保持线宽与线型信息的图像轮廓矢量化方法

对工程图进行矢量化,提取有用信息,用于工程设计,可以大大提高设计效率.在图像矢量化的方法中,基于细化的算法容易丢失一些有用信息,造成数据畸变,影响矢量化结果.因此,在矢量化过程中,沿图像边缘进行轮廓匹配时,同时求出拟合段图线的曲率和法向量,充分利用其特性,从而兼顾线宽和线型,为图像矢量化提供了一个实用的方法.     

MAPGIS地图矢量化误差分析及校正

MAPGIS作为深受广大用户喜爱的一款国产GIS软件,已经从4.0,5.0,5.32,6.0,6.5,6.6发展到目前的7.0版本。但是在图形矢量化过程中依然不可避免各种类型误差的产生,针对这一情况,对MAPGIS6.5图形处理模块在地图矢量化过程中产生误差的原因及减小误差、误差校正等问题进行了深入的分析和探讨。     

测井工程图的前景背景分割方法

在测井工程图纸的矢量化过程中经常采用二值化的方法达到分割前景与背景的目的，但是目前许多陈旧图纸严重退化，经典的大津阈值法二值化分割测井工程图纸的前景与背景存在着不足，该文针对这一问题提出了一种有效的前景背景分割方法，该方法先对背景图像进行采样，再利用双3次内插法生成背景图像，实现退化图纸的前、背景分割，为进一步分析测井工程图纸提供了方便．     

Hypercube stacking: A potts-spin model for surface growth

We present a deposition and evaporation model for surface growth under a solid-on-solid constraint. We generalize the Ising-spin representation of a two-dimensional surface by Blöte and Hilhorst to ad-dimensional surface of a (d+1)-dimensional hypercubic lattice. The allowed surface configurations correspond to the (degenerate) ground states of a chirald-state Potts model. We describe a vectorized multisite-coding implementation for the corresponding kinetic Potts-spin model ford=2 andd=3. For thed=2 equilibrium surface our simulation results show excellent agreement with an exact analysis.     

Some remarks on completely vectorizing point Gauss-Seidel while using the natural ordering

A common statement in papers in the vectorization field is to note that point SOR methods with the natural ordering cannot be vectorized. The usual approach is to reorder the unknowns using a red-black or diagonal ordering and vectorize that. In this paper we construct a point Gauss-Seidel iteration which completely vectorizes and still uses the natural ordering. The work here also applies to both point SOR and single program, multiple data (SPMD) parallel computer architectures. When this approach is reasonable to use is also shown.     

Diffusion of lattice gases without double occupancy on three-dimensional percolation lattices

We examined the diffusion of lattice gases, where double occupancy of sites is excluded, on three-dimensional percolation lattices at the percolation thresholdp _c . The critical exponent for the root-mean-square displacement was determined to bek=0.183±0.010, which is similiar to the result of Roman for the problem of the ant in the labyrinth. Furthermore, we found a plateau value fork at intermediate times for systems with higher concentrations of lattice gas particles.     

工程图纸并行矢量化算法的研究

研究了一种在细化线的基础上的工程图纸并行矢量化方法．它的原理是根据曙光１０００Ａ并行机的特点,通过并行检测图形向前和向后的光栅来度量直线长度检测线记号,然后通过拟合线记号得出一组组合线,再将这些近似的线段合并为矢量数据来描述原始的图像．     

Sentiment Classification Method Based on Blending of Emoticons and Short Texts

With the development of Internet technology, short texts have gradually become the main medium for people to obtain information and communicate. Short text reduces the threshold of information production and reading by virtue of its short length, which is in line with the trend of fragmented reading in the context of the current fast-paced life. In addition, short texts contain emojis to make the communication immersive. However, short-text content means it contains relatively little information, which is not conducive to the analysis of sentiment characteristics. Therefore, this paper proposes a sentiment classification method based on the blending of emoticons and short-text content. Emoticons and short-text content are transformed into vectors, and the corresponding word vector and emoticon vector are connected into a sentencing matrix in turn. The sentence matrix is input into a convolution neural network classification model for classification. The results indicate that, compared with existing methods, the proposed method improves the accuracy of analysis.     

EDrus:一个基于整体识别方法的工程图纸转换系统

整体识别方法是工程图纸扫描转换领域中一种值得研究的矢量化方法,本文给出了整体识别方法中基于图段的数据结构,分析了一个基于整体识别方法的图纸转换系统－ＥＤｒｕｓ系统的组成,并介绍限几个主要的矢量转换算法,本文最后给出了一个实例,用以说明系统的有效性。     

Running large‐scale CFD applications on Intel‐KNL–based clusters

Intel's latest Xeon Phi processor, Knights Landing (KNL), has the potential to provide over 2.6 TFLOPS. However, to obtain maximum performance on the KNL, significant refactoring and optimization of application codes are still required to exploit key architectural innovations that KNL features—wide vector units, many‐core node design, and deep memory hierarchy. The experience and insights gained in porting and running FEFLO (a typical edge‐based finite element code for the solution of compressible and incompressible flows) on the KNL platform are described in this paper. In particular, optimizations used to extract on‐node parallelism via vectorization and multithreading and improve internode communication are considered. These optimizations resulted in a 2.3× performance gain on a 16 node runs of FEFLO, with the potential for larger performance gains as the code is scaled beyond 16 nodes. The impact of the different configurations of KNL's on‐package MCDRAM (Multi‐Channel DRAM) memory on FEFLO's performance is also explored. Finally, the performance of the optimized versions of FEFLO for KNL and Haswell (Intel Xeon) is compared.