自然册区大气景观模拟显示方法初探

提出了一模拟大气，云雾等自然环境的照明模型，对视线距离较大，视野开阔的自然景物造型，如山体造型，更具有真实感效果，可获得模拟云，雾等天气特征的三维地形风景图。     

动态真实感自然景物图象的生成模型

提出了一种计算机图象生成模型，利用预测加伪随机噪声的方法实现几何造型及模拟光学模型，生成了可控宏观结构且具有丰富微观结构的真实感自然景物图象，例如云、水域、草地及山体等。该模型的特点是运算量少，几何造型与光照计算均可同一模型产生，简化了仿真过程。     

喷泉景观的造型设计与模型研究

在分析现有喷泉模拟的基础上，针对喷泉造型的研究相对较少的问题，进行了喷泉造型设计并建模。运用多种数学曲线、曲面方程建立了复杂特殊的喷泉造型模型，并分析喷泉粒子的运动特性建立了喷泉运动模型。采用Visual Studio为编程工具，结合OpenGL技术渲染场景，在Windows XP环境下开发了基于粒子系统的喷泉模拟系统，仿真效果真实。     

基于CAD／CAM的自动编程及零件简化造型的研究

零件加工造型具有不同于零件设计造型的特点和要求，在自动编程中合理选择适当的造型方法，有利于高效、准确地生成符合要求的刀具路径，从而收到良好的效果。     

辐射度技术用于随机分维几何面的全局光照计算

分维几何为模拟自然体和景物提供了十分卓越的工具，然而，分维几何的造型是一个无限细分的随机造型过程，这就为分维几何的绘制带来了极大的困难，到目前为止，只有某些特殊的光线跟踪技术能够用于绘制分维几何曲面，主要产生高光效果。     

CAXA-ME软件中曲面造型和实体造型的融合

CAXA－ME软件存在曲面造型和Parasolid实体造型两个平台，在分析两者曲面造型模块的基础上，介绍CAXA－ME内部在这两个造型之间进行类型转换的方法，并给出主要的转换算法和接口函数，实例显示数据转换方法具有满意的效果。     

基于粒子系统的实时雨模拟

基于流体动力学和粒子系统理论，给出了一种实时生成三维雨的方法。算法以矩形基本粒子对雨粒子进行造型，采用动态纹理映射技术和透明度扰动方法，根据雨滴的降落运动方程，来描述不同大小雨粒子受到重力和空气浮力、阻力影响时的运动效果，采用与视点相关技术动态生成三维降雨场景。与传统的雨模拟算法相比，该算法既正确模拟了雨的运动行为，又降低了计算复杂性，真实再现了雨的三维视觉效果，在满足实时交互漫游的前提下表现出较强的真实感，具有一定的实用价值。     

利用Rhino软件进行首饰拟实造型的技巧

首饰产品的拟实造型因其逼真的效果及视觉,越来越受到设计、开发人员的青睐。利用Rhino软件所具有的渲染器及插件的光影、材质、环境、展台和镶嵌等功能,对戒指进行产品的拟实造型,获得了比较满意的效果。通过拟实造型,总结了一些技巧,供有关人士参考。     

基于细分曲面的三维服装柔性实体模拟

提出一种基于细分曲面的三维服装柔性实体模拟算法，该算法将整个模拟过程分为两个阶段：首先利用四点细分曲面造型方法生成三维服装刚性曲面，然后在刚性曲面基础上通过引入织物的物理模型来模拟三维服装柔性曲面，通过物理和几何模拟方法有机结合，算法有效解决了复杂衣片间的缝合问题，较大地提高了模拟的计算效率，同时，也提出了一种基于细分曲面层次数据结构的碰撞检测算法，有效提高了模拟速度，提出的算法已全部在所开发的三维虚拟服装试衣系统中得以实现，实验结果表明：该算法具有模拟效率高、交互性强和易于计算机实现等优点。     

玉米叶片形态的几何造型研究

为了更好地进行玉米叶片几何造型模拟，基于对玉米叶片形态建成过程的观测研究，首先提取了玉米叶片形态结构和形态建成过程的主要特征，然后构建了参数化的玉米叶片几何模型。该模型用较少几个具有较明确的生物学意义的形态参数，就可实现玉米叶片形态和形变过程的矢量化，再结合VC 和OpenGL，就可在计算机上重现玉米叶片的虚拟生长，模拟结果表明，图像上的效果、产生的数据和实际叶片基本一致，从而为相关领域研究者提供了一个可视化的玉米叶片模型。该模型结构简单、易于交互、真实感强，可较好地模拟玉米叶片建成过程中的形态变化特征。     

Detecting ground fog from space – a microphysics-based approach

The detection of ground fog from satellite data is of interest in operational nowcasting applications, as well as in studies of the climate system. A discrimination between fog at the ground and other low-stratus situations from satellite data requires information on cloud vertical geometry to establish whether the cloud touches the ground. This article introduces a technique that allows for the discrimination between low stratus and (ground) fog on the basis of geostationary satellite imagery. The cloud-base height is derived using a subadiabatic model of cloud microphysics. In this model, the cloud base is varied until model liquid–water path matches that retrieved from satellite data. The performance of this technique is shown to be good in a comparison with METeorological Aerodrome Report data comprising 1030 satellite scenes. With a hit rate of 81% and a threat score of 0.62, the skill is satisfactory.     

模拟雾景图像的算法研究和应用

户外成像图像处理系统容易受到天气变化的影响，为测试图像处理算法对天气变化的敏感程度，人们提出多种虚拟现实算法生成各种气候条件下图像，本文提出了一种可行的户外雾景图像生成算法，能调控雾的浓度，摸拟现实场景中雾的复杂多变的形态对图像造成的影响。     

An object-oriented daytime land fog detection approach based on NDFI and fractal dimension using EOS/MODIS data

A new approach for land fog detection using daytime imagery from Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) data based on the normalized difference fog index (NDFI) is proposed. NDFI is used to discriminate fog from clouds based on simulating and analysing the radiation characteristics of fog and cloud with MODIS data and the Streamer radiative transfer model. In this paper, in addition to the spectral and spatial characteristics of NDFI, the textural characteristics are introduced by using a fractal dimension. The fractal dimension is calculated with a differential box-counting approach to differentiate the texture characteristics of cloud and fog, and then the spectral and texture features are combined using an NDFI weighted fractal dimension algorithm as a new feature to improve the existing daytime fog detection approach. The performance of this approach is evaluated against ground-based measurements over China in winter, and the approach is proved to be effective in detecting land fog accurately based on the three cases.     

基于云雾边缘高程特性的云雾分离检测算法研究

云雾本身具有的某种相似性造成它们分离检测的困难。国内外研究工作者基于云雾的色调特性差异和纹理特性差异进行了一定程度的云雾分离检测研究,但仍未能很好地解决该问题。在分析气象专家判别云雾属性所应用的图像的6个基本特征的基础上,本文首次基于云雾边缘高程特性差异进行云雾分离检测研究,并选取MODIS传感器数据作为实验数据。实验结果表明:该算法具有较强的稳定性和普适性,但算法中的特征检测指标及特征检测指标的适用性需进一步改进。     

Journey from cloud of things to fog of things: Survey,new trends,and research directions

With the advent of the Internet of Things (IoT) paradigm, the cloud model is unable to offer satisfactory services for latency-sensitive and real-time applications due to high latency and scalability issues. Hence, an emerging computing paradigm named as fog/edge computing was evolved, to offer services close to the data source and optimize the quality of services (QoS) parameters such as latency, scalability, reliability, energy, privacy, and security of data. This article presents the evolution in the computing paradigm from the client-server model to edge computing along with their objectives and limitations. A state-of-the-art review of Cloud Computing and Cloud of Things (CoT) is presented that addressed the techniques, constraints, limitations, and research challenges. Further, we have discussed the role and mechanism of fog/edge computing and Fog of Things (FoT), along with necessitating amalgamation with CoT. We reviewed the several architecture, features, applications, and existing research challenges of fog/edge computing. The comprehensive survey of these computing paradigms offers the depth knowledge about the various aspects, trends, motivation, vision, and integrated architectures. In the end, experimental tools and future research directions are discussed with the hope that this study will work as a stepping-stone in the field of emerging computing paradigms.     

基于面向对象方法的白天雾检测

通过遥感技术进行雾检测的难点在于云和雾的分离,传统的基于像素的雾检测方法只考虑到云和雾的光谱信息,但是云和雾的光谱信息极为相似,不易区分。本文提出一种基于面向对象的白天雾检测方法,首先从遥感影像中提取云雾目标,然后对云雾目标进行分割,最后选取云雾分离的特征参数,完成对雾区的检测。试验结果显示,相对于传统的基于像素光谱信息的多层次阈值法,本文提出的基于对象的雾检测方法相对于传统方法在检测效果上有较大的提高。     

利用环境一号卫星数据监测雾分布

雾是环境空气监测的一个重要内容之一。根据环境一号卫星B星（HJ-1B）的数据特点,从典型地物、云、雾的微物理特性的RT3辐射传输模拟出发,分析不同波段典型地物和云、雾的反射率、亮温差别,提出了综合利用HJ-1B卫星CCD相机和红外相机数据进行雾监测的方法与流程。最后,使用2009年3月12日我国南方地区的HJ-1B数据为卫星监测数据进行了监测试验。结果表明:HJ-1B卫星数据能够实现雾的监测,但由于薄云受到地表影响,无法准确区分薄云与雾。     

物联网的边界计算模型：雾计算

在物联网和云计算带来技术变革和带动产业发展的过程中,由于网络接入设备激增,而网络带宽有限的情况下,思科公司推出了雾计算的概念。首先探讨雾计算的特征和应用模式,然后分析雾计算的＂雾节点＂与云计算的＂云节点＂以及物联网的＂物节点＂的互操作方法,并总结了雾计算的用例,最后给出了前景展望。     

Efficient and dynamic scaling of fog nodes for IoT devices

It is predicted by the year 2020, more than 50 billion devices will be connected to the Internet. Traditionally, cloud computing has been used as the preferred platform for aggregating, processing, and analyzing IoT traffic. However, the cloud may not be the preferred platform for IoT devices in terms of responsiveness and immediate processing and analysis of IoT data and requests. For this reason, fog or edge computing has emerged to overcome such problems, whereby fog nodes are placed in close proximity to IoT devices. Fog nodes are primarily responsible of the local aggregation, processing, and analysis of IoT workload, thereby resulting in significant notable performance and responsiveness. One of the open issues and challenges in the area of fog computing is efficient scalability in which a minimal number of fog nodes are allocated based on the IoT workload and such that the SLA and QoS parameters are satisfied. To address this problem, we present a queuing mathematical and analytical model to study and analyze the performance of fog computing system. Our mathematical model determines under any offered IoT workload the number of fog nodes needed so that the QoS parameters are satisfied. From the model, we derived formulas for key performance metrics which include system response time, system loss rate, system throughput, CPU utilization, and the mean number of messages request. Our analytical model is cross-validated using discrete event simulator simulations.