IP网络传输技术的研究与发展

分析了IP网络传输技术的现状和以太网技术的发展 ,研究了几种新的以太网传输技术 ,提出了以太网技术将覆盖从LAN、MAN乃至WAN ,成为全面构建下一代网络主流技术的新观点。     

高加速应力筛选(HASS)概述

高加速应力筛选（HASS）是一种新兴的试验技术，用于产品的生产阶段。在暴露和剔除产品的制造和工艺缺陷，提高可靠性，降低野外失败和返修率等方面非常有效。从研究开发HASS的背景出发，介绍了HASS的目的及作用，重点探讨了高加速的基本原理，典型的HASS过程。     

无线公话及POS系统的设计与实现

提出了一种基于公共通信网络的无线公话及POS系统的设计与实现方案,解决了当前烟草物流配送信息化系统的销售终端环节在信息采集、传送、数据处理等方面技术手段落后以及各烟草销售终端成了物流配送信息化系统中的"信息孤岛"等问题。采用将无线POS机与无线公话(采用无线本地回路WLL技术)计费系统有机结合一体的技术思路,大大地节约了产品硬件开销及使用成本,提高了无线网络的利用率。     

基于藏语字性标注的词性预测研究

该文选取了藏语文中小学教材的部分语料,构建了带有藏语字性标记、词边界标记和词性标记的语料库,通过比较不同的分词、标注方法,证明分词、词性标注一体化效果比分步进行的效果好,准确率、召回率和F值分别提高了0.067、0.073和0.07。但词级标注模型难以解决词边界划分的一致性和未登录词的问题。基于此,作者提出可以利用字性和字构词的规律预测合成词的词性,既可以融入语言学知识又可以减少由未登录词导致的标注错误,实验结果证明,作为词性标注的后处理模块,基于字性标注的词性预测准确率提高到了0.916,这个结果已经比分词标注一体化结果好,说明字性标注对纠正词性错误标注有明显的效果。
     

Towards the appropriate human-centred information systems: A case study of the Japanese retail industry

The industries of Japan have developed by learning from Western industries, especially the USA, and by implementing many of their concepts and technologies. However, Japanese industries have often implemented these concepts and technologies in a very different way from the USA. For example, while the USA uses information systems in retail industries as a tool by which data are collected and analysed to control the market, in Japan this same technology is considered rather as a learning device to interpret the market. While in the USA the market is seen as a natural phenomenon capable of being controlled, the Japanese see it as an ambiguous phenomenon that is ever changing and is not capable of being controlled. Rather it is important to feel the change in the market itself.This paper introduces human centredness to the information system, and argues against modern rationalism, i.e. human versus technology, taking the case of use of POS data from the POS system (point of sale: a system that collects data on both the customer and goods sold by scanning bar codes that are attached to the surface of the goods) by the eminent Japanese retailer, Ito-Yokado. It emphasises an interactive concept of interaction between human and technology of the postmodern paradigm.     

统计模型中附加语言学规则的蒙古语词法分析

蒙古词法分析是蒙古语信息处理的基础性问题,是蒙古语信息处理工作的第一步。通过对统计模型和蒙古语构词规则进行深入研究,提出了一种融合统计和规则技术的蒙古语词切分和词性标注的方法。该方法以统计模型作为基本框架,采用树形结构描述系统的解空间,并加入了蒙古语语言学规则和词干、词缀词典。实验结果表明,该系统分词和词性标注的词级准确率为95.1%,词干/词缀级准确率为94.6%,较已有蒙古语词法分析系统的准确率有所提高。     

基于深度神经网络的中文命名实体识别

由于中文词语缺乏明确的边界和大小写特征,单字在不同词语下的意思也不尽相同,较于英文,中文命名实体识别显得更加困难。该文利用词向量的特点,提出了一种用于深度学习框架的字词联合方法,将字特征和词特征统一地结合起来,它弥补了词特征分词错误蔓延和字典稀疏的不足,也改善了字特征因固定窗口大小导致的上下文缺失。在词特征中加入词性信息后,进一步提高了系统的性能。在1998年《人民日报》语料上的实验结果表明,该方法达到了良好的效果,在地名、人名、机构名识别任务上分别提高1.6%、8%、3%,加入词性特征的字词联合方法的F1值可以达到96.8%、94.6%、88.6%。     

一个基于POS的燃气用户收费及管理系统的开发

本文介绍了一个基于POS的燃气用户收费及管理系统的设计和实现,给出了系统的总体结构,并对其主要组成的原理和功能作了阐述。     

POS机软件升级的方法与设计

该文介绍了POS（Point of Sales,销售点终端）系统中软件升级的方法,从中选出一种方法作为软件升级的案例,从硬件的设计开始,一直到软件的设计,详细说明了如何进行软件升级。     

Improving Korean verb-verb morphological disambiguation using lexical knowledge from unambiguous unlabeled data and selective web counts

This paper deals with verb-verb morphological disambiguation of two different verbs that have the same inflected form. The verb-verb morphological ambiguity (VVMA) is one of the critical Korean parts of speech (POS) tagging issues. The recognition of verb base forms related to ambiguous words highly depends on the lexical information in their surrounding contexts and the domains they occur in. However, current probabilistic morpheme-based POS tagging systems cannot handle VVMA adequately since most of them have a limitation to reflect a broad context of word level, and they are trained on too small amount of labeled training data to represent sufficient lexical information required for VVMA disambiguation.In this study, we suggest a classifier based on a large pool of raw text that contains sufficient lexical information to handle the VVMA. The underlying idea is that we automatically generate the annotated training set applicable to the ambiguity problem such as VVMA resolution via unlabeled unambiguous instances which belong to the same class. This enables to label ambiguous instances with the knowledge that can be induced from unambiguous instances. Since the unambiguous instances have only one label, the automatic generation of their annotated corpus are possible with unlabeled data.In our problem, since all conjugations of irregular verbs do not lead to the spelling changes that cause the VVMA, a training data for the VVMA disambiguation are generated via the instances of unambiguous conjugations related to each possible verb base form of ambiguous words. This approach does not require an additional annotation process for an initial training data set or a selection process for good seeds to iteratively augment a labeling set which are important issues in bootstrapping methods using unlabeled data. Thus, this can be strength against previous related works using unlabeled data. Furthermore, a plenty of confident seeds that are unambiguous and can show enough coverage for learning process are assured as well.We also suggest a strategy to extend the context information incrementally with web counts only to selected test examples that are difficult to predict using the current classifier or that are highly different from the pre-trained data set.As a result, automatic data generation and knowledge acquisition from unlabeled text for the VVMA resolution improved the overall tagging accuracy (token-level) by 0.04%. In practice, 9-10% out of verb-related tagging errors are fixed by the VVMA resolution whose accuracy was about 98% by using the Naïve Bayes classifier coupled with selective web counts.