提取地震信号高频信息方法的若干问题

岩性油气藏勘探已成为当代油气勘探的重要组成部分,因此提取地震资料高频信息已成为一个重要研究课题。文中对分辨率、分频处理地震信号、波阻抗反演中的一些问题进行了较深入的讨论,并得出以下认识:1要提高垂向和横向分辨率,必须设法提高野外采集地震资料的频率;2地震分频处理是偏移后提高分辨率的常用方法之一,这种方法应该限定在地震波的有效频带内,而超出有效频带,可能会带来很多假像;3低频合成地震记录中高频反射系数存在不确定性。在基于模型波阻抗反演的方法中,反演结果受初始模型的影响非常大,初始模型是依据测井资料建立的,初始模型与实际情况越接近,反演效果就越好;否则,会产生模型化的现象;4在相对波阻抗数据体(相当于地震数据体)作为约束条件下的SP测井参数协克里金插值是正演过程,消除了模型化的问题,使反演结果更接近真实情况,提高了砂层真实的分辨率。     

WPAN/WLAN应用环境下基于PER的链路自适应算法

本文重点研究基于包错误率测量的链路自适应算法，分析了包错误率与信道参数的关系，提出了一种有别于固定门限值方案的优化门限值方案。仿真结果表明，优化门限值方案的网络吞吐量要大于固定门限值方案和基于信干比估计的链路自适应算法，最大增幅可达12Mbit/s。在系统引入重传机制后，网络吞吐量将有所损失，但最大不超过1Mbit/s，相比较服务质量的提高是值得的。需指出的是，虽然分析和仿真均以HIPERLAN／2为例，但不失一般性，它们同样适合于WPAN/WLAN等类似系统。     

变换域数字水印处理技术

数字水印是信息安全领域的一项新技术,给出了相对明确的定义。着重分析了变换域数字水印系统的特征及常见攻击,给出了一些相应的对策。最后指出变换域水印的重要问题,即频率的选择问题。     

海拉尔盆地的古河道砂体识别方法

本文基于海拉尔盆地贝尔凹陷西北部高精度三维地震资料,通过对时间域、频率域地震属性的分析,研究了河道砂体的变化及分布规律,总结出了一套利用时间域、频率域地震属性识别古河道的方法。其中对河道砂体较为敏感的沿层属性主要有均方根振幅、反射强度梯度、有效带宽及瞬时频度等。利用这种识别方法在该区找到水下分流河道砂体和河口坝砂体,为该区的岩性勘探部署提供了具体目标。     

机器人腕力传感器的动态负载效应

本文从时域和频域两方面研究机器人腕力传感器在加载情况下的动态响应，进行动态建模和频谱分析，探讨负载效应的影响。     

Bandwidth Adaptation Algorithms for Adaptive Multimedia Services in Mobile Cellular Networks

The fluctuation of available link bandwidth in mobilecellular networks motivates the study of adaptive multimediaservices, where the bandwidth of an ongoing multimedia call can bedynamically adjusted. We analyze the diverse objectives of theadaptive multimedia framework and propose two bandwidth adaptationalgorithms (BAAs) that can satisfy these objectives. The firstalgorithm, BAA-RA, takes into consideration revenue and``anti-adaptation' where anti-adaptation means that a user feelsuncomfortable whenever the bandwidth of the user's call ischanged. This algorithm achieves near-optimal total revenue withmuch less complexity compared to an optimal BAA. The secondalgorithm, BAA-RF, considers revenue and fairness, and aims at themaximum revenue generation while satisfying the fairnessconstraint defined herein. Comprehensive simulation experimentsshow that the difference of the total revenue of BAA-RA and thatof an optimal BAA is negligible. Also, numerical results revealthat there is a conflicting relationship between anti-adaptationand fairness.     

一种支持QoS的拓扑自适应动态组播路由算法

YAM、QoSMIC、DSDMR等一类支持QoS的动态组播路由算法允许组播成员动态地加入和离开，同时为接收方提供多个可选择的组播接入路径，以满足不同应用的QoS需求。但这些算法普遍存在控制信令开销大和结点加入时延长，可扩展性不好等问题。本文在分析这些算法的基础上，提出改进的支持QoS的动态组播路由算法，即拓扑自适应动态组播路由（Topology Adaptive Dynamic Multicast Routing，TADMR）算法。该算法避免了以往算法中大部分盲目的路径搜索，并使结点加入时延不再受限于固定的等待时钟，而与网络拓扑相自适应。性能分析和仿真结果表明，该算法具有较低的控制信令开销和结点加入时延，适用于各种网络规模和群组规模，具有良好的可扩展性。     

Comment on Greenwood (2007): Solving the puzzle of structure/function relations in the aging brain?

Neuroimaging experiments have shown that prefrontal regions of the brain, which have the most age-related volume loss, are also the regions most likely to be more active in older adults than in younger adults. In an attempt to solve this puzzle, P. M. Greenwood (see record 2007-15625-001) has proposed a cascade that flows from age-related atrophy in the brain to changed processing strategies that result in plastic changes in regions adjacent and contralateral to the atrophic areas, culminating in greater functional activity. This hypothesis should stimulate research into these mechanisms and hopefully will ultimately inform researchers' ability to rehabilitate cognitive disorders in the elderly. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Extending boosting for large scale spoken language understanding

We propose three methods for extending the Boosting family of classifiers motivated by the real-life problems we have encountered. First, we propose a semisupervised learning method for exploiting the unlabeled data in Boosting. We then present a novel classification model adaptation method. The goal of adaptation is optimizing an existing model for a new target application, which is similar to the previous one but may have different classes or class distributions. Finally, we present an efficient and effective cost-sensitive classification method that extends Boosting to allow for weighted classes. We evaluated these methods for call classification in the AT&;T VoiceTone^® spoken language understanding system. Our results indicate that it is possible to obtain the same classification performance by using 30% less labeled data when the unlabeled data is utilized through semisupervised learning. Using model adaptation we can achieve the same classification accuracy using less than half of the labeled data from the new application. Finally, we present significant improvements in the “important” (i.e., higher weighted) classes without a significant loss in overall performance using the proposed cost-sensitive classification method.     

A new adaptation of mapping method to study mixing of multiphase flows in mixers with complex geometries

The main objective of the present work is to modify the traditional mapping method for the simulation of distributive mixing of multiphase flows in geometries involving moving parts such as, internal mixers or twin-screw extruders without a limitation on their geometrical periodicity. The periodicity condition, limits the results of traditional mapping method to tracking mapping mesh between specific discrete time intervals or distances for that geometry is repeated, hence, result is only for fixed orientation of rotors. Imaginary domain method is introduced to track mapping mesh from one state to the next free of geometrical periodicity limitations. In this work the method is introduced and its applicability and accuracy is discussed in details. A two-dimensional (2D) simulation of mixing of two Newtonian fluids with different viscosities in an intermeshing internal mixer is used as a test case study. In this example the key issues of ability to predict mixing state in details for all orientations of rotors is presented. To reduce diffusion errors of mapping method in the boundaries of the rotors, mapping mesh refinement technique that relies upon one single reference mesh is also presented.