• 제목/요약/키워드: U-coefficient

검색결과 764건 처리시간 0.027초

유한(有限)깊이의 물에서의 선체운동(船體運動) -선수선형(船首船型)의 영향(影響)- (The Effect of Forebody Forms on the Ship Motion in Water of Finite Depth)

  • 황종흘;이기표
    • 대한조선학회지
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    • 제13권1호
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    • pp.11-16
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    • 1976
  • The effect of the bow shape on the ship motion response in longitudinal regular waves of water of finite depth is investigated by employing the strip theory. The two-dimensional hydrodynamic forces(added mass and damping) were calculated by close-fit method for water of finite depth. The models for investigation are U and V bow ship forms of block coefficient 0.8 with constant after body which were used by Yourkov [2] and recently by Kim [3] for their deep water investigations. The following results are obtained by the present numerical experiments. (1) It is confirmed that the damping coefficient of the V-bow ship is greater than that of U-bow ship and in consquence the amplitude of heave and pitch of V-bow ship is smaller than that of U-bow ship among longitudinal regular head waves in water of finite depth (2) The merit of the V-bow ship on the motion damping is more significant in heave than in pitch, and is decreasing with the shallowness of water depth. (3) The change of bow form gives little effect on the wave exciting force and moment compared with the motion responce.

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Energy demand analysis according to window size and performance for Korean multi-family buildings

  • Huh, Jung-Ho;Mun, Sun-Hye
    • Architectural research
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    • 제15권4호
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    • pp.201-206
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    • 2013
  • Special attention is required for the design of windows due to their high thermal vulnerability. This paper examines the problems that might arise in the application of the u-value, by reflecting the changes in the u-value of the window, depending on the window-to-wall ratio obtained in an energy demand analysis. Research indicates that the u-value of a window increases with an increase in the difference between the u-values of the frames and the glass. Relative to the changes in the u-value of the windows, the energy demand varied from 1.3% to 9.3%. Windows with a g-value of 0.3 or 0.5 displayed a higher energy demand than windows with a g-value of 0.7. Therefore, when the difference between the performance of the glass and the frame is significant, especially when the g-value is small, a modified heat transmission coefficient should be applied to the window size during the evaluation of the building energy demand.

생체인식을 위한 Attention U-Net 기반 손금 추출 기법 (Attention U-Net Based Palm Line Segmentation for Biometrics)

  • 김인기;김범준;곽정환
    • 한국컴퓨터정보학회:학술대회논문집
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    • 한국컴퓨터정보학회 2022년도 제65차 동계학술대회논문집 30권1호
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    • pp.89-91
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    • 2022
  • 본 논문에서는 생체인식 수단 중 하나인 손금을 이용한 생체인식에서 Attention U-Net을 기반으로 손금을 추출하는 방법을 제안한다. 손바닥의 손금 중 주요선이라 불리는 생명선, 지능선, 감정선은 거의 변하지 않는 특징을 가지고 있다. 기존의 손금 추출 방법인 비슷한 색상에서 손금 추출, 제한된 Background에서 손금을 추출하는 것이 아닌 피부색과 비슷하거나, 다양한 Background에서 적용될 수 있다. 이를 통해 사용자를 인식하는 생체인식 방법에서 사용할 수 있다. 본 논문에서 사용된 Attention U-Net의 특징을 통해 손금의 Segmentation 영역을 Attention Coefficient를 업데이트하며 효율적으로 학습할 수 있음을 확인하였다.

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A FUNCTIONAL CENTRAL LIMIT THEOREM FOR MULTIVARIATE LINEAR PROCESS WITH POSITIVELY DEPENDENT RANDOM VECTORS

  • KO, MI-HWA;KIM, TAE-SUNG;KIM, HYUN-CHULL
    • 호남수학학술지
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    • 제27권2호
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    • pp.301-315
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    • 2005
  • Let $\{A_u,\;u=0,\;1,\;2,\;{\cdots}\}$ be a sequence of coefficient matrices such that ${\sum}_{u=0}^{\infty}{\parallel}A_u{\parallel}<{\infty}$ and ${\sum}_{u=0}^{\infty}\;A_u{\neq}O_{m{\times}m}$, where for any $m{\times}m(m{\geq}1)$, matrix $A=(a_{ij})$, ${\parallel}A{\parallel}={\sum}_{i=1}^m{\sum}_{j=1}^m{\mid}a_{ij}{\mid}$ and $O_{m{\times}m}$ denotes the $m{\times}m$ zero matrix. In this paper, a functional central limit theorem is derived for a stationary m-dimensional linear process ${\mathbb{X}}_t$ of the form ${\mathbb{X}_t}={\sum}_{u=0}^{\infty}A_u{\mathbb{Z}_{t-u}}$, where $\{\mathbb{Z}_t,\;t=0,\;{\pm}1,\;{\pm}2,\;{\cdots}\}$ is a stationary sequence of linearly positive quadrant dependent m-dimensional random vectors with $E({\mathbb{Z}_t})={{\mathbb{O}}$ and $E{\parallel}{\mathbb{Z}_t}{\parallel}^2<{\infty}$.

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SCM435 강의 고온마찰계수 계산 (Computation of High Temperature Friction Coefficient of SCM435 Steel)

  • 성중의;조상흠;이형직;이영석
    • 소성∙가공
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    • 제20권3호
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    • pp.243-249
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    • 2011
  • In this study, an approach designed to compute high temperature friction coefficients for SCM 435 steel through a pilot hot rolling test and a finite element analysis, is proposed. Single pass pilot hot flat rolling tests with reduction ratios varying from 20 to 40% were carried out at temperatures ranging from 900 to $1200^{\circ}C$. In the proposed approach, the friction coefficient is calculated by comparing the measured strip spread and the roll force with the simulation results. This study showed that the temperature and reduction ratio had a significant influence on the friction coefficient. As both material temperature and reduction ratio become higher, the friction coefficient increases monotonically. This finding is not in agreement with the Ekelund model, which is widely used in the analysis of the hot rolling process. In the present work, the friction coefficient at a reduction ratio of 40% was found to be 1.2 times greater than that at a reduction of 30%. This higher friction coefficient means that an increment of the roll thrust force is expected at the next stand. Therefore, a roll pass designer must understand this phenomenon in order to adjust the reduction ratio at the stands while keeping the driving power, the roll housing structure and the work roll strength within the allowable range.

효율적인 화상회의 동영상 압축을 위한 블록기반 얼굴 검출 방식 (A block-based face detection algorithm for the efficient video coding of a videophone)

  • 김기주;방경구;문정미;김재호
    • 한국통신학회논문지
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    • 제29권9C호
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    • pp.1258-1268
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    • 2004
  • 비디오화상회의 시스템을 위하여 동영상 압축 DCT 계수와 피부색정보를 이용하여 주파수 영역에서 정연 얼굴 을 실시간으로 검출하는 알고리즘을 제안한다. 동영상 압축과정 중에 얻어지는 DCT계수 값의 U 와 V 색상정보로 피부색 범위를 추출하며 잡음성분제거를 위해 형태학적필터와 Labeling을 적용하고 피부색블록의 방향성과 평탄도를 고려하여 검출하였다. 제안 알고리즘은, 배경에 피부색과 유사한 객체가 있는 경우와 배경이 단순한 경우에 대 해 적응적으로 검출이 가능하도록 하였다 여러 인종에 대한 모의실험결과 제안 알고리즘이 약 94% 의 검출 성공률을 보였다.

Effect of Outliers on Sample Correlation Coefficient

  • Kim, Chooongrak;Park, Byeong U.;Park, Kook L.;Whasoo Bae
    • Journal of the Korean Statistical Society
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    • 제29권3호
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    • pp.285-294
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    • 2000
  • In analyzing bivariate date the sample correlation coefficient is often used, and it is quite sensitive to one or few isolated cases. In this article we derive a formula for the effect of $textsc{k}$ observations on the samples correlation coefficient by the deletion method. To give a reference value for the isolated cases the asymptotic distribution fo the formula is derived. Also, we give some interpretations on several types of isolated cases and an example based on a real data set.

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투수성 폴리머 콘크리트의 성능 향상에 관한 실험적 연구 (An Experimental Study on Performance in Elevation of Porous Polymer Concrete)

  • 최규형;노병철;주명기;이복규
    • 한국콘크리트학회:학술대회논문집
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    • 한국콘크리트학회 2008년도 춘계 학술발표회 제20권1호
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    • pp.953-956
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    • 2008
  • 본 연구에서는 불포화폴리에스터 수지(U.P.)를 이용한 투수성 폴리머 콘크리트를 제조하여 투수성 및 강도 특성을 실험적으로 규명하였다. 그 결과 투수성 폴리머 콘크리트의 공극률 및 투수계수는 폴리머 결합재량의 증가에 따라 감소하는 경향을 나타내었다. 또한 투수성 폴리머 콘크리트의 압축강도는 폴리머 결합재량의 증가에 따라 감소하는 경향을 나타내었다. 투수성 폴리머 콘크리트의 압축강도는 투수계수가 증가함에 따라 감소하였다.

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SSResUnet 모델을 이용한 위성 영상 토지피복분류 (Land Cover Classification of Satellite Image using SSResUnet Model)

  • 강주형;김민성;김성진;곽수영
    • 전기전자학회논문지
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    • 제27권4호
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    • pp.456-463
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    • 2023
  • 본 논문에서는 사용자의 개입없이 고해상도 위성 영상을 활용하여 정밀한 토지피복분류를 위해 U-Net 네트워크 모델에 SPADE 구조를 결합한 SSResUNet 모델을 제안한다. 제안하는 네트워크는 위성 영상의 공간적 특성을 보존하여 복잡도가 높은 환경에서도 강인한 분류모델이라는 장점이 있다. 다목적실용위성 3A 영상을 통해 학습한 결과 기존 U-Net, U-Net++ 대비 뛰어난 결과를 보였으며 평균 IoU 76.10, Dice 86.22의 성능을 도출하였다.

Coefficient Estimates for Sãlãgean Type λ-bi-pseudo-starlike Functions

  • Joshi Santosh;Altinkaya, Sahsene;Yalcin, Sibel
    • Kyungpook Mathematical Journal
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    • 제57권4호
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    • pp.613-621
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    • 2017
  • In this paper, we have constructed subclasses of bi-univalent functions associated with ${\lambda}$-bi-pseudo-starlike functions in the unit disc U. Furthermore we established bound on the coefficients for the subclasses $S^{\lambda}_{\Sigma}(k,{\alpha})$ and $S^{\lambda}_{\Sigma}(k,{\beta})$.