Word recognition: From letters to meaning.

Reviews the book, Basic Processes in Reading Visual Word Recognition by Derek Besner and Glyn W. Humphreys (see record 1990-99017-000). While there has been an increase in the amount of work on many different aspects of reading, as Besner and Humphreys point out in the overview to their book, the vast majority of the research on the topic of reading in the past twenty years has been concerned with the processes involved in word recognition. For this reason, Besner and Humphreys have attempted to bring together studies on topics which are both relevant to current debates in the field of word recognition, and which are likely to be important for future developments in the field. They have compiled an edited volume consisting of their overview and eight additional chapters. The editors have attempted to span the continuum of processes involved in word recognition and thus have included chapters which cover topics ranging from the visual analysis of words, to those on the influence of semantic factors on word recognition. The authors of these chapters comprise an impressive list of researchers in the field of word recognition, with the majority of chapters being authored by leading researchers on the topic. Given the stature of the authors and the range of topics covered, in theory this volume should provide a very thorough overview of current theory and research on reading. There is no question that each of the chapters is interesting and important in its own right. However, in practice the volume as a whole fell somewhat short of my expectations. The different tacts taken by different authors has resulted in a very uneven coverage of the current debates in the field. Notwithstanding these criticisms, I am sure that the majority of researchers in this field will consider this volume to be an important contribution. The book would provide a very useful addition to graduate courses in cognitive sciences and as a supplemental text for an undergraduate course on the psychology of reading. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Learning-based dynamic coupling of discrete and continuous trackers

We present a data-driven dynamic coupling between discrete and continuous methods for tracking objects of high dofs, which overcomes the limitations of previous techniques. In our approach, two trackers work in parallel, and the coupling between them is based on the tracking error. We use a model-based continuous method to achieve accurate results and, in cases of failure, we re-initialize the model using our discrete tracker. This method maintains the accuracy of a more tightly coupled system, while increasing its efficiency. At any given frame, our discrete tracker uses the current and several previous frames to search into a database for the best matching solution. For improved robustness, object configuration sequences, rather than single configurations, are stored in the database. We apply our framework to the problem of 3D hand tracking from image sequences and the discrimination between fingerspelling and continuous signs in American Sign Language.     

基桩反射波法动测曲线的数值模拟与特征分析

采用美国PDI公司开发的PDI-S软件,对不同缺陷基桩的反射波法低应变动测曲线进行数值模拟,对动测曲线的特征进行归纳与总结,以便在解释反射波法曲线时作为参考与借鉴,提高基桩质量检测的可靠度。     

大庆油田杏1-3区三次加密试验区剩余油分布研究

通过对试验区近年完钻的检查井各单砂层水淹状况及其影响因素的分析。利用神经网络模式识别方法建立起单层剩余油识别模型，在此基础上对三次加密试验区各小层剩余油分布进行研究，总结出各类油层剩余油分布特征及成因类型，并分析了试验区剩余油潜力分布，从而为三次加密布井及射孔方案编制提供了可靠的依据。     

Two-tier architecture for unconstrained handwritten character recognition

In this paper, we propose an approach that combines the unsupervised and supervised learning techniques for unconstrained handwritten numeral recognition. This approach uses the Kohonen self-organizing neural network for data classification in the first stage and the learning vector quantization (LVQ) model in the second stage to improve classification accuracy. The combined architecture performs better than the Kohonen self-organizing map alone. In the proposed approach, the collection of centroids at different phases of training plays a vital role in the performance of the recognition system. Four experiments have been conducted and experimental results show that the collection of centroids in the middle of the training gives high performance in terms of speed and accuracy. The systems developed also resolve the confusion between handwritten numerals.     

基于HOP的可调光编码／解码器的研究

提出了一种基于全息光处理器的可调光编码/解码器的实现方案。全息光处理器可以在空间进行编/解码，每个通信网络单元可以采用任意速率的数字或模拟的调制信号，它非常适合于多媒体的通信网络环境，通过对全息光处理器的折射率大小和位置的控制，当一个输入光脉冲经过光处理器中具有特定折射率的空间位置后，便可在处理器的输出端口得到合适的输出信号。本文给出了这种基于全息光处理器的可调光编码/解码器的仿真实验，结果是可行的，与以前文献中提出的结构相比，减小了硬件实现的复杂性，降低了成本和功耗，便于集成。     

检测骨架图形特征点的新方法

端点、折点、歧点和交点是骨架图形的重要特点是，提出用快速查表法检测侯选特征点，再进行侯选特征点聚集，用局部结构分析，去除假特征点，判别真特征点的类型，并对折点给以大致的定量描述。实验结果表明，该方法能快速有效地找出骨架图形的特征点，在目标识别、字符识别等应用中起着关键作用。     

继续引领光的方向

光通信仍将在未来电信竞争中扮演制高点的角色。运营商建设光网络首先应充分利用光层的技术，提高系统容量，降低系统成本；其次应提供多业务接入平台；最后发展智能光传输网络，增强网络适应能力。北电网络具有优势的城域网络技术集中在三大领域，即城域DWDM、多业务提供平台（MSPP）和弹性分组环（RPR）；北电网络OPTera城域系列产品正是在上述技术优势支撑下的产品。     

论网络升级方式与光纤选择的关系

在重点说明影响传输光纤设计的主要问题的同时，简要介绍了各种升级方式所面临的主要技术挑战，并详细说明这些挑战对传输光纤提出的技术要求。