120 research outputs found

    LED ์กฐ๋ช… ํ•˜์—์„œ ๋‹จ์ผ์—ฝ๊ณผ ๊ตฐ๋ฝ์˜ ์ŠคํŽ™ํŠธ๋Ÿผ์— ๋Œ€ํ•œ ์†Œ๋น„์ „๊ธฐ ์—๋„ˆ์ง€ ๋Œ€๋น„ ๊ด‘ํ•ฉ์„ฑ ํšจ์œจ

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์‹๋ฌผ์ƒ์‚ฐ๊ณผํ•™๋ถ€(์›์˜ˆ๊ณผํ•™์ „๊ณต), 2014. 2. ์†์ •์ต.In plant factories using LED as artificial light source, photosynthetic efficiency of crops and electrical energy consumption are affected by spectral characteristics of the LED. And most of previous observations on the spectral dependence of photosynthesis and optical property have been limited to a single leaf so far. The objectives of this study were to investigate photosynthetic efficiency and the related optical properties of four cultivars of lettuce (two reddish and two green leaves) and to quantify the spectral dependence of photosynthetic efficiency at the canopy level for selecting the optimum spectrum of LED regarding the electrical energy consumption. Absorptances, photosynthetic efficiencies of a single leaf of the plants, and electrical energy consumption of LED were measured at 18 wavelengths with a narrow band of 10 nm from 400 to 700 nm. Anthocyanin and chlorophyll contents (SPAD value) were measured to explain the difference between each cultivars. Light penetrations into crop canopy were estimated by models. Light absoprtances over PAR range were similar among the green and reddish lettuce cultivars, while that around 550 nm (green region) was slightly higher in the reddish leaves. Photosynthetic rates per incident photon of a single leaf had two peaks at 650-660 and 400-410 nm and those per absorbed photon (quantum yield) had three peaks at 650-660, 400-410, and 540-560 nm. In the green region of spectrum, both photosynthetic rates per incident photon and those per absorbed photon were lower in reddish cultivars than green ones. The differences in color and photosynthetic rate between reddish and green cultivars were due to anthocyanin contents in leaves. Spectral dependence of light absorptance at canopy level was much weaker than that at a single leaf. Light absorptance of green light was almost the same as that of blue or red light. As the quantum yield and absorptance of green light at canopy level was not lower than that of blue or red light, the photosynthetic efficiency of green light at canopy level became higher than that at the single leaf. Due to the fact that light conversion efficiency in terms of electrical energy consumption was lower in green LED than red or blue one, therefore, photosynthetic efficiency considering electrical energy consumption was much lower in green LED than that of blue or red LED even at canopy level. These results could reflect the actual plant response to light spectrum more accurately at canopy level and give more information to optimize the artificial lighting strategies for energy-saving.ABSTRACT CONTENTS LIST OF TABLES LIST OF FIGURES INTRODUCTION LITERATURE REVIEW Photosynthetic efficiency of plants Estimation of crop light interception Literature cited MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS APPENDIX ABSTRACT IN KOREANMaste

    Study on the Characteristics of Base Pressure and Heat Transfer by Underexpanding Jet

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :๊ณต๊ณผ๋Œ€ํ•™ ๊ธฐ๊ณ„ํ•ญ๊ณต๊ณตํ•™๋ถ€,2020. 2. ๊น€๊ทœํ™.๋น„ํ–‰ ์ค‘์ธ ์ดˆ์Œ์† ๋น„ํ–‰์ฒด์˜ ๋…ธ์ฆ์—์„œ ๋‚˜์˜ค๋Š” ์œ ๋™์ด ๊ณผ์†Œ ํŒฝ์ฐฝํ•  ๋•Œ ๊ธฐ์ €๋ฉด ์ฃผ์œ„์—์„œ๋Š” ์ž์œ ๋ฅ˜์™€ ๊ณผ์†Œ ํŒฝ์ฐฝํ•˜๋Š” ์ œํŠธ ์œ ๋™์ด ๋งŒ๋‚˜ ๋ณต์žกํ•œ ์œ ๋™ ํ˜„์ƒ์ด ๋ฐœ์ƒํ•œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์ด๋Ÿฌํ•œ ์ƒํ™ฉ์—์„œ ์ˆ˜์น˜ ํ•ด์„์„ ํ†ตํ•ด ๊ธฐ์ €๋ฉด ์ฃผ์œ„์—์„œ ๋ฐœ์ƒํ•˜๋Š” ๋‹ค์–‘ํ•œ ๋ฌผ๋ฆฌ์  ํ˜„์ƒ์„ ๊ทœ๋ช…ํ•˜๊ณ  ์ด์— ๋”ฐ๋ฅธ ๊ธฐ์ € ํ•ญ๋ ฅ๊ณผ ๊ธฐ์ €๋ฉด์œผ๋กœ์˜ ์—ด์ „๋‹ฌ๋Ÿ‰ ํŠน์„ฑ์„ ์—ฐ๊ตฌํ•˜์˜€๋‹ค. ๊ธฐ์ €๋ฉด ์ง๊ฒฝ, ๋™์ฒด์˜ ๊ธธ์ด์™€ ๊ฐ™์€ ๋น„ํ–‰์ฒด ํ˜•์ƒ๊ณผ ์ž์œ ๋ฅ˜ ๋งˆํ•˜์ˆ˜, ๋ฐฐ์••๋น„, ํ”Œ๋ฃธ ๋น„์—ด๋น„์™€ ๊ฐ™์€ ์œ ๋™ ์กฐ๊ฑด์ด ๊ธฐ์ € ํ•ญ๋ ฅ๊ณผ ์—ด์ „๋‹ฌ๋Ÿ‰์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ๋ถ„์„ํ•˜์˜€๋‹ค. ๋…ธ์ฆ ์ถœ๊ตฌ์˜ ํฌ๊ธฐ๊ฐ€ ๊ณ ์ •์ด๊ณ  ๊ธฐ์ €๋ฉด ์ง๊ฒฝ์ด ์ฆ๊ฐ€ํ•˜๋ฉด ๊ธฐ์ € ์••๋ ฅ์ด ๊ฐ์†Œํ•˜๊ณ  ์—ด์ „๋‹ฌ๋Ÿ‰๋„ ๊ฐ์†Œํ•œ๋‹ค. ๋™์ฒด์˜ ๊ธธ์ด๊ฐ€ ์ฆ๊ฐ€ํ•˜๋ฉด ๊ธฐ์ € ์••๋ ฅ์ด ์ฆ๊ฐ€ํ•˜๊ณ  ์—ด์ „๋‹ฌ๋Ÿ‰๋„ ์ฆ๊ฐ€ํ•œ๋‹ค. ๊ธฐ์ค€ ํ˜•์ƒ์— ๋Œ€ํ•˜์—ฌ ์ž์œ ๋ฅ˜ ๋งˆํ•˜์ˆ˜๊ฐ€ 3, 4, 5์ธ ๊ฒฝ์šฐ์— ๋Œ€ํ•˜์—ฌ ์ˆ˜์น˜ ํ•ด์„์„ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ์ž์œ ๋ฅ˜ ๋งˆํ•˜์ˆ˜๊ฐ€ ์ฆ๊ฐ€ํ•˜๋ฉด ๊ธฐ์ € ์••๋ ฅ์€ ๊ฐ์†Œํ•˜์ง€๋งŒ ์—ด์ „๋‹ฌ๋Ÿ‰์€ ์ฆ๊ฐ€ํ•œ๋‹ค. ๋ฐฐ์••๋น„๋Š” ์ œํŠธ ์œ ๋™์˜ ์••๋ ฅ๊ณผ ๋Œ€๊ธฐ์••์˜ ๋น„๋กœ ๊ฒฐ์ •๋˜๋ฉฐ ๋ฐฐ์••๋น„๊ฐ€ 5, 20, 35, 50, 65์ธ ๊ฒฝ์šฐ์— ๋Œ€ํ•˜์—ฌ ์—ฐ๊ตฌํ•˜์˜€๋‹ค. ๋ฐฐ์••๋น„๊ฐ€ ์ฆ๊ฐ€ํ•˜๋ฉด ๊ธฐ์ € ์••๋ ฅ์ด ์ฆ๊ฐ€ํ•˜์ง€๋งŒ ์—ด์ „๋‹ฌ๋Ÿ‰์€ ๊ฐ์†Œํ•œ๋‹ค. ํ”Œ๋ฃธ ๋น„์—ด๋น„๊ฐ€ 1.1, 1.2, 1.3, 1.4์ผ ๋•Œ์˜ ๊ธฐ์ € ์••๋ ฅ ๋ฐ ์—ด์ „๋‹ฌ๋Ÿ‰ ํŠน์„ฑ์„ ์—ฐ๊ตฌํ•˜์˜€๋‹ค. ํ”Œ๋ฃธ ๋น„์—ด๋น„๊ฐ€ ์ฆ๊ฐ€ํ• ์ˆ˜๋ก ๊ธฐ์ € ์••๋ ฅ์€ ๊ฐ์†Œํ•˜๋ฉฐ ์—ด์ „๋‹ฌ๋Ÿ‰๋„ ๊ฐ์†Œํ•œ๋‹ค. ์ด์™€ ๊ฐ™์ด ๊ณผ์†Œ ํŒฝ์ฐฝํ•˜๋Š” ์ œํŠธ์— ์˜ํ•ด ์ „๋‹ฌ๋˜๋Š” ๊ธฐ์ € ํ•ญ๋ ฅ๊ณผ ์—ด์ „๋‹ฌ๋Ÿ‰์€ ๋‹ค์–‘ํ•œ ์š”์ธ๋“ค์— ์˜ํ•ด์„œ ์˜ํ–ฅ์„ ๋ฐ›๊ณ  ๊ฐ ์š”์ธ๋“ค์ด ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ๋ฌผ๋ฆฌ์ ์ธ ์ด์œ ๊ฐ€ ๋‹ค๋ฅด๊ธฐ ๋•Œ๋ฌธ์— ํ•˜๋‚˜์˜ ์‹คํ—˜์‹์ด๋‚˜ ์ด๋ก ์œผ๋กœ ์ •๋ฆฝ๋  ์ˆ˜ ์—†์œผ๋ฉฐ ์ƒˆ๋กœ์šด ์ดˆ์Œ์† ๋น„ํ–‰์ฒด์˜ ๊ฐœ๋ฐœ ์‹œ ์ด๋ฅผ ํ•„์ˆ˜์ ์œผ๋กœ ๊ณ ๋ คํ•ด์•ผํ•œ๋‹ค.When the flow from the nozzle of a supersonic vehicle in flight highly underexpands, a complex flow phenomenon occurs due to the interaction of freestream flow and the underexpanded jet around the base. In this situation, this study attempted to identify physical phenomena and research the characteristics of base drag and heat transfer through numerical analysis. The effects of vehicle shape such as base diameter and fuselage length and flow conditions such as freestream Mach number, back pressure ratio and plume specific heat constant were analyzed. If the nozzle exit is fixed in size and the base diameter increases,the base pressure decreases and the heat transfer rate decreases. As the fuselage length increases, the base pressure increases and the heat transfer rate increases. In order to investigate the influence of freestream Mach, numerical analysis were performed for the Mach 3, 4, 5. As the freestream Mach number increases, the base pressure decreases but the heat transfer rate increases. The back pressure ratio is determined by the ratio of the jet pressure to the atmospheric pressure and the back pressure ratios were studied for 5, 20, 35, 50 and 65. As the back pressure ratio increases, the base pressure increases but the heat transfer rate decreases. The base drag and heat transfer rate characteristics of the plume specific heat constant ratios of 1.1, 1.2, 1.3 and 1.4 were studied. As the plume specific heat constant ratio increases, the base pressure decreases and the heat transfer rate decreases. Since the base drag and heat transfer delivered by underexpanded jets are influenced by various factors and the physical reasons for each of these factors are different. Therefore, they cannot be established by one empirical formula or theory. This must be taken into account during a new supersonic vehicle development.์ œ 1 ์žฅ ์„œ๋ก  1 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ 1 ์ œ 2 ์ ˆ ๊ธฐ์กด ์—ฐ๊ตฌ ๋™ํ–ฅ 9 ์ œ 3 ์ ˆ ์—ฐ๊ตฌ ๋‚ด์šฉ 14 ์ œ 2 ์žฅ ์ง€๋ฐฐ๋ฐฉ์ •์‹๊ณผ ์ˆ˜์น˜ ๊ธฐ๋ฒ• 17 ์ œ 1 ์ ˆ ํ™”ํ•™์ข… ๋ฐฉ์ •์‹์ด ํฌํ•จ๋œ ์ง€๋ฐฐ๋ฐฉ์ •์‹ 17 ์ œ 2 ์ ˆ ์ˆ˜์น˜ ๊ธฐ๋ฒ• 25 ์ œ 3 ์žฅ ์ˆ˜์น˜ ํ•ด์„ ์ฝ”๋“œ ๊ฒ€์ฆ๊ณผ ๊ฒฉ์ž ์ˆ˜๋ ด๋„ ์‹œํ—˜ 32 ์ œ 1 ์ ˆ ์ˆ˜์น˜ ํ•ด์„ ์ฝ”๋“œ์˜ ๊ฒ€์ฆ 32 ์ œ 2 ์ ˆ ๊ฒฉ์ž ์ˆ˜๋ ด๋„ ์‹œํ—˜ 42 ์ œ 3 ์ ˆ ๋‹คํ™”ํ•™์ข…๊ณผ 2ํ™”ํ•™์ข… ํ”Œ๋ฃธ ๋ชจ๋ธ ๋น„๊ต 44 ์ œ 4 ์žฅ ๋น„ํ–‰์ฒด ํ˜•์ƒ์— ๋”ฐ๋ฅธ ๊ธฐ์ € ์œ ๋™ ๋ณ€ํ™” 48 ์ œ 1 ์ ˆ ๊ธฐ์ €๋ฉด ์ง๊ฒฝ 51 ์ œ 2 ์ ˆ ๋™์ฒด ๊ธธ์ด 63 ์ œ 5 ์žฅ ์œ ๋™ ์กฐ๊ฑด์— ๋”ฐ๋ฅธ ๊ธฐ์ € ์œ ๋™ ๋ณ€ํ™” 74 ์ œ 1 ์ ˆ ์ž์œ ๋ฅ˜ ๋งˆํ•˜์ˆ˜ 75 ์ œ 2 ์ ˆ ๋ฐฐ์••๋น„ 88 ์ œ 3 ์ ˆ ํ”Œ๋ฃธ ๋น„์—ด๋น„ 104 ์ œ 6 ์žฅ ๊ฒฐ๋ก  119 Appendix 122 ์ฐธ๊ณ ๋ฌธํ—Œ 144 Abstract 151Docto

    Growth Estimation of Hydroponically-grown Bell Pepper (Capsicum annuum L.) using Recurrent Neural Network through Nondestructive Measurement of Leaf Area Index and Fresh Weight

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :๋†์—…์ƒ๋ช…๊ณผํ•™๋Œ€ํ•™ ์‹๋ฌผ์ƒ์‚ฐ๊ณผํ•™๋ถ€,2019. 8. ์†์ •์ต.ICT ๊ธฐ์ˆ ์ด ๊ธฐ์กด์˜ ๋†์—… ๊ธฐ์ˆ ์— ์ ์šฉ๋˜๋ฉด์„œ ์Šค๋งˆํŠธ ํŒœ์ด ๋Œ€๋‘๋˜๊ณ  ์žˆ๋‹ค. ์Šค๋งˆํŠธ ํŒœ์˜ ์™„์„ฑ์„ ์œ„ํ•ด์„œ๋Š” ์ž‘๋ฌผ๊ณผ ํ™˜๊ฒฝ ์‚ฌ์ด์˜ ๋ณต์žกํ•˜๊ณ  ๋‹ค์–‘ํ•˜๊ณ  ์˜ˆ์ธก ๋ถˆ๊ฐ€๋Šฅํ•œ ๊ด€๊ณ„์— ๋Œ€ํ•œ ์ •๋Ÿ‰์ ์ธ ๋ถ„์„์ด ๊ฐ€๋Šฅํ•ด์•ผ ํ•œ๋‹ค. ์ด๋ฅผ ์œ„ํ•ด ํ™˜๊ฒฝ์— ๋Œ€ํ•œ ์ž‘๋ฌผ์˜ ๋ฐ˜์‘์„ ์—ฐ์†์ , ์ž๋™์ , ๋น„ํŒŒ๊ดด์ ์œผ๋กœ ๋ชจ๋‹ˆํ„ฐ๋งํ•  ์ˆ˜ ์žˆ๋Š” ์‹œ์Šคํ…œ๊ณผ ๋†์—… ๋น…๋ฐ์ดํ„ฐ๋ฅผ ํ•ด์„ํ•  ์ˆ˜ ์žˆ๋Š” ์ƒˆ๋กœ์šด ์•Œ๊ณ ๋ฆฌ์ฆ˜ ๊ฐœ๋ฐœ์ด ์š”๊ตฌ๋œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ํŒŒํ”„๋ฆฌ์นด ์ˆ˜๊ฒฝ ์žฌ๋ฐฐ ์กฐ๊ฑด์—์„œ ๋‹ค์–‘ํ•œ ํ™˜๊ฒฝ ์š”์ธ์— ์˜ํ•œ ์ž‘๋ฌผ์˜ ์ƒ์œก์˜ ๋ณ€ํ™”๋ฅผ ์˜ˆ์ธกํ•˜๋Š” ์ˆœํ™˜ ์‹ ๊ฒฝ ํšŒ๋กœ๋ง ๊ธฐ๋ฐ˜ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ๊ฐœ๋ฐœํ•˜์˜€๋‹ค. ํŒŒํ”„๋ฆฌ์นด์˜ ์ƒ์œก ์˜ˆ์ธก ์•Œ๊ณ ๋ฆฌ์ฆ˜ ๊ฐœ๋ฐœ์— ์•ž์„œ ์ฃผ์š”ํ•œ ์ƒ์œก ๋ณ€์ˆ˜์ธ ์—ฝ๋ฉด์  ์ง€์ˆ˜(LAI)์™€ ์ž‘๋ฌผ์˜ ์ƒ์ฒด์ค‘ ์ •๋ณด๋ฅผ ์ž๋™์ , ์—ฐ์†์ ์œผ๋กœ ์ˆ˜์ง‘ํ•  ์ˆ˜ ์žˆ๋Š” ์‹œ์Šคํ…œ ๊ฐœ๋ฐœ์„ ์„ ํ–‰ํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๊ธฐ์กด์˜ LAI ๋น„ํŒŒ๊ดด์  ์ธก์ • ๋ฐฉ๋ฒ•๋ก ์—์„œ ๊ณ ๋ คํ•˜์ง€ ์•Š์•˜๋˜ ์š”์ธ๋“ค(๊ธฐ์ƒ ์กฐ๊ฑด, ์ธก์ • ์‹œ๊ฐ„)์— ๋Œ€ํ•œ ์ •๋Ÿ‰์ ์ธ ๋ถ„์„์„ ์ถ”๊ฐ€ํ•˜์˜€๋‹ค. ์ด๋Ÿฌํ•œ ์š”์ธ๋“ค์„ ๋ถ„์„ํ•˜๊ธฐ ์œ„ํ•ด ๊ด‘์ถ”์  ์‹œ๋ฎฌ๋ ˆ์ด์…˜๊ณผ ์ธ๊ณต์‹ ๊ฒฝํšŒ๋กœ๋ง ๊ธฐ๊ณ„ ํ•™์Šต์„ ํ™œ์šฉํ•˜์˜€๋‹ค. ๊ฐœ๋ฐœ๋œ LAI์ธก์ • ์‹œ์Šคํ…œ์€ ๋†’์€ ์ •ํ™•๋„๋กœ ์‹ค์ œ LAI๋ฅผ ์ถ”์ •ํ•˜๋Š” ๊ฒƒ์ด ๊ฐ€๋Šฅํ•˜์˜€๋‹ค. ์ž‘๋ฌผ์˜ ์ƒ์ฒด์ค‘ ์ •๋ณด ์ˆ˜์ง‘ ์‹œ์Šคํ…œ์€ ํŒŒํ”„๋ฆฌ์นด์˜ ์ƒ๋ฆฌ์ , ์žฌ๋ฐฐ์  ํŠน์„ฑ์„ ๋ฐ˜์˜ํ•˜์—ฌ ์žฌ๋ฐฐ ์‹œ์Šคํ…œ ์ „์ฒด์˜ ๋ฌด๊ฒŒ๋ฅผ ์ธก์ •ํ•  ์ˆ˜ ์žˆ๋Š” ํ˜•ํƒœ๋กœ ์„ค๊ณ„ํ•˜์˜€๋‹ค. ๋˜ํ•œ ๋ฐฐ์ง€์˜ ๋‚ด ์ˆ˜๋ถ„์˜ ๋ฌด๊ฒŒ๋ฅผ ๋ฐฐ์ง€ ๋‚ด ํ•จ์ˆ˜์œจ์„ ํ†ตํ•ด ๋ณด์ •ํ•˜์—ฌ ์ž‘๋ฌผ์˜ ์ƒ์ฒด์ค‘์„ ๊ณ„์‚ฐํ•˜์˜€๋‹ค. ๊ฐœ๋ฐœ๋œ ์ƒ์ฒด์ค‘ ์ธก์ • ์‹œ์Šคํ…œ์€ ๋†’์€ ์ •ํ™•๋„๋กœ ์‹ค์ œ ์ƒ์ฒด์ค‘์„ ์ถ”์ •ํ•˜๋Š” ๊ฒƒ์ด ๊ฐ€๋Šฅํ•˜์˜€๋‹ค. ๊ฐœ๋ฐœ๋œ ์ž‘๋ฌผ ํŠน์„ฑ ์ธก์ • ์‹œ์Šคํ…œ์„ ์ด์šฉํ•˜์—ฌ ์ˆ˜์ง‘๋œ ์ž‘๋ฌผ ์ƒ์œก ์ •๋ณด์™€ ์„ผ์„œ๋ฅผ ์ด์šฉํ•˜์—ฌ ์ˆ˜์ง‘๋œ ํ™˜๊ฒฝ ๋ณ€์ˆ˜๋ฅผ ์ด์šฉํ•˜์—ฌ ์ž‘๋ฌผ ์ƒ์œก ์˜ˆ์ธก ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ๊ธฐ๊ณ„ ํ•™์Šตํ•˜์˜€๋‹ค. ์ž‘๋ฌผ์˜ ์ƒ์œก์€ ๊ณผ๊ฑฐ๋กœ๋ถ€ํ„ฐ ๋ˆ„์ ๋œ ํ™˜๊ฒฝ ์š”์ธ์— ์˜ํ•ด ๊ฒฐ์ •๋˜๊ธฐ ๋•Œ๋ฌธ์— ์‹œ๊ณ„์—ด ๋ฐ์ดํ„ฐ ๋ถ„์„์— ํŠนํ™”๋˜์–ด ์žˆ๋Š” ์ˆœํ™˜์‹ ๊ฒฝํšŒ๋กœ๋ง ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ํ™œ์šฉํ•˜์˜€๋‹ค. ์•Œ๊ณ ๋ฆฌ์ฆ˜์˜ ํ•™์Šต ์ •ํ™•๋„๋ฅผ ์ด์šฉํ•˜์—ฌ ์ฃผ์š”ํ•œ ํ™˜๊ฒฝ ์š”์ธ์„ ์„ ์ •ํ•˜๊ณ  ์ตœ์ ์˜ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ๊ฐœ๋ฐœํ•˜์˜€๋‹ค. ๊ฐœ๋ฐœ๋œ ์•Œ๊ณ ๋ฆฌ์ฆ˜์˜ ํ•™์Šต ์ •ํ™•๋„๋ฅผ ๊ฒ€์ฆํ•˜๊ธฐ ์œ„ํ•ด ์•Œ๊ณ ๋ฆฌ์ฆ˜ ํ•™์Šต ์กฐ๊ฑด๊ณผ ๋…๋ฆฝ๋œ ์‹คํ—˜ ์กฐ๊ฑด์—์„œ ์ถ”๊ฐ€ ์ž๋ฃŒ๋ฅผ ์ˆ˜์ง‘ํ•˜์˜€๋‹ค. ๊ฐœ๋ฐœ๋œ ์•Œ๊ณ ๋ฆฌ์ฆ˜์˜ ์ •ํ™•๋„๋ฅผ ํ‰๊ฐ€ํ•˜๊ธฐ ์œ„ํ•ด ๊ธฐ์กด์˜ ์ˆ˜์‹ ๊ธฐ๋ฐ˜ ์ž‘๋ฌผ ์ƒ์œก ๋ชจ๋ธ์˜ ์ •ํ™•๋„์™€ ๋น„๊ต ๋ถ„์„ํ•˜์˜€๋‹ค. ๊ฒ€์ฆ ๊ฒฐ๊ณผ ๊ฐœ๋ฐœ๋œ ์ƒ์œก ์˜ˆ์ธก ์•Œ๊ณ ๋ฆฌ์ฆ˜์€ ์ž‘๋ฌผ ์ƒ์œก ๋ชจ๋ธ๋ณด๋‹ค ๋” ๋†’๊ฑฐ๋‚˜ ๋น„์Šทํ•œ ์ˆ˜์ค€์˜ ์ •ํ™•๋„๋ฅผ ๋‚˜ํƒ€๋‚ด์—ˆ๋‹ค. ๊ฒฐ๊ณผ์ ์œผ๋กœ ๋ณธ ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด ๊ฐœ๋ฐœ๋œ ์ž‘๋ฌผ ์ƒ์œก ํŠน์„ฑ ์ธก์ • ์‹œ์Šคํ…œ๊ณผ ์ž‘๋ฌผ ์ƒ์œก ์ถ”์ • ์•Œ๊ณ ๋ฆฌ์ฆ˜์€ ์ž‘๋ฌผ์˜ ์ƒ์œก ์ •๋ณด๋ฅผ ์—ฐ์†์ ์œผ๋กœ ์ˆ˜์ง‘ํ•˜๊ฑฐ๋‚˜ ์ž‘๋ฌผ ์ƒ์œก๊ณผ ํ™˜๊ฒฝ ์‚ฌ์ด์˜ ๊ด€๊ณ„๋ฅผ ์ •๋Ÿ‰์ ์œผ๋กœ ๋ถ„์„ํ•˜๋Š” ๋ฐ ์œ ์šฉํ•œ ๋„๊ตฌ๋กœ ํ™œ์šฉ ๊ฐ€๋Šฅํ•  ๊ฒƒ์œผ๋กœ ํŒ๋‹จํ•˜์˜€๋‹ค.Smart farms are emerging as ICT technologies have recently been applied to existing agricultural technologies. Completion of smart farms requires quantitative analysis of complex, diverse, and unpredictable relationships between crops and the environment. This calls for the development of new algorithms to interpret agricultural big data and systems that can continuously, automatically, and non-destructively monitor the response of crops to the environment. In this study, an algorithm was developed to estimate the growth of hydroponically grown bell pepper crops in response to environmental factors. The development of measuring methods that could automatically and continuously collect the growth characteristics was preceded. The leaf area index (LAI) of the bell pepper crops was estimated using light interception profile of crop canopy, including quantitative relationship between external weather, and time factors. Ray-tracing simulation and machine learning were used to analyze these factors quantitatively. The actual LAI was estimated with high accuracy for the developed method. The fresh weight measurement system of was designed to measure the weight of the total cultivation system considering the physiological and cultural characteristics of bell pepper crops. In addition, changes of water content in the substrate were corrected to calculate only the fresh weight of the crop. Developed fresh weight measurement systems were able to estimate the actual fresh weight with high accuracy. With crop growth characteristics collected using the developed measurement methods, and the environment factors collected using sensors, the crop growth estimation algorithm was machine learned. As crop growth affected by cumulative changes of the environmental factors, the RNN algorithm, specialized in chronologically data, was selected. Using the training test accuracy, major environmental factors were selected and the optimal algorithm was developed. Additional data were collected from the experimental conditions independently of the algorithm training conditions, to validate the developed algorithm. The accuracy of the process-based growth model (PBM) was compared to evaluate that of the developed algorithm. In validation, the accuracy of the developed algorithm showed a similar to or higher than that of the PBM. Therefore it was conformed that the growth characteristics of crops could be collected as big data and the crop growth could be efficiently analyzed by using the systems and methodologies developed in this study.GENERAL INTRODUCTION 1 LITERATURE REVIEW 3 Non-destructive measurements of leaf area index. 3 Non-destructive measurements of crop fresh weight 4 Crop growth models 5 Application of artificial neural network to agricultural research . 6 LITERATURE CITED . 7 CHAPTER 1. Estimating Leaf Area Index of Bell Pepper According to Growth Stage Using Ray-tracing Simulation and Long Short-term Memory 26 ABSTRACT . 26 INTRODUCTION 28 MATERIALS AND METHODS 31 RESULTS AND DISCUSSION . 35 LITERATURE CITED 41 CHAPTER 2. Nondestructive and Continuous Measurement of Fresh Weights of Hydroponically-grown Bell Pepper 65 ABSTRACT . 65 INTRODUCTION 67 MATERIALS AND METHODS 70 RESULTS AND DISCUSSION . 75 LITERATURE CITED 82 CHAPTER 3. Development of Growth Estimation Algorithms for Hydroponicallygrown Bell Pepper Based on Recurrent Neural Network 100 ABSTRACT . 100 INTRODUCTION 102 MATERIALS AND METHODS 104 RESULTS AND DISCUSSION . 109 LITERATURE CITED 114 CHAPTER 4. Validation and Evaluation of Growth Estimation Algorithms for Hydroponically-grown Bell Pepper Based on Recurrent Neural Network 128 ABSTRACT . 128 INTRODUCTION 130 MATERIALS AND METHODS 132 RESULTS AND DISCUSSION . 135 LITERATURE CITED . 139 CONCLUSIONS 158 ABSTRACT IN KOREAN 160Docto

    POM ๊ณต์ •์—์„œ ๊ณ ์ˆœ๋„ formaldehyde ์ƒ์‚ฐ์„ ์œ„ํ•œ ํ˜ผํ•ฉ๋ฌผ์˜ ์ €์•• ๊ธฐ์•ก ์ƒํ‰ํ˜•

    No full text
    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :ํ™”ํ•™์ƒ๋ฌผ๊ณตํ•™๋ถ€,2006.Maste

    ๋ณ€๋™์„ฑ ์Šคํ”„๋ ˆ๋“œ๊ฐ€ ๊ฐ€์ง€๋Š” ์ •๋ณดํšจ๊ณผ์— ๋Œ€ํ•œ ์›์ธ๋ถ„์„

    No full text
    ๊ตญ๋‚ด ๊ธˆ์œต์‹œ์žฅ ์ž์œจํ™” ๋ฐ ๊ฐœ๋ฐฉํ™” ์ •์ฑ…์˜ ์ผํ™˜์œผ๋กœ KOSPI200์„ ๋ฌผ๊ณผ KOSPI 200์˜ต์…˜์ด ๋„์ž…๋จ์œผ๋กœ์จ ํ•œ๊ตญ์‹œ์žฅ์—๋„ ํŒŒ์ƒ์ƒํ’ˆ์˜ ์‹œ๋Œ€๊ฐ€ ์—ด๋ฆฌ๊ฒŒ ๋˜์—ˆ๋‹ค. KOSPI200 ์„ ๋ฌผ ์˜ต์…˜์˜ ๋„์ž… ์ดˆ๊ธฐ์—๋Š” ํˆฌ๊ธฐ๋ชฉ์ ์„ ์ง€๋‹Œ ํˆฌ๊ธฐ์ž๋“ค์— ์˜ํ•ด ์ฃผ๋กœ ๊ฑฐ๋ž˜๊ฐ€ ์ด๋ฃจ์–ด ์กŒ์ง€๋งŒ, ์ง€์†์ ์ธ ์„ฑ์žฅ์„ ๊ฑฐ๋“ญํ•˜์—ฌ ๊ฑฐ๋ž˜๋Ÿ‰ ๋ฉด์—์„œ ์„ธ๊ณ„ 1์œ„์ธ ํฐ ์‹œ์žฅ์œผ๋กœ ๋ฐœ์ „ ํ•˜๊ฒŒ ๋˜์—ˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” KOSPI200์ง€์ˆ˜์˜ต์…˜์˜ ๋“ฑ๊ฐ€๊ฒฉ ์ฝœ์˜ต์…˜๊ณผ ํ’‹์˜ต์…˜์—์„œ ๊ตฌํ•  ์ˆ˜ ์žˆ๋Š” ๋‚ด์žฌ ๋ณ€๋™์„ฑ์˜ ์Šคํ”„๋ ˆ๋“œ๊ฐ€ KOSPI200์ง€์ˆ˜ ์ˆ˜์ต๋ฅ ์„ ์„ ํ–‰ํ•จ์„ ๋ฐํ˜”๋‹ค. ๋‚˜์•„๊ฐ€ ๋ณ€๋™์„ฑ ์Šคํ”„๋ ˆ๋“œ์˜ ๊ทผ๋ณธ์ ์ธ ์›์ธ์ด ํ˜„๋ฌผ๊ณผ ์„ ๋ฌผ์˜ ์Šคํ”„๋ ˆ๋“œ์ž„์„ ๋ฐํžˆ๊ณ , VAR ๋ชจํ˜•์„ ํ†ตํ•ด ํ˜„๋ฌผ๊ณผ ์„ ๋ฌผ์˜ ์Šคํ”„๋ ˆ๋“œ๊ฐ€ ๊ฐ€์žฅ ๊ฐ•๋ ฅํ•œ ์ •๋ณด๋ ฅ์ž„์„ ๋ณด์ž„๊ณผ ๋™์‹œ์— ์ด๋ก ์ ์ธ ์„ค๋ช…์„ ํ†ตํ•ด ํ˜„๋ฌผ๊ณผ ์„ ๋ฌผ์˜ ์Šคํ”„๋ ˆ๋“œ๊ฐ€ KOSPI200 ์ง€์ˆ˜ ์ˆ˜์ต๋ฅ ์„ ์„ ๋„ํ•จ์„ ๋ฐํ˜”๋‹ค.Maste

    Optimization of acquisition parameters of diffusion-tensor MR imaging in the spinal cord

    No full text
    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์˜ํ•™๊ณผ ๋ฐฉ์‚ฌ์„ ๊ณผํ•™์ „๊ณต,2006.Docto

    A Study on Expression of Identity-Fluid through Disturbance of Semanic Systems of Ideology -Based on my works-

    No full text
    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๋ฏธ์ˆ ๋Œ€ํ•™ ์„œ์–‘ํ™”๊ณผ, 2018. 8. ์‹ฌ์ฒ ์›….๋‚˜์˜ ์ฒซ ๋ฒˆ์งธ ๊ฐœ์ธ์ „ ์ œ๋ชฉ์€ ์ €๋Š” ์ž…๋‹ˆ๋‹ค.์ด๋‹ค. ์ด ๋ฌธ์žฅ์˜ ๋ชฉ์ ์–ด์— ํ•ด๋‹นํ•˜๋Š” ๋‚˜์˜ ์ด๋ฆ„์€ ํˆฌ๋ช…ํ•œ ๊ธ€์ž๋กœ ์ถœ๋ ฅํ•˜์˜€๋‹ค. ์ด๋Ÿฌํ•œ ํ‘œํ˜„์€ ๋‚˜์˜ ์„ฑ ์ •์ฒด์„ฑ๊ณผ ๋‚˜์™€ ์—ฐ๊ด€๋˜์–ด ์žˆ๋Š” ๋ฏธ๊ตญ ์ด๋ฏผ ์‚ฌํšŒ ์† ํƒ€์ž๋กœ์„œ์˜ ์ •์ฒด์„ฑ์„ ์ง์ ‘์ ์œผ๋กœ ๋“œ๋Ÿฌ๋‚ผ ์ˆ˜ ์—†๋Š” ์‚ฌํšŒ, ์ •์น˜์  ๋งฅ๋ฝ์„ ๋“œ๋Ÿฌ๋‚ด๊ธฐ ์œ„ํ•จ์ด์—ˆ๋‹ค. ์ •์ฒด์„ฑ์€ ๊ฐ๊ฐ์˜ ๊ณ ์œ ํ•œ ์ž์•„๊ฐ€ ์ฒ˜ํ•œ ์ •์น˜, ๊ฒฝ์ œ, ๋ฌธํ™” ๋“ฑ์˜ ๋งฅ๋ฝ์—์„œ ์ž๊ธฐ ์Šค์Šค๋กœ๋ฅผ ๊ทœ๋ช…ํ•˜๋Š” ๊ฒƒ๊ณผ ๊ฐ™๋‹ค๊ณ  ํ•  ๋•Œ, ๋‚˜์˜ ์ •์ฒด์„ฑ์€ ์—ฌ๋Ÿฌ ๋‹ค์–‘ํ•œ ๋งฅ๋ฝ์˜ ๊ฒƒ๋“ค๋กœ ๊ตฌ์„ฑ๋  ๊ฒƒ์ด๋‹ค. ํ•˜์ง€๋งŒ ์ฒซ ๋ฒˆ์งธ ๊ฐœ์ธ์ „์—์„œ ํ™•์ธํ•  ์ˆ˜ ์žˆ๋“ฏ์ด, ๋‚˜์˜ ํŠน์ • ์ •์ฒด์„ฑ๋“ค์€ ์ €๋Š” ์ž…๋‹ˆ๋‹ค.์™€ ๊ฐ™์ด ๊ฐ์ถ”๊ฑฐ๋‚˜ ์ง์ ‘์ ์œผ๋กœ ๋ฐœํ˜„๋˜์ง€ ์•Š๋Š” ์ƒํƒœ์˜ ๊ฒƒ๋“ค์ด๋‹ค. ์ฆ‰ ๋‚˜์˜ ์ž‘์—…์—์„œ ์ •์ฒด์„ฑ์ด๋ž€ ๊ทธ๊ฒƒ์ด ์ฒ˜ํ•ด ์žˆ๋Š” ์ •์น˜, ๊ฒฝ์ œ, ๋ฌธํ™”์  ์ด๋ฐ์˜ฌ๋กœ๊ธฐ์— ์˜ํ•ด ํŠน์ •์ ์œผ๋กœ ๋ช…๋ช…๋˜๋Š” ๋ถ„๋ฅ˜์˜ ๊ฐœ๋…์— ๊ฐ€๊น๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ๊ณ ์œ ํ•œ ๊ฐ๊ฐ์˜ ์ •์ฒด์„ฑ์„ ์ƒ์ง•ํ™”-์†Œ์ˆ˜, ํƒ€์ž, ํŠน์ •์„ธ๋Œ€ ๋“ฑ์œผ๋กœ ํ‘œ์ƒํ•˜๊ณ  ์žˆ๋Š”-ํ•˜๋Š” ์ง€๋ฐฐ ์ด๋ฐ์˜ฌ๋กœ๊ธฐ์˜ ์˜๋ฏธ์ฒด๊ณ„๋ฅผ ๊ต๋ž€์‹œํ‚ค๊ณ , ์ด๋ฅผ ํ†ตํ•ด์„œ ์œ ๋™์  ์ •์ฒด์„ฑ(identity-fluid) ์„ ํ˜•์„ฑํ•˜๋Š” ๊ณผ์ •์„ ์ž‘ํ’ˆ์„ ํ†ตํ•ด ์‚ดํŽด๋ณด๊ณ ์ž ํ•œ๋‹ค. ์œ ๋™์  ์ •์ฒด์„ฑ์€ ์ •์ฒด์„ฑ ์ •์น˜ ์† ๋‹จํŽธํ™”๋œ ์ •์ฒด์„ฑ์—์„œ ๋ฒ—์–ด๋‚˜, ๋‹ค์–‘ํ•œ ๋งฅ๋ฝ์˜ ํ˜•์„ฑ๊ณผ ์ˆ˜์ •์ด ๊ฐ€๋Šฅํ•œ ์ƒํƒœ์˜ ์ •์ฒด์„ฑ์„ ์˜๋ฏธํ•œ๋‹ค. ๋˜ํ•œ ์œ ๋™์  ์ •์ฒด์„ฑ์€ ๋ณธ์งˆ์ฃผ์˜์  ์ž…์žฅ์—์„œ ์ƒ์„ฑ๋˜๋Š” ๊ฒƒ์ด ์•„๋‹ˆ๋ผ, ๊ตฌ์กฐ์ฃผ์˜์  ์ž…์žฅ์—์„œ ๊ตฌ์„ฑ๋œ๋‹ค. ๋‚˜์˜ ์ •์ฒด์„ฑ์— ๋Œ€ํ•œ ๊ด€์‹ฌ๊ณผ ์—ฐ๊ตฌ๋Š” ์ž์‹ ์˜ ์„ฑ ์ •์ฒด์„ฑ์ด ๋‹ค์ˆ˜์˜ ์„ฑ ์ •์ฒด์„ฑ๊ณผ ๋‹ค๋ฆ„์„ ์ธ์ง€ํ•˜๊ฒŒ ๋˜๋ฉด์„œ๋ถ€ํ„ฐ ์‹œ์ž‘๋˜์—ˆ๋‹ค. ์ž‘ํ’ˆ ํ™œ๋™ ์ดˆ๊ธฐ, ์ด๋Ÿฌํ•œ ๋‹ค๋ฆ„์˜ ์ธ์‹์€ ์ผ์ฐจ์ ์œผ๋กœ ๋‹ค์ˆ˜์˜ ์ •์ฒด์„ฑ๋“ค๋กœ๋ถ€ํ„ฐ ๋‚˜์˜ ์„ฑ ์ •์ฒด์„ฑ์„ ๊ตฌ๋ณ„ํ•ด ๋‚ด๋Š” ๊ณผ์ •์„ ์ˆ˜๋ฐ˜ํ•˜์˜€๋‹ค. ๊ทธ๋ฆฌ๊ณ  ๊ทธ ๊ณผ์ •์€ ๋‚˜์—๊ฒŒ ๊ธฐ์กด์˜ ์ด์„ฑ์•  ์ค‘์‹ฌ์  ์‚ฌํšŒ๊ตฌ์กฐ์™€ ์ •์น˜์ ์œผ๋กœ ์‚ฌ์šฉ๋˜๊ณ  ์žˆ๋Š” ๊ณ ์•ˆ๋œ ๋‚จ์„ฑ์„ฑ์— ๋Œ€ํ•œ ์ผ์ฐจ์ ์ธ ๋ฐ˜๊ฐ์„ ๋ถˆ๋Ÿฌ์™”๋‹ค. ๋˜ํ•œ ์ด๋Ÿฌํ•œ ํŠน์ • ์„ฑ ์ •์ฒด์„ฑ ๋ฐฐ์ œ์˜ ๋…ผ๋ฆฌ์™€ ์™œ๊ณก๋œ ๋‚จ์„ฑ์„ฑ์˜ ์ด๋ฏธ์ง€๋“ค์ด ๊ตญ๊ฐ€ ์ง‘๋‹จ, ๊ตฐ๋Œ€ ์ง‘๋‹จ ๋“ฑ์—์„œ ์ง€๋ฐฐ์˜ ์ด๋ฐ์˜ฌ๋กœ๊ธฐ๋ฅผ ๊ตฌ์„ฑ์›์—๊ฒŒ ์ „ํŒŒ-์€๋ฐ€ํ•˜๊ณ  ๋ฌด์˜์‹์ ์ธ ์ธก๋ฉด์—์„œ ์ˆ˜์šฉํ•˜๋„๋ก-ํ•˜๊ธฐ ์œ„ํ•œ ์ƒ์ง•์˜ ํ˜•ํƒœ๋“ค๋กœ ๊ณ ์•ˆ๋˜์–ด ์ง€์†์ ์œผ๋กœ ์žฌ์ƒ์‚ฐ๋˜๊ณ  ์žˆ์Œ์„ ๋ฐœ๊ฒฌํ•˜์˜€๋‹ค. ๋‚˜๋Š” ์ž‘ํ’ˆ (2009)์—์„œ ๊ตฐ๊ฐ€๋ผ๋Š” ์ƒ์ง•์„ ํ†ตํ•ด ์ด์— ๋Œ€ํ•œ ๋น„ํŒ์  ๋…ผ์˜๋ฅผ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ํ•˜์ง€๋งŒ ์œ„์™€ ๊ฐ™์€ ์ฃผ๋ฅ˜ ์ •์ฒด์„ฑ๊ณผ์˜ ๋น„๊ต, ๋‹ค์ˆ˜๋กœ๋ถ€ํ„ฐ์˜ ๊ตฌ๋ณ„๋กœ ์ธํ•œ ๋ถˆํ•ฉ๋ฆฌํ•จ์˜ ํ‘œํ˜„์€ ๋‚˜์˜ ์ •์ฒด์„ฑ์ด ์ด์„ฑ์• ์˜ ๋ฐ˜๋Œ€, ์ค‘์‹ฌ์ด ์•„๋‹Œ ์ฃผ๋ณ€, ๋‹ค์ˆ˜๊ฐ€ ์•„๋‹Œ ์†Œ์ˆ˜๋กœ์„œ์˜ ํƒ€์ž์™€ ๊ฐ™์€ ๊ธฐ์กด์˜ ์ด๋ถ„๋ฒ•์  ๋Œ€์น˜ ๊ตฌ์กฐ์— ๋‹น์ฐฉํ•˜๊ณ  ์žˆ์Œ์„ ์ž๊ฐํ•˜๊ฒŒ ๋˜์—ˆ๋‹ค. ๋˜ํ•œ ์ด๋Ÿฌํ•œ ์ด๋ถ„๋ฒ•์  ๋Œ€์น˜ ์†์—์„œ ์ •์ฒด์„ฑ ํ‘œํ˜„์€ ์ž์•„์˜ ๊ณ ์œ ํ•œ ์„œ์‚ฌ๋ฅผ ๋ฐ˜์˜ํ•˜์ง€ ๋ชปํ•œ ์ฑ„ ์ง‘๋‹จ ์ •์ฒด์„ฑ์˜ ์ผ๋ถ€๋กœ ์ถ”์ƒํ™”๋˜์—ˆ๋‹ค๋Š” ํŒ๋‹จ์œผ๋กœ ์ด์–ด์กŒ๋‹ค. ๋‚˜๋Š” ์ด์™€ ๊ฐ™์€ ์ •์ฒด์„ฑ์˜ ์ถ”์ƒํ™”๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด์„œ ์ž๊ธฐ ์„ฑ ์ •์ฒด์„ฑ์˜ ๊ฐ€์‹œํ™” ๊ณผ์ •-์ปค๋ฐ์•„์›ƒ(coming out)๊ณผ ๊ฐ™์€-์—์„œ ๋‚˜์™€ ์–ด๋จธ๋‹ˆ ์‚ฌ์ด์—์„œ ๋ฐœ์ƒํ•œ ๋งค์šฐ ์‚ฌ์ ์ธ ์‚ฌ๊ฑด์„ ์ž‘ํ’ˆ์˜ ์„œ์‚ฌ ๊ตฌ์กฐ๋กœ ์‚ฌ์šฉํ•˜์˜€๋‹ค. ์ด์™€ ๊ฐ™์€ ์‚ฌ์  ์„œ์‚ฌ์˜ ์ ๊ทน์ ์ธ ์‚ฌ์šฉ์€, ๋‚˜์˜ ์„ฑ ์ •์ฒด์„ฑ ์—ฐ๊ตฌ๊ฐ€ ์†Œ์ˆ˜์˜ ํŠน์ • ์„ฑ ์ •์ฒด์„ฑ์œผ๋กœ ๋‹จ์ •๋˜์–ด ๋ฐœ์ƒํ•˜๋Š” ์ผ๋ฐ˜ํ™”์˜ ๊ณผ์ •์„ ๊ฑฐ๋ถ€ํ•˜๊ธฐ ์œ„ํ•จ์ด๋‹ค. ๋˜ํ•œ ์ž‘ํ’ˆ (2011)๊ณผ (2011)์—์„œ ์„ฑ ์ •์ฒด์„ฑ์— ๋Œ€ํ•œ ์ตœ์†Œํ•œ์˜ ์ƒ์ง•์  ์–ธ๊ธ‰์€, ๋‚˜์˜ ์ •์ฒด์„ฑ ์—ฐ๊ตฌ๊ฐ€ ์‚ฌ์  ์‚ฌ๊ฑด์˜ ํŠน์ˆ˜ํ•œ ์„œ์‚ฌ๋ฅผ ํ†ตํ•ด์„œ ๋‹ค์‹œ๊ธˆ ํƒ€์žํ™”๋˜๋Š” ๊ฒƒ์„ ๋ฐฉ์ง€ํ•˜๊ธฐ ์œ„ํ•จ์ด์—ˆ๋‹ค. ์ด๋Š” ์†Œ์ˆ˜, ํƒ€์ž, ๋˜๋Š” ํ”ผํ•ด์ž๋กœ์„œ ํŠน์ • ์ •์ฒด์„ฑ์„ ์ƒ์ •ํ•˜๊ณ  ์žˆ๋Š” ์ •์ฒด์„ฑ ์ •์น˜์— ๋Œ€ํ•œ ๊ฒฝ๊ณ„์ž„๊ณผ ๋™์‹œ์—, ๋‚˜์™€ ์–ด๋จธ๋‹ˆ ์‚ฌ์ด์˜ ์‚ฌ์ ์ธ ๊ธด์žฅ ๊ด€๊ณ„๋ฅผ ํ†ตํ•ด์„œ ๊ทธ ๊ฐˆ๋“ฑ์˜ ์›์ธ์ด ๋˜๋Š” ์ •์น˜, ๊ฒฝ์ œ, ๋ฌธํ™”์  ์ด๋ฐ์˜ฌ๋กœ๊ธฐ์˜ ๊ตฌ์กฐ๋ฅผ ์˜์‹ฌํ•  ์ˆ˜ ์žˆ๊ฒŒ ํ•œ๋‹ค. ์ฆ‰ ์ž‘ํ’ˆ ์†์˜ ๋งค์šฐ ์‚ฌ์ ์ธ ํƒ€์ธ์˜ ์„œ์‚ฌ๋Š” ์ž‘ํ’ˆ์˜ ์ˆ˜์šฉ ๊ณผ์ •์—์„œ ๋ณดํŽธ์ ์ธ ๊ฐ€์น˜๋กœ์„œ์˜ ์ •์ฒด์„ฑ ๊ณ ์ฐฐ์„ ์œ ๋„ํ•˜๊ฒŒ ๋œ๋‹ค. ๋‚˜์˜ ์„ฑ ์ •์ฒด์„ฑ ์ธ์‹๊ณผ ๊ทธ ๊ณผ์ •์—์„œ ๋ฐœ์ƒํ•œ ์™œ๊ณก๋œ ๋‚จ์„ฑ์„ฑ์— ๋Œ€ํ•œ ๋น„ํŒ์  ์‹œ๊ฐ์€ ํŠน์ • ์ •์ฒด์„ฑ์œผ๋กœ์˜ ๋ช…๋ช…(ๅ‘ฝๅ)์— ๋Œ€ํ•œ ๊ฑฐ๋ถ€์™€๋„ ๊ฐ™๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์ด๋Ÿฌํ•œ ๋ถ„๋ฅ˜์™€ ๊ตฌ๋ถ„์˜ ๊ธฐ๋Šฅ์„ ์ˆ˜ํ–‰ํ•˜๋Š” ๊ณ ์ •์  ์ •์ฒด์„ฑ์œผ๋กœ์˜ ๋ช…๋ช…์€ ๋น„๋‹จ ์„ฑ ์ •์ฒด์„ฑ๋งŒ์˜ ๋ฌธ์ œ๊ฐ€ ์•„๋‹ˆ๋ผ, ์ „๋ฐ˜์ ์ธ ์‚ฌํšŒ ๊ตฌ์กฐ์— ๊ฑธ์ณ ๋“œ๋Ÿฌ๋‚˜๋Š” ์ง€๋ฐฐ ์ด๋ฐ์˜ฌ๋กœ๊ธฐ ์˜๋ฏธ์ฒด๊ณ„์˜ ์ „๋žต์ผ ๊ฒƒ์ด๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ๋…ผ๋ฌธ์˜ ์ฒซ ๋ฒˆ์งธ ๋ชฉ์ ์€ ๋ณธ์ธ์˜ ์ž‘ํ’ˆ ๋ถ„์„์„ ํ†ตํ•ด ์ •์ฒด์„ฑ์ด ์ž์•„์˜ ์ž๊ฐ์— ์˜ํ•œ ์ •์‹ ์  ๊ฒฐ๊ณผ๋ฌผ์ผ ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ, ์ง€๋ฐฐ ์ด๋ฐ์˜ฌ๋กœ๊ธฐ์˜ ์˜๋ฏธ์ฒด๊ณ„์— ์˜ํ•ด ํ˜•์„ฑ๋˜์–ด ์ง€๋ฐฐ์˜ ๋„๊ตฌ-์„ ๋ณ„, ๊ตฌ๋ถ„, ์ถ”์ƒํ™” ๋“ฑ์˜ ์ „๋žต-๋กœ ์‚ฌ์šฉ๋˜๊ณ  ์žˆ์Œ์„ ์ธ์‹ํ•˜๋Š” ๊ฒƒ์ด๋‹ค. ๋‘ ๋ฒˆ์งธ๋กœ ๊ทธ๋Ÿฌํ•œ ์ •์ฒด์„ฑ ์ •์น˜์— ๋Œ€ํ•œ ๋น„ํŒ์  ํƒœ๋„๋ฅผ ์œ ์ง€ํ•˜๋ฉฐ ์ง„์ •ํ•œ ์˜๋ฏธ์˜ ์ •์ฒด์„ฑ ํƒ์ƒ‰ ๋ฐ ํ‘œํ˜„์„ ๋ชจ์ƒ‰ํ•˜๋Š” ๊ฒƒ์ด๋‹ค. ์ด๋Š” ์Šค์Šค๋กœ์˜ ์ •์ฒด์„ฑ์ด ์œ ๋™์  ์ƒํƒœ์ธ๊ฐ€์— ๋Œ€ํ•œ ์ž๋ฌธ(่‡ชๅ•)์ด๋ฉฐ, ๊ทธ๋Ÿฌํ•œ ์œ ๋™์  ์ƒํƒœ ์†์—์„œ ๋ฐœ์ƒํ•˜๋Š” ๋‹ค์–‘ํ•œ ์ •์ฒด์„ฑ ๊ฐ„์˜ ์œ ๊ธฐ์  ๊ด€๊ณ„์™€ ํ™˜๊ฒฝ์— ๋Œ€ํ•œ ์‹ฌ๋ฏธ์  ํ‘œํ˜„์˜ ์—ฐ๊ตฌ๋ผ๊ณ  ํ•  ์ˆ˜ ์žˆ๋‹ค. ์ฃผ์š”์–ด : ๊ตญ๊ฐ€ ์ด๋ฐ์˜ฌ๋กœ๊ธฐ, ์ƒ์ง•์˜ ์˜๋ฏธ์ฒด๊ณ„, ์ƒ์ง•์„ฑ์˜ ํ•ด์ฒด, ์ƒ์ง•์œผ๋กœ์˜ ์ •์ฒด์„ฑ, ์œ ๋™์  ์ •์ฒด์„ฑ(Identity-fluid), ๊ณ ์ •์  ์ •์ฒด์„ฑ, ๋น„์ •์ฒด์„ฑ, ์ •์ฒด์„ฑ ํ™˜๊ฒฝโ… . ์„œ๋ก  6 โ…ก. ๋ณธ๋ก  9 1. ๊ตญ๊ฐ€ ์ด๋ฐ์˜ฌ๋กœ๊ธฐ์™€ ์ง‘๋‹จ ์ •์ฒด์„ฑ 9 1.1 ๊ตญ๊ฐ€ (ๅœ‹ๆญŒ)์™€ ๊ตญ๊ฐ€ (ๅœ‹ๅฎถ) ํŒํƒ€์ง€์•„(Fantasia) 9 1.2 ์ฃผ๋ณ€ํ™”ํ•œ ์ƒ์ง•๊ณผ ๊ตญ๊ฐ€ ํŒํƒ€์ง€์•„์˜ ํ•ด์ฒด 14 1.3 ์‹œ๊ฐ„์„ฑ์˜ ์˜ค๋ฅ˜๋ฅผ ํ†ตํ•œ ์ƒ์‹ค์˜ ๋“œ๋Ÿฌ๋ƒ„ 19 1.4 ๋™์‹œ๋Œ€ ๋ฏธ์ˆ  ์† ์ง‘๋‹จ ์ •์ฒด์„ฑ์˜ ํ‘œํ˜„ 23 2. ์ „์ฒด์ฃผ์˜์™€ ๊ณ ์•ˆ๋œ ์ •์ฒด์„ฑ 28 2.1 ์ „์ฒด์ฃผ์˜์™€ ์ƒ์ง• 28 2.2 ๊ตฐ๊ฐ€(่ปๆญŒ)์™€ ๊ณ ์•ˆ๋œ ๋‚จ์„ฑ์„ฑ 30 3. ๋ฐฐ์ œ๋œ ์ •์ฒด์„ฑ์™€ ์œ ๋™์  ์ •์ฒด์„ฑ 38 3.1 ์‚ฌ์  ์„œ์‚ฌ๋ฅผ ํ†ตํ•œ ๋น„์ •์ฒด์„ฑํ™” 38 3.2 ๊ฐ์ถค์„ ํ†ตํ•œ ๋“œ๋Ÿฌ๋ƒ„ 43 3.3 ๋‹ค์ธต์  ์ •์ฒด์„ฑ๊ณผ ์œ ๋™์  ์ •์ฒด์„ฑ 45 โ…ข. ๊ฒฐ๋ก  50 ๋„ํŒ๋ชฉ๋ก 53 ์ฐธ๊ณ ๋ฌธํ—Œ 55 Abstract 56Maste

    (A)Research on formation and transformation of human resource management in Korean business groups

    No full text
    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :๊ฒฝ์˜ํ•™๊ณผ ๊ฒฝ์˜ํ•™์ „๊ณต,2005.Docto

    A Study on design and fabrication of optimized AlGaAs/GaAs power HBTs

    No full text
    Maste
    • โ€ฆ
    corecore