基于热度曲线分类建模的微博热门话题预测

及时掌握大众关心的热点话题是企业进行商业创新和商务营销的重要前提。现有方法大都依赖于非结构化数据的处理或反复遍历样本集,使算法复杂性较高。文中从话题的统计特性出发,提出建立在结构化数据上的非参数方法。首先对单个话题构建表征话题传播扩散程度和关注聚焦程度的热度曲线;然后对这些形态丰富的热度曲线进行分类建模,得到不同类别曲线的共性特征及发展规律;最后使用分类模型上的加权投票规则预测新话题是否会发展成为热门话题。基于新浪微博平台进行数据收集和实验,结果表明该方法数据结构简单、效果良好、复杂度低且易于控制。     

Experiencing Nature: Embodying Animals in Immersive Virtual Environments Increases Inclusion of Nature in Self and Involvement With Nature

Immersive virtual environments (IVEs) produce simulations that mimic unmediated sensory experiences. 3 experiments (N = 228) tested how different modalities increase environmental involvement by allowing users to inhabit the body of animals in IVEs or watch the experience on video. Embodying sensory‐rich experiences of animals in IVEs led to greater feeling of embodiment, perception of being present in the virtual world, and interconnection between the self and nature compared to video. Heightened interconnection with nature elicited greater perceptions of imminence of the environmental risk and involvement with nature, which persisted for 1 week. Although the effect sizes were small to moderate, findings suggest that embodied experiences in IVEs may be an effective tool to promote involvement with environmental issues.     

An overview of methods to evaluate uncertainty of deterministic models in decision support

There is an increasing need for environmental management advice that is wide-scoped, covering various interlinked policies, and realistic about the uncertainties related to the possible management actions. To achieve this, efficient decision support integrates the results of pre-existing models. Many environmental models are deterministic, but the uncertainty of their outcomes needs to be estimated when they are utilized for decision support. We review various methods that have been or could be applied to evaluate the uncertainty related to deterministic models' outputs. We cover expert judgement, model emulation, sensitivity analysis, temporal and spatial variability in the model outputs, the use of multiple models, and statistical approaches, and evaluate when these methods are appropriate and what must be taken into account when utilizing them. The best way to evaluate the uncertainty depends on the definitions of the source models and the amount and quality of information available to the modeller.     

Blending science and public policies for remediation of a degraded ecosystem: Jackfish Bay, north shore of Lake Superior, Ontario, Canada

The Jackfish Bay Remedial Action Plan is the first of Lake Superior's Areas of Concern (AOCs) to consider recognition as an Area in Recovery (AiR). As a result of a high degree of complexity and uncertainty, ecosystem recovery in Jackfish Bay has been determined using a combination of regulatory policies and scientific evidence and extensive public and expert-based decision making. As a result, the conceptualization of the AiR status in Jackfish Bay has been developed with the adaptive management and the ecosystem approach, which provide the basic principles of assessing, monitoring, and managing the Area of Concern. To determine the status of beneficial use impairments caused by effluent from the Terrace Bay Pulp Inc., three public advisory committees—an academic panel of experts, a government technical review committee, and the Jackfish Bay Public Area in Recovery Review Committee (PARRC)—reviewed relevant scientific data and documents, including peer-reviewed publications, to assess changes in pollution levels in Jackfish Bay and improvements to aquatic, biotic, and benthic environments of the bay. The public decision-making process concluded with recommendations by the PARRC to develop a systematic monitoring program so that the ecosystem recovery process in the bay could be assessed on a continued basis, leading to its eventual delisting as an AOC. The entire process provides an example of blending science and public policies for remediation of a degraded ecosystem on the Great Lakes.     

基于无线物联网数据库的环境监测系统的实现

基于ARM9s3c2440处理器和嵌入式Linux系统平台,利用嵌入式数据库SQLite设计了环境监测系统。通过无线网络访问数据库里的温湿度数据,并利用JavaScript脚本绘制出温湿度随时间变化的曲线。该方案运行可靠、管理方便。     

基于系统动力学的环境承载力仿真与调控

环境承载力是区域环境系统结构与区域社会经济活动适宦程度的一种表示。环境承载研究很重要。为使陕西省经济发展与环境保护相协调,优化陕西省环境承载能力,采用定性和定量相结合的方法,通过建立系统动力学模型,仿真陕西省中长期（2007—2020年）不同发展策略下各指标数值,并采用综合评价方法计算不同策略下环境承载力的值,最终得出承载状态（超载、满载、可载）。仿真结果表明基于系统动力学的环境承载力模型能够动态仿真现实的环境承载力;研究结果可为陕西省发展规划的制定提供一定的理论依据。     

Particle Level Set Advection for the Interactive Visualization of Unsteady 3D Flow

Typically, flow volumes are visualized by defining their boundary as iso‐surface of a level set function. Grid‐based level sets offer a good global representation but suffer from numerical diffusion of surface detail, whereas particle‐based methods preserve details more accurately but introduce the problem of unequal global representation. The particle level set (PLS) method combines the advantages of both approaches by interchanging the information between the grid and the particles. Our work demonstrates that the PLS technique can be adapted to volumetric dye advection via streak volumes, and to the visualization by time surfaces and path volumes. We achieve this with a modified and extended PLS, including a model for dye injection. A new algorithmic interpretation of PLS is introduced to exploit the efficiency of the GPU, leading to interactive visualization. Finally, we demonstrate the high quality and usefulness of PLS flow visualization by providing quantitative results on volume preservation and by discussing typical applications of 3D flow visualization.     

Extraction Of Feature Lines On Surface Meshes Based On Discrete Morse Theory

We present an approach for extracting extremal feature lines of scalar indicators on surface meshes, based on discrete Morse Theory. By computing initial Morse‐Smale complexes of the scalar indicators of the mesh, we obtain a candidate set of extremal feature lines of the surface. A hierarchy of Morse‐Smale complexes is computed by prioritizing feature lines according to a novel criterion and applying a cancellation procedure that allows us to select the most significant lines. Given the scalar indicators on the vertices of the mesh, the presented feature line extraction scheme is interpolation free and needs no derivative estimates. The technique is insensitive to noise and depends only on one parameter: the feature significance. We use the technique to extract surface features yielding impressive, non photorealistic images.     

Real-Time GPU Silhouette Refinement using Adaptively Blended Bézier Patches

We present an algorithm for detecting and extracting the silhouette edges of a triangle mesh in real time using Graphical Processing Units (GPUs). We also propose a tessellation strategy for visualizing the mesh with smooth silhouettes through a continuous blend between Bézier patches with varying level of detail. Furthermore, we show how our techniques can be integrated with displacement and normal mapping. We give details on our GPU implementation and provide a performance analysis with respect to mesh size.