2021 13th International Conference on Communication Software and Networks (ICCSN)最新文献_第4页

Reliability Implementation Technology of Distrubution Automation System Based on 5G 基于5G的配电自动化系统可靠性实现技术

2021 13th International Conference on Communication Software and Networks (ICCSN) Pub Date : 2021-06-04 DOI: 10.1109/ICCSN52437.2021.9463661

M. Yue, Wu Shaocheng, Liang Honghao, Chen Xiaowei, Li Xiang, Huang Wenqian

引用次数: 0

Injection Tube Direction Recognition Based on Boundary Correction and Support Vector Machine 基于边界校正和支持向量机的注射管方向识别

2021 13th International Conference on Communication Software and Networks (ICCSN) Pub Date : 2021-06-04 DOI: 10.1109/ICCSN52437.2021.9463646

Sen-quan Yang, Fan Ding, Pu Li, Songxi Hu

引用次数: 0

Object Tracking in Satellite Videos Based on Improved Correlation Filters 基于改进相关滤波器的卫星视频目标跟踪

2021 13th International Conference on Communication Software and Networks (ICCSN) Pub Date : 2021-06-04 DOI: 10.1109/ICCSN52437.2021.9463667

Liu Yaosheng, Liao Yurong, Lin Cunbao, Li Zhaoming, Yang Xinyan, Zhang Aidi

{"title":"Object Tracking in Satellite Videos Based on Improved Correlation Filters","authors":"Liu Yaosheng, Liao Yurong, Lin Cunbao, Li Zhaoming, Yang Xinyan, Zhang Aidi","doi":"10.1109/ICCSN52437.2021.9463667","DOIUrl":"https://doi.org/10.1109/ICCSN52437.2021.9463667","url":null,"abstract":"With the continuous progress of the society, video satellite has been paid more and more attention. As a new type of earth observation satellite, it can observe the certain area and obtain more and more dynamic information than traditional satellites. In this paper, we propose a novel algorithm based on the improved kernel correlation filters (KCF) to track the object in satellite videos. The improvements are as follows: 1) fusing the different features of the object, whose purpose is to describe the object information more effectively and reduce the impact of moving scene changes in object tracking and 2) proposing a motion position compensation algorithm through combines Kalman filter and motion trajectory. Its purpose is to improve the effectiveness of object tracking and avoid tracking error when used alone. What is more important is that it can also solve the problem of tracking failure when the object is partially or completely occluded and 3) extracting the local object region for normalized cross-correlation matching, and its function is to improve the success rate and accuracy of object tracking. The experimental results show that our algorithm can more effectively track the moving object in satellite video with high accuracy.","PeriodicalId":263568,"journal":{"name":"2021 13th International Conference on Communication Software and Networks (ICCSN)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123502627","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

A Time-Frequency Information Based Method for BSS Output FH Signal Recognition 基于时频信息的BSS输出跳频信号识别方法

2021 13th International Conference on Communication Software and Networks (ICCSN) Pub Date : 2021-06-04 DOI: 10.1109/ICCSN52437.2021.9463637

Miao Yu, Longsheng Yu, Cheng Li, Ba Xu

{"title":"A Time-Frequency Information Based Method for BSS Output FH Signal Recognition","authors":"Miao Yu, Longsheng Yu, Cheng Li, Ba Xu","doi":"10.1109/ICCSN52437.2021.9463637","DOIUrl":"https://doi.org/10.1109/ICCSN52437.2021.9463637","url":null,"abstract":"Frequency hopping (FH) communication signal is usually statistically independent from common jamming signals. Blind source separation (BSS) or independent component analysis (ICA) can be introduced to separate the useful FH communication signal from the jamming signals. Through the separation, the jamming signals are suppressed and the quality of the object signal is improved. However, BSS is suffered from the inherent permutation ambiguity, which makes it difficult to select object signal from the multiple separated signals. According to the frequency spectrum characteristics of FH signal, a time-frequency (TF) information based method for FH signal recognition is proposed. Firstly, the TF matrices of the separated signal and the expected FH signal are constructed respectively. Secondly, the correlation value between each separated TF matrix and the expected TF matrix is calculated. Finally, the separated signal which has the biggest correlation value is identified as the object FH signal. The proposed method can eliminate the permutation ambiguity of BSS, so as to make BSS more applicable. Simulation experiments are carried out to test the performance of the proposed method. The simulation results show that the proposed method can recognize the FH signal among the multiple separated signals effectively.","PeriodicalId":263568,"journal":{"name":"2021 13th International Conference on Communication Software and Networks (ICCSN)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114194038","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

Machine Learning-Based Speech Recognition of Chinese Dialects Method for Mobile Forensics 基于机器学习的汉语方言语音识别移动取证方法

2021 13th International Conference on Communication Software and Networks (ICCSN) Pub Date : 2021-06-04 DOI: 10.1109/ICCSN52437.2021.9463649

Liwen Peng, Xiaolin Zhu, Peng Zhang

引用次数: 0

Artificial Neural Network Equalizer for Discrete B-coefficients Modulated NFDM System 离散b系数调制NFDM系统的人工神经网络均衡器

2021 13th International Conference on Communication Software and Networks (ICCSN) Pub Date : 2021-06-04 DOI: 10.1109/ICCSN52437.2021.9463616

Yingrong Chen, Xi Fang, Qian Liao, Lei Zhang

引用次数: 0

DFT-Based Channel Estimation with Maximum Points Selection for OFDM System 基于dft的OFDM系统最大点选择信道估计

2021 13th International Conference on Communication Software and Networks (ICCSN) Pub Date : 2021-06-04 DOI: 10.1109/ICCSN52437.2021.9463638

Jiayi Lv, Liang Liu, Jiaxuan Li, Han Yang, Qian Li

引用次数: 2

An Algorithm for Locating PVC and SPB in Wearable ECGs 一种可穿戴心电图中PVC和SPB定位算法

2021 13th International Conference on Communication Software and Networks (ICCSN) Pub Date : 2021-06-04 DOI: 10.1109/ICCSN52437.2021.9463595

Yibo Yin, Sitao Zhang, Kainan Ma, Tao Li, Ming Liu, Yijun Wang

{"title":"An Algorithm for Locating PVC and SPB in Wearable ECGs","authors":"Yibo Yin, Sitao Zhang, Kainan Ma, Tao Li, Ming Liu, Yijun Wang","doi":"10.1109/ICCSN52437.2021.9463595","DOIUrl":"https://doi.org/10.1109/ICCSN52437.2021.9463595","url":null,"abstract":"Wearable electrocardiogram devices are being developed rapidly as they can be used to monitor the user’s health in the long term. Their development is dependent on advances in automatic processing algorithms. Given that its intended use requires the wearable device to collect a large amount of data, and in light of the context where its hardware is limited by cost and power consumption, this paper proposes an algorithmic framework that can automatically identify position premature ventricular contraction (PVC) and supraventricular premature beat (SPB) at low computational cost by using 24-hour dynamic single-lead ECG recordings. We first use convolutional neural networks that require a small number of calculations to find problematic segments in the signal, and then use bidirectional long short-term memory networks to accurately locate the PVC and SPB. In addition to using the second-level structure that reduces the total amount of computation required by the task to 1/3.78, the algorithm has adopted focal loss to ensure the accuracy of classification of the disease samples. The algorithm was used in the Third China Physiological Signal Challenge (CPSC) 2020 and came in 10th place, which verified its effectiveness. We trained the model once again by using the data provided at CPSC 2020, and obtained the F1 scores of PVC and SPB were 0.6698 and 0.6111.","PeriodicalId":263568,"journal":{"name":"2021 13th International Conference on Communication Software and Networks (ICCSN)","volume":"431 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123411902","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

An Atmospheric Particulate Matter Forecast Model Based on Time Series Data 基于时间序列数据的大气颗粒物预测模型

2021 13th International Conference on Communication Software and Networks (ICCSN) Pub Date : 2021-06-04 DOI: 10.1109/ICCSN52437.2021.9463628

Li Bao, Quan Li

{"title":"An Atmospheric Particulate Matter Forecast Model Based on Time Series Data","authors":"Li Bao, Quan Li","doi":"10.1109/ICCSN52437.2021.9463628","DOIUrl":"https://doi.org/10.1109/ICCSN52437.2021.9463628","url":null,"abstract":"In recent years, air pollution becomes an increasing concern globally because it directly affects people’s health and daily life. Especially the particulate matter with diameters less than 2.5 micrometers (PM2.5), which is one of the most common air pollutants. Air quality forecast helps to give early warnings and prevent the effects of air pollution. Effective air quality forecast has become one of the hot research issues. In this paper, the advantages of the existing prediction algorithms are analyzed and compared, and then the Long Short Term Memory (LSTM) network was applied to the research of atmospheric particulate matter forecast, and an atmospheric particulate matter prediction model based on time series data was constructed. The model was implemented based on the TensorFlow deep learning framework, Keras neural network library and Python language. It was tested on 365 daily mean concentration data and 22,287 hourly concentration data, and the prediction results were visualized. Finally, the established model was evaluated by mean square error (MSE). The experimental results demonstrate that the proposed prediction model can achieve better prediction performance for the PM2.5 concentration data even if it has a simple network structure and sample data of single factor.","PeriodicalId":263568,"journal":{"name":"2021 13th International Conference on Communication Software and Networks (ICCSN)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130156869","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

A Modified Blockchain DPoS Consensus Algorithm Based on Anomaly Detection and Reward-Punishment 一种基于异常检测和奖惩的改进区块链DPoS共识算法

2021 13th International Conference on Communication Software and Networks (ICCSN) Pub Date : 2021-06-04 DOI: 10.1109/ICCSN52437.2021.9463634

Yaxing Wei, Liang Liang, Bo Zhou, Xinsong Feng

引用次数: 6