2020 IEEE 17th Annual Consumer Communications & Networking Conference (CCNC)最新文献_第10页

A Framework for Predicting Haptic Feedback in Needle Insertion in 5G Remote Robotic Surgery 5G远程机器人手术中插入针的触觉反馈预测框架

2020 IEEE 17th Annual Consumer Communications & Networking Conference (CCNC) Pub Date : 2020-01-01 DOI: 10.1109/CCNC46108.2020.9045432

Francis Boabang, R. Glitho, H. Elbiaze, F. Belqasmi, O. Alfandi

{"title":"A Framework for Predicting Haptic Feedback in Needle Insertion in 5G Remote Robotic Surgery","authors":"Francis Boabang, R. Glitho, H. Elbiaze, F. Belqasmi, O. Alfandi","doi":"10.1109/CCNC46108.2020.9045432","DOIUrl":"https://doi.org/10.1109/CCNC46108.2020.9045432","url":null,"abstract":"Robots are being used more and more in surgery due to the many benefits they bring (e.g. reduction of patient discomfort, precision, reliability). Remote robotic surgery is now expected to become a reality due to the emergence of 5G. Needle insertion is a crucial element of many robotic surgical procedures such as biopsies, injections, neurosurgery, and brachytherapy cancer treatment. During needle insertion in remote robotic surgery, there is still no guarantee that the surgeon will obtain the haptic feedback from the patient side within the stringent deadlines, even in 5G settings. This paper proposes a framework for learning by imitation as a way to predict the messages that will eventually fail to reach their destination within the required deadlines. By leveraging expert demonstrations, the Hidden Markov Model is used to encapsulate a set of expert force/torque profiles and corresponding parameters during the off-line training process. A Gaussian mixture regression is then used to reproduce a generalized version of the force/torque profile and corresponding parameters during the prediction. Simulations are conducted to evaluate the performance of the proposed method. They show that our proposed framework is able to execute predictions in much less than the 1ms end-to-end latency requirement of remote robotic surgery.","PeriodicalId":443862,"journal":{"name":"2020 IEEE 17th Annual Consumer Communications & Networking Conference (CCNC)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121165918","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: 12

Real-time Crop Classification Using Edge Computing and Deep Learning 利用边缘计算和深度学习的实时作物分类

2020 IEEE 17th Annual Consumer Communications & Networking Conference (CCNC) Pub Date : 2020-01-01 DOI: 10.1109/CCNC46108.2020.9045498

M. Yang, Hsin-Hung Tseng, Yu-Chun Hsu, Wei Chen Tseng

{"title":"Real-time Crop Classification Using Edge Computing and Deep Learning","authors":"M. Yang, Hsin-Hung Tseng, Yu-Chun Hsu, Wei Chen Tseng","doi":"10.1109/CCNC46108.2020.9045498","DOIUrl":"https://doi.org/10.1109/CCNC46108.2020.9045498","url":null,"abstract":"In recent years, edge computing and deep learning have been successfully performed processing and classification tasks in a variety of fields including agriculture. Therefore, this research aims to use unmanned aerial vehicle (UAV) for agriculture applications with integrating edge computing and deep learning techniques. This research experiment was carried out in the NCHU Experimental Farm. The DJI Matrice 100 drone with ASUS Tinker Board S embedded system, which connects a Logitech C925e webcam to capture images are used in this study. The ASUS Tinker Board S runs a folder monitoring program and sends images over the 4G LTE network to the backend server whenever new images are captured and stored. The backend server runs a pre-trained image semantic segmentation model and provides image inference service. The image inference results with the associated segmented image will be sent to the mobile device of the drone controller, and a dynamic flight control action can be triggered. The image semantic segmentation model adopts SegNet network architecture. For a comparison purpose, another network architecture, FCN-AlexNet, was also trained and validated. The preliminary results show SegNet outperformed FCN-AlexNet in image semantic segmentation tasks in terms of the evaluation between training and validation. The average inference speed of the semantic image segmentation model is 0.7s with segmentation identification accuracy is 89%. The promising results shed light on many agriculture applications, such as crop growth condition assessment, fertilizer management, and yield prediction. Additionally, this research provides possible solutions for the labor shortage issue of agriculture which is a common challenge in an aging community like Taiwan and many countries worldwide.","PeriodicalId":443862,"journal":{"name":"2020 IEEE 17th Annual Consumer Communications & Networking Conference (CCNC)","volume":"499 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124566654","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: 13

High Security Bare Metal Bluetooth Blockchain Payment Terminal For Trusted Ethereum Transaction 用于可信以太坊交易的高安全性裸机蓝牙区块链支付终端

2020 IEEE 17th Annual Consumer Communications & Networking Conference (CCNC) Pub Date : 2020-01-01 DOI: 10.1109/CCNC46108.2020.9045146

P. Urien

引用次数: 2

Load Balancing in Cellular Networks: A Reinforcement Learning Approach 蜂窝网络中的负载平衡:一种强化学习方法

2020 IEEE 17th Annual Consumer Communications & Networking Conference (CCNC) Pub Date : 2020-01-01 DOI: 10.1109/CCNC46108.2020.9045699

Kareem M. Attiah, Karim A. Banawan, Ayman Gaber, A. Elezabi, Karim G. Seddik, Y. Gadallah, Kareem Abdullah

引用次数: 13

Remote Authentication Using an Ultra-Wideband Radio Frequency Transceiver 使用超宽带射频收发器的远程认证

2020 IEEE 17th Annual Consumer Communications & Networking Conference (CCNC) Pub Date : 2020-01-01 DOI: 10.1109/CCNC46108.2020.9045438

Seong Kyu Leem, Faheem Khan, S. Cho

{"title":"Remote Authentication Using an Ultra-Wideband Radio Frequency Transceiver","authors":"Seong Kyu Leem, Faheem Khan, S. Cho","doi":"10.1109/CCNC46108.2020.9045438","DOIUrl":"https://doi.org/10.1109/CCNC46108.2020.9045438","url":null,"abstract":"In this paper, we propose three new authentication methods using ultra-wideband (UWB) radio frequency (RF) signals. These mid-air-based authentication techniques are different from the conventional touch-based authentication approaches and provide a more convenient and safer user experience. In these methods, the impulse radio UWB transceiver receives the reflected RF signal corresponding to the movement pattern of the user, extracts the pattern information after noise removal, and converts it into image data suitable for use as classifier input through image signal processing. After that, it verifies whether the pattern is the authentication pattern of the user by employing a convolutional neural network and a one-class support vector machine. This report describes the three proposed authentication methods using the advantages of UWB RF signals, as well as their experimental verification. In the first authentication method, ShapeSec, authentication is performed by writing a simple shape pattern in the air. This technique is simple but very convenient. The second method, SignSec, correctly detects the handwriting of different users when signing and overcomes the security vulnerability of signing with the existing pens. Finally, BreatheSec is based on breathing patterns and takes advantage of the ability of a UWB RF transceiver to detect minute breath movements. The authentication pattern could not be imitated even after it was watched from the side, proving that the proposed method has excellent security characteristics. Experiments showed that each method has over 95% accuracy.","PeriodicalId":443862,"journal":{"name":"2020 IEEE 17th Annual Consumer Communications & Networking Conference (CCNC)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121570738","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: 6

Machine Learning-Based MIMO Enabling Techniques for Energy Optimization in Cellular Networks 基于机器学习的蜂窝网络能量优化MIMO使能技术

2020 IEEE 17th Annual Consumer Communications & Networking Conference (CCNC) Pub Date : 2020-01-01 DOI: 10.1109/CCNC46108.2020.9045149

Mariam M. N. Aboelwafa, M. Zaki, Ayman Gaber, Karim G. Seddik, Y. Gadallah, A. Elezabi

引用次数: 2

Deceptor-in-the-Middle (DitM): Cyber Deception for Security in Wireless Network Virtualization 中间欺骗者(DitM):无线网络虚拟化中的网络欺骗安全

2020 IEEE 17th Annual Consumer Communications & Networking Conference (CCNC) Pub Date : 2020-01-01 DOI: 10.1109/CCNC46108.2020.9045164

Abdulhamid A. Adebayo, D. Rawat

{"title":"Deceptor-in-the-Middle (DitM): Cyber Deception for Security in Wireless Network Virtualization","authors":"Abdulhamid A. Adebayo, D. Rawat","doi":"10.1109/CCNC46108.2020.9045164","DOIUrl":"https://doi.org/10.1109/CCNC46108.2020.9045164","url":null,"abstract":"Wireless virtualization has emerged as a technology of interest to overcome resource sharing problem by allowing multiple virtual networks to access the same physical wireless infrastructure concurrently based on service level agreements (SLAs). The main focus so far has been on improving the efficiency of wireless resource sharing process. From a security perspective, this technology and its variations have not commanded as much attention partly due to the early state of wireless virtualization development and the undefined nature of potential attacks. In this paper, we present a Deceptor-in-the-Middle (DitM) cyber-deception mechanism that leverages the wireless virtualization architecture to enable virtual network operators to learn about the interest and nature of attacks without the attacker being aware and also not compromising the security and quality of service requirements of the virtual network users. We also propose a detection mechanism for identifying the presence of an attacker and redirecting to deception virtual networks. The performance of the proposed approach is evaluated using numerical results obtained from Monte Carlo simulations. The numerical results signify that the proposed DitM results in higher throughput than that of without the deceptor. We also analyzed the DitM using different metrics including the probability of miss detection and false alarm.","PeriodicalId":443862,"journal":{"name":"2020 IEEE 17th Annual Consumer Communications & Networking Conference (CCNC)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114262033","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: 6

Evaluating the performance of NRENs in deploying IoT in Africa: the case for TTN 评估nren在非洲部署物联网的表现:以TTN为例

2020 IEEE 17th Annual Consumer Communications & Networking Conference (CCNC) Pub Date : 2020-01-01 DOI: 10.1109/CCNC46108.2020.9045213

M. Zennaro, C. Pelsser, F. Albinet, P. Manzoni

引用次数: 5

Performance of SWIPT in Cell-free Massive MIMO: A Stochastic Geometry Based Perspective SWIPT在无单元大规模MIMO中的性能:基于随机几何的视角

2020 IEEE 17th Annual Consumer Communications & Networking Conference (CCNC) Pub Date : 2020-01-01 DOI: 10.1109/CCNC46108.2020.9045726

S. Kusaladharma, Weiping Zhu, W. Ajib, Gayan Amarasuriya

{"title":"Performance of SWIPT in Cell-free Massive MIMO: A Stochastic Geometry Based Perspective","authors":"S. Kusaladharma, Weiping Zhu, W. Ajib, Gayan Amarasuriya","doi":"10.1109/CCNC46108.2020.9045726","DOIUrl":"https://doi.org/10.1109/CCNC46108.2020.9045726","url":null,"abstract":"Simultaneous wireless information and power transfer (SWIPT) is increasingly seen as a viable technique to power energy constrained user devices while transmitting data. SWIPT can be readily implemented within the recently proposed cell-free massive MIMO networks, where a large number of interconnected access points (APs) simultaneously serve users. This paper characterizes the coexistence and interplay between these two technologies by using tools from stochastic geometry. To this end, we consider a spatially random network, where the APs are modeled stochastically using a Poisson point process, and a time-switching protocol is used for the SWIPT operation at the users. A time-division-duplexing protocol is considered in which uplink pilots are used to obtain channel state information at the APs, while conjugate beamforming is performed in the downlink. Moreover, we consider blockages due to obstacles in the channel and the resulting line-of-sight and non-line-of-sight conditions affecting the fading and path loss. We derive the mean and variance of the harvested energy along with the average achievable rate in the downlink for an energy user. The tradeoff between the downlink data throughput and harvested energy is quantified, and thereby, we show that spatially-distributed APs in a cell-free arrangement can boost the energy-rate trade-off of SWIPT.","PeriodicalId":443862,"journal":{"name":"2020 IEEE 17th Annual Consumer Communications & Networking Conference (CCNC)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114506731","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: 5

On BER of Fixed-Scale MIMO Underwater Wireless Optical Communication Systems 固定尺度MIMO水下无线光通信系统误码率研究

2020 IEEE 17th Annual Consumer Communications & Networking Conference (CCNC) Pub Date : 2020-01-01 DOI: 10.1109/CCNC46108.2020.9045256

Runing Xu, Yingjie Chen, Zixian Wei, H. Fu, Julian Cheng, Yuhan Dong

引用次数: 1