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Search Results: 1 - 10 of 75183 matches for " Yan Xu "
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Reconstruction of conductivity distribution of brain tissue from two components magnetic flux density  [PDF]
Wenlong Xu, Dandan Yan
Journal of Biomedical Science and Engineering (JBiSE) , 2010, DOI: 10.4236/jbise.2010.37099
Abstract: In this paper the recent Magnetic resonance electrical impedance imaging (MREIT) technique is used to image non-invasively the three-dimensional continuous conductivity distribution of the head tissues. With the feasibility of the human head being rotated twice in the magnetic resonance imaging (MRI) system, a continuous conductivity reconstruction MREIT algorithm based on two components of the measured magnetic flux density is introduced. The reconstructed conductivity image could be obtained through solving iter- atively a non-linear matrix equation. According to the present algorithm of using two magnetic flux den- sity components, numerical simulations were per- formed on a concentric three-sphere and realistic human head model (consisting of the scalp, skull and brain) with the uniform and non-uniform isotropic target conductivity distributions. Based on the algorithm, the reconstruction of scalp and brain conductivity ratios could be figured out even under the condition that only one current is injected into the brain. The present results show that the three-dimensional continuous conductivity reconstruction method with two magnetic flux density components for the realistic head could get better results than the method with only one magnetic flux density component. Given the skull conductivity ratio, the relative errors of scalp and brain conductivity values were reduced to less than 1% with the uniform conductivity distribution and less than 6.5% with the non-uniform distribution for different noise levels. Furthermore, the algorithm also shows fast convergence and improved robustness against noise.
New Common Fixed Point Results for Four Maps on Cone Metric Spaces  [PDF]
Yan Han, Shaoyuan Xu
Applied Mathematics (AM) , 2011, DOI: 10.4236/am.2011.29153
Abstract: In this paper, some new existence and uniqueness of common fixed points for four mappings are obtained, which do not satisfy continuity and commutation on non-normal cone metric spaces. These results improve and generalize several well-known comparable results in the literature.
Application of Single Channel Blind Separation Algorithm Based on EEMD-PCA-RobustICA in Bearing Fault Diagnosis  [PDF]
Wei Xu, Xiangzhou Yan
Int'l J. of Communications, Network and System Sciences (IJCNS) , 2017, DOI: 10.4236/ijcns.2017.108B015
Abstract:
Aiming at the problem that ICA can only be confined to the condition that the number of observed signals is larger than the number of source signals; a single channel blind source separation method combining EEMD, PCA and RobustICA is proposed. Through the eemd decomposition of the single-channel mechanical vibration observation signal the multidimensional IMF components are obtained, and the principal component analysis (PCA) is performed on the matrix of these IMF components. The number of principal components is determined and a new matrix is generated to satisfy the overdetermined blind source separation conditions, the new matrix input RobustICA, to achieve the separation of the source signal. Finally, the isolated signals are respectively analyzed by the envelope spectrum, the fault frequency is extracted, and the fault type is judged according to the prior knowledge. The experiment was carried out by using the simulation signal and the mechanical signal. The results show that the algorithm is effective and can accurately diagnose the location of mechanical fault.
A Data-drive Feature Selection Method in Text Categorization
Yan Xu
Journal of Software , 2011, DOI: 10.4304/jsw.6.4.620-627
Abstract: Text Categorization (TC) is the process of grouping texts into one or more predefined categories based on their content. It has become a key technique for handling and organizing text data. One of the most important issues in TC is Feature Selection (FS). Many FS methods have been put forward and widely used in TC field, such as Information Gain (IG), Document Frequency thresholding (DF) and Mutual Information. Empirical studies show that some of these (e.g. IG, DF) produce better categorization performance than others (e.g. MI). A basic research question is why these FS methods cause different performance. Many existing works seek to answer this question based on empirical studies. In this paper, we present a formal study of FS in TC. We first define three desirable constraints that any reasonable FS function should satisfy, then check these constraints on some popular FS methods, including IG, DF, MI and two other methods. We find that IG satisfies the first two constraints, and that there are strong statistical correlations between DF and the first constraint, whilst MI does not satisfy any of the constraints. Experimental results indicate that the empirical performance of a FS function is tightly related to how well it satisfies these constraints and none of the investigated FS functions can satisfy all the three constraints at the same time. Finally we present a novel framework for developing FS functions which satisfy all the three constraints, and design several new FS functions using this framework. Experimental results on Reuters21578 and Newsgroup corpora show that our new FS function DFICF outperforms IG and DF when using either Micro- or Macro-averaged-measures.
Asymptotic properties of biorthogonal polynomials systems related to Hermite and Laguerre polynomials
Yan Xu
Mathematics , 2015,
Abstract: In this paper, the structures to a family of biorthogonal polynomials that approximate to the Hermite and Generalized Laguerre polynomials are discussed respectively. Therefore, the asymptotic relation between several orthogonal polynomials and combinatorial polynomials are derived from the systems, which in turn verify the Askey scheme of hypergeometric orthogonal polynomials. As the applications of these properties, the asymptotic representations of the generalized Buchholz, Laguerre, Ultraspherical(Gegenbauer), Bernoulli, Euler, Meixner and Meixner-Pllaczekare polynomials are derived from the theorems directly. The relationship between Bernoulli and Euler polynomials are shown as a special case of the characterization theorem of the Appell sequence generated by $\alpha$ scaling functions.
Tea polyphenol inhibits colorectal cancer with microsatellite instability by regulating the expressions of HES1, JAG1, MT2A and MAFA
Yan-yan Xu
Zhong Xi Yi Jie He Xue Bao , 2010,
Abstract: Objective: To investigate the mechanism of tea polyphenol in inhibiting microsatellite instability (MSI) of colorectal cancer.Methods: Using LoVo cells and SW480 cells treated with aqueous solution of tea polyphenol, cell proliferation was detected by methyl thiazolyl tetrazolium (MTT) method, changes in microsatellite sequences were detected by genescan method and changes in gene expression of LoVo cells were detected by illumina expression arrays and quantitative real-time polymerase chain reaction (PCR).Results: The proliferation inhibition rates of LoVo and SW480 cells treated with tea polyphenol increased with the increasing of drug concentration and showed an increasing tendency with time. The proliferation inhibition rate of LoVo cells with tea polyphenol was higher than that of SW480 cells, and there was a significant difference in the proliferation inhibition rates at 24 h, 72 h and one week. The microsatellite sequence of LoVo cells treated with tea polyphenol remained stable. The gene expression arrays and quantitative real-time PCR suggested that tea polyphenol inhibited the gene expressions of MT2A, MAFA, HES1 and JAG1 nearly two-fold over controls. It was also found that tea polyphenol inhibited the BAX and p38 genes with a more than two-fold difference but did not significantly inhibit the nuclear factor-κB pathway.Conclusion: Tea polyphenol significantly inhibited the proliferation of MSI colorectal cancer cells and stably maintained the microsatellite state in MSI colorectal cancer. Tea polyphenol inhibited the gene expressions of HES1, JAG1, MT2A and MAFA, up-regulated the gene expression of BAX and down-regulated that of P38. Further research is required to investigate how these pathways are interrelated.
Fuzzy comprehensive evaluation of five forage shrubs in Mu Us sandland, China  [PDF]
Dongmei Xu, Xinzhong Xu, Hongbin Ma, Yan Shen
Agricultural Sciences (AS) , 2012, DOI: 10.4236/as.2012.31010
Abstract: Chemical compositions during different growing periods, preference and in vitro digestibility at the post-fruiting period of five psammophyte shrubs, which include Caragana intermedia, Caragana korshinskii, Hedysarum scoparium, Hedysarum laeve, Salix psammophylla were determined. The nutritive values were synthetically evaluated in terms of chemical composition, preference and in vitro digestibility through fuzzy multifactorial model. The crude protein (CP) concentrations of the five shrubs had the tendency to decrease with growing stage, the peak values of C. intermedia, C. korshinskii and S. psammophylla appeared at blooming period and those of H. scoparium and H. laeve appeared at vegetative period. The neutral-detergent fiber (NDF), acid-detergent fiber (ADF) and lignin concentrations of C. intermedia, C. korshinskii and S. psammophylla were all decreased before post-fruiting period and then increased significantly; while the variation tendency of those of H. scoparium and H. leave were alike, and the lowest NDF, ADF and lignin concentrations were at vegetative period or post-fruiting period. The five shrubs can be used as feedstuffs, the synthetical nutritive value at the post-fruiting period were high in order of C. intermedia, H. scoparium, H. laeve, C. korshinskii and S. psammophylla. Considering the characteristics of growth and nutritive value, the optimum time to use these shrubs as feedstuffs is the post-fruiting period in autumn. Among the five shrubs, C. intermedia is the best as feed-stuff for raising the production of livestock.
Research on Interlayer Alloys for Transient Liquid Phase Diffusion Bonding of Single Crystal Nickel Base Superalloy DD6  [PDF]
Qiuya Zhai, Jinfeng Xu, Tianyu Lu, Yan Xu
Journal of Materials Science and Chemical Engineering (MSCE) , 2014, DOI: 10.4236/msce.2014.29002
Abstract: Transient Liquid Phase Diffusion bonding (TLP bonding) is an effective method to achieve excellent joint of DD6, which is a new generation single crystal superalloy to manufacture aero-engine turbine blades. In this paper, the interlayer alloys for DD6 TLP bonding were designed. The alloy foils with thickness 40 μm ~ 60 μm, width 4 mm were prepared by using a single roller rapid solidification apparatus and the TLP bonding of DD6 was conducted. Then the joint microstructure and alloying elements diffusion behaviors were analyzed. The results indicate that microstructures of interlayer alloys prepared are fine and homogeneous, the melting point range of alloys from 1070°C to 1074°C and their melting temperature interval is merely 20°C, when the chemical composition of alloys are 1.5 ~ 2.0Cr, 3.2 ~ 4.0W, 3.7 ~ 4.5Co, 2.2 ~ 3.0Al, 0.7 ~ 1.0Mo, 3.2B, remain Ni (wt%). When the welding parameters are bonding temperature 1200?C, holding time 8.0 hour and welding pressure 0.3 MPa, the compacted joints obtained and the microstructure of TLP bonding seams were similar to base metal. The bonding joint is composed of weld center zone, isothermal solidification zone and diffusion-affected zone. Within joint, the elements diffusion is sufficient and borides in the diffusion zone are fewer.
Anisotropic WM conductivity reconstruction based on diffusion tensor magnetic resonance imaging: a simulation study  [PDF]
Dandan Yan, Wenlong Xu, Jing Li
Journal of Biomedical Science and Engineering (JBiSE) , 2010, DOI: 10.4236/jbise.2010.38103
Abstract: The present study aims to estimate the in vivo anisotropic conductivities of the White Matter (WM) tissues by means of Magnetic Resonance Electrical Impedance Tomography (MREIT) technique. The realistic anisotropic volume conductor model with different conductivity properties (scalp, skull, CSF, gray matter and WM) is constructed based on the Diffusion Tensor Magnetic Resonance Imaging (DT- MRI) from a healthy human subject. The Radius Basic Function (RBF)-MREIT algorithm of using only one magnetic flux density component was applied to evaluate the eigenvalues of the anisotropic WM with target values set according to the DT-MRI data based on the Wolter’s model, which is more physiologically reliable. The numerical simulations study performed on the five-layer realistic human head model showed that the conductivity reconstruction method had higher accuracy and better robustness against noise. The pilot research was used to judge the feasibility, meaningfulness and reliability of the MREIT applied on the electrical impedance tomography of the complicated human head tissues including anisotropic characteristics.
Large-scale Surveillance System based on Hybrid Cooperative Multi-Camera Tracking  [PDF]
Xiao Yan, Dan Xu, Bo Yao
Open Journal of Applied Sciences (OJAppS) , 2013, DOI: 10.4236/ojapps.2013.31B016
Abstract: In this paper, we proposed an optimized real-time hybrid cooperative multi-camera tracking system for large-scale au-tomate surveillance based on embedded smart cameras including stationary cameras and moving pan/tilt/zoom (PTZ) cameras embedded with TI DSP TMS320DM6446 for intelligent visual analysis. Firstly, the overlapping areas and projection relations between adjacent cameras' field of view (FOV) is calculated. Based on the relations of FOV ob-tained and tracking information of each single camera, a homography based target handover procedure is done for long-term multi-camera tracking. After that, we fully implemented the tracking system on the embedded platform de-veloped by our group. Finally, to reduce the huge computational complexity, a novel hierarchical optimization method is proposed. Experimental results demonstrate the robustness and real-time efficiency in dynamic real-world environ-ments and the computational burden is significantly reduced by 98.84%. Our results demonstrate that our proposed sys-tem is capable of tracking targets effectively and achieve large-scale surveillance with clear detailed close-up visual features capturing and recording in dynamic real-life environments.
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