2019 IEEE 5th International Conference on Computer and Communications (ICCC)最新文献_第2页

Privacy-protected Electronic Voting System Based on Blockchin and Trusted Execution Environment 基于区块链和可信执行环境的隐私保护电子投票系统

2019 IEEE 5th International Conference on Computer and Communications (ICCC) Pub Date : 2019-12-01 DOI: 10.1109/ICCC47050.2019.9064387

Yuxian Zhang, Yi Li, Li Fang, Ping Chen, Xinghua Dong

引用次数: 12

An Inversion for LF-NMR Signals Processing with BFGS Algorithm 用BFGS算法反演LF-NMR信号处理

2019 IEEE 5th International Conference on Computer and Communications (ICCC) Pub Date : 2019-12-01 DOI: 10.1109/ICCC47050.2019.9064303

Lang Chen, Rongsheng Lu, Yuchen Wu, Z. Ni

引用次数: 0

Research on Privacy Concerns of Social Network Users 社交网络用户隐私问题研究

2019 IEEE 5th International Conference on Computer and Communications (ICCC) Pub Date : 2019-12-01 DOI: 10.1109/ICCC47050.2019.9064266

Qiutian Sun, Yabin Xu

引用次数: 2

Dynamic Control Model Based on State Perception 基于状态感知的动态控制模型

2019 IEEE 5th International Conference on Computer and Communications (ICCC) Pub Date : 2019-12-01 DOI: 10.1109/ICCC47050.2019.9064363

Anying Chai, Yue Ma, Zhenyu Yin, Mingshi Li, Zhihao Zhao

{"title":"Dynamic Control Model Based on State Perception","authors":"Anying Chai, Yue Ma, Zhenyu Yin, Mingshi Li, Zhihao Zhao","doi":"10.1109/ICCC47050.2019.9064363","DOIUrl":"https://doi.org/10.1109/ICCC47050.2019.9064363","url":null,"abstract":"The monitoring system built on the OPC UA (object linking and embedding (OLE) for process control unified architecture) protocol cannot detect the congestion of each terminal network and the load pressure of the cluster server nodes in real time. In the case that the number of terminal accesses is increasing and the traffic volume is gradually increasing, some server nodes of the system are overloaded or crash. In response to these questions, this paper presents a dynamic control model based on state perception. This model can perceive the communication state of client and server in real time, and uses the current resource occupancy index of the server and the network congestion indicators of each client as the adjustment conditions. The model algorithm can dynamically adjust the client served by the overload node to the server node with small load. Meanwhile, the model uses the congestion estimation method based on bandwidth estimation to accurately estimate the network conditions of each client and improve the validity of state-aware information. The simulation results show that the model can sense the load of each server and make reasonable adjustments to achieve a good load balancing effect. At the same time, the experiment verifies the feasibility and efficiency of the model.","PeriodicalId":6739,"journal":{"name":"2019 IEEE 5th International Conference on Computer and Communications (ICCC)","volume":"6 1","pages":"1406-1411"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79122830","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: 3

Research of Adaptive Routing Scheme for LEO Network LEO网络自适应路由方案研究

2019 IEEE 5th International Conference on Computer and Communications (ICCC) Pub Date : 2019-12-01 DOI: 10.1109/ICCC47050.2019.9064312

Yuancao Lv, Chuan Xing, Nan Xu, Xiaodong Han, Feng-Chao Wang

引用次数: 6

Full Attention-Based Bi-GRU Neural Network for News Text Classification 基于全注意力的Bi-GRU神经网络新闻文本分类

2019 IEEE 5th International Conference on Computer and Communications (ICCC) Pub Date : 2019-12-01 DOI: 10.1109/ICCC47050.2019.9064061

Qinting Tang, Jian Li, Jiayu Chen, Hengtong Lu, Yu Du, Kehan Yang

{"title":"Full Attention-Based Bi-GRU Neural Network for News Text Classification","authors":"Qinting Tang, Jian Li, Jiayu Chen, Hengtong Lu, Yu Du, Kehan Yang","doi":"10.1109/ICCC47050.2019.9064061","DOIUrl":"https://doi.org/10.1109/ICCC47050.2019.9064061","url":null,"abstract":"This paper proposes a novel approach for text classification by using attention mechanism. In recent works, several models based on deep learning with traditional attention mechanism mainly learn the weights of steps in the entire text. However, the information of each step is filtered by the encoder, and the same information has different effects on different steps. This paper proposes a full attention-based bidirectional GRU (Bi-GRU) neural network, which is called FABG. FABG uses a Bi-GRU to learn the semantic information of text, and uses full attention mechanism to learn the weights of previous and current outputs of the Bi-GRU at each step, which enables the representation of each step to obtain the important information and ignore the irrelevant information. Finally, through a pooling layer, we get the representation of the text. Thereby FABG can learn more information, which enhances the effect of text classification. Experiments on the English news dataset agnews and the Chinese news dataset chnews show that FABG achieve better performance than the baselines.","PeriodicalId":6739,"journal":{"name":"2019 IEEE 5th International Conference on Computer and Communications (ICCC)","volume":"1 1","pages":"1970-1974"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84442139","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: 8

Rate Analysis of Full-Pilot Zero-Forcing in Cell-Free Massive MIMO with Low- Resolution ADCs 低分辨率adc无小区大规模MIMO全导频零强迫速率分析

2019 IEEE 5th International Conference on Computer and Communications (ICCC) Pub Date : 2019-12-01 DOI: 10.1109/ICCC47050.2019.9064282

X. Ruan, Meng Zhou, Xu Qiao, Xiaotao Wang, Yao Zhang, Longxiang Yang

{"title":"Rate Analysis of Full-Pilot Zero-Forcing in Cell-Free Massive MIMO with Low- Resolution ADCs","authors":"X. Ruan, Meng Zhou, Xu Qiao, Xiaotao Wang, Yao Zhang, Longxiang Yang","doi":"10.1109/ICCC47050.2019.9064282","DOIUrl":"https://doi.org/10.1109/ICCC47050.2019.9064282","url":null,"abstract":"In contrast to classical zero-forcing (ZF) receiver, a new one called full-pilot zero-forcing (fpZF) receiver is exploited in our work. Based on this, we investigate the achievable uplink rate of a cell-free massive multi-input multi-output (MIMO) system with low-resolution analog-to-digital converters (ADCs) at the access points (APs). In order to carry out the tractable analysis on multiple quantization bits, we advocate the additive quantization noise model (AQNM). Quantization technology is a very effective method to lower the cost of transmission in the case where high data fidelity is not needed. After each AP receiving the payload data transmitted from all users, the quantization procedure is implemented in a distributed manner. Then a closed-form expression of achievable uplink rate is derived, which helps us to investigate system performance. The results in our simulation experiments indicate the fpZF receiver performs much better than the conjugate beamforming (CB) receiver when high-bit ADCs are used to process these received signals. However, when few-bit ADCs are adopted, its performance will decrease a lot and is dramatically inferior to the CB receiver, which is not as well as we expect. This observation demonstrates the fpZF receiver is more sensitive to the quantization operation than the CB receiver.","PeriodicalId":6739,"journal":{"name":"2019 IEEE 5th International Conference on Computer and Communications (ICCC)","volume":"185 1","pages":"2072-2076"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86006209","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-Task Collaborative Scheduling System for Industrial Control Data Acquisition 工业控制数据采集多任务协同调度系统

2019 IEEE 5th International Conference on Computer and Communications (ICCC) Pub Date : 2019-12-01 DOI: 10.1109/ICCC47050.2019.9064250

Wei Yang, Jinlei Zhou, Xinna Zhou, Yu Yao

引用次数: 0

Simulated Analysis of Processing Satellite Laser Ranging Data Using Neural Networks Trained by DeepLabCut deepplabcut训练神经网络处理卫星激光测距数据的仿真分析

2019 IEEE 5th International Conference on Computer and Communications (ICCC) Pub Date : 2019-12-01 DOI: 10.1109/ICCC47050.2019.9064092

Li Xue, Zhaokun Zhu, Wentang Wu, Meiya Duan, Kunpeng Wang, Dongya Wang

{"title":"Simulated Analysis of Processing Satellite Laser Ranging Data Using Neural Networks Trained by DeepLabCut","authors":"Li Xue, Zhaokun Zhu, Wentang Wu, Meiya Duan, Kunpeng Wang, Dongya Wang","doi":"10.1109/ICCC47050.2019.9064092","DOIUrl":"https://doi.org/10.1109/ICCC47050.2019.9064092","url":null,"abstract":"With the development of high-repetition rate laser ranging, huge amount of laser ranging data are generated. DeepLabCut is a novel automatic annotation method for markerless motion capture from big data. With the advantage of only small size of training dataset needed, it has been successfully applied to various research fields. However, few researches can be found related to data processing for satellite laser ranging using DeepLabCut method. In this paper, different satellite laser ranging data are simulated by two polynomials according to the characteristics of echoes and noise. Secondly, two extraction strategies of time-drift and global-uniform are proposed for key points extraction to generate training datasets as ground truth. And two training datasets including 50 key points from 10 frames and 5 frames are generated, respectively. Then, deep neural networks are trained using DeepLabCut based on the training datasets. Finally, satellite laser ranging data as videos are tested with the trained neural networks. Results show that the key points suffered from drift and mismatching without uniform distribution, which indicates that DeepLabCut is not an applicable method based on the two proposed extraction strategies for satellite laser ranging data processing. Possible reasons including image textures, indiscrimination of echoes and noise are concluded. The simulation analysis in this paper is useful for deciding whether to apply DeepLabCut to process satellite laser ranging data.","PeriodicalId":6739,"journal":{"name":"2019 IEEE 5th International Conference on Computer and Communications (ICCC)","volume":"72 1","pages":"468-472"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84122209","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

An Improved Genetic Algorithm 一种改进的遗传算法

2019 IEEE 5th International Conference on Computer and Communications (ICCC) Pub Date : 2019-12-01 DOI: 10.1109/ICCC47050.2019.9064374

Liyuan Deng, Ping Yang, Weidong Liu

引用次数: 0