32 research outputs found

    Patterns of Korean Spontaneous Reports of Topical Corticosteroids

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์•ฝํ•™๊ณผ, 2017. 2. ์‹ ์™„๊ท .์Šคํ…Œ๋กœ์ด๋“œ ์™ธ์šฉ์ œ๋Š” 1950๋…„๋Œ€์— ์ฒ˜์Œ ์†Œ๊ฐœ๋˜์–ด ๋‹ค์–‘ํ•œ ํ”ผ๋ถ€๊ณผ์  ์ƒํƒœ์—์„œ ์‚ฌ์šฉํ•ด์˜จ ์•ฝ์ œ์ด๋‹ค. ๋งŽ์€ ์ข…๋ฅ˜์˜ ์„ฑ๋ถ„๊ณผ ์ œํ˜•์ด ๋‚˜์™€ ์žˆ์œผ๋ฉฐ, ๊ทธ๋งŒํผ ํ™˜์ž์˜ ์ƒํƒœ์— ๋”ฐ๋ผ ์•ฝ์ œ๋ฅผ ์„ ํƒํ•  ์ˆ˜ ์žˆ๋Š” ์„ ํƒ์˜ ํญ์ด ๋„“๋‹ค. ๊ทธ๋งŒํผ ์Šคํ…Œ๋กœ์ด๋“œ ์™ธ์šฉ์ œ์— ๋Œ€ํ•œ ์•ฝ๋ฌผ์ด์ƒ๋ฐ˜์‘์— ๊ด€ํ•œ ์—ฐ๊ตฌ๋Š” ๋งŽ์œผ๋‚˜ ์ž„์ƒ์—์„œ์˜ ์—ฐ๊ตฌ๋Š” ์•„์ง ๋ฏธ๋น„ํ•œ ํŽธ์ด๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ๊ตญ๋‚ด ์Šคํ…Œ๋กœ์ด๋“œ ์™ธ์šฉ์ œ์— ๋Œ€ํ•œ ์ž๋ฐœ์  ๋ถ€์ž‘์šฉ ๋ณด๊ณ ์‚ฌ๋ก€์˜ ์–‘์ƒ์„ ๋ถ„์„ํ•˜์—ฌ ์Šคํ…Œ๋กœ์ด๋“œ ์™ธ์šฉ์ œ ์•ฝ๋ฌผ์ด์ƒ๋ฐ˜์‘์˜ ํŠน์„ฑ์„ ์•Œ์•„๋ณด๊ณ , ์Šคํ…Œ๋กœ์ด๋“œ ์„ฑ๋ถ„, ์ œํ˜•, ์—ญ๊ฐ€์— ๋”ฐ๋ฅธ ์•ฝ๋ฌผ์ด์ƒ๋ฐ˜์‘ ์–‘์ƒ์„ ๋ถ„์„ํ•˜๋Š” ๊ฒƒ์ด ๋ชฉ์ ์ด์—ˆ๋‹ค. ํ›„ํ–ฅ์  ๊ด€์ฐฐ์—ฐ๊ตฌ๋กœ ํ•œ๊ตญ์˜์•ฝํ’ˆ์•ˆ์ „๊ด€๋ฆฌ์›์— 2009๋…„ 1์›”๋ถ€ํ„ฐ 2014๋…„ 12์›”๊นŒ์ง€ ๋ณด๊ณ ๋œ ๊ธ‰์—ฌ ์Šคํ…Œ๋กœ์ด๋“œ ์™ธ์šฉ์ œ(530ํ’ˆ๋ชฉ)์˜ ์˜์•ฝํ’ˆ๋ถ€์ž‘์šฉ๋ณด๊ณ ์›์‹œ์ž๋ฃŒ๋ฅผ WHO Adverse Reaction Terminology(WHO-ART)092 ver.์˜ ์šฐ์„  ์šฉ์–ด(preferred term, PT)๋ฅผ ๊ธฐ์ค€์œผ๋กœ ๋ถ„์„ํ•˜์˜€๋‹ค. ๊ทธ ์ค‘ WHO-UMC causality assessment๋ฅผ ๊ธฐ์ค€์œผ๋กœ ํ™•์‹คํ•จ(certain), ๊ฑฐ์˜ ํ™•์‹คํ•จ(probable) ๊ทธ๋ฆฌ๊ณ  ๊ฐ€๋Šฅํ•จ(possible)์œผ๋กœ ํ‰๊ฐ€ํ•œ ์•ฝ๋ฌผ์ด์ƒ๋ฐ˜์‘ ์‚ฌ๋ก€๋ฅผ ๋ถ„์„์— ์ด์šฉํ•˜์˜€๊ณ  ๊ธฐ์ˆ ํ†ต๊ณ„๋ฅผ ์‚ฌ์šฉํ–ˆ๋‹ค. ์‹ํ’ˆ์˜์•ฝํ’ˆ์•ˆ์ „์ฒ˜ ์˜์•ฝํ’ˆ๊ด€๋ฆฌ์ด๊ด„๊ณผ์—์„œ ์ œ๊ณตํ•˜๋Š” ์˜์•ฝํ’ˆ ์ƒ์‚ฐ/์ˆ˜์ž… ์‹ค์ ์„ 2009๋…„๋ถ€ํ„ฐ 2014๋…„๊นŒ์ง€ ๋งค ํ•ด ์„ฑ๋ถ„/์ œํ˜•๋ณ„๋กœ ๊ฑด๊ฐ•๋ณดํ—˜๊ณต๋‹จ์— ์ฒญ๊ตฌ๋˜๋Š” ์•ฝ๋ฌผ์˜ ์‚ฌ์šฉ๋Ÿ‰์„ ๋ฐ˜์˜ํ•˜์—ฌ ๋ฐœํ‘œํ•˜๋Š” ์ฃผ์„ฑ๋ถ„๋ณ„ ๊ฐ€์ค‘ํ‰๊ท ๊ฐ€๋กœ ๋‚˜๋ˆ„์–ด ์ƒ์‚ฐ๋Ÿ‰ ์ถ”์ •๊ฐ’, ์—ฐ๊ตฌ์—์„œ ์ƒ์‚ฐ์ˆ˜์น˜๋ผ ๋ถ€๋ฅด๋Š” ๊ฐ’์„ ์ฐธ๊ณ ํ•˜์—ฌ ์‚ฌ์šฉํ•˜์˜€๋‹ค. ๋ณด๊ณ  ์–‘์ƒ ๋ถ„์„์œผ๋กœ ์ „์ฒด PT์™€ ์˜์‹ฌ ์ฝ”๋ฅดํ‹ฐ์ฝ”์Šคํ…Œ๋กœ์ด๋“œ๋ณ„ ๋ณด๊ณ ๋Ÿ‰ ๊ธฐ์ค€์œผ๋กœ ์ •๋ฆฌํ•˜์˜€๋‹ค. ATC๋ถ„๋ฅ˜ 3๋‹จ๊ณ„์— ๋”ฐ๋ผ ์•ฝ๋ฌผ์˜ ํšจ๋Šฅ๊ตฐ๋ณ„ ๋ณด๊ณ ๋Ÿ‰ ๋ถ„์„์„ ํ•˜์˜€๋‹ค. ๋˜ํ•œ, ์„ฑ๋ถ„, ํ•จ๋Ÿ‰, ์ œํ˜•์— ๋”ฐ๋ผ ๊ฒฐ์ •๋˜๋Š” ์Šคํ…Œ๋กœ์ด๋“œ ์—ญ๊ฐ€๋ฅผ ๋ฏธ๊ตญํ”ผ๋ถ€๊ณผํ•™ํšŒ์—์„œ ์ œ์•ˆํ•œ ๋ฐ”์— ๋”ฐ๋ผ ๋ถ„๋ฅ˜ํ•˜์—ฌ ๋ณด๊ณ ๋Ÿ‰ ๋ถ„์„์„ ์ˆ˜ํ–‰ํ–ˆ๋‹ค. ์ด 6๊ฐœ๋…„์˜ ์—ฐ๊ตฌ๊ธฐ๊ฐ„ ์ค‘์— 262๊ฑด์˜ ๋ณด๊ณ ๊ฐ€ ์žˆ์—ˆ๊ณ , 426๊ฑด์˜ ์•ฝ๋ฌผ-์ด์ƒ๋ฐ˜์‘์กฐํ•ฉ์ด ์žˆ์—ˆ๋‹ค. ๋ถ€์ž‘์šฉ ๋ถ„๋ฅ˜๋ณ„๋กœ ํ”ผ๋ถ€๊ฐ€ 260๊ฑด(61.0%)์œผ๋กœ ์ฃผ๋กœ ๋ณด๊ณ ๋˜์—ˆ๋‹ค. ํ”ผ๋ถ€ ์™ธ๋Š” 165๊ฑด(38.7%) ๋ณด๊ณ ๋˜์—ˆ๊ณ , ๊ทธ ์ค‘ ์Šคํ…Œ๋กœ์ด๋“œ ์„ฑ๋ถ„ ๋•Œ๋ฌธ์— ๋‚˜ํƒ€๋‚  ์ˆ˜ ์žˆ๋Š” ๋ถ€์ž‘์šฉ์€ 26๊ฑด(6.1%)์ด ๋ณด๊ณ ๋˜์—ˆ๋‹ค. ์ƒ์‚ฐ์ˆ˜์น˜ ๋Œ€๋น„ ๋ณด๊ณ ๊ฑด์ด ๋งŽ์€ ์„ฑ๋ถ„์œผ๋กœ๋Š” betamethasone 0.064% ๊ฒ”(24๊ฑด, 5.6%, ์ƒ์‚ฐ์ˆ˜์น˜ 43์œ„), methylprednisolone 0.1% ์—ฐ๊ณ (27๊ฑด, 6.3%, ์ƒ์‚ฐ์ˆ˜์น˜ 31์œ„)๊ฐ€ ์žˆ์—ˆ๋‹ค. ATC ์ฝ”๋“œ 3๋‹จ๊ณ„ ์ฆ‰, ์น˜๋ฃŒ์ /์•ฝ๋ฌผํ•™์  ํ•˜์œ„๊ทธ๋ฃน์— ๋”ฐ๋ฅธ ๋ถ„๋ฅ˜๋กœ ๋ณด๋ฉด, ๊ตญ์†Œ์‚ฌ์šฉ ๊ฑด์„ ์น˜๋ฃŒ์ œ๊ฐ€ ์ƒ์‚ฐ์ˆ˜์น˜ ๋Œ€๋น„ ๊ฐ€์žฅ ๋งŽ์€ ๋ณด๊ณ ๋ฅผ ๋ณด์˜€๋‹ค. ์ œํ˜• ๋ถ„๋ฅ˜๋กœ ๋ณด๋ฉด ๊ฒ”๊ณผ ์—ฐ๊ณ ๊ฐ€ ์ƒ์‚ฐ์ˆ˜์น˜ ๋Œ€๋น„ ๊ฐ€์žฅ ๋งŽ์€ ๋ณด๊ณ ๋ฅผ ๋ณด์˜€๊ณ , ๋กœ์…˜, ํฌ๋ฆผ, ์•ก์ƒ ์ˆœ์„œ๋กœ ๋ณด๊ณ ๊ฐ€ ์ด๋ฃจ์–ด์กŒ๋‹ค. ์—ญ๊ฐ€์™€ ์ƒ์‚ฐ์ˆ˜์น˜ ๋Œ€๋น„ ๋ณด๊ณ ๊ฑด์ˆ˜์—๋Š” ์ผ์ •ํ•œ ํŒจํ„ด์„ ์ฐพ์„ ์ˆ˜ ์—†์—ˆ๋‹ค. ์Šคํ…Œ๋กœ์ด๋“œ ์™ธ์šฉ์ œ์˜ ๋ถ€์ž‘์šฉ ๋ฐœ์ƒ์–‘์ƒ์€ ์ •๋ฆฌํ•˜์ž๋ฉด ๋ณตํ•ฉ์„ฑ๋ถ„์„ ํฌํ•จํ•ด ์•ฝ์ œ๋ฅผ ์‚ฌ์šฉํ•˜๋Š” ์ ์‘์ฆ๊ณผ ์•ฝ์ œ์˜ ์ œํ˜•์— ๋”ฐ๋ผ ๋‹ฌ๋ผ์กŒ๋‹ค. ์˜ˆ์ƒํ•˜๋Š” ๋ฐ”์™€ ๋‹ฌ๋ฆฌ ์Šคํ…Œ๋กœ์ด๋“œ ์—ญ๊ฐ€์™€ ๋ถ€์ž‘์šฉ ๋ฐœ์ƒ์–‘์ƒ ๊ฐ„์—๋Š” ์ผ์ •ํ•œ ํŒจํ„ด์„ ๋ณด์ด์ง€ ์•Š์•˜๋‹ค. ๋ณด๊ณ ๋œ ์•ฝ๋ฌผ์ด์ƒ๋ฐ˜์‘ ์ค‘ 61.1%๊ฐ€ ํ”ผ๋ถ€ ์•ฝ๋ฌผ์ด์ƒ๋ฐ˜์‘์ด, 37.8%๊ฐ€ ํ”ผ๋ถ€ ์™ธ ์•ฝ๋ฌผ์ด์ƒ๋ฐ˜์‘์ด์—ˆ๊ณ  ํ”ผ๋ถ€ ์™ธ ์ค‘ ๊ฐ€๋Šฅํ•จ์œผ๋กœ ํŒ๋ณ„๋œ ๊ฒƒ์ด 82.4%์ด์—ˆ๋‹ค. ํ”ผ๋ถ€ ์™ธ ์•ฝ๋ฌผ์ด์ƒ๋ฐ˜์‘ ์ค‘ 26๊ฑด๋งŒ์ด ๋ถ€์ข…์ด๋‚˜ ์‹์š•์ฆ๊ฐ€ ๋“ฑ๊ณผ ๊ฐ™์€ ์Šคํ…Œ๋กœ์ด๋“œ๋กœ ์ธํ•ด ์ผ์–ด๋‚˜๋Š” ๊ฒƒ์œผ๋กœ ์•Œ๋ ค์ง„ ์•ฝ๋ฌผ์ด์ƒ๋ฐ˜์‘์ด์—ˆ๋‹ค. ์Šคํ…Œ๋กœ์ด๋“œ ์™ธ์šฉ์ œ์˜ ๋ถ€์ž‘์šฉ์€ ์Šคํ…Œ๋กœ์ด๋“œ ์„ฑ๋ถ„์„ ๋น„๋กฏํ•˜์—ฌ ์™ธ์šฉ์ œ์˜ ์ œํ˜•, ๋ณตํ•ฉ์„ฑ๋ถ„ ๋ฐ ์‚ฌ์šฉ๋ถ€์œ„์— ๋”ฐ๋ผ ๋ณด๊ณ ์–‘์ƒ์ด ์ƒ์ดํ–ˆ๋‹ค.์ดˆ ๋ก i ๋ชฉ ์ฐจ iv ํ‘œ ๋ชฉ์ฐจ v ์„œ ๋ก  1 ์—ฐ๊ตฌ๋ฐฉ๋ฒ• 3 ์—ฐ๊ตฌ๊ฒฐ๊ณผ 6 ๊ณ  ์ฐฐ 16 ๊ฒฐ ๋ก  20 ์ฐธ๊ณ ๋ฌธํ—Œ 21 ๋ถ€ ๋ก 23 Abstract 36Maste

    ์ด์˜จ์„ฑ ์•ก์ฒด์˜ ๋™๋ ฅํ•™์  ๋ถˆ๊ท ์ผ์„ฑ๊ณผ ์ „ํ•ด์งˆ๋กœ์จ ์‘์šฉ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ํ™”ํ•™๋ถ€ ๋ฌผ๋ฆฌํ™”ํ•™ ์ „๊ณต, 2016. 2. ์ •์—ฐ์ค€.Ionic liquids (ILs), or room-temperature ionic liquids (RTILs), have attracted considerable attention from both academia and industry, due to their peculiar properties and wide applicabilities as electrolytes. In this dissertation, we study both their dynamic properties as a glass-forming liquid and the applicability as electrolytes in supercapacitors via molecular dynamics simulations. In the first part, we study how dynamic heterogeneity in ionic liquids is affected by the length scale of structural relaxation and the ionic charge distribution by adopting two differently charged models of ionic liquid and their uncharged counterpart. In one model of ionic liquid, the charge distribution in the cation is asymmetric, and in the other it is symmetric, while their neutral counterpart has no charge with the ions. It is found that all the models display heterogeneous dynamics, exhibiting subdiffusive dynamics and nonexponential decay of structural relaxation. We investigate the lifetime of dynamic heterogeneity, ฯ„dh, in these systems by calculating the three-time correlation functions to find that ฯ„_dh has in general a power-law behavior with respect to the structural relaxation time, ฯ„_ฮฑ : ฯ„_dh โˆ (ฯ„_ฮฑ)^(ฮถ_dh). Although the dynamics of the asymmetric-charge model is seemingly more heterogeneous than that of the symmetric-charge model, the exponent is found to be similar, ฮถ_dh โ‰ˆ 1.2, for all the models studied in this work. The same scaling relation is found regardless of interactions, i.e., with or without Coulomb interaction, and it holds even when the length scale of structural relaxation is long enough to become the Fickian diffusion. This fact indicates ฯ„_dh is a distinctive time scale from ฯ„_ฮฑ, and the dynamic heterogeneity in these systems is mainly affected by the short-range interaction and the molecular structure. In the second part, we study electric double layer capacitors (EDLCs) in the parallel plate configuration of graphene oxide (GO). Electric double layer capacitors (EDLCs), or supercapacitors, offer high power densities and moderate energy densities for energy storage applications. The oxidation range of electrode is varied from 0% (pure graphene) to 100% (fully oxidized GO) by decorating graphene surface with hydroxyl groups. Two different electrolytes, 1-ethyl-3-methylimidazolium tetrafluoroborate (EMI+BF4โ€“) as an ionic liquid (IL) and its 1.3 M solution in acetonitrile as an organic electrolyte (OE), are considered. While the area-specific capacitance tends to decrease with increasing electrode oxidation for both electrolytes, its details show interesting differences between OE and IL, including the extent of decrease. The difference in the capacitances between them is pronounced at the cathode of low oxidation, and the anion is identified as the key species in screening ability that makes the difference in the capacitance. Hydrogen bonding between the hydroxyl groups of GO and the anions is the major factor that yields this unexpected result. For detailed insight into these differences, the screening mechanisms of electrode charges by electrolytes and their variations with electrode oxidation are analyzed with special attention paid to the aspects shared by and the contrasts between IL and OE.Chapter 1 Overview 1 1.1 Heterogeneous dynamics of ionic liquids 2 1.2 Electrolyte applications of ionic liquids 3 Part I Dynamic Heterogeneity of Model Ionic Liquids 5 Chapter 2 Introduction 7 Chapter 3 Theoretical background of dynamic heterogeneity 11 3.1 Four-pointcorrelationfunctions 11 3.2 Dynamic heterogeneity and the Stokes-Einstein relation breakdown 16 Chapter 4 Models and simulation methods 19 4.1 Toy models of ionic liquids and their neutral counter part 19 4.2 Modelsofglass-formingbinarymixtures 25 4.2.1 Kob-Andersen model 25 4.2.2 Wahnstrm model 26 4.2.3 Wahnstrm model with WCA potential 26 Chapter 5 Results and discussion 27 5.1 Liquid structure 27 5.2 Dynamic properties 31 5.3 Dynamic heterogeneity 40 Chapter 6 Conclusions 47 Part II Electric Double Layer Capacitors with Ionic Liquids and Graphene Oxide 49 Chapter 7 Introduction 51 Chapter 8 Models and simulation methods 55 Chapter 9 Results and discussion 59 9.1 Overall properties of the GO supercapacitors with oxidation 59 9.2 Hydrogen bonding at the screening zone 64 9.3 Screening by cations and anions at the screening zone 71 Chapter 10 Conclusions 79 Appendix 83 A Supplementary materials for rotational diffusion calculation in Part I 83 A.1 Method of ฯ†(t,t) calculation 83 A.2 Dependence of the time interval on ฯ†(t,t) 85 B Supplementary materials for Part II 87 B.1 Screening zone in the supercapacitors 87 B.2 Number density profiles 91 B.3 Charge density profiles 94 B.4 Orientation of molecules 97 B.5 Electric potential profiles 99 Bibliography 101 ๊ตญ๋ฌธ์ดˆ๋ก 121Docto

    A Study on Development of Decision Making Support Model for Efficient Vessel Traffic Service

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    The purpose of this study is to proposes a quantitative standard to support decision making supporting so that VTS operator can provide optimal information for efficient maritime traffic control. To achieve this purpose, the following research questions were posed; First, under what circumstances should the VTS operator begin control? Second, is there any way to effectively use the VHF communication channel to avoid congestion? Third, is there any way to use efficient waterways in a situation where safety is guaranteed? Fourth, can't VTS operator quickly identify a failure vessel? To respond to these questions, Three types of data (marine traffic surveys, VHF communication, marine accidents) were investigated and analyzed. The findings of this study are as follows; First, Busan North Port VHF communication analysis confirmed that the probability of controlling vessels with a risk level of 5.0 or higher by the PARK model per unit time in the control area was based on the Poisson distribution. Through this, it was possible to predict the time interval for controlling the vessel at future risk 5.0, which can help the VTS operator to make the decision on the timing of the time communication. and a relatively dangerous zone could be derived by performing spatial analysis and PARK model risk assessment using marine traffic survey data near Busan New Port. This can assist VTS operator in making decisions about when to communicate spatially. Second, quantitative analysis of VHF communication status in Busan North Port using queuing theory and three ways to reduce traffic congestion for safe and efficient maritime traffic management. Each element of the queue theory is the increase of communication channels, the elimination of passing reports, and the reduction of basic ship traffic information. Third. as a basic step to design the minimum speed for the efficient operation of the route in the VTS area, the impact on the waiting time of the ship to approach the route when the minimum speed was limited was analyzed. The simulation was designed using the data from the Busan North Port, and the results showed that the latency and the speed limit had a negative relationship. In other words, the higher the speed limit, the lower the waiting time. In addition, safety distance and waiting time were positively related, and traffic volume and waiting time were positively positive. Forth, based on the AIS data of the actual accident ship, made a model that can identify the accidents of the not under command ships including the engine failure and the steering failure that occur most frequently in Korea's waters. In addition, it was applied to the Busan North Port VTS area, and the ratio of the current speed to the average speed was the most important factor to determine the failure. However, it was difficult to distinguish ships in anchorages, docks, and pilot station, and further studies should be conducted. The result of this study will contribute to the VTS operator to decide quantitatively and ship operator also will be provided with the same service under same circumstances. However, although this study aimed at the port VTS, if it is extended to the coastal VTS, it can be developed into a model that can cover the entire sea area of โ€‹โ€‹Korea.์ œ 1 ์žฅ ์„œ ๋ก  1 1.1 ์—ฐ๊ตฌ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉ์  1 1.2 ์—ฐ๊ตฌ๋ฐฉ๋ฒ• ๋ฐ ๋‚ด์šฉ 3 ์ œ 2 ์žฅ ์˜์‚ฌ๊ฒฐ์ •์ง€์› ๋ชจ๋ธ 6 2.1 ํ•ด์ƒ๊ตํ†ต๊ด€์ œ์˜ ์ •์˜์™€ ๋ชฉ์  6 2.2 ํ•ด์ƒ๊ตํ†ต๊ด€์ œ์˜ ์„œ๋น„์Šค 6 2.3 ํ•ด์ƒ๊ตํ†ต๊ด€์ œ ์˜์‚ฌ๊ฒฐ์ •์ง€์› ๋ชจ๋ธ์˜ ์ •์˜ 11 ์ œ 3 ์žฅ ํ†ตํ•ญ์•ˆ์ „ ํ™•๋ณด๋ฅผ ์œ„ํ•œ ์‹œ๊ฐ„ใ†๊ณต๊ฐ„ ๊ด€๋ฆฌ ๋ฐฉ์•ˆ 15 3.1 ํ•ด์ƒ๊ตํ†ต๊ด€์ œ ์‹œ๊ฐ„์  ๊ต์‹  ์‹œ์  15 3.1.1 ๊ด€์ œ๊ตฌ์—ญ ๋‚ด ์œ„ํ—˜์ƒํ™ฉ ํŒŒ์•…์„ ์œ„ํ•œ ๊ต์‹ ๋ถ„์„ 15 3.1.2 ์œ„ํ—˜์ƒํ™ฉ ๋ฐœ์ƒ๊ฐ„๊ฒฉ ์˜ˆ์ธก 22 3.2 ํ•ด์ƒ๊ตํ†ต๊ด€์ œ ๊ณต๊ฐ„์  ๊ต์‹  ์‹œ์  32 3.2.1 ๊ณต๊ฐ„์  ๊ต์‹ ์‹œ์  ํŒŒ์•…์„ ์œ„ํ•œ ์š”์ธ๋ถ„์„ 33 3.2.2 ๊ณต๊ฐ„์  ๊ต์‹ ์‹œ์  ์ œ์•ˆ 37 3.3 ์†Œ๊ฒฐ 54 3.3.1 ์‹œ๊ฐ„์  ๊ต์‹  ์‹œ์  ๋„์ถœ 54 3.3.2 ๊ณต๊ฐ„์  ๊ต์‹  ์‹œ์  ๋„์ถœ 55 ์ œ 4 ์žฅ ์›ํ™œํ•œ ๊ด€์ œ ๊ต์‹ ์„ ์œ„ํ•œ ์˜์‚ฌ์†Œํ†ต๊ด€๋ฆฌ ๋ฐฉ์•ˆ 59 4.1 ๋Œ€๊ธฐํ–‰๋ ฌ์„ ์ด์šฉํ•œ ๊ด€์ œ๊ตฌ์—ญ ๊ต์‹  ์‹œ๊ฐ„ ๋ถ„์„ 62 4.1.1 ๋Œ€๊ธฐํ–‰๋ ฌ ๋ชจ๋ธ ์†Œ๊ฐœ 62 4.1.2 ๊ต์‹ ๋ถ„์„ ๋Œ€์ƒ 66 4.1.3 ๋ถ€์‚ฐํ•ญ ๋ถํ•ญ ๊ด€์ œ๊ตฌ์—ญ ๊ต์‹ ํ˜„ํ™ฉ 68 4.2 ํ•ด์ƒ๊ตํ†ต๊ด€์ œ ์ฑ„๋„์˜ ํšจ์œจ์  ์šด์˜ ๋ฐฉ์•ˆ 77 4.2.1 ์ฃผ๊ฐ„์‹œ๊ฐ„๋Œ€ ๋ณต์ˆ˜์˜ ๊ด€์ œ์ฑ„๋„ ์šด์šฉ 79 4.2.2 ํ†ต๊ณผ๋ณด๊ณ  ๊ฐ„์†Œํ™” ๋ฐฉ์•ˆ 81 4.2.3 ์„ ๋ฐ•๋™์ •๋ณด๊ณ  ์‹œ๊ฐ„ ์ถ•์†Œ ๋ฐฉ์•ˆ 84 4.3 ์†Œ๊ฒฐ 86 ์ œ 5 ์žฅ ์ง€์ •ํ•ญ๋กœ์˜ ํšจ์œจ์  ์šด์˜์„ ์œ„ํ•œ ์•ˆ์ „์šดํ•ญ๊ด€๋ฆฌ ๋ฐฉ์•ˆ 89 5.1 ์•ˆ์ „์šดํ•ญ๊ด€๋ฆฌ๋ฅผ ์œ„ํ•œ ์ตœ์ €์†๋ ฅ ์ œํ•œ 89 5.1.1 ์†๋ ฅ์ œํ•œ ์‚ฌ๋ก€์—ฐ๊ตฌ 89 5.1.2 ์†๋ ฅ์ œํ•œ์„ ํ†ตํ•œ ์ˆ˜๋กœ ์šด์˜์˜ ํ•„์š”์„ฑ 95 5.1.3 ์ตœ์ €์†๋ ฅ ์ œํ•œ ํšจ๊ณผ ๊ฒ€์ฆ์„ ์œ„ํ•œ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ 96 5.2 ์•ˆ์ „์šดํ•ญ๊ด€๋ฆฌ๋ฅผ ์œ„ํ•œ ๊ณ ์žฅ์„ ๋ฐ• ํŒ๋‹จ๊ธฐ๋ฒ• 113 5.2.1 ๊ณ ์žฅ์„ ๋ฐ• ์‹๋ณ„ ํ•„์š”์„ฑ 113 5.2.2 ๊ณ ์žฅ์ƒํ™ฉ ํŒ๋‹จ๊ธฐ๋ฒ• 116 5.2.3 ํŒ๋‹จ๊ธฐ๋ฒ•์„ ์ด์šฉํ•œ ๊ณ ์žฅ์„ ๋ฐ• ๋ถ„๋ฅ˜ 119 5.3 ์†Œ๊ฒฐ 129 5.3.1 ์•ˆ์ „์šดํ•ญ๊ด€๋ฆฌ๋ฅผ ์œ„ํ•œ ์ตœ์ €์†๋ ฅ ์ œํ•œ 129 5.3.2 ์•ˆ์ „์šดํ•ญ๊ด€๋ฆฌ๋ฅผ ์œ„ํ•œ ๊ณ ์žฅ์„ ๋ฐ• ํŒ๋‹จ๊ธฐ๋ฒ• 131 ์ œ 6 ์žฅ ๊ฒฐ๋ก  132 ์ฐธ๊ณ ๋ฌธํ—Œ 137Docto

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) --์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์˜ํ•™๊ณผ(๋‚ด๊ณผํ•™ ์ „๊ณต),2009.2.Docto

    Mobile Shopping Service that Reflected the On-Offline Converged Circumstance

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๋””์ž์ธํ•™๋ถ€, 2015. 2. ์œค์ฃผํ˜„.๋ฏธ๋””์–ด์— ์˜ํ–ฅ์„ ๋ฐ›๋Š” ์†Œ๋น„์ž ํ–‰๋™์— ๋Œ€ํ•œ ์ดํ•ด ๋…ธ๋ ฅ์€ 1920๋…„๋Œ€ AIDMA ๋ชจ๋ธ๋กœ๋ถ€ํ„ฐ ์‹œ์ž‘๋˜์—ˆ๋‹ค. ์ด ๋‹น์‹œ์— ์†Œ๋น„์ž๋Š” ๊ธฐ์—…์˜ ๋งˆ์ผ€ํŒ… ๋ฉ”์‹œ์ง€๋ฅผ ์ผ๋ฐฉ์ ์œผ๋กœ ๋ฐ›๊ธฐ๋งŒ ํ–ˆ์œผ๋‚˜, ์ดํ›„ 1960๋…„๋Œ€ ํ›„๋ฐ˜์˜ EKB ๋ชจ๋ธ์ด ๋‹ค๋ฃจ๋“ฏ์ด ์†Œ๋น„์ž๊ฐ„์˜ ์†Œํ†ต์ด ์‹œ์ž‘๋˜์—ˆ๊ณ , 2000๋…„๋Œ€์— ๋“ค์–ด์„œ ์ธํ„ฐ๋„ท์˜ ๋ฐœ์ „์œผ๋กœ ์†Œํ†ต์˜ ๋ฐฉ๋ฒ•์€ ๋”์šฑ ๋‹ค์–‘ํ•ด์ง€๋ฉฐ ๊ทœ๋ชจ๋„ ์ปค์ง€๊ณ  ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ์ง„ํ™”๋Š” ์˜จ๋ผ์ธ ์‡ผํ•‘์˜ ๋ฐœ์ „์— ๋”ฐ๋ฅธ ๊ฒƒ์œผ๋กœ, ์„ธ๊ณ„์˜ ๊ฒฝ์ œ์—์„œ ์†Œ๋น„์ž์˜ ๋ชฉ์†Œ๋ฆฌ๋Š” ๊ณผ๊ฑฐ์˜ ์–ด๋Š ๋•Œ๋ณด๋‹ค ์ปค์กŒ๋‹ค. ํ•˜์ง€๋งŒ ๋™์‹œ์— ์˜จ๋ผ์ธ ์‡ผํ•‘์˜ ๋ฌด๋ถ„๋ณ„ํ•œ ์–‘์  ์„ฑ์žฅ๊ณผ ์น˜์—ดํ•œ ๋งˆ์ผ€ํŒ… ๊ฒฝ์Ÿ์œผ๋กœ ์†Œ๋น„์ž๊ฐ€ ๊ฐ์ข… ํ˜ผ๋ž€๊ณผ ํ”ผ๋กœ๊ฐ์„ ๋Š๋ผ๊ฒŒ ํ•˜๊ณ  ์žˆ๊ณ , ์˜จ๋ผ์ธ์ƒ์˜ ์˜ํ–ฅ๋ ฅ์ด ํฐ ์†Œ์ˆ˜๊ฐ€ ์—ฐ๊ด€๋œ ์‚ฌ๊ฑด ์‚ฌ๊ณ ๊ฐ€ ์ข…์ข… ๋ฐœ์ƒํ•œ๋‹ค. ๋˜ํ•œ ๋‹ค์ˆ˜์˜ ์ •๋ณด๊ฐ€ ํ•ญ์ƒ ์˜ณ์€ ๊ฒƒ์€ ์•„๋‹ˆ๋ฉฐ ์ˆ˜๋งŽ์€ ์‹ ์ œํ’ˆ๋“ค์ด ์†Œ๋น„์ž๋‚˜ ๋ธŒ๋žœ๋“œ ์ด๋ฏธ์ง€์— ์ข‹์ง€๋งŒ์€ ์•Š์€ ๊ฒƒ์œผ๋กœ ๋ฐํ˜€์ง€๊ณ  ์žˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ๊ฐ€์žฅ ํฐ ๋ฌธ์ œ๋กœ๋Š” ์‡ผ๋ฃจ๋ฐ์„ ํ™•์‚ฐ์‹œ์ผœ ์˜คํ”„๋ผ์ธ ๋งค์žฅ์˜ ์šด์˜์„ ์–ด๋ ต๊ฒŒ ํ•˜๊ณ  ์žˆ๋‹ค๋Š” ์ ์ด๋‹ค. ๊ทธ๋Ÿฐ๋ฐ ์˜คํ”„๋ผ์ธ ๋งค์žฅ์€ ์˜จ๋ผ์ธ ์‡ผํ•‘์˜ ๋‹จ์ ์„ ๊ทน๋ณตํ•  ์—ฌ๋Ÿฌ ์žฅ์ ์„ ๊ฐ–๊ณ  ์žˆ๋‹ค. ํŠนํžˆ ์†Œ๋น„์ž๊ฐ€ ์ œํ’ˆ์„ ์ง์ ‘ ์ฒดํ—˜ํ•˜๋ฉฐ ๋งค์žฅ ์ ์›๊ณผ ์ง์ ‘ ์†Œํ†ตํ•  ์ˆ˜ ์žˆ์–ด ๋ธŒ๋žœ๋“œ ๊ฐ€์น˜์™€ ํŒ๋งค์œจ ์ƒ์Šน ํšจ๊ณผ๋ฅผ ๊ธฐ๋Œ€ํ•  ์ˆ˜ ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ํšจ๊ณผ๋Š” ์‹ฌ๋ฆฌํ•™ ์—ฐ๊ตฌ๋กœ๋„ ๋’ท๋ฐ›์นจ๋˜๊ณ  ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ์•ž์œผ๋กœ์˜ ์‡ผํ•‘์€ ์˜จ๋ผ์ธ๊ณผ ์˜คํ”„๋ผ์ธ์˜ ๊ฒฐํ•ฉ์„ ํ•ต์‹ฌ ์ „๋žต์œผ๋กœ ๊ฐ€์ ธ๊ฐ€์•ผ ํ•  ๊ฒƒ์ด๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์ตœ๊ทผ์˜ ๋ชจ๋ฐ”์ผ ๊ธฐ์ˆ ์˜ ๋ฐœ์ „์€ ์ด ๊ฐ™์€ ์ „๋žต์„ ์ ๊ทน์ ์œผ๋กœ ์‹คํ˜„ํ•˜๊ธฐ์— ์ถฉ๋ถ„ํ•œ ํ™˜๊ฒฝ์„ ๋งŒ๋“ค์–ด์ฃผ์—ˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ด์— ๋งž์ถฐ ์†Œ๋น„์ž๋“ค์ด ์˜จ๋ผ์ธ๊ณผ ์˜คํ”„๋ผ์ธ์˜ ๋‘ ์‡ผํ•‘ ํ™˜๊ฒฝ์—์„œ ์‚ฌ์šฉํ•˜๊ธฐ์— ์ ํ•ฉํ•œ ๋ชจ๋ฐ”์ผ ์„œ๋น„์Šค๋ฅผ ์ œ์•ˆํ•œ๋‹ค. ๋ชจ๋ฐ”์ผ ์„œ๋น„์Šค๋Š” ์• ํ”Œ๋ฆฌ์ผ€์ด์…˜(Application) ํ˜•ํƒœ๋กœ ๊ตฌํ˜„ํ•˜๋ฉฐ, ๋‹ด๊ณ  ์žˆ๋Š” ๊ธฐ๋Šฅ์€ ๊ด€์‹ฌ, ์†Œํ†ต, ์ฒดํ—˜์ด๋ผ๋Š” 3๊ฐ€์ง€ ํ‚ค์›Œ๋“œ์— ๋งž์ถฐ ๊ฐœ๋ฐœํ•œ๋‹ค. ์ด๋Š” ๊ณผ๊ฑฐ๋ถ€ํ„ฐ ์˜ค๋Š˜๋‚ ๊นŒ์ง€์˜ ์†Œ๋น„ํ™˜๊ฒฝ ๊ณ ์ฐฐ์„ ํ†ตํ•œ ๋ถ„๋ฅ˜์ด๋‹ค. ๊ด€์‹ฌ์€ ๋‹ค์‹œ ์ œํ’ˆ ์ž์ฒด๋‚˜ ์‡ผํ•‘์˜ ๋™๊ธฐ์— ๋Œ€ํ•œ ๊ด€์‹ฌ์œผ๋กœ ๋‚˜๋ˆŒ ์ˆ˜ ์žˆ๊ณ , ์†Œํ†ต์€ ์†Œ๋น„์ž ๋‚ด๋ถ€๋‚˜ ์™ธ๋ถ€์™€์˜ ์†Œํ†ต์œผ๋กœ ๋‚˜๋ˆ„์–ด ๊ฐ๊ฐ์˜ ๋‹จ๊ณ„์— ๋งž์ถ˜ 6๊ฐ€์ง€ ์ „๋žต ๊ธฐ๋Šฅ์„ ์ œ์•ˆํ•œ๋‹ค. ๋ณธ ๋ชจ๋ฐ”์ผ ์„œ๋น„์Šค๋ฅผ ํ†ตํ•ด ์†Œ๋น„์ž๋Š” ์˜จ๋ผ์ธ์—์„œ ์ŠคํŠธ๋ ˆ์Šค๋Š” ์ ์œผ๋ฉด์„œ ์†Œ๋น„์ž์—๊ฒŒ ๊ผญ ํ•„์š”ํ•œ ์ œํ’ˆ์„ ์ฐพ๊ณ  ์ตํžˆ๊ณ , ์˜คํ”„๋ผ์ธ์—์„œ์˜ ์ฒดํ—˜์— ๋„์›€์„ ๋ฐ›์„ ์ˆ˜ ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์™€ ์ œ์•ˆํ•˜๋Š” ์„œ๋น„์Šค๊ฐ€ ์•ž์œผ๋กœ์˜ ์˜จ-์˜คํ”„ ์œตํ•ฉ ๋ชจ๋ฐ”์ผ ์‡ผํ•‘ ์„œ๋น„์Šค์˜ ์†”๋ฃจ์…˜์ด ๋  ๊ฒƒ์ด๋ผ ๊ธฐ๋Œ€ํ•œ๋‹ค.์ดˆ ๋ก i I. ์„œ๋ก  1 1. ์—ฐ๊ตฌ์˜ ๋ฐฐ๊ฒฝ๊ณผ ๋ชฉ์  1 2. ์—ฐ๊ตฌ์˜ ๋ฒ”์œ„์™€ ๋ฐฉ๋ฒ• 3 3. ์šฉ์–ด ์„ค๋ช… 6 II. ์†Œ๋น„์ž ํ–‰๋™์˜ ์ดํ•ด 7 1. AIDMA 7 1) Attention(์ฃผ๋ชฉ) 7 2) Interest(ํฅ๋ฏธ) 8 3) Desire(์š•๊ตฌ) 8 4) Memory(๊ฐ์ธ) 8 5) Action(๊ตฌ๋งค) 8 2. EKB ๋ชจ๋ธ 9 1) ๋ฌธ์ œ ์ธ์‹ 9 2) ์ •๋ณด์˜ ํƒ์ƒ‰, ๋Œ€์•ˆ์˜ ํ‰๊ฐ€ 10 3) ๊ตฌ๋งค 11 4) ๊ตฌ๋งค ํ›„ ํ‰๊ฐ€ 11 3. AISAS 11 4. AISCEAS 13 5. AIDEES 14 6. ์†Œ๋น„์ž ํ–‰๋™ ๋ชจ๋ธ ์ข…ํ•ฉ ๋น„๊ต 14 1) ํƒ์ƒ‰ํ•  ์ •๋ณด์™€ ์ฑ„๋„์˜ ๋‹ค์–‘ํ™” 15 2) ์†Œ๋น„์ž๊ฐ„ ์†Œํ†ต์˜ ์ฆ๊ฐ€ 16 3) ์ฒดํ—˜๊ณผ ๋ธŒ๋žœ๋“œ ์ด๋ฏธ์ง€ 18 III. ์˜จ๋ผ์ธ ์‡ผํ•‘์˜ ๋ฐœ์ „๊ณผ ํ˜„ํ™ฉ 19 1. ์˜จ๋ผ์ธ ์‡ผํ•‘๊ณผ ์„ ํƒ๊ถŒ ํ™•์žฅ์˜ ์—ญ์‚ฌ 19 1) 1888๋…„ ์ด์ „ 19 2) 1888๋…„ ์‹œ์–ด์Šค ์นดํƒˆ๋กœ๊ทธ 20 3) 1949๋…„ ์ผ€์ด๋ธ”TV์˜ ์‹œ์ž‘๊ณผ 1977๋…„ TV ํ™ˆ์‡ผํ•‘ 22 4) 1982๋…„ ์˜จ๋ผ์ธ ์ƒ๊ฑฐ๋ž˜์˜ ์‹œ์ž‘๊ณผ 1990๋…„ WWW์˜ ๋ฐœ๋ช… 24 5) 1995๋…„ ๋Œ€ํ˜• ์ข…ํ•ฉ ์˜จ๋ผ์ธ ์‡ผํ•‘๋ชฐ 25 6) 1997๋…„ ์˜คํ”ˆ ๋งˆ์ผ“ 28 7) 2010๋…„ ์Šค๋งˆํŠธํฐ์˜ ๋ณด๊ธ‰๊ณผ ์†Œ์…œ ์ปค๋จธ์Šค 29 8) 2013๋…„ iBeacon 30 9) ์˜จ๋ผ์ธ ์‡ผํ•‘์˜ ๋ฐœ์ „์ด ๊ฐ€์ ธ์˜จ ๋ณ€ํ™” 32 2. ์ฃผ๋„๊ถŒ ์ƒ์‹ค๊ณผ ์†Œ๋น„์ž ํ”ผํ•ด 34 1) ์†Œ๋น„์ž ํ˜ผ๋ž€ 34 2) ๋””์ง€ํ„ธ ํ”ผ๋กœ 37 3) ๋ฒ ์ด์ปจ์˜ ๊ทน์žฅ์˜ ์šฐ์ƒ 40 4) ๋‹ค์ˆ˜์˜ ์˜ค๋ฅ˜ 42 5) ์‹ ์ œํ’ˆ ์ถœ์‹œ ์ฃผ๊ธฐ ๋‹จ์ถ• 44 3. ์‡ผ๋ฃจ๋ฐ๊ณผ ์˜คํ”„๋ผ์ธ ๋งค์žฅ์˜ ์œ„๊ธฐ 47 1) ์‡ผ๋ฃจ๋ฐ ํ˜„์ƒ 47 2) Best Buy์˜ ์ˆ˜์ต ์•…ํ™” 50 3) ๊ทธ ์™ธ์˜ ํ˜„ํ™ฉ 52 4) ์˜คํ”„๋ผ์ธ ๋งค์žฅ์˜ ์ „๋ง 55 IV. ์˜คํ”„๋ผ์ธ ์‡ผํ•‘์˜ ์ดํ•ด 56 1. ์ œํ’ˆ ์ฒดํ—˜์œผ๋กœ ๋ธŒ๋žœ๋“œ์˜ ๊ฐ€์น˜ ์ƒ์Šน 56 1) ์• ํ”Œ ์Šคํ† ์–ด 56 2) ๋ผ์ธํ”„๋ Œ์ฆˆ ์Šคํ† ์–ด 59 3) ์ธ๋ฌธ๊นŒํŽ˜ ์ฐฝ๋น„ 61 4) ์•„๋””๋‹ค์Šค ์ด๋…ธ๋ฒ ์ด์…˜ ๋žฉ, SK-II ํ”ผํ…Œ๋ผ ํ•˜์šฐ์Šค 62 2. ์†Œ๋น„์ž์™€์˜ ์†Œํ†ต์œผ๋กœ ํŒ๋งค ์ฆ๊ฐ€ 64 1) ๋ฒ ์ŠคํŠธ ์…€๋Ÿฌ์Šค ์™€์ธ ๋งค์žฅ 64 2) ์• ํ”Œ ์Šคํ† ์–ด์˜ ์ง€๋‹ˆ์–ด์Šค ๋ฐ” 66 3) ์‚ผ์„ฑ์ƒ๋ช…์˜ ์˜์‚ผ์„ฑ ๋ผ์ดํ”„ ์นดํŽ˜ 67 4) ํ•˜๋‚˜ํˆฌ์–ด์˜ ๋šœ๋ฅด ๋“œ ์นดํŽ˜ 68 3. ์‚ฌํšŒ์  ์ˆœ๊ธฐ๋Šฅ 69 4. ์†Œ๋น„์‹ฌ๋ฆฌํ•™ ์—ฐ๊ตฌ 70 1) ๋ˆˆ์•ž์— ์ œํ’ˆ์ด ์‹ค์žฌํ•  ๋•Œ ๊ฐ€์น˜๋ฅผ ๋”์šฑ ๋†’๊ฒŒ ํ‰๊ฐ€ 70 2) ์ ๋‹นํ•œ ์ˆ˜์˜ ์ œํ’ˆ ์ง„์—ด์ด ๋งค์ถœ์— ๋„์›€ 71 V. ์˜จ-์˜คํ”„๋ผ์ธ ์‡ผํ•‘ ์„œ๋น„์Šค ์ „๋žต 73 1. ์‡ผํ•‘์˜ ํ๋ฆ„ 73 1) ๊ด€์‹ฌ 74 2) ์†Œํ†ต 76 3) ์ฒดํ—˜ 78 4) ์‡ผํ•‘์˜ ํ๋ฆ„ ์ข…ํ•ฉ 79 2. ์ „๋žต ๊ธฐ๋Šฅ 79 1) ํ€ด์ฆˆ ํ๋ ˆ์ด์…˜(Quiz Curation) 80 2) ๊ฐ€์ด๋“œ ๋งค์น˜(Guide Match) 82 3) ์ฒด์ธ ๋‚ด๋น„๊ฒŒ์ด์…˜(Chain Navigation) 83 4) ์ฒดํฌ๋ฆฌ์ŠคํŠธ(Checklist) 86 5) ์ƒ˜ํ”Œ ๋ฆฌ์ŠคํŠธ(Sample List) 88 6) ์Šคํ† ์–ด ๋กœ์ผ€์ดํ„ฐ(Store Locator), ํ”Œ๋กœ์–ด ํ”Œ๋žœ(Floor Plan) 90 3. ์ฐธ๊ณ  ์‚ฌ๋ก€ ๋ถ„์„ 92 1) ๋กฏ๋ฐ๋ฐฑํ™”์  ์Šค๋งˆํŠธํ”ฝ 92 2) ํ™ˆํ”Œ๋Ÿฌ์Šค ์ง€ํ•˜์ฒ ์—ญ ๊ฐ€์ƒ ์Šคํ† ์–ด 93 3) ์•„๋งˆ์กด ๋Œ€์‰ฌ 95 4) ์•„๋งˆ์กด ํ”„๋ผ์ด์Šค ์ฒดํฌ 95 5) ์Šคํƒญ ์Šค๋ƒ… 96 6) C&A์˜ Fashion Like ์บ ํŽ˜์ธ 97 7) ์ด๋งˆํŠธ ๋Š˜ ์‚ฌ๋˜๊ฑฐ ํ•œ๋ฐฉ์— 98 8) ๋ฒ„๋ฒ„๋ฆฌ ํŒจ์…˜์‡ผ ์˜จ๋ผ์ธ ์ค‘๊ณ„ 99 9) ์ฐธ๊ณ  ์‚ฌ๋ก€ ์ข…ํ•ฉ 100 VI. ๋ชจ๋ฐ”์ผ ์„œ๋น„์Šค ํ”„๋กœํ† ํƒ€์ž… ์ œ์•ˆ 103 1. Concept Model 103 2. IA & Flow 104 3. UI/GUI & Interaction 105 1) UI/GUI ์ปจ์…‰ํŠธ 105 2) ์ธํ„ฐ๋ž™์…˜ ์ปจ์…‰ํŠธ 112 3) ์ฃผ์š” UI/GUI 114 4. ์„œ๋น„์Šค ์‚ฌ์šฉ ์‹œ๋‚˜๋ฆฌ์˜ค 125 1) ์‹œ๋‚˜๋ฆฌ์˜ค A: ๋‚ด์  ์†Œํ†ต 126 2) ์‹œ๋‚˜๋ฆฌ์˜ค B: ์™ธ์  ์†Œํ†ต 127 5. ์„œ๋น„์Šค ์‚ฌ์šฉ์„ฑ ๊ฒ€์ฆ 128 1) ๊ฒ€์ฆ ๊ฐœ์š” ๋ฐ ๋ฐฉ๋ฒ• 128 2) ํ€ด์ฆˆ ํ๋ ˆ์ด์…˜๊ณผ ์ฒด์ธ ๋‚ด๋น„๊ฒŒ์ด์…˜ ๊ฒ€์ฆ 130 3) ์ฒดํฌ๋ฆฌ์ŠคํŠธ์™€ ๊ฐ€์ด๋“œ ๋งค์น˜ ๊ฒ€์ฆ 136 4) ์‚ฌ์šฉ์„ฑ ๊ฒ€์ฆ ์ข…ํ•ฉ ๋ฐ ํ•œ๊ณ„์  140 6. ์ตœ์ข… ๊ฒฐ๊ณผ๋ฌผ 142 1) ์ „์ฒด ํ™”๋ฉด ์ผ๋žŒ 142 2) ์„œ๋น„์Šค ์‹œ๋ฎฌ๋ ˆ์ดํ„ฐ 144 3) ์ „์‹œํšŒ 146 VII. ๊ฒฐ๋ก  ๋ฐ ๊ธฐ๋Œ€ํšจ๊ณผ 149 ์ฐธ๊ณ ๋ฌธํ—Œ 152 Abstract 156Maste

    ์„ ๋ฐ• ์กฐ์šฐ ์ƒํ™ฉ์— ๋Œ€ํ•œ ์ ์ • ๊ด€์ œ ๊ฐœ์ž…์‹œ๊ธฐ์— ๊ด€ํ•œ ๊ธฐ์ดˆ ์—ฐ๊ตฌ

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    Korea's world seaborne trade has been continuously increasing as the maritime shipping is actively developing due to a geographic characteristic. Also, increased demand of water leisure activities by the rise of GDP(Gross Domestic Product) and increased numbers of fishing vessels made the marine traffic volume increase gradually. Especially around the marine traffic control areas, marine traffic flow is complicated by the ships that are entering, departing and crossing. And this results in bigger danger of marine accidents. In order to decrease these dangers of marine accidents and secure safety of marine traffic, VTS(Vessel Traffic Service) services are being provided in Korea, where there are 18 VTS centers being operated in ports and on the coasts. Despite the continuous efforts by VTS, annual average of marine accidents were 161.4 in recent five years(2010~2014) in the control areas and they are continuously increasing in these areas. Especially, lots of marine accidents occur in the areas of Busan VTS accounting for 29.6% of the total. Meanwhile, guidelines of control procedures are set on the VTS control according to IALA VTS Manual and Public Order in Open Ports Act of Korea. However, there are no guidelines about control orders and avoiding methods since these can't be applied uniformly depending on the ships' encountering situations while controlling. So, even on similar traffic situations, orders of the VTS center are being proceeded differently depending on the VTS officers in charge of this. This is why it is desperately needed to prepare guidelines for the time of avoidance on each encountering situations. Therefore, this paper is intended to provide guidelines for the time of control on each encountering situations by using PARK model based on the consciousness of ship operators in Busan Port where there are lots of dangerous elements lurking in marine traffic. Firstly, the result of survey aimed at Busan VTS officers about the occurrence of dangerous situations while on duty showed that they felt average of 7.8 times of danger at daytime and 6.6 times of that at night. And by each duty time, they felt the dangerous traffic situations at every 15 minutes during daytime and every 18 minutes at night. Secondly, the control channels of VTS were watched for three days to distinguish dangerous situations in the vicinity of Busan Port. There were total 2,965 communications and the analysis showed that the percentage of the matters related to the encountering of ship is in total of 22% Thirdly, in order to check the risk among vessels at the time during the duty of the VTS officer, there were four derived elements which are the time of order or advice by the VTS officer intervening in the communications about the ships' encountering situations, CPA in case of sailing after deciding the sailing methods by the communications among ships, the distance at the first communication and the risk showed by PARK Model. The derived risks were classified under ships' encountering situations. Lastly, after analyzing the risk of PARK Model derived from three days of the investigation by each encountering situations, this paper suggested a guideline for the appropriate time for control.1. ์„œ ๋ก  1 1.1 ์—ฐ๊ตฌ์˜ ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉ์  1 1.2 ์—ฐ๊ตฌ์˜ ๋‚ด์šฉ ๋ฐ ๋ฐฉ๋ฒ• 3 2. ํ•ด์ƒ๊ตํ†ต๊ด€์ œ ๋ฐ ์œ„ํ—˜๋„ ํ‰๊ฐ€ ๋ชจ๋ธ์˜ ๊ณ ์ฐฐ 5 2.1 ํ•ด์ƒ๊ตํ†ต๊ด€์ œ์˜ ์ •์˜ 5 2.2 VTS์˜ ๊ด€์ œ๋ฅผ ์œ„ํ•œ ๊ถŒํ•œใƒป์ ˆ์ฐจ ๋ฐ ์„œ๋น„์Šค ์กฐ์‚ฌ 6 2.2.1 ํ†ตํ•ญ๊ด€์ œ๋ฅผ ์œ„ํ•œ VTS์˜ 3๊ฐ€์ง€ ๊ถŒํ•œ 6 2.2.2 VTS์˜ ์ผ๋ฐ˜์  ๊ด€์ œ์ ˆ์ฐจ 7 2.2.3 VTS์˜ 3๊ฐ€์ง€ ์ œ๊ณต ์„œ๋น„์Šค 8 2.3 ์„ ๋ฐ•์กฐ์šฐ ์ƒํ™ฉ์˜ ์œ„ํ—˜๋„ ํ‰๊ฐ€๋ชจ๋ธ 10 2.3.1 ํ‰๊ฐ€๋ชจ๋ธ ์ ์šฉ์˜ ํ•„์š”์„ฑ 10 2.3.2 ํ•ด์ƒ๊ตํ†ต ์œ„ํ—˜ ํ‰๊ฐ€ ๋ชจ๋ธ 11 3. ๋ถ€์‚ฐํ•ญ VTS ๊ด€์ œ๊ตฌ์—ญ ๋ถ€๊ทผ ๊ตํ†ตํ˜„ํ™ฉ ์กฐ์‚ฌ ๋ถ„์„ 15 3.1 ์šฐ๋ฆฌ๋‚˜๋ผ ํ•ญ๋งŒ์˜ ์„ ๋ฐ• ์ž…ใƒป์ถœํ•ญ ํ˜„ํ™ฉ ์กฐ์‚ฌ ๋ถ„์„ 15 3.2 ์šฐ๋ฆฌ๋‚˜๋ผ ํ•ญ๋งŒ์˜ ํ•ด์–‘์‚ฌ๊ณ  ์กฐ์‚ฌ ๋ถ„์„ 17 3.3 ๋ถ€์‚ฐํ•ญ VTS ๊ด€์ œ๊ตฌ์—ญ ๋ถ€๊ทผ ์ง€๋ฆฌ์  ํ™˜๊ฒฝ ์กฐ์‚ฌ 20 3.4 ๋ถ€์‚ฐํ•ญ VTS ๋ถ€๊ทผ ํ•ด์—ญ ํ•ด์ƒ๊ตํ†ต ํ๋ฆ„ ๋ถ„์„ 20 4. ๋ถ€์‚ฐํ•ญ VTS ๊ด€์ œ๊ตฌ์—ญ ๋ถ€๊ทผ ์œ„ํ—˜์ƒํ™ฉ์˜ ๊ด€์ œ๊ฐœ์ž…์‹œ๊ธฐ ์กฐ์‚ฌ ๋ถ„์„ 22 4.1 ๋ถ€์‚ฐํ•ญ VTS์˜ ๊ด€์ œํ˜„ํ™ฉ ์กฐ์‚ฌ ๋ถ„์„ 22 4.1.1 ๋ถ€์‚ฐํ•ญ VTS์˜ ๊ด€์ œ๊ตฌ์—ญ 22 4.1.2 ๋ถ€์‚ฐํ•ญ VTS ๊ด€์ œ์‚ฌ ๋‹น์ง ์ฃผ๊ธฐ ์กฐ์‚ฌ 24 4.1.3 ๋ถ€์‚ฐํ•ญ VTS ๊ด€์ œ์‚ฌ ๋‹น์ง ์ค‘ ์œ„ํ—˜ ๋ฐœ์ƒ์ƒํ™ฉ ์„ค๋ฌธ์กฐ์‚ฌ 25 4.2 ์œ„ํ—˜์ƒํ™ฉ ์‹๋ณ„์„ ์œ„ํ•œ ๋ถ€์‚ฐํ•ญ VTS ๊ต์‹  ๋ถ„์„ 28 4.2.1 ์„ ๋ฐ•์ด VTS๋ฅผ ํ˜ธ์ถœํ•œ ๊ฒฝ์šฐ์˜ ๊ต์‹ ๋ถ„์„ 30 4.2.2 VTS ๋ฐ ์„ ๋ฐ• ๊ฐ„ ๊ต์‹ ๋‚ด์šฉ ๋นˆ๋„ ๋ถ„์„ 33 4.2.3 ์„ ๋ฐ• ๊ฐ„ ๊ต์‹ ๋‚ด์šฉ ๋นˆ๋„ ๋ถ„์„ 34 4.3 ์œ„ํ—˜์กฐ์šฐ์ƒํ™ฉ์˜ ๊ด€์ œ๊ฐœ์ž… ์‹œ๊ธฐ ์กฐ์‚ฌ ๋ถ„์„ 36 4.3.1 ์œ„ํ—˜๋„ ํ‰๊ฐ€๋ฅผ ํ†ตํ•œ ๊ด€์ œ๊ฐœ์ž… ์‹œ๊ธฐ ๋ถ„์„ 36 4.3.2 ์กฐ์šฐ์ƒํ™ฉ๋ณ„ ๊ด€์ œ๊ฐœ์ž… ์‹œ๊ธฐ ๋ถ„์„ 42 4.3.3 ๊ด€์ œ๊ฐœ์ž… ์‹œ๊ธฐ์˜ ๊ฐ€์ด๋“œ๋ผ์ธ ์ œ๊ณต 47 5. ๊ฒฐ ๋ก  48 ์ฐธ๊ณ ๋ฌธํ—Œ 50 ๋ถ€ ๋ก 5

    ํšจ์œจ์ ์ธ ๊ฐ์ฒด ํƒ์ƒ‰์— ๊ธฐ๋ฐ˜ํ•œ XML ์งˆ์˜ ์ตœ์ ํ™”

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    Thesis (doctoral)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์ „๊ธฐยท ์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€ ์ปดํ“จํ„ฐ๊ณตํ•™๊ณผ,2002.Docto

    Rapid identification of coxsackievirus A24 variant by molecular serotyping in an outbreak of acute hemorrhagic conjunctivitis

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    Thesis(master`s)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์˜ํ•™๊ณผ ๋‚ด๊ณผํ•™์ „๊ณต,2004.Maste

    ๋…ผ ๅœŸๅฃคไธญ quinclorac์˜ ๅธ็€, ่„ซ็€ ๋ฐ ็งปๅ‹•ๆ€ง

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