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Search Results: 1 - 10 of 35161 matches for " Jianfeng Zhou "
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Transformed Auto-correlation
Jianfeng Zhou,Yang Gao
Physics , 2014,
Abstract: A transformed auto-correlation method is presented here, where a received signal is transformed based on a priori reflecting model, and then the transformed signal is cross-correlated to its original one. If the model is correct, after transformation, the reflected signal will be coherent to the transmitted signal, with zero delay. A map of transformed auto-correlation function with zero delay can be generated in a given parametric space. The significant peaks in the map may indicate the possible reflectors nearby the central transmitter. The true values of the parameters of reflectors can be estimated at the same time.
Bloch dynamics with second order Berry phase correction
Jianfeng Lu,Zhennan Zhou
Mathematics , 2015,
Abstract: We derive the semiclassical Bloch dynamics with the second order Berry phase correction, based on a two-scale WKB asymptotic analysis. For uniform external electric field, the bi-characteristics system after a positional shift introduced by Berry connections agrees with the recent result in the physics literature.
Biomass Production of Poplar Plantation Ecosystem in Yangtze River Beach Land  [PDF]
Jianfeng ZHANG, Qixiang SUN, Jinxing ZHOU, Qihua SHAN, Lixun WU
Energy and Power Engineering (EPE) , 2009, DOI: 10.4236/epe.2009.12012
Abstract: Currently, China is home to more than four million hectares of oil plants nationwide, and 154 kinds of energy trees could produce seeds containing more than 40 percent of oil, with total production of the seeds totaling five million tons. Another 57 million hectares of waste land are available and suitable for planting trees for the production of forest-based bioenergy, of which there is 630,000 hm2 beach land in the middle and lower reaches of Yangtze River where is suited for poplar growing. In order to approach the potential of poplar biomass production, the test was conducted in the paper. The result indicated that in the poplar forest ecosystem the herbaceous biomass production was 15.554 t/hm2. While biomass production for trees was 43.164 t/hm2, totally in the poplar plantation ecosystem biomass production reached 58.718 t/hm2. As well, poplars growing added incomes for local farmers.
A machine learning approach to explore the spectra intensity pattern of peptides using tandem mass spectrometry data
Cong Zhou, Lucas D Bowler, Jianfeng Feng
BMC Bioinformatics , 2008, DOI: 10.1186/1471-2105-9-325
Abstract: In this work, a Bayesian neural network approach is employed to analyze ion intensity information present in 13878 different MS/MS spectra. The influence of a library of 35 features on peptide fragmentation is examined under different proton mobility conditions. Useful rules involved in peptide fragmentation are found and subsets of features which have significant influence on fragmentation pathway of peptides are characterised. An intensity model is built based on the selected features and the model can make an accurate prediction of the intensity patterns for given MS/MS spectra. The predictions include not only the mean values of spectra intensity but also the variances that can be used to tolerate noises and system biases within experimental MS/MS spectra.The intensity patterns of fragmentation spectra are informative and can be used to analyze the influence of various characteristics of fragmented peptides on their fragmentation pathway. The features with significant influence can be used in turn to predict spectra intensities. Such information can help develop more reliable algorithms for peptide and protein identification.Mass spectrometry (MS) has emerged in recent years as one of the most powerful tools for protein analysis available to proteomics research. MS-based protein identification strategies typically involve the digestion of protein samples prior to introduction into the mass spectrometer by a site-specific protease such as trypsin. The derived peptides are subsequently ionized at entry into the mass spectrometer and measured as intact fragment (parent) ions. Subsets of these ions can then be selected on the basis of their mass-to-charge ratio (m/z) and subject to further fragmentation, most commonly using collision induced dissociation (CID), in a process known as tandem mass spectrometry (MS/MS). Under the conditions utilized in CID, peptides fragment in predictable patterns resulting in a series of signature spectra. Identification of the protei
Boundary velocity slip of pressure driven liquid flow in a micron pipe
JianFeng Zhou,BoQin Gu,ChunLei Shao
Chinese Science Bulletin , 2011, DOI: 10.1007/s11434-010-4188-y
Abstract: The velocity slip of gas flow in a micron channel has been widely recognized. For pressure driven liquid flow in a macro pipe, the minute velocity slip at the wall boundary is usually neglected. With a decreasing scale in the cross section of the flow passage, the effect of velocity slip on flow and heat transfer behaviors becomes progressively more noticeable. Based on the three Hamaker homogeneous material hypotheses, the method for calculating the acting force between the solid and liquid molecular groups is established. By analyzing the forces exerted on the liquid group near the pipe wall, it is found that the active force arising from the rough solid wall can provide the component force to resist the shearing force and keep the liquid group immobile. Based on this a velocity slip criterion is proposed. Considering the force balance of a slipping liquid group, the frictional force caused by the solid wall can be obtained and then the velocity of the liquid group can be calculated using the derived coefficient of friction. The investigation reveals that, in a micron pipe, a small velocity slip may occur when the flow pressure gradient is relatively large, and will cause errors in the pipe flow estimates.
A PARALIND Decomposition-Based Coherent Two-Dimensional Direction of Arrival Estimation Algorithm for Acoustic Vector-Sensor Arrays
Xiaofei Zhang,Min Zhou,Jianfeng Li
Sensors , 2013, DOI: 10.3390/s130405302
Abstract: In this paper, we combine the acoustic vector-sensor array parameter estimation problem with the parallel profiles with linear dependencies (PARALIND) model, which was originally applied to biology and chemistry. Exploiting the PARALIND decomposition approach, we propose a blind coherent two-dimensional direction of arrival (2D-DOA) estimation algorithm for arbitrarily spaced acoustic vector-sensor arrays subject to unknown locations. The proposed algorithm works well to achieve automatically paired azimuth and elevation angles for coherent and incoherent angle estimation of acoustic vector-sensor arrays, as well as the paired correlated matrix of the sources. Our algorithm, in contrast with conventional coherent angle estimation algorithms such as the forward backward spatial smoothing (FBSS) estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm, not only has much better angle estimation performance, even for closely-spaced sources, but is also available for arbitrary arrays. Simulation results verify the effectiveness of our algorithm.
Research Advance on the Role of IGF Network in Non-small Cell Lung Cancer
Yuzhou WANG,Xiaohong NING,Jianfeng ZHOU
Chinese Journal of Lung Cancer , 2009,
Efficient rare event simulation for failure problems in random media
Jingchen Liu,Jianfeng Lu,Xiang Zhou
Mathematics , 2014,
Abstract: In this paper we study rare events associated to solutions of elliptic partial differential equations with spatially varying random coefficients. The random coefficients follow the lognormal distribution, which is determined by a Gaussian process. This model is employed to study the failure problem of elastic materials in random media in which the failure is characterized by that the strain field exceeds a high threshold. We propose an efficient importance sampling scheme to compute small failure probabilities in the high threshold limit. The change of measure in our scheme is parametrized by two density functions. The efficiency of the importance sampling scheme is validated by numerical examples.
Multidimensional Analysis of System Logs in Large-scale Cluster Systems
Wei Zhou,Jianfeng Zhan,Dan Meng
Computer Science , 2009,
Abstract: It is effective to improve the reliability and availability of large-scale cluster systems through the analysis of failures. Existed failure analysis methods understand and analyze failures from one or few dimension. The analysis results are partial and with less precision because of the limitation of data source. This paper presents multidimensional analysis based on graph mining to analyze multi-source system logs, which is a promising failure analysis method to get more complete and precise failure knowledge.
Secure Network Coding Against the Contamination and Eavesdropping Adversaries
Yejun Zhou,Hui Li,Jianfeng Ma
Computer Science , 2008,
Abstract: In this paper, we propose an algorithm that targets contamination and eavesdropping adversaries. We consider the case when the number of independent packets available to the eavesdropper is less than the multicast capacity of the network. By means of our algorithm every node can verify the integrity of the received packets easily and an eavesdropper is unable to get any meaningful information about the source. We call it practical security if an eavesdropper is unable to get any meaningful information about the source.We show that, by giving up a small amount of overall capacity, our algorithm achieves achieves the practically secure condition at a probability of one. Furthermore, the communication overhead of our algorithm are negligible compared with previous works, since the transmission of the hash values and the code coefficients are both avoided.
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