• Communications for Statistical Applications and Methods
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• 제27권6호
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• pp.625-639
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• 2020

The gamma distribution is a flexible right-skewed distribution widely used in many areas, and it is of great interest to estimate the probability of a random variable exceeding a specified value in survival and reliability analysis. Therefore, the study develops a fixed-accuracy confidence interval for P(X > c) when X follows a gamma distribution, Γ(α, β), and c is a preassigned positive constant through: 1) a purely sequential procedure with known shape parameter α and unknown rate parameter β; and 2) a nonparametric purely sequential procedure with both shape and rate parameters unknown. Both procedures enjoy appealing asymptotic first-order efficiency and asymptotic consistency properties. Extensive simulations validate the theoretical findings. Three real-life data examples from health studies and steel manufacturing study are discussed to illustrate the practical applicability of both procedures.

• 대한수학회지
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• 제44권2호
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• pp.261-273
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• 2007

In this paper, we introduce some new properties of a topological space which are respectively generalizations of $Fr\'{e}chet$-Urysohn property. We show that countably AP property is a sufficient condition for a space being countable tightness, sequential, weakly first countable and symmetrizable, to be ACP, $Fr\'{e}chet-Urysohn$, first countable and semimetrizable, respectively. We also prove that countable compactness is a sufficient condition for a countably AP space to be countably $Fr\'{e}chet-Urysohn$. We then show that a countably compact space satisfying one of the properties mentioned here is sequentially compact. And we show that a countably compact and countably AP space is maximal countably compact if and only if it is $Fr\'{e}chet-Urysohn$. We finally obtain a sufficient condition for the ACP closure operator $[{\cdot}]_{ACP}$ to be a Kuratowski topological closure operator and related results.

• 대한수학회논문집
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• 제38권1호
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• pp.267-280
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• 2023

In this article, we show that the family of all 𝓘^𝒦-open subsets in a topological space forms a topology if 𝒦 is a maximal ideal. We introduce the notion of 𝓘^𝒦-covering map and investigate some basic properties. The notion of quotient map is studied in the context of 𝓘^𝒦-convergence and the relationship between 𝓘^𝒦-continuity and 𝓘^𝒦-quotient map is established. We show that for a maximal ideal 𝒦, the properties of continuity and preserving 𝓘^𝒦-convergence of a function defined on X coincide if and only if X is an 𝓘^𝒦-sequential space.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.383-388
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• 2005

Depth recovery in robot vision is an essential problem to infer the three dimensional geometry of scenes from a sequence of the two dimensional images. In the past, many studies have been proposed for the depth estimation such as stereopsis, motion parallax and blurring phenomena. Among cues for depth estimation, depth from lens translation is based on shape from motion by using feature points. This approach is derived from the correspondence of feature points detected in images and performs the depth estimation that uses information on the motion of feature points. The approaches using motion vectors suffer from the occlusion or missing part problem, and the image blur is ignored in the feature point detection. This paper presents a novel approach to the defocus technique based depth from lens translation using sequential SVD factorization. Solving such the problems requires modeling of mutual relationship between the light and optics until reaching the image plane. For this mutuality, we first discuss the optical properties of a camera system, because the image blur varies according to camera parameter settings. The camera system accounts for the camera model integrating a thin lens based camera model to explain the light and optical properties and a perspective projection camera model to explain the depth from lens translation. Then, depth from lens translation is proposed to use the feature points detected in edges of the image blur. The feature points contain the depth information derived from an amount of blur of width. The shape and motion can be estimated from the motion of feature points. This method uses the sequential SVD factorization to represent the orthogonal matrices that are singular value decomposition. Some experiments have been performed with a sequence of real and synthetic images comparing the presented method with the depth from lens translation. Experimental results have demonstrated the validity and shown the applicability of the proposed method to the depth estimation.

• 한국터널지하공간학회 논문집
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• 제10권2호
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• pp.177-184
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• 2008

본 연구에서는 발파 진동 및 소음에 관한 문제를 최소화하기 위해 발파진동 파형합성과 발파 시뮬레이션을 통해 진동을 최소화시킬 수 있는 전자뇌관의 최적초시를 찾고, 또한 전단면 분할 발파의 감쇄특성에 대한 연구를 토대로 하여 전단면 다단시차 분할 발파기법을 개발하였다. 경부고속철도 OO공구 수직구 시공현장에서 전자뇌관을 이용한 파형합성 최적초시적용과 전단면 다단시차 분할발파를 동시에 수행하는 발파기법을 현장에 적용함으로써 그 타당성을 검토하였다.

• 전자공학회논문지S
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• 제35S권3호
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• pp.176-184
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• 1998

We present a sequential factorization method using singular value decomposition (SVD) for recovering both the three-dimensional shape of an object and the motion of camera from a sequence of images. We employ paraperpective projection [6] for camera model to handle significant translational motion toward the camera or across the image. The proposed mthod not only quickly gives robust and accurate results, but also provides results at each frame becauseit is a sequential method. These properties make our method practically applicable to real time applications. Considerable research has been devoted to the problem of recovering motion and shape of object from image [2] [3] [4] [5] [6] [7] [8] [9]. Among many different approaches, we adopt a factorization method using SVD because of its robustness and computational efficiency. The factorization method based on batch-type computation, originally proposed by Tomasi and Kanade [1] proposed the feature trajectory information using singular value decomposition (SVD). Morita and Kanade [10] have extenened [1] to asequential type solution. However, Both methods used an orthographic projection and they cannot be applied to image sequences containing significant translational motion toward the camera or across the image. Poleman and Kanade [11] have developed a batch-type factorization method using paraperspective camera model is a sueful technique, the method cannot be employed for real-time applications because it is based on batch-type computation. This work presents a sequential factorization methodusing SVD for paraperspective projection. Initial experimental results show that the performance of our method is almost equivalent to that of [11] although it is sequential.

• Korean Journal of Mathematics
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• 제5권2호
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• pp.227-232
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• 1997

Banach-Steinhaus type results are established for sequentially continuous operators and bounded operators between locally convex spaces without barrelledness.

• Smart Structures and Systems
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• 제21권5호
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• pp.601-609
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• 2018

The estimated probabilistic model of wind data based on the conventional approach may have high discrepancy compared with the true distribution because of the uncertainty caused by the instrument error and limited monitoring data. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method has been developed in the companion paper and is conducted to formulate the joint probability density function (PDF) of wind speed and direction using the wind monitoring data of the investigated bridge. The established bivariate model of wind speed and direction only represents the features of available wind monitoring data. To characterize the stochastic properties of the wind parameters with the subsequent wind monitoring data, in this study, Bayesian inference approach considering the uncertainty is proposed to update the wind parameters in the bivariate probabilistic model. The slice sampling algorithm of Markov chain Monte Carlo (MCMC) method is applied to establish the multi-dimensional and complex posterior distribution which is analytically intractable. The numerical simulation examples for univariate and bivariate models are carried out to verify the effectiveness of the proposed method. In addition, the proposed Bayesian inference approach is used to update and optimize the parameters in the bivariate model using the wind monitoring data from the investigated bridge. The results indicate that the proposed Bayesian inference approach is feasible and can be employed to predict the bivariate distribution of wind speed and direction with limited monitoring data.

• 한국측량학회지
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• 제28권2호
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• pp.233-237
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• 2010

The recent advance of sensor networks and ubiquitous techniques allow collecting and analyzing of the data which overcome the limitation imposed by time and space in real-time for making decisions. Also, analysis and prediction of collected data can support useful and necessary information to users. The collected data in sensor networks environment is the stream data which has continuous, unlimited and sequential properties. Because of the continuous, unlimited and large volume properties of stream data, managing stream data is difficult. And the stream data needs dynamic processing method because of the memory constraint and access limitation. Accordingly, we analyze correlation stream data using principal component analysis. And using result of analysis, it helps users for making decisions.

• 대한토목학회논문집
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• 제33권5호
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• pp.1797-1807
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• 2013

예상하지 못한 자연 현상으로 인해 붕괴될 가능성을 항상 내포하고 있으며 특히 댐 하류부 지역이 인구밀집 지역이거나 중요 국가 시설물이 위치하고 있는 경우에는 인명 및 재산피해 등 막대한 손실을 초래할 수 있다. 지금까지의 연구는 단독댐 붕괴에 따른 홍수파 해석에 대한 연구는 많이 있었으나 세계적으로 유명한 테네시강 등의 순차적 댐이나 우리나라의 북한강 상류로부터 연속으로 이어진 댐 등에 대한 붕괴 홍수파 해석에 대한 연구는 미흡한 실정이다. 따라서 본 연구의 목적은 순차적 댐 붕괴 홍수파 해석을 통해 순차적 댐 붕괴 첨두유량을 계산하고 하류부에서의 홍수파 전파상황을 예측할 수 있는 해석기법을 제시하는데 있다. 이를 위해 DAMBRK를 이용하여 실제 붕괴 사례 중 순차적 댐 붕괴 사례인 Lawn Lake Dam에 대하여 붕괴 홍수파 해석을 실시하여 댐 붕괴 홍수파 해석 모형의 적절성을 검증하였다. 이를 기초로 하여 가상의 극한홍수에 대하여 국내의 A 댐에 대하여 순차적 댐 붕괴 홍수파 해석을 실시하여 홍수파 전파상황을 예측하였으며, 범람 중요 지점에 대하여 2차원 홍수범람해석을 수행하여 1 2차원 홍수파 해석을 비교 분석한 결과 적합도가 90%를 상회하여 1차원 순차적 댐 붕괴 모의의 정확성을 확인할 수 있었다. 이는 순차적 댐 붕괴와 관련된 하천에서의 방재대책 수립을 위한 기본자료를 제공하는데 기여할 수 있을 것으로 판단된다.