30 research outputs found

    Rhodium-Catalyzed Carbonylative [3+2+1] Cycloaddition of Alkyne-Tethered Alkylidenecyclopropanes to Phenols in the Presence of Carbon Monoxide

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ํ™”ํ•™๋ถ€, 2014. 8. ์ •์˜๊ทผ.We have developed a novel Rh-catalyzed carbonylative [3+2+1] cycloaddition of alkyne-tethered alkylidenecyclopropanes, for the facile synthesis of bicyclic phenols in high yields. The reaction tolerated carbon and heteroatoms in the tether.Abstract 2 Introduction 4 Results and Discussion 8 Conclusion 16 Experimental Section 17 References 47 ๊ตญ๋ฌธ์ดˆ๋ก 53Maste

    Expression of bcl-2 and bax proteins in astrocytic tumors

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    ์˜ํ•™๊ณผ/์„์‚ฌ[์˜๋ฌธ] [ํ•œ๊ธ€] Apoptosis์˜ ์ค‘์š”ํ•œ ์กฐ์ ˆ์ธ์ž์ธ bcl-2์™€ bax ์œ ์ „์ž ์ค‘ bcl-2๋Š” ์ข…์–‘์„ธํฌ๋ฅผ ์„ธํฌ์ฃผ๊ธฐ์˜ G0/GI ๊ธฐ์— ์ •์ง€์‹œํ‚ค๊ฑฐ๋‚˜ APO-1/fas ํ•ญ์ฒด๋ฅผ ํ†ตํ•˜์—ฌ apoptosis๋ฅผ ์–ต์ œํ•˜๊ณ , bax๋Š” apoptos is๋ฅผ ์ด‰์ง„ํ•˜๋Š”๋ฐ ์ž‘์šฉํ•˜๋Š” ๊ฒƒ์œผ๋กœ ์•Œ๋ ค์ ธ ์žˆ๋‹ค. ๋‡Œ์ข…์–‘์—์„œ์˜ bcl-2 ๋ฐœํ˜„์— ๋Œ€ํ•œ ๋ช‡ ์—ฐ๊ตฌ ์—์„œ bcl-2์˜ ๋ฐœํ˜„์ด ์ข…์–‘์˜ ์•…์„ฑ๋„๋ฅผ ๋ฐ˜์˜ํ•˜์ง€ ๋ชปํ•˜๊ณ  ์˜ˆํ›„์™€๋„ ์—ฐ๊ด€์„ฑ์ด ์—†๋‹ค๊ณ  ๋ฐœํ‘œ๋˜ ์—ˆ์œผ๋‚˜, ์—ฐ๊ตฌ ๋Œ€์ƒ์˜ ์ˆ˜๊ฐ€ ๋„ˆ๋ฌด ์ ์–ด์„œ ๊ทธ ์˜๋ฏธ๋ฅผ ์ฐพ๊ธฐ ์–ด๋ ค์› ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ apoptosis๋Š” ์•… ์„ฑ ์ข…์–‘์˜ ์ฆ์‹์ด๋‚˜ ์–ต์ œ์— ์˜๋ฏธ๊ฐ€ ์žˆ์Œ์ด ๋ฐฑํ˜ˆ๋ณ‘์„ ๋น„๋กฏํ•œ ๋‹ค๋ฅธ ์•”์ข…์—์„œ ๋ณด๊ณ ๋˜๊ณ  ์žˆ์ง€ ๋งŒ, ๋ณ„์•„๊ต์„ธํฌ์ข…์—์„œ๋Š” apoptosis ๊ด€๋ จ ์œ ์ „์ž๊ฐ€ ์–ผ๋งˆ๋‚˜ ๋ฐœํ˜„๋˜๊ณ  ์–ด๋–ค ์ข…๋ฅ˜์˜ ์ข…์–‘ ์„ธ ํฌ์—์„œ ๋ฐœํ˜„๋˜๋Š”์ง€ ์ž˜ ์•Œ๋ ค์ ธ ์žˆ์ง€ ์•Š๋‹ค. ์ด์— ๋ณ„์•„๊ต์„ธํฌ์ข…์—์„œ apoptosis์˜ ์กฐ์ ˆ์ธ์ž์ธ bcl-2์™€ bax ์œ ์ „์ž๊ฐ€ ์–ด๋–ป๊ฒŒ ๋ฐœํ˜„๋˜๊ณ  ์ข…์–‘์˜ ์ฆ์‹ ์ง€์ˆ˜๋กœ ์‚ฌ์šฉ๋˜๋Š” Ki-67 ๋ฐœํ˜„์œจ๊ณผ ์–ด ๋–ค ๊ด€๊ณ„๊ฐ€ ์žˆ๋Š”์ง€๋ฅผ ์•Œ์•„๋ณด๊ณ , bcl-2, bax, Ki-67 ๋ฐœํ˜„์œจ๊ณผ ์ž„์ƒ ์†Œ๊ฒฌ, ๋ณ‘๋ฆฌํ•™ ์†Œ๊ฒฌ, ํ™˜ ์ž์˜ ์ƒ์กด๊ธฐ๊ฐ„ ๋“ฑ์„ ๋น„๊ตํ•˜์—ฌ ์˜ˆํ›„์ธ์ž๋กœ์„œ์˜ ์œ ์šฉ์„ฑ์— ์•Œ์•„๋ณด๊ณ ์ž ๋ณธ ์—ฐ๊ตฌ๋ฅผ ์‹œํ–‰ํ•˜์˜€๋‹ค . ์—ฐ๊ตฌ๋Œ€์ƒ์€ ์ˆ˜์ˆ ๋กœ ํ™•์ธ๋œ ๋ณ„์•„๊ต์„ธํฌ์ข… 42์˜ˆ๋ฅผ ํ›„ํ–ฅ์ ์œผ๋กœ ์กฐ์‚ฌํ•˜์˜€์œผ๋ฉฐ, WHO ๋ถ„๋ฅ˜๋ฒ•์— ๋”ฐ๋ผ 4๊ฐœ์˜ ์กฐ์งํ•™์  ๋“ฑ๊ธ‰์„ ๋‚˜๋ˆ„์—ˆ๋‹ค. ์ง„๋ฃŒ๊ธฐ๋ก๊ณผ ๋ฐฉ์‚ฌ์„ ํ•™ ๊ฒ€์‚ฌ๋ฅผ ํ†ตํ•ด์„œ ๋‚˜์ด, ์„ฑ๋ณ„, ์ข…์–‘์˜ ํฌ๊ธฐ์™€ ์œ„์น˜์— ๋Œ€ํ•˜์—ฌ ์กฐ์‚ฌํ•˜์˜€์œผ๋ฉฐ, ์ƒ์กด ์—ฌ๋ถ€๋ฅผ ํ™•์ธํ•˜์˜€๋‹ค. ํŒŒ๋ผํ•€ ํฌ๋งค์กฐ์ง ์„ ์ด์šฉํ•˜์—ฌ bcl-2, bax, Ki-67์— ๋Œ€ํ•˜์—ฌ ๋ฉด์—ญ์กฐ์งํ™”ํ•™์—ผ์ƒ‰์„ ์‹œํ–‰ํ•œ ํ›„, ๊ทธ ๊ฒฐ๊ณผ๋ฅผ SPSS (win 10.0)๋ฅผ ์ด์šฉํ•˜์—ฌ ํ†ต๊ณ„ํ•™์ ์œผ๋กœ ๋ถ„์„ํ•˜์˜€์œผ๋ฉฐ, ์ƒ์กด์œจ๊ณผ์˜ ๊ด€๊ณ„๋Š” Kaplan-Meier ๋ถ„ ์„์„ ์ด์šฉํ•˜์˜€๋‹ค. ๋ณ„์•„๊ต์„ธํฌ์ข… 42์˜ˆ ์ค‘ 1๋“ฑ๊ธ‰์ด 2์˜ˆ, 2๋“ฑ๊ธ‰์ด 10์˜ˆ, 3๋“ฑ๊ธ‰์ด 10์˜ˆ, 4๋“ฑ๊ธ‰์ด 20์˜ˆ์˜€๋‹ค. bc l-2 ๋‹จ๋ฐฑ์— ๋Œ€ํ•œ ๋ฉด์—ญ์กฐ์งํ™”ํ•™ ์—ผ์ƒ‰ ๊ฒฐ๊ณผ 2๋“ฑ๊ธ‰์—์„œ 1์˜ˆ, 4๋“ฑ๊ธ‰์—์„œ 1์˜ˆ๋งŒ์ด ์–‘์„ฑ์œผ๋กœ, ์ „์ฒด 42์˜ˆ ์ค‘ 2์˜ˆ (4.76%)์—์„œ๋งŒ ์–‘์„ฑ์ด์—ˆ๋‹ค. bax ๋‹จ๋ฐฑ์— ๋Œ€ํ•œ ๋ฉด์—ญ์กฐ์งํ™”ํ•™ ์—ผ์ƒ‰ ๊ฒฐ๊ณผ๋Š” ์ข…์–‘์„ธํฌ์˜ ์„ธํฌ์งˆ์— ๋ฏธ๋งŒ์„ฑ์œผ๋กœ ์—ผ์ƒ‰๋˜์—ˆ๋Š”๋ฐ, ์ „์ฒด 42์˜ˆ ์ค‘ 35์˜ˆ (83.3%)๊ฐ€ ์–‘์„ฑ์œผ๋กœ ๋†’์€ ๋ฐœํ˜„์œจ์„ ๋ณด์˜€์œผ๋‚˜ ๋“ฑ๊ธ‰๊ฐ„์— ๋ฐœํ˜„์œจ์˜ ์ฐจ์ด๋Š” ์—†์—ˆ๋‹ค. Ki-67์— ๋Œ€ํ•œ ๋ฉด์—ญ์กฐ์งํ™”ํ•™์—ผ ์ƒ‰ ๊ฒฐ๊ณผ labeling index(LI)๋Š” 1๋“ฑ๊ธ‰์ด 60%, 2๋“ฑ๊ธ‰์ด 45.5%, 3๋“ฑ๊ธ‰์ด 139.8%, 4๋“ฑ๊ธ‰์ด 28 0.85%๋กœ ์ข…์–‘์˜ ๋“ฑ๊ธ‰์ด ๋†’์•„์งˆ์ˆ˜๋ก Ki-67 LI๊ฐ€ ๋†’์•˜๋‹ค (p<0.05). ๊ทธ๋Ÿฌ๋‚˜ bcl-2, bax ๋‹จ๋ฐฑ ์˜ ๋ฐœํ˜„๊ณผ ๋‚˜์ด, ์„ฑ๋ณ„, ์ข…์–‘์˜ ์œ„์น˜, ํฌ๊ธฐ, ์กฐ์งํ•™์  ๋“ฑ๊ธ‰๊ณผ๋Š” ํ†ต๊ณ„ํ•™์ ์œผ๋กœ ์œ ์˜ํ•œ ์ฐจ์ด ๋Š” ์—†์—ˆ๋‹ค. Kaplan-Meier analysis์—์„œ log rank test์ƒ bcl-2, bax์˜ ๋ฐœํ˜„์—ฌ๋ถ€์— ๋”ฐ๋ฅธ ์ƒ์กด์œจ๋„ ์œ ์˜ํ•œ ์ฐจ์ด๋Š” ์—†์—ˆ์œผ๋‚˜, ki-67 LI๋ฅผ 92.5%๋ฅผ ๊ธฐ์ค€์œผ๋กœ 92.5% ์ด์ƒ์ธ ๊ฒฝ์šฐ ํ‰๊ท  ์ƒ์กด๊ธฐ๊ฐ„์ด 15.2๊ฐœ์›”์ด๋‚˜, 92.5% ์ดํ•˜์ธ ๊ฒฝ์šฐ 45.5๊ฐœ์›”๋กœ ์˜๋ฏธ์žˆ๊ฒŒ ์ฐจ์ด๊ฐ€ ์žˆ์—ˆ๋‹ค (p<0. 05). ๊ฒฐ๋ก ์ ์œผ๋กœ ๋ณ„์•„๊ต์„ธํฌ์ข…์—์„œ apoptosis ์กฐ์ ˆ์ธ์ž ์ค‘ bcl-2๋Š” ๊ฑฐ์˜ ๋ฐœํ˜„๋˜์ง€ ์•Š์•˜๊ณ , ba x ๋‹จ๋ฐฑ์˜ ๊ฒฝ์šฐ ๋ฐœํ˜„์œจ์€ ๋†’์•˜์œผ๋‚˜ ์˜ˆํ›„์ธ์ž๋กœ์„œ์˜ ์˜๋ฏธ๋Š” ์—†์—ˆ๋‹ค. ์˜คํžˆ๋ ค Ki-67 LI๊ฐ€ ๋ณ„ ์•„๊ต์„ธํฌ์ข…์˜ ์กฐ์งํ•™์  ๋“ฑ๊ธ‰๊ณผ ๊ด€๋ จํ•˜์—ฌ ์ข…์–‘์˜ ์•…์„ฑ๋„์™€ ์ฆ์‹๋Šฅ์„ ์ถ”์ •ํ•  ์ˆ˜ ์žˆ๊ณ , ํ™˜์ž ์˜ ์˜ˆํ›„๋ฅผ ์˜ˆ์ธกํ•  ์ˆ˜ ์žˆ๋Š” ์˜๋ฏธ์žˆ๋Š” ์ธ์ž๋กœ ์ œ์‹œ๋˜์—ˆ๋‹ค. -------------------- ํ•ต์‹ฌ๋˜๋Š” ๋ง : ๋ณ„์•„๊ต์„ธํฌ์ข…, bcl-2, bax, Ki-67, ์˜ˆํ›„ ์ธ์ž Neuroepithelial tumors account for 50 to 60 per cent of primary intracranial tumors in adults. Astrocytic tumors constitute about 75 per cent of gliomas. Histologic grade significantly influences survival and prognosis among patients with astrocytic tumors. But progression from initial low grade to high grade on repeat tissue sampling usually confused us. Another prognostic factor of astrocytic tumors is an estimation of proliferative index in tumor cells. Bcl-2 and bax protooncogene regulate apoptosis. Bcl-2 prolongs survival by arresting cells in the G0/G1 phase of the cell cycle or inhibiting of APO-1/Fas antibody-mediated apoptosis. Bax generally promotes apoptosis. In brain tumor, it has been published that bcl-2 expression was not related malignancy and prognosis. Because the number of the study case was limited, there were some pitfalls. We studied forty-two cases retrospectively in order to investigate the relationship between the immunohistochemical expression of bcl-2 & bax protein in astrocytic tumors and prognosis. We classified the astrocytic tumors according to WHO grading system and reviewed the clinical information and survival time. The sections were taken from surgically resected paraffin-embedded tissue and performed immunohistochemical stains (ABC method) for bcl-2, bax, and Ki-67. Ki-67 labeling index (LI) were expressed as percentile of positively stained nuclei to 1,000 neoplastic cells. Forty-two cases of astrocytic tumors were grade I (2 cases), grade II (10 cases), grade III (10 cases), and grade IV (20 cases) according to WHO grading system. The immunohistochemical stain for bcl-2 revealed a positivity in only two (4.76%) among forty-two cases. The immunostain for bax protein was positive in 35 cases (83.3%). However, the correlation between bcl-2 & bax protein expression and age, sex, tumor location, size, and histologic grade was not found. By Kaplan-Meier analysis, bcl-2 & bax protein expression and survival time in astrocytic tumors was not statistically significant in log rank test (p>0.05). There were statistically significant differences between Ki-67 LI and histologic grade and between Ki-67 LI and survival time, respectively (p<0.05). But the relationship of Ki-67 labeling index (LI) and age, sex, tumor location, and size was not present. As a conclusion, bcl-2 and bax protein as apoptosis-regulating factor were not significant, whereas Ki-67 LI was suggested as a significant prognostic factor, associated with histologic grade and survival time of astrocytic tumors.ope

    Strengthening Mechanism of CFRPs through Incorporation of Halloysite Nanotubes by Electrophoretic Deposition Process

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    Fiber reinforced polymers (FRPs) are extensively utilized in various industries such as aerospace, aviation, automotive, marine, and civil construction, due to their exceptional stiffness-to-weight and stiffness-to-weight ratio. However, unlike isotropic materials such as metals and ceramics, the mechanical properties of FRPs in the transverse and through-thickness directions are inherently inferior to those in the primary direction due to their orthogonal anisotropic nature. The interfacial and interlaminar strength and toughness of FRPs can pose significant limitations to their performance and application breakthrough. Incorporating nano-additives has been demonstrated as an effective method for enhancing the interfacial and interlaminar properties of FRPs in recent decades. However, most studies have conventionally involved the random dispersion of nano-additives in the matrix, and a comprehensive investigation into the distribution conditions remains limited. The primary aim of this dissertation is to explore the interfacial toughening mechanism through the innovative hierarchical distribution of nanoclays, by experimental. To achieve this, various halloysite nanotubes (HNTs) with distinct structures were successfully synthesized using multiple techniques, and a hierarchical distribution was achieved by employing the electrophoresis deposition (EPD) technique. The study also delves into investigating the optimal EPD parameters and the potential agglomeration problem during the Vacuum-assisted Resin Transfer Molding (VaRTM) fabrication process, which is essential for developing an efficient and effective approach to enhancing the interfacial properties of nanocomposites. The study carefully selected the voltage range for electrophoretic deposition (EPD) to be between 6 and 12 V, which corresponds to the nanoparticle deposition working range. The carbon fabric was modified using this process to enhance its through-thickness strength, and the resulting modified fabric was incorporated into CFRP composites using vacuum-assisted resin transfer molding (VaRTM). This approach enabled precise control of several deposition parameters to achieve optimal distribution of HNTs on the carbon fabric surface. The mechanical properties of the modified CFRP composites were evaluated, and it was observed that the EPD-modified CFRPs exhibited superior mechanical properties compared to neat CFRPs. The study also found that the highest values were obtained at 0.7 wt.% and 6 V, indicating the feasibility of the EPD process and the well-dispersed morphology of HNTs, as confirmed by SEM-EDS analysis. The zeta potential plays a crucial role in determining the colloidal stability of nanoparticle suspensions and their suitability for electrophoretic deposition (EPD). The magnitude and sign of the zeta potential affect the repulsive forces between particles, which in turn determine their aggregation and sedimentation behavior. EPD typically requires a high zeta potential to ensure stable suspensions and promote uniform deposition of particles. In this investigation, the stability of the HNT dispersion was evaluated as a function of nanoparticle concentration, and the optimal dispersion range was identified through systematic experimentation. Subsequently, an HNT-reinforced composite material was synthesized by identifying the optimal range of dispersion stability and evaluating the impact strength and fracture mechanism of the interface. The study found that the HNT dispersion exhibited optimal stability in the pH range of 6.6-6.8, resulting in the highest degree of dispersion and impact strength of the composite material. The highest impact strength was achieved at a concentration of 0.7 wt.%. The interfacial dispersion of the EPD-fibers was confirmed using scanning electron microscopy and dispersive X-ray spectroscopy (SEM-EDS). The implementation of hierarchical distributed nanoclays proved effective in enhancing the interlaminar strength and toughness of FRPs by selectively reinforcing the vulnerable interfacial region. The findings and methods presented in this dissertation can be applied and cited in future research involving other nanoclays/FRPs systems.Chapter 1: Background and Objectives 1 1-1 Background and Significance 1 1-2 Literature Review 12 1-3 Objectives 15 Chapter 2: Introduction 17 2-1 Introduction 17 2-1-1 Composite Materials 17 2-1-2 Classifications of the Composite Materials 18 2-1-3 Advantages, Necessity, and Benefits of the Composite Materials 19 2-1-4 Fiber Reinforced Polymer Composites 23 2-1-5 Manufacturing of the Fiber Reinforced Polymer Composites 34 Chapter 3: Optimization of HNT Nanoparticle Distribution based on EPD Process in Epoxy-CFRP Composites 46 3-1 Introduction 47 3-2 Experimental Details 50 3-2-1 Materials 50 3-2-2 Electrophoresis Deposition (EPD) Method for HNTs Deposition 50 3-3 Specimensโ€™ Preparation 53 3-4 Mechanical Tests 55 3-4-1 Short Beam Shear Test 55 3-4-2 Flexural Test 55 3-5 Results and Discussion 57 3-5-1 Dispersion Mechanism and FT-IR 57 3-5-2 Short Beam Shear Properties of the Composite 59 3-5-3 Flexural Properties of Composite 64 3-6 Conclusions 65 Chapter 4: Improvement of Mechanical Property on HNT Modified CFRP composites through Optimization of HNT based EPD Process 66 4-1 Introduction 67 4-2 Experimental Details 70 4-2-1 Materials 70 4-2-2 Electrophoresis Deposition (EPD) Method for HNTs Deposition 70 4-2-3 Specimensโ€™ Preparation 71 4-3 Mechanical Tests 72 4-3-1 Short Beam Shear Test 72 4-3-2 Flexural Test 73 4-3-3 Uniaxial Tensile Test 75 4-4 Results and Discussion 76 4-4-1 Short Beam Shear Properties of the Composite 76 4-4-2 Flexural Properties of Composite 78 4-4-3 Tensile strength of the composite 80 4-5 Conclusions 83 Chapter 5: Impact Strength and Fracture Behavior of Halloysite Nanotube (HNT)-Modified Carbon Fiber-Reinforced Polymers (CFRP) based on the Electrophoretic Deposition (EPD) Process 84 5-1 Introduction 86 5-2 Experimental Works 88 5-2-1 Zeta Potential Analysis 89 5-2-2 Uniaxial Tensile Test 90 5-2-3 Izod Impact Test 90 5-3 Results and Discussions 92 5-3-1 Zeta Potential 92 5-3-2 Tensile Strength of the Composite 94 5-3-3 Izod Impact Strength 98 5-4 Conclusions 103 Chapter 6: Investigating the Impact of Extreme Environments on the Fracture Toughness of Nanoparticle-Reinforced Composites 104 6-1 Introduction 105 6-2 Experimental Works 108 6-2-1 Materials 108 6-2-2 Fiber and HNTs Pre-treatment 109 6.2.3 HNTs Distribution by EPD 110 6-2-4 Fabrication of HNTs Incorporated CFRPs 111 6-2-5 Methodologies of Mechanical Tests 114 6-2-6 Mechanism that Effects on the Properties after Fiber Exposed to the Humidity Condition 118 6-3 Results and Discussion 119 6-3-1 Mode I Fracture Toughness 119 6-3-2 Mode II Fracture Toughness 127 6-4 Conclusions 135 Chapter 7: Overall Conclusions 136 References 141Docto

    Study on Evaluation of Mechanical and Environmental Properties of Slag Fiber Reinforced Composites

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    Industrial development has caused problems such as energy depletion and environmental pollution. As a result, it is necessary to develop new materials that can cope with alternative energy and deteriorating environment, and to promote light weighting of structural materials and eco-friendly materials. Therefore, the use of fiber reinforced polymers (Fiber Reinforced Polymer) is increasing rapidly to improve the high energy requirements needed to produce the product. In this study, mechanical properties, composition and surface analysis were carried out through the manufacture of slag fiber-reinforced composite materials to be used to replace basalt fiber-reinforced composite materials applicable to marine structures, ships and simple components that could be exposed to marine environment. The surface conditions were observed through Scanning Electron Microscope (SEM) in order to analyze the resulting surface conditions, with each 720 hours of immersion in the fresh water and seawater environment, and the change in mechanical strength according to the amount of material absorbed over the time of the erosion. Following fresh-water and sea-water absorption, the rate of absorption in the sea was small, but higher than in the desalination environment, and mechanical strength was also small in the sea-water environment, but also reduced rates. In addition, in acid/base environmental tests, the composition changes and surfaces over the bedding time were analyzed through the Scanning Electron Microscopy-Energy Dispersive X-ray Spectrometer (SEM-EDS). It is possible to predict the applicability in the polar environment. The decrease in tensile strength in the sea was small but large through the absorption of fresh water and sea water, and the acid and salt environmental tests showed a significant decrease in tensile strength in the mountain environment. Through this study, the mechanical characteristics of basalt fiber reinforced composite materials and slag fiber reinforced composite materials based on fresh-water, sea-water absorption days and acid/base environmental tests will be examined and the potential for use of eco-friendly fiber reinforced composite materials applied to marine structures, ship and marine environmental sectors and polar environments will be expected.List of Tables โ…ฒ List of Figures โ…ณ Abstract โ…ต 1. ์„œ๋ก  1 1.1 ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ 1 1.2 ์œ ๋ฆฌ ์„ฌ์œ  5 1.3 ํƒ„์†Œ ์„ฌ์œ  7 1.4 ํ˜„๋ฌด์•” ์„ฌ์œ  11 1.5 ์—ฐ๊ตฌ ๋ชฉ์  14 2. ์žฌ๋ฃŒ ๋ฐ ์‹คํ—˜ ๊ณผ์ • 15 2.1. ์žฌ๋ฃŒ ์ค€๋น„ 15 2.1.1. ์Šฌ๋ž˜๊ทธ ์„ฌ์œ  ๊ฐ•ํ™”์žฌ๋ฃŒ 15 2.1.1. ์—ํญ์‹œ ๊ณ ๋ถ„์ž ๊ธฐ์ง€์žฌ๋ฃŒ 20 2.2. ์‹คํ—˜ ๊ณผ์ • 21 2.2.1. ์ˆ˜๋ถ„ ํก์Šต 21 2.2.2. ์‚ฐ/์—ผ๊ธฐ ํ™˜๊ฒฝ 27 2.2.3. ํ‘œ๋ฉด ๋ถ„์„ 29 2.2.4. ์ธ์žฅ๊ฐ•๋„ 30 3. ์‹คํ—˜ ๊ฒฐ๊ณผ ๋ฐ ๊ณ ์ฐฐ 35 3.1. ๋‹ด์ˆ˜ ๋ฐ ํ•ด์ˆ˜ ํก์Šต ํŠน์„ฑ 35 3.2. ์‚ฐ/์—ผ๊ธฐ ํ™˜๊ฒฝ ํŠน์„ฑ 37 3.3. ํ‘œ๋ฉด ํŠน์„ฑ 44 3.4. ์ธ์žฅ ํŠน์„ฑ 46 4. ๊ฒฐ๋ก  50 ๊ฐ์‚ฌ์˜ ๊ธ€ 52 ์ฐธ๊ณ ๋ฌธํ—Œ 53Maste

    ์ปฌ๋Ÿฌ ์˜์ƒ๊ณผ Color Filter Array ์˜์ƒ์˜ ๋ฌด์†์‹ค ์••์ถ•์— ๊ด€ํ•œ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ „๊ธฐยท์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€, 2013. 8. ์กฐ๋‚จ์ต.๋ฌด์†์‹ค ์••์ถ•์€ ๋ฉ”๋ชจ๋ฆฌ์™€ ๋Œ€์—ญํญ์„ ๋งŽ์ด ์‚ฌ์šฉํ•˜๊ธฐ ๋•Œ๋ฌธ์— ์†์‹ค ์••์ถ•์— ๋น„ํ•ด ๋œ ์‚ฌ์šฉ๋œ๋‹ค. ํ•˜์ง€๋งŒ ์˜๋ฃŒ, ์ถœํŒ, ๊ณผํ•™, ์˜ˆ์ˆ ๊ณผ ๊ฐ™์€ ๋ถ„์•ผ์—์„œ๋Š” ๋ฌด์†์‹ค ์••์ถ•์ด ํ•„์ˆ˜์ ์ด๋‹ค. ๋˜ํ•œ ์นด๋ฉ”๋ผ์™€ ์˜์ƒ ํ‘œ์‹œ ์žฅ์น˜์˜ ์„ฑ๋Šฅ์ด ํ–ฅ์ƒ๋˜๊ณ  ๋ฉ”๋ชจ๋ฆฌ์˜ ๊ฐ€๊ฒฉ์€ ๋‚ฎ์•„์ง€๋ฉด์„œ ์••์ถ•์œผ๋กœ ์ธํ•œ ์˜์ƒ ์—ดํ™”๋ฅผ ํ”ผํ•˜๊ณ ์žํ•˜๋Š” ์š”๊ตฌ๊ฐ€ ์ฆ๊ฐ€ํ•˜๊ณ  ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ๋งŽ์€ ๊ฒฝ์šฐ์— ์†์‹ค ์••์ถ•์ด ์‚ฌ์šฉ๋จ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ํšจ์œจ์ ์ธ ๋ฌด์†์‹ค ์••์ถ•์˜ ์ค‘์š”์„ฑ์€ ์ ์  ์ปค์ง€๊ณ  ์žˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ฑ„๋„ ๊ฐ„์˜ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ์ด์šฉํ•œ ์ปฌ๋Ÿฌ ์˜์ƒ๊ณผ ์ปฌ๋Ÿฌ ํ•„ํ„ฐ ์–ด๋ ˆ์ด ์˜์ƒ์˜ ๋ฌด์†์‹ค ์••์ถ• ๋ฐฉ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ๋จผ์ € ๊ธฐ์กด์˜ ๋ฌด์†์‹ค ์ƒ‰์ƒ ๋ณ€ํ™˜ ๋ฐฉ๋ฒ•์— lifting step์„ ์ถ”๊ฐ€ํ•˜์—ฌ ์„ฑ๋Šฅ์„ ํ–ฅ์ƒ์‹œํ‚จ ์ƒˆ๋กœ์šด ๋ฌด์†์‹ค ์ƒ‰์ƒ ๋ณ€ํ™˜ ๋ฐฉ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ์ด๋ฏธ์ง€์˜ ์ ์ƒ‰, ๋…น์ƒ‰, ์ฒญ์ƒ‰ ์ฑ„๋„ ๊ฐ„์—๋Š” ๋†’์€ ์ˆ˜์ค€์˜ ์ƒ๊ด€๊ด€๊ณ„๊ฐ€ ์žˆ๋Š”๋ฐ, ์ด๋Š” YCbCr ๋ณ€ํ™˜์„ ํ†ตํ•ด์„œ ์„ฑ๊ณต์ ์œผ๋กœ ์ œ๊ฑฐ๋œ๋‹ค. ํ•˜์ง€๋งŒ, ์ด ๋ณ€ํ™˜์€ ๋ฌด์†์‹ค ์••์ถ•์—๋Š” ์‚ฌ์šฉ๋  ์ˆ˜ ์—†๊ธฐ ๋•Œ๋ฌธ์— JPEG2000์„ ํฌํ•จํ•œ ํ‘œ์ค€ ๋ฌด์†์‹ค ์••์ถ• ๋ฐฉ๋ฒ•์—์„œ๋Š” ๋ฌด์†์‹ค ์ƒ‰์ƒ ๋ณ€ํ™˜์ด ์‚ฌ์šฉ๋œ๋‹ค. ์ด ๋ณ€ํ™˜์€ ๊ฐ€์—ญ์ ์ด๊ณ  ๊ฐ„๋‹จํ•˜๊ธฐ ๋•Œ๋ฌธ์— ์„ฑ๋Šฅ์ด ๋ถ€์กฑํ•˜์—ฌ, ์ด๋ฅผ ํ–ฅ์ƒ์‹œํ‚ฌ ํ•„์š”๊ฐ€ ์žˆ๋‹ค. ๊ฐ„๋‹จํ•˜์ง€๋งŒ ํšจ๊ณผ์ ์ธ ์—ฐ์‚ฐ์„ ํ†ตํ•ด์„œ ์ œ์•ˆํ•˜๋Š” ๋ฐฉ๋ฒ•์€ ๊ธฐ์กด์˜ ๋ฌด์†์‹ค ์ƒ‰์ƒ ๋ณ€ํ™˜์˜ ์„ฑ๋Šฅ์„ ํ–ฅ์ƒ์‹œ์ผœ YCbCr๊ณผ ๋น„์Šทํ•œ ์„ฑ๋Šฅ์„ ๋ณด์—ฌ์ค€๋‹ค. ๋˜ํ•œ, ํ‘œ์ค€ ์••์ถ• ๋ฐฉ๋ฒ•์ธ JPEG-LS๋ฅผ ์ด์šฉํ•˜์—ฌ ์‹คํ—˜ํ•œ ๊ฒฐ๊ณผ ๊ธฐ์กด์˜ ๋ฌด์†์‹ค ์ƒ‰์ƒ ๋ณ€ํ™˜์— ๋น„ํ•ด 1.46%์˜ ์••์ถ•๋ฅ  ํ–ฅ์ƒ ํšจ๊ณผ๊ฐ€ ์žˆ์—ˆ๋‹ค. ๋‹ค์Œ์œผ๋กœ ๊ณ„์ธต์ ์ธ ์˜ˆ์ธก์„ ํ†ตํ•œ ์ปฌ๋Ÿฌ ์˜์ƒ์˜ ๋ฌด์†์‹ค ์••์ถ• ๋ฐฉ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ์•ž์—์„œ ์ œ์•ˆํ•œ ์ƒˆ๋กœ์šด ๋ฌด์†์‹ค ์ƒ‰์ƒ ๋ณ€ํ™˜์„ ํ†ตํ•ด RGB ์˜์ƒ์„ ๋ณ€ํ™˜ํ•˜๊ณ , ๋ฐ๊ธฐ ์„ฑ๋ถ„์ธ Y๋Š” ๊ธฐ์กด์˜ ๋ฌด์†์‹ค ์••์ถ• ๋ฐฉ๋ฒ•์œผ๋กœ ์••์ถ•์„ ํ•œ๋‹ค. ์ƒ‰์ƒ ์ฑ„๋„ Cu'์™€ Cv'๋Š” ์ œ์•ˆํ•˜๋Š” ๊ณ„์ธต์ ์œผ๋กœ ๋ถ„ํ•ด๋˜์–ด ๋ฐฉํ–ฅ์„ฑ์„ ์ด์šฉํ•ด ์˜ˆ์ธก๋˜๋ฉฐ, ์˜ˆ์ธก ์˜ค์ฐจ๋Š” context modeling์„ ํ†ตํ•ด ๋ถ€ํ˜ธํ™”๋œ๋‹ค. ์ œ์•ˆํ•˜๋Š” ๋ฐฉ๋ฒ•์€ Kodak ์˜์ƒ, ์˜๋ฃŒ ์˜์ƒ, ๋””์ง€ํ„ธ ์นด๋ฉ”๋ผ ์˜์ƒ์— ๋Œ€ํ•ด ์—ฌ๋Ÿฌ ๊ธฐ์กด ๋ฐฉ๋ฒ•๊ณผ ๋น„๊ต๋˜์—ˆ์œผ๋ฉฐ, ๊ฐ€์žฅ ์šฐ์ˆ˜ํ•œ JPEG2000 ๋Œ€๋น„ ๊ฐ ์…‹์— ๋Œ€ํ•ด 5.85%, 10.40%, 4.89% ํ–ฅ์ƒ๋œ ์••์ถ•๋ฅ ์„ ์–ป์—ˆ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ ํšจ๊ณผ์ ์ธ context modeling์„ ์ด์šฉํ•œ Bayer ์ปฌ๋Ÿฌ ํ•„ํ„ฐ ์–ด๋ ˆ์ด ์˜์ƒ์˜ ๋ฌด์†์‹ค ์••์ถ• ๋ฐฉ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ์˜ˆ์ธก ์˜ค์ฐจ์˜ ํšจ๊ณผ์ ์ธ context modeling์„ ์œ„ํ•ด์„œ ๊ณ„์ธต์  ์˜ˆ์ธก์ด ์‚ฌ์šฉ๋˜์—ˆ์œผ๋ฉฐ, ์ด ๊ณผ์ •์—์„œ mosaic ์˜์ƒ์€ 4๊ฐœ์˜ ๋ถ€์˜์ƒ์œผ๋กœ ๋‚˜๋ˆ„์–ด์ง€๊ณ  ์ˆœ์„œ๋Œ€๋กœ ์••์ถ•๋œ๋‹ค. ์ž„์˜์˜ ๋ถ€์˜์ƒ์„ ์˜ˆ์ธกํ•˜๊ธฐ ์œ„ํ•ด์„œ ์ด์ „์— ์••์ถ•๋œ ๋ถ€์˜์ƒ์ด ๋ชจ๋‘ ์ด์šฉ๋˜์–ด ํ•ด๋‹น ํ”ฝ์…€ ์œ„์น˜์˜ ์—์ง€ ๋ฐฉํ–ฅ๊ณผ ํ›„๋ณด ์˜ˆ์ธก๊ฐ’์„ ๊ณ„์‚ฐํ•œ๋‹ค. ์ด ๊ฐ’๋“ค์€ ๋‹ค์‹œ ์˜ˆ์ธก ์˜ค์ฐจ์˜ ํšจ๊ณผ์ ์ธ context modeling์„ ์œ„ํ•ด์„œ๋„ ์‚ฌ์šฉ๋œ๋‹ค. ์ œ์•ˆํ•œ ๋ฐฉ๋ฒ•์€ ์‹ค์ œ ์ปฌ๋Ÿฌ ํ•„ํ„ฐ ์–ด๋ ˆ์ด ์˜์ƒ๊ณผ Kodak ์˜์ƒ, ๋””์ง€ํ„ธ ์นด๋ฉ”๋ผ ์˜์ƒ์— ๋Œ€ํ•œ ์‹คํ—˜์—์„œ ๋น„๊ตํ•œ ๋ชจ๋“  ๋ฐฉ๋ฒ•๋ณด๋‹ค ์šฐ์ˆ˜ํ•œ ์„ฑ๋Šฅ์„ ๋ณด์˜€๋‹ค.Lossless image compression is less used than lossy compression due to its large memory or bandwidth requirements. However in some fields, such as medical, prepress, scientific, and artistic areas, lossy compression cannot substitute for lossless compression. As cameras and display systems are going high quality and as the cost of memory is lowered, we may also wish to keep our precious and artistic photos free from compression artifacts. Hence efficient lossless compression will become more and more important, although the lossy compressed images are usually satisfactory in most cases. In this dissertation, algorithms using interchannel correlation are studied, with which lossless compression schemes for color image and color filter array image are proposed. At first, a new reversible color transform (RCT) is proposed, which consists of the conventional RCT and additional lifting steps to further decorrelate chroma images Cu and Cv. Red, green, and blue samples in an image are highly correlated, but YCbCr transform shows good decorrelation performance for RGB images. However because the transform cannot be used for lossless compression, RCT is used for lossless coding standards including JPEG2000. Due to its invertibility and simplicity, the decorrelation performance of the conventional RCT is not satisfying, so the improvement is required. With effective but simple operations, the proposed scheme shows much higher decorrelation performance than the conventional RCT, and the improved performance is comparable with YCbCr. In addition, lossless bit rates of JPEG-LS, the standard lossless image coder, after color transforms are presented, in which the proposed RCT outperforms the conventional RCT over 1.46% with minimum increase in operations. Next, a lossless color image compression method based on a new hierarchical encoding scheme is proposed. Specifically, an input RGB image is transformed into YCu'Cv' color space using the new RCT. After the color transformation, the luminance channel Y is compressed by a conventional lossless image coder. The chrominance channels are encoded with the proposed hierarchical decomposition and directional prediction. Finally, an appropriate context modeling of prediction residuals is introduced and generic arithmetic coding is applied. The proposed method and several conventional methods are tested on the Kodak image set, some medical images, and digital camera images, and it is shown that average file size reductions over JPEG2000 for these sets are 5.85%, 10.40%, and 4.89% respectively. When the mode selection is tried, further encoding gain can be obtained. At last, a new lossless compression method for Bayer color filter array (CFA) images is proposed, which focuses on efficient context modeling. For the efficient modeling of prediction errors, hierarchical prediction scheme is adopted, in which input mosaic image is divided into four subimages, and the subimages are encoded in order. For the prediction of a subimage, all of subimages which are already encoded are used to estimate edge direction and candidate predictors. The already encoded subimages and pixels in causal neighborhood are also used to estimate the magnitude of prediction error, and the prediction error is encoded by adaptive arithmetic coder along with the estimated context. The proposed method is test for real CFA images and simulated CFA images from Kodak set and commercial digital camera images, and it outperforms all the compared methods.Abstract i Contents iv List of Figures vii List of Tables x 1 Introduction 1 1.1 Lossless Color Image Compression 1 1.2 Interchannel Correlation 2 1.3 Lossless Compression of CFA Image 3 1.4 Outline of This Dissertation . 5 2 Related Works 9 2.1 Lossless Image Compression Using Interchannel Correlation 9 2.1.1 Interband CALIC 9 2.1.2 RCT 12 2.2 Lossless Compression of Mosaic Image 13 2.2.1 LCMI 13 2.2.2 CMBP 16 3 New Reversible Color Transform 21 3.1 Introduction 21 3.2 Proposed Method 22 3.3 Experimental Results . 23 3.4 Conclusion 25 4 Hierarchical Prediction Scheme for Lossless Color Image Compres-sion 29 4.1 Introduction 29 4.2 Proposed Method 30 4.2.1 Hierarchical Decomposition 30 4.2.2 Directional Prediction 31 4.2.3 Proposed Coding Scheme 32 4.3 Experimental Results 34 4.4 Conclusion 38 5 Color Filter Array Compression 45 5.1 Introduction 45 5.2 Overview of Proposed Encoder 49 5.3 Hierarchical Prediction of CFA data 50 5.3.1 Prediction of G2 51 5.3.2 Interpolation of green values in the positions of R and B 54 5.3.3 Prediction of red and blue pixels 55 5.4 Encoding Prediction Errors 57 5.5 Experimental Results 59 5.5.1 The Proposed Method 59 5.5.2 Demosaic-first and Compression-first Schemes 62 5.6 Conclusion 66 6 Conclusions 71 Bibliography 75 Abstract (Korean) 83Docto

    Analysis of surface plasmon in nano-scale grating structures by using parallel computing

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) --์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์ „๊ธฐ. ์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€,2007.Maste

    ๋‹ค์–‘ํ•œ ๋™๋ฌผ์˜ ๋ถ„๋ณ€์—์„œ ๋ถ„๋ฆฌํ•œ ์žฅ๊ตฌ๊ท ์˜ ๋ถ„๋ณ€์˜ค์—ผ ์ง€ํ‘œ ๋ฏธ์ƒ๋ฌผ์—์˜ ์ ์šฉ

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    Thesis(masters) --์„œ์šธ๋Œ€ํ•™๊ต ๋ณด๊ฑด๋Œ€ํ•™์› :ํ™˜๊ฒฝ๋ณด๊ฑดํ•™๊ณผ (ํ™˜๊ฒฝ๋ณด๊ฑดํ•™์ „๊ณต),2009.8.Maste

    Preparation method of inverted Pb free perovskite solar cell

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    ๋ณธ ๋ฐœ๋ช…์€ ์—ญ๊ตฌ์กฐ์˜ ๋ฌด์—ฐ ํŽ˜๋กœ๋ธŒ์Šค์นด์ดํŠธ ํƒœ์–‘์ „์ง€์˜ ์ œ์กฐ๋ฐฉ๋ฒ•์— ๊ด€ํ•œ ๊ฒƒ์œผ๋กœ, ์ƒ์„ธํ•˜๊ฒŒ๋Š” ๊ธฐํŒ ์ƒ๋ถ€์— P-type ๊ธˆ์†์‚ฐํ™”๋ฌผ์„ ํฌํ•จํ•˜๋Š” ์ •๊ณต์ˆ˜์†ก์ธต(hole transport layer, HTL)์„ ํ˜•์„ฑํ•˜๋Š” ๋‹จ๊ณ„(๋‹จ๊ณ„ 1); ์ƒ๊ธฐ ์ •๊ณต์ˆ˜์†ก์ธต(HTL) ์ƒ๋ถ€์— ํ• ๋ผ์ด๋“œ ์œ ๊ธฐ ๋˜๋Š” ๋ฌด๊ธฐ ๋ฐ•๋ง‰์„ ํ˜•์„ฑํ•˜๋Š” ๋‹จ๊ณ„(๋‹จ๊ณ„ 2); ๋ฐ ์ƒ๊ธฐ ์ •๊ณต์ˆ˜์†ก์ธต(HTL) ๋ฐ ํ• ๋ผ์ด๋“œ ์œ ๊ธฐ ๋˜๋Š” ๋ฌด๊ธฐ ๋ฐ•๋ง‰์„ ๋ฐ˜์‘์‹œ์ผœ ์ƒ๊ธฐ ์ •๊ณต์ˆ˜์†ก์ธต(HTL) ์ƒ๋ถ€์— ํŽ˜๋กœ๋ธŒ์Šค์นด์ดํŠธ ๊ด‘ํก์ˆ˜์ธต์„ ํ˜•์„ฑํ•˜๋Š” ๋‹จ๊ณ„(๋‹จ๊ณ„ 3);๋ฅผ ํฌํ•จํ•˜๋Š” ์—ญ๊ตฌ์กฐ์˜ ํŽ˜๋กœ๋ธŒ์Šค์นด์ดํŠธ ํƒœ์–‘์ „์ง€(Inverted perovskite solar cell)์˜ ์ œ์กฐ๋ฐฉ๋ฒ•์— ๊ด€ํ•œ ๊ฒƒ์ด๋‹ค

    Method of manufacturing thin-film or thick-film of porous metal halides

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    ๋ณธ ๋ฐœ๋ช…์€ ๋‹ค๊ณต์„ฑ์˜ ๊ธˆ์† ํ• ๋ผ์ด๋“œ ๋ฐ•๋ง‰ ๋˜๋Š” ํ›„๋ง‰ ์ œ์กฐ๋ฐฉ๋ฒ•์— ๊ด€ํ•œ ๊ฒƒ์œผ๋กœ์„œ, ์ƒ๊ธฐ ์ œ์กฐ๋ฐฉ๋ฒ•์€ ํƒœ์–‘์ „์ง€์˜ ํšจ์œจ์„ ๋†’์ผ ์ˆ˜ ์žˆ๋Š” ๋‹ค๊ณต์„ฑ ๊ตฌ์กฐ๋ฅผ ๊ฐ–๋Š” ๊ธˆ์† ํ• ๋ผ์ด๋“œ ๋ฐ•๋ง‰ ๋˜๋Š” ํ›„๋ง‰์„ ์ œ์กฐํ•  ์ˆ˜ ์žˆ๋Š” ์ƒˆ๋กœ์šด ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•œ๋‹ค. ๋‹ค๊ณต์„ฑ์˜ ๊ธˆ์† ํ• ๋ผ์ด๋“œ ๋ฐ•๋ง‰ ๋˜๋Š” ํ›„๋ง‰ ์ œ์กฐ๋ฐฉ๋ฒ•์€ ๋‹ค๊ณต์„ฑ ๊ธˆ์† ํ• ๋ผ์ด๋“œ ๋ฐ•๋ง‰ ๋˜๋Š” ํ›„๋ง‰์„ ํ†ตํ•ด ๋ฐ˜์‘ ํ›„ ์ž”์—ฌ ๊ธˆ์† ํ• ๋ผ์ด๋“œ๋ฅผ ์ตœ์†Œํ™”ํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ, ์Šต๋ง‰ ์ƒํƒœ์˜ ๊ธˆ์† ํ• ๋ผ์ด๋“œ์— ๋Œ€๊ธฐ ์ค‘ ์ˆ˜๋ถ„์ด๊ฑฐ๋‚˜, ์™ธ๋ถ€์—์„œ ์ˆ˜๋ถ„์„ ๋ถ„์‚ฌํ•˜์—ฌ ์ˆ˜๋ถ„์„ ๊ณต๊ธ‰ํ•จ์œผ๋กœ์จ ๊ธˆ์† ํ• ๋ผ์ด๋“œ ๋ฐ•๋ง‰์˜ ๊ธฐ๊ณต ์ •๋„๋ฅผ ์ œ์–ดํ•  ์ˆ˜ ์žˆ์–ด, ์ž”์—ฌ ๊ธˆ์† ํ• ๋ผ์ด๋“œ๊ฐ€ ๋‚จ๋Š” ๊ฒƒ์„ ๋ฐฉ์ง€ํ•จ์œผ๋กœ์จ ๊ณ ํšจ์œจ ํƒœ์–‘์ „์ง€๋ฅผ ํ•ฉ์„ฑํ•  ์ˆ˜ ์žˆ๋Š” ๋งค์šฐ ์œ ์šฉํ•œ ๊ธฐ์ˆ ์ด๋‹ค.๋‹ค๊ณต์„ฑ์˜ ๊ธˆ์† ํ• ๋ผ์ด๋“œ ๋ฐ•๋ง‰ ๋˜๋Š” ํ›„๋ง‰ ์ œ์กฐ๋ฐฉ๋ฒ•์— ์žˆ์–ด์„œ,ํŽ˜๋กœ๋ธŒ์Šค์นด์ดํŠธ ์ „๊ตฌ์ฒด ์šฉ์•ก์„ ์ œ์กฐํ•˜๋Š” ๋‹จ๊ณ„ (์ œ1๋‹จ๊ณ„);์ƒ๊ธฐ ์ „๊ตฌ์ฒด ์šฉ์•ก ์ด 100 ์ค‘๋Ÿ‰๋ถ€์— ๋Œ€ํ•ด์„œ 5 ๋‚ด์ง€ 30 ์ค‘๋Ÿ‰๋ถ€์˜ ์š”์˜ค๋“œ์‚ฐ ๋ฐ 5 ๋‚ด์ง€ 30 ์ค‘๋Ÿ‰๋ถ€์˜ ๋ฌผ์„ ์ฒจ๊ฐ€ํ•˜์—ฌ 20 ๋‚ด์ง€ 30โ„ƒ์—์„œ 5 ๋‚ด์ง€ 30๋ถ„ ๋™์•ˆ ๊ต๋ฐ˜๊ณผ์ •์„ ํ†ตํ•ด ์กธ(sol)์„ ํ•ฉ์„ฑํ•˜๋Š” ๋‹จ๊ณ„ (์ œ2๋‹จ๊ณ„); ๋ฐ์ƒ๊ธฐ ํ•ฉ์„ฑ๋œ ์กธ์„ ๊ธฐํŒ ์ƒ์— ์ฝ”ํŒ…ํ•˜๋Š” ๋‹จ๊ณ„ (์ œ3๋‹จ๊ณ„);๋ฅผํฌํ•จํ•˜๋Š”, ๋‹ค๊ณต์„ฑ์˜ ๊ธˆ์† ํ• ๋ผ์ด๋“œ ๋ฐ•๋ง‰ ๋˜๋Š” ํ›„๋ง‰ ์ œ์กฐ๋ฐฉ๋ฒ•
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