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2021 15th International Conference on Ubiquitous Information Management and Communication (IMCOM)最新文献

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A Cross-Cultural Comparative Study on the Startup Discourse in 2000–2019 between United States and China 2000-2019年中美创业话语的跨文化比较研究
Jaeyeon Jang, Byungjun Kim, Kveo Re Lee, J. Kim
This essay explores significant cultural differences on startup discourses between United States and China by demonstrating a big data analysis through Structural Topic Modeling. Results and findings were interpreted with Hofstede”s cultural dimensions, indicating that the conventional theory of social science was applicable when it comes to explaining technological subjects
本文通过结构主题模型的大数据分析,探讨了中美两国创业话语的显著文化差异。结果和发现用Hofstede的文化维度来解释,表明传统的社会科学理论在解释技术主题时是适用的
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引用次数: 0
Authentication and Trustful Communication Protocol for IoT Devices 物联网设备的认证和可信通信协议
Seiya Kobayashi, T. Miyazaki
This study proposes a network protocol that enables connecting Internet-of-Things (IoT) devices to IoT servers without modifying the original IoT service applications. Access proxies, introduced at the edge of an IoT network cloud, intercept packets flowing between the IoT devices and servers, and examine the credibility of each loT device in real time. After registering a new IoT device using an access proxy, the data produced by the IoT device or the server were significantly protected. Intended attacks and spoofing were also blocked at the access proxies. Therefore, IoT services are safe for use in the proposed network environment.
本研究提出一种网络协议,可以在不修改原有物联网服务应用的情况下,将物联网(IoT)设备连接到物联网服务器。接入代理,在物联网网络云的边缘引入,拦截在物联网设备和服务器之间流动的数据包,并实时检查每个loT设备的可信度。在使用访问代理注册新的物联网设备后,物联网设备或服务器产生的数据得到了显著的保护。有意的攻击和欺骗也在访问代理上被阻止。因此,在建议的网络环境中使用物联网服务是安全的。
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引用次数: 0
Inter-dependent LSTM: Baseball Game Prediction with Starting and Finishing Lineups 相互依赖的LSTM:棒球比赛首发和结束阵容预测
Sungjin Chun, C. Son, Hyunseung Choo
With the wide availability of historical data from baseball games, one of the most popular sports, high accurate winner prediction has become a significant target of statistical analysis and machine learning. However, existing techniques for a pre-game prediction yield poor accuracies due to the incomplete player lists given in starting lineups and substitutions occurring during the game. We exploit the capability of Long Short-Term Memory (LSTM) in identifying hidden patterns of time series data to propose inter-dependent LSTM baseball game prediction with only the starting lineup information. Particularly, we preprocess historical data to generate a pair of pre-game and post-game records for each baseball game. The pre-game record indicates the incomplete player lists given in starting lineups, and the post-game one contains the list of all players who participated in the game. The inter-dependent LSTM model exploits the dependencies of the pairs to predict a game result with only pre-game input. Our experiment results show that the proposed model achieves up to 12% higher accuracy than the existing ones.
棒球比赛是最受欢迎的运动之一,随着棒球比赛历史数据的广泛可用性,高精度的赢家预测已成为统计分析和机器学习的重要目标。然而,由于首发阵容和换人名单不完整,现有的赛前预测技术的准确性很低。利用长短期记忆(LSTM)识别时间序列数据隐藏模式的能力,提出了仅使用首发阵容信息进行相互依赖的LSTM棒球比赛预测。特别是,我们对历史数据进行预处理,为每场棒球比赛生成一对赛前和赛后记录。赛前记录表示首发阵容中不完整的球员名单,赛后记录包含所有参加比赛的球员名单。相互依赖的LSTM模型利用对的依赖性来预测只有赛前输入的比赛结果。实验结果表明,该模型比现有模型的准确率提高了12%。
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引用次数: 3
A Reconcile of Density Based and Hierarchical Clustering Based on the Laws of Physics 基于物理定律的密度聚类与层次聚类的调和
Nader Bazyari, H. Sajedi
In this paper a new approach toward data processing is proposed that is inspired by all the prominent data clustering algorithms proposed by scholars. The main motif that drove this approach was to mix hierarchical clustering methods with Gaussian Estimators as to find a hidden structure in data that was not reachable using traditional bandwidth estimators. Instead the criteria for assessing similarity among data was the principles for Newtonian Physics.
本文在学者们提出的所有优秀的数据聚类算法的启发下,提出了一种新的数据处理方法。驱动这种方法的主要主题是混合层次聚类方法和高斯估计方法,以发现使用传统带宽估计器无法到达的数据中的隐藏结构。相反,评估数据相似性的标准是牛顿物理学原理。
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引用次数: 0
Differential Privacy using Fuzzy Convolution Neural Network (DP-FCNN) with Laplace Mechanism and Authenticated Access in Edge Computing 边缘计算中基于拉普拉斯机制和认证访问的模糊卷积神经网络差分隐私
Jhilakshi Sharma, Donghyun Kim, Ahyoung Lee, Daehee Seo
During recent years, mobile edge computing is getting much attention from both academia and industry. However, many found that this emerging architecture needs a proper data privacy protection mechanism at mobile edge nodes against unintended data use by authorized data analysts. Due to the reason, the development of a proper lightweight privacy-preserving data analysis mechanism is of great urgency. Thus, we propose DP-FCNN, a light-weight Differential Privacy (DP) framework using Fuzzy Convolution Neural Network (FCNN) with Laplace Mechanism which injects noise into the personal data before uploading data from users generating the data into the storage so that the data is still useful but data privacy can be properly protected against unauthorized data analysis attempt. We implemented the proposed framework, and tested its performance in terms of scalability, processing time, and accuracy. The result shows that the proposed framework is very practical.
近年来,移动边缘计算受到了学术界和工业界的广泛关注。然而,许多人发现,这种新兴架构需要在移动边缘节点上建立适当的数据隐私保护机制,以防止授权数据分析师意外使用数据。因此,开发一种合适的轻量级隐私保护数据分析机制迫在眉睫。因此,我们提出了DP-FCNN,这是一个轻量级的差分隐私(DP)框架,使用模糊卷积神经网络(FCNN)和拉普拉斯机制,在用户将生成数据的数据上传到存储之前向个人数据注入噪声,这样数据仍然有用,但数据隐私可以得到适当的保护,防止未经授权的数据分析企图。我们实现了提出的框架,并在可伸缩性、处理时间和准确性方面测试了它的性能。结果表明,该框架具有很强的实用性。
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引用次数: 1
Improving the Two-stage Detection of Cyberattacks in SDN Environment Using Dynamic Thresholding 利用动态阈值改进SDN环境下网络攻击的两阶段检测
Tao Wang, Yaokai Feng, K. Sakurai
In recent years, the DDoS (Distributed Denial of Service) attack continues to be one of the most dangerous threats even in the SDN (Software Defined Networking) environment. Many approaches have been proposed to deal with the DDoS attacks in the SDN environment. Among those approaches, the two-step detection, in which a trigger mechanism is added before the detection algorithm is called, is gaining more and more attention. In other words, it is the trigger, not the resource-consuming detection algorithm, that constantly monitors network traffic. Thus, the detection algorithm is only called when it is triggered. However, in the existing two-step methods, the trigger uses a static threshold to determine whether or not to start the detection process. In practice, it is difficult to determine an appropriate threshold, and the threshold has a decisive effect on the frequency of the detection process being called and ultimately, it impacts detection performance. In this paper, we propose a self-feedback dynamic thresholding system in which the threshold used in the trigger is dynamically adjusted based on the previous results of trigger and detection. Experimental results and our discussion show that our proposal significantly reduces the number of calls to the resource-consuming detection algorithm with no sacrifice of detection result.
近年来,即使在软件定义网络(SDN)环境中,DDoS(分布式拒绝服务)攻击仍然是最危险的威胁之一。针对SDN环境下的DDoS攻击,人们提出了多种应对方法。其中,在调用检测算法之前添加触发机制的两步检测方法越来越受到人们的关注。换句话说,持续监控网络流量的是触发器,而不是消耗资源的检测算法。因此,仅在触发检测算法时才调用检测算法。但是,在现有的两步方法中,触发器使用静态阈值来确定是否启动检测过程。在实践中,很难确定一个合适的阈值,并且阈值对被调用的检测过程的频率有决定性的影响,最终影响检测性能。在本文中,我们提出了一种自反馈动态阈值系统,在该系统中,触发器中使用的阈值是根据先前的触发和检测结果动态调整的。实验结果和我们的讨论表明,我们的提议在不牺牲检测结果的情况下显著减少了对资源消耗检测算法的调用次数。
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引用次数: 3
A Cluster Analysis of Lotte Young Plaza Using Semantic Network Analysis Method 用语义网络分析法对乐天青年广场的聚类分析
ShaoPeng Che, Dongyan Nan, Pim Kamphuis, Xinvu Jin, J. Kim
The COVID-19 pandemic has had a significant impact on tourism-driven industries worldwide. As East Asia is gaining control in the fight against the coronavirus, countries in this region started easing their travel restrictions. Tourist-oriented retail stores are slowly preparing to receive international visitors again, and to be well adjusted, it is crucial to understand foreign customers' perceptions. From the seven most popular tourism platforms in China, we collected comments about Lotte Young Plaza in South Korea and applied semantic network analysis to understand its perception among young Chinese customers. Based on this analysis, we divided the conclusions into 6 aspects: People whose main purpose is to buy clothes, people who have communication needs in Chinese, the Lotte Department Store's driving force on customer flow to Lotte Young Plaza, young people, features of Lotte Young Plaza (mouthwash) and cosmetics.
2019冠状病毒病大流行对全球旅游业产生了重大影响。随着东亚地区在抗击新冠肺炎疫情中取得控制权,该地区国家开始放松旅行限制。以游客为导向的零售商店正慢慢准备再次接待国际游客,要做好调整,了解外国顾客的看法至关重要。从中国七个最受欢迎的旅游平台中,我们收集了关于韩国乐天青年广场的评论,并应用语义网络分析来了解中国年轻客户对其的看法。在此基础上,我们将结论分为6个方面:以购买服装为主要目的的人群、有中文交流需求的人群、乐天百货对乐天青年广场客流的驱动力、年轻人、乐天青年广场的特色(漱口水)、化妆品。
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引用次数: 3
A Geographical Object Extraction Method Using User's Trajectories for Generating Artificial Maps 一种利用用户轨迹生成人工地图的地理目标提取方法
Koki Ohtsuka, D. Kitayama, K. Sumiya, Kazushi Fujita, Goto Shin, Isshu Munemasa
There have been many studies on automatic generation of artificial maps, but few have focused on the objects displayed on artificial maps. Therefore, in this research, we analyzed an object extraction method for automatically generating artificial map. In this research, objects are extracted using Biased Page Rank. Biased Page Rank is a method for improving the quality of search results by changing the rank source according to the interests and interests of individual users. By using this method for object extraction, it is possible to display the objects with a high evaluation value among the objects existing in a specific area on artificial map.
关于人工地图自动生成的研究很多,但很少关注人工地图上显示的对象。因此,在本研究中,我们分析了一种自动生成人工地图的目标提取方法。在本研究中,使用有偏差的页面排名来提取对象。有偏差的页面排名是一种根据个人用户的兴趣和兴趣改变排名来源来提高搜索结果质量的方法。利用该方法进行对象提取,可以在人工地图上显示特定区域内存在的对象中具有较高评价价值的对象。
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引用次数: 0
Face Detection using Local Patterns in FPGA 基于FPGA的局部模式人脸检测
Jin Young Byun, J. Jeon
Face detection is currently one of the most common technologies used in a variety of applications. This paper presents the design and implementation of face detection with some local patterns for achieving real-time performance. It is designed to process the image received in real time from an industrial camera using local patterns to detect the face on the FPGA. Each development result is separately analyzed specifically in terms of hardware resources.
人脸检测是目前各种应用中最常用的技术之一。本文提出了基于局部模式的人脸检测的设计与实现,以达到实时检测的目的。它设计用于处理从工业相机实时接收的图像,使用局部模式检测FPGA上的人脸。每个开发结果分别从硬件资源的角度进行具体分析。
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引用次数: 1
Enhanced Random Access with Beamforming Techniques in 5G Networks 5G网络波束成形技术增强随机接入
Jun-Woo Won, K. Kim, Tae-Jin Lee
In cellular networks, User Equipments (UEs) must perform a Random Access (RA) process in which UEs are allocated resources for data transmission from the Base Station (BS). The 5G network using the high-frequency band adopts the beamforming technology in order to overcome the high path-loss. As the narrow coverage characteristic of the beam, the BS and UEs use the beam-sweeping and beam-switching methods at the RA process. In this paper, we propose an Enhanced Random Access (E-RA) process, in which the UE selects multiple preambles and transmits them through the beam-sweeping method, and transmits the Connection Request Message (Msg3) through the random beam-switching method. Furthermore, we also propose an improved re-access process that begins with Msg3 retransmission. Through the E-RA process, we can reduce the access delay of the network and the number of transmitted messages causing the energy consumption of the UE and increase the success probability of the RA process.
在蜂窝网络中,用户设备(ue)必须执行随机访问(RA)过程,在此过程中,ue被分配资源用于从基站(BS)传输数据。使用高频频段的5G网络采用波束形成技术,以克服高路径损耗。由于波束的窄覆盖特性,BS和ue在RA过程中采用了波束扫描和波束切换方法。本文提出了一种增强型随机接入(Enhanced Random Access, E-RA)过程,该过程中终端选择多个前导,通过波束扫描方式发送,通过随机波束切换方式发送连接请求消息(Msg3)。此外,我们还提出了一个改进的重访问过程,从Msg3重传开始。通过E-RA过程,我们可以减少网络的接入延迟和传输消息的数量,从而降低终端的能耗,提高RA过程的成功概率。
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引用次数: 0
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2021 15th International Conference on Ubiquitous Information Management and Communication (IMCOM)
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