• Journal of the Optical Society of Korea
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• 제12권4호
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• pp.221-225
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• 2008

We propose a simple hydrogen detection scheme based on a Mach-Zehnder interferometer formed with a pair of palladium-coated long-period fiber gratings (LPGs). Since an LPG pair offered a fine-structured interference fringe in its transmission spectrum, the resolution as a sensor could be appreciably enhanced compared to that of a single LPG. As the palladium layer absorbed hydrogen, the effective refractive indices of the cladding modes were increased so that the interference spectrum was blue-shifted up to 2.3 nm with a wavelength sensitivity of -0.29 nm/min for 4% of hydrogen concentration.

• Bulletin of the Korean Chemical Society
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• 제23권12호
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• pp.1839-1841
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• 2002

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송∙미디어공학회 2017년도 추계학술대회
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• pp.139-141
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• 2017

화재는 다른 재난보다 확산 속도가 빠르기 때문에 신속하고 정확한 감지와 지속적인 감시가 요구된다. 최근, 신속하고 정확한 화재 감지를 위해, CCTV(Closed-Circuit TeleVision)으로 획득한 이미지를 기계학습(Machine Learning)을 이용해 화재 발생 여부를 감지하는 화재 감지 시스템이 주목받고 있다. 본 논문에서는 기계학습의 기술 중 정확도가 가장 높은 딥러닝(Deep Learning)기반의 CCTV 화재 감지 시스템을 제안한다. 본 논문의 시스템은 딥러닝 기술 적용뿐만이 아니라, CCTV 이미지 전처리 과정을 보완함으로써 딥러닝에서의 미지 데이터(unseen data)의 낮은 분류 정확도 문제인 과적합(overfitting)문제를 해결하였다. 본 논문의 시스템은 약 80,000 개의 CCTV 이미지 데이터를 학습하여, 90% 이상의 화재 이미지 분류 정확도의 성능을 보여주었다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2006년도 하계종합학술대회
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• pp.183-184
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• 2006

The simulation on the mechanism of terahertz NSOM(near-field scanning optical microscopy) have been investigated. Based on experimental results, we have demonstrated the antenna effects on the coupling between a metal tip and substrate for an emission-type terahertz NSOM. It has been found that the lateral resolution can be estimated by a simplified model using an infinitesimal dipole in the substrate.

• 로봇학회논문지
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• 제17권3호
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• pp.339-346
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• 2022

To operate in real environment, humanoid robots should be able to react to unknown disturbances. To deal with disturbances, various robust control algorithms have been developed for decades. But for collaborative works such as teleoperation system, a compliance control can be the better solution for disturbance reactions. In this paper, a center of mass (CoM) compliance control algorithm for humanoid robots is proposed. The proposed algorithm is based on the state observer and positive feedback of disturbance. With the state observer based on humanoid CoM control performance model, disturbance in each direction can be observed. The positive feedback of disturbances to the reference CoM trajectory enables compliant motion. The main contributions of this algorithm are achieving compliance independently in each axis and maintaining balance against external force. Through dynamic simulations, the performance of the proposed method was demonstrated. Under two types of disturbance conditions, humanoid robot DYROS-JET reacted with compliant motion via the proposed algorithm.

• Journal of Animal Science and Technology
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• 제65권6호
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• pp.1254-1269
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• 2023

This study aims to predict the change in corn share according to the grazing of 20 gestational sows in a mature corn field by taking images with a camera-equipped unmanned air vehicle (UAV). Deep learning based on convolutional neural networks (CNNs) has been verified for its performance in various areas. It has also demonstrated high recognition accuracy and detection time in agricultural applications such as pest and disease diagnosis and prediction. A large amount of data is required to train CNNs effectively. Still, since UAVs capture only a limited number of images, we propose a data augmentation method that can effectively increase data. And most occupancy prediction predicts occupancy by designing a CNN-based object detector for an image and counting the number of recognized objects or calculating the number of pixels occupied by an object. These methods require complex occupancy rate calculations; the accuracy depends on whether the object features of interest are visible in the image. However, in this study, CNN is not approached as a corn object detection and classification problem but as a function approximation and regression problem so that the occupancy rate of corn objects in an image can be represented as the CNN output. The proposed method effectively estimates occupancy for a limited number of cornfield photos, shows excellent prediction accuracy, and confirms the potential and scalability of deep learning.

• 한국응용과학기술학회지
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• 제31권1호
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• pp.59-65
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• 2014

Indoor air quality including metro subway is of recent interests in large cities. Inflow air to the inside of the train and circulating air flow through MVAC of stations contain large amount of iron based fine particles. This paper evaluated the collection of such a dust by magnetic filters as comparing to conventional particle capturing mechanisms such as inertia, direct impaction and diffusion. It was found that filtration velocity, magnetic field intensity, and fiber size were the most important parameters for magnetic filtration. Application of magnetic force obviously enhances the collection efficiency particularly in fine modes smaller than 10 mm. However, its effect was found greater in 2.5 mm than submicron particles.

• 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
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• 한국정보과학회언어공학연구회 2011년도 제23회 한글 및 한국어 정보처리 학술대회
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• pp.41-46
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• 2011

스마트폰의 대중화와 함께 그에 내장된 GPS를 활용하여 컨텐츠를 제공하는 서비스들이 점차 늘어나고 있다. 그러나 이런 컨텐츠를 단지 위도, 경도 좌표 정보만을 기초로 구성하게 되면 실제 그 위치가 가지는 의미적 특성을 제대로 반영하지 못하게 된다. 사용자의 위치를 기반으로 그에 맞는 서비스를 제공하기 위해서는 장소의 토픽을 고려해야한다. 본 논문은 장소에 내재된 토픽을 바탕으로 한 기사 추천 방법을 제안한다. 장소와 관련된 문서로부터 장소의 토픽을 표현하고 그 토픽을 기사 추천에 이용한다. 제안한 방법이 실제로 장소에 내재된 토픽을 잘 반영함을 보이고 또한 이를 바탕으로 장소와 관련된 적합한 기사를 추천하는 것을 보여준다.

• 한국우주과학회:학술대회논문집(한국우주과학회보)
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• 한국우주과학회 2009년도 한국우주과학회보 제18권1호
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• pp.64.2-64.2
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• 2009

• 식품과학과 산업
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• 제54권1호
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• pp.29-33
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• 2021

Particulate matter (PM) is an air pollutant that causes serious environmental problems in Korea and other countries. The annual average PM10 concentration in Korea is around 40 ㎛/㎥, which is more than twice as high as the WHO recommended standard. When consumed with food, fine PM can pose a risk to humans. However, the risk of fine PM has been focused on the risk of fine PM introduced through the respiratory system. We investigated the quantitative measuring methods of PM10 on food surface to identify possible risk analysis of fine PM. The surfaces of food with artificially contaminated PM10 were observed with a scanning electron microscope(SEM). An automatic object-based image analysis was used to analyze the amount and size distribution of particulate matter contained in SEM micrographs.