• Journal of the Korean Solar Energy Society
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• v.31 no.2
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• pp.82-88
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• 2011

The artificial increase in the solar intensity incident on solar cells using lenses or mirrors can allow solar cells to generate equivalent power with a lower cost. There are two types of concentration optics for solar energy conversion. One is to use mirrors, and the other is to use Fresnel lenses. The gains that can be achieved with a Fresnel lens or a parabolic mirror are compared. The result showed the gains are comparable and the two configurations were developed competitively. In application areas of Fresnel lenses as solar concentrators, several variations of design were devised and tested. Some PV systems still use commercially available flat Fresnel lenses as concentrators. A convex linear Fresnel lens to improve the concentration ratio and the efficiency is devised and flat linear Fresnel lens in thermal energy collection is utilized. In this study, we designed and optimized flat Fresnel lens and the 'light pipe' to develop 500X concentrated solar PV system. In the process, we compare the transmission efficiencies according to groove types. We performed rigorous ray tracing simulation of the flat Fresnel lenses. The computer aided simulation showed the 'grooves in case' has the better efficiency than that of 'grooves out case'. Based on the ray-trace results we designed and manufactured sample Fresnel lenses. The optical performance were measured and compared with ray-trace results. Finally, the optical efficiency was measured to be above 75%. All the design and manufacturing were performed based on that InGaP/InGaAs/Ge triple junction solar cell is used to convert the photon energy to electrical power. Field test will be made and analyzed in the near future.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1013-1027
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• 2021

Images taken with KOMPSAT-3 have additional NIR and PAN bands, as well as RGB regions of the visible ray band, compared to imagestaken with a standard camera. Furthermore, electrical and optical properties must be considered because a wide radius area of approximately 17 km or more is photographed at an altitude of 685 km above the ground. In other words, the camera sensor of KOMPSAT-3 is distorted by each CCD pixel, characteristics of each band,sensitivity and time-dependent change, CCD geometry. In order to solve the distortion, correction of the sensors is essential. In this paper, we propose a method for detecting uniform regions in side-slider-based KOMPSAT-3 images using segment-based noise analysis. After detecting a uniform area with the corresponding algorithm, a correction table was created for each sensor to apply the non-uniformity correction algorithm, and satellite image correction was performed using the created correction table. As a result, the proposed method reduced the distortion of the satellite image,such as vertical noise, compared to the conventional method. The relative radiation accuracy index, which is an index based on mean square error (RA) and an index based on absolute error (RE), wasfound to have a comparative advantage of 0.3 percent and 0.15 percent, respectively, over the conventional method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.80-85
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• 2019

Vanadium dioxide is a well-known metal-insulator phase transition material. Lots of researches of vanadium redox flow batteries have been researched as large scale energy storage system. In this study, vanadium oxide($VO_x$) thin films were applied to cathode for lithium ion battery. The $VO_x$ thin films were deposited on Si substrate($SiO_2$ layer of 300 nm thickness was formed on Si wafer via thermal oxidation process), quartz substrate by RF magnetron sputter system for 60 minutes at $500^{\circ}C$ with different RF powers. The surface morphology of as-deposited $VO_x$ thin films was characterized by field-emission scanning electron microscopy. The crystallographic property was confirmed by Raman spectroscopy. The optical properties were characterized by UV-visible spectrophotometer. The coin cell lithium-ion battery of CR2032 was fabricated with cathode material of $VO_x$ thin films on Cu foil. Electrochemical property of the coin cell was investigated by electrochemical analyzer. As the results, as increased of RF power, grain size of as-deposited $VO_x$ thin films was increased. As-deposited thin films exhibit $VO_2$ phase with RF power of 200 W above. The transmittance of as-deposited $VO_x$ films exhibits different values for different crystalline phase. The cyclic performance of $VO_x$ films exhibits higher values for large surface area and mixed crystalline phase.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.253-265
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• 2020

As the risk of landslide is recently increasing due to the typhoons and localized heavy rains, effective techniques for the landslide damage detection are required to support the establishment of the recovery planning. This study describes the analysis of landslide-damaged areas using ISODATA(Iterative Self-Organizing Data Analysis Technique Algorithm) with Sentinel-2 image, regarding the case of Gokseong in August 7, 2020. A total of 4.75 ha of landslide-damaged areas was detected from the Sentinel-2 image using spectral characteristics of red, NIR(Near Infrared), and SWIR(Shortwave Infrared) bands. We made sure that the satellite remote sensing is an effective method to detect the landslide-damaged areas and support the establishment of the recovery planning, followed by the field surveys that require a lot of manpower and time. Also, this study can be used as a reference for the landslide management for the CAS500-1/2(Compact Advanced Satellite) scheduled to launch in 2021 and the Korean Medium Satellite for Agriculture and Forestry scheduled to launch in 2024.

• Journal of Powder Materials
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• v.28 no.2
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• pp.143-149
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• 2021

In this study, (GaN)_1-x(ZnO)_x solid solution nanoparticles with a high zinc content are prepared by ultrasonic spray pyrolysis and subsequent nitridation. The structure and morphology of the samples are investigated by X-ray diffraction (XRD), field-emission scanning electron microscopy, and energy-dispersive X-ray spectroscopy. The characterization results show a phase transition from the Zn and Ga-based oxides (ZnO or ZnGa₂O₄) to a (GaN)_1-x(ZnO)_x solid solution under an NH3 atmosphere. The effect of the precursor solution concentration and nitridation temperature on the final products are systematically investigated to obtain (GaN)_1-x(ZnO)_x nanoparticles with a high Zn concentration. It is confirmed that the powder synthesized from the solution in which the ratio of Zn and Ga was set to 0.8:0.2, as the initial precursor composition was composed of about 0.8-mole fraction of Zn, similar to the initially set one, through nitriding treatment at 700℃. Besides, the synthesized nanoparticles exhibited the typical XRD pattern of (GaN)_1-x(ZnO)_x, and a strong absorption of visible light with a bandgap energy of approximately 2.78 eV, confirming their potential use as a hydrogen production photocatalyst.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.91-108
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• 2022

In most cases, optical images have been used as training data of DL (Deep Learning) models for object detection, recognition, identification, classification, semantic segmentation, and instance segmentation. However, properties of 3D objects in the real-world could not be fully explored with 2D images. One of the major sources of the 3D geospatial information is DSM (Digital Surface Model). In this matter, characteristic information derived from DSM would be effective to analyze 3D terrain features. Especially, man-made objects such as buildings having geometrically unique shape could be described by geometric elements that are obtained from 3D geospatial data. The background and motivation of this paper were drawn from concept of the intrinsic image that is involved in high-level visual information processing. This paper aims to extract buildings after classifying terrain features by training DL model with DSM-derived information including slope, aspect, and SRI (Shaded Relief Image). The experiments were carried out using DSM and label dataset provided by ISPRS (International Society for Photogrammetry and Remote Sensing) for CNN-based SegNet model. In particular, experiments focus on combining multi-source information to improve training performance and synergistic effect of the DL model. The results demonstrate that buildings were effectively classified and extracted by the proposed approach.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.135-155
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• 2022

This study analyzes patent trends by deriving sub-technical fields of Organic Light-Emitting Diodes (OLEDs) industry, and analyzing technology value, originality, and diversity for each sub-technical field. To collect patent data, a set of international patent classification(IPC) codes related to OLED technology was defined, and OLED-related patents applied from 2005 to 2017 were collected using a set of IPC codes. Then, a large number of collected patent documents were classified into 12 major technologies using the Latent Dirichlet Allocation(LDA) topic model and trends for each technology were investigated. Patents related to touch sensor, module, image processing, and circuit driving showed an increasing trend, but virtual reality and user interface recently decreased, and thin film transistor, fingerprint recognition, and optical film showed a continuous trend. To compare the technological value, the number of forward citations, originality, and diversity of patents included in each technology group were investigated. From the results, image processing, user interface(UI) and user experience(UX), module, and adhesive technology with high number of forward citations, originality and diversity showed relatively high technological value. The results provide useful information in the process of establishing a company's technology strategy.

• Geophysics and Geophysical Exploration
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• v.26 no.1
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• pp.8-17
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• 2023

Various sources, such as wind, waves, ships, and gas leaks from the seafloor, forms bubbles in the ocean. Underwater bubbles cause signal scattering, considerably affecting acoustic measurements. This characteristic of bubbles is used to block underwater noise by attenuating the intensity of the propagated signal. Recently, researchers have been studying the large-scale release of methane gas as bubble plumes from the seabed. Understanding the physical properties and distribution of bubble plumes is crucial for studying the relation between leaked methane gas and climate change. Therefore, a water tank experiment was conducted to estimate the distribution of bubble plumes using seismic imaging techniques and acoustic signals obtained from artificially generated bubbles using a bubble generator. Reverse time migration was applied to image the bubble plumes while the acquired acoustic envelope signal was used to effectively estimate bubble distribution. Imaging results were compared with optical camera images to verify the estimated bubble distribution. The water tank experiment confirmed that the proposed system could successfully image the distribution of bubble plumes using reverse time migration and the envelope signal. The experiment showed that the scattering signal of artificial bubble plumes can be used for seismic imaging.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.233-247
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• 2023

Recently, research on detecting objects in hidden spaces beyond the direct line-of-sight of observers has received attention. Most studies use optical equipment that utilizes the directional of light, but sound that has both diffraction and directional is also suitable for non-line-of-sight(NLOS) research. In this paper, we propose a novel method of detecting objects in non-line-of-sight (NLOS) areas using acoustic signals in the audible frequency range. We developed a deep learning model that extracts information from the NLOS area by inputting only acoustic signals and predicts the properties and location of hidden objects. Additionally, for the training and evaluation of the deep learning model, we collected data by varying the signal transmission and reception location for a total of 11 objects. We show that the deep learning model demonstrates outstanding performance in detecting objects in the NLOS area using acoustic signals. We observed that the performance decreases as the distance between the signal collection location and the reflecting wall, and the performance improves through the combination of signals collected from multiple locations. Finally, we propose the optimal conditions for detecting objects in the NLOS area using acoustic signals.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.77.1-77.1
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• 2021

한국천문연구원은 천문우주분야의 과학임무 탑재체 개발을 주도적으로 수행해오고 있다. 과학기술위성1호 주탑재체 원자외선영상분광기 FIMS 개발, 과학기술위성3호 주탑재체 다목적적외선영상시스템 MIRIS 개발, 차세대소 형위성1호 주탑재체 근적외선영상분광기 NISS 개발을 수행하였고, 현재는 NASA와 국제협력으로 SPHEREx 우주 망원경을 개발하고 있다. 이러한 개발 과정을 거치면서 주경 20cm 이하의 소형 탑재체 과학임무 한계와 더불어 연구 현장에서 더 큰 우주망원경의 수요가 제기되었고, 현재의 국가우주개발 중장기계획에도 2030년대 한국형 우주망원경을 포함하게 되었다. 이러한 일정에 발맞추어 한국천문연구원은 2030년대 한국형 우주망원경 독자 운영을 대비하기 위해서 2020년 1월부터 주요 사업으로 한국형 우주망원경 개발을 위한 기획연구를 시작하였다. 이 기획연구는 2021년 말까지 2년 동안 수행하고 있으며, 이 기획연구를 통해서 학계의 과학임무 요구사항을 종합 수렴하였고, 관련 컨설팅 업체와 협업하여 사전 기획연구 활동들을 수행하였으며, 향후 우주망원경 개발에 대한 전략을 제안하고 보고서를 마무리하는 단계에 와 있다. 이 발표에서는 이러한 기획연구의 세부 활동을 공유하고 보고하고자 한다.