2021 6th International Conference on Communication, Image and Signal Processing (CCISP)最新文献

The vegetation coverage change analysis based on the time series of images for construction area of pumped storage power station 基于时间序列影像的抽水蓄能电站建设区域植被覆盖度变化分析

2021 6th International Conference on Communication, Image and Signal Processing (CCISP) Pub Date : 2021-11-01 DOI: 10.1109/CCISP52774.2021.9639309

Qian Hong, Zhibin Li, Xiaofeng Chen, Benliang Li, Xiaoxiao Ma, Yang Li, Y. Zhang

{"title":"The vegetation coverage change analysis based on the time series of images for construction area of pumped storage power station","authors":"Qian Hong, Zhibin Li, Xiaofeng Chen, Benliang Li, Xiaoxiao Ma, Yang Li, Y. Zhang","doi":"10.1109/CCISP52774.2021.9639309","DOIUrl":"https://doi.org/10.1109/CCISP52774.2021.9639309","url":null,"abstract":"The vegetation change monitoring of engineering construction project usually adopts manual investigation, which is difficult to timely monitor the change. The pumped storage power station project is often constructed in mountain area, which will damage natural resources and arises soil erosion. In order to timely analyse vegetation change caused by pumped storage power station project, the study uses five series of remote sensing image data with sub-meter resolution to obtain the vegetation coverage among different construction stages. The pixel binary model was used to estimate the vegetation coverage. The results shows the vegetation coverage for whole study area is decreasing trend since the Jixi pumped storage power station has begun to construct. In 2015~2017, there is obviously reduction in the stage of large excavation. In 2017~2020, a increasing trend of vegetation coverage appears because of manually vegetation restoration measures with project completion. Therefore, the vegetation coverage rate of remote sensing images can be used to monitor the vegetation change due to project construction. And it is better to select the time series of images in the same season for ensuring the accuracy of the analysis. The study provides a method of vegetation change monitoring based on remote sensing during engineering construction period, which can improve the ability of project supervision.","PeriodicalId":323074,"journal":{"name":"2021 6th International Conference on Communication, Image and Signal Processing (CCISP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115632217","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 Security Access Control Scheme of Smart Community under Epidemic Situation 疫情下智慧社区安全访问控制方案

2021 6th International Conference on Communication, Image and Signal Processing (CCISP) Pub Date : 2021-11-01 DOI: 10.1109/CCISP52774.2021.9639089

Yue Zhao, Yiru Niu, Leyu Lin, Kaijun Wu, Yao Hao, Hong Su, Yarang Yang

引用次数: 1

An Inter-Satellite Communication Scheme Based on Real-time Doppler Frequency Offset Compensation 基于实时多普勒频偏补偿的星间通信方案

2021 6th International Conference on Communication, Image and Signal Processing (CCISP) Pub Date : 2021-11-01 DOI: 10.1109/CCISP52774.2021.9639284

Yuan Fu

引用次数: 0

Radar Emitter Recognition Method Based on Bispectrum and Improved Multi-channel Convolutional Neural Network 基于双谱和改进多通道卷积神经网络的雷达辐射源识别方法

2021 6th International Conference on Communication, Image and Signal Processing (CCISP) Pub Date : 2021-11-01 DOI: 10.1109/CCISP52774.2021.9639328

Lei Yang, Pan Zhen, Jian Wang, Jie Zhang, D. Guo

引用次数: 2

Wind Speed Prediction based on Long Short-Term Memory network and Policy Suggestions for Wind Power Industry Development 基于长短期记忆网络的风速预测及风电产业发展政策建议

2021 6th International Conference on Communication, Image and Signal Processing (CCISP) Pub Date : 2021-11-01 DOI: 10.1109/CCISP52774.2021.9639329

Daihong Tian, Danyang Zhao

{"title":"Wind Speed Prediction based on Long Short-Term Memory network and Policy Suggestions for Wind Power Industry Development","authors":"Daihong Tian, Danyang Zhao","doi":"10.1109/CCISP52774.2021.9639329","DOIUrl":"https://doi.org/10.1109/CCISP52774.2021.9639329","url":null,"abstract":"As a new energy source, the use of wind power is conducive to the protection of global resources and the environment, thus it plays an increasingly important role in alleviating the energy crisis. Due to the fluctuation and strong randomness of wind speed, wind power generation is difficult to integrate into the grid. To overcome these challenges and further enhance wind speed forecasting performance and stability, a forecasting method is developed based on long short-term memory network. To verify the properties of this deep learning algorithm, the 15-min wind speed data of four wind farms in Inner Mongolia of China are analyzed. The results of root mean square error, mean absolute error and mean absolute percentage error show that this new algorithm is superior to the autoregressive integrated moving average model in prediction accuracy and stability. Among them, compared with the ARIMA model, the root mean square error of the new model for Datasets 1-4 decreased by 60.40%, 52.19%, 75.12% and 85.64%, respectively. Thus, deep learning algorithm based on long short-term memory network is extremely useful for enhancing prediction precision, and is a reasonable and valid tool for intelligent grid programming. It also provides strong technical support for the formulation of wind power industry policies. In the future, we should improve the legal regulatory system and diversified financial tools, as well as strengthening scientific research incentive mechanisms to promote the development of the wind power industry.","PeriodicalId":323074,"journal":{"name":"2021 6th International Conference on Communication, Image and Signal Processing (CCISP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129761537","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

IHFM: An Improved Hierarchical Filtering Method for Multi-source malicious alerts 一种改进的多源恶意警报分层过滤方法

2021 6th International Conference on Communication, Image and Signal Processing (CCISP) Pub Date : 2021-11-01 DOI: 10.1109/CCISP52774.2021.9639307

Gengxin Li, Hui Li, Xin Yang

{"title":"IHFM: An Improved Hierarchical Filtering Method for Multi-source malicious alerts","authors":"Gengxin Li, Hui Li, Xin Yang","doi":"10.1109/CCISP52774.2021.9639307","DOIUrl":"https://doi.org/10.1109/CCISP52774.2021.9639307","url":null,"abstract":"Network security situation awareness has recently emerged as a game changer in the security landscape due to its proven potential to help security managers accurately control the system status in real time. However, the exiting method suffer from a large number of misjudgments in the active defense mechanism established based on the alarm data when deal with the huge massive threat logs and event information.Therefore, the method filtering huge warning logs with a fine granularity becomes one of the key problem, which is the basis for the accuracy of the subsequent security situation assessment algorithm. Experiments show that hierarchical filtering performs well for screening of alarm events. In this paper, we propose a five-layer filtering model named IHFM to flexibility filter a large number of alarms in an efficient way. Besides, to further improve the accuracy of model filtering, we propose a concept of the difference in joint performance entropy and introduce the FAHP algorithm to calculate its weight parameters. Lastly, the comparative analysis with experiments in real network environment proves that our proposed method classify and filter malicious events accurately with high flexibility while guaranteeing low false alarm rate.","PeriodicalId":323074,"journal":{"name":"2021 6th International Conference on Communication, Image and Signal Processing (CCISP)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126528023","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

Design of scenario experiment framework for security protocol 安全协议场景实验框架设计

2021 6th International Conference on Communication, Image and Signal Processing (CCISP) Pub Date : 2021-11-01 DOI: 10.1109/CCISP52774.2021.9639368

Qi Zhao, Yiru Niu, Yue Zhao, Kaijun Wu, Haiyang Peng

引用次数: 0

Low Complexity Data Mapping and Detection for Jointly Mapping Generalized Spatial Modulation 联合映射广义空间调制的低复杂度数据映射与检测

2021 6th International Conference on Communication, Image and Signal Processing (CCISP) Pub Date : 2021-11-01 DOI: 10.1109/CCISP52774.2021.9639324

Yun Wu, Mengyao Li, Xueqin Jiang, Enjian Bai

引用次数: 0

Urban Fault Detection based on AETA: A Case Study on Line 9 Subway of Shenzhen, China 基于AETA的城市故障检测——以深圳地铁9号线为例

2021 6th International Conference on Communication, Image and Signal Processing (CCISP) Pub Date : 2021-11-01 DOI: 10.1109/CCISP52774.2021.9639281

Shan-shan Yong, Qinmeng Guo, Xin'an Wang, Jing Wang, Chao Yang, Binghui Jiang

{"title":"Urban Fault Detection based on AETA: A Case Study on Line 9 Subway of Shenzhen, China","authors":"Shan-shan Yong, Qinmeng Guo, Xin'an Wang, Jing Wang, Chao Yang, Binghui Jiang","doi":"10.1109/CCISP52774.2021.9639281","DOIUrl":"https://doi.org/10.1109/CCISP52774.2021.9639281","url":null,"abstract":"To protect human life and social development, it is necessary to be able to rapidly and accurately identify active faults in urban areas. The traditional methods for detecting active faults, such as geological surveys, artificial seismic exploration, and electromagnetic exploration, are less viable in urban areas with a high concentration of buildings, railway traffic, and underground oil and gas pipelines. Acoustic and Electromagnetic Testing All (AETA) in one system is a system that monitors electromagnetic signals; while this system is typically used to capture abnormal activity prior to the onset of earthquakes, it can also be used as an alternative way to detect geological activity in urban areas. In this study, we propose a novel AETA-based method to determine the location of active faults in urban regions. In order to validate this method, we applied our technique to the Line 9 subway area in Shenzhen. Using AETA data, our model indicated the presence of an activity boundary that has a similar orientation and location to that of a nearby fault. With more measurements, we believe that we can further improve the effectiveness of this new methodology.","PeriodicalId":323074,"journal":{"name":"2021 6th International Conference on Communication, Image and Signal Processing (CCISP)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133276649","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

Characterizing Laser-induced Acoustic Signals Based on Thermal Expansion Mechanism: Simulation Studies and Experiment Verifications 基于热膨胀机理的激光诱导声信号表征:仿真研究与实验验证

2021 6th International Conference on Communication, Image and Signal Processing (CCISP) Pub Date : 2021-11-01 DOI: 10.1109/CCISP52774.2021.9639342

Jiehong Luo, Xiang Pan, L. Cheng

引用次数: 0