• 천문학회보
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• 제36권2호
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• pp.103.2-103.2
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• 2011

We measure the degree of polarization of the lunar regolith to map the distributions of the age and the particle size. We use a 12cm refracting telescope with a 2k-square pixel color CCD (R band) and a polarization filter. The angular resolution obtained is 3.02 km/pixel. Our goal is to obtain a map of the lunar particle size distribution on the lunar regolith and then that of the age distribution. Polarization of the light scattered by lunar surface contains information on their mean particle size. The mean particle size of the lunar surface has been decreased by continued micro-meteoroid impact over a long period. One can estimate the age of the lunar surface if the mean particle size is known. Particle sizes can be measured through observations of polarization because the mean particle size is related to the maximum polarization and albedo. The age and the particle size of the lunar regolith can give vital information for the future lunar exploration.

• 한국멀티미디어학회논문지
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• 제25권9호
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• pp.1266-1272
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• 2022

With the recent development of computer vision technology, image processing-based mechanical devices are being developed to realize autonomous driving. The camera-taken images of image processing-based machines are invisible due to scattering and absorption of light in foggy conditions. This lowers the object recognition rate and causes malfunction. The safety of the technology is very important because the malfunction of autonomous driving leads to human casualties. In order to increase the stability of the technology, it is necessary to apply an efficient haze removal algorithm to the camera. In the conventional haze removal method, since the haze removal operation is performed regardless of the haze concentration of the input image, excessive haze is removed and the quality of the resulting image is deteriorated. In this paper, we propose an automatic haze removal method that removes haze according to the haze density of the input image by applying Ngo's Haziness Degree Evaluator (HDE) to Kim's haze removal algorithm using Hazy Particle Map. The proposed haze removal method removes the haze according to the haze concentration of the input image, thereby preventing the quality degradation of the input image that does not require haze removal and solving the problem of excessive haze removal. The superiority of the proposed haze removal method is verified through qualitative and quantitative evaluation.

• 제어로봇시스템학회논문지
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• 제22권10호
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• pp.803-810
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• 2016

This paper presents a study of localization methods based on particle filter using 2D laser sensor measurements and road feature map information, for autonomous vehicles. In order to navigate in an urban environment, an autonomous vehicle should be able to estimate the location of the ego-vehicle with reasonable accuracy. In this study, road features such as curbs and road markings are detected to construct a grid-based feature map using 2D laser range finder measurements. Then, we describe a particle filter-based method for accurate positional estimation of the autonomous vehicle in real-time. Finally, the performance of the proposed method is verified through real road driving experiments, in comparison with accurate DGPS data as a reference.

• 대한임베디드공학회논문지
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• 제3권2호
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• pp.109-118
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• 2008

We present a robust localization algorithm using particle filter for mobile robots in a dynamic environment. It is difficult to describe moving obstacles like people or other robots on the map and the environment is changed after mapping. A mobile robot cannot estimate its pose robustly with this incomplete map because sensor observations are corrupted by un-modeled obstacles. The proposed algorithms provide robustness in such a dynamic environment by suppressing the effect of corrupted sensor observations with a selective update or a sampling from non-corrupted window. A selective update method makes some particles keep track of the robot, not affected by the corrupted observation. In a sampling from non-corrupted window method, particles are always sampled from several particle sets which use only non-corrupted observation. The robustness of proposed algorithm is validated with experiments and simulations.

• 한국정밀공학회지
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• 제30권3호
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• pp.308-316
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• 2013

This paper proposes an observation model for a particle filter-based localization using a sonar grid map. The proposed model estimates a predicted observation by considering the properties of a sonar sensor which has a large angular uncertainty. The proposed model searches a grid which has the highest probability to reflect a sonar beam using the following procedures; (1) the reliable area of a single sonar data is determined using the footprint association model; (2) the detection probability of each grid cell in a sonar beam coverage in estimated. The proposed model was applied to the particle filter based localization, and was verified by experiments in indoor environments.

• Journal of Information Processing Systems
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• 제18권3호
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• pp.332-343
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• 2022

To address the problems of the gravitational search algorithm (GSA) in which the population is prone to converge prematurely and fall into the local solution when solving the single-objective optimization problem, a sine map jumping gravity search algorithm based on asynchronous learning is proposed. First, a learning mechanism is introduced into the GSA. The agents keep learning from the excellent agents of the population while they are evolving, thus maintaining the memory and sharing of evolution information, addressing the algorithm's shortcoming in evolution that particle information depends on the current position information only, improving the diversity of the population, and avoiding premature convergence. Second, the sine function is used to map the change of the particle velocity into the position probability to improve the convergence accuracy. Third, the Levy flight strategy is introduced to prevent particles from falling into the local optimization. Finally, the proposed algorithm and other intelligent algorithms are simulated on 18 benchmark functions. The simulation results show that the proposed algorithm achieved improved the better performance.

• 한국컴퓨터그래픽스학회논문지
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• 제14권4호
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• pp.7-18
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• 2008

연기와 같은 유체의 모습을 영화나 애니메이션에서의 특수 효과에 활용하기 위해는 연기를 사실적으로 모델링하는 과정과 모델링 된 연기 내부에서의 빛의 흐름이 잘 반영된 렌더링 과정이 필요하다. 컴퓨터 그래픽스 분야에서는 연기 모델링의 사실성을 살리기 위해 물리 기반의 유체 시뮬레이션 기법을 많이 차용하고 있는데, 그동안 시뮬레이션 기법으로 주로 연구되어 온, 격자 기반의 Euler 방법과는 근본적으로 다른, 파티클 기반의 Lagrange 방법이 시뮬레이션 단계에서 얻을 수 있는 장점 때문에 최근 관심이 높아지고 있다. 연기 렌더링은 연기 모델링 방법에 종속적일 수밖에 없으므로, 결과적으로 격자 기반의 시뮬레이션 결과에 대한 렌더링 방법은 많이 연구되고 있는 데 비해, 파티클 형태로 산출된 연기 데이터에 대하여 사실적인 영상을 생성해주는 랜더링 기술에 대한 연구는 아직 부족한 상황이다. 이에, 본 논문에서는 Lagrange 기법을 적용하여 생성한 파티클 집합 형태의 연기 시뮬레이션 데이터를 사실적으로 렌더링하기 위해, 전역 조영을 위한 최신 랜더링 기술인 포톤 매핑 기법을 파티클 데이터에 맞게 변형 및 확장한 파티클맵 기법을 소개하고, 개선된 파티클템 기법을 제시하여, 기존 연구와의 차이점을 보여준다. 또한 렌더링 과정에서 효율성을 높이기 위해 볼륨 렌더링 방정식의 다중 산란 항을 미리 계산하는 광도맵이라는 방법을 제시한다.

• 천문학회보
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• 제40권1호
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• pp.62.1-62.1
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• 2015

Polarization of the light reflected off the Moon provides information on the size and composition of the particles in the lunar regolith. The mean particle size of the regolith can be estimated from the combination of the albedo and degree of polarization, while the color ratio of the parallel-component polarization (CP) has been suggested to be related to the amount of nanophase metallic iron (npFe^0) inside the regolith particles. Both the mean size and npFe^0 abundance of the particles have been used as maturity indicators of the regolith since sustained impacts of high energy particles and micro-meteoroids cause comminution of particles and production of npFe^0. Based on our multispectral polarimetric observations of the whole near side of the Moon in the U, B, V, R, and I bands, we compare the maps of the mean particle size, CP, and the optical maturity (OM). We find that the mean particle size map is sensitive to the most immature (~0.1 Gyr) soil, the OP map to the intermediate immaturity (a few 0.1 Gyr) soil, and the CP map to the least immature (~1 Gyr) soil.

• 한국분말야금학회:학술대회논문집
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• 한국분말야금학회 2006년도 Extended Abstracts of 2006 POWDER METALLURGY World Congress Part2
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• pp.704-705
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• 2006

Discrete element analysis is used to map various log-normal particle size distributions into measures of the in-sphere pore size distribution. Combinations evaluated range from monosized spheres to include bimodal mixtures and various log-normal distributions. The latter proves most useful in providing a mapping of one distribution into the other (knowing the particle size distribution we want to predict the pore size distribution). Such metrics show predictions where the presence of large pores is anticipated that need to be avoided to ensure high sintered properties.

• 로봇학회논문지
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• 제9권2호
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• pp.96-103
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• 2014

Global localization is one of the essential issues for mobile robot navigation. In this study, an indoor global localization method is proposed which uses a Kinect sensor and a monocular upward-looking camera. The proposed method generates an environment map which consists of a grid map, a ceiling feature map from the upward-looking camera, and a spatial feature map obtained from the Kinect sensor. The method selects robot pose candidates using the spatial feature map and updates sample poses by particle filter based on the grid map. Localization success is determined by calculating the matching error from the ceiling feature map. In various experiments, the proposed method achieved a position accuracy of 0.12m and a position update speed of 10.4s, which is robust enough for real-world applications.