基于DDS和WPF技术的试飞实时监控系统设计

针对以服务为中心的客户端服务器(C/S)架构监控模式存在着数据融合困难、传输协议单一、扩展灵活性差等不足,将数据分发服务(DDS)技术引入到试飞实时监控系统中,结合WPF图形引擎技术形成了一整套解决方案。在完全兼容当前架构规范的前提下,采用DDS技术作为数据传输中间件,有效提高了试飞监控系统的实时性,加强了多源数据融合粒度,降低了试验资源的集成难度;采用WPF图形引擎技术构建实时监控可视化编辑平台,最终实现了空天地综合监控环境下多源数据接收、处理、分发以及可视化展示等关键技术。此方案已经在飞行试验地面实时监控中得到了成功应用。     

VDM-RS: A visual data mining system for exploring and classifying remotely sensed images

Remotely sensed imagery has become increasingly important in several applications domains, such as environmental monitoring, change detection, fire risk mapping and land use, to name only a few. Several advanced image classification techniques have been developed to analyze such imagery and in particular to improve the accuracy of classifying images in the context of such applications. However, most of the proposed classifiers remain a black box to users, leaving them with little to no means to explore and thus further improve the classification process, in particular for misclassified pixel samples. In this paper, we present the concepts, design and implementation of VDM-RS, a visual data mining system for classifying remotely sensed images and exploring image classification processes. The system provides users with two classes of components. First, visual components are offered that are specific to classifying remotely sensed images and provide traditional interfaces, such as a map view and an error matrix view. Second, the decision tree classifier view provides users with the functionality to trace and explore the classification process of individual pixel samples. This feature allows users to inspect how a sample has been correctly classified using the classifier, but more importantly, it also allows for a detailed exploration of the steps in which a sample has been misclassified. The integration of these features into a coherent, user-friendly system not only helps users in getting more insights into the data, but also to better understand and subsequently improve a classifier for remotely sensed images. We demonstrate the functionality of the system's components and their interaction for classifying imagery using a hyperspectral image dataset.     

基于平行坐标法的可视数据挖掘

数据挖掘和数据可视化技术的结合形成可视数据挖掘。通过可视化技术的运用,数据挖掘可以增加其数据的针对性和结果的可信度。平行坐标法是数据可视化的代表方法之一,该文在平行坐标法的基础上,探讨了在其中实现可视化数据挖掘的基本方法,是进一步开发可视数据挖掘系统的初步研究。     

基于Web的黑河流域生态水文WSN自动观测数据可视化系统应用研究

正在执行的黑河流域生态-水文过程综合遥感观测联合试验中的WSN系统不断产出数量巨大、种类繁多的自动观测数据,为了有效管理和应用这些数据,设计并实现了一个在线的可视化Web系统。整体工作从观测数据管理与可视化角度出发,对系统进行了详细的设计,系统包括观测数据可视化、静态信息录入、设备监控、管理、示范应用五大功能模块,提供了地图、各种类型矢量图、拓扑图、列表、图片和视频等可视化手段。目前系统已正常运行超过10个月,管理观测数据记录超过4亿条,对WSN设备和数据的管理,以及相关研究人员的研究工作具有重要意义。     

遥感影像Web共享关键技术应用研究

研究海量遥感数据在Web 共享中所需要的网络支撑环境、数据自动入库、数据自动传输、影像高效查询等关键运行技术。在关键技术研究的基础上,详细分析与设计了针对海量遥感数据的可视化查询、浏览及下载功能,并基于 Web服务等相关计算机技术,实现了海量遥感数据共享原型系统,完成海量遥感数据的 Web 共享。
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PDB: A pictorial database oriented to data analysis

The paper describes a new pictorial database oriented to image analysis, implemented inside the MIDAS data analysis system. Pictorial databases need expressive data structures in order to represent a wide class of information from the numerical to the visual. The model of the database is relational; however, a full normalization is not achievable, owing to the complexity of the visual information. The paper reports the general design and notes on the software implementation. Preliminary experiments show the performance of the pictorial database.     

Design Factors for Summary Visualization in Visual Analytics

Data summarization allows analysts to explore datasets that may be too complex or too large to visualize in detail. Designers face a number of design and implementation choices when using summarization in visual analytics systems. While these choices influence the utility of the resulting system, there are no clear guidelines for the use of these summarization techniques. In this paper, we codify summarization use in existing systems to identify key factors in the design of summary visualizations. We use quantitative content analysis to systematically survey examples of visual analytics systems and enumerate the use of these design factors in data summarization. Through this analysis, we expose the relationship between design considerations, strategies for data summarization in visualization systems, and how different summarization methods influence the analyses supported by systems. We use these results to synthesize common patterns in real‐world use of summary visualizations and highlight open challenges and opportunities that these patterns offer for designing effective systems. This work provides a more principled understanding of design practices for summary visualization and offers insight into underutilized approaches.     

院内感染系统中的数据预处理

在医院中院内感染是一个不可忽视的问题。医院内每天产生大量的数据,迫切需要挖掘出这些数据中与院内感染有关的因素。而数据预处理技术的好坏直接影响到数据挖掘的结果。介绍了针对院内感染数据挖掘系统,在关联规则挖掘前的数据预处理技术。     

Visual Recommendations for Network Navigation

Understanding large, complex networks is important for many critical tasks, including decision making, process optimization, and threat detection. Existing network analysis tools often lack intuitive interfaces to support the exploration of large scale data. We present a visual recommendation system to help guide users during navigation of network data. Collaborative filtering, similarity metrics, and relative importance are used to generate recommendations of potentially significant nodes for users to explore. In addition, graph layout and node visibility are adjusted in real‐time to accommodate recommendation display and to reduce visual clutter. Case studies are presented to show how our design can improve network exploration.     

EasyXplorer: A Flexible Visual Exploration Approach for Multivariate Spatial Data

Exploring multivariate spatial data attracts much attention in the visualization community. The main challenge lies in that automatic analysis techniques is insufficient in discovering complicated patterns with the perspective of human beings, while visualization techniques are incapable of accurately identifying the features of interest. This paper addresses this contradiction by enhancing automatic analysis techniques with human intelligence in an iterative visual exploration process. The integrated system, called EasyXplorer, provides a suite of intuitive clustering, dimension reduction, visual encoding and filtering widgets within 2D and 3D views, allowing an inexperienced user to visually explore and reason undiscovered features with several simple interactions. Case studies show the quality and scalability of our approach in quite challenging examples.     

Networks of Names: Visual Exploration and Semi‐Automatic Tagging of Social Networks from Newspaper Articles

Understanding relationships between people and organizations by reading newspaper articles is difficult to manage for humans due to the large amount of data. To address this problem, we present and evaluate a new visual analytics system, which offers interactive exploration and tagging of social networks extracted from newspapers. For the visual exploration of the network, we extract “interesting” neighbourhoods of nodes, using a new degree of interest (DOI) measure based on edges instead of nodes. It improves the seminal definition of DOI, which we find to produce the same “globally interesting” neighbourhoods in our use case, regardless of the query. Our approach allows answering different user queries appropriately, avoiding uniform search results. We propose a user‐driven pattern‐based classifier for discovery and tagging of non‐taxonomic semantic relations. Our approach does not require any a‐priori user knowledge, such as expertise in syntax or pattern creation. An evaluation shows that our classifier is capable of identifying known lexico‐syntactic patterns as well as various domain‐specific patters. Our classifier yields good results already with a small amount of training, and continuously improves through user feedback. We conduct a user study to evaluate whether our visual interactive system has an impact on how users tag relationships, as compared to traditional text‐based interfaces. Study results suggest that users of the visual system tend to tag more concisely, avoiding too abstract or overly specific relationship labels.     

交互式数据清理系统的研究

当今数据清理方案需要反复进行数据质量分析以查找错误，为修复它们而进行的转换需要运行很长的时间。用户需要忍受长时间的等待，而且经常需要撰写复杂的转换脚本。我们所探讨的交互式数据清理系统，它能紧密地将转换和偏差检测集成在一起，只要发现偏差，用户就可以交互式地使用简单的图表操作、实例描述逐渐建立一个转换，无需书写复杂的程序或忍受很长的延时。     

GraphDice: A System for Exploring Multivariate Social Networks

Social networks collected by historians or sociologists typically have a large number of actors and edge attributes. Applying social network analysis (SNA) algorithms to these networks produces additional attributes such as degree, centrality, and clustering coefficients. Understanding the effects of this plethora of attributes is one of the main challenges of multivariate SNA. We present the design of GraphDice, a multivariate network visualization system for exploring the attribute space of edges and actors. GraphDice builds upon the ScatterDice system for its main multidimensional navigation paradigm, and extends it with novel mechanisms to support network exploration in general and SNA tasks in particular. Novel mechanisms include visualization of attributes of interval type and projection of numerical edge attributes to node attributes. We show how these extensions to the original ScatterDice system allow to support complex visual analysis tasks on networks with hundreds of actors and up to 30 attributes, while providing a simple and consistent interface for interacting with network data.     

基于MATLAB、MFC和Vega的飞机刹车视景仿真

采用Multigen Creator建立飞机三维实体模型,利用视景开发软件Vega进行场景管理,实现飞机、刹车过程的视景仿真技术。将MFC作为中间环节,通过接口函数完成MATLAB仿真与Vega之间的实时数据传输,了飞机实体模型刹车过程中的运动视觉效果,使刹车过程可视化,对研究飞机刹车过程的影响因素和刹车控制规律有着重要作用。     

HarVis: An integrated social media content analysis framework for YouTube platform

YouTube (owned by Google Inc.) is arguably among most popular social media platforms used by millions across the globe. It provides an ever-growing, unique and rich source of content which presents new opportunities and challenges for information discovery and analysis. It is pertinent to explore and understand a topic via YouTube content to discover interesting information about public opinions and sentiments. This paper presents an integrated framework to facilitate the acquisition, storage, management, processing, and visualization of relevant content with the objective to assist in such analysis. It not only collects a significant portion of content, relevant to a given topic, in short time but also offers tools for visual exploratory analysis such as; (i) temporal evolution, (ii) vocabulary network, (iii) authors relative popularity and influence (iv) categories and (v) user communities and influencers. The utility and effectiveness is demonstrated through content analysis of a famous YouTube entertainment topic, the “Gangnam Style”.     

Towards Perceptual Simplification of Models with Arbitrary Materials

Real‐time rendering of models with high polygon count is still an important issue in interactive computer graphics. A common way to improve rendering performance is to generate different levels of detail of a model. These are mostly computed using polygonal simplification techniques, which aim to reduce the number of polygons without significant loss of visual fidelity. Most existing algorithms use geometric error bounds, which are well‐suited for silhouette preservation. They ignore the fact that a much more aggressive simplification is possible in low‐contrast areas inside the model. The main contribution of this paper is an efficient simplification algorithm based on the human visual system. The key idea is to move the domain of error computation from image‐space to vertex‐space to avoid a costly per‐pixel comparison. This way the error estimation of a simplification operation can be accelerated significantly. To account for the human vision, we introduce a perceptually based metric depending on the contrast and spatial frequency of the model at a single vertex. Finally, we validate our approach with a user study.     

一个可视化的多XML文档映射系统的设计与实现

在分析了Biztalk等商业化XML文档映射系统优缺点的基础上,设计和实现了一个多XML文档映射系统TRANSer,提供可视化设计工具让用户通过拖拉等简单操作设计映射关系,同时提供各种各样的函数来配合实现复杂的映射。它允许多个源XML文档映射到目标XML文档,还可以在设计映射关系的同时创建和修改目标XML文档的格式。实践证明,该系统开发效率高,捕述能力强,并且具有良好的扩展性。     

电力营销决策支持系统的设计

本文对当前电力营销管理信息系统存在的问题进行探讨,通过对相关软件平台、技术难点的分析,提出了以大型数据库系统和商业智能系统为基础平台开发电力营销决策支持系统设计方案,讨论了系统的功能和实现.     

旋转、缩放、位移不变的小波域图像水印算法

介绍了一种基本上不受旋转、缩放、位移影响的小波域图像水印算法.该算法根据人类视觉系统的特性,将水印自适应地嵌入图像小波域的低频子带.为计算和校正旋转及缩放造成水印位置的移动,采用一种新的滤波方法.该滤波方法需要使用原始图像对数极坐标域中的一小方块信息来计算水印位置的平移.实验结果表明,该水印对旋转、缩放、平移和常规的图像处理具有较强的鲁棒性.     

实时飞行仿真显示系统设计

目前飞行器设计中的数据分析,依赖多台飞行器仪器共同完成,操作不灵活;设备的研制、生产、维修、扩展也很不方便。采用虚拟仪器技术设计实时飞行仿真显示系统,该系统采用分布交互式网络结构。讨论了OpenGL和C++Builder混合编程,采用数学仿真,仿真环境及设备。重点阐述了其中的一些关键性的技术,并将其运用于实时飞行仿真显示系统的数据计算中,提高了飞行数据研究的便利性和测试方法。应用结果表明该系统运行可靠,具有一定的适用性,提高了数据分析、测试的效率。