提高虚拟空间会议系统服务质量QoS的若干技术

虚拟空间会议系统是视频会汉系统发展的最高形式．本文结合作者研究工作，通过分析与视频会议系统服务质量相关的技术，提出了基于VST系统的相关技术策略，这些策略能够有效地提高VST系统的服务质量．     

实型和虚型结构因子的代数公式

应用晶体正空间和倒易空间等效点的矩阵表示讨论结构因子类型，在得到倒易空间点的一般型结构因子类型和系统消光型结构因子类型的代数公式之后，得到并证明了倒易空间点的实型和虚型结构因子的代数公式．即满足提出的实型结构因子类型或虚型结构因子类型的代数公式的任意一倒易空间点h，其结构因子Fh分别为实型和虚型．     

飞行时间质谱峰形分析

从离子运动方程出发，用峰形分析方法离子的质谱峰进行数据再处理，首次从飞行时间质谱峰峰形中获得离子产生时的空间分布信息。这种峰形分析方法可以广泛应用于分析飞行时间质谱的各种离子源中离子的分布。     

Application of design parameters space search for belt conveyor design

Belt conveyor design is examined as an application of a proposed Design Parameters Space Search technique. First, the main characteristics of the belt-conveyor design process are presented as they appear in the current literature. Furthermore, a proposed general knowledge-representation platform is described, and its ability to house the relevant conveyor design knowledge is also shown.

Next, the extended search technique of the design space is discussed, and an integrated example of a belt-conveyor design is presented, based on the proposed representation platform and the extended search technique. Finally, it is shown that the design of belt conveyors according to the proposed approach presents the following significant advantages:

• • Due to the knowledge-representation scheme adopted, both qualitative and quantitative knowledge can be used within the same platform.

• • Multiple solutions can be easily produced through user-defined design criteria. These solutions can be further modified and/or evaluated to produce more-specific designs.

• • The required for user-input data is kept to a minimum. Due to the applied extended search method, semiautomatic design can be achieved. As a consequence, the design process is completed in less time than that required by the conventional methods.

     

创造绿地型国际性花园城市——深圳特区绿地系统规划设计探讨

从深圳生态环境与现有城市绿地系统特点、深圳建设绿地型国际性花园城市的优势和绿地系统规划设计思路等三个方面扼要介绍了深圳特区的绿地系统规划设计方案．     

LF半准开集的一种新定义

给出了一种新的ＬＦ半准开集定义，采用新的ＬＦ半准开集定义，较详细地研究了ＬＦ半准开集及半准连续函数的一些重要性质。     

The Challenges of Cross-Modal Translation: English-to-Sign-Language Translation in the Zardoz System

The sign languages used by deaf communities around the world represent a linguistic challenge that natural-language researchers in AI have only recently begun to take up. This challenge is particularly relevant to research in Machine Translation (MT), as natural sign languages have evolved in deaf communities into efficient modes of gestural communication, which differ from English not only in modality but in grammatical structure, exploiting a higher dimensionality of spatial expression. In this paper we describe Zardoz, an on-going AI research system that tackles the cross-modal MT problem, translating English text into fluid sign language. The paper presents an architectural overview of Zardoz, describing its central blackboard organization, the nature of its interlingual representation, and the major components which interact through this blackboard both to analyze the verbal input and generate the corresponding gestural output in one of a number of sign variants.     

模糊核聚类的自适应算法

针对模糊聚类算法在样本特征不明显时不能取得很好的聚类效果，以及现有的模糊聚类算法需要事先确定聚类数，随机性强、容易陷入局部最优等弱点，将核函数和有效性函数引入到模糊聚类中，提出了模糊核聚类的自适应算法,此方法在性能上比经典的聚类算法有了较大的改进,取得了更好的聚类效果,实验结果证实了该方法的有效性和可行性.     

Evaluation of Linguistic Features for Word Sense Disambiguation with Self-Organized Document Maps

Word sense disambiguation automatically determines the appropriate senses of a word in context. We have previously shown that self-organized document maps have properties similar to a large-scale semantic structure that is useful for word sense disambiguation. This work evaluates the impact of different linguistic features on self-organized document maps for word sense disambiguation. The features evaluated are various qualitative features, e.g. part-of-speech and syntactic labels, and quantitative features, e.g. cut-off levels for word frequency. It is shown that linguistic features help make contextual information explicit. If the training corpus is large even contextually weak features, such as base forms, will act in concert to produce sense distinctions in a statistically significant way. However, the most important features are syntactic dependency relations and base forms annotated with part of speech or syntactic labels. We achieve 62.9% ± 0.73% correct results on the fine grained lexical task of the English SENSEVAL-2 data. On the 96.7% of the test cases which need no back-off to the most frequent sense we achieve 65.7% correct results.     

Optimal Ordered Problem Solver

We introduce a general and in a certain sense time-optimal way of solving one problem after another, efficiently searching the space of programs that compute solution candidates, including those programs that organize and manage and adapt and reuse earlier acquired knowledge. The Optimal Ordered Problem Solver (OOPS) draws inspiration from Levin's Universal Search designed for single problems and universal Turing machines. It spends part of the total search time for a new problem on testing programs that exploit previous solution-computing programs in computable ways. If the new problem can be solved faster by copy-editing/invoking previous code than by solving the new problem from scratch, then OOPS will find this out. If not, then at least the previous solutions will not cause much harm. We introduce an efficient, recursive, backtracking-based way of implementing OOPS on realistic computers with limited storage. Experiments illustrate how OOPS can greatly profit from metalearning or metasearching, that is, searching for faster search procedures.