33 research outputs found
๊ณ ํด์๋ PET ์์คํ ์ ์ํ PET ๊ฒ์ถ๊ธฐ์ 3์ฐจ์ ์์น ์ ๋ณด ์ ํ๋ ํฅ์ ๊ธฐ์ ๊ฐ๋ฐ
ํ์๋
ผ๋ฌธ (๋ฐ์ฌ)-- ์์ธ๋ํ๊ต ๋ํ์ : ์๊ณผ๋ํ ํ๋๊ณผ์ ๋ฐฉ์ฌ์ ์์ฉ์๋ช
๊ณผํ์ ๊ณต, 2018. 2. ์ด์ฌ์ฑ.The positron emission tomography (PET) is a widely used imaging modality that provides biological information at the molecular level. The biological information in molecular and cellular level enables a new discovery in both pre-clinical studies and clinical cases. However, due to the fundamental limits of the spatial resolution in the PET system, the effectiveness of PET is limited when diagnosing small-sized lesions. Hence, improving the spatial resolution in PET is important for the maximization of the diagnosing power of the PET system.
In this thesis, studies on enhancing 3-dimensional (3D) positioning accuracy in PET detector for the high resolution PET system were conducted and presented. The depth-of-interaction (DOI) encoding/decoding and inter-crystal scattering (ICS) event identification technologies were developed and evaluated in the PET detector and system level.
Firstly, the DOI encoding PET detector was developed and detector performances were evaluated. Maximum-likelihood estimation based DOI decoding methodology was developed and optimization studies in several aspects were conducted to achieve the high z-axis positioning accuracy. Secondly, based on the developed DOI encoding/decoding technologies, a prototype DOI PET system was developed and system-level performances were evaluated. Phantom and animal imaging studies were conducted to evaluate imaging performances of the prototype DOI PET system. The proposed DOI encoding/decoding technology was successfully demonstrated at the system level showing its feasibility for the high resolution PET application. Thirdly, a new ICS event identification method was proposed: a new technology of classifying and identifying ICS events in PET detectors with light sharing design, which was not feasible with existing technologies. The proposed method was validated by conducting simulation and experimental studies. By recovering identified ICS events, which is improving x- and y-direction positioning accuracy in the PET detector, improvement in the PET intrinsic spatial resolution was observed. In conclusion, the technologies developed in this thesis enhanced the spatial resolution of the PET system.Chapter 1. Introduction 1
1.1. Background 1
1.2. Purpose of this study 5
Chapter 2. Depth-of-interaction PET detector 7
2.1. Background 7
2.2. Materials and methods 10
2.2.1. Continuous DOI-encoding detector 10
2.2.2. DOI decoding methodology 11
2.2.3. DOI detector optimization study 13
2.3. Results 19
2.3.1 DOI detector optimization results 19
2.3.2 DOI detector performances 23
2.4 Discussion 29
Chapter 3. Depth-of-interaction PET system 30
3.1. Background 30
3.2. Materials and methods 30
3.2.1. DOI-encoding PET detector 30
3.2.2. Prototype PET scanner 32
3.2.3. Detector performance evaluation 34
3.2.4. Spatial resolution measurement 35
3.2.5. Phantom and animal imaging studies 36
3.3. Results 37
3.3.1. Detector performance 37
3.3.2. Spatial resolution of prototype system 39
3.3.3. Phantom and animal imaging study 40
3.4 Discussion 43
Chapter 4. Inter-crystal event identification 45
4.1. Background 45
4.2. Materials and methods 47
4.2.1. ICS event identification 47
4.2.2. Monte Carlo simulation study 50
4.2.3. ICS event recovery scheme 51
4.2.4. Experimental study 52
4.3. Results 55
4.3.1. Simulation results 55
4.3.2. Experimental results 62
4.4. Discussion 68
Chapter 5. Conclusion 71
Bibliography 73
Abstract in Korean 77Docto
์ฃผ๋ณ ์กฐ์ง๊ณผ์ ๊ฒฝ๊ณ๋ฉด ๋ถํ ์ ๋ํ ๊ณ ์ฐฐ
ํ์๋
ผ๋ฌธ(์์ฌ) -- ์์ธ๋ํ๊ต๋ํ์ : ์น๊ณผ๋ํ ์น์๊ณผํ๊ณผ, 2022. 8. ์ด์ฌ์ผ.Objectives
The purpose of this study is to examine whether deep learning technique can be used as an efficient and consistent aids in the bone histomorphometry of dental implant tissue images. To this end, the image segmentation accuracy of the implant and the surrounding tissue was evaluated compared to the previously developed staining color-based method.
Methods
In this study, images taken at 200x magnification from 16 dental implant specimens placed in the tibiae of rabbits were used. Through image annotation processing for use as ground truth, an entire image was divided into two classes: an implant area and a tissue area. The region of interest(ROI) was set around the boundary line of the two classes. The artificial intelligence methodologies used in this study are kNN and deep learning U-Net models, where kNN is a method of segmenting color based on the representative pixel value(instance) of each class. The U-Net is a model actively used in AI-based medical image segmentation research. This study used the Vanilla U-Net, which is the most basic structure. To compare the results between the two methodologies, test images not used for deep learning training were used. The ground truth image and the predicted image were compared on a pixel-by-pixel basis, and the accuracy, sensitivity, and the area under the ROC curve (AUROC) were evaluated. Also, the segmentation accuracy was compared using two evaluation indicators: IOU (Intersection Over Union) and DSC (Dice Similarity Coefficient).
Results
An instance was designated by randomly selecting a single image from kNN, and the accuracy with ground truth was compared as an IOU index by extracting predicted results from all image data. The accuracy of ROI was 90.39% on average in the range of 65-96%. Of these, the lowest accuracy was 65.83%, which rose to 91.39% when the instances were reselected according to the image, and in the predicted images, it was observed that the boundaries of each class became clearer. Through this, it was confirmed that there is a limitation of requiring the observerโs manual intervention to adjust the reference value each time the tissue image to be evaluated is changed, which is the same limitation shown in the previously developed staining color-based method. In the ROI, based on the implant, the average sensitivity was 90.68% for kNN and 98.32% for U-Net with data augmentation. The accuracy was 94.89% in kNN and 97.86% in U-Net, and AUROC was 93.69% in kNN and 99.79% in U-Net. IOU was 84.19% in kNN and 93.4% in U-Net, and DSC was 91.03% in kNN and 96.58% in U-Net model. When the deep learning method was used, superior performance was confirmed compared to the existing color-based segmentation method. In addition, in the segmented image, it was shown that the segmentation into two classes was more clear than kNN without encroaching on each other.
Conclusions
Deep learning technique can compensate for differences in results between observers that may appear when measuring bone to implant contact (BIC) and bone area (BA), which are important indicators in histological analysis of dental implants. The potential of deep learning technique was confirmed for development as an auxiliary tool to improve the consistency and efficiency of analysis. If tissue images including various aspects are obtained and training based on expert annotations is accompanied, it is determined that it could be used as an assisting means of bone-tissue analysis in pathology laboratories by possibly achieving segmentation accuracy from tissue area to bone and non-bone area.๋ชฉ ์
์ด ์ฐ๊ตฌ์ ๋ชฉ์ ์ ์น๊ณผ์ฉ ์ํ๋ํธ ์กฐ์ง ์ด๋ฏธ์ง์ ๋ผ ์กฐ์งํํ๊ณ์ธก์์ ์ธ๊ณต์ง๋ฅ ๋ฅ๋ฌ๋ ๊ธฐ๋ฒ์ด ํจ์จ์ ์ด๊ณ ์ผ๊ด์ ์ธ ๋ณด์กฐ์๋จ์ผ๋ก ํ์ฉ์ด ๊ฐ๋ฅํ ์ง ๊ณ ์ฐฐํ๋ ๊ฒ์ด๋ค. ์ด๋ฅผ ์ํด ์ผ์๋ ์์ ๊ธฐ๋ฐ์ ์ ํ ๊ฐ๋ฐ ๋ฐฉ์๊ณผ ๋ฅ๋ฌ๋ ๊ธฐ๋ฒ์ ๋น๊ตํ์ฌ ์ํ๋ํธ์ ์ฃผ๋ณ ์กฐ์ง์ผ๋ก์ ์ด๋ฏธ์ง ๋ถํ ์ ํ๋๋ฅผ ํ๊ฐํ์๋ค.
๋ฐฉ ๋ฒ
๋ณธ ์ฐ๊ตฌ์์๋ ํ ๋ผ์ ๊ฒฝ๊ณจ์ ์๋ฆฝ๋ ์น๊ณผ์ฉ ์ํ๋ํธ ํ๋ณธ 16์ฅ์์ 200๋ฐฐ์จ๋ก ์ดฌ์๋ ์ด๋ฏธ์ง๋ฅผ ์ฌ์ฉํ์๋ค. Ground truth๋ก ์ฌ์ฉํ๊ธฐ ์ํ ์ด๋ฏธ์ง ์ฃผ์(annotation) ์ฒ๋ฆฌ๋ฅผ ํตํด ํ๋์ ์ด๋ฏธ์ง ์ ์ฒด๋ฅผ ์ํ๋ํธ ์์ญ๊ณผ ์กฐ์ง ์์ญ์ ๋๊ฐ์ง ํด๋์ค๋ก ๊ตฌ๋ถํ์๋ค. ๊ด์ฌ ์์ญ์ ๋๊ฐ์ง ํด๋์ค์ ๊ฒฝ๊ณ์ ์ ์ค์ฌ์ผ๋ก ์ค์ ํ์๋ค. ์ฐ๊ตฌ์์ ์ฌ์ฉํ ์ธ๊ณต์ง๋ฅ ๋ฐฉ๋ฒ๋ก ์ kNN๊ณผ ๋ฅ๋ฌ๋ U-Net ๋ชจ๋ธ ๋๊ฐ์ง๋ก, kNN์ ์์์ ๋ํ๋ด๋ ๊ฐ ํด๋์ค์ ๋ํ ํฝ์
๊ฐ(instance)์ ๊ธฐ๋ฐํ์ฌ ๋ถํ ์ด ์ด๋ฃจ์ด์ง๋ค. ๋ฅ๋ฌ๋ U-Net ๋ชจ๋ธ์ ์ธ๊ณต์ง๋ฅ ๊ธฐ๋ฐ ์๋ฃ ์ด๋ฏธ์ง ๋ถํ ์ฐ๊ตฌ์์ ํ๋ฐํ๊ฒ ์ฌ์ฉ ์ค์ธ ๋ชจ๋ธ๋ก, ๋ณธ ์ฐ๊ตฌ๋ ๊ฐ์ฅ ๊ธฐ๋ณธ์ ์ธ ๊ตฌ์กฐ์ธ Vanilla U-Net์ ์ฌ์ฉํ์๋ค. ๋๊ฐ์ง ๋ฐฉ๋ฒ๋ก ๊ฐ์ ๊ฒฐ๊ณผ๋ฅผ ๋น๊ตํ๊ธฐ ์ํด ๋ฅ๋ฌ๋ ํ๋ จ์ ์ฌ์ฉํ์ง ์์ ํ
์คํธ ์ด๋ฏธ์ง๋ฅผ ์ฌ์ฉํ์๊ณ , Ground truth ์ด๋ฏธ์ง์ ์์ธก๋ ์ด๋ฏธ์ง๋ฅผ ํฝ์
๋จ์๋ก ๋น๊ตํ์ฌ ์ ํ๋์ ๋ฏผ๊ฐ๋, Area under ROC curve(AUROC)๋ก ํ๊ฐํ์๋ค. ๊ทธ๋ฆฌ๊ณ Intersection Over Union(IOU), Dice similarity coefficient(DSC)์ ๋๊ฐ์ง ์งํ๋ก ๋ํ๋ด์ด ๋ถํ ์ ํ๋๋ฅผ ๋น๊ตํ์๋ค.
๊ฒฐ ๊ณผ
kNN์์ ์์๋ก ํ ์ฅ์ ์ด๋ฏธ์ง๋ฅผ ์ ํํ์ฌ instance๋ฅผ ์ง์ ํ์๊ณ , ๋ชจ๋ ์ด๋ฏธ์ง ๋ฐ์ดํฐ์์ ์์ธก ๊ฒฐ๊ณผ๋ฅผ ์ถ์ถํ์ฌ Ground truth์์ ์ ํ๋๋ฅผ IOU ์งํ๋ก์ ๋น๊ตํ์๋ค. ๊ด์ฌ ์์ญ์ ์ ํ๋๋ 65~96% ๋ฒ์์์ ํ๊ท 90.39%๋ก ๋ํ๋ฌ๋ค. ์ด์ค 65.83%๋ก ๊ฐ์ฅ ๋ฎ์ ์ ํ๋๋ฅผ ๋ณด์ธ ์ด๋ฏธ์ง์ ๋ง์ถ์ด ๋ค์ instance๋ฅผ ์ง์ ํ์์ ๋ ํด๋น ์ฌ์ง์ 91.39%๊น์ง ์ ํ๋๊ฐ ์์นํ์๊ณ , ์์ธก ๊ฒฐ๊ณผ ์ด๋ฏธ์ง์์ ๊ฐ ํด๋์ค์ ์๋ก ์์ญ์ผ๋ก ์นจ๋ฒ ์์ด ๊ฒฝ๊ณ๊ฐ ๋ช
ํํด์ง๋ ์์์ ํ์ธํ์๋ค. ์ด๋ฅผ ํตํด ํ๊ฐํ๊ณ ์ ํ๋ ์กฐ์ง ์ด๋ฏธ์ง๊ฐ ๋ณ๊ฒฝ๋ ๋๋ง๋ค ๊ทธ ์ด๋ฏธ์ง์ ๋ง์ถ์ด ๊ธฐ์ค๊ฐ์ ์กฐ์ ํด์ผ ํ๋ ๊ด์ฐฐ์์ ์๋ ๊ฐ์
์ด ๋งค๋ฒ ํ์ํ๋ค๋ ํ๊ณ์ ์ ํ์ธํ์๊ณ , ์ด๋ ์ ํ ๊ฐ๋ฐ๋ ์ผ์๋ ์์ ๊ธฐ๋ฐ ๋ฐฉ์์์ ๋ํ๋๋ ํ๊ณ์ ๊ณผ ๋์ผํ์๋ค.
๊ด์ฌ ์์ญ์์ ์ํ๋ํธ๋ฅผ ๊ธฐ์ค์ผ๋ก sensitivity๋ ํ
์คํธ ์ด๋ฏธ์ง ํ๊ท kNN์ 90.68%, ๋ฐ์ดํฐ ์ฆ๊ฐ์ ์งํํ U-Net ๋ชจ๋ธ์์๋ 98.32%, accuracy๋ kNN์์ 94.89%, U-Net ๋ชจ๋ธ์์ 97.86%, AUROC๋ kNN์์ 93.69%, U-Net ๋ชจ๋ธ์์ 99.79%๋ก ๋ํ๋ฌ๋ค. IOU๋ kNN์์ 84.19%, U-Net ๋ชจ๋ธ์์ 93.4%์์ผ๋ฉฐ, DSC๋ kNN์์ 91.03%, U-Net ๋ชจ๋ธ์์ 96.58%๋ฅผ ๋ณด์ด๋ฉฐ ๋ฅ๋ฌ๋ ๊ธฐ๋ฒ์ ์ฌ์ฉํ์์ ๋ ๊ธฐ์กด์ ์์ ๊ธฐ๋ฐ ๋ถํ ๋ฐฉ์๊ณผ ๋น๊ตํ์ฌ ์ฐ์ํ ์ฑ๋ฅ์ด ํ์ธ๋์๋ค. ๋๋ถ์ด ๋ถํ ๊ฒฐ๊ณผ ์ด๋ฏธ์ง๋ฅผ ํ์ธํ์์ ๋ kNN์ ๋นํด ๋๊ฐ์ง ํด๋์ค๋ก์ ๋ถํ ์ด ์๋ก์ ์์ญ์ผ๋ก ์นจ๋ฒ ์์ด ๋์ฑ ๋ช
ํํ ์์์ ํ์ธํ์๋ค.
๊ฒฐ ๋ก
์ธ๊ณต์ง๋ฅ ๋ฅ๋ฌ๋ ๊ธฐ๋ฒ์ ์น๊ณผ์ฉ ์ํ๋ํธ์ ์กฐ์งํ์ ๋ถ์์์ ์ค์ํ ์งํ์ธ Bone to implant contact(BIC)์ Bone area(BA)๋ฅผ ์ธก์ ํ ๋ ๋ํ๋ ์ ์๋ ๊ด์ฐฐ์ ๊ฐ์ ๊ฒฐ๊ณผ ์ฐจ์ด๋ฅผ ๋ณด์ํ๋ฉฐ ๋ถ์์ ์ผ๊ด์ฑ๊ณผ ํจ์จ์ฑ์ ํฅ์์ํค๋ ๋ณด์กฐ ๋๊ตฌ๋ก์ ๋ฐ์ ๊ฐ๋ฅ์ฑ์ด ํ์ธ๋์๋ค. ๋ค์ํ ์์์ ํฌํจํ ์กฐ์ง ์ด๋ฏธ์ง๋ฅผ ํ๋ณดํ๊ณ , ์ ๋ฌธ๊ฐ์ ์ฃผ์์ ํ ๋๋ก ํ ํ๋ จ์ด ๋๋ฐ๋๋ค๋ฉด ์กฐ์ง ์์ญ์์ ๋ผ์ ๋ผ๊ฐ ์๋ ์์ญ์ผ๋ก์ ๋ถํ ์ ํ๋๊น์ง ๋ฌ์ฑํ์ฌ ๋ณ๋ฆฌํ ์คํ์ค์์ ๋ผ์กฐ์ง ๋ถ์์ ๋ณด์กฐ ์๋จ์ผ๋ก ํ์ฉํ ์ ์์ ๊ฒ์ผ๋ก ํ๋จํ์๋ค.์ 1 ์ฅ ์๋ก 1
์ 1 ์ ์ฐ๊ตฌ์ ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉ์ 1
์ 2 ์ฅ ์ฐ๊ตฌ ๋ฐฉ๋ฒ 5
์ 1 ์ ๋ฐ์ดํฐ๋ฒ ์ด์ค ๊ตฌ์ถ 5
1. ๋ฐ์ดํฐ ์์ง 5
2. ์ด๋ฏธ์ง ์ฃผ์ ์ฒ๋ฆฌ ๋ฐ ground truth ์ด๋ฏธ์ง ์์ฑ 7
3. ๊ด์ฌ์์ญ(Region of interest, ROI) ์ค์ ๋ฐฉ๋ฒ 7
์ 2 ์ ์ธ๊ณต์ง๋ฅ ๊ธฐ๊ณํ์ต ๋ฐฉ๋ฒ๋ก 8
1. kNN 8
2. U-Net 9
์ 3 ์ ์ธ๊ณต์ง๋ฅ ๋ฅ๋ฌ๋ ์คํ ๋ฐฉ๋ฒ 11
1. ๋ฐ์ดํฐ์
์ค๋น 11
2. ๋ฐ์ดํฐ ์ฆ๊ฐ 13
3. ๋ชจ๋ธ ๋งค๊ฐ๋ณ์(parameter) ์ ์ 13
4. ์ญ์นซ๊ฐ(threshold) ์ค์ ์ ํตํ ๊ฒฐ๊ณผ ์ด๋ฏธ์ง ์ด๋ถํ 13
5. ์ต์ข
์์ธก ์ด๋ฏธ์ง ์์ฑ 13
์ 4 ์ ๊ธฐ๊ณํ์ต ์คํ ํ๊ฒฝ 14
์ 5 ์ ํ๊ฐ ๋ฐฉ๋ฒ 14
์ 3 ์ฅ ์ฐ๊ตฌ ๊ฒฐ๊ณผ 15
์ 1 ์ ๋ฅ๋ฌ๋ ๋ฐ์ดํฐ ๊ตฌ์ฑ 15
์ 2 ์ ์ํ๋ํธ์ ์กฐ์ง์ผ๋ก์ ๊ฒฝ๊ณ ๋ถํ ๊ฒฐ๊ณผ 16
1. kNN ๊ฒฐ๊ณผ 16
2. ๋ฅ๋ฌ๋ ๋ชจ๋ธ ํ๋ผ๋ฏธํฐ ์ ์ 34
3. ๋ฅ๋ฌ๋ ๊ฒฐ๊ณผ ๋น๊ต 36
์ 4 ์ฅ ๊ณ ์ฐฐ 49
์ฐธ๊ณ ๋ฌธํ 54
Abstract 62์
๊ธฐ์ ์ ์ง๋ฐฐ๊ตฌ์กฐ์ ํ๊ตญ ๊ฐ์กฑ๊ธฐ์ ์ ์ฌํ์ ์ฑ๊ณผ์ ๊ดํ ์ฐ๊ตฌ
ํ์๋
ผ๋ฌธ (์์ฌ)-- ์์ธ๋ํ๊ต ๋ํ์ : ๊ฒฝ์ํ๊ณผ ๊ตญ์ ๊ฒฝ์์ ๊ณต, 2016. 2. ์ด๋๊ธฐ.๊ธฐ์กด ์ฐ๊ตฌ๋ค์ ๊ฒฝ์ ํ์ ๊ธฐ๋ฐํ ๋๋ฆฌ์ธ ์ด๋ก ๊ณผ ์ฌ๋ฆฌํ์ ๊ธฐ๋ฐํ ์ฒญ์ง๊ธฐ ์ด๋ก ์ ๋ฐ๋ผ ๊ฐ์กฑ๊ธฐ์
์ ์ด์ํ๋ ๊ฐ์กฑ์๊ฒ ๋ํ๋ ์ ์๋ ํน์ง๋ค์ ์๋ฐ๋๊ฒ ์ค๋ช
ํ๊ณ ์์ด, ๊ฐ์กฑ์ ๊ฒฝ์์ฐธ์ฌ์ ๊ธฐ์
์ ์ฑ๊ณผ์ ๊ด๊ณ์ ๋ํด์๋ ๋
ผ๋์ด ์๋ค. ์ด์ ๋ฐ๋ผ, ์ฌ๋ฌด์ ์ฑ๊ณผ๋ก ๊ฐ์กฑ๊ธฐ์
์ ํ๊ฐํด์๋ ๊ฐ์กฑ๊ธฐ์
์ ๋ํ ๊ธฐ์กด ์ฐ๊ตฌ์๋ ๋ฌ๋ฆฌ, ๋ณธ ์ฐ๊ตฌ์์๋ ๊ธฐ์
์ ์ฌํ์ ์ฑ๊ณผ (corporate social performance)๋ฅผ ํตํด ๊ฐ์กฑ๊ธฐ์
์ ํน์ฑ์ ์ดํด๋ณด๊ณ ์ ํ์๋ค. ๋ณธ ์ฐ๊ตฌ๋ ๊ฐ์กฑ๊ธฐ์
์ฌ๋ถ, ์ฌ์ธ์ด์ฌ๋น์จ, ๊ธฐ๊ดํฌ์์๋น์จ์ ๋
๋ฆฝ๋ณ์๋ก ํ์ฌ ์ข
์๋ณ์์ธ ๊ธฐ์
์ ์ฌํ์ ์ฑ๊ณผ์ ์ด๋ค ์ํฅ์ ๋ฏธ์น๋์ง ์ฐ๊ตฌํ์์ผ๋ฉฐ, ๊ธฐ๊ดํฌ์์๋น์จ์ ์กฐ์ ๋ณ์๋ก ํ์๋ค. ๊ธฐ์
์ ์ฌํ์ ์ฑ๊ณผ๋ 2007๋
๋ถํฐ 2009๋
๊น์ง ํ๊ตญ๊ฒฝ์ ์ ์์ฐ๊ตฌ์์์ ๋ฐํ๋ ๊ฒฝ์ ์ ์์ง์(KEJI Index)๋ฅผ ์ด์ฉํ์๋ค. ์ฐ๊ตฌ ๊ฒฐ๊ณผ, ๊ฐ์กฑ๊ธฐ์
์ ๋น๊ฐ์กฑ๊ธฐ์
๋ณด๋ค ๋์ ์ฌํ์ ์ฑ๊ณผ๋ฅผ ๋ฌ์ฑํ๋ ๊ฒ์ผ๋ก ๋ํ๋ฌ์ผ๋ฉฐ, ์ฌ์ธ์ด์ฌ์ ๋น์จ์ ๊ธฐ์
์ ์ฌํ์ ์ฑ๊ณผ์ ์ ์๋ฏธํ ๊ด๊ณ๊ฐ ์๋ ๊ฒ์ผ๋ก ๋ํ๋ฌ๋ค. ํํธ, ๊ธฐ๊ดํฌ์์ ๋น์จ์ ๊ฐ์กฑ๊ธฐ์
๊ณผ ์ฌํ์ ์ฑ๊ณผ์ ์กฐ์ ๋ณ์๋ก์๋ ์ ์๋ฏธํ ๊ฒฐ๊ณผ๊ฐ ๋์ค์ง ์์์ง๋ง, ๊ธฐ๊ดํฌ์์๋น์จ์ ์ฌํ์ ์ฑ๊ณผ์ ๊ธ์ ์ ์ธ ์ํฅ์ ๋ฏธ์น ๊ฒ์ผ๋ก ๋ํ๋ฌ๋ค.Agency theory from economics and stewardship theory based on psychology have emerged over the last decade to explain performance and conduct of family firms, and the two theories have found contradicting results and relationship between family firm and firm performance is still disputed. Therefore, unlike existing family firm researches that focused on financial performance of firms, this paper tests relationship and characteristics of corporate social performance and family firms. Family firm status, outside director ratio and institutional ownership are used as independent variables to test influences on corporate social performance, dependent variable of this paper. The samples are collected from KEJI Index from 2007 to 2009. The results indicate that family firms engage more in socially responsible activities and institutional ownership exerts positive influence on firms corporate social performance. However, outside director ratio did not have significant influence on corporate social performance and institutional ownership also did not have moderating effects on family firm and corporate social performance relation.1. Introduction 1
2. Literature review 4
2.1 Family firm 4
2.1.1 Definition of family firm 4
2.1.2 Agency theory and stewardship theory 5
2.2 Firms corproate social performance 7
2.2.1 Definition of corporate social performance 7
2.2.2 Corporate social performance of family firms 10
3. Hypothesis 11
4. Methods 17
4.1 Data and sample 17
4.2 Variables 18
4.2.1 Independent variables 18
4.2.2 Dependent variable 19
4.2.3 Control variable 20
4.3 Analysis methods 22
5. Results 23
6. Conclusion and limitation 26
6.1 Conclusion and discussion 26
6.2 Limitation 28
Reference 29
Abstract in Korean 40Maste
์ํ ์ฝํฌ๋ฆฌํธ์ถฉ์ ๊ฐ๊ด ๋ถ์ฌ์ ํจ๊ฐ๋ ๋ฐ ๊ฑฐ๋
ํ์๋
ผ๋ฌธ (์์ฌ)-- ์์ธ๋ํ๊ต ๋ํ์ : ๊ฑด์ถํ๊ณผ, 2017. 2. ๊ฐํ๊ตฌ.ํฉ์ฑ๊ตฌ์กฐ๋ ๊ธฐ์กด์ ์ฒ ๊ทผ์ฝํฌ๋ฆฌํธ๊ตฌ์กฐ๋ ๊ฐ๊ตฌ์กฐ์ ๋น๊ตํ์ฌ ๊ฐ๋์ ๊ฐ์ฑ ์ธก๋ฉด์์ ๋ณด๋ค ์ ๋ฆฌํ๋ค. ์ด๋ฌํ ๊ตฌ์กฐ์ ์ฅ์ ๋๋ฌธ์ ์ด๊ณ ์ธต ๊ฑด๋ฌผ๊ณผ ์ฅ๊ฒฝ๊ฐ ๊ตฌ์กฐ๋ฌผ์ ์์๊ฐ ๋์ด๋๋ ํ๋์ ์ด๋ฅด๋ฌ ํฉ์ฑ๊ตฌ์กฐ๊ฐ ๋๋ฆฌ ์ฌ์ฉ๋๊ณ ์๋ค. ํฉ์ฑ๊ตฌ์กฐ์ ์ข
๋ฅ๋ ๊ทธ ํ์์ ๋ฐ๋ผ ์ถฉ์ ํ(CFTConcrete Filled Tube)๊ณผ ๋งค์
ํ(SRCSteel Reinforced Concrete)์ผ๋ก ํฌ๊ฒ ๋๋๋๋ฐ, ๋ณธ ์ฐ๊ตฌ์์๋ ์ถฉ์ ํ(CFT) ๊ตฌ์กฐ๋ฅผ ๋ค๋ฃฌ๋ค. ํนํ ์ถฉ์ ํ(CFT)๋ ์์ถ์ ์ง๋ฐฐ์ ์ผ๋ก ๋ฐ๋ ๊ธฐ๋ฅ ๋ถ์ฌ๋ก ์ฃผ๋ก ์ฌ์ฉ๋์ด ์์ผ๋ฉฐ, ๋ฐ๋ผ์ ํธ์ฌ์ ์ ๋ฌด์ ๋ฐ๋ฅธ ์์ถ์ ๋ฐ์ ๋ CFT ๊ธฐ๋ฅ ๋ถ์ฌ์ ๊ฑฐ๋์ ๊ดํ ์ฐ๊ตฌ๊ฐ ๋ค์ ์ํ๋์๋ค. ๊ทธ๋ฌ๋ ๊ตญ๋ด์ธ์ ์ผ๋ก CFT ๊ตฌ์กฐ๊ฐ ๊ธฐ๋ฅ ๋ฟ๋ง ์๋๋ผ ๋ณด๋ก์ ์ฅ๊ฒฝ๊ฐ์ ์ํ๋ ๊ฑด์ถ๋ฌผ๊ณผ ๊ต๋ ๋ฑ์ ํ์ฉ๋จ์๋ ๋ถ๊ตฌํ๊ณ , ์ด์ ๋ํ ์ฐ๊ตฌ๋ ๋ถ์กฑํ ์ค์ ์ด๋ค.
์ง๋ ์ฐ๊ตฌ ๊ฒฐ๊ณผ, CFT๋ณด์ ๊ฑฐ๋์ด ์์ด ๋น ๊ฐ๊ด์ ๊ฑฐ๋๊ณผ ๋งค์ฐ ์ ์ฌํ๋ค๊ณ ๋ณด๊ณ ๋์๋ ์ด๊ธฐ์ ์ฐ๊ตฌ์๋ ๋ฌ๋ฆฌ(Furlong, 1967), ์ถฉ์ ๋ ์ฝํฌ๋ฆฌํธ๊ฐ ์์ถ ์ ํญ์ ํ๋ฉฐ ์ค๋ฆฝ์ถ์ ์์ถ์ธก์ผ๋ก ์ด๋์ํด์ผ๋ก์จ ๊ฑฐ๋์ ์ํฅ์ ๋ฏธ์น๋ฉฐ, ์์ถ์ ๋ฐ๋ ๊ฐ๊ด์ ๊ตญ๋ถ์ข๊ตด์ ๋ฐฉ์งํ๋ค๋ ๊ฒ ๋ฑ ๋ณด๋ค ์ ํํ CFT๋ณด์ ํจ๊ฑฐ๋์ ๋ํ ์ฐ๊ตฌ๊ฐ ์ต๊ทผ๊น์ง ๋ณด๊ณ ๋๊ณ ์๋ค. ๊ทธ๋ฌ๋ ์ด๋ค ์ฐ๊ตฌ์ ๋๋ถ๋ถ์ ์ถ์ ๋ชจํ์ผ๋ก ์ ์๋ CFT(๋ก) ๋ถ์๋์์ผ๋ฉฐ ์ค๋ฌผ๋ ํฌ๊ธฐ์ ์ค์ CFT ๋ณด์ ๊ฑฐ๋์ ๋ํ ์ฐ๊ตฌ๋ ๊ทนํ ๋ถ์กฑํ ์ํ์ด๋ค. ๋ํ, ์ํ CFT(CCFT)์ ๊ฒฝ์ฐ ๊ทธ ๋จ๋ฉด ํํ์ ํน์ฑ์ ์ธ๋ฐํ ์ฐ๊ตฌ๊ฐ ์งํ๋์ด์ผ ํจ์๋ ๋ถ๊ตฌํ๊ณ ์ด์ ๋ํ ์ฐ๊ตฌ๋ ๋์ฑ ๋ถ์กฑํ ์ค์ ์ด๋ค.
๋ฐ๋ผ์ ๋ณธ ์ฐ๊ตฌ์์๋ ์ค๋ฌผํฌ๊ธฐ CCFT ์คํ ๋ฐ์ดํฐ๋ฅผ ๋ถ์ํ์ฌ ์ถ๋ ฅ์ ๋ฐ์ง ์๋ ์ํ์์์ CCFT(์ ํจ๊ฑฐ๋์ ์ฐ๊ตฌํ์๋ค. ํนํ CCFT(์ ํจ๊ฐ๋์ ์์ด์ ์ฌ๋ฌ ์ฝ๋๋ณ๋ก ์ฐ์ ์์ด ์กด์ฌํ์ง๋ง ๊ทธ ๋ฐฉ์์ด ๋์ผํ์ง ์์ ๋ฟ๋ง ์๋๋ผ, ์ต๊ทผ ๋ณด๊ณ ๋ ์ค๋ฌผ ํฌ๊ธฐ ์คํ๊ฐ๊ณผ ๋น๊ตํ์ฌ ๋ณผ ๋๋ ๋ณด์์ ์ด์ง ๋ชปํ ์ค๊ณ๋ก ์ด์ด์ง๋ ๊ฒ์ผ๋ก ๋ํ๋ฌ๋ค. ๋ํ, ์ถ๊ฐ์ ์ผ๋ก ์ค์ ์ธก์ ๋ CCFT๋ถ์ฌ์ ํจ๊ฐ๋๊ฐ๊ณผ ์ฝ๋์ ๋ฐ๋ผ ๊ณ์ฐ๋ ๊ฐ์ ๋น๊ต ๋ถ์ํ์์ ๋ ๊ฐ๊ด์ ๋๊ป๊ฐ ๊ฐ์ํ ๋, ์ฆ ๋ฐํ์ผ ๋ ์์ ์จ์ด ๊ฐ์ํ๋ ๊ฒ์ผ๋ก ๋ํ๋ฌ๋ค.
๋จ๋ฉด์ด ์ํ์ธ ํน์ฑ์ CCFT(์ ํจ๊ฐ๋๋ฅผ ์์ฝ๊ฒ ๊ณ์ฐํ ์ ์๊ธฐ ๋๋ฌธ์, ๋ณธ ์ฐ๊ตฌ์์๋ ์ค๊ณ์๊ฐ CCFT๋ถ์ฌ์ ๋ฌผ์ฑ์น๋ฅผ ์
๋ ฅํ์ฌ CCFT(์ ํจ๊ฐ๋๋ฅผ ์ฐ์ ํ ์ ์๋ ํ๋ก๊ทธ๋จ์ ๊ฐ๋ฐํ์๋ค. ์ด์ ๋ํ์ฌ, ์ ๋ฐํ ๊ณ์ฐ๊ณผ์ ์์ด๋ CCFT๋ถ์ฌ์ ํจ๊ฐ๋๋ฅผ ์ฐ์ ํ ์ ์๋ ์ค๊ณ ๊ทธ๋ํ๋ฅผ ์ ์ํ์ฌ ๋ณด๋ค ์ ํํ๊ณ ํธ๋ฆฌํ ์ค๊ณ๊ฐ ๊ฐ๋ฅํ๋๋ก ์ ๋ํ์๋ค.The use of concrete filled tubes (CFTs) with its own structural advantages has been used relatively recent comparing to other structural materials such as regular structural steel or regular reinforced concrete. Moreover, circular concrete filled tubes (CCFTs) provide more effective confinement by circular steel tube, bond stress transfer, and shear reinforcement to the concrete fill than rectangular concrete filled tubes. However, most prior experimental researches have been done focusing on the concrete filled tube columns. Even though some of them have been considered under pure bending, those have been done only using small sized specimens. The aim of this study is to examine the flexural behavior of full scaled circular concrete filled tube (CCFT) beams. Moreover, it attempts to investigate the effect of end plate. Five full scaled specimens were used to examine the flexural behavior. One was thick walled steel tubes without concrete fill, two were thick walled CCFTs with and without end plate, and other two were thin walled CCFTs with and without end plate. The test results about flexural behavior of CCFTs are shown with applied moment, displacement, steel and concrete strain at each location.
This study also collected all the test specimens from the prior researches and this current test to make a comparison between the measured flexural strength and calculated nominal flexural capacity of CCFT according to common methods such as methods according to the ACI, AISC and Eurocode 4. One of the reasons is that due to the complexity of calculation for circular shapes, it is difficult to hand calculate the flexural strength of CCFT following the methods except the plastic stress distribution method of AISC which provides the closed form equations. Another reason is that all these methods give different calculated nominal flexural capacities of CCFT. In this study, an effort is made to review and compare the codes to identify their differences and also develop a computing program for the nominal flexural capacity of circular concrete filled tubes under pure bending that is in accordance with the codes. The developed computing algorithm, which is programmed in MATLAB, is not only used to compare the measured and calculated flexural strength of CCFT in this study but also is used to generate design aid graphs for various steel grades and a variety of strengths of steel and concrete. The design aid graphs for CCFT beams can be used as a preliminary design tool.Chapter 1. Introduction 1
1.1 Introduction 1
1.2 Objectives and scope 4
1.3 Organization 5
Chapter 2. Literature Review 7
2.1 General overview 7
2.2 Previous studies 9
2.2.1 Researches on small scaled CFT 9
2.2.2 Researches on full scaled CFT 15
Chapter 3. Assessment of Experimental Results 19
3.1 Experimental program 19
3.1.1 Specimen design 19
3.1.2 Materials 21
3.1.3 Test setup 23
3.2 Assessment of experimental results 28
3.2.1 Moment-mid span deflection 29
3.2.2 Upward shift of plastic neutral axis 34
3.2.3 Concrete push-out 36
3.2.4 End plate effect 38
3.2.5 Stiffness 40
3.3 Summary 43
Chapter 4. Nominal Flexural Capacity of CCFT and Comparison with Test Results 45
4.1 Review on design codes 45
4.2 Suggested program for estimating nominal flexural capacity of CCFT 50
4.3 Design aid graphs for nominal flexural capacity of CCFT 59
4.4 Tests from previous experiments 65
4.5 Comparison of experimental results and predictions 67
4.6 Summary 71
Chapter 5. Conclusion 73
References 76
๊ตญ ๋ฌธ ์ด ๋ก 79Maste
์์ผ๋ก ๋ง๋ฆฌ๋ ์ ๊ธฐ์ฅ๋ ์์ ์ธํฌ๊ฐ ์ ํธ์ ๋ฌ๊ณผ ๊ด๋ จ๋ ์๋ก์ด ์ ๊ธฐ์ฅ๋ ์ ์ ์์ ๋ํ ์ฐ๊ตฌ
Thesis(master`s)--์์ธ๋ํ๊ต ๋ํ์ :ํํ๋ถ ์ํํ์ ๊ณต,2005.Maste
ํจ์ ๋์์ด๋์ ์ฐฝ์์ฑ ๋ฐํ์์ธ ๋น๊ต ์ฐ๊ตฌ
ํ์๋
ผ๋ฌธ (๋ฐ์ฌ)-- ์์ธ๋ํ๊ต ๋ํ์ : ์๋ฅํ๊ณผ, 2013. 8. ๊น๋ฏผ์.ํ์ , ์๋ก์, ๋ณํ๋ฅผ ์ค์ํ ๊ฐ์น๋ก ์ฌ๊ธฐ๋ ํจ์
์์ ์ฐฝ์์ฑ์ ๊ฒฝ์๋ ฅ์ ๊ทผ์์ด๊ณ ๊ฐ์ฅ ์ค์ํ ์ด์ ์ด๋ค. 21์ธ๊ธฐ ์ ๋ณด ํต์ ์ ๋ฐ๋ฌ์ ์ ์์ฌ์ ์ ๊ธฐ์ ์ ๊ณต์ ๋ฅผ ๊ฐ์ ธ์ ํจ์
์ ํ ๊ฐ์ ๊ธฐ์ ๊ฒฉ์ฐจ๊ฐ ํ๊ฒฉํ๊ฒ ์ค์ด๋ค์๋ค. ํ์คํ๋ ํจ์
์ํ๋ค์ ํ์ ์์์ ํจ์
๋์์ด๋์ ์์ ์์ง์ ์์๋ ฅ์ด ๋ํด์ง ์ฐฝ์์ฑ์ด ์ฐจ๋ณํ์ ํต์ฌ์์๋ก ๋์ฑ ๊ฐ์กฐ๋๊ณ ์๋ค. ๋ณธ ์ฐ๊ตฌ๋ ํจ์
์ ์๋ก์์ ๊ฐ์ ธ์ค๋ ํจ์
๋์์ด๋๋ค์ ์ฐฝ์์ฑ ๋ฐํ์์ธ์ ๋ฏธํ์ด ์น์ผํธ๋ฏธํ์ด(M. Csikszentmihalyi)์ ํ์๋ ๊ฐ๋๋(H. Gardener)์ ํตํฉ์ ์ธ ๊ด์ ์ ์ค์ฌ์ผ๋ก ๊ณ ์ฐฐํ๊ณ ์ ํ๋ค. ํจ์
๋์์ด๋์ ๊ฐ์ธ์ ์ธ ํน์ฑ๊ณผ ์ฌ๋ฅ๊ณผ ํจ๊ป ํจ์
์์ญ ๋ด์์ ์ฌํยท๋ฌธํ ์ฒด๊ณ์ ๋ฐ์ํ๊ณ ์์ ์์ง์ ์ฒ ํ์ ํํํ๋ ๋ฐฉ์, ์๋ก์ด ๋์์ธ์ ๊ฐ์น๊ฐ ํ๊ฐํ๋ ํ์ฅ๊ณผ์ ๊ด๊ณ๋ฅผ ๋ฐํ์ผ๋ก ํญ๋๊ฒ ๋ถ์ํ๊ณ ์ ํ๋ค.
๋ณธ ๋
ผ๋ฌธ์ ๊ฒฐ๊ณผ๋ ๋ค์๊ณผ ๊ฐ๋ค.
์ฒซ์งธ, ์ฐฝ์์ฑ์ ์ผ๋ฐ์ ๊ณ ์ฐฐ์ ๋ฐํ์ผ๋ก ํจ์
๋์์ด๋ ์ฐฝ์์ฑ์ ์ ์ํ๊ณ ๋ถ์์ ๋ชจํ์ ๊ฐ๋ฐํ์๋ค. ํจ์
๋์์ด๋์ ์ฐฝ์์ฑ์ ํจ์
์์คํ
์ ์ํด์๋ ํจ์
๋์์ด๋๊ฐ ํจ์
์ด๋ผ๋ ์์ง์ฒด๊ณ์ ๋ํ ์ง์์ ๋ฐํ์ผ๋ก ์๋กญ๊ณ ์ ์ฉํ ์ฐ๋ฌผ์ ๋ง๋ค์ด๋ด๋ ๋ฅ๋ ฅ์ผ๋ก, ๋์๋์ ํ์ฅ์์ ์๋ก์๊ณผ ์ ์ฉ์ฑ์ ์ธ์ ์ ๋ฐ๊ณ ํจ์
์์ญ์ ํฌํจ๋ ๋ ๋ฐํ๋๋ ๊ฒ์ด๋ผ๊ณ ์ ์ํ์๋ค. ํจ์
๋์์ด๋์ ์ฐฝ์์ฑ ๋ฐํ์์ธ์ ๊ฐ์ธ, ํจ์
์์ญ, ํจ์
ํ์ฅ์ผ๋ก ๋๋์ด ์ธ๋ถ์์ธ์ ๋ฐํ๋ค. ํจ์
๋์์ด๋์ ๊ฐ์ธ์ ์์ธ์ ์ธ์ง์ ๋ฅ๋ ฅ(๊ธฐ์ , ๊ต์, ์ฌํ์ฑ), ๋น์ธ์ง์ ๋ฅ๋ ฅ(์ฑ๊ฒฉ์ ํน์ฑ, ๋งค๋ ฅ์๋ณธ), ์ฌํยท์ฌ๋ฆฌํ์ ์์ธ(๊ฐ์กฑ, ์ฑ์ ์ ์ฒด์ฑ, ๊ฒฐํผ, ๊ฑด๊ฐ)์ด๋ค. ํจ์
์์ญ์ ์ฐฝ์์ฑ ๋ฐํ์์ธ์ ํจ์
๋์์ด๋์ ์ฃผ์ ์ฐฝ์ํ๊ณผ ํจ์
์ ์ฌํยท๋ฌธํ์ ๋งฅ๋ฝ์ธ ์๋์ ์ , ์ฌํ๊ตฌ์กฐ, ๊ธฐ์ ์ ์ธก๋ฉด๊ณผ์ ์ํธ ์์ฉ๊ณผ ๋์์ด๋์ ์ฐฝ์กฐ๋ฌผ์ด ์์ญ์ ์ผ๋ถ๋ก ํธ์
๋๋ ํจ๋ฌ๋ค์์ด์๋ค. ํจ์
ํ์ฅ์ ํจ์
์ฐ์
์์ ์ผ์ ํ๊ฑฐ๋ ํจ์
์ฐฝ์กฐ์ ์ํฅ์ ์ฃผ๋ ๋ฌธ์ง๊ธฐ๋ค๋ก ํจ์
์๋ํฐ, ๋ฐ์ด์ด, ํจ์
๊ต์ก์, ํจ์
๋์์ด๋, ํฌ์์, ๋น์ฆ๋์ค ํํธ๋, ํจ์
๋ชจ๋ธ, ๊ณ ์ฉ์ธ, ํจ์
ํ๋ ์ดํฐ ๋ฑ ํจ์
์
๊ณ ์ข
์ฌ์๋ค๊ณผ ํจ์
์ ๋์๋ก ๊ตฌ์ฑ๋์๋ค.
๋์งธ, ์์ ๊ฐ๋ฐํ ํจ์
๋์์ด๋ ์ฐฝ์์ฑ ๋ถ์์ ๋ชจํ์ ์ด์ฉํ์ฌ ์คํธ์ฟ ํ๋ฅดยทํ๋ ํํฌ๋ฅดํ
ยท๊ธ๋ก๋ฒ ํจ์
์๋์ ์ฐฝ์์ ํจ์
๋์์ด๋ 9์ธ์ ์ฌ๋ก์ฐ๊ตฌ๋ฅผ ์งํํ ๊ฒฐ๊ณผ๋ ๋ค์๊ณผ ๊ฐ๋ค.
๊ฐ๋ธ๋ฆฌ์ ์ฝ์ฝ ์ค๋ฌ(Gabrielle "Coco" Chanel)์ ์ฌํ์ฑ, ๊ธฐ์ ์ ์ธ์ง์ ๋ฅ๋ ฅ, ์ผ๋ง์ฑ, ๋
๋ฆฝ์ฑ์ ์ฑ๊ฒฉ์ ํน์ฑ, ๋งค๋ ฅ ์๋ณธ์ ์์ ์๋ก ์ฌ์ฑ์ ์ข
์์ ์ธ ์กด์ฌ๋ก ๋จธ๋ฌผ๊ฒ ํ๋ ๊ณผ์์ ์ธ ํจ์
์ ๋ฐ๋ฐํด, ๋จ์ฑ๋ณต์ ์ค์ฉ์ฑ์ ๋์
ํ ๊ธฐ๋ฅ์ฃผ์ ํจ์
์ด๋ผ๋ ์๋ก์ด ํจ๋ฌ๋ค์์ ์ ์ํ๋ค. ๋ค์์ ์ ์ธ, ์๋ฐฉ๊ฐ๋ฅด๋ ์์ ๊ฐ ์ง๋จ, ๋ฏธ๊ตญ์ ํจ์
์๋ํฐ์ ๋ฐ์ด์ด๊ฐ ์ฐฝ์์ฑ ๋ฐํ์ ์ง์งํ์๋ค. ํฌ๋ฆฌ์คํ ๋ฐ ๋ฐ๋ ์์๊ฐ(Cristรณbal Balenciaga)๋ ๋ฐ์ด๋ ์
์ฒดํํ(3D) ์ง๋ฅ์ ์ฑ์ค์ฑ์ด๋ผ๋ ์ฑ๊ฒฉ์ ํน์ฑ์ด ํฉํด์ ธ ํ๋ ํจ์
์ ๋๋ถ๋ถ์ ์ค๋ฃจ์ฃ์ ์ฐฝ์กฐํ์๋ค. ์์
์ฃผ์๋ฅผ ๊ฑฐ๋ถํ๊ณ ์์ํ ํํ๋ฏธ ๊ตฌํ์ ๋ชฐ๋ํ ๋ฐ๋ ์์๊ฐ์ ํ์ ์ ์ธ ์๋ณต๊ตฌ์ฑ ํํ๋ ํจ์
์๋ํฐ, ๋๋ฃ ๋์์ด๋์ ์ด๋ ฌํ ์ง์ง๋ฅผ ๋ฐ์ ์๋ก์ด ํจ๋ฌ๋ค์์ผ๋ก ์๋ฆฌ ์ก์๋ค. ํฌ๋ฆฌ์ค์ฐฌ ๋์ค๋ฅด(Christian Dior)๋ ์ฌํ์ฑ, ๊ต์, ๊ธฐ์ ๋ฑ์ ๊ณ ๋ฅธ ์ธ์ง์ ๋ฅ๋ ฅ์ ์์ ์๋ก ๊ฐ๋ฐฉ์ฑ๊ณผ ๊ฐ์์ฑ์ ์ฑ๊ฒฉ์ ํน์ฑ์ ๊ฐ์ง๊ณ ์์๋ค. ์ ์ ํ ํจ์
์ ์นจ์ฒด๊ธฐ์ ํ์ค๋ํผ์ ์ธ ๋ก๋งจํฐ์์ฆ ์์์ ํจ๋ฌ๋ค์์ ์ฐฝ์กฐํด ์คํธ์ฟ ํ๋ฅด ์ ํต์ ๋ถํ์์ผฐ๋ค. ๋ผ์ด์ ์ค ์ฌ์
, ๊ธฐ์ฑ๋ณต ์ฌ์
๋ฑ ์ฌ์
์ ๋ค๊ฐํ๋ฅผ ํตํด ์์
์ฃผ์๋ฅผ ์ถ๊ตฌํ์๊ณ ์์ ๊ฐ ์ง๋จ, ํจ์
์ธ๋ก ์ ์ ๊ทน์ ์ธ ์ง์ง๋ฅผ ๋ฐ์๋ค.
์
์ ๋ก๋(Yves Saint Laurent)์ ๊ธฐ์ , ์ฌํ์ฑ, ๊ต์์ ์ธ์ง์ ๋ฅ๋ ฅ, ๊ฐ์์ฑ, ๊ฐ๋ฐฉ์ฑ์ ์ฑ๊ฒฉ์ ํน์ฑ, ๋์ ๋งค๋ ฅ ์๋ณธ์ ์์ ์๋ฅผ ์ง๋
๋ค. ์๋์ ํ๋ฆ์ ๋ฐ๋ผ ๋จ์ฑ๋ณต, ์คํธ๋ฆฌํธ ํจ์
, ์์ ์ํ, ๊ฐ๊ตญ์ ์ ํต์์์์ ์๊ฐ์ ๋ฐ์ ํญ๋์ ์ํ ํ๋์ผ๋ก ํ๋ ํจ์
์ ๋ชจ๋ ์คํ์ผ์ ์ฐฝ์กฐํ์๋ค. ํจ์
์ธ๋ก , ๋น์ฆ๋์ค ํํธ๋์ ์ง์์ ๋ฐ์์ผ๋ฉฐ ์๋ง์ ํ๋ ๋์์ด๋์ ์ถ์ข
์ ๋ฐ์๋ค. ์นผ ๋ผ๊ฑฐํ ํธ(Karl Lagerfeld)๋ ์ฌํ์ฑ, ๊ต์, ๊ธฐ์ ์ ๋์ ์ธ์ง์ ๋ฅ๋ ฅ, ๊ฐ๋ฐฉ์ฑ์ ์ฑ๊ฒฉ์ ํน์ฑ, ๋ฐ์ด๋ ์ฌํ์ ํํ๋ ฅ์ด๋ผ๋ ๋งค๋ ฅ ์๋ณธ์ ๊ฐ์ก๋ค. ํจ์
์์คํ
๋ณํ์ ๋ฐ๋ผ, ํ๋ ํํฌ๋ฅดํ
์
๊ณ์ ์ง์ถํ๊ณ , ์ค๋ฌ ์ฟ ํ๋ฅด ํ์ฐ์ค๋ฅผ ์ด๋๋ ๋ฑ ๊ธฐ์กด ๋์์ธํ์ฐ์ค์ ๊ณ ์ ์ฑ์ ์๋ก์์ ๊ฐ๋ฏธํ๋ ํจ์
์ฉ๋ณ์ด๋ผ๋ ์๋ก์ด ํจ๋ฌ๋ค์์ ๋ณ์๋ค. ๊ฐ๊ฐ ์๋ ์ ์ ์์ ๊ฐ ์ง๋จ์๊ฒ ์๊ฐ์ ์ป์ด ์๋์ ์ ์ ํ์
ํ๋ฉฐ ํจ์
์ ๋๋ ฅ์ ์ ์งํ์๋ค. ๋น๋น์ ์จ์คํธ์ฐ๋(Vivienne Westwood)๋ ๊ธฐ์ , ๊ต์์ ์ธ์ง์ ๋ฅ๋ ฅ์ ๊ฐ์ง๊ณ ์์ผ๋ฉฐ ๋
๋ฆฝ์ฑ์ด๋ผ๋ ์ฑ๊ฒฉ์ ํน์ฑ์ ํ ๋๋ก ๊ธฐ์กด์ ํธ๋ ๋์ ๋ฐ๋ฐ, ํํฌ ํจ์
, ์ญ์ฌ์ฃผ์ ์์์ ๊ธฐ๋ฐ์ผ๋ก ํ ํฌ์คํธ๋ชจ๋๋์ฆ ํจ์
์ด๋ผ๋ ์๋ก์ด ํจ๋ฌ๋ค์์ ๋์๋ค. ๋งค๋ ฅ ์๋ณธ์ ์์ ์๋ก ์์ ์ ์ค์ค๋ก๊ฐ ๋์์ธํ์ฐ์ค์ ๋ฎค์ฆ๊ฐ ๋์๋ค. ๋ถํฐํฌ ๋์์ด๋ ์์ ์๋ ์ ์์ด ์ง๋จ์ ์ง์ง๋ฅผ ๋ฐ์๊ณ ํ์ดํจ์
๋์์ด๋๋ก ์ฑ์ฅํ ํ์๋ ํจ์
์๋ํฐ, ํจ์
ํ๋ ์ดํฐ ๋ฑ์๊ฒ ์ธ์ ์ ๋ฐ์๋ค.
๋ฏธ์ฐ์น์ ํ๋ผ๋ค(Miuccia Prada)๋ ๊ต์, ์ฌํ์ฑ์ ์ธ์ง์ ๋ฅ๋ ฅ์ ๊ฐ๋ฐฉ์ฑ์ ์ฑ๊ฒฉ์ ํน์ฑ์ ๊ฐ์ง๊ณ ์๋ค. ์ฐฉ์ฉํ๊ธฐ ์ข์ ์ท์ ๋ง๋๋ ๊ฒ์ ์ค์ํ๊ฒ ์ฌ๊ฒจ 1990๋
๋ ์ดํ ๋ฏธ๋๋ฉ๋ฆฌ์ฆ, ์๋ฐฑ ์ดํ, ์ง์ ์ธ ์๋ฆฌํธ์ธต์ ์ํ ์ด๊ธ๋ฆฌ ์ํฌ(Ugly Chic)๋ผ๋ ์๋ก์ด ํจ๋ฌ๋ค์์ ์ ์ํ์๋ค. ๋น์ฆ๋์ค ํํธ๋์ธ ๋จํธ์ผ๋ก๋ถํฐ ์ ์์ , ์ธ์ง์ ์ง์์ ๋ฐ๊ณ ์์ผ๋ฉฐ ํจ์
์๋ํฐ๋ค์ ์ง์ง๋ฅผ ๋ฐ์๋ค. ์๋ ์ฐ๋ ๋งฅํธ(Alexander McQueen)์ ๊ธฐ์ , ๊ต์, ์ฌํ์ฑ์ ์ธ์ง์ ๋ฅ๋ ฅ๊ณผ ๊ฐ์์ฑ, ๋
๋ฆฝ์ฑ์ ์ฑ๊ฒฉ์ ํน์ฑ์ ๊ฐ์ง๊ณ ์๋ค. ์๋ฏผํ ๊ฐ์ฑ๊ณผ ๋ฐ์ด๋ ๊ธฐ์ ๋ ฅ์ ๋ฐํ์ผ๋ก ์์์ ์ ์ธ ํํ์ฃผ์ ํจ์
์ ์ ๋ณด์์ผ๋ฉฐ ํจ์
์ผ์ ํ์์์ ํ๋ฅผ ํตํ ๊ฐ์ ์ ๋ฌ์ด๋ผ๋ ์๋ก์ด ํจ๋ฌ๋ค์์ ์ฐฝ์กฐํ์๋ค. ๊ทธ๋ ์๊ตญ์ ์ ์์ ์ธ ํ๋ ๋ฏธ์ ๊ฐ๋ค์ ์ํฅ์ ๋ฐ์์ผ๋ฉฐ, ๊ทธ์ ์ฐฝ์ํ๋ค์ ํจ์
์๋ํฐ๋ค์ ์ฃผ๋ชฉ์ ๋ฐ์๋ค. ๋งํฌ ์ ์ด์ฝฅ์ค(Marc Jacobs)๋ ์ฌํ์ฑ, ๊ต์์ ์ธ์ง์ ๋ฅ๋ ฅ, ๊ฐ๋ฐฉ์ฑ, ๊ฐ์์ฑ์ ์ฑ๊ฒฉ์ ํน์ฑ์ ๊ฐ๊ณ ์๋ค. ์๋ฆ๋ค์ด ์ธ๋ชจ, ํ๋ ฅ, ์ฌํ์ ๊ธฐ์ ๋ฑ ๋งค๋ ฅ ์๋ณธ์ ์์ ์๋ก ๋์ค์ ํฌ์ ๊ฑฐ๋๋ฆฌ๊ณ ์๋ค. ๋์ค๋ฌธํ, ์ค๊ณ ์๋ฅ, ํ ๋ฎค์ง์์ ์๊ฐ์ ๋ฐ์ ๊ทธ๋ฐ์ง ๋ฃฉ์ ์ฐฝ์ํ์์ผ๋ฉฐ, ๋๋ดํ ์ฐจ์ฉ์ ํตํ ์ ์์ ์ด๋ฉด์ ์
๊ธฐ ์ฌ์ด ํจ์
, ํจ์
๋์์ด๋์ ์ํฐํ
์ด๋ํ ๋ฑ์ ํจ๋ฌ๋ค์์ ์ฐฝ์กฐํ์๋ค. ํจ์
์๋ํฐ, ํ๋ ๋ฏธ์ ๊ฐ, ๊ธ๋ก๋ฒ ๊ทธ๋ฃน, ํจ์
๋ชจ๋ธ, ๋์ค, ๋ฑ์ ์ง์ง๋ฅผ ๋ฐ์ ์์
์ ์ธ ์ฑ๊ณต์ ๊ฑฐ๋๊ณ ์๋ค.
์
์งธ, ํ๋ ํจ์
์๋์ ์ฐฝ์์ ํจ์
๋์์ด๋ 9์ธ์ ์ฌ๋ก์ฐ๊ตฌ๋ฅผ ํตํด ๊ณ ์ฐฐํ ์ฐฝ์์ฑ ๋ฐํ์์ธ์ ๊ฐ์ธ, ์์ญ, ํ์ฅ ๋ณ๋ก ๋ถ์ํ๋ฉด ๋ค์๊ณผ ๊ฐ๋ค.
๊ฐ์ธ์ ์์ธ ์ค ๋์์ด๋์ ์ธ์ง์ ๋ฅ๋ ฅ์ ์๋์ ํ๋ฆ์ ๋ฐ๋ผ ๊ฐ์กฐ๋๋ ๊ฒ์ ์ฐจ์ด๊ฐ ์์๋ค. ์คํธ์ฟ ํ๋ฅด ์๋๋ ๊ธฐ์ ์ด, ํ๋ ํํฌ๋ฅดํ
ํจ์
์๋์๋ ๊ธฐ์ , ๊ต์, ์ฌํ์ฑ์ด ๊ธ๋ก๋ฒ ํจ์
์๋๋ ์ค์ํ ๊ฒ์ ์ท ์์ฒด๊ฐ ์๋๋ผ ์์ด๋์ด๋ก ์คํ ๋ฆฌํ
๋ง ํ๋ ๊ต์๊ณผ ์ฌํ์ฑ์ด ๊ฐ์กฐ๋์๋ค. ์ ์๋๋ฅผ ๊ดํตํ๋ ๋์์ด๋์ ์ค์ํ ๊ฐ์ธ์ ์์ธ์ ๋งค๋ ฅ์๋ณธ์ผ๋ก ๋์์ด๋๋ค์ ํ๊ณ ๋ ์ธ๋ชจ, ์ฑ์ ๋งค๋ ฅ, ํ๋ ฅ, ๊ฐ์ฑ ์๋ ํจ์
์ผ์ค, ์ฌ๊ต์ ๋ฑ์ ์ด์ฉํ์ฌ ํจ์
ํ์ฅ์ ๋งคํน์์ผฐ๋ค. ์ด๋ฐ์ ์ฌํ์ฌ๋ฆฌํ์ ์ํฉ ์ค ํน์ด์ฌํญ์ ๋ชจ๋ ๋จ์ฑ ํจ์
๋์์ด๋๋ค์ด ๋์ฑ์ ์์๋ค๋ ์ ์ด ์๋ค.
ํจ์
์์ญ์ ์ฐฝ์์ฑ ์์ธ์ ์ดํด๋ณด๋ฉด, ํจ์
๋์์ด๋๋ค์ ์คํธ์ฟ ํ๋ฅด ํ์ฐ์ค์ ์์ต์ํ, ์ ๋ฌธ ํจ์
๊ต์ก ๋ฑ์ ํตํด์ ํจ์
์์ญ ์ง์์ ์ตํ๊ณ , ํ์กดํ๋ ์ด๋ฐ์ฌ๋ก๊ธฐ์ ๋ฐ๋ฐํ๊ฑฐ๋ ์ ๊ทน ๋์กฐํ๋ฉด์ ์๋ก์ด ์ฐ์ถ๋ฌผ์ ์ ์ํ์๋ค. 9์ธ์ ํจ์
๋์์ด๋์ ์ฐฝ์์ ์ธ ์ฐ์ถ๋ฌผ์ ํจ์
์๋ํฐ, ๋ฐ์ด์ด, ํจ์
์ ๋์๋ค์ ์ง์ง๋ฅผ ๋ฐ์ ๋ค์ ์์ญ์ผ๋ก ํธ์
๋์ด ํจ์
์์ญ์ ์๋ก์ด ํจ๋ฌ๋ค์์ด ๋์๋ค. ํจ๋ฌ๋ค์์ ๊ฐ๋ธ๋ฆฌ์ ์ฝ์ฝ ์ค๋ฌ(Gabrielle "Coco" Chanel)์ ๊ธฐ๋ฅ์ฃผ์ ํจ์
๊ณผ ๊ฐ์ ํจ์
์ฌ์กฐ์ ์นผ ๋ผ๊ฑฐํ ํธ(Karl Lagerfeld)์ ์ ๋์์ธํ์ฐ์ค ๋ถํ ๋ฑ๊ณผ ๊ฐ์ ํจ์
๊ด๋ก๋ฅผ ํฌํจํ๋ค. ํจ์
์ ์ด์ต์ ์ฐฝ์ถํด์ผํ๋ ์ฐ์
์ ์ฐ๋ฌผ๋ก, ๋์์ด๋์ ์์
์ฃผ์์ ๊ฐ๋ ๊ด์ ์ ์ฐฝ์์ ํ๋์ ์ค์ํ ์ํฅ์ ๋ผ์น๋ค. ์
์ ๋ก๋(Yves Saint Laurent), ์นผ ๋ผ๊ฑฐํ ํธ(Karl Lagerfeld), ๋ฏธ์ฐ์น์ ํ๋ผ๋ค(Miuccia Prada), ๋งํฌ ์ ์ด์ฝฅ์ค(Marc Jacobs)๋ ๊ณ ์ ์คํ์ผ๋ณด๋ค๋ ์๋์ ๋ถ์๊ธฐ์ ์ฃผ๋ชฉํ์ฌ ๋์์์ด ์๋ก์ด ์คํ์ผ์ ์ ์ํ๊ณ ํธ๋ ๋ ์ธํฐ๋ก ์๋ฆฌ๋งค๊นํ์๋ค. ํฌ๋ฆฌ์คํ ๋ฐ ๋ฐ๋ ์์๊ฐ(Cristรณbal Balenciaga), ๋น๋น์ ์จ์คํธ์ฐ๋(Vivienne Westwood), ์๋ ์ฐ๋ ๋งฅํธ(Alexander McQueen) ๋ฑ์ ๊ธฐ์ ๋ ฅ์ด ๋ฐ์ด๋ ๋์์ด๋๋ค๋ก ์ฐฝ์กฐ์ ์๊ฐ์ ์์ ์ ๊ธฐ์ ์์ ์ฐพ๊ณ ์ผ๊ด์ฑ ์๋ ์ํ์ธ๊ณ๋ฅผ ๋ณด์ฌ์ฃผ์๋ค. ๋ํ ๋ชจ๋ ํจ์
๋์์ด๋๋ค์ ํจ์
์์ญ์ ์ ๋ณด์ ๊ธฐ์ ๋ ฅ์ด ๋ฐ์ง๋์ด ์๋ ์ฃผ์ ํจ์
๋์๋ก ์ด๋ํจ์ด ํ์ธ๋์๋ค.
ํจ์
ํ์ฅ์์ ์ ์๋๋ฅผ ๊ฑธ์ณ ํจ์
๋์์ด๋์ ์ฑ๊ณต์ ์ค์ํ ์ด์ ๊ฐ ๋ ๋ฌธ์ง๊ธฐ๋ ํจ์
์๋ํฐ์๋ค. ํจ์
๋์์ด๋๋ค์ ์ฌํ์ฑ๊ณผ ๋งค๋ ฅ์๋ณธ์ ๋ฌด๊ธฐ๋ก ์ผ์ ํจ์
์๋ํฐ๋ค๊ณผ ์ ๊ทน์ ์ผ๋ก ์ํตํ์๋ค. ๊ฐ๋ธ๋ฆฌ์ ์ฝ์ฝ ์ค๋ฌ(Gabrielle "Coco" Chanel)๊ณผ ์นผ ๋ผ๊ฑฐํ ํธ(Karl Lagerfeld)๋ ๋
์ค, ์๋ ์ฐ๋ ๋งฅํธ(Alexander McQueen)์ ์ ์์ ์ธ ํจ์
์ผ, ์
์ ๋ก๋(Yves Saint Laurent)๊ณผ ๋งํฌ ์ ์ด์ฝฅ์ค(Marc Jacobs)๋ ์ฌ์ํ, ๋ฏธ์ฐ์น์ ํ๋ผ๋ค(Miuccia Prada)๋ ์์ ์ฌ๋จ ์ด์์ผ๋ก ํญ์ ์ธ๋ก ์ ๊ด์ฌ์ ๋ฐ์ผ๋ฉด์ ๋์์ธํ์ฐ์ค๋ฅผ ๋์ค์๊ฒ ๊ฐ์ธ์์ผฐ๋ค. ์คํธ์ฟ ํ๋ฅด ์๋์ ํ๋ ํํฌ๋ฅดํ
์๋์ ๋์์ด๋๋ค์ ๊ฐ์ธ ํฌ์์๋ค์ ํฌ์๋ฅผ ๋ฐ์ ๋์์ธํ์ฐ์ค๋ฅผ ์ด์๋ค. ๊ธ๋ก๋ฒ ํจ์
์๋์๋ ์ ์ธ๊ณ ๋ง์ผ ์๋๋ก ์ฌ์
์ ์งํํด ๋ง๋ํ ๋น์ฉ์ด ํ์ํ๊ธฐ ๋๋ฌธ์ ๊ฑฐ๋ ๋ณตํฉ๊ธฐ์
๋ค์ด ์ค์ํ ํฌ์์๊ฐ ๋์๋ค. ์ด ๋ฐ์ ํจ์
์ ์๊ฐ ์๋ก์ด ๋ฌธํ ํ์์ผ๋ก ์๋ฆฌ ์ก์ผ๋ฉด์ ํ๋ ํํฌ๋ฅดํ
์๋์ ๊ธ๋ก๋ฒ ํจ์
์๋์๋ ํจ์
ํ๋ ์ดํฐ๋ผ๋ ๋ฌธ์ง๊ธฐ๊ฐ ์ถ๊ฐ๋์๋ค.
๋ฏธํ์ด ์น์ผํธ๋ฏธํ์ด(M. Csikszentmihalyi)์ ํ์๋ ๊ฐ๋๋(H. Gardener)์ ์ด๋ก ์ ๊ธฐ๋ฐ์ผ๋ก ์ฐฝ์์ ์ธ ํ๋ํจ์
๋์์ด๋ 9์ธ์ ์ฌ๋ก์ฐ๊ตฌ๋ฅผ ์งํํ ๊ฒฐ๊ณผ ํจ์
์ ๋๋ฌ์ผ ์ฌํยท๋ฌธํ ๋งฅ๋ฝ ์์์ ํจ์
๋์์ด๋ ๊ฐ์ธ์ ๋ฌธ์ ์ ์ ๋ฐ๊ฒฌํ๊ณ ์๋ก์ด ์ฐ์ถ๋ฌผ์ ์ ์ํ๊ณ , ์๋ง์ ์ฐ์ถ๋ฌผ๋ค์ด ํจ์
ํ์ฅ์ด ํ๊ฐํ๋ ๊ณผ์ ์ ํตํด ๋ค์ ์๋ฏธ ์๋ ํจ์
๋ฌธํ๋ก ์ฐฝ์ถ๋จ์ ํ์ธํ์๋ค. ํจ์
๋์์ด๋๋ ์ฐฝ์์ฑ ๋ฐํ์ ์ํด์ ์ฌํ์ฑ, ๊ต์, ๊ธฐ์ ๋ฑ ์ธ์ง์ ๋ฅ๋ ฅ์ ํค์ฐ๊ณ , ํจ์
์์ญ์ ์ ๋ณด๊ฐ ์์ง๋์ด์๋ ๊ณณ์ผ๋ก ์ด๋ํ์ฌ ์ ๊ทน์ ์ผ๋ก ํจ์
ํ์ฅ๊ณผ ์ํธ์์ฉ์ ํด์ผ ํ๋ค๋ ์ ์ด ํ์ธ๋์๋ค.In fashion attaching great importance to values of innovation, newness and a change, 'creativity' is the source of competitive power as the most important key. Development of the 21st info-communications caused sharing of new materials and technologies, outstandingly lessening a technological gap among fashion products. In a flood of standardized fashion products, creativity along with art will and imagination of a fashion designer is being emphasized as the key element of differentiation. This study aims at examining factors influencing on fashion designers' creativity presenting fashion the new centered on integrated perspectives of M. Csikszentmihalyi and H. Gardener. Together with fashion designers' domain characteristic and talent, this study presents a broad analysis centered on the method responding to sociocultural systems in the fashion domain and expressing art will and philosophy, and relationship with the field evaluating value of a new design.
Research findings of this thesis are as follows.
Firstly, this study defined creativity of fashion designers and developed an analytic model based on the general consideration of creativity. It gave a definition on the creativity of fashion designers as 'a competence a fashion designer belonging to the fashion system can create a new and useful product based on knowledge of the symbolic system of fashion, revealed when winning recognition of newness and usefulness in the contemporary field with inclusion into the fashion domain. Influencing factors of fashion designers were subdivided into person, fashion domain and the fashion field. Personal factors of fashion designers contain cognitive abilities(skill, culture, sociality),non-cognitive abilities(character, Erotic Capital), socialยทpsychological factors(family, sexual identity, marriage, health). Influencing factors of creativity in the fashion domain could be mentioned as interaction between fashion designer's main creation and Zeitgeist, social structure, technology of the social cultural context of fashion, as a paradigm designer's creation is incorporated into part of the domain. Fashion field is composed of fashion workers and leaders including a fashion editor, buyer, fashion educator, fashion designer, investor, business partner, fashion model, staff as gatekeepers who are working in the fashion industry or influencing on the fashion creation.
Secondly, using an analytic model of fashion designers' creativity developed already, a case study was conducted about 9 creative fashion designers of Haute CoutureยทPret-A-Porter in the global fashion age. The findings are as follows.
As a person having characters of sociality, cognitive competence for technology, ambition, independence with Erotic Capital, Gabrielle "Coco" Chanel suggested a new paradigm of the functionalist design introducing practicality of men's wear while resisting the conspicuous fashion that makes women dependent. A lot of lovers, avant garde artist groups, American fashion editors and buyers supported revelation of creativity. Cristรณbal Balenciaga, along with excellent cubic expression(3D) intelligence and sincere character, created most of silhouettes in the contemporary fashion. An innovative clothing construction of Cristรณbal Balenciaga, rejecting commercialism and concentrating on realization of pure formative beauty, was established as a new paradigm under enthusiastic support from fashion editor and colleagues. Equipped with cognitive capabilities including sociality, refinement and skills, Christian Dior had character of openness and sensibility. He created a paradigm of romantic clothing having a property of escapism in the fashion recession after the war and revived a tradition of Haute Couture. Through business diversification including licensing and a Pret-A-Porter enterprise, he pursued commercialism, supported by artist groups and fashion press.
Yves Saint Laurent had cognitive abilities including skills, sociality and culture, character of sensibility and openness and higher Erotic Capital. Together with the flow of the age, he created every style of the contemporary fashion through various works inspired by men's wear, street fashion, art works and traditional costumes of many nations. He was supported by fashion press, business partners and followed by numerous designers of future generations. Karl Lagerfeld has higher cognitive abilities of sociality, culture and skills, character of openness and Erotic Capita of outstanding social presentation. With the change of the fashion system, he created a new paradigm of the brave fashion soldiers that added newness to the uniqueness of the existing design house while advancing into Pret-A-Porter industry and leading House of Chanel. Inspired by young sensuous artist groups, he understood the spirit of Zeitgeist and maintained fashion leadership. Vivienne Westwood has cognitive capabilities of skills and culture, and character of independence. She created a new paradigm of the postmodernism fashion based on the punk fashion and costumes of historicism while resisting the existing trend. As a person having Erotic Capital, she was supported by youngsters when working as a boutique designer. After growing up as a high fashion designer, she was supported by fashion editors and curators.
Miuccia Prada has cognitive abilities of refinement and sociality with character of openness. Thinking much of making clothes easy to wear, since 1990s, she's suggested a new paradigm of minimalism, fever of it bag and 'Ugly Chic' for intelligent elites. With the emotional and cognitive supports of her husband, a business partner, she's also supported by fashion editors. Alexander McQueen had cognitive abilities of skills, culture, sociality and character of sensibility and independence. Based on the keen sensitivity and brilliant technical skills, he presented an autobiographical fashion of expressionism and created a new paradigm of transmitting feelings by converting a fashion show to the performance. He was influenced by avant-garde contemporary artists in Britain, attracting attention from fashion editors. Marc Jacobs has cognitive abilities of sociality, refinement and character of openness and sensibility. As a person having Erotic Capital including beauty, vivaciousness and energy, social attractiveness, he has fans from the masses. He created a grunge look inspired by pop culture, pop music and secondhand clothes with a paradigm of fashion avant-garde but easy to wear through daring borrowing and turning a fashion designer into an entertainer. With the support of fashion editors, contemporary artists, global groups, fashion models including the general, he's winning a commercial success.
Thirdly, influencing factors of creativity, identified through case studies of 9 creative fashion designers in the contemporary fashion period, were analyzed by person, domain and field, The findings are as follows.
In the personal factors, cognitive abilities of a designer were given different emphasis according to the times. Skills were emphasized in the age of Haute Couture and culture and skill in the Pret-A-Porter age. Global fashion age gave emphasis on culture and sociality for storytelling, making much of ideas rather than clothing itself. As for designers, the important personal factor penetrating every period is Erotic Capital. Designers have fascinated the fashion field using innate beauty, sexual attractiveness, vivaciousness and energy, characteristic fashion sense and sociality. In addition, in terms of the social psychological situation, particularly every male designer was homosexuals.
As the result of examining factors of creativity in the fashion domain, fashion designers cultivated the fashion domain knowledge through apprenticeship at the Haute Couture House and professional fashion training, and suggested a new product while resisting or following the existing ideology actively. Creative products of 9 fashion designers were incorporated again into the domain with the support of fashion editors, buyers and fashion leaders, becoming a new paradigm of the fashion domain. Paradigms contain fashion trends like the functionalist fashion of Gabrielle "Coco" Chanel and fashion practices like revival of the old design house. Fashion is an industrial product for making a profit, so designers' perspective to commercialism has an important effect on creative activities. Yves Saint Laurent, Karl Lagerfeld, Miuccia Prada, Marc Jacobs, taking notice of the periodic atmosphere rather than of the unique style, suggested a new style every season and became a trend-setter. As designers having outstanding technical skills, Cristรณbal Balenciaga, Vivienne Westwood, Alexander McQueen discovered inspiration for creation from their skills and showed the consistent work world. Furthermore, it was identified that every fashion designer moved to the main fashion cities information and technical skills of the fashion domain are centralized.
In the fashion field all over the ages, a gatekeeper who became a key of fashion designers' success, was a fashion editor. Having sociality and Erotic Capital as a weapon, fashion designers communicated with fashion editors actively. Gabrielle "Coco" Chanel and Karl Lagerfeld always dominated press headlines for a venomous tongue, Alexander McQueen for the avant garde fashion show, Marc Jacobs and Yves Saint Laurent for privacy and Miuccia Prada for the art foundation operation, making the public aware of the design house. In the age of Haute Couture and Pret-A-Porter, designers opened a design house attracting funding from private investors. In the global fashion age, as business targeting global markets requires enormous expenses, conglomerates became important investors. In addition, with a new cultural phenomenon of the fashion exhibition, in the Pret-A-Porter and global age, a gatekeeper of a fashion curator was added.
This study conducted case studies of 9 creative contemporary fashion designers based on theories of M. Csikszentmihalyi and H. Gardener. As the result, it identified that a person, fashion designer, finds out a problem and suggests a new product in the sociocultural context surrounding the fashion. Also, numerous products are recreated as the meaningful fashion culture through a process fashion field evaluates. It shows that fashion designers should cultivate cognitive abilities of sociality, culture and skills for revelation of creativity, move to the place information of the fashion domain is aggregated and interact with the fashion field actively.๋ชฉ ์ฐจ
์ 1 ์ฅ ์๋ก 1
์ 1 ์ ์ฐ๊ตฌ์ ๋ชฉ์ ๊ณผ ์์ 1
์ 2 ์ ์ฐ๊ตฌ์ ๋ฐฉ๋ฒ๊ณผ ๋ฒ์ 7
์ 2 ์ฅ ์ฐฝ์์ฑ์ ์ด๋ก ์ ๋ฐฐ๊ฒฝ 10
์ 1 ์ ์ฐฝ์์ฑ์ ๋ํ ์ผ๋ฐ์ ๊ณ ์ฐฐ 10
1. ์ฐฝ์์ฑ์ ๊ฐ๋
10
2. ์ฐฝ์์ฑ ์ฐ๊ตฌ์ ์๊ฐ 14
1) ์ธ์ง์ ์ ๊ทผ 15
2) ๋น์ธ์ง์ ์ ๊ทผ 16
3) ๋ค์์ ์ ๊ทผ 19
์ 2 ์ ์น์ผํธ๋ฏธํ์ด์ ๊ฐ๋๋์ ์ฐฝ์์ฑ์ ์์คํ
๋ชจ๋ธ ๊ณ ์ฐฐ 23
1. ์น์ผํธ๋ฏธํ์ด์ ์ฐฝ์์ฑ์ ์์คํ
๋ชจ๋ธ ๊ณ ์ฐฐ 23
1) ์น์ผํธ๋ฏธํ์ด์ ์ฐฝ์์ฑ์ ์์คํ
๋ชจ๋ธ ์ฌ๋ก 24
2) ์น์ผํธ๋ฏธํ์ด์ ์ฐฝ์์ฑ์ ์์คํ
๋ชจ๋ธ ๊ตฌ์ฑ ์์ธ 26
2. ๊ฐ๋๋์ ์ฌ๋ก์ฐ๊ตฌ ์ ๊ทผ๋ฒ 34
1) ๊ตฌ์ฑ์ ์ฃผ์ 36
2) ๊ตฌ์ฑ์ ํ 37
3) ๊ฒฝํ์ ์กฐ์ฌ ๋ฌธ์ 40
4) ์๋ก ๋ฐ๊ฒฌํ ์ฃผ์ 44
์ 3 ์ ํจ์
๋์์ด๋์ ์ฐฝ์์ฑ ์ ์์ ๋ชจํ ๊ฐ๋ฐ 46
1. ํจ์
๋์์ด๋์ ์ฐฝ์์ฑ ์กฐ์์ ์ ์ 46
2. ํจ์
๋์์ด๋์ ์ฐฝ์์ฑ ๋ถ์์ ๋ชจํ ๊ฐ๋ฐ 50
1) ๊ฐ์ธ(person) 50
2) ์์ญ(domain) 64
3) ํ์ฅ(field) 71
4) ์ข
ํฉ์ ๋
ผ์ 75
์ 3 ์ฅ ์คํธ์ฟ ํ๋ฅดยทํ๋ ํํฌ๋ฅดํ
ยท๊ธ๋ก๋ฒ ํจ์
์๋์ ํจ์
๋์์ด๋ ์ฌ๋ก์ฐ๊ตฌ 80
์ 1 ์ ์คํธ์ฟ ํ๋ฅด ์๋(1900๋
๋~1950๋
๋) 80
1. ์คํธ์ฟ ํ๋ฅด ์๋์ ์ผ๋ฐ์ ๊ณ ์ฐฐ 80
2. ์คํธ์ฟ ํ๋ฅด ์๋์ ํจ์
๋์์ด๋ 88
1) ๊ฐ๋ธ๋ฆฌ์ ์ฝ์ฝ ์ค๋ฌ 88
2) ํฌ๋ฆฌ์คํ ๋ฐ ๋ฐ๋ ์์๊ฐ 105
3) ํฌ๋ฆฌ์ค์ฐฌ ๋์ค๋ฅด 122
์ 2 ์ ํ๋ ํํฌ๋ฅดํ
์๋(1960๋
๋~1980๋
๋) 142
1. ํ๋ ํํฌ๋ฅดํ
์๋์ ์ผ๋ฐ์ ๊ณ ์ฐฐ 142
2. ํ๋ ํํฌ๋ฅดํ
์๋์ ํจ์
๋์์ด๋ 149
1) ์
์ ๋ก๋ 149
2) ์นผ ๋ผ๊ฑฐํ ํธ 166
3) ๋น๋น์ ์จ์คํธ์ฐ๋ 184
์ 3 ์ ๊ธ๋ก๋ฒ ํจ์
์๋(1990๋
๋~ ํ์ฌ) 202
1. ๊ธ๋ก๋ฒ ํจ์
์๋์ ์ผ๋ฐ์ ๊ณ ์ฐฐ 202
2. ๊ธ๋ก๋ฒ ํจ์
์๋์ ํจ์
๋์์ด๋ 209
1) ๋ฏธ์ฐ์น์ ํ๋ผ๋ค 209
2) ์๋ ์ฐ๋ ๋งฅํธ 226
3) ๋งํฌ ์ ์ด์ฝฅ์ค 246
์ 4 ์ฅ ์คํธ์ฟ ํ๋ฅดยทํ๋ ํํฌ๋ฅดํ
ยท๊ธ๋ก๋ฒ ํจ์
์๋์ ํจ์
๋์์ด๋ ์ฐฝ์์ฑ ๋ฐํ์์ธ ๋ถ์ 267
์ 1 ์ ์คํธ์ฟ ํ๋ฅดยทํ๋ ํํฌ๋ฅดํ
ยท๊ธ๋ก๋ฒ ํจ์
์๋์ ๋ฐ๋ฅธ
ํจ์
๋์์ด๋์ ์ฐฝ์์ฑ ๋น๊ต ๋ถ์ 267
1. ๊ฐ์ธ์ ํน์ฑ ์์ธ ๋น๊ต ๋ถ์ 267
1) ์คํธ์ฟ ํ๋ฅด ์๋ ๋์์ด๋ 267
2) ํ๋ ํํฌ๋ฅดํ
์๋ ๋์์ด๋ 272
3) ๊ธ๋ก๋ฒ ํจ์
์๋ ๋์์ด๋ 277
2. ์์ญ ํน์ฑ ์์ธ ๋น๊ต ๋ถ์ 282
1) ์คํธ์ฟ ํ๋ฅด ์๋ ๋์์ด๋ 282
2) ํ๋ ํํฌ๋ฅดํ
์๋ ๋์์ด๋ 285
3) ๊ธ๋ก๋ฒ ํจ์
์๋ ๋์์ด๋ 290
3. ํ์ฅ ํน์ฑ ์์ธ ๋น๊ต ๋ถ์ 294
1) ์คํธ์ฟ ํ๋ฅด ์๋ ๋์์ด๋ 294
2) ํ๋ ํํฌ๋ฅดํ
์๋ ๋์์ด๋ 296
3) ๊ธ๋ก๋ฒ ํจ์
์๋ ๋์์ด๋ 299
์ 2 ์ ์ข
ํฉ์ ๋
ผ์ 302
1. ํจ์
๋์์ด๋์ ์ฐฝ์์ฑ ๋ฐํ์ ์ํฅ์ ์ค ๊ฐ์ธ์ ํน์ฑ์์ธ 302
2. ํจ์
๋์์ด๋์ ์ฐฝ์์ฑ ๋ฐํ์ ์ํฅ์ ์ค ์์ญ ์์ธ 312
3. ํจ์
๋์์ด๋์ ์ฐฝ์์ฑ ๋ฐํ์ ์ํฅ์ ์ค ํ์ฅ ์์ธ 316
์ 5 ์ฅ ๊ฒฐ๋ก ๋ฐ ์ ์ธ 320
์ฐธ ๊ณ ๋ฌธ ํ 325
๊ทธ ๋ฆผ ์ถ ์ 334
Abstract 338Docto
์ ๋ฐฉ์๊ณผ ๋์์์ ๋ฐ ์ ์์ ์ ์๊ณผ์ ๊ด๊ณ
ํ์๋
ผ๋ฌธ(์์ฌ)--์์ธ๋ํ๊ต ๋ํ์ :์ฌ๋ฆฌํ๊ณผ ์์์ฌ๋ฆฌํ์ ๊ณต,1997.Maste
-๊ถ์คํํ์ ์ ์น์ ์ฑ๊ฒฉ๊ณผ ๊ด๋ จํ์ฌ
ํ์๋
ผ๋ฌธ (์์ฌ)-- ์์ธ๋ํ๊ต ๋ํ์ : ๊ณ ๊ณ ๋ฏธ์ ์ฌํ๊ณผ(๋ฏธ์ ์ฌํ์ ๊ณต), 2012. 2. ์ฅ์ง์ฑ.๋ ์ฃผ์๊ฐ ๋ณต๊ฑด์ฑ ์ฅ์ฃผ์์ ๊ด์ง ์ํ์ ํ ๋ ๋ง๋ค์๋ค๋ ํ์(ๅพๅ)์ ๋ชจ์ต์ ๊ทธ๋ฆฐ ๊ทธ๋ฆผ์ด๋ค. ์ด ๊ทธ๋ฆผ์ 1746๋
์์กฐ(่ฑ็ฅ, ์ฌ์ 1724-1776)์ ์ฃผ๋ฌธ์ ์ํด ์ ์๋์๋ค. ๋ณธ๊ณ ๋ ์ ์์์ ์ฌ๊ฒํ ํ๊ณ ๊ทธ๋ฆผ์ ์ฃผ๋ฌธํ ์์กฐ์ ์
์ฅ์์ ๊ทธ๋ฆผ์ ๋ด์ฉ๊ณผ ์ฑ๊ฒฉ์ ์๋กญ๊ฒ ๊ท๋ช
ํ ์ฐ๊ตฌ์ด๋ค.
๊ธฐ์กด ์ฐ๊ตฌ์์๋ ๋ฅผ ์ ์ (้ญๆพ, 1676-1759)์ ์ํ์ผ๋ก ์ถ์ ํ์๋ค. ์ด์ ๋ฐ๋ผ ๊ทธ๋ฆผ์ ๋ํ ๋
ผ์ ์ญ์ ์ ์ ์ ์ค์ฌ์ผ๋ก ์ด๋ฃจ์ด์ก๋ค. ๊ทธ๋ฌ๋ ์ ์ฒด์ ์ธ ํ๋ฉด ๊ตฌ์ฑ๋ ฅ๊ณผ ๊ฑด๋ฌผ ๋ฐ ๋๋ฌด ๋ฑ์ ์ธ๋ถ ํํ, ๊ทธ๋ฆฌ๊ณ ๊ด๋ จ ๋ฌธํ๊ธฐ๋ก๋ค์ ๊ฒํ ํด๋ณธ ๊ฒฐ๊ณผ ๋ฅผ ์ ์ ์ ์ํ์ผ๋ก ๋ณด๊ธฐ๋ ์ด๋ ต๋ค. ๋์ ์ธ๋ถ ํํ์์ ๊ธฐ์กด ๊ถ์ค๊ธฐ๋กํ์ ์ ํต์ฑ์ ์ฟ๋ณผ ์ ์์ด ๋ ์ ์ ์ด ์๋ 18์ธ๊ธฐ์ ๋ํ์ ํ์์ ์ํด ๊ทธ๋ ค์ง ๊ทธ๋ฆผ์ผ๋ก ์ดํดํ๋ ๊ฒ์ด ์ ํฉํ๋ค.
๊ฐ ์ ์ ์ ์ํ์ด ์๋๋ผ๋ ์ฌ์ค์ ํ์ฌ๊น์ง ์ ์ ์ ๋ง๋
์ ๋๋ ์ ์ ์ ๊ณ ์ฌ์ธ๋ฌผ๋๋ผ๋ ๋งฅ๋ฝ์์ ์ฐ๊ตฌ๋์๋ ๋ฅผ ์๋ก์ด ๊ฐ๋์์ ์ฌ๊ฒํ ํด์ผ ํ ํ์์ฑ์ ์ ๊ธฐํ๋ค. ํ์๋ ๋ฅผ ์ฃผ๋ฌธํ ์์กฐ์ ์ฃผ๋ชฉํ์๋ค. ์์กฐ๋ ๊ทธ๋ฆผ์ ์ฃผ์ ๋ฅผ ๋ฐ์ํ์์ ๋ฟ ์๋๋ผ ํ๋ฉด ๊ตฌ์ฑ์ ์ง์ ์ง์ํ๊ณ ์ ๋ฌธ์ ๋ด์ฉ๊น์ง ๊ฒฐ์ ํ, ๊ทธ๋ฆผ์ ์ ์๊ณผ์ ์ ์ฃผ๋ํ ์ธ๋ฌผ์ด์๊ธฐ ๋๋ฌธ์ด๋ค.
์์กฐ๊ฐ ๋ฅผ ์ฃผ๋ฌธํ ์ผ์ฐจ์ ์ธ ์ด์ ๋ ์ฃผ์์ ์ฅ์ฃผํ์์ ์์ ํ๊ธฐ ์ํด์์๋ค. ์์กฐ๋ ๊ทธ๋ฆผ์ ์๋จ ์ด์ ์์ ์ด์ง ์ด(์ฃผ์)๊ฐ ๋
ธ๋๋ ๊ณณ์ ์์ ๋ฏ์ด ํ๊ฒ ๋ค๋ผ๊ณ ์ ์ด๋๊ณ ใ์ฅ์ฃผ๋ฌ์๋ใ๋ฅผ ๊ฐ์ํ๋ฉฐ ์ ์์ ์ธ ํด์๊ณผ ์ฌ์ถฉ์ ์ ์๊ฐ์ ๊ฐ๊ณ ์ ํ์๋ค.
๊ทธ๋ฌ๋ ์์กฐ๋ ๋ฅผ ์ ํฌ์ ์ฐจ์์ ๊ตญํ์ํค์ง ์์๋ค. ์์กฐ๋ ๊ทธ๋ฆผ ์๋จ์ ์ด์ ์์ ์ผ์ฐ์ด ใ์์ฑํธใ์ ๊ธฐ์๋ฌด์ฐ ๋ง์์ ๋ํด ์ ์ ๋ฐ ์๋๋ฐ, ์ง๊ธ ๋ ์ด ๊ทธ๋ฆผ์ ๋ช
ํ ๊ฒ์ ๊ทธ๋์ ๋ป๊ณผ ํจ๊ปํ๋ ๊ฒ์ด๋ค๋ผ๊ณ ์ ์ด ๊ธฐ์๋ฌด์ฐ๋ฅผ ๊ทธ๋ฆผ์ ์ ์์๋๋ก์จ ๋ฐํ๋ค. ์์กฐ๊ฐ ํ๊ธฐ์ํจ ใ์์ฑํธใ์ ๊ธฐ์๋ฌด์ฐ ๊ตฌ์ ์ ์์กฐ ์์ ์ ๊ณ ๊ฒฐํ ๋๋์ฑ์ ์ค๋ช
ํ ๋ฌธ์ฅ์ผ๋ก์จ ํ์์ธ ์ฌ๋์ธ์์๊ฒ ํ ๋๋ผ์ ๊ตฐ์ฃผ๋ก์ ๊ฐ์ ธ์ผ ํ๋ ๋๋๊ด๋
์ฆ, ์ฒ๋ฆฌ๋ฅผ ์งํค๊ณ ์ธ์์ ๋ฒ๋ ค์ผ ํ๋ค(ๅญๅคฉ็ยท็ฅไบบๆฌฒ)๋ ๊ฒ์ ๊ฐ๋ฅด์น๊ธฐ ์ํด ์ง์ ๊ฒ์ด๋ค. ์ด์ ๊ฐ์ด ์์กฐ๋ ๋ฅผ ํตํด ์์ ์ ๋์ ๋๋์ฑ์ ๋ด๋ณด์ด๊ณ , ๋์์ ๊ตฐ์ฃผ๋ก์ ๊ฐ์ ธ์ผ ํ๋ ๋ง์๊ฐ์ง์ ํ์๊ณผ ์ ๋ฃ๋ค์๊ฒ ์ ํ๊ณ ์ ํ์๋ค.
๊ธฐ์๋ฌด์ฐ ์ฆ, ๊ธฐ์์์ ๋ชฉ์ํ๊ณ ๋ฌด์ฐ์์ ๋ฐ๋์ ์ฌ๊ฒ ๋ค๋ ์ด ๊ตฌ์ ์ ใ๋
ผ์ดใ์์ ๋ฐ์ท๋ ๊ฒ์ด๋ค. ์์กฐ๋ ๊ธฐ์๋ฌด์ฐ๋ผ๋ ๊ตฌ์ ์ ์กฑ์์ ๋จ๋
ํ์ (็ต้ก)๋ก ์ ํํ ์ ๋๋ก ์๋นํ ์ค์ํ๊ฒ ์๊ฐํ์๋ค. ์ด๋ ๊ธฐ์๋ฌด์ฐ๋ฅผ ์์์ ์ ์น์ ์ฐ๊ฒฐ์ํค๋ ๋ถ์ก๋ ์ฑ๋ฆฌํ์๋ค์ ํด์ ๋๋ฌธ์ด์๋ค. ์์์ ์์กฐ๊ฐ ๋ถ๋น์ ์น๋ฅผ ๊ทน๋ณตํ๊ณ ํํ์ ์น๋ก ๋์๊ฐ๊ธฐ ์ํด ๋ด์ธ์ด ์ด์์ ์ธ ๊ตฐ์ฃผ์ ๋ชจ์ต์ด์๋ค. ์์กฐ๊ฐ ์ฃผ์์ ๊ณ ์ฌ๋ฅผ ๊ทธ๋ฆผ์ผ๋ก ๊ทธ๋ฆฌ๊ณ ๊ธฐ์๋ฌด์ฐ๋ฅผ ์ด์ ์์ ๋ช
์ํ ์ด์ ๋ ๋ฅผ ํตํด ์์ ์ด ์์์ ๋์
์ ์ด๋ฃฐ ์ ์๋ ์ฑ์์์ ์์ํ๊ธฐ ์ํด์์๋ค.
์์กฐ๊ฐ ๋ฅผ ํตํด ํ์ํํ๊ณ ์ ํ์๋ ์ด์์ ์น์ ๋ชจ์ต์ ์ฅ์ฃผํ์์ ํํ ์์๋ค์ ํตํด์๋ ํ์ธ๋๋ค. ๋จผ์ ๊ทธ๋ฆผ ์ ์ฒด์ ไบ์ํ ๊ตฌ์กฐ๋ ์ด์์ ์ธ ์ ์น์ง์๊ฐ ํ์ํ๋ ๋ชจ์ต์ด๋ค. ๋ํ ๋ฌ์์ ๊ทธ๋ ค์ง ํ๊ด์ ๋ณต๊ด๋ ์กฐ์ ์ ์ํต ๋ฐ ํํฉ, ๋ฐฑ์ฑ๋ค์ ์์๊ณผ ๊ตฐ์์ ์ถํ์ ๋ฐ๋ฅธ ๋๋ผ์ ์คํฅ์ผ๋ก ํด์ํ ์ ์๋ค. ๊ฐ ์ ์ฒด ๊ตฌ์กฐ๋ฅผ ํตํด ์ด์์ ์ธ ๊ตญ๊ฐ์ ๋ชจ์ต์ ๋ณด์ฌ์ฃผ๊ณ ์๋ค๋ฉด, ๋ฌ์์ ๊ทธ๋ ค์ง ํ๊ด์ ๋ณต๊ด๋ ๊ทธ ์ด์ํฅ์ผ๋ก ๋์๊ฐ๋ ๋ฐฉ๋ฒ์ ์์ง์ ์ผ๋ก ํํํ ๊ฒ์ด๋ค. ๊ฒฐ๊ตญ ๋ ์ด์๊ตญ๊ฐ๋ฅผ ๊ฑด์คํ๊ณ ์ ํ๋ ์์กฐ์ ์ ์น์ ๋ชฉ์ ๊ณผ ํ์์ด ์์ ์ ์ฌ์
์ ๊ณ์ ํ ๊ฒ์ด๋ผ๋ ๊ธฐ๋๊ฐ ๋ฐ์๋ ๊ทธ๋ฆผ์ด๋ผ๊ณ ํ ์ ์๋ค.The Thatched Hut of Zhangzhou(ๆผณๅท่ๅบตๅ), illustrating a story of Zhu Xi(ๆฑ็น, 1130-1200) when he was the magistrate of Zhangzhou, was commissioned by the king Yeongjo(่ฑ็ฅ, r. 1724-1776) in 1746. This thesis reexamines its style and explores its political aspect.
Because The Thatched Hut of Zhangzhou was attributed to Zheng Shan(1676-1759), one of the most renowned painter in late Joseon dynasty, its discussions were mainly about Zheng Shan's style. But based on careful consideration of its style and literature, The Thatched Hut of Zhangzhou is hardly painted by Zheng Shan. Its style show that The Thatched Hut of Zhangzhou is a court painting made by a professional painter who belongs to Joseon court at the second quarter of 18th century.
King Yeongjo led the whole process with choosing its theme, indicating the separated structure, and writing an inscription on the painting. He ordered The Thatched Hut of Zhangzhou for several reason. First, the painting was purely for relaxation. Yeongjo wanted to rest in Zhangzhou garden and share the experience with Zhu Xi.
But Yeongjo did not narrow its subject down to an enjoyment. On top of the painting, he wroted "I had recorded my mind of Yishuiwuyu(ๆฒๆฐด่้ฉ) in Zishengpian(Book of self-examination, ใ่ช็็ทจใ), and now I am ordering this painting in that same reason." This statement indicates that the Yishuiwuyu is very important clue for understanding the painting's contents and character. The sentence in Zishengpian, which Yeongjo had recalled from the statement, is about his nobility and purity. He tried to show his noble mind to the Crown Prince inspiring him to follow his path. And it is also a showoff for court official to inform his pure mind without any greediness.
Yishuiwuyu is a quotation from the analects of confucius and it means "I would cleanse ourselves in the Yi river, and revel in the cool breezes at the Wuyu alter." This sentence symbolical expression for ideal governance of Yao and shun(ๅ ฏ่), which are significant and political concept in king Yeongjo's court. In this context, Yeongjo mentioned Yishuiwuyu to suggest that he was the ideal monarch, like Yao and shun.
The image of ideal governance is support by the other pictorial element from The Thatched Hut of Zhangzhou. First of all, the frame of garden which resembles a character ไบ show an strictly established order made by ancient sages. And two divination signs inscribed on the thatched hut represents harmony and revival. In conclusion, The Thatched Hut of Zhangzhou is a reflection of Yeongjo's ambition toward the ideal governance and also his expectation with his son, the Crown Prince.Maste
ํด์ ์ฌํดํ์์ ๋ํ ๊ณ ๋น๋ ๊ดํ์์ฑ์๋ฃ ์์ฉ์ ๊ดํ ์ฐ๊ตฌ : ์ ๋ฅ ์ ์ถ ๋ฐ ์ ์กฐ๋ฅผ ์ค์ฌ์ผ๋ก
ํ์๋
ผ๋ฌธ (๋ฐ์ฌ)-- ์์ธ๋ํ๊ต ๋ํ์ : ๊ณผํ๊ต์ก๊ณผ ์ง๊ตฌ๊ณผํ์ ๊ณต, 2017. 2. ๋ฐ๊ฒฝ์ .The spatial distribution of an oil spill and its temporal dispersion within a coastal bay were investigated using high-resolution optical images. A neural network method was applied to Landsat and DubaiSat-2 images to detect the oil spill. We conducted field observations to measure spectral characteristics of the oil spill and the oil-free sea surface. We were able to detect and eliminate pixels corresponding to ships and ship shadows on the satellite image, resulting in successful oil spill detection. A new recursive neural network method using a near-infrared band was developed to classify oil types into thick or film-like oil and to estimate their areal extents. To understand potential causes of the temporal evolution of the oil spill, we performed numerical modeling with atmospheric and oceanic inputs. Overall, trajectories of oil particles controlled by tidal currents showed good agreement with the detection results from satellite data. Slight discrepancies occurred between satellite data and results from the model simulation using only tidal currents, particularly in the southeastward dispersion or in the spreading of film-like oils into the northern inner channels. This was attributed to the effect of wind-driven Ekman drift. This study suggests that tidal currents played an important role in the temporal dispersion of oil in the bay during initial phases, when wind conditions were relatively weak, and that the Ekman drift became the dominant control on oil movement during periods of weak tidal currents and strong winds.
Speckles in the suspended particulate matter (SPM) data of the Geostationary Ocean Color Imager (GOCI) were spatiotemporally analyzed. The speckles were classified into four types based on their appearance: isolated speckle, speckle near cloud, patch-type speckle, and slot-related speckle. The spectral characteristics of the speckles were analyzed. We developed a speckle removal procedure to detect the speckles. The speckle removal improved the quality of the GOCI SPM data. We conclude that the speckles were generated by the unmasked clouds edge, water vapor, and small clouds that move during the spectral scanning sequences.
From field cruises around the Korean coast, we found that red tide had a bimodal spectral distribution, having two peaks at 555 nm and 680 nm. A red tide index (RTI) algorithm was developed based on in situ spectral characteristics of red tide bloom and validated by in situ red tide measurements. The RTI algorithm was applied to reprocessed GOCI data with speckle removal for the period from 2011 to 2016. The phenology of red tide, such as starting time, ending time, duration, and spatial probability, was estimated using satellite RTI data. Migration and propagation of red tide along and across the coast was investigated spatially and temporally. The relationship between RTI and environmental parameters, such as sea surface temperature, cloudiness, sea surface wind, river discharge, colored dissolved organic matter, Chlorophyll-a, SPM, were clarified.Overview 1
Part I. Oil Spill 2
Chapter 1. Introduction 3
1.1. Previous Study 3
1.2. Objectives of This Study 7
Chapter 2. Data Description 10
2.1. Satellite Data 10
2.1.1. Landsat ETM+/OLI 10
2.1.2. DubaiSat-2 13
2.2. Field Observation 17
2.2.1. Oceanic Optical Measurement 17
2.2.2. Wind Data 18
Chapter 3. Methods 19
3.1. Field Observation 19
3.2. Conversion of In Situ Measurements 20
3.3. Neural Network 22
3.4. Ship and Ship Shadow Masking 24
3.4.1. Ship Mask 24
3.4.2. Ship Shadow Mask 25
3.5. Particle Tracking 27
3.5.1. Numerical Tide Model 27
3.5.2. Ekman Drift Surface Current 29
3.5.3. Oil Spill Trajectory 30
Chapter 4. Result 31
4.1. Removal of Ship and Ship Shadow Pixels 31
4.2. Spectral Characteristics of Oil 33
4.3. Ship and Ship Shadow Masking 36
4.4. Image Classification into Thick oil/Film-like oil 39
4.5. Tidal Effects on Oil Spill Dispersion 43
4.6. Effect of Wind on Oil Spill Dispersion 49
Chaper 5. Summary and Conclusion 55
References 58
Part II. Speckle 68
Chapter 1. Introduction 69
Chapter 2. Data and Method 73
Chapter 3. Results 76
3.1. Speckle Types 76
3.1.1. Isolated Speckles 80
3.1.2. Speckles Near/Along Clouds 82
3.1.3. Patch-type Speckles 85
3.1.4. Slot-related Speckles 87
3.2. Causes of Speckles 89
3.2.1. Cloud Movement 89
3.2.2. Cloud and Cloud Shadowing 91
3.2.3. Atmospheric Correction for Water Vapor 93
3.2.4. Sensor Calibration 95
3.3. Removal Process of Speckles 96
3.4. Comparison with a Reprocessed SPM Map 99
Chapter 4. Summary and Conclusion 106
References 108
Part โ
ข. Red Tide 112
Chapter 1. Introduction 113
1.1. Previous Research 113
1.2. Satellite Application to Red Tide Detection 117
1.3. Study Objectives 119
Chapter 2. Data 120
2.1. Satellite Data 120
2.2. In-Situ Optical Measurement 121
2.3. In-Situ Red Tide Observation 125
2.4. Wind Data 130
Chapter 3. Methods 131
3.1. Algorithm Development 131
3.2. Digitization of Red Tide Report 135
3.3. Relation with Red Tide Index and Red Tide Density 137
3.4. Algorithms of Ocean Color Parameters 139
3.5. Cloudiness 140
Chapter 4. Results 141
4.1. Comparison with Previous RTIs 141
4.2. Validation of RTI 143
4.2.1. Relationship with SPM, CDOM, and Chl-a 143
4.2.2. Diurnal Variation of Red Tide 146
4.3. Fundamental Variability of Red Tide 151
4.3.1. Along-Shore Variability of Red Tides 159
4.3.2. Across-Shore Variability of Red Tides 165
4.3.3. Occurrence Time of Maximum Red Tide Bloom 167
4.3.4. Life Span of Red Tide Bloom 170
4.3.5. Red Tide Bloom near Jeju Island 174
4.3.5.1. Peculiar spatial distribution of red tides in 2016 174
4.3.5.2. Tracking red tides in the Yangtze River region 179
4.3.5.3. In-situ red tide occurrence around Jeju island 182
4.3.5.4. Spatial variability of red tides around Jeju island 185
4.4. Potential Causes of Red Tide Bloom 186
Chapter 5. Discussion 191
5.1. In-situ Measurement Data and RTI Validation 191
5.2. Satellite Sensor-Generated Problems 194
5.3. Limitation of RTI Index 195
5.4. Red Tide Species around Jeju 199
5.5. Case of Yellow Sea 200
5.6. Difference between Region Classifications between Scientists 202
5.7. Yangtze River Discharge 204
5.8. Further Study 206
Chapter 6. Summary and Conclusion 207
References 210
Abstract in Korean 214Docto
Study of work on caricature
ํ์๋
ผ๋ฌธ (์์ฌ)-- ์์ธ๋ํ๊ต ๋ํ์ : ์กฐ์๊ณผ ์กฐ์์ ๊ณต, 2011.8. ์ต์ธ์.Maste