• 한국환경과학회지
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• 제3권1호
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• pp.39-47
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• 1994

Dispersion characteristics of air pollutants in the mountainous coastal area are investigated in considering with the mesoscale local circulations using a two dimensional numerical model with two kinds of topograpy of 500m and 300m. In the model, land-sea breezes and mountain-valley wind are mainly considered under the condition of the absence of large scale prevailing flow in the circulation analysis, and the pollutants dispersion is traced by the Lagrangian methods. According to the results, the wind velocity is affected by topography and is stronger in the case of 500m height mountain than that of 300m, the Pollutants that source is near the coast transported over the mountain and dispersed to behind inland area. It is classified that the topography change control affects the wind velocity and the circulations. The pollutants that source is different transported and concentrated to behind inland and/or diffused to the sea area by the combination of the wind system with topographic changes. The results can be applied to the air pollution control with the arrangement design of industrial area and the planning of coastal developments.

• 제어로봇시스템학회논문지
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• 제13권9호
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• pp.868-874
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• 2007

This paper proposes an efficient partial matching system and representation by using a region-based method for 2D image, and we applied to an extraction of the ROI(Region of Interest) according to its matching score. The matching templates consist of the global pattern and the local one. The global pattern can make it by using region-based relation between center region and its rest regions in an object. And, the local pattern can be obtained appling to the same method as global, except relation between objects. As the templates can be normalized, we use this templates for extraction of ROI with invariant to size and position. And, our system operates only one try to match, due to normalizing of region size. To use our system for searching and examining if it's the ROI by evaluating the matching function, at first, we are searching to find candidate regions with the global template. Then, we try to find the ROI among the candidates, and it works this time by using the local template. We experimented to the binary and the color image respectively, they showed that the proposed system can be used efficiently for representing of the template and the useful applications, such as partially retrievals of 2D image.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2004년도 제5회 압연심포지엄 신 시장 개척을 위한 압연기술
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• pp.317-326
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• 2004

This study investigated tile local austenite grain size (AGS) distribution In rolling of SCM435 steel which is commonly used for high strength bolt. To investigate AGS distribution, round-oval (R-O) and square-diamond (S-D) rolling experiments were carried out with pilot mill. In round-oval rolling, local AGS has a tendency to increase when it goes to outward. In square-diamond rolling, local AGS has a tendency to increase when it goes to free surface. To investigate relation between AGS and process parameter, three dimensional FE analysis was carried out along with rolling experiment. To validate accuracy of FE analysis, we compared deformed geometry with FE result. The AGS prediction combined AGS model with numerical analysis was also carried out for center node of S-D rolling. Although this study brought experimental observation and its qualitative analysis into focus and quantitative AGS prediction will be done as a further work.

• 제어로봇시스템학회논문지
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• 제12권5호
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• pp.450-456
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• 2006

Monte Carlo localization is known to be one of the most reliable methods for pose estimation of a mobile robot. Although MCL is capable of estimating the robot pose even for a completely unknown initial pose in the known environment, it takes considerable time to give an initial pose estimate because the number of random samples is usually very large especially for a large-scale environment. For practical implementation of MCL, therefore, a reduction in sample size is desirable. This paper presents a novel approach to reducing the number of samples used in the particle filter for efficient implementation of MCL. To this end, the topological information generated through the thinning technique, which is commonly used in image processing, is employed. The global topological map is first created from the given grid map for the environment. The robot then scans the local environment using a laser rangefinder and generates a local topological map. The robot then navigates only on this local topological edge, which is likely to be similar to the one obtained off-line from the given grid map. Random samples are drawn near the topological edge instead of being taken with uniform distribution all over the environment, since the robot traverses along the edge. Experimental results using the proposed method show that the number of samples can be reduced considerably, and the time required for robot pose estimation can also be substantially decreased without adverse effects on the performance of MCL.

• 제어로봇시스템학회논문지
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• 제17권10호
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• pp.1059-1066
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• 2011

This paper makes a close inquiry into ill-conditioning that may be occurred in wireless localization of the sensor nodes based on network signals in the wireless sensor network and provides the clue for solving the problem. In order to estimate the location of a node based on the range information calculated using the signal propagation time, LS (Least Squares) method is usually used. The LS method estimates the solution that makes the squared estimation error minimal. When a nonlinear function is used for the wireless localization, ILS (Iterative Least Squares) method is used. The ILS method process the LS method iteratively after linearizing the nonlinear function at the initial nominal point. This method, however, has a problem that the final solution may converge into a LM (Local Minimum) instead of a GM (Global Minimum) according to the deployment of the fixed nodes and the initial nominal point. The conditions that cause the problem are explained and an adaptive method is presented to solve it, in this paper. It can be expected that the stable location solution can be provided in implementation of the wireless localization methods based on the results of this paper.

• 제어로봇시스템학회논문지
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• 제17권10호
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• pp.995-1005
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• 2011

An efficient outdoor local localization method is suggested using multi-sensor fusion with MU-EKF (Multi-Update Extended Kalman Filter) for car-like mobile robots. In outdoor environments, where mobile robots are used for explorations or military services, accurate localization with multiple sensors is indispensable. In this paper, multi-sensor fusion outdoor local localization algorithm is proposed, which fuses sensor data from LRF (Laser Range Finder), Encoder, and GPS. First, encoder data is used for the prediction stage of MU-EKF. Then the LRF data obtained by scanning the environment is used to extract objects, and estimates the robot position and orientation by mapping with map objects, as the first update stage of MU-EKF. This estimation is finally fused with GPS as the second update stage of MU-EKF. This MU-EKF algorithm can also fuse more than three sensor data efficiently even with different sensor data sampling periods, and ensures high accuracy in localization. The validity of the proposed algorithm is revealed via experiments.

• International journal of advanced smart convergence
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• 제7권3호
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• pp.44-60
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• 2018

This study is to identify the effects of hypertension management program at a community health center on the disease-related knowledge, self-efficacy, anthropometric measurements and blood pressure of a hypertensive patient in local community. This study is a quasi-experimental study using nonequivalence control group no-synchronized design in order to verify the effects of the hypertension management program at a community health center on the hypertension-related knowledge, self-efficacy, anthropometric measurements and blood pressure of a hypertensive patient in local community. The result indicated a significant difference between the experimental group and control group in the scores of hypertension-related knowledge (t=-4.25, p<.001), self-efficacy (t=-4.20, p<.001), systolic blood pressure (t=7.70, p<.001) and diastolic blood(t=5.91, p<.001), body weight(t=2.32, p=.026) and abdominal circumference(t=2.17, p=.036). The hypertensive patients' knowledge and self-efficacy were improved, and their weight and abdominal circumference as well as systolic blood pressure and diastolic blood pressure were reduced. Therefore, it was confirmed that multilateral approaches in terms of physical and psychosocial aspects only targeting hypertensive patients were required for managing hypertensive patients in local community.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2015년도 추계학술대회
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• pp.900-902
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• 2015

현대사회에서 디지털 영상 처리 기술이 발전함에 따라 에지 검출은 스마트 기기, 의료 등 여러 응용 분야에서 활용되고 있다. 기존의 에지 검출 방법에는 마스크를 이용한 Sobel, Prewitt, Roberts, Laplacian 등이 있다. 이러한 기존의 방법은 구현이 간단하나 다소 미흡한 결과를 나타낸다. 따라서 이와 같은 기존의 방법의 문제점을 보완하기 위하여, 본 논문에서는 모폴로지 연산 및 국부 마스크를 이용하여 에지를 검출하는 알고리즘을 제안하였으며, 기존의 방법들과 검출 성능을 비교하였다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2015년도 추계학술대회
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• pp.328-330
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• 2015

에지는 영상에 포함된 물체의 크기, 방향, 위치 등을 쉽게 획득할 수 있는 특징 정보이며, 에지 검출은 물체 검출, 물체 인식 등의 여러 영상 처리 응용 분야에서 전처리 과정으로 활용되고 있다. 기존의 에지 검출 방법에는 Sobel, Prewitt, Roberts 에지 검출 방법 등이 있다. 이러한 기존의 에지 검출 방법들은 구현이 간단하며, 고정 가중치 마스크를 적용하므로 에지 검출 특성이 다소 미흡하다. 따라서 기존의 에지 검출 방법들의 문제점을 보완하기 위하여, 본 논문에서는 국부 마스크 내의 평균 및 표준편차에 따라 가중치를 적용한 후 에지를 검출하는 알고리즘을 제안하였다.

• 제어로봇시스템학회논문지
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• 제17권5호
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• pp.471-478
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• 2011

This UGV (Unmanned Ground Vehicle) is not only widely used in various practical applications but is also currently being researched in many disciplines. In particular, obstacle avoidance is considered one of the most important technologies in the navigation of an unmanned vehicle. In this paper, we introduce a simple algorithm for path planning in order to reach a destination while avoiding a polygonal-shaped static obstacle. To effectively avoid such an obstacle, a path planned near the obstacle is much shorter than a path planned far from the obstacle, on the condition that both paths guarantee that the robot will not collide with the obstacle. So, to generate a path near the obstacle, we have developed an algorithm that combines an edge detection method and a limit-cycle navigation method. The edge detection method, based on Hough Transform and IR sensors, finds an obstacle's edge, and the limit-cycle navigation method generates a path that is smooth enough to reach a detected obstacle's edge. And we proposed novel algorithm to solve local minima using the virtual wall in the local vision. Finally, we verify performances of the proposed algorithm through simulations and experiments.