11 research outputs found

    ์ตœ์ ์˜ ํ„ฐ์น˜ ๋™์ž‘ ์„ค๊ณ„๋ฅผ ์œ„ํ•œ ์ธ๊ฐ„ ์„ฑ๋Šฅ ๋ชจํ˜• ๊ฐœ๋ฐœ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› ๊ณต๊ณผ๋Œ€ํ•™ ์‚ฐ์—…๊ณตํ•™๊ณผ, 2017. 8. ์œค๋ช…ํ™˜.Touch interface has evolved into dominant interface system for smartphones over the last 10 years. This evolutionary process has been applicable not only to the smartphone, but also to small hand-held smart devices like portable game consoles and tablet devices. Even further, the most recent Microsoft Windows operating system supports both traditional point and click interface as well as touch interface for broader coverage of OS on digital devices. Identifying factors contributing the human performance on touch interface system has been studied by wide range of researchers globally. Designers and manufacturers of smart devices with touch interface system could benefit from the findings of these studies since they may provide opportunities to design and implement better performing and more usable product with competitive edge over competitors. In this study, we investigated factors affecting human performance on touch interface systems to establish practical design guidelines for designers and manufacturers of smart devices with touch interface system. The first group of factors is demography related variables such as gender, regions and age. The second group of factors is interaction related variables such as number of hands involved in interacting with touch system โ€“ one handed versus two handed postures. Finally and most importantly, design-related variables such as sizes, shapes or locations of touch targets are investigated. Our main goal of this study is to identify what are the most affecting factors to human performance of touch interface systems and establish mathematical modeling among them. Developed performance modeling will be leveraged to estimate expected human performance without conducting usability testing on given touch interface system. Once demography, interaction and design related variables are given, we will be able to propose expected performance level by inputting those variables into the established model, thus will contribute to the optimal design practice. Touch gestures considered in this study are tap touch, move touch and flick touch, which are the most widely used touch gestures in designing and implementing touch interface system. We have recruited 259 subjects from 4 major metropolitan areas across 3 different countries โ€“ New York, San Francisco, London and Paris and conducted controlled laboratory experiment. In order to assess human performance of each touch gesture, we have defined individual performance measures of each gesture such as task completion time, velocity, throughput introduced by Fitts law (Fitts, 1954), variance/accuracy ratio introduced by Chan & Childress (1990), accuracy or offset tendency from a desired line of target. By investigating these performance measures, we could come up with design guidelines about design specifications such as size and movement direction as well as qualitative insights on how touch gestures are different across all the factors we have gathered from the experimental setup. Design strategies and guidelines as well as human performance modeling will contribute to develop effective and efficient touch interface systems.Introduction 1 1.1Background 1 1.2Research questions 2 1.3Document Outline 3 Literature reviews 5 2.1Potential variables affecting touch interface 5 2.2Gestures used in touch interface design 6 2.3How people hold mobile devices 9 2.4Design for thumbs 13 2.5Touch target size guidelines 14 2.6Estimating touch sizes 17 2.7Human performance models 20 2.8Human performance by gender and age 27 2.9Thumb-based touch interaction 29 2.10Models of human motor control 32 Tap touch experiment 37 3.1Introduction 37 3.2Methods 40 3.2.1 Task design 40 3.2.2 Experimental design 41 3.2.3 Subjects 42 3.2.4 Data analysis method 43 3.3Results 45 3.3.1 Normality check 45 3.3.2 Variables affecting task completion time on tap touch 47 3.3.3 Variables affecting distance to target on tap touch 55 3.3.4 Variables affecting angle from positive x-axis to touch point on tap touch 62 3.3.5 Variables affecting speed accuracy ratio on tap touch 68 3.4Conclusion and discussion 75 3.4.1 Speed accuracy trade off 75 3.4.2 Implications on angle from X axis 78 3.4.3 Leveraging performance prediction models 79 3.4.4 Recommended design strategies 80 3.4.5 Tap target size recommendation 81 Move touch experiment 85 4.1Introduction 85 4.2Methods 88 4.2.1 Task design 88 4.2.2 Experimental design 89 4.2.3 Subjects 90 4.3Data analysis method 91 4.3.1 Data handling 92 4.3.2 Result 92 4.3.3 Normality check 92 4.3.4 Variables affecting task velocity on move touch 94 4.3.5 Variables affecting accuracy of initial touch on move touch 105 4.3.6 Variables affecting accuracy of final release on move touch 113 4.3.7 Variables affecting throughput on move touch 121 4.4Conclusion and discussion 130 4.4.1 Design strategy for one hand versus two hands 130 4.4.2 Design strategy on moving direction 131 4.4.3 Design strategy on object sizes 132 4.4.4 Leveraging performance prediction models 132 Flick touch experiment 135 5.1Introduction 135 5.2Method 137 5.2.1 Task design 137 5.2.2 Experimental design 137 5.3Data analysis method 139 5.3.1 Data handling 140 5.4Results 140 5.4.1 Normality check 140 5.4.2 Variables affecting task completion time on flick touch 142 5.4.3 Variables affecting travel distance on flick touch 148 5.4.4 Variables affecting angle on flick touch 154 5.4.5 Variables affecting offset Y on flick touch 159 5.5Conclusion and discussion 164 5.5.1 Design strategy on demography and interaction related variables for flick movement 165 5.5.2 Design strategy on design-related variables for flick movement 166 5.5.3 Leveraging performance prediction models 167 Conclusion 169 6.1Research goals 169 6.2Summary of findings 170 6.3Performance prediction models 172 6.4Limitations and future studies 172 Bibliography 175 Abstract (in Korean) 186Docto

    High-resolution Observation of Nucleation and Growth Behavior of Nanomaterials on Graphene

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์žฌ๋ฃŒ๊ณตํ•™๋ถ€, 2014. 2. ๊น€๋ฏธ์˜.Studying nucleation and growth has been one of the major goals in materials science. Fundamental understanding of initial growth is essential for fabrication of nanomaterials with desired physical properties. Consequently, atomic level investigation on as-grown nuclei and local atomic arrangements around defects is required. Such high-resolution study along with crystallographic analysis could be performed using transmission electron microscopy (TEM). Here, we report on atomic-resolution observation of initial growth behavior using TEM by growing nanomaterials directly on graphene. Graphene exhibiting excellent electron beam transparency and high mechanical strength is an ideal supporting layer for TEM measurements by minimizing the background signal from the underlying membrane. In addition to merely sustaining nanomaterials as a support, graphene can be further used as a substrate for nanomaterials growth. The crystalline nature of graphene along with its electron beam transparency ultimately enables direct imaging of nanomaterials and allows us to systematically investigate the initial growth mechanisms. Using direct growth and imaging method, we could clearly observe the initial states of Zinc oxide (ZnO) nanomaterials. This enabled the observation of the transition in crystal structure of ZnO nuclei along with their orientational relationship with graphene. Furthermore, formation of various defects during nanomaterial growth could be clearly visualized with atomic-resolution. More generally, we believe that this simple technique may be readily expanded to investigate the growth mechanisms of many other nanomaterials on various two-dimensional layered substrates.Chapter 1 Introduction 1 1.1 Importance of studying the initial growth behavior of nanomaterials 1 1.2 Materials of interest 10 1.2.1 ZnO 10 1.2.2 Graphene 12 Chapter 2 Literature Survey 17 2.1 Direct crystal growth on prefabricated thin membranes for TEM measurements 17 2.2 Graphene as a supporting layer for TEM measurements 23 Chapter 3 Experimental Method 30 3.1 Growth of CVD graphene 30 3.2 Transfer of CVD graphene onto a TEM grid 31 3.3 Growth of ZnO nanomaterials on graphene placed on a TEM grid 35 3.4 Structural characterization of ZnO nanomaterials 35 3.4.1 SEM 35 3.4.2 TEM 36 3.5 First principles calculations 39 Chapter 4 Results and Discussions 40 4.1 Feasibility of the experimental technique for ZnO growth and TEM measurements 40 4.2 Overall growth behavior of ZnO nanomaterials on graphene 43 4.2.1 Nucleation and cluster growth stages 43 4.2.2 Postnucleation stages: coalescence 45 4.2.3 Postnucleation stages: formation of epitaxial relationship 46 4.3 Crystal structure of ZnO in the initial stage of growth 51 4.3.1 Formation of rocksalt ZnO structure 51 4.3.2 Nucleation barrier in heteroepitaxial growth 52 4.4 Disorder in the atomic arrangements around defects 58 4.5 Diverse applicability of the experimental technique for the initial growth study: ZnO nanomaterials on h-BN 63 4.5.1 Hexagonal boron nitride 63 4.5.2 Initial growth behavior of ZnO nanomaterials on h-BN 64 Chapter 5 Conclusions 73 References 74 Abstract 81Maste

    ๊ฐœ์„ ๋œ ํˆฌ๊ณผ์ „์žํ˜„๋ฏธ๊ฒฝ ๋ถ„์„๋ฒ•์„ ์ด์šฉํ•œ ์ด์ฐจ์› ๋ฌผ์งˆ ์œ„์—์„œ์˜ ํ™”ํ•ฉ๋ฌผ ๋ฐ˜๋„์ฒด ๋‚˜๋…ธ๊ตฌ์กฐ๋ฌผ์˜ ๊ฒฐ์ •์„ฑ์žฅ ๋ฉ”์ปค๋‹ˆ์ฆ˜ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› ๊ณต๊ณผ๋Œ€ํ•™ ์žฌ๋ฃŒ๊ณตํ•™๋ถ€, 2017. 8. ๊น€๋ฏธ์˜.Atomically thin layered crystals isolated by mechanical exfoliation method have exhibited new physical properties and provided novel applications. Moreover, hybrid structures of these 2-dimensional (2-D) layered materials with semiconductor thin films and nanostructures offer additional functionalities, such as flexibility and transferability, thereby greatly extending the applicability to the electronic and optoelectronic devices. Accordingly, many efforts have focused on the growth of nanomaterials using 2-D materials as substrates. In order to fabricate such nanomaterials with desired shapes and physical properties, the study on the initial growth mechanisms, such as nucleation, nuclei growth, and orientational relationship with substrate, should be accompanied in detail. This work mainly focuses on exploring the growth mechanisms of compound semiconductor nanomaterials on graphene, as a representative material among various 2-D layered materials, using transmission electron microscopy (TEM). In order to avoid unintentional damages arising from conventional TEM sample preparation processes, direct growth and observation method was developed to observe nanomaterials at the early growth stages. In this method, electron-beam transparent graphene was exploited as a supporting layer for TEM measurements as well as a substrate for nanomaterials growth. Compound semiconductor nanomaterials including ZnO, InAs, and GaAs were grown on graphene which had been transferred onto a TEM grid, followed by TEM measurements conducted without TEM sample preparation processes. Reflection high-energy electron diffraction (RHEED) transmission mode was also employed to analyze the structural information of nanostructures in real time during the growth. Contrary to its conventional usage in reflection mode, RHEED was used in transmission mode. This new technique allows us to obtain diffraction patterns containing the structural information of nanomaterials, which is analogous to the principle of electron diffraction in TEM. Using these newly developed methods, the growth mechanisms of compound semiconductor nanomaterials were thoroughly investigated. First, the growth behavior of ZnO nanomaterials was clearly observed with atomic-resolution and high-sensitivity using a graphene template for the direct growth and observation method. This method successfully disclosed the growth behavior of ZnO nanomaterials on graphene, such as nucleation of ZnO cubic phase and formation of โˆ‘7 coincidence site lattice boundary, which are previously unknown. Second, the growth mechanisms of GaAs/single-layer graphene (SLG)/InAs double heterostructures were unraveled with an aid of a further improved direct growth and observation method. This study showed that InAs nanorods grown on SLG can influence on the nucleation and growth behavior of GaAs nanomaterials on the other side of SLG. Lastly, the growth behavior of InAs nanorods were investigated in real time using the RHEED transmission mode. Time-resolved observation using RHEED transmission mode revealed the transition in local growth condition from In-rich to As-rich at the very early stage of InAs nanorods growth and the strain relaxation process of GaAs/InAs coaxial nanorods during the shell layer coating.Table of contents Abstract i Table of contents iv List of Tables vii List of Figures viii CHAPTER 1 1 CHAPTER 2 9 2.1 Theory 10 2.1.1 Crystal growth: nucleation and growth 10 2.1.2 Heteroepitaxy 20 2.1.3. Van der Waals epitaxy 22 2.1.4. III-V nanorod growth mechanism: VLS growth 24 2.1.5. III-V nanorod growth mechanism: VS growth 26 2.2 Transmission electron microscopy 27 2.2.1 High-resolution TEM 27 CHAPTER 3 34 3.1 Fabrication of graphene templates 35 3.1.1 Growth of CVD graphene 35 3.1.2 Fabrication of SiNx membrane TEM grid 36 3.1.3 Graphene transfer 42 3.2 Materials growth 43 3.2.1 ZnO nanomaterials on a graphene template 43 3.2.2 GaAs/SLG/InAs double heterostructures 45 3.2.3 InAs coaxial nanorods on Si(111) and graphene 48 3.3 Materials characterization 50 3.3.1 Scanning electron microscopy 50 3.3.2 Transmission electron microscopy 50 3.3.3 Reflection high-energy electron diffraction 51 CHAPTER 4 53 4.1 Introduction 54 4.2 Direct growth and observation of nanomaterials using a graphene template 56 4.3 Feasibility of the new method for crystal growth and TEM measurements 59 4.4 Growth mechanism of ZnO nanomaterials on graphene 62 4.4.1 Nucleation 62 4.4.2 Grain boundary formation 67 4.5 Summary and outlook 71 CHAPTER 5 73 5.1 Introduction 74 5.2 Direct growth and observation of nanomaterials using a graphene and prefabricated SiNx membrane TEM grid 79 5.2.1 Prefabricated SiNx membrane TEM grid 79 5.2.2 Direct growth and observation of GaAs and InAs nanomaterials 84 5.3 Feasibility of the improved method for crystal growth and TEM measurements 86 5.4 Growth mechanism of GaAs/SLG/InAs double heterostructures 90 5.4.1 Control group: growth behavior of GaAs on SLG 90 5.4.2 Experimental group: growth behavior of GaAs on SLG/InAs 94 5.4.3 General growth mechanism of double heterostructures 103 5.5 Summary and outlook 106 CHAPTER 6 107 6.1 Introduction 108 6.2 RHEED transmission mode 110 6.3 Feasibility of RHEED transmission mode for the real-time structural analysis of nanomaterials 113 6.4 Growth mechanism of InAs nanorods and GaAs(InxGa1-xAs)/InAs coaxial nanorods 121 6.4.1 Initial growth behavior of InAs nanorods 121 6.4.2 Strain relaxation of shell layers during the epitaxial growth 128 6.4.3 InAs nanorods growth on graphene layers 134 6.5 Summary and outlook 136 CHAPTER 7 138 7.1 Summary 138 7.2 Outlook 141 REFERENCES 142 ABSTRACT (IN KOREAN) 150Docto

    Galileo's Study on Sunspots and His Argument on the Solar Rotation

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์ž์—ฐ๊ณผํ•™๋Œ€ํ•™ ํ˜‘๋™๊ณผ์ • ๊ณผํ•™์‚ฌ๋ฐ๊ณผํ•™์ฒ ํ•™์ „๊ณต,2020. 2. ํ™์„ฑ์šฑ.This paper examines how Galileo Galilei(1564-1642), a mathematician, astronomer, and philosopher from Florence, Italy, proved the rotation of the Sun. In particular, by analyzing his works Letters on the Sunspots and Discourse on Bodies in Water, this paper reveals that Galileo could reach his conclusion by introducing extra elements of the natural philosophy in addition to the elements of the mixed mathematical sciences, unlike previous studies which suggested that Galileo reached his conclusion of solar rotation only with observations of sunspots and mathematical reasoning on the location of sunspots. First of all, against the backdrop of the fluid-heaven view which had emerged as an alternative to the Aristotle-Ptolemy's universe system since the end of the 16th century, Galileo compared the Sun to the Earth and argued that the fluid-like atmosphere including sunspots surrounded the Sun. Furthermore, by applying his material theory which had been established for the purpose of determining the structures and properties of solids and fluids, Galileo reasoned that because there is no "coherence" in the fluid, the regular motion of sunspots inevitably comes from the rotation of the Sun, and because there is "affinity" between the Sun and the atmosphere, the Sun's motion is transmitted to the atmosphere. Out of this reasoning, Galileo drew his conclusion of solar rotation. As such, the primary purpose of this paper is to show that to claim the solar rotation, Galileo introduced elements of the natural philosophy, such as fluid-heaven view, the atmosphere of the Sun, and material theory, in addition to observations of sunspots and mathematical reasoning based on them. Furthermore, beyond showing that previous researchers have not faithfully read Galileo's historical records, this paper aims to point out that the hybrid of natural philosophy and mathematics, an important innovation that Galileo has made, has not been fully appreciated. The fact that previous research suggested that Galileo reached the conclusion of the solar rotation only with observation of sunspots and mathematical reasoning seems to be in line with the fact that among Galileos various works, scholars have emphasized Galileos practice as a mathematician by studying Galileo in relation to the so-called the Scientific Revolution, a period when the importance of the mixed mathematical science was increasing. As this paper shows, however, Galileo was able to draw the conclusion that the Sun rotates by introducing natural philosophical discourse besides observation and mathematical reasoning. This means that in Galileos argument for solar rotation, the strict boundaries that had existed between the two disciplines of the mixed mathematical science and natural philosophy were starting to blur. The conclusion of the solar rotation was the product of a hybrid discipline, in which Galileo crisscrossed between the two disciplines, combining elements of the mixed mathematical sciences such as mathematical reasoning with elements of the natural philosophy such as cosmology and material theory.๋ณธ ๋…ผ๋ฌธ์€ ์ดํƒˆ๋ฆฌ์•„ ํ”ผ๋ Œ์ฒด ์ถœ์‹ ์˜ ์ˆ˜ํ•™์ž ๋ฐ ์ฒœ๋ฌธํ•™์ž์ด์ž ์ฒ ํ•™์ž์˜€๋˜ ๊ฐˆ๋ฆด๋ ˆ์˜ค ๊ฐˆ๋ฆด๋ ˆ์ด(1564-1642)๊ฐ€ ์–ด๋–ป๊ฒŒ ํƒœ์–‘์˜ ์ž์ „์„ ์ฆ๋ช…ํ–ˆ๋Š”์ง€ ์‚ดํŽด๋ณธ๋‹ค. ํŠนํžˆ ๊ทธ์˜ ์ €์ž‘ ใ€Žํ‘์ ์— ๊ด€ํ•œ ํŽธ์ง€ใ€์™€ ใ€Ž๋ฌผ์†์˜ ๋ฌผ์ฒด์— ๋Œ€ํ•œ ๋…ผ์„คใ€์„ ์ค‘์ ์ ์œผ๋กœ ๋ถ„์„ํ•จ์œผ๋กœ์จ, ๊ฐˆ๋ฆด๋ ˆ์˜ค๊ฐ€ ํ‘์  ๊ด€์ธก ์ž๋ฃŒ์™€ ํ‘์ ์˜ ์œ„์น˜์— ๊ด€ํ•œ ์ˆ˜ํ•™์  ๋…ผ์ฆ๋งŒ์œผ๋กœ ํƒœ์–‘ ์ž์ „์˜ ๊ฒฐ๋ก ์— ๋„๋‹ฌํ–ˆ๋‹ค๊ณ  ๋ณธ ๊ธฐ์กด ์—ฐ๊ตฌ์™€๋Š” ๋‹ฌ๋ฆฌ ๊ทธ๊ฐ€ ๊ทธ๋Ÿฌํ•œ ์ˆ˜๋ฆฌ๊ณผํ•™์  ์š”์†Œ ์ด์™ธ์—๋„ ์—ฌ๋Ÿฌ ์ž์—ฐ์ฒ ํ•™์  ์š”์†Œ๋ฅผ ๋„์ž…ํ•ด์„œ์•ผ ํƒœ์–‘ ์ž์ „์ด๋ผ๋Š” ๊ฒฐ๋ก ์„ ๋‚ด๋ฆด ์ˆ˜ ์žˆ์—ˆ์Œ์„ ๋ฐํžŒ๋‹ค. ์šฐ์„  ๊ฐˆ๋ฆด๋ ˆ์˜ค๋Š” 16์„ธ๊ธฐ ๋ง๋ถ€ํ„ฐ ์•„๋ฆฌ์Šคํ† ํ…”๋ ˆ์Šค-ํ”„ํ†จ๋ ˆ๋งˆ์ด์˜ค์Šค ์šฐ์ฃผ์ฒด๊ณ„์˜ ๋Œ€์•ˆ์œผ๋กœ ๋ถ€์ƒํ–ˆ๋˜ ์œ ์ฒด์šฐ์ฃผ์„ค์˜ ๋ฐฐ๊ฒฝ ์•„๋ž˜, ํƒœ์–‘์„ ์ง€๊ตฌ์— ๋น„์œ ํ•˜์—ฌ ์œ ์ฒด์˜ ์„ฑ์งˆ์„ ๊ฐ€์ง„ ๋Œ€๊ธฐ๊ฐ€ ํ‘์ ์„ ํฌํ•จํ•œ ์ฑ„ ํƒœ์–‘์„ ๋‘˜๋Ÿฌ์‹ธ๊ณ  ์žˆ๋‹ค๊ณ  ์ฃผ์žฅํ–ˆ๋‹ค. ๋” ๋‚˜์•„๊ฐ€ ๊ฐˆ๋ฆด๋ ˆ์˜ค๋Š” ๊ณ ์ฒด์™€ ์œ ์ฒด์˜ ๊ตฌ์กฐ์™€ ์„ฑ์งˆ ๊ทœ๋ช…์„ ๋ชฉ์ ์œผ๋กœ ์ˆ˜๋ฆฝํ•œ ์ž์‹ ์˜ ๋ฌผ์งˆ ์ด๋ก ์„ ํƒœ์–‘ ์ž์ „ ๋…ผ์ฆ์— ์ ์šฉํ–ˆ๋‹ค. ์œ ์ฒด์—๋Š” ์‘์ง‘์„ฑ์ด ์—†์œผ๋ฏ€๋กœ ํ‘์ ์˜ ๊ด€์ธก์ƒ ๊ทœ์น™์ ์ธ ์šด๋™์ด ํƒœ์–‘์˜ ์ž์ „์œผ๋กœ๋ถ€ํ„ฐ ์˜ฌ ์ˆ˜๋ฐ–์— ์—†๊ณ  ํƒœ์–‘๊ณผ ๋Œ€๊ธฐ ์‚ฌ์ด์—๋Š” ์นœํ™”์„ฑ์ด ์กด์žฌํ•˜๋ฏ€๋กœ ํƒœ์–‘์˜ ์šด๋™์ด ๋Œ€๊ธฐ๋กœ ์ „๋‹ฌ๋˜๊ธฐ ๋•Œ๋ฌธ์— ํƒœ์–‘ ์ž์ „์˜ ๊ฒฐ๋ก ์ด ๋„์ถœ๋œ๋‹ค๊ณ  ๋ณด์•˜๋˜ ๊ฒƒ์ด๋‹ค. ์ด๋ ‡๊ฒŒ ๊ฐˆ๋ฆด๋ ˆ์˜ค๊ฐ€ ํƒœ์–‘ ์ž์ „์„ ์ฃผ์žฅํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ํ‘์ ์˜ ๊ด€์ธก ์ž๋ฃŒ์™€ ์ด์— ๊ธฐ์ดˆํ•œ ์ˆ˜ํ•™์  ๋…ผ์ฆ ์ด์™ธ์—๋„ ์œ ์ฒด์šฐ์ฃผ์„ค, ํƒœ์–‘์˜ ๋Œ€๊ธฐ, ๋ฌผ์งˆ๋ก  ๋“ฑ์˜ ์ž์—ฐ์ฒ ํ•™์  ์š”์†Œ๋ฅผ ๋„์ž…ํ–ˆ๋‹ค๋Š” ์‚ฌ์‹ค์„ ๋ณด์ด๋Š” ๊ฒƒ์ด ๋ณธ ๋…ผ๋ฌธ์˜ ์ผ์ฐจ์ ์ธ ๋ชฉ์ ์ด๋‹ค. ๋” ๋‚˜์•„๊ฐ€ ๊ธฐ์กด ์—ฐ๊ตฌ์ž๋“ค์ด ๊ฐˆ๋ฆด๋ ˆ์˜ค๊ฐ€ ๋‚จ๊ธด ์‚ฌ๋ฃŒ๋ฅผ ์ถฉ์‹คํžˆ ๋…ํ•ดํ•˜์ง€ ๋ชปํ–ˆ๋‹ค๋Š” ์ ์„ ๋„˜์–ด, ๊ฐˆ๋ฆด๋ ˆ์˜ค๊ฐ€ ์ด๋ฃฉํ•œ ์ค‘์š”ํ•œ ํ˜์‹ ์ธ ์ž์—ฐ์ฒ ํ•™๊ณผ ์ˆ˜ํ•™์˜ ์œตํ•ฉ์ด ์ถฉ๋ถ„ํžˆ ์ดํ•ด๋˜์ง€ ๋ชปํ–ˆ๋‹ค๋Š” ์‚ฌ์‹ค์„ ์ง€์ ํ•˜๋Š” ๊ฒƒ์ด ๋ณธ ๋…ผ๋ฌธ์˜ ์ด์ฐจ ๋ชฉ์ ์ด๋‹ค. ๊ธฐ์กด ์—ฐ๊ตฌ๊ฐ€ ๊ด€์ธก๊ณผ ์ˆ˜ํ•™ ๋…ผ์ฆ๋งŒ์œผ๋กœ ๊ฐˆ๋ฆด๋ ˆ์˜ค๊ฐ€ ํƒœ์–‘ ์ž์ „์ด๋ผ๋Š” ๊ฒฐ๋ก ์— ๋„๋‹ฌํ–ˆ๋‹ค๊ณ  ๋ณด์•˜๋‹ค๋Š” ์ ์€ ๊ทธ๋™์•ˆ ์ฃผ๋กœ ๊ฐˆ๋ฆด๋ ˆ์˜ค๋ฅผ ์ˆ˜๋ฆฌ๊ณผํ•™์˜ ์ค‘์š”์„ฑ์ด ์ฆ์ง„ํ•˜๋˜ ์‹œ๊ธฐ์ธ ์ด๋ฅธ๋ฐ” ๊ณผํ•™ํ˜๋ช…๊ธฐ์™€ ๊ด€๋ จํ•˜์—ฌ ๋‹ค๋ฃธ์œผ๋กœ์จ ๊ทธ์˜ ์ž‘์—…์—์„œ ๋Œ€์ฒด๋กœ ์ˆ˜ํ•™์ž๋กœ์„œ์˜ ์‹ค์ฒœ์ด ๊ฐ•์กฐ๋˜์—ˆ๋‹ค๋Š” ์‚ฌ์‹ค๊ณผ ๊ถค๋ฅผ ๊ฐ™์ดํ•œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๋ณธ ๋…ผ๋ฌธ์ด ๋ณด์—ฌ์ฃผ๋“ฏ์ด, ๊ฐˆ๋ฆด๋ ˆ์˜ค๋Š” ๊ด€์ธก๊ณผ ์ˆ˜ํ•™ ๋…ผ์ฆ ์ด์™ธ์—๋„ ์—ฌ๋Ÿฌ ์ž์—ฐ์ฒ ํ•™์  ๋‹ด๋ก ์„ ๋„์ž…ํ•ด์„œ์•ผ ํƒœ์–‘์ด ์ž์ „ํ•œ๋‹ค๋Š” ๊ฒฐ๋ก ์„ ๋„์ถœํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ด๋Š” ๊ฐˆ๋ฆด๋ ˆ์˜ค์˜ ํƒœ์–‘ ์ž์ „ ๋…ผ์ฆ ์†์—์„œ ์ˆ˜๋ฆฌ๊ณผํ•™๊ณผ ์ž์—ฐ์ฒ ํ•™์ด๋ผ๋Š” ๋‘ ๋ถ„๊ณผ ์‚ฌ์ด์— ์กด์žฌํ–ˆ๋˜ ์—„๊ฒฉํ•œ ๊ฒฝ๊ณ„์„ ์ด ํ๋ ค์ง€๊ณ  ์žˆ์—ˆ์Œ์„ ์˜๋ฏธํ•œ๋‹ค. ํƒœ์–‘์˜ ์ž์ „์ด๋ผ๋Š” ๊ฒฐ๋ก ์€ ๊ฐˆ๋ฆด๋ ˆ์˜ค๊ฐ€ ๋‘ ๋ถ„๊ณผ ์‚ฌ์ด๋ฅผ ์ข…ํšก๋ฌด์ง„ ๋„˜๋‚˜๋“ค๋ฉฐ ๊ด€์ธก ๋ฐ ์ˆ˜ํ•™์  ๋…ผ์ฆ์ด๋ผ๋Š” ์ˆ˜๋ฆฌ๊ณผํ•™์  ์š”์†Œ์™€ ์šฐ์ฃผ์„ค ๋ฐ ๋ฌผ์งˆ ์ด๋ก ๊ณผ ๊ฐ™์€ ์ž์—ฐ์ฒ ํ•™์  ์š”์†Œ๋ฅผ ์—ฎ์–ด ๋งŒ๋“ค์–ด๋ƒˆ๋˜ ํ˜ผ์ข…์  ๋ถ„๊ณผ์˜ ์‚ฐ๋ฌผ์ด์—ˆ๋˜ ๊ฒƒ์ด๋‹ค.1 ์„œ๋ก  1 2 ๋ง์›๊ฒฝ ์ œ์ž‘์—์„œ ํ‘์  ์—ฐ๊ตฌ๊นŒ์ง€: ๊ฐˆ๋ฆด๋ ˆ์˜ค ํ‘์  ์—ฐ๊ตฌ์˜ ๋ฐฐ๊ฒฝ 10 3 ํ‘์ ์˜ ์œ„์น˜์— ๊ด€ํ•œ ์ˆ˜ํ•™์  ๋…ผ์ฆ 17 4 ์œ ์ฒด์šฐ์ฃผ์„ค๊ณผ ์ง€๊ตฌํƒœ์–‘ ๋น„์œ ์— ๊ธฐ๋ฐ˜ํ•œ ํƒœ์–‘ ๋Œ€๊ธฐ ์ถ”๋ก  38 5 ๋ฌผ์งˆ๋ก ์— ๊ธฐ์ดˆํ•œ ํƒœ์–‘ ์ž์ „ ๋…ผ์ฆ 50 6 ๊ฒฐ๋ก  67 ์ฐธ๊ณ ๋ฌธํ—Œ 70Maste

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