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| 1 | First China ocean reflection experiment using coastal GNSS-R显示文摘It is a new way for oceanographic remote sensing using the GNSS-Reflection technique. Sea waves, tides and sea surface wind can be obtained by analyzing the direct and reflected GPS signals from sea surface. It has become an advanced field concerned by many researchers. In this paper the first China Ocean Reflection Experiment (CORE) with the coastal GNSS-R in the southeast is reported and the method to retrieve oceanographic parameters with the direct and reflected GPS signals is studied. The primary retrievals of Significant Wave Height (SWH) are presented and also compared with the meas-urements from Ultrasonic Wave Gauge (UWG) in situ. | WANG Xin SUN Qiang ZHANG XunXie LU DaRen SHAO LianJun HU Xiong RUFFINI Giulio DUNNE Stephen FRANCOIS Soulat | 2008 | Chinese Science Bulletin2008，53，7： | 15 |
| 2 | Decomposition of CF_3CI by corona discharge显示文摘In this paper pulsed corona discharge is shown to be effective for the decomposition ofCF3Cl(Freon-13).The pressure of CF3Cl was 2.67×103Pa,after discharged for 2 min,39.5% ofCF3Cl was decomposed.The products were mainly CF4,Cl2 and CF2Cl2.The yield increased byadding O2 or air.Under the same conditions,more than 94% decomposition yield was obtained if5.32×103Pa O2 or air was added.The composition of products became CF2O,Cl2 and CF4.Whilethe partial pressure of O2 or air reached 1 arm,the decomposition yield decreased to 54.5% and 48.5% respectively. | Liu Zhengchao Pan Xunxi Dong Wenbo Hou Huiqi Environmental Science Institute,Fudan University,Shanghai 200433,ChinaZhang Zhenman Hou Jian Yu Yong Li Changlin Department of Physics Ⅱ,Fudan University,Shanghai 200433,China | 1997 | Journal of Environmental Sciences1997，9，1： | 2 |
| 3 | Analysis of inversion errors of ionospheric radio occultation显示文摘 | Xiaocheng Wu Xiong Hu Xiaoyan Gong Xunxie Zhang Xin Wang | 2009 | GPS Solutions2009，，3： | 1 |
| 4 | The stratigraphical division of DC-2 columnar core from the East China Sea显示文摘 | Huang Qingfu Gou Shuming Sun Weimin Shen Xunxi Xu Shanmin Cang Shuxi | | 0，，01： | 1 |
| 5 | ,One Potential Source of the Potent Greenhouse Gas SF5CF3:The Reaction of SF6with Fluorocarbon under Discharge显示文摘 | Huang Li Zhu Lili Pan Xunxi | 2005 | Atmospheric Environment2005，39，： | 1 |
| 6 | Study on gaseous CS_2 using laser-induced fluorescence显示文摘The fluorescence of gaseous CS_2 was studied by laser - induced fluorescence (LIF) method. Aworking curve of gaseous CS_2 was obtained and the detection limit was less than 1 ppm. The time - resolvedfluorescence emission spectrum of CS_2 vapor was recorde | Pan Zhe Zhang Yue Deng Guohong Pan Xunxi , Hou Huiqi Li Changlin(Environmental Science Institute , Fudan University, Shanghai 200433 , China) | 1995 | Journal of Environmental Sciences1995，7，4： | 0 |
| 7 | A Time Series Intrusion Detection Method Based on SSAE,TCN and Bi-LSTM显示文摘In the fast-evolving landscape of digital networks,the incidence of network intrusions has escalated alarmingly.Simultaneously,the crucial role of time series data in intrusion detection remains largely underappreciated,with most systems failing to capture the time-bound nuances of network traffic.This leads to compromised detection accuracy and overlooked temporal patterns.Addressing this gap,we introduce a novel SSAE-TCN-BiLSTM(STL)model that integrates time series analysis,significantly enhancing detection capabilities.Our approach reduces feature dimensionalitywith a Stacked Sparse Autoencoder(SSAE)and extracts temporally relevant features through a Temporal Convolutional Network(TCN)and Bidirectional Long Short-term Memory Network(Bi-LSTM).By meticulously adjusting time steps,we underscore the significance of temporal data in bolstering detection accuracy.On the UNSW-NB15 dataset,ourmodel achieved an F1-score of 99.49%,Accuracy of 99.43%,Precision of 99.38%,Recall of 99.60%,and an inference time of 4.24 s.For the CICDS2017 dataset,we recorded an F1-score of 99.53%,Accuracy of 99.62%,Precision of 99.27%,Recall of 99.79%,and an inference time of 5.72 s.These findings not only confirm the STL model’s superior performance but also its operational efficiency,underpinning its significance in real-world cybersecurity scenarios where rapid response is paramount.Our contribution represents a significant advance in cybersecurity,proposing a model that excels in accuracy and adaptability to the dynamic nature of network traffic,setting a new benchmark for intrusion detection systems. | Zhenxiang He Xunxi Wang Chunwei Li | 2024 | Computers, Materials & Continua2024，78，1： | 0 |
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