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匹配条件: “Lirong Wang” ,找到相关结果约115137条。
Empirical likelihood confidence intervals for the differences of quantiles with missing data
Lirong Wang
Journal of Global Research in Mathematical Archives , 2013,
Abstract: Suppose there are two nonparametric populations X and Y with missing data on both of them. Random imputation is used to fill in missing data, so the “complete”samples of X and Y can be constructed. Then the empirical likelihood confidence intervals for the differences of quantile are constructed. Key words:Empirical likelihood; Confidence interval; Quantile; Missing data; Imputation. 2000 MR subject classification: 62G05, 62E20
A Globally Convergent Parallel SSLE Algorithm for Inequality Constrained Optimization
Zhijun Luo,Lirong Wang
Journal of Mathematics , 2014, DOI: 10.1155/2014/461902
Abstract: A new parallel variable distribution algorithm based on interior point SSLE algorithm is proposed for solving inequality constrained optimization problems under the condition that the constraints are block-separable by the technology of sequential system of linear equation. Each iteration of this algorithm only needs to solve three systems of linear equations with the same coefficient matrix to obtain the descent direction. Furthermore, under certain conditions, the global convergence is achieved. 1. Introduction Consider the following inequality constrained optimization problems: where , are continuously differentiable. We denote To solve the problem (1), there are two type methods with superlinear convergence: sequential quadratic programming (SQP) type algorithms (see [1–4], etc.) and SSLE (sequential system of linear equations) type algorithms (see [5–9], etc.). In general, since SQP algorithms are necessary to solve one or more quadratic programming subproblems in single iteration, the computation effort is very large. SSLE algorithms were proposed to solve the problem (1), in which an iteration similar to the following linear system was considered: where is Lagrangian function, is an estimate of the Hessian of , is the current estimate of a solution , is the search direction, and is the next estimate of the Kuhn-Tucker multiplier vector associated with . Obviously, it is simpler to solve system of linear equations than to solve the QP (quadratic programming) problem with inequality constraints. In addition, parallel variable distribution (PVD) algorithm [10] is a method that distributes the variables among parallel processors. The problem is parted into many respective subproblems and each subproblem is arranged to a different processor in it. Each processor has the primary responsibility for updating its block of variables while allowing the remaining secondary variables to change in a restricted fashion along some easily computable directions. In 2002, Sagastizábal and Solodov [11] proposed two new variants of PVD for the constrained case. Without assuming convexity of constraints, but assuming block-separable structure, they showed that PVD subproblems can be solved inexactly by solving their quadratic programming approximations. Han et al. [12] proposed an asynchronous PVT algorithm for solving large-scale linearly constrained convex minimization problems with the idea in 2009, which is based on the idea that a constrained optimization problem is equivalent to a differentiable unconstrained optimization problem by introducing the Fischer
A Microarray Analysis of Parkinson’s Disease: New Clues and Evaluation  [PDF]
Lirong Huo, Xibin Liang, Yi He, Xiaomin Wang
Journal of Biosciences and Medicines (JBM) , 2015, DOI: 10.4236/jbm.2015.39009

Parkinson’s disease (PD) is complex and most likely results from an unknown combination of genetic and environmental factors. Here, we defined discrete genes (DGs) in a microarray analysis and found that the percentage of DGs versus all analyzable genes correlated with PD progression. Furthermore, this new parameter was also easily used to evaluate the therapeutic effect of high- frequency electro-acupuncture (EA), thus improving symptoms of PD model rats.

Study on Undergraduates Employment Ideological Education Practice  [PDF]
Lirong Ai
Creative Education (CE) , 2015, DOI: 10.4236/ce.2015.63029
Abstract: The critical solution to the employment of graduates with difficulties in finding a job, which is initially contributed to the stresses and strains of the career guidance in higher vocational colleges, is to solve the problem of ideological and political education the graduates should have. This paper analyzed the data from a survey, taken in a vocational college in Hubei Province in China, on what kinds of problems and why the graduates with difficulties in finding a job might suffer from in their minds. And then the reasonable comments and proper suggestions were presented to solve the problem in higher vocational colleges in China under the guidance of related theories of Chinese and Western ideological and political education.
Source of a floating dust episode over the Qingdao region and dust throughput to the ocean
Anchun Li,Lirong Chen,Pigao Wang
Chinese Science Bulletin , 1998, DOI: 10.1007/BF02885515
Abstract: A floating dust weather happened on March 11–12, 1995 over the Qingdao region. Its source’s and throughput to the ocean were studied. The result indicated that the floating dust was caused by the dust storm that started in northwestern China and developed in northern China. 21 × 106t fine soil particles were carried to the ocean during the episode.
The Design of Digital Video Monitor System Based on LAN in Library

Wang Lirong,

现代图书情报技术 , 2004,
Abstract: This paper introduces the actuality of monitor system and discusses the design of digital video monitor system based on LAN in Library.
A quality assurance procedure and evaluation of rainfall estimates for C-band polarimetric radar

Zhiqun Hu,Liping Liu,Lirong Wang,

大气科学进展 , 2012,
Abstract: A mobile C-band dual polarimetric weather radar J type (PCDJ), which adopts simultaneous transmission and simultaneous reception (STSR) of horizontally and vertically polarized signals, was first developed in China in 2008. It was deployed in the radar observation plan in the South China Heavy Rainfall Experiment (SCHeREX) in the summer of 2008 and 2009, as well as in Tropical Western Pacific Ocean Observation Experiments and Research on the Predictability of High Impact Weather Events from 2008 to 2010 in China (TWPOR).
Research on the Dynamic Data-driven Application System Architecture for Flight Delay Prediction
Haiyan Chen,Jiandong Wang,Lirong Feng
Journal of Software , 2012, DOI: 10.4304/jsw.7.2.263-268
Abstract: Flight delay prediction remains an important research topic due to the dynamics of the flight operating process. To solve this problem, a dynamic data-driven approach from the control area has been introduced, in which real-time data was collected and injected into the prediction process to get more accurate and reliable results. In the case of predicting the landing delays of consecutive arrival flights, delay propagation was analyzed to establish the corresponding state space model. Then, dynamic data-driven prediction architecture for flight delay and the prediction steps of on this architecture were presented. Several experiments were carried out on historic flight data to validate the performance of this solution. Results show that the accuracy is high, and not sensitive to the number of the predicted flights. Therefore, the solution has good predictive stability and reliability.
SDED: A novel filter method for cancer-related gene selection
Wenlong Xu,Minghui Wang,Xianghua Zhang,Lirong Wang
Bioinformation , 2008,
Abstract: Gene selection is to detect the most significantly expressed genes under different conditions expression data. The current challenge in gene selection is the comparison of a large number of genes with limited patient samples. Thus it is trivial task in simple statistical analysis. Various statistical measurements are adopted by filter methods applied in gene selection studies. Their ability to discriminate phenotypes is crucial in classification and selection. Here we describe the standard deviation error distribution (SDED) method for gene selection. It utilizes variations within-class and among-class in gene expression data. We tested the method using 4 leukemia datasets available in the public domain. The method was compared with the GS2 and CHO methods. The Prediction accuracies by SDED are better than both GS2 and CHO for different datasets. These are 0.8-4.2% and 1.6-8.4% more that in GS2 and CHO. The related OMIM annotations and KEGG pathways analyses verified that SDED can pick out more 4.0% and 6.1% genes with biological significance than GS2 and CHO, respectively.
Observation on Poterioochromonas sp. (Chrysophyte)  [PDF]
Shengjuan Guo, Lirong Song
Journal of Water Resource and Protection (JWARP) , 2010, DOI: 10.4236/jwarp.2010.26068
Abstract: Poterrioochromonas sp., isolated from Microcystis cultures in 2002, was described with LM, SEM, TEM. The grazing characteristics of this strain were also observed in laboratory experiments. The results showed that this strain has the representative features of the genus except for the lorica, and the most conspicuous feature of Poterioochromonas sp. was about the chromatophores.

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