104 research outputs found

    A cystic artery arising from the middle hepatic artery detected during laparoscopic cholecystectomy: a case report

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    We herein report a case in which a cystic artery arising from the middle hepatic artery (MHA) was encountered during cholecystectomy. A 42-year-old man visited the outpatient department complaining of chronic epigastric pain and a laparoscopic cholecystectomy was decided upon. During the preoperative evaluation, an interesting finding was observed on computed tomography. The patient had a cystic artery arising from the MHA. An MHA derived from the hilum of the proper hepatic artery runs along the medial border of the gallbladder and enters segment IV. In the operative field, the MHA that entered segment IV was observed. Dissecting downward along the MHA, a cystic artery was observed around the cystic duct. The cystic artery and duct were isolated and each was separately ligated and cut. Rare anatomical variations of the cystic artery, as in this case, can be a pitfall inducing complications during cholecystectomy.ope

    RC ๋ฒฝ์ฒด์˜ ์„ฑ๋Šฅ๊ธฐ๋ฐ˜ ๋‚ด์ง„์„ค๊ณ„ ๋ฐ ํ‰๊ฐ€๋ฅผ ์œ„ํ•œ ์ „๋‹จ ๊ฐ•๋„์™€ ๊ฐ•๋„์ €ํ•˜ ์˜ˆ์ธก๋ชจ๋ธ

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ๊ฑด์ถ•ํ•™๊ณผ, 2021.8. ๋ฐ•ํ™๊ทผ.In the performance based seismic design/evaluation, the behavior of structure by earthquakes is evaluated by the nonlinear analysis. In the slender walls of high-rise residential buildings, because the large shear force is applied by a dynamic mode effect, the high-strength reinforcement is required for economic design. Therefore, in this dissertation, experimental studies were conducted to provide the evidence of validity of RC walls with 700 MPa high-strength reinforcement. In the case of walls in the existing buildings, because the deformation capacity is limited by not applying the seismic design, it is necessary to evaluate the shear strength and inelastic deformation of the walls accurately. Therefore, the present dissertation investigated the major design parameters affecting the shear strength of wall, and developed the shear strength and strength degradation model based on the shear failure mechanism. The large demand force is applied by the gravity loads and earthquake loads at the walls in the high-rise residential buildings. Thus, the validity of 700 MPa reinforcement should be verified for the walls with high shear reinforcement ratio and high axial force. Even the demand force is small, the current design code requires the minimum reinforcement ratio for serviceability and safety. Thus, it is required to investigate the effects of the low reinforcement ratio on the strength and deformation capacity of the walls. For these purpose, the cyclic loading tests were conducted for the 700 MPa RC walls with various test parameters. The test results showed that the shear strength of walls with 700 MPa reinforcement was greater than the design strength, regardless of the test parameters. 700 MPa shear reinforcement was yielded at the peak shear strength. However, because of the greater yield strain and less reinforcement ratio, the walls with 700 MPa rebars showed the less strength margin, the greater crack width, the less energy dissipation and the less drift ductility ratio. Based on the test results, the effects of design parameters on the shear strength were investigated. The major design parameters were the yield strength of shear reinforcement, the vertical web reinforcement ratio, the axial load ratio, and the shape of the cross section. Since such parameters are closely related to the compression zone depth, the shear strength and shear strength degradation of walls are explained based on the effective compressive stress of concrete and effective area of concrete in compression. Based on the consideration, the present study developed the shear strength and strength degradation model. The major failure mechanisms of diagonal tension cracking and web crushing were addressed. The diagonal tension strength was defined by the compression zone depth and the normal stress of concrete in the compression zone. As the inelastic deformation increased, concrete crushing occurred in the compression zone. Thus, the effective compression zone gradually decreased, and diagonal tension strength degraded. The web crushing strength was defined by effective compressive stress of diagonal strut. By the compression softening effect, the effective concrete stress decreased as the crack width increased. Therefore, the web crushing strength degraded as the lateral deformation increased. Based on these shear failure mechanisms, simplified shear strength and strength degradation models were developed. Compared to existing design method, the proposed model agreed with the existing test results. To implement the proposed model into the practical design, design tables and guideline were suggested. The proposed model was applied in the Perform 3D, and the analysis results were compared with the test results. The Perform 3D analysis results showed that the strength degradation occurred after flexural yielding, and the deformation capacity was limited by the strength degradation.์„ฑ๋Šฅ๊ธฐ๋ฐ˜ ๋‚ด์ง„์„ค๊ณ„ ๋ฐ ํ‰๊ฐ€ ๊ธฐ๋ฒ•์—์„œ๋Š” ๋น„์„ ํ˜• ํ•ด์„์„ ํ†ตํ•ด ์ง€์ง„์— ์˜ํ•œ ๊ฑด์ถ•๋ฌผ์˜ ๊ฑฐ๋™์„ ํ‰๊ฐ€ํ•œ๋‹ค. ์„ฑ๋Šฅ์„ค๊ณ„ ์‹œ, ๊ณ ์ธต ๊ณต๋™์ฃผํƒ์˜ ์„ธ์žฅํ•œ ๋ฒฝ์ฒด๋Š” ๊ตฌ์กฐ์  ๋™์  ํŠน์„ฑ์œผ๋กœ ์ธํ•ด ์ง€์ง„ํ•˜์ค‘์— ์˜ํ•ด ํฐ ์ „๋‹จ๋ ฅ์ด ๋ฒฝ์ฒด์— ์ž‘์šฉํ•˜๋ฏ€๋กœ ๊ฒฝ์ œ์ ์ธ ์„ค๊ณ„๋ฅผ ์œ„ํ•ด ๊ณ ๊ฐ•๋„ ์ฒ ๊ทผ์˜ ์‚ฌ์šฉ์ด ์š”๊ตฌ๋œ๋‹ค. ์ด๋ฅผ ์œ„ํ•˜์—ฌ ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์‹คํ—˜์  ์—ฐ๊ตฌ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ 700 MPa ์ฒ ๊ทผ์„ ์‚ฌ์šฉํ•œ ๋ฒฝ์ฒด์˜ ์œ ํšจ์„ฑ์— ๋Œ€ํ•˜์—ฌ ์ž…์ฆ ์ž๋ฃŒ๋ฅผ ์ œ๊ณตํ•˜์˜€๋‹ค. ํ•œํŽธ, ๊ธฐ์กด ๊ฑด๋ฌผ์˜ ๋ฒฝ์ฒด๋Š” ๋‚ด์ง„์„ค๊ณ„๊ฐ€ ๋ฏธ๋น„ํ•˜์—ฌ ์—ฐ์„ฑ๋Šฅ๋ ฅ์ด ๋ถ€์กฑํ•˜๊ณ  ์ „๋‹จํŒŒ๊ดด์— ์ทจ์•ฝํ•˜๊ธฐ ๋•Œ๋ฌธ์—, ์„ฑ๋Šฅ ํ‰๊ฐ€ ์‹œ ๋ฒฝ์ฒด์˜ ์ „๋‹จ๊ฐ•๋„์™€ ๋ณ€ํ˜•๋Šฅ๋ ฅ์„ ์ •ํ™•ํžˆ ํ‰๊ฐ€ํ•˜๋Š” ๊ฒƒ์ด ์ค‘์š”ํ•˜๋‹ค. ๋”ฐ๋ผ์„œ, ๋ฒฝ์ฒด์˜ ์ „๋‹จ๊ฑฐ๋™์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์ฃผ์š” ์š”์ธ์„ ์กฐ์‚ฌํ•˜๊ณ , ๋ฒฝ์ฒด์˜ ์ „๋‹จ ๊ฑฐ๋™ ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ๊ธฐ๋ฐ˜์œผ๋กœ ์ „๋‹จ ๊ฐ•๋„์™€ ๋ณ€ํ˜•๋Šฅ๋ ฅ์„ ํ‰๊ฐ€ํ•˜๋Š” ์„ค๊ณ„๋ชจ๋ธ์„ ๊ฐœ๋ฐœํ•˜์˜€๋‹ค. ๊ณ ์ธต ๊ณต๋™์ฃผํƒ์˜ ๋ฒฝ์ฒด์—๋Š” ์ค‘๋ ฅํ•˜์ค‘๊ณผ ์ง€์ง„ํ•˜์ค‘์— ์˜ํ•˜์—ฌ ํฐ ์š”๊ตฌํ•˜์ค‘์ด ์ž‘์šฉํ•œ๋‹ค. ๋”ฐ๋ผ์„œ ๋†’์€ ์ถ•๋ ฅ๋น„๊ฐ€ ์ž‘์šฉํ•˜๊ณ  ์ฒ ๊ทผ๋น„๊ฐ€ ๋†’์€ ๋ฒฝ์ฒด์— ๋Œ€ํ•˜์—ฌ 700 MPa ์ฒ ๊ทผ์˜ ์œ ํšจ์„ฑ์ด ๊ฒ€์ฆ๋˜์–ด์•ผ ํ•œ๋‹ค. ํ•œํŽธ ์š”๊ตฌ๊ฐ•๋„๊ฐ€ ํฌ์ง€ ์•Š๋”๋ผ๋„ ํ˜„ํ–‰ ์„ค๊ณ„ ๊ธฐ์ค€์€ ๋ฒฝ์ฒด์˜ ์‚ฌ์šฉ์„ฑ ๋ฐ ์•ˆ์ „์„ฑ์„ ํ™•๋ณดํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ์ตœ์†Œ ์ฒ ๊ทผ๋น„๋ฅผ ๊ทœ์ •ํ•˜๊ณ  ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ๋‚ฎ์€ ์ฒ ๊ทผ๋น„๊ฐ€ ๋ฒฝ์ฒด์˜ ๊ฐ•๋„์™€ ๋ณ€ํ˜•๋Šฅ๋ ฅ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์ด ํ‰๊ฐ€๋˜์–ด์•ผ ํ•œ๋‹ค. ์ด๋ฅผ ์œ„ํ•˜์—ฌ 700 MPa ์ฒ ๊ทผ์„ ์‚ฌ์šฉํ•œ ๋ฒฝ์ฒด์— ๋Œ€ํ•˜์—ฌ ๋ฐ˜๋ณต ์ฃผ๊ธฐ ํšก ํ•˜์ค‘ ์‹คํ—˜์ด ์ˆ˜ํ–‰๋˜์—ˆ๋‹ค. ์‹คํ—˜ ๊ฒฐ๊ณผ, 700 MPa ์ฒ ๊ทผ์„ ์‚ฌ์šฉํ•œ ๋ฒฝ์ฒด๋Š” ํŒŒ๊ดด๋ชจ๋“œ ๋ฐ ์„ค๊ณ„๋ณ€์ˆ˜์™€ ๊ด€๊ณ„์—†์ด ์„ค๊ณ„ ๊ฐ•๋„ ์ด์ƒ์˜ ์ „๋‹จ ๊ฐ•๋„๋ฅผ ๋‚˜ํƒ€๋ƒˆ๋‹ค. 700 MPa ์ „๋‹จ์ฒ ๊ทผ์€ ์ตœ๋Œ€๊ฐ•๋„์—์„œ ํ•ญ๋ณตํ•˜์˜€๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ 700 MPa ์ฒ ๊ทผ์€ ํ•ญ๋ณต ๋ณ€ํ˜•๋ฅ ์ด ํฌ๊ณ  ์ฒ ๊ทผ๋น„๊ฐ€ ๊ฐ์†Œํ•˜๊ธฐ ๋•Œ๋ฌธ์— ์ผ๋ฐ˜๊ฐ•๋„ (400 MPa) ์ฒ ๊ทผ์„ ์‚ฌ์šฉํ•œ ๋ฒฝ์ฒด์™€ ๋น„๊ตํ•˜์—ฌ ๊ฐ•๋„ ์—ฌ์œ ์น˜๋Š” ๊ฐ์†Œํ•˜์˜€๊ณ , ๊ท ์—ดํญ ์ฆ๊ฐ€, ์—๋„ˆ์ง€ ์†Œ์‚ฐ๋Ÿ‰ ๊ฐ์†Œ, ์—ฐ์„ฑ๋Šฅ๋ ฅ ๊ฐ์†Œ๊ฐ€ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์‹คํ—˜ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ๋ฒฝ์ฒด ์ „๋‹จ ๊ฐ•๋„์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์„ค๊ณ„ ๋ณ€์ˆ˜๋ฅผ ๋ถ„์„ํ•˜์˜€๋‹ค. ์ฃผ์š”ํ•œ ์„ค๊ณ„๋ณ€์ˆ˜๋Š” ์ „๋‹จ์ฒ ๊ทผ ๊ฐ•๋„, ๋ณต๋ถ€ ์ˆ˜์ง์ฒ ๊ทผ๋น„, ์ถ•๋ ฅ๋น„, ๋‹จ๋ฉด ํ˜•์ƒ ๋“ฑ์ด์—ˆ๋‹ค. ์ด๋Ÿฌํ•œ ์„ค๊ณ„๋ณ€์ˆ˜๋“ค์€ ์••์ถ•๋Œ€ ๊นŠ์ด์™€ ๋ฐ€์ ‘ํ•œ ๊ด€๋ จ์ด ์žˆ์œผ๋ฏ€๋กœ ์ฝ˜ํฌ๋ฆฌํŠธ์˜ ์••์ถ• ์‘๋ ฅ์„ ๊ธฐ๋ฐ˜์œผ๋กœ ์ „๋‹จ๊ฐ•๋„์™€ ๊ฐ•๋„์ €ํ•˜๋ฅผ ์„ค๋ช…ํ•  ์ˆ˜ ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ๊ณ ์ฐฐ์„ ๋ฐ”ํƒ•์œผ๋กœ ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ „๋‹จ๊ฐ•๋„์™€ ๊ฐ•๋„์ €ํ•˜ ์˜ˆ์ธก๋ชจ๋ธ์„ ๊ฐœ๋ฐœํ•˜์˜€๋‹ค. ๋Œ€ํ‘œ์ ์ธ ์ „๋‹จํŒŒ๊ดด ๋ฉ”์ปค๋‹ˆ์ฆ˜์ธ ๋Œ€๊ฐ ์ธ์žฅ ๊ท ์—ด ํŒŒ๊ดด์™€ ๋ณต๋ถ€ ์••๊ดด ํŒŒ๊ดด๋ฅผ ๊ณ ๋ คํ•˜์˜€๋‹ค. ๋Œ€๊ฐ์ธ์žฅ ๊ท ์—ด ๊ฐ•๋„๋Š” ์ฝ˜ํฌ๋ฆฌํŠธ ์••์ถ•๋Œ€์˜ ๊นŠ์ด์™€ ์••์ถ•๋Œ€์— ์ž‘์šฉํ•˜๋Š” ํ‰๊ท  ์‘๋ ฅ์œผ๋กœ๋ถ€ํ„ฐ ์‚ฐ์ •ํ•˜์˜€๋‹ค. ๋น„ํƒ„์„ฑ ๋ณ€ํ˜•์ด ์ฆ๊ฐ€ํ•˜๋ฉด ์ฝ˜ํฌ๋ฆฌํŠธ ์••๊ดด๊ฐ€ ์••์ถ•๋Œ€์—์„œ ๋ฐœ์ƒํ•œ๋‹ค. ์œ ํšจ ์••์ถ•๋Œ€ ๊นŠ์ด๊ฐ€ ๊ฐ์†Œํ•จ์— ๋”ฐ๋ผ ๋Œ€๊ฐ ์ธ์žฅ ๊ท ์—ด ๊ฐ•๋„๋Š” ์ €ํ•˜๋œ๋‹ค. ๋ณต๋ถ€ ์••๊ดด ๊ฐ•๋„๋Š” ๋Œ€๊ฐ ์••์ถ• ์ŠคํŠธ๋Ÿฟ์˜ ์œ ํšจ ์‘๋ ฅ์„ ์‚ฌ์šฉํ•˜์—ฌ ์ •์˜ํ•˜์˜€๋‹ค. ์ฝ˜ํฌ๋ฆฌํŠธ์˜ ์••์ถ•๊ฐ•๋„ ์—ฐํ™” ์ž‘์šฉ์— ์˜ํ•˜์—ฌ ์œ ํšจ ์ฝ˜ํฌ๋ฆฌํŠธ ์‘๋ ฅ์€ ๊ท ์—ดํญ์ด ์ฆ๊ฐ€ํ•จ์— ๋”ฐ๋ผ ๊ฐ์†Œํ•œ๋‹ค. ๋”ฐ๋ผ์„œ ํšก ๋ณ€ํ˜•์ด ์ฆ๊ฐ€ํ• ์ˆ˜๋ก ๋ณต๋ถ€ ์••๊ดด ๊ฐ•๋„๋Š” ์ €ํ•˜๋œ๋‹ค. ์ด๋Ÿฌํ•œ ์ „๋‹จ๊ฑฐ๋™ ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ๋ฐ”ํƒ•์œผ๋กœ ๋‹จ์ˆœ ๋ชจ๋ธ์„ ๊ฐœ๋ฐœํ•˜์˜€๋‹ค. ๊ธฐ์กด ์„ค๊ณ„ ๊ธฐ์ค€๊ณผ ๋น„๊ตํ•˜์—ฌ ์ œ์•ˆ ๋ชจ๋ธ์€ ์‹คํ—˜ ๊ฒฐ๊ณผ๋ฅผ ๋น„๊ต์  ์ž˜ ์˜ˆ์ธกํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ์˜ ์ œ์•ˆ ๋ชจ๋ธ์„ ์‹ค๋ฌด์„ค๊ณ„์— ์ ์šฉํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ์„ค๊ณ„ ํ…Œ์ด๋ธ”๊ณผ ๊ฐ€์ด๋“œ๋ผ์ธ์ด ์ œ์‹œ๋˜์—ˆ๋‹ค. Perform 3D ํ•ด์„ ํ”„๋กœ๊ทธ๋žจ์„ ๊ธฐ๋ฐ˜์œผ๋กœ ์ œ์•ˆ ๋ชจ๋ธ์„ ์ ์šฉํ•˜๊ณ  ์‹คํ—˜๊ฒฐ๊ณผ์™€ ๋น„๊ตํ•˜์˜€๋‹ค. Perform 3D๋ฅผ ์‚ฌ์šฉํ•œ ํ•ด์„ ๊ฒฐ๊ณผ๋Š” ํ•ญ๋ณต ์ดํ›„ ๊ฐ•๋„ ์ €ํ•˜๋ฅผ ๋ชจ์‚ฌํ•  ์ˆ˜ ์žˆ์—ˆ์œผ๋ฉฐ, ๋ฒฝ์ฒด์˜ ๋ณ€ํ˜•๋Šฅ๋ ฅ์ด ๊ฐ•๋„์ €ํ•˜์— ์˜ํ•˜์—ฌ ์ œํ•œ๋˜์—ˆ๋‹ค.Chapter 1. Introduction 1 1.1 General 1 1.2 Scope and objectives 9 1.3 Outline of dissertation 11 Chapter 2. Literature Review 14 2.1 Current design codes 14 2.1.1 ACI 318-19 (ACI Committee 318, 2019) 14 2.1.2 Eurocode 2 and 8 (British Standards Institution, 2004) 16 2.1.3 KDS 14 20 22 (Korean Concrete Institute, 2020) 18 2.1.4 ASCE/SEI 41-17 (American Society of Civil Engineers, 2017) 21 2.1.5 Design guideline for performance based design of RC structure (Architectural Institute of Korea, 2020) 23 2.2 Existing model for shear strength and deformation capacity of RC shear walls 25 2.2.1 Cardenas et al. (1973) 25 2.2.2 Barda et al. (1977) 27 2.2.3 Duffey et al. (1994) 28 2.2.4 Hidalgo and Jordan (1996) 29 2.2.5 Carrillo and Alcocer (2012) 31 2.2.6 Sanchez (2013) 34 2.2.7 Carlos (2016) 37 2.2.8 Epackachi et al. (2019) 39 2.2.9 Gulec and Whittaker (2011) 40 2.2.10 Zeynep and Cagri (2021) 41 2.3 Shear wall failure mechanism models 42 2.3.1 Compression zone failure mechanism model (Choi et al., 2007) 44 2.3.2 Truss mechanism model (Eom and Park, 2010) 51 Chapter 3. Shear Strength of RC Walls with Various Design Parameters 59 3.1 Overview 59 3.2 Backgrounds 60 3.3 Test program 64 3.3.1 Test parameters and specimens details 64 3.3.2 Test setup and instrumentation 78 3.4 Test results 80 3.4.1 Failure modes 80 3.4.2 Lateral load- displacement relationships 90 3.4.3 Strains of reinforcing bars 98 3.4.4 Contributions of displacement components 105 3.4.5 Average crack width 109 3.4.6 Energy dissipation and drift ductility ratio 112 3.5 Shear strength predictions of existing methods 116 3.5.1 Predictions of existing methods 116 3.5.2 Strength and deformation predictions by compression zone failure mechanism model 118 3.6 Summary 122 Chapter 4. Effects of Design Parameters on Wall Shear Strength and Deformation 124 4.1 Overview 124 4.2 Shear reinforcement 125 4.3 Wall aspect ratio and axial load ratio 130 4.4 Vertical web reinforcement ratio 136 4.5 Shape of wall section 140 4.6 Summary 144 Chapter 5. Simplified Wall Shear Strength Model 146 5.1 Overview 146 5.2 Background 147 5.3 Shear strength of walls controlled by diagonal tension failure 149 5.3.1 Diagonal tension cracking mechanism model 149 5.3.2 Simplified diagonal tension strength 152 5.4 Shear strength of walls controlled by web crushing failure 163 5.5 Verification of proposed shear strength model 168 5.6 Summary 176 Chapter 6. Simplified Wall Shear Strength Degradation Model 177 6.1 Overview 177 6.2 Background 178 6.3 Shear strength degradation controlled by tension failure 183 6.3.1 Compression zone failure mechanism model 183 6.3.2 Deformation model 190 6.3.3 Simplified strength degradation model controlled by diagonal tension failure 199 6.4 Shear strength degradation controlled by web crushing failure 205 6.4.1 Truss mechanism model 205 6.4.2 Simplified strength degradation model controlled by web crushing failure 207 6.5 Verification of proposed shear strength degradation model 210 6.6 Summary 224 Chapter 7. Application of Proposed Models 225 7.1 Overview 225 7.2 Review on Perform 3D wall element 226 7.3 Envelope curve model for the plastic hinge region 227 7.3.1 Envelope curve model 227 7.3.2 Design table 235 7.4 Perform 3D modeling procedure 238 7.4.1 Overview 238 7.4.2 Example walls 239 7.4.3 Geometries of model 241 7.4.4 Materials 243 7.4.5 Cyclic properties 251 7.4.6 Loading conditions 253 7.4.7 Boundary conditions 254 7.4.8 Analysis results 255 7.5 Limitations 258 7.6 Summary 260 Chapter 8. Conclusions 261 References 265 Appendix: Verification of Simplified Strength Degrdation Models 273 ์ดˆ ๋ก 298๋ฐ•

    Mixed neuroendocrine-non-neuroendocrine carcinoma (MiNEN) in gallbladder with liver metastasis of neuroendocrine carcinoma component: a case report

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    Mixed neuroendocrine-non-neuroendocrine neoplasms of the gallbladder are rare with a lack of established standardized therapeutic strategies. We report a case of gallbladder mixed neuroendocrine-non-neuroendocrine neoplasm with liver metastasis of neuroendocrine carcinoma. A patient who underwent radical cholecystectomy for gallbladder adenocarcinoma was detected with increasing liver mass, and hepatectomy was performed. Pathological report revealed neuroendocrine carcinoma. To find primary origin, pathological review of the old specimen from previous cholecystectomy with a slightly different perspective was conducted, where the neuroendocrine component was positively dyed. In conclusion, though it might be impossible to review every pathological result in cases with ambiguous findings, reviewing the previous specimen can be a useful option in diagnosis. Published by Oxford University Press and JSCR Publishing Ltd. ยฉ The Author(s) 2023.ope

    Inguinal hernia repair with or without mesh in late adolescent males

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    Purpose: Inguinal hernia repair is one of the most common treatments worldwide, but there are few studies about the use of mesh in late adolescent patients because hernias are rare in this group. This study aimed to evaluate the postoperative outcomes of hernia repair with and without mesh in late adolescent patients. Methods: We retrospectively reviewed the data of 243 male patients aged between 18 and 21 years who underwent inguinal hernia repair at a single institution from January 2013 to December 2017. We distinguished 2 groups depending on the repair method; mesh (n = 121) and no-mesh (n = 122) groups. We compared the baseline characteristics, immediate postoperative outcomes, and recurrence and chronic pain rates between the 2 groups. Results: There were no significant differences between the mesh and no-mesh groups on immediate postoperative outcomes (length of stay: 18.5 ยฑ 8.9 days vs. 17.0 ยฑ 6.0 days, P = 0.139; postoperative complications: 8.2% vs. 6.6%, P = 0.821) and 2-year recurrence rate (0.8% vs. 2.6%, P = 0.194). There was a significant difference in the chronic pain rate (9.0% vs. 1.7%, P = 0.023). Conclusion: Using mesh for inguinal hernia repair in late adolescent male patients increases chronic postoperative inguinal pain.ope

    ๊ณ ์ธต์ฃผ๊ฑฐ์šฉ๊ฑด๋ฌผ์˜ ์„ฑ๋Šฅ์„ค๊ณ„ ๊ณผ์ •์—์„œ ์„ธ์žฅํ•œ ๋ฒฝ์ฒด์™€ ํ•„๋กœํ‹ฐ๊ฐ€ ์žˆ๋Š” ๋ฒฝ์ฒด์˜ ์„ค๊ณ„

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ฑด์ถ•ํ•™๊ณผ, 2017. 2. ๋ฐ•ํ™๊ทผ.As the risk of earthquake in Korea increases, interest in seismic design increases and application of related design standard is strengthened. It is difficult to predict seismic load accurately by seismic design method based on conventional elastic analysis. Therefore, capacity design method can be used for seismic design of high-rise residential building to evaluate seismic load more accurately and obtain optimal design result. However, in order to apply the capacity design method in design of Korean high-rise residential buildings, some precautions due to characteristics of structural system should be considered. Therefore, in this study, among the considerations for capacity design of high-rise residential building, the shear demand distribution for the slender shear wall system and the design of transfer zone in the pilotis-wall system were studied. First, the problem that occurred in the capacity design of slender shear wall system was that shear demand of actual case is considerably amplified compared to that of design case. If the amplified shear demand is not considered in design, structural members can be under-designed, resulting structural unsafety of the building. Therefore, amplification effect of shear demand was investigated and some design factors reflecting it in the capacity design process were proposed. By using Perform 3D, a nonlinear analysis program, nonlinear analysis modeling for each parameter were established and nonlinear dynamic analysis was carried out. Based on the analysis results, the factors affecting the shear demand amplification effect were analyzed and the base shear amplification factor for predicting the nonlinear shear demand was proposed. The proposed base shear amplification factor was determined by base over-strength factor and it can predict the nonlinear shear demand within the error range of 20%. Also, the story shear distribution model for nonlinear shear demand was suggested on the basis of average shear distribution of analysis results. The proposed story shear distribution model can predict the story shear demand more economically than conventional model which is suggested in Eurocode 8. The proposed base shear amplification factor and story shear distribution model can predict nonlinear shear demand of the wall more reasonably and secure the structural safety by preventing under-design. Next, the design consideration of the capacity design of the pilotis-wall system was an economical design method for the transfer zone in which the pilotis and wall are connected. A system in which the transfer girder was eliminated was proposed and a reasonable capacity design method for this system is proposed. To evaluate the structural performance of proposed system and verify the design method, cyclic loading tests and compression test were carried out. Based on principle of capacity design, the proposed pilotis-wall system without transfer girder was designed to prevent premature brittle failure in the transfer zone and pilotis and to induce ductile failure in the upper wall. Test results show that, in all the specimens, the premature brittle failure of the transfer zone and pilotis did not occurred, but in the upper wall, re-bars were yielded in the tensile side and concrete crushing occurred in the compressive side. The internal and external damage of the transfer zone and the pilotis were relatively limited. Through these results, it was confirmed that the preliminary design of the pilotis-wall system can be improved more economically without applying the special earthquake load and the presence of transfer girder.Chapter 1. Introduction 1 1.1 General 1 1.2 Scope and Objectives 7 1.3 Outline of the masters thesis 8 Chapter 2. Literature Review 9 2.1 Capacity design 9 2.2 Shear amplification and the story shear distribution 11 2.2.1 Blakeley et al 11 2.2.2 Eibl and keintzel et al 13 2.2.3 Rutenberg and Nsieri 13 2.3 Pilotis-wall system 16 2.3.1 Jung, Yoon, Hong and Kim 16 2.3.2 Jang, Kim and Hong 20 Chapter 3. Capacity Design of Slender Shear Wall 25 3.1 Introduction 25 3.2 Analysis model 26 3.2.1 Modeling concept 26 3.2.2 Modeling procedure 30 3.3 Analysis parameters 41 3.3.1 Parameter 1 : Axial force ratio 41 3.3.2 Parameter 2 : Response modification factor (R factor) 42 3.3.3 Parameter 3 : The number of stories designed identically 45 3.3.4 Parameter 4 : Characteristics of selected ground motions 46 3.3.5 Parameter 5 : Detail of connection beam 47 3.4 Analysis results 50 3.4.1 Parameter 1 : Axial force ratio 50 3.4.2 Parameter 2 : Response modification factor (R factor) 52 3.4.3 Parameter 3 : The number of stories designed identically 53 3.4.4 Parameter 4 : Characteristics of selected ground motions 56 3.4.5 Parameter 5 : Detail of connection beam 58 3.5 Design of slender shear wall 59 3.5.1 Base shear amplification factor 59 3.5.2 Story shear distribution model 64 Chapter 4. Capacity Design of Pilotis-Wall System without Transfer Girder 67 4.1 Introduction 67 4.2 Test program 69 4.2.1 Design concept 69 4.2.2 Design procedure 70 4.2.3 Test parameters 73 4.2.4 Test specimens 73 4.2.5 Test setups 82 4.3 Test results 88 4.3.1 Cyclic loading tests 88 4.3.2 Compression Test 102 Chapter 5. Conclusion 108 References 112 ์ดˆ ๋ก 114Maste

    The improving accuracy of classifying an image \\ using interpretable machine learning (IML)

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณตํ•™์ „๋ฌธ๋Œ€ํ•™์› ์‘์šฉ๊ณตํ•™๊ณผ, 2021. 2. ์œค์„ฑ๋กœ.์ธ๊ณต ์ง€๋Šฅ์€ ๋ฐ์ดํ„ฐ์— ํŽธํ–ฅ์ด ์—†๋‹ค๋ฉด, ์ธ๊ณผ ๊ด€๊ณ„๊ฐ€ ์•„๋‹Œ ๋ฐ์ดํ„ฐ ๋‚ด์˜ ํŒจํ„ด์— ์žˆ์–ด์„œ ๊ฐ€์žฅ ๋†’์€ ํ™•๋ฅ ์„ ๋ณด์—ฌ์ค€๋‹ค. ์™œ๋ƒํ•˜๋ฉด ๋Œ€๋ถ€๋ถ„์˜ ๊ธฐ๊ณ„ ํ•™์Šต ์•Œ๊ณ ๋ฆฌ์ฆ˜์€ ๋ฐ์ดํ„ฐ์— ์˜์กดํ•˜๊ณ  ์žˆ๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. ์ด ๋…ผ๋ฌธ์€ ๋ณต์žก์„ฑ๊ณผ ์‹ ๋ขฐ์„ฑ ์‚ฌ์ด์˜ ๊ท ํ˜•์„ ๊ธฐ๋ฐ˜์œผ๋กœ ์ธ๊ฐ„์˜ ํ•ด์„ ๊ฐ€๋Šฅ์„ฑ์„ ๋‹ค๋ฃจ๋Š” ๊ฒƒ์„ ๋ชฉํ‘œ๋กœ ํ•œ๋‹ค. ๊ทธ๋Ÿฌ๊ธฐ ์œ„ํ•ด์„œ, IML ๋˜๋Š” XAI ๊ธฐ์ˆ ๋“ค ์ค‘์—์„œ ๋ช‡ ๊ฐ€์ง€ ์ด๋ก ์  ๊ด€์ ์„ ์†Œ๊ฐœํ•˜๊ณ , ๊ทธ ์ ‘๊ทผ ๋ฐฉ์‹์˜ ์ดํ•ด๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ์‹ค์ œ ๋ฐ์ดํ„ฐ ์ƒ˜ํ”Œ์„ ์‚ฌ์šฉํ•˜์—ฌ ๋ชจ๋ธ์„ ๊ตฌํ˜„ํ•˜๊ณ , ๊ทธ ์‹œ๊ฐํ™” ๊ฒฐ๊ณผ๋Š” ๊ธฐ๊ณ„ ํ•™์Šต ๋ชจ๋ธ์˜ ํ•ด์„์—์„œ ์ผ๋ฐ˜ํ™” ์˜ค๋ฅ˜์— ๋Œ€ํ•œ ๋” ๋‚˜์€ ์ดํ•ด๋ฅผ ์ œ๊ณตํ•จ์„ ํ™•์ธํ–ˆ๋‹ค. ๊ฒฐ๊ณผ์ ์œผ๋กœ ๋ชจ๋ธ์˜ ํ•ด์„์€ ๋ฐ์ดํ„ฐ์— ์ž˜๋ชป๋œ ๋‹ต์ด๋‚˜ ์งˆ๋ฌธ์ด ์žˆ๋Š”์ง€ ๋ถ„์„๊ฐ€์˜ ํŽธ๊ฒฌ์„ ๋ช…ํ™•ํžˆ ํ•˜๊ณ , ์ „์ด ํ•™์Šต์— ๊ธฐ๋ฐ˜ํ•œ ๋ฏธ์„ธ ์กฐ์ •์˜ ๊ทผ๊ฑฐ๋ฅผ ์ œ์‹œํ•œ๋‹ค.Artificial Intelligence illustrate not the causality, but the highest probability of the pattern in data unless the data has a bias because many algorithms depend on the data. This paper aims to tackle human interpretability based on the trade-off between complexity and reliability. This study first emphasized several theoretical perspectives among IML methods taxonomy. Based on the comprehension of IML approaches, it highlighted the implementation of modeling using real data sample. The research results give better understanding of generalization error in the interpretation of Machine Learning. Consequently, the interpretation of a model is to clarify the bias of the analysts whether data has a wrong answer or question.I. ์„œ๋ก  1 1.1 ์—ฐ๊ตฌ๋™๊ธฐ 1 1.2 ์—ฐ๊ตฌ๋ฒ”์œ„ 2 1.3 ๋…ผ๋ฌธ์˜๊ตฌ์„ฑ 3 II. ๊ด€๋ จ์—ฐ๊ตฌ 4 2.1 ํ•ด์„๊ฐ€๋Šฅํ•œ์ธ๊ณต์ง€๋Šฅ (IML) 4 2.1.1 IML ๊ธฐ์ˆ ๋ถ„๋ฅ˜ (Taxonomy) 6 2.2 ๋ฐ์ดํ„ฐ์ฃผ๋ณ€์˜ํฌ์†Œ์„ ํ˜•๊ฒฐํ•ฉํ•ด์„ 8 2.3 CNN ๋ชจ๋ธ์˜ํŠน์ง•์ถ”์ถœ์‹œ๊ฐํ™” 11 2.3.1 ํด๋ž˜์Šคํ™œ์„ฑํ™”๋งต (CAM) 12 2.3.2 Gradient-weighted CAM 12 2.3.3 CAM vs. Grad-CAM 14 2.4 ํ•ฉ์„ฑ๊ณฑ์‹ ๊ฒฝ๋ง (CNN) 15 2.5 ์ „์ดํ•™์Šต (Transfer Learning) 19 2.6 ๋ฏธ์„ธ์กฐ์ • (Fine Tuning) 21 2.7 ์ตœ์ ํ™” (Optimization) 24 III. ์—ฐ๊ตฌ๋ฐฉ๋ฒ• 28 3.1 ์ด๋ฏธ์ง€๋ถ„๋ฅ˜๋ชจ๋ธ๋ง๊ฐœ๋ฐœ 28 3.2 ์„ฑ๋Šฅ๊ฐœ์„ ๋ฌธ์ œ์˜ํ•ด๊ฒฐ๋ฐฉ์•ˆ 29 3.3 ์„ฑ๋Šฅํ‰๊ฐ€์ง€ํ‘œ 31 IV. ์‹คํ—˜๋ฐ๊ฒฐ๊ณผ 33 4.1 ์‹คํ—˜๊ฐœ์š” 33 4.2 ์‹คํ—˜ํ™˜๊ฒฝ 35 4.3 ๋น„์ •ํ˜•๋ฐ์ดํ„ฐ์˜๊ฒฐํ•จํŒจํ„ด๋ถ„๋ฅ˜๋ชจ๋ธ๋ง 36 4.3.1 ์Šคํฌ๋ž˜์น˜ 37 4.3.2 ์ „์ดํ•™์Šต 39 4.4 ์ˆ˜ํผํ”ฝ์…€๋กœํ‘œํ˜„ํ•œ๋ชจ๋ธ๋ง๊ฒฐ๊ณผ๋ถ„์„ 40 4.5 ํŠน์ง•์‹œ๊ฐํ™”๋ฅผํ™œ์šฉํ•œ๋ชจ๋ธ๋ง๊ฒฐ๊ณผ๋ถ„์„ 41 4.5.1 CAM 41 4.5.2 Grad-CAM 42 4.6 ๋ฏธ์„ธ์กฐ์ •์—๋”ฐ๋ฅธ๋ชจ๋ธ๋ง๊ฒฐ๊ณผ 43 4.7 ์„ฑ๋Šฅํ‰๊ฐ€ 44 4.8 ๊ฒฐ๊ณผ๋ถ„์„ 45 V. ๊ฒฐ๋ก  49 5.1 ๊ณ ์ฐฐ 49 5.2 ์—ฐ๊ตฌ์ œํ•œ 50 5.3 ํ–ฅํ›„๊ณ„ํš 51 ์ฐธ๊ณ ๋ฌธํ—Œ 52 Abstract 59Maste

    ์›ƒ๊ณ  ์žˆ๋Š” ์กฐ์„ ํ™” : ๋ถํ•œ ํšŒํ™”์— ๋‹ด๊ธด ์›ƒ์Œ์˜ ์ •์น˜

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    ์ธ๋ฅ˜ํ•™๊ณผ "๋ถํ•œ์˜ ์ธ๋ฅ˜ํ•™" ์ˆ˜์—… ์ˆ˜๊ฐ•์ƒ๋“ค์ด ์ œ์ž‘ํ•œ ๋ฏธ๋‹ˆ

    Dynamics of Business Cycles in Korea: The Role of External Shocks

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    Using a multi-sector dynamic stochastic general equilibrium model, we investigate the dynamic effects of a variety of shocks to a small open economy. In particular, we calibrate the model to match the main characteristics of business cycles in Korea and aI. Introduction ใ€€ใ€€II. Properties of Business Cycles in Korea ใ€€ใ€€III. Model ใ€€ใ€€IV. calibration ใ€€ใ€€V. Comparing the Second Moments ใ€€ใ€€VI. Impulse Responses ใ€€ใ€€VII. Conclusion ใ€€ใ€€Reference ใ€€ใ€€Appendix. Data Sources and Definitio

    ๋‹จ์–ด ์ž„๋ฒ ๋”ฉ์„ ํ™œ์šฉํ•œ ํ…์ŠคํŠธ ์ž„๋ฒ ๋”ฉ ๋ชจ๋ธ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์œตํ•ฉ๊ณผํ•™๊ธฐ์ˆ ๋Œ€ํ•™์› ์œตํ•ฉ๊ณผํ•™๋ถ€(๋””์ง€ํ„ธ์ •๋ณด์œตํ•ฉ์ „๊ณต), 2018. 8. ์„œ๋ด‰์›.๊ฐ€๋ณ€ ๊ธธ์ด์˜ ํ…์ŠคํŠธ๋ฅผ ํ…์ŠคํŠธ์˜ ๋งฅ๋ฝ ์ •๋ณด๋ฅผ ๋ฐ˜์˜ํ•œ ๋ฒกํ„ฐ๋กœ ๋ณ€ํ™˜ํ•˜๋Š” ๋ฐฉ๋ฒ•์ธ ๋ฌธ์žฅ ํ˜น์€ ๋ฌธ๋‹จ ์ž„๋ฒ ๋”ฉ์€ ๋‹ค์–‘ํ•œ ๊ธฐ๊ณ„ํ•™์Šต ์‹œ์Šคํ…œ์—์„œ ๊ฐ์„ฑ ๋ถ„์„ ๋“ฑ์˜ ํ…์ŠคํŠธ ๋ถ„๋ฅ˜ ๋ฌธ์ œ, ํ…์ŠคํŠธ์˜ ์œ ์‚ฌ๋„ ์ธก์ •, ํด๋Ÿฌ์Šคํ„ฐ๋ง, ์‹œ๊ฐํ™” ๋“ฑ ๊ณ ์ •๋œ ์ฐจ์›์˜ ๋ฒกํ„ฐ๋ฅผ ์ž…๋ ฅ์œผ๋กœ ์š”๊ตฌํ•˜๋Š” ๊ฐ์ข… ๊ณผ์ œ๋ฅผ ์ˆ˜ํ–‰ํ•˜๊ธฐ ์œ„ํ•œ ๊ธฐ๋ณธ์ ์ธ ํŠน์ง• ์ถ”์ถœ ๋ฐฉ๋ฒ•์œผ๋กœ ์‚ฌ์šฉ๋˜๊ณ  ์žˆ๋‹ค. ๊ธฐ์กด์˜ ํ…์ŠคํŠธ์˜ ๋ฒกํ„ฐ ํ‘œํ˜„์„ ์œ„ํ•ด ๋„๋ฆฌ ์‚ฌ์šฉ๋˜๊ณ  ์žˆ์—ˆ๋˜ ๋‹จ์–ด ์ž๋ฃจ(Bag-of-Words) ๋ชจํ˜•์€ ๋‹จ์ˆœํ•˜๊ณ  ํšจ๊ณผ์ ์ด์ง€๋งŒ ์ฐจ์›์˜ ํฌ๊ธฐ๊ฐ€ ๋‹จ์–ด์˜ ์ˆซ์ž์— ๋น„๋ก€ํ•ด์„œ ์ฆ๊ฐ€ํ•˜๋ฉฐ ๋ ˆ์ด๋ธ” ์—†๋Š” ํ…์ŠคํŠธ ๋ฐ์ดํ„ฐ๋ฅผ ํ™œ์šฉํ•˜๊ธฐ ์–ด๋ ต๋‹ค๋Š” ๋‹จ์ ์ด ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ํ•œ๊ณ„๋ฅผ ๊ทน๋ณตํ•˜๊ธฐ ์œ„ํ•ด ์ œ์•ˆ๋œ ๋ฌธ๋‹จ ๋ฒกํ„ฐ(Paragraph Vector)๋Š” ์ƒˆ๋กœ์šด ๋ฐ์ดํ„ฐ์— ๋Œ€ํ•œ ๋ฒกํ„ฐ ํ‘œํ˜„์„ ํ•™์Šตํ•˜๊ณ  ์ƒ์„ฑํ•˜๋Š”๋ฐ ์ ์šฉํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ๊ธฐ์กด ๋ชจ๋ธ์„ ์ƒˆ๋กœ์šด ๋ฐ์ดํ„ฐ์— ๋Œ€ํ•ด ์ถ”๊ฐ€์ ์œผ๋กœ ํ•™์Šต์‹œํ‚ค๋Š” ์ถ”์ • ๊ณผ์ •์„ ํ•„์š”๋กœ ํ•œ๋‹ค๋Š” ํ•œ๊ณ„๊ฐ€ ์žˆ๋‹ค. ์‹œํ€€์Šค ํˆฌ ์‹œํ€€์Šค(Sequence to Sequence) ๋ชจํ˜•์„ ๊ธฐ๋ฐ˜์œผ๋กœ ์„ ํ›„ ๋ฌธ์žฅ๊ณผ์˜ ๋ฌธ์žฅ ๊ฐ„ ๊ด€๊ณ„๋ฅผ ํ™œ์šฉํ•ด ๋ฌธ์žฅ์˜ ๋ฒกํ„ฐ ํ‘œํ˜„์„ ์ƒ์„ฑํ•˜๋Š” ์ธ์ฝ”๋”๋ฅผ ํ•™์Šตํ•˜๋Š” ์ƒ๊ฐ ์ƒ๋žต ๋ฒกํ„ฐ(Skip-Thought Vectors) ๋ชจํ˜•์€ ํ•™์Šต์„ ์œ„ํ•ด ๋ฌธ์žฅ ๊ฐ„ ์„ ํ›„ ๊ด€๊ณ„๋ฅผ ํ™œ์šฉํ•˜๊ธฐ์— ์—ฌ๋Ÿฌ ๋ฌธ์žฅ์ด ํฌํ•จ๋˜๋ฉฐ ์„ ํ›„ ๊ด€๊ณ„๋ฅผ ์„ค์ •ํ•˜๊ธฐ ์–ด๋ ค์šด ๋ฌธ๋‹จ ์ˆ˜์ค€์—๋Š” ๋ฐ”๋กœ ์ ์šฉ๋˜๊ธฐ ์–ด๋ ค์šฐ๋ฉฐ ํ…์ŠคํŠธ ์ž„๋ฒ ๋”ฉ์˜ ์ƒ์„ฑ์— ๋งŽ์€ ์—ฐ์‚ฐ ์ž์›์„ ํ•„์š”๋กœ ํ•œ๋‹ค๋Š” ๋‹จ์ ์„ ๊ฐ–๊ณ  ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ „์ด ํ•™์Šต์˜ ๋ฌธ์ œ์™€ ์ž„๋ฒ ๋”ฉ ์ƒ์„ฑ์— ํ•„์š”ํ•œ ์—ฐ์‚ฐ๋Ÿ‰ ๋ฐ ๊ฐ€๋ณ€ ๊ธธ์ด ํ…์ŠคํŠธ ์ฒ˜๋ฆฌ์˜ ์šฉ์ด์„ฑ์˜ ๋ฌธ์ œ ๋“ฑ์„ ๊ณ ๋ คํ•˜์—ฌ ๋‹จ์–ด ์ž„๋ฒ ๋”ฉ์˜ ํ•ฉ์„ ํ†ตํ•ด ํ…์ŠคํŠธ ์ž„๋ฒ ๋”ฉ์„ ์ƒ์„ฑํ•˜๋Š” ๋ชจํ˜•์„ ์ œ์•ˆํ•œ๋‹ค. ๊ธฐ์กด์˜ ๋‹จ์–ด ์ž„๋ฒ ๋”ฉ์ด ์œ ๋‹ˆ๊ทธ๋žจ(Unigram)์„ ์‚ฌ์šฉํ•˜๋Š” ๊ฒƒ๊ณผ๋Š” ๋‹ฌ๋ฆฌ ๋ณธ ์—ฐ๊ตฌ์˜ ๋ชจํ˜•์—์„œ๋Š” ๋ฐ”์ด๊ทธ๋žจ(Bigram) ๋ฐ ํŠธ๋ผ์ด๊ทธ๋žจ(Trigram) ๋“ฑ์˜ n-๊ทธ๋žจ(n-gram)์„ ํ™œ์šฉํ•ด ํ…์ŠคํŠธ ์ž„๋ฒ ๋”ฉ์„ ๊ฐœ์„ ํ•˜์˜€๋‹ค. ๋˜ํ•œ ์ด๋ฅผ ์ปจ๋ณผ๋ฃจ์…˜ ์‹ ๊ฒฝ๋ง์„ ์‚ฌ์šฉํ•œ ๋ชจํ˜•๊ณผ ๋น„๊ตํ•˜์—ฌ ์ปจ๋ณผ๋ฃจ์…˜ ์‹ ๊ฒฝ๋ง๊ณผ ๊ฐ™์€ ์ถ”๊ฐ€์ ์ธ ๊ตฌ์กฐ์˜ ๋„์ž… ์—†์ด๋„ ์ข‹์€ ์„ฑ๋Šฅ์  ํŠน์„ฑ์„ ๋ณด์ผ ์ˆ˜ ์žˆ์Œ์„ ๊ฒ€ํ† ํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ๋ฌธ์žฅ ํ˜น์€ ๋ฌธ๋‹จ์˜ ๋ฒกํ„ฐ ํ‘œํ˜„์„ ์ƒ์„ฑํ•˜๊ธฐ ์œ„ํ•œ ๋‹จ์ˆœํ•œ ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•˜๋Š” ๋™์‹œ์— ๋ถ€์ˆ˜์ ์œผ๋กœ ํ•™์Šตํ•œ n-๊ทธ๋žจ ๋‹จ์–ด ์ž„๋ฒ ๋”ฉ์˜ ํŠน์„ฑ์„ ๋ถ„์„ํ•˜์˜€๋‹ค. ๋‹จ์–ด ์ž„๋ฒ ๋”ฉ์˜ ํŠน์„ฑ์— ๋Œ€ํ•œ ๋ถ„์„๊ณผ ๋‹จ์–ด ์ž„๋ฒ ๋”ฉ์˜ ๋‹จ์ˆœํ•œ ๊ฒฐํ•ฉ์ด ๋ณด์—ฌ์ฃผ๋Š” ํšจ๊ณผ์„ฑ์„ ํ†ตํ•ด ์ž์—ฐ์–ด ์ฒ˜๋ฆฌ ๊ณผ์ œ์— ์š”๊ตฌ๋˜๋Š” ํ…์ŠคํŠธ์˜ ํŠน์„ฑ์„ ํฌ์ฐฉํ•˜๊ธฐ ์œ„ํ•ด ํ•„์š”ํ•œ ์กฐ๊ฑด์„ ์ดํ•ดํ•˜๋Š” ๊ฒƒ๊ณผ ํ•จ๊ป˜ ํ…์ŠคํŠธ์˜ ๊ณ ์† ์ฒ˜๋ฆฌ๊ฐ€ ํ•„์š”ํ•œ ์‹ค์šฉ์ ์ธ ์ƒํ™ฉ์—์„œ ์‚ฌ์šฉํ•  ์ˆ˜ ์žˆ๋Š” ๋„๊ตฌ๋กœ์„œ ๊ธฐ์—ฌํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€ํ•œ๋‹ค.์ œ 1 ์žฅ ์„œ ๋ก  6 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ์˜ ๋ฐฐ๊ฒฝ 6 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ์˜ ๋ชฉํ‘œ 9 ์ œ 2 ์žฅ ์„ ํ–‰ ์—ฐ๊ตฌ 11 ์ œ 1 ์ ˆ ๋ฌธ์žฅ ๋ฐ ๋ฌธ๋‹จ ์ž„๋ฒ ๋”ฉ 11 1.1 Word2vec 12 1.2 ๋ฌธ๋‹จ ๋ฒกํ„ฐ(Paragraph Vector) 14 1.3 ์ƒ๊ฐ์ƒ๋žต ๋ฒกํ„ฐ(Skip-Thought Vectors) 16 ์ œ 2 ์ ˆ ํ…์ŠคํŠธ ์ฒ˜๋ฆฌ๋ฅผ ์œ„ํ•œ ์‹ ๊ฒฝ๋ง ๊ตฌ์กฐ 19 2.1 ๋ฌธ์žฅ ๋ถ„๋ฅ˜๋ฅผ ์œ„ํ•œ ์ปจ๋ณผ๋ฃจ์…˜ ์‹ ๊ฒฝ๋ง(Convolutional Neural Networks for Sentence Classification) 19 2.2 ๊ตฌ์กฐ์  ์ž๊ธฐ ์ฃผ์˜ ๋ฌธ์žฅ ์ž„๋ฒ ๋”ฉ(A Structured Self-Attentive Sentence Embedding) 20 ์ œ 3 ์žฅ ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• ๋ฐ ์„ค๊ณ„ 23 ์ œ 1 ์ ˆ ์‹œ์Šคํ…œ ๊ตฌ์กฐ 23 ์ œ 2 ์ ˆ ๋ฐ์ดํ„ฐ์…‹๊ณผ ์ „์ฒ˜๋ฆฌ ๋ฐ ํ•™์Šต ์ ˆ์ฐจ 31 2.1 ๋ฐ์ดํ„ฐ์…‹ 31 2.1 ํ•™์Šต ์ ˆ์ฐจ ๋ฐ ๋ชจํ˜• ์ƒ์„ธ 34 ์ œ 4 ์žฅ ์‹คํ—˜ ๊ฒฐ๊ณผ 38 ์ œ 1 ์ ˆ ๋ฐ์ดํ„ฐ์…‹์— ๋Œ€ํ•œ ์ „์ด ํ•™์Šต ๊ฒฐ๊ณผ 38 ์ œ 2 ์ ˆ ๋ชจํ˜•์˜ ๋ณ€ํ˜•์— ๋”ฐ๋ฅธ ์„ฑ๋Šฅ ๋ณ€ํ™” 41 ์ œ 2 ์ ˆ ํ•™์Šต๋œ ๋ชจํ˜•์˜ ํŠน์„ฑ ๋ถ„์„ 44 ์ œ 5 ์žฅ ๋…ผ์˜ 52 ์ œ 6 ์žฅ ๊ฒฐ๋ก  ๋ฐ ํ–ฅํ›„ ์—ฐ๊ตฌ๋ฅผ ์œ„ํ•œ ์ œ์–ธ 59 ์ฐธ๊ณ ๋ฌธํ—Œ 62Maste

    Dynamic Welfare Effects of Tax Reform: Case of Korea

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    This paper analyzes welfare effects of revenue neutral tax reform using a small open economy dynamic general equilibrium model. We apply this model to the Korean data and examine welfare effects of various tax reformsremoval of capital income tax and/orโ… . Introduction โ…ก. Model ใ€€1. Consumer ใ€€2. Firms ใ€€3. Government โ…ข. Solution Method โ…ฃ. Calibration โ…ค. The Effects of Tax Reforms ใ€€1. Comparison of welfare effects ใ€€2. Dynamics of welfare gains ใ€€3. Sensitivity Analysi
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