Proceedings of the 2018 VII International Conference on Network, Communication and Computing最新文献_第3页

Research of Palmprint Authentication Arithmetic Based on Smartphone 基于智能手机的掌纹认证算法研究

Proceedings of the 2018 VII International Conference on Network, Communication and Computing Pub Date : 2018-12-14 DOI: 10.1145/3301326.3301382

Xinman Zhang, Kunlei Jing, Guoqi Yan, Xuebin Xu, Weiyong Gong

引用次数: 1

Performance Analysis of Full Duplex Network Based on Non-orthogonal Multiple Access 基于非正交多址的全双工网络性能分析

Proceedings of the 2018 VII International Conference on Network, Communication and Computing Pub Date : 2018-12-14 DOI: 10.1145/3301326.3301366

Kaikai Wang, Kaixin Zhang

引用次数: 0

Modeling and Analysis of the Anti-Jamming (AJ) Spread Spectrum System Using Quantized Chaotic Sequence with LDPC for Reliable Data Link 基于量化混沌序列和LDPC的可靠数据链路抗干扰扩频系统建模与分析

Proceedings of the 2018 VII International Conference on Network, Communication and Computing Pub Date : 2018-12-14 DOI: 10.1145/3301326.3301340

Wei Wei, Junghwan Kim

{"title":"Modeling and Analysis of the Anti-Jamming (AJ) Spread Spectrum System Using Quantized Chaotic Sequence with LDPC for Reliable Data Link","authors":"Wei Wei, Junghwan Kim","doi":"10.1145/3301326.3301340","DOIUrl":"https://doi.org/10.1145/3301326.3301340","url":null,"abstract":"Due to the capability of interference rejection and low probability of interception (LPI), the spread spectrum technique is widely used in modern data link. However, its wideband, low power spectral density (PSD) signal may result in the degradation of the reliable data communication. To compensate this drawback, utilization of low density parity check (LDPC) can significantly reduce the required signal-to-noise ratio (SNR) per information bit for fixed bit error rate (BER), while quantized chaotic sequence makes the fixed energy-per-bit Eb for the quality of reliable data communication. In this work, toward an appropriate anti-jamming (AJ) spread spectrum system using chaotic waveform against possible jamming scenarios, the 1-bit quantized chaotic sequence generated from the chaotic waveform using the Logistic Map is utilized as the spreading code as well as the differential chaos shift keying (DCSK) as the modulation scheme. The simulation results shows that, under single-tone jamming (STJ), the power requirement of the spread spectrum requires only about -5 dB power for the fixed BER of 10-6 in additive white Gaussian noise (AWGN). Obviously, it shows that SNR per information bit requirement of the system for the targeted BER has been greatly reduced due to the use of LDPC and quantized chaotic sequence.","PeriodicalId":294040,"journal":{"name":"Proceedings of the 2018 VII International Conference on Network, Communication and Computing","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127533069","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

End-to-end Multiplayer Violence Detection based on Deep 3D CNN 基于深度3D CNN的端到端多人暴力检测

Proceedings of the 2018 VII International Conference on Network, Communication and Computing Pub Date : 2018-12-14 DOI: 10.1145/3301326.3301367

Chengyang Li, Liping Zhu, Dandan Zhu, Jiale Chen, Z. Pan, Xue Li, Bing Wang

引用次数: 12

Evaluating Machine Learning Models for Android Malware Detection: A Comparison Study 评估Android恶意软件检测的机器学习模型:一项比较研究

Proceedings of the 2018 VII International Conference on Network, Communication and Computing Pub Date : 2018-12-14 DOI: 10.1145/3301326.3301390

M. Rana, Charan Gudla, A. Sung

引用次数: 24

Efficient Copy-Move Forgery Detection using Blur and Rotation Invariant Technique 使用模糊和旋转不变性技术的高效复制-移动伪造检测

Proceedings of the 2018 VII International Conference on Network, Communication and Computing Pub Date : 2018-12-14 DOI: 10.1145/3301326.3301327

Ankita Verma, V. Kapoor, Sangita Roy

引用次数: 1

An Instruction Blocking Methods for Disk Data Protection 一种用于磁盘数据保护的指令阻塞方法

Proceedings of the 2018 VII International Conference on Network, Communication and Computing Pub Date : 2018-12-14 DOI: 10.1145/3301326.3301334

Di Xue, Jingmei Li, Weifei Wu, Jiaxiang Wang, Xiaoyun Wang

引用次数: 0

A Deep Learning Based Geosteering Method Assembled with "Wide-angle Eye" 基于深度学习的“广角眼”组合地质导向方法

Proceedings of the 2018 VII International Conference on Network, Communication and Computing Pub Date : 2018-12-14 DOI: 10.1145/3301326.3301370

Yi Liu, Dandan Zhu, Hao Liu, A. Du, Dong Chen, Zhihui Ye

{"title":"A Deep Learning Based Geosteering Method Assembled with \"Wide-angle Eye\"","authors":"Yi Liu, Dandan Zhu, Hao Liu, A. Du, Dong Chen, Zhihui Ye","doi":"10.1145/3301326.3301370","DOIUrl":"https://doi.org/10.1145/3301326.3301370","url":null,"abstract":"The intelligent guided drilling system adopts the precise guided drilling geological system and a new rotary steering drilling tool to achieve deep drilling intelligent cruise. It can increase the amount of oil and gas exploration and ensure safety in production. However, the geosteering problem in deep wells and ultra-deep wells is still an outstanding issue due to the hostile environment for signal transmission. In this research, an autonomous geosteering method based on deep learning model is proposed, which is able to make the strategic decision of the drill bit direction in downhole operating mode. According to the characteristics of the Logging While Drilling (LWD) data, the \"Wide-angle Eye\" mechanism is embedded to feel the future change of stratum ahead and give preview information to the drill bit. Consequencely, the Drilling Decision Model is designed to be a Convolutional Neural Network (ConvNet). The performance of the proposed model was validated in simulation, and the experimental results indicate that the proposed method has high accuracy and robustness, appearing an enhanced capacity to predict stratigraphic changes.","PeriodicalId":294040,"journal":{"name":"Proceedings of the 2018 VII International Conference on Network, Communication and Computing","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127581333","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

Investigating the Influence of CPU Load, Memory Usage and Environmental Conditions on the Jittering of Android Devices 调查CPU负载，内存使用和环境条件对Android设备抖动的影响

Proceedings of the 2018 VII International Conference on Network, Communication and Computing Pub Date : 2018-12-14 DOI: 10.1145/3301326.3301361

Maik Benndorf, M. Kaden, Frederic Ringsleben, Christian Roschke, Rico Thomanek, M. Gaedke, T. Haenselmann

引用次数: 0

A Reinforcement Learning Based 3D Guided Drilling Method: Beyond Ground Control 一种基于强化学习的三维导向钻井方法:超越地面控制

Proceedings of the 2018 VII International Conference on Network, Communication and Computing Pub Date : 2018-12-14 DOI: 10.1145/3301326.3301374

Hao Liu, Dandan Zhu, Yi Liu, A. Du, Dong Chen, Zhihui Ye

{"title":"A Reinforcement Learning Based 3D Guided Drilling Method: Beyond Ground Control","authors":"Hao Liu, Dandan Zhu, Yi Liu, A. Du, Dong Chen, Zhihui Ye","doi":"10.1145/3301326.3301374","DOIUrl":"https://doi.org/10.1145/3301326.3301374","url":null,"abstract":"The current drilling guide operation relies on the two-way transmission of signals between the downhole drilling tools and the ground control center. However, the downhole environment is sometimes not conducive to such real-time signal transmission, and the analysis and decision-making in the ground involves complex human expert analysis and fine management. To deal with these problems, this paper proposes a downhole self-steering guided drilling method based on a reinforcement learning framework to achieve the 3D well trajectory design and control in real-time. In every time interval of the drilling process, the proposed system evaluates the drilling status and gives the adjustment action of drill bit in 3D space according to the received data, guiding the drill bit to the target reservoir without the involvement of human. The main module is a modified deep Q network using Sarsa algorithm for online self-learning. The experimental results show that after training, the drill bit is increasingly able to select control actions closer to the target reservoir. The frequency of effective actions is approximately 258% higher after the algorithm converges. The proposed system has the ability of online self-learning, which can automatically adjust the evaluation and decision models without manual monitoring.","PeriodicalId":294040,"journal":{"name":"Proceedings of the 2018 VII International Conference on Network, Communication and Computing","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121637086","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