健壮性学习算法

使用统计方法可以对汉英机器翻译的词性标注和句法语义分析阶段产生的歧义进行消歧,在估计过程中往往使用最大可能方法,但是并不是在所有的情况下取最大值都是正确的。为了从所有候选结果中取到正确的结果,本文使用健壮性学习算法。使用这个算法,当正确的候选结果评分不是最高时,仍能通过健壮性算法来调整正确结果的评分,使之最大,并且降低不正确候选的评分。而且,由于训练集与测试集存在不同,使训练集中的错误率最小不能保证测试集中的错误率也最小。因此当考虑训练语料库和测试语料库存在统计变化时,应该使用健壮性学习算法。     

Adaptive channel allocation for large-scale streaming content delivery systems

Scheduling algorithms are used in content delivery systems to control the resource allocation rate. They not only improve system efficiency, but also increase user satisfaction. Lower renege rate and less waiting time for users are the main goals for a scheduling algorithm. Among existing algorithms, On-Demand strategy does not perform well, while rate control channel allocation policies performs much better. Pure-Rate-Control (PRC) and Multiple-Service-Class (MSC) belong to the rate control algorithms. MSC performs well, but a drawback is that it uses the Hot Index, which is hard to decide and has significant effects on the performance. In order to solve this problem and to improve the overall system performance, two new algorithms, Modified MSC(MMSC) and Adaptive Algorithm (AA), are proposed in this paper. Both of them solved the problem of MSC very well and improved the overall performance. For example, the renege rate of AA is about 5.4% less than that of MMSC, and about 9.8% less than that of MSC.

动态地构建和维护基于小波的直方图*

利用小波变换的数学理论和方法,对基本的数据分布进行小波分解,在此基础上采用一种新的方法来动态地构建和维护基于小波的直方图,并给出相应的算法。实验证明基于这种方法的小波直方图能提供好的选择性估算和近似技术。     

Mechanical behaviour of cadmium-boron and cadmium-tungsten particulate composites

Mechanical behaviour of particulate composites of cadmium containing 0.6 to 3 m size particles of boron and tungsten (up to 30 vol %) were studied from –196 to 260° C (0.13 to 0.9T _m). The marked strengthening of cadmium by the presence of fine particles is attributed to significant grain size and texture strengthening effects as well as to dispersion hardening effects.     

Generalized Adjusted Rand Indices for cluster ensembles

In this paper, Adjusted Rand Index (ARI) is generalized to two new measures based on matrix comparison: (i) Adjusted Rand Index between a similarity matrix and a cluster partition (ARImp), to evaluate the consistency of a set of clustering solutions with their corresponding consensus matrix in a cluster ensemble, and (ii) Adjusted Rand Index between similarity matrices (ARImm), to evaluate the consistency between two similarity matrices. Desirable properties of ARI are preserved in the two new measures, and new properties are discussed. These properties include: (i) detection of uncorrelatedness; (ii) computation of ARImp/ARImm in a distributed environment; and (iii) characterization of the degree of uncertainty of a consensus matrix. All of these properties are investigated from both the perspectives of theoretical analysis and experimental validation. We have also performed a number of experiments to show the usefulness and effectiveness of the two proposed measures in practical applications.     

Identification of Breast Cancer Prognosis Markers via Integrative Analysis

In breast cancer research, it is of great interest to identify genomic markers associated with prognosis. Multiple gene profiling studies have been conducted for such a purpose. Genomic markers identified from the analysis of single datasets often do not have satisfactory reproducibility. Among the multiple possible reasons, the most important one is the small sample sizes of individual studies. A cost-effective solution is to pool data from multiple comparable studies and conduct integrative analysis. In this study, we collect four breast cancer prognosis studies with gene expression measurements. We describe the relationship between prognosis and gene expressions using the accelerated failure time (AFT) models. We adopt a 2-norm group bridge penalization approach for marker identification. This integrative analysis approach can effectively identify markers with consistent effects across multiple datasets and naturally accommodate the heterogeneity among studies. Statistical and simulation studies demonstrate satisfactory performance of this approach. Breast cancer prognosis markers identified using this approach have sound biological implications and satisfactory prediction performance.     

汉语同语的功能特点与英译策略

以北大语料库(CCL)为例,分析论述汉语同语的功能特点.除了和英语同语一样可以表示强调以外,它们还具有转折、让步和赞誉的功能.对汉语同语进行英译时,应通过“理解-传递-体现”三个阶段实现功能对等.对表强调功能的单举式同语,可以保留其语言形式;对具有转折、让步和赞誉功能以及表强调功能的对举式同语,则应弃形式、保功能.     

Model experiment on anti-deformation performance of a self-supporting transmission tower in a subsidence area

A large number of high-voltage power transmission towers have recently been constructed in mining areas prone to subsidence.In order to ensure the safety of the transmission towers and the safe operati...     

A MKL based on-line prediction for gasholder level in steel industry

The real-time prediction for gasholder level is significant for gas scheduling in steel enterprises. In this study, we extended the least squares support vector regression (LSSVR) to multiple kernel learning (MKL) based on reduced gradient method. The MKL based LSSVR, using the optimal linear combination of kernels, improves the generalization of the model and reduces the training time. The experiments using the classical non-flat function and the practical problem shows that the proposed method achieves well performance and high computational efficiency. And, an application system based on the approach is developed and applied to the practice of Shanghai Baosteel Co. Ltd.     

基于模糊控制的微型燃机燃料压力控制

针对微型燃气轮机在控制时由于压力不恒定而导致的运行效率低的问题,将模糊PID控制思想运用到控制系统。在传统的PID控制下加入模糊控制,使其PID参数具有在线自整定功能。仿真结果表明,该方法能够很好地提高压力控制效果。