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    ์œ ๊ฒฉ์„ ๊ณ ๋ คํ•œ ๋ฌด๋ฏธ์ต ์ดˆ์†Œํ˜• ๋‚ ๊ฐฏ์ง“ ๋น„ํ–‰์ฒด ํ†ตํ•ฉ ์„ค๊ณ„: ๊ธฐํ•˜๋ถ„์„ ๋ฐ ์ˆ˜์น˜ ํ•ด์„์„ ํ†ตํ•œ ์ ‘๊ทผ

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ํ˜‘๋™๊ณผ์ • ์šฐ์ฃผ์‹œ์Šคํ…œ ์ „๊ณต, 2021. 2. ์‹ ์ƒ์ค€.Unlike birds, an insect type tailless flapping wing does not possess tail wings. Therefore, insect type flapping wing may be fabricated in small size and of decreased weight. Because of the taillessness, however, stable flight of an insect type flapping wing depends only on main wings. Thus, a number of researches were conducted regarding its control mechanisms. In this thesis, the trailing edge control, one of the methods developed to produce control moments, is adopted. Such method requires additional shafts that connect the root of the main wing and control mechanism, and the shafts are rotated to deform the wing shape. In this manner, asymmetric aerodynamic forces are produced. The control mechanism uses micro actuators for compact design. However, small size of the micro actuator gearbox causes relatively large backlash and the resulting free play of the main wings that generates undesirable aerodynamic forces. Under such circumstance, design improvement of the control mechanism is conducted to minimize the effects of the free play. First, geometry analysis is performed to investigate the factors that cause the free play. Control mechanism design for the minimized free play is obtained. Then, three-dimensional computer aided design (CAD) of modified configuration is drawn, and kinematic simulations are conducted by RecurDyn to determine the prevention of interference. Finally, the feasibility of modified design is examined by the numerical simulation. The main wings are modeled by the displacement-based geometrically exact beam model combined with cross-sectional analysis. To mimic the free play appropriately, the spring elements are attached to the joints. At the same time, two-dimensional unsteady aerodynamic model is used for aerodynamic forces. Consequently, the reasonable control moments are gathered in terms of the maneuverability.๊ณค์ถฉ ๋ชจ๋ฐฉํ˜• ๋‚ ๊ฐฏ์ง“ ๋น„ํ–‰์ฒด๋Š” ๊ผฌ๋ฆฌ๋‚ ๊ฐœ๊ฐ€ ์—†๊ธฐ ๋•Œ๋ฌธ์— ์ƒˆ ๋ชจ๋ฐฉํ˜• ๋‚ ๊ฐฏ์ง“ ๋น„ํ–‰์ฒด์™€ ๋น„๊ตํ•˜์—ฌ ๊ฐ€๋ณ๊ณ  ์ž‘๊ฒŒ ์„ค๊ณ„๋  ์ˆ˜ ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜, ๊ณค์ถฉ ๋ชจ๋ฐฉํ˜• ๋‚ ๊ฐฏ์ง“ ๋น„ํ–‰์ฒด๋Š” ๊ผฌ๋ฆฌ๋‚ ๊ฐœ๊ฐ€ ์—†๋‹ค๋Š” ํŠน์ง•์œผ๋กœ ์ธํ•˜์—ฌ, ์˜ค์ง ๋‘ ๋‚ ๊ฐœ๋งŒ์„ ์ด์šฉํ•˜์—ฌ ์กฐ์ข…๋ ฅ์„ ๋ฐœ์ƒ์‹œํ‚จ๋‹ค. ๋”ฐ๋ผ์„œ, ์ด์— ๋Œ€ํ•œ ๋งŽ์€ ์—ฐ๊ตฌ๊ฐ€ ์ˆ˜ํ–‰๋˜์—ˆ๊ณ  ๊ฐœ๋ฐœ๋œ ์—ฌ๋Ÿฌ ์ž์„ธ ์ œ์–ด ๋ฐฉ๋ฒ• ์ค‘ ๋ณธ ํ•™์œ„ ๋…ผ๋ฌธ์—์„  ๋‚ ๊ฐœ ๋๋‹จ ๋น„ํ‹€๋ฆผ์„ ์ด์šฉํ•œ ์ž์„ธ ์ œ์–ด ์žฅ์น˜๋ฅผ ๋‹ค๋ฃฌ๋‹ค. ํ•ด๋‹น ๋ฐฉ๋ฒ•์€ ์ฃผ๋‚ ๊ฐœ์˜ ๋ฟŒ๋ฆฌ ๋ถ€๋ถ„์„ ์ž์„ธ ์ œ์–ด ์žฅ์น˜์™€ ์—ฐ๊ฒฐํ•˜๊ณ  ์ด๋ฅผ ํšŒ์ „์‹œ์ผœ ๋‚ ๊ฐœ ๋๋‹จ์— ๋ณ€ํ˜•์„ ๋ฐœ์ƒ์‹œํ‚จ๋‹ค. ์ž์„ธ ์ œ์–ด ์žฅ์น˜์—๋Š” ๊ฒฝ๋Ÿ‰ํ™”๋ฅผ ์œ„ํ•˜์—ฌ ๊ฐ€๋ณ๊ณ  ์ž‘์€ ์žฅ๋น„๋“ค์ด ์‚ฌ์šฉ๋œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜, ์ž์„ธ ์ œ์–ด ์žฅ์น˜ ์ œ์ž‘์— ์‚ฌ์šฉ๋˜๋Š” ์ดˆ์†Œํ˜• ๊ตฌ๋™๊ธฐ๋Š” ์ž‘์€ ํฌ๊ธฐ๋กœ ์ธํ•˜์—ฌ ๋‚ด๋ถ€ ๊ธฐ์–ด์— ๋ฐฑ๋ž˜์‹œ๋ฅผ ๊ฐ–๊ณ  ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ, ์ด๋Š” ์ฃผ๋‚ ๊ฐœ์˜ ๋ถˆํ•„์š”ํ•œ ์œ ๊ฒฉ์„ ๋ฐœ์ƒ์‹œํ‚ฌ ์ˆ˜ ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ์œ ๊ฒฉ์€ ์ฃผ๋‚ ๊ฐœ์˜ ์ง„๋™์œผ๋กœ ์ด์–ด์ ธ, ๋ถˆํ•„์š”ํ•œ ๋น„๋Œ€์นญ์  ๊ณต๋ ฅ์„ ๋ฐœ์ƒ์‹œํ‚ฌ ์ˆ˜ ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ์ƒํ™ฉ ๋•Œ๋ฌธ์— ์œ ๊ฒฉ์ด ์ตœ์†Œํ™”๋œ ์ž์„ธ ์ œ์–ด ์žฅ์น˜ ์„ค๊ณ„๋ฅผ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ์ฒซ์งธ๋กœ, ๊ธฐํ•˜ํ•™์  ํ•ด์„์„ ํ†ตํ•˜์—ฌ ์œ ๊ฒฉ์— ์˜ํ–ฅ์„ ์ฃผ๋Š” ์š”์ธ์„ ํŒŒ์•…ํ•˜์˜€๋‹ค. ์ด๋ฅผ ํ†ตํ•˜์—ฌ ์œ ๊ฒฉ์„ ์ตœ์†Œํ™”ํ•œ ์„ค๊ณ„๋ฅผ ๋„์ถœํ•˜์˜€์œผ๋ฉฐ, 3์ฐจ์› computer aided design (CAD) ํ˜•์ƒ๊ณผ RecurDyn์„ ์ด์šฉํ•˜์—ฌ ๋™์—ญํ•™์  ํ•ด์„์„ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ์ด๋ฅผ ํ†ตํ•˜์—ฌ ์ž์„ธ ์ œ์–ด ์žฅ์น˜์˜ ๊ตฌ๋™ ์ค‘ ๋ฐœ์ƒํ•˜๋Š” ๊ฐ„์„ญ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์ตœ์ข…์ ์œผ๋กœ, ์ˆ˜์น˜์  ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ์ด์šฉํ•˜์—ฌ ๊ฐœ์„ ๋œ ์ž์„ธ ์ œ์–ด ์žฅ์น˜์˜ ํƒ€๋‹น์„ฑ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์ด๋•Œ, ์ฃผ๋‚ ๊ฐœ๋Š” ๋ณ€์œ„ ๊ธฐ๋ฐ˜ ๊ธฐํ•˜ํ•™์  ์ •๋ฐ€ ๋ณด๋กœ ๋ชจ๋ธ๋ง ๋˜์—ˆ์œผ๋ฉฐ, 2์ฐจ์› ๋‹จ๋ฉด ํ•ด์„ ๊ฒฐ๊ณผ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ํ•ด์„์„ ์ˆ˜ํ–‰ํ•˜์˜€๊ณ  ๊ณต๋ ฅ ๋ชจ๋ธ์€ 2์ฐจ์› ๋น„์ •์ƒ ๋ชจ๋ธ์„ ์‚ฌ์šฉํ•˜์˜€๋‹ค. ๋˜ํ•œ, ์œ ๊ฒฉ์„ ๋ชจ์‚ฌํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ์Šคํ”„๋ง ์š”์†Œ๋ฅผ ๊ด€์ ˆ์— ์‚ฝ์ž…ํ•˜์—ฌ ํ•ด์„์„ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ๊ฒฐ๊ณผ์ ์œผ๋กœ, ๋ณธ ์—ฐ๊ตฌ์—์„œ ์„ค๊ณ„ํ•œ ์ž์„ธ ์ œ์–ด ์žฅ์น˜๊ฐ€ ์œ ํšจํ•œ ์กฐ์ข…๋ ฅ์„ ๋ฐœ์ƒ์‹œํ‚ค๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค.Abstract i Contents iii List of Tables vi List of Figures vii List of Symbols x Preface xi Chpater 1 Introduction 1 1.1 Background 1 1.2 Previous Researches 3 1.2.1 Review of Control Mechanism Design Regarding the Insect-Type Flapping Wing 3 1.2.2 Review of Numerical Simulation Studies Regarding the Insect-type Flapping Wing 6 1.3 Research Objectives and Thesis Outline 8 Chpater 2 Control Mechanism Design with Free play 9 2.1 Overview of Control Mechanism Design with Free play 9 2.2 Control Mechanism: Trailing Edge Control 11 2.3 Components of the Control Mechanism 14 2.4 Control Mechanism Design with Minimize free play effect 17 Chpater 3 Numerical Simulations of FWMAV 25 3.1 Overview of Numerical Simulation based on Flexible Multibody Dynamics 25 3.2 Simulation Setup 26 3.2.1 Simulation Methodology 31 3.2.2 Aerodynamics 34 3.3 Numerical Simulation 37 Chpater 4 Conclusions 47 4.1 Contirbutions 47 4.2 Future Works 48 Acknowledgments 50 References 50 ๊ตญ๋ฌธ์ดˆ๋ก 55Maste

    ํ†ต์ผ์ธ์‹ ์ œ๊ณ ๋ฅผ ์œ„ํ•œ ํ†ต์ผ ์œ ๊ด€๊ธฐ๊ด€๋“ค์˜ ICT ํ™œ์šฉ๋ฐฉ์•ˆ

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    ํ‰ํ™”ํ†ต์ผ์€ ๊ตญ๊ฐ€์ ์ธ ๊ณผ์ œ์ด์ง€๋งŒ ํ‰ํ™”ํ†ต์ผ์— ๋Œ€ํ•œ ๊ตญ๋ฏผ๋“ค์˜ ์ธ์‹์€ ๊ณผ๊ฑฐ์— ๋น„ํ•ด ์ƒ๋‹นํžˆ ๋‚ฎ์€ ๊ฒƒ์œผ๋กœ ํŒŒ์•…๋˜๊ณ  ์žˆ๋‹ค. ํŠนํžˆ ์ Š์€ ์„ธ๋Œ€์˜ ํ†ต์ผ์ธ์‹์€ ์ง€์†์ ์œผ๋กœ ๋‚ฎ๊ฒŒ ๋‚˜ํƒ€๋‚˜๊ณ  ์žˆ๋Š” ํ˜„์‹ค์ด๋‹ค. ํ•œํŽธ ์šฐ๋ฆฌ๋‚˜๋ผ๋Š” ICT ๊ฐ•๊ตญ์œผ๋กœ์„œ ์„ธ๊ณ„ ์ตœ๊ณ  ์ˆ˜์ค€์˜ ICT ์ธํ”„๋ผ์™€ ICT ํ™œ์šฉ ๋Šฅ๋ ฅ์„ ๋ณด์œ ํ•˜๊ณ  ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์šฐ๋ฆฌ๋‚˜๋ผ์˜ ๊ฐ•์ ์ธ ICT๋ฅผ ํ™œ์šฉํ•˜์—ฌ ๊ตญ๋ฏผ๋“ค์˜ ํ‰ํ™”ํ†ต์ผ ์ธ์‹์„ ์ œ๊ณ ํ•  ์ˆ˜ ์žˆ๋Š” ๋ฐฉ์•ˆ์„ ๋ชจ์ƒ‰ํ•ด ๋ณด๋Š”๋ฐ ๊ทธ ๋ชฉ์ ์ด ์žˆ๋‹ค. ์šฐ์„  ๊ตญ๋ฏผ๋“ค์˜ ํ†ต์ผ์ธ์‹ ์ œ๊ณ ๋ฅผ ์œ„ํ•ด ํ†ต์ผ ๊ด€๋ จ ๊ธฐ๊ด€๋“ค์ด ์–ด๋– ํ•œ ํ™œ๋™์„ ํ•˜๋Š”์ง€ ์กฐ์‚ฌํ•˜๋˜ ICT์˜ ํ™œ์šฉ ํ˜„ํ™ฉ๊ณผ ๋ฌธ์ œ์ ์„ ์งš์–ด ๋ณด์•˜๋‹ค. ๋ถ„์„ ๋Œ€์ƒ์—๋Š” ์ •๋ถ€ ๋ฐ ๊ณต๊ณต๊ธฐ๊ด€์œผ๋กœ์„œ๋Š” ํ†ต์ผ๋ถ€์™€ ํ†ต์ผ์ค€๋น„์œ„์›ํšŒ๊ฐ€, ๋ฏผ๊ฐ„๊ธฐ๊ด€์œผ๋กœ์„œ๋Š” ๋ฏผ์กฑํ†ต์ผ์ค‘์•™ํ˜‘์˜ํšŒ, ํ†ต์ผ์„ ์ƒ๊ฐํ•˜๋Š” ์‚ฌ๋žŒ๋“ค์˜ ๋ชจ์ž„, ๋‚จ๋ถ์‚ฌํšŒํ†ตํ•ฉ์—ฐ๊ตฌ์›์ด ํฌํ•จ๋˜์—ˆ๋‹ค. ๋ถ„์„ ๊ฒฐ๊ณผ์— ์˜ํ•˜๋ฉด ์ด ๊ธฐ๊ด€๋“ค์€ SNS ๋“ฑ ICT์˜ ํ™•์‚ฐ ์ถ”์„ธ์™€ ๊ทธ ์ค‘์š”์„ฑ์„ ์ธ์‹ํ•˜๊ณ  ์ด๋ฅผ ํ™œ์šฉํ•˜๋ ค๋Š” ๋…ธ๋ ฅ์€ ํ•˜๊ณ  ์žˆ์œผ๋‚˜ ์‹ค์ œ๋กœ๋Š” ๋ช…๋ชฉ์ƒ์˜ ์šด์˜์— ๊ทธ์น˜๊ณ  ์žˆ์œผ๋ฉฐ ICT์˜ ํŠน์„ฑ์„ ์‚ด๋ฆฌ๋Š” ํšจ๊ณผ์ ์ธ ํ™œ๋™์€ ํ•˜์ง€ ๋ชปํ•˜๊ณ  ์žˆ์—ˆ๋‹ค. ์ด๋Ÿฌํ•œ ๋ถ„์„ ๊ฒฐ๊ณผ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ICT์˜ ํšจ๊ณผ์ ์ธ ํ™œ์šฉ์„ ํ†ตํ•œ ๊ตญ๋ฏผ๋“ค์˜ ํ‰ํ™”ํ†ต์ผ ์ธ์‹ ์ œ๊ณ ๋ฅผ ์œ„ํ•ด์„œ SNS ํŠน์„ฑ์˜ ๊ทน๋Œ€ํ™”, ์ Š์€์ธต์— ๋Œ€ํ•œ ํƒ€๊ฒŸํŒ…, ๋ธŒ๋žœ๋”ฉ ๋ฐ ์ง€์†์  ์ปค๋ฎค๋‹ˆ์ผ€์ด์…˜์ด๋ผ๋Š” ์ธก๋ฉด์—์„œ ๊ตฌ์ฒด์ ์ธ ์ œ์–ธ์„ ์ œ์‹œํ•˜์˜€๋‹ค. ์ด์™€ ๋”๋ถˆ์–ด ICT ํ™œ์šฉ๋„ ํ–ฅ์ƒ์„ ์œ„ํ•œ ๋‹ค์–‘ํ•œ ์‹œ์‚ฌ์ ์„ ์ œ์‹œํ•˜์˜€๋‹ค

    Influence of ovarian hormones on the exocrine secretion in isolated cat pancreas

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    ์˜ํ•™๊ณผ/์„์‚ฌ[ํ•œ๊ธ€] ์ทจ์™ธ๋ถ„๋น„๋Š” ์ฃผ๋กœ ์‹ ๊ฒฝ์„ฑ์ธ์ž ๋ฐ ์œ„์žฅํ™€๋ชฌ์— ์˜ํ•˜์—ฌ ์กฐ์ ˆ๋˜๋ฉฐ, steroidํ™€๋ชฌ๋„ ์ทจ์™ธ๋ถ„๋น„๊ธฐ๋Šฅ ์กฐ์ ˆ์— ํ•œ ์š”์ธ์œผ๋กœ ๊ด€์—ฌํ•œ๋‹ค๊ณ  ์•Œ๋ ค์ ธ ์žˆ๋‹ค. ์ฒด๋‚ด steroidํ™€๋ชฌ์€ ๋ถ€์‹ ๊ณผ ๋‚œ์†Œ์—์„œ cholesterol๋กœ๋ถ€ํ„ฐ ํ•ฉ์„ฑ๋˜๋ฉฐ ์ด๋“ค์€ ์ƒ์ฒด์˜ ํ•ญ์ƒ์„ฑ ์œ ์ง€์— ์ค‘์š”ํ•œ ์ž‘์šฉ์„ ํ•œ๋‹ค. ์ทจ์™ธ๋ถ„๋น„์— ๋Œ€ํ•œ ๋ถ€์‹ ํ”ผ์งˆํ™€๋ชฌ์˜ ์˜ํ–ฅ์— ๊ด€ํ•ด์„œ๋Š” ์ƒ๋ฐ˜๋œ ๋ณด๊ณ ๊ฐ€ ๋งŽ์œผ๋‚˜, ๋Œ€์ฒด๋กœ glucocorticoid๋Š” ์ทจ์™ธ๋ถ„๋น„๋ฅผ ์–ต์••ํ•˜๋ฉฐ, mineralocorticoid๋Š” ์ทจ์™ธ๋ถ„๋น„๋ฅผ ํ•ญ์ง„์‹œํ‚ค๋Š” ๊ฒƒ์œผ๋กœ ๋ฐ›์•„๋“ค์—ฌ์ง€๊ณ  ์žˆ๋‹ค. ๋˜ํ•œ ์ทจ์„ ํฌ ์„ธํฌ์งˆ์— estrogen๊ณผ ๊ฒฐํ•ฉํ•˜๋Š” ๋‹จ๋ฐฑ์ด ์žˆ์Œ์ด ์•Œ๋ ค์ ธ ์žˆ๊ณ  progesterone์€ ์ทจ์ข…์–‘ ์„ธํฌ์˜ ์„ธํฌ๋‚ด mRNA ๋ฐ amylase์˜ ์–‘์„ ์ฆ๊ฐ€์‹œํ‚จ๋‹ค๊ณ  ํ•˜์—ฌ ๋‚œ์†Œํ™€๋ชฌ ์—ญ์‹œ ์ทจ์™ธ๋ถ„๋น„๊ธฐ๋Šฅ๊ณผ ๊ด€๋ จ์„ฑ์ด ์žˆ์Œ์ด ์‹œ์‚ฌ๋˜๊ณ  ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ์‹คํ—˜์—์„œ๋Š” ์ „ํ•ด์งˆ ์šฉ์•ก์„ ๊ด€๋ฅ˜ํ•˜๋Š” ์ƒ์ฒด์™ธ ์ ์ถœ ๊ณ ์–‘์ด ์ทจ์žฅํ‘œ๋ณธ์„ ์ด์šฉํ•˜์—ฌ ์ทจ์™ธ๋ถ„๋น„๊ธฐ๋Šฅ์— ๋Œ€ํ•œ ๋‚œ์†Œํ™€๋ชฌ์˜ ์ง์ ‘์ ์ธ ์˜ํ–ฅ์„ ๊ฒ€์ƒ‰ํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ์‹คํ—˜๋™๋ฌผ๋กœ๋Š” 1.5kg๋‚ด์™ธ์˜ ์žก์ข…๊ณ ์–‘์ด๋ฅผ ์•”์ˆ˜ ๊ตฌ๋ณ„์—†์ด ์‚ฌ์šฉํ•˜์˜€์œผ๋ฉฐ secobarbital ๋งˆ์ทจํ•˜์— ์ทจ์žฅ์„ ์ ์ถœํ•˜์—ฌ Krebs Ringer bicarbonate buffer(KRBB)๋ฅผ ๊ด€๋ฅ˜์‹œ์ผฐ๋‹ค. ๋‚œ์†Œํ™€๋ชฌ์˜ ์˜ํ–ฅ์„ ๊ฒ€์ƒ‰ํ•˜๊ธฐ ์œ„ํ•˜์—ฌ estrogen ๋˜๋Š” progesterone์„ ๊ฐ๊ฐ 10**-8 โ€• 10**-6 M๋˜๊ฒŒ KRBB์— ์ฒจ๊ฐ€ํ•˜์—ฌ 30๋ถ„๊ฐ„์”ฉ ๊ด€๋ฅ˜ํ•˜์˜€๋‹ค. ์ทจ์•ก๋ถ„๋น„๋Š” secretin์˜ submaximal dose ์ฃผ์ž…์œผ๋กœ ์ผ์ •ํ•˜๊ฒŒ ์œ ์ง€์‹œ์ผฐ๊ณ  ์ทจํšจ์†Œ๋ถ„๋น„๋Š” secretin ์ฃผ์ž…ํ•˜์— cholecystokinin(CCK) ์ž๊ทน์œผ๋กœ ์œ ๋ฐœ์‹œ์ผฐ๋‹ค. ์‹คํ—˜์„ฑ์ ์„ ์š”์•ฝํ•˜๋ฉด ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. 1. Estrogen๊ด€๋ฅ˜๋กœ ์ ์ถœ์ทจ์žฅ์˜ ์™ธ๋ถ„๋น„๊ธฐ๋Šฅ์€ ํ•ญ์ง„๋˜์—ˆ์œผ๋ฉฐ estrogen 10**-8 M์ด์ƒ์˜ ๋†๋„์—์„œ secretin์— ์˜ํ•œ ์ทจ์•ก๋ถ„๋น„์™€ CCK์ž๊ทน์— ์˜ํ•œ amylase๋ถ„๋น„๊ฐ€ ์ฆ๊ฐ€๋˜์—ˆ๋‹ค. 2. Progesterone๊ด€๋ฅ˜๋กœ ์ทจ์™ธ๋ถ„๋น„๋Š” ์ฆ๊ฐ€ํ•˜์—ฌ secretin์ž๊ทน์— ์˜ํ•œ ์ทจ์•ก๋ถ„๋น„๋Š” 10**-6 M๊ด€๋ฅ˜์‹œ ์ฆ๊ฐ€ํ•˜์˜€๊ณ , amylase๋ถ„๋น„๋Š” CCK์ž๊ทน์— ์˜ํ•œ progesterone 10**-7 M์ฒจ๊ฐ€๋กœ ์ฆ๊ฐ€ํ•˜์˜€๋‹ค. 3. Estrogen 10**-7 M ์กด์žฌํ•˜์— progesterone์„ ๊ด€๋ฅ˜ํ•จ์œผ๋กœ์จ amylase ๋ถ„๋น„ ๋ณ€๋™์€ ๊ด€์ฐฐ๋˜์ง€ ์•Š์•˜์œผ๋ฉฐ, secretin์ž๊ทน์— ์˜ํ•œ ์ทจ์•ก์œ ์ถœ์€ ๋ณ€๋™์ด ์—†์—ˆ๋‹ค. ์ด์ƒ์˜ ๊ฒฐ๊ณผ๋กœ ๋ฏธ๋ฃจ์–ด ๋ณด์•„ estrogen ๋ฐ progesterone๋“ฑ ๋‚œ์†Œ ํ™€๋ชฌ์€ ์ทจ์„ ํฌ์— ์ง์ ‘ ์ž‘์šฉํ•˜์—ฌ, ์ทจ์•ก ๋ฐ ์ทจํšจ์†Œ๋ถ„๋น„๋ฅผ ํ•ญ์ง„์‹œํ‚ค๋ฉฐ ์ทจ์™ธ๋ถ„๋น„์— ๋Œ€ํ•œ progesterone์˜ ํšจ๊ณผ๋Š” estrogen๊ณผ ์ƒ๊ด€์—†์ด ๋‚˜ํƒ€๋‚œ๋‹ค๊ณ  ์ƒ๊ฐํ•œ๋‹ค. Influence of Ovarian Hormones on the Exocrine Secretion in Isolated Cat Pancreas Jae Won choi Department of Medical Science, The Graduate School, Yonsei University (Directed by Professor Kyung Hwan Kim) Regulation of pancreatic exocrine secretion is comprised of a complex interplay between hormonal and nervous systems. It has been claimed that steroid hormones may participate in maintaining the exocrine function of the pancreas. Corticosteroids and ovarian hormones are synthesized from the same precursor, cholesterol, in vivo and they are important regulators of homeostasis. Though the effects of corticosteroids on pancreatic function are not consistant, it is widely accepted that the glucocorticoid inhibits the secretory function whereas mineralocorticoid stimulates. Several studies have suggested that ovarian hormones exert significant influence on the exocrine pancreas. And pancreatic function of exocrine cells may be regulated by estrogen and estrogen-binding protein. Also, it was reported that protesterone increased both the cellular content of amylase and cytoplasmic mRNA of rat tumor cell line AR 42J. In the present study, attempt was made to examine the direct effects of estrogen and progesterone on exocrine function employing saline perfused isolated cat pancreas. Mongrel cats, of both sexes weighing about 1.5Kg , were anesthetized with secobarbital (30mg/kg, ip), then the pancreas was isolated and perfused with Krebs Ringer bicarbonate buffer(KRBB) gassed with 95% 0^^2-5% CO^^2 at the rate of 6 ml/min. Ovarian hormone, estrogen or progesterone was added to the perfusate for 30 minutes. Submaximal dose of secretin was infused to maintain pancreatic flow and cholecystokinin was injected to evoke the enzyme secretion in the presence or absence of ovarian hormones. The results are summarized as fellows. 1. Perfusion of estrogen increased the pancreatic flow as well as CCK-stimulated amylase secretion. 2. CCK-stimulated secretion of amylase was increased by perfusion with progesterone and over 10**-6 M concentration secretin-stimulated pancreatic flow was also increased. 3. The effect of progesterone on the exocrine secretory function was not enhanced or inhibited by background perfusion of estrogen in isolated perfused pancreas. These results suggest that ovarian hormones exert significant influence on the exocrine secretory function, both enzyme and waters of the pancreas and this effect might be exerted by direct effect on the pancreas. [์˜๋ฌธ] Regulation of pancreatic exocrine secretion is comprised of a complex interplay between hormonal and nervous systems. It has been claimed that steroid hormones may participate in maintaining the exocrine function of the pancreas. Corticosteroids and ovarian hormones are synthesized from the same precursor, cholesterol, in vivo and they are important regulators of homeostasis. Though the effects of corticosteroids on pancreatic function are not consistant, it is widely accepted that the glucocorticoid inhibits the secretory function whereas mineralocorticoid stimulates. Several studies have suggested that ovarian hormones exert significant influence on the exocrine pancreas. And pancreatic function of exocrine cells may be regulated by estrogen and estrogen-binding protein. Also, it was reported that protesterone increased both the cellular content of amylase and cytoplasmic mRNA of rat tumor cell line AR 42J. In the present study, attempt was made to examine the direct effects of estrogen and progesterone on exocrine function employing saline perfused isolated cat pancreas. Mongrel cats, of both sexes weighing about 1.5Kg , were anesthetized with secobarbital (30mg/kg, ip), then the pancreas was isolated and perfused with Krebs Ringer bicarbonate buffer(KRBB) gassed with 95% 0^^2-5% CO^^2 at the rate of 6 ml/min. Ovarian hormone, estrogen or progesterone was added to the perfusate for 30 minutes. Submaximal dose of secretin was infused to maintain pancreatic flow and cholecystokinin was injected to evoke the enzyme secretion in the presence or absence of ovarian hormones. The results are summarized as fellows. 1. Perfusion of estrogen increased the pancreatic flow as well as CCK-stimulated amylase secretion. 2. CCK-stimulated secretion of amylase was increased by perfusion with progesterone and over 10**-6 M concentration secretin-stimulated pancreatic flow was also increased. 3. The effect of progesterone on the exocrine secretory function was not enhanced or inhibited by background perfusion of estrogen in isolated perfused pancreas. These results suggest that ovarian hormones exert significant influence on the exocrine secretory function, both enzyme and waters of the pancreas and this effect might be exerted by direct effect on the pancreas.restrictio

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We conducted a two-session observer study on the external test set that radiologists participated without and with the assistance of the model in each session. To evaluate the diagnostic performance of the model and radiologists, we calculated the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), as well as their 95% confidence intervals (CI). Results: Our trained model showed an AUC of 0.984 (95% CI, 0.929โ€“0.999) in the internal test set and 0.791 (95% CI, 0.695โ€“0.868) in the external test set. The model had a sensitivity of 90.6% (95% CI, 0.750โ€“0.980), a specificity of 94.3% (95% CI, 0.843โ€“0.988), a PPV of 90.6% (95% CI, 0.762โ€“0.967), and an NPV of 94.3% (95% CI, 0.850โ€“0.980) for the internal test set. For the external test set, the model had a sensitivity of 68.4% (95% CI, 0.435โ€“0.874), a specificity of 88.2% (95% CI, 0.787โ€“0.944), a PPV of 59.1% (95% CI, 0.421โ€“0.741), and an NPV of 91.8% (95% CI, 0.851โ€“0.956). The AUCs of the radiologists were 0.765 (95% CI, 0.667โ€“0.846) and 0.908 (95% CI, 0.831โ€“0.958) in the first sessions and 0.812 (95% CI, 0.718โ€“0.885) and 0.925 (95% CI, 0.852โ€“0.969), respectively, in the second sessions, but the differences were not statistically significant (Pโ€™s > 0.05). The less-experienced radiologist showed a higher specificity (71.1% to 93.4%, P 0.05). Conclusions: Our study demonstrated a deep learning model for the diagnosis of pediatric skull fracture on plain radiographs, which is the first to date that has succeeded in such a task and may improve the diagnostic performance of inexperienced radiologists.๋ชฉ์ : ๋‹จ์ˆœ ๋ฐฉ์‚ฌ์„  ์˜์ƒ์—์„œ ์†Œ์•„ ๋‘๊ฐœ๊ณจ ๊ณจ์ ˆ์„ ์ง„๋‹จํ•˜๋Š” ๋”ฅ๋Ÿฌ๋‹ ๊ธฐ๋ฐ˜ ๋ชจ๋ธ์„ ๊ฐœ๋ฐœํ•˜๊ณ  ํ‰๊ฐ€ํ•˜๊ณ ์ž ํ•œ๋‹ค. ๋Œ€์ƒ ๋ฐ ๋ฐฉ๋ฒ•: ๋ณธ ํ›„ํ–ฅ์  ๋‹ค๊ธฐ๊ด€ ์—ฐ๊ตฌ๋Š” ๋‘ ๋ณ‘์›์œผ๋กœ๋ถ€ํ„ฐ ๊ตฌ์„ฑ๋œ ๊ฐœ๋ฐœ์šฉ ๋ฐ์ดํ„ฐ๊ตฐ๊ณผ ์ œ3๋ณ‘์›์œผ๋กœ๋ถ€ํ„ฐ ๊ตฌ์„ฑ๋œ ์™ธ๋ถ€ ๊ฒ€์ • ๋ฐ์ดํ„ฐ๊ตฐ์œผ๋กœ ์ด๋ฃจ์–ด์กŒ๋‹ค. ๋‘๋ถ€ ์™ธ์ƒ์œผ๋กœ ๋‚ด์›ํ•˜์˜€๊ณ  ๋‘๊ฐœ๊ณจ ๋‹จ์ˆœ ๋ฐฉ์‚ฌ์„  ์ดฌ์˜์„ ์‹œํ–‰ํ•œ ์†Œ์•„ ํ™˜์ž๋“ค์ด ํฌํ•จ๋˜์—ˆ์œผ๋ฉฐ, ๊ฐ ๋ณ‘์› ๋ณ„ ๋‚ด์› ๋‚ ์งœ ๊ธฐ์ค€์€ ์ƒ์ดํ•˜์˜€๋‹ค. ๊ฐœ๋ฐœ์šฉ ๋ฐ์ดํ„ฐ๊ตฐ์—์„œ๋Š” ๋‹จ์ˆœ ๋ฐฉ์‚ฌ์„  ์†Œ๊ฒฌ์„ ๊ธฐ์ค€์œผ๋กœ ๊ณจ์ ˆ ์—ฌ๋ถ€๋ฅผ ๋ถ„๋ฅ˜ํ•˜์˜€๊ณ , ์™ธ๋ถ€ ๊ฒ€์ • ๋ฐ์ดํ„ฐ๊ตฐ์—์„œ๋Š” ์ „์‚ฐํ™”๋‹จ์ธต์ดฌ์˜ ์†Œ๊ฒฌ์„ ๊ธฐ์ค€์œผ๋กœ ํ•˜์˜€๋‹ค. ๊ฐœ๋ฐœ์šฉ ๋ฐ์ดํ„ฐ๊ตฐ์€ 6:1:2 ๋น„์œจ๋กœ ํ›ˆ๋ จ, ๊ฒ€์ฆ, ๋‚ด๋ถ€ ๊ฒ€์ •๊ตฐ์œผ๋กœ ๋‚˜๋‰˜์–ด์กŒ๋‹ค. ๋”ฅ๋Ÿฌ๋‹ ๋ชจ๋ธ๋กœ ์˜์‹ฌ ๋ณ‘๋ณ€์— ๋Œ€ํ•œ ๊ฒฝ๊ณ„ ์ƒ์ž์™€ ๊ทธ ์ ์ˆ˜๋ฅผ ์ถœ๋ ฅํ•˜๋Š” YOLOv3 ๊ตฌ์กฐ๋ฅผ ์‚ฌ์šฉํ•˜์˜€๋‹ค. ์™ธ๋ถ€ ๊ฒ€์ •๊ตฐ์„ ๋Œ€์ƒ์œผ๋กœ ์˜์ƒ์˜ํ•™๊ณผ ์˜์‚ฌ๊ฐ€ ๋‘๊ฐœ๊ณจ ๊ณจ์ ˆ์„ ํŒ๋…ํ•˜์˜€๋Š”๋ฐ ๋‹จ๋…์œผ๋กœ ํŒ๋…ํ•˜๋Š” ์ฒซ๋ฒˆ์งธ ์„ธ์…˜, ๋ชจ๋ธ์˜ ์˜ˆ์ธก ๊ฒฐ๊ณผ์˜ ๋„์›€์„ ๋ฐ›์œผ๋ฉฐ ํŒ๋…ํ•˜๋Š” ๋‘๋ฒˆ์งธ ์„ธ์…˜์œผ๋กœ ๊ตฌ์„ฑ๋˜์—ˆ๋‹ค. ๋ชจ๋ธ ๋ฐ ์˜์ƒ์˜ํ•™๊ณผ ์˜์‚ฌ์˜ ์ง„๋‹จ ์„ฑ๋Šฅ์„ ํ‰๊ฐ€ํ•˜๊ธฐ ์œ„ํ•ด ์ˆ˜์‹ ์ž ์กฐ์ž‘ ํŠน์„ฑ ๊ณก์„ ํ•˜ ๋ฉด์  (AUC), ๋ฏผ๊ฐ๋„, ํŠน์ด๋„, ์–‘์„ฑ์˜ˆ์ธก๋„ ๋ฐ ์Œ์„ฑ ์˜ˆ์ธก๋„์™€ ๋Œ€์‘๋˜๋Š” 95% ์‹ ๋ขฐ๊ตฌ๊ฐ„ (CI)๋ฅผ ๊ณ„์‚ฐํ•˜์˜€๋‹ค. ๊ฒฐ๊ณผ: ๋ชจ๋ธ์˜ ์ง„๋‹จ๋Šฅ ๋ถ„์„ ๊ฒฐ๊ณผ, ๋‚ด๋ถ€ ๊ฒ€์ •๊ตฐ์—์„œ AUC 0.984 (95% CI, 0.929โ€“0.999), ๊ทธ๋ฆฌ๊ณ  ์™ธ๋ถ€ ๊ฒ€์ •๊ตฐ์—์„œ 0.791 (95% CI, 0.695โ€“0.868)์˜ ๊ฒฐ๊ณผ๋ฅผ ๋ณด์—ฌ์ฃผ์—ˆ๋‹ค. ๋ชจ๋ธ์˜ ๋ฏผ๊ฐ๋„๋Š” ๋‚ด๋ถ€ ๊ฒ€์ •๊ตฐ์—์„œ 90.6% (95% CI, 0.750โ€“0.980), ํŠน์ด๋„๋Š” 94.3% (95% CI, 0.843โ€“0.988), ์–‘์„ฑ์˜ˆ์ธก๋„๋Š” 90.6% (95% CI, 0.762โ€“0.967), ์Œ์„ฑ์˜ˆ์ธก๋„๋Š” 94.3% (95% CI, 0.850โ€“0.980)์œผ๋กœ ๊ณ„์‚ฐ๋˜์—ˆ๋‹ค. ์™ธ๋ถ€ ๊ฒ€์ •๊ตฐ์—์„œ์˜ ๋ชจ๋ธ์˜ ๋ถ„์„ ๊ฒฐ๊ณผ, ๋ฏผ๊ฐ๋„ 68.4% (95% CI, 0.435โ€“0.874), ํŠน์ด๋„ 88.2% (95% CI, 0.787โ€“0.944), ์–‘์„ฑ์˜ˆ์ธก๋„ 59.1% (95% CI, 0.421โ€“0.741), ์Œ์„ฑ์˜ˆ์ธก๋„ 91.8% (95% CI, 0.851โ€“0.956)์˜ ์ง„๋‹จ๋Šฅ์„ ๋ณด์˜€๋‹ค. ์˜์ƒ์˜ํ•™๊ณผ ์˜์‚ฌ์˜ AUC๊ฐ’์€ ์ฒซ๋ฒˆ์งธ ์„ธ์…˜์—์„œ๋Š” 0.765 (95% CI, 0.667โ€“0.846), 0.908 (95% CI, 0.831โ€“0.958)์ด์—ˆ๊ณ , ๋‘๋ฒˆ์งธ ์„ธ์…˜์—์„œ๋Š” ๊ฐ๊ฐ 0.812 (95% CI, 0.718โ€“0.885), 0.925 (95% CI, 0.852โ€“0.969)์ด์—ˆ์œผ๋‚˜ ๊ทธ ์ฐจ์ด๋“ค์€ ๋ชจ๋‘ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜๋ฏธํ•˜์ง€ ์•Š์•˜๋‹ค (Pโ€™s > 0.05). ๊ฒฝํ—˜์ด ์ ์€ ์˜์ƒ์˜ํ•™๊ณผ ์˜์‚ฌ๋Š” ๋ชจ๋ธ์˜ ๋„์›€์„ ๋ฐ›์•˜์„ ๋•Œ ํŠน์ด๋„๊ฐ€ ์œ ์˜๋ฏธํ•˜๊ฒŒ ์ฆ๊ฐ€ํ•˜์˜€๊ณ  (71.1%์—์„œ 93.4%, P 0.05). ๊ฒฐ๋ก : ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๋‹จ์ˆœ ๋ฐฉ์‚ฌ์„  ์˜์ƒ์—์„œ์˜ ์†Œ์•„ ๋‘๊ฐœ๊ณจ ๊ณจ์ ˆ ์ง„๋‹จ์„ ์œ„ํ•œ ๋”ฅ๋Ÿฌ๋‹ ๋ชจ๋ธ์„ ๊ฐœ๋ฐœ ๋ฐ ํ‰๊ฐ€ํ–ˆ๋‹ค. ํ˜„์žฌ๊นŒ์ง€ ๋ฐœํ‘œ๋œ ๊ฐ™์€ ์ฃผ์ œ๋ฅผ ๋‹ค๋ฃฌ ๋”ฅ๋Ÿฌ๋‹ ๊ด€๋ จ ์—ฐ๊ตฌ๊ฐ€ ์—†์–ด, ์ตœ์ดˆ์˜ ์—ฐ๊ตฌ์ž„์— ์˜์˜๊ฐ€ ์žˆ์œผ๋ฉฐ, ๊ฒฝํ—˜์ด ์ ์€ ์˜์ƒ์˜ํ•™๊ณผ ์˜์‚ฌ์˜ ์ง„๋‹จ๋Šฅ์„ ํ–ฅ์ƒ์‹œํ‚ฌ ๊ฐ€๋Šฅ์„ฑ์ด ์žˆ๋‹ค.Table of Contents Introduction 1 Materials and Methods 2 Results 8 Discussion 13 References 19 Abstract in Korean 36Maste

    ์ถฉ๋ถ ๋‹จ์–‘ ์ง€์—ญ์— ๋ฐœ๋‹ฌํ•˜๋Š” ์ฃฝ๋ น ๋‹จ์ธต๋Œ€์˜ ํŠน์„ฑ

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    Thesis (master`s)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์ง€๊ตฌํ™˜๊ฒฝ๊ณผํ•™๋ถ€,2001.Maste
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