• 천문학회보
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• 제43권1호
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• pp.32.1-32.1
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• 2018

Searching for low surface brightness (LSB) dwarf galaxies in low density environments (isolated and group) can help us resolve the discrepancy between observation and theory known as the 'missing satellite' problem. They are also important to study the evolution of low mass galaxies in these environments. Although the number of dwarfs in such environments is rapidly increasing in many recent studies, it is still not easy to characterize their general properties. Motivated by this, we present preliminary results of our search for LSB dwarf galaxies around 60 nearby galaxies (D<50Mpc) using deep optical images. Imaging data from Maidanak Astronomical Observatory (MAO) in Uzbekistan as a part of Intensive Monitoring Survey of Nearby Galaxies (IMSNG; Im in prep.) and other archival data are used to find previously unknown LSB dwarf galaxies. Extended LSB sources (central surface brightness ${\mu}_0$ > $23mag/arcsec^2$) are first selected in the ${\mu}_0$ - magnitude plane (Rines & Geller 2008). The dwarf galaxy candidates are chosen by visual inspection. We discuss whether these candidates are actual satellite galaxies, by measuring the projected number densities in group environments and in the field. Also, their structural and photometric properties are compared with those of previously discovered dwarf galaxies in the literature.

• 한국지능시스템학회논문지
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• 제17권7호
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• pp.901-906
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• 2007

미지의 환경에서 이동로봇이 자율 주행을 할 수 있기 위해서는 경로 설정 및 장애물 회피가 필수적인 요소이다. 이를 위해 본 논문에서는 비전과 IR 센서로부터 획득한 데이터와 퍼지규칙을 이용하는 자율 주행 알고리즘을 구현하고자 한다. 로봇과 장애물과의 거리가 멀리 떨어져 있는 경우는 비전에서 얻은 2차원 이미지를 메디안 필터링, 에지 추출, 모폴로지, 세선화 과정을 거쳐 임시 목표물을 설정한 다음, 거리 변화율 기법과 퍼지 규칙을 이용하여 경로 설정을 한다. 로봇과 장애물과의 거리가 근접할 경우는 IR 센서를 이용하여 경로 설정 및 근접 장애물 회피를 하도록 한다. 그리고 본 논문에서는 제안된 퍼지규칙을 이용한 데이터 융합 알고리즘이 이동로봇을 미지의 환경에서 보다 효율적으로 주행하게 할 수 있음을 실제 실험을 통해 보여주고자 한다.

• 제어로봇시스템학회논문지
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• 제6권2호
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• pp.155-163
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• 2000

This paper presents a path planning method of the sensor based intelligent vehicle using fuzzy logic controller for avoidance of moving obstacles in unknown environments. Generally it is too difficult and complicated to control intelligent vehicle properly by recognizing unknown terrain with sensors because the great amount of imprecise and ambiguous information has to be considered. In this respect a fuzzy logic can manage such the enormous information in a quite efficient manner. Furthermore it is necessary to use the relative velocity to consider the mobility of obstacles, In order to avoid moving obstacles we must deliberate not only vehicle's relative speed toward obstacles but also self-determined acceleration and steering for the satisfaction of avoidance efficiency. In this study all the primary factors mentioned before are used as the input elements of fuzzy controllers and output signals to control velocity and steering angle of the vehicle. The main purpose of this study is to develop fuzzy controllers for avoiding collision with moving obstacles when they approach the vehicle travelling with straight line and for returning to original trajectory. The ability are and effectiveness of the proposed algorithm are demonstrated by simulations and experiments.

• 한국정밀공학회지
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• 제16권1호통권94호
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• pp.253-264
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• 1999

Most autonomous mobile robots view only things in front of them, and as a result, they may collide with objects moving from the side or behind. To overcome this problem. an Active Omni-directional Range Sensor System has been built that can obtain an omni-directional range data through the use of a laser conic plane and a conic mirror. Also, mobile robot has to know its current location and heading angle by itself as accurately as possible to successfully navigate in real environments. To achieve this capability, we propose a self-localization algorithm of a mobile robot using an active omni-directional range sensor in an unknown environment. The proposed algorithm estimates the current position and head angle of a mobile robot by a registration of the range data obtained at two positions, current and previous. To show the effectiveness of the proposed algorithm, a series of simulations was conducted and the results show that the proposed algorithm is very efficient, and can be utilized for self-localization of a mobile robot in an unknown environment.

• Clinical and Experimental Pediatrics
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• 제59권8호
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• pp.319-327
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• 2016

Allergic diseases such as asthma, allergic rhinitis, atopic dermatitis, and food allergy, are most common chronic, noncommunicable diseases in childhood. In the past few decades, the prevalence has increased abruptly worldwide. There are 2 possible explanations for the rising prevalence of allergic diseases worldwide, that an increased disease-awareness of physician, patient, or caregivers, and an abrupt exposure to unknown hazards. Unfortunately, the underlying mechanisms remain largely unknown. Despite the continuing efforts worldwide, the etiologies and rising prevalence remain unclear. Thus, it is important to identify and control risk factors in the susceptible individual for the best prevention and management. Genetic susceptibility or environments may be a potential background for the development of allergic disease, however they alone cannot explain the rising prevalence worldwide. There is growing evidence that epigenetic change depends on the gene, environment, and their interactions, may induce a long-lasting altered gene expression and the consequent development of allergic diseases. In epigenetic mechanisms, environmental tobacco smoke (ETS) exposure during critical period (i.e., during pregnancy and early life) are considered as a potential cause of the development of childhood allergic diseases. However, the causal relationship is still unclear. This review aimed to highlight the impact of ETS exposure during the perinatal period on the development of childhood allergic diseases and to propose a future research direction.

• Journal of Electrical Engineering and Technology
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• 제11권3호
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• pp.733-740
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• 2016

To achieve bipedal walking in real human environments, a bipedal robot should be capable of modifiable walking both on uneven terrain with different heights and on flat terrain. In this paper, a novel walking pattern generator based on a 3-D linear inverted pendulum model (LIPM) is proposed to achieve this objective. By adopting a zero moment point (ZMP) variation scheme in real time, it is possible to change the center-of-mass (COM) position and the velocity of the 3-D LIPM throughout the single support phase. Consequently, the proposed method offers the ability to generate a modifiable pattern for walking on uneven terrain without the necessity for any extra footsteps to adjust the COM motion. In addition, a control strategy for bipedal walking on uneven terrain with unknown height is developed. The torques and ground reaction force are measured through force-sensing resisters (FSRs) on each foot and the foot of the robot is modeled as three virtual spring-damper models for the disturbance compensation. The methods for generating the foot and vertical COM of 3-D LIPM trajectories are proposed to achieve modifiable bipedal walking on uneven terrain without any information regarding the height of the terrain. The effectiveness of the proposed method is confirmed through dynamic simulations.

• 한국통신학회논문지
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• 제12권5호
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• pp.519-526
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• 1987

백색 잡음에 알 수 없는 크기를 갖는 바이어스와 충격성 잡음이 부가되어 혼입되는 상황에서 적절한 동작특성을 갖는 적응 추정 계통을 제안하였다 측정계통에 알 수 없는 바이어스가 인가되었을 때 R.L.Moose에 의해 제안된 적응 추정 이론에 Feed Forward Loop를 부가 삽입하여 충격성 잡음이 혼입되었을 때도 시간 변화 가중치(Time Varying Weights)의 합이 0이 되지 않고 적응 추정이 가능한 방법이다. 추정 기준 벡터의 요소 값들을 충분히 큰 값을 줄 수 있어 측정 신호에 부가된 어떤 크기의 바이어스와 충격성 잡음에도 적응 추정이 중단되지 않고 효율적으로 진행되는 컴퓨터 시뮬레이션 결과를 얻었다.

• Journal of the Optical Society of Korea
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• 제16권3호
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• pp.236-242
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• 2012

In general, such methods as interferometers or wavefront sensors are commonly used for testing of an optical system and optical components. In these cases, the surrounding environments are unlikely to affect the measurements. On the other hand, intraocular lenses of hydrophilic materials with special properties experience a certain difficulty in testing the optical properties. An intraocular lens is dried in the air, which causes deformation and changes the optical characteristics such as index of refraction and thickness. Thus, it is hard to measure the optical characteristics of an intraocular lens by using common methods. In this study, a special structure is used for measuring of the transmission wavefront aberration and effective focal length of an intraocular lens of hydrophilic materials by using a Shark-Hartmann sensor among the various measuring methods. As an application of this measuring method, this study shows a simple method to measure the index of refraction of unknown liquids with a plano-convex lens with a well known index of refraction. Also, this method is used to measure the optical properties of a plano-convex such as index of refraction and curvature by using a liquid with a well known index of refraction.

• 한국군사과학기술학회지
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• 제24권5호
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• pp.527-536
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• 2021

In wireless environments, wideband receivers are used in a communication intelligent system to detect unknown signals and obtain azimuth information. To design a wideband receiver that performs multiple signal detection and direction finding simultaneously, it is necessary to consider a reception structure composed of multiple channels. In this paper, we propose a wideband multi-channel receiver for direction finding of unknown wideband communication signals including frequency hopping signals. A signal processing method for detecting received signals and estimating azimuth information is presented, and components of the manufactured wideband receiver are described. In addition, test results of the signal detection performance by mounting the proposed wideband multi-channel receiver on the flight system are included.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제11권12호
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• pp.509-516
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• 2022

3차원 공간에서 물체들의 정확한 자세 예측은 실내외 환경에서 장면 이해, 로봇의 물체 조작, 자율 주행, 증강 현실 등과 같은 많은 응용 분야들에서 폭넓게 활용되는 중요한 시각 인식 기술이다. 물체들의 자세 예측을 위한 과거 연구들은 대부분 각 인식 대상 물체마다 정확한 3차원 CAD 모델을 요구한다는 한계점이 있었다. 이러한 과거 연구들과는 달리, 본 논문에서는 3차원 CAD 모델이 없어도 RGB 컬러 영상들만 이용해서 미지 물체들의 자세를 예측해낼 수 있는 새로운 신경망 모델을 제안한다. 제안 모델은 적응형 깊이 추정기인 AdaBins를 이용하여 스스로 미지 물체 자세 예측에 필요한 각 물체의 깊이 지도를 효과적으로 추정해낼 수 있다. 벤치마크 데이터 집합들을 이용한 다양한 실험들을 통해, 본 논문에서 제안한 모델의 유용성과 성능을 평가한다.