指針丟失 的英文怎麼說
中文拼音 [zhǐzhēndiūshī]
指針丟失
英文
au-lop:loss of administrative unit pointer au-
The appraising methods used often ca n ' t describe the relation of determination and disdetermination in the appraising process so that information probably has been lost or repeated. connection degrees of intensity have been set up to show the relation of determination and disdetermination by set pair analysis in the two important links of evaluation _ the determination of norm importance and the foundation of appraising model. in the connection degrees of intensity, determinational information has been used to build norm importance and show the good - bad relation of every plan
針對目前常用的評標方法因沒有系統地描述評標過程中的確定性與不確定性的聯系而造成的信息丟失或信息重復的現狀，筆者在指標權重的確定和評價數學模型兩個環節中利用集對分析方法建立了反映確定性與不確定性關系的聯系度，利用其中的相對確定性信息確定指標權重和對各個方案進行排序，利用其中的相對不確定性信息反映指標權重的變化趨勢，較好地克服了以往評標中出現的主觀隨意性，客觀地描述了評標過程。Tributary unit loss of pointer tu - lop
支路單元指針丟失Administration unit loss of pointer au - lop
管理單元指針丟失The contributions of this dissertation is listed below. aiming at existing defects of traditional beeline detection by hough transformation ( ht ) arithmetic, such as large storage space consuming, imprecise beeline detection effect and information loss of image feature pixels etc, we suggest two new beeline detection methods. ( 1 ) based on infinite symmetry exponential filter and its recursion arithmetic, new beeline detection methods can get exact direction of image edge pixels in advance, so it reduces highly the calculation quantity of the conventional ht, and improves the speed and the precision of beeline detection greatly
本論文的主要研究成果列舉如下：針對傳統直線檢測霍夫變換（ houghtransform ， ht ）所存在的參數空間存儲量大，直線檢測不精確以及圖像特徵點信息丟失等缺點，提出兩種新的直線段檢測演算法： （ 1 ）提出一種基於無限對稱指數濾波的ht直線段檢測演算法，在進行邊緣檢測的同時，提前精確定位邊緣點的方向，減少了ht的運算量，提高了運算速度和檢測精度，而且整體演算法便於硬體的并行執行，使得實時處理成為可能。Abstract : in a network system, overflow or overwrite of message buffer will cause missing of messages. for a timed token network, message transmission time and the message buffering space allocation in a node are very important issues on network real time capability. this paper analyses the message buffering mechanism, describes the relationship of message buffering space and message transmission bandwidth allocation, and proposes a space determination method of message buffer for ltpb network. the maximum space redundancy avoiding buffer overflow for “ send ” and “ receive ” buffers has been derived. it is found that the space of “ send ” and “ receive ” buffers is equal to the message size under condition that the message gap time is greater than message latency and node response time
文摘:在網路系統中，節點緩沖區內消息發生覆蓋或溢出會造成消息的丟失，對于限時令牌網路，節點消息發送時間和消息緩沖容量的分配是影響消息實時性的重要因素.針對令牌傳遞網路分析了節點消息緩沖機制，說明了消息緩沖容量的確定與網路帶寬分配方法的關系，並提出了消息緩沖容量的確定方法，導出了避免消息覆蓋或溢出所需的最大發送和接收緩沖容量余度.指出在消息的產生間隔大於該消息的最大允許的延遲時間和接收節點響應時間的條件下，發送和接收端的消息緩沖容量等於被緩沖消息的長度In a network system, overflow or overwrite of message buffer will cause missing of messages. for a timed token network, message transmission time and the message buffering space allocation in a node are very important issues on network real time capability. this paper analyses the message buffering mechanism, describes the relationship of message buffering space and message transmission bandwidth allocation, and proposes a space determination method of message buffer for ltpb network. the maximum space redundancy avoiding buffer overflow for “ send ” and “ receive ” buffers has been derived. it is found that the space of “ send ” and “ receive ” buffers is equal to the message size under condition that the message gap time is greater than message latency and node response time
在網路系統中，節點緩沖區內消息發生覆蓋或溢出會造成消息的丟失，對于限時令牌網路，節點消息發送時間和消息緩沖容量的分配是影響消息實時性的重要因素.針對令牌傳遞網路分析了節點消息緩沖機制，說明了消息緩沖容量的確定與網路帶寬分配方法的關系，並提出了消息緩沖容量的確定方法，導出了避免消息覆蓋或溢出所需的最大發送和接收緩沖容量余度.指出在消息的產生間隔大於該消息的最大允許的延遲時間和接收節點響應時間的條件下，發送和接收端的消息緩沖容量等於被緩沖消息的長度Aiming at the condition of losing some delta points, we bring forward a new method of secondary fingerprint classification. by the new method, we can classify a nice bit of fingerprint images that cannot be classified by the former method
針對指紋圖像中常常丟失「三角點」的情況，我們又提出了一種對指紋圖像進行二次分類的方法，從而避免了相當一部分指紋圖像不能分類的情況。分享友人