2021 IEEE 4th International Conference on Electronics and Communication Engineering (ICECE)最新文献_第3页

Research on Optimization Algorithm of Power Allocation for High-Speed Railway Mobile Communications 高速铁路移动通信功率分配优化算法研究

2021 IEEE 4th International Conference on Electronics and Communication Engineering (ICECE) Pub Date : 2021-12-17 DOI: 10.1109/ICECE54449.2021.9674635

Xue-shu Liu, Cuiran Li, Jianli Xie

引用次数: 3

An Improved DCGAN for Fabric Defect Detection 织物缺陷检测的改进DCGAN

2021 IEEE 4th International Conference on Electronics and Communication Engineering (ICECE) Pub Date : 2021-12-17 DOI: 10.1109/ICECE54449.2021.9674302

Zheyu Zhang, Xianfu Wan, Liqing Li, Jun Wang

{"title":"An Improved DCGAN for Fabric Defect Detection","authors":"Zheyu Zhang, Xianfu Wan, Liqing Li, Jun Wang","doi":"10.1109/ICECE54449.2021.9674302","DOIUrl":"https://doi.org/10.1109/ICECE54449.2021.9674302","url":null,"abstract":"Textile defect detection is an important part of textile quality control. Due to the diversity of fabric texture and the lack of defect fabric images, detection methods based on deep learning which does not rely on defective fabric samples has been gradually applied. However, in previous methods, the ability to distinguish the image features of fabric texture and defects is insufficient. In order to solve this problem, this paper proposed an improved generative adversarial network, which introduced a self-encoder with MLP layers into the generator module. Fabric images with defects will be reconstructed into the ones without defects through the trained generator. Then some image processing operations will be carried out to compare the original defect image and the reconstructed image in order to obtain the segmentation of the defect area. By adding MLP layers to extract lower rank fabric image features, the developed model has a stronger ability to capture fabric texture features. Compared with previous studies, it can achieve a better segmentation effect of defects. Precision, recall rate and Fl-score are improved significantly in the experiments.","PeriodicalId":166178,"journal":{"name":"2021 IEEE 4th International Conference on Electronics and Communication Engineering (ICECE)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124865333","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

Ray Tracing Based Sub-6 GHz Wireless Channel Characteristics Analysis in Underground Garage Environments 基于光线追踪的地下车库Sub-6 GHz无线信道特性分析

2021 IEEE 4th International Conference on Electronics and Communication Engineering (ICECE) Pub Date : 2021-12-17 DOI: 10.1109/ICECE54449.2021.9674274

Xiaole Li, Cuiping Zhang, Jian Sun, Wensheng Zhang, Chengxiang Wang

{"title":"Ray Tracing Based Sub-6 GHz Wireless Channel Characteristics Analysis in Underground Garage Environments","authors":"Xiaole Li, Cuiping Zhang, Jian Sun, Wensheng Zhang, Chengxiang Wang","doi":"10.1109/ICECE54449.2021.9674274","DOIUrl":"https://doi.org/10.1109/ICECE54449.2021.9674274","url":null,"abstract":"Indoor hot spots is a major deployment scenario of the fifth generation (5G) network. In the indoor scenario, the radio wave propagation characteristics of underground garages are still not fully understood. In addition, Sub-6 GHz band is the main frequency band used in domestic 5G networks recently. This paper mainly uses ray tracing to study the wireless channel characteristics in the scenario of underground garage under Sub6 GHz frequency band. Firstly, a three-dimensional (3D) simulation scenario is built, and the channel simulation is carried out at 3.5 GHz frequency band. According to the simulation data, the results shows that the path loss index is smaller than that in the 3GPP indoor scenario. Then, the channel data of Sub-6 GHz continuous frequency band is simulated at 500 MHz interval, the influence of material properties on channel characteristics is studied. We find that the path loss increases while the distance between the transmitter (Tx) and receiver (Rx) increases, and the change is obvious at a long distance with increasing frequency.","PeriodicalId":166178,"journal":{"name":"2021 IEEE 4th International Conference on Electronics and Communication Engineering (ICECE)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124339308","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

Malicious Code Detection Method Based on Multiple Features 基于多特征的恶意代码检测方法

2021 IEEE 4th International Conference on Electronics and Communication Engineering (ICECE) Pub Date : 2021-12-17 DOI: 10.1109/ICECE54449.2021.9674573

Mingdi Xu, Hui Tong, Chaoyang Jin, Yu Wang

引用次数: 2

Slice Resource Allocation Technology of Cognitive Wireless Network Based on NOMA 基于NOMA的认知无线网络切片资源分配技术

2021 IEEE 4th International Conference on Electronics and Communication Engineering (ICECE) Pub Date : 2021-12-17 DOI: 10.1109/ICECE54449.2021.9674344

Yong Zhang, Siyu Yuan, Lizi Hu, W. Qie, Da Guo

引用次数: 0

Fishing Vessel Type Recognition Based on Ship Position Data 基于船舶位置数据的渔船类型识别

2021 IEEE 4th International Conference on Electronics and Communication Engineering (ICECE) Pub Date : 2021-12-17 DOI: 10.1109/ICECE54449.2021.9674416

Shengmao Zhang, Jiaze Zhang, Kaiyang Pei, Xianfeng Tang, J. Hou, Fenghua Tang, Shenglong Yang, Heng Zhang

{"title":"Fishing Vessel Type Recognition Based on Ship Position Data","authors":"Shengmao Zhang, Jiaze Zhang, Kaiyang Pei, Xianfeng Tang, J. Hou, Fenghua Tang, Shenglong Yang, Heng Zhang","doi":"10.1109/ICECE54449.2021.9674416","DOIUrl":"https://doi.org/10.1109/ICECE54449.2021.9674416","url":null,"abstract":"The type of fishing vessel operation is an important parameter for the fishing and management of fishery resources. The offshore motor fishing vessels in the East China Sea and the Yellow Sea were taken as the object of the research, and the BeiDou Vessel Monitoring System (VMS) position data from 2018 of these objects were used. The data is filtered and extracted according to the operating characteristics of the canvas stow net fishing vessel, and the trajectory map of the fishing vessel is drawn. On this basis, a fishing vessel classification method based on migration learning is proposed. This method uses VGG16 as the basic network, uses the parameters that have been trained on the ImageNet data set as the initial weights, and uses the preprocessing feature trajectory map as input of the network. Through training the model, the accuracy of the canvas stow net fishing boat and other fishing boats can be obtained. The experimental results show that the model classifies 4,974 canvas stow net voyages out of 54,120 effective voyages. The final accuracy rate was 91.8%, of which the recall rate of sailing net fishing boats was 91.9%, and the recall rate of other types of fishing boats was 91.8%. It provides a new solution for the identification of fishing vessel operation types.","PeriodicalId":166178,"journal":{"name":"2021 IEEE 4th International Conference on Electronics and Communication Engineering (ICECE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129500379","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

Readout Time Measurement in Optical Camera Communication using Commercial LED Light Source 商用LED光源光学相机通信中读出时间的测量

2021 IEEE 4th International Conference on Electronics and Communication Engineering (ICECE) Pub Date : 2021-12-17 DOI: 10.1109/ICECE54449.2021.9674666

Ke Dong, Xizheng Ke, Hui Li, Zifan Duan

引用次数: 1

Remote Power of Rural Network Nodes for Future Optical Networks 面向未来光网络的农村网络节点远程供电

2021 IEEE 4th International Conference on Electronics and Communication Engineering (ICECE) Pub Date : 2021-12-17 DOI: 10.1109/ICECE54449.2021.9674271

K. Wang, Yitong Wang, S. Kandeepan

{"title":"Remote Power of Rural Network Nodes for Future Optical Networks","authors":"K. Wang, Yitong Wang, S. Kandeepan","doi":"10.1109/ICECE54449.2021.9674271","DOIUrl":"https://doi.org/10.1109/ICECE54449.2021.9674271","url":null,"abstract":"Broadband Internet access is highly demanded by end users and it is now widely available in urban areas, primarily using optical networks. However, delivering reliable broadband network access in remote areas is still challenging, due to the limitations faced by network node locations, where the local power supply required by the network node may be not available. To solve this issue, in this paper we study the remote power scheme, where the power required by the off-grid network node can be delivered remotely in the format of optical pump. In this scheme, the optical pump will propagate together with the data-carrying signal through the same optical fiber, and it is then converted to the electrical domain to power the remote network node. The selection of optical pump wavelength, the impact of optical pump on the performance of the data signal, and the new multiple optical pumps scheme to increase the total amount of power delivered to the remote network node are studied here. Results show that the use of multiple 1550 nm band optical pumps located at different sides of the data signal (in the spectrum) provides the optimum remote power performance. The remote power scheme enables off-grid network nodes and their flexible locations, and hence, it provides a promising solution to the network design to deliver reliable broadband network access to remote areas.","PeriodicalId":166178,"journal":{"name":"2021 IEEE 4th International Conference on Electronics and Communication Engineering (ICECE)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121900104","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

Abnormal Data Flow Detection in the Internet of Things 物联网中的异常数据流检测

2021 IEEE 4th International Conference on Electronics and Communication Engineering (ICECE) Pub Date : 2021-12-17 DOI: 10.1109/ICECE54449.2021.9674234

Jin Wang, Jiangpei Xu, Jie Wang, Chang Liu, Yicong Wang

{"title":"Abnormal Data Flow Detection in the Internet of Things","authors":"Jin Wang, Jiangpei Xu, Jie Wang, Chang Liu, Yicong Wang","doi":"10.1109/ICECE54449.2021.9674234","DOIUrl":"https://doi.org/10.1109/ICECE54449.2021.9674234","url":null,"abstract":"In recent years, the Internet of things has developed rapidly, but the security problems are becoming more and more serious. Sensor nodes are important sources of data in the Internet of things. The abnormal and failure of sensing data in the Internet of Things will affect the connectivity of the network. If the accuracy and reliability of the corresponding perception data can be effectively improved, we can timely and accurately find out the emergency and monitor the working status of the network. Therefore, it is of great significance to detect the abnormal data of data streams in the sensor network nodes and confirm its source. Compared with traditional computers, the terminal devices in the perception layer of the Internet of things are more vulnerable to physical attacks. Aiming at the problems of abnormal traffic detection in Internet of things, this paper proposes an abnormal traffic detection method based on machine learning and sliding window, and an abnormal traffic detection method based on neural network and sliding window. Combined with the above two methods, a sliding window abnormal traffic detection method based on the mixed dimension of time and space is proposed so as to further improve the detection accuracy and efficiency. The detection algorithm adopts the combination of machine learning and neural network. This detection method not only improves the accuracy of the final detection results, but also reduces the detection time and improves the detection efficiency.","PeriodicalId":166178,"journal":{"name":"2021 IEEE 4th International Conference on Electronics and Communication Engineering (ICECE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126067035","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

Influence of Different Optimizers on Classification Results in Deep Learning 深度学习中不同优化器对分类结果的影响

2021 IEEE 4th International Conference on Electronics and Communication Engineering (ICECE) Pub Date : 2021-12-17 DOI: 10.1109/ICECE54449.2021.9674293

Hao Li, Chengui Guo, Zeweiyi Gong, Zhanguoi Cao, Feng Shen

引用次数: 0