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Search Results: 1 - 10 of 79148 matches for " Xiaoyan Chen "
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Strong Law of Large Numbers under an Upper Probability  [PDF]
Xiaoyan Chen
Applied Mathematics (AM) , 2012, DOI: 10.4236/am.2012.312A284
Abstract:

Strong law of large numbers is a fundamental theory in probability and statistics. When the measure tool is nonadditive, this law is very different from additive case. In 2010 Chen investigated the strong law of large numbers under upper probabilityVby assumingVis continuous. This assumption is very strong. Upper probabilities may not be continuous. In this paper we prove the strong law of large numbers for an upper probability without the continuity assumption whereby random variables are quasi-continuous and the upper probability is generated by a weakly compact family of probabilities on a complete and separable metric sample space.

Threshold strategy to improve the images reconstructed by electrical impedance tomography  [PDF]
Xiaoyan Chen, Jing Zhang
Journal of Biosciences and Medicines (JBM) , 2013, DOI: 10.4236/jbm.2013.12008
Abstract:


Because of the illposedness of soft field, the quality of EIT images is not satisfied as expected. This paper puts forward a threshold strategy to decrease the artifacts in the reconstructed images by modifying the solutions of inverse problem. Threshold strategy is a kind of post processing method with merits of easy, direct and efficient. Reconstructed by Gauss-Newton algorithm, the simulation image’s quality is improved evidently. We take two performance targets, image reconstruction error and correlation coefficient, to evaluate the improvement. The images and the data show that threshold strategy is effective and achievable.


Digital biomedical electrical impedance tomography based on FPGA  [PDF]
Jiani Wu, Xiaoyan Chen, Zhonglin Ding
Journal of Biosciences and Medicines (JBM) , 2013, DOI: 10.4236/jbm.2013.12004
Abstract:

A digital biomedical electrical impedance tomography (EIT) system is developed with the aid of FPGA. The key elements of EIT system are described specifically in the paper. The functions are realized to generate excitation source, switch electrode channels, deal collected signals, demodulate measured voltages etc. The system is tested by a circular tank with 16 stainless electrodes attached around the boundary. The adjacent incentive adjacent measurement mode is adapted to collect boundary voltages of the interesting field. By testing, the system works with 36 dB signal-to-noise ratio (SNR) when 1 mA 100 KHz current is applied into a homogenous tank.

Mapping and Evaluating Regional University-Industry Knowledge Flow through Patent Licensing  [PDF]
Xiaopei Gao, Yuming Chen, Wei Song, Xiaobao Peng, Xiaoyan Song
Open Journal of Social Sciences (JSS) , 2015, DOI: 10.4236/jss.2015.31001
Abstract: Different regions had various kinds of academic resources and industries competitors. The knowledge and innovation output generated by researchers in academy had been transferred into industries through patent licensing. Using the patent licensing document analyzing method and the mapping technique, the academic-industry knowledge flowing patterns of different regions in China had been discovered and visualized in maps. The regional performance of academic-industry knowledge transfer was rather mixed and unbalanced. Based on the licensing performance data, this paper had also generated a 4 × 4 block matrix as evaluation tool and ranked 28 Chinese regions into 8 levels according to their academic licensing performance. Further suggestions and advice had been given for regions in different levels.
Regional University-Industry Knowledge Flow: A Study of Chinese Academic Patent Licensing Data  [PDF]
Xiaopei Gao, Yuming Chen, Wei Song, Xiaobao Peng, Xiaoyan Song
Open Journal of Social Sciences (JSS) , 2015, DOI: 10.4236/jss.2015.32009
Abstract: Knowledge and technology transferring between universities and industries had been an important research focus of innovation management. Bibliometric research on the university-industry knowledge transferring had always used patent collaboration and citation data as indicators. However, patent licensing data were more representative and could target the knowledge transferring directions. This paper had gone through the data of Chinese academic-industry patent licensing and focused on the variances in regional level and geographic distance. Using patent licensing document analyzing method, the academic-industry knowledge flowing patterns had been discovered. Results showed that localization effects had been existed in those Chinese regions and the engagement of knowledge transferring was severely unbalanced.
A Data-Driven Simulation Model for China Haze Monitor and Governance  [PDF]
Xiaoyan Lu, Hong Chen, Miao Wang, Zhengying Cai
World Journal of Engineering and Technology (WJET) , 2016, DOI: 10.4236/wjet.2016.42036
Abstract: Recently, the China haze becomes more and more serious, but it is very difficult to model and control it. Here, a data-driven model is introduced for the simulation and monitoring of China haze. First, a multi-dimensional evaluation system is built to evaluate the government performance of China haze. Second, a data-driven model is employed to reveal the operation mechanism of China’s haze and is described as a multi input and multi output system. Third, a prototype system is set up to verify the proposed scheme, and the result provides us with a graphical tool to monitor different haze control strategies.
Coal Deformation, Metamorphism and Tectonic Environment in Xinhua, Hunan  [PDF]
Huantong Li, Xiaoyan Zou, Jiafeng Mo, Yifan Wang, Fei Chen
Journal of Geoscience and Environment Protection (GEP) , 2018, DOI: 10.4236/gep.2018.69013
Abstract: This article discusses in detail chemical composition, molecular structure, microstructure phenomena, estimate of the palaeo-stress, paleo-temperature and the strain rate to deepen the knowledge for the correlation of coal deformation and metamorphism with structural environment in Xinhua Hunan by coal quality analysis, XRD and SEM methods, which provide dependable theoretical foundation for coal resource exploitation and utilization. The results show that 1) d002 value of six coal samples is from 3.36 to 3.39 nm, coal resolved itself into aphanitic graphite with the increase of coal rank during coalification, which is characterized by graphite flakes, and the crystallite size is from 50 nm to 250 nm; A certain degree of 3R-structure content is increases and the crystallite size is extend with the coalification process, but RH-structure content is decreased; 2) the tectonic environment of research area belongs to the ductile-brittle deformation, which was characterized by low temperature, low stress, high strain rate; 3) Tianlongshan magmatic intrusion provided heat source, its side-extrusion made the molecules structure of coal ordering, distance between layers decreased, finally it caused the formation of aphanitic graphite.
The Effects of Fe2+ on the Aggregation Behavior of Residual Hydrophobic Modified Polyacryamide  [PDF]
Bin Chen, Shijia Chen, Xiaoyan Wu, Chengsheng Wang, Binbin Wu, Li Qi
Journal of Materials Science and Chemical Engineering (MSCE) , 2016, DOI: 10.4236/msce.2016.412001
Abstract:
The influences of Fe2+ on the aggregation behavior of residual hydrophobic modified polyacryamide (HMPAM) in treated oily wastewater were studied by fluorescence spectrum and DLS. The result of I1/I3 showed that the polarity of hydrophobic domain increased and the size of hydrophobic domain may be decreased with the increasing of Fe2+ in produced water. Fe2+ was helpful for the increase of hydrophobic domain, therefore due to the aggregation degree for HMPAM.
Adaptive Stabilization of the Korteweg-de Vries-Burgers Equation with Unknown Dispersion
Xiaoyan Deng,Lixin Tian,Wenxia Chen
Journal of Applied Mathematics , 2012, DOI: 10.1155/2012/389450
Abstract: This paper studies the adaptive control problem of the Korteweg-de Vries-Burgers equation. Using the Lyapunov function method, we prove that the closed-loop system including the parameter estimator as a dynamic component is globally stable. Furthermore, we show that the state of the system is regulated to zero by developing an alternative to Barbalat's lemma which cannot be used in the present situation. The closed-loop system is shown to be well posed.
Building Disease-Specific Drug-Protein Connectivity Maps from Molecular Interaction Networks and PubMed Abstracts
Jiao Li,Xiaoyan Zhu,Jake Yue Chen
PLOS Computational Biology , 2009, DOI: 10.1371/journal.pcbi.1000450
Abstract: The recently proposed concept of molecular connectivity maps enables researchers to integrate experimental measurements of genes, proteins, metabolites, and drug compounds under similar biological conditions. The study of these maps provides opportunities for future toxicogenomics and drug discovery applications. We developed a computational framework to build disease-specific drug-protein connectivity maps. We integrated gene/protein and drug connectivity information based on protein interaction networks and literature mining, without requiring gene expression profile information derived from drug perturbation experiments on disease samples. We described the development and application of this computational framework using Alzheimer's Disease (AD) as a primary example in three steps. First, molecular interaction networks were incorporated to reduce bias and improve relevance of AD seed proteins. Second, PubMed abstracts were used to retrieve enriched drug terms that are indirectly associated with AD through molecular mechanistic studies. Third and lastly, a comprehensive AD connectivity map was created by relating enriched drugs and related proteins in literature. We showed that this molecular connectivity map development approach outperformed both curated drug target databases and conventional information retrieval systems. Our initial explorations of the AD connectivity map yielded a new hypothesis that diltiazem and quinidine may be investigated as candidate drugs for AD treatment. Molecular connectivity maps derived computationally can help study molecular signature differences between different classes of drugs in specific disease contexts. To achieve overall good data coverage and quality, a series of statistical methods have been developed to overcome high levels of data noise in biological networks and literature mining results. Further development of computational molecular connectivity maps to cover major disease areas will likely set up a new model for drug development, in which therapeutic/toxicological profiles of candidate drugs can be checked computationally before costly clinical trials begin.
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