为应用程序制作启动封面的几种方法

介绍为应用程序制作启动封面的四种方法.     

多源信息融合关键问题、研究进展与新动向

近年来,国内外掀起了多源信息融合技术研究的新热潮。对信息融合技术的最新研究进展进行了综述;首先探讨了信息融合的概念与本质;然后从信息处理和融合系统设计的角度,全面阐述了信息融合所面临的问题与挑战,以及现有的主要融合模型与方法分类,同时分析了信息融合方法论研究的发展趋势和一些新领域;接着纵览了信息融合技术的广泛应用;特别讨论了几个新兴的应用领域。最后对信息融合研究路线作了总结和展望。     

Distributed and Collaborative Visualization

Visualization is a powerful tool for analyzing data and presenting results in science, engineering and medicine. This paper reviews ways in which it can be used in distributed and/or collaborative environments. Distributed visualization addresses a number of resource allocation problems, including the location of processing close to data for the minimization of data traffic. The advent of the Grid Computing paradigm and the link to Web Services provides fresh challenges and opportunities for distributed visualization—including the close coupling of simulations and visualizations in a steering environment. Recent developments in collaboration have seen the growth of specialized facilities (such as Access Grid) which have supplemented traditional desktop video conferencing using the Internet and multicast communications. Collaboration allows multiple users—possibly at remote sites—to take part in the visualization process at levels which range from the viewing of images to the shared control of the visualization methods. In this review, we present a model framework for distributed and collaborative visualization and assess a selection of visualization systems and frameworks for their use in a distributed or collaborative environment. We also discuss some examples of enabling technology and review recent work from research projects in this field.     

Continuous Levels‐of‐Detail and Visual Abstraction for Seamless Molecular Visualization

Molecular visualization is often challenged with rendering of large molecular structures in real time. We introduce a novel approach that enables us to show even large protein complexes. Our method is based on the level‐of‐detail concept, where we exploit three different abstractions combined in one visualization. Firstly, molecular surface abstraction exploits three different surfaces, solvent‐excluded surface (SES), Gaussian kernels and van der Waals spheres, combined as one surface by linear interpolation. Secondly, we introduce three shading abstraction levels and a method for creating seamless transitions between these representations. The SES representation with full shading and added contours stands in focus while on the other side a sphere representation of a cluster of atoms with constant shading and without contours provide the context. Thirdly, we propose a hierarchical abstraction based on a set of clusters formed on molecular atoms. All three abstraction models are driven by one importance function classifying the scene into the near‐, mid‐ and far‐field. Moreover, we introduce a methodology to render the entire molecule directly using the A‐buffer technique, which further improves the performance. The rendering performance is evaluated on series of molecules of varying atom counts.     

Visual Analysis of Trajectories in Multi‐Dimensional State Spaces

Multi‐dimensional data originate from many different sources and are relevant for many applications. One specific sub‐type of such data is continuous trajectory data in multi‐dimensional state spaces of complex systems. We adapt the concept of spatially continuous scatterplots and spatially continuous parallel coordinate plots to such trajectory data, leading to continuous‐time scatterplots and continuous‐time parallel coordinates. Together with a temporal heat map representation, we design coordinated views for visual analysis and interactive exploration. We demonstrate the usefulness of our visualization approach for three case studies that cover examples of complex dynamic systems: cyber‐physical systems consisting of heterogeneous sensors and actuators networks (the collection of time‐dependent sensor network data of an exemplary smart home environment), the dynamics of robot arm movement and motion characteristics of humanoids.     

A cognitive component analysis approach for developing game-based spatial learning tools

Spatial ability has been recognized as one of the most important factors affecting the mathematical performance of students. Previous studies on spatial learning have mainly focused on developing strategies to shorten the problem-solving time of learners for very specific learning tasks. Such an approach usually has limited effects on improving the mathematical performance of students. In this study, a cognitive analysis approach is proposed for developing spatial learning tools by taking game characteristics into consideration. Moreover, the validation of the cognitive components of the spatial sense test for constructing two different kinds of intervention is verified, and the effects of the interventions are compared. To evaluate the performance of the proposed approach, an experiment was conducted on the mathematics course of an elementary school. The experimental results show that the spatial learning tool promotes not only the learning achievement, but also the spatial sense of the students.     

分层分类教学法在“计算机应用基础”课程中的应用

本文分析了目前计算机应用基础教学中存在的若干问题,并结合地方性高校的实际情况,针对各个问题分别提出了可行的对策,最后说明了实施的情况和取得的教学效果。     

NASA EOS Terra ASTER: Volcanic topographic mapping and capability

Up-to-date, accurate topographic data are a crucial resource for volcanic research and risk mitigation efforts, in particular, for modeling volcanic flow processes at a detailed spatial resolution. In this paper, we examine the utility of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument currently operating on the NASA Terra satellite, which provides near infrared (VNIR) stereo imaging from which topography can be derived. We wrote software to generate digital elevation models (DEMs) from the ASTER level 1A product, which employs an automated stereo matching technique to calculate the parallax offsets between the images acquired by the nadir- and aft-looking sensors. Comparison of ASTER DEMs with DEMs derived from other sources (digitized 1:50 K topographic maps and aerial interferometric radar) at Ruapehu volcano reveal an RMS error of about 10 m for the ASTER DEM, in the absence of significant atmospheric water vapor. A qualitative assessment of surface features showed that the ASTER DEM is superior to the interpolated 1:50 K map product but falls short of the detail provided by aerial interferometric radar, especially in terms of stream channel preservation. A second ASTER DEM was generated for Taranaki volcano, where previously only 1:50 K topographic map data were available. Although the 2000 Space Shuttle radar topography mission (SRTM) will largely remedy the previous global paucity of adequate topographic data at volcanoes, such as Taranaki, we anticipate the problem that at active volcanoes, the topography may change significantly following activity, rendering the SRTM data inaccurate. With the high temporal coverage of the dataset, ASTER not only provides a means to update significant (>10 m) topographic measurements at active volcanoes via a time-series of DEMs, but also provides a simultaneous means to map surface cover and localized land-use via the near infrared sensors. Thus we demonstrate the potential for up-to-date volcanic economic risk assessment using geographic information systems (GIS) analysis.     

基于改进单类支持向量机的工业控制网络入侵检测方法

针对单类支持向量机（OCSVM）入侵检测方法无法检测内部异常点和离群点导致决策函数偏离训练样本的问题,提出了一种结合具有噪声的密度聚类（DBSCAN）方法和K-means方法的OCSVM异常入侵检测算法。首先通过DBSCAN算法,剔除训练数据中的离群点,消除离群点的影响;然后利用K-means划分数据类簇的方法筛选出内部异常点;最后利用OCSVM算法为每一个类簇建立单分类器用于检测异常数据。工控网络数据集上的实验结果表明,该组合分类器能够利用无异常数据样本检测出工控网络入侵,并且提高了OCSVM方法的检测效果。在气体管道网络数据集入侵检测实验中,所提方法的总体检测率为91.81%;而原始OCSVM算法则为80.77%。     

Visual Analysis of Tumor Control Models for Prediction of Radiotherapy Response

In radiotherapy, tumors are irradiated with a high dose, while surrounding healthy tissues are spared. To quantify the probability that a tumor is effectively treated with a given dose, statistical models were built and employed in clinical research. These are called tumor control probability (TCP) models. Recently, TCP models started incorporating additional information from imaging modalities. In this way, patient‐specific properties of tumor tissues are included, improving the radiobiological accuracy of models. Yet, the employed imaging modalities are subject to uncertainties with significant impact on the modeling outcome, while the models are sensitive to a number of parameter assumptions. Currently, uncertainty and parameter sensitivity are not incorporated in the analysis, due to time and resource constraints. To this end, we propose a visual tool that enables clinical researchers working on TCP modeling, to explore the information provided by their models, to discover new knowledge and to confirm or generate hypotheses within their data. Our approach incorporates the following four main components: (1) It supports the exploration of uncertainty and its effect on TCP models; (2) It facilitates parameter sensitivity analysis to common assumptions; (3) It enables the identification of inter‐patient response variability; (4) It allows starting the analysis from the desired treatment outcome, to identify treatment strategies that achieve it. We conducted an evaluation with nine clinical researchers. All participants agreed that the proposed visual tool provides better understanding and new opportunities for the exploration and analysis of TCP modeling.