• Korean Journal of Remote Sensing
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• v.26 no.5
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• pp.593-603
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• 2010

Most spatial data acquisition systems employing a set of frame cameras may have suffered from their small fields of view and poor base-distance ratio. These limitations can be significantly reduced by employing an omni-directional camera that is capable of acquiring images in every direction. Bundle Block Adjustment (BBA) is one of the existing georeferencing methods to determine the exterior orientation parameters of two or more images. In this study, by extending the concept of the traditional BBA method, we attempt to develop a mathematical model of BBA for omni-directional images. The proposed mathematical model includes three main parts; observation equations based on the collinearity equations newly derived for omni-directional images, stochastic constraints imposed from GPS/INS data and GCPs. We also report the experimental results from the application of our proposed BBA to the real data obtained mainly in urban areas. With the different combinations of the constraints, we applied four different types of mathematical models. With the type where only GCPs are used as the constraints, the proposed BBA can provide the most accurate results, ${\pm}5cm$ of RMSE in the estimated ground point coordinates. In future, we plan to perform more sophisticated lens calibration for the omni-directional camera to improve the georeferencing accuracy of omni-directional images. These georeferenced omni-directional images can be effectively utilized for city modelling, particularly autonomous texture mapping for realistic street view.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.spc4_2
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• pp.401-412
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• 2014

This study is purposed on showing an effective process for coordinate transformation of cadastral maps, based on the local datum, in the World Geodetic System (WGS) for Cadastral Reform Project (CRP). The process follows three steps: coordinate adjustment, datum transformation and distortion modeling. The first procedure is that point coordinates on local datum has to be adjusted by those GPS observed point-to-point distances, using trilateration. Secondly, the adjusted coordinates need to be transformed to WGS by applying the Affine model, while the verification of the methodology is implemented under numerical experiments. To conduct this procedure, 195 points in the same coordinate origins in Seoul and 61 points in several different origins in Incheon are used in the estimation. As a result, there are less than 2cm coordinate differences between transformed coordinates and measured ones at everywhere. Also, it is remarkable that the transformation does not depend on either of the particular common points or the sizes of computed region. Therefore, this suggested methodology is expected to easily provide identifications and corrections for points-deviations for improved quality of the cadastral map by distortion modeling through CRP.

• 산림경영
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• s.133
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• pp.4-7
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• 1998

과거의 조림을 중심으로 하던 녹화임정을 산림의 이용을 증진하도록 하는 경영임정으로 바꾸기 위한 패러다임 전환은 1.적극적인 산업정신 형성 2.시대통찰력 가진 전문가 양성 3.산림경영의 비효율성 제거방안 4. 산림경영모델(범위경영) 확립 5.정부의 실질적인 역할조정 등 5가지 주요문제를 검토하여 우리실정에 맞도록 새롭게 정립하여야 한다.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.1541-1542
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• 2013

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2006.07a
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• pp.379-379
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• 2006

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.59-60
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• 2011

• Annual Conference on Human and Language Technology
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• 2022.10a
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• pp.507-511
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• 2022

문법 교정 모델은 입력된 텍스트에 존재하는 문법 오류를 탐지하여 이를 문법적으로 옳게 고치는 작업을 수행하며, 학습자에게 더 나은 학습 경험을 제공하기 위해 높은 정확도와 재현율을 필요로 한다. 이를 위해 최근 연구에서는 문단 단위 사전 학습을 완료한 모델을 맞춤법 교정 데이터셋으로 미세 조정하여 사용한다. 하지만 본 연구에서는 기존 사전 학습 방법이 문법 교정에 적합하지 않다고 판단하여 문단 단위 데이터셋을 문장 단위로 나눈 뒤 각 문장에 G2P 노이즈와 편집거리 기반 노이즈를 추가한 데이터셋을 제작하였다. 그리고 문단 단위 사전 학습한 모델에 해당 데이터셋으로 문장 단위 디노이징 사전 학습을 추가했고, 그 결과 성능이 향상되었다. 노이즈 없이 문장 단위로 분할된 데이터셋을 사용하여 디노이징 사전 학습한 모델을 통해 문장 단위 분할의 효과를 검증하고자 했고, 디노이징 사전 학습하지 않은 기존 모델보다 성능이 향상되는 것을 확인하였다. 또한 둘 중 하나의 노이즈만을 사용하여 디노이징 사전 학습한 두 모델의 성능이 큰 차이를 보이지 않는 것을 통해 인공적인 무작위 편집거리 노이즈만을 사용한 모델이 언어학적 지식이 필요한 G2P 노이즈만을 사용한 모델에 필적하는 성능을 보일 수 있다는 것을 확인할 수 있었다.

• Korean Journal of Psychosomatic Medicine
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• v.16 no.1
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• pp.17-24
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• 2008

Psychosomatic medicine is also known as consultation-liaison psychiatry. Pediatric consultation-liaison psychiatry is composed of all consultation, liaison, diagnostic, therapeutic support and research activities carried out by psychiatrists and other mental professionals in pediatric ward to provide mental health services to physically ill pediatric patients. As the differences in the basic concepts of disease models between psychiatry (psychosocial model) and pediatrics(biomedical model) exist, active communication between the child psychiatrist and pediatric medical staffs is required. Although the general guidelines are similar, there are specific considerations for consultation in children and adolescents. Much work is still needed to identify empirically supported treatments which are effective for managing a board range of psychosocial difficulties in children and adolescents.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.19 no.5
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• pp.457-466
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• 2007

The effect of depth correction in the coastal sea has been investigated through a series of tide simulations in the area of $115{\sim}150^{\circ}E,\;20{\sim}52^{\circ}N$ of northwestern Pacific with $1/12^{\circ}$ resolution. Comparison of the solutions varying the minimum depth from 10m to 35 m with the 5m interval shows that the amplitude accuracies of $M_2,\;S_2,\;K_1$ tide using the minimum depth of 25 m have been improved up to 42%, 32%, 26%, respectively, comparing to those using the minimum depth of 10m. The discrepancy between model results using different minimum depth is found to be up to 20 cm for $M_2$ tidal amplitude around Cheju Islands and the positions of amphidromes are dramatically changed in the Bohai Sea. The calculated ARE(Averaged Relative Error) values have been minimized when the bottom frictional coefficient and the minimum depth is 0.0015 and 25 m, respectively.

• The Journal of the Korea Contents Association
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• v.21 no.9
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• pp.105-116
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• 2021

Habruta is a question-based learning that talks, discusses, and argues in pairs. In particular, the famous painting Habruta is being implemented for the purpose of enhancing the appreciation ability of paintings and enriching the expressive power through questions and answers about the famous paintings. In this study, in order to support the famous painting Habruta for oriental paintings, we propose a method of automatically generating questions from the gender perspective of oriental painting characters using the current deep learning technology. Specifically, in this study, based on the pre-trained model, VGG16, we propose a model that can effectively analyze the features of Asian paintings by performing fine-tuning. In addition, we classify the types of questions into three types: fact, imagination, and applied questions used in the famous Habruta, and subdivide each question according to the character to derive a total of 9 question patterns. In order to verify the feasibilityof the proposed methodology, we conducted an experiment that analyzed 300 characters of actual oriental paintings. As a result of the experiment, we confirmed that the gender classification model according to our methodology shows higher accuracy than the existing model.