2021 IEEE 6th International Conference on Computer and Communication Systems (ICCCS)最新文献_第9页

An SDN Based Highly Reliable in-Band Control Framework for LEO Mega-Constellations 基于SDN的低轨道巨型星座高可靠带内控制框架

2021 IEEE 6th International Conference on Computer and Communication Systems (ICCCS) Pub Date : 2021-04-23 DOI: 10.1109/ICCCS52626.2021.9449244

Ningyuan Wang, Chen Dong, Liang Liu, Wang Mian, Bingyuan Liang

引用次数: 2

Distribution Based Learning Network for Motor Imagery Electroencephalogram Classification 基于分布的运动图像脑电图分类学习网络

2021 IEEE 6th International Conference on Computer and Communication Systems (ICCCS) Pub Date : 2021-04-23 DOI: 10.1109/ICCCS52626.2021.9449094

Annan Wang, Ziyang Gong

引用次数: 1

Design of Low Spurious Phase Locked Loop for Vector Network Analyzer 矢量网络分析仪低杂散锁相环设计

2021 IEEE 6th International Conference on Computer and Communication Systems (ICCCS) Pub Date : 2021-04-23 DOI: 10.1109/ICCCS52626.2021.9449298

E. Chen, Qinglong Zhang, Yubin Yang, Zhiying Cao, Shengkai Sun

引用次数: 0

A Method of Measuring Data Fusion Based on EMBET 基于EMBET的测量数据融合方法

2021 IEEE 6th International Conference on Computer and Communication Systems (ICCCS) Pub Date : 2021-04-23 DOI: 10.1109/ICCCS52626.2021.9449219

Kechang Qian, Ying Wan, Youchen Fan, Dapeng Xiong

引用次数: 0

Convolutional Neural Network-Based Obstructive Sleep Apnea Identification 基于卷积神经网络的阻塞性睡眠呼吸暂停识别

2021 IEEE 6th International Conference on Computer and Communication Systems (ICCCS) Pub Date : 2021-04-23 DOI: 10.1109/ICCCS52626.2021.9449255

Qimin Dong, Y. Jiraraksopakun, A. Bhatranand

{"title":"Convolutional Neural Network-Based Obstructive Sleep Apnea Identification","authors":"Qimin Dong, Y. Jiraraksopakun, A. Bhatranand","doi":"10.1109/ICCCS52626.2021.9449255","DOIUrl":"https://doi.org/10.1109/ICCCS52626.2021.9449255","url":null,"abstract":"Obstructive Sleep Apnea (OSA) identification aims to recognize the sounds from the obstructive sleep apneahypopnea syndrome (OSANHS) patients. Despite remarkable advances have been made, the performance heavily relies on the sound representation. Feature selection is needed to improve the performance. Generally, the normal snoring and the snoring of OSANHS patients have a greater difference in acoustic characteristics. Ordinary snoring of human breathing is a regular, fluctuating and cyclical state, while OSANHS pathological snoring is often accompanied by a long pause. Based on the acoustic characteristics, this paper proposes an OSA recognition algorithm based on a convolutional neural network. First, the Mel-scale frequency cepstral coefficient (MFCC) of the sound are extracted. Then, convolutional neural network is deployed to predict the possibility of OSA. To empirically investigate the effectiveness and robustness of the proposed approach, extensive experiments were performed on a benchmark dataset. The obtained results showed that our method significantly outperforms related baselines and is also competitive or superior to the recently reported systems.","PeriodicalId":376290,"journal":{"name":"2021 IEEE 6th International Conference on Computer and Communication Systems (ICCCS)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116839787","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

A Novel Modified Sparrow Search Algorithm Based on Adaptive Weight and Improved Boundary Constraints 一种基于自适应权值和改进边界约束的麻雀搜索算法

2021 IEEE 6th International Conference on Computer and Communication Systems (ICCCS) Pub Date : 2021-04-23 DOI: 10.1109/ICCCS52626.2021.9449311

Qian Liang, Bin Chen, Huaning Wu, Meng Han

引用次数: 3

A Pilot-Aided Method of Doppler Offset Estimation and Compensation 一种导航辅助的多普勒偏置估计与补偿方法

2021 IEEE 6th International Conference on Computer and Communication Systems (ICCCS) Pub Date : 2021-04-23 DOI: 10.1109/ICCCS52626.2021.9449150

Zhao-Ming Huang

引用次数: 3

Construction of Power Communication Network Knowledge Graph with BERT-BiLSTM-CRF Model Based Entity Recognition 基于BERT-BiLSTM-CRF模型实体识别的电力通信网知识图谱构建

2021 IEEE 6th International Conference on Computer and Communication Systems (ICCCS) Pub Date : 2021-04-23 DOI: 10.1109/ICCCS52626.2021.9449229

Haiyang Wu, Peng Chen, Wei Li, Yong Dai, Chunxia Jiang, Jixuan Li, Pengyu Zhu

{"title":"Construction of Power Communication Network Knowledge Graph with BERT-BiLSTM-CRF Model Based Entity Recognition","authors":"Haiyang Wu, Peng Chen, Wei Li, Yong Dai, Chunxia Jiang, Jixuan Li, Pengyu Zhu","doi":"10.1109/ICCCS52626.2021.9449229","DOIUrl":"https://doi.org/10.1109/ICCCS52626.2021.9449229","url":null,"abstract":"By extensively mining system data and integrating with artificial intelligence means, knowledge graph can be exploited in various tasks of power communication network, effectively prompting the efficiency and performance of maintenance. One of the pivotal step of the knowledge graph construction is the named entity recognition. Abundant semantic features extracted from corpus can directly improve the accuracy of resulting concepts in knowledge graph. However, existing entity recognition method is mainly based on conventional word embedding technique such as Word2Vec, which still focuses on information within single word. In this paper, we propose to construct knowledge graph with the most recently proposed BERT-BiLSTM-CRF. This model can fully consider contextual information over words and extract more semantic features for further procedures. Our experimental results on realistic maintenance data of power communication networks proved the efficacy of BERT-BiLSTM-CRF model in the construction of knowledge graph. With the assistance of knowledge graph, we build applications for two typical maintenance scenarios, process standardization and fault disposal instruction, respectively. The knowledge graph has shown promising prospect as a novel auxiliary mechanism to power communication networks.","PeriodicalId":376290,"journal":{"name":"2021 IEEE 6th International Conference on Computer and Communication Systems (ICCCS)","volume":"os-10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127687860","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

Design and Simulation of VANETs Testbed Using OpenStreetMap, SUMO, and NS-2 基于OpenStreetMap、SUMO和NS-2的VANETs试验台设计与仿真

2021 IEEE 6th International Conference on Computer and Communication Systems (ICCCS) Pub Date : 2021-04-23 DOI: 10.1109/ICCCS52626.2021.9449197

Claude Nawej, P. Owolawi, Tom Walingo

引用次数: 2

A Keystroke-based Continuous User Authentication in Virtual Desktop Infrastructure 虚拟桌面基础架构中基于按键的连续用户认证

2021 IEEE 6th International Conference on Computer and Communication Systems (ICCCS) Pub Date : 2021-04-23 DOI: 10.1109/ICCCS52626.2021.9449286

Lulu Yang, Chen Li, Ruibang You, Bibo Tu

{"title":"A Keystroke-based Continuous User Authentication in Virtual Desktop Infrastructure","authors":"Lulu Yang, Chen Li, Ruibang You, Bibo Tu","doi":"10.1109/ICCCS52626.2021.9449286","DOIUrl":"https://doi.org/10.1109/ICCCS52626.2021.9449286","url":null,"abstract":"Demand for remote work has surged as the COVID-19 epidemic has spread around the world. As one of the main implementations of desktop virtualization, Virtual Desktop Infrastructure (VDI) is popular and widely used in corporate remote work. A VDI user can connect to and use a virtual machine in a remote data center by logging in with a username and password using any device anywhere with Internet access. VDI has mobile convenience but is at risk of password leakage and insider threat. Traditional authentication methods, such as password and PIN, cannot withstand these threats. This work presents a keystroke-based continuous user authentication based on the Bidirectional Long Short-Term Memory (Bi-LSTM) network and embedding mechanism in deep learning to defend against such risks. It verifies the current user's identity based on the user's typing behavior continuously and non-invasively. We implement it on SPICE VDI and evaluate its performance and deployment feasibility on a public keystroke dataset - the Clarkson II dataset, which collected in uncontrolled and natural settings. The results show that it achieves state-of-art performance. It detects intruders with 8.28% of EER when only using 30 keystrokes and 0.85% of EER when using 990 keystrokes.","PeriodicalId":376290,"journal":{"name":"2021 IEEE 6th International Conference on Computer and Communication Systems (ICCCS)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117031532","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