Intra-habitat heterogeneity of microbial food web structure under the regime of eutrophication and sediment resuspension in the large subtropical shallow Lake Taihu, China

Planktonic microbial community structure and classical food web were investigated in the large shallow eutrophic Lake Taihu (2338 km(2), mean depth 1.9 m) located in subtropical Southeast China. The water column of the lake was sampled biweekly at two sites located 22 km apart over a period of twelve month. Site 1 is under the regime of heavy eutrophication while Site 2 is governed by wind-driven sediment resuspension. Within-lake comparison indicates that phosphorus enrichment resulted in increased abundance of microbial components. However, the coupling between total phosphorus and abundance of microbial components was different between the two sites. Much stronger coupling was observed at Site 1 than at Site 2. The weak coupling at Site 2 was mainly caused by strong sediment resuspension, which limited growth of phytoplankton and, consequently, growth of bacterioplankton and other microbial components. High percentages of attached bacteria, which were strongly correlated with the biomass of phytoplankton, especially Microcystis spp., were found at Site 1 during summer and early autumn, but no such correlation was observed at Site 2. This potentially leads to differences in carbon flow through microbial food web at different locations. Overall, significant heterogeneity of microbial food web structure between the two sites was observed. Site-specific differences in nutrient enrichment (i.e. nitrogen and phosphorus) and sediment resuspension were identified as driving forces of the observed intra-habitat differences in food web structure.

基于web的遥操作系统时延分析

采用预测控制算法给出了一种带有时延补偿器的新的控制结构,分别在前向通道和反馈通道设计补偿器对网络时延进行补偿.实验结果表明:带有预测器及补偿器的新的控制结构可以改善系统的动态性能,并且能够保证系统在具有时延和数据丢失的环境下的稳定性.

基于Petri网的Web数据库访问的建模研究

本文针对多用户访问Web数据库的过程进行了分析并提出改进思路,然后利用带抑止弧的扩充Petri网对改进后的访问过程进行建模。

基于web的远程控制机器人研究

Internet连接了全球的计算机 ,它为人们提供了分享数据、图片、影像甚至实时影像的机会 ,但与远程地点的真实交互还是离不开象机器人这样的智能设备 .Web技术与机器人控制技术的结合 ,促成了基于 web的远程控制机器人概念的诞生 .本文将就基于 web的远程控制机器人的发展历程、研究现状、主要技术与实现、发展趋势及应用前景等做综合的介绍 .

基于WEB支持的市场客户管理系统的设计

本文阐述了采用Ｉｎｔｅｒｎｅｔ／Ｉｎｔｒａｎｅｔ技术和利用ＡＳＰ实现数据的动态发布技术以及基于分布网络环境下的异地设计与制造技术，设计了基于ｗｅｂ的支持机器人异地设计制造的市场客户管理系统，从而探讨了Ｂｒｏｗｓｅｒ／Ｓｅｒｖｅｒ结构的数据库发布系统的设计方法。

Web数据挖掘的原理、方法及用途

Web数据挖掘是将数据挖掘技术和理论应用于对WWW资源进行挖掘的一个新兴的研究领域,本文介绍了Web数据挖掘的基本概念,分类,并给出 Web数据挖掘的基本原理,基本方法,最后指出 Web数据挖掘的用途,展望了其美好的发展前景。

基于XML/Web Services的月球探测数据管理与集成技术研究

随着网络技术、特别是Internet技术的发展，分布式系统的高睦能、高可靠性、高灵敏度、可扩展性和系统透明性使得基于分布式系统的应用越来越广泛。在分布式坏境下，信息系统的集成是必须认真考虑的问题。研究如何集成和统一访问分布的、异构的数据资源，实现各种数据的转换、交流与共享；以及如何建立一个开放、可扩展和异构兼容的新一代信息管理系统成为当今网络应用的重要研究方向。本文针对建立月球探测数据管理和集成系统的数据集成与操作集成两方面的内容，重点分析和研究了数据存储管理和系统集成技术，结合月球探测数据管理的应用集成需求与特点提出了基于XML技术的数据存储与管理和基于Web Service技术的系统集成方案。并利用XML／WebService技术基于Net平台开发了一个月球探测数据管理与集成系统实例。研究内容主要包括以下四个方面： （1）基于XML的数据模型与数据库存储。利用XML的自描述性、独立于平台和应用、半结构化，机器可处理、可扩展性以及便于网络传输和广泛支持的特性，实现了基于关系数据库的XML数据存储。对系统中的结构化和非结构化数据信息、都进行了XML标记定义，实现了信息存储和查询的小粒度，增强了数据的表示、查询、插入和删除等数据处理能力和效率。同时，利用XML作为月球探测数据交换和信息传输的格式，也为实现与异构系统数据的互操作提供了理想的角军决方案。（2）基于WebServices的分布式信息系统集成的体系结构。在对XML、SOAP、WSDL和UDDI关键技术和标准规范进行研究与探讨基础上，针对绕月探测数据管理的需求提出了基于XML／Web Service的三层分布式结构模型。分别是表示层、应用逻辑层、服务端数据层。实现了系统功能的可迁移性和可装配性、各层间传输过程中数据流的XML化、接口定义的动态性。与传统技术开发的耦合的分布式应用系统相比，系统在跨平台性、可配置性、可伸缩性、可维护性等方面都有了大幅度的提高。（3）基于，NET平台系统的开发与实现。深入分析和研究了Mic1’osoft．NET平台的核心技术与整体技术框架，在VisLla1Sttldio．NET开发环境中利用C＃、ASP．NET、ADO．NET基于关系型数据库Oracle9i开发实现了统一身份认证系统和月球探测数据管理与集成系统。统一身份认证系统是一个通用的统一用户身份认证管理系统，包括用户管理、身份验证、实体管理、日志监控和消息、管理等功能，达到了一次登录，所有系统共用的目的。月球探测数据管理与集成系统包括数据管理、信息发布、系统管理、综合查询和应用集成五大功能模块，相对于原来的紧祸合的应用系统而言，系统的开发效率、重用性、祸合度、灵活性和自适 应性都有了很大的提高。（4）基于XML／WebServices的动态系统集成。分析了传统分布式对象模型在异构环境集成的弊端，基于XML、SOAP和WSDL等技术规范基础上，实现了统一身份认证系统、月球探测数据管理与集成系统、小空间碎片数据库系统以及其它语言开发的应用系统的信息集成、实现了资源时空的有效整合。通过这些集成应用实例，充分体现和说明了Web Services技术在应用系统集成方面的优越性。本研究的成果，也将为地球化学研究领域涉及海量数据的处理、管理和系统集成提供示范实例，推动地球化学数据的融合和综合应用。

Analysis of Differential and Matching Methods for Optical Flow

Several algorithms for optical flow are studied theoretically and experimentally. Differential and matching methods are examined; these two methods have differing domains of application- differential methods are best when displacements in the image are small (<2 pixels) while matching methods work well for moderate displacements but do not handle sub-pixel motions. Both types of optical flow algorithm can use either local or global constraints, such as spatial smoothness. Local matching and differential techniques and global differential techniques will be examined. Most algorithms for optical flow utilize weak assumptions on the local variation of the flow and on the variation of image brightness. Strengthening these assumptions improves the flow computation. The computational consequence of this is a need for larger spatial and temporal support. Global differential approaches can be extended to local (patchwise) differential methods and local differential methods using higher derivatives. Using larger support is valid when constraint on the local shape of the flow are satisfied. We show that a simple constraint on the local shape of the optical flow, that there is slow spatial variation in the image plane, is often satisfied. We show how local differential methods imply the constraints for related methods using higher derivatives. Experiments show the behavior of these optical flow methods on velocity fields which so not obey the assumptions. Implementation of these methods highlights the importance of numerical differentiation. Numerical approximation of derivatives require care, in two respects: first, it is important that the temporal and spatial derivatives be matched, because of the significant scale differences in space and time, and, second, the derivative estimates improve with larger support.

Feature Matching for Object Localization in the Presence of Uncertainty

We consider the problem of matching model and sensory data features in the presence of geometric uncertainty, for the purpose of object localization and identification. The problem is to construct sets of model feature and sensory data feature pairs that are geometrically consistent given that there is uncertainty in the geometry of the sensory data features. If there is no geometric uncertainty, polynomial-time algorithms are possible for feature matching, yet these approaches can fail when there is uncertainty in the geometry of data features. Existing matching and recognition techniques which account for the geometric uncertainty in features either cannot guarantee finding a correct solution, or can construct geometrically consistent sets of feature pairs yet have worst case exponential complexity in terms of the number of features. The major new contribution of this work is to demonstrate a polynomial-time algorithm for constructing sets of geometrically consistent feature pairs given uncertainty in the geometry of the data features. We show that under a certain model of geometric uncertainty the feature matching problem in the presence of uncertainty is of polynomial complexity. This has important theoretical implications by demonstrating an upper bound on the complexity of the matching problem, an by offering insight into the nature of the matching problem itself. These insights prove useful in the solution to the matching problem in higher dimensional cases as well, such as matching three-dimensional models to either two or three-dimensional sensory data. The approach is based on an analysis of the space of feasible transformation parameters. This paper outlines the mathematical basis for the method, and describes the implementation of an algorithm for the procedure. Experiments demonstrating the method are reported.

Affine Matching with Bounded Sensor Error: A Study of Geometric Hashing and Alignment

Affine transformations are often used in recognition systems, to approximate the effects of perspective projection. The underlying mathematics is for exact feature data, with no positional uncertainty. In practice, heuristics are added to handle uncertainty. We provide a precise analysis of affine point matching, obtaining an expression for the range of affine-invariant values consistent with bounded uncertainty. This analysis reveals that the range of affine-invariant values depends on the actual $x$-$y$-positions of the features, i.e. with uncertainty, affine representations are not invariant with respect to the Cartesian coordinate system. We analyze the effect of this on geometric hashing and alignment recognition methods.

The Matching of Doubly Ambiguous Stereograms

I have previously described psychophysical experiments that involved the perception of many transparent layers, corresponding to multiple matching, in doubly ambiguous random dot stereograms. Additional experiments are described in the first part of this paper. In one experiment, subjects were required to report the density of dots on each transparent layer. In another experiment, the minimal density of dots on each layer, which is required for the subjects to perceive it as a distinct transparent layer, was measured. The difficulties encountered by stereo matching algorithms, when applied to doubly ambiguous stereograms, are described in the second part of this paper. Algorithms that can be modified to perform consistently with human perception, and the constraints imposed on their parameters by human perception, are discussed.

Template Matching: Matched Spatial Filters and Beyond

Template matching by means of cross-correlation is common practice in pattern recognition. However, its sensitivity to deformations of the pattern and the broad and unsharp peaks it produces are significant drawbacks. This paper reviews some results on how these shortcomings can be removed. Several techniques (Matched Spatial Filters, Synthetic Discriminant Functions, Principal Components Projections and Reconstruction Residuals) are reviewed and compared on a common task: locating eyes in a database of faces. New variants are also proposed and compared: least squares Discriminant Functions and the combined use of projections on eigenfunctions and the corresponding reconstruction residuals. Finally, approximation networks are introduced in an attempt to improve filter design by the introduction of nonlinearity.

Fast Contour Matching Using Approximate Earth Mover's Distance

Weighted graph matching is a good way to align a pair of shapes represented by a set of descriptive local features; the set of correspondences produced by the minimum cost of matching features from one shape to the features of the other often reveals how similar the two shapes are. However, due to the complexity of computing the exact minimum cost matching, previous algorithms could only run efficiently when using a limited number of features per shape, and could not scale to perform retrievals from large databases. We present a contour matching algorithm that quickly computes the minimum weight matching between sets of descriptive local features using a recently introduced low-distortion embedding of the Earth Mover's Distance (EMD) into a normed space. Given a novel embedded contour, the nearest neighbors in a database of embedded contours are retrieved in sublinear time via approximate nearest neighbors search. We demonstrate our shape matching method on databases of 10,000 images of human figures and 60,000 images of handwritten digits.