微通信元系统构架和QoS

微通信元系统构架是一种易于从TCP／IP过渡的服务元网络体系结构的构架。作为微通信元的服务元被组织成微通信系统，大量的微通信系统被组织成网络系统。微通信元系统构架具有简洁、可扩展和容易实现的特点。文中重点讨论了微通信元系统构架对QoS的支持，并且将它和层次结构对QoS的支持进行了比较。     

微通信元系统构架对QoS的支持*

微通信元系统架构是新型网络体系结构——服务元网络体系结构的第一个网络架构。针对现有TCP/IP网络体系结构对QoS的支持不足,提出基于微通信元系统构架的QoS服务模型,阐述了服务模型工作机制。     

微通信元架构的面向对象设计

在分析现存网络体系架构的技术弱点后,简述了微通信元架构的思想,进而提出以面向对象技术为基础的设计实现方法。     

微通讯元架构基于UML的面向对象设计

对微通讯元架构提出了基于统一建模语言UML的面向对象设计建模。该方法能满足微通讯元架构的各种要求,适合于系统的迭代开发,具有可视化的特点,直观、清晰,易于理解和实现。进而以无连接服务为例,通过抽象、分析、设计,建立了一个实验模型。     

基于MCES网络原型的测试和分析

基于服务元网络体系结构（SUNA）的微通信元系统（MCES）体现了一种新型的网络设计思想。针对研发的MCES网络原型进行有效测试以进一步验证SUNA的可行性和有效性是一个值得研究的问题。介绍了这种网络原型的测试方法和过程,并对测试结果进行分析。测试结果表明,服务元网络体系结构和微通信元系统架构是可行的。     

基于元胞自动机的地下水突出与漫延仿真方法

提出了基于元胞自动机模型的地下矿水灾发生时水灾在巷道网络系统中蔓延的可视化仿真方法。在该方法中，用元胞自动机模型描述地下矿巷道网络系统，用元胞来描述突水漫延能量单元，该单元用突水漫延速度和含水量等状态参数来描述。在仿真过程中，可以获得大量关于水灾蔓延、灾害动态、灾害严重程度的量化指标及其可行的调控方法。该方法将时间、空间和系统行为有机地结合起来，在形象、直观、真实的条件下完成水灾在巷道系统中蔓延的仿真。     

面向对象的有限空间内人群流动CA模型研究

为了模拟在有限空间中大量人员的流动分布，基于面向对象技术，在已有交通流模型和行人流模型的基础上，建立了一个在有限空间内高密度人群流动的元胞自动机模型。采用面向对象思想的建模方法，使得模型具有很好的适用性、扩展性和复用性。并根据出现高密度人群的一般情况和控制对象的需求，提出“元胞控制块”的概念，使整个模型架构具有很强的应用转化能力。计算机模拟验证的结果良好，充分显示了元胞自动机模型对复杂人群流动的模拟能力。     

串口通信新模型的研究与C#实现

借鉴I/O完成端口模型(IOCP)的核心思想,建立了一个适用于协议性串口通信的新模型。该模型提出了一个协议性串口通信的最小单位———"通信元",将"通信元"提交到事件队列线程中自动处理,简化了处理过程并提高了运行效率。同时,基于该模型用C#设计出了一个协议性串口通信模块,以封装通信底层的细节,从而提供方便的通信接口。将该模块应用于工业造气炉监控组态软件设计中,实际运行表明:该模型具有简单的接口和稳定、高效的运行机制。     

基于MCES的网络编程接口研究

本文对目前网络编程接口的局限性进行了分析，发现其已经难以适应网络应用的需求和网络技术的最新发展.微通信元系统构架（MCES）是一种易于从TCP/IP过渡的服务元网络体系结构的构架，为了应用微通信元系统构架提供的高级网络服务，根据当前网络编程接口方面的研究情况，提出了新的网络API：GSocket.GSocket采用合理的设计，完全兼容传统的网络编程方法和接口函数，能自动适应不同的网络系统，支持QoS等多种高级网络服务功能，还具有良好的可扩展性。     

基于目标定位的低功耗无线传感器网络节点设计

介绍了一种具有目标定位功能的新型无线传感器网络节点,通过该节点可以确定目标节点(以下简称为目标)的方位和距离,对目标方位的确定基于四元十字阵列的时延估计法,对目标距离的确定采用TDOA的射频+音频信号的测距机理;硬件电路以Micro-chip公司的dsPIC微处理器芯片和Altera公司的MAXⅡ系列CPLD为核心,包括4路音频信号采集调理单元、一个外部SRAM存储器、一个2.4G频段的无线收发单元和一个电源管理单元,实验数据表明,该节点测距误差小于2.5%,角度误差小于±3°。     

MCES: A Novel Monte Carlo Evaluative Selection Approach for Objective Feature Selections

Most recent research efforts on feature selection have focused mainly on classification task due to its popularity in the data-mining community. However, feature selection research in nonlinear system estimations has been very limited. Hence, it is reasonable to devise a feature selection approach that is computationally efficient on nonlinear system estimations context. A novel feature selection approach, the Monte Carlo evaluative selection (MCES), is proposed in this paper. MCES is an objective sampling method that derives a better estimation of the relevancy measure. The algorithm is objectively designed to be applicable to both classification and nonlinear regressive tasks. The MCES method has been demonstrated to perform well with four sets of experiments, consisting of two classification and two regressive tasks. The results demonstrate that the MCES method has following strong advantages: 1) ability to identify correlated and irrelevant features based on weight ranking, 2) application to both nonlinear system estimation and classification tasks, and 3) independence of the underlying induction algorithms used to derive the performance measures     

基于时延的微通信元主机原型性能测试

介绍服务元网络体系结构（SUNA）和基于非层次网络体系结构的微通信元系统架构（MCES）。针对MCES主机原型进行有效测试,以进一步验证SUNA的可行性和有效性。讨论基于时延的MCES主机原型性能测试方法和过程。测试结果表明SUNA和MCES是可行的。     

微通信元系统架构下的拥塞控制机制研究*

在简述现存网络架构的技术弱点后,提出了微通信元系统架构的思想,微通信元体系结构对不同服务类型的数据构建不同的虚电路进行传输.针对这种数据通信策略,提出了一种基于反馈信息位的拥塞控制机制,该机制根据来自路由节点的反馈信息调整一个虚电路发送端的发送速率,以实现拥塞控制.NS仿真表明,此机制能有效提高网络的吞吐量,改善网络的性能.     

基于服务的网络体系结构的设计和实现

对网络体系结构的研究现状进行了介绍.基于MCES(micro-communicationel ement structure)架构设计了一种基于服务的网络体系结构原型.在原型系统中,实现了服务元的合理组合和调度,并从体系结构上更好地支持QoS和网络安全.同时,通过改进的套接字机制实现了向后兼容现有TCP/IP网络应用程序,满足了用户不断增长的网络服务要求.基于Linux的实验结果显示,该体系结构组成的系统是合理的、可行的,并具有很好的传输效率和可扩展性.     

The Shared Control Parallel Architecture Model

SIMD machines are considered special purpose architectures chiefly because of their inability to support control parallelism. This restriction exists because there is a single control unit that is shared at the thread level; concurrent control threads must time-share the control unit (they are sequentially executed). We present an alternative model for building centralized control architectures that allows better support for control parallelism. This model, called shared control, shares the control unit(s) at the instruction level. More precisely, in each cycle the control signals for all the supported instructions are broadcast to the PEs. In turn, each PE receives its control by synchronizing with the control unit responsible for its local instruction. The shared control model is fundamentally different from the SIMD model. There are a number of architectural issues that must be resolved in order for this model to be useful. This paper identifies some of these issues and discusses their respective trade-off spaces. An integrated shared-control/SIMD architecture design (SharC) is presented and used to demonstrate the relative performance relative to a SIMD architecture.     

A coarse-grained parallel approach for seismic damage simulations of urban areas based on refined models and GPU/CPU cooperative computing

Refined models and nonlinear time-history analysis have been important developments in the field of urban regional seismic damage simulation. However, the application of refined models has been limited because of their high computational cost if they are implemented on traditional central processing unit (CPU) platforms. In recent years, graphics processing unit (GPU) technology has been developed and applied rapidly because of its powerful parallel computing capability and low cost. Hence, a coarse-grained parallel approach for seismic damage simulations of urban areas based on refined models and GPU/CPU cooperative computing is proposed. The buildings are modeled using a multi-story concentrated-mass shear (MCS) model, and their seismic responses are simulated using nonlinear time-history analysis. The benchmark cases demonstrate the performance-to-price ratio of the proposed approach can be 39 times as great as that of a traditional CPU approach. Finally, a seismic damage simulation of a medium-sized urban area is implemented to demonstrate the capacity and advantages of the proposed method.     

GENETIC ALGORITHM MODEL FOR PROFIT MAXIMIZATION OF GENERATING COMPANIES IN DEREGULATED ELECTRICITY MARKETS

In deregulated and rapidly changing electricity markets, there is strong interest on how to solve the new price-based unit commitment (PBUC) problem used by each generating company to optimize its generation schedule in order to maximize its profit. This article proposes a genetic algorithm (GA) solution to the PBUC problem. The advantages of the proposed GA are: 1) flexibility in modeling problem constraints because the PBUC problem is not decomposed either by time or by unit; 2) smooth and easier convergence to the optimum solution thanks to the proposed variable fitness function which not only penalizes solutions that violate the constraints but also this penalization is smoothly increasing as the number of generations increases; 3) easy implementation to work on parallel computers, and 4) production of multiple unit commitment schedules, some of which may be well suited to situations that may arise quickly due to unexpected contingencies. The method has been applied to systems of up to 120 units and the results show that the proposed GA constantly outperforms the Lagrangian relaxation PBUC method for systems with more than 60 units. Moreover, the difference between the worst and the best GA solution is very small, ranging from 0.10% to 0.49%.     

Resolving Ambiguous Segmentation of Korean Compound Nouns Using Statistics and Rules

Korean compound nouns may be written as a sequence of characters without blanks between unit nouns. For Korean processing systems, Korean compound nouns have to be first segmented into a sequence of unit nouns. However, the segmentation task is difficult because a sequence of characters may be ambiguously segmented to several sequences of appropriate unit nouns. Moreover, this task is not trivial because Korean compound nouns may include many unknown unit nouns.
This paper proposes a new method for KCNS (Korean Compound Noun Segmentation) and reports on the appliccation of such a segmentationtechnique to enhance the performance of an information retrieval system. According to our method, compound nouns are first segmented by using a dictionary and structure patterns. If they are ambiguously segmented, we resolve the ambiguities by using statistical information and a preference rule. Moreover, we employ three kinds of heuristics in order to segment compound nouns with unknown unit nouns.
To evaluate KCNS, we use three kinds of data from various domains. Experimental results show that the precision of KCNS's output is approximately 96% on average, regardless of domains. The effectiveness of using the segmented unit nouns provided by KCNS for indexing is proved by improving retrieval performance of our information retrieval system.