• Journal of Information Processing Systems
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• 제6권1호
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• pp.67-78
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• 2010

In this study, a clustering algorithm that uses DCT transformed data is presented. The algorithm is a grid density-based clustering algorithm that can identify clusters of arbitrary shape. Streaming data are transformed and reconstructed as needed for clustering. Experimental results show that DCT is able to approximate a data distribution efficiently using only a small number of coefficients and preserve the clusters well. The grid based clustering algorithm works well with DCT transformed data, demonstrating the viability of DCT for data stream clustering applications.

• 정보처리학회논문지B
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• 제15B권6호
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• pp.533-542
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• 2008

동영상에서의 배경제거는 다양한 실시간 머신 비젼 응용에서 매우 중요한 단계이다. 본 논문에서는 이러한 배경제거를 위한 육각화소 기반의 새로운 접근 방법을 제안한다. 일반적으로 육각형 샘플링 영상은 양자화 오차가 적으며, 이웃화소의 연결성 정의를 크게 개선한다고 알려져 있는데, 제안된 방법은 비매개변수형 배경제거 방법의 하나인 지역적 이진패턴 기반 알고리즘에 이러한 육각 샘플링 영상을 적용하는 것을 특징으로 한다. 이를 통해, 지역적 이진패턴의 추출과정에서 필요한 쌍선형 보간을 없애고 계산량을 줄일 수 있었다. 실험을 통해 이러한 육각화소의 적용이 배경제거 분야에 매우 효율적으로 적용될 수 있음을 확인할 수 있었다.

• 한국측량학회지
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• 제30권4호
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• pp.335-342
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• 2012

건축, 토목, 의료, 컴퓨터 그래픽스 분야 등 다양한 분야에서 이용되는 3D point cloud는 최근 레이저 스캐너의 발달로 인해 그 용량이 점점 커지게 되었다. 컴퓨터 메모리의 용량을 넘어서서 모든 데이터를 한 번에 처리할 수 없는 대용량 3D point cloud를 가시화하고 편집하기 위해 여러 전처리 및 가시화 방법들이 소개되었고 본 논문에서 비교한 QSplat의 경우 3D 모델의 형상 확인과 용량 감소를 목적으로 원본 좌표를 손실 압축하여 저장하였다. 본 논문에서 제시하는 방법은 3D point cloud를 정육면체 격자로 분할하고 center sampling을 통해 가상점 집합을 생성하며 가시화 과정에서 격자에 저장된 point 집합 취득을 통한 빠른 렌더링이 가능하다. 홍익대학교 인근 지역을 측정한 약 1억 2천만 개 point의 대용량 3D point cloud를 QSplat과 다단계 정육면체 격자 기반 방법으로 비교한 결과 전처리 과정에서는 QSplat이, 가시화 과정에서는 다단계 정육면체 격자 기반 방법이 빠른 속도를 보여주었다. 또한 다단계 정육면체 격자 기반 방법은 point의 원본 좌표를 저장하기에 추후 가시화 외에 편집, segmentation 등의 작업을 고려하여 고안되었다.

• Journal of Power Electronics
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• 제18권3호
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• pp.910-922
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• 2018

Conventional battery state-of-charge (SoC) estimation methods either involve sophisticated models or consume considerable computational resource. This study constructs an enhanced coulomb counting method (Ah method) for the SoC estimation of lithium-ion batteries (LiBs) by expanding the Peukert equation for the discharging process and incorporating the Coulombic efficiency for the charging process. Both the rate- and temperature-dependence of battery capacity are encompassed. An SoC mapping approach is also devised for initial SoC determination and Ah method correction. The charge counting performance at different sampling frequencies is analyzed experimentally and theoretically. To achieve a favorable compromise between sampling frequency and accumulation accuracy, a frequency-adjustable current sampling solution is developed. Experiments under the augmented urban dynamometer driving schedule cycles at different temperatures are conducted on two LiBs of different chemistries. Results verify the effectiveness and generalization ability of the proposed SoC estimation method.

• Journal of the Korean Data and Information Science Society
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• 제21권1호
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• pp.121-128
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• 2010

케이-평균 군집분석은 데이터들을 k개의 군집으로 임의로 분할을 하여 군집의 평균을 대푯값으로 분할해 나가는 방법으로 데이터들을 유사성을 바탕으로 재배치를 하는 방법이다. 이러한 케이-평균 군집분석은 시장조사, 패턴분석 및 인식, 그리고 이미지 처리 분야 등에서 폭넓게 응용되고 있다. 그러나 대용량의 데이터베이스를 분석대상으로 하므로 그 만큼 데이터 처리 시간이 많이 소요되는 것이 문제 중의 하나이다. 특히 웹이 보편화된 현재 사용자들의 다양한 패턴을 분석하기 위한 데이터 마이닝 방법이 사용되어지고 있는데 처리 속도 문제는 더욱 중요하게 생각하고 있다. 이러한 속도 문제를 해결하기 위해 본 논문에서는 분할 군집법에서 가장 일반적으로 사용되고 있는 케이-평균 알고리즘에 대해 그리드를 기반으로 한 무게중심 알고리즘을 제안하고자 한다.

• Journal of the Korean Data and Information Science Society
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• 제14권3호
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• pp.535-543
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• 2003

Cluster analysis has been widely used in many applications, such as pattern analysis or recognition, data analysis, image processing, market research on on-line or off-line and so on. Clustering can identify dense and sparse regions among data attributes or object attributes. But it requires many hours to get clusters that we want, because clustering is more primitive, explorative and we make many data an object of cluster analysis. In this paper we propose a new method of clustering using sample based on grid. It is more fast than any traditional clustering method and maintains its accuracy.

• Journal of Electrical Engineering and Technology
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• 제11권6호
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• pp.1527-1534
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• 2016

Online voltage stability monitoring using real-time measurements is one of the most important tasks in a smart grid system to maintain the grid stability. Loading margin is a good indicator for assessing the voltage stability level. This paper presents an Extreme Learning Machine (ELM) approach for estimation of voltage stability level under credible contingencies using real-time measurements from Phasor Measurement Units (PMUs). PMUs enable a much higher data sampling rate and provide synchronized measurements of real-time phasors of voltages and currents. Depth First (DF) algorithm is used for optimally placing the PMUs. To make the ELM approach applicable for a large scale power system problem, Mutual information (MI)-based feature selection is proposed to achieve the dimensionality reduction. MI-based feature selection reduces the number of network input features which reduces the network training time and improves the generalization capability. Voltage magnitudes and phase angles received from PMUs are fed as inputs to the ELM model. IEEE 30-bus test system is considered for demonstrating the effectiveness of the proposed methodology for estimating the voltage stability level under various loading conditions considering single line contingencies. Simulation results validate the suitability of the technique for fast and accurate online voltage stability assessment using PMU data.

• Journal of Power Electronics
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• 제19권4호
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• pp.1034-1044
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• 2019

In medium-voltage and high-voltage high-power converters, the switching devices need to operate at a low switching frequency to reduce power loss and increase the power capacity. This increases the delay of the signal sampling and PWM. It also makes the cross-couplings of the d-q current components more severe. In addition, the LCL filter has three cross-coupling loops and is prone to resonance. In order to solve these problems, this paper establishes a complex vector model of an LCL type grid-connected converter. Based on this model, two multiple decoupling current control strategies with passive damping / notch damping are proposed for the LCL type grid-connected converter. The proposed strategies can effectively eliminate the cross-couplings of the converter, achieve independent control of the d-q current components, expand the stable region and suppress the resonance of the LCL filter. Simulation and experimental results verify the correctness of the theoretical analysis and the feasibility of the proposed strategies.

• 한국지진공학회:학술대회논문집
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• 한국지진공학회 2003년도 춘계 학술발표회논문집
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• pp.50-58
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• 2003

We have developed a locally variable time-step scheme matching with discontinuous grids in the flute-difference method for the efficient simulation of seismic wave propagation. The first-order velocity-stress formulations are used to obtain the spatial derivatives using finite-difference operators on a staggered grid. A three-times coarser grid in the high-velocity region compared with the grid in the low-velocity region is used to avoid spatial oversampling. Temporal steps corresponding to the spatial sampling ratio between both regions are determined based on proper stability criteria. The wavefield in the margin of the region with smaller time-step are linearly interpolated in time using the values calculated in the region with larger one. The accuracy of the proposed scheme is tested through comparisons with analytic solutions and conventional finite-difference scheme with constant grid spacing and time step. The use of the locally variable time-step scheme with discontinuous grids results in remarkable saving of the computation time and memory requirement with dependency of the efficiency on the simulation model. This implies that ground motion for a realistic velocity structures including near-surface sediments can be modeled to high frequency (several Hz) without requiring severe computer memory

• 제어로봇시스템학회논문지
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• 제22권9호
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• pp.710-715
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• 2016

Due to its simplicity and high reliability, the box-counting(BC) method is one of the most frequently used techniques to estimate the fractal dimensions of a binary image with a self-similarity property. The fractal calculation requires data sampling that determines the size of boxes to be sampled from the given image and directly affects the accuracy of the fractal dimension estimation. There are three non-overlapping regular grid methods: geometric-step method, arithmetic-step method and divisor-step method. These methods have some drawbacks when the image size M becomes large. This paper presents a BC algorithm for enhancing the accuracy of the fractal dimension estimation based on a new sampling method. Instead of using the geometric-step method, the new sampling method, called the coverage ratio-step method, selects the number of steps according to the coverage ratio. A set of experiments using well-known fractal images showed that the proposed method outperforms the existing BC method and the triangular BC method.