无线传感器网络检测系统研究与实现

无线传感器网络能够获取客观信息,具有十分广泛的应用前景,被认为是21世纪最重要的技术之一.本文设计了一套无线传感器网络温度监测系统,在网络硬件节点设计和网络组织这两个方面进行了重点讨论,最后对该网络系统进行了温度数据采集和通信距离两个方面进行了测试.该网络系统成本低,工作稳定,可以用于一些小型任务.     

基于词平台的中文文档实验系统的构建

文章提出一种新的中文文档实验系统,力求建立一个克服束缚中文信息处理发展的自动分词问题的实验研究平台.文章采用一种新的基于中文词的文本编码方法,对每个词进行编码,并使新编码与机内码联系起来.使用这种基于词的编码格式可以使词成为计算机中文处理中的最小信息栽体,无须再进行中文分词.文章使用该方法进行了关键词自动抽取的实验研究.结果显示,基于词编码的中文文档实验系统能很好的解决中文分词问题,并给其它中文文本分析奠定良好基础.     

Theoretical research progress in new-generation Internet architecture

Internet has become the most important information infrastructure supporting modern socio-economic development, social progress and technological Innovation. Invented 30 years ago, today Internet is facing increasingly severe technical challenges. This paper introduces the progress of the major international newgeneration Internet research plans; analyzes its basic characteristics and the principal contradictions during the development; detsiledly introduces the research carried out by 973 Project ＂Research of Future Internet Architecture＂ on the key scientific issues of new-generation Internet architecture and its latest research results; and looks to the future of the research-focus faced with the new situations of the basic research of new-generation Internet architecture as well as the new demands of innovative applications on Internet architecture.     

轻量级J2EE架构的研究

随着开源运动的不断发展,从数据持久层到业务层再到表现层都涌现了一批优秀的轻量级开源框架。针对轻量级J2EE架构的整体设计和各个层的具体设计展开研究,综述了各个层中出现的主要框架和设计方案,分别对它们进行了比较分析。     

TD-SCDMA无线网络控制系统——传输信道转换的软件设计与实现

分析了TD-SCDMA无线接入系统的主要特征。介绍了TD-SCDMA系统中资源优化的意义以及无线传输信道转换的方法,设计实现了一套根据不同的Qos的进行无线资源与网络带宽动态配置的软件系统。重点介绍了无线传输信道转换的系统结构和主要关键技术。     

基于ASP．Net技术实现网站新闻系统

本文以网站新闻系统的功能设计为例,详细介绍了ASP．NET技术的先进性,代码更易于编写,结构更清晰,程序的可靠性和稳定性有了很大的改善和提高。降低了系统的开发与维护的复杂度。     

触摸传感器QST108与PIC单片机的接口设计

QST108为意法半导体公司生产的电容触摸传感器,具有功能强大且易操作等特点,非常适合应用在能够对用户触摸做出响应的智能控制界面中。本文重点介绍了QST108的工作方式及主要操作命令,给出了QST108与PIC单片机的接口设计以及部分程序代码。     

A forward-constrained regression algorithm for sparse kernel density estimation.

Using the classical Parzen window (PW) estimate as the target function, the sparse kernel density estimator is constructed in a forward-constrained regression (FCR) manner. The proposed algorithm selects significant kernels one at a time, while the leave-one-out (LOO) test score is minimized subject to a simple positivity constraint in each forward stage. The model parameter estimation in each forward stage is simply the solution of jackknife parameter estimator for a single parameter, subject to the same positivity constraint check. For each selected kernels, the associated kernel width is updated via the Gauss-Newton method with the model parameter estimate fixed. The proposed approach is simple to implement and the associated computational cost is very low. Numerical examples are employed to demonstrate the efficacy of the proposed approach.     

An efficient non-dominated sorting method for evolutionary algorithms

We present a new non-dominated sorting algorithm to generate the non-dominated fronts in multi-objective optimization with evolutionary algorithms, particularly the NSGA-II. The non-dominated sorting algorithm used by NSGA-II has a time complexity of O(MN(2)) in generating non-dominated fronts in one generation (iteration) for a population size N and M objective functions. Since generating non-dominated fronts takes the majority of total computational time (excluding the cost of fitness evaluations) of NSGA-II, making this algorithm faster will significantly improve the overall efficiency of NSGA-II and other genetic algorithms using non-dominated sorting. The new non-dominated sorting algorithm proposed in this study reduces the number of redundant comparisons existing in the algorithm of NSGA-II by recording the dominance information among solutions from their first comparisons. By utilizing a new data structure called the dominance tree and the divide-and-conquer mechanism, the new algorithm is faster than NSGA-II for different numbers of objective functions. Although the number of solution comparisons by the proposed algorithm is close to that of NSGA-II when the number of objectives becomes large, the total computational time shows that the proposed algorithm still has better efficiency because of the adoption of the dominance tree structure and the divide-and-conquer mechanism.     

Effective visualization of complex vascular structures using a non-parametric vessel detection method

The effective visualization of vascular structures is critical for diagnosis, surgical planning as well as treatment evaluation. In recent work, we have developed an algorithm for vessel detection that examines the intensity profile around each voxel in an angiographic image and determines the likelihood that any given voxel belongs to a vessel; we term this the "vesselness coefficient" of the voxel. Our results show that our algorithm works particularly well for visualizing branch points in vessels. Compared to standard Hessian based techniques, which are fine-tuned to identify long cylindrical structures, our technique identifies branches and connections with other vessels. Using our computed vesselness coefficient, we explore a set of techniques for visualizing vasculature. Visualizing vessels is particularly challenging because not only is their position in space important for clinicians but it is also important to be able to resolve their spatial relationship. We applied visualization techniques that provide shape cues as well as depth cues to allow the viewer to differentiate between vessels that are closer from those that are farther. We use our computed vesselness coefficient to effectively visualize vasculature in both clinical neurovascular x-ray computed tomography based angiography images, as well as images from three different animal studies. We conducted a formal user evaluation of our visualization techniques with the help of radiologists, surgeons, and other expert users. Results indicate that experts preferred distance color blending and tone shading for conveying depth over standard visualization techniques.