压裂斜井时射孔处雁形裂缝产生及干扰分析

在已射孔的斜井压裂过程中，射孔孔眼处会出现一系列的几乎相互平行的雁形裂缝。这些裂缝的延伸、连接受到地层应力及裂缝本身的影响，情况较为复杂，但它们的延伸和连接对压裂的成功与否至关重要。笔者对裂缝模型进行简化，将复变函数理论与位错理论相结合，并且考虑了裂缝表面有流体压力作用且裂缝之间存在相互干扰的情况下，建立了无限大介质中裂尖应力强度因子的数学模型，利用该模型可对雁型裂缝之间的相互干扰进行力学分析。应用数值方法对所建立的数学模型求解，得到裂尖的应力强度因子及转角，来预测裂缝连接情况。该结果可用来指导压裂井的射孔施工。     

非理想信道下Colpitts混沌电路的自适应同步研究

本文研究了Colpitts混沌电路在非理想信道条件下的自适应同步问题。引入自适应控制器对输入到响应部分（response system）的衰变混沌信号进行预处理，来补偿衰落信道对于同步性能的影响。给出了系统的数学模型，对恒定信道衰变和时变信道衰变两种非理想信道条件下的混沌ColpiRs电路的自适应同步进行了数值仿真研究。仿真结果表明，对于恒定或慢变化的时变信道衰变，自适应控制器可以有效的提高Colpitts电路响应部分和驱动部分（Drive system）的同步性能。     

区域内旱情监测站点的布设研究

本文对北京通州辖区范围内组织的大规模的土壤墒情调查数据进行总结。基于地理统计、空间分析以及统计学知识，分析了北京通州旱情分布形势。运用数值分类学的知识对测量数据进行了聚类分析，同时用DB(DaviesBouldin)指标准则研究了区域内合理布设旱情监测站的数量及位置，为建立旱情监测站点提供了理论依据。     

On denoising and compression of DNA microarray images

We address the problems of noise and huge data sizes in microarray images. First, we propose a mixture model for describing the statistical and structural properties of microarray images. Then, based on the microarray image model, we present methods for denoising and for compressing microarray images. The denoising method is based on a variant of the translation-invariant wavelet transform. The compression method introduces the notion of approximate contexts (rather than traditional exact contexts) in modeling the symbol probabilities in a microarray image. This inexact context modeling approach is important in dealing with the noisy nature of microarray images. Using the proposed denoising and compression methods, we describe a near-lossless compression scheme suitable for microarray images. Results on both denoising and compression are included, which show the performance of the proposed methods. Further experiments using the results of the proposed near-lossless compression scheme in gene clustering using cell-cycle microarray data for S. cerevisiae showed a general improvement in the clustering performance, when compared with using the original data. This provides an indirect validation of the effectiveness of the proposed denoising method.     

Non-redundant data clustering

Data clustering is a popular approach for automatically finding classes, concepts, or groups of patterns. In practice, this discovery process should avoid redundancies with existing knowledge about class structures or groupings, and reveal novel, previously unknown aspects of the data. In order to deal with this problem, we present an extension of the information bottleneck framework, called coordinated conditional information bottleneck, which takes negative relevance information into account by maximizing a conditional mutual information score subject to constraints. Algorithmically, one can apply an alternating optimization scheme that can be used in conjunction with different types of numeric and non-numeric attributes. We discuss extensions of the technique to the tasks of semi-supervised classification and enumeration of successive non-redundant clusterings. We present experimental results for applications in text mining and computer vision.     

基于多信道预约可冲突避免的多址接入协议

本文为多跳分布多无线网络提出了一套灵活而有效的自适应获取冲突避免（AACA）的多址接入协议。在该协议中，各节点竞争公共信道，利用RTS/CTS对话形式来预约各业务信道，成功预约后的分组传输不会受到其他节点的干扰。它使用任意确定数目信道，以异步方式工作，并且使得各节点利用半双工无线电台就可以灵活、简便地实现资源预约。分析和比较结果说明，所提出的多信道预约协议可以有效地解决隐藏终端、暴露终端以及侵入终端的问题。     

Learning Recursive Bayesian Multinets for Data Clustering by Means of Constructive Induction

This paper introduces and evaluates a new class of knowledge model, the recursive Bayesian multinet (RBMN), which encodes the joint probability distribution of a given database. RBMNs extend Bayesian networks (BNs) as well as partitional clustering systems. Briefly, a RBMN is a decision tree with component BNs at the leaves. A RBMN is learnt using a greedy, heuristic approach akin to that used by many supervised decision tree learners, but where BNs are learnt at leaves using constructive induction. A key idea is to treat expected data as real data. This allows us to complete the database and to take advantage of a closed form for the marginal likelihood of the expected complete data that factorizes into separate marginal likelihoods for each family (a node and its parents). Our approach is evaluated on synthetic and real-world databases.     

Question hard, answer simply: A comment on Storms et al. (2003).

It seems clear that, for whatever reasons, the dementia of the Alzheimer type patient group (as well as other patient groups) exhibits behavior that is different from the normal control group. G. Storms, T. Dirikx, J. Saerens, S. Verstraeten, and P. P. De Deyn (2003) rightfully argue that the observed behavior (similarity judgments) does not tell us the source (cause) of the differences between the 2 groups. Rather, the focus of the study should be placed more on finding the ways the 2 groups are different. They also point out various methodological problems in some of the previous attempts to characterize the nature of the differences. Further methodological issues in G. Storms et al.'s study are examined. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A Low-Complexity Multiuser Detector for Asynchronous CDMA QPSK Adaptive Antenna Array Systems

This paper proposes a low complexity joint space-time multiuser detection algorithm for asynchronous DS/CDMA antenna array systems. The proposed multiuser detector is composed of an adaptive antenna array, used as a linear beamformer, and a sliding window decorrelator. A QPSK modulation scheme is used in order to increase bandwidth efficiency. Numerical results are given in terms of Bit Error Rate (BER) under the assumption of a frequency-selective Rayleigh slow fading channel. In particular, the proposed receiver is shown to be near-far resistant, even in worst fading cases, and to exploit completely array introduction while maintaining acceptable computational complexity. The proposed architecture avoids linear filter realization of the decorrelator, which is impractical in the case of a large number of users, and operates with relatively short data frames instead of the complete information sequence. Finally, this receiver is very flexible to changes in timing configuration.     

SAR图像组合分割算法

由于存在乘性斑点噪声的影响,给SAR图像分割造成很大困难,本文研究利用最大似然区域增长分割算法,提出区域增长前引入自适应边缘检测,图像分割性能获得较大提高.介绍了我们研究的分割性能优异的模拟退火分割算法,提出了分割性能接近模拟退火并且在SAR图像分割中比较实用的模拟退火和最大似然混合分割算法,并给出了这些分割算法的分割性能比较,以及在实际分割SAR图像时应当如何选择分割算法.