一种中文文档的非受限无词典抽词方法

本文提出了一种非受限无词典抽词模型,该模型通过自增长算法获取中文文档中的汉字结合模式,并引入支持度、置信度等概念来筛选词条。实验表明:在无需词典支持和利用语料库学习的前提下,该算法能够快速、准确地抽取中文文档中的中、高频词条。适于对词条频度敏感,而又对计算速度要求很高的中文信息处理应用,例如实时文档自动分类系统。     

基于矢量模型的语音线性预测研究

研究语音参数线性预测的并行处理问题。通过把语音源序列的相邻样本分组能够构成一个均方差平稳的语音向量自回归序列,在Hilbert空间中运用正交投影原理导出具有高度并行处理能力的一预测编码策略,由此可推出参数线性预测的并行处理自适应算法。同传统格型算法相比,这种算法的计算复杂度及存贮量有明显改善。最后通过仿真运算检测了算法的性能。     

一个基于CORBA和Java技术的分布式并行有限元计算环境

该文结合ＣＯＲＢＡ（Ｃｏｍｍｏｎ Ｏｂｊｅｃｔ Ｂｒｏｋｅｒ Ａｒｃｈｉｔｅｃｔｕｒｅ）和Ｊａｖａ技术,提出了一个能在支持ＴＣＰ／ＩＰ协议的异构网络环境下实现分布式有限元计算环境的具体方案,为了验证方案的可行性,在西南交通大学应用力学与工程系计算中心的局域网上实现了分布式并行计算环境的基本框架,并进行了１０００阶矩阵相乘的计算。     

安全事件关联模型的研究与实现

基于攻击前提和后果关联的技术有多种,在此基础上,研究并实现了一种面向分布式的多源实时报警收集及关联分析的框架。初步实验证明,该框架在复杂的网络环境下能够有效地减少和分析报警事件,帮助管理员从大量数据中找到重要信息。     

基于机器视觉的实时丸药检测系统

丸药是最为常见的药品剂型,最后成品的外观都要求圆整均匀、色泽一致,在丸药检测方面使用机器视觉技术有着良好的应用前景。通过对丸药实时检测方法和途径的分析探讨,提出了完整的工作循环模式。根据此模式,给出了利用Matlab和visual studio开发实时检测系统的完整方案。     

电信计费分析数据仓库系统的设计与实现

该文主要研究如何用数据仓库及其技术解决电信计费分析的实际问题。     

Towards a Mobile Code Management Environment for Complex,Real-Time,Distributed Systems

We present a novel mobile code management environment,currently under design and development. Our design employs anopen architecture, suitable for ``plug-and-play' with COTS andother groups' tools. While we have studied new algorithms, costand objective functions, and other fundamental issues, the maincontribution of this experimental research work is in the environmentitself. It should be noted that networked platforms, such asthe World Wide Web, are inherently not suitable for traditional,predictable real-time applications. Thus, real-time concernsnecessarily need to be blended with others concerns, and thetarget applications, making use of our environment, will toobe a blend of partially hard real-time and partially (or mostly)soft-real- time ones. The prototype environment will thereforesupport performance-based analysis and management focusing notonly on predictability but also on compilation, efficiency, safetyand other tradeoffs. We have selected the Java language and itsbytecode format as a representation for mobile code as well asa language for our implementation.     

Parallel Implementation of a Class of Adaptive Signal Processing Applications

Recently, High Performance Computing (HPC) platforms have been employed to realize many computationally demanding applications in signal and image processing. These applications require real-time performance constraints to be met. These constraints include latency as well as throughput. In order to meet these performance requirements, efficient parallel algorithms are needed. These algorithms must be engineered to exploit the computational characteristics of such applications. In this paper we present a methodology for mapping a class of adaptive signal processing applications onto HPC platforms such that the throughput performance is optimized. We first define a new task model using the salient computational characteristics of a class of adaptive signal processing applications. Based on this task model, we propose a new execution model. In the earlier linear pipelined execution model, the task mapping choices were restricted. The new model permits flexible task mapping choices, leading to improved throughput performance compared with the previous model. Using the new model, a three-step task mapping methodology is developed. It consists of (1) a data remapping step, (2) a coarse resource allocation step, and (3) a fine performance tuning step. The methodology is demonstrated by designing parallel algorithms for modern radar and sonar signal processing applications. These are implemented on IBM SP2 and Cray T3E, state-of-the-art HPC platforms, to show the effectiveness of our approach. Experimental results show significant performance improvement over those obtained by previous approaches. Our code is written using C and the Message Passing Interface (MPI). Thus, it is portable across various HPC platforms. Received April 8, 1998; revised February 2, 1999.     

BPL: A set-based language for distributed system prototyping

Rapid prototyping of software and hardware is recognized as a very important step in timely, cost-effective system development. The complexity inherent in designing distributed computing systems and distributed problem solutions emphasizes the need for effective rapid prototyping tools. ADL/ADS is a testbed user interface tool for experimentation with critical research and design issues pertaining to distributed data processing (DDP). The experimenter expresses a candidate distributed system in terms of experiment objects, along with attributes and relationships. The experiment objects represent hardware, software, and behavior. This paper provides a brief overview of ADL/ADS, and gives especial emphasis to the Behavior Prototyping Language (BPL) within ADL/ADS. BPL is designed for expressing Behavior Modules (B_MODULEs)—the most versatile of the behavior objects. BPL incorporates set-theoretical approaches, and provides syntax designed for effectively describing manipulations of experiment objects, and their attributes and relationships.