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    ๋น„๊ตฌ์กฐ์š”์†Œ์˜ ๋‚ด์ง„์„ค๊ณ„๋ฅผ ์œ„ํ•œ ๋“ฑ๊ฐ€์ •์  ๋ฐ ๋™์  ์ธต์‘๋‹ต ๋ถ„์„

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :๊ณต๊ณผ๋Œ€ํ•™ ๊ฑด์ถ•ํ•™๊ณผ,2019. 8. ์ด์ฒ ํ˜ธ.In this study, the commonly used method, equivalent static approach for seismic design of non-structural elements, was evaluated to find the possibility of developing current provisions. To evaluate current design code, ASCE7 is reviewed. By evaluating static load approach suggested in current code provisions, it seemingly revealed shortcomings of the static method while using dynamic method considering fundamental period of supporting structure. A total of five three-dimensional models were analyzed using structural analysis program. In the first set of analysis, 3-, 9-, 20-story three-dimensional SAC building models were evaluated and in the second set of analysis, 4-, 8-story asymmetrical telecommunication buildings were proposed for analyzing floor spectrum based on linear static analysis and dynamic analysis from ASCE7-16. Dynamic Analysis includes response spectrum analysis, linear time history analysis, nonlinear time history analysis and alternative floor response spectra. The result from both linear static analysis and dynamic analysis is typically used for floor response spectrum for nonstructural elements because each floors maximum acceleration can mitigate the process of reinforcement for nonstructural elements under earthquakes. Typically, most evaluations for spectrum analysis depend heavily on simplified two-dimensional numerical models. In this study, the equivalent static method was evaluated based on elementary structural dynamics and numerical case study of realistic three-dimensional model. The inaccuracy of the equivalent static approach resulting from the negligence of the fundamental period of supporting structures was clearly illustrated using elementary structural dynamics. The numerical dynamic analysis of 3-dimensional building models also showed that the magnitude and distribution of the maximum floor acceleration can significantly be influenced by the supporting structural characteristics such as fundamental period, higher modes, nonlinearity and torsion. The current equivalent static approach needs to be improved such that some of the key influential structural parameters are selectively included within the limit of practicality.์ตœ๊ทผ 2 ๋…„๊ฐ„ ํ•œ๊ตญ์—์„œ๋Š” ๋ฆฌํžˆํ„ฐ ๊ทœ๋ชจ 5.8์˜ ๊ฒฝ์ฃผ์ง€์ง„(2016)๊ณผ 5.4์˜ ํฌํ•ญ์ง€์ง„(2017)์ด ์—ฐ๋‹ฌ์•„ ๋ฐœ์ƒํ•˜๋ฉฐ ์ˆ˜๋งŽ์€ ์žฌ์‚ฐํ”ผํ•ด๋ฅผ ์ž…ํžˆ๊ณ  ๋” ์ด์ƒ ํ•œ๊ตญ์€ ์ง€์ง„์˜ ์•ˆ์ „์ง€๋Œ€๊ฐ€ ์•„๋‹ˆ๋ผ๋Š” ์‚ฌ์‹ค๊ณผ ํ•จ๊ป˜ ๊ตญ๋ฏผ๋“ค์—๊ฒŒ ์ง€์ง„์— ๋Œ€ํ•œ ๊ฒฝ๊ฐ์‹ฌ์„ ๋ถˆ๋Ÿฌ์ผ์œผ์ผฐ๋‹ค. ํŠนํžˆ ์ด๋ฒˆ ํฌํ•ญ์ง€์ง„์—์„œ๋Š” ๋ณด๋‚˜ ๊ธฐ๋‘ฅ, ์Šฌ๋ž˜๋ธŒ๋“ฑ์˜ ๊ตฌ์กฐ์š”์†Œ์˜ ํ”ผํ•ด๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ๋น„๊ตฌ์กฐ์š”์†Œ์˜ ํ”ผํ•ด๊ทœ๋ชจ๊ฐ€ ์ปธ๊ธฐ ๋•Œ๋ฌธ์— ๋น„๊ตฌ์กฐ์š”์†Œ์˜ ๋‚ด์ง„์„ค๊ณ„์— ๋Œ€ํ•œ ๊ด€์‹ฌ์ด ๋†’์•„์ง„ ๊ฒƒ์ด ์‚ฌ์‹ค์ด๋‹ค. ๊ฑด์ถ•๊ตฌ์กฐ๊ธฐ์ค€์— ๋”ฐ๋ฅด๋ฉด ๊ฑด์ถ•๊ตฌ์กฐ์š”์†Œ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ๊ตฌ์กฐ๋‚ด๋ ฅ์„ ๋ถ€๋‹ดํ•˜์ง€ ์•Š๋Š” ๋น„๊ตฌ์กฐ์š”์†Œ์ธ ๋น„๊ตฌ์กฐ๋ฒฝ์ฒด, ์ด์ค‘๋ฐ”๋‹ฅ, ์ฒœ์žฅ ๋ฐ ์บ๋น„๋‹› ๋“ฑ๋„ ๊ธฐ์ค€์„ ๋”ฐ๋ผ์•ผ ํ•œ๋‹ค๊ณ  ๋ช…์‹œ๋˜์–ด ์žˆ์ง€๋งŒ ์‚ฌ์‹ค์ƒ ์ ์šฉ์‚ฌ์‹ค์œ ๋ฌด๋Š” ํ™•์ธํ•˜๊ธฐ ์–ด๋ ค์šด ์‹ค์ •์ด๋‹ค. ์ด๋ฒˆ ์—ฐ๊ตฌ์—์„œ๋Š” ๋น„๊ตฌ์กฐ์š”์†Œ์˜ ๋‚ด์ง„์„ค๊ณ„๋ฅผ ์œ„ํ•ด ์ผ๋ฐ˜์ ์œผ๋กœ ์‚ฌ์šฉ๋˜๋Š” ๋ฐฉ๋ฒ•์ธ ๋“ฑ๊ฐ€ ์ •์ ํ•ด์„๋ฒ•์„ ํ‰๊ฐ€ํ•˜์—ฌ ํ˜„ํ–‰ ์ฝ”๋“œ๋ฅผ ๋ฐœ์ „์‹œํ‚ฌ ์ˆ˜ ์žˆ๋Š” ๊ฐ€๋Šฅ์„ฑ์„ ๋ชจ์ƒ‰ํ•˜์˜€๋‹ค. ํ˜„์žฌ ์„ค๊ณ„์ฝ”๋“œ๋ฅผ ํ‰๊ฐ€ํ•˜๊ธฐ ์œ„ํ•ด ASCE7๋ฅผ ๊ฒ€ํ† ํ•ด ํ˜„ํ–‰ ์ฝ”๋“œ ์กฐํ•ญ์— ์ œ์‹œ๋˜์–ด ์žˆ๋Š” ๋“ฑ๊ฐ€์ •์  ์ ‘๊ทผ๋ฐฉ์‹์˜ ๋ฌธ์ œ์ ์„ ๋ถ„์„ํ•œ๋‹ค. ๊ฑด๋ฌผ์˜ ๊ณ ์œ ์ฃผ๊ธฐ๋ฅผ ๊ณ ๋ คํ•œ ๋™์ ํ•ด์„๋ฒ•์„ ์‚ฌ์šฉํ•ด ๋“ฑ๊ฐ€์ •์ ํ•ด์„๋ฒ•์˜ ๋ฌธ์ œ์ ์„ ๋ฐํ˜€๋‚ด๊ณ  ๊ตฌ์กฐํ•ด์„ ํ”„๋กœ๊ทธ๋žจ์„ ์‚ฌ์šฉํ•˜์—ฌ ์ˆ˜์น˜ํ•ด์„์  ๊ฒฐ๊ณผ๋ฅผ ๋ถ„์„ํ•˜์˜€๋‹ค. ASCE7-16์˜ ์„ ํ˜• ์ •์ ํ•ด์„๊ณผ ๋™์ ํ•ด์„์„ ๊ธฐ๋ฐ˜์œผ๋กœ ์ธต์‘๋‹ต ๋ถ„์„์„ ์ˆ˜ํ–‰ํ•˜์˜€์œผ๋ฉฐ ์ˆ˜์น˜ํ•ด์„์€ ์ด 5๊ฐœ์˜ 3์ฐจ์› ๊ฑด๋ฌผ๋ชจ๋ธ๋“ค์„ ํ‰๊ฐ€ํ•˜์˜€๊ณ  ์ฒซ ๋ฒˆ์งธ ํŒŒํŠธ์—์„œ๋Š” 3์ธต, 9์ธต, 20์ธต์˜ 3์ฐจ์› SAC๊ฑด๋ฌผ ๋ชจ๋ธ์„ ํ‰๊ฐ€ํ•˜์˜€๊ณ  ๋‘ ๋ฒˆ์งธ ํŒŒํŠธ์—์„œ๋Š” ๋น„์ •ํ˜•์„ฑ์ด ์žˆ๋Š” 4์ธต, 8์ธต ํ†ต์‹ ๊ฑด๋ฌผ์„ ๋ถ„์„ํ•˜์˜€๋‹ค. ๋™์ ๋ถ„์„์€ ์‘๋‹ต ์ŠคํŽ™ํŠธ๋Ÿผ ํ•ด์„, ์„ ํ˜• ์‹œ๊ฐ„์ด๋ ฅ ํ•ด์„, ๋น„์„ ํ˜• ์‹œ๊ฐ„์ด๋ ฅ ํ•ด์„ ๋ฐ ๊ฐ„๋žต ์ธต์‘๋‹ต ์ŠคํŽ™ํŠธ๋Ÿผ ํ•ด์„์„ ํฌํ•จํ•˜๋Š”๋ฐ ์ด๋ฒˆ ์—ฐ๊ตฌ์—์„œ๋Š” ์‘๋‹ต ์ŠคํŽ™ํŠธ๋Ÿผ ํ•ด์„, ์„ ํ˜• ์‹œ๊ฐ„์ด๋ ฅ ํ•ด์„๊ณผ ๋น„์„ ํ˜• ์‹œ๊ฐ„์ด๋ ฅ ํ•ด์„์„ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ๋“ฑ๊ฐ€์ •์ ํ•ด์„๊ณผ ๋™์  ํ•ด์„์˜ ๊ฒฐ๊ณผ๋Š” ์ฃผ๋กœ ๋น„๊ตฌ์กฐ์š”์†Œ๋ฅผ ์œ„ํ•œ ์ธต์‘๋‹ต์ŠคํŽ™ํŠธ๋Ÿผ์„ ๊ตฌํ•˜๊ธฐ ์œ„ํ•ด ์‚ฌ์šฉ๋˜๋Š”๋ฐ ์ด๋Š” ๊ฐ ์ธต์˜ ์ตœ๋Œ€ ๊ฐ€์†๋„๊ฐ€ ์ง€์ง„์˜ ์˜ํ–ฅ์„ ๋ฐ›๊ณ ์žˆ๋Š” ๋น„๊ตฌ์กฐ์š”์†Œ์˜ ๋‚ด์ง„์„ค๊ณ„ ๊ณผ์ •์„ ๋‹จ์ˆœํ™” ์‹œ์ผœ์ฃผ๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. ์ผ๋ฐ˜์ ์œผ๋กœ ์ŠคํŽ™ํŠธ๋Ÿผ ๋ถ„์„์— ๋Œ€ํ•œ ํ‰๊ฐ€๋Š” 2์ฐจ์› ์ˆ˜์น˜ํ•ด์„ ๋ชจ๋ธ์— ํฌ๊ฒŒ ์˜์กดํ•˜๊ธฐ ๋•Œ๋ฌธ์— ์ค‘์š”ํ•œ ๋งค๊ฐœ๋ณ€์ˆ˜๋“ค์„ ๊ณ ๋ คํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” 3์ฐจ์› ๋ชจ๋ธ์˜ ์ˆ˜์น˜ํ•ด์„์ด ํ•„์š”ํ•˜๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ํ˜„์‹ค์ ์ธ 3์ฐจ์› ์ˆ˜์น˜ํ•ด์„ ๋ชจ๋ธ์˜ ๊ธฐ์ดˆ ๊ตฌ์กฐ์—ญํ•™๊ณผ ์ˆ˜์น˜ํ•ด์„ ์—ฐ๊ตฌ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ๋“ฑ๊ฐ€์ •์ ํ•ด์„๋ฒ•์„ ํ‰๊ฐ€ํ•˜์˜€๋‹ค. ๊ธฐ์ดˆ ๊ตฌ์กฐ์—ญํ•™์„ ํ†ตํ•ด ๊ฑด๋ฌผ์˜ ๊ณ ์œ ์ฃผ๊ธฐ๋ฅผ ๋ฐ˜์˜ํ•˜์ง€ ์•Š์€ ๋“ฑ๊ฐ€์ •์ ํ•ด์„๋ฒ•์ด ์ •ํ™•ํ•˜์ง€ ์•Š๋‹ค๋Š” ๊ฒƒ์ด ๋ช…ํ™•ํ•˜๊ฒŒ ์„ค๋ช…๋œ๋‹ค. ๋˜ํ•œ 3์ฐจ์› ๊ฑด๋ฌผ ๋ชจ๋ธ์˜ ๋™์  ์ˆ˜์น˜ํ•ด์„์€ ์ตœ๋Œ€ ์ธต์‘๋‹ต์˜ ํฌ๊ธฐ์™€ ๋ถ„ํฌ๊ฐ€ ๊ณ ์œ ์ฃผ๊ธฐ, ๊ณ ์ฐจ๋ชจ๋“œ, ๋น„์„ ํ˜•์„ฑ ๋ฐ ๋น„ํ‹€๋ฆผ๊ณผ ๊ฐ™์€ ๊ฑด๋ฌผ ํŠน์„ฑ์— ๋”ฐ๋ผ ํฌ๊ฒŒ ์˜ํ–ฅ์„ ๋ฐ›์„ ์ˆ˜ ์žˆ์Œ์„ ๋ณด์—ฌ์ค€๋‹ค. ํ˜„ํ–‰ ๋“ฑ๊ฐ€ ์ •์  ๋ฐฉ๋ฒ•์€ ์ผ๋ถ€ ์˜ํ–ฅ๋ ฅ ์žˆ๋Š” ๋งค๊ฐœ๋ณ€์ˆ˜๊ฐ€ ์‹ค์šฉ์„ฑ์„ ๊ณ ๋ คํ•œ ํ•œ๊ณ„ ๋‚ด์—์„œ ์„ ํƒ์ ์œผ๋กœ ํฌํ•จ๋˜๋„๋ก ๊ฐœ์„ ๋  ํ•„์š”๊ฐ€ ์žˆ๋‹ค.Table of Contents Abstract Table of Contents List of Figures Chapter 1 Introduction 1.1. Research background 1.2. Objectives and scope 1.3. Outline of thesis Chapter 2 Review of Equivalent Static Approach in Design Standards and Previous Studies 2.1. Backgrounds of current design standards 2.1.1. 1994 NEHRP 2.1.2. 1994 /1997 UBC 2.2. Current design codes 2.2.1. ASCE7-16 2.2.1.1. Equivalent static analysis 2.2.1.2. Dynamic analysis 2.2.2. EUROCODE 8 2.3. Previous studies 2.3.1. Kehoe and Freeman (1998) 2.3.2. Drake and Bachman (1995) 2.3.3. Singh (1987) 2.3.4. Anajafi and Medina (2018) 2.3.5. Villaverde (2000) Chapter 3 Evaluation Based on Elementary Dynamic Theory 3.1. Introduction 3.2. Preliminary analysis of instrumented building database 3.3. Absolute floor acceleration based on structural dynamics 3.4. Response of non-structural element supporting structures natural frequency 3.5. Summary Chapter 4 Evaluation of Equivalent Static Method based on Numerical Analysis 4.1. Introduction 4.2. Numerical model: 3-, 9-, 20-story SAC model, 4-, 8-story telecommunication building model 4.3. Effect of structural period 4.4. Effect of higher modes 4.5. Effect of Nonlinearity 4.6. Torsion 4.6.1. Introduction 4.6.2. Evaluation of ASCE 7-16 method 4.7. Floor response spectrum method application Chapter 5 Case study: Effect of ap, and Rp application 5.1. Acceleration sensitive non-structural component 5.2. Deformation sensitive non-structural component Chapter 6 Summary and Conclusions Bibliography Abstract (in Korean) AcknowledgementsMaste

    ๋ผํ‹ด์•„๋ฉ”๋ฆฌ์นด์—์„œ ํฌํ“ฐ๋ฆฌ์ŠคํŠธ ํ†ต์น˜๊ฐ€ ์ž์œ ๋ฏผ์ฃผ์ฃผ์˜์— ๋ฏธ์น˜๋Š” ๊ฐ€๋ณ€์  ์˜ํ–ฅ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ตญ์ œ๋Œ€ํ•™์› ๊ตญ์ œํ•™๊ณผ, 2020. 8. ๊น€์ข…์„ญ.Populist rule is one of the most symbolic features that have characterized modern politics in Latin America. In so far as the outcomes of populist rule in the region are studied, one of the main interests in the existing literature is its impact on the quality of liberal democracy. This thesis seeks to contribute to the existing literature on the relationship between the two variables by conducting empirical research based on a panel dataset covering 18 Latin American countries from 1991 to 2017. I find an overall negative relationship between populist rule and liberal democracy, which is a reflection of their inherent incompatibility and the populist project of maximizing the utility of the individuals forming a majority at the expense of the elite and minority. However, what has been observed across the countries in the region is that some populist presidents distort liberal democratic institutions with a high level of discretion, whereas others relatively conform to the constraints imposed by liberal democracy and have a limited impact on it. I argue that the capability of populist presidents to attack liberal democratic institutions is determined by the estimated costs of doing so incurred by a set of constraints arising from three groups in society: the informal working class; the formal working class; and the capitalist class. Each of these three groups, with class-specific socioeconomic demands, curtails populist incumbents room to maneuver by posing a probable threat to governability. The populist government is by nature constrained by the requirement to please the informal working class, who constitute a majority in a typical Latin American society and are willing to support the populist project only if their socioeconomic demands are met. Its policy choices are also constrained by the formal working class and the capitalist class, who possess disproportionate influences in the society and are interested in the protection of the existing political order. I identify three variables that are closely related to each of the three potential veto players to the populist project: natural resource rents, industrial employment, and financial development. Depending on the levels of these three variables, the extent to which populist presidents can actually pursue strengthening of executive power and radical institutional changes that are consistent with their populist discourse is determined. I find that the negative impact of populist rule on liberal democracy is exacerbated with a higher level of natural resource rents and lower levels of industrial employment and financial development. Finally, I complement my quantitative analysis with an examination of the experiences of a number of Latin American countries under populist rule. This study is one of the first systematic evaluations of the constraints that shape governing populists capability to damage liberal democratic institutions.1. Introduction 1 2. Populism 9 2.1. Defining Populism 9 2.1.1 The Ideational Definition of Populism 9 2.1.2. The ideational Definition of Populism in Comparison 11 2.1.3. Advantages of the Ideational Definition of Populism 15 2.2. A Brief History of Populism in Latin America 17 2.3. Identifying Populist Presidents 22 3. Liberal Democracy 29 3.1. Defining Liberal Democracy 29 3.1.1. Democracy "without Adjectives" 29 3.1.2. The Definition of Liberal Democracy 30 3.2. Measuring Liberal Democracy 32 3.3. Liberal Democracy in Latin America 35 4. The Relationship between Populism and Liberal Democracy 44 4.1. Populist Threats to Liberal Democracy 44 4.1.1. The Impossibility of Coexistence 44 4.1.2. Populism as a Corrective to Democracy 46 4.1.3. The Populist Playbook 47 4.2. Populists Gone "Radical" and "Moderate" 57 4.3. Populist Presidents' Room to Maneuver and its Constraints 61 4.3.1. Populist Presidents and Constraints from Three Groups 61 4.3.2. Joint Effect of Populist Rule and Natural Resource Rents on Liberal Democracy 67 4.3.3. Joint Effect of Populist Rule and Industrial Employment on Liberal Democracy 72 4.3.4. Joint Effect of Populist Rule and Financial Development on Liberal Democracy 78 5. Empirical Analysis 83 5.1. Research Hypotheses 83 5.2. Model Specification 83 5.3. Regression Results 89 6. Case Study 105 6.1. Populist Rule, Natural Resource Rents and Liberal Democracy 105 6.2. Populist Rule, Industrial Employment and Liberal Democracy 110 6.3. Populist Rule, Financial Development and Liberal Democracy 116 7. Conclusion 121 References 127Docto

    ๊ฐ€์ƒ ๋„คํŠธ์›Œํฌ์˜ ์ž์› ํ• ๋‹น, ๊ฐ€๊ฒฉ ๊ฒฐ์ • ๋ฐ ๊ณ ์žฅ ๊ด€๋ฆฌ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ „๊ธฐยท์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€, 2013. 8. ์„œ์Šน์šฐ.๋„คํŠธ์›Œํฌ ๊ฐ€์ƒํ™”๋Š” ๋ฌผ๋ฆฌ์  ๋„คํŠธ์›Œํฌ์˜ ๊ณต์œ  ์ž์›๋“ค์„ ๋ณต์ˆ˜ ๊ฐœ์˜ ๊ฐ€์ƒ ๋„คํŠธ์›Œํฌ๋“ค์— ๋™์ ์œผ๋กœ ํ• ๋‹นํ•  ์ˆ˜ ์žˆ๊ฒŒ ํ•ด์ฃผ๋Š” ๊ธฐ์ˆ ์ด๋‹ค. ์ž์› ํ• ๋‹น์˜ ์œ ์—ฐ์„ฑ๊ณผ ๊ฐ€์ƒ ๋„คํŠธ์›Œํฌ๋“ค ์‚ฌ์ด์˜ ๋…๋ฆฝ์„ฑ ๋•Œ๋ฌธ์—, ๋„คํŠธ์›Œํฌ ๊ฐ€์ƒํ™”๋Š” ๋„คํŠธ์›Œํฌ ํ…Œ์ŠคํŠธ๋ฒ ๋“œ๋ฅผ ์„ค๊ณ„ํ•˜๊ธฐ ์œ„ํ•œ ๊ธฐ๋ฐ˜ ๊ธฐ์ˆ ๋กœ์จ ์ฃผ๋กœ ํ™œ์šฉ๋˜์–ด ์™”์„ ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ, ์ธํ„ฐ๋„ท์˜ ๋‹ค์–‘ํ™”๋ฅผ ์ง€์›ํ•˜๊ธฐ ์œ„ํ•œ ๋น„์šฉ ํšจ์œจ ๋†’์€ ํ•ด๊ฒฐ์ฑ…์œผ๋กœ์จ ์—ฌ๊ฒจ์ง€๊ธฐ ์‹œ์ž‘ํ–ˆ๋‹ค. ์„œ๋น„์Šค์— ๋”ฐ๋ผ ๊ณ„์ธตํ™”๋œ ์ธํ„ฐ๋„ท์„ ์„ค๊ณ„ํ•˜๊ธฐ ์œ„ํ•œ ํ•˜๋‚˜์˜ ์ˆ˜๋‹จ์œผ๋กœ์จ, ๋„คํŠธ์›Œํฌ ๊ฐ€์ƒํ™”๋Š” ์—ฌ์ „ํžˆ ํ•ด๊ฒฐํ•ด์•ผ ํ•  ๋งŽ์€ ๋„์ „ ๊ณผ์ œ๋“ค์„ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค. ์ด ํ•™์œ„ ๋…ผ๋ฌธ์€ ๊ฐ€์ƒ ๋„คํŠธ์›Œํฌ ํ™˜๊ฒฝ์—์„œ ์ค‘์š”ํ•œ ๋ช‡ ๊ฐ€์ง€ ์ƒˆ๋กœ์šด ์—ฐ๊ตฌ ์ฃผ์ œ๋“ค์„ ์ œ์‹œํ•˜๊ณ , ๊ทธ์— ๋Œ€ํ•œ ํšจ๊ณผ์ ์ธ ํ•ด๋ฒ•๋“ค์„ ์ œ์•ˆํ•œ๋‹ค. ์ฒซ ๋ฒˆ์งธ๋กœ, ๊ฐ€์ƒ ๋„คํŠธ์›Œํฌ์˜ ๋‹ค์–‘ํ•œ QoS ์š”๊ตฌ์‚ฌํ•ญ์„ ๋งŒ์กฑ์‹œํ‚ฌ ์ˆ˜ ์žˆ๋Š” ๋„คํŠธ์›Œํฌ ์ตœ์  ๋ถ„ํ•  ๋ฐฉ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. QoS์™€ ๋Œ€์—ญํญ ์ œํ•œ ์กฐ๊ฑด์„ ๊ณ ๋ คํ•˜์—ฌ ๊ฐ€์ƒ ๋„คํŠธ์›Œํฌ ๋ถ„ํ•  ๋ฌธ์ œ๋ฅผ ์ตœ์ ํ™” ๋ฌธ์ œ๋กœ ๋ชจํ˜•ํ™”ํ•˜๊ณ , ๋ฌธ์ œ์˜ ๊ตฌ์กฐ์  ๋ณต์žก์„ฑ์„ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ์ตœ๋‹จ ๊ฒฝ๋กœ ๋ผ์šฐํŒ…์— ๊ธฐ๋ฐ˜ํ•œ ํœด๋ฆฌ์Šคํ‹ฑ์„ ์ œ์•ˆํ•œ๋‹ค. ์‹ค์ œ ์ธํ„ฐ๋„ท ํ™˜๊ฒฝ์„ ๊ณ ๋ คํ•œ ๋Œ€๊ทœ๋ชจ ์‹คํ—˜์„ ํ†ตํ•ด, ์ œ์•ˆํ•œ ํœด๋ฆฌ์Šคํ‹ฑ์˜ ํšจ์œจ์„ฑ๊ณผ ํ™•์žฅ์„ฑ์„ ์ž…์ฆํ•œ๋‹ค. ๋‹ค์Œ์œผ๋กœ, ๊ฐ€์ƒ ๋„คํŠธ์›Œํฌ์—์„œ ์ฐจ๋“ฑ ์ ‘์† ์„œ๋น„์Šค๋ฅผ ์œ„ํ•œ ๊ฒฝ์ œ์„ฑ ๋ถ„์„ ๋ชจ๋ธ์„ ์ œ์‹œํ•œ๋‹ค. ๋จผ์ € ์‚ฌ์šฉ์ž ๊ฐ€์ž… ๋ณ€๋™ ๋ชจํ˜•์ด ํ•œ ๊ฐ’์œผ๋กœ ์ˆ˜๋ ดํ•˜๊ธฐ ์œ„ํ•œ ์ถฉ๋ถ„ ์กฐ๊ฑด์„ ์œ ๋„ํ•˜๊ณ , ์ด๋Ÿฌํ•œ ์กฐ๊ฑด ํ•˜์—์„œ ์ธํ„ฐ๋„ท ์„œ๋น„์Šค ์ œ๊ณต์ž์˜ ์ˆ˜์ต์„ ์ตœ๋Œ€ํ™”ํ•  ์ˆ˜ ์žˆ๋Š” ์ตœ์ ์˜ ๊ฐ€๊ฒฉ ๊ฒฐ์ • ๋ฐฉ๋ฒ• ๋ฐ ๋Œ€์—ญํญ ๋ถ„ํ•  ๋ฐฉ๋ฒ•์„ ์ฐพ๋Š”๋‹ค. ์ˆ˜์น˜ ์‹คํ—˜์„ ํ†ตํ•ด, ์ ์ ˆํ•œ ๊ฐ€๊ฒฉ ๊ฒฐ์ •๊ณผ ๋Œ€์—ญํญ ๋ถ„ํ• ์ด ์ด๋ฃจ์–ด์ง„๋‹ค๋Š” ๊ฐ€์ • ํ•˜์—์„œ ์ฐจ๋“ฑํ™” ์„œ๋น„์Šค๊ฐ€ ๋‹จ์ผ ์„œ๋น„์Šค๋ณด๋‹ค ๋” ๋†’์€ ์ˆ˜์ต์„ฑ์„ ๋‚˜ํƒ€๋‚ผ ์ˆ˜ ์žˆ์Œ์„ ์ฆ๋ช…ํ•œ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ, ๊ฐ€์ƒ ๋„คํŠธ์›Œํฌ ๊ฐ„ ํŠธ๋ž˜ํ”ฝ ์ „ํ™˜์„ ํ†ตํ•œ ๋น ๋ฅด๊ณ  ํšจ๊ณผ์ ์ธ ๊ณ ์žฅ ํšŒ๋ณต ๊ธฐ์ˆ ์„ ๊ฐœ๋ฐœํ•œ๋‹ค. ๊ฐ€์ƒ ๋„คํŠธ์›Œํฌ์˜ ๊ตฌ์กฐ์  ํŠน์„ฑ์„ ํ™œ์šฉํ•œ ๊ณ ์žฅ ํšŒ๋ณต ๊ธฐ์ˆ ์„ ์ด์šฉํ•˜๋ฉด, ๋ชจ๋“  ๋งํฌ์— ๋Œ€ํ•œ ๋ฐฑ์—… ๊ฒฝ๋กœ๊ฐ€ ํ•ญ์ƒ ์กด์žฌํ•˜๋„๋ก ๋ฏธ๋ฆฌ ํ† ํด๋กœ์ง€๋ฅผ ์„ค๊ณ„ํ•ด์•ผ ํ•  ํ•„์š”๊ฐ€ ์—†๊ณ , ๊ฐ ๋ผ์šฐํ„ฐ์—์„œ ๊ทธ ๊ฒฝ๋กœ๋“ค์— ๋Œ€ํ•œ ๊ณ„์‚ฐ์„ ๋ฏธ๋ฆฌ ํ•ด ๋†“์„ ํ•„์š”๊ฐ€ ์—†๋‹ค. ๊ทธ๋Ÿผ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ , ์ œ์•ˆํ•œ ๊ณ ์žฅ ํšŒ๋ณต ๋ฐฉ๋ฒ•์€ ๊ธฐ์กด์˜ ๊ธฐ์ˆ ๋“ค๊ณผ ๊ฐ™์€ ์ข‹์€ ์„ฑ๋Šฅ์„ ๋ณด์ธ๋‹ค. ์ด ํ•™์œ„ ๋…ผ๋ฌธ์€ ๊ฐ€์ƒ ๋„คํŠธ์›Œํฌ๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•˜๋Š” ์ธํ„ฐ๋„ท ํ™˜๊ฒฝ์—์„œ ๋ฐœ์ƒํ•  ์ˆ˜ ์žˆ๋Š” ์ค‘์š”ํ•œ ๋ฌธ์ œ๋“ค์„ ๋‹ค๋ฃจ๊ณ ์ž ํ•œ๋‹ค. ์ด ๋…ผ๋ฌธ์—์„œ ์ œ์•ˆํ•˜๋Š” ๋ถ„์„ ๋ชจ๋ธ ๋ฐ ์‹คํ—˜ ๊ฒฐ๊ณผ๋“ค์€ ํ˜„์žฌ ์ธํ„ฐ๋„ท์˜ ํ•œ๊ณ„๋ฅผ ๊ทน๋ณตํ•˜๊ณ , ๋ฏธ๋ž˜ ์ธํ„ฐ๋„ท ์•„ํ‚คํ…์ฒ˜๋ฅผ ์„ค๊ณ„ํ•˜๊ธฐ ์œ„ํ•œ ์œ ์šฉํ•œ ์ง€์นจ์„ ์ œ๊ณตํ•  ๊ฒƒ์ด๋‹ค.Network virtualization is an emerging technology that enables the dynamic partitioning of a shared physical network infrastructure into multiple virtual networks. Because of its flexibility in resource allocation and independency among virtual networks, the network virtualization technology has not only been mainly deployed to build a testbed network, but also has come to be regarded as a cost-effective solution for diversifying the Internet. As a means of building the multi-layered Internet, network virtualization still faces a number of challenging issues that need to be addressed. This dissertation deals with several important research topics and provides effective solutions in network virtualization environment. First, I focus on the optimal partitioning of finite substrate resources for satisfying the diverse QoS requirements of virtual networks. I formulate virtual network partitioning problem as a mixed integer multi-commodity flow problem. Then, to tackle the structural complexity of the problem, I propose a simple heuristic based on shortest path routing algorithm. By conducting large-scale network experiments, I verify the efficiency and scalability of the heuristic. Next, I propose an economic model for tiered access service in virtual networks in order to remedy the deficiency of the existing tiered service schemes. I first derive a sufficient condition for stability of user subscription dynamics, and find the optimal pricing and capacity partitioning by addressing the revenue maximization problem of the tiered access service in a network virtualization environment. Numerical results show that the tiered service can be more profitable than the non-tiered service under proper pricing and capacity partitioning conditions. Last, I develop a fast and effective failure recovery mechanism through inter-virtual network traffic switching in virtual networks. The proposed failure recovery mechanism neither has topological constraints for the existence of backup paths, nor requires the pre-computation of them, but nevertheless guarantees as fast recovery as the existing failure recovery methods. This dissertation aims to address important issues in the virtual network-based Internet. I believe that the analysis and results in this dissertation will provide useful guidelines to improve the Internet.1 Introduction 1.1 Background and Motivation 1.2 Contributions and Outline of the Dissertation 2 Effective Partitioning for Service Level Differentiation in Virtual Networks 2.1 Introduction 2.2 Related Work 2.3 Model and Assumption 2.3.1 Business Model 2.3.2 Network Model 2.3.3 Traffic Demands 2.3.4 QoS Metric 2.4 Formulation 2.4.1 Objective 2.4.2 Substrate Partitioning Problem 2.4.3 Decomposition 2.5 Heuristic 2.6 Evaluation 2.6.1 Small Network Experiment 2.6.2 Large Network Experiment 2.7 Summary 3 Optimal Pricing and Capacity Partitioning for Tiered Access Service in Virtual Networks 3.1 Introduction 3.2 Motivating Example 3.3 A Tiered Service Model 3.3.1 Network Virtualization Environment 3.3.2 Effective Access Rate 3.3.3 Valuation Parameter and User Utility 3.3.4 User Subscription and the ISP Revenue 3.4 Non-tiered Service Analysis 3.4.1 User Subscription Dynamics 3.4.2 Optimal Pricing for Maximizing the ISP Revenue 3.5 Tiered Service Analysis 3.5.1 User Subscription Dynamics 3.5.2 Convergence of the User Subscription Dynamics 3.5.3 Optimal Pricing for Maximizing the ISP Revenue 3.6 Numerical Results 3.6.1 Non-tiered Service Example 3.6.2 Tiered Service Example 3.7 Related Work and Discussion 3.8 Summary 4 Inter-Virtual Network Traffic Switching for Fast Failure Recovery 4.1 Introduction 4.2 Background 4.3 Preliminaries 4.3.1 Virtual Network Model 4.3.2 Design Goals 4.3.3 Business Models and Switching Policy Agreement 4.3.4 Other Considerations 4.4 Failure Recovery based on Traffic Switching 4.4.1 Inter-VN Traffic Switching 4.4.2 Failure Recovery Process 4.5 Numerical Analysis 4.5.1 Delay 4.5.2 Congestion probability 4.6 Summary 5 Conclusion A Proofs of Lemmas A.1 Proof of Lemma 2 A.2 Proof of Lemma 3Docto

    ๊ธฐ์ดˆ๊ต์œก์›์ดˆ๋น™๊ต์ˆ˜-๊ณ ์€ ์‹œ์ธ์„ ๋งŒ๋‚˜๋‹ค

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    2008-2016๋…„ ๊ณ ์šฉ๋ฅ  ๋ณ€ํ™”๋ฅผ ์ค‘์‹ฌ์œผ๋กœ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์‚ฌํšŒ๊ณผํ•™๋Œ€ํ•™ ์‚ฌํšŒ๋ณต์ง€ํ•™๊ณผ, 2019. 2. ๊ตฌ์ธํšŒ.์ธ๊ตฌ๊ณ ๋ นํ™”๊ฐ€ ์‹ฌ๊ฐํ•œ ์‚ฌํšŒ๋ฌธ์ œ๋กœ ๋ถ€๊ฐ๋˜๋ฉด์„œ ๋…ธ์ธ์˜ ๋…ธ๋™์ฐธ์—ฌ์— ๋Œ€ํ•œ ์‚ฌํšŒ์  ๊ด€์‹ฌ์ด ์ปค์ง€๊ณ  ์žˆ๋‹ค. ๋…ธ์ธ์˜ ๊ฒฝ์ œํ™œ๋™ ์ฐธ์—ฌ๋Š” ์ƒ์‚ฐ์ธ๊ตฌ์˜ ๊ฐ์†Œ์— ๋Œ€์‘ํ•˜๊ณ , ์ •๋ถ€์˜ ์žฌ์ • ๋ถ€๋‹ด์„ ์ค„์ด๋ฉฐ, ๊ฐœ์ธ์˜ ์‚ถ์˜ ์งˆ์„ ๋†’์ด๋Š” ๋ฐ ๊ธฐ์—ฌํ•  ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€๋ฅผ ๋ฐ›๊ณ  ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ํ•œ๊ตญ ์‚ฌํšŒ๋Š” OECD ํ‰๊ท ์˜ ๋‘ ๋ฐฐ๊ฐ€ ๋„˜๋Š” ๋…ธ์ธ ๊ณ ์šฉ๋ฅ ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ์—ฌ์ „ํžˆ ์ ˆ๋ฐ˜์— ๊ฐ€๊นŒ์šด ๋…ธ์ธ์ด ๋นˆ๊ณค์— ์ฒ˜ํ•ด ์žˆ๊ณ , ์ผํ•˜๋Š” ๋…ธ์ธ์˜ ์ƒ๋‹น์ˆ˜๋Š” ๊ณ ์šฉ๋ถˆ์•ˆ๊ณผ ์ €์ž„๊ธˆ์— ์‹œ๋‹ฌ๋ฆฌ๊ณ  ์žˆ๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” ๋…ธ์ธ์˜ ๋…ธ๋™์‹œ์žฅ ์ฐธ์—ฌ๋ฅผ ๋†’์ด๋ ค๋Š” ์‚ฌํšŒ์ •์ฑ…์  ๋…ธ๋ ฅ์— ์•ž์„œ, ํ•œ๊ตญ์˜ ๋…ธ์ธ ๊ณ ์šฉ๋ฅ ์ด ์ง€์†์ ์œผ๋กœ ๋†’์€ ์ˆ˜์ค€์„ ์œ ์ง€ํ•˜๋Š” ์ด์œ ๊ฐ€ ๋ฌด์—‡์ธ์ง€์— ๋Œ€ํ•œ ์ดํ•ด๊ฐ€ ์„ ํ–‰๋  ํ•„์š”๊ฐ€ ์žˆ๋‹ค๋Š” ์ธ์‹์—์„œ ์ถœ๋ฐœํ•œ๋‹ค. ์„œ๊ตฌ์˜ ๊ฒฝ์šฐ, 20์„ธ๊ธฐ ์ดํ›„๋ถ€ํ„ฐ 1980๋…„๋Œ€ ์ค‘๋ฐ˜๊นŒ์ง€ ๋…ธ์ธ์„ ๋น„๋กฏํ•œ ๊ณ ๋ น์ธต์˜ ๋…ธ๋™์‹œ์žฅ์ฐธ์—ฌ๊ฐ€ ์ง€์†์ ์œผ๋กœ ๊ฐ์†Œํ•˜๋Š” ์ถ”์ด๋ฅผ ๋ณด์—ฌ์™”์œผ๋ฉฐ, ์ดํ›„ 1990๋…„๋Œ€ ๋“ค์–ด์„œ ๋น„๊ต์  ์•ˆ์ •์ ์ธ ์ˆ˜์ค€์„ ์œ ์ง€ํ•˜๋‹ค๊ฐ€, 1990๋…„๋Œ€ ํ›„๋ฐ˜๋ถ€ํ„ฐ๋Š” ์ด์ „๊ณผ ๋‹ฌ๋ฆฌ ์ฆ๊ฐ€ํ•˜๊ธฐ ์‹œ์ž‘ํ•˜์˜€๋‹ค. ๋…ธ์ธ ๋…ธ๋™์ด ๊ฐ์†Œํ•˜๋˜ ์‹œ๊ธฐ์—๋Š” ๋†์—… ๋น„์ค‘์˜ ๊ฐ์†Œ์™€ ๊ฐ™์€ ์‚ฐ์—…๊ตฌ์กฐ์˜ ๋ณ€ํ™”, ๋…ธ์ธ์„ ๋Œ€์ƒ์œผ๋กœ ํ•œ ์†Œ๋“๋ณด์žฅ์ œ๋„์˜ ํ™•๋Œ€๊ฐ€ ์ฃผ๋„์ ์ธ ์˜ํ–ฅ์„ ๋ฏธ์ณค๋‹ค. ๋ฐ˜๋ฉด, ๋…ธ์ธ์˜ ๊ณ ์šฉ๋ฅ ์ด ๋ฐ˜๋“ฑํ•œ ์‹œ๊ธฐ์—๋Š” ๋…ธ์ธ์˜ ๋…ธ๋™์ƒ์‚ฐ์„ฑ ํ–ฅ์ƒ์ด๋‚˜, ์—ฌ์„ฑ์˜ ๋…ธ๋™์‹œ์žฅ ์ฐธ์—ฌ๊ฐ€ ํ™œ๋ฐœํ•ด์ง„ ๋ณ€ํ™” ์™ธ์—๋„, ๊ณต์ ์—ฐ๊ธˆ์ œ๋„๋ฅผ ๋น„๋กฏํ•œ ๋…ธํ›„์†Œ๋“๋ณด์žฅ์ œ๋„๊ฐ€ ์ถ•์†Œ๋˜๋Š” ๋“ฑ ์ด์ „ ์‹œ๊ธฐ์™€๋Š” ๋‹ค๋ฅธ ๋ฐฉํ–ฅ์˜ ์‚ฌํšŒ์ œ๋„์  ๋ณ€ํ™”๊ฐ€ ์ฃผ๋œ ์˜ํ–ฅ์„ ๋ฏธ์นœ ๊ฒƒ์œผ๋กœ ํ‰๊ฐ€๋œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์„œ๊ตฌ์˜ ๊ฒฝํ—˜์— ๊ธฐ์ดˆํ•œ ์ด๋Ÿฌํ•œ ์„ค๋ช…๋“ค๋กœ ํ•œ๊ตญ ๋…ธ์ธ์˜ ๊ณ ์šฉ๋ฅ  ๋ณ€ํ™” ์ถ”์ด๋ฅผ ์ดํ•ดํ•˜๊ธฐ์—๋Š” ๋ฌด๋ฆฌ๊ฐ€ ์žˆ์–ด ๋ณด์ธ๋‹ค. 1960๋…„๋Œ€ ์ดํ›„ ์‚ฐ์—…๊ตฌ์กฐ์˜ ๋ณ€ํ™”๊ฐ€ ๊ฐ€์žฅ ๋น ๋ฅด๊ฒŒ ๋‚˜ํƒ€๋‚œ ์‹œ๊ธฐ์— ์„œ๊ตฌ์™€๋Š” ๋ฐ˜๋Œ€๋กœ ๋…ธ์ธ์˜ ๋…ธ๋™์ฐธ์—ฌ๊ฐ€ ๋†’์•„์กŒ๊ณ , 2000๋…„๋Œ€ ์ดํ›„ ๋…ธํ›„์†Œ๋“๋ณด์žฅ์ œ๋„๊ฐ€ ์ง€์†์ ์œผ๋กœ ํ™•๋Œ€๋œ ์‹œ๊ธฐ์—๋„ ๋…ธ์ธ์˜ ๋…ธ๋™์ฐธ์—ฌ๋Š” ๊ฐ์†Œํ•˜์ง€ ์•Š์•˜๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. ์„œ๊ตฌ์—์„œ ๋…ธ์ธ์˜ ๋…ธ๋™์ฐธ์—ฌ๊ฐ€ ๊ฐ์†Œํ•œ ์‹œ๊ธฐ์™€ ๋น„์Šทํ•œ ๋ฐฉํ–ฅ์˜ ๋ณ€ํ™” ์†์—์„œ๋„, ํ•œ๊ตญ ๋…ธ์ธ์˜ ๋…ธ๋™์ฐธ์—ฌ๊ฐ€ ์„œ๊ตฌ์™€๋Š” ๋‹ค๋ฅธ ๋ณ€ํ™” ์ถ”์ด๋ฅผ ๋ณด์ด๋Š” ์ด์œ ๊ฐ€ ๋ฌด์—‡์ผ๊นŒ? ์ด ์—ฐ๊ตฌ๋Š” ๋…ธํ›„์†Œ๋“๋ณด์žฅ์ œ๋„๊ฐ€ ํ™•๋Œ€๋œ 2000๋…„๋Œ€ ์ค‘๋ฐ˜ ์ดํ›„ ์‹œ๊ธฐ๋ฅผ ์ค‘์‹ฌ์œผ๋กœ ํ•œ๊ตญ์˜ ๋…ธ์ธ ๊ณ ์šฉ๋ฅ  ๋ณ€ํ™” ์ถ”์ด๋ฅผ ํ™•์ธํ•˜๊ณ , ์–ด๋– ํ•œ ์š”์ธ๋“ค์ด ๊ทธ๋Ÿฌํ•œ ๋ณ€ํ™”์— ์˜ํ–ฅ์„ ๋ฏธ์ณค๋Š”์ง€๋ฅผ ๋ถ„์„ํ•œ๋‹ค. ๋ถ„์„์— ์‚ฌ์šฉํ•˜๋Š” ์ž๋ฃŒ๋Š” ๊ณ ๋ นํ™”์—ฐ๊ตฌํŒจ๋„์กฐ์‚ฌ์˜ 2008๋…„, 2016๋…„์˜ ๊ธฐ๋ณธ์กฐ์‚ฌ ์ž๋ฃŒ์™€ 2007๋…„์— ์กฐ์‚ฌ๋œ ์ง์—…๋ ฅ ์ž๋ฃŒ์ด๋ฉฐ, ๊ตญ๋ฏผ์—ฐ๊ธˆ์„ ์ˆ˜๊ธ‰ํ•˜๋Š” ์—ฐ๋ น๋Œ€๋ฅผ ๊ณ ๋ คํ•˜์—ฌ 60-84์„ธ ์—ฐ๋ น์ง‘๋‹จ์„ ๋ถ„์„๋Œ€์ƒ์œผ๋กœ ํ•œ๋‹ค. ๋ถ„์„๋ฐฉ๋ฒ•์œผ๋กœ๋Š” ๋…ธ๋™๊ฒฝ์ œํ•™์—์„œ ์‹œ์  ๊ฐ„(ํ˜น์€ ์ง‘๋‹จ ๊ฐ„) ๊ฒฐ๊ณผ๋ณ€์ˆ˜์˜ ์ฐจ์ด๋ฅผ ๋ถ„ํ•ดํ•˜๋Š” ๋ฐ ๋งŽ์ด ์‚ฌ์šฉ๋˜์–ด ์˜จ ๋ถ„ํ•ด๋ฐฉ๋ฒ•(decomposition methods) ์ค‘, ๋น„๋ชจ์ˆ˜์  ๋ฐฉ๋ฒ•์— ๊ธฐ์ดˆํ•œ ์žฌ๊ฐ€์ค‘(reweighting) ๋ถ„ํ•ด๋ฐฉ๋ฒ•์„ ์ ์šฉํ•œ๋‹ค. ์ด ๋ฐฉ๋ฒ•์€ ๊ด€์ธก๋œ ๋‘ ์‹œ์  ์ค‘ ํ•œ ์‹œ์ ์— ์žฌ๊ฐ€์ค‘์น˜๋ฅผ ๋ถ€์—ฌํ•˜์—ฌ ๋…ธ์ธ์˜ ์ทจ์—…์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์š”์ธ๋“ค์˜ ๋ถ„ํฌ๊ฐ€ ๋‹ค๋ฅธ ์‹œ์ ๊ณผ ๋™์ผํ•ด์ง€๋„๋ก ์กฐ์ •ํ•œ ์žฌ๊ฐ€์ค‘ ํ‘œ๋ณธ์„ ๊ตฌ์„ฑํ•œ ํ›„, ๋‘ ์‹œ์  ๊ฐ„ ๊ฒฐ๊ณผ๋ณ€์ˆ˜์˜ ์ฐจ์ด๋ฅผ ์„ค๋ช…๋ณ€์ˆ˜์˜ ๋ถ„ํฌ ๋ณ€ํ™”๋กœ ์ธํ•œ ์ฐจ์ด์™€ ๊ธฐํƒ€ ๋‹ค๋ฅธ ์š”์ธ์˜ ๋ณ€ํ™”๋กœ ์ธํ•œ ์ฐจ์ด๋กœ ๊ตฌ๋ถ„ํ•œ๋‹ค(์ง‘๊ณ„๋ถ„ํ•ด). ๋˜ํ•œ ์„ค๋ช…๋ณ€์ˆ˜์˜ ๋ถ„ํฌ ๋ณ€ํ™”๋กœ ์ธํ•œ ๊ฒฐ๊ณผ๋ณ€์ˆ˜์˜ ๋ณ€ํ™”๋ฅผ ๋‹ค์‹œ ๊ฐœ๋ณ„ ์„ค๋ช…๋ณ€์ˆ˜์˜ ๋ณ€ํ™”๋กœ ์ธํ•œ ๊ธฐ์—ฌ ์ •๋„๋กœ ๊ตฌ๋ถ„ํ•˜๋Š” ์„ธ๋ถ€๋ถ„ํ•ด๋„ ๊ฐ€๋Šฅํ•˜์—ฌ, ์—ฌ๋Ÿฌ ์š”์ธ๋“ค์˜ ์ƒ๋Œ€์ ์ธ ์˜ํ–ฅ ์ •๋„๋ฅผ ๋น„๊ตํ•˜๋Š” ๋ณธ ์—ฐ๊ตฌ์— ์ ํ•ฉํ•œ ๋ฐฉ๋ฒ•์ด๋ผ ํŒ๋‹จํ•˜์˜€๋‹ค. ๋…ธ์ธ์˜ ๋…ธ๋™์ฐธ์—ฌ์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์š”์ธ์€ ๋…ธ๋™๊ฒฝ์ œํ•™์˜ ํ•ฉ๋ฆฌ์  ์„ ํƒ ์ด๋ก (rational choice theory)๊ณผ ์‚ฌํšŒํ•™์˜ ์ƒ์• ๊ณผ์ • ๊ด€์ (life-course perspective)์— ๊ธฐ์ดˆํ•˜์—ฌ ์„ ์ •ํ•˜์˜€๋‹ค. ๊ตฌ์ฒด์ ์œผ๋กœ๋Š”, ์ฃผ๋กœ ๋…ธ๋™๊ณต๊ธ‰ ์ธก๋ฉด๊ณผ ๊ด€๋ จ๋œ ์„ฑ, ์—ฐ๋ น, ๊ต์œก์ˆ˜์ค€, ๊ฑด๊ฐ•, ๋ฐฐ์šฐ์ž ์ง€์œ„์™€ ๊ฐ™์€ ๋ฏธ์‹œ์  ์š”์ธ๋“ค๊ณผ ๋…ธ์ธ์ด ๊ฑฐ์ฃผํ•˜๋Š” ์ง€์—ญ์˜ ๋…ธ๋™์‹œ์žฅ ํŠน์„ฑ๋“ค์„ ํฌํ•จํ•˜๋Š” ๊ฑฐ์‹œ์  ์š”์ธ์„ ๋น„๋กฏํ•˜์—ฌ, ๊ฐœ๋ณ„ ๋…ธ์ธ์ด ํ•ต์‹ฌ ๋…ธ๋™์—ฐ๋ น๋Œ€์— ์ฃผ๋กœ ๊ฒฝํ—˜ํ•œ ์ข…์‚ฌ์ƒ ์ง€์œ„์™€ ์ฃผ๋œ ์‚ฐ์—…, ๊ฒฝ๋ ฅ ๊ธฐ๊ฐ„๊ณผ ๊ฐ™์€ ์ƒ์• ๊ณผ์ • ์š”์ธ๋“ค๋„ ํฌํ•จํ•˜์˜€๋‹ค. ๋ฏธ์‹œ์  ์š”์ธ ์ค‘, ์ด ๋…ผ๋ฌธ์—์„œ ์ฃผ๋กœ ๊ด€์‹ฌ์„ ๊ฐ€์ง€๋Š” ๋…ธ์ธ์˜ ๊ฒฝ์ œ์  ๋ถ€์–‘๊ณผ ๊ด€๋ จ๋œ ๊ณต์ ๋ถ€์–‘ ๋ฐ ์‚ฌ์ ๋ถ€์–‘ ๊ด€๋ จ ์š”์ธ๋“ค์€ ๋ณ„๋„์˜ ๋ฒ”์ฃผ๋กœ ๊ตฌ๋ถ„ํ•˜์—ฌ ์‚ดํŽด๋ดค์œผ๋ฉฐ, ๊ฒฐ๊ณผ๋ณ€์ˆ˜์ธ ๋…ธ๋™์ฐธ์—ฌ์™€์˜ ์—ญ์ธ๊ณผ๊ด€๊ณ„(reverse causality)๋ฅผ ์ค„์ด๊ธฐ ์œ„ํ•ด์„œ, ์ธก์ • ๋ฐฉ๋ฒ•์„ ์กฐ์ •ํ•œ ๋ณ€์ˆ˜๋ฅผ ์‚ฌ์šฉํ•˜์˜€๋‹ค. ๋…ธ์ธ ๋‚ด ์กด์žฌํ•˜๋Š” ๋‹ค์–‘ํ•œ ์ด์งˆ์„ฑ์„ ๊ณ ๋ คํ•˜์—ฌ, ์‘๋‹ต์ž์˜ ์„ฑ๊ณผ ์ฃผ๋œ ์ข…์‚ฌ์ƒ ์ง€์œ„๋ฅผ ๊ธฐ์ค€์œผ๋กœ ํ•˜์œ„์ง‘๋‹จ์„ ๊ตฌ์„ฑํ•˜์˜€๊ณ , ๋ชจ๋“  ๋ถ„์„์—์„œ ํ•˜์œ„์ง‘๋‹จ๋ณ„ ๋ถ„์„๊ฒฐ๊ณผ๋ฅผ ๊ฐ™์ด ์ œ์‹œํ•˜์˜€๋‹ค. ์ฃผ์š” ๋ถ„์„๊ฒฐ๊ณผ๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ์ฒซ์งธ, 2008-2016๋…„์˜ ๋‘ ์‹œ์  ์‚ฌ์ด์— 60-84์„ธ ์—ฐ๋ น์ง‘๋‹จ์˜ ๊ณ ์šฉ๋ฅ ์€ 29.8%์—์„œ 38.7%๋กœ 8.9%p ์ƒ์Šนํ•˜์˜€์œผ๋ฉฐ, ์ง‘๊ณ„๋ถ„ํ•ด ๋ถ„์„๊ฒฐ๊ณผ, ๋ถ„์„์— ํฌํ•จ๋œ ์„ค๋ช…๋ณ€์ˆ˜์˜ ๋ถ„ํฌ ๋ณ€ํ™”๋Š” ์ „์ฒด ๋ณ€ํ™” ์ค‘ 3.6%p๋ฅผ ์„ค๋ช…ํ•˜์˜€๊ณ , ๋‚˜๋จธ์ง€ 5.3%p๋Š” ๋‘ ์‹œ์  ๊ฐ„ ์„ค๋ช…๋ณ€์ˆ˜์™€ ๊ฒฐ๊ณผ๋ณ€์ˆ˜์˜ ํšก๋‹จ์  ๊ด€๊ณ„ ๋ณ€ํ™” ๋ฐ ๋ถ„์„์— ํฌํ•จ๋˜์ง€ ์•Š์€ ์š”์ธ์˜ ๋ณ€ํ™”๋กœ ์ธํ•œ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ด๋Ÿฌํ•œ ๊ฒฐ๊ณผ๋Š” 2000๋…„๋Œ€ ์ค‘๋ฐ˜ ์ดํ›„ ๋…ธ์ธ ๊ณ ์šฉ๋ฅ ์ด ๋†’์•„์ง„ ๊ฒƒ์€ ๋…ธ์ธ์˜ ์ทจ์—…์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์ฃผ์š” ํŠน์„ฑ์˜ ๋ณ€ํ™”๋ณด๋‹ค ์‚ฌํšŒ๊ตฌ์กฐ์ ์ธ ๋ณ€ํ™”๋กœ ์ธํ•œ ์„ค๋ช…๋ณ€์ˆ˜์™€ ๊ฒฐ๊ณผ๋ณ€์ˆ˜์˜ ๊ด€๊ณ„ ๋ณ€ํ™”๊ฐ€ ๋” ํฐ ์˜ํ–ฅ์„ ๋ฏธ์ณค์Œ์„ ์˜๋ฏธํ•œ๋‹ค. ๋‘˜์งธ, ์ „์ฒด ๋ถ„์„๋Œ€์ƒ์˜ ๊ตฌ์„ฑํšจ๊ณผ์— ๋Œ€ํ•œ ์„ธ๋ถ€๋ถ„ํ•ด ๊ฒฐ๊ณผ, ๋…ธ์ธ์˜ ์ทจ์—…์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์ฃผ์š” ํŠน์„ฑ์˜ ๋ณ€ํ™”๊ฐ€ ๋…ธ์ธ ๊ณ ์šฉ๋ฅ ์˜ ๋ณ€ํ™”์— ๋ฏธ์นœ ์˜ํ–ฅ์€ ์ •(+)์ ์ธ ํšจ๊ณผ์™€ ๋ถ€(-)์ ์ธ ํšจ๊ณผ๊ฐ€ ๋ชจ๋‘ ๊ด€์ฐฐ๋˜์—ˆ๊ณ , ์„œ๋กœ์˜ ์˜ํ–ฅ์„ ์ƒ๋‹น ๋ถ€๋ถ„ ์ƒ์‡„ํ•˜์˜€๋‹ค. ์„ฑ, ๊ฒฝ๋ ฅ, ๋ฐฐ์šฐ์ž ์ง€์œ„, ๊ฑด๊ฐ•๊ณผ ๊ฐ™์€ ํŠน์„ฑ์˜ ๋ณ€ํ™”๋Š” ๋…ธ์ธ์˜ ๊ณ ์šฉ๋ฅ ์„ ๋†’์ด๋Š” ๋ฐฉํ–ฅ์œผ๋กœ ์˜ํ–ฅ์„ ๋ฏธ์นœ ๋ฐ˜๋ฉด, ๊ต์œก์ˆ˜์ค€์ด๋‚˜ ์ฃผ๋œ ์ข…์‚ฌ์ƒ ์ง€์œ„, ์ฃผ๋œ ์‚ฐ์—…๊ณผ ๊ฐ™์€ ํŠน์„ฑ์˜ ๋ณ€ํ™”๋Š” ๋…ธ์ธ์˜ ๊ณ ์šฉ๋ฅ ์„ ๊ฐ์†Œ์‹œํ‚ค๋Š” ๋ฐฉํ–ฅ์œผ๋กœ ์˜ํ–ฅ์„ ๋ฏธ์ณค๋‹ค. ์ด์ฒ˜๋Ÿผ ์„ค๋ช…๋ณ€์ˆ˜๋“ค ๊ฐ„ ์—‡๊ฐˆ๋ฆฌ๋Š” ํšจ๊ณผ๋Š” ๋ถ„ํ•ด๋ถ„์„์— ์žˆ์–ด์„œ ์„ธ๋ถ€๋ถ„ํ•ด๊ฐ€ ๊ฐ€์ง€๋Š” ์ค‘์š”์„ฑ์„ ๋ณด์—ฌ์ค€๋‹ค. ์…‹์งธ, ๋…ธ์ธ์„ ๋Œ€์ƒ์œผ๋กœ ํ•œ ๊ณต์ ๋ถ€์–‘ ์ œ๋„์˜ ํ™•๋Œ€๋Š” ์„œ๊ตฌ์˜ ์—ฐ๊ตฌ๋“ค๊ณผ๋Š” ์ƒ์ดํ•œ ๊ฒฐ๊ณผ๋ฅผ ๋ณด์˜€๋‹ค. ๊ณต์ ์—ฐ๊ธˆ ์†Œ๋“์˜ ๋ถ„ํฌ ๋ณ€ํ™”๋Š” ์˜คํžˆ๋ ค ๋…ธ์ธ์˜ ๊ณ ์šฉ๋ฅ  ์ฆ๊ฐ€์™€ ๊ด€๋ จ์ด ์žˆ์—ˆ๊ณ , ๊ธฐ์ดˆ(๋…ธ๋ น)์—ฐ๊ธˆ์˜ ์ˆ˜๊ธ‰๊ทœ๋ชจ ํ™•๋Œ€๋Š” ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•œ ์ˆ˜์ค€์˜ ์˜ํ–ฅ์„ ๋ฏธ์น˜์ง€ ์•Š์€ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๊ณต์ ์—ฐ๊ธˆ ํ™•๋Œ€์˜ ๊ฒฝ์šฐ, ๋น„์ˆ˜๊ธ‰์ง‘๋‹จ๋ณด๋‹ค ์ทจ์—…ํ™•๋ฅ ์ด ๋†’์€ ์ €์—ฐ๊ธˆ ์ˆ˜๊ธ‰์ง‘๋‹จ์˜ ๋น„์ค‘์ด ์ฆ๊ฐ€ํ•˜์—ฌ ๋…ธ์ธ ๊ณ ์šฉ๋ฅ ์„ ๋†’์ด๋Š” ๋ฐฉํ–ฅ์œผ๋กœ ์ž‘์šฉํ•˜์˜€๋‹ค. ๊ธฐ์ดˆ์—ฐ๊ธˆ์€ ๊ธฐ์ค€์‹œ์ ์ธ 2016๋…„์˜ ๊ฒฝ์šฐ ์ˆ˜๊ธ‰์ง‘๋‹จ๊ณผ ๋น„์ˆ˜๊ธ‰์ง‘๋‹จ์˜ ์กฐ๊ฑด๋ถ€ ๊ณ ์šฉ๋ฅ  ์ฐจ์ด๊ฐ€ ํฌ๊ฒŒ ๊ฐ์†Œํ•˜์—ฌ, ๊ธ‰์—ฌ์ˆ˜์ค€ ๋ฐ ์ˆ˜๊ธ‰์ง‘๋‹จ์˜ ๊ทœ๋ชจ ํ™•๋Œ€๊ฐ€ ๋…ธ์ธ์˜ ๊ณ ์šฉ๋ฅ  ๋ณ€ํ™”์— ์œ ์˜ํ•œ ์ˆ˜์ค€์˜ ์˜ํ–ฅ์„ ๋ฏธ์น˜์ง€ ๋ชปํ•˜์˜€๋‹ค. ๋„ท์งธ, ๋…ธ์ธ์ด ์ž๋…€์—๊ฒŒ์„œ ๋ฐ›๋Š” ์‚ฌ์ ๋ถ€์–‘์—์„œ๋Š” ๋™๊ฑฐ์™€ ์‚ฌ์ ์ด์ „์˜ ์˜ํ–ฅ์ด ์ฐจ์ด๋ฅผ ๋ณด์˜€๋‹ค. 2008-2016๋…„ ์‚ฌ์ด ๊ธฐํ˜ผ์ž๋…€์™€ ๋™๊ฑฐํ•˜๋Š” ๋…ธ์ธ์˜ ๋น„์ค‘์ด ๊ฐ์†Œํ•˜์˜€๊ณ , ๋น„๋™๊ฑฐ ์ž๋…€๋กœ๋ถ€ํ„ฐ ์‚ฌ์ ์ด์ „์„ ๋ฐ›๋Š” ๋น„์ค‘๊ณผ ์‚ฌ์ ์ด์ „ ์†Œ๋“์˜ ๊ทœ๋ชจ๋„ ๊ฐ์†Œํ•˜์˜€๋‹ค. ๋‘ ์š”์ธ์—์„œ ๋ชจ๋‘ ์‚ฌ์ ๋ถ€์–‘์˜ ๊ฐ์†Œ ์ถ”์ด๊ฐ€ ํ™•์ธ๋˜์—ˆ์ง€๋งŒ, ๋™๊ฑฐ์˜ ๊ฐ์†Œ๋Š” ์ „์ฒด ๋…ธ์ธ์˜ ๊ณ ์šฉ๋ฅ ์— ์œ ์˜ํ•œ ์˜ํ–ฅ์„ ๋ฏธ์น˜์ง€ ๋ชปํ•œ ๋ฐ˜๋ฉด, ์‚ฌ์ ์ด์ „์˜ ๊ฐ์†Œ๋Š” ๋…ธ์ธ์˜ ๊ณ ์šฉ๋ฅ ์„ ๋†’์ด๋Š” ๋ฐฉํ–ฅ์œผ๋กœ ์˜ํ–ฅ์„ ๋ฏธ์ณค๋‹ค. ๋˜ํ•œ ์‚ฌ์ ์ด์ „์˜ ๊ฐ์†Œ๋Š” ๋ถ„์„์— ํฌํ•จ๋œ ์˜ํ–ฅ์š”์ธ๋“ค ์ค‘์—์„œ ๊ณ ์šฉ๋ฅ  ๋ณ€ํ™”์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์˜ ์ •๋„๊ฐ€ ๊ฐ€์žฅ ํฐ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋Š”๋ฐ, ์ด๋Š” 2000๋…„๋Œ€ ์ค‘๋ฐ˜ ์ดํ›„ ๋…ธ์ธ ๊ณ ์šฉ๋ฅ  ์ฆ๊ฐ€์˜ ์ƒ๋‹น ๋ถ€๋ถ„์ด ๊ฒฝ์ œ์ ์ธ ๋ชฉ์ ์œผ๋กœ ๋…ธ๋™์‹œ์žฅ์— ์ฐธ์—ฌํ•˜๋Š” ์ƒ๊ณ„ํ˜• ๋…ธ๋™์˜ ์ฆ๊ฐ€์— ๊ธฐ์ธํ•œ ๊ฒƒ์ž„์„ ๋ณด์—ฌ์ค€๋‹ค. ๋‹ค์„ฏ์งธ, ํ•˜์œ„์ง‘๋‹จ๋ณ„ ์„ธ๋ถ€๋ถ„ํ•ด ๊ฒฐ๊ณผ๋Š” ์ง‘๊ณ„๋ถ„ํ•ด๋ณด๋‹ค ๋” ํฐ ์ฐจ์ด๋ฅผ ๋ณด์˜€๋‹ค. ์„ฑ๋ณ„ ํ•˜์œ„์ง‘๋‹จ์˜ ์„ธ๋ถ€๋ถ„ํ•ด ๊ฒฐ๊ณผ๋ฅผ ๋ณด๋ฉด, ๊ฐ ์ง‘๋‹จ์˜ ๊ณ ์šฉ๋ฅ  ๋ณ€ํ™”์— ์˜ํ–ฅ์„ ๋ฏธ์นœ ์„ค๋ช…๋ณ€์ˆ˜์˜ ๋ณ€ํ™”๊ฐ€ ํ™•์—ฐํ•˜๊ฒŒ ๊ตฌ๋ถ„๋˜์—ˆ๋‹ค. ๋‚จ์„ฑ ๋…ธ์ธ์˜ ๊ณ ์šฉ๋ฅ  ๋ณ€ํ™”์—๋Š” ์ฃผ๋œ ์ข…์‚ฌ์ƒ ์ง€์œ„, ๋ฐฐ์šฐ์ž ์ง€์œ„, ๊ธฐํƒ€ ์‚ฌํšŒ๋ณด์žฅ๊ธ‰์—ฌ์˜ ์ˆ˜๊ธ‰ ๋ณ€ํ™”๊ฐ€ ์˜ํ–ฅ์„ ๋ฏธ์นœ ๋ฐ˜๋ฉด, ์—ฌ์„ฑ ๋…ธ์ธ์˜ ๊ณ ์šฉ๋ฅ  ๋ณ€ํ™”์—๋Š” ๊ต์œก์ˆ˜์ค€, ์ฃผ๋œ ์‚ฐ์—…, ๊ฒฝ๋ ฅ, ๊ฑฐ์ฃผ์ง€์—ญ, ๊ฑด๊ฐ• ์ˆ˜์ค€์˜ ๋ณ€ํ™”๊ฐ€ ์˜ํ–ฅ์„ ๋ฏธ์นœ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ํ•œํŽธ, ์ฃผ๋œ ์ข…์‚ฌ์ƒ ์ง€์œ„๋ณ„๋กœ ๊ตฌ๋ถ„ํ•œ ํ•˜์œ„์ง‘๋‹จ์—์„œ๋„ ์„ธ ์ง‘๋‹จ ๊ฐ„ ์™„์ „ํžˆ ๋‹ค๋ฅธ ์–‘์ƒ์ด ๋ฐœ๊ฒฌ๋˜์—ˆ๋‹ค. ์ž„๊ธˆ๋…ธ๋™ ์ง‘๋‹จ์€ ๊ณต์ ์—ฐ๊ธˆ์ด๋‚˜ ๋™๊ฑฐ, ์‚ฌ์ ์ด์ „๊ณผ ๊ฐ™์€ ๊ฒฝ์ œ์  ๋ถ€์–‘ ๊ด€๋ จ ์š”์ธ์˜ ๋ณ€ํ™”๊ฐ€ ๊ณ ์šฉ๋ฅ  ๋ณ€ํ™”์— ์ฃผ๋กœ ์˜ํ–ฅ์„ ๋ฏธ์นœ ๋ฐ˜๋ฉด, ์ž์˜์—… ์ง‘๋‹จ์—์„œ๋Š” ์ƒ์•  ์ดˆ๊ธฐ์™€ ํ›„๊ธฐ์˜ ๋ฏธ์‹œ์  ์š”์ธ๋“ค๊ณผ ๊ธฐํƒ€ ์‚ฌํšŒ๋ณด์žฅ๊ธ‰์—ฌ์˜ ๋ณ€ํ™”๋งŒ์ด ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•œ ๊ด€๊ณ„๋ฅผ ๋ณด์˜€๊ณ , ๊ธฐํƒ€ ๋…ธ๋™์ง€์œ„ ์ง‘๋‹จ์—์„œ๋Š” ์ƒ์•  ์ดˆ๊ธฐ์™€ ์ค‘๊ธฐ์˜ ๋ฏธ์‹œ์  ์š”์ธ ๋ณ€ํ™”๊ฐ€ ๊ณ ์šฉ๋ฅ  ๋ณ€ํ™”์— ์œ ์˜ํ•œ ์ˆ˜์ค€์˜ ์˜ํ–ฅ์„ ๋ฏธ์ณค๋‹ค. ์ด๋Ÿฌํ•œ ๊ฒฐ๊ณผ๋Š” ํ•˜์œ„์ง‘๋‹จ๋ณ„๋กœ ๋…ธ๋™๊ณต๊ธ‰์ด ๋‹ค๋ฅธ ์ง‘๋‹จ๊ณผ ๊ตฌ๋ณ„๋˜๋Š” ๊ณ ์œ ์˜ ๋ฐฉ์‹์œผ๋กœ ์ด๋ค„์ง€๊ณ  ์žˆ์„ ๊ฐ€๋Šฅ์„ฑ์„ ์‹œ์‚ฌํ•œ๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” ์ด๋ก ์  ์ธก๋ฉด์—์„œ, ์„œ๊ตฌ์˜ ๊ฒฝํ—˜์— ๊ธฐ์ดˆํ•˜์—ฌ ํ˜•์„ฑ๋œ ๋…ธ์ธ ๋…ธ๋™์˜ ๋ณ€ํ™”์— ๋Œ€ํ•œ ์ด๋ก ์„ ํ•œ๊ตญ ์‚ฌํšŒ์— ๋น„ํŒ์ ์œผ๋กœ ์ ์šฉํ•ด ๋ณธ๋‹ค๋Š” ์˜๋ฏธ๋ฅผ ์ง€๋‹Œ๋‹ค. ์„œ๊ตฌ์—์„œ ๋…ธ์ธ์˜ ๋…ธ๋™์ฐธ์—ฌ๊ฐ€ ๊ฐ์†Œํ•˜๋˜ ์‹œ๊ธฐ์™€ ๋น„์Šทํ•œ ๋ฐฉํ–ฅ์œผ๋กœ์˜ ์‚ฌํšŒ์  ๋ณ€ํ™”์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ , ํ•œ๊ตญ์—์„œ ๋…ธ์ธ์˜ ๋…ธ๋™์ฐธ์—ฌ๊ฐ€ ์ฆ๊ฐ€ํ•œ ์›์ธ์œผ๋กœ๋Š” ๊ณต์ ๋ถ€์–‘์˜ ํ™•๋Œ€๊ฐ€ ๋…ธ์ธ์˜ ๊ณ ์šฉ๋ฅ ์„ ๊ฐ์†Œ์‹œํ‚ค์ง€ ์•Š์€ ์ƒํ™ฉ์—์„œ ์‚ฌ์ ๋ถ€์–‘์˜ ๊ฐ์†Œ๊ฐ€ ๋…ธ์ธ์˜ ๊ณ ์šฉ๋ฅ ์„ ๋†’์ด๋Š” ํšจ๊ณผ๋ฅผ ๋ณด์˜€๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. ๋˜ํ•œ, ๊ต์œก์ˆ˜์ค€๊ณผ ์—ฐ๋ น์˜ ๋ณ€ํ™”๊ฐ€ ๋ฏธ์นœ ์˜ํ–ฅ๋„ ์„œ๊ตฌ์™€๋Š” ์ฐจ์ด๋ฅผ ๋ณด์˜€๋‹ค. ์ •์ฑ…์  ์ธก๋ฉด์—์„œ ๋ณธ ์—ฐ๊ตฌ์˜ ๋ถ„์„๊ฒฐ๊ณผ๋Š” 2000๋…„๋Œ€ ์ค‘๋ฐ˜ ์ดํ›„ ๋…ธ์ธ ๊ณ ์šฉ๋ฅ  ์ฆ๊ฐ€์˜ ์ƒ๋‹น ๋ถ€๋ถ„์ด ๊ฒฝ์ œ์ ์ธ ํ•„์š”๋กœ ์ธํ•ด ๋…ธ๋™์‹œ์žฅ์— ์ฐธ์—ฌํ•˜๋Š” ๋…ธ์ธ์˜ ์ฆ๊ฐ€์— ๊ธฐ์ธํ•  ๊ฐ€๋Šฅ์„ฑ์„ ์‹œ์‚ฌํ•œ๋‹ค. ์‚ฌ์ ๋ถ€์–‘์˜ ๊ฐ์†Œ ์ถ”์ด๊ฐ€ ๋‹น๋ถ„๊ฐ„ ์ง€์†๋  ๊ฒƒ์œผ๋กœ ์˜ˆ์ƒ๋˜๋Š” ์ƒํ™ฉ์—์„œ, ์ด๋Ÿฌํ•œ ์ถ”์ด๋ฅผ ๋ฐ˜๋“ฑ์‹œํ‚ค๊ธฐ ์œ„ํ•ด์„œ๋Š” ์‚ฌ์ ๋ถ€์–‘๊ณผ ๋…ธ์ธ ๋…ธ๋™์ฐธ์—ฌ์˜ ํšก๋‹จ์  ๊ด€๊ณ„๋ฅผ ๋ณ€ํ™”์‹œํ‚ค๊ธฐ ์œ„ํ•œ ๋…ธ๋ ฅ์ด ํ•„์š”ํ•˜๋‹ค. ์ด๋ฅผ ์œ„ํ•ด์„œ๋Š” ๊ณต์ ์—ฐ๊ธˆ์„ ์ค‘์‹ฌ์œผ๋กœ ํ•œ ๊ณต์ ๋ถ€์–‘์„ ์ง€์†์ ์œผ๋กœ ํ™•๋Œ€ํ•˜๊ณ , ๊ฐœ์ธ์—ฐ๊ธˆ์ด๋‚˜ ์ž์‚ฐ ์ถ•์ ์„ ํ†ตํ•ด ๋‹ค์ธต์ ์ธ ๋…ธํ›„ ์ค€๋น„๋ฅผ ์œ ๋„ํ•˜๋ฉฐ, ๊ธฐ์ดˆ์—ฐ๊ธˆ์„ ํ†ตํ•ด์„œ ์ตœ์†Œํ•œ์˜ ์ƒํ™œ์ˆ˜์ค€์„ ๋ณด์žฅํ•˜๋Š” ๋“ฑ์˜ ๋ฐฉ๋ฒ•์„ ํ†ตํ•ด์„œ, ์ž๋…€์˜ ์‚ฌ์ ๋ถ€์–‘์— ์˜์กดํ•˜์—ฌ ์ƒ๊ณ„๋ฅผ ์œ ์ง€ํ•˜๋Š” ๋…ธ์ธ์˜ ๋น„์ค‘์„ ์ค„์—ฌ๋‚˜๊ฐ€๊ธฐ ์œ„ํ•œ ์ •์ฑ…์  ๋…ธ๋ ฅ์ด ์š”๊ตฌ๋œ๋‹ค. ๋˜ํ•œ, ์žฅ๊ธฐ์ ์ธ ๊ด€์ ์—์„œ๋Š” ๋…ธ๋™์‹œ์žฅ ๋‚ด์— ์—ฐ๋ น์œผ๋กœ ์ธํ•œ ์ฐจ๋ณ„์„ ํ•ด์†Œํ•˜๊ณ , ๋…ธ์ธ ์นœํ™”์ ์ธ ๊ณ ์šฉํ™˜๊ฒฝ์„ ์กฐ์„ฑํ•˜๋ฉฐ, ๋…ธ์ธ์ด ์ทจ์—…ํ•  ์ˆ˜ ์žˆ๋Š” ์ง์ข…์„ ๋‹ค์–‘ํ•œ ๋ฒ”์œ„๋กœ ํ™•๋Œ€ํ•˜๋Š” ๋“ฑ์˜ ๋…ธ๋ ฅ์ด ํ•„์š”ํ•˜๋‹ค.This study aims to investigate why the old people in Korea have participated in the labor market after the expansion of social security institutions for the aged since 2000. In Western countries, the change of the employment rate has connected to the social security system. Specifically, a decrease of agriculture and an expansion of the social security system for the old had led the declining of the employment rates of older people from the 20th century until the mid-1980s. As public pensions shrunk due to the welfare state reorganization after the 1990s, the old people's employment rate started to increase. However, in South Korea, many old people still participated in the labor market, even though Korea also implemented old-age pension system and had expanded the coverage of social security as well as also experienced industrial structure change from primary industry to secondary and tertiary industry. The employment rate of the old Koreans is more than twice the OECD average. Why do many old people in Korea have paid job? This study analyzed which factors, selected based on the rational choice theory of labor economics and the life-course perspective of sociology, have significant impacts on the employment of the old people. For analyzing the trend and determinants of the change of the employment of the old people aged 60 to 84 who covered by the National Pension Scheme (NPS), this study used Korean Longitudinal Study of Ageing (KLoSA). With considering various heterogeneities in older people, this study divided into subgroups based on their gender and main job career. Besides, this study adopted the reweighting decomposition method based on the non-parametric process which has widely used to decompose the difference between groups in labor economics. The main results are as follows. First, between 2008-2016, the employment rate of the increased by 8.9%p from 29.8% to 38.7%. The change of covariates distribution, which included in the analysis model, explained 3.6%p of the total change. That is, the increase in the employment rate of older adults since the mid-2000s is due to the social structural change rather than the change of the major influencing factors. Second, in the detailed decomposition results, both positive and negative effects on the change of the old employment rate were observed, and these factors largely offset each other's influence. For instances, Sex, and the change of career, spouse status, and health status have positive impacts on the employment rate of the old. On the other hand, the level of education, and the change in job position and industry reduced the employment rate of the old. The opposite effects among influencing factors show the importance of detailed decomposition analysis. Third, the extension of the public support for the aged showed different outcomes according to the scheme. The expansion of the earned-related pension encouraged the employment rate of the old by increasing the proportion of low-pension entrants with a higher probability of employment than non-pensioners while the expansion of the coverage of the Basic Pension Scheme (BPS) had no significant effect on the employment. Because the difference in the conditional employment rates between the beneficiary and non-beneficiary groups drastically decreased in 2016. Fourth, during the analysis period, the decline in private transfers is noticeable. This reduction in private transfers has a stronger positive impact on employment for the old than any other factor. Since the mid-2000s, many old people have participated in the labor market for economic reasons. Fifth, the effects of individual factors on the employment of the old differ according to gender and job status. For examples, changes in other social security benefit levels that affect the employment of the old male people have no significant impact on the female. Change in public pension affects employment of wage workers, but they are ineffective for self-employed. This result suggests that the labor supply in each subgroup may have a unique way of distinguishing it from other groups. This study showed the unique feature of the employment of old Korean people. The employment of old Korean people mainly depends on the decrease in private transfer not the increase of public support. Further, the old people work to earn a living since the mid-2000s. The problems are, most of them have faced job insecurity, low wages as well as poverty. For promoting the economic stability of the old, it is necessary to expand the public support for the aged and to guarantee the minimum standard of living through the basic pension. Besides, it is also useful to prepare for retirement through personal pension and asset accumulation. Moreover, it is essential to create an elderly-friendly working environment, such as eliminating age discrimination and expanding the elderly-friendly occupations.์ œ1์žฅ. ์„œ๋ก  1 ์ œ2์žฅ. ๋ฌธํ—Œ ๊ฒ€ํ†  7 ์ œ1์ ˆ. ์ด๋ก ์  ๋…ผ์˜ ๋ฐ ์„ ํ–‰์—ฐ๊ตฌ ๊ฒ€ํ†  7 1. ๋…ธ์ธ ๋…ธ๋™์ฐธ์—ฌ์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์š”์ธ 7 2. ๋…ธ์ธ ๋…ธ๋™์ฐธ์—ฌ์˜ ๋ณ€ํ™”๋ฅผ ๋ถ„์„ํ•œ ์„ ํ–‰์—ฐ๊ตฌ ๊ฒ€ํ†  17 ์ œ2์ ˆ. ๋…ธ์ธ ๋…ธ๋™์ฐธ์—ฌ ๋ฐ ์˜ํ–ฅ์š”์ธ์˜ ๋ณ€ํ™” ์ถ”์ด ๊ฒ€ํ†  22 1. ๊ณ ์šฉ๋ฅ  ๋ณ€ํ™” ์ถ”์ด 22 2. ์˜ํ–ฅ์š”์ธ๋ณ„ ๋ณ€ํ™” ์ถ”์ด 25 ์ œ3์ ˆ. ์—ฐ๊ตฌ๋ฌธ์ œ 42 ์ œ3์žฅ. ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• 44 ์ œ1์ ˆ. ๋ถ„์„ ์ž๋ฃŒ 44 ์ œ2์ ˆ. ๋ณ€์ˆ˜์˜ ์ธก์ • 51 1. ๊ฒฐ๊ณผ๋ณ€์ˆ˜ 51 2. ์„ค๋ช…๋ณ€์ˆ˜ 52 ์ œ3์ ˆ. ๋ถ„์„๋ฐฉ๋ฒ• 60 1. ๋ถ„ํ•ด๋ฐฉ๋ฒ• ๊ด€๋ จ ์„ ํ–‰์—ฐ๊ตฌ ๊ฒ€ํ†  60 2. ์žฌ๊ฐ€์ค‘ ๋ถ„ํ•ด๋ฐฉ๋ฒ• 62 3. ์„ ํ–‰ ๋ถ„์„ ๋ฐ ํ•˜์œ„์ง‘๋‹จ์˜ ๊ตฌ๋ถ„ 65 4. ๊ฒฝ์ œ์  ๋ถ€์–‘ ์š”์ธ์˜ ์—ญ์ธ๊ณผ๊ด€๊ณ„ 66 ์ œ4์ ˆ. ์—ฐ๊ตฌ๋ชจํ˜• 74 ์ œ4์žฅ. ๋ถ„์„ ๊ฒฐ๊ณผ 77 ์ œ1์ ˆ. ๊ณ ์šฉ๋ฅ ๊ณผ ํŠน์„ฑ์˜ ๋ณ€ํ™” 77 1. ๊ณ ์šฉ๋ฅ  ๋ณ€ํ™” ์ถ”์ด 77 2. ์˜ํ–ฅ์š”์ธ๋ณ„ ๋ณ€ํ™” ์ถ”์ด 80 ์ œ2์ ˆ. ์„ค๋ช…๋ณ€์ˆ˜์™€ ๊ฒฐ๊ณผ๋ณ€์ˆ˜์˜ ํšก๋‹จ์  ๊ด€๊ณ„ ๋ถ„์„ 98 1. ์ „์ฒด ๋ถ„์„๋Œ€์ƒ์—์„œ์˜ ํšก๋‹จ์  ๊ด€๊ณ„ 99 2. ํ•˜์œ„์ง‘๋‹จ๋ณ„ ํšก๋‹จ์  ๊ด€๊ณ„ 108 ์ œ3์ ˆ. ์žฌ๊ฐ€์ค‘ ๋ถ„ํ•ด ๋ถ„์„๊ฒฐ๊ณผ 115 1. ์žฌ๊ฐ€์ค‘ ํ‘œ๋ณธ์˜ ํŠน์„ฑ 117 2. ์„ค๋ช…๋ณ€์ˆ˜ ๋ณ€ํ™”์™€ ๋…ธ์ธ ๊ณ ์šฉ๋ฅ  ๋ณ€ํ™”์˜ ๊ด€๊ณ„ ๋ถ„ํ•ด 120 3. ์ถ”๊ฐ€๋ถ„์„ 147 ์ œ5์žฅ. ๊ฒฐ๋ก  154 ์ œ1์ ˆ. ๋ถ„์„๊ฒฐ๊ณผ ์š”์•ฝ 154 ์ œ2์ ˆ. ์ด๋ก ์  ํ•จ์˜ 158 ์ œ3์ ˆ. ์ •์ฑ…์  ํ•จ์˜ 161 ์ œ4์ ˆ. ์—ฐ๊ตฌ์˜ ํ•œ๊ณ„ 165 ์ฐธ๊ณ  ๋ฌธํ—Œ 167 ๋ถ€ํ‘œ 182 Abstract 191Docto

    ์•ฝ๋ฌผ ์กฐ์ ˆ์ „๋‹ฌ์„ ์œ„ํ•œ ํ˜์‹ ์  ์ด์‹ํ˜• ์•ฝ๋ฌผ์ฃผ์ž…์žฅ์น˜

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› ๊ณต๊ณผ๋Œ€ํ•™ ํ˜‘๋™๊ณผ์ • ๋ฐ”์ด์˜ค์—”์ง€๋‹ˆ์–ด๋ง์ „๊ณต, 2017. 8. ์ตœ์˜๋นˆ.This dissertation focuses on the design, development and evaluation of implantable drug delivery devices that can replace frequent injections and oral administrations with single implantation and maximize the therapeutic effect of chronic diseases. Currently, implantable drug delivery devices have been widely developed and used in clinical practice, but there are still a number of limitations. Therefore, I propose new innovative implantable drug delivery devices based on a new operating principle. First, I developed a microchannel-based implantable microchip that can be pre-programmed prior to implantation and released in a self-controlled manner after implantation. The key of this study is that the device can control the desired amount of drug release by adjusting channel dimensions (i.e., cross-sectional area (A) and length (L)) based on the Diffusion flux and Fick's first law of diffusion equation. The microchip was made of poly(methyl methacrylate), where a pair of micro-channels and micro-wells was embedded to serve as a drug diffusion barrier and a reservoir, respectively. Micro-channel can be precisely fabricated by controlling the CO2 laser output, processing speed, and irradiation height. To achieve both almost immediate onset and continuous release of DS, a single microchip equipped with the micro-channels with A/Ls of 0.0280 mm, 0.0217 mm and 0.0108 mm was prepared and exhibited continuous drug release for 70 days (almost zero-order pattern for 31 days, R2 > 0.996). When the resulting microchip was implanted in living rats, the drug concentration in the blood could be maintained at 148 ng/mlโ€“225 ng/ml for the first 30 days while showing good biocompatibility. In addition, I also designed an implantable battery-less device enabled with patient-driven, on-demand insulin release to be actuated by an externally applied magnetic field. The key of this study is that the device can be operated without battery. So just apply a magnetic field on the skin instead of an injection needle, the exact amount of drug can be delivered. Unlike other active implantable drug delivery devices where an internal battery is required, MDP does not require a battery. Therefore, it is small in size and does not require re-surgery, so it can be used semi-permanently. To demonstrate in vivo feasibility, it was proved that the insulin concentration and decreased glucose level in the STZ-induced diabetes rat model were maintained at 741.8 ยฑ 4.13 ยตUml-1 and 300.3 ยฑ 10.8 mg dl-1, respectively in the MDP group similar to the values of 683.3ยฑ16.9 ยตUml-1 and 251.1 ยฑ 6.41mg dl-1 in the S.C injection group for 60 days. Through these studies, I envision that microchannel-based implantable microchip and implantable battery-less device can offer a patient-oriented new concept biomedical technology.Abstract โ…ฐ Contents iโ…ด List of Tables viii List of Figures ix Chapter 1. Introduction 1 1.1 Chronic Diseases and its Current Therapy 1 1.2 Implantable Drug Delivery Device 3 1.3 Passive Drug Delivery Device 5 1.3.1 Matrix Controlled System 5 1.3.2 Microscale Constrained System 6 1.3.3 Nanoscale Constrained System 6 1.3.4 Osmotic Based System 7 1.4 Active Drug Delivery Device 7 1.4.1 Peristaltic Actuated System 8 1.4.2 Electrochemical Dissolution System 9 1.4.3 Electrothermal Ablation System 9 1.4.4 Piezoelectric Actuated System 10 1.4.5 Electrolysis Based System 10 1.5 Current Drawback and Research Aims 11 Chapter 2. Multi-channel Based Implantable Micro-chip for Controlled Drug Delivery 13 2.1 Introduction 13 2.2 Materials and Methods 17 2.2.1 Materials 17 2.2.2 Fabrication of DMCs 17 2.2.3 Characterization of Micro-channels and Micro-wells 21 2.2.4 In Vitro Drug Release Study 21 2.2.5 Selection of Micro-channel Combination for Zero-order release 22 2.2.6 Implantation of I_DMC 27 2.2.7 In Vivo Pharmacokinetic Study 29 2.2.8 Histophathologic Evaluation 30 2.3 Results 31 2.3.1 Characterization of DMC 31 2.3.2 In Vitro Drug Release Profiles of DMC 35 2.3.3 I_DMC for Zero-order Drug Release 40 2.3.4 In Vivo Pharmacokinetics Study from the I_DMC 45 2.3.5 Histophathology 47 2.4 Discussion 49 2.5 Conclusion 54 Chapter 3. Implantable Battery-less Device for On-demand, Controlled Delivery of Insulin 54 3.1 Introduction 54 3.2 Materials and Methods 56 3.2.1 MDP Fabrication 56 3.2.2 Measurement of Insulin Concentration 57 3.2.3 In Vivo Experiments 57 3.2.4 Histopathology 69 3.2.5 Statistical Analysis 69 3.3 Results 70 3.3.1 MDP Design and Working Principles 70 3.3.2 In Vitro Performance Test 77 3.3.3 In Vivo Evaluation 87 3.3.4 Histophathology 100 3.4 Discussion 106 3.5 Conclusion 117 Chapter 4. Conclusion and Perspective 118 References 122 Abstract in Korean 128 Appendix 130Docto

    ๋น„์†Œ ์ œ๊ฑฐ ๋ฐ ํ”ผ์…”-ํŠธ๋กญ์‰ฌ ๋ฐ˜์‘์—์„œ ๋‚˜๋…ธ์ž…์ž์˜ ํฌ๊ธฐ ํšจ๊ณผ

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    Metal oxide nanoparticles have become an area of growing interest and importance in a wide range of fundamental studies and technological applications, due to their unique optical, electronic, magnetic, chemical, and mechanical properties. Furthermore, metal oxides nanoparticles are increasingly being associated with important environmental processes occurring in water and catalysts in synthetic fuel processes. In this thesis, we demonstrate Iron and cobalt oxide nanoparticle for environmental and catalytic application. In Chapter 1, we briefly summarized magnetic iron oxide nanoparticle, nano for oil and gas, and Design, synthesis, and use of cobalt-based Fischer-Tropsch synthesis catalysts. In Chapter 2, Magnetic multi-granule nanoclusters (MGNCs) were investigated as an inexpensive means to effectively remove arsenic from aqueous environment, particularly groundwater sources consumed by humans. Various size MGNCs were examined to determine both their capacity and efficiency for arsenic adsorption for different initial arsenic concentrations. The MGNCs showed highly efficient arsenic adsorption characteristics, thereby meeting the allowable safety limit of 10 g/L (ppb), prescribed by the World Health Organization (WHO), and confirming that 0.4 g/L and 0.6 g/L of MGNCs were sufficient to remove 0.5 mg/L and 1.0 mg/L of arsenate (AsO43โˆ’) from water, respectively. Adsorption isotherm models for the MGNCs were used to estimate the adsorption parameters. They showed similar parameters for both the Langmuir and Sips models, confirming that the adsorption process in this work was active at a region of low arsenic concentration. The actual efficiency of arsenate removal was then tested against 1 L of artificial arsenic-contaminated groundwater with an arsenic concentration of 0.6 mg/L in the presence of competing ions. In this case, only 1.0 g of 100 nm MGNCs was sufficient to reduce the arsenic concentrations to below the WHO permissible safety limit for drinking water, without adjusting the pH or temperature, which is highly advantageous for practical field applications. In Chapter 3, Fischer-Tropsch synthesis (FTS) reaction is a reaction used for producing hydrocarbon compounds from a gas mixture (syngas) containing carbon monoxide and hydrogen generated by reforming natural gas, gasification of coal, or biomass. This study provides a novel cobalt-based catalyst having an improved catalytic activity and stability, concurrently with an enhanced selectivity for liquid and high melting point hydrocarbons, at the expense of a low methane selectivity over conventional cobalt-based Fisher-Tropsch catalysts. We report on the conversion of synthesis gas to C5+ with enhanced FTS activity by a factor of 5, applying catalysts that constitute cobalt nanoparticles (using a polyether and promoters) homogeneously dispersed on silica supports.Chapter 1. Research Background 1 1.1 Magnetic Iron Oxide Nanoparticles for Arsenic Removal 2 1.2 Nano Technology for Oil and Gas 5 1.3 Cobalt-based Fischer-Tropsch synthesis catalysts 16 1.4 Scope of Dissertion 22 1.5 References 24 Chapter 2. Efficient Removal of Arsenic Using Magnetic Multi-Granule Nanoclusters 28 2.1 Introduction 29 2.2 Experimental Section 33 2.3 Results and Discussion 35 2.4 Conclusions 53 2.5 References 54 Chapter 3. Influence of Cobalt Nanoparticle Dispersion for Fischer-Tropsch Synthesis Activity 57 3.1 Introduction 58 3.2 Experimental Section 72 3.3 Results and Discussion 75 3.4 Conclusions 85 3.5 References 86 Korean Abstract 89Docto

    A TrueNorth Based Accelerator Architecture for Rate Coded Spiking Neural Network

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    Spiking Neural Network is an Artificial Neural Network that emulates the biological behavior of the human brain. SNN consists of spiking neurons, which is the computational model of a biological neuron, communicating through spike signals. In the area of artificial intelligence, SNNs are expected to show high energy efficiency similar to human brain level, since they mimic the brain realistically. However, SNN faces a low accuracy problem due to the spike signalโ€™s lack of representation variety and the under-discovered principle of the human brain. ANN-converted-SNN is a neural network converted from a trained ANN using a backpropagation algorithm. It converts a network by applying trained parameters to the weight and parameters of spiking neurons. ANN-converted-SNN can achieve high accuracy similar to that of ANN, since it exploits ANNโ€™s trained parameters. Researchers are trying to convert more various types of ANN components into SNN counterparts. Neuromorphic hardware is an electrical device that emulates the structure and function of a biological neural network using an analog circuit or VLSI. Since it implements the working mechanism of the human brain on hardware, it has been used for accelerating brain simulation or spiking neural networks. IBMโ€™s TrueNorth is one of the representative neuromorphic chips. It successfully implements a densely connected neural network with 1 million neurons and 256 million synapses in a single chip. However, TrueNorth lacks target workloads. As part of that, TrueNorth has an inefficient structure for accelerating ANN-converted-SNNs. This paper proposes a novel architecture, RSTN (Rate-coded Spiking neural network TrueNorth), which enables accelerating the ANN-converted-SNNs by modifying TrueNorth architecture. We define the necessary hardware design points that need to be considered when running SNNs on hardware. We design the RSTN after setting the specific running environment through our defined design points. We propose baseline accelerator architecture(RSTN-baseline) for ANN-converted-SNN, by modifying TrueNorth. Then, we optimize the input spike receiving process to reduce the on-chip memory capacity of RSTN-baseline, and named it as RSTN-IS. Next, we propose an additionally optimized architecture, RSTN-ISWS, which saves energy and latency from RSTN-IS by skipping the computation of zero-valued weights. We measure the hardware metric of accelerators by implementing a time-accurate simulator for each RSTN. The evaluation shows that RSTN-IS reduces 92% of RSTN-baselineโ€™s on-chip memory capacity by replacing synaptic connectivity memory with scheduler memory. Moreover, RSTN-ISWS saves 34% energy and 10% latency from RSTN-IS by utilizing the sparsity of zero-valued weights.์ŠคํŒŒ์ดํ‚น ์‹ ๊ฒฝ๋ง(Spiking Neural Network, SNN)์€ ์ŠคํŒŒ์ดํ‚น ๋‰ด๋Ÿฐ(Spking Neuron)์„ ์‚ฌ์šฉํ•˜์—ฌ ๋‡Œ์˜ ์ƒ๋ฌผํ•™์  ๋™์ž‘ ๋ฐฉ์‹์„ ์‚ฌ์‹ค์ ์œผ๋กœ ๋ชจ๋ฐฉํ•œ ์ธ๊ณต ์‹ ๊ฒฝ๋ง(Artificial Neural Network, ANN)์˜ ํ•œ ์ข…๋ฅ˜์ด๋‹ค. ์ŠคํŒŒ์ดํ‚น ๋‰ด๋Ÿฐ์€ ์ƒ๋ฌผํ•™์  ๋‰ด๋Ÿฐ์„ ๋ชจ๋ธ๋งํ•œ ๊ฒƒ์œผ๋กœ ์ŠคํŒŒ์ดํฌ๋ฅผ ์ด์šฉํ•ด ์ƒํ˜ธ์ž‘์šฉํ•œ๋‹ค. ์ธ๊ณต ์ง€๋Šฅ ๋ถ„์•ผ์—์„œ ์ŠคํŒŒ์ดํ‚น ์‹ ๊ฒฝ๋ง์€ ๋‡Œ๋ฅผ ์‚ฌ์‹ค์ ์œผ๋กœ ๋ชจ๋ฐฉํ•œ๋‹ค๋Š” ์ ์—์„œ ๋‡Œ์™€ ๋น„์Šทํ•œ ์ˆ˜์ค€์˜ ๋†’์€ ์—๋„ˆ์ง€ ํšจ์œจ์„ฑ์„ ๋ณด์ผ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€๋˜๊ณ  ์žˆ๋‹ค. ํ•˜์ง€๋งŒ ์ŠคํŒŒ์ดํฌ ์‹ ํ˜ธ๊ฐ€ ํ‘œํ˜„ํ•  ์ˆ˜ ์žˆ๋Š” ๋‹ค์–‘์„ฑ์˜ ์ œํ•œ๊ณผ ๋‡Œ์˜ ์ •ํ™•ํ•œ ํ•™์Šต์›๋ฆฌ์— ๋Œ€ํ•œ ์ดํ•ด ๋ถ€์กฑ์œผ๋กœ ์ธ๊ณต ์‹ ๊ฒฝ๋ง ๋Œ€๋น„ ๋‚ฎ์€ ์ •ํ™•๋„ ๋ฌธ์ œ์— ์ง๋ฉดํ•˜๊ณ  ์žˆ๋‹ค. ์ธ๊ณต ์‹ ๊ฒฝ๋ง ๋ณ€ํ™˜ ์ŠคํŒŒ์ดํ‚น ์‹ ๊ฒฝ๋ง(ANN-converted-SNN)์€ ์ธ๊ณต ์‹ ๊ฒฝ๋ง์„ ์—ญ์ „ํŒŒ(backpropagation) ์•Œ๊ณ ๋ฆฌ์ฆ˜์œผ๋กœ ํ•™์Šตํ•œ ํ›„, ์ธ๊ณต ๋‰ด๋Ÿฐ์„ ์ŠคํŒŒ์ดํ‚น ๋‰ด๋Ÿฐ์œผ๋กœ ๋ณ€ํ™˜ํ•œ ์‹ ๊ฒฝ๋ง์ด๋‹ค. ํ•™์Šต๋œ ์‹ ๊ฒฝ๋ง์„ ์ŠคํŒŒ์ดํ‚น ๋‰ด๋Ÿฐ์˜ ๊ฐ€์ค‘์น˜์™€ ํŒŒ๋ผ๋ฏธํ„ฐ์— ์ ์šฉํ•˜์—ฌ ์‹ ๊ฒฝ๋ง์„ ๋ณ€ํ™˜ํ•œ๋‹ค. ์ธ๊ณต ์‹ ๊ฒฝ๋ง์˜ ํ•™์Šต๋œ ๊ฐ€์ค‘์น˜๋ฅผ ์ด์šฉํ•˜๊ธฐ ๋•Œ๋ฌธ์— ์ธ๊ณต ์‹ ๊ฒฝ๋ง๊ณผ ๋น„์Šทํ•œ ์ˆ˜์ค€์˜ ๋†’์€ ์ •ํ™•๋„๋ฅผ ๋ณด์ธ๋‹ค. ์ ์ฐจ ๋‹ค์–‘ํ•œ ์ธ๊ณต ์‹ ๊ฒฝ๋ง ๊ตฌ์„ฑ์š”์†Œ๋“ค์„ ์ŠคํŒŒ์ดํ‚น ์‹ ๊ฒฝ๋ง์œผ๋กœ ๋ณ€ํ™˜ํ•˜๊ธฐ ์œ„ํ•œ ์—ฐ๊ตฌ๊ฐ€ ์ง„ํ–‰๋˜๊ณ  ์žˆ๋‹ค. ๋‰ด๋กœ๋ชจํ”ฝ ํ•˜๋“œ์›จ์–ด๋Š” ์ƒ๋ฌผํ•™์  ์‹ ๊ฒฝ๋ง์˜ ๊ตฌ์กฐ์™€ ๊ธฐ๋Šฅ์„ ์•„๋‚ ๋กœ๊ทธ ํšŒ๋กœ ํ˜น์€ VLSI๋ฅผ ์ด์šฉํ•˜์—ฌ ๋ชจ๋ฐฉํ•œ ์ „๊ธฐ์  ์žฅ์น˜์ด๋‹ค. ๋‡Œ์˜ ๋™์ž‘ ํŠน์„ฑ์„ ํ•˜๋“œ์›จ์–ด๋กœ ๊ตฌํ˜„ํ•˜๊ธฐ ๋•Œ๋ฌธ์— ๋‡Œ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์ด๋‚˜ ์ŠคํŒŒ์ดํ‚น ์‹ ๊ฒฝ๋ง ๊ฐ€์†์— ์‚ฌ์šฉ๋œ๋‹ค. ๋Œ€ํ‘œ์ ์ธ ๋‰ด๋กœ๋ชจํ”ฝ ํ•˜๋“œ์›จ์–ด๋กœ IBM์—์„œ ๊ฐœ๋ฐœํ•œ TrueNorth๊ฐ€ ์žˆ๋‹ค. ๋ฐฑ ๋งŒ๊ฐœ ๋‰ด๋Ÿฐ๊ณผ 2์–ต๊ฐœ ์‹œ๋ƒ…์Šค ๊ฐ„ ๋นฝ๋นฝํ•œ ์—ฐ๊ฒฐ์„ ํ•˜๋‚˜์˜ ์นฉ์œผ๋กœ ๊ตฌํ˜„ํ•˜๋Š”๋ฐ ์„ฑ๊ณตํ–ˆ๋‹ค. ํ•˜์ง€๋งŒ TrueNorth๋Š” ๋šœ๋ ทํ•œ ๋ชฉ์  ์›Œํฌ๋กœ๋“œ๊ฐ€ ๋ถ€์กฑํ•˜๋‹ค. ๊ทธ ์ผํ™˜์œผ๋กœ TrueNorth๋Š” ์ธ๊ณต ์‹ ๊ฒฝ๋ง ๋ณ€ํ™˜ ์ŠคํŒŒ์ดํ‚น ์‹ ๊ฒฝ๋ง๊ณผ ๊ฐ™์ด ์ธ๊ณต ์ง€๋Šฅ ๋ถ„์•ผ์—์„œ ์‚ฌ์šฉํ•˜๋Š” ์ŠคํŒŒ์ดํ‚น ์‹ ๊ฒฝ๋ง์„ ๊ฐ€์†ํ•˜๋Š”๋ฐ ๋ถ€์ ํ•ฉํ•œ ๊ตฌ์กฐ๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ ์ œ์‹œํ•˜๋Š” RSTN (Rate-coded Spiking neural network TrueNorth) ๊ฐ€์†๊ธฐ๋Š” ๊ธฐ์กด TrueNorth ๊ฐ€์†๊ธฐ์˜ ๊ตฌ์กฐ๋ฅผ ๋ณ€ํ˜•ํ•˜์—ฌ ๋น„์œจ ์ฝ”๋”ฉ ๊ธฐ๋ฐ˜ ์ŠคํŒŒ์ดํ‚น ์‹ ๊ฒฝ๋ง ๊ฐ€์†์„ ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•œ๋‹ค. ๊ฐ€์†๊ธฐ ๊ตฌ์กฐ ๋””์ž์ธ์„ ์œ„ํ•ด ๋จผ์ € ์ŠคํŒŒ์ดํ‚น ์‹ ๊ฒฝ๋ง์„ ํ•˜๋“œ์›จ์–ด ์ƒ์—์„œ ๋Œ๋ฆด ๋•Œ ๊ณ ๋ คํ•ด์•ผํ•˜๋Š” ๋””์ž์ธ ํฌ์ธํŠธ๋“ค์„ ์ •์˜ํ•œ๋‹ค. ์ •์˜ํ•œ ๋””์ž์ธ ํฌ์ธํŠธ๋“ค์„ ์ด์šฉํ•˜์—ฌ ์ŠคํŒŒ์ดํ‚น ์‹ ๊ฒฝ๋ง์„ ๊ฐ€์†ํ•˜๋Š” ๊ตฌ์ฒด์ ์ธ ์ƒํ™ฉ์„ ์„ค์ •ํ•œ ํ›„ RSTN์„ ๋””์ž์ธ ํ•œ๋‹ค. ๊ธฐ์กด TrueNorth ๊ตฌ์กฐ๋ฅผ ๋ณ€ํ˜•ํ•˜์—ฌ ๋น„์œจ ์ฝ”๋”ฉ ๊ธฐ๋ฐ˜ ์ŠคํŒŒ์ดํ‚น ์‹ ๊ฒฝ๋ง์„ ๊ฐ€์†ํ•  ์ˆ˜ ์žˆ๋Š” ๋ฒ ์ด์Šค๋ผ์ธ ๊ฐ€์†๊ธฐ(RSTN-baseline)๋ฅผ ์ œ์•ˆํ•œ๋‹ค. ๊ทธ ํ›„ ์ž…๋ ฅ ์ŠคํŒŒ์ดํฌ ์ฒ˜๋ฆฌ ๋ฐฉ์‹์„ ์ตœ์ ํ™”ํ•˜์—ฌ ์˜จ ์นฉ ๋ฉ”๋ชจ๋ฆฌ ํฌ๊ธฐ๋ฅผ ์ค„์ธ ์ž…๋ ฅ ์ŠคํŒŒ์ดํฌ ์ฒ˜๋ฆฌ ๋ฐฉ์‹ ์ตœ์ ํ™” ๊ฐ€์†๊ธฐ (RSTN-IS)๋ฅผ ์ œ์•ˆํ•œ๋‹ค. ๊ทธ์— ๋”ํ•ด 0์˜ ๊ฐ’์„ ๊ฐ–๋Š” ๊ฐ€์ค‘์น˜๋“ค์— ๋Œ€ํ•œ ์—ฐ์‚ฐ์„ ๊ฑด๋„ˆ๋›ฐ์–ด ์—ฐ์‚ฐ๊ณผ ๋ฉ”๋ชจ๋ฆฌ ์ ‘๊ทผ์— ์†Œ๋ชจ๋˜๋Š” ์—๋„ˆ์ง€ ๋ฐ ์ง€์—ฐ์‹œ๊ฐ„์„ ์ ˆ์•ฝํ•œ ๊ฐ€์ค‘์น˜ ํฌ์†Œ์„ฑ ํ™œ์šฉ ๊ฐ€์†๊ธฐ(RSTN-ISWS)๋ฅผ ์ œ์•ˆํ•œ๋‹ค. ๊ฐ ๊ฐ€์†๊ธฐ๋ฅผ ํƒ€์ด๋ฐ ์‹œ๋ฎฌ๋ ˆ์ดํ„ฐ๋กœ ๊ตฌํ˜„ํ•˜์—ฌ ์ตœ์ ํ™” ๊ธฐ๋ฒ•์˜ ์„ฑ๋Šฅ์„ ์ธก์ •ํ•˜์˜€๋‹ค. ์ธก์ • ๊ฒฐ๊ณผ ์ž…๋ ฅ ์ŠคํŒŒ์ดํฌ ์ฒ˜๋ฆฌ ์ตœ์ ํ™” ๊ธฐ๋ฒ•์„ ์ ์šฉํ•œ RSTN-IS๊ฐ€ RSTN-baseline ๋Œ€๋น„ ํ‰๊ท  0.92๋ฐฐ ์ ์€ ์˜จ ์นฉ ๋ฉ”๋ชจ๋ฆฌ๋ฅผ ๊ฐ€์กŒ๋‹ค. ๊ฐ€์ค‘์น˜ ํฌ์†Œ์„ฑ์„ ํ™œ์šฉํ•œ ์ตœ์ ํ™” ๊ธฐ๋ฒ•์„ ํ†ตํ•ด RSTN-ISWS๊ฐ€ RSTN-IS ๋Œ€๋น„ ํ‰๊ท  0.34๋ฐฐ ์—๋„ˆ์ง€ ์ด๋“๊ณผ 0.10๋ฐฐ ์ง€์—ฐ์‹œ๊ฐ„ ์ด๋“์„ ๋ณด์˜€๋‹ค.์ œ 1 ์žฅ ์„œ ๋ก  1 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ์˜ ๋ฐฐ๊ฒฝ 1 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ์˜ ๋‚ด์šฉ 2 ์ œ 2 ์žฅ ์ŠคํŒŒ์ดํ‚น ์‹ ๊ฒฝ๋ง 5 ์ œ 1 ์ ˆ ์ƒ๋ฌผํ•™์  ๋‰ด๋Ÿฐ 5 ์ œ 2 ์ ˆ ์ŠคํŒŒ์ดํ‚น ๋‰ด๋Ÿฐ ๋ชจ๋ธ 7 ์ œ 3 ์ ˆ ๋‰ด๋Ÿด ์ฝ”๋”ฉ 7 ์ œ 4 ์ ˆ ์ŠคํŒŒ์ดํ‚น ์‹ ๊ฒฝ๋ง 9 ์ œ 5 ์ ˆ ๋‰ด๋กœ๋ชจํ”ฝ ํ•˜๋“œ์›จ์–ด 11 ์ œ 3 ์žฅ ์ŠคํŒŒ์ดํ‚น ์‹ ๊ฒฝ๋ง ํ•˜๋“œ์›จ์–ด ๋””์ž์ธ ํฌ์ธํŠธ ๋ถ„์„ 16 ์ œ 1 ์ ˆ ๊ณต๊ฐ„์  ํ™•์žฅ v.s. ๊ณต๊ฐ„์  ์ ‘ํž˜ 16 ์ œ 2 ์ ˆ ์‹ ๊ฒฝ๋ง ๋ถ„ํ•  ๋งคํ•‘ 21 ์ œ 4 ์žฅ TrueNorth ๊ธฐ๋ฐ˜ ๊ฐ€์†๊ธฐ ๊ตฌ์กฐ ์ตœ์ ํ™” 25 ์ œ 1 ์ ˆ ๋ฒ ์ด์Šค๋ผ์ธ ๊ฐ€์†๊ธฐ ์•„ํ‚คํ…์ณ 26 ์ œ 2 ์ ˆ ์ž…๋ ฅ ์ŠคํŒŒ์ดํฌ ์ €์žฅ ๋ฐฉ์‹ ์ตœ์ ํ™” 31 ์ œ 3 ์ ˆ ๊ฐ€์ค‘์น˜ ํฌ์†Œ์„ฑ์„ ํ™œ์šฉํ•œ ๋ฉ”๋ชจ๋ฆฌ ๊ตฌ์กฐ ์ตœ์ ํ™” 35 ์ œ 5 ์žฅ ์ตœ์ ํ™” ๊ธฐ๋ฒ• ํšจ๊ณผ ๋ถ„์„ 39 ์ œ 1 ์ ˆ ์‹คํ—˜ ์ค€๋น„ 39 ์ œ 2 ์ ˆ ์ž…๋ ฅ ์ŠคํŒŒ์ดํฌ ์ €์žฅ ๋ฐฉ์‹ ์ตœ์ ํ™” ํšจ๊ณผ ๋ถ„์„ 40 ์ œ 3 ์ ˆ ๊ฐ€์ค‘์น˜ ํฌ์†Œ์„ฑ์„ ํ™œ์šฉํ•œ ๋ฉ”๋ชจ๋ฆฌ ๊ตฌ์กฐ ์ตœ์ ํ™” ํšจ๊ณผ ๋ถ„์„ 42 ์ œ 6 ์žฅ ๊ฒฐ ๋ก  46 ์ฐธ๊ณ ๋ฌธํ—Œ 47 Abstract 51์„

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋ณด๊ฑด๋Œ€ํ•™์› ํ™˜๊ฒฝ๋ณด๊ฑดํ•™๊ณผ, 2017. 8. ๊น€์„ฑ๊ท .ratios of MeHg intake to model-predicted blood MeHg were then combined with KoNEHS-based blood MeHg values to produce MeHg intake estimates. These intake estimates were ultimately compared with the Reference Dose (RfD) for MeHg (0.1 ฮผg/kg/day) and reported as hazard quotient (HQ) for specific KoNEHS subgroups. The GM of blood Hg was 3.08 ฮผg/L and about 25 % of total population exceeded the HBM-I. Though the exceedances were derived from single measurement per individual, however those were decreasing with the lower ICC and the more repeated data. The predicted exposure dose was 35.8 ng/kg/day for total population. And the corresponding HQ value was 0.36 for total (range: 0.24 ~ 0.63). The GM was only used for deriving the HQ because using the tail of simulation data requires careful interpretation. Considering the results were derived using only the GM, the potential at-risk population could be existed for each population. In Chapter III, the perturbation of clinical chemistry markers including ALT, ฮณ-GTP, total cholesterol, triglyceride, total lipid, and IgE were investigated as the effects associated with exposure to Hg. GMs of blood Hg and clinical chemistry markers were determined and odds ratios of out-of-reference range for each marker were estimated by gender and quantile of blood Hg adjusted for age, BMI, smoking and alcohol consumption. The blood Hg level was categorized into quantile groups - low: 75th โ€“ to diagnose the effect of Hg on the reference ranges. The levels of ALT, ฮณ-GTP and total lipid were increased with blood Hg group for both sexes, and the GMs for total cholesterol and TG were significantly increased in men across the blood Hg. Regarding to ฮณ-GTP, the high blood Hg group was associated with a 2.8-fold increase for being out-of reference range in the male group (OR=2.7795% CI: 1.72-4.46), while 2.1-fold increase in the female group (OR=2.1195% CI: 1.35-3.30). High Hg group in men was associated with about 1.5-fold risk for total cholesterol. Especially, the significant contribution of blood Hg to high ฮณ-GTP were retained after adjustment for other co-exposing chemicals in the multivariate linear model. Our results suggest that Hg exposure even as low as environmental levels among general population could perturbate lipid metabolism although further mechanistic researches needs to be confirmed. In Chapter IV, the association between environmental exposures and health outcomes in children were investigated using the Childrens Health and Environmental Chemicals in Korea (CHECK). The fetal body burden for Hg was derived by using PBPK model, and the growth effects from Hg exposure at the developmental period were analyzed using several statistical approaches. Among 106 paired data out of total 334 pairs, the GM for Hg in maternal blood and cord blood was 4.47, 7.35 ฮผg/L, and that of placenta and meconium was 9.0, 36.9 ng/g, respectively. Though the sample size of infants hair was too small (n=25) for the following analysis, however, the GM was as high as 443 ng/g. The derived fetal body burden was ranged between 26.3 and 86.9 mg based on the 106 cord blood. Cord blood Hg was positively associated with length at birth (p-value: 0.0132), while weight at birth (p-value: 0.1764) and head circumference (p-value: 0.4579) were not associated with cord blood Hg. According to the logistic regression model, the cord blood Hg were not significant for the standardized height (OR: 1.30 (0.55, 3.07)), weight (OR: 0.76 (0.36, 1.62)), and PI (OR: 0.817 (0.377, 1.77)). However, the LS mean estimates for the follow up weights represent the more rapid increasing slopes in the high cord blood Hg group compared to the low Hg group for both sexes. These results indicated that fetus would have high body burden, and exposure to Hg associated with the taller height at birth and the rapid weight increasing. This study revealed the highly exposed population for Hg and conducted exposure assessment across the population based on the estimated MeHg. All HQs were below 1, but the upper 5 percentiles of HQ were above 1 except for those who consumed fish rarely. These results indicate that the potential at-risk population could be existed for each population, not only for those in consuming fish frequently. Also, Hg exposure even as low as environmental levels among general population could perturbate lipid metabolism although further mechanistic researches confirm. Furthermore, fetus would be exposed to certain amount of Hg (26.3 ~ 86.9 ฮผg/kg/day), and that could be influenced on the growth at birth and weight inceasing in later life. Therefore, more researches for fetal body burden are required, and growth effects should be investigated adjusting for other confounders including Hg level in diet and coexposure from other chemicals.Mercury (Hg) is a naturally occurring heavy metal compound and a ubiquitous contaminant of soil, air, foods, and other media. There are several forms of Hg in the environmentinorganic Hg such as amalgam, and organic Hg, especially methylmercury (MeHg), which is known for the most toxic form of Hg. According to two Korean national surveys, the geometric mean (GM) for Hg in blood was higher than that in similar national surveys done in Canada and the USA, and a substantial people in South Korea have the high level of blood Hg. Regarding to the biomonitoring level, the German Federal Environmental Agency set the guideline values for 5 ฮผg/L (The HBM-I) as a control value for which no action is needed, and 15 ฮผg/L (The HBM-II) as an action level for which medical care or advice is recommended. Meanwhile, the main exposure source for the general population is diet, especially fish consumption. It is absorbed and condensed in the human body via fish intake. In fact, about 80 % of blood Hg consists of MeHg. In order to regulate the exposure amount, the United States Environmental Protection Agency (US.EPA) recommended 0.1 ฮผg/Kg/day for MeHg as the reference dose (RfD). There have been several studies conducted investigating Hg exposure, however, there has been no study for the exposure amount of Hg based on the individual internal dose among the South Korean population. And the extent of Hg exposure should be investigated, especially for the related health effects as a suspected obesogen. In addition, Hg can be transferred from mother to fetus via placenta. Though women in South Korea have the high blood Hg compared to those in other countries, there has been no study for fetal body burden during pregnancy. Thus, exposure assessment for sensitive population is required. Therefore, this study was conducted for investigating the exceedances above the guidance values among South Korean. And the corresponding exposure dose for MeHg was calculated, which can be compared to the RfD. Next, the associations between Hg and health outcomes were investigated using clinical chemistry markers. Lastly, fetal body burden was derived by using the PBPK model and investigated the growth effects of exposure to Hg among infants. In Chapter II, the Korean National Environmental Health Survey (KoNEHS 2009-2011) were used to derive the exposure amount for Hg. Gender, age, and frequency of fish consumption were first identified as important predictors of KoNEHS blood Hg levels using generalized linear models. Stratified distributions of total blood Hg were then converted into distributions of blood MeHg using fractions of MeHg to total Hg from the literature. Next, a published physiologically-based pharmacokinetic (PBPK) model was used to predict distributions of blood MeHg as a function of MeHg intakeCHAPTER I. BACKGROUNDS 1 1 Mercury (Hg) exposure in general population 2 Reconstruction of exposure dose 4 Association between Hg and health outcomes 7 Health outcomes after early exposure 8 Objectives 9 CHAPTER II. ESTIMATING METHYLMERCURY INTAKE FOR THE GENERAL POPULATION OF SOUTH KOREA USING PBPK MODELING 11 Introduction 12 Materials and Methods 15 Results 23 Discussion 31 CHAPTER III. MERCURY IMPACTS ON OUT-OF-REFERENCE RANGE FOR CLINICAL CHEMISTRY INCLUDING HEPATIC AND METABOLIC MARKERS 37 Introduction 38 Materials and Methods 40 Results 44 Discussion 54 CHAPTER IV. FETAL BODY BURDEN FOR MERCURY EXPOSURE DURING PREGNANCY AND THE ASSOCIATION OF GROWTH 58 Introduction 59 Materials and Methods 61 Results 66 Discussion 78 CHAPTER V. CONCLUSIONS 83 Summary and Conclusions 84 BIBLIOGRAPHY 88 APPENDICES 102Docto

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