FacetAtlas: multifaceted visualization for rich text corpora

Documents in rich text corpora usually contain multiple facets of information. For example, an article about a specific disease often consists of different facets such as symptom, treatment, cause, diagnosis, prognosis, and prevention. Thus, documents may have different relations based on different facets. Powerful search tools have been developed to help users locate lists of individual documents that are most related to specific keywords. However, there is a lack of effective analysis tools that reveal the multifaceted relations of documents within or cross the document clusters. In this paper, we present FacetAtlas, a multifaceted visualization technique for visually analyzing rich text corpora. FacetAtlas combines search technology with advanced visual analytical tools to convey both global and local patterns simultaneously. We describe several unique aspects of FacetAtlas, including (1) node cliques and multifaceted edges, (2) an optimized density map, and (3) automated opacity pattern enhancement for highlighting visual patterns, (4) interactive context switch between facets. In addition, we demonstrate the power of FacetAtlas through a case study that targets patient education in the health care domain. Our evaluation shows the benefits of this work, especially in support of complex multifaceted data analysis.     

现代空间环境中屏风设计理念的拓展和延伸

本文着重论述了在现代空间环境中如何拓展和延伸屏风的设计理念,使其在丰富多元的现代社会中具有更广阔的发展空间,并符合现代人的需求。     

高速网络Fast TCP拥塞控制算法的改进

随着网络技术的飞速发展和接入性能的不断提高,如今全世界的互联主干网络呈现出一种高速网络的特性。在这种网络特性下,传统网络中的TCP拥塞控制协议已经开始显现出不适应性,发现了FAST TCP协议中＂持续拥塞＂的形成机制,建立了数学模型来准确的描述＂持续拥塞＂所导致数据流之间带宽分配不公平的问题,进一步利用优先服务队列的方法解决了FAST TCP在网络中的持续拥塞现象。     

A rough set approach to feature selection based on power set tree

Feature selection is viewed as an important preprocessing step for pattern recognition, machine learning and data mining. Traditional hill-climbing search approaches to feature selection have difficulties to find optimal reducts. And the current stochastic search strategies, such as GA, ACO and PSO, provide a more robust solution but at the expense of increased computational effort. It is necessary to investigate fast and effective search algorithms. Rough set theory provides a mathematical tool to discover data dependencies and reduce the number of features contained in a dataset by purely structural methods. In this paper, we define a structure called power set tree (PS-tree), which is an order tree representing the power set, and each possible reduct is mapped to a node of the tree. Then, we present a rough set approach to feature selection based on PS-tree. Two kinds of pruning rules for PS-tree are given. And two novel feature selection algorithms based on PS-tree are also given. Experiment results demonstrate that our algorithms are effective and efficient.     

医院虚拟化服务器部署

随着医院信息化的发展,需要有一种更有效率的方式来调配管理服务器资源。虚拟化能使服务器的资源被更有效地利用起来。通过虚拟化的技术,能将不适宜放在同一台服务器中的应用整合于一台物理服务器中。通过虚拟化软件的调配,能将一台服务器的资源利用率最大化。虚拟化服务器还能解决由于硬件、环境不足造成的资源紧张,提高医院信息系统管理的效率。     

A comment on “Using locally estimated geodesic distance to optimize neighborhood graph for isometric data embedding”

A geodesic distance-based approach to build the neighborhood graph for isometric embedding is proposed to deal with the highly twisted and folded manifold by Wen et al. [Using locally estimated geodesic distance to optimize neighborhood graph for isometric data embedding, Pattern Recognition 41 (2008) 2226-2236]. This comment is to identify the error in their example and the ineffectiveness of their algorithm.     

Sentinel-1-based flood mapping: a fully automated processing chain

This article presents an automated Sentinel-1-based processing chain designed for flood detection and monitoring in near-real-time (NRT). Since no user intervention is required at any stage of the flood mapping procedure, the processing chain allows deriving time-critical disaster information in less than 45 min after a new data set is available on the Sentinel Data Hub of the European Space Agency (ESA). Due to the systematic acquisition strategy and high repetition rate of Sentinel-1, the processing chain can be set up as a web-based service that regularly informs users about the current flood conditions in a given area of interest. The thematic accuracy of the thematic processor has been assessed for two test sites of a flood situation at the border between Greece and Turkey with encouraging overall accuracies between 94.0% and 96.1% and Cohen’s kappa coefficients (κ) ranging from 0.879 to 0.910. The accuracy assessment, which was performed separately for the standard polarizations (VV/VH) of the interferometric wide swath (IW) mode of Sentinel-1, further indicates that under calm wind conditions, slightly higher thematic accuracies can be achieved by using VV instead of VH polarization data.