• 한국안전학회지
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• 제20권4호
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• pp.171-179
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• 2005

건물의 마감재료가 화재에 노출될 때 그 마감재료의 역할을 이해하는 것은 필수적이다. 실물화재실험을 통해서 재료의 성능을 평가하는 것이 가능하다. 그러나 실물화재 실험 시 소요되는 시간과 높은 비용으로 인해 실물 화재 실험이 수행되는 경우는 드물고 대신 컴퓨터 화재 시뮬레이션이 개발되어 왔다. 컴퓨터 화재 시뮬레이션에서는 초기입력 데이터로서 점화 버너의 화염으로부터의 Heat Flux Map이 요구된다. 현재까지의 연구에서는 열전대 혹은 열유속 센서와 같은 실험장치의 제한으로 인해 $10kW/m^2$간격의 Heat Flux Map이 나와있을 뿐이고 공간적으로 더 상세한 Heat Flux Map은 없는 실정이다. 화재 시뮬레이션의 성능을 증가시키기 위해서는 점화 버너로부터의 정확하고 상세한 Heat Flux Map이 필요불가결하다. 본 연구의 목적은 적외선 카메라로부터 얻어진 표면온도를 이용하여 벽에서 점화 버너 화염에 대한 Heat Flux Happing Procedure를 개발하는 것이다. 높은 수준의 공간적 해상도는 적외선 카메라로부터 제공된다. 개발된 Heat Flux Mapping Procedure를 증명하기 위해서 ISO 9705 점화버너를 이용해서 실험이 행해졌다. 실험 결과를 통해 개발된 Heat Flux Mapping방법의 열유속 해상도와 공간적 해상도가 얻어졌다. 또한 그 실험 결과가 현재 쓰여지고 있는 Heat Flux Map과 비교되었다.

• 한국정보과학회논문지:시스템및이론
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• 제34권5_6호
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• pp.228-237
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• 2007

역변위 매핑은 기하정보를 증가시키지 않고, 모델에 상세함을 더하는데 사용된다. 우리는 부드럽고 정확한 굴곡을 표현할 수 있는 GPU 기반의 실시간 역변위 매핑 기법을 제안한다. 이를 위하여, 렌더될 각 픽셀에서 광선을 만들고 이를 전진시켜 나가며 변위 맵과의 교차점을 찾는다. 광선 추적을 안전하고 효율적으로 수행하기 위하여, 변위 맵을 쿼드트리 형태의 이미지 피라미드로 만들고, 이 트리를 하향식으로 탐색하며 전진해 나간다. 나아가, 변위 맵이 화면에서 확대되었을 때 선형 보간을, 그리고 화면에서 멀어져 작게 보일때는 때는 밉맵 필터링을 통해 화질을 향상시키고 렌더링을 가속화한다. 실험을 통해, 기존의 GPU 기반의 기법들과는 달리 날카로운 변위 맵에 대해 예각에서도 깨끗한 이미지를 생성하는 것을 확인하였다. 초당 수 백 프레임의 빠른 속도로 렌더링할 수 있었으며, 변위 맵의 해상도가 커져도 렌더링 속도의 저하가 적었다. 우리의 기법은 구현이 간단하고 수행속도가 빠르기 때문에 현존하는 게임이나 가상 현실 시스템 등에 쉽게 적용할 수 있다.

• 패션비즈니스
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• 제13권6호
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• pp.20-30
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• 2009

The purpose of this study is to develop the effective customized elderly fashion marketing process based on the web site, where older customer will be able to choose various fabrics and to try them out. This aims to establish new prototype of internet shopping mall for customized elderly fashion clothing. In this study, new method of product presentation on the online shopping mall is proposed to offer product information through 3D virtual reality. With the online shopping mall(SATC Mall) as a showcase, we presented virtual mapping system so that it enable the customers to select the fabrics and to see exactly how chosen fabric will look when applied to image of clothing. As an initial test of the application of simulation to measure 3D visualization of product, mapping software Vision Easy Map Pro Version 6.0(NedGraphics) Vision Easy Map Viewer Version 5.0(NedGraphics) were chosen and applied. By using this mapping system, the fabric change of the apparel product could be made on the internet shopping web site. However, this approach has been successful applied for presenting and customizing garment products. Future research will focus on the integration of mapping coordination into SATC Mall.

• Asian-Australasian Journal of Animal Sciences
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• 제19권12호
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• pp.1702-1705
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• 2006

A simulation study was conducted to evaluate a fine-mapping method exploiting population-wide linkage disequilibrium. Data were simulated according to the pedigree structure based on a large paternal half-sib family population with a total of 1,034 or 2,068 progeny. Twenty autosomes of 100 cM were generated with 5 cM or 1 cM marker intervals for all founder individuals in the pedigree, and marker alleles and a number of quantitative trait loci (QTL) explaining a total of 70% phenotypic variance were generated and randomly assigned across the whole chromosomes, assuming linkage equilibrium between the markers. The founder chromosomes were then descended through the pedigree to the current offspring generation, including recombinants that were generated by recombination between adjacent markers. Power to detect QTL was high for the QTL with at least moderate size, which was more pronounced with larger sample size and denser marker map. However, sample size contributed much more significantly to power to detect QTL than map density to the precise estimate of QTL position. No QTL was detected on the test chromosomes in which QTL was not assigned, which did not allow detection of false positive QTL. For the multiple QTL that were closely located, the estimates of the QTL positions were biased, except when the QTL were located on the right marker positions. Our fine mapping simulation results indicate that construction of dense maps and large sample size is needed to increase power to detect QTL and mapping precision for QTL position.

• 대한안전경영과학회지
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• 제1권1호
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• pp.197-206
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• 1999

Mind mapping is an efficient thinking skill which utilizes the whole left-right brain. The several studies which examine the effects of the mind map activities on the school education attain the desirable enhancement of the students' schoolwork achievement ＆ learning attitude. We now propose the utilization of the mind map activities at the safety education in order to decrease the students' accidents in school and to enhance the awareness of safety.

• 신재생에너지
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• 제3권1호
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• pp.20-26
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• 2007

A low-resolution national wind map, which is a prerequisite for setting up the national dissemination target and strategy of wind energy development, has been established by numerical wind simulation using the synoptic wind map, developed at the first stage, as an upper boundary condition. Based on the wind map, Wind Resource Information System has been composed in order to support scientific and systematic wind resource assessment and analysis.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.101.1-101
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• 2001

This paper describes a grid mapping for a vision based mobile robot in uncertain indoor environment. The map building is a prerequisite for navigation of a mobile robot and the problem of feature correspondence across two images is well known to be of crucial Importance for vision-based mapping We use a stereo matching algorithm obtained by singular value decomposition of an appropriate correspondence strength matrix. This new correspondence strength means a correlation weight for some local measurements to quantify similarity between features. The visual range data from the reconstructed disparity image form an occupancy grid representation. The occupancy map is a grid-based map in which each cell has some value indicating the probability at that location ...

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.856-858
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• 2003

Biotop map can be utilized in the urban area for nature conservation and impact assessment for the proposed activities. High resolution satellite data such as IKONOS and KOMPSAT1-EOS were used to classify land use activities in biotop mapping. After land use classification, field -check was done to survey the wildlife and vegetation. These maps were combined and the boundaries were delineated to produce the biotop map. Within the boundary the characteristics of each polygon were identified, and named. This study was carried out at Daedok Science Town in Taejeon Metropolitan Area. The purpose of this study is to produce the biotop map using high resolution remote sensing data together with other ground data.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2014년도 추계학술대회
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• pp.652-653
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• 2014

본 논문에서는 카르노 맵상에서 생성된 Cell [fi]을 이용하여 GRM 상수를 생성하는 방법에 대해 논의하였다. Cell을 이용한 방법은 GRM 상수를 구하는 일반적인 방법과는 다르게 카르노 맵상에서 임의의 Cell들을 선택하여 그 Cell들을 단일변수 변환행렬과 연산해서 다시 카르노 맵으로 mapping하는 방법이다. 또한 이 방법을 극수의 순환성에 적용하여 새로운 GRM 상수 생성 방법에 대해 논의하였다.

• 한국측량학회지
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• 제36권5호
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• pp.423-432
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• 2018

Surface water mapping has been widely used in various remote sensing applications. Water indices have been commonly used to distinguish water bodies from land; however, determining the optimal threshold and discriminating water bodies from similar objects such as shadows and snow is difficult. Deep learning algorithms have greatly advanced image segmentation and classification. In particular, FCN (Fully Convolutional Network) is state-of-the-art in per-pixel image segmentation and are used in most benchmarks such as PASCAL VOC2012 and Microsoft COCO (Common Objects in Context). However, these data sets are designed for daily scenarios and a few studies have conducted on applications of FCN using large scale remotely sensed data set. This paper aims to fine-tune the pre-trained FCN network using the CRMS (Coastwide Reference Monitoring System) data set for surface water mapping. The CRMS provides color infrared aerial photos and ground truth maps for the monitoring and restoration of wetlands in Louisiana, USA. To effectively learn the characteristics of surface water, we used pre-trained the DeepWaterMap network, which classifies water, land, snow, ice, clouds, and shadows using Landsat satellite images. Furthermore, the DeepWaterMap network was fine-tuned for the CRMS data set using two classes: water and land. The fine-tuned network finally classifies surface water without any additional learning process. The experimental results show that the proposed method enables high-quality surface mapping from CRMS data set and show the suitability of pre-trained FCN networks using remote sensing data for surface water mapping.