• 한국소음진동공학회논문집
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• 제26권5호
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• pp.594-601
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• 2016

Mass estimation analysis of loose-parts in pressure vessel is necessary for the structural integrity assessment of pressure boundary in nuclear power plants. Mass of loose-parts can be generally estimated from the peak values and the center frequency of impact signals. Magnitude of impact signals is, however, inevitably attenuated according to the traveling distance of the signals and depending on the frequencies. Attenuation rate must be therefore carefully compensated for the precise estimation of loose-part mass. This paper proposes a new compensation method for the attenuation rate based on Bessel function instead of Hankel function in conventional method which has a limitation of usage in near the impact location. It was verified that the suggested compensating equation based on the Bessel function can be applied to the attenuation rate calculation without any limitation.

• 한국음향학회:학술대회논문집
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• 한국음향학회 1994년도 제11회 음성통신 및 신호처리 워크샵 논문집 (SCAS 11권 1호)
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• pp.133-137
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• 1994

In this paper, a method for designing an optimal weight function for the weighted cepstral distance measure is proposed. A conventional weight function or cepstral lifter is obtained eperimentally depending on the spectral components to be emphasized. The proposed method minimizes the error between word reference patterns and the traning data. To compare the proposed optimal weight function with conventional function, speech recognition systems based on Dpynamic Time Warping and Hidden Markov Models were constructed to conduct speaker independent isolated word necogination eperiment. Results show that the proposed method gives better performance than conventional weight functions.

• Journal of Forest and Environmental Science
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• 제33권4호
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• pp.305-314
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• 2017

This study aimed to predict changes in forest area using a probability density function, in order to promote effective forest management in the area north of the civilian control line (known as the Minbuk area) in Korea. Time series analysis (2010 and 2016) of forest area using land cover maps and accessibility expressed by distance covariates (distance from buildings, roads, and civilian control line) was applied to a probability density function. In order to estimate the probability density function, mean and variance were calculated using three methods: area weight (AW), area rate weight (ARW), and sample area change rate weight (SRW). Forest area increases in regions with lower accessibility (i.e., greater distance) from buildings and roads, but no relationship with accessibility from the civilian control line was found. Estimation of forest area change using different distance covariates shows that SRW using distance from buildings provides the most accurate estimation, with around 0.98-fold difference from actual forest area change, and performs well in a Chi-Square test. Furthermore, estimation of forest area until 2028 using SRW and distance from buildings most closely replicates patterns of actual forest area changes, suggesting that estimation of future change could be possible using this method. The method allows investigation of the current status of land cover in the Minbuk area, as well as predictions of future changes in forest area that could be utilized in forest management planning and policymaking in the northern area.

• 대한수학회보
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• 제54권2호
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• pp.507-519
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• 2017

We present an upper bound on the Cheeger constant of a distance-regular graph. Recently, the authors found an upper bound on the Cheeger constant of distance-regular graph under a certain restriction in their previous work. Our new bound in the current paper is much better than the previous bound, and it is a general bound with no restriction. We point out that our bound is explicitly computable by using the valencies and the intersection matrix of a distance-regular graph. As a major tool, we use the discrete Green's function, which is defined as the inverse of ${\beta}$-Laplacian for some positive real number ${\beta}$. We present some examples of distance-regular graphs, where we compute our upper bound on their Cheeger constants.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제12권2호
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• pp.143-148
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• 2012

This paper proposes a new method to improve performance of AdaBoost by using a distance weight function to increase the accuracy of its machine learning processes. The proposed distance weight algorithm improves classification in areas where the original binary classifier is weak. This paper derives the new algorithm's optimal solution, and it demonstrates how classifier accuracy can be improved using the proposed Distance Sensitive AdaBoost in a simulation experiment of pedestrian detection.

• Journal of the Optical Society of Korea
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• 제18권2호
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• pp.110-117
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• 2014

In this study, we objectively determined whether the ReSTOR as a multifocal IOL (intraocular lens) has a multifocal function compared to the IQ as a monofocal IOL in vivo by OQAS (Optical Quality Analysis System). Eighteen patients who had cataract surgery with implantation of ReSTOR (27 eyes) and 15 patients with IQ (21 eyes), were included inthis study. Uncorrected distance visual acuity (UCDVA), corrected distance visual acuity (CDVA), uncorrected near visual acuity (UCNVA)and distance corrected near visual acuity (DCNVA) were measured. After setting the artificial pupil size to 3 mm, we performed 'Optical quality'. We inputted defocus diopters of (objective spherical refraction)(far), (objective spherical refraction-1.25 D)(intermediate),(objective spherical refraction-2.5 D)(near), and (objective spherical refraction-3.5 D)(very near) into 'selected spherical refraction' simulating the optical quality at far, intermediate, and near distance. We changed the pupil size to 5 mm and repeated the same measurements. The UCDVA and CDVA did not show significant differences between the 2 groups. But, the UCNVA and DCNVA of the ReSTOR group were better than those of the IQ group (p=0.000, p=0.000). For 3 mm pupil, at far distance, modulation transfer function (MTF) cut off and point spread function (PSF) width at 50% of ReSTOR were worse than those of IQ (p=0.039, p=0.020). At intermediate distance, MTF cut off, Strehl ratio and PSF width at 50% of ReSTOR were worse than those of IQ (p=0.001, p=0.001, p=0.000). At near distance, MTF cut off of ReSTOR was worse than that of IQ (p=0.033). At very near distance, MTF cut off and Strehl ratio of ReSTOR were worse than those of IQ (p=0.002, p=0.002), but PSF width at 50% of ReSTOR was better than that of IQ. For 5 mm pupil, most parameters at each distance, there was no significant difference between the 2 groups. Only PSF width at 50% of ReSTOR were worse than those of IQ at intermediate distance (p=0.013). It was impossible to show the multifocal function of ReSTOR compared to the IQ byOQAS.

• 제어로봇시스템학회논문지
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• 제3권2호
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• pp.169-178
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• 1997

This paper presents a new solution approach to moving obstacle avoidance problem of a robot. A new concept, avoidability measure(AVM) is defined to describe the state of a pair of a robot and an obstacle regarding the collision between them. As an AVM, virtual distance function(VDF) is derived as a function of three state variables: the distance from the obstacle to the robot, outward speed of the obstacle relative to the robot, and outward speed of the robot relative to the obstacle. By keeping the virtual distance above some positive limit value, the robot avoids the obstacle. In terms of the VDF, an artificial potential is constructed to repel the robot away from the obstacle and to attract the robot toward a goal location. At every sampling time, the artificial potential field is updated and the force driving the robot is derived from the gradient of the artificial potential field. The suggested algorithm drives the robot to avoid a moving obstacle in real time. Since the algorithm considers the mobility of the obstacle and robot as well as the distance, it is effective for moving obstacle avoidance. Some simulation studies show the effectiveness of the proposed approach.

• 도시과학
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• 제11권2호
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• pp.9-17
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• 2022

The purpose of this study is to develop an index for evaluating the function of a new motorway using the travel distance frequency distribution (TLFD) calculated using the vehicle travel route big data, and to overcome the limitations of the evaluation through the existing traffic volume. The mobility evaluation index of motorways was developed by applying it to the TLFD data table in 2019. The smaller the value of the mobility evaluation index of the link is calculated, the more it is a link with mainly short-distance travel, and the higher the value of the mobility evaluation index, the more it means a link with mainly long-distance travel. The accessibility evaluation index was calculated through the result of the mobility evaluation index of all motorways developed, and all motorways were grouped into three groups using K-means clustering. Group A was found to exist inside a large city and consisted of motorways with many short-distance traffic, Group B was investigated as acting as an arterial between groups, and Group C was classified as a motorway consisting mainly of long-distance traffic connecting large cities and large cities. This study is significant in developing a new motorway function evaluation index that can overcome the limitations of motorway function evaluation through the existing traffic volume. It is expected that this study can be a reasonable comprehensive indicator in the operation and planning process of motorways.

• 전기학회논문지
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• 제66권6호
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• pp.935-941
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• 2017

This paper proposes a method for estimating the distance betweeen vehicles in a moving situation using the image ratio of the distance between the tail lamps of a front vehicle. The actual distance between the tail lamps of a front vehicle was transmitted by LED tail lamps using visible light communication. As the distance between the front vehicle and the rear vehicle changes, it calculates the ratio of the pixel width between the tail lamps of the front vehicle projected on the image. The calculated values are used to derive a distance-mapping function through non-linear regression technique. Then, the distance between vehicles in the moving situation is estimated based on this function.

• 한국산업정보학회논문지
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• 제14권5호
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• pp.43-51
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• 2009

본 논문에서는 PCA(principal component analysis)기반의 특징을 이용한 효율적인 얼굴검색 방법을 제안한다. coarse-to-fine 전략을 사용하여 저차원 고유얼굴 공간에서 검색 결과들을 1차 정렬한 후 상위 후보들을 확장된 차원의 고유얼굴 공간에서 재정렬하는 방식으로 검색 순위를 재조정한다. 질의 영상과 클래스간의 유사도의 측정을 위해 PD(projection distance), MQDF(modified quadratic distance function), MED(minimum Euclidean distance)를 사용한다. 실험 결과 $32{\times}32$ 크기의 질의 영상에 PD를 활용하여 점진적으로 검색 결과를 조정하는 제안하는 방법이 얼굴검색에 효율적임을 알 수 있었다.