邊角細節 的英文怎麼說

中文拼音 [biānjiǎoxìjié]
邊角細節 英文
corner detail
  • 邊 : 邊Ⅰ名詞1 （幾何圖形上夾成角的直線或圍成多邊形的線段） side; section 2 （邊緣） edge; margin; oute...
  • 角 : 角Ⅰ名詞1 （牛、羊、 鹿等頭上長出的堅硬的東西） horn 2 （古時軍中吹的樂器） bugle; horn 3 （形狀像...
  • 細 : 形容詞1 （條狀物橫剖面小） thin; slender 2 （顆粒小） in small particles; fine 3 （音量小） thin ...
  • 節 : 節構詞成分。
  • 邊角 : corner pin
  • 細節 : 1. （細小的環節或情節） details; particulars; specific; minutia; minutiae 2. [紡織] snicks
  1. Horn changes spine skin tumour to often produce yu yangguang to expose place according to what shoot, below the circumstance of extremelying he xianzhao, 2 3 weeks inside appear quickly smooth red is nodal, there is corneous embolus in the center of its, nodal brim sees outspread blood capillary

    角化棘皮瘤常發生於陽光照射的暴露部位，在無任何先兆的情況下， 2 3周內迅速出現光滑的紅色結節，其中心有角質栓子，結節邊緣可見擴張的毛細血管。
  2. Based on this kind of relations between the topological structures and the content distributions we study the web modelling, community identification and some related application problems in detail : first, after some existed characteristics of the web topology are verified, some new characteristics are discovered : the high clustering property in micro - topology ( high average gathering coefficient ), the obvious mapping relation between the topological struture and the content in micro - level 、 linear irrelevant between the degree distribution of network nodes and the relative degree distribution of contents etc. then after analysis the topology of the complex network and the network modeling, the muti - scale determinism is proposed, especially for the information network a web evolvement model ( prcp model ) that fused the node authority and the node correlation is proposed. the model deduction, evolving learning verification and large scale experiment proof indicate that the model can explain the micro - topology centralizing phenomena, can imitate the mapping relation between the network connecting distribution and network content relative distribution and also can predict the mapping relation between the topology clustering and content clustering

    本文在詳細觀察了web網路的拓撲結構特徵以及拓撲結構與內容分佈相互關系的基礎上，以信息網路的物理連接拓撲結構與節點內容相關度分佈之間的相互關系為主線，從網路特徵、網路建模、社區分析及相關應用方面問題進行了深入細致地探討:首先在驗證了前人提出的web網路拓撲結構特徵基礎上，進一步發現了信息網路所具有的一些新特徵: 1 ）網路微觀顆粒度的拓撲結構聚團與內容聚團存在明顯的映射關系，具體包括節點之間的物理連邊概率與節點之間的內容相關度成指數比例關系、節點形成三角形拓撲結構的概率與節點內容相關緊密程度之間同樣具有一種指數比例關系; 2 ）網路節點連接度整體分佈與節點內容相關度整體分佈是線性無關的; 3 ）網路微觀拓撲結構中的存在很強的集聚性（平均聚團系數很高） 。
  3. In the terms of interpolation, the image reconstructed from nearest interpolation or linear interpolation has good edge but serious noise ; reconstruction from 4 * 4cubic interpolation or three b - spline or three - order lagrange interpolations has better local character. 2 x 2cubic interpolations which has both better edge and local character is the ideal interpolation, the following is the basic principle during reconstruction : ( 1 ) the more width of interpolation, the more number of summation and the more order of interpolation polynomial, the higher of density resolution ; ( 2 ) the more of interpolation polynomial and width of interpolation, the more of reconstruction time simultaneously, aimed at eliminating the effects of noise contained in projection data, in this paper, author analysis cause and effects of common artifacts. importantly, discusses convolution back - projection reconstruction algorithm with a shift axis of rotation has been derived for correcting images that acquired with a divergence axis of rotation using the fan beam geometry with an angle - equaled detector

    在ct圖像重建時，選擇有限帶寬窗有較好的空間解析度，三角形窗有較好的密度解析度，選擇餘弦窗則使得空間解析度與密度解析度的折衷；從窗函數的頻譜角度來講，可以用於圖像重建的一個良好的卷積窗函數應該具備以下條件： （ ? ）小的3db帶寬b ，即最小的主瓣寬度； （ ? ）最小的旁瓣最大峰值a ； （ ? ）最大的旁瓣峰值衰減速度d ；就內插函數而言，臨近點內插與線性內插重建圖像噪聲大，但有較好的邊緣與細節； 4 4三次內插、三次b -樣條與四次拉格朗日多項式內插圖像平滑，局部特性較好。
  4. Firstly in this part, computer simulation methodology based on the baecher model for generating network of discrete fractures was presented, which includes the follow details : probability distributions of fracture density, orientation, trace length, size, and aperture and estimation of their statistical parameters ; stochastic models of fracture network ; monte - carlo ' s simulation method ; numerical simulation procedure and technicality. then, boundary element method was used to calculate flow through the generated fractured network. assuming single fracture as a two - dimension inexpressible isotropic porous media, boundary element method equations for flow in single fracture and then in fracture network were derived using the weighted residual method

    給出了離散裂隙網路模型所依據的基本假定；發展了基於baecher模型的離散裂隙網路計算機隨機生成技術：詳細地推導了單裂隙滲流和多裂隙相交網路滲流的邊界單元法公式，發展了離散裂隙網路中穩態滲流的邊界元數值技術，並且討論了相關的具體數值技術細節，如角點的處理方法，單元的自動剖分等：描述了混合邊界元?管流模擬方法及其數值實現；研究了裂隙網路的簡化方法，並針對裂隙網路邊界元法的特點提出了一種改進的分塊三角分解法。
  5. In general, point and curve primitives are able to provide sharp corners and ridge features ; sphere primitives are able to achieve smoothing effects and provide semi - sharp features ; and cube primitives are able to handle sharp corners, sharp edges and flat faces with the corners, edges and faces of the cubes respectively

    點和曲線編輯工具可以用來獲取尖銳的或「脊」的編輯效果，球體編輯工具可以用來作為平滑工具或得到半尖銳的細節特徵，立方體編輯工具可以用來獲取尖角、尖銳的棱邊和平坦的小面。
  6. Finite volume method can deal with irregular boundary conditions. in this paper, we discrete the water domain into triangular meshes, and simulate dam breaking, water droplets. the same as finite difference method, we just specify waves source, the movement of water waves can be simulated automatically

    有限體積方法能夠處理具有不規則邊界水域的水流現象，在本文中，我們把求解的水域離散成無結構三角形網格，對潰壩問題、雨景等水流現象進行了模擬，和有限差分方法一樣，我們僅僅指定產生水流動畫的波源，水流動畫的細節均由數值方法產生，不需要人工的干預。
  7. The former is the combination of human vision characters and image ' s local statistics, and judge the quality of image subjectively. but the latter judge the quality of image both subjectively and objectively. moreover, the latter compare result edge, this work is an innovation

    不同之處在於：前者結合人類視覺特性，對于處理后的圖像主要從主觀視覺角度評價；而後者則採用在與傳統方法處理結果比較的基礎上，進一步比較它們的邊緣圖像，在達到客觀評價準則意義下最優的同時盡可能多的保持圖像邊緣位置和細節信息。
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