基于Java2和COM的应用程序综合

讨论了基于Java（或J2EE）的应用程序和基于Microsoft Win32（COM）的应用程序组件整合起来的一些技术和实现策略。并介绍了一种在分布式环境下Java2调用COM组件的实现方法。     

Sun发布Java 2平台的新授权模式

Sun公司宣布将改变Java2平台的授权模式。这个新的授权模式是基于Sun在最近发布的Sun社团源代码授权文件中所规定的一系列基本原则,该文件的规定今访问源代码更简便。Java2平台新授权模式的优势在于：它对开发。利用Java技术的任何参与者都是公平开放的。它鼓励参与者间的合作,这将有助于加快创新速度,促使基于源代码技术的产品间的迅速交流。Java技术的新授权模式将继续免费向非商业（研究与教育旧的的应用提供源代码,向软件编程人员和开发人员提供二进制的JavaRuntimeEnvironment（Java运行环境）,使他们能将Java技术融入他们的…     

基于SSH框架的医疗信息系统浅析

为了便于进行医疗信息的管理,提高医疗信息资源的使用率,提出了基于Java Web技术的医疗信息管理系统的方案。从系统的实际应用出发,详细介绍了Struts2、Spring、Hibernate这三个基于Java EE架构的Web框架（简称SSH）,构建一个易于维护和扩展的系统;并且详细讨论了系统中各个层,包括MCV、Controller控制器所使用的关键技术。为以后这类框架系统提供高效、便捷、稳定的开发打下基础。     

基于手机定位技术的WAP网站的设计与实现

运用WAP、WML Java Servlet等技术建立了基于手机定位技术的WAP网站，为手机用户提供了个人定位服务及地理信息查询(银行、医院、购物中心等的位置查询)。     

Sun推出新版门户服务器

Sun宣布推出基于具有突破性能的新版Sun Java System Portal Server（第七版），其可使Java企业系统和Java系统套件获得强化，为开发人员和客户提供一种非常安全的方法。让他们通过Web应用程序提供协作性的、基于身份识别的内容。     

基于多源信息融合的RBF神经网络室内可见光定位算法

针对基于接收信号强度（RSS）的定位技术易受环境干扰而导致定位精度不高和稳定性较差的问题,提出了一种基于多源信息融合的径向基函数（RBF）神经网络室内可见光定位算法。通过将图像的颜色矩特征与RSS矩特征融合,构建指纹库,并采用RBF神经网络进行预测,实现了图像与RSS之间的优势互补,最后对定位算法进行了验证。实验结果表明,经过优化的多源信息融合定位算法较单一RSS定位算法的定位精度提高了9.4%。     

基于JMF的局域网视频电话(会议)系统开发

局域网（LAN）视频电话（会议）系统有广阔的应用前景,而基于Java实现的应用系统,具有跨平台等诸多优点.本文介绍了实际开发局域网视频电话（会议）系统的基本构成和主要功能,重点描述了服务器客户管理、系统通信控制和客户多媒体处理方案.该系统采用Java多媒体框架（JMF）类库和纯Java编程,界面友好、功能强大.     

王者之风 NOKIA 9500

诺基亚9500通讯器兼容现有IT基础设备，可通过无线功能，用于设备管理的个人电脑工具和定制能力进行远程管理。该机基于Symbian 7.0操作系统和Series 80平台，支持Java MIDP 2.0 和个人情景模式。这是一款三频GSM手机，同时兼顾数据传输高速灵活的GPRS、EGPRS（EDGE）和Wireless LAN (Wi-Fi IEEE 802.11b）网络，支持IPv4和IPv6双重协议，而蓝牙无线技术，红外和USB 2.0连接（NOKIA Commectivity Cable DKU-2）更是不在话下。诺基亚为9500通讯器搭建了无所不能的连接兼容系统，方便用户随时随地以任何方式进行沟通和数据传输。     

用RMI开发基于Java的分布式应用

由于Java具有跨平台、代码可移植性、安全高效等广泛而强大的功能，因而在开发网络分布式应用的时候，可以用它自身的机制实现分布式计算，一种基于Java的远程方法调用（RMI）为我们开发分布式应用提供了行之有效的解决方案。     

WAP中用Java实现分布式处理

当前,分布式处理和计算使用的范围越来越广泛。这是因为一方面使用分布式系统能够获得种种好处（例如共享稀有资源和平衡负载等）,另一方面,随着移动通信的迅速发展,移动通信设备的使用越来越广,我们期待能够将这两种技术结合起来。目前,有两种常用的方法构造分布式方案,一种是远程过程调用（RPC）,另外一种是CORBA技术。Java语言能够运行在各种不同的平台上,具有语言上的优势。在Java语言中,远程方法调用（RMI）提供了远程通信的能力,即指运行在一个Java虚拟机上的对象能够调用运行在另外一个虚拟机上对象的方法。Java I…     

RSS技术在网上学习平台设计中的应用

网上学习平台，顾名思义，就是通过互联网建立的虚拟学习空间，让学习者在教室以外的环境根据自身的情况选择学习的时间、内容、方式等，增加学习过程的弹性。当前，网上学习平台已得到广泛应用。但传统的网上学习平台存在许多不足，如信息冗余、时效性不强等。对RSS技术特点进行了详细分析，提出了一个如何利用RSS技术改进现有网上学习平台的新的思路。     

一种新的无线异构网络的自适应垂直切换算法

针对当前无线异构网络融合技术中的垂直切换机制,提出了一种以平均接收信号强度为评价指标,并由此指标判断可能的运动趋势的自适应垂直切换算法。仿真结果表明:相比于传统的固定门限的平均接收信号强度垂直切换算法,提出的方法能较好地预测并提前触发该发生的切换,改善切换性能。     

An Adaptive AP Selection Scheme Based on RSS for Enhancing Positioning Accuracy

In recent years, the indoor positioning technologies have been recognized as core technologies for realizing smart space, a ubiquitous society, context awareness, and various location-based services. There are several approaches for positioning with radio signals, but the received signal strength (RSS)-based technology is considered a promising scheme because of its simplicity and practicality in implementation. In this paper, the positioning performance of the RSS value-based scheme is analyzed with respect to the location of access points (APs) and the number of APs in an indoor environment. An adaptive AP selection scheme and a base AP changing scheme are then proposed to enhance the positioning accuracy. In order to estimate the RSS characteristics, RSS values are measured as the distance between the AP and the receiver increases. The positioning performance is evaluated with differing AP numbers, which form a triangle or a quadrilateral. The performance of the proposed schemes is evaluated via experiments using wireless local area network APs. Results show that the performance of proposed schemes is enhanced compared to that of conventional scheme.     

位置指纹定位技术

在室内利用无线网络对移动目标定位,可用的技术有基于波达时间(TOA/TDOA)、基于波达角度(AOA)、以及基于接收信号强度(RSS)的技术等。比较而言,基于接收信号强度(RSS)的位置指纹(LF)技术更适合于复杂的室内环境。对该技术目前的研究情况进行比较全面和详细的介绍。     

Earth Science Datacasting: Informed Pull and Information Integration

The intent of Datacasting is to empower consumers of Earth science data with the ability to extract from a stream of data granules (or files) precisely those granules that are required to meet a predefined need, for example, ldquoAcquire from a MODIS L2 data stream only the granules that contain information about a wild fire in Southern California.rdquo Our approach to solving this problem has been to take the concept of Really Simple Syndication (RSS) feeds, for delivering regularly changing web content, and extend this to represent a stream of data granules and deliver regularly changing Earth science data content. In essence, this project is doing for Earth science what Podcasting has done for audio and video. Where Podcasting extended RSS to revolutionize how users access audio and video content provided by various media outlets, so Datacasting extends RSS to provide users with the ability to download data granules provided by Earth science data providers as the data are made available. Moreover, we have taken the concept one step further by creating a solution for filtering on the metadata of a feed in order to identify granules of interest based on user-defined criteria. In this paper, we also show how Datacasting feeds can be combined with other RSS-based feeds to identify relationships between information sources and extract new knowledge, as well as aid the development of new geo-based web services not currently envisaged.     

Web 2.0 is here and ready for use [your internet connection]

Web 2.0 is still a technology in progress, nonetheless it is a collection of numerous useful and popular technologies, including blogs, wikis, tags, mashups, RSS feeds, etc.     

基于RSS典型性判定的室内定位算法研究

在基于RSS指纹集的定位算法中,相似样本集的质量,是影响定位精度的一个关键性因素;而待定位点的RSS向量,则是影响相似样本点质量的一个重要元素。通过对D-RSS分布规律分析,提出了RSS典型性的概念,并且提出了基于RSS典型性判定的室内定位算法。该算法根据RSS的典型性特征与有效的相似样本点之间的关系,提出了RSS典型性的辨别方法以及与典型性相关的动态K值。通过实验证明,该算法不仅能完整地找出有效的相似样本点,排除非实质性相似点的干扰,而且在不同的定位场景中具有较强的适应性,同时具有较高的定位精度。     

Improved RSS Data Generation Method Based on Kriging Interpolation Algorithm

The traditional method of constructing RSS fingerprint database costs a large amount of time and human resource due to adopting the point-by-point method to sample RSS value, and consequently the positioning method based on RSS fingerprint model is difficult to be widely applied. In this paper, a RSS data generation method is proposed based on Kriging spatial interpolation algorithm. The proposed method firstly selects the model of variogram according to the properties of field, and subsequently solves the variogram by using the observation points with the restriction of unbiased estimation and minimum estimation variance, finally calculates RSS data for the estimation points. The experimental results show that the proposed method accurately acquires the RSS data of estimation points while the required reference points are much less than that of conventional point-by-point method.

     

基于接收信号强度非齐性分布特征的半监督学习室内定位指纹库构建

室内定位中半监督学习的指纹库构建方法能够降低人力开销,但忽略了高维接收信号强度(RSS)数据不均匀的非齐分布特点,影响定位精度,针对此问题该文提出一种基于RSS非齐性分布特征的半监督流形对齐指纹库构建方法。该算法运用局部RSS尺度参数以及共享近邻相似性构造权重矩阵,得到精确反映RSS数据流形结构的权重图,利用该权重图通过求解流形对齐的目标函数最优解,实现运用少量标记数据对大量未标记数据的位置标定。实验结果表明,该算法可以显著降低离线阶段数据采集的工作量,同时可以取得较高的定位精度。     

Target Positioning Algorithm Based on RSS Fingerprints of SVM of Fuzzy Kernel Clustering

The positioning technology based on receive signal strength (RSS) fingerprints has become one of the hottest research spots with its advantages of simple deployment, low cost, and single parameter. However, in the limited space, the multipath and shadowing, result in poor separability of the fingerprint data, and low accuracy of target localization. In this paper, a novel RSS fingerprints positioning algorithm that is based on fuzzy kernel clustering SVM is proposed to combat the multipath and shadowing effects. The first step of the proposed positioning algorithm is to use kernel function to map the traditional fingerprints sample data to high-dimensional feature space to generate fuzzy classes. The second step is to generate binary-class SVM of fuzzy class based on the relationship between classes and internal discrete information of each class. After that, we can use the binary fuzzy class SVM to dichotomize the classified fingerprints in the first step, and combine these dichotomous SVMs into a handstand classification binary tree. And thus, the proposed positioning algorithm achieves quick and accurate positioning. Experimental results show that the positioning accuracy and locating stability of proposed positioning algorithm are improved by 38.73% and 59.26%, respectively, compared with the traditional RSS fingerprints algorithm.