36 research outputs found

    Pathological T3a upstaging of clinical T1 renal cell carcinoma: outcomes according to surgical technique and predictors of upstaging

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์˜ํ•™๊ณผ ๋น„๋‡จ๊ธฐ๊ณผํ•™์ „๊ณต, 2016. 8. ๊ณฝ์ฒ .Purpose: To evaluate the prognosis of pT3a upstaging from cT1 renal cell carcinoma, and to compare the outcomes of partial or radical nephrectomy in cases of pT3a upstaging. Materials and Methods: We reviewed the records of patients who underwent partial or radical nephrectomy for cT1 at our center between January 2001 and October 2013. We compared the 2-year recurrence-free survivals for cases with pT1 or pT3a upstaging, and for partial or radical nephrectomy in cases with pT3a upstaging. Clinicopathological parameters were analyzed in univariate and multivariate analyses to evaluate their associations with upstaging. Results: Among the 1,009 eligible patients, 987 patients were included in the analysis. The mean follow-up was 48.5 months. The 2-year recurrence-free survival was worse in the pT3a upstaging group, compared to the pT1 group (87.3% vs. 99.3%p < 0.001). Partial nephrectomy and radical nephrectomy provided comparable 2-year recurrence-free survivals (88.2% vs. 83.7%p = 0.251). The multivariate analysis revealed that upstaging was associated with old age, cT1b stage, clinical symptoms, and a high Fuhrman grade. Conclusions: Pathological T3a upstaging of cT1 renal cell carcinoma was associated with a poorer prognosis, compared to pT1 disease. However, the surgical technique (radical or partial nephrectomy) did not affect the recurrence rate. Therefore, clinicians should select the treatment method based on the clinical stage, and consider the pathological stage during the follow-up.Introduction 1 Materials and Methods 2 Results 4 Discussion 6 Conclusions 9 References 10 ๊ตญ๋ฌธ ์ดˆ๋ก 17Maste

    Comparative Analysis of Teacher Performance for Pay Policy

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ต์œกํ•™๊ณผ(๊ต์œกํ–‰์ •์ „๊ณต), 2015. 2. ์ •๋™์šฑ.์ „ ์„ธ๊ณ„์ ์œผ๋กœ ์‹ ์ž์œ ์ฃผ์˜์— ๊ธฐ์ดˆํ•œ ์„ฑ๊ณผ์ฃผ์˜ ํ‰๊ฐ€์ •์ฑ…์€ ์„ธ๊ณ„ ์—ฌ๋Ÿฌ ๋‚˜๋ผ์—์„œ ๊ณตํ†ต์œผ๋กœ ๊ด€์ฐฐ๋˜๋Š” ํ˜„์ƒ์œผ๋กœ, 2000๋…„ ๋Œ€ ํ›„๋ฐ˜ ๊ณต๊ณต๊ต์œก ๊ฐœํ˜์˜ ํ•ด๊ฒฐ์ฑ…์œผ๋กœ ์ œ์‹œ๋˜์—ˆ๋‹ค. ์‹ค์ œ๋กœ ๊ณต๊ต์œก์˜์—ญ์—์„œ ์ฑ…๋ฌด์„ฑ์— ๋Œ€ํ•œ ๊ฐ•์กฐ๋Š” ์ ์ฐจ ๋†’์•„์ง€๊ณ  ์žˆ์œผ๋ฉฐ ์„ฑ๊ณผ์— ๋Œ€ํ•œ ์š”๊ตฌ๋„ ์ฑ…๋ฌด์š”๊ตฌ์ž, ์ฆ‰ ์ •๋ถ€๋‚˜ ํ•™์ƒ, ํ•™๋ถ€๋ชจ๋“ค๋กœ๋ถ€ํ„ฐ ๊ฐ•ํ•˜๊ฒŒ ๋ฐ›๊ณ  ์žˆ๋Š” ๊ฒƒ์ด ํ˜„์‹ค์ด๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๊ตญ๋‚ด์˜ ์„ ํ–‰์—ฐ๊ตฌ๋“ค์€ ๊ต์›์„ฑ๊ณผ๊ธ‰์ •์ฑ…์˜ ์‹œํ–‰์œผ๋กœ ์ธํ•œ ๊ต์›๋“ค์˜ ๊ธˆ์ „์  ๋ณด์ƒ์— ๋Œ€ํ•œ ๋งŒ์กฑ๋„, ํ‰๊ฐ€์˜ ๊ณต์ •์„ฑ ๋“ฑ ์ธ์‹์— ๋Œ€ํ•œ ๊ฒƒ์— ์ฃผ๋ชฉํ•˜์˜€๊ณ , ๊ตญ์™ธ์˜ ์„ ํ–‰์—ฐ๊ตฌ๋“ค์€ ํ’๋ถ€ํ•œ ๋ฐ์ดํ„ฐ๋ฅผ ํ†ตํ•˜์—ฌ ๊ต์›์„ฑ๊ณผ๊ธ‰ ์ •์ฑ…์ด ์ ์šฉ๋˜๋Š” ๋Œ€์ƒ๊ณผ ๊ทธ๋ ‡์ง€ ์•Š์€ ๋Œ€์ƒ์˜ ๋น„๊ต๋ฅผ ํ†ตํ•˜์—ฌ ํ•™์—…์„ฑ์ทจ๋„ ํšจ๊ณผ๋ฅผ ์ถ”์ •ํ•˜๋Š” ๊ฒƒ์— ์ฃผ๋ชฉํ–ˆ์„ ๋ฟ, ๊ต์›์„ฑ๊ณผ๊ธ‰ ์ •์ฑ…์„ ์‹œํ–‰ํ•˜๋Š” ๊ตญ๊ฐ€์™€ ๊ทธ๋ ‡์ง€ ์•Š์€ ๊ตญ๊ฐ€ ๊ฐ„์˜ ์–ด๋–ค ํŠน์„ฑ์ด ์žˆ๋Š”์ง€ ๋˜๋Š” ๊ต์›์„ฑ๊ณผ๊ธ‰ ์ •์ฑ…์„ ์‹œํ–‰ํ•˜๋Š” ๊ตญ๊ฐ€ ๊ฐ„์˜ ์œ ์‚ฌ์ ๊ณผ ์ฐจ์ด์ ์ด ๋ฌด์—‡์ด ์žˆ๋Š”์ง€๋Š” ๋‹ค๋ฃจ์ง€ ์•Š์•˜๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ์—ฐ๊ตฌ๋Š” ๊ต์›์„ฑ๊ณผ๊ธ‰ ์ •์ฑ…์„ ์‹œํ–‰ํ•˜๋Š” ๊ตญ๊ฐ€์™€ ๊ทธ๋ ‡์ง€ ์•Š์€ ๊ตญ๊ฐ€๋“ค ์‚ฌ์ด์— ์œ ์‚ฌ์ ๊ณผ ์ฐจ์ด์ ์„ ์ฐพ๊ณ  ์‚ฌํšŒ๊ฒฝ์ œ์ , ์ •์น˜์  ํŠน์„ฑ์„ ๋น„๊ตํ•˜๊ณ ์ž ํ•œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ ์„ค์ •ํ•œ ์—ฐ๊ตฌ๋ฌธ์ œ๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ์ฒซ์งธ, ๊ต์›์„ฑ๊ณผ๊ธ‰ ์ •์ฑ…์„ ์‹œํ–‰ํ•˜๋Š” ๊ตญ๊ฐ€์™€ ๊ทธ๋ ‡์ง€ ์•Š์€ ๊ตญ๊ฐ€ ์‚ฌ์ด์—๋Š” ์–ด๋–ค ํŠน์„ฑ์ด ์žˆ์„๊นŒ? ๋‘˜์งธ, ๊ต์›์„ฑ๊ณผ๊ธ‰ ์ •์ฑ…์„ ์‹œํ–‰ํ•˜๋Š” ๊ตญ๊ฐ€์™€ ๊ทธ๋ ‡์ง€ ์•Š์€ ๊ตญ๊ฐ€์˜ ๊ต์‚ฌ๋“ค์—๊ฒŒ์„œ ๋‚˜ํƒ€๋‚˜๋Š” ํŠน์„ฑ์€ ๋ฌด์—‡์ธ๊ฐ€? ์ด ์—ฐ๊ตฌ๋Š” ๊ฒฝ์ œ๊ฐœ๋ฐœํ˜‘๋ ฅ๊ธฐ๊ตฌ์˜ ๊ต์œก์ง€ํ‘œ(OECD Education at a glance)์ž๋ฃŒ์™€ ๊ต์ˆ˜ํ•™์Šต ๊ตญ์ œ๋น„๊ต(Teaching And Learning International Survey : TALIS)์ž๋ฃŒ์— ๊ณตํ†ต์ ์œผ๋กœ ๋“ค์–ด๊ฐ€๋Š” ๊ตญ๊ฐ€์™€ ํ•ด๋‹น๊ตญ๊ฐ€์˜ ๊ต์‚ฌ๋ฅผ ์—ฐ๊ตฌ๋Œ€์ƒ์œผ๋กœ ์‚ผ์•˜๋‹ค. ๊ตญ๊ฐ€๋ณ„ ๊ต์›์„ฑ๊ณผ๊ธ‰ ์ •์ฑ…์˜ ์‹œํ–‰์—ฌ๋ถ€์™€ ์ ์šฉ๋‹จ์œ„, ๊ทธ๋ฆฌ๊ณ  ์–ด๋–ค ์ค€๊ฑฐ๋ฅผ ํ† ๋Œ€๋กœ ์„ฑ๊ณผ๊ธ‰์ •์ฑ…์ด ์ด๋ฃจ์–ด์ง€๋Š”์ง€๋ฅผ ๋ถ€์šธ ๋„์ˆ˜ ๋ฐฉ๋ฒ•์œผ๋กœ ๋ถ„์„ํ•˜์˜€๋‹ค. ์ดํ›„, ๋ถ€์šธ ๋ถ„์„์˜ ๊ฒฐ๊ณผ๋ฅผ ์ข…์†๋ณ€์ˆ˜๋กœ ํ•˜์—ฌ ์„ฑ๊ณผ๊ธ‰์ •์ฑ…์„ ์‹œํ–‰ํ•˜๋Š” ๋‚˜๋ผ์™€ ๊ทธ๋ ‡์ง€ ์•Š์€ ๋‚˜๋ผ์˜ ํŠน์„ฑ์„ ์‚ฌํšŒ๊ฒฝ์ œ์ , ์ •์น˜์ ์œผ๋กœ ์‚ดํŽด๋ณด์•˜๋‹ค. ๊ทธ๋ฆฌ๊ณ  TALIS๋ฐ์ดํ„ฐ ์ƒ์˜ ์ฃผ๋‹น ์ „์ฒด๊ทผ๋ฌด์‹œ๊ฐ„, ์ˆ˜์—…์‹œ๊ฐ„, ์ˆ˜์—…์ค€๋น„์‹œ๊ฐ„, ํ•™์ƒ์ƒ๋‹ด์‹œ๊ฐ„, ๊ณต๋™์—…๋ฌด์‹œ๊ฐ„, ๊ต์ง๋งŒ์กฑ๋„๋ฅผ ์œ„๊ณ„์  ์„ ํ˜•๋ชจํ˜•์„ ํ†ตํ•˜์—ฌ ๋ถ„์„ํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ์ฒซ์งธ, ๊ต์›์„ฑ๊ณผ๊ธ‰์ •์ฑ…์€ ์˜๋ฏธ๋ฌธํ™”๊ถŒ์˜ ๊ตญ๊ฐ€์—์„œ ์ˆ˜์—…์ค€๋น„์‹œ์ˆ˜๋ฅผ ๋Š˜๋ฆฌ๊ณ  ๊ณผ์ œ์ ๊ฒ€์‹œ๊ฐ„์„ ๋Š˜๋ฆฌ๋Š” ๋“ฑ ํ•™์Šต์ž๋ฅผ ์ง€ํ–ฅํ•˜๋Š” ๊ทผ๋ฌด์–‘ํƒœ๋ฅผ ๋ณด์ด๋‚˜ ๋‹ค๋ฅธ ๋ฌธํ™”๊ถŒ์—์„œ๋Š” ํ•™์Šต์ž ์ง€ํ–ฅ์ ์ธ ๊ทผ๋ฌด์–‘ํƒœ๊ฐ€ ๋‚˜ํƒ€๋‚˜์ง€ ์•Š์•˜๋‹ค. ๋‘˜์งธ, ๊ต์‚ฌ์˜ ์‚ฌ๊ธฐ์ง„์ž‘ ๋ฉด์—์„œ๋„ ๊ต์›์„ฑ๊ณผ๊ธ‰ ์ •์ฑ…์˜ ์‹œํ–‰์€ ์˜๋ฏธ๋ฌธํ™”๊ถŒ์˜ ๊ต์‚ฌ์—๊ฒŒ์„œ๋Š” ๊ธ์ •์ ์ธ ํŠน์„ฑ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋ฐ˜๋ฉด, ๋‹ค๋ฅธ ๋ฌธํ™”๊ถŒ์˜ ๊ต์‚ฌ์—๊ฒŒ์„œ๋Š” ๊ต์›์„ฑ๊ณผ๊ธ‰์ •์ฑ…์˜ ์‹œํ–‰์— ๋”ฐ๋ฅธ ์‚ฌ๊ธฐ์ง„์ž‘์˜ ํŠน์„ฑ์„ ๊ด€์ฐฐํ•  ์ˆ˜ ์—†์—ˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ๊ต์›์„ฑ๊ณผ๊ธ‰์ •์ฑ…์˜ ์ ์šฉ์— ์žˆ์–ด์„œ ์ธ๋ฅ˜ํ•™๊ณผ ์‚ฌํšŒํ•™์—์„œ ๋ฐํ˜”๋˜ ๊ตญ์ง€์ (ๅฑ€ๅœฐ็š„)์ธ ๋ถ€์ž‘์šฉ์„ ์‚ฌ๋ก€์—ฐ๊ตฌ๊ฐ€ ์•„๋‹Œ ์‹ค์ฆ์  ์—ฐ๊ตฌ๋กœ ๋ณด์—ฌ์ฃผ์—ˆ๋‹ค๋Š” ์ ์—์„œ ์˜์˜๋ฅผ ์ฐพ์„ ์ˆ˜ ์žˆ๋‹ค. ๋˜ํ•œ ๊ต์œก์ •์ฑ…์˜ ์ฐจ์šฉ์— ์žˆ์–ด์„œ๋„ ๊ตญ๊ฐ€ใ†์‚ฌํšŒ์˜ ๋ฌธํ™”์  ๋ฐฐ๊ฒฝ์„ ๊ณ ๋ คํ•ด์•ผํ•œ๋‹ค๋Š” ์‹œ์‚ฌ์ ์„ ์ฃผ๊ณ  ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๋ณธ ๋…ผ๋ฌธ์˜ ๊ฒฐ๊ณผ๋Š” ๊ต์›์˜ ๊ทผ๋ฌด๋…ธ๋ ฅ์„ ๊ทผ๋ฌด์‹œ๊ฐ„ ๋ฐฐ๋ถ„ํ˜•ํƒœ๋กœ ๋ณด์•˜๋‹ค๋Š” ์ ๊ณผ ํšก๋‹จ๋ฉด ๋ฐ์ดํ„ฐ๋ฅผ ์ด์šฉํ•˜์˜€๋‹ค๋Š” ์ ์—์„œ ์ธ๊ณผํšจ๊ณผ๋ผ๊ณ  ๋ณผ ์ˆ˜๋Š” ์—†๋‹ค.๋ชฉ ์ฐจ I. ์„œ๋ก  1 1. ์—ฐ๊ตฌ์˜ ํ•„์š”์„ฑ ๋ฐ ๋ชฉ์  1 2. ์—ฐ๊ตฌ ๋ฌธ์ œ 4 3. ์—ฐ๊ตฌ์˜ ์˜์˜ 5 4. ์—ฐ๊ตฌ์˜ ์ œํ•œ์  6 II. ์ด๋ก ์  ๋ฐฐ๊ฒฝ 7 1. ์ •์ฑ…๊ฒฐ์ •์š”์ธ์ด๋ก  7 ๊ฐ€. ์‚ฌํšŒ๊ฒฝ์ œ์  ๋ฐ ์ •์น˜์  ์ •์ฑ…๊ฒฐ์ •์š”์ธ 7 ๋‚˜. ๋ฌธํ™”์  ์ •์ฑ…๊ฒฐ์ •์š”์ธ 8 2. ๊ต์›์„ฑ๊ณผ๊ธ‰์ •์ฑ… 9 ๊ฐ€. ๋™์•„์‹œ์•„๋ฌธํ™”๊ถŒ์—์„œ์˜ ๊ต์›์„ฑ๊ณผ๊ธ‰์ •์ฑ… 9 ๋‚˜. ์˜๋ฏธ๋ฌธํ™”๊ถŒ์—์„œ์˜ ๊ต์›์„ฑ๊ณผ๊ธ‰์ •์ฑ… 18 ๋‹ค. ๋ถ์œ ๋Ÿฝ๋ฌธํ™”๊ถŒ์—์„œ์˜ ๊ต์›์„ฑ๊ณผ๊ธ‰์ •์ฑ… 24 ๋ผ. ๋ผํ‹ด์œ ๋Ÿฝ๋ฌธํ™”๊ถŒ์—์„œ์˜ ๊ต์›์„ฑ๊ณผ๊ธ‰์ •์ฑ… 34 ๋งˆ. ์ค‘๋‚จ๋ฏธ๋ฌธํ™”๊ถŒ์—์„œ์˜ ๊ต์›์„ฑ๊ณผ๊ธ‰์ •์ฑ… 39 3. ๊ต์›์„ฑ๊ณผ๊ธ‰์ •์ฑ…์˜ ๋น„๊ต๋ถ„์„์˜ ํ‹€ 40 ๊ฐ€. ๊ต์›์„ฑ๊ณผ๊ธ‰์ •์ฑ…๊ด€๋ จ ์„ ํ–‰์—ฐ๊ตฌ 40 ๋‚˜. ๋น„๊ต๋ถ„์„์˜ ํ‹€ 43 III. ์—ฐ๊ตฌ๋ฐฉ๋ฒ• 46 1. ๋ถ„์„ ์ž๋ฃŒ 46 ๊ฐ€. ์„ธ๊ณ„์€ํ–‰๋ฐ์ดํ„ฐ 46 ๋‚˜. ๊ฒฝ์ œ๊ฐœ๋ฐœํ˜‘๋ ฅ๊ธฐ๊ตฌ ๊ต์œก์ง€ํ‘œ 46 ๋‹ค. ๊ต์ˆ˜ํ•™์Šต ๊ตญ์ œ์„ค๋ฌธ์กฐ์‚ฌ์ž๋ฃŒ 47 2. ๋ณ€์ˆ˜ ๊ตฌ์„ฑ 49 ๊ฐ€. ๊ต์›์„ฑ๊ณผ๊ธ‰์ •์ฑ… ์‹œํ–‰์—ฌ๋ถ€์— ๋”ฐ๋ฅธ ๊ตญ๊ฐ€ํŠน์„ฑ 49 ๋‚˜. ๊ต์›์„ฑ๊ณผ๊ธ‰์ •์ฑ… ์‹œํ–‰์—ฌ๋ถ€์— ๋”ฐ๋ฅธ ๊ต์‚ฌํŠน์„ฑ 50 3. ์—ฐ๊ตฌ ๋ชจํ˜• ๋ฐ ๋ถ„์„ ๋ฐฉ๋ฒ• 52 ๊ฐ€. ์—ฐ๊ตฌ๋ชจํ˜• 52 ๋‚˜. ๋ถ„์„๋ฐฉ๋ฒ• 56 IV. ์—ฐ๊ตฌ ๊ฒฐ๊ณผ ๋ฐ ๋…ผ์˜ 59 1. ๊ต์›์„ฑ๊ณผ๊ธ‰์ •์ฑ…์˜ ์ฐจ์ด 59 ๊ฐ€. ๊ต์›์„ฑ๊ณผ๊ธ‰์ •์ฑ… ์‹œํ–‰ ๋ฐ ์ •์ฑ…๊ฒฐ์ •์˜ ๋ถ„๊ถŒํ™” ์—ฌ๋ถ€ 59 ๋‚˜. ๊ต์›์„ฑ๊ณผ๊ธ‰์ •์ฑ…์˜ ์ค€๊ฑฐ๋ณ„ ์ฐจ์ด 61 2. ๊ต์›์„ฑ๊ณผ๊ธ‰์ •์ฑ… ์‹œํ–‰ ๊ตญ๊ฐ€ํŠน์„ฑ 63 ๊ฐ€. ๊ธฐ์ˆ ํ†ต๊ณ„ 63 ๋‚˜. ๊ต์›์„ฑ๊ณผ๊ธ‰์ •์ฑ… ์‹œํ–‰์—ฌ๋ถ€์™€ ๊ตญ๊ฐ€ํŠน์„ฑ 64 ๋‹ค. ๊ต์›์„ฑ๊ณผ๊ธ‰์ •์ฑ… ๊ฒฐ์ •์˜ ๋ถ„๊ถŒํ™” ๊ตญ๊ฐ€ํŠน์„ฑ 65 ๋ผ. ํ•™์—…์„ฑ์ทจ๋„์˜ ์„ฑ๊ณผ๊ธ‰์ •์ฑ… ์ค€๊ฑฐ์‚ฌ์šฉ ๊ตญ๊ฐ€ํŠน์„ฑ 66 3. ๊ต์›์„ฑ๊ณผ๊ธ‰์ •์ฑ… ์‹œํ–‰ ๊ตญ๊ฐ€์˜ ๊ต์‚ฌํŠน์„ฑ 67 ๊ฐ€. ๊ธฐ์ˆ ํ†ต๊ณ„ 67 ๋‚˜. ๊ต์›์„ฑ๊ณผ๊ธ‰์ •์ฑ…์˜ ์‹œํ–‰์—ฌ๋ถ€์— ๋”ฐ๋ฅธ ๊ต์‚ฌํŠน์„ฑ 73 V. ๊ฒฐ๋ก  ๋ฐ ์ œ์–ธ 77 ์ฐธ๊ณ ๋ฌธํ—Œ 83 Abstract 91Maste

    Application of high-speed slit scanning confocal laser microscope in biology

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    ์˜๊ณตํ•™๊ณผ/์„์‚ฌ[ํ•œ๊ธ€]ํ˜„๋ฏธ๊ฒฝ์€ ์ƒ๋ฌผํ•™์„ ๋น„๋กฏํ•œ ์—ฌ๋Ÿฌ ๊ณผํ•™ ๋ถ„์•ผ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์‚ฐ์—… ํ˜„์žฅ์—๊นŒ์ง€ ๋‹ค์–‘ํ•œ ๋ชฉ์ ์œผ๋กœ ํ™œ์šฉ๋˜๊ณ  ์žˆ์œผ๋ฉฐ, ํŠนํžˆ ์ƒ๋ช…๊ณผํ•™ ๋ถ„์•ผ์—์„œ๋Š” ๊ฐ€์žฅ ๊ธฐ๋ณธ์ ์ด๋ฉด์„œ๋„ ํ•„์ˆ˜์ ์ธ ์‹คํ—˜ ๊ธฐ๊ตฌ์ด๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๊ธฐ์กด์— ๊ฐœ๋ฐœ ๋œ ๊ณ ์† ์„ ์ฃผ์‚ฌ ๊ณต์ดˆ์  ๋ ˆ์ด์ € ํ˜„๋ฏธ๊ฒฝ ์‹œ์Šคํ…œ์„ ๋ณด์™„ํ•˜์—ฌ ์ตœ์ ํ™” ์‹œํ‚ค๊ณ  ์ž„์ƒ์ด๋‚˜ ์ƒ๋ฌผํ•™ ๋ถ„์•ผ์—์„œ ์‹คํ—˜ ๋ชฉ์ ์— ๋”ฐ๋ผ ์œ ์—ฐํ•˜๊ฒŒ ๋Œ€์ฒ˜๊ฐ€ ๊ฐ€๋Šฅํ•œ ์‹œ์Šคํ…œ์œผ๋กœ ๋ณ€๊ฒฝํ•˜์˜€๋‹ค. ๊ธฐ์กด์˜ ์•ˆ๊ตฌ ์ธก์ • ์‹œ์Šคํ…œ์„ ๋„๋ฆฝ(inverted)๋กœ ๋ณ€๊ฒฝํ•˜์—ฌ ์ƒ๋ฌผํ•™์  ์‹œ๋ฃŒ ์ค‘ ๋น„๊ต์  ์„ธํฌ์˜ ํฌ๊ธฐ๊ฐ€ ํฐ ์–‘ํŒŒ ์„ธํฌ๋ฅผ ์˜์ƒํ™” ํ•˜์˜€๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์ธํ๋ฒ ์ดํ„ฐ์—์„œ ๋ฐฐ์–‘๋œ ์•”์„ธํฌ๋ฅผ ์‹ค์‹œ๊ฐ„์œผ๋กœ ์˜์ƒํ™” ํ•˜๊ณ  ๊ทธ ๊ฒฐ๊ณผ๋ฅผ ์ผ๋ฐ˜์  ๊ด‘ํ•™ํ˜„๋ฏธ๊ฒฝ์˜ ์ด๋ฏธ์ง€์™€ ๋น„๊ตํ•˜์˜€๋‹ค. ๋ณธ ์‹œ์Šคํ…œ์˜ ์•ˆ์ •์ ์ธ ์˜์ƒํš๋“ ์†๋„๋Š” 512 X 512 ํ”ฝ์…€์˜ ์ด๋ฏธ์ง€์—์„œ ์ดˆ๋‹น 176 ํ”„๋ ˆ์ž„์ด๋‹ค. ๋ฌผ๋ก  ์ด๋Ÿฌํ•œ ์˜์ƒ ํš๋“ ์†๋„๋„ ์ถฉ๋ถ„ํžˆ ๋น ๋ฅด์ง€๋งŒ ์ƒ๋ฌผํ•™์  ๋‹ค์ด๋‚ด๋ฏน ํ˜„์ƒ์„ ๊ด€์ฐฐํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” 1000 frames/s ์ •๋„์˜ ์˜์ƒ ํš๋“ ์†๋„๊ฐ€ ํ•„์š”ํ•˜๋‹ค. ์‹œ์Šคํ…œ์˜ ์˜์ƒํš๋“ ์†๋„๋ฅผ ๋” ๋†’์ด๊ธฐ ์œ„ํ•˜์—ฌ ์ด๋ฏธ์ง€์˜ ํ”ฝ์…€์ˆ˜๋ฅผ ์ค„์—ฌ 512 X 128 ํ”ฝ์…€์˜ ์ด๋ฏธ์ง€์—์„œ ์ดˆ๋‹น 710 ํ”„๋ ˆ์ž„์˜ ์˜์ƒํš๋“ ์†๋„๋ฅผ ๋ฐœํ˜„ ํ•˜์˜€๋‹ค. ๊ณ ์†์˜ ์˜์ƒ ํš๋“์€ ๊ธฐ์กด์— ๊ด€์ฐฐ ํ•  ์ˆ˜ ์—†์—ˆ๋˜ ๋‹ค์ด๋‚ด๋ฏนํ•œ ํ˜„์ƒ์„ ๊ด€์ฐฐ ํ•  ์ˆ˜ ์žˆ๋Š” ๊ฐ€๋Šฅ์„ฑ์ด ์žˆ๋‹ค. ์ด๋ฅผ ํ™•์ธํ•˜๊ธฐ ์œ„ํ•ด์„œ ์˜ค์ง•์–ด์˜ ์‹ ๊ฒฝ ์„ธํฌ์— ์ „๊ธฐ์  ์ž๊ทน์„ ์ฃผ์–ด ๋น ๋ฅด๊ฒŒ ์ผ์–ด๋‚˜๋Š” ๊ตฌ์กฐ์ ์ธ ๋ณ€ํ™”๋ฅผ ๊ด€์ฐฐ ํ•˜๊ณ ์ž ํ–ˆ๋‹ค [์˜๋ฌธ]I constructed a high-speed laser line-scanning confocal microscope (LSCM) using He-Ne laser (633 nm), a line CCD camera and an acousto-optic deflector (AOD). The line scanner consists of an AOD and a cylindrical lens, which creates a line focus sweeping over the sample. It generates two-dimensional confocal images (512 X 512 pixel image) up to 176 frame/s without any mechanically-moving parts. Our system is configured as an inverted microscope for imaging biological samples. We obtained images of various biological samples including onion cells, mouse melanoma tumor cells (B16BL6) and human breast tumor cells (BT-20). Also, the frame rate can be further improved up to over 710 frame/s when the image size is reduced (512 X 128 pixel image). This system may be useful for analyzing fast phenomena during biological and chemical interactions and for rapid imaging of 3D structures.ope

    ์ด์ค‘ ๋Œ€์—ญ ํ™€๋กœ๊ทธ๋žจ ๊ฒฉ์ž๋ฅผ ์ด์šฉํ•œ ์ˆœํ™˜ ํŒŒ์žฅ ๋ณ€ํ™˜๊ธฐ

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    Thesis(doctoral)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์ „๊ธฐยท์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€,2006.Docto

    ํŽธ๊ด‘ ์œ ์ง€ ๊ด‘์„ฌ์œ  ๋ฃจํ”„ ๋ฏธ๋Ÿฌ๋ฅผ ์ด์šฉํ•œ ๊ด‘์„ฌ์œ  ๊ฒฉ์ž ์„ผ์„œ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ

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    Thesis (master`s)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์ „๊ธฐยท์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€,2002.Maste

    The geometric growth model of complex networks

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    Maste

    ๊ธฐ์—…์—์„œ ํ•™๋ ฅ์˜ ์™ธ๋ถ€ํšจ๊ณผ ๋ถ„์„(An analysis on human capital externality within firms)

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    ๋ณธ ์—ฐ๊ตฌ๋Š” ์ด์›๊ณ ์ •ํšจ๊ณผ๋ชจ๋ธ์„ ํ™œ์šฉํ•˜์—ฌ ๊ธฐ์—… ๋‚ด ํ•™๋ ฅ์˜ ์™ธ๋ถ€ํšจ๊ณผ์™€ ๊ฐœ์ธ ๋ฐ ๊ธฐ์—… ํŠน์„ฑ์— ๋”ฐ๋ฅธ ์™ธ๋ถ€ํšจ๊ณผ์˜ ์ฐจ๋ณ„์  ํšจ๊ณผ๋ฅผ ๋ถ„์„ํ•˜์˜€๋‹ค. ๋ถ„์„๊ฒฐ๊ณผ, ๊ธฐ์—…์—์„œ ํ•™๋ ฅ์˜ ์™ธ๋ถ€ํšจ๊ณผ๋Š” ์†Œ์†์ง‘๋‹จ์˜ ํ‰๊ท ๊ต์œก์—ฐํ•œ์ด 1๋…„ ์ฆ๊ฐ€ํ•จ์— ๋”ฐ๋ผ์„œ 1.2% ๋งŒํผ์˜ ์ž„๊ธˆ์ƒ์Šนํšจ๊ณผ๋ฅผ ๊ฐ€์ ธ์˜ค๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋˜ํ•œ ํ•™๋ ฅ์˜ ์™ธ๋ถ€ํšจ๊ณผ๋Š” ๊ฐœ์ธํŠน์„ฑ ๋ฐ ๊ธฐ์—…ํŠน์„ฑ์— ๋”ฐ๋ผ ๊ทธ ํšจ๊ณผ๊ฐ€ ๋‹ค๋ฅด๊ฒŒ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ด๋Ÿฐ ๊ฒฐ๊ณผ๋Š” ๊ต์œก์˜ ํšจ๊ณผ๋ฅผ ์ œ๋Œ€๋กœ ํ‰๊ฐ€ํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ๊ฐœ์ธ์˜ ๊ต์œกํˆฌ์ž์ˆ˜์ต๋ฅ ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์™ธ๋ถ€ํšจ๊ณผ๊นŒ์ง€ ๊ณ ๋ คํ•ด์•ผ ํ•˜๋ฉฐ, ๊ฐœ์ธ ๋ฐ ์กฐ์ง์˜ ํŠน์„ฑ์— ๋”ฐ๋ฅธ ์ฐจ๋ณ„์  ํšจ๊ณผ๊นŒ์ง€ ๊ณ ๋ คํ•˜์—ฌ ์กฐ์ง์„ ์ „๋žต์ ์œผ๋กœ ์šด์˜ํ•ด์•ผ ํ•  ํ•„์š”์„ฑ์ด ์žˆ์Œ์„ ๋ณด์—ฌ์ค€๋‹ค. ์ด์— ๋ณธ ์—ฐ๊ตฌ๋Š” ๊ต์œก์˜ ํšจ๊ณผ๊ฐ€ ๊ฐœ์ธ์˜ ๊ต์œกํˆฌ์ž์ˆ˜์ต๋ฅ ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์ œ3์ž์—๊ฒŒ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์™ธ๋ถ€ํšจ๊ณผ๊นŒ์ง€ ๊ณ ๋ คํ•˜์—ฌ ํ‰๊ฐ€๋˜์–ด์•ผ ํ•œ๋‹ค๋Š” ์ธ์‹์˜ ์ „ํ™˜๊ณผ, ์™ธ๋ถ€ํšจ๊ณผ๋ฅผ ๋†’์ผ ์ˆ˜ ์žˆ๋„๋ก ๊ธฐ์—… ๋‚ด ๊ฐ ๊ตฌ์„ฑ์›๋“ค ๊ฐ„ ์ƒํ˜ธ์ž‘์šฉ์˜ ๊ธฐํšŒ๋ฅผ ์ฆ๊ฐ€์‹œํ‚ฌ ์ˆ˜ ์žˆ๋Š” ์—ฌ๊ฑด์„ ๋งˆ๋ จํ•ด์•ผํ•จ์„ ์ •์ฑ…์  ์‹œ์‚ฌ์ ์œผ๋กœ ์ œ๊ธฐํ•˜๋Š” ๋ฐ”์ด๋‹ค.In this paper, we estimate human capital externality within the firm and identify its differential effects, exploiting two-way fixed effect model. Our results show significantly 1.2% external effects within the firm. This result means that a worker within the firm that has high level of workers' average years of schooling has wage premium. This result suggests that the social returns to education from human capital externality are strongly positive, implying that the effect of education should be evaluated by positive human capital externality as well as private return to education not to underestimate the effect of education. We also estimate the differential effect of human capital externality with regard to personal and company characters. Human capital externality has differential effects by gender, marital status, occupational type, and incentive type. These results emphasize that a company should establish proper strategies in order to maximize the benefit of human capital externality

    Design of Buck Converter Controller in a Photovoltaic Power Conditioning System

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    Generally, buck converter controller is designed to control the output voltage of the converter. However, design of the controller in a photovoltaic power conditioning system is different from theoretical design guideline. The controller in a photovoltaic power conditioning system controls the input voltage of the converter (the output voltage of the solar cell) to meet a maximum power point tracking (MPPT) performance. In this study, a new model for buck converter used in a photovoltaic power conditioning system is proposed, which is linearized after state-space averaging in each period. Also, mathematical expression of the modeled buck converter is interpreted separately as small and large signals; therefore its appropriateness is measured to design linear voltage and current controllers.2
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