Based on the massive data collected with a passive network monitoring equipment placed in China＇s backbone, we present a deep insight into the network backbone traffic and evaluate various ways for inproving traffic ...Based on the massive data collected with a passive network monitoring equipment placed in China＇s backbone, we present a deep insight into the network backbone traffic and evaluate various ways for inproving traffic classifying efficiency in this pa- per. In particular, the study has scrutinized the net- work traffic in terms of protocol types and signatures, flow length, and port distffoution, from which mean- ingful and interesting insights on the current Intemet of China from the perspective of both the packet and flow levels are derived. We show that the classifica- tion efficiency can be greatly irrproved by using the information of preferred ports of the network applica- tions. Quantitatively, we find two traffic duration thresholds, with which 40% of TCP flows and 70% of UDP flows can be excluded from classification pro- cessing while the in^act on classification accuracy is trivial, i.e., the classification accuracy can still reach a high level by saving 85% of the resources.展开更多
The wavelet packet is presented as a new kind of multiscale analysis technique followed by Wavelet analysis. The fundamental and realization arithmetic of the wavelet packet analysis method are described in this paper...The wavelet packet is presented as a new kind of multiscale analysis technique followed by Wavelet analysis. The fundamental and realization arithmetic of the wavelet packet analysis method are described in this paper. A new application approach of the wavelet packed method to extract the feature of the pulse signal from energy distributing angle is expatiated. It is convenient for the microchip to process and judge by using the wavelet packet analysis method to make the pulse signals quantized and analyzed. Kinds of experiments are simulated in the lab, and the experiments prove that it is a convenient and accurate method to extract the feature of the pulse signal based on wavelet packed-energy spectrumanalysis.展开更多
The present study analyzed the electromagnetic radiation(EMR) time series of the destruction process of coal or rock sample under uniaxial loading and the monitoring process in working face by means of fractal geometr...The present study analyzed the electromagnetic radiation(EMR) time series of the destruction process of coal or rock sample under uniaxial loading and the monitoring process in working face by means of fractal geometry,and results of the correlation dimension change curve of EMR time series were obtained.In the meantime,the current study also sought the fractal characteristic to the EMR signals by contrast to the change curve of EMR signals and explored the precursory phenomenon of rock burst.This paper concluded the main findings as followed:the EMR time series of the destruction process of coal or rock sample under uniaxial loading and the monitoring process in working face corresponded to fractal;the correlation dimension of EMR time series reflected the process of coal or rock damage deformation,that is,the inner damage of coal or rock made a change from random to order.In the field application,the correlation dimension served as a new index of forecasting the coal or rock dynamic disaster.展开更多
Processes like combustion, pyrolysis or gasification of coal and biomass are typical applications of gas-solid fluidized beds. These reactors normally use silica sand as the inert material inside the bed and the sand ...Processes like combustion, pyrolysis or gasification of coal and biomass are typical applications of gas-solid fluidized beds. These reactors normally use silica sand as the inert material inside the bed and the sand particles represent around 95% of the total bed weight. Pressure measurements have been used to characterize the dynamic behavior of fluidized beds since early researches in the area. Pressure fluctuations are generally due to bubbles flow which characterizes the fluidization regime. The present work aims to perform a time-frequency analysis of the pressure signal acquired in an experimental apparatus on different gas-solid flow regimes. Continuous and discrete wavelet transforms were applied and the results were compared with image records acquired simultaneously with the pressure signal. The main frequencies observed are in accordance with the ones obtained through Fourier spectra. The time-frequency distribution of the signal agrees with the phenomena observed in the image record, remarkably for the slugging flow. Some additional research is still necessary to completely characterize the flow regimes using the wavelet scalograms but the present results show that the task is a very promising one.展开更多
基金This paper was partially supported by the National Natural Science Foundation of China under Crant No. 61072061111 Project of China under Crant No. B08004 the Fundamental Research Funds for the Central Universities under Grant No. 2009RC0122. References
文摘Based on the massive data collected with a passive network monitoring equipment placed in China＇s backbone, we present a deep insight into the network backbone traffic and evaluate various ways for inproving traffic classifying efficiency in this pa- per. In particular, the study has scrutinized the net- work traffic in terms of protocol types and signatures, flow length, and port distffoution, from which mean- ingful and interesting insights on the current Intemet of China from the perspective of both the packet and flow levels are derived. We show that the classifica- tion efficiency can be greatly irrproved by using the information of preferred ports of the network applica- tions. Quantitatively, we find two traffic duration thresholds, with which 40% of TCP flows and 70% of UDP flows can be excluded from classification pro- cessing while the in^act on classification accuracy is trivial, i.e., the classification accuracy can still reach a high level by saving 85% of the resources.
文摘The wavelet packet is presented as a new kind of multiscale analysis technique followed by Wavelet analysis. The fundamental and realization arithmetic of the wavelet packet analysis method are described in this paper. A new application approach of the wavelet packed method to extract the feature of the pulse signal from energy distributing angle is expatiated. It is convenient for the microchip to process and judge by using the wavelet packet analysis method to make the pulse signals quantized and analyzed. Kinds of experiments are simulated in the lab, and the experiments prove that it is a convenient and accurate method to extract the feature of the pulse signal based on wavelet packed-energy spectrumanalysis.
基金supported by the Fundamental Research Funds for the Central Universities in China University of Mining and Technology (No. 2010QNB23)the Open Fund of Laboratory in China University of Mining and Technology (No. 2010-II-004)
文摘The present study analyzed the electromagnetic radiation(EMR) time series of the destruction process of coal or rock sample under uniaxial loading and the monitoring process in working face by means of fractal geometry,and results of the correlation dimension change curve of EMR time series were obtained.In the meantime,the current study also sought the fractal characteristic to the EMR signals by contrast to the change curve of EMR signals and explored the precursory phenomenon of rock burst.This paper concluded the main findings as followed:the EMR time series of the destruction process of coal or rock sample under uniaxial loading and the monitoring process in working face corresponded to fractal;the correlation dimension of EMR time series reflected the process of coal or rock damage deformation,that is,the inner damage of coal or rock made a change from random to order.In the field application,the correlation dimension served as a new index of forecasting the coal or rock dynamic disaster.
文摘Processes like combustion, pyrolysis or gasification of coal and biomass are typical applications of gas-solid fluidized beds. These reactors normally use silica sand as the inert material inside the bed and the sand particles represent around 95% of the total bed weight. Pressure measurements have been used to characterize the dynamic behavior of fluidized beds since early researches in the area. Pressure fluctuations are generally due to bubbles flow which characterizes the fluidization regime. The present work aims to perform a time-frequency analysis of the pressure signal acquired in an experimental apparatus on different gas-solid flow regimes. Continuous and discrete wavelet transforms were applied and the results were compared with image records acquired simultaneously with the pressure signal. The main frequencies observed are in accordance with the ones obtained through Fourier spectra. The time-frequency distribution of the signal agrees with the phenomena observed in the image record, remarkably for the slugging flow. Some additional research is still necessary to completely characterize the flow regimes using the wavelet scalograms but the present results show that the task is a very promising one.
