流动及无线通讯网络[目录]

2021 International Conference on Information and Communication Technologies for Disaster Management (ICT-DM) Pub Date : 2021-12-03 DOI: 10.1109/ict-dm52643.2021.9664194

引用次数: 0

Satellite Data Transmission Method for Deep Learning-Based AutoEncoders 基于深度学习的自动编码器卫星数据传输方法

2021 International Conference on Information and Communication Technologies for Disaster Management (ICT-DM) Pub Date : 2021-12-03 DOI: 10.1109/ict-dm52643.2021.9664172

Yile Fan, Yuanpeng Li, Tianyi Chai, Dan Ding

{"title":"Satellite Data Transmission Method for Deep Learning-Based AutoEncoders","authors":"Yile Fan, Yuanpeng Li, Tianyi Chai, Dan Ding","doi":"10.1109/ict-dm52643.2021.9664172","DOIUrl":"https://doi.org/10.1109/ict-dm52643.2021.9664172","url":null,"abstract":"To improve the accuracy of satellite data transmission, deep learning (DL) are applied to the Ka-band satellite communication system under complex channel conditions, and a satellite data transmission method for deep learning-based auto encoder (AE) is proposed in this paper. Specifically, the transmitter and receiver are integrated with deep neural network (DNN), and an interference layer is used to simulate the complex channels that may occur during the satellite data transmission. Finally, we trained the entire network iteratively. And optimized the entire network performance. The result exposed that the proposed method achieve an order of magnitude higher than traditional BPSK modulation, coherent demodulation, Hamming code (HC) and hard-decision decoding method, and two orders of magnitude higher than Hamming code and maximum likelihood estimation (MLE) methods. It has been verified that the new network structure of the AE can improve the data transmission accuracy, thus providing new avenues for promoting the application of deep learning in wireless transmission, as well as new ideas for satellite data transmission.","PeriodicalId":337000,"journal":{"name":"2021 International Conference on Information and Communication Technologies for Disaster Management (ICT-DM)","volume":"1 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":"129465603","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