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    ๊ณ ํ•ด์ƒ๋„ PET ์‹œ์Šคํ…œ์„ ์œ„ํ•œ PET ๊ฒ€์ถœ๊ธฐ์˜ 3์ฐจ์› ์œ„์น˜ ์ •๋ณด ์ •ํ™•๋„ ํ–ฅ์ƒ ๊ธฐ์ˆ  ๊ฐœ๋ฐœ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์˜๊ณผ๋Œ€ํ•™ ํ˜‘๋™๊ณผ์ • ๋ฐฉ์‚ฌ์„ ์‘์šฉ์ƒ๋ช…๊ณผํ•™์ „๊ณต, 2018. 2. ์ด์žฌ์„ฑ.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€ ์กฐ์ง๊ณผ์˜ ๊ฒฝ๊ณ„๋ฉด ๋ถ„ํ• ์— ๋Œ€ํ•œ ๊ณ ์ฐฐ

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ์น˜๊ณผ๋Œ€ํ•™ ์น˜์˜๊ณผํ•™๊ณผ, 2022. 8. ์ด์žฌ์ผ.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 observerโ€™s 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 ์€ ์น˜๊ณผ์šฉ ์ž„ํ”Œ๋ž€ํŠธ ์กฐ์ง ์ด๋ฏธ์ง€์˜ ๋ผˆ ์กฐ์งํ˜•ํƒœ๊ณ„์ธก์—์„œ ์ธ๊ณต์ง€๋Šฅ ๋”ฅ๋Ÿฌ๋‹ ๊ธฐ๋ฒ•์ด ํšจ์œจ์ ์ด๊ณ  ์ผ๊ด€์ ์ธ ๋ณด์กฐ์ˆ˜๋‹จ์œผ๋กœ ํ™œ์šฉ์ด ๊ฐ€๋Šฅํ•œ ์ง€ ๊ณ ์ฐฐํ•˜๋Š” ๊ฒƒ์ด๋‹ค. ์ด๋ฅผ ์œ„ํ•ด ์—ผ์ƒ‰๋œ ์ƒ‰์ƒ ๊ธฐ๋ฐ˜์˜ ์„ ํ–‰ ๊ฐœ๋ฐœ ๋ฐฉ์‹๊ณผ ๋”ฅ๋Ÿฌ๋‹ ๊ธฐ๋ฒ•์„ ๋น„๊ตํ•˜์—ฌ ์ž„ํ”Œ๋ž€ํŠธ์™€ ์ฃผ๋ณ€ ์กฐ์ง์œผ๋กœ์˜ ์ด๋ฏธ์ง€ ๋ถ„ํ•  ์ •ํ™•๋„๋ฅผ ํ‰๊ฐ€ํ•˜์˜€๋‹ค. ๋ฐฉ ๋ฒ• ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ํ† ๋ผ์˜ ๊ฒฝ๊ณจ์— ์‹๋ฆฝ๋œ ์น˜๊ณผ์šฉ ์ž„ํ”Œ๋ž€ํŠธ ํ‘œ๋ณธ 16์žฅ์—์„œ 200๋ฐฐ์œจ๋กœ ์ดฌ์˜๋œ ์ด๋ฏธ์ง€๋ฅผ ์‚ฌ์šฉํ•˜์˜€๋‹ค. Ground truth๋กœ ์‚ฌ์šฉํ•˜๊ธฐ ์œ„ํ•œ ์ด๋ฏธ์ง€ ์ฃผ์„(annotation) ์ฒ˜๋ฆฌ๋ฅผ ํ†ตํ•ด ํ•˜๋‚˜์˜ ์ด๋ฏธ์ง€ ์ „์ฒด๋ฅผ ์ž„ํ”Œ๋ž€ํŠธ ์˜์—ญ๊ณผ ์กฐ์ง ์˜์—ญ์˜ ๋‘๊ฐ€์ง€ ํด๋ž˜์Šค๋กœ ๊ตฌ๋ถ„ํ•˜์˜€๋‹ค. ๊ด€์‹ฌ ์˜์—ญ์€ ๋‘๊ฐ€์ง€ ํด๋ž˜์Šค์˜ ๊ฒฝ๊ณ„์„ ์„ ์ค‘์‹ฌ์œผ๋กœ ์„ค์ •ํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ์—์„œ ์‚ฌ์šฉํ•œ ์ธ๊ณต์ง€๋Šฅ ๋ฐฉ๋ฒ•๋ก ์€ kNN๊ณผ ๋”ฅ๋Ÿฌ๋‹ U-Net ๋ชจ๋ธ ๋‘๊ฐ€์ง€๋กœ, kNN์€ ์ƒ‰์ƒ์„ ๋‚˜ํƒ€๋‚ด๋Š” ๊ฐ ํด๋ž˜์Šค์˜ ๋Œ€ํ‘œ ํ”ฝ์…€๊ฐ’(instance)์— ๊ธฐ๋ฐ˜ํ•˜์—ฌ ๋ถ„ํ• ์ด ์ด๋ฃจ์–ด์ง„๋‹ค. ๋”ฅ๋Ÿฌ๋‹ U-Net ๋ชจ๋ธ์€ ์ธ๊ณต์ง€๋Šฅ ๊ธฐ๋ฐ˜ ์˜๋ฃŒ ์ด๋ฏธ์ง€ ๋ถ„ํ•  ์—ฐ๊ตฌ์—์„œ ํ™œ๋ฐœํ•˜๊ฒŒ ์‚ฌ์šฉ ์ค‘์ธ ๋ชจ๋ธ๋กœ, ๋ณธ ์—ฐ๊ตฌ๋Š” ๊ฐ€์žฅ ๊ธฐ๋ณธ์ ์ธ ๊ตฌ์กฐ์ธ Vanilla U-Net์„ ์‚ฌ์šฉํ•˜์˜€๋‹ค. ๋‘๊ฐ€์ง€ ๋ฐฉ๋ฒ•๋ก  ๊ฐ„์˜ ๊ฒฐ๊ณผ๋ฅผ ๋น„๊ตํ•˜๊ธฐ ์œ„ํ•ด ๋”ฅ๋Ÿฌ๋‹ ํ›ˆ๋ จ์— ์‚ฌ์šฉํ•˜์ง€ ์•Š์€ ํ…Œ์ŠคํŠธ ์ด๋ฏธ์ง€๋ฅผ ์‚ฌ์šฉํ•˜์˜€๊ณ , Ground truth ์ด๋ฏธ์ง€์™€ ์˜ˆ์ธก๋œ ์ด๋ฏธ์ง€๋ฅผ ํ”ฝ์…€ ๋‹จ์œ„๋กœ ๋น„๊ตํ•˜์—ฌ ์ •ํ™•๋„์™€ ๋ฏผ๊ฐ๋„, Area under ROC curve(AUROC)๋กœ ํ‰๊ฐ€ํ•˜์˜€๋‹ค. ๊ทธ๋ฆฌ๊ณ  Intersection Over Union(IOU), Dice similarity coefficient(DSC)์˜ ๋‘๊ฐ€์ง€ ์ง€ํ‘œ๋กœ ๋‚˜ํƒ€๋‚ด์–ด ๋ถ„ํ•  ์ •ํ™•๋„๋ฅผ ๋น„๊ตํ•˜์˜€๋‹ค. ๊ฒฐ ๊ณผ kNN์—์„œ ์ž„์˜๋กœ ํ•œ ์žฅ์˜ ์ด๋ฏธ์ง€๋ฅผ ์„ ํƒํ•˜์—ฌ instance๋ฅผ ์ง€์ •ํ•˜์˜€๊ณ , ๋ชจ๋“  ์ด๋ฏธ์ง€ ๋ฐ์ดํ„ฐ์—์„œ ์˜ˆ์ธก ๊ฒฐ๊ณผ๋ฅผ ์ถ”์ถœํ•˜์—ฌ Ground truth์™€์˜ ์ •ํ™•๋„๋ฅผ IOU ์ง€ํ‘œ๋กœ์„œ ๋น„๊ตํ•˜์˜€๋‹ค. ๊ด€์‹ฌ ์˜์—ญ์˜ ์ •ํ™•๋„๋Š” 65~96% ๋ฒ”์œ„์—์„œ ํ‰๊ท  90.39%๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ด์ค‘ 65.83%๋กœ ๊ฐ€์žฅ ๋‚ฎ์€ ์ •ํ™•๋„๋ฅผ ๋ณด์ธ ์ด๋ฏธ์ง€์— ๋งž์ถ”์–ด ๋‹ค์‹œ instance๋ฅผ ์ง€์ •ํ•˜์˜€์„ ๋•Œ ํ•ด๋‹น ์‚ฌ์ง„์€ 91.39%๊นŒ์ง€ ์ •ํ™•๋„๊ฐ€ ์ƒ์Šนํ•˜์˜€๊ณ , ์˜ˆ์ธก ๊ฒฐ๊ณผ ์ด๋ฏธ์ง€์—์„œ ๊ฐ ํด๋ž˜์Šค์˜ ์„œ๋กœ ์˜์—ญ์œผ๋กœ ์นจ๋ฒ” ์—†์ด ๊ฒฝ๊ณ„๊ฐ€ ๋ช…ํ™•ํ•ด์ง€๋Š” ์–‘์ƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์ด๋ฅผ ํ†ตํ•ด ํ‰๊ฐ€ํ•˜๊ณ ์ž ํ•˜๋Š” ์กฐ์ง ์ด๋ฏธ์ง€๊ฐ€ ๋ณ€๊ฒฝ๋  ๋•Œ๋งˆ๋‹ค ๊ทธ ์ด๋ฏธ์ง€์— ๋งž์ถ”์–ด ๊ธฐ์ค€๊ฐ’์„ ์กฐ์ •ํ•ด์•ผ ํ•˜๋Š” ๊ด€์ฐฐ์ž์˜ ์ˆ˜๋™ ๊ฐœ์ž…์ด ๋งค๋ฒˆ ํ•„์š”ํ•˜๋‹ค๋Š” ํ•œ๊ณ„์ ์„ ํ™•์ธํ•˜์˜€๊ณ , ์ด๋Š” ์„ ํ–‰ ๊ฐœ๋ฐœ๋œ ์—ผ์ƒ‰๋œ ์ƒ‰์ƒ ๊ธฐ๋ฐ˜ ๋ฐฉ์‹์—์„œ ๋‚˜ํƒ€๋‚˜๋Š” ํ•œ๊ณ„์ ๊ณผ ๋™์ผํ•˜์˜€๋‹ค. ๊ด€์‹ฌ ์˜์—ญ์—์„œ ์ž„ํ”Œ๋ž€ํŠธ๋ฅผ ๊ธฐ์ค€์œผ๋กœ sensitivity๋Š” ํ…Œ์ŠคํŠธ ์ด๋ฏธ์ง€ ํ‰๊ท  kNN์€ 90.68%, ๋ฐ์ดํ„ฐ ์ฆ๊ฐ•์„ ์ง„ํ–‰ํ•œ U-Net ๋ชจ๋ธ์—์„œ๋Š” 98.32%, accuracy๋Š” kNN์—์„œ 94.89%, U-Net ๋ชจ๋ธ์—์„œ 97.86%, AUROC๋Š” kNN์—์„œ 93.69%, U-Net ๋ชจ๋ธ์—์„œ 99.79%๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. IOU๋Š” kNN์—์„œ 84.19%, U-Net ๋ชจ๋ธ์—์„œ 93.4%์˜€์œผ๋ฉฐ, DSC๋Š” kNN์—์„œ 91.03%, U-Net ๋ชจ๋ธ์—์„œ 96.58%๋ฅผ ๋ณด์ด๋ฉฐ ๋”ฅ๋Ÿฌ๋‹ ๊ธฐ๋ฒ•์„ ์‚ฌ์šฉํ•˜์˜€์„ ๋•Œ ๊ธฐ์กด์˜ ์ƒ‰์ƒ ๊ธฐ๋ฐ˜ ๋ถ„ํ•  ๋ฐฉ์‹๊ณผ ๋น„๊ตํ•˜์—ฌ ์šฐ์ˆ˜ํ•œ ์„ฑ๋Šฅ์ด ํ™•์ธ๋˜์—ˆ๋‹ค. ๋”๋ถˆ์–ด ๋ถ„ํ•  ๊ฒฐ๊ณผ ์ด๋ฏธ์ง€๋ฅผ ํ™•์ธํ•˜์˜€์„ ๋•Œ kNN์— ๋น„ํ•ด ๋‘๊ฐ€์ง€ ํด๋ž˜์Šค๋กœ์˜ ๋ถ„ํ• ์ด ์„œ๋กœ์˜ ์˜์—ญ์œผ๋กœ ์นจ๋ฒ” ์—†์ด ๋”์šฑ ๋ช…ํ™•ํ•œ ์–‘์ƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๊ฒฐ ๋ก  ์ธ๊ณต์ง€๋Šฅ ๋”ฅ๋Ÿฌ๋‹ ๊ธฐ๋ฒ•์€ ์น˜๊ณผ์šฉ ์ž„ํ”Œ๋ž€ํŠธ์˜ ์กฐ์งํ•™์  ๋ถ„์„์—์„œ ์ค‘์š”ํ•œ ์ง€ํ‘œ์ธ Bone to implant contact(BIC)์™€ Bone area(BA)๋ฅผ ์ธก์ •ํ•  ๋•Œ ๋‚˜ํƒ€๋‚  ์ˆ˜ ์žˆ๋Š” ๊ด€์ฐฐ์ž ๊ฐ„์˜ ๊ฒฐ๊ณผ ์ฐจ์ด๋ฅผ ๋ณด์™„ํ•˜๋ฉฐ ๋ถ„์„์˜ ์ผ๊ด€์„ฑ๊ณผ ํšจ์œจ์„ฑ์„ ํ–ฅ์ƒ์‹œํ‚ค๋Š” ๋ณด์กฐ ๋„๊ตฌ๋กœ์˜ ๋ฐœ์ „ ๊ฐ€๋Šฅ์„ฑ์ด ํ™•์ธ๋˜์—ˆ๋‹ค. ๋‹ค์–‘ํ•œ ์–‘์ƒ์„ ํฌํ•จํ•œ ์กฐ์ง ์ด๋ฏธ์ง€๋ฅผ ํ™•๋ณดํ•˜๊ณ , ์ „๋ฌธ๊ฐ€์˜ ์ฃผ์„์„ ํ† ๋Œ€๋กœ ํ•œ ํ›ˆ๋ จ์ด ๋™๋ฐ˜๋œ๋‹ค๋ฉด ์กฐ์ง ์˜์—ญ์—์„œ ๋ผˆ์™€ ๋ผˆ๊ฐ€ ์•„๋‹Œ ์˜์—ญ์œผ๋กœ์˜ ๋ถ„ํ•  ์ •ํ™•๋„๊นŒ์ง€ ๋‹ฌ์„ฑํ•˜์—ฌ ๋ณ‘๋ฆฌํ•™ ์‹คํ—˜์‹ค์—์„œ ๋ผˆ์กฐ์ง ๋ถ„์„์˜ ๋ณด์กฐ ์ˆ˜๋‹จ์œผ๋กœ ํ™œ์šฉํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ํŒ๋‹จํ•˜์˜€๋‹ค.์ œ 1 ์žฅ ์„œ๋ก  1 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ์˜ ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉ์  1 ์ œ 2 ์žฅ ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• 5 ์ œ 1 ์ ˆ ๋ฐ์ดํ„ฐ๋ฒ ์ด์Šค ๊ตฌ์ถ• 5 1. ๋ฐ์ดํ„ฐ ์ˆ˜์ง‘ 5 2. ์ด๋ฏธ์ง€ ์ฃผ์„ ์ฒ˜๋ฆฌ ๋ฐ ground truth ์ด๋ฏธ์ง€ ์ƒ์„ฑ 7 3. ๊ด€์‹ฌ์˜์—ญ(Region of interest, ROI) ์„ค์ • ๋ฐฉ๋ฒ• 7 ์ œ 2 ์ ˆ ์ธ๊ณต์ง€๋Šฅ ๊ธฐ๊ณ„ํ•™์Šต ๋ฐฉ๋ฒ•๋ก  8 1. kNN 8 2. U-Net 9 ์ œ 3 ์ ˆ ์ธ๊ณต์ง€๋Šฅ ๋”ฅ๋Ÿฌ๋‹ ์‹คํ—˜ ๋ฐฉ๋ฒ• 11 1. ๋ฐ์ดํ„ฐ์…‹ ์ค€๋น„ 11 2. ๋ฐ์ดํ„ฐ ์ฆ๊ฐ• 13 3. ๋ชจ๋ธ ๋งค๊ฐœ๋ณ€์ˆ˜(parameter) ์„ ์ • 13 4. ์—ญ์นซ๊ฐ’(threshold) ์„ค์ •์„ ํ†ตํ•œ ๊ฒฐ๊ณผ ์ด๋ฏธ์ง€ ์ด๋ถ„ํ™” 13 5. ์ตœ์ข… ์˜ˆ์ธก ์ด๋ฏธ์ง€ ์ƒ์„ฑ 13 ์ œ 4 ์ ˆ ๊ธฐ๊ณ„ํ•™์Šต ์‹คํ—˜ ํ™˜๊ฒฝ 14 ์ œ 5 ์ ˆ ํ‰๊ฐ€ ๋ฐฉ๋ฒ• 14 ์ œ 3 ์žฅ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ 15 ์ œ 1 ์ ˆ ๋”ฅ๋Ÿฌ๋‹ ๋ฐ์ดํ„ฐ ๊ตฌ์„ฑ 15 ์ œ 2 ์ ˆ ์ž„ํ”Œ๋ž€ํŠธ์™€ ์กฐ์ง์œผ๋กœ์˜ ๊ฒฝ๊ณ„ ๋ถ„ํ•  ๊ฒฐ๊ณผ 16 1. kNN ๊ฒฐ๊ณผ 16 2. ๋”ฅ๋Ÿฌ๋‹ ๋ชจ๋ธ ํŒŒ๋ผ๋ฏธํ„ฐ ์„ ์ • 34 3. ๋”ฅ๋Ÿฌ๋‹ ๊ฒฐ๊ณผ ๋น„๊ต 36 ์ œ 4 ์žฅ ๊ณ ์ฐฐ 49 ์ฐธ๊ณ ๋ฌธํ—Œ 54 Abstract 62์„

    ๊ธฐ์—…์˜ ์ง€๋ฐฐ๊ตฌ์กฐ์™€ ํ•œ๊ตญ ๊ฐ€์กฑ๊ธฐ์—…์˜ ์‚ฌํšŒ์  ์„ฑ๊ณผ์— ๊ด€ํ•œ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ฒฝ์˜ํ•™๊ณผ ๊ตญ์ œ๊ฒฝ์˜์ „๊ณต, 2016. 2. ์ด๋™๊ธฐ.๊ธฐ์กด ์—ฐ๊ตฌ๋“ค์€ ๊ฒฝ์ œํ•™์— ๊ธฐ๋ฐ˜ํ•œ ๋Œ€๋ฆฌ์ธ ์ด๋ก ๊ณผ ์‹ฌ๋ฆฌํ•™์— ๊ธฐ๋ฐ˜ํ•œ ์ฒญ์ง€๊ธฐ ์ด๋ก ์— ๋”ฐ๋ผ ๊ฐ€์กฑ๊ธฐ์—…์„ ์šด์˜ํ•˜๋Š” ๊ฐ€์กฑ์—๊ฒŒ ๋‚˜ํƒ€๋‚  ์ˆ˜ ์žˆ๋Š” ํŠน์ง•๋“ค์„ ์ƒ๋ฐ˜๋˜๊ฒŒ ์„ค๋ช…ํ•˜๊ณ  ์žˆ์–ด, ๊ฐ€์กฑ์˜ ๊ฒฝ์˜์ฐธ์—ฌ์™€ ๊ธฐ์—…์˜ ์„ฑ๊ณผ์˜ ๊ด€๊ณ„์— ๋Œ€ํ•ด์„œ๋Š” ๋…ผ๋ž€์ด ์žˆ๋‹ค. ์ด์— ๋”ฐ๋ผ, ์žฌ๋ฌด์  ์„ฑ๊ณผ๋กœ ๊ฐ€์กฑ๊ธฐ์—…์„ ํ‰๊ฐ€ํ•ด์™”๋˜ ๊ฐ€์กฑ๊ธฐ์—…์— ๋Œ€ํ•œ ๊ธฐ์กด ์—ฐ๊ตฌ์™€๋Š” ๋‹ฌ๋ฆฌ, ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๊ธฐ์—…์˜ ์‚ฌํšŒ์  ์„ฑ๊ณผ (corporate social performance)๋ฅผ ํ†ตํ•ด ๊ฐ€์กฑ๊ธฐ์—…์˜ ํŠน์„ฑ์„ ์‚ดํŽด๋ณด๊ณ ์ž ํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ๊ฐ€์กฑ๊ธฐ์—…์—ฌ๋ถ€, ์‚ฌ์™ธ์ด์‚ฌ๋น„์œจ, ๊ธฐ๊ด€ํˆฌ์ž์ž๋น„์œจ์„ ๋…๋ฆฝ๋ณ€์ˆ˜๋กœ ํ•˜์—ฌ ์ข…์†๋ณ€์ˆ˜์ธ ๊ธฐ์—…์˜ ์‚ฌํšŒ์  ์„ฑ๊ณผ์— ์–ด๋–ค ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š”์ง€ ์—ฐ๊ตฌํ•˜์˜€์œผ๋ฉฐ, ๊ธฐ๊ด€ํˆฌ์ž์ž๋น„์œจ์„ ์กฐ์ ˆ๋ณ€์ˆ˜๋กœ ํ•˜์˜€๋‹ค. ๊ธฐ์—…์˜ ์‚ฌํšŒ์  ์„ฑ๊ณผ๋Š” 2007๋…„๋ถ€ํ„ฐ 2009๋…„๊นŒ์ง€ ํ•œ๊ตญ๊ฒฝ์ œ์ •์˜์—ฐ๊ตฌ์†Œ์—์„œ ๋ฐœํ‘œ๋œ ๊ฒฝ์ œ์ •์˜์ง€์ˆ˜(KEJI Index)๋ฅผ ์ด์šฉํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ ๊ฒฐ๊ณผ, ๊ฐ€์กฑ๊ธฐ์—…์€ ๋น„๊ฐ€์กฑ๊ธฐ์—…๋ณด๋‹ค ๋†’์€ ์‚ฌํšŒ์  ์„ฑ๊ณผ๋ฅผ ๋‹ฌ์„ฑํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ์œผ๋ฉฐ, ์‚ฌ์™ธ์ด์‚ฌ์˜ ๋น„์œจ์€ ๊ธฐ์—…์˜ ์‚ฌํšŒ์  ์„ฑ๊ณผ์™€ ์œ ์˜๋ฏธํ•œ ๊ด€๊ณ„๊ฐ€ ์—†๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ํ•œํŽธ, ๊ธฐ๊ด€ํˆฌ์ž์ž ๋น„์œจ์€ ๊ฐ€์กฑ๊ธฐ์—…๊ณผ ์‚ฌํšŒ์  ์„ฑ๊ณผ์— ์กฐ์ ˆ๋ณ€์ˆ˜๋กœ์„œ๋Š” ์œ ์˜๋ฏธํ•œ ๊ฒฐ๊ณผ๊ฐ€ ๋‚˜์˜ค์ง€ ์•Š์•˜์ง€๋งŒ, ๊ธฐ๊ด€ํˆฌ์ž์ž๋น„์œจ์€ ์‚ฌํšŒ์  ์„ฑ๊ณผ์— ๊ธ์ •์ ์ธ ์˜ํ–ฅ์„ ๋ฏธ์นœ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค.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

    ์›ํ˜• ์ฝ˜ํฌ๋ฆฌํŠธ์ถฉ์ „๊ฐ•๊ด€ ๋ถ€์žฌ์˜ ํœจ๊ฐ•๋„ ๋ฐ ๊ฑฐ๋™

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ฑด์ถ•ํ•™๊ณผ, 2017. 2. ๊ฐ•ํ˜„๊ตฌ.ํ•ฉ์„ฑ๊ตฌ์กฐ๋Š” ๊ธฐ์กด์˜ ์ฒ ๊ทผ์ฝ˜ํฌ๋ฆฌํŠธ๊ตฌ์กฐ๋‚˜ ๊ฐ•๊ตฌ์กฐ์™€ ๋น„๊ตํ•˜์—ฌ ๊ฐ•๋„์™€ ๊ฐ•์„ฑ ์ธก๋ฉด์—์„œ ๋ณด๋‹ค ์œ ๋ฆฌํ•˜๋‹ค. ์ด๋Ÿฌํ•œ ๊ตฌ์กฐ์  ์žฅ์  ๋•Œ๋ฌธ์— ์ดˆ๊ณ ์ธต ๊ฑด๋ฌผ๊ณผ ์žฅ๊ฒฝ๊ฐ„ ๊ตฌ์กฐ๋ฌผ์˜ ์ˆ˜์š”๊ฐ€ ๋Š˜์–ด๋‚˜๋Š” ํ˜„๋Œ€์— ์ด๋ฅด๋Ÿฌ ํ•ฉ์„ฑ๊ตฌ์กฐ๊ฐ€ ๋„๋ฆฌ ์‚ฌ์šฉ๋˜๊ณ  ์žˆ๋‹ค. ํ•ฉ์„ฑ๊ตฌ์กฐ์˜ ์ข…๋ฅ˜๋Š” ๊ทธ ํ˜•์‹์— ๋”ฐ๋ผ ์ถฉ์ „ํ˜•(CFTConcrete Filled Tube)๊ณผ ๋งค์ž…ํ˜•(SRCSteel Reinforced Concrete)์œผ๋กœ ํฌ๊ฒŒ ๋‚˜๋‰˜๋Š”๋ฐ, ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ถฉ์ „ํ˜•(CFT) ๊ตฌ์กฐ๋ฅผ ๋‹ค๋ฃฌ๋‹ค. ํŠนํžˆ ์ถฉ์ „ํ˜•(CFT)๋Š” ์••์ถ•์„ ์ง€๋ฐฐ์ ์œผ๋กœ ๋ฐ›๋Š” ๊ธฐ๋‘ฅ ๋ถ€์žฌ๋กœ ์ฃผ๋กœ ์‚ฌ์šฉ๋˜์–ด ์™”์œผ๋ฉฐ, ๋”ฐ๋ผ์„œ ํŽธ์‹ฌ์˜ ์œ ๋ฌด์— ๋”ฐ๋ฅธ ์••์ถ•์„ ๋ฐ›์„ ๋•Œ CFT ๊ธฐ๋‘ฅ ๋ถ€์žฌ์˜ ๊ฑฐ๋™์— ๊ด€ํ•œ ์—ฐ๊ตฌ๊ฐ€ ๋‹ค์ˆ˜ ์ˆ˜ํ–‰๋˜์—ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๊ตญ๋‚ด์™ธ์ ์œผ๋กœ CFT ๊ตฌ์กฐ๊ฐ€ ๊ธฐ๋‘ฅ ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ๋ณด๋กœ์„œ ์žฅ๊ฒฝ๊ฐ„์„ ์š”ํ•˜๋Š” ๊ฑด์ถ•๋ฌผ๊ณผ ๊ต๋Ÿ‰ ๋“ฑ์— ํ™œ์šฉ๋จ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ , ์ด์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋Š” ๋ถ€์กฑํ•œ ์‹ค์ •์ด๋‹ค. ์ง€๋‚œ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ, CFT๋ณด์˜ ๊ฑฐ๋™์ด ์†์ด ๋นˆ ๊ฐ•๊ด€์˜ ๊ฑฐ๋™๊ณผ ๋งค์šฐ ์œ ์‚ฌํ•˜๋‹ค๊ณ  ๋ณด๊ณ ๋˜์—ˆ๋˜ ์ดˆ๊ธฐ์˜ ์—ฐ๊ตฌ์™€๋Š” ๋‹ฌ๋ฆฌ(Furlong, 1967), ์ถฉ์ „๋œ ์ฝ˜ํฌ๋ฆฌํŠธ๊ฐ€ ์••์ถ• ์ €ํ•ญ์„ ํ•˜๋ฉฐ ์ค‘๋ฆฝ์ถ•์„ ์••์ถ•์ธก์œผ๋กœ ์ด๋™์‹œํ‚ด์œผ๋กœ์จ ๊ฑฐ๋™์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋ฉฐ, ์••์ถ•์„ ๋ฐ›๋Š” ๊ฐ•๊ด€์˜ ๊ตญ๋ถ€์ขŒ๊ตด์„ ๋ฐฉ์ง€ํ•œ๋‹ค๋Š” ๊ฒƒ ๋“ฑ ๋ณด๋‹ค ์ •ํ™•ํ•œ CFT๋ณด์˜ ํœจ๊ฑฐ๋™์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๊ฐ€ ์ตœ๊ทผ๊นŒ์ง€ ๋ณด๊ณ ๋˜๊ณ  ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ด๋“ค ์—ฐ๊ตฌ์˜ ๋Œ€๋ถ€๋ถ„์€ ์ถ•์†Œ ๋ชจํ˜•์œผ๋กœ ์ œ์ž‘๋œ CFT(๋กœ) ๋ถ„์„๋˜์—ˆ์œผ๋ฉฐ ์‹ค๋ฌผ๋Œ€ ํฌ๊ธฐ์˜ ์‹ค์ œ CFT ๋ณด์˜ ๊ฑฐ๋™์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋Š” ๊ทนํžˆ ๋ถ€์กฑํ•œ ์ƒํƒœ์ด๋‹ค. ๋˜ํ•œ, ์›ํ˜• CFT(CCFT)์˜ ๊ฒฝ์šฐ ๊ทธ ๋‹จ๋ฉด ํ˜•ํƒœ์˜ ํŠน์„ฑ์ƒ ์„ธ๋ฐ€ํ•œ ์—ฐ๊ตฌ๊ฐ€ ์ง„ํ–‰๋˜์–ด์•ผ ํ•จ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ์ด์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋Š” ๋”์šฑ ๋ถ€์กฑํ•œ ์‹ค์ •์ด๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์‹ค๋ฌผํฌ๊ธฐ CCFT ์‹คํ—˜ ๋ฐ์ดํ„ฐ๋ฅผ ๋ถ„์„ํ•˜์—ฌ ์ถ•๋ ฅ์„ ๋ฐ›์ง€ ์•Š๋Š” ์ƒํƒœ์—์„œ์˜ CCFT(์˜ ํœจ๊ฑฐ๋™์„ ์—ฐ๊ตฌํ•˜์˜€๋‹ค. ํŠนํžˆ CCFT(์˜ ํœจ๊ฐ•๋„์— ์žˆ์–ด์„œ ์—ฌ๋Ÿฌ ์ฝ”๋“œ๋ณ„๋กœ ์‚ฐ์ •์‹์ด ์กด์žฌํ•˜์ง€๋งŒ ๊ทธ ๋ฐฉ์‹์ด ๋™์ผํ•˜์ง€ ์•Š์„ ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ, ์ตœ๊ทผ ๋ณด๊ณ ๋œ ์‹ค๋ฌผ ํฌ๊ธฐ ์‹คํ—˜๊ฐ’๊ณผ ๋น„๊ตํ•˜์—ฌ ๋ณผ ๋•Œ๋„ ๋ณด์ˆ˜์ ์ด์ง€ ๋ชปํ•œ ์„ค๊ณ„๋กœ ์ด์–ด์ง€๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋˜ํ•œ, ์ถ”๊ฐ€์ ์œผ๋กœ ์‹ค์ œ ์ธก์ •๋œ CCFT๋ถ€์žฌ์˜ ํœจ๊ฐ•๋„๊ฐ’๊ณผ ์ฝ”๋“œ์— ๋”ฐ๋ผ ๊ณ„์‚ฐ๋œ ๊ฐ’์„ ๋น„๊ต ๋ถ„์„ํ•˜์˜€์„ ๋•Œ ๊ฐ•๊ด€์˜ ๋‘๊ป˜๊ฐ€ ๊ฐ์†Œํ•  ๋•Œ, ์ฆ‰ ๋ฐ•ํŒ์ผ ๋•Œ ์•ˆ์ „์œจ์ด ๊ฐ์†Œํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋‹จ๋ฉด์ด ์›ํ˜•์ธ ํŠน์„ฑ์ƒ CCFT(์˜ ํœจ๊ฐ•๋„๋ฅผ ์†์‰ฝ๊ฒŒ ๊ณ„์‚ฐํ•  ์ˆ˜ ์—†๊ธฐ ๋•Œ๋ฌธ์—, ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์„ค๊ณ„์ž๊ฐ€ CCFT๋ถ€์žฌ์˜ ๋ฌผ์„ฑ์น˜๋ฅผ ์ž…๋ ฅํ•˜์—ฌ CCFT(์˜ ํœจ๊ฐ•๋„๋ฅผ ์‚ฐ์ •ํ•  ์ˆ˜ ์žˆ๋Š” ํ”„๋กœ๊ทธ๋žจ์„ ๊ฐœ๋ฐœํ•˜์˜€๋‹ค. ์ด์— ๋”ํ•˜์—ฌ, ์ •๋ฐ€ํ•œ ๊ณ„์‚ฐ๊ณผ์ • ์—†์ด๋„ CCFT๋ถ€์žฌ์˜ ํœจ๊ฐ•๋„๋ฅผ ์‚ฐ์ •ํ•  ์ˆ˜ ์žˆ๋Š” ์„ค๊ณ„ ๊ทธ๋ž˜ํ”„๋ฅผ ์ œ์‹œํ•˜์—ฌ ๋ณด๋‹ค ์ •ํ™•ํ•˜๊ณ  ํŽธ๋ฆฌํ•œ ์„ค๊ณ„๊ฐ€ ๊ฐ€๋Šฅํ•˜๋„๋ก ์œ ๋„ํ•˜์˜€๋‹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 ์ดˆ ๋ก 79Maste

    ์•ˆ์œผ๋กœ ๋ง๋ฆฌ๋Š” ์• ๊ธฐ์žฅ๋Œ€ ์žŽ์˜ ์„ธํฌ๊ฐ„ ์‹ ํ˜ธ์ „๋‹ฌ๊ณผ ๊ด€๋ จ๋œ ์ƒˆ๋กœ์šด ์• ๊ธฐ์žฅ๋Œ€ ์œ ์ „์ž์— ๋Œ€ํ•œ ์—ฐ๊ตฌ

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    Thesis(master`s)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :ํ™”ํ•™๋ถ€ ์ƒํ™”ํ•™์ „๊ณต,2005.Maste

    ํŒจ์…˜๋””์ž์ด๋„ˆ์˜ ์ฐฝ์˜์„ฑ ๋ฐœํ˜„์š”์ธ ๋น„๊ต ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์˜๋ฅ˜ํ•™๊ณผ, 2013. 8. ๊น€๋ฏผ์ž.ํ˜์‹ , ์ƒˆ๋กœ์›€, ๋ณ€ํ™”๋ฅผ ์ค‘์š”ํ•œ ๊ฐ€์น˜๋กœ ์—ฌ๊ธฐ๋Š” ํŒจ์…˜์—์„œ ์ฐฝ์˜์„ฑ์€ ๊ฒฝ์Ÿ๋ ฅ์˜ ๊ทผ์›์ด๊ณ  ๊ฐ€์žฅ ์ค‘์š”ํ•œ ์—ด์‡ ์ด๋‹ค. 21์„ธ๊ธฐ ์ •๋ณด ํ†ต์‹ ์˜ ๋ฐœ๋‹ฌ์€ ์‹ ์†Œ์žฌ์™€ ์‹ ๊ธฐ์ˆ ์˜ ๊ณต์œ ๋ฅผ ๊ฐ€์ ธ์™€ ํŒจ์…˜ ์ œํ’ˆ ๊ฐ„์˜ ๊ธฐ์ˆ  ๊ฒฉ์ฐจ๊ฐ€ ํ˜„๊ฒฉํ•˜๊ฒŒ ์ค„์–ด๋“ค์—ˆ๋‹ค. ํ‘œ์ค€ํ™”๋œ ํŒจ์…˜ ์ƒํ’ˆ๋“ค์˜ ํ™์ˆ˜ ์†์—์„œ ํŒจ์…˜๋””์ž์ด๋„ˆ์˜ ์˜ˆ์ˆ ์˜์ง€์™€ ์ƒ์ƒ๋ ฅ์ด ๋”ํ•ด์ง„ ์ฐฝ์˜์„ฑ์ด ์ฐจ๋ณ„ํ™”์˜ ํ•ต์‹ฌ์š”์†Œ๋กœ ๋”์šฑ ๊ฐ•์กฐ๋˜๊ณ  ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ํŒจ์…˜์— ์ƒˆ๋กœ์›€์„ ๊ฐ€์ ธ์˜ค๋Š” ํŒจ์…˜๋””์ž์ด๋„ˆ๋“ค์˜ ์ฐฝ์˜์„ฑ ๋ฐœํ˜„์š”์ธ์„ ๋ฏธํ•˜์ด ์น™์„ผํŠธ๋ฏธํ•˜์ด(M. Csikszentmihalyi)์™€ ํ•˜์›Œ๋“œ ๊ฐ€๋“œ๋„ˆ(H. Gardener)์˜ ํ†ตํ•ฉ์ ์ธ ๊ด€์ ์„ ์ค‘์‹ฌ์œผ๋กœ ๊ณ ์ฐฐํ•˜๊ณ ์ž ํ•œ๋‹ค. ํŒจ์…˜๋””์ž์ด๋„ˆ์˜ ๊ฐœ์ธ์ ์ธ ํŠน์„ฑ๊ณผ ์žฌ๋Šฅ๊ณผ ํ•จ๊ป˜ ํŒจ์…˜ ์˜์—ญ ๋‚ด์—์„œ ์‚ฌํšŒยท๋ฌธํ™” ์ฒด๊ณ„์— ๋ฐ˜์‘ํ•˜๊ณ  ์˜ˆ์ˆ ์˜์ง€์™€ ์ฒ ํ•™์„ ํ‘œํ˜„ํ•˜๋Š” ๋ฐฉ์‹, ์ƒˆ๋กœ์šด ๋””์ž์ธ์˜ ๊ฐ€์น˜๊ฐ€ ํ‰๊ฐ€ํ•˜๋Š” ํ˜„์žฅ๊ณผ์˜ ๊ด€๊ณ„๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ํญ๋„“๊ฒŒ ๋ถ„์„ํ•˜๊ณ ์ž ํ•œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์˜ ๊ฒฐ๊ณผ๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ์ฒซ์งธ, ์ฐฝ์˜์„ฑ์˜ ์ผ๋ฐ˜์  ๊ณ ์ฐฐ์„ ๋ฐ”ํƒ•์œผ๋กœ ํŒจ์…˜๋””์ž์ด๋„ˆ ์ฐฝ์˜์„ฑ์„ ์ •์˜ํ•˜๊ณ  ๋ถ„์„์˜ ๋ชจํ˜•์„ ๊ฐœ๋ฐœํ•˜์˜€๋‹ค. ํŒจ์…˜๋””์ž์ด๋„ˆ์˜ ์ฐฝ์˜์„ฑ์„ ํŒจ์…˜ ์‹œ์Šคํ…œ์— ์†ํ•ด์žˆ๋Š” ํŒจ์…˜๋””์ž์ด๋„ˆ๊ฐ€ ํŒจ์…˜์ด๋ผ๋Š” ์ƒ์ง•์ฒด๊ณ„์— ๋Œ€ํ•œ ์ง€์‹์„ ๋ฐ”ํƒ•์œผ๋กœ ์ƒˆ๋กญ๊ณ  ์œ ์šฉํ•œ ์‚ฐ๋ฌผ์„ ๋งŒ๋“ค์–ด๋‚ด๋Š” ๋Šฅ๋ ฅ์œผ๋กœ, ๋™์‹œ๋Œ€์˜ ํ˜„์žฅ์—์„œ ์ƒˆ๋กœ์›€๊ณผ ์œ ์šฉ์„ฑ์„ ์ธ์ •์„ ๋ฐ›๊ณ  ํŒจ์…˜ ์˜์—ญ์— ํฌํ•จ๋  ๋•Œ ๋ฐœํœ˜๋˜๋Š” ๊ฒƒ์ด๋ผ๊ณ  ์ •์˜ํ•˜์˜€๋‹ค. ํŒจ์…˜๋””์ž์ด๋„ˆ์˜ ์ฐฝ์˜์„ฑ ๋ฐœํ˜„์š”์ธ์„ ๊ฐœ์ธ, ํŒจ์…˜ ์˜์—ญ, ํŒจ์…˜ ํ˜„์žฅ์œผ๋กœ ๋‚˜๋ˆ„์–ด ์„ธ๋ถ€์š”์ธ์„ ๋ฐํ˜”๋‹ค. ํŒจ์…˜๋””์ž์ด๋„ˆ์˜ ๊ฐœ์ธ์  ์š”์ธ์€ ์ธ์ง€์  ๋Šฅ๋ ฅ(๊ธฐ์ˆ , ๊ต์–‘, ์‚ฌํšŒ์„ฑ), ๋น„์ธ์ง€์  ๋Šฅ๋ ฅ(์„ฑ๊ฒฉ์  ํŠน์„ฑ, ๋งค๋ ฅ์ž๋ณธ), ์‚ฌํšŒยท์‹ฌ๋ฆฌํ•™์  ์š”์ธ(๊ฐ€์กฑ, ์„ฑ์  ์ •์ฒด์„ฑ, ๊ฒฐํ˜ผ, ๊ฑด๊ฐ•)์ด๋‹ค. ํŒจ์…˜ ์˜์—ญ์˜ ์ฐฝ์˜์„ฑ ๋ฐœํ˜„์š”์ธ์€ ํŒจ์…˜๋””์ž์ด๋„ˆ์˜ ์ฃผ์š” ์ฐฝ์ž‘ํ’ˆ๊ณผ ํŒจ์…˜์˜ ์‚ฌํšŒยท๋ฌธํ™”์  ๋งฅ๋ฝ์ธ ์‹œ๋Œ€์ •์‹ , ์‚ฌํšŒ๊ตฌ์กฐ, ๊ธฐ์ˆ ์  ์ธก๋ฉด๊ณผ์˜ ์ƒํ˜ธ ์ž‘์šฉ๊ณผ ๋””์ž์ด๋„ˆ์˜ ์ฐฝ์กฐ๋ฌผ์ด ์˜์—ญ์˜ ์ผ๋ถ€๋กœ ํŽธ์ž…๋˜๋Š” ํŒจ๋Ÿฌ๋‹ค์ž„์ด์—ˆ๋‹ค. ํŒจ์…˜ ํ˜„์žฅ์€ ํŒจ์…˜์‚ฐ์—…์—์„œ ์ผ์„ ํ•˜๊ฑฐ๋‚˜ ํŒจ์…˜ ์ฐฝ์กฐ์— ์˜ํ–ฅ์„ ์ฃผ๋Š” ๋ฌธ์ง€๊ธฐ๋“ค๋กœ ํŒจ์…˜ ์—๋””ํ„ฐ, ๋ฐ”์ด์–ด, ํŒจ์…˜ ๊ต์œก์ž, ํŒจ์…˜๋””์ž์ด๋„ˆ, ํˆฌ์ž์ž, ๋น„์ฆˆ๋‹ˆ์Šค ํŒŒํŠธ๋„ˆ, ํŒจ์…˜๋ชจ๋ธ, ๊ณ ์šฉ์ธ, ํŒจ์…˜ ํ๋ ˆ์ดํ„ฐ ๋“ฑ ํŒจ์…˜์—…๊ณ„ ์ข…์‚ฌ์ž๋“ค๊ณผ ํŒจ์…˜ ์„ ๋„์ž๋กœ ๊ตฌ์„ฑ๋˜์—ˆ๋‹ค. ๋‘˜์งธ, ์•ž์„œ ๊ฐœ๋ฐœํ•œ ํŒจ์…˜๋””์ž์ด๋„ˆ ์ฐฝ์˜์„ฑ ๋ถ„์„์˜ ๋ชจํ˜•์„ ์ด์šฉํ•˜์—ฌ ์˜คํŠธ์ฟ ํŠ€๋ฅดยทํ”„๋ ˆํƒ€ํฌ๋ฅดํ…Œยท๊ธ€๋กœ๋ฒŒ ํŒจ์…˜ ์‹œ๋Œ€์˜ ์ฐฝ์˜์  ํŒจ์…˜๋””์ž์ด๋„ˆ 9์ธ์˜ ์‚ฌ๋ก€์—ฐ๊ตฌ๋ฅผ ์ง„ํ–‰ํ•œ ๊ฒฐ๊ณผ๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ๊ฐ€๋ธŒ๋ฆฌ์—˜ ์ฝ”์ฝ” ์ƒค๋„ฌ(Gabrielle "Coco" Chanel)์€ ์‚ฌํšŒ์„ฑ, ๊ธฐ์ˆ ์˜ ์ธ์ง€์  ๋Šฅ๋ ฅ, ์•ผ๋ง์„ฑ, ๋…๋ฆฝ์„ฑ์˜ ์„ฑ๊ฒฉ์  ํŠน์„ฑ, ๋งค๋ ฅ ์ž๋ณธ์˜ ์†Œ์œ ์ž๋กœ ์—ฌ์„ฑ์˜ ์ข…์†์ ์ธ ์กด์žฌ๋กœ ๋จธ๋ฌผ๊ฒŒ ํ•˜๋Š” ๊ณผ์‹œ์ ์ธ ํŒจ์…˜์— ๋ฐ˜๋ฐœํ•ด, ๋‚จ์„ฑ๋ณต์˜ ์‹ค์šฉ์„ฑ์„ ๋„์ž…ํ•œ ๊ธฐ๋Šฅ์ฃผ์˜ ํŒจ์…˜์ด๋ผ๋Š” ์ƒˆ๋กœ์šด ํŒจ๋Ÿฌ๋‹ค์ž„์„ ์ œ์‹œํ–ˆ๋‹ค. ๋‹ค์ˆ˜์˜ ์• ์ธ, ์•„๋ฐฉ๊ฐ€๋ฅด๋“œ ์˜ˆ์ˆ ๊ฐ€ ์ง‘๋‹จ, ๋ฏธ๊ตญ์˜ ํŒจ์…˜ ์—๋””ํ„ฐ์™€ ๋ฐ”์ด์–ด๊ฐ€ ์ฐฝ์˜์„ฑ ๋ฐœํ˜„์„ ์ง€์ง€ํ•˜์˜€๋‹ค. ํฌ๋ฆฌ์Šคํ† ๋ฐœ ๋ฐœ๋ Œ์‹œ์•„๊ฐ€(Cristรณbal Balenciaga)๋Š” ๋›ฐ์–ด๋‚œ ์ž…์ฒดํ‘œํ˜„(3D) ์ง€๋Šฅ์— ์„ฑ์‹ค์„ฑ์ด๋ผ๋Š” ์„ฑ๊ฒฉ์  ํŠน์„ฑ์ด ํ•ฉํ•ด์ ธ ํ˜„๋Œ€ ํŒจ์…˜์˜ ๋Œ€๋ถ€๋ถ„์˜ ์‹ค๋ฃจ์—ฃ์„ ์ฐฝ์กฐํ•˜์˜€๋‹ค. ์ƒ์—…์ฃผ์˜๋ฅผ ๊ฑฐ๋ถ€ํ•˜๊ณ  ์ˆœ์ˆ˜ํ•œ ํ˜•ํƒœ๋ฏธ ๊ตฌํ˜„์— ๋ชฐ๋‘ํ•œ ๋ฐœ๋ Œ์‹œ์•„๊ฐ€์˜ ํ˜์‹ ์ ์ธ ์˜๋ณต๊ตฌ์„ฑ ํ˜•ํƒœ๋Š” ํŒจ์…˜ ์—๋””ํ„ฐ, ๋™๋ฃŒ ๋””์ž์ด๋„ˆ์˜ ์—ด๋ ฌํ•œ ์ง€์ง€๋ฅผ ๋ฐ›์•„ ์ƒˆ๋กœ์šด ํŒจ๋Ÿฌ๋‹ค์ž„์œผ๋กœ ์ž๋ฆฌ ์žก์•˜๋‹ค. ํฌ๋ฆฌ์Šค์ฐฌ ๋””์˜ค๋ฅด(Christian Dior)๋Š” ์‚ฌํšŒ์„ฑ, ๊ต์–‘, ๊ธฐ์ˆ  ๋“ฑ์˜ ๊ณ ๋ฅธ ์ธ์ง€์  ๋Šฅ๋ ฅ์˜ ์†Œ์œ ์ž๋กœ ๊ฐœ๋ฐฉ์„ฑ๊ณผ ๊ฐ์ˆ˜์„ฑ์˜ ์„ฑ๊ฒฉ์  ํŠน์„ฑ์„ ๊ฐ€์ง€๊ณ  ์žˆ์—ˆ๋‹ค. ์ „์Ÿ ํ›„ ํŒจ์…˜์˜ ์นจ์ฒด๊ธฐ์— ํ˜„์‹ค๋„ํ”ผ์ ์ธ ๋กœ๋งจํ‹ฐ์‹œ์ฆ˜ ์˜์ƒ์˜ ํŒจ๋Ÿฌ๋‹ค์ž„์„ ์ฐฝ์กฐํ•ด ์˜คํŠธ์ฟ ํŠ€๋ฅด ์ „ํ†ต์„ ๋ถ€ํ™œ์‹œ์ผฐ๋‹ค. ๋ผ์ด์„ ์Šค ์‚ฌ์—…, ๊ธฐ์„ฑ๋ณต ์‚ฌ์—… ๋“ฑ ์‚ฌ์—…์˜ ๋‹ค๊ฐํ™”๋ฅผ ํ†ตํ•ด ์ƒ์—…์ฃผ์˜๋ฅผ ์ถ”๊ตฌํ•˜์˜€๊ณ  ์˜ˆ์ˆ ๊ฐ€ ์ง‘๋‹จ, ํŒจ์…˜ ์–ธ๋ก ์˜ ์ ๊ทน์ ์ธ ์ง€์ง€๋ฅผ ๋ฐ›์•˜๋‹ค. ์ž… ์ƒ ๋กœ๋ž‘(Yves Saint Laurent)์€ ๊ธฐ์ˆ , ์‚ฌํšŒ์„ฑ, ๊ต์–‘์˜ ์ธ์ง€์  ๋Šฅ๋ ฅ, ๊ฐ์ˆ˜์„ฑ, ๊ฐœ๋ฐฉ์„ฑ์˜ ์„ฑ๊ฒฉ์  ํŠน์„ฑ, ๋†’์€ ๋งค๋ ฅ ์ž๋ณธ์˜ ์†Œ์œ ์ž๋ฅผ ์ง€๋…”๋‹ค. ์‹œ๋Œ€์˜ ํ๋ฆ„์— ๋”ฐ๋ผ ๋‚จ์„ฑ๋ณต, ์ŠคํŠธ๋ฆฌํŠธ ํŒจ์…˜, ์˜ˆ์ˆ  ์ž‘ํ’ˆ, ๊ฐ๊ตญ์˜ ์ „ํ†ต์˜์ƒ์—์„œ ์˜๊ฐ์„ ๋ฐ›์€ ํญ๋„“์€ ์ž‘ํ’ˆ ํ™œ๋™์œผ๋กœ ํ˜„๋Œ€ ํŒจ์…˜์˜ ๋ชจ๋“  ์Šคํƒ€์ผ์„ ์ฐฝ์กฐํ•˜์˜€๋‹ค. ํŒจ์…˜ ์–ธ๋ก , ๋น„์ฆˆ๋‹ˆ์Šค ํŒŒํŠธ๋„ˆ์˜ ์ง€์›์„ ๋ฐ›์•˜์œผ๋ฉฐ ์ˆ˜๋งŽ์€ ํ›„๋Œ€ ๋””์ž์ด๋„ˆ์˜ ์ถ”์ข…์„ ๋ฐ›์•˜๋‹ค. ์นผ ๋ผ๊ฑฐํŽ ํŠธ(Karl Lagerfeld)๋Š” ์‚ฌํšŒ์„ฑ, ๊ต์–‘, ๊ธฐ์ˆ ์˜ ๋†’์€ ์ธ์ง€์  ๋Šฅ๋ ฅ, ๊ฐœ๋ฐฉ์„ฑ์˜ ์„ฑ๊ฒฉ์  ํŠน์„ฑ, ๋›ฐ์–ด๋‚œ ์‚ฌํšŒ์  ํ‘œํ˜„๋ ฅ์ด๋ผ๋Š” ๋งค๋ ฅ ์ž๋ณธ์„ ๊ฐ€์กŒ๋‹ค. ํŒจ์…˜ ์‹œ์Šคํ…œ ๋ณ€ํ™”์— ๋”ฐ๋ผ, ํ”„๋ ˆํƒ€ํฌ๋ฅดํ…Œ ์—…๊ณ„์— ์ง„์ถœํ•˜๊ณ , ์ƒค๋„ฌ ์ฟ ํŠ€๋ฅด ํ•˜์šฐ์Šค๋ฅผ ์ด๋„๋Š” ๋“ฑ ๊ธฐ์กด ๋””์ž์ธํ•˜์šฐ์Šค์˜ ๊ณ ์œ ์„ฑ์— ์ƒˆ๋กœ์›€์„ ๊ฐ€๋ฏธํ•˜๋Š” ํŒจ์…˜ ์šฉ๋ณ‘์ด๋ผ๋Š” ์ƒˆ๋กœ์šด ํŒจ๋Ÿฌ๋‹ค์ž„์„ ๋‚ณ์•˜๋‹ค. ๊ฐ๊ฐ ์žˆ๋Š” ์ Š์€ ์˜ˆ์ˆ ๊ฐ€ ์ง‘๋‹จ์—๊ฒŒ ์˜๊ฐ์„ ์–ป์–ด ์‹œ๋Œ€์ •์‹ ์„ ํŒŒ์•…ํ•˜๋ฉฐ ํŒจ์…˜ ์„ ๋„๋ ฅ์„ ์œ ์ง€ํ•˜์˜€๋‹ค. ๋น„๋น„์•ˆ ์›จ์ŠคํŠธ์šฐ๋“œ(Vivienne Westwood)๋Š” ๊ธฐ์ˆ , ๊ต์–‘์˜ ์ธ์ง€์  ๋Šฅ๋ ฅ์„ ๊ฐ€์ง€๊ณ  ์žˆ์œผ๋ฉฐ ๋…๋ฆฝ์„ฑ์ด๋ผ๋Š” ์„ฑ๊ฒฉ์  ํŠน์„ฑ์„ ํ† ๋Œ€๋กœ ๊ธฐ์กด์˜ ํŠธ๋ Œ๋“œ์— ๋ฐ˜๋ฐœ, ํŽ‘ํฌ ํŒจ์…˜, ์—ญ์‚ฌ์ฃผ์˜ ์˜์ƒ์„ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•œ ํฌ์ŠคํŠธ๋ชจ๋”๋‹ˆ์ฆ˜ ํŒจ์…˜์ด๋ผ๋Š” ์ƒˆ๋กœ์šด ํŒจ๋Ÿฌ๋‹ค์ž„์„ ๋‚˜์•˜๋‹ค. ๋งค๋ ฅ ์ž๋ณธ์˜ ์†Œ์œ ์ž๋กœ ์ž์‹ ์˜ ์Šค์Šค๋กœ๊ฐ€ ๋””์ž์ธํ•˜์šฐ์Šค์˜ ๋ฎค์ฆˆ๊ฐ€ ๋˜์—ˆ๋‹ค. ๋ถ€ํ‹ฐํฌ ๋””์ž์ด๋„ˆ ์‹œ์ ˆ์—๋Š” ์ Š์€์ด ์ง‘๋‹จ์˜ ์ง€์ง€๋ฅผ ๋ฐ›์•˜๊ณ  ํ•˜์ดํŒจ์…˜ ๋””์ž์ด๋„ˆ๋กœ ์„ฑ์žฅํ•œ ํ›„์—๋Š” ํŒจ์…˜ ์—๋””ํ„ฐ, ํŒจ์…˜ ํ๋ ˆ์ดํ„ฐ ๋“ฑ์—๊ฒŒ ์ธ์ •์„ ๋ฐ›์•˜๋‹ค. ๋ฏธ์šฐ์น˜์•„ ํ”„๋ผ๋‹ค(Miuccia Prada)๋Š” ๊ต์–‘, ์‚ฌํšŒ์„ฑ์˜ ์ธ์ง€์  ๋Šฅ๋ ฅ์— ๊ฐœ๋ฐฉ์„ฑ์˜ ์„ฑ๊ฒฉ์  ํŠน์„ฑ์„ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค. ์ฐฉ์šฉํ•˜๊ธฐ ์ข‹์€ ์˜ท์„ ๋งŒ๋“œ๋Š” ๊ฒƒ์„ ์ค‘์š”ํ•˜๊ฒŒ ์—ฌ๊ฒจ 1990๋…„๋Œ€ ์ดํ›„ ๋ฏธ๋‹ˆ๋ฉ€๋ฆฌ์ฆ˜, ์ž‡๋ฐฑ ์—ดํ’, ์ง€์ ์ธ ์—˜๋ฆฌํŠธ์ธต์„ ์œ„ํ•œ ์–ด๊ธ€๋ฆฌ ์‹œํฌ(Ugly Chic)๋ผ๋Š” ์ƒˆ๋กœ์šด ํŒจ๋Ÿฌ๋‹ค์ž„์„ ์ œ์‹œํ•˜์˜€๋‹ค. ๋น„์ฆˆ๋‹ˆ์Šค ํŒŒํŠธ๋„ˆ์ธ ๋‚จํŽธ์œผ๋กœ๋ถ€ํ„ฐ ์ •์„œ์ , ์ธ์ง€์  ์ง€์›์„ ๋ฐ›๊ณ  ์žˆ์œผ๋ฉฐ ํŒจ์…˜ ์—๋””ํ„ฐ๋“ค์˜ ์ง€์ง€๋ฅผ ๋ฐ›์•˜๋‹ค. ์•Œ๋ ‰์‚ฐ๋” ๋งฅํ€ธ(Alexander McQueen)์€ ๊ธฐ์ˆ , ๊ต์–‘, ์‚ฌํšŒ์„ฑ์˜ ์ธ์ง€์  ๋Šฅ๋ ฅ๊ณผ ๊ฐ์ˆ˜์„ฑ, ๋…๋ฆฝ์„ฑ์˜ ์„ฑ๊ฒฉ์  ํŠน์„ฑ์„ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค. ์˜ˆ๋ฏผํ•œ ๊ฐ์„ฑ๊ณผ ๋›ฐ์–ด๋‚œ ๊ธฐ์ˆ ๋ ฅ์„ ๋ฐ”ํƒ•์œผ๋กœ ์ž์„œ์ „์ ์ธ ํ‘œํ˜„์ฃผ์˜ ํŒจ์…˜์„ ์„ ๋ณด์˜€์œผ๋ฉฐ ํŒจ์…˜์‡ผ์˜ ํ–‰์œ„์˜ˆ์ˆ ํ™”๋ฅผ ํ†ตํ•œ ๊ฐ์ • ์ „๋‹ฌ์ด๋ผ๋Š” ์ƒˆ๋กœ์šด ํŒจ๋Ÿฌ๋‹ค์ž„์„ ์ฐฝ์กฐํ•˜์˜€๋‹ค. ๊ทธ๋Š” ์˜๊ตญ์˜ ์ „์œ„์ ์ธ ํ˜„๋Œ€ ๋ฏธ์ˆ ๊ฐ€๋“ค์˜ ์˜ํ–ฅ์„ ๋ฐ›์•˜์œผ๋ฉฐ, ๊ทธ์˜ ์ฐฝ์ž‘ํ’ˆ๋“ค์€ ํŒจ์…˜ ์—๋””ํ„ฐ๋“ค์˜ ์ฃผ๋ชฉ์„ ๋ฐ›์•˜๋‹ค. ๋งˆํฌ ์ œ์ด์ฝฅ์Šค(Marc Jacobs)๋Š” ์‚ฌํšŒ์„ฑ, ๊ต์–‘์˜ ์ธ์ง€์  ๋Šฅ๋ ฅ, ๊ฐœ๋ฐฉ์„ฑ, ๊ฐ์ˆ˜์„ฑ์˜ ์„ฑ๊ฒฉ์  ํŠน์„ฑ์„ ๊ฐ–๊ณ  ์žˆ๋‹ค. ์•„๋ฆ„๋‹ค์šด ์™ธ๋ชจ, ํ™œ๋ ฅ, ์‚ฌํšŒ์  ๊ธฐ์ˆ  ๋“ฑ ๋งค๋ ฅ ์ž๋ณธ์˜ ์†Œ์œ ์ž๋กœ ๋Œ€์ค‘์˜ ํŒฌ์„ ๊ฑฐ๋Š๋ฆฌ๊ณ  ์žˆ๋‹ค. ๋Œ€์ค‘๋ฌธํ™”, ์ค‘๊ณ ์˜๋ฅ˜, ํŒ ๋ฎค์ง์—์„œ ์˜๊ฐ์„ ๋ฐ›์•„ ๊ทธ๋Ÿฐ์ง€ ๋ฃฉ์„ ์ฐฝ์‹œํ•˜์˜€์œผ๋ฉฐ, ๋Œ€๋‹ดํ•œ ์ฐจ์šฉ์„ ํ†ตํ•œ ์ „์œ„์ ์ด๋ฉด์„œ ์ž…๊ธฐ ์‰ฌ์šด ํŒจ์…˜, ํŒจ์…˜๋””์ž์ด๋„ˆ์˜ ์—”ํ„ฐํ…Œ์ด๋„ˆํ™” ๋“ฑ์˜ ํŒจ๋Ÿฌ๋‹ค์ž„์„ ์ฐฝ์กฐํ•˜์˜€๋‹ค. ํŒจ์…˜ ์—๋””ํ„ฐ, ํ˜„๋Œ€ ๋ฏธ์ˆ ๊ฐ€, ๊ธ€๋กœ๋ฒŒ ๊ทธ๋ฃน, ํŒจ์…˜๋ชจ๋ธ, ๋Œ€์ค‘, ๋“ฑ์˜ ์ง€์ง€๋ฅผ ๋ฐ›์•„ ์ƒ์—…์ ์ธ ์„ฑ๊ณต์„ ๊ฑฐ๋‘๊ณ  ์žˆ๋‹ค. ์…‹์งธ, ํ˜„๋Œ€ ํŒจ์…˜ ์‹œ๋Œ€์˜ ์ฐฝ์˜์  ํŒจ์…˜๋””์ž์ด๋„ˆ 9์ธ์˜ ์‚ฌ๋ก€์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด ๊ณ ์ฐฐํ•œ ์ฐฝ์˜์„ฑ ๋ฐœํ˜„์š”์ธ์„ ๊ฐœ์ธ, ์˜์—ญ, ํ˜„์žฅ ๋ณ„๋กœ ๋ถ„์„ํ•˜๋ฉด ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ๊ฐœ์ธ์  ์š”์ธ ์ค‘ ๋””์ž์ด๋„ˆ์˜ ์ธ์ง€์  ๋Šฅ๋ ฅ์€ ์‹œ๋Œ€์˜ ํ๋ฆ„์— ๋”ฐ๋ผ ๊ฐ•์กฐ๋˜๋Š” ๊ฒƒ์— ์ฐจ์ด๊ฐ€ ์žˆ์—ˆ๋‹ค. ์˜คํŠธ์ฟ ํŠ€๋ฅด ์‹œ๋Œ€๋Š” ๊ธฐ์ˆ ์ด, ํ”„๋ ˆํƒ€ํฌ๋ฅดํ…Œ ํŒจ์…˜ ์‹œ๋Œ€์—๋Š” ๊ธฐ์ˆ , ๊ต์–‘, ์‚ฌํšŒ์„ฑ์ด ๊ธ€๋กœ๋ฒŒ ํŒจ์…˜ ์‹œ๋Œ€๋Š” ์ค‘์š”ํ•œ ๊ฒƒ์€ ์˜ท ์ž์ฒด๊ฐ€ ์•„๋‹ˆ๋ผ ์•„์ด๋””์–ด๋กœ ์Šคํ† ๋ฆฌํ…”๋ง ํ•˜๋Š” ๊ต์–‘๊ณผ ์‚ฌํšŒ์„ฑ์ด ๊ฐ•์กฐ๋˜์—ˆ๋‹ค. ์ „ ์‹œ๋Œ€๋ฅผ ๊ด€ํ†ตํ•˜๋Š” ๋””์ž์ด๋„ˆ์˜ ์ค‘์š”ํ•œ ๊ฐœ์ธ์  ์š”์ธ์€ ๋งค๋ ฅ์ž๋ณธ์œผ๋กœ ๋””์ž์ด๋„ˆ๋“ค์€ ํƒ€๊ณ ๋‚œ ์™ธ๋ชจ, ์„ฑ์  ๋งค๋ ฅ, ํ™œ๋ ฅ, ๊ฐœ์„ฑ ์žˆ๋Š” ํŒจ์…˜ ์„ผ์Šค, ์‚ฌ๊ต์ˆ  ๋“ฑ์„ ์ด์šฉํ•˜์—ฌ ํŒจ์…˜ ํ˜„์žฅ์„ ๋งคํ˜น์‹œ์ผฐ๋‹ค. ์ด๋ฐ–์— ์‚ฌํšŒ์‹ฌ๋ฆฌํ•™์  ์ƒํ™ฉ ์ค‘ ํŠน์ด์‚ฌํ•ญ์€ ๋ชจ๋“  ๋‚จ์„ฑ ํŒจ์…˜๋””์ž์ด๋„ˆ๋“ค์ด ๋™์„ฑ์• ์ž์˜€๋‹ค๋Š” ์ ์ด ์žˆ๋‹ค. ํŒจ์…˜ ์˜์—ญ์˜ ์ฐฝ์˜์„ฑ ์š”์ธ์„ ์‚ดํŽด๋ณด๋ฉด, ํŒจ์…˜๋””์ž์ด๋„ˆ๋“ค์€ ์˜คํŠธ์ฟ ํŠ€๋ฅด ํ•˜์šฐ์Šค์˜ ์ˆ˜์Šต์ƒํ™œ, ์ „๋ฌธ ํŒจ์…˜ ๊ต์œก ๋“ฑ์„ ํ†ตํ•ด์„œ ํŒจ์…˜ ์˜์—ญ ์ง€์‹์„ ์ตํžˆ๊ณ , ํ˜„์กดํ•˜๋Š” ์ด๋ฐ์˜ฌ๋กœ๊ธฐ์— ๋ฐ˜๋ฐœํ•˜๊ฑฐ๋‚˜ ์ ๊ทน ๋™์กฐํ•˜๋ฉด์„œ ์ƒˆ๋กœ์šด ์‚ฐ์ถœ๋ฌผ์„ ์ œ์‹œํ•˜์˜€๋‹ค. 9์ธ์˜ ํŒจ์…˜๋””์ž์ด๋„ˆ์˜ ์ฐฝ์˜์ ์ธ ์‚ฐ์ถœ๋ฌผ์€ ํŒจ์…˜ ์—๋””ํ„ฐ, ๋ฐ”์ด์–ด, ํŒจ์…˜ ์„ ๋„์ž๋“ค์˜ ์ง€์ง€๋ฅผ ๋ฐ›์•„ ๋‹ค์‹œ ์˜์—ญ์œผ๋กœ ํŽธ์ž…๋˜์–ด ํŒจ์…˜ ์˜์—ญ์˜ ์ƒˆ๋กœ์šด ํŒจ๋Ÿฌ๋‹ค์ž„์ด ๋˜์—ˆ๋‹ค. ํŒจ๋Ÿฌ๋‹ค์ž„์€ ๊ฐ€๋ธŒ๋ฆฌ์—˜ ์ฝ”์ฝ” ์ƒค๋„ฌ(Gabrielle "Coco" Chanel)์˜ ๊ธฐ๋Šฅ์ฃผ์˜ ํŒจ์…˜๊ณผ ๊ฐ™์€ ํŒจ์…˜์‚ฌ์กฐ์™€ ์นผ ๋ผ๊ฑฐํŽ ํŠธ(Karl Lagerfeld)์˜ ์˜› ๋””์ž์ธํ•˜์šฐ์Šค ๋ถ€ํ™œ ๋“ฑ๊ณผ ๊ฐ™์€ ํŒจ์…˜ ๊ด€๋ก€๋ฅผ ํฌํ•จํ•œ๋‹ค. ํŒจ์…˜์€ ์ด์ต์„ ์ฐฝ์ถœํ•ด์•ผํ•˜๋Š” ์‚ฐ์—…์˜ ์‚ฐ๋ฌผ๋กœ, ๋””์ž์ด๋„ˆ์˜ ์ƒ์—…์ฃผ์˜์— ๊ฐ–๋Š” ๊ด€์ ์€ ์ฐฝ์˜์  ํ™œ๋™์— ์ค‘์š”ํ•œ ์˜ํ–ฅ์„ ๋ผ์นœ๋‹ค. ์ž… ์ƒ ๋กœ๋ž‘(Yves Saint Laurent), ์นผ ๋ผ๊ฑฐํŽ ํŠธ(Karl Lagerfeld), ๋ฏธ์šฐ์น˜์•„ ํ”„๋ผ๋‹ค(Miuccia Prada), ๋งˆํฌ ์ œ์ด์ฝฅ์Šค(Marc Jacobs)๋Š” ๊ณ ์œ  ์Šคํƒ€์ผ๋ณด๋‹ค๋Š” ์‹œ๋Œ€์˜ ๋ถ„์œ„๊ธฐ์— ์ฃผ๋ชฉํ•˜์—ฌ ๋Š์ž„์—†์ด ์ƒˆ๋กœ์šด ์Šคํƒ€์ผ์„ ์ œ์•ˆํ•˜๊ณ  ํŠธ๋ Œ๋“œ ์„ธํ„ฐ๋กœ ์ž๋ฆฌ๋งค๊น€ํ•˜์˜€๋‹ค. ํฌ๋ฆฌ์Šคํ† ๋ฐœ ๋ฐœ๋ Œ์‹œ์•„๊ฐ€(Cristรณbal Balenciaga), ๋น„๋น„์•ˆ ์›จ์ŠคํŠธ์šฐ๋“œ(Vivienne Westwood), ์•Œ๋ ‰์‚ฐ๋” ๋งฅํ€ธ(Alexander McQueen) ๋“ฑ์€ ๊ธฐ์ˆ ๋ ฅ์ด ๋›ฐ์–ด๋‚œ ๋””์ž์ด๋„ˆ๋“ค๋กœ ์ฐฝ์กฐ์˜ ์˜๊ฐ์„ ์ž์‹ ์˜ ๊ธฐ์ˆ ์—์„œ ์ฐพ๊ณ  ์ผ๊ด€์„ฑ ์žˆ๋Š” ์ž‘ํ’ˆ์„ธ๊ณ„๋ฅผ ๋ณด์—ฌ์ฃผ์—ˆ๋‹ค. ๋˜ํ•œ ๋ชจ๋“  ํŒจ์…˜๋””์ž์ด๋„ˆ๋“ค์€ ํŒจ์…˜ ์˜์—ญ์˜ ์ •๋ณด์™€ ๊ธฐ์ˆ ๋ ฅ์ด ๋ฐ€์ง‘๋˜์–ด ์žˆ๋Š” ์ฃผ์š” ํŒจ์…˜ ๋„์‹œ๋กœ ์ด๋™ํ•จ์ด ํ™•์ธ๋˜์—ˆ๋‹ค. ํŒจ์…˜ ํ˜„์žฅ์—์„œ ์ „ ์‹œ๋Œ€๋ฅผ ๊ฑธ์ณ ํŒจ์…˜๋””์ž์ด๋„ˆ์˜ ์„ฑ๊ณต์˜ ์ค‘์š”ํ•œ ์—ด์‡ ๊ฐ€ ๋œ ๋ฌธ์ง€๊ธฐ๋Š” ํŒจ์…˜ ์—๋””ํ„ฐ์˜€๋‹ค. ํŒจ์…˜๋””์ž์ด๋„ˆ๋“ค์€ ์‚ฌํšŒ์„ฑ๊ณผ ๋งค๋ ฅ์ž๋ณธ์„ ๋ฌด๊ธฐ๋กœ ์‚ผ์•„ ํŒจ์…˜ ์—๋””ํ„ฐ๋“ค๊ณผ ์ ๊ทน์ ์œผ๋กœ ์†Œํ†ตํ•˜์˜€๋‹ค. ๊ฐ€๋ธŒ๋ฆฌ์—˜ ์ฝ”์ฝ” ์ƒค๋„ฌ(Gabrielle "Coco" Chanel)๊ณผ ์นผ ๋ผ๊ฑฐํŽ ํŠธ(Karl Lagerfeld)๋Š” ๋…์„ค, ์•Œ๋ ‰์‚ฐ๋” ๋งฅํ€ธ(Alexander McQueen)์€ ์ „์œ„์ ์ธ ํŒจ์…˜์‡ผ, ์ž… ์ƒ ๋กœ๋ž‘(Yves Saint Laurent)๊ณผ ๋งˆํฌ ์ œ์ด์ฝฅ์Šค(Marc Jacobs)๋Š” ์‚ฌ์ƒํ™œ, ๋ฏธ์šฐ์น˜์•„ ํ”„๋ผ๋‹ค(Miuccia Prada)๋Š” ์˜ˆ์ˆ  ์žฌ๋‹จ ์šด์˜์œผ๋กœ ํ•ญ์ƒ ์–ธ๋ก ์˜ ๊ด€์‹ฌ์„ ๋ฐ›์œผ๋ฉด์„œ ๋””์ž์ธํ•˜์šฐ์Šค๋ฅผ ๋Œ€์ค‘์—๊ฒŒ ๊ฐ์ธ์‹œ์ผฐ๋‹ค. ์˜คํŠธ์ฟ ํŠ€๋ฅด ์‹œ๋Œ€์™€ ํ”„๋ ˆํƒ€ํฌ๋ฅดํ…Œ ์‹œ๋Œ€์˜ ๋””์ž์ด๋„ˆ๋“ค์€ ๊ฐœ์ธ ํˆฌ์ž์ž๋“ค์˜ ํˆฌ์ž๋ฅผ ๋ฐ›์•„ ๋””์ž์ธํ•˜์šฐ์Šค๋ฅผ ์—ด์—ˆ๋‹ค. ๊ธ€๋กœ๋ฒŒ ํŒจ์…˜์‹œ๋Œ€์—๋Š” ์ „ ์„ธ๊ณ„ ๋งˆ์ผ“ ์ƒ๋Œ€๋กœ ์‚ฌ์—…์„ ์ง„ํ–‰ํ•ด ๋ง‰๋Œ€ํ•œ ๋น„์šฉ์ด ํ•„์š”ํ•˜๊ธฐ ๋•Œ๋ฌธ์— ๊ฑฐ๋Œ€ ๋ณตํ•ฉ๊ธฐ์—…๋“ค์ด ์ค‘์š”ํ•œ ํˆฌ์ž์ž๊ฐ€ ๋˜์—ˆ๋‹ค. ์ด ๋ฐ–์— ํŒจ์…˜ ์ „์‹œ๊ฐ€ ์ƒˆ๋กœ์šด ๋ฌธํ™” ํ˜„์ƒ์œผ๋กœ ์ž๋ฆฌ ์žก์œผ๋ฉด์„œ ํ”„๋ ˆํƒ€ํฌ๋ฅดํ…Œ ์‹œ๋Œ€์™€ ๊ธ€๋กœ๋ฒŒ ํŒจ์…˜ ์‹œ๋Œ€์—๋Š” ํŒจ์…˜ ํ๋ ˆ์ดํ„ฐ๋ผ๋Š” ๋ฌธ์ง€๊ธฐ๊ฐ€ ์ถ”๊ฐ€๋˜์—ˆ๋‹ค. ๋ฏธํ•˜์ด ์น™์„ผํŠธ๋ฏธํ•˜์ด(M. Csikszentmihalyi)์™€ ํ•˜์›Œ๋“œ ๊ฐ€๋“œ๋„ˆ(H. Gardener)์˜ ์ด๋ก ์„ ๊ธฐ๋ฐ˜์œผ๋กœ ์ฐฝ์˜์ ์ธ ํ˜„๋Œ€ํŒจ์…˜๋””์ž์ด๋„ˆ 9์ธ์˜ ์‚ฌ๋ก€์—ฐ๊ตฌ๋ฅผ ์ง„ํ–‰ํ•œ ๊ฒฐ๊ณผ ํŒจ์…˜์„ ๋‘˜๋Ÿฌ์‹ผ ์‚ฌํšŒยท๋ฌธํ™” ๋งฅ๋ฝ ์†์—์„œ ํŒจ์…˜๋””์ž์ด๋„ˆ ๊ฐœ์ธ์€ ๋ฌธ์ œ์ ์„ ๋ฐœ๊ฒฌํ•˜๊ณ  ์ƒˆ๋กœ์šด ์‚ฐ์ถœ๋ฌผ์„ ์ œ์‹œํ•˜๊ณ , ์ˆ˜๋งŽ์€ ์‚ฐ์ถœ๋ฌผ๋“ค์ด ํŒจ์…˜ ํ˜„์žฅ์ด ํ‰๊ฐ€ํ•˜๋Š” ๊ณผ์ •์„ ํ†ตํ•ด ๋‹ค์‹œ ์˜๋ฏธ ์žˆ๋Š” ํŒจ์…˜ ๋ฌธํ™”๋กœ ์ฐฝ์ถœ๋จ์„ ํ™•์ธํ•˜์˜€๋‹ค. ํŒจ์…˜๋””์ž์ด๋„ˆ๋Š” ์ฐฝ์˜์„ฑ ๋ฐœํ˜„์„ ์œ„ํ•ด์„œ ์‚ฌํšŒ์„ฑ, ๊ต์–‘, ๊ธฐ์ˆ  ๋“ฑ ์ธ์ง€์  ๋Šฅ๋ ฅ์„ ํ‚ค์šฐ๊ณ , ํŒจ์…˜ ์˜์—ญ์˜ ์ •๋ณด๊ฐ€ ์‘์ง‘๋˜์–ด์žˆ๋Š” ๊ณณ์œผ๋กœ ์ด๋™ํ•˜์—ฌ ์ ๊ทน์ ์œผ๋กœ ํŒจ์…˜ ํ˜„์žฅ๊ณผ ์ƒํ˜ธ์ž‘์šฉ์„ ํ•ด์•ผ ํ•œ๋‹ค๋Š” ์ ์ด ํ™•์ธ๋˜์—ˆ๋‹ค.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 ์ œ 1 ์žฅ ์„œ๋ก  1 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ์˜ ๋ชฉ์ ๊ณผ ์˜์˜ 1 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ์˜ ๋ฐฉ๋ฒ•๊ณผ ๋ฒ”์œ„ 7 ์ œ 2 ์žฅ ์ฐฝ์˜์„ฑ์˜ ์ด๋ก ์  ๋ฐฐ๊ฒฝ 10 ์ œ 1 ์ ˆ ์ฐฝ์˜์„ฑ์— ๋Œ€ํ•œ ์ผ๋ฐ˜์  ๊ณ ์ฐฐ 10 1. ์ฐฝ์˜์„ฑ์˜ ๊ฐœ๋… 10 2. ์ฐฝ์˜์„ฑ ์—ฐ๊ตฌ์˜ ์‹œ๊ฐ 14 1) ์ธ์ง€์  ์ ‘๊ทผ 15 2) ๋น„์ธ์ง€์  ์ ‘๊ทผ 16 3) ๋‹ค์›์  ์ ‘๊ทผ 19 ์ œ 2 ์ ˆ ์น™์„ผํŠธ๋ฏธํ•˜์ด์™€ ๊ฐ€๋“œ๋„ˆ์˜ ์ฐฝ์˜์„ฑ์˜ ์‹œ์Šคํ…œ ๋ชจ๋ธ ๊ณ ์ฐฐ 23 1. ์น™์„ผํŠธ๋ฏธํ•˜์ด์˜ ์ฐฝ์˜์„ฑ์˜ ์‹œ์Šคํ…œ ๋ชจ๋ธ ๊ณ ์ฐฐ 23 1) ์น™์„ผํŠธ๋ฏธํ•˜์ด์˜ ์ฐฝ์˜์„ฑ์˜ ์‹œ์Šคํ…œ ๋ชจ๋ธ ์‚ฌ๋ก€ 24 2) ์น™์„ผํŠธ๋ฏธํ•˜์ด์˜ ์ฐฝ์˜์„ฑ์˜ ์‹œ์Šคํ…œ ๋ชจ๋ธ ๊ตฌ์„ฑ ์š”์ธ 26 2. ๊ฐ€๋“œ๋„ˆ์˜ ์‚ฌ๋ก€์—ฐ๊ตฌ ์ ‘๊ทผ๋ฒ• 34 1) ๊ตฌ์„ฑ์  ์ฃผ์ œ 36 2) ๊ตฌ์„ฑ์  ํ‹€ 37 3) ๊ฒฝํ—˜์  ์กฐ์‚ฌ ๋ฌธ์ œ 40 4) ์ƒˆ๋กœ ๋ฐœ๊ฒฌํ•œ ์ฃผ์ œ 44 ์ œ 3 ์ ˆ ํŒจ์…˜๋””์ž์ด๋„ˆ์˜ ์ฐฝ์˜์„ฑ ์ •์˜์™€ ๋ชจํ˜• ๊ฐœ๋ฐœ 46 1. ํŒจ์…˜๋””์ž์ด๋„ˆ์˜ ์ฐฝ์˜์„ฑ ์กฐ์ž‘์  ์ •์˜ 46 2. ํŒจ์…˜๋””์ž์ด๋„ˆ์˜ ์ฐฝ์˜์„ฑ ๋ถ„์„์˜ ๋ชจํ˜• ๊ฐœ๋ฐœ 50 1) ๊ฐœ์ธ(person) 50 2) ์˜์—ญ(domain) 64 3) ํ˜„์žฅ(field) 71 4) ์ข…ํ•ฉ์  ๋…ผ์˜ 75 ์ œ 3 ์žฅ ์˜คํŠธ์ฟ ํŠ€๋ฅดยทํ”„๋ ˆํƒ€ํฌ๋ฅดํ…Œยท๊ธ€๋กœ๋ฒŒ ํŒจ์…˜ ์‹œ๋Œ€์˜ ํŒจ์…˜๋””์ž์ด๋„ˆ ์‚ฌ๋ก€์—ฐ๊ตฌ 80 ์ œ 1 ์ ˆ ์˜คํŠธ์ฟ ํŠ€๋ฅด ์‹œ๋Œ€(1900๋…„๋Œ€~1950๋…„๋Œ€) 80 1. ์˜คํŠธ์ฟ ํŠ€๋ฅด ์‹œ๋Œ€์˜ ์ผ๋ฐ˜์  ๊ณ ์ฐฐ 80 2. ์˜คํŠธ์ฟ ํŠ€๋ฅด ์‹œ๋Œ€์˜ ํŒจ์…˜๋””์ž์ด๋„ˆ 88 1) ๊ฐ€๋ธŒ๋ฆฌ์—˜ ์ฝ”์ฝ” ์ƒค๋„ฌ 88 2) ํฌ๋ฆฌ์Šคํ† ๋ฐœ ๋ฐœ๋ Œ์‹œ์•„๊ฐ€ 105 3) ํฌ๋ฆฌ์Šค์ฐฌ ๋””์˜ค๋ฅด 122 ์ œ 2 ์ ˆ ํ”„๋ ˆํƒ€ํฌ๋ฅดํ…Œ ์‹œ๋Œ€(1960๋…„๋Œ€~1980๋…„๋Œ€) 142 1. ํ”„๋ ˆํƒ€ํฌ๋ฅดํ…Œ ์‹œ๋Œ€์˜ ์ผ๋ฐ˜์  ๊ณ ์ฐฐ 142 2. ํ”„๋ ˆํƒ€ํฌ๋ฅดํ…Œ ์‹œ๋Œ€์˜ ํŒจ์…˜๋””์ž์ด๋„ˆ 149 1) ์ž… ์ƒ ๋กœ๋ž‘ 149 2) ์นผ ๋ผ๊ฑฐํŽ ํŠธ 166 3) ๋น„๋น„์•ˆ ์›จ์ŠคํŠธ์šฐ๋“œ 184 ์ œ 3 ์ ˆ ๊ธ€๋กœ๋ฒŒ ํŒจ์…˜ ์‹œ๋Œ€(1990๋…„๋Œ€~ ํ˜„์žฌ) 202 1. ๊ธ€๋กœ๋ฒŒ ํŒจ์…˜ ์‹œ๋Œ€์˜ ์ผ๋ฐ˜์  ๊ณ ์ฐฐ 202 2. ๊ธ€๋กœ๋ฒŒ ํŒจ์…˜ ์‹œ๋Œ€์˜ ํŒจ์…˜๋””์ž์ด๋„ˆ 209 1) ๋ฏธ์šฐ์น˜์•„ ํ”„๋ผ๋‹ค 209 2) ์•Œ๋ ‰์‚ฐ๋” ๋งฅํ€ธ 226 3) ๋งˆํฌ ์ œ์ด์ฝฅ์Šค 246 ์ œ 4 ์žฅ ์˜คํŠธ์ฟ ํŠ€๋ฅดยทํ”„๋ ˆํƒ€ํฌ๋ฅดํ…Œยท๊ธ€๋กœ๋ฒŒ ํŒจ์…˜ ์‹œ๋Œ€์˜ ํŒจ์…˜๋””์ž์ด๋„ˆ ์ฐฝ์˜์„ฑ ๋ฐœํ˜„์š”์ธ ๋ถ„์„ 267 ์ œ 1 ์ ˆ ์˜คํŠธ์ฟ ํŠ€๋ฅดยทํ”„๋ ˆํƒ€ํฌ๋ฅดํ…Œยท๊ธ€๋กœ๋ฒŒ ํŒจ์…˜ ์‹œ๋Œ€์— ๋”ฐ๋ฅธ ํŒจ์…˜๋””์ž์ด๋„ˆ์˜ ์ฐฝ์˜์„ฑ ๋น„๊ต ๋ถ„์„ 267 1. ๊ฐœ์ธ์  ํŠน์„ฑ ์š”์ธ ๋น„๊ต ๋ถ„์„ 267 1) ์˜คํŠธ์ฟ ํŠ€๋ฅด ์‹œ๋Œ€ ๋””์ž์ด๋„ˆ 267 2) ํ”„๋ ˆํƒ€ํฌ๋ฅดํ…Œ ์‹œ๋Œ€ ๋””์ž์ด๋„ˆ 272 3) ๊ธ€๋กœ๋ฒŒ ํŒจ์…˜ ์‹œ๋Œ€ ๋””์ž์ด๋„ˆ 277 2. ์˜์—ญ ํŠน์„ฑ ์š”์ธ ๋น„๊ต ๋ถ„์„ 282 1) ์˜คํŠธ์ฟ ํŠ€๋ฅด ์‹œ๋Œ€ ๋””์ž์ด๋„ˆ 282 2) ํ”„๋ ˆํƒ€ํฌ๋ฅดํ…Œ ์‹œ๋Œ€ ๋””์ž์ด๋„ˆ 285 3) ๊ธ€๋กœ๋ฒŒ ํŒจ์…˜ ์‹œ๋Œ€ ๋””์ž์ด๋„ˆ 290 3. ํ˜„์žฅ ํŠน์„ฑ ์š”์ธ ๋น„๊ต ๋ถ„์„ 294 1) ์˜คํŠธ์ฟ ํŠ€๋ฅด ์‹œ๋Œ€ ๋””์ž์ด๋„ˆ 294 2) ํ”„๋ ˆํƒ€ํฌ๋ฅดํ…Œ ์‹œ๋Œ€ ๋””์ž์ด๋„ˆ 296 3) ๊ธ€๋กœ๋ฒŒ ํŒจ์…˜ ์‹œ๋Œ€ ๋””์ž์ด๋„ˆ 299 ์ œ 2 ์ ˆ ์ข…ํ•ฉ์  ๋…ผ์˜ 302 1. ํŒจ์…˜๋””์ž์ด๋„ˆ์˜ ์ฐฝ์˜์„ฑ ๋ฐœํ˜„์— ์˜ํ–ฅ์„ ์ค€ ๊ฐœ์ธ์  ํŠน์„ฑ์š”์ธ 302 2. ํŒจ์…˜๋””์ž์ด๋„ˆ์˜ ์ฐฝ์˜์„ฑ ๋ฐœํ˜„์— ์˜ํ–ฅ์„ ์ค€ ์˜์—ญ ์š”์ธ 312 3. ํŒจ์…˜๋””์ž์ด๋„ˆ์˜ ์ฐฝ์˜์„ฑ ๋ฐœํ˜„์— ์˜ํ–ฅ์„ ์ค€ ํ˜„์žฅ ์š”์ธ 316 ์ œ 5 ์žฅ ๊ฒฐ๋ก  ๋ฐ ์ œ์–ธ 320 ์ฐธ ๊ณ  ๋ฌธ ํ—Œ 325 ๊ทธ ๋ฆผ ์ถœ ์ „ 334 Abstract 338Docto

    ์œ ๋ฐฉ์•”๊ณผ ๋Œ€์‘์–‘์‹ ๋ฐ ์ •์„œ์  ์ ์‘๊ณผ์˜ ๊ด€๊ณ„

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์‹ฌ๋ฆฌํ•™๊ณผ ์ž„์ƒ์‹ฌ๋ฆฌํ•™์ „๊ณต,1997.Maste

    -๊ถ์ค‘ํšŒํ™”์˜ ์ •์น˜์  ์„ฑ๊ฒฉ๊ณผ ๊ด€๋ จํ•˜์—ฌ

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณ ๊ณ ๋ฏธ์ˆ ์‚ฌํ•™๊ณผ(๋ฏธ์ˆ ์‚ฌํ•™์ „๊ณต), 2012. 2. ์žฅ์ง„์„ฑ.๋Š” ์ฃผ์ž๊ฐ€ ๋ณต๊ฑด์„ฑ ์žฅ์ฃผ์—์„œ ๊ด€์ง ์ƒํ™œ์„ ํ•  ๋•Œ ๋งŒ๋“ค์—ˆ๋‹ค๋Š” ํ›„์›(ๅพŒๅœ’)์˜ ๋ชจ์Šต์„ ๊ทธ๋ฆฐ ๊ทธ๋ฆผ์ด๋‹ค. ์ด ๊ทธ๋ฆผ์€ 1746๋…„ ์˜์กฐ(่‹ฑ็ฅ–, ์žฌ์œ„ 1724-1776)์˜ ์ฃผ๋ฌธ์— ์˜ํ•ด ์ œ์ž‘๋˜์—ˆ๋‹ค. ๋ณธ๊ณ ๋Š” ์˜ ์–‘์‹์„ ์žฌ๊ฒ€ํ† ํ•˜๊ณ  ๊ทธ๋ฆผ์„ ์ฃผ๋ฌธํ•œ ์˜์กฐ์˜ ์ž…์žฅ์—์„œ ๊ทธ๋ฆผ์˜ ๋‚ด์šฉ๊ณผ ์„ฑ๊ฒฉ์„ ์ƒˆ๋กญ๊ฒŒ ๊ทœ๋ช…ํ•œ ์—ฐ๊ตฌ์ด๋‹ค. ๊ธฐ์กด ์—ฐ๊ตฌ์—์„œ๋Š” ๋ฅผ ์ •์„ (้„ญๆ•พ, 1676-1759)์˜ ์ž‘ํ’ˆ์œผ๋กœ ์ถ”์ •ํ•˜์˜€๋‹ค. ์ด์— ๋”ฐ๋ผ ๊ทธ๋ฆผ์— ๋Œ€ํ•œ ๋…ผ์˜ ์—ญ์‹œ ์ •์„ ์„ ์ค‘์‹ฌ์œผ๋กœ ์ด๋ฃจ์–ด์กŒ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ „์ฒด์ ์ธ ํ™”๋ฉด ๊ตฌ์„ฑ๋ ฅ๊ณผ ๊ฑด๋ฌผ ๋ฐ ๋‚˜๋ฌด ๋“ฑ์˜ ์„ธ๋ถ€ ํ‘œํ˜„, ๊ทธ๋ฆฌ๊ณ  ๊ด€๋ จ ๋ฌธํ—Œ๊ธฐ๋ก๋“ค์„ ๊ฒ€ํ† ํ•ด๋ณธ ๊ฒฐ๊ณผ ๋ฅผ ์ •์„ ์˜ ์ž‘ํ’ˆ์œผ๋กœ ๋ณด๊ธฐ๋Š” ์–ด๋ ต๋‹ค. ๋Œ€์‹  ์„ธ๋ถ€ ํ‘œํ˜„์—์„œ ๊ธฐ์กด ๊ถ์ค‘๊ธฐ๋กํ™”์˜ ์ „ํ†ต์„ฑ์„ ์—ฟ๋ณผ ์ˆ˜ ์žˆ์–ด ๋Š” ์ •์„ ์ด ์•„๋‹Œ 18์„ธ๊ธฐ์˜ ๋„ํ™”์„œ ํ™”์›์— ์˜ํ•ด ๊ทธ๋ ค์ง„ ๊ทธ๋ฆผ์œผ๋กœ ์ดํ•ดํ•˜๋Š” ๊ฒƒ์ด ์ ํ•ฉํ•˜๋‹ค. ๊ฐ€ ์ •์„ ์˜ ์ž‘ํ’ˆ์ด ์•„๋‹ˆ๋ผ๋Š” ์‚ฌ์‹ค์€ ํ˜„์žฌ๊นŒ์ง€ ์ •์„ ์˜ ๋งŒ๋…„์ž‘ ๋˜๋Š” ์ •์„ ์˜ ๊ณ ์‚ฌ์ธ๋ฌผ๋„๋ผ๋Š” ๋งฅ๋ฝ์—์„œ ์—ฐ๊ตฌ๋˜์—ˆ๋˜ ๋ฅผ ์ƒˆ๋กœ์šด ๊ฐ๋„์—์„œ ์žฌ๊ฒ€ํ† ํ•ด์•ผ ํ•  ํ•„์š”์„ฑ์„ ์ œ๊ธฐํ•œ๋‹ค. ํ•„์ž๋Š” ๋ฅผ ์ฃผ๋ฌธํ•œ ์˜์กฐ์— ์ฃผ๋ชฉํ•˜์˜€๋‹ค. ์˜์กฐ๋Š” ๊ทธ๋ฆผ์˜ ์ฃผ์ œ๋ฅผ ๋ฐœ์˜ํ•˜์˜€์„ ๋ฟ ์•„๋‹ˆ๋ผ ํ™”๋ฉด ๊ตฌ์„ฑ์„ ์ง์ ‘ ์ง€์‹œํ•˜๊ณ  ์ œ๋ฌธ์˜ ๋‚ด์šฉ๊นŒ์ง€ ๊ฒฐ์ •ํ•œ, ๊ทธ๋ฆผ์˜ ์ œ์ž‘๊ณผ์ •์„ ์ฃผ๋„ํ•œ ์ธ๋ฌผ์ด์—ˆ๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. ์˜์กฐ๊ฐ€ ๋ฅผ ์ฃผ๋ฌธํ•œ ์ผ์ฐจ์ ์ธ ์ด์œ ๋Š” ์ฃผ์ž์˜ ์žฅ์ฃผํ›„์›์„ ์™€์œ ํ•˜๊ธฐ ์œ„ํ•ด์„œ์˜€๋‹ค. ์˜์กฐ๋Š” ๊ทธ๋ฆผ์˜ ์ƒ๋‹จ ์–ด์ œ์‹œ์— ์–ด์ง„ ์ด(์ฃผ์ž)๊ฐ€ ๋…ธ๋‹๋˜ ๊ณณ์— ์•‰์€ ๋“ฏ์ด ํ•˜๊ฒ ๋‹ค๋ผ๊ณ  ์ ์–ด๋‘๊ณ  ใ€ˆ์žฅ์ฃผ๋ฌ˜์•”๋„ใ€‰๋ฅผ ๊ฐ์ƒํ•˜๋ฉฐ ์ •์„œ์ ์ธ ํœด์‹๊ณผ ์žฌ์ถฉ์ „์˜ ์‹œ๊ฐ„์„ ๊ฐ–๊ณ ์ž ํ•˜์˜€๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์˜์กฐ๋Š” ๋ฅผ ์œ ํฌ์  ์ฐจ์›์— ๊ตญํ•œ์‹œํ‚ค์ง€ ์•Š์•˜๋‹ค. ์˜์กฐ๋Š” ๊ทธ๋ฆผ ์ƒ๋‹จ์˜ ์–ด์ œ์‹œ์— ์ผ์ฐ์ด ใ€Ž์ž์„ฑํŽธใ€์— ๊ธฐ์ˆ˜๋ฌด์šฐ ๋งˆ์Œ์— ๋Œ€ํ•ด ์ ์€ ๋ฐ” ์žˆ๋Š”๋ฐ, ์ง€๊ธˆ ๋˜ ์ด ๊ทธ๋ฆผ์„ ๋ช…ํ•œ ๊ฒƒ์€ ๊ทธ๋•Œ์˜ ๋œป๊ณผ ํ•จ๊ป˜ํ•˜๋Š” ๊ฒƒ์ด๋‹ค๋ผ๊ณ  ์ ์–ด ๊ธฐ์ˆ˜๋ฌด์šฐ๋ฅผ ๊ทธ๋ฆผ์˜ ์ œ์ž‘์˜๋„๋กœ์จ ๋ฐํ˜”๋‹ค. ์˜์กฐ๊ฐ€ ํ™˜๊ธฐ์‹œํ‚จ ใ€Ž์ž์„ฑํŽธใ€์˜ ๊ธฐ์ˆ˜๋ฌด์šฐ ๊ตฌ์ ˆ์€ ์˜์กฐ ์ž์‹ ์˜ ๊ณ ๊ฒฐํ•œ ๋„๋•์„ฑ์„ ์„ค๋ช…ํ•œ ๋ฌธ์žฅ์œผ๋กœ์จ ํ›„์™•์ธ ์‚ฌ๋„์„ธ์ž์—๊ฒŒ ํ•œ ๋‚˜๋ผ์˜ ๊ตฐ์ฃผ๋กœ์„œ ๊ฐ€์ ธ์•ผ ํ•˜๋Š” ๋„๋•๊ด€๋… ์ฆ‰, ์ฒœ๋ฆฌ๋ฅผ ์ง€ํ‚ค๊ณ  ์ธ์š•์€ ๋ฒ„๋ ค์•ผ ํ•œ๋‹ค(ๅญ˜ๅคฉ็†ยท็ฅ›ไบบๆฌฒ)๋Š” ๊ฒƒ์„ ๊ฐ€๋ฅด์น˜๊ธฐ ์œ„ํ•ด ์ง€์€ ๊ฒƒ์ด๋‹ค. ์ด์™€ ๊ฐ™์ด ์˜์กฐ๋Š” ๋ฅผ ํ†ตํ•ด ์ž์‹ ์˜ ๋†’์€ ๋„๋•์„ฑ์„ ๋‚ด๋ณด์ด๊ณ , ๋™์‹œ์— ๊ตฐ์ฃผ๋กœ์„œ ๊ฐ€์ ธ์•ผ ํ•˜๋Š” ๋งˆ์Œ๊ฐ€์ง์„ ํ›„์™•๊ณผ ์‹ ๋ฃŒ๋“ค์—๊ฒŒ ์ „ํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ๊ธฐ์ˆ˜๋ฌด์šฐ ์ฆ‰, ๊ธฐ์ˆ˜์—์„œ ๋ชฉ์š•ํ•˜๊ณ  ๋ฌด์šฐ์—์„œ ๋ฐ”๋žŒ์„ ์ฌ๊ฒ ๋‹ค๋Š” ์ด ๊ตฌ์ ˆ์€ ใ€Ž๋…ผ์–ดใ€์—์„œ ๋ฐœ์ทŒ๋œ ๊ฒƒ์ด๋‹ค. ์˜์กฐ๋Š” ๊ธฐ์ˆ˜๋ฌด์šฐ๋ผ๋Š” ๊ตฌ์ ˆ์„ ์กฑ์ž์— ๋‹จ๋… ํ™”์ œ(็•ต้กŒ)๋กœ ์„ ํƒํ•  ์ •๋„๋กœ ์ƒ๋‹นํžˆ ์ค‘์š”ํ•˜๊ฒŒ ์ƒ๊ฐํ•˜์˜€๋‹ค. ์ด๋Š” ๊ธฐ์ˆ˜๋ฌด์šฐ๋ฅผ ์š”์ˆœ์˜ ์ •์น˜์™€ ์—ฐ๊ฒฐ์‹œํ‚ค๋Š” ๋ถ์†ก๋Œ€ ์„ฑ๋ฆฌํ•™์ž๋“ค์˜ ํ•ด์„ ๋•Œ๋ฌธ์ด์—ˆ๋‹ค. ์š”์ˆœ์€ ์˜์กฐ๊ฐ€ ๋ถ•๋‹น์ •์น˜๋ฅผ ๊ทน๋ณตํ•˜๊ณ  ํƒ•ํ‰์ •์น˜๋กœ ๋‚˜์•„๊ฐ€๊ธฐ ์œ„ํ•ด ๋‚ด์„ธ์šด ์ด์ƒ์ ์ธ ๊ตฐ์ฃผ์˜ ๋ชจ์Šต์ด์—ˆ๋‹ค. ์˜์กฐ๊ฐ€ ์ฃผ์ž์˜ ๊ณ ์‚ฌ๋ฅผ ๊ทธ๋ฆผ์œผ๋กœ ๊ทธ๋ฆฌ๊ณ  ๊ธฐ์ˆ˜๋ฌด์šฐ๋ฅผ ์–ด์ œ์—์„œ ๋ช…์‹œํ•œ ์ด์œ ๋Š” ๋ฅผ ํ†ตํ•ด ์ž์‹ ์ด ์š”์ˆœ์˜ ๋Œ€์—…์„ ์ด๋ฃฐ ์ˆ˜ ์žˆ๋Š” ์„ฑ์™•์ž„์„ ์•”์‹œํ•˜๊ธฐ ์œ„ํ•ด์„œ์˜€๋‹ค. ์˜์กฐ๊ฐ€ ๋ฅผ ํ†ตํ•ด ํ˜•์ƒํ™”ํ•˜๊ณ ์ž ํ•˜์˜€๋˜ ์ด์ƒ์ •์น˜์˜ ๋ชจ์Šต์€ ์žฅ์ฃผํ›„์›์˜ ํ‘œํ˜„ ์š”์†Œ๋“ค์„ ํ†ตํ•ด์„œ๋„ ํ™•์ธ๋œ๋‹ค. ๋จผ์ € ๊ทธ๋ฆผ ์ „์ฒด์˜ ไบ•์žํ˜• ๊ตฌ์กฐ๋Š” ์ด์ƒ์ ์ธ ์ •์น˜์งˆ์„œ๊ฐ€ ํ˜•์ƒํ™”๋œ ๋ชจ์Šต์ด๋‹ค. ๋˜ํ•œ ๋ฌ˜์•”์— ๊ทธ๋ ค์ง„ ํƒœ๊ด˜์™€ ๋ณต๊ด˜๋Š” ์กฐ์ •์˜ ์†Œํ†ต ๋ฐ ํ™”ํ•ฉ, ๋ฐฑ์„ฑ๋“ค์˜ ์†Œ์ƒ๊ณผ ๊ตฐ์ž์˜ ์ถœํ˜„์— ๋”ฐ๋ฅธ ๋‚˜๋ผ์˜ ์ค‘ํฅ์œผ๋กœ ํ•ด์„ํ•  ์ˆ˜ ์žˆ๋‹ค. ๊ฐ€ ์ „์ฒด ๊ตฌ์กฐ๋ฅผ ํ†ตํ•ด ์ด์ƒ์ ์ธ ๊ตญ๊ฐ€์˜ ๋ชจ์Šต์„ ๋ณด์—ฌ์ฃผ๊ณ  ์žˆ๋‹ค๋ฉด, ๋ฌ˜์•”์— ๊ทธ๋ ค์ง„ ํƒœ๊ด˜์™€ ๋ณต๊ด˜๋Š” ๊ทธ ์ด์ƒํ–ฅ์œผ๋กœ ๋‚˜์•„๊ฐ€๋Š” ๋ฐฉ๋ฒ•์„ ์ƒ์ง•์ ์œผ๋กœ ํ‘œํ˜„ํ•œ ๊ฒƒ์ด๋‹ค. ๊ฒฐ๊ตญ ๋Š” ์ด์ƒ๊ตญ๊ฐ€๋ฅผ ๊ฑด์„คํ•˜๊ณ ์ž ํ•˜๋Š” ์˜์กฐ์˜ ์ •์น˜์  ๋ชฉ์ ๊ณผ ํ›„์™•์ด ์ž์‹ ์˜ ์‚ฌ์—…์„ ๊ณ„์ˆ ํ•  ๊ฒƒ์ด๋ผ๋Š” ๊ธฐ๋Œ€๊ฐ€ ๋ฐ˜์˜๋œ ๊ทธ๋ฆผ์ด๋ผ๊ณ  ํ•  ์ˆ˜ ์žˆ๋‹ค.The Thatched Hut of Zhangzhou(ๆผณๅทž่Œ†ๅบตๅœ–), illustrating a story of Zhu Xi(ๆœฑ็†น, 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(ๆฒ‚ๆฐด่ˆž้›ฉ) in Zishengpian(Book of self-examination, ใ€Ž่‡ช็œ็ทจใ€), 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 ฏ่ˆœ), 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–‘ ์žฌํ•ดํ˜„์ƒ์— ๋Œ€ํ•œ ๊ณ ๋นˆ๋„ ๊ด‘ํ•™์œ„์„ฑ์ž๋ฃŒ ์‘์šฉ์— ๊ด€ํ•œ ์—ฐ๊ตฌ : ์œ ๋ฅ˜ ์œ ์ถœ ๋ฐ ์ ์กฐ๋ฅผ ์ค‘์‹ฌ์œผ๋กœ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณผํ•™๊ต์œก๊ณผ ์ง€๊ตฌ๊ณผํ•™์ „๊ณต, 2017. 2. ๋ฐ•๊ฒฝ์• .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

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์กฐ์†Œ๊ณผ ์กฐ์†Œ์ „๊ณต, 2011.8. ์ตœ์ธ์ˆ˜.Maste
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