• 대한한방내과학회지
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• 제18권2호
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• pp.160-166
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• 1997

To evaluate the effect of acupuncture on the hypertension, the study was done by acupuncture on bilateral Inyong(ST9) with rats which are normal and acutely increased hypertensive. The results are as follows: 1. Under the normal condition, the acupuncture on bilateral Inyong caused a quick drop of mean arterial pressure(MAP), but heart rate(HR) was not changed significantly. 2. To increase the blood pressure, acutely epinephrine was administered and it caused a increase in both MAP and HR. With acupuncture, the MAP was decreased while HR did not show a significant change. In conclusion, the acupuncture was somewhat effective in lowering the mean arterial pressure in the rat.

• 대한원격탐사학회지
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• 제23권5호
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• pp.455-464
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• 2007

Lee(2007) suggested the Point-Jacobian iteration MAP estimation(PJIMAP) for noise removal of the images that are corrupted by multiplicative speckle noise. It is to find a MAP estimation of noisy-free imagery based on a Bayesian model using the lognormal distribution for image intensity and an MRF for image texture. When the image intensity is logarithmically transformed, the speckle noise is approximately Gaussian additive noise, and it tends to a normal probability much faster than the intensity distribution. The MRF is incorporated into digital image analysis by viewing pixel types as states of molecules in a lattice-like physical system. In this study, the MAP estimation is computed by the Point-Jacobian iteration using adaptive parameters. At each iteration, the parameters related to the Bayesian model are adaptively estimated using the updated information. The results of the proposed scheme were compared to them of PJIMAP with SAR simulation data generated by the Monte Carlo method. The experiments demonstrated an improvement in relaxing speckle noise and estimating noise-free intensity by using the adaptive parameters for the Ponit-Jacobian iteration.

• 대한수학회지
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• 제32권3호
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• pp.509-518
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• 1995

Let $M^n$ be a hypersurface in the Euclidean space $R^{n+1}$ with position vector field x and unit normal vector field G.

• 대한원격탐사학회지
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• 제35권6_2호
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• pp.1133-1148
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• 2019

산림지역은 계절에 따라 생장 및 활력 특성이 변화하기 때문에 산림피해를 정확하게 탐지하기 위해서는 과거 동일한 계절적 시기의 영상정보 확보가 필요하다. 그러나 고해상도 또는 중해상도 영상은 영상촬영주가 높지 않아 동일 시기의 영상 정보들을 확보하는 것은 쉽지 않다. 따라서 본 연구에서는 산림생태계의 피해를 평가하기 위해 시계열 영상정보를 통해 피해발생 이전 과거 동일 시점의 분광정보를 추정하여 산림피해 평가의 기준정보로 활용하는 방법을 연구했다. 연구대상지는 2017년 우박과 가뭄으로 인해 대규모 산림피해가 발생한 전라남도 화순지역이며, 과거 3년간 해당 지역에서 촬영된 모든 Landsat 8 영상의 시계열 식생지수(NDVI, EVI, NDMI) 자료를 구축하고 이를 일별 연속자료로 자료보간을 실시하였다. 그리고 이를 통해 교란 발생 이전의 정상적인 일별 식생지수 추정 지도를 제작하였으며, 동일 날짜의 일별 평년 식생지수와 교란발생 이후의 식생지수의 차이값을 구하고 피해등급 기준을 적용하여 최종적인 위성자료 기반의 피해등급지도가 산출되었다. 위성기반 피해등급지도는 기존의 항공사진 기반 피해등급지도에 비해 미세한 식생활력도 변화를 효과적으로 탐지하였으며, 피해극심지역을 대상으로 비교하였을 때 SWIR 밴드를 이용한 식생지수(NDMI)가 기존의 피해등급평가 결과와 유사한 결과를 산출하여 활용도가 높은 것으로 평가되었다. 결과적으로, 일별 평년식생활력도 지도의 제작을 통해 신속하고 정확한 피해지 탐지가 가능해졌다.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2004년도 춘계학술발표회논문집
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• pp.541-546
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• 2004

This study compare the coordination and area between cadastral map digital data corrected by normal nap and serial cadastral map edited by formal data. By superposition ortho image made from aerial photo to serial cadastral map, we propose the method to improve the confidence and use the ortho image efficiently in cadastral part.

• 로봇학회논문지
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• 제12권3호
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• pp.322-331
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• 2017

In this paper we present a novel robotic palpation method for the lump shape estimation using contact pressure distribution. Many previous researches about the robotic palpation have used a stiffness map, which is not suitable to obtain geometrical information of a lump. As a result, they require a large data set and long palpation time to estimate the lump shape. Instead of using the stiffness map, the proposed palpation method uses the difference between the normal force direction and the surface normal to detect the lump boundary and estimate its normal. The palpation trajectory is generated by the normal of the lump boundary to track the lump boundary in real-time. The proposed approach requires small data set and short palpation time for the lump shape estimation since the shape can be directly estimated from the optimally generated palpation trajectory. An experiment result shows that our method can find the lump shape accurately in real-time with small data and short time.

• 산업경영시스템학회지
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• 제46권2호
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• pp.1-12
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• 2023

To make semiconductor chips, a number of complex semiconductor manufacturing processes are required. Semiconductor chips that have undergone complex processes are subjected to EDS(Electrical Die Sorting) tests to check product quality, and a wafer bin map reflecting the information about the normal and defective chips is created. Defective chips found in the wafer bin map form various patterns, which are called defective patterns, and the defective patterns are a very important clue in determining the cause of defects in the process and design of semiconductors. Therefore, it is desired to automatically and quickly detect defective patterns in the field, and various methods have been proposed to detect defective patterns. Existing methods have considered simple, complex, and new defect patterns, but they had the disadvantage of being unable to provide field engineers the evidence of classification results through deep learning. It is necessary to supplement this and provide detailed information on the size, location, and patterns of the defects. In this paper, we propose an anomaly detection framework that can be explained through FCDD(Fully Convolutional Data Description) trained only with normal data to provide field engineers with details such as detection results of abnormal defect patterns, defect size, and location of defect patterns on wafer bin map. The results are analyzed using open dataset, providing prominent results of the proposed anomaly detection framework.

• 자동차안전학회지
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• 제14권2호
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• pp.39-44
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• 2022

This paper presents LiDAR static obstacle map based vehicle position correction algorithm for urban autonomous driving. Real Time Kinematic (RTK) GPS is commonly used in highway automated vehicle systems. For urban automated vehicle systems, RTK GPS have some trouble in shaded area. Therefore, this paper represents a method to estimate the position of the host vehicle using AVM camera, front camera, LiDAR and low-cost GPS based on Extended Kalman Filter (EKF). Static obstacle map (STOM) is constructed only with static object based on Bayesian rule. To run the algorithm, HD map and Static obstacle reference map (STORM) must be prepared in advance. STORM is constructed by accumulating and voxelizing the static obstacle map (STOM). The algorithm consists of three main process. The first process is to acquire sensor data from low-cost GPS, AVM camera, front camera, and LiDAR. Second, low-cost GPS data is used to define initial point. Third, AVM camera, front camera, LiDAR point cloud matching to HD map and STORM is conducted using Normal Distribution Transformation (NDT) method. Third, position of the host vehicle position is corrected based on the Extended Kalman Filter (EKF).The proposed algorithm is implemented in the Linux Robot Operating System (ROS) environment and showed better performance than only lane-detection algorithm. It is expected to be more robust and accurate than raw lidar point cloud matching algorithm in autonomous driving.

• 한국게임학회 논문지
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• 제10권6호
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• pp.169-178
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• 2010

본 논문은 실시간 응용 프로그램에서 사실적인 금속 재질을 렌더링하기 위한 효과적인 기법을 제안한다. 제안된 기법은 금속면의 미세한 흡집을 표현하기 위해 법선 벡터를 섭동(perturbation)하는 방법을 사용한다. 법선 벡터를 섭동하는 일반적인 방법은 범프(bump) 매핑이나 법선(normal) 매핑 등의 방법을 사용하는 것이다. 그러나 이러한 방식은 이방성 반사 특성을 갖는 표면에서는 사실적인 빛의 산란을 보이지 못한다. 금속 특유의 반사를 표현하기 위해서는 미세면 분포 함수를 이용하여 이방성 반사 특성을 모델링하는 것이 일반적이므로 일반적 법선 섭동만으로는 만족스런 결과를 얻지 못한다. 본 논문은 법선 벡터의 섭동과 함께 미세면 분포 함수를 변형하는 기법을 통해 매우 사실적인 금속면 재질 렌더링이 가능한 기법을 제안한 다. 제안된 기법은 쉽게 GPU 프로그램으로 구현되며, 실시간 환경에서 동작한다.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2005년도 춘계학술대회 논문집
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• pp.91-96
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• 2005

In this study, researchers developed the estimative algorithm for artificial defects in semiconductor packages and performed it by pattern recognition technology. For this purpose, the estimative algorithm was included that researchers made software with MATLAB. The software consists of some procedures including ultrasonic image acquisition, equalization filtering, Self-Organizing Map and Backpropagation Neural Network. Self-Organizing Map and Backpropagation Neural Network are belong to methods of Neural Networks. And the pattern recognition technology has applied to classify three kinds of detective patterns in semiconductor packages: Crack, Delamination and Normal. According to the results, we were confirmed that estimative algorithm was provided the recognition rates of $75.7\%$ (for Crack) and $83_4\%$ (for Delamination) and $87.2\%$ (for Normal).