Nowadays,industrial control system(ICS)has begun to integrate with the Internet.While the Internet has brought convenience to ICS,it has also brought severe security concerns.Traditional ICS network traffic anomaly de...Nowadays,industrial control system(ICS)has begun to integrate with the Internet.While the Internet has brought convenience to ICS,it has also brought severe security concerns.Traditional ICS network traffic anomaly detection methods rely on statistical features manually extracted using the experience of network security experts.They are not aimed at the original network data,nor can they capture the potential characteristics of network packets.Therefore,the following improvements were made in this study:(1)A dataset that can be used to evaluate anomaly detection algorithms is produced,which provides raw network data.(2)A request response-based convolutional neural network named RRCNN is proposed,which can be used for anomaly detection of ICS network traffic.Instead of using statistical features manually extracted by security experts,this method uses the byte sequences of the original network packets directly,which can extract potential features of the network packets in greater depth.It regards the request packet and response packet in a session as a Request-Response Pair(RRP).The feature of RRP is extracted using a one-dimensional convolutional neural network,and then the RRP is judged to be normal or abnormal based on the extracted feature.Experimental results demonstrate that this model is better than several other machine learning and neural network models,with F1,accuracy,precision,and recall above 99%.展开更多
Ice detecting and measuring technologies used and developed for high voltage transmission lines are introduced in this paper. The Icing Rate Meter developed by Hydro-Quebec, working with the magnetostriction principle...Ice detecting and measuring technologies used and developed for high voltage transmission lines are introduced in this paper. The Icing Rate Meter developed by Hydro-Quebec, working with the magnetostriction principle and regulated by an electronic control system is analyzed and the resonant piezoelectric transducers operated by a microprocessor-controlled electronic circuitry is also analyzed in great detail. It shows that the Icing Rate Meter (IRM) developed by Hydro-Quebec can record the occur- rence and duration of icing events, but has two limitations: information on changes in the rate of icing within each hour is lost and the amount of time consumed during heating cycles is not taken into account. A resonant piezoelectric ice detector can automatically and distinctly sense ice and water films up to 0.5 mm thick. It is a smart ice detection system, which might be used widely.展开更多
In the present work, a novel analytical method was proposed for the determination of toluene diisocyanate （TDI） in syntheticrubber track by ion chromatography （IC） coupled with an ultraviolet detector setting at 2...In the present work, a novel analytical method was proposed for the determination of toluene diisocyanate （TDI） in syntheticrubber track by ion chromatography （IC） coupled with an ultraviolet detector setting at 212 nm. TDI can be hydrolyzed to toluene diamine （TDA） which can be separated by cation-exchange IC easily. The optimum IC separation was performed on an IonPac CS12A column （150 mm ×4.0 mm） using 20 mmol L^-1 sodium sulfate, 10 mmol L^-1 sulfuric acid and 10% acetonitrile as eluent. It was found that a higher signal response of TDA could be obtained under alkaline condition. A suppressor was used to change the acidic eluent into alkaline one. 0.8 mol L^-1 potassium hydroxide was chosen as the optimum regeneration eluent. With the added suppressor and regenerant, signal response was magnified by about 16 times and lower limit of detection （LOD, 0.13 μg L^-1） was obtained. Within-day relative standard deviation （R.S.D.） was less than 3.6%. The recoveries of TDI spiked in synthetic-rubber track samoles were 96.4-110.6%.展开更多
Nowadays, digital camera based remote controllers are widely used in people’s daily lives. It is known that the edge detection process plays an essential role in remote controlled applications. In this paper, a syste...Nowadays, digital camera based remote controllers are widely used in people’s daily lives. It is known that the edge detection process plays an essential role in remote controlled applications. In this paper, a system verification platform of hardware optimization based on the edge detection is proposed. The Field-Programmable Gate Array (FPGA) validation is an important step in the Integrated Circuit (IC) design workflow. The Sobel edge detection algorithm is chosen and optimized through the FPGA verification platform. Hardware optimization techniques are used to create a high performance, low cost design. The Sobel edge detection operator is designed and mounted through the system Advanced High-performance Bus (AHB). Different FPGA boards are used for evaluation purposes. It is proved that with the proposed hardware optimization method, the hardware design of the Sobel edge detection operator can save 6% of on-chip resources for the Sobel core calculation and 42% for the whole frame calculation.展开更多
In polar regions, cloud and underlying ice-snow areas are difficult to distinguish in satellite images because of their high albedo in the visible band and low surface temperature of ice-snow areas in the infrared ban...In polar regions, cloud and underlying ice-snow areas are difficult to distinguish in satellite images because of their high albedo in the visible band and low surface temperature of ice-snow areas in the infrared band. A cloud detection method over ice-snow covered areas in Antarctica is presented. On account of different texture features of cloud and ice-snow areas, five texture features are extracted based on GLCM. Nonlinear SVM is then used to obtain the optimal classification hyperplane from training data. The experiment results indicate that this algorithm performs well in cloud detection in Antarctica, especially for thin cirrus detection. Furthermore, when images are resampled to a quarter or 1/16 of the full size, cloud percentages are still at the same level, while the processing time decreases exponentially.展开更多
基金supported by the National Natural Science Foundation of China(No.62076042,No.62102049)the Key Research and Development Project of Sichuan Province(No.2021YFSY0012,No.2020YFG0307,No.2021YFG0332)+3 种基金the Science and Technology Innovation Project of Sichuan(No.2020017)the Key Research and Development Project of Chengdu(No.2019-YF05-02028-GX)the Innovation Team of Quantum Security Communication of Sichuan Province(No.17TD0009)the Academic and Technical Leaders Training Funding Support Projects of Sichuan Province(No.2016120080102643).
文摘Nowadays,industrial control system(ICS)has begun to integrate with the Internet.While the Internet has brought convenience to ICS,it has also brought severe security concerns.Traditional ICS network traffic anomaly detection methods rely on statistical features manually extracted using the experience of network security experts.They are not aimed at the original network data,nor can they capture the potential characteristics of network packets.Therefore,the following improvements were made in this study:(1)A dataset that can be used to evaluate anomaly detection algorithms is produced,which provides raw network data.(2)A request response-based convolutional neural network named RRCNN is proposed,which can be used for anomaly detection of ICS network traffic.Instead of using statistical features manually extracted by security experts,this method uses the byte sequences of the original network packets directly,which can extract potential features of the network packets in greater depth.It regards the request packet and response packet in a session as a Request-Response Pair(RRP).The feature of RRP is extracted using a one-dimensional convolutional neural network,and then the RRP is judged to be normal or abnormal based on the extracted feature.Experimental results demonstrate that this model is better than several other machine learning and neural network models,with F1,accuracy,precision,and recall above 99%.
文摘Ice detecting and measuring technologies used and developed for high voltage transmission lines are introduced in this paper. The Icing Rate Meter developed by Hydro-Quebec, working with the magnetostriction principle and regulated by an electronic control system is analyzed and the resonant piezoelectric transducers operated by a microprocessor-controlled electronic circuitry is also analyzed in great detail. It shows that the Icing Rate Meter (IRM) developed by Hydro-Quebec can record the occur- rence and duration of icing events, but has two limitations: information on changes in the rate of icing within each hour is lost and the amount of time consumed during heating cycles is not taken into account. A resonant piezoelectric ice detector can automatically and distinctly sense ice and water films up to 0.5 mm thick. It is a smart ice detection system, which might be used widely.
基金supported by the National Natural Science Foundation of China(No.20775070)Zhejiang Provincial Natural Science Foundation of China(No.Y507252).
文摘In the present work, a novel analytical method was proposed for the determination of toluene diisocyanate （TDI） in syntheticrubber track by ion chromatography （IC） coupled with an ultraviolet detector setting at 212 nm. TDI can be hydrolyzed to toluene diamine （TDA） which can be separated by cation-exchange IC easily. The optimum IC separation was performed on an IonPac CS12A column （150 mm ×4.0 mm） using 20 mmol L^-1 sodium sulfate, 10 mmol L^-1 sulfuric acid and 10% acetonitrile as eluent. It was found that a higher signal response of TDA could be obtained under alkaline condition. A suppressor was used to change the acidic eluent into alkaline one. 0.8 mol L^-1 potassium hydroxide was chosen as the optimum regeneration eluent. With the added suppressor and regenerant, signal response was magnified by about 16 times and lower limit of detection （LOD, 0.13 μg L^-1） was obtained. Within-day relative standard deviation （R.S.D.） was less than 3.6%. The recoveries of TDI spiked in synthetic-rubber track samoles were 96.4-110.6%.
文摘Nowadays, digital camera based remote controllers are widely used in people’s daily lives. It is known that the edge detection process plays an essential role in remote controlled applications. In this paper, a system verification platform of hardware optimization based on the edge detection is proposed. The Field-Programmable Gate Array (FPGA) validation is an important step in the Integrated Circuit (IC) design workflow. The Sobel edge detection algorithm is chosen and optimized through the FPGA verification platform. Hardware optimization techniques are used to create a high performance, low cost design. The Sobel edge detection operator is designed and mounted through the system Advanced High-performance Bus (AHB). Different FPGA boards are used for evaluation purposes. It is proved that with the proposed hardware optimization method, the hardware design of the Sobel edge detection operator can save 6% of on-chip resources for the Sobel core calculation and 42% for the whole frame calculation.
基金Supported by the Antarctic Geography Information Acquisition and Environmental Change Research of China (No.14601402024-04-06).
文摘In polar regions, cloud and underlying ice-snow areas are difficult to distinguish in satellite images because of their high albedo in the visible band and low surface temperature of ice-snow areas in the infrared band. A cloud detection method over ice-snow covered areas in Antarctica is presented. On account of different texture features of cloud and ice-snow areas, five texture features are extracted based on GLCM. Nonlinear SVM is then used to obtain the optimal classification hyperplane from training data. The experiment results indicate that this algorithm performs well in cloud detection in Antarctica, especially for thin cirrus detection. Furthermore, when images are resampled to a quarter or 1/16 of the full size, cloud percentages are still at the same level, while the processing time decreases exponentially.
