119 research outputs found

    ๋ฌด์ต๊ธฐํ˜• ์ „๊ธฐ ์ถ”์ง„ ์ˆ˜์ง ์ด์ฐฉ๋ฅ™๊ธฐ์— ๋Œ€ํ•œ ๋‹คํ•™์ œ ํ•ด์„ ๋ฐ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ํ”„๋ ˆ์ž„์›Œํฌ

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ํ•ญ๊ณต์šฐ์ฃผ๊ณตํ•™๊ณผ, 2023. 2. ์ด๊ด€์ค‘.A wingless-type electric vertical take-off and landing (eVTOL) is one of the representative aircrafts utilized logistics and delivery, search and rescue, military, agriculture, and inspection of structures. For a small unmanned aerial vehicles of the wingless-type eVTOL, a quadrotor is a representative configuration to operate those missions. For a large size of the wingless-type eVTOL, it is an aircraft for urban air mobility service (UAM) specialized for intracity point-to-point due to its advantages such as efficient hover performance, high gust resistance, and relatively low noisiness. The rotating speed of the multiple rotors in the wingless-type eVTOL has to be changed continuously to achieve stable flight. Moreover, the speed and the loaded torque of the motors also continuously change. Therefore, it is necessary to analyze the rotor thrust and torque with respect to the speed of each rotor as assigned by the controller to predict the flight performance of the wingless-type eVTOL. The electric power required by the motors is also necessary to be predicted based on the torque loaded to the motors to maintain the rotating speed. This study suggests a flight simulation framework based on these multidisciplinary analyses including control, rotor aerodynamics, and electric propulsion system analysis. Using the flight simulation framework, it is possible to predict the flight performance of the wingless-type eVTOL for given operating conditions. The flight simulation framework can predict the overall performance required to resist the winds and the corresponding battery energy of a quadrotor. Flight endurance of an industrial quadrotor was examined under light, moderate, and strong breeze modeled by von Kรกrmรกn wind turbulence with Beaufort wind force scale. As a result, it is found that the excess battery energy is increased with ground speed, even under the same wind conditions. As the ground speed increases, the airspeed is increased, led to higher frame drag, position error, pitch angle, and required mechanical power, consequently. Moreover, the quadrotor is not operable beyond a certain wind and ground speed since the required rotational speed of rotors exceeds the speed limit of motors. The simulation framework can also predict the overall performance of a wingless eVTOL for UAM service. Because of its multiple rotors, rotorโ€“rotor interference inevitably affects flight performance, mainly depending on inter-rotor distance and rotor rotation directions. In this case, there is an optimal rotation direction of the multiple rotors to be favorable in actual operation. In this study, it was proposed that a concept of rotor rotation direction that achieves the desirable flight performance in actual operation. The concept is called FRRA (Front rotors Retreating side and Rear rotors Advancing side). It was found that FRRA minimizes thrust loss due to rotor-rotor interference in high-speed forward flight. For a generic mission profile of UAM service, the rotation direction set by FRRA reduces the battery energy consumption of 7 % in comparison to the rotation direction of unfavorable rotor-rotor interference in operation.๋ฌด์ต๊ธฐํ˜• ์ „๊ธฐ ์ถ”์ง„ ์ˆ˜์ง ์ด์ฐฉ๋ฅ™๊ธฐ๋Š” ํƒ๋ฐฐ ๋ฐ ์šด์†ก ์„œ๋น„์Šค, ์ˆ˜์ƒ‰ ๋ฐ ๊ตฌ์กฐ, ๊ตญ๋ฐฉ, ๋†์—…, ๊ตฌ์กฐ๋ฌผ ์ ๊ฒ€๊ณผ ๊ฐ™์€ ๋ถ„์•ผ์—์„œ ๋Œ€ํ‘œ์ ์œผ๋กœ ์ด์šฉ๋˜๊ณ  ์žˆ๋Š” ํ•ญ๊ณต๊ธฐ์ด๋‹ค. ์ฟผ๋“œ๋กœํ„ฐ๋Š” ์ด๋Ÿฌํ•œ ์ž„๋ฌด๋ฅผ ์ˆ˜ํ–‰ํ•˜๊ธฐ ์œ„ํ•œ ๋Œ€ํ‘œ์ ์ธ ์†Œํ˜• ๋ฌด์ต๊ธฐํ˜• ์ „๊ธฐ ์ถ”์ง„ ์ˆ˜์ง ์ด์ฐฉ๋ฅ™๊ธฐ์ด๋‹ค. ๋Œ€ํ˜• ๋ฌด์ต๊ธฐํ˜• ์ „๊ธฐ ์ถ”์ง„ ์ˆ˜์ง ์ด์ฐฉ๋ฅ™๊ธฐ๋Š” ํšจ์œจ์ ์ธ ์ œ์ž๋ฆฌ ๋น„ํ–‰ ์„ฑ๋Šฅ, ๋†’์€ ๋‚ดํ’์„ฑ, ๋‚ฎ์€ ์†Œ์Œ ๊ณตํ•ด์™€ ๊ฐ™์€ ํŠน์ง•์œผ๋กœ ์ธํ•ด ๋„์‹ฌ ๋‚ด ์šดํ•ญ ์„œ๋น„์Šค๋ฅผ ์œ„ํ•œ ํ•ญ๊ณต๊ธฐ๋กœ ํ™œ์šฉ๋˜๊ณ  ์žˆ๋‹ค. ๋ฌด์ต๊ธฐํ˜• ์ „๊ธฐ ์ถ”์ง„ ์ˆ˜์ง ์ด์ฐฉ๋ฅ™๊ธฐ์˜ ์—ฌ๋Ÿฌ ํšŒ์ „ ๋‚ ๊ฐœ๋Š” ์•ˆ์ •๋œ ๋น„ํ–‰์„ ์œ ์ง€ํ•˜๊ธฐ ์œ„ํ•ด, ์ง€์†ํ•ด์„œ ํšŒ์ „ ์†๋„๋ฅผ ๋ณ€ํ™”์‹œํ‚จ๋‹ค. ๊ฒŒ๋‹ค๊ฐ€, ๋ชจํ„ฐ์˜ ํšŒ์ „ ์†๋„์™€ ๋ถ€ํ•˜๋˜๋Š” ํ† ํฌ ๋˜ํ•œ ์ง€์†์ ์œผ๋กœ ๋ณ€ํ™”ํ•œ๋‹ค. ๊ทธ๋Ÿฌ๋ฏ€๋กœ ๋ฌด์ต๊ธฐํ˜• ์ „๊ธฐ ์ถ”์ง„ ์ˆ˜์ง ์ด์ฐฉ๋ฅ™๊ธฐ์˜ ๋น„ํ–‰ ์„ฑ๋Šฅ์„ ์˜ˆ์ธกํ•˜๊ธฐ ์œ„ํ•ด, ์ œ์–ด๊ธฐ์—์„œ ๊ฐ ํšŒ์ „ ๋‚ ๊ฐœ์— ๋ถ€์—ฌ๋œ ํšŒ์ „ ์†๋„์— ๋”ฐ๋ฅธ ์ถ”๋ ฅ ๋ฐ ํ† ํฌ๋ฅผ ํ•ด์„ํ•ด์•ผ ํ•œ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์ด๋Ÿฌํ•œ ํšŒ์ „ ๋‚ ๊ฐœ์˜ ํšŒ์ „ ์†๋„๋ฅผ ์œ ์ง€ํ•˜๊ธฐ ์œ„ํ•ด ๋ชจํ„ฐ์— ๋ถ€ํ•˜ ๋˜๋Š” ํ† ํฌ๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ, ๋ชจํ„ฐ์—์„œ ์š”๊ตฌ๋˜๋Š” ์ „๋ ฅ์„ ์˜ˆ์ธกํ•ด์•ผ ํ•œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ œ์–ด, ํšŒ์ „ ๋‚ ๊ฐœ ๊ณต๋ ฅ, ์ „๊ธฐ ์ถ”์ง„ ์‹œ์Šคํ…œ ํ•ด์„์ด ํฌํ•จ๋œ ๋‹คํ•™์ œ ํ•ด์„ ๊ธฐ๋ฐ˜์˜ ๋น„ํ–‰ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ํ”„๋ ˆ์ž„์›Œํฌ๋ฅผ ์ œ์‹œํ•œ๋‹ค. ๋น„ํ–‰ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ํ”„๋ ˆ์ž„์›Œํฌ๋ฅผ ์ด์šฉํ•˜์—ฌ, ์‹ค์ œ ์šด์šฉ ํ™˜๊ฒฝ์—์„œ์˜ ๋ฌด์ต๊ธฐํ˜• ์ „๊ธฐ ์ถ”์ง„ ์ˆ˜์ง ์ด์ฐฉ๋ฅ™๊ธฐ ๋น„ํ–‰ ์„ฑ๋Šฅ์„ ์˜ˆ์ธกํ•  ์ˆ˜ ์žˆ๋‹ค. ๋น„ํ–‰ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ํ”„๋ ˆ์ž„์›Œํฌ๋ฅผ ํ™œ์šฉํ•˜์—ฌ ์ฟผ๋“œ๋กœํ„ฐ์— ๋Œ€ํ•ด ์™ธํ’์„ ์ €ํ•ญํ•˜๊ธฐ ์œ„ํ•œ ๋น„ํ–‰ ์ „๋ฐ˜์ ์ธ ์„ฑ๋Šฅ๊ณผ ๊ทธ์— ๋”ฐ๋ฅธ ๋ฐฐํ„ฐ๋ฆฌ ์—๋„ˆ์ง€ ์†Œ๋ชจ๋ฅผ ์˜ˆ์ธกํ•˜์˜€๋‹ค. Von Kรกrmรกn ์™ธํ’ ๋‚œ๋ฅ˜์™€ Beaufort ์™ธํ’ ๊ฐ•๋„ ๋“ฑ๊ธ‰์„ ํ™œ์šฉํ•˜์—ฌ ๋‚จ์‹ค๋ฐ”๋žŒ, ๊ฑด๋“ค๋ฐ”๋žŒ, ๋œ๋ฐ”๋žŒ ํ™˜๊ฒฝ์— ๋Œ€ํ•œ ์‚ฐ์—…์šฉ ์ฟผ๋“œ๋กœํ„ฐ์˜ ๋น„ํ–‰์‹œ๊ฐ„์„ ์กฐ์‚ฌํ•˜์˜€๋‹ค. ๊ทธ ๊ฒฐ๊ณผ, ๋™์ผํ•œ ์™ธํ’ ํ™˜๊ฒฝ์ผ์ง€๋ผ๋„ ์ „์ง„ ๋น„ํ–‰ ์†๋„๊ฐ€ ์ฆ๊ฐ€ํ• ์ˆ˜๋ก ๋ฐฐํ„ฐ๋ฆฌ ์†Œ์š” ์—๋„ˆ์ง€๊ฐ€ ์ฆ๊ฐ€ํ•œ๋‹ค๋Š” ๊ฒƒ์„ ๋ฐํ˜”๋‹ค. ์ „์ง„ ๋น„ํ–‰ ์†๋„์˜ ์ฆ๊ฐ€๋กœ ์ธํ•ด ์ฟผ๋“œ๋กœํ„ฐ์— ์œ ์ž…๋˜๋Š” ์œ ์†์ด ์ฆ๊ฐ€ํ•˜์—ฌ, ๋™์ฒด ํ•ญ๋ ฅ, ์œ„์น˜ ์˜ค์ฐจ, ๊ธฐ์ˆ˜ ๋‚ด๋ฆผ ๊ฐ๋„, ์š”๊ตฌ ๊ธฐ๊ณ„ ๋™๋ ฅ์ด ์ฆ๊ฐ€ํ•˜์˜€๋‹ค. ๊ทธ๋ฆฌ๊ณ  ํŠน์ • ์™ธํ’ ์†๋„์™€ ์ „์ง„ ์†๋„ ์ด์ƒ์—์„œ์˜ ์ฟผ๋“œ๋กœํ„ฐ๋Š” ์š”๊ตฌ๋˜๋Š” ํšŒ์ „ ๋‚ ๊ฐœ์˜ ํšŒ์ „ ์†๋„๊ฐ€ ๋ชจํ„ฐ์˜ ํšŒ์ „ ์†๋„์˜ ํ•œ๊ณ„๋ณด๋‹ค ๋†’์œผ๋ฏ€๋กœ ๋น„ํ–‰ํ•  ์ˆ˜ ์—†์—ˆ๋‹ค. ๋˜ํ•œ, ๋น„ํ–‰ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ํ”„๋ ˆ์ž„์›Œํฌ๋ฅผ ํ™œ์šฉํ•˜์—ฌ ๋„์‹ฌ ์šดํ•ญ ์„œ๋น„์Šค์šฉ ๋ฌด์ต๊ธฐํ˜• ์ „๊ธฐ ์ถ”์ง„ ์ˆ˜์ง ์ด์ฐฉ๋ฅ™๊ธฐ์˜ ์ „๋ฐ˜์ ์ธ ๋น„ํ–‰ ์„ฑ๋Šฅ์„ ์˜ˆ์ธกํ•˜์˜€๋‹ค. ์—ฌ๋Ÿฌ ํšŒ์ „ ๋‚ ๊ฐœ์˜ ํŠน์ง•์œผ๋กœ ์ธํ•ด, ํšŒ์ „ ๋‚ ๊ฐœ ๊ฐ„ ๊ฑฐ๋ฆฌ์™€ ํšŒ์ „ ๋‚ ๊ฐœ์˜ ํšŒ์ „ ๋ฐฉํ–ฅ์— ๋”ฐ๋ผ ํšŒ์ „ ๋‚ ๊ฐœ ๊ฐ„ ๊ฐ„์„ญํšจ๊ณผ๊ฐ€ ํ•„์—ฐ์ ์œผ๋กœ ๋น„ํ–‰ ์„ฑ๋Šฅ์— ์˜ํ–ฅ์„ ๋ฏธ์นœ๋‹ค. ์ด๋•Œ, ์šด์šฉ์— ์œ ๋ฆฌํ•œ ์ตœ์ ์˜ ํšŒ์ „ ๋‚ ๊ฐœ ํšŒ์ „ ๋ฐฉํ–ฅ์ด ์กด์žฌํ•œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ ์‹ค์ œ ์šด์šฉ์—์„œ ๋ฐ”๋žŒ์งํ•œ ๋น„ํ–‰ ์„ฑ๋Šฅ์„ ๋ฐœํœ˜ํ•˜๋Š” ํšŒ์ „ ๋‚ ๊ฐœ์˜ ํšŒ์ „ ๋ฐฉํ–ฅ์— ๋Œ€ํ•œ ๊ฐœ๋…์ธ FRRA๋ฅผ ์ œ์‹œํ•˜์˜€๋‹ค. FRRA๋Š” ์ „๋ฐฉ ๋กœํ„ฐ์˜ ํ›„ํ‡ด ์ธก๊ณผ ํ›„๋ฐฉ ๋กœํ„ฐ์˜ ์ „์ง„ ์ธก์ด ์ผ์ง์„ ์œผ๋กœ ์ •๋ ฌ๋œ ์ƒํƒœ์˜ ํšŒ์ „ ๋ฐฉํ–ฅ์ด๋‹ค. FRRA ํšŒ์ „ ๋ฐฉํ–ฅ์€ ๊ณ ์† ์ „์ง„ ๋น„ํ–‰์—์„œ ํšŒ์ „ ๋‚ ๊ฐœ ๊ฐ„ ๊ฐ„์„ญํšจ๊ณผ๋กœ ์ธํ•œ ์ถ”๋ ฅ ์†์‹ค์ด ์ตœ์†Œํ™”๋œ๋‹ค. ํšŒ์ „ ๋‚ ๊ฐœ ๊ฐ„ ๊ฐ„์„ญํšจ๊ณผ๋กœ ์ธํ•ด ๋ถˆ๋ฆฌํ•œ ๋น„ํ–‰ ์„ฑ๋Šฅ์„ ๊ฐ€์ง€๋Š” ํšŒ์ „ ๋ฐฉํ–ฅ ๋Œ€๋น„ FRRA ํšŒ์ „ ๋ฐฉํ–ฅ์€ ๋„์‹ฌ ํ•ญ๊ณต ๊ตํ†ต ์„œ๋น„์Šค์— ๋Œ€ํ•œ ์ผ๋ฐ˜์ ์ธ ์šด์šฉ์—์„œ ๋ฐฐํ„ฐ๋ฆฌ ์†Œ๋ชจ์œจ์ด 7% ์ •๋„ ๊ฐ์†Œํ•˜์˜€๋‹ค.Chapter 1. Introduction 1 1.1 Overview of wingless-type eVTOL 1 1.2 Previous studies about wingless-type eVTOL 6 1.2.1 Multidisciplinary analysis of control, aerodynamic, and EPS 6 1.2.2 External wind of wingless-type eVTOLs for small UAVs 9 1.2.3 Rotor-rotor interference of wingless-type eVTOLs for UAM 10 1.3 Motivation and scope of the dissertation 12 Chapter 2. Simulation Framework 16 2.1 Layout and analysis modules in simulation framework 16 2.1.1 Cascade PID control module 19 2.1.1 Aerodynamic analysis module 24 2.1.2 Electric propulsion system analysis module 30 2.1.3 6-DOF dynamics analysis module 33 2.2 Add-on modules for actual operation 37 2.2.1 Wind turbulence module 37 2.2.2 Rotor-rotor interference module 39 Chapter 3. Validation of Simulation Framework 44 3.1 Static thrust and torque on a single rotor test 44 3.2 Wind resistance test 46 3.3 Rotor-rotor interference of tandem rotors 52 3.4 Rotor-rotor interaction of a quadrotor in CFD 54 3.5 Investigation of rotor-rotor interference with respect to rotation directions in a quadrotor 58 Chapter 4. Flight Performance of Quadrotor under Wind Turbulence 65 4.1 Flight conditions 65 4.2 Wind turbulence conditions 66 4.3 Simulation results 69 Chapter 5. Flight Performance of Wingless-type eVTOL for UAM Service with Respect to the Rotor Rotation Directions 78 5.1 Hypothetical model of a wingless-type eVTOL for UAM service 78 5.2 Rotor rotation directions and aerodynamic performance 83 5.2.1 Hover flight 86 5.2.2 Forward flight at 100 km/h 88 5.2.3 Forward flight in the airspeed of 100 km/h with 30 yaw angle 93 5.3 Surrogate models including the rotor-rotor interaction effect 96 5.4 Simulation results 99 Chapter 6. Conclusion 112 6.1 Summary 112 6.2 Originalities of the dissertation 113 6.3 Future works 116 Appendix 118 References 127 ๊ตญ๋ฌธ ์ดˆ๋ก 144๋ฐ•

    ์ด์งˆ์  ๋„์‹œ ๊ณต์›์—์„œ์˜ ํƒ„์†Œ์™€ ์—๋„ˆ์ง€ ํ”Œ๋Ÿญ์Šค ๋ชจ๋ธ๋ง

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ƒํƒœ์กฐ๊ฒฝยท์ง€์—ญ์‹œ์Šคํ…œ๊ณตํ•™๋ถ€, 2015. 2. ๋ฅ˜์˜๋ ฌ.๋„์‹œ ๊ณต์›์€ ๋„์‹œ ์ง€์—ญ ๋‚ด์—์„œ์˜ ์ƒ๋‹นํ•œ ๋น„์œจ์„ ์ฐจ์ง€ํ•˜์ง€๋งŒ, ๊ธฐ์กด์˜ ๋„์‹œ ๊ด€๋ จ ์—ฐ๊ตฌ๋“ค์€ ๋„์‹œ ๊ณต์› ์‹์ƒ์˜ ํƒ„์†Œ ํก์ˆ˜์— ๋Œ€ํ•ด์„œ๋Š” ์—ฐ๊ตฌ๊ฐ€ ๋งŽ์ด ์ด๋ค„์ง€์ง€ ์•Š์•˜๋‹ค. ์ผ๋ฐ˜์ ์ธ ๋„์‹œ ๊ณต์›์€ ๋‹ค์–‘ํ•œ ์ˆ˜์ข…์„ ํฌ๊ด„ํ•˜๊ณ , ๊ฐœ๋ฐฉ์  ์ˆ˜๊ด€๋ถ€์˜ ๋ฐฐ์น˜๋ฅผ ํ†ตํ•ด ์‹œ๊ฐ„์ , ๊ณต๊ฐ„์ ์œผ๋กœ ๋งค์šฐ ๋ณตํ•ฉ์ ์ธ ๊ฒฝ๊ด€์„ ๊ตฌ์„ฑํ•œ๋‹ค. ๋”ฐ๋ผ์„œ, ๋„์‹œ ๊ณต์›์—์„œ์˜ ๊ด‘ํ•ฉ์„ฑ์„ ๋ณด๋‹ค ์ž˜ ์ดํ•ดํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ๊ด‘ํ•ฉ์„ฑ ๋งค๊ฐœ๋ณ€์ˆ˜์™€ ์ˆ˜๊ด€ ๊ตฌ์กฐ ๋ณ€์ˆ˜์˜ ๊ณต๊ฐ„์ , ์‹œ๊ฐ„์  ์ฐจ์ด๋ฅผ ๊ด€์ธกํ•˜๋Š” ๊ฒƒ์ด ํ•„์ˆ˜์ ์ด๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์„œ์šธ ์ˆฒ ๊ณต์›์„ ๋Œ€์ƒ์œผ๋กœ, ๋‘ ๊ฐœ์˜ ํ•ต์‹ฌ์ ์ธ ๊ด‘ํ•ฉ์„ฑ ๋งค๊ฐœ๋ณ€์ˆ˜ (์ตœ๋Œ€ ์นด๋ฅด๋ณต์‹œํ™”์œจ๊ณผ ์ตœ๋Œ€ ์ „์ž ์ „๋‹ฌ๋ฅ ์„ ๋‚˜ํƒ€๋‚ด๋Š” Vcmax ์™€ Jmax) ์™€ ์—ฝ๋ฉด์ ์ง€์ˆ˜์˜ ๊ณ„์ ˆ์ , ๊ณต๊ฐ„์  ์ฐจ์ด๋ฅผ ๋ณด์ธ๋‹ค. ์ตœ๋Œ€ ์„ฑ์žฅ ์‹œ๊ธฐ์— 10๊ฐœ์˜ ์ˆ˜์ข… ๊ฐ„์— Vcmax ์™€ Jmax ๋Š” ๊ฐ๊ฐ 8๋ฐฐ, 4๋ฐฐ์˜ ์ฐจ์ด๋ฅผ ๋ณด์˜€๋‹ค. ๊ณ„์ ˆ์ ์œผ๋กœ๋Š” ๋‘ ๋Œ€ํ‘œ ์ˆ˜์ข…์ธ, ๋Šํ‹ฐ๋‚˜๋ฌด์™€ ๋ฒš๋‚˜๋ฌด๊ฐ€ Vcmax ์—์„œ๋Š” ๊ฐ๊ฐ 3๋ฐฐ, 5๋ฐฐ์˜ ์ฐจ์ด๋ฅผ, Jmax ์—์„œ๋Š” 2๋ฐฐ, 5๋ฐฐ์˜ ์ฐจ์ด๋ฅผ ๋ณด์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ๋˜ํ•œ ์žŽ์˜ ์งˆ์†Œ ํ•จ๋Ÿ‰์„ ํ†ตํ•ด ๋‘ ๋งค๊ฐœ๋ณ€์ˆ˜ ์ถ”์ •์ด ๊ฐ€๋Šฅํ•œ ์ง€๋ฅผ ํ‰๊ฐ€ํ–ˆ๊ณ , ์ตœ๋Œ€ ์„ฑ์žฅ๊ธฐ์˜ 10๊ฐœ ์ˆ˜์ข… ๋Œ€์ƒ์˜ ๊ด€์ธก์ž๋ฃŒ์—์„œ๋Š” ์งˆ์†Œ ํ•จ๋Ÿ‰๊ณผ ๋‘ ๋งค๊ฐœ ๋ณ€์ˆ˜ ์‚ฌ์ด์—์„œ์˜ ์ƒ๋‹นํ•œ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ํ™•์ธํ–ˆ์œผ๋‚˜, ๋‘ ์ˆ˜์ข…์˜ ์—ฌ๋Ÿฌ ๊ณ„์ ˆ ๊ฐ„ ๊ด€์ธก์ž๋ฃŒ๋ฅผ ๋ถ„์„ํ•œ ๊ฒฐ๊ณผ์—์„œ๋Š” ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ํŠน์ • ์ง€์„ ์ˆ˜ ์—†์—ˆ๋‹ค. ์—ฝ๋ฉด์  ์ง€์ˆ˜๋Š” ํ˜„์žฅ ๊ด€์ธก๊ณผ ์œ„์„ฑ ์›๊ฒฉ ํƒ์‚ฌ ์˜์ƒ์„ ํ†ตํ•ด ๊ณ„์‚ฐํ–ˆ์œผ๋ฉฐ, ์‹œ๊ฐ„์ , ๊ณต๊ฐ„์ ์œผ๋กœ ๋น„์ •๊ทœ๋ถ„ํฌ๋ฅผ ๋ณด์ด๋ฉฐ ํฐ ์ฐจ์ด๋ฅผ ๋‚˜ํƒ€๋ƒˆ๋‹ค. ์ •๊ตํ•˜๊ฒŒ ๋„์‹œ ๊ณต์› ๋‚ด ๋ณตํ•ฉ์ ์ธ ๊ตฌ์กฐ์  ํŠน์„ฑ์„ ๋ฐ˜์˜ํ•œ 3์ฐจ์› ๋ชจ๋ธ์€ ํƒ„์†Œ์™€ ์—๋„ˆ์ง€ ํ”Œ๋Ÿญ์Šค๋ฅผ ๋น„๊ต์  ์ •ํ™•ํžˆ ์ถ”์ •ํ–ˆ๋‹ค. ๋˜ํ•œ, ๊ฐ€์ƒ ์‹œ๋‚˜๋ฆฌ์˜ค๋ฅผ ํ™œ์šฉํ•œ ๋ชจ๋ธ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์€ ์ˆ˜๋ชฉ์˜ ๋ถ„ํฌ์™€ ๊ฐœ๋ณ„ ์ˆ˜๊ด€์˜ ํฌ๊ธฐ์— ๋”ฐ๋ฅธ ํšจ๊ณผ๋ฅผ ๋ช…ํ™•ํžˆ ๋ณด์—ฌ์ฃผ์—ˆ๋‹ค. ์ˆ˜๋ชฉ ๋ถ„ํฌ ์ฐจ์ด๋Š” ํƒ„์†Œ ๋ฐ ์—๋„ˆ์ง€ ํ”Œ๋Ÿญ์Šค ๊ฒฐ๊ณผ์—์„œ ์ตœ๋Œ€ 3 % ์˜ ์ฐจ์ด๋งŒ์„ ๋ณด์˜€๊ณ , ๋ฐ˜๋ฉด์— ๊ฐœ๋ณ„ ์ˆ˜๊ด€์˜ ํฌ๊ธฐ ์ฐจ์ด๋Š” ์ตœ๋Œ€ 40% ์˜ ํฐ ์ฐจ์ด๋ฅผ ๋ณด์˜€๋‹ค. ๋ณธ ๊ฒฐ๊ณผ๋Š” ๊ฐ๊ฐ์˜ ์š”์†Œ๊ฐ€ ํƒ„์†Œ์ˆ˜์ง€ ๋ฐ ์—๋„ˆ์ง€ ๋ถ„ํ• ์— ๋ฏธ์น  ์ˆ˜ ์žˆ๋Š” ํšจ๊ณผ๋ฅผ ํ‰๊ฐ€ํ•  ์ˆ˜ ์žˆ๋Š” ๋„๊ตฌ์ž„์„ ์‹œ์‚ฌํ•œ๋‹ค. ์œ„์—์„œ ์ œ์‹œ๋œ ๋ณธ ๋…ผ๋ฌธ์˜ ๊ฒฐ๊ณผ๋“ค์€ ์ •ํ™•ํ•œ ๊ด‘ํ•ฉ์„ฑ ์ถ”์ •์„ ์œ„ํ•ด ๊ด‘ํ•ฉ์„ฑ ๋งค๊ฐœ๋ณ€์ˆ˜ ๋ฐ ์—ฝ๋ฉด์  ์ง€์ˆ˜์˜ ๊ณต๊ฐ„์ , ์‹œ๊ฐ„์  ๋ณ€์ด๋ฅผ ๊ณ ๋ คํ•จ์ด ์ค‘์š”ํ•จ์„ ๋ถ€๊ฐ์‹œํ‚ฌ ๋ฟ ์•„๋‹ˆ๋ผ, ๊ณต์› ์„ค๊ณ„์•ˆ ํ‰๊ฐ€ ํ”Œ๋žซํผ์œผ๋กœ์„œ์˜ 3์ฐจ์› ๋ชจ๋ธ๋ง์˜ ์ž ์žฌ์  ์—ญํ• ์„ ์‹œ์‚ฌํ•œ๋‹ค.Parks account for a large proportion of green spaces in urban regions, but most previous studies have focused on the values of recreational services in urban parksโ€”carbon uptake by plants in urban parks has been studied less extensively. Urban parks typically form complex landscapes in space and time by integrating multiple species with open canopies. Thus, to better understand canopy photosynthesis in urban park, measuring spatial and temporal variations in photosynthetic parameters and canopy structural variables is essential. Here, we report seasonal and spatial variations in two key photosynthetic parameters (Vcmax and Jmax which are the maximum rates of carboxylation and electron transport, respectively) and leaf area index (LAI) in Seoul Forest Park. During the peak growing season, we found an eightfold difference (20 to 149 ฮผmol m-2 s-1) and fourfold difference (38 to 141 ฮผmol mโ€“2 sโ€“1) in Vcmax and Jmax, respectively, across 10 species. Over the seasons, two woody species (Zelkova serrata and Prunus yedoensis Matsum) respectively showed three- to fivefold differences in Vcmax and two- to fivefold differences in Jmax. We evaluated whether leaf nitrogen contents could predict Vcmax and Jmax, and found significant correlations among the three variables during the peak growing season across 10 species, but no significant correlations among them over the seasons in the two woody species. LAI computed using in- situ observations and satellite remote-sensing imagery showed a non-normal distribution with marked variation during the growing season. A sophisticated 3 dimensional model, which reflects complexity of vegetation structure in the park, well predicted carbon and energy fluxes for a day. Moreover, the model simulation with simplistic virtual scenarios clearly showed the effects of difference in tree distribution and tree size on carbon and energy fluxes (~ 3 % and ~ 40 %, respectively). These results highlight not only necessity of consideration of spatial and temporal variability in photosynthetic parameters and LAI for accurate estimation of canopy photosynthesis in urban parks, but also an important role of individual tree based model as a potential park design evaluating platform.CONTENTS ABSTRACT CONTENTS LIST OF TABLES LIST OF FIGURES I. INTRODUCTION II. MATERIALS AND METHODS 1. Site 2. Photosynthetic parameters and leaf traits measurement 3. Leaf area index measurement 3.1. Plot design 3.2. Digital cover photography 4. Satellite remote-sensing data processing 5. Model simulation 5.1. Model description 5.2. Collecting crown data 5.3. Flux measurement 5.4. Simulations with virtual scenarios III. RESULT AND DISCUSSION 1. To what extent do photosynthetic parameters vary spatially during the peak growing season and temporally across the seasons? 2. Can Vcmax and Jmax be estimated indirectly from leaf traits data? 3. To what extent does the LAI vary across different land cover types over the seasons? 4. Can park design strategy affect carbon and energy fluxes? 5. Broader implications for future urban park design IV. SUMMARY AND CONCLUSIONS REFERENCE ABSTRACT (Korean) ACKNOWLEDGEMENTMaste

    An Iterative Detection Algorithm of Bootstrap Signals for ATSC 3.0 System

    Get PDF
    ๋ณธ ํ•™์œ„๋…ผ๋ฌธ์—์„œ๋Š” ATSC 3.0 ์‹œ์Šคํ…œ์„ ์œ„ํ•œ ๋ถ€ํŠธ์ŠคํŠธ๋žฉ ์‹ ํ˜ธ์˜ ๋ฐ˜๋ณต ๊ฒ€์ถœ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ œ์•ˆํ•œ๋‹ค. ๋ถ€ํŠธ์ŠคํŠธ๋žฉ ์‹ ํ˜ธ์— ํฌํ•จ๋œ ์‹œ๊ทธ๋„๋ง ์ •๋ณด๋ฅผ ๊ฒ€์ถœํ•˜๊ธฐ ์œ„ํ•œ ์ตœ๋Œ€์šฐ๋„ ๊ฒฐ์ • ๊ทœ์น™์„ ์œ ๋„ํ•˜์˜€๊ณ , ๊ฒ€์ถœ ์„ฑ๋Šฅ์„ ํ–ฅ์ƒ์‹œํ‚ค๊ธฐ ์œ„ํ•œ ๋ฐ˜๋ณต ๊ฒ€์ถœ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ œ์•ˆํ•œ๋‹ค. ์ œ์•ˆํ•˜๋Š” ๊ฒ€์ถœ ์•Œ๊ณ ๋ฆฌ์ฆ˜์€ ์—ฐ์†ํ•˜๋Š” ์ด์ „ ๋‘ ๊ฐœ์˜ ๋ถ€ํŠธ์ŠคํŠธ๋žฉ ์‹ฌ๋ณผ์— ๋Œ€ํ•œ ์ฑ„๋„ ์ถ”์ • ๊ฐ’๋“ค์„ ๋ฐ˜๋ณต์ ์œผ๋กœ ํ‰๊ท ํ•œ๋‹ค. ๋˜ํ•œ, ๋ณธ ํ•™์œ„๋…ผ๋ฌธ์—์„œ๋Š” ์ œ์•ˆํ•˜๋Š” ๊ฒ€์ถœ ์•Œ๊ณ ๋ฆฌ์ฆ˜์˜ ์ˆ˜์‹ ๊ธฐ ๋ณต์žก๋„๋ฅผ ๋ถ„์„ํ•˜์˜€๋‹ค. ์ „์‚ฐ ์‹คํ—˜ ๊ฒฐ๊ณผ๋Š” ๊ธฐ์กด ๋ฐฉ๋ฒ•๊ณผ ๋น„๊ตํ–ˆ์„ ๋•Œ ํ”„๋ ˆ์ž„ ์˜ค์œจ์ด ์ธ ๊ฒฝ์šฐ ์•ฝ 2 dB์˜ ์‹ ํ˜ธ ๋Œ€ ์žก์Œ๋น„ ์ด๋“์„ ์–ป์„ ์ˆ˜ ์žˆ์Œ์„ ๋ณด์—ฌ์ค€๋‹ค. ๋˜ํ•œ, ๊ฒ€์ถœ ์„ฑ๋Šฅ๊ณผ ๋ณต์žก๋„๋ฅผ ๊ณ ๋ คํ•œ ์ตœ์ ์˜ ๋ฐ˜๋ณต ํšŸ์ˆ˜๋ฅผ ์ œ์‹œํ•˜์˜€๋‹ค.|In this thesis, an iterative detection algorithm of bootstrap signals for ATSC 3.0 system is proposed. A maximum-likelihood decision rule to detect the signaling information included in the bootstrap signals is derived and the iterative detection algorithm to improve the detection performance is described. The proposed detection algorithm iteratively averages the channel estimates for the two consecutive symbols. Furthermore, this thesis analyzes the computational complexity of the proposed detection algorithm. The simulation results show that the proposed detection algorithm can obtain the signal-to-noise ratio gain of approximately 2.0 dB at frame error rate of compared to the conventional detection scheme. Also, this thesis presents the sufficient number of iterations to provide a good performance-complexity trade-off.1. ์„œ ๋ก  1 2. ATSC 3.0 ๋ฐ ๋ถ€ํŠธ์ŠคํŠธ๋žฉ ์‹ ํ˜ธ์˜ ๊ตฌ์กฐ 3 2.1 ATSC 3.0 ๊ฐœ์š” 3 2.2 ๋ถ€ํŠธ์ŠคํŠธ๋žฉ ์‹ ํ˜ธ์˜ ๊ตฌ์กฐ 5 2.2.1 ๋ถ€ํŠธ์ŠคํŠธ๋žฉ ์‹ ํ˜ธ ์ƒ์„ฑ 5 2.2.2 ๋ถ€ํŠธ์ŠคํŠธ๋žฉ ์‹ ํ˜ธ์˜ ์ˆœํ™˜ ์ด๋™ 11 2.2.3 ๋ถ€ํŠธ์ŠคํŠธ๋žฉ ์‹ ํ˜ธ์˜ ์‹œ๊ฐ„ ์˜์—ญ ๊ตฌ์กฐ 14 2.2.4 ๋ถ€ํŠธ์ŠคํŠธ๋žฉ ์‹ ํ˜ธ์˜ ์‹œ๊ทธ๋„๋ง ๊ตฌ์กฐ 15 3. ๋ถ€ํŠธ์ŠคํŠธ๋žฉ ๊ฒ€์ถœ๊ธฐ 19 3.1 ๋ถ€ํŠธ์ŠคํŠธ๋žฉ ์ˆ˜์‹ ๊ธฐ 19 3.2 ๋ถ€ํŠธ์ŠคํŠธ๋žฉ ์‹ ํ˜ธ ๊ฒ€์ถœ์„ ์œ„ํ•œ ์ตœ๋Œ€์šฐ๋„ ๊ฒฐ์ • ๊ทœ์น™ 20 4. ๋ถ€ํŠธ์ŠคํŠธ๋žฉ ๊ฒ€์ถœ์„ ์œ„ํ•œ ์ œ์•ˆํ•˜๋Š” ๋ฐ˜๋ณต ๊ฒ€์ถœ ์•Œ๊ณ ๋ฆฌ์ฆ˜ 24 4.1 ์ฑ„๋„ ์ถ”์ • 24 4.2 ์ˆœ๋ฐฉํ–ฅ ๊ฒ€์ถœ 24 4.3 ์—ญ๋ฐฉํ–ฅ ๊ฒ€์ถœ์„ ์œ„ํ•œ ์ตœ๋Œ€์šฐ๋„ ๊ฒฐ์ • ๊ทœ์น™ 27 4.4 ๋ฐ˜๋ณต ๊ฒ€์ถœ 29 5. ๋ณต์žก๋„ ๋ถ„์„ 33 6. ์ „์‚ฐ ์‹คํ—˜ ๊ฒฐ๊ณผ 35 7. ๊ฒฐ๋ก  52 ์ฐธ๊ณ ๋ฌธํ—Œ 53 ๊ฐ์‚ฌ์˜ ๊ธ€ 57Maste

    ๊ทผ์นจ์œค์„ฑ ๋ฐฉ๊ด‘์•”์— ๋Œ€ํ•œ ์ˆ˜์ˆ  ํ›„ ๋ณด์กฐ ํ•ญ์•”์น˜๋ฃŒ: ์ฒด๊ณ„์  ๋ฌธํ—Œ๊ณ ์ฐฐ ๋ฐ ๋ฌด์ž‘์œ„๋ฐฐ์ • ์ž„์ƒ์‹œํ—˜๋“ค์— ๋Œ€ํ•œ ๋„คํŠธ์›Œํฌ ๋ฉ”ํƒ€๋ถ„์„

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์˜๊ณผ๋Œ€ํ•™ ์˜ํ•™๊ณผ, 2018. 2. ๊ตฌ์žํ˜„.95% CI, 0.68-0.92) than RC alone. In the network meta-analysis, the gemcitabine/cisplatin/paclitaxel (GCP) combination was the only ACH regimen associated with significant improvement in both the PFS (HR, 0.3895% CrI, 0.25-0.58) and OS (HR, 0.3895% CrI, 0.22-0.65). Conclusions: ACH following RC for MIBC may therefore contribute to improved PFS and OS. In particular, the GCP combination may be the optimal ACH regimen for improving postoperative survival outcomes. Additional well-designed, large scale, prospective, randomized trials are still required to establish the optimal ACH regimen in MIBC patients.Objective: Although adjuvant chemotherapy (ACH) is widely used in clinical practice for the management of muscle-invasive bladder cancer (MIBC), a consensus has yet to be established on which ACH regimen is the most effective for improving postoperative survival. In this study, we aimed to systematically assess the optimal ACH regimen for improving survival outcomes in patients treated with radical cystectomy (RC) for MIBC. Materials and Methods: A comprehensive literature search was conducted in the PubMed, Embase, and the Cochrane Library databases for all articles published until December 2016 in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. The study end-points were progression-free survival (PFS) and overall survival (OS). A direct pairwise meta-analysis was conducted by pooling the studies that compared RC with ACH and RC alone, and the results are presented as a pooled hazard ratio (HR) with a 95% confidence interval (CI). A Bayesian network meta-analysis was adopted for indirect comparisons among various ACH regimens, and the outcomes are presented as HRs with 95% credible intervals (CrI). Results: The eleven randomized controlled trials ultimately selected for the current analysis comprised of 1,546 patients with 49 to 327 subjects per study. Based on the pairwise meta-analysis, the use of ACH showed significantly better PFS (HR, 0.6495% CI, 0.49-0.85) and OS (HR, 0.79Introduction 1 Materials and Methods 3 Results 10 Discussion 29 Conclusions 35 References 36 Abstract in Korean 43Docto

    An efficient prefetching algorithm for fast address translation in a PCM controller

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์ „๊ธฐยท์ •๋ณด๊ณตํ•™๋ถ€, 2021.8. ์ดํ˜์žฌ.DRAM์˜ ์Šค์ผ€์ผ๋ง ๊ธฐ์ˆ ์€ ํ•œ๊ณ„์— ๋„๋‹ฌํ–ˆ๊ณ  ์ด์— ๋”ฐ๋ผ DRAM์„ ๋Œ€์ฒดํ•  ์—ฌ๋Ÿฌ ์ฐจ์„ธ๋Œ€ ๋ฉ”๋ชจ๋ฆฌ ๊ธฐ์ˆ ์ด ์ œ์•ˆ๋˜์—ˆ๋‹ค. ๊ทธ ์ค‘ ์ƒ ๋ณ€ํ™” ๋ฉ”๋ชจ๋ฆฌ (phase change memory, PCM)๋Š” ๋ฌผ์งˆ์˜ ์ƒ ๋ณ€ํ™”๋ฅผ ํ†ตํ•œ ์ €ํ•ญ ๋ณ€ํ™”๋กœ ๋ฐ์ดํ„ฐ๋ฅผ ์ €์žฅํ•˜๋ฉฐ ์ด์— ๋”ฐ๋ผ ํšจ๊ณผ์ ์ธ ์Šค์ผ€์ผ๋ง์ด ๊ฐ€๋Šฅํ•˜๋‹ค. PCM์— ์ ‘๊ทผํ•˜๊ธฐ ์œ„ํ•ด PCM controller์—์„œ ๋…ผ๋ฆฌ์  ์ฃผ์†Œ๋ฅผ ๋ฌผ๋ฆฌ์  ์ฃผ์†Œ๋กœ ๋ณ€ํ™˜ํ•˜๋Š” ๊ณผ์ •์„ ๊ฑฐ์นœ๋‹ค. ์ฃผ์†Œ ๋ณ€ํ™˜ ์š”์ฒญ ๋ฐœ์ƒ ์‹œ DRAM์— ์ ‘๊ทผํ•˜์—ฌ ์ฃผ์†Œ ๋ณ€ํ™˜ ๋ฐ์ดํ„ฐ๋ฅผ ๋ฐ›์•„์˜จ๋‹ค. ์ฃผ์†Œ ๋ณ€ํ™˜์„ ์œ„ํ•œ ์ง€์†์ ์ธ ๋ฉ”๋ชจ๋ฆฌ ์ ‘๊ทผ์€ ์ „์ฒด์ ์ธ ์„ฑ๋Šฅ ์ €ํ•˜๋ฅผ ์•ผ๊ธฐํ•œ๋‹ค. Prefetcher๋Š” ์ด๋Ÿฌํ•œ ๋ฌธ์ œ๋ฅผ ํšจ๊ณผ์ ์œผ๋กœ ํ•ด๊ฒฐํ•  ์ˆ˜ ์žˆ๋‹ค. PCM workload์˜ ๊ฒฝ์šฐ ์ˆœ ๋ฐฉํ–ฅ ์ˆœ์ฐจ ํŒจํ„ด ๋ฐ ์—ญ ๋ฐฉํ–ฅ ์ˆœ์ฐจ ํŒจํ„ด์ด ์ฃผ๋ฅผ ์ด๋ฃฌ๋‹ค. ๋˜ํ•œ ์ผ๋ถ€ ๋น„ ์ˆœ์ฐจ ํŒจํ„ด์˜ ๊ฒฝ์šฐ PCM workload ๋‚ด์— ์กด์žฌํ•˜๋Š” ์ˆœ์ฐจ ํŒจํ„ด๊ณผ ์—ฐ๊ด€์„ฑ์„ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ๋น„ ์ˆœ์ฐจ ํŒจํ„ด์˜ ๊ฒฝ์šฐ ๋šœ๋ ทํ•œ ํŒจํ„ด์ด ์กด์žฌํ•˜์ง€ ์•Š์•„ ๊ธฐ์กด์˜ prefetch ์•Œ๊ณ ๋ฆฌ์ฆ˜์œผ๋กœ ์„ฑ๊ณต์ ์ธ prefetch๋ฅผ ์ง„ํ–‰ํ•  ์ˆ˜ ์—†๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ ์ œ์•ˆํ•˜๋Š” prefetcher๋Š” stream prefetcher์™€ ์œ ์‚ฌํ•œ ๋ฐฉ์‹์„ ํƒํ•จ์œผ๋กœ ์ˆœ์ฐจ ํŒจํ„ด์„ ํšจ์œจ์ ์œผ๋กœ ํƒ์ง€ํ•  ์ˆ˜ ์žˆ๋‹ค. ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ endurance์™€ depth parameter๋ฅผ ํ†ตํ•ด ๋šœ๋ ทํ•œ ํŒจํ„ด์ด ์กด์žฌํ•˜์ง€ ์•Š์ง€๋งŒ workload ๋‚ด ์ˆœ์ฐจ ํŒจํ„ด๊ณผ ์—ฐ๊ด€์„ฑ์„ ๊ฐ€์ง€๋Š” ํŒจํ„ด์— ๋Œ€ํ•ด prefetch hit์„ ๋ฐœ์ƒ์‹œํ‚ฌ ์ˆ˜ ์žˆ๋‹ค. ์ œ์•ˆํ•œ prefetcher์˜ ๊ฒฝ์šฐ ๊ธฐ์กด prefetch ์•Œ๊ณ ๋ฆฌ์ฆ˜ ๋Œ€๋น„ 7% ์ด์ƒ์˜ ์ „์ฒด ์‹œ์Šคํ…œ ์„ฑ๋Šฅ ํ–ฅ์ƒ์„ ๋ณด์˜€๋‹ค. ๋˜ํ•œ prefetch๋ฅผ ์ง„ํ–‰ํ•˜์ง€ ์•Š์•˜์„ ๊ฒฝ์šฐ์— ๋น„ํ•ด ์ฃผ์†Œ ๋ณ€ํ™˜ ์‹œ๊ฐ„์„ 17% ์ˆ˜์ค€์œผ๋กœ ๋‹จ์ถ•์‹œ์ผฐ์œผ๋ฉฐ ์ „์ฒด ์‹œ์Šคํ…œ ์ง€์—ฐ์‹œ๊ฐ„์„ 40% ์ˆ˜์ค€์œผ๋กœ ๋‹จ์ถ•์‹œ์ผฐ๋‹ค.DRAM's scaling technology has reached its limit and several next-generation memory technologies have been proposed to replace DRAM. Among them, phase change memory (PCM) stores data as resistance changes through phase changes in matter, enabling effective scaling. To access PCM, PCM controller converts logical address to physical address. When an address conversion request occurs, DRAM is accessed to receive address conversion data. Continuous memory access for address translation causes overall performance degradation. Prefetcher can solve these problems effectively. For PCM workloads, forward sequential patterns and reverse sequential patterns are the main ones. Some non-sequential patterns have associations with sequential patterns that exist within PCM workloads. For these non-sequential patterns, no distinct pattern exists, and successful prefetching cannot be carried out with existing prefetch algorithms. Prefetcher proposed in this work can efficiently detect sequential patterns by taking a similar approach to stream prefetcher. Furthermore, the endurance and depth parameters allow a prefetch hit to occur for patterns that no distinct pattern exists but are associated with sequential patterns in the workload. The proposed prefetcher showed more than 7% improvement in overall system performance compared to the existing prefetch algorithm. It also reduced address translation time to 17% and overall system latency to 40% compared to the case of not proceeding prefetch.์ œ 1 ์žฅ ์„œ ๋ก  1 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ์˜ ๋ฐฐ๊ฒฝ 1 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ์˜ ๋‚ด์šฉ 2 ์ œ 3 ์ ˆ ๋…ผ๋ฌธ์˜ ๊ตฌ์„ฑ 3 ์ œ 2 ์žฅ ๊ด€๋ จ ์—ฐ๊ตฌ 5 ์ œ 1 ์ ˆ Stream Prefetcher 5 ์ œ 2 ์ ˆ Signature Path Prefetcher 6 ์ œ 3 ์ ˆ Variable Length Delta Prefetcher 8 ์ œ 3 ์žฅ ์ œ์•ˆ ๋ฐฉ๋ฒ• ๋ฐ ๊ตฌํ˜„ 12 ์ œ 1 ์ ˆ ํŒจํ„ด ๋ถ„์„ 12 ์ œ 2 ์ ˆ ์ œ์•ˆ ๋ฐฉ๋ฒ• 18 ์ œ 3 ์ ˆ ๊ตฌํ˜„ ๋ฐฉ๋ฒ• 20 ์ œ 4 ์žฅ ์‹ค ํ—˜ 28 ์ œ 1 ์ ˆ ์‹คํ—˜ ํ™˜๊ฒฝ ๋ฐ ๊ตฌ์„ฑ 28 ์ œ 2 ์ ˆ ์‹คํ—˜ ๊ฒฐ๊ณผ 31 ์ œ 5 ์žฅ ๊ฒฐ ๋ก  48 ์ฐธ๊ณ ๋ฌธํ—Œ 49 Abstract 53์„

    ATSC 3.0 ๋ฐ MBMS ์‹œ์Šคํ…œ ๋ถ„์„๊ณผ ATSC 3.0์„ ์œ„ํ•œ LDM ๊ธฐ๋ฐ˜ ์ตœ์  ์ „์†ก ๋ฐ MIMO ๊ธฐ๋ฐ˜ ๊ฒ€์ถœ ์„ฑ๋Šฅ ํ–ฅ์ƒ ๋ฐฉ๋ฒ•

    No full text
    ์ตœ๊ทผ, ํ†ต์‹  ์‹œ์Šคํ…œ๊ณผ ๋ฏธ๋””์–ด ์‚ฐ์—…์˜ ๋ฐœ์ „์œผ๋กœ ์ธํ•ด, ์Šค๋งˆํŠธํฐ์„ ์ด์šฉํ•œ ๋ฏธ๋””์–ด ์„œ๋น„์Šค์˜ ์†Œ๋น„๊ฐ€ ๊ธ‰์ฆํ•˜๊ณ  ์žˆ๋‹ค. ํŠนํžˆ, OTT (over the top)์™€ ๊ฐ™์€ ํ”Œ๋žซํผ์˜ ์ธ๊ธฐ๋กœ ์ธํ•ด, ๋” ๋†’์€ ํ’ˆ์งˆ์˜ ๋น„๋””์˜ค/์˜ค๋””์˜ค ์„œ๋น„์Šค์— ๋Œ€ํ•œ ์ˆ˜์š”๊ฐ€ ์ฆ๊ฐ€ํ•˜๊ณ  ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ์ถ”์„ธ์— ๋”ฐ๋ผ, ๊ณ ์šฉ๋Ÿ‰์˜ ์„œ๋น„์Šค๋ฅผ ์•ˆ์ •์ ์ด๊ณ  ํšจ์œจ์ ์œผ๋กœ ์ „์†กํ•  ์ˆ˜ ์žˆ๋Š” ์ฐจ์„ธ๋Œ€ ๋ฐฉ์†ก ๊ทœ๊ฒฉ์— ๋Œ€ํ•œ ํ•„์š”์„ฑ์ด ๋Œ€๋‘๋˜๊ณ  ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ์š”๊ตฌ๋ฅผ ๋งŒ์กฑํ•˜๊ธฐ ์œ„ํ•ด, ATSC (Advanced Television Systems Committee) 3.0๊ณผ 5G MBMS (fifth-generation multimedia broadcast/multicast service) ๋“ฑ์ด ์ตœ๊ทผ์— ๊ฐœ๋ฐœ๋˜์—ˆ๋‹ค. ๋ณธ ํ•™์œ„๋…ผ๋ฌธ์—์„œ๋Š” ATSC 3.0๊ณผ 5G MBMS์˜ ์‹œ์Šคํ…œ ๋ฐ ์ˆ˜์‹  ์„ฑ๋Šฅ์„ ๋ถ„์„ํ•˜๊ณ , ATSC 3.0 ๊ธฐ๋ฐ˜์˜ LDM (layered-division multiplexing)์„ ํ™œ์šฉํ•œ ๋‹ค์ค‘ ์„œ๋น„์Šค์˜ ์ตœ์  ์ „์†ก ๋ฐ MIMO (multiple-input multiple-output)๋ฅผ ํ™œ์šฉํ•œ ๊ฒ€์ถœ ์„ฑ๋Šฅ ํ–ฅ์ƒ ๋ฐฉ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ๋จผ์ €, ATSC 3.0๊ณผ 5G MBMS์˜ ์‹œ์Šคํ…œ ๋ถ„์„ ๋ฐ ์„ฑ๋Šฅ ํ‰๊ฐ€๋ฅผ ์ˆ˜ํ–‰ํ•œ๋‹ค. ATSC 3.0๊ณผ 5G MBMS ์‹ ํ˜ธ๋ฅผ ๊ฐ๊ฐ ๋ฐ์ดํ„ฐ ์˜์—ญ (data part)๊ณผ ์ œ์–ด ์˜์—ญ (control part)์— ํ•ด๋‹นํ•˜๋Š” ๋ฌผ๋ฆฌ ์ฑ„๋„๋กœ ๋‚˜๋ˆ„๊ณ , ๊ฐ ์‹ ํ˜ธ ์˜์—ญ์— ๋Œ€ํ•ด ๋…๋ฆฝ์ ์œผ๋กœ ์„ฑ๋Šฅ ํ‰๊ฐ€๋ฅผ ์ˆ˜ํ–‰ํ•œ๋‹ค. ๋˜ํ•œ, ๋‹ค์–‘ํ•œ ์ˆ˜์‹  ์„ฑ๋Šฅ ๋ถ„์„์„ ์œ„ํ•ด, ๋ฐฉ์†ก๋ง๊ณผ ๊ฐ™์ด ๋งค์šฐ ๋„“์€ ์ปค๋ฒ„๋ฆฌ์ง€ (coverage)์—์„œ ๋ฐœ์ƒํ•  ์ˆ˜ ์žˆ๋Š” ๋งค์šฐ ๊ธด ์ง€์—ฐ (delay)์„ ํฌํ•จํ•œ ์ด๋™ ๋ฐ ๊ณ ์ • ์ฑ„๋„ ํ™˜๊ฒฝ์„ ๊ณ ๋ คํ•˜๊ณ , ์ด์ƒ์ ์ธ ์ฑ„๋„ ์ถ”์ •์„ ํฌํ•จํ•œ ์„ฑ๋Šฅ์ด ๋‹ค๋ฅธ 3๊ฐ€์ง€ ์ฑ„๋„ ์ถ”์ • ๋ฐฉ๋ฒ•์„ ์ ์šฉํ•œ๋‹ค. ์ „์‚ฐ ์‹คํ—˜ ๊ฒฐ๊ณผ๋Š” ๋ฐ์ดํ„ฐ ์˜์—ญ๊ณผ ์ œ์–ด ์˜์—ญ ๋ชจ๋‘์—์„œ ATSC 3.0์ด 5G MBMS์— ๋น„ํ•ด ์ƒ๋‹นํ•œ ์„ฑ๋Šฅ ์ด๋“์„ ์–ป์„ ์ˆ˜ ์žˆ๊ณ , ATSC 3.0์ด 5G MBMS ๋ณด๋‹ค ํšจ์œจ์ ์ธ ๋ฐฉ์†ก๋ง ๊ตฌ์ถ•์— ์œ ๋ฆฌํ•˜๋‹ค๋Š” ๊ฒƒ์„ ๋ณด์—ฌ์ค€๋‹ค. ๋˜ํ•œ, ์ฐจ์„ธ๋Œ€ ๋ฐฉ์†ก ๊ทœ๊ฒฉ์ธ NR MBS (new radio multicast and broadcase service)๋Š” 5G MBMS์— ๋น„ํ•ด BICM (bit interleaved coded modulation)์ด ๊ฐœ์„ ๋˜์—ˆ๊ธฐ ๋•Œ๋ฌธ์— ํ–ฅ์ƒ๋œ ์„ฑ๋Šฅ์„ ์–ป์„ ์ˆ˜ ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜, ๋†’์€ ์†๋„์—์„œ๋Š” ์—ฌ์ „ํžˆ ๋„ํ”Œ๋Ÿฌ (Doppler)์— ์˜ํ•œ ์„ฑ๋Šฅ ์—ดํ™”๊ฐ€ ๋ฐœ์ƒํ•˜๊ธฐ ๋•Œ๋ฌธ์—, ATSC 3.0์˜ ์ธํ„ฐ๋ฆฌ๋น™ (interleaving)๊ณผ ๊ฐ™์€ ์ถ”๊ฐ€์ ์ธ ๋‹ค์ด๋ฒ„์‹œํ‹ฐ (diversity) ์ด๋“์„ ์–ป์„ ์ˆ˜ ์žˆ๋Š” ๋ฐฉ๋ฒ•์„ ์ถ”๊ฐ€๋กœ ์ ์šฉํ•จ์œผ๋กœ์จ, ๋†’์€ ์†๋„์—์„œ ๋”์šฑ ๊ฐœ์„ ๋œ ์„ฑ๋Šฅ์„ ์–ป์„ ์ˆ˜ ์žˆ๊ณ , ๋”ฐ๋ผ์„œ ๋ฐฉ์†ก๋ง์—์„œ ํ–ฅ์ƒ๋œ ์ „์†ก ํšจ์œจ์„ ์–ป์„ ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ์˜ˆ์ƒํ•  ์ˆ˜ ์žˆ๋‹ค. ๋˜ํ•œ, ATSC 3.0 ์‹œ์Šคํ…œ์„ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•œ ๋ฐฉ์†ก๋ง์˜ ์ „์†ก ํšจ์œจ์„ ๊ทน๋Œ€ํ™”ํ•˜๊ธฐ ์œ„ํ•œ ๋‘ ๊ฐ€์ง€ ๊ฐœ์„  ๋ฐฉ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ์ฒซ ๋ฒˆ์งธ๋กœ, LDM์„ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•œ ๋‹ค์ค‘ PLP (physical layer pipe)์˜ ์ตœ์  ์ „์†ก ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•œ๋‹ค. ๊ทœ๊ฒฉ์„ ํ™•์žฅํ•˜์—ฌ ์ตœ๋Œ€ 4๊ฐœ PLP์™€ 4๊ฐœ ๊ณ„์ธต (layer)๊นŒ์ง€ ๊ณ ๋ คํ•œ LDM ๊ธฐ๋ฐ˜ M-PLP (multiple-PLP) configuration๋“ค์˜ ์ฑ„๋„ ์šฉ๋Ÿ‰ (channel capacity) ๋ถ„์„๊ณผ ์ˆ˜์‹  ์„ฑ๋Šฅ ํ‰๊ฐ€๊ฐ€ ์ˆ˜ํ–‰๋œ๋‹ค. LDM์€ ๋‹ค๋ฅธ ์ง๊ต ๋‹ค์ค‘ํ™” (orthogonal multiplexing) ๋ฐฉ๋ฒ•์— ๋น„ํ•ด ์ตœ์†Œ ์ฑ„๋„ ์šฉ๋Ÿ‰์„ ์ตœ๋Œ€ํ™”ํ•˜๋Š” ๊ด€์ ์—์„œ ๋” ๋†’์€ ์ „์†ก ํšจ์œจ์„ ์–ป์„ ์ˆ˜ ์žˆ๋‹ค. ์ „์‚ฐ ์‹คํ—˜ ๊ฒฐ๊ณผ๋Š” ๊ฐ PLP๋ฅผ ๊ฐ ๊ณ„์ธต์— ํ• ๋‹นํ•˜๋Š” ๋‹ค๊ณ„์ธต LDM์˜ ๊ฒฝ์šฐ๊ฐ€ ๋‚˜๋จธ์ง€ ๋‹ค์ค‘ํ™” ๋ฐฉ๋ฒ•์— ๋น„ํ•ด ๊ฐ€์žฅ ๋†’์€ ์ฑ„๋„ ์šฉ๋Ÿ‰๊ณผ ๊ฐ€์žฅ ์ข‹์€ ์ˆ˜์‹  ์„ฑ๋Šฅ์„ ๋‹ฌ์„ฑํ•  ์ˆ˜ ์žˆ์Œ์„ ๋ณด์—ฌ์ค€๋‹ค. ๋˜ํ•œ, LTDM (layered time-division multiplexing)์˜ ์„ฑ๋Šฅ ์—ดํ™”๊ฐ€ ๋‹ค๊ณ„์ธต LDM์— ๋น„ํ•ด ํฌ์ง€ ์•Š์œผ๋ฏ€๋กœ, LTDM ๋˜ํ•œ ํšจ์œจ์ ์ธ ์ „์†ก์„ ์œ„ํ•œ ์ข‹์€ ์†”๋ฃจ์…˜์ด ๋  ์ˆ˜ ์žˆ์Œ์„ ๋ณด์—ฌ์ค€๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ, ๋ฐฉ์†ก๋ง์˜ ์ „์†ก ํšจ์œจ ๊ฐœ์„ ์„ ์œ„ํ•œ ๋˜ ๋‹ค๋ฅธ ๋ฐฉ๋ฒ•์œผ๋กœ์„œ MIMO ์‹œ์Šคํ…œ์—์„œ์˜ ๊ฒ€์ถœ ์„ฑ๋Šฅ ํ–ฅ์ƒ ๋ฐฉ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ATSC 3.0์˜ MIMO ์‹œ์Šคํ…œ์€ MIMO precoding ๋‚ด I/Q polarization interleaving์˜ ๋น„์„ ํ˜• ๋™์ž‘์œผ๋กœ ์ธํ•ด ์—ฐ์† ๊ฐ„์„ญ ์ œ๊ฑฐ (successive interference cancellation: SIC) ๊ธฐ๋ฐ˜ ๋ฐฉ๋ฒ•์˜ ์ ์šฉ์ด ๋ถˆ๊ฐ€๋Šฅํ•˜๋‹ค. ๋”ฐ๋ผ์„œ, SIC ๊ธฐ๋ฐ˜์˜ ์ค€์ตœ์  (suboptimal) ๊ฒ€์ถœ ๋ฐฉ๋ฒ•์„ ์‰ฝ๊ฒŒ ์ ์šฉํ•  ์ˆ˜ ์žˆ๋„๋ก, ์ˆ˜์‹  ์‹ ํ˜ธ์— ๋Œ€ํ•ด ๋‹ค๋ฅธ ํ˜•ํƒœ์˜ real-valued representation์„ ์ œ์‹œํ•œ๋‹ค. ๋˜ํ•œ, ์„ฑ๋Šฅ ๊ฐœ์„ ๊ณผ ๋ณต์žก๋„ ๊ฐ์†Œ๋ฅผ ์œ„ํ•ด ATSC 3.0์—์„œ ์‚ฌ์šฉ๋˜๋Š” 2D NUC (two-dimensional non-uniform constellation)์˜ ๊ตฌ์กฐ์  ํŠน์ง•์„ ๋ฐ˜์˜ํ•œ ๋ธ”๋ก ๋‹จ์œ„์˜ -best ์•Œ๊ณ ๋ฆฌ์ฆ˜ ๊ธฐ๋ฐ˜ ๊ฒ€์ถœ ๋ฐฉ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ์ „์‚ฐ ์‹คํ—˜ ๊ฒฐ๊ณผ๋Š” ๊ณ ์ • ๋ฐ ์ด๋™ ์ฑ„๋„ ํ™˜๊ฒฝ์—์„œ ์ œ์•ˆํ•˜๋Š” ๋ฐฉ๋ฒ•์ด ๊ธฐ์กด ์„ ํ˜• ํ•„ํ„ฐ๋ฅผ ์ ์šฉํ•œ ๋ฐฉ๋ฒ•์— ๋น„ํ•ด ๋ณต์žก๋„๋Š” ์•ฝ๊ฐ„ ์ฆ๊ฐ€ํ•˜์ง€๋งŒ, ๋งค์šฐ ํ–ฅ์ƒ๋œ ์„ฑ๋Šฅ์„ ์–ป์„ ์ˆ˜ ์žˆ์Œ์„ ๋ณด์—ฌ์ค€๋‹ค. ๋˜ํ•œ, ์ œ์•ˆํ•˜๋Š” ๋ฐฉ๋ฒ•์—์„œ ์ ์ ˆํ•œ ํ›„๋ณด ์‹ฌ๋ณผ์˜ ๊ฐœ์ˆ˜๋ฅผ ์„ ํƒํ•จ์œผ๋กœ์จ ์ข‹์€ ์„ฑ๋Šฅ-๋ณต์žก๋„ trade-off๋ฅผ ๋งŒ์กฑํ•  ์ˆ˜ ์žˆ์Œ์„ ๋ณด์—ฌ์ค€๋‹ค.|Recently, with the development of communication systems and the media industry, the consumption of media services using smartphones has rapidly increased. In particular, owing to the popularity of media platforms, such as over the top (OTT), the demands for higher-quality video/audio services have increased. To satisfy the requirements, Advanced Television Systems Committee (ATSC) 3.0 and fifth-generation (5G) multimedia broadcast/multicast service (MBMS) have been recently developed as next-generation terrestrial broadcasting standards. To realize an efficient broadcasting network, the system and reception performance of ATSC 3.0 and 5G MBMS are analyzed. Furthermore, to maximize the transmission efficiency in broadcasting networks, an optimal transmission scheme of multiple services using layered-division multiplexing (LDM) and an improved detection scheme using multiple-input multiple-output (MIMO) are proposed based on the ATSC 3.0 system. First, system analysis and performance evaluation of ATSC 3.0 and 5G MBMS are performed. The ATSC 3.0 and 5G MBMS signals can be divided into several physical channels corresponding to the data and control parts. Subsequently, the reception performance is evaluated independently for the physical channels corresponding to each part. In addition, as channel environments, mobile and fixed channels with very long delay spread, which may occur in very wide coverage for broadcasting networks, are considered. Moreover, three channel estimation schemes corresponding to ideal, low-complexity, and practical estimation are applied. The simulation results show that ATSC 3.0 can obtain significant performance gain compared to 5G MBMS in both the data and control parts. Therefore, ATSC 3.0 is more advantageous than 5G MBMS for efficient broadcasting networks. In addition, 5G-based new radio (NR) multicast and broadcast service (MBS), which is considered as a next-generation broadcasting standard, can obtain improved performance by using enhanced bit-interleaved coded modulation (BICM) compared to 5G MBMS. However, to obtain additional performance gain under higher mobile speeds, it is necessary to apply the schemes such as interleaving used in ATSC 3.0. Furthermore, two improved schemes aimed to maximize of transmission efficiency are proposed based on the ATSC 3.0 system. First, an optimal transmission scheme of multiple physical layer pipes (M-PLPs) based on LDM is presented. Considering up to 4 PLPs and four layers based on LDM extension, the capacity analysis and performance evaluation of LDM-based M-PLP configurations are performed. LDM can provide higher transmission efficiency from the perspective of maximizing the minimum rate than other orthogonal multiplexing schemes. The simulation results show that multi-layer LDM, which allocates each PLP to each layer, can achieve the highest capacity and best reception performance compared to other configurations. In addition, since the performance degradation of layered time-division multiplexing (LTDM) is not significant compared to the multi-layer LDM, it is shown that LTDM may also be a good solution for the efficient transmission of M-PLPs. Finally, as another improvement of the broadcasting network, an improved detection scheme for the ATSC 3.0 MIMO system is proposed. The MIMO system of ATSC 3.0 cannot use the successive interference cancellation (SIC)-based scheme owing to the non-linear operation of I/Q polarization interleaving in the MIMO precoding. Therefore, this thesis presents an alternative approach to the real-valued representation for the received signal to facilitate a simpler application of various SIC-based detection schemes than other forms of real-valued representations. In addition, to improve the detection performance and complexity, an improved detection scheme using -best algorithm based on block cancellation, which reflects the structural property of two-dimensional non-uniform constellation (2D NUC) defined in ATSC 3.0, is proposed. The simulation results show that the proposed detection scheme outperforms the linear detection under mobile and fixed channels, although the complexity increases slightly. Furthermore, a good performance- complexity trade-off can be satisfied by selecting the appropriate number of candidate symbols for the proposed detection scheme.1. Introduction 1 1.1 Problems and Related Previous Works 6 1.2 Summary of Contributions 11 2. Study on ATSC 3.0 and 5G MBMS Systems 14 2.1 Structure of ATSC 3.0 System 16 2.2 Structure of 5G MBMS System 22 2.3 Simulation Results 31 2.4 Summary 49 3. Optimization of LDM-Based Transmission for ATSC 3.0 51 3.1 LDM-Based M-PLP Configuration in ATSC 3.0 52 3.2 Extension to Multi-Layer LDM 57 3.3 Capacity Analysis for LDM-Based M-PLP Configurations 66 3.4 Simulation Results 70 3.5 Summary 87 4. Improved Detection Scheme of ATSC 3.0 MIMO 88 4.1 ATSC 3.0 MIMO System 89 4.2 Real-Valued Representation of Received Signals 93 4.3 Improved SIC-Based Detection Scheme 96 4.4 Simulation Results 105 4.5 Summary 111 5. Conclusions 112Docto

    ์†Œ๋น„์‚ฌํšŒ์˜ ๊ธฐํ˜ธ(่จ˜่™Ÿ)์™€ ์ด๋ฏธ์ง€์˜ ํ•ด์„์„ ํ†ตํ•œ ํ‘œํ˜„์˜ ์—ฐ๊ตฌ : ๋ณธ์ธ์˜ ์ž‘ํ’ˆ์„ ์ค‘์‹ฌ์œผ๋กœ

    No full text
    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์„œ์–‘ํ™”๊ณผ ์„œ์–‘ํ™”์ „๊ณต,1999.Maste

    New Security Rights on Movables and Claims: An Overview

    No full text
    ์šฐ๋ฆฌ ๋ฒ•์ œ์—์„œ ํ™œ์šฉํ•  ์ˆ˜ ์žˆ๋Š” ๋™์‚ฐใ†์ฑ„๊ถŒ๋‹ด๋ณด๋กœ์„œ๋Š” ๋ฏผ๋ฒ•์ด ์ •ํ•˜๋Š” ์งˆ๊ถŒ(๋ฏผ๋ฒ• ์ œ329์กฐ, ์ œ345์กฐ)๊ณผ ๊ฑฐ๋ž˜๊ณ„์—์„œ ๋ฐœ๋‹ฌํ•ด์˜จ ์–‘๋„๋‹ด๋ณด๊ฐ€ ์กด์žฌํ•œ๋‹ค. ๊ทธ๋Ÿฐ๋ฐ ์ฃผ์ง€ํ•˜๋Š” ๋ฐ”์™€ ๊ฐ™์ด ์งˆ๊ถŒ๊ณผ ์–‘๋„๋‹ด๋ณด๋Š” ๊ทธ๊ฒƒ์˜ ๊ฒฝ์‹œํ•  ์ˆ˜ ์—†๋Š” ์ˆœ๊ธฐ๋Šฅ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ๊ฑฐ๋ž˜๊ณ„์˜ ์ˆ˜์š”์— ๋น„์ถ”์–ด ๋ถˆ์ถฉ๋ถ„ํ•œ ๋‹จ์ ๋“ค์ด ์žˆ๋‹ค๊ณ  ์ง€์ ๋˜์–ด ์™”๋‹ค. ์ด๋Ÿฌํ•œ ๋™์‚ฐโ‹…์ฑ„๊ถŒ๋‹ด๋ณด์—์„œ์˜ ๋ฌธ์ œ์ ์— ๋Œ€์ฒ˜ํ•˜๊ธฐ ์œ„ํ•ด ์ œ์ •๋œ ๋ฒ•๋ฅ ์ด ๏ฝข๋™์‚ฐโ‹…์ฑ„๊ถŒ ๋“ฑ์˜ ๋‹ด๋ณด์— ๊ด€ํ•œ ๋ฒ•๋ฅ ๏ฝฃ (2010๋…„ 6์›” 10์ผ, ๋ฒ•๋ฅ  ์ œ10366ํ˜ธ)์ด๋‹ค. ๋™๋ฒ•์€ ๋™์‚ฐโ‹…์ฑ„๊ถŒ์„ ๋ชฉ์ ์œผ๋กœ ํ•˜๋Š” ์ƒˆ๋กœ์šด ๋‹ด๋ณด๋ฌผ๊ถŒ์„ ์ฐฝ์„คํ•˜๊ณ  ์ด๋ฅผ ๋“ฑ๊ธฐํ•˜์—ฌ ๊ณต์‹œํ•  ์ˆ˜ ์žˆ๋„๋ก ํ•œ๋‹ค. ์ด ๊ธ€์€ ๏ฝข๋™์‚ฐโ‹…์ฑ„๊ถŒ ๋“ฑ์˜ ๋‹ด๋ณด์— ๊ด€ํ•œ ๋ฒ•๋ฅ ๏ฝฃ์— ๋”ฐ๋ผ ์šฐ๋ฆฌ ๋ฒ•์ œ์— ๋„์ž…๋œ ๋™์‚ฐ๋‹ด๋ณด๊ถŒ๊ณผ ์ฑ„๊ถŒ๋‹ด๋ณด๊ถŒ ์ œ๋„์˜ ๊ตฌ์ฒด์ ์ธ ๋‚ด์šฉ์„ ๊ฐœ๊ด€ํ•˜๊ณ , ๊ทธ ์ ์šฉ์—์„œ ์ œ๊ธฐ๋  ์ˆ˜ ์žˆ๋Š” ๋ช‡ ๊ฐ€์ง€ ๋ฒ•๋ฅ ๋ฌธ์ œ๋“ค์— ๋Œ€ํ•ด ์‹œ๋ก ์ ์ธ ํ•ด์„๋ก ์„ ์ƒ๊ฐํ•ด ๋ณด๋Š” ๊ฒƒ์„ ๋ชฉ์ ์œผ๋กœ ํ•œ๋‹ค. ๋™์‹œ์— ์ด๋Ÿฌํ•œ ๋‚ด์šฉ์„ ๋ฐ”ํƒ•์œผ๋กœ ๋™๋ฒ•์ด ๋„์ž…ํ•˜๋Š” ๋“ฑ๊ธฐ๋‹ด๋ณด๊ถŒ์˜ ์žฅ๋‹จ์ ์„ ํ‰๊ฐ€ํ•œ๋‹ค

    ์œ„์„ฑDMB์‚ฌ์—… ์ •์ฑ…๊ฒฐ์ • ์‚ฌ๋ก€ ์—ฐ๊ตฌ

    No full text
    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) --์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :ํ–‰์ •ํ•™๊ณผ(์ •์ฑ…ํ•™์ „๊ณต),2008.Maste

    ๋ฐฉ๊ด‘์•”์— ๋Œ€ํ•œ ๊ฒฝ์š”๋„ ์ ˆ์ œ ๊ฒ€์ฒด์—์„œ ๊ด€์ฐฐ๋˜๋Š” ์ž„ํŒŒ ํ˜ˆ๊ด€ ์นจ์œค์˜ ์ˆ  ํ›„ ์ข…์–‘ ๋ณ‘๊ธฐ ์ƒ์Šน๊ณผ ์ƒ์กด๊ณผ์˜ ๊ด€๋ จ์„ฑ :

    No full text
    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์˜ํ•™๊ณผ ๋น„๋‡จ๊ธฐ๊ณผํ•™ ์ „๊ณต, 2016. 2. ๊ตฌ์žํ˜„.Objectives: This study aimed to elucidate the relationship between lymphovascular invasion (LVI) at transurethral resection of bladder tumor (TURBT) and the risk of pathological upstaging as well as the clinical outcomes. Materials and Methods: PubMed, SCOPUS, Web of Science and Cochrane Library databases were searched from the respective dates of inception until November 11, 2013. Results: A total of 16 articles met the eligibility criteria for this systematic review, which included a total of 3,905 patients. LVI was detected in 18.6% in TURBT specimens. The significant association was found between LVI at TURBT and pathological upstaging of bladder cancer (odds ratio 2.21, 95% confidence interval [CI] 1.44-3.39) without heterogeneity (I2 45%, p = 0.14). The pooled hazard ratio (HR) was statistically significant for recurrence-free survival (HR 1.47, 95% CI 1.24-1.74), progression-free survival (HR 2.28, 95% CI 1.45-3.58), and disease-specific survival HR, 1.3595% CI, 1.01-1.81), but not overall survival (HR, 1.5595% CI, 0.90-2.67). Tests of inconsistency for disease-specific survival (I2 66%, p = 0.007) and overall survival (I2 72%, p = 0.03) could not exclude a significant heterogeneity. The results of Beggs and Eggers test showed that there was evidence of publication bias on pathological upstaging and progression-free survival. Conclusions: The data obtained in this meta-analysis indicate that the presence of LVI at TURBT portends the increased risk of pathological upstaging and may provide additional prognostic information. However, a large, well-designed, prospective study is needed to investigate potential treatment options for bladder cancer with LVI.์„œ ๋ก  1 ์‹คํ—˜ ์žฌ๋ฃŒ ๋ฐ ๋ฐฉ๋ฒ• 3 ๊ฒฐ ๊ณผ 6 ๊ณ  ์ฐฐ 23 ๊ฒฐ ๋ก  26 ์ฐธ๊ณ  ๋ฌธํ—Œ 27 ์ดˆ ๋ก (๊ตญ ๋ฌธ) 32Maste
    • โ€ฆ
    corecore