• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.661-664
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• 2008

U-Eco City is promoted nation-wide by development of recent IT technology, method of effective countermeasure disasters, which real-time wire/wireless communication network, and 3D-Web GIS shall be connected that massive database, intelligent service be perceived. U&V-City is the four-dimensional future city that actualizes an intelligent daily ubiquitous computing service by embodying 3D-Virtual City, the reproduction of real world U-City while using Digital map, satellite image, VRML(Virtual Reality Modeling Language), which are presentation tool to describe city components and by efficiently catch and cope about nature and human disasters while employing EAI(External Authoring Interface) that provides HTML&JAVA, and interface for efficient removal/process of massive information/service and also by employing GPS/LBS/Navigation in support of the world-wide orientation concept, and RTLS(Real Time Location System).

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.132-134
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• 2003

The likelihood ratio, logistic regression and artificial neural networks methods are applied and verified for analysis of landslide susceptibility in Yongin, Korea using GIS. From a spatial database containing such data as landslide location, topography, soil, forest, geology and land use, the 14 landsliderelated factors were calculated or extracted. Using these factors, landslide susceptibility indexes were calculated by likelihood ratio, logistic regression and artificial neural network methods. Before the calculation, the study area was divided into two sides (west and east) of equal area, for verification of the methods. Thus, the west side was used to assess the landslide susceptibility, and the east side was used to verify the derived susceptibility. The results of the landslide susceptibility analysis were verified using success and prediction rates. The v erification results showed satisfactory agreement between the susceptibility map and the exis ting data on landslide locations.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.296-296
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• 2019

전 세계적으로 기후변화로 인한 국지성 집중호우 및 태풍으로 인한 피해가 지속적으로 발생하고 있으며, 그에 따른 2차 피해인 산사태 및 토석류 피해 또한 증가하고 있는 추세이다. 최근 국내의 산사태 및 토석류에 대한 선행연구는 지속적으로 수행되고 있으나, 산사태 및 토석류 위험성이 높은 구간, 즉, 발생기작을 판단할 수 있도록 지표화 해놓은 것이며, 현재 피해예측지도 및 피해 하류부의 시설물을 고려한 연구는 미비한 실정이다. 따라서 본 연구에서는 강우-유출모형인 S-RAT모형 및 토석류 수치해석 프로그램 RAMMS 모형을 이용하여 산사태 및 토석류 피해를 극대화 시키는 인자인 토석유동심(H), 토석유속(V)을 이용하여 토석류피해예측지도를 작성하였으며, 피해 하류부의 시설물을 건물 유형별 시설물의 중요도로 구분하였다. 또한 작성된 피해예측지도 및 시설물 중요도를 중첩하여 위험성 지도를 제시하였다.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.33.1-33.1
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• 2019

Protostars grow their mass by the accretion of disk material, which is infalling from the envelope. This accretion process is important to the physical and chemical conditions of the disk and envelope, and thus, the planets yet to be formed from the disk material. Therefore, if we map the physical and chemical properties of disks and envelopes, we can study indirectly the accretion process in star formation. In particular, the chemical distribution in the disk and the inner envelope of a young stellar object is greatly affected by the thermal history, which is mainly determined by the accretion process in the system. In my talk, I will review the episodic accretion model for the low mass star formation and observational efforts to find the evidence of episodic accretion. Finally, I will present our recent ALMA detection of several complex organic molecules associated directly with the planet formation in V883 Ori, which is in the burst accretion phase.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.97-108
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• 2022

The video-assisted human action recognition [1] field is one of the most active ones in computer vision research. Since the depth data [2] obtained by Kinect cameras has more benefits than traditional RGB data, research on human action detection has recently increased because of the Kinect camera. We conducted a systematic study of strategies for recognizing human activity based on deep data in this article. All methods are grouped into deep map tactics and skeleton tactics. A comparison of some of the more traditional strategies is also covered. We then examined the specifics of different depth behavior databases and provided a straightforward distinction between them. We address the advantages and disadvantages of depth and skeleton-based techniques in this discussion.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.663-665
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• 2009

Ubi-Home 환경에서 장치제어를 하기위해 다양한 방법이 제안되었다. 그 중 원격지에서 장치제어를 하기 위해 특정 기기(로봇)를 활용할 수 있다. 하지만 이와 같은 방법에는 로봇과 장치들의 위치인식과 이동경로 설정에 따른 제약사항이 따른다. 또한 이러한 위치인식 및 이동에는 미리 작성된 하나의 맵이 사용되므로 새로운 환경의 변화나 확장에 적용할 수 없다. 따라서 본 논문에서는 로봇과 장비의 위치인식과 이동경로를 위한 학습형 맵 작성 기법을 제안하며, 테스트를 위해 Atmega128v4 MCU와 AX-12+ Motor, AX-S1 Sensor, ZBS-200 Zigbee, CL-1L5/603LM Infrared Ray Sensor로 로봇을 제작하여 실내 환경 모형에서 테스트하였다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.1343-1345
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• 2022

본 논문에서는 다해상도 피라미드 피처 맵 압축 손상 보상 방법을 제안한다. 본 논문에서 제안하는 방법은 패킹된 C-레이어 피처 맵을 비디오 코덱으로 압축할 때, 저해상도 계층의 원본 피처 맵과 복원된 피처 맵 간의 차분 값을 구해 이를 고해상도 계층의 피처 맵에 더해줌으로써 부호화 과정에서 발생하는 오차를 보상하는 방법이다. 본 논문에서 제안하는 방법의 성능을 평가하기 위하여 OpenImageV6 데이터셋 중 1000 장에 대해 객체 검출 성능을 평가하였다. 본 논문에서 제안하는 피처 맵 압축 방법은 C-레이어 피처 맵 압축 방법 대비 bpp 와 mAP 의 BD-rate 관점에서 35.10%의 성능 향상을 보인다.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.31 no.4
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• pp.207-213
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• 2018

This paper investigates applicability of Microsoft $Kinect^{(R)}$, RGB-depth camera, to implement a 3D image and spatial information for sensing a target. The relationship between the image of the Kinect camera and the pixel coordinate system is formulated. The calibration of the camera provides the depth and RGB information of the target. The intrinsic parameters are calculated through a checker board experiment and focal length, principal point, and distortion coefficient are obtained. The extrinsic parameters regarding the relationship between the two Kinect cameras consist of rotational matrix and translational vector. The spatial images of 2D projection space are converted to a 3D images, resulting on spatial information on the basis of the depth and RGB information. The measurement is verified through comparison with the length and location of the 2D images of the target structure.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.938-958
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• 2024

Unsupervised Video Object Segmentation (UVOS) is a highly challenging problem in computer vision as the annotation of the target object in the testing video is unknown at all. The main difficulty is to effectively handle the complicated and changeable motion state of the target object and the confusion of similar background objects in video sequence. In this paper, we propose a novel deep Dual-stream Co-enhanced Network (DC-Net) for UVOS via bidirectional motion cues refinement and multi-level feature aggregation, which can fully take advantage of motion cues and effectively integrate different level features to produce high-quality segmentation mask. DC-Net is a dual-stream architecture where the two streams are co-enhanced by each other. One is a motion stream with a Motion-cues Refine Module (MRM), which learns from bidirectional optical flow images and produces fine-grained and complete distinctive motion saliency map, and the other is an appearance stream with a Multi-level Feature Aggregation Module (MFAM) and a Context Attention Module (CAM) which are designed to integrate the different level features effectively. Specifically, the motion saliency map obtained by the motion stream is fused with each stage of the decoder in the appearance stream to improve the segmentation, and in turn the segmentation loss in the appearance stream feeds back into the motion stream to enhance the motion refinement. Experimental results on three datasets (Davis2016, VideoSD, SegTrack-v2) demonstrate that DC-Net has achieved comparable results with some state-of-the-art methods.

• Applied Chemistry for Engineering
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• v.8 no.5
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• pp.796-803
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• 1997

The PVT and $^2H$-NMR characteristic of main-chain dimer liquid crystals having structures such as ${\alpha}$, ${\omega}$-bis[4,4'-cyanobiphenyl) oxy] alkane(CBA-10) were studied. In this work, V-T curves obtained from isobaris measurements on various pressures, volume changes were observed at the nematic-isotropic and nematic-crystal phase transition. The volume changes at the transition exhibit slight odd-even effect with respect to the number of methylene unit n. The values of the$({\Delta}S_{tr})_V$ obtained at the NI transition for CBA-10 was $12.6J/mol{\cdot}K$. The values of $({\Delta}S_{CN})_V$ for the CN transition was estimated on the basis of DSC data : $65.3J/mol{\cdot}K$. For both transition, it was found that the correction about the volume change is significant, ranging from 40 to 60% of the total transition entropy observed under constant pressure. The RIS analysis of the spectra was performed so as to elucidate the conformational characteristics of the spacer in the nematic phase. The conformational entropy changes at both CN and NI interphases were estimated on the basis of the nematic conformations taken from the conformation map as well as those derived from the simulation. The estimated conformational entropy change values were then compared with the corresponding constant-volume entropies obtained from PVT measurements. The correspondence between both entropy values was found to be quite good in consideration of the uncertainties involved in both experiment and calculations.