In order to effectively detect malicious phishing behaviors, a phishing detection method based on the uniform resource locator （URL） features is proposed. First, the method compares the phishing URLs with legal ones...In order to effectively detect malicious phishing behaviors, a phishing detection method based on the uniform resource locator （URL） features is proposed. First, the method compares the phishing URLs with legal ones to extract the features of phishing URLs. Then a machine learning algorithm is applied to obtain the URL classification model from the sample data set training. In order to adapt to the change of a phishing URL, the classification model should be constantly updated according to the new samples. So, an incremental learning algorithm based on the feedback of the original sample data set is designed. The experiments verify that the combination of the URL features extracted in this paper and the support vector machine （SVM） classification algorithm can achieve a high phishing detection accuracy, and the incremental learning algorithm is also effective.展开更多
In chemical process, a large number of measured and manipulated variables are highly correlated. Principal component analysis(PCA) is widely applied as a dimension reduction technique for capturing strong correlation ...In chemical process, a large number of measured and manipulated variables are highly correlated. Principal component analysis(PCA) is widely applied as a dimension reduction technique for capturing strong correlation underlying in the process measurements. However, it is difficult for PCA based fault detection results to be interpreted physically and to provide support for isolation. Some approaches incorporating process knowledge are developed, but the information is always shortage and deficient in practice. Therefore, this work proposes an adaptive partitioning PCA algorithm entirely based on operation data. The process feature space is partitioned into several sub-feature spaces. Constructed sub-block models can not only reflect the local behavior of process change, namely to grasp the intrinsic local information underlying the process changes, but also improve the fault detection and isolation through the combination of local fault detection results and reduction of smearing effect.The method is demonstrated in TE process, and the results show that the new method is much better in fault detection and isolation compared to conventional PCA method.展开更多
To automatically detecting whether a person is wearing mask properly,we propose a face mask detection algorithm based on hue-saturation-value(HSV)+histogram of oriented gradient(HOG)features and support vector machine...To automatically detecting whether a person is wearing mask properly,we propose a face mask detection algorithm based on hue-saturation-value(HSV)+histogram of oriented gradient(HOG)features and support vector machines(SVM).Firstly,human face and five feature points are detected with RetinaFace face detection algorithm.The feature points are used to locate to mouth and nose region,and HSV+HOG features of this region are extracted and input to SVM for training to realize detection of wearing masks or not.Secondly,RetinaFace is used to locate to nasal tip area of face,and YCrCb elliptical skin tone model is used to detect the exposure of skin in the nasal tip area,and the optimal classification threshold can be found to determine whether the wear is properly according to experimental results.Experiments show that the accuracy of detecting whether mask is worn can reach 97.9%,and the accuracy of detecting whether mask is worn correctly can reach 87.55%,which verifies the feasibility of the algorithm.展开更多
Target detection in low light background is one of the main tasks of night patrol robots for airport terminal.However,if some algorithms can run on a robot platform with limited computing resources,it is difficult for...Target detection in low light background is one of the main tasks of night patrol robots for airport terminal.However,if some algorithms can run on a robot platform with limited computing resources,it is difficult for these algorithms to ensure the detection accuracy of human body in the airport terminal. A novel thermal infrared salient human detection model combined with thermal features called TFSHD is proposed. The TFSHD model is still based on U-Net,but the decoder module structure and model lightweight have been redesigned. In order to improve the detection accuracy of the algorithm in complex scenes,a fusion module composed of thermal branch and saliency branch is added to the decoder of the TFSHD model. Furthermore,a predictive loss function that is more sensitive to high temperature regions of the image is designed. Additionally,for the sake of reducing the computing resource requirements of the algorithm,a model lightweight scheme that includes simplifying the encoder network structure and controlling the number of decoder channels is adopted. The experimental results on four data sets show that the proposed method can not only ensure high detection accuracy and robustness of the algorithm,but also meet the needs of real-time detection of patrol robots with detection speed above 40 f/s.展开更多
With the rapid development of powerful image, editing software makes the forgery of the digital image easy. Researchers proposed methods to cope with image authentication in recent years. We proposed a passive image a...With the rapid development of powerful image, editing software makes the forgery of the digital image easy. Researchers proposed methods to cope with image authentication in recent years. We proposed a passive image authentication technique to determine the copy move forgery that copied a part of an image and pasted it on the other region in the same image. First, the method divides the image into overlapping blocks. It uses LPQ （local phase quantization） to label each block. The column average value of labeled blocks constitutes the feature vector for the block. Similarity among the feature vectors gives a clue about the forgery. Local phase quantization has not been used to detect copy move forgery in the literature before. Experimental results show that, the method has higher accuracy ratios and lower false negative values under blurring operation at high levels compared to other methods. Our method can also detect multiple copy move forgery.展开更多
Due to overvoltage produced by inverter output,inverter-fed motor insulation systems often experience fast electrical aging process,especially when partial discharge(PD) is incepted.Before putting into use,the PD dete...Due to overvoltage produced by inverter output,inverter-fed motor insulation systems often experience fast electrical aging process,especially when partial discharge(PD) is incepted.Before putting into use,the PD detection should be performed on inverter-fed motors at repetitive square voltages to avoid the PD caused insulation deterioration when the motors are collected to inverters having specific characteristics.However,unlike PD tests at AC/DC voltages proposed in IEC 60270,the PD detection at repetitive square voltages is much more complex because of serious interference generated by impulse generator.To solve the problem,ultra-high frequency(UHF) method seems recommendable for its preferable signal-to-noise ratio(SNR).The chief aim of this study is to investigate PD pulse and statistical characteristics of turn-to-turn insulation for inverter-fed traction motors.A square-shaped Archimedes antenna,specially designed for the PD detection at repetitive square voltages of fast rise times,was used to perform PD tests on turn-to-turn insulation models.Time and frequency analysis results indicate that energy component of generator disturbance and PD pulses are mainly distributed in the 0-0.5 GHz and 0.6-1.5 GHz range,respectively.Based on the results,suitable filter was designed for power disturbance suppression.Additionally,resorting to the sensor unit(i.e.antenna and filter) and the PD test system,the PD statistical features at square voltages of different frequencies were obtained.Experimental results show that higher frequency will give rise,statistically,to PD of lower magnitudes distributing at smaller phases.A reasonable interpretation of this phenomenon was presented.Lastly,according to the PD statistical features,some suggestions for the PD detection system design,generator parameter optimization and the PD pulse extracting were given.The results of this work would be beneficial to the increase of the sensitivity when performing the PD detection on insulation systems for inverter-fed motors at repetitive square voltages and thus,improving the reliability of inverter-fed motors.展开更多
Flow cytometry(FCM)is a powerful technique for single-bacteria analysis via simultaneous light-scattering and fluorescence measurements.By offering high-throughput,quantitative,and multiparameter analysis at the singl...Flow cytometry(FCM)is a powerful technique for single-bacteria analysis via simultaneous light-scattering and fluorescence measurements.By offering high-throughput,quantitative,and multiparameter analysis at the single-cell level,FCM has gained an increased popularity in microbiological research,food safety monitoring,water quality control,and clinical diagnosis.Here we will review the recent applications of flow cytometry in areas such as(1)total bacterial cell count,(2)bacterial viability analysis,(3)specific bacterial detection and identification,(4)characterization of physiological changes under environmental perturbations,and(5)biological function studies.Nevertheless,despite these widespread applications,challenges still remain for the detection of small sizes of bacteria and biochemical features that cannot be brightly stained via fluorescence.Recent improvement in FCM instrumentation will be discussed,and particularly the development of high sensitivity flow cytometry for advanced analysis of single bacterial cells will be highlighted.展开更多
基金The National Basic Research Program of China(973 Program)(No.2010CB328104,2009CB320501)the National Natural Science Foundation of China(No.61272531,61070158,61003257,61060161,61003311,41201486)+4 种基金the National Key Technology R&D Program during the11th Five-Year Plan Period(No.2010BAI88B03)Specialized Research Fund for the Doctoral Program of Higher Education(No.20110092130002)the National Science and Technology Major Project(No.2009ZX03004-004-04)the Foundation of the Key Laboratory of Netw ork and Information Security of Jiangsu Province(No.BM2003201)the Key Laboratory of Computer Netw ork and Information Integration of the Ministry of Education of China(No.93K-9)
文摘In order to effectively detect malicious phishing behaviors, a phishing detection method based on the uniform resource locator （URL） features is proposed. First, the method compares the phishing URLs with legal ones to extract the features of phishing URLs. Then a machine learning algorithm is applied to obtain the URL classification model from the sample data set training. In order to adapt to the change of a phishing URL, the classification model should be constantly updated according to the new samples. So, an incremental learning algorithm based on the feedback of the original sample data set is designed. The experiments verify that the combination of the URL features extracted in this paper and the support vector machine （SVM） classification algorithm can achieve a high phishing detection accuracy, and the incremental learning algorithm is also effective.
基金Support by the National Natural Science Foundation of China(61174114)the Research Fund for the Doctoral Program of Higher Education in China(20120101130016)Zhejiang Provincial Science and Technology Planning Projects of China(2014C31019)
文摘In chemical process, a large number of measured and manipulated variables are highly correlated. Principal component analysis(PCA) is widely applied as a dimension reduction technique for capturing strong correlation underlying in the process measurements. However, it is difficult for PCA based fault detection results to be interpreted physically and to provide support for isolation. Some approaches incorporating process knowledge are developed, but the information is always shortage and deficient in practice. Therefore, this work proposes an adaptive partitioning PCA algorithm entirely based on operation data. The process feature space is partitioned into several sub-feature spaces. Constructed sub-block models can not only reflect the local behavior of process change, namely to grasp the intrinsic local information underlying the process changes, but also improve the fault detection and isolation through the combination of local fault detection results and reduction of smearing effect.The method is demonstrated in TE process, and the results show that the new method is much better in fault detection and isolation compared to conventional PCA method.
基金National Natural Science Foundation of China(No.519705449)。
文摘To automatically detecting whether a person is wearing mask properly,we propose a face mask detection algorithm based on hue-saturation-value(HSV)+histogram of oriented gradient(HOG)features and support vector machines(SVM).Firstly,human face and five feature points are detected with RetinaFace face detection algorithm.The feature points are used to locate to mouth and nose region,and HSV+HOG features of this region are extracted and input to SVM for training to realize detection of wearing masks or not.Secondly,RetinaFace is used to locate to nasal tip area of face,and YCrCb elliptical skin tone model is used to detect the exposure of skin in the nasal tip area,and the optimal classification threshold can be found to determine whether the wear is properly according to experimental results.Experiments show that the accuracy of detecting whether mask is worn can reach 97.9%,and the accuracy of detecting whether mask is worn correctly can reach 87.55%,which verifies the feasibility of the algorithm.
基金supported in part by the National Key Research and Development Program of China(No. 2018YFC0309104)the Construction System Science and Technology Project of Jiangsu Province (No.2021JH03)。
文摘Target detection in low light background is one of the main tasks of night patrol robots for airport terminal.However,if some algorithms can run on a robot platform with limited computing resources,it is difficult for these algorithms to ensure the detection accuracy of human body in the airport terminal. A novel thermal infrared salient human detection model combined with thermal features called TFSHD is proposed. The TFSHD model is still based on U-Net,but the decoder module structure and model lightweight have been redesigned. In order to improve the detection accuracy of the algorithm in complex scenes,a fusion module composed of thermal branch and saliency branch is added to the decoder of the TFSHD model. Furthermore,a predictive loss function that is more sensitive to high temperature regions of the image is designed. Additionally,for the sake of reducing the computing resource requirements of the algorithm,a model lightweight scheme that includes simplifying the encoder network structure and controlling the number of decoder channels is adopted. The experimental results on four data sets show that the proposed method can not only ensure high detection accuracy and robustness of the algorithm,but also meet the needs of real-time detection of patrol robots with detection speed above 40 f/s.
文摘With the rapid development of powerful image, editing software makes the forgery of the digital image easy. Researchers proposed methods to cope with image authentication in recent years. We proposed a passive image authentication technique to determine the copy move forgery that copied a part of an image and pasted it on the other region in the same image. First, the method divides the image into overlapping blocks. It uses LPQ （local phase quantization） to label each block. The column average value of labeled blocks constitutes the feature vector for the block. Similarity among the feature vectors gives a clue about the forgery. Local phase quantization has not been used to detect copy move forgery in the literature before. Experimental results show that, the method has higher accuracy ratios and lower false negative values under blurring operation at high levels compared to other methods. Our method can also detect multiple copy move forgery.
基金supported by the National Natural Science Foundation of China (Grant Nos. 51177136,50377035)Zhuzhou Electric Motor Company of South China Locomotive & Rolling Stock Corporation Lim-ited
文摘Due to overvoltage produced by inverter output,inverter-fed motor insulation systems often experience fast electrical aging process,especially when partial discharge(PD) is incepted.Before putting into use,the PD detection should be performed on inverter-fed motors at repetitive square voltages to avoid the PD caused insulation deterioration when the motors are collected to inverters having specific characteristics.However,unlike PD tests at AC/DC voltages proposed in IEC 60270,the PD detection at repetitive square voltages is much more complex because of serious interference generated by impulse generator.To solve the problem,ultra-high frequency(UHF) method seems recommendable for its preferable signal-to-noise ratio(SNR).The chief aim of this study is to investigate PD pulse and statistical characteristics of turn-to-turn insulation for inverter-fed traction motors.A square-shaped Archimedes antenna,specially designed for the PD detection at repetitive square voltages of fast rise times,was used to perform PD tests on turn-to-turn insulation models.Time and frequency analysis results indicate that energy component of generator disturbance and PD pulses are mainly distributed in the 0-0.5 GHz and 0.6-1.5 GHz range,respectively.Based on the results,suitable filter was designed for power disturbance suppression.Additionally,resorting to the sensor unit(i.e.antenna and filter) and the PD test system,the PD statistical features at square voltages of different frequencies were obtained.Experimental results show that higher frequency will give rise,statistically,to PD of lower magnitudes distributing at smaller phases.A reasonable interpretation of this phenomenon was presented.Lastly,according to the PD statistical features,some suggestions for the PD detection system design,generator parameter optimization and the PD pulse extracting were given.The results of this work would be beneficial to the increase of the sensitivity when performing the PD detection on insulation systems for inverter-fed motors at repetitive square voltages and thus,improving the reliability of inverter-fed motors.
基金the National Key Basic Research Program of China(2013CB933703)the National Natural Science Foundation of China(91313302,21105082,21225523,21472158,21027010,21521004)the Program for Changjiang Scholars and Innovative Research Team in University(IRT13036)
文摘Flow cytometry(FCM)is a powerful technique for single-bacteria analysis via simultaneous light-scattering and fluorescence measurements.By offering high-throughput,quantitative,and multiparameter analysis at the single-cell level,FCM has gained an increased popularity in microbiological research,food safety monitoring,water quality control,and clinical diagnosis.Here we will review the recent applications of flow cytometry in areas such as(1)total bacterial cell count,(2)bacterial viability analysis,(3)specific bacterial detection and identification,(4)characterization of physiological changes under environmental perturbations,and(5)biological function studies.Nevertheless,despite these widespread applications,challenges still remain for the detection of small sizes of bacteria and biochemical features that cannot be brightly stained via fluorescence.Recent improvement in FCM instrumentation will be discussed,and particularly the development of high sensitivity flow cytometry for advanced analysis of single bacterial cells will be highlighted.
