138 research outputs found

    ์ทŒ์žฅ์•” ์กฐ๊ธฐ ์ง„๋‹จ์„ ์œ„ํ•œ ๋ณตํ•ฉ ๋ฐ”์ด์˜ค๋งˆ์ปค ๊ฐœ๋ฐœ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์˜๊ณผ๋Œ€ํ•™ ์˜ํ•™๊ณผ, 2021. 2. ์žฅ์ง„์˜.Background: The diagnostic value of a single tumor marker for pancreatic cancer is not high. To overcome this limitation, combinations of multiple biomarkers and unique analysis algorithms can be applied. The purpose of this study was to develop multiple biomarker panel and to validate its performance diagnosing pancreatic ductal adenocarcinoma (PDAC). Methods: From July 2010 to May 2015, 180 PDAC and 573 normal control serum samples were used. As benign pancreatic disease, low grade intradctal papillary mucinous neoplasm (IPMN) samples were used. Candidate markers consisted of 11 markers. Two-thirds of the samples were used as a training set. Validation was performed with the remaining one-third. Five linear or nonlinear classification methods were used to select the optimal model. Results: There were differences in 10 out of 11 markers (ApoA1, CA125, CA19-9, CRP, CYFRA21.1, LRG1, CEA, ApoA2, TTR and D.Dimer). Using 11 markers, 2047 combinations were made and all combinations were applied to 5 algorithms. The optimal multiple biomarker combination consisted of 6 marker ApoA1, CA125, CA19-9, CEA, ApoA2, and TTR with the random forest classification algorithms method. The AUC, sensitivity and specificity were 0.992, 95% and 96% and in training set, respectively. In the validation set the AUC, sensitivity, and specificity were 0.993, 96% and 93%, respectively. Diagnostically, CA9-9 alone was 71% accurate in stage 1 and 83% accurate in stage 2. However, the diagnostic accuracy of new panel were 89% and 92% in validation set. When comparing IPMN and PDAC, the AUC, sensitivity and specificity were 0.964, 91.1% and 81.4% Conclusion: This study demonstrated the usefulness of the combination of multiple biomarkers for early detection of PDAC. Diagnostic biomarker panel algorithms that included 6 biomarkers were developed and validated. These algorithms help to diagnosis pancreatic cancer, especially stage 1, 2 PDAC.๋ฐฐ๊ฒฝ: ์ทŒ์žฅ์•”์—์„œ ๋‹จ์ผ ์ข…์–‘ ํ‘œ์ง€์ž๋Š” ์ง„๋‹จ ๊ฐ€์น˜๊ฐ€ ๋†’์ง€ ์•Š๋‹ค. ์ด๋Ÿฌํ•œ ํ•œ๊ณ„๋Š” ์—ฌ๋Ÿฌ๊ฐœ์˜ ๋ฐ”์ด์˜ค ๋งˆ์ปค ์กฐํ•ฉ์„ ๊ณ ์œ  ๋ถ„์„ ์•Œ๊ณ ๋ฆฌ์ฆ˜์— ์ ์šฉ ํ•˜์—ฌ ์ง„๋‹จ ๋Šฅ๋ ฅ์„ ํ–ฅ์ƒ์‹œํ‚ฌ ์ˆ˜ ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์ทŒ๊ด€์„ ์•”์— ์ง„๋‹จ์—์„œ ๋‹ค์ค‘ ๋ฐ”์ด์˜ค ๋งˆ์ปค ์กฐํ•ฉ๊ณผ ์ง„๋‹จ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ๊ฐœ๋ฐœํ•˜๊ณ  ์„ฑ๋Šฅ์„ ๊ฒ€์ฆํ•˜๋Š” ๊ฒƒ์ด๋‹ค. ๋ฐฉ๋ฒ•: ๋ณธ ์—ฐ๊ตฌ๋Š” 180 ๋ช…์˜ ์ทŒ๊ด€์„ ์•” ํ™˜์ž์™€ 573 ๋ช…์˜ ๊ฑด๊ฐ•ํ•œ ๋Œ€์กฐ๊ตฐ์˜ ํ˜ˆ์•ก ์ƒ˜ํ”Œ์„ ์‚ฌ์šฉํ•˜์˜€๋‹ค. ์ทŒ์žฅ ์–‘์„ฑ์งˆํ™˜๊ณผ ๊ฐ๋ณ„ํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ์ทŒ๊ด€๋‚ด์œ ๋‘์ƒ์ข…์–‘ ์ƒ˜ํ”Œ์„ ์‚ฌ์šฉํ•˜์˜€๋‹ค. ํ›„๋ณด ๋งˆ์ปค๋Š” ๋‹ค์–‘ํ•œ ์•”์—์„œ ์ผ๋ฐ˜์ ์œผ๋กœ ๋ฐœํ˜„๋˜๊ณ  ์ทŒ์žฅ์•”์—์„œ๋„ ๋ฐœํ˜„์ด ์ž…์ฆ ๋œ 11 ๊ฐœ์˜ ๋งˆ์ปค๋กœ ๊ตฌ์„ฑํ•˜์˜€๋‹ค. ์ƒ˜ํ”Œ์€ ๊ฐœ๋ฐœ, ํ›ˆ๋ จ ์„ธํŠธ ๋ฐ ๊ฒ€์ฆ ์„ธํŠธ๋กœ ๊ตฌ๋ถ„ํ•˜์˜€๋‹ค. ์ตœ์ ์˜ ๋ชจ๋ธ์„ ๊ฒฐ์ •ํ•˜๊ธฐ ์œ„ํ•ด ๋‹ค์„ฏ ๊ฐ€์ง€ ์„ ํ˜• ๋˜๋Š” ๋น„์„ ํ˜• ๋ถ„๋ฅ˜ ๋ฐฉ๋ฒ•์„ ์‚ฌ์šฉํ•˜์˜€๋‹ค. ๊ฒฐ๊ณผ: 11 ๊ฐœ ๋งˆ์ปค ์ค‘ 10 ๊ฐœ์˜ ๋งˆ์ปค๊ฐ€ ๋Œ€์กฐ๊ตฐ๊ณผ ์ทŒ๊ด€์„ ์•” ์‚ฌ์ด์—์„œ ์œ ์˜ํ•œ ์ฐจ์ด๋ฅผ ๋ณด์˜€๋‹ค. 5 ๊ฐœ์˜ ๊ฐœ๋ณ„ ์•Œ๊ณ ๋ฆฌ์ฆ˜์— ๋ชจ๋‘ ์ ์šฉ๋˜๋Š” 2047 ๊ฐœ์˜ ์กฐํ•ฉ์„ ํ™•์ธํ•˜์˜€๊ณ  6๊ฐœ๋กœ (ApoA1, CA125, CA19-9, CEA, ApoA2 ๋ฐ TTR) ๊ตฌ์„ฑ๋œ ์ƒˆ๋กœ์šด ๋ฐ”์ด์˜ค ๋งˆ์ปค ์กฐํ•ฉ์„ ์ฐพ์•˜๋‹ค. ๊ณก์„  ์•„๋ž˜ ์˜์—ญ (Area under the curve; AUC), ํŠน์ด๋„ ๋ฐ ๋ฏผ๊ฐ๋„๋Š” ํ›ˆ๋ จ ์„ธํŠธ์—์„œ ๊ฐ๊ฐ 0.992, 95 % ๋ฐ 96 % ์˜€๊ณ  ๊ฒ€์ฆ ์„ธํŠธ์—์„œ 0.993, 96 % ๋ฐ 93 %์˜€๋‹ค. ์ทŒ๊ด€๋‚ด์œ ๋‘์ƒ ์ข…์–‘๊ณผ ๋น„๊ตํ•˜์˜€์„ ๋•Œ AUC๋Š” 0.964์˜€๊ณ , ํŠน์ด๋„ ๋ฐ ๋ฏผ๊ฐ๋„๋Š” 91.1%, 81.4%์˜€๋‹ค. ๊ฒฐ๋ก : ๋ณธ ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•˜์—ฌ ์ทŒ๊ด€์„ ์•”์˜ ์ง„๋‹จ์—์„œ 6๊ฐœ์˜ ๋ฐ”์ด์˜ค ๋งˆ์ปค๋กœ ๊ตฌ์„ฑ๋œ ์ง„๋‹จ ์•Œ๊ณ ๋ฆฌ์ฆ˜์ด ๊ฐœ๋ฐœ๋˜๊ณ  ๊ฒ€์ฆ ๋˜์—ˆ๋‹ค. ์ด๋Ÿฌํ•œ ์•Œ๊ณ ๋ฆฌ์ฆ˜์€ ์ทŒ๊ด€์„ ์•”์˜ ์กฐ๊ธฐ ์ง„๋‹จ์— ๋„์›€์ด ๋  ๊ฒƒ์ด๋‹ค.Abstract - i Contents iii List of Tables iv List of Figures - v Introduction 1 Materials and methods - 3 Results - 6 Discussion - 9 References 14 Tables 18 Figures 23 ๊ตญ๋ฌธ์ดˆ๋ก - 28Docto

    A study on the Turning Heel Angle of Passenger Type Vessel in Lightship Condition

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    Vessels are audited at regular intervals for the maintenance of various functions according to the Ships Safety Act. For a docking survey, the vessel maintains a minimum amount of fuel oil, ballast water, etc. and is in a status similar to a light weight status so has a high center of gravity than a normal sailing condition. The ship shall undertake the voyage to be docked. The vessel needs to turn due to an action of avoiding the dangerous obstruction that may result from during sailing or due to an action for altering course and may occur to the risk of heeling depending on the degree of turning. If the stability is not good during turning, it may lead to major accidents such as sinking or capsizing. In this paper, we selected 2 passenger ships(Seokyung Island, Seokyung Paradise) and 2 training ships(Hanwoori, Hanbada) to perform a study on the heeling angle during turing for passenger type vessel in lightship condition. Of 4 kinds of turnings in the light ship condition of the passenger type vessel, the heeling angle formula (A heeling angle formula during turning of passenger ship based on IMO stability criteria, modified heeling angle formula during turning of passenger ship based on IMO stability criteria, a heeling angle formula in steady turning and heeling angle formula taken account of drift angle in steady turning) the heeling during turing was calculated according to GoM, the speed, and the speed length ratio. The heeling angle calculation during turning was verified through an experiment of the real vessel: training ships โ€œHanwooriโ€ and โ€œHanbadaโ€. Average value was calculated through L/B based on selected vessel, the heeling angle during turning calculated for universalization and the numerical result was compared and analyzed. The GoM, the speed, and the speed length ratio were presented that can meet the heeling less than 10 degree during turning, presented in the IMO stability criteria in the light ship condition of the G/T 4,000 ~ 6,000 ton class, L/Bโ‰’5 passenger type vessel.์ œ1์žฅ ์„œ๋ก  1 1.1 ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉ์  1 1.2 ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• ๋ฐ ๋‚ด์šฉ 2 ์ œ2์žฅ ์—ฌ๊ฐ์„ ์˜ ์„ ํšŒ ์ค‘ ํšก๊ฒฝ์‚ฌ ๊ณ„์‚ฐ ์ด๋ก  6 2.1 ์„ ๋ฐ• ๊ณ ์ • ์ขŒํ‘œ๊ณ„ ์ •์˜ 6 2.2 ๋ณต์›์„ฑ์˜ ๊ฐœ์š” 6 2.2.1 ๋ณต์›์„ฑ์˜ ์›๋ฆฌ์™€ ๊ฐœ๋… 7 2.2.2 ์ดˆ๊ธฐ ๋ณต์›๋ ฅ 8 2.2.3 ์ •์ ๋ณต์›๋ ฅ๊ณก์„ ๋„์™€ ๋™์ ๋ณต์›๋ ฅ 10 2.2.4 IMO ๋ณต์›์„ฑ ์„ฑ๋Šฅ๊ธฐ์ค€ 13 2.3 ์„ ํšŒ ์ค‘ ํšก๊ฒฝ์‚ฌ ๊ณ„์‚ฐ์‹ 14 2.3.1 IMO ๋ณต์›์„ฑ ์„ฑ๋Šฅ๊ธฐ์ค€ ์„ ํšŒ ์ค‘ ํšก๊ฒฝ์‚ฌ ๊ณ„์‚ฐ์‹ 15 2.3.2 ์ •์ƒ ์„ ํšŒ ์ค‘ ์™ธ๋ฐฉ๊ฒฝ์‚ฌ ์ด๋ก ์‹ 16 2.3.3 ํŽธ๊ฐ์„ ๊ณ ๋ คํ•œ ์„ ํšŒ ์ค‘ ์™ธ๋ฐฉ๊ฒฝ์‚ฌ ์ด๋ก ์‹ 18 2.3.4 ์„ ํšŒ ์ค‘ ํšก๊ฒฝ์‚ฌ ๊ณ„์‚ฐ์„ ์œ„ํ•œ ์ž๋ฃŒ 20 ์ œ3์žฅ ์—ฌ๊ฐ์„ ํ˜•์˜ ์„ ํšŒ ์ค‘ ํšก๊ฒฝ์‚ฌ๊ฐ ๊ณ„์‚ฐ 21 3.1 ๋Œ€์ƒ ์„ ๋ฐ•์˜ ์ œ์› 21 3.1.1 ์„œ๊ฒฝ ์•„์ผ๋žœ๋“œํ˜ธ 21 3.1.2 ์„œ๊ฒฝ ํŒŒ๋ผ๋‹ค์ด์Šคํ˜ธ 23 3.1.3 ์‹ค์Šต์„  ํ•œ์šฐ๋ฆฌํ˜ธ 24 3.1.4 ์‹ค์Šต์„  ํ•œ๋ฐ”๋‹คํ˜ธ 25 3.2 ๊ณ„์‚ฐ์‹๋ณ„ ์„ ํšŒ ์ค‘ ํšก๊ฒฝ์‚ฌ๊ฐ์˜ ๋น„๊ต ๋ถ„์„ 26 3.2.1 ์„œ๊ฒฝ ์•„์ผ๋žœ๋“œํ˜ธ์˜ ํšก๊ฒฝ์‚ฌ๊ฐ ๊ณ„์‚ฐ 26 3.2.2 ์„œ๊ฒฝ ํŒŒ๋ผ๋‹ค์ด์Šคํ˜ธ์˜ ํšก๊ฒฝ์‚ฌ๊ฐ ๊ณ„์‚ฐ 30 3.2.3 ์‹ค์Šต์„  ํ•œ์šฐ๋ฆฌํ˜ธ์˜ ํšก๊ฒฝ์‚ฌ๊ฐ ๊ณ„์‚ฐ 33 3.2.4 ์‹ค์Šต์„  ํ•œ๋ฐ”๋‹คํ˜ธ์˜ ํšก๊ฒฝ์‚ฌ๊ฐ ๊ณ„์‚ฐ 36 3.3 GoM, ์„ ์†, ์†์žฅ๋น„์— ๋”ฐ๋ฅธ ํšก๊ฒฝ์‚ฌ๊ฐ ๋น„๊ต ๋ถ„์„ 39 3.3.1 GoM์— ๋”ฐ๋ฅธ ํšก๊ฒฝ์‚ฌ๊ฐ ๊ณ„์‚ฐ 39 3.3.2 ์„ ์†์— ๋”ฐ๋ฅธ ํšก๊ฒฝ์‚ฌ๊ฐ ๊ณ„์‚ฐ 47 3.3.3 ์†์žฅ๋น„์— ๋”ฐ๋ฅธ ํšก๊ฒฝ์‚ฌ๊ฐ ๊ณ„์‚ฐ 53 ์ œ4์žฅ ์‹ค์„  ์‹คํ—˜์„ ํ†ตํ•œ ๊ฒ€์ฆ ๋ฐ ์ข…ํ•ฉ ๋ถ„์„ 61 4.1 ์‹ค์Šต์„  ํ•œ์šฐ๋ฆฌํ˜ธ ์‹ค์„  ์‹คํ—˜ 61 4.1.1 ์‹คํ—˜ ๊ฐœ์š” 61 4.1.2 ์‹คํ—˜ ๊ฒฐ๊ณผ 62 4.1.3 ์‹คํ—˜ ๋‹น์‹œ ํšก๊ฒฝ์‚ฌ์™€ ๊ฐ ๊ณ„์‚ฐ์‹ ๊ณ„์‚ฐ ๊ฒฐ๊ณผ ๋น„๊ต 64 4.2 ์‹ค์Šต์„  ํ•œ๋ฐ”๋‹คํ˜ธ ์‹ค์„  ์‹คํ—˜ 67 4.2.1 ์‹คํ—˜ ๊ฐœ์š” 67 4.2.2 ์‹คํ—˜ ๊ฒฐ๊ณผ 68 4.2.3 ์‹คํ—˜ ๋‹น์‹œ ํšก๊ฒฝ์‚ฌ์™€ ๊ฐ ๊ณ„์‚ฐ์‹ ๊ณ„์‚ฐ ๊ฒฐ๊ณผ ๋น„๊ต 70 4.3 ์ข…ํ•ฉ ๋ถ„์„ 73 4.3.1 GoM๊ณผ ์„ ์†์— ๋”ฐ๋ฅธ ํšก๊ฒฝ์‚ฌ๊ฐ ๊ณ„์‚ฐ ์ข…ํ•ฉ ๋ถ„์„ 73 4.3.2 ์†์žฅ๋น„์— ๋”ฐ๋ฅธ ํšก๊ฒฝ์‚ฌ๊ฐ ๊ณ„์‚ฐ ์ข…ํ•ฉ ๋ถ„์„ 76 ์ œ5์žฅ ๊ฒฐ๋ก  78 ์ฐธ๊ณ ๋ฌธํ—Œ 8

    ๊ธฐ์ˆ  ์ฑ„ํƒ ๊ด€์ ์˜ ํ‘œ์ค€ํ™” ์ •์ฑ… ๋ถ„์„ : ํ•œ๊ตญ์˜ ์ •๋ณดํ†ต์‹ ์ •์ฑ…์„ ์ค‘์‹ฌ์œผ๋กœ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ํ˜‘๋™๊ณผ์ • ๊ธฐ์ˆ ๊ฒฝ์˜ยท๊ฒฝ์ œยท์ •์ฑ…์ „๊ณต, 2013. 8. ํ™ฉ์ค€์„.์šฐ๋ฆฌ๋‚˜๋ผ์˜ ์ •๋ณดํ†ต์‹ ์‚ฐ์—…์€ ๊ตญ๊ฐ€ ๊ฒฝ์ œ์„ฑ์žฅ์˜ ์ค‘์ถ”์ ์ธ ์—ญํ• ์„ ํ•˜๊ณ  ์žˆ๋‹ค. ์ •๋ณดํ†ต์‹ ์‚ฐ์—…์ด ๋ฐœ์ „ํ•˜๊ฒŒ ๋œ ์š”์ธ์€ ๋‹ค์–‘ํ•˜๋‚˜, ํŠนํžˆ CDMA ๊ธฐ์ˆ ์„ ์„ธ๊ณ„ ์ตœ์ดˆ๋กœ ์ƒ์šฉํ™”ํ•˜์—ฌ 2์„ธ๋Œ€ ์ด๋™ํ†ต์‹ ์˜ ํ‘œ์ค€์œผ๋กœ ์„ค์ •ํ•œ ๊ฒƒ์ด ๋ณธ๊ฒฉ์ ์ธ ๊ณ„๊ธฐ๊ฐ€ ๋˜์—ˆ๋‹ค. ์ดํ›„ ๋‹ค์–‘ํ•œ ๊ธฐ์ˆ ํ‘œ์ค€ํ™” ์ •์ฑ…์„ ํ†ตํ•ด ์ •๋ณดํ†ต์‹ ์‚ฐ์—…์„ ๋ฐœ์ „์‹œํ‚ค๊ณ ์ž ํ•˜์˜€์œผ๋‚˜, ํ˜„์žฌ๊นŒ์ง€์˜ ๊ฒฐ๊ณผ๋ฅผ ๋ณด์•˜์„ ๋•Œ ํ•ญ์ƒ ์„ฑ๊ณต์ ์ด์ง€๋Š” ๋ชปํ•˜์˜€๋‹ค. ํ‘œ์ค€ํ™” ์ „๋žต ์ž์ฒด๋Š” ๋งค์šฐ ํšจ๊ณผ์ ์ธ ์ „๋žต์ด๋ผ๊ณ  ํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ, ํ•œ๊ตญ์˜ ๊ฒฝ์šฐ ์ถ”๊ฒฉ์ž ์ „๋žต์˜ ์ˆ˜๋‹จ์œผ๋กœ๋„ ์ž์ฃผ ํ™œ์šฉ๋˜์—ˆ๋‹ค. ์ค‘์š”ํ•œ ๊ฒƒ์€, ์„ฑ๊ณต๊ณผ ์‹คํŒจ์˜ ์—ฌ๋ถ€๋ฅผ ๋– ๋‚˜์„œ ์ด์™€ ๊ฐ™์€ ๊ตญ๊ฐ€ ์ฃผ๋„์˜ ํ‘œ์ค€ํ™” ์ •์ฑ…์ด ์œ ํšจํ•˜์˜€๋Š”์ง€์— ๋Œ€ํ•œ ํ™•์ธ์ด ํ•„์š”ํ•˜๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ •๋ณดํ†ต์‹ ์‚ฐ์—…์˜ ํ‘œ์ค€ํ™” ์ •์ฑ…์„ ํ†ตํ•˜์—ฌ ๊ตญ๊ฐ€๊ฐ€ ๊ธฐ์ˆ  ํ‘œ์ค€์˜ ๊ณต๊ธ‰์ž๊ฐ€ ๋˜์—ˆ์„ ๋•Œ, ํ‘œ์ค€ ์ˆ˜์š”์ž์˜ ์ž…์žฅ์—์„œ ์ถฉ๋ถ„ํžˆ ํšจ๊ณผ์ ์ด์—ˆ๋Š”์ง€๋ฅผ ๋‹ค์–‘ํ•œ ๊ด€์ ์œผ๋กœ ์‚ดํŽด๋ณด๊ณ ์ž ํ•œ๋‹ค. ๋”ฐ๋ผ์„œ ํ•œ๊ตญ์˜ ๋Œ€ํ‘œ์ ์ธ ํ‘œ์ค€ํ™” ์ •์ฑ…์ด ์ ์šฉ๋˜์—ˆ๋˜ ์ด๋™ํ†ต์‹  ๋„คํŠธ์›Œํฌ, ๊ด‘๋Œ€์—ญ์œตํ•ฉ๋ง, ๋ชจ๋ฐ”์ผ ํ”Œ๋žซํผ์˜ ์‚ฌ๋ก€๋ฅผ ํ†ตํ•ด ํ‘œ์ค€ํ™” ์ •์ฑ…์˜ ์œ ํšจ์„ฑ์„ ์‚ดํŽด๋ณด๋ฉฐ, ์ด๋ฅผ ํ†ตํ•ด ์ถ”ํ›„ ํ•œ๊ตญ์ด ์ „๊ฐœํ•ด์•ผ ํ•  ํ‘œ์ค€ํ™” ์ •์ฑ…์— ๋Œ€ํ•œ ์‹œ์‚ฌ์ ์„ ๋„์ถœํ•˜๊ณ ์ž ํ•œ๋‹ค. ์ฒซ์งธ, ์ด๋™ํ†ต์‹  ์‚ฐ์—…์—์„œ ๋ณด์กฐ๊ธˆ ํ˜•ํƒœ์˜ ํ‘œ์ค€ํ™” ์ •์ฑ…์„ ํ†ตํ•œ ์ •๋ถ€ ๊ฐœ์ž…์˜ ํšจ๊ณผ๋ฅผ ์‚ดํŽด๋ณธ๋‹ค. ์ด๋™ํ†ต์‹  ๊ธฐ์ˆ ์€ ๋Š์ž„์—†๋Š” ํ˜์‹ ์„ ํ†ตํ•ด ์ƒˆ๋กœ์šด ํ‘œ์ค€์œผ๋กœ ์ง€์†์ ์ธ ์„ธ๋Œ€๊ฐ„ ์ง„ํ™”๊ฐ€ ์ด๋ฃจ์–ด์ง€๊ณ  ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ์†Œ๋น„์ž๋Š” ๊ธฐ์กด ํ‘œ์ค€์„ ๊ณ„์†ํ•ด์„œ ์‚ฌ์šฉํ•  ๊ฒƒ์ธ์ง€ ํ˜น์€ ์ƒˆ๋กœ์šด ํ‘œ์ค€์„ ์ฑ„ํƒํ• ์ง€ ๊ฒฐ์ •ํ•ด์•ผ ํ•œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ํ›„์ƒ ๊ด€์ ์œผ๋กœ ๋ดค์„ ๋•Œ ์ƒˆ๋กœ์šด ๊ธฐ์ˆ ํ‘œ์ค€์ด ๊ณผ๋„ํ•˜๊ฒŒ ๋นจ๋ฆฌ ์ฑ„ํƒ๋  ๊ฒฝ์šฐ ๋ฐœ์ƒํ•˜๋Š” ์ดˆ๊ณผ์ฑ„ํƒ๊ณผ ๊ฐ™์€ ์‚ฌํšŒ์ ์œผ๋กœ ๋ฐ”๋žŒ์งํ•˜์ง€ ์•Š์€ ๊ฒฐ๊ณผ๊ฐ€ ๋ฐœ์ƒํ•˜๊ธฐ๋„ ํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ์‹œ์žฅ ์‹คํŒจ๋ฅผ ๋ฐฉ์ง€ํ•˜๊ธฐ ์œ„ํ•ด ์ •๋ถ€๋Š” ๋ณด์กฐ๊ธˆ๊ณผ ๊ฐ™์€ ์ •์ฑ… ๋„๊ตฌ๋ฅผ ํ™œ์šฉํ•ด ์‹œ์žฅ์— ๊ฐœ์ž…ํ•˜๊ธฐ๋„ ํ•œ๋‹ค. ๋”ฐ๋ผ์„œ 3์žฅ์€ ์ดˆ๊ณผ์ฑ„ํƒ๊ณผ ๊ฐ™์€ ๊ฐœ๋…์„ ํ™œ์šฉํ•˜์—ฌ ๊ธฐ์ˆ ํ‘œ์ค€์˜ ์ง„ํ™”๊ฐ€ ์ง„ํ–‰๋  ๋•Œ ์ •๋ถ€ ์ •์ฑ…์  ๊ฐœ์ž…์˜ ์‚ฌํšŒ์  ํšจ๊ณผ๋ฅผ ์ˆ˜ํ•™์  ๋ชจํ˜•์„ ํ†ตํ•ด ์‚ดํŽด๋ณธ๋‹ค. ๋ถ„์„ ๊ฒฐ๊ณผ ๋‘ ๊ธฐ์ˆ ์˜ ํ˜ธํ™˜์„ฑ๊ณผ ๊ด€๊ณ„์—†์ด ์ดˆ๊ณผ ์ฑ„ํƒ ํ˜„์ƒ๊ณผ ์‚ฌํšŒ ํ›„์ƒ์˜ ๊ฐ์†Œ๊ฐ€ ๋ฐœ์ƒํ•˜๊ธฐ๋„ ํ•˜๋ฉฐ, ํŠนํžˆ ๋‘ ๊ธฐ์ˆ ๊ฐ„์˜ ์ฐจ์ด ํ˜น์€ ์‹ ๊ธฐ์ˆ ์˜ ๊ฐœ์„  ์ •๋„๊ฐ€ ๋‚ฎ์„ ๊ฒฝ์šฐ ์ดˆ๊ณผ ์ฑ„ํƒ์˜ ๊ฐ€๋Šฅ์„ฑ์€ ๋”์šฑ ๋†’์•„์ง„๋‹ค. ๋˜ํ•œ ํ•œ๊ตญ์˜ ์ด๋™ํ†ต์‹  ์‚ฌ๋ก€๋ฅผ ํ†ตํ•ด ์ดˆ๊ณผ ์ฑ„ํƒ์˜ ๊ฐ€๋Šฅ์„ฑ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋‘˜์งธ, ๋Œ€๊ทœ๋ชจ ๊ณต๊ณต ์‚ฌ์—…์ธ ๊ด‘๋Œ€์—ญ์œตํ•ฉ๋ง(BcN)์„ ํ†ตํ•œ ํ‘œ์ค€ํ™” ๋…ธ๋ ฅ์„ ์‚ดํŽด๋ณธ๋‹ค. ํ•œ๊ตญ ๋ฐ ์ค‘๊ตญ๊ณผ ๊ฐ™์€ ์‹ ํฅ์‚ฐ์—…๊ตญ์€ ์ •๋ถ€ ์ฃผ๋„์˜ ๋Œ€ํ˜• R&D ์‚ฌ์—…์„ ์ „๊ฐœํ•˜๋ฉด์„œ ๋™์‹œ์— ๊ณต์  ํ‘œ์ค€ํ™” ๋“ฑ์˜ ๊ตญ๊ฐ€ ํ‘œ์ค€ํ™” ์ •์ฑ…์„ ์ ๊ทน์ ์œผ๋กœ ํ™œ์šฉํ•˜์˜€๋‹ค. ์ด๋Ÿฌํ•œ ์ •์ฑ…์€ ์ด๋™ํ†ต์‹  ๊ด€๋ จ ํ‘œ์ค€์œผ๋กœ ์ž์ฃผ ํ™•์ธ๋˜๋‚˜, BcN ์‚ฌ์—… ๋‚ด์—์„œ๋„ ๊ทธ ์‹œ์ž‘๊ณผ ํ•จ๊ป˜ ํ‘œ์ค€ํ™”๋ฅผ ๋™์‹œ์— ๊ณ ๋ คํ•œ BcN ํ‘œ์ค€ ๋ชจ๋ธ ์‚ฌ์—…์ด ํ•จ๊ป˜ ์ „๊ฐœํ•˜์˜€๋‹ค. BcN ์‚ฌ์—…์˜ ์„ฑ๊ณผ๋Š” ์ •์„ฑ์ ์ธ ๋ฐฉ๋ฒ•์„ ํ†ตํ•ด ๋งŽ์ด ๋ถ„์„๋˜์—ˆ์œผ๋‚˜, BcN ํ‘œ์ค€ ๋ชจ๋ธ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋Š” ์ฐพ์•„๋ณด๊ธฐ ์‰ฝ์ง€ ์•Š๋‹ค. ๋”ฐ๋ผ์„œ 4์žฅ์—์„œ๋Š” BcN ํ‘œ์ค€ ๋ชจ๋ธ์„ ํ‰๊ฐ€ํ•˜์—ฌ ์ •๋ถ€์ฃผ๋„ ํ‘œ์ค€ํ™” ์ •์ฑ…์˜ ํšจ๊ณผ๋ฅผ ์‚ดํŽด๋ณธ๋‹ค. ์‚ฌ๋ก€ ๋ถ„์„์„ ์œ„ํ•ด ํ‘œ์ค€ ๋ชจ๋ธ์˜ ์ฑ„ํƒ๋ฅ ์„ ์กฐ์‚ฌํ•˜์˜€์œผ๋ฉฐ ์ถ”๊ฐ€์ ์ธ ์ธํ„ฐ๋ทฐ๋กœ ๊ทธ ๊ณผ์ •์„ ์‚ดํŽด๋ณด์•˜๋‹ค. ์„ค๋ฌธ์กฐ์‚ฌ ๊ฒฐ๊ณผ ๋งŽ์€ ํˆฌ์ž๊ฐ€ ํ•„์š”ํ•œ BcN ํ‘œ์ค€ ๋ชจ๋ธ์˜ ํ•˜์œ„ ๊ณ„์ธต์€ ์ฑ„ํƒ๋ฅ ์ด ๋‚ฎ์€ ๋ฐ˜๋ฉด ๋†’์€ ๊ณ„์ธต์€ ์ค‘์†Œ๊ธฐ์—…์˜ ๋งŽ์€ ์ฐธ์—ฌ๋กœ ์ธํ•ด ๋†’์€ ์ฑ„ํƒ๋ฅ ์„ ๋ณด์˜€๋‹ค. ์ด๋Š” ์ •๋ถ€ ์ฃผ๋„์˜ ๊ณต์  ํ‘œ์ค€ํ™”๊ฐ€ ์˜๋„ํ•˜์ง€ ์•Š์€ ๊ฒฐ๊ณผ์ด๋ฉฐ, ์˜คํžˆ๋ ค ์ปจ์†Œ์‹œ์—„ ์ฃผ๋„์˜ ํ‘œ์ค€ํ™”๊ฐ€ ํ™•์ธ๋˜์—ˆ๋‹ค. ์ด์™€ ๊ฐ™์€ ๋Œ€ํ˜• ๊ณต๊ณต ์‚ฌ์—…์˜ ๊ฒฝ์šฐ ๋งŽ์€ ์ˆ˜์˜ ์ดํ•ด๊ด€๊ณ„์ž๊ฐ€ ๋™์‹œ์— ์กด์žฌํ•˜๋ฏ€๋กœ ํ‘œ์ค€ํ™” ์ •์ฑ…์˜ ๋…ธ๋ ฅ์ด ํšจ๊ณผ์ ์ด์ง€ ์•Š์Œ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์…‹์งธ, ํ‘œ์ค€ํ™”๋œ ๋ชจ๋ฐ”์ผ ํ”Œ๋žซํผ์˜ ํšจ์œจ์„ฑ์„ ์ธก์ •ํ•˜๊ธฐ ์œ„ํ•ด WIPI๋ฅผ ์„ ํƒํ•˜์˜€๋‹ค. ํ˜„์žฌ ๋ชจ๋ฐ”์ผ ์ƒํƒœ๊ณ„์—์„œ ์•ˆ๋“œ๋กœ์ด๋“œ์™€ iOS๋Š” ์‚ฌ์‹ค์ƒ ํ‘œ์ค€์ด๋‚˜ ์ฝ˜ํ…์ธ  ๊ธฐ์—…์˜ ํšจ์œจ์„ฑ์„ ์œ„ํ•ด ํ‘œ์ค€ ๋ชจ๋ฐ”์ผ ํ”Œ๋žซํผ์ด ํ•„์š”ํ•˜๋‹ค๋Š” ์˜๊ฒฌ๋„ ์กด์žฌํ•œ๋‹ค. ๋”ฐ๋ผ์„œ ์ •๋ถ€ ์ฃผ๋„ ํ‘œ์ค€ํ™” ์ •์ฑ…์„ ํ†ตํ•ด ์ œ์ •๋œ WIPI๊ฐ€ ์ฝ˜ํ…์ธ  ๊ธฐ์—…์—๊ฒŒ ํšจ์œจ์ ์ด์—ˆ๋Š”์ง€ ์‚ดํŽด๋ณผ ํ•„์š”๊ฐ€ ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ 5์žฅ์—์„œ๋Š” ๋ชจ๋ฐ”์ผ ํ”Œ๋žซํผ์˜ ๊ธฐ์ˆ ์ด ์‚ฌ์šฉ๋œ ๊ธฐ๊ฐ„์— ๋”ฐ๋ผ pre-WIPI, on-WIPI, post-WIPI ๋“ฑ ์„ธ ๊ฐœ์˜ ์ฝ˜ํ…์ธ  ๊ธฐ์—… ๊ทธ๋ฃน์œผ๋กœ ๋‚˜๋ˆ„๊ณ  ํ™•๋ฅ ๋ณ€๊ฒฝ๋ถ„์„(SFA)์„ ์‚ฌ์šฉํ•˜์—ฌ ๊ฐ ๊ทธ๋ฃน์˜ ํšจ์œจ์„ฑ์„ ์‚ดํŽด๋ณด์•˜๋‹ค. ๊ทธ ๊ฒฐ๊ณผ ์‚ฌ์—…์ž ์ฃผ๋„์˜ ํ”Œ๋žซํผ์„ ํ™œ์šฉํ•œ ์ฝ˜ํ…์ธ  ๊ธฐ์—… ๊ทธ๋ฃน(pre-WIPI)์ด ๊ฐ€์žฅ ํšจ์œจ์ ์ธ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๊ฐ ๊ทธ๋ฃน์˜ ์ƒ์‚ฐํ•จ์ˆ˜๊ฐ€ ๋™์ผํ•˜์ง€ ์•Š์œผ๋ฏ€๋กœ, ๋ฉ”ํƒ€ํ”„๋ก ํ‹ฐ์–ด ์ƒ์‚ฐํ•จ์ˆ˜๋ฅผ ์ด์šฉํ•˜์—ฌ ๊ฐ ๊ทธ๋ฃน์˜ ํšจ์œจ์„ฑ์„ ๋‹ค์‹œ ๋น„๊ตํ•˜์˜€๋‹ค. ๊ทธ ๊ฒฐ๊ณผ ์ •๋ถ€์ฃผ๋„ ํ‘œ์ค€ ํ”Œ๋žซํผ(on-WIPI)์„ ์‚ฌ์šฉํ•˜๋Š” ๊ธฐ์—…์ด ๊ฐ€์žฅ ๋น„ํšจ์œจ์ ์ด์—ˆ์œผ๋ฉฐ, ์‚ฌ์‹ค์ƒ ํ‘œ์ค€์„ ์‚ฌ์šฉํ•˜๋Š” ๊ธฐ์—…(post-WIPI)์ด ๊ฐ€์žฅ ํšจ์œจ์ ์ด์—ˆ๋‹ค. ์ข…ํ•ฉ์ ์œผ๋กœ ํ•œ๊ตญ์˜ ๋‹ค์–‘ํ•œ ํ‘œ์ค€ํ™” ์ •์ฑ…์€ ๊ธฐ๋Œ€๋งŒํผ ํšจ๊ณผ์ ์ด์ง€๋Š” ์•Š์•˜๋˜ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์„ ํ†ตํ•ด ์ •๋ถ€๊ฐ€ ์ „ํ†ต์  ํ‘œ์ค€ํ™” ์ •์ฑ…๋งŒ์„ ๊ณ ์ˆ˜ํ•˜๊ธฐ ๋ณด๋‹ค๋Š” ์ƒˆ๋กœ์šด ๋Œ€์•ˆ์ด ํ•„์š”ํ•˜๋‹ค๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋˜ํ•œ ๊ณต์  ํ‘œ์ค€ํ™”์˜ ์ค‘์‹ฌ์  ์—ญํ• ์—์„œ ์‚ฌ์‹ค์ƒ ํ‘œ์ค€ํ™”์˜ ์กฐ๋ ฅ์ž๋กœ ์ •์ฑ… ๋ฐฉํ–ฅ์„ ์ „ํ™˜ํ•  ๊ฒƒ์„ ์ œ์•ˆํ•˜์˜€๋‹ค.South Korea has achieved remarkable economic growth backed by the growth of the information and communication technology (ICT) industry. Not only foresight activities and proactive investments of conglomerates in the ICT industry, but the government-led standardization policies were significant factors in facilitating the economic growth. Encouraged by the success in CDMA, South Korea has implemented various standardization policies. However, the technology standardization policies up to date have not produced remarkable results that could meet the expectations. As seen in many cases, a standardization policy is an important strategy for countries which want to catch up with more developed countries. Given the importance, many countries seek to identify the effectiveness of their national standardization policies regardless of their success or failure. Governments need to examine social effects of standardization policy in various perspectives. This study focuses on the following contexts. First, the mobile communication industry was selected to examine the effectiveness of a standardization policy based on government intervention in the form of subsidies. Since mobile communication technology standards continue to make progress and go through generational transition, consumers have to decide whether they stay in using the existing technology standard or adopt a new technology standard. In terms of social welfare, however, socially undesirable outcome may occur, such as excess momentum which means a market failure when a new technology standard is adopted too quickly. In order to control the risk of such market failure, governments occasionally intervene in the generational transition of technology standards via policy instruments such as subsidies. Using the concept of excess momentum, a type of market failure, Chapter 3 examines the social effect of governmental policy intervention in the form of subsidies when a technology standard transition is in progress. This chapter uses a simple two-stage model and especially analyzes two scenarios in which existing and new technology standards are compatible or incompatible. The results reveal that regardless of whether existing and new technology standards are compatible, a situation of excess momentum and decreased social welfare may occur. In particular, if the technological difference between existing and new technology standards is less significant, and improvement in the new technology standard is also less significant, the possibility of excess momentum increases. Furthermore, in a case analysis, the mobile communication industry in South Korea is examined as an example and the possibility of excess momentum in this industry is identified. Second, the Broadband convergence Network (BcN) was selected to evaluate the standardization efforts in large scale public projects. Attempts by government-led large scale R&D projects are frequently identified and proactive national standardization policies named de jure standardization are implemented in newly industrialized countries such as South Korea and China. Though these policies usually focus on technology standards associated with mobile communication, the BcN project was also planned to consider standardization by implementing a subproject, BcN standard model from the beginning. While the performance of BcN is largely evaluated using qualitative methodologies, studies on standardization policy by BcN standard model are not investigated. Therefore, Chapter 4 evaluates the BcN standard model in order to examine the effectiveness of a government-led standardization policy. For the case analysis, a survey is conducted to observe the adoption rate of the BcN standard model, and an interview is entailed to review the efforts on BcN standard model. According to the adoption rate of the BcN standard model, the lower layer which needs a significant amount of investments shows a low adoption rate, while the higher layer shows a high adoption rate due to small and medium enterprises (SMEs). Different adoption rates of the layers are unintended results of de jure standardization, and rather a form of consortia-led standardization is revealed. In such large scale public sector projects in which multiple stakeholders are involved, standardization policies may not be effective. Third, as for a mobile platform, wireless Internet platform for interoperability (WIPI) was selected to measure the efficiency of content providers which use standardized mobile platform. While two de facto standards, Android and iOS, are now prevalent platforms in the mobile ecosystem, some still argue that one standardized mobile platform is necessary to ensure the efficiency of content providers. For this reason, it is pertinent to examine whether government-led standardization policy for mobile platform standard, WIPI, was efficient to content providers in South Korea. Therefore, Chapter 5 categorizes content providers into three groups โ€“ pre-WIPI, on-WIPI, and post-WIPI โ€“ in accordance with the period of mobile platform technologies and measures efficiency of each group based on stochastic frontier analysis. The results show that content providers using MNO-dependent mobile platform, the pre-WIPI group, are most efficient. However, as a hypothesis that the production function for each group is identical is rejected, additional analysis using meta-frontier production function is conducted to compare different efficiency levels for each group. In this case, content providers using a standardized mobile platform are least efficient rather, and firms in the post-WIPI group, revealing de facto standards, are most efficient. In South Korea, several standardization policies were introduced in order to achieve national economic growth. However, the standardization policies were not so effective as expected. This study suggests that the government consider alternatives to traditional standardization policies, switching its role from a core actor of de jure standardization to a facilitator for de facto standardization.Abstract iii Contents vii List of Tables xi List of Figures xii Chapter 1. Introduction 1 1.1 Research Background 1 1.2 Problem Description 3 1.3 Research Objectives 6 1.4 Research Questions 7 1.5 Research Outline 10 1.6 Contribution 12 Chapter 2. Literature Review 15 2.1 The Origin of Standardization Research 15 2.2 Demand Side of Standardization Research 18 2.3 Supply Side of Standardization Research 20 2.4 Standardization for Innovation 23 2.5 Standardization Strategy for National Innovation Policy 25 Chapter 3. Examining Policy Intervention on the Standard Transition: A Case of Mobile Communication 28 3.1 Introduction 28 3.2 Basic Model 33 3.2.1 Description of the Game 33 3.2.2 Preference of Consumers for the New Technology 34 3.3 New Technology Compatible with Existing Technology 37 3.3.1 Without Subsidies 37 3.3.2 With Subsidies 43 3.4 New Technology Incompatible with Existing Technology 45 3.4.1 Without Subsidies 45 3.4.2 With Subsidies 50 3.5 Analysis 53 3.6 Evidence of Excess Momentum: the Case of 3G Mobile Communication in South Korea 57 3.7 Implication: Beyond 3G 61 3.8 Conclusion 63 Chapter 4. Evaluating Government-Led Standardization Policy: A Case of Broadband Convergence Network Standard Model 65 4.1 Introduction 65 4.2 Broadband Convergence Network 68 4.3 BcN Standard Model 71 4.4 Case description 73 4.5 Analysis 75 4.5.1 Survey Result 75 4.5.2 Discussion 76 4.6 Conclusion 82 Chapter 5. Measuring the Efficiency of Standardization Policy Using Meta-Frontier Analysis: A Case of Mobile Platform Standardization 84 5.1 Introduction 84 5.2 Wireless Internet Platform for Interoperability (WIPI) 89 5.3 Methodology 91 5.3.1 Production Efficiency Analysis 91 5.3.2 Stochastic Frontier Analysis 95 5.3.3 Meta-Frontier Analysis 98 5.3.4 Data and Model Specification 104 5.4 Empirical Results 106 5.4.1 Stochastic Frontier Analysis Estimation Results 106 5.4.2 Meta-Frontier Function Estimation Results 110 5.5 Implications 116 5.6 Conclusion 117 Chapter 6. Conclusion 120 6.1 Summary 120 6.2 Policy Implications 124 6.3 Limitations and Further Research 126 Bibliography 128 Appendix 1: Summary of Equilibrium 148 Abstract (Korean) 151Docto

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