• 정보과학회 컴퓨팅의 실제 논문지
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• 제21권1호
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• pp.94-99
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• 2015

비모수 베이스 통계학, 확률적 표집에 기반한 추론 등이 기계학습의 주요 패러다임으로 등장하면서 디리슐레(Dirichlet) 분포는 최근 다양한 그래프 모형 곳곳에 등장하고 있다. 디리슐레 분포는 일변수 감마 분포를 벡터 분포로 확장한 형태의 하나이다. 본 논문에서는 감마 분포를 갖는 임의의 자연수 X를 K개의 자연수의 합으로 임의 분할 할 때 각 부분의 크기 비율을 디리슐레 분포에서 표집하는 방법을 제안한다. 일반적으로 디리슐레 분포는 연속적인 (K-1)-단체(simplex) 위에 정의 되지만 자연수로 분할하는 표본은 자연수라는 조건 때문에 단체 내부의 이산 그리드 점에만 정의된다. 본 논문에서는 단체 위의 그리드 상의 이웃 점들의 확률 분포로부터 마르코프연쇄 몬테 칼로(MCMC) 제안 분포를 정의하고 일련의 표본들의 마르코프 연쇄를 구현하는 알고리듬을 제안한다. 본 방법은 마르코프 모델, HMM 및 준-HMM 등에서 각 상태별 시간 지속 분포를 표현하는데 활용 가능하다. 나아가 최근 제안된 전역-지역(global-local) 상태지속 분포를 동시에 모형화하는 감마-디리슐레 HMM에도 응용가능하다.

• Journal of Computational Design and Engineering
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• 제1권4호
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• pp.223-232
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• 2014

This paper describes a variant of the extended Gaussian image based registration algorithm for point clouds with surface color information. The method correlates the distributions of surface normals for rotational alignment and grid occupancy for translational alignment with hue filters applied during the construction of surface normal histograms and occupancy grids. In this method, the size of the point cloud is reduced with a hue-based down sampling that is independent of the point sample density or local geometry. Experimental results show that use of the hue filters increases the registration speed and improves the registration accuracy. Coarse rigid transformations determined in this step enable fine alignment with dense, unfiltered point clouds or using Iterative Common Point (ICP) alignment techniques.

• 소성∙가공
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• 제29권4호
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• pp.218-228
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• 2020

The prediction of final mass and optimized process conditions of injection molded products using Artificial Neural Network (ANN) were demonstrated. The ANN was modeled with 10 input parameters and one output parameter (mass). The input parameters, i.e.; melt temperature, mold temperature, injection speed, packing pressure, packing time, cooling time, back pressure, plastification speed, V/P switchover, and suck back were selected. To generate training data for the ANN model, 77 experiments based on the combination of orthogonal sampling and random sampling were performed. The collected training data were normalized to eliminate scale differences between factors to improve the prediction performance of the ANN model. Grid search and random search method were used to find the optimized hyper-parameter of the ANN model. After the training of ANN model, optimized process conditions that satisfied the target mass of 41.14 g were predicted. The predicted process conditions were verified through actual injection molding experiments. Through the verification, it was found that the average deviation in the optimized conditions was 0.15±0.07 g. This value confirms that our proposed procedure can successfully predict the optimized process conditions for the target mass of injection molded products.

• 한국기후변화학회지
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• 제8권4호
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• pp.329-337
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• 2017

In this study, land-use changes from 1990 to 2010 in Jeju Island by different approaches were produced and compared to suggest a more efficient approach. In a sample-based method, land-use changes were analyzed with different sampling intensities of 2 km and 4 km grids, which were distributed by the fifth National Forest Inventory (NFI5), and their uncertainty was assessed. When comparing the uncertainty for different sampling intensities, the one with the grid of 2 km provided more precise information; ranged from 6.6 to 31.3% of the relative standard error for remaining land-use categories for 20 years. On the other hand, land-cover maps by a wall-to-wall approach were produced by using time-series Landsat imageries. Forest land increased from 34,194 ha to 44,154 ha for 20 years, where about 69% of total forest land were remained as forest land and 19% and 8% within forest lands were converted to grassland and cropland, respectively. In the case of grassland, only about 40% of which were remained as grassland and most of the area were converted to forest land and cropland. When comparing land-cover area by land-use categories with land-use statistics, forest areas were underestimated while areas of cropland and grassland were overestimated. In order to analyze land use change, it is necessary to establish a clear and consistent definition on the six land use classification.

• Journal of Power Electronics
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• 제16권2호
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• pp.717-730
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• 2016

The harmonic components of grid voltage result in oscillations of the calculated phase obtained via phase synchronization. This affects the security and stability of grid-connected converters. Moving average filter, delayed signal cancellation and their related harmonic elimination algorithms are major methods for such issues. However, all of the existing methods have their limitations in dealing with multiple harmonics issues. Furthermore, few studies have focused on a comparison and evaluation of these algorithms to achieve optimal algorithm selections in specific applications. In this paper, these algorithms are quantitatively analyzed based on the derived mathematical models. Moreover, an enhanced moving average filter and enhanced delayed signal cancellation algorithms, which are applicable for eliminating a group of selective harmonics with only one calculation block, are proposed. On this basis, both a comprehensive comparison and a quantitative evaluation of all of the aforementioned algorithms are made from several aspects, including response speed, required data storage size, sensitivity to sampling frequency, and elimination of random noise and harmonics. With the conclusions derived in this paper, better overall performance in terms of harmonic elimination can be achieved. In addition, experimental results under different conditions demonstrate the validity of this study.

• 로봇학회논문지
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• 제18권3호
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• pp.337-345
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• 2023

In this paper, we propose a 3D LiDAR sensor-based costmap generation and path planning algorithm using it for reliable autonomous flight in complex indoor environments. 3D path planning is essential for reliable operation of UAVs. However, existing grid search-based or random sampling-based path planning algorithms in 3D space require a large amount of computation, and UAVs with weight constraints require reliable path planning results in real time. To solve this problem, we propose a method that divides a 3D space into several 2D spaces and a path planning algorithm that considers the distance to obstacles within each space. Among the paths generated in each space, the final path (Best path) that the UAV will follow is determined through the proposed objective function, and for this purpose, we consider the rotation angle of the 2D space, the path length, and the previous best path information. The proposed methods have been verified through autonomous flight of UAVs in real environments, and shows reliable obstacle avoidance performance in various complex environments.

• 환경생물
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• 제39권4호
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• pp.526-535
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• 2021

공간 샘플링은 공간모델링 연구에 활용되어 샘플링 비용을 줄이면서 모델링의 효율성을 높이는 역할을 한다. 농업분야에서는 기후변화 영향을 예측하고 평가하기 위한 고해상도 공간자료 기반 모델링에 대한 연구 수요가 빠르게 증가하고 있으며, 이에 따라 공간 샘플링의 필요성과 중요성이 증가하고 있다. 본 연구는 국내 농지 공간샘플링 연구를 통해 농업분야 기후변화연구의 공간자료 활용의 효율성을 제고하고자 하였다. 본 연구는 층화랜덤샘플링을 기반으로 하였으며, 1 km 해상도의 농지 공간격자자료 모집단(11,386개 격자)에 대해서 RCP 시나리오별(RCP 4.5/8.5) 연대별(2030/2050/2080년대) 공간샘플링을 설계하였다. 국내 농지는 기상 및 토양 특성에 따라 계층화 되었으며, 샘플링 효율 극대화를 위해 최적 층화 및 샘플 배정 최적화를 수행하였다. 최적화는 작물수량, 온실가스 배출량, 해충 분포 확률을 포함하는 16개 목표 변수에 대해 주어진 정밀도 제한 내에서 샘플 수를 최소화하는 방향으로 진행되었다. 샘플링의 정밀도와 정확도 평가는 각각 변동계수(CV)와 상대적 편향을 기반으로 하였다. 국내 농지 공간격자 모집단 계층화 및 샘플 배정 및 샘플 수 최적화 결과, 전체 농지는 5~21개 계층, 46~69개 샘플 수 수준에서 최적화되었다. 본 연구결과물들은 국내 농업시스템 대표 공간격자로써 널리 활용될 수 있을 것으로 기대된다. 또한, 기후변화 영향예측 공간모델링 연구들에 활용되어 샘플링 비용 및 계산 시간을 줄이면서도 모델의 효율성을 높이는 데에 기여할 수 있다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.156-161
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• 2003

It is an interest problem to predict substance distributions in three-dimensional space. Recently, a research field as Geostatistics is advanced. It is a kind of inter- or extrapolation mathematically. Some useful means for the inter- and extrapolation are known, in which slide window method with neural networks is hopeful one. We propose multi-dimensional extrapolation using multi-layer neural networks and the slide-window method. The multi-dimensional extrapolation is not similar to one-dimension. It has plural algorithms. We researched line predictors and local-plain predictors I two-dimensional space. The both predictors are equivalent; however, in multi-dimensional extrapolation, it is very important to find the direction of predictions. Especially, since the slide window method requires information to predict the future in sampling data, if they are not ordered appropriately in the direction, the predictor cannot operate. We tested the extrapolation for typical two-dimensional functions, and found an excellent character of slide-window method based on local-plain. By using the method, we can extrapolate the function until twice-outer regions of the definitions.

• 한국대기환경학회지
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• 제13권6호
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• pp.463-474
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• 1997

Metallic elements in dustfall have been known as notable air pollutants directly or indirectly influencing human health and wealth. The first aim of this study was to obtain precise spatial distribution patterns of 5 elements (Pb, Zn, K, Cr, and Al) in dustfall around Suwon area. To predict isometric lines of metal fluxes deposited on unsupervised random sites, the study has applied both spatial statistics as a receptor model and a GIS (geographic information system). Total of 31 sampling sites were selected in the study area (roughly 3 by 3 km grid basis) and dustfall samples were then collected monthly basis by the British deposit gauges from Dec., 1995 to Nov., 1996. The metallic elements in the dustfall were then analyzed by an atomic absorption spectrometer (AAS). On the other hand, a base map overlapped by 7 layers was constructed by using the AutoCAD R13 and ARC/INFO 3.4D. Four different spatial interpolation and expolation techniques such as IDW (inverse distance weighted averaging), TIN (triangulated irregular network), polynomial regression, and kriging technique were examined to compare spatial distribution patterns. Each pattern obtained by each technique was substantally different as varing pollutant types, land of use types, and topological conditions, etc. Thus, our study focused intensively on uncertainty analysis based on a concept of the jackknife and the sum of error distance. It was found that a kriging technique was the best applicalbe in this study area.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권11호
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• pp.2068-2086
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• 2011

Based on the quincunx sub-sampling grid, the New Interleaved Hierarchical INTerpolation (NIHINT) method is recognized as a superior pyramid data structure for the lossless and progressive coding of natural images. In this paper, we propose a new image interpolation algorithm, Edge Adaptive Hierarchical INTerpolation (EAHINT), for a further reduction in the entropy of interpolation errors. We compute the local variance of the causal context to model the strength of a local edge around a target pixel and then apply three statistical decision rules to classify the local edge into a strong edge, a weak edge, or a medium edge. According to these local edge types, we apply an interpolation method to the target pixel using a one-directional interpolator for a strong edge, a multi-directional adaptive weighting interpolator for a medium edge, or a non-directional static weighting linear interpolator for a weak edge. Experimental results show that the proposed algorithm achieves a better compression bit rate than the NIHINT method for lossless image coding. It is shown that the compression bit rate is much better for images that are rich in directional edges and textures. Our algorithm also shows better rate-distortion performance and visual quality for progressive image transmission.