基于JNLP协议的软件上下载服务器的设计与实现

本文分析指出了在Internet环境下软件发布所面临的问题，提出了一种在JNLP（Java Network Launch Protocol)协议的基础上基于网络的软件发布模式，设计并实现了一个基于JNLP协议使用Java语言的软件上传和下载并具备管理功能的服务器系统。     

一种B/S模式下基于角色的权限管理方案

针对开发“中小学管理信息系统”中安全管理的需要，提出了一种基于B／S开发模式下权限管理方案－匹配式权限认证模式，满足了大用户群体使用的系统权限管理的需求。     

自然图像中混叠的概率模型

我们为建立自然图像中混叠的概率模型提供了一个数学框架。假设：(1)图像是由三维物体的二维投影轮廓组成．(2)在简化条件下．我们推导出自然图像的一种解析概率密度函数。已经证明．这种解析表达式可以很好地比配观测到的密度函数(直方图)。我们首先推导图像像素的边缘概率密度函数，然后推广到多维边缘概率密度函数，最后提出了几种改进措施。     

An efficient self-organizing map designed by genetic algorithms for the traveling salesman problem

As a typical combinatorial optimization problem, the traveling salesman problem (TSP) has attracted extensive research interest. In this paper, we develop a self-organizing map (SOM) with a novel learning rule. It is called the integrated SOM (ISOM) since its learning rule integrates the three learning mechanisms in the SOM literature. Within a single learning step, the excited neuron is first dragged toward the input city, then pushed to the convex hull of the TSP, and finally drawn toward the middle point of its two neighboring neurons. A genetic algorithm is successfully specified to determine the elaborate coordination among the three learning mechanisms as well as the suitable parameter setting. The evolved ISOM (eISOM) is examined on three sets of TSP to demonstrate its power and efficiency. The computation complexity of the eISOM is quadratic, which is comparable to other SOM-like neural networks. Moreover, the eISOM can generate more accurate solutions than several typical approaches for TSP including the SOM developed by Budinich, the expanding SOM, the convex elastic net, and the FLEXMAP algorithm. Though its solution accuracy is not yet comparable to some sophisticated heuristics, the eISOM is one of the most accurate neural networks for the TSP.     

Smart shopper: an agent-based web-mining approach to Internet shopping

This paper presents an agent-based Web-mining approach to Internet shopping. We propose a fuzzy neural network to tackle the uncertainties in practical shopping activities, such as consumer preferences, product specification, product selection, price negotiation, purchase, delivery, after-sales service and evaluation. The fuzzy neural network provides an automatic and autonomous product classification and selection scheme to support fuzzy decision making by integrating fuzzy logic technology and the backpropagation feed forward neural network. In addition, a new visual data model is introduced to overcome the limitations of the current Web browsers that lack flexibility for customers to view products from different perspectives. Such a model also extends the conventional data warehouse schema to deal with intensive data volumes and complex transformations with a high degree of flexibility for multiperspective visualization and morphing capability in an interactive environment. Furthermore, an agent development tool named "Aglet" is used as a programming framework for system implementation. The integration of dynamic object visualization, interactive user interface and data mining decision support provides an effective technique to close the gap between the "real world" and the "cyber world" from a business perspective. The experimental results demonstrate the feasibility of the proposed approach for Web-based business transactions.     

Extracting Interpretable Fuzzy Rules from RBF Networks

Radial basis function networks and fuzzy rule systems are functionally equivalent under some mild conditions. Therefore, the learning algorithms developed in the field of artificial neural networks can be used to adapt the parameters of fuzzy systems. Unfortunately, after the neural network learning, the structure of the original fuzzy system is changed and interpretability, which is considered to be one of the most important features of fuzzy systems, is usually impaired. This Letter discusses the differences between RBF networks and interpretable fuzzy systems. Based on these discussions, a method for extracting interpretable fuzzy rules from RBF networks is suggested. Simulation examples are given to embody the idea of this paper.     

A flight control system for aerial robots: algorithms and experiments

This paper presents a hierarchical flight control system for unmanned aerial vehicles. The proposed system executes high-level mission objectives by progressively substantiating them into machine-level commands. The acquired information from various sensors is propagated back to the higher layers for reactive decision making. Each vehicle is connected via standardized wireless communication protocol for scalable multi-agent coordination. The proposed system has been successfully implemented on a number of small helicopters and validated in various applications. Results from waypoint navigation, a probabilistic pursuit-evasion game and vision-based target tracking demonstrate the potential of the proposed approach toward intelligent flying robots.     

On the Optimality of Randomized Deadlock Avoidance Policies

This paper revisits the problem of selecting an optimal deadlock resolution strategy, when the selection criterion is the maximization of the system throughput, and the system is Markovian in terms of its timing and routing characteristics. This problem was recently addressed in some of our previous work, that (i) provided an analytical formulation for it, (ii) introduced the notion of randomized deadlock avoidance as a generalization of the more traditional approaches of deadlock prevention/avoidance, and detection and recovery, and (iii) provided a methodology for selecting the optimal randomized deadlock avoidance policy for a given resource allocation system (RAS) configuration. An issue that remained open in the problem treatment of that past work, was whether the proposed policy randomization is essential, i.e., whether there exist any RAS configurations for which a randomized deadlock avoidance policy is superior to any other policy that does not employ randomization. The work presented in this paper establishes that for the basic problem formulation where the only concern is the (unconstrained) maximization of the system throughput—or the other typical performance objectives of minimizing the system work-in-process and mean sojourn time—randomization of the deadlock resolution strategy is not essential. However, it is also shown that, sometimes, it can offer an effective mechanism for accommodating additional operational constraints, like the requirement for production according to a specified product mix. Furthermore, the undertaken analysis provides an analytical characterization of the dependence of the aforementioned performance measures on the transition rates relating to the various events of the underlying state space, which can be useful for the broader problem of synthesizing efficient scheduling policies for the considered class of resource allocation systems.     

电脑维护的利器-"Norton Utilities for Windows"

介绍Norton的安装及主要选项的应用方法。     

一种用于数字图象传感器的彩色插值算法

由于物理结构的限制 ,单片 CCD和 CMOS彩色图象传感器在每个像素的位置上只能采集一个颜色分量 ,其余两个颜色分量只能通过插值的办法得到 .鉴于通常的线性插值方法容易使图象的边缘变得模糊 ,并可能出现较为明显的颜色失真 ,而一些新方法尽管可以得到较高质量的插值图象 ,然而运算的复杂性限制了它们的应用 .为此提出了一种在色差空间进行插值的算法 ,以代替普通颜色空间的插值 ,同时用基于有理函数的插值算子来代替普通的线性算子 ,并通过后处理来进一步提高插值图象的质量 .由于色差空间的插值考虑了不同颜色分量间的耦合性 ,并利用了有理函数插值算子固有的边缘自适应特性 ,因而得到了较好的效果 .该方法另外的一个优点是计算速度较快 .实验结果表明 ,该该算法是有效的 .