智能家庭网络的实现

介绍了智能家庭网络的概念、要求和结构，指出当前家庭网络存在的问题，提出了相应于OSI模型的家庭网络的分层结构和智能家庭网络的控制平台，剖析了家庭网关结构，并对智能家庭网络的软件结构作了进一步的分析。     

超级计算机体系结构及应用情况

本文概述了当今超级计算机体系结构类型及特点，考察了国外超级计算机在气象、核模拟、CFD、生物信息学和医学、天体物理学等典型应用领域的应用情况，分析了超级计算机体系结构与应用领域之间的关系。     

基于J2EE的医药电子商务系统的设计与实现

本文首先简述了J2EE分布式计算平台,然后介绍了我们基于J2EE自主设计开发的振湘医 药电子商务系统的总体结构和主要设计思想,最后以购物车为例讨论了该系统的设计与实现。     

对象关系数据库管理系统体系结构的研究

In last years, with the Object-Oriented Programming popular and the field of database application extend-ed,many DBMS manufacturers integrate the object model into traditional Relational Database Management Systems (RDBMSs)one after another ,in order to meet the needs for complex engineering applications. This paper firstly givesa total remark on the reason for the prevalence of the Object-Relational Database Systems (ORDBMs)and on the ben-efit of ORDBMSs comparing with RDBMSs and Object Oriented Database Management Systems(OODBMSs) ,then in-troduces an approach for ORDBMS architecture which integrates the Java class library into ORDBMS metadata repos-itory.     

浅析可信计算技术及其发展

首先介绍了可信计算技术的发展背景,然后对可信计算技术的体系结构进行了研究,最后列举了一些可信计算技术在实际中一些的应用。     

基于HLA的水中兵器仿真系统框架

为了解决我国水中兵器传统的仿真系统,局限于某些参数的数学仿真和部分半实物仿真,没有实现系统化、可视化,实时化,文章提出一种采用高层体系结构（HLA）作为分布交互的仿真体系框架,通过对水中兵器对抗系统仿真建模,解决了不同仿真应用之间的集成问题,较好地满足仿真系统的可视化、可操作性、强实时性及强交互性等要求。该仿真系统可以为水中兵器作战研究和武器装备论证提供仿真试验环境,检验装备各项战略战术指标,并为装备研制和战略战术决策提供依据,具有很高的实用价值。     

高校学生注册收费管理系统研究——以南海广播电视大学为例

学生注册收费管理工作是学校财务管理工作的中枢。随着学校规模的不断扩大,各种类型的学生逐渐增多,传统的账务管理方式和工作手段已经难以满足要求。财务收费任务繁重,出现缴费统计困难或者信息流转通畅程度差、在各部门信息先后不一致、信息时效性滞后等问题。针对这些问题,开发了基于B/S结构的学生注册收费管理系统。     

基于虚拟机的软件保护研究与设计

虚拟机技术一直是当今计算机安全领域研究的热点之一。从软件保护的角度出发,介绍了基于虚拟机的软件保护设计方案中的关键技术,并给出了一个范例,说明具体步骤和方法。该方法将保护对象细化为函数,给出了单函数识别的具体步骤和方法,利用基本的x86编码来构造虚拟机,对基本指令集采用基于字节码的加解密技术,此外还对各类指令进行了必要的模块化扩展以增加保护力度。目前国内对于虚拟机的保护技术处于起步阶段,因而对于虚拟机技术的理论基础研究和技术实践应用均具有较高的研究价值和发展空间。     

Language of Thought: The Connectionist Contribution

Fodor and Pylyshyn's critique of connectionism has posed a challenge to connectionists: Adequately explain such nomological regularities as systematicity and productivity without postulating a "language of thought" (LOT). Some connectionists like Smolensky took the challenge very seriously, and attempted to meet it by developing models that were supposed to be non-classical. At the core of these attempts lies the claim that connectionist models can provide a representational system with a combinatorial syntax and processes sensitive to syntactic structure. They are not implementation models because, it is claimed, the way they obtain syntax and structure sensitivity is not "concatenative," hence "radically different" from the way classicists handle them. In this paper, I offer an analysis of what it is to physically satisfy/realize a formal system. In this context, I examine the minimal truth-conditions of LOT Hypothesis. From my analysis it will follow that concatenative realization of formal systems is irrelevant to LOTH since the very notion of LOT is indifferent to such an implementation level issue as concatenation. I will conclude that to the extent to which they can explain the law-like cognitive regularities, a certain class of connectionist models proposed as radical alternatives to the classical LOT paradigm will in fact turn out to be LOT models, even though new and potentially very exciting ones.     

Phylogenetic and Ontogenetic Learning in a Colony of Interacting Robots

The objective of this paper is to describe the development of a specific theory of interactions and learning among multiple robots performing certain tasks. One of the primary objectives of the research was to study the feasibility of a robot colony in achieving global objectives, when each individual robot is provided only with local goals and local information. In order to achieve this objective the paper introduces a novel cognitive architecture for the individual behavior of robots in a colony. Experimental investigation of the properties of the colony demonstrates its ability to achieve global goals, such as the gathering of objects, and to improve its performance as a result of learning, without explicit instructions for cooperation. Since this architecture is based on representation of the likes and dislikes of the robots, it is called the Tropism System Cognitive Architecture. This paper addresses learning in the framework of the cognitive architecture, specifically, phylogenetic and ontogenetic learning by the robots. The results show that learning is indeed possible with the Tropism Architecture, that the ability of a simulated robot colony to perform a gathering task improves with practice and that it can further improve with evolution over successive generations. Experimental results also show that the variability of the results decreases over successive generations.