Evaluation of intratympanic dexamethasone for treatment of refractory sudden sensorineural hearing loss

Objective  

To observe and compare the efficacy of intratympanic application of dexamethasone (DXM) for the treatment of refractory sudden sensorineural hearing loss (SSNHL), the DXM was given in three different ways: by tympanic membrane injection, by drip through a ventilation tube, and by perfusion through a round window catheter.     

霍山北平林区灌丛自然林窗特征调查研究

本文采用野外取样调查方法,主要在山西霍山北平林区选择了具有代表性的灌丛如黄刺玫、榛子、虎榛子、连翘、辽东栎、荚迷等灌丛林窗为研究对象。从林窗的大小、形状、结构、环境特点、种类成分等方面调查暖温带灌丛自然林窗的一般特征。共取林窗40个。研究结果表明:本区灌丛破坏程度比较严重,而且破坏时间比较早。植被丰富。榛子、黄刺玫、连翘是优势种群。     

基于Windows CE的嵌入式数字地形测图系统开发

介绍了以PDA为载体,在W indows CE平台下用EVC开发的嵌入式数字地形测图系统,着重对该系统的主要结构、功能、特点等进行了论述。     

基于PowerBuilder设计实现通用动态报表系统

通过对报表的分析，提出了新的动态报表生成技术，即由用户定义整张报表的报表格式、标题和小结区域、数据区域三部分，然后动态生成报表，有效地降低了用户自定义生成报表的难度。     

用Session变量实现数据控件在浏览器中的使用

ASP中的ADO控件提供了一种数据库操作能力，但是由于HTTP协议本身的原因，数据操作能力不足。探讨了产生这种情况的原因，并给出一个在WEB下的数据浏览修改窗口的算法。     

基于流媒体的VOD远程教学系统的构建与实现

视频点播作为远程教育的主要部分，越来越受到大家的重视，通过对流式媒体传输的关键技术的介绍，并结合笔者实践给出了基于window media流媒体技术的VOD远程教学系统的构建和实现技术。     

整数对的2-Ary自适应窗口表示算法

在有些公钥密码体制的实现中，特别是大多数数字签名（除了RSA）的验证过程，不仅需要指数运算，还需要能直接计算指数对。本文研究分析了整数对的从左到右的2阶自适应窗口表示（2-AWR），使用该表示可以使得Shamir算法实时实现，并且在同类算法中具有明显的速度优势。     

非线性振荡电路的混沌分析

分析了具有混沌动力学特征的非线性三阶自治电路，给出了混沌电路中非线性电阻的构造方法，通过EWB软件对混沌电路进行了计算机仿真，实际硬件电路板测试得到混沌吸引子、倍周期分岔、周期性窗口等预期分析结果，此结果对深入研究混沌理论及混沌的同步和控制有积极借鉴作用。     

基于数据窗口技术的通用组合查询

对数据进行批量分析、汇总、打印在管理信息系统中是比较常见的应用,本文提出了一种基于Power Builder中数据窗口技术的通用多条件组合查询的方法,并给出了具体的设计思想、关键代码及相关界面,极大的方便了对数据的批量处理。     

Using the revised EM algorithm to remove noisy data for improving the one-against-the-rest method in binary text classification

Automatic text classification is the problem of automatically assigning predefined categories to free text documents, thus allowing for less manual labors required by traditional classification methods. When we apply binary classification to multi-class classification for text classification, we usually use the one-against-the-rest method. In this method, if a document belongs to a particular category, the document is regarded as a positive example of that category; otherwise, the document is regarded as a negative example. Finally, each category has a positive data set and a negative data set. But, this one-against-the-rest method has a problem. That is, the documents of a negative data set are not labeled manually, while those of a positive set are labeled by human. Therefore, the negative data set probably includes a lot of noisy data. In this paper, we propose that the sliding window technique and the revised EM (Expectation Maximization) algorithm are applied to binary text classification for solving this problem. As a result, we can improve binary text classification through extracting potentially noisy documents from the negative data set using the sliding window technique and removing actually noisy documents using the revised EM algorithm. The results of our experiments showed that our method achieved better performance than the original one-against-the-rest method in all the data sets and all the classifiers used in the experiments.