CSCW系统中协同机制及协同活动模型

分析了当前计算机支持协同工作 (ComputerSupportedCooperativeWork ,CSCW)系统普遍存在的问题 ,首先定义了协同的基本概念和类型 ,并引入协同代理的新概念 ,研究了CSCW这样的人机结合系统中协同成员间的语义通信机制和信息共享机制。在此基础上 ,分离出协同活动中的独立信息实体 ,建立了面向对象的协同活动模型。最后 ,用协同活动模型分析了一个典型的协同工作的实例。     

上海电子金融发展战略目标分析

面对网络经济与互联网的飞速发展,金融作为高度信息化的产业,对信息和信息科学有着密切的依赖关系。阐述了电子金融的基本概念;对上海国际金融中心建设的目标、途径和发展现状进行了分析,指出发展电子金融是上海国际金融中心发展的重要途径。最后在分析了上海电子金融发展相关因素的基础上,提出了上海电子金融发展的战略和战略目标。     

工程系统多目标多层次模糊决策模型及其应用

在进行工程系统某些的问题决策时 ,需考虑的因素 (目标 )往往很多 ,且各因素之间还存在不同的层次。为此 ,根据模糊数学的基本理论 ,首先提出层次判断矩阵的建立和层次单排序方法 ,在此基础上 ,利用合成层次总权重来构筑多目标多层次模糊决策模型。最后 ,结合具体实例展开应用研究 ,该结果可为实际的工程系统决策由定性到定量计算提供一种新的思路。     

相控阵雷达旁瓣对消工作模式研究

从解矩阵方程的角度出发 ,在理论上分析了雷达旁瓣对消系统对消旁瓣干扰的工作原理 ,并由此得出了雷达实现最佳旁瓣干扰对消所需满足的条件 ,同时给出了实际的雷达旁瓣对消系统可能的四种工作模式 ,并比较了其优缺点。给出的最佳旁瓣对消条件 ,在雷达旁瓣对消系统的整体设计和对消系统性能的分析中将具有实际的指导意义。     

晋西北地区农业可持续发展的对策研究

晋西北地区是山西农业最落后的地区,也是黄土高原农业生产最落后的地区之一,如何尽快改变这种状况,已经成为一个急待解决的重要问题。通过对导致晋西北农业生产落后的因素进行了深入分析,提出了使该地区农业生产在短期内走了持续增长轨道的对策。参2。     

四维搜索——交通OD流的一种解法

交通ＯＤ流的解法从二维搜索发展到三维探索。本文提出四维搜索的方法。二维搜索是解决所谓的“两端守恒”问题,三维搜索是求解网络特性参数问题,而四维则是将节点的直达流与迂回流分离,即求解节 生量和集中量问题。     

Robust fault detection and diagnosis for uncertain nonlinear systems

This paper considers robust fault detection and diagnosis for input uncertain nonlinear systems. It proposes a multi-objective fault detection criterion so that the fault residual is sensitive to the fault but insensitive to the uncertainty as much as possible. Then the paper solves the proposed criterion by maximizing the smallest singular value of the transformation from faults to fault detection residuals while minimizing the largest singular value of the transformation from input uncertainty to the fault detection residuals. This method is applied to an aircraft which has a fault in the left elevator or rudder. The simulation results show the proposed method can detect the control surface failures rapidly and efficiently.     

Online blind source separation based on joint diagonalization

A now algorithm is proposed for joint diagonalization. With a modified objective function, the now algorithm not only excludes trivial and unbalanced solutions successfully, but is also easily optimized. In addition, with the new objective function, the proposed algorithm can work well in online blind source separation (BSS) for the first time, although this family of algorithms is always thought to be valid only in batch-mode BSS by far. Simulations show that it is a very competitive joint diagonalization algorithm.     

Closed circle DNA algorithm of change positive-weighted Hamilton circuit problem

Chain length of closed circle DNA is equal. The same closed circle DNA's position corresponds to different recognition sequence, and the same recognition sequence corresponds to different foreign DNA segment, so closed circle DNA computing model is generalized. For change positive-weighted Hamilton circuit problem, closed circle DNA algorithm is put forward. First, three groups of DNA encoding are encoded for all arcs, and deck groups are designed for all vertices. All possible solutions axe composed. Then, the feasible solutions axe filtered out by using group detect experiment, and the optimization solutions are obtained by using group insert experiment and electrophoresis experiment. Finally, all optimization solutions are found by using detect experiment. Complexity of algorithm is concluded and validity of DNA algorithm is explained by an example. Three dominances of the closed circle DNA algorithm are analyzed, and characteristics and dominances of group delete experiment axe discussed.     

High efficient moving object extraction and classification in traffic video surveillance

Moving object extraction and classification are important problems in automated video surveillance systems. A background model based on region segmentation is proposed. An adaptive single Gaussian background model is used in the stable region with gradual changes, and a nonparametric model is used in the variable region with jumping changes. A generalized agglomerative scheme is used to merge the pixels in the variable region and fill in the small interspaces. A two-threshold sequential algorithmic scheme is used to group the background samples of the variable region into distinct Gaussian distributions to accelerate the kernel density computation speed of the nonparametric model. In the feature-based object classification phase, the surveillance scene is first partitioned according to the road boundaries of different traffic directions and then re-segmented according to their scene localities. The method improves the discriminability of the features in each partition. AdaBoost method is applied to evaluate the relative importance of the features in each partition respectively and distinguish whether an object is a vehicle, a single human, a human group, or a bike. Experimental results show that the proposed method achieves higher performance in comparison with the existing method.