Jingbo Wang

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An unknown transient heat source in a three-dimensional participating medium is reconstructed from temperature measurements using a Bayesian inference method. The heat source is modeled as a stochastic process. The joint posterior probability density function (PPDF) of heat source values at consecutive time points is computed using the Bayes' formula. The(More)
Stochastic inverse problems in heat conduction with consideration of uncertainties in the measured temperature data, temperature sensor locations and thermophysical properties are addressed using a Bayesian statistical inference method. Both parameter estimation and thermal history reconstruction problems, including boundary heat flux and heat source(More)
Automatically mining protein pathway information from the vast amount of published literature has been an increasing need from the pharmaceutical industry and biomedical research community. This task has been proved to be a formidable one. Many systems have been implemented, but few are practical. Some are too restricted and some are overly ambitious. 1(More)
A Bayesian inference approach is presented for the solution of the inverse heat conduction problem. The posterior probability density function (PPDF) of the boundary heat flux is computed given temperature measurements within a conducting solid. Uncertainty in temperature measurements is modeled as stationary zero-mean white noise. The inverse solution is(More)
A contamination source identification problem in constant porous media flow is addressed by solving the advection-dispersion equation (ADE) with a hierarchical Bayesian computation method backward through time. The contaminant concentration is modeled as a pair-wise Markov Random Field (MRF) and the distribution is updated using current concentration(More)
Revenue management (RM) enhances the revenues of a company by means of demand-management decisions. An RM system must take into account the possibility that a booking may be canceled, or that a booked customer may fail to show up at the time of service (no-show). We review the Passenger Name Record data mining based cancellation rate forecasting models(More)
This paper studies a multi-stage stochastic programming model for large-scale network revenue management. We solve the model by means of the so-called Expected Future Value (EFV) decomposition via scenario analysis, estimating the impact of the decisions made at a given stage on the objective function value related to the future stages. The EFV curves are(More)
Our previous study revealed that human ribosomal protein L6 (RPL6) was up-regulated in multidrug-resistant gastric cancer cells and over-expression of RPL6 could protect gastric cancer from drug-induced apoptosis. It was further demonstrated that up-regulation of RPL6 accelerated growth and enhanced in vitro colony forming ability of GES cells while(More)
  • Jiugang Song, Liucun Gao, Guang Yang, Shanhong Tang, Huahong Xie, Yongji Wang +10 others
  • 2014
A growing amount of evidence indicates that miRNAs are important regulators of multiple cellular processes and, when expressed aberrantly in different types of cancer such as hepatocellular carcinoma (HCC), play significant roles in tumorigenesis and progression. Aberrant expression of miR-199a-5p (also called miR-199a) was found to contribute to(More)