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昔格达土路基填料压实度影响因素的试验研究  [PDF]
王维早,许强
重庆交通大学学报(自然科学版) , 2010,
Abstract: :?以昔格达土作为路基填料,进行了该填料的含水量、颗粒级配、施工工艺对压实度影响的相关性试验。试验结果表明:昔格达土填料含水量在12%~17%之间时,路基的压实效果最佳;压实前后其Cu和Cc均满足要求,昔格达土填料是一种级配好的填料;16t压路机碾压方式下适合昔格达土填料的松铺厚度为30~35cm,18t压路机碾压方式下为35~40cm;2种压路机均以采用先强振后弱振的碾压方式压实度效果较好;16t压路机最佳的碾压遍数为6遍、18t压路机为5遍时,效果最好。
计算机地貌晕渲效果增强方法研究  [PDF]
姜文亮, 李 霖, 应 申
武汉大学学报(信息科学版) , 2007,
Abstract: ?在总结传统手工晕渲经验和方法的基础上,深入分析了计算机地貌晕渲的原理,着重研究了坡度和坡向对地貌晕渲中阴影强弱和明暗程度的影响,提出了变比例调整高程和晕渲笔调调整两种方法。实验表明,利用本文方法能有效改善地貌晕渲图的三维立体视觉效果。
实值离散Gabor变换块时间递归算法的并行格型结构实现方法  [PDF]
陶亮,庄镇泉
电子学报 , 2002,
Abstract: Gabor变换在很多领域被认为是非常有用的方法,如语音与图像处理,雷达、声纳、振动信号的处理与理解等,然而实时应用却因其很高的计算复杂性而受到限制.为了减小计算复杂性,我们曾提出了实值离散Gabor变换法.本文首先简单回顾了作者曾提出的实值离散Gabor变换及其与复值离散Gabor变换的关系,然后为了有效地和快速地计算实值离散Gabor变换,提出了在临界抽样条件下和在过抽样条件下,一维实值离散Gabor变换系数求解的块时间递归算法以及由变换系数重建原信号的块时间递归算法,研究了两算法使用并行格型结构的实现方法,并讨论和比较了算法的计算复杂性和优越性.
基于GlobalMapper的地貌晕渲制图——以西安幅(Ⅰ-49)为例  [PDF]
林松,程维明,乔玉良
地球信息科学学报 , 2009,
Abstract: 地貌晕渲图自动制图是以计算机软、硬件为基础,对DEM数据实现的一种三维立体可视化表达。本文从地貌晕渲的基本理论出发,以我国1100万标准分幅的西安幅(1-49)为例,采用GlobalMapper软件实现了计算机地貌晕渲自动制作的全过程,主要内容包括计算机地貌晕渲关键技术的实现,地貌晕渲效果与参数设置之间的关系,GlobalMapper软件中各种参数设置的合理性分析,使用分层设色的办法对晕渲图进行色彩的设计,并利用PHOTOSHOP软件对结果进行整饰等。该方法可实现地貌晕渲图的自动制图。
基于熵的彩色晕渲图设色方案辅助设计  [PDF]
余建伟,朱海红,姜文亮,应申
武汉大学学报(信息科学版) , 2008,
Abstract: ?在熵理论和地图分级评价模型的基础上,提出了基于熵的彩色晕渲图设色方案辅助设计方法,并进行了晕渲制图实验。从客观信息量测定和主观评价结果的分析表明,本文方法制作的晕渲图色彩过渡自然,地形区分明显,层次清晰,能更好地表达地貌形态。
计算机环境下地貌晕渲图制作的探讨  [PDF]
赵尚民,程维明,周成虎,陈曦
地球信息科学学报 , 2009,
Abstract: 本文以1∶100万标准分幅的成都幅(H-48)为例,采用SRTM-DEM数据,利用ERDAS软件、MicroDEM软件和GlobalMapper软件,进行地貌晕渲图原图的制作,并利用Photoshop软件,对它们生成的地貌晕渲图原图进行了颜色调整、效果优化和与地图底图叠加生成最终的地貌晕渲图。研究表明(1)利用3种软件进行地貌晕渲图原图的制作各有优缺点,但就最终成果图的整体质量和效果来看,GlobalMapper软件制作的地貌晕渲图要优于MicroDEM软件制作的地貌晕渲图,而以ERDAS软件制作的地貌晕渲图的质量和效果最差;(2)Photoshop软件作为强大的图形图像处理软件,可以在地貌晕渲图的效果调整和质量优化上起到重要作用;(3)由于数字环境下地貌晕渲图可以表达更多的信息量和色彩效果,它对于制图人员色彩的运用、表达效果的判断和调整能力等提出了更高的要求和挑战。
名与实: 格尔必齐河位置之争的起源
The Origin of the Dispute on Gorbitsa River’s Location
 [PDF]

杨丽婷
- , 2015,
Abstract: 摘要 关于康熙年间中俄《尼布楚条约》议定界河格尔必齐河的位置,学界一直存在两种不同的观点,国内学者一般认为今东经 119°10′,北纬 35°08′的格尔必齐河就是当年的界河,而国外有些学者则认为是其东边的阿玛扎尔河 (在清代曾被称为大格尔必齐河)。本文从分析大量的清代有关界河格尔必齐河的舆图和文献资料入手,爬梳两种界河位置观点的资料依据及起源,认为外国传教士负责绘制的 ?皇舆全览图?错误地把格尔必齐河标注在大格尔必齐河的东边,之后清代编纂的大量舆图、文献甚至西方介绍中国疆域的书籍不加考辨地沿袭传抄,这成为误解界河格尔必齐河位置的资料基础。格尔必齐河位置之争,揭示了清代舆图文献编纂过程中沿袭传抄的弊病,只有不断追溯资料的原始来源,辨别原始资料的正误,才能从根本上还原历史真相。
Abstract: There are two different views on the location of Gorbitsa River,which forms part of the boundary between China and Russia that was agreed to in the Treaty of Nerchinsk 1689. Chinese scholars generally believe that the Gorbitsa River ( 119 °10'E,35 ° 08'N) was the old border,but some foreign scholars hold that today’s Amazar river,which is east of the present-day Gorbitsa River,was the old Gorbitsa River. This paper sorts out these two views’and data biases and their original dates. It is noteworthy that although the records on Gorbitsa River were quite different, whether west or east of the great Gorbitsa River,the records on boundary tablets were the same. The tablet was always near the west river. It turns out that the boundary river agreed on in the Treaty of Nerchinsk was the western one,and this river was called Gorbitsa River in the Treaty of Nerchinsk. Huang Yuquan Lantu,which was drawn by foreign Jesuits, mistakenly marked the Gorbitsa River on east of the great Gorbitsa River. Yet,because of its authority,a large number of subsequent maps and literature, even Western literature about China, perpetuated this mistake. These erroneous maps and literature became the source of misunderstanding for the location of the Gorbitsa River. By the dispute of the Gorbitsa River’s location, this paper reveals the shortcomings of private copying of Qing Dynasty maps and literature,and demonstrates that only by tracing back the original sources and identifying the original data,we can restore the fundamental historical truth.
Monte Carlo integration on GPU  [PDF]
J. Kanzaki
Physics , 2010, DOI: 10.1140/epjc/s10052-011-1559-8
Abstract: We use a graphics processing unit (GPU) for fast computations of Monte Carlo integrations. Two widely used Monte Carlo integration programs, VEGAS and BASES, are parallelized on GPU. By using $W^{+}$ plus multi-gluon production processes at LHC, we test integrated cross sections and execution time for programs in FORTRAN and C on CPU and those on GPU. Integrated results agree with each other within statistical errors. Execution time of programs on GPU run about 50 times faster than those in C, and more than 60 times faster than the original FORTRAN programs.
CPU and/or GPU: Revisiting the GPU Vs. CPU Myth  [PDF]
Kishore Kothapalli,Dip Sankar Banerjee,P. J. Narayanan,Surinder Sood,Aman Kumar Bahl,Shashank Sharma,Shrenik Lad,Krishna Kumar Singh,Kiran Matam,Sivaramakrishna Bharadwaj,Rohit Nigam,Parikshit Sakurikar,Aditya Deshpande,Ishan Misra,Siddharth Choudhary,Shubham Gupta
Computer Science , 2013,
Abstract: Parallel computing using accelerators has gained widespread research attention in the past few years. In particular, using GPUs for general purpose computing has brought forth several success stories with respect to time taken, cost, power, and other metrics. However, accelerator based computing has signifi- cantly relegated the role of CPUs in computation. As CPUs evolve and also offer matching computational resources, it is important to also include CPUs in the computation. We call this the hybrid computing model. Indeed, most computer systems of the present age offer a degree of heterogeneity and therefore such a model is quite natural. We reevaluate the claim of a recent paper by Lee et al.(ISCA 2010). We argue that the right question arising out of Lee et al. (ISCA 2010) should be how to use a CPU+GPU platform efficiently, instead of whether one should use a CPU or a GPU exclusively. To this end, we experiment with a set of 13 diverse workloads ranging from databases, image processing, sparse matrix kernels, and graphs. We experiment with two different hybrid platforms: one consisting of a 6-core Intel i7-980X CPU and an NVidia Tesla T10 GPU, and another consisting of an Intel E7400 dual core CPU with an NVidia GT520 GPU. On both these platforms, we show that hybrid solutions offer good advantage over CPU or GPU alone solutions. On both these platforms, we also show that our solutions are 90% resource efficient on average. Our work therefore suggests that hybrid computing can offer tremendous advantages at not only research-scale platforms but also the more realistic scale systems with significant performance gains and resource efficiency to the large scale user community.
Augmenting Operating Systems With the GPU  [PDF]
Weibin Sun,Robert Ricci
Computer Science , 2013,
Abstract: The most popular heterogeneous many-core platform, the CPU+GPU combination, has received relatively little attention in operating systems research. This platform is already widely deployed: GPUs can be found, in some form, in most desktop and laptop PCs. Used for more than just graphics processing, modern GPUs have proved themselves versatile enough to be adapted to other applications as well. Though GPUs have strengths that can be exploited in systems software, this remains a largely untapped resource. We argue that augmenting the OS kernel with GPU computing power opens the door to a number of new opportunities. GPUs can be used to speed up some kernel functions, make other scale better, and make it feasible to bring some computation-heavy functionality into the kernel. We present our framework for using the GPU as a co-processor from an OS kernel, and demonstrate a prototype in Linux.
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