269 research outputs found

    Lung Segmentation Considering Global and Local Properties in Chest X-ray Images

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    In this paper, we propose a new lung segmentation method for chest x-ray images which can take both global and local properties into account. Firstly, the initial lung segmentation is computed by applying the active shape model (ASM) which keeps the shape of deformable model from the pre-learned model and searches the image boundaries. At the second segmentation stage, we also applied the localizing region-based active contour model (LRACM) for correcting various regional errors in the initial segmentation. Finally, to measure the similarities, we calculated the Dice coefficient of the segmented area using each semiautomatic method with the result of the manually segmented area by a radiologist. The comparison experiments were performed using 5 lung x-ray images. In our experiment, the Dice coefficient with manually segmented area was 95.3395.33%{\pm}0.93% for the proposed method. Effective segmentation methods will be essential for the development of computer-aided diagnosis systems for a more accurate early diagnosis and prognosis regarding lung cancer in chest x-ray images.ope

    Ossification of the Transverse Ligament of the Atlas on CT: Frequency and Associated Findings

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    Purpose To determine the frequency of ossification of the transverse ligament of the atlas (OTLA) and to investigate the associated findings on cervical spine CT and plain radiography. Materials and Methods We reviewed 5201 CT scans of the cervical spine of 3975 consecutive patients over an 11-year period for the presence of OTLA and compared them with those of ageand sex-matched controls. The frequency and associated findings of OTLA were investigated and statistically correlated. Results The overall frequency of OTLA was 1.1% (45 of 3975 patients) and increased with age (p < 0.005). The frequency of OTLA in patients over 80 years was 12%. The space available for the spinal cord (SAC) was smaller in patients with OTLA (p < 0.005). Mineralization of the complex of the anterior atlantooccipital membrane and Barkow ligament, ossification of the ligamentum flavum, and kyphosis of the cervical spine positively correlated to the presence of OTLA (p < 0.005). Conclusion OTLA was associated with age, SAC narrowing, cervical kyphosis, and ossification of other cervical ligaments and may be associated with degenerative spondylosis, systemic hyperostotic status, or mechanical stress or instability.ope

    ๋ฆฌํŠฌ ์ด์˜จ ์ด์ฐจ์ „์ง€์˜ ์Œ๊ทน ๋ฌผ์งˆ์— ์‚ฌ์šฉ๋˜๋Š” ์ „๋„์„ฑ ๊ณ ๋ถ„์ž๋กœ ์ฝ”ํŒ…๋œ ์•ŒํŒŒ ๋ง๊ฐ„ ์˜ฅ์‚ฌ์ด๋“œ ๋‚˜๋…ธ ์™€์ด์–ด์˜ ํ•ฉ์„ฑ ๋ฐ ์‘์šฉ

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ํ™”ํ•™๋ถ€, 2016. 2. ์†๋ณ‘ํ˜.Transition metal oxides have been considered as promising lithium storage materials that undergo a conversion reaction with Li ion, exhib-iting high specific capacity. Among them, manganese oxides have high capacity compared to other metal oxides, and also their costs are inex-pensive. However, capacity fading during cycling is the most serious obstacle for their commercialization. To slove the problems, poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) was coated onto ฮฑ-Mn2O3 nanowires while maintaining the structure of ฮฑ-Mn2O3. PEDOT:PSS on the ฮฑ-Mn2O3 reduced the resistance of the surface and protected the surface electron channels from the pulverization effect of the chargeโ€“discharge operation. ฮฑ-Mn2O3/PEDOT:PSS showed excellent cyclability with a reversible capacity of 1450 mAhยทg-1 after 200 cycles at a current density of 100 mAยทg-1. An increase in ca-pacity was observed with continuous cycling, which may be attributed to further oxidation of the manganese species and a reversible reaction of the gel-like polymer on the manganese surface. The results demon-strate that PEDOT:PSS enhances the electrochemical activity by providing electron channels and prevents pulverization caused by the charge and discharge process.Charpter 1. ษ‘-Mn2O3 nanowires coated with conductive polymer for Li-ion battery anode materialsSynthesis,Characterization, and Application 8 1. Introduction 9 2. Experimental section 12 2.1 Synthesis of ฮฑ-Mn2O3 nanowires 12 2.2 Coating PEDOT:PSS onto ฮฑ-Mn2O3 nanowires 13 2.3 Materials characterization 13 2.4 Electrochemical measurements 14 3. Result and discussion 15 3.1 Synthesis and characterization of materials 15 3.2 Electrochemical performance in Li ion battery 22 4. Conclusions 29 5. References 30 6. Abstract (in Korean) 40 Appendix. Fabrication of Three-Dimensionally Ordered Nickel Cobalt Sulfide Electrodes for Pseudocapacitor 42 1. Abstract 43 2. Introduction 44 3. Experimental Section 46 4. Results and Discussion 49 5. Conclusions 56 6. References 57Maste

    ์‹ ๋„์‹œ ์กฐ์„ฑ ์ดํ›„ ์‹ ใ†๊ตฌ๋„์‹œ์˜ ์ง€์—ญ ๋ถ„ํ™” ๋ฐ ๋„์‹œ์„œ๋น„์Šค ๊ฒฉ์ฐจ ๋ถ„์„

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ํ˜‘๋™๊ณผ์ • ๋„์‹œ์„ค๊ณ„ํ•™์ „๊ณต, 2013. 2. ์•ˆ๊ฑดํ˜.1990๋…„๋Œ€์— ๋„์ž…๋œ 1๊ธฐ ์‹ ๋„์‹œ๋“ค์€ ์ง€๋ฆฌ์ ใ†ํ–‰์ •์  ์œ„์ƒ ๋•Œ๋ฌธ์— ์„œ์šธ ๋ฟ ์•„๋‹ˆ๋ผ ์ธ์ ‘ํ•œ ๊ธฐ์กด ๊ตฌ๋„์‹œ์˜ ๋ฌผ๋ฆฌ์ ใ†๊ฒฝ์ œ์  ์‚ฌํšŒ์  ๊ณต๊ฐ„๊ตฌ์กฐ์™€๋„ ๋งŽ์€ ์˜ํ–ฅ์„ ์ฃผ๊ณ ๋ฐ›์•„ ์™”์œผ๋ฉฐ, ๊ทธ ๊ฒฐ๊ณผ ๋‘ ๋„์‹œ์—๋Š” ๊ณต๊ฐ„๊ตฌ์กฐ์ƒ ๋ถ„ํ™”๊ฐ€ ๋‚˜ํƒ€๋‚˜๊ฒŒ ๋˜์—ˆ๋‹ค. ์ด๋Ÿฌํ•œ ๊ณต๊ฐ„๊ตฌ์กฐ์ƒ์˜ ์‹ ใ†๊ตฌ๋„์‹œ๊ฐ„ ๋ถ„ํ™” ํ˜„์ƒ์€ ๋‹จ์ˆœํžˆ ๊ฐ€์‹œ์ ์ธ ๋„์‹œ ๋ณ€ํ™”๋งŒ์„ ์˜๋ฏธํ•˜๋Š” ๊ฒƒ์ด ์•„๋‹ˆ๋ผ ์ง€์—ญ ์ฃผ๋ฏผ์˜ ์˜์‹์ด๋‚˜ ๊ฐ ์ง€์—ญ ์ฃผ๋ฏผ๋“ค์—๊ฒŒ ์ œ๊ณต๋˜๋Š” ๋„์‹œ์„œ๋น„์Šค์—๋„ ์˜ํ–ฅ์„ ๋ฏธ์น˜๊ฒŒ ๋˜์–ด ์ด๋“ค ๋„์‹œ ๊ฐ„์— ๊ฒฉ์ฐจ๊ฐ€ ๋‚˜ํƒ€๋‚˜๊ฒŒ ๋˜๊ณ  ์ด๊ฒƒ์ด ์ง€์—ญ์ด๊ธฐ์ฃผ์˜์˜ ํ˜•ํƒœ๋กœ ๋ฐœ์ „ํ•˜๊ฒŒ ๋˜์–ด ์—ฌ๋Ÿฌ ๊ฐ€์ง€ ์‚ฌํšŒ๋ฌธ์ œ๋ฅผ ์ดˆ๋ž˜ํ•  ๊ฐ€๋Šฅ์„ฑ๋„ ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๊ด€๋ จ ์ฃผ์ฒด๋“ค์€ ๋Œ€๋ถ€๋ถ„ ์ด๋ฅผ ๋„์‹œ ๋ฐœ์ „ ๊ณผ์ •์ƒ ๋‹ค๋ถ„ํžˆ ๊ฒฝ์ œ์  ๋…ผ๋ฆฌ์— ๋”ฐ๋ผ ๋ฏผ๊ฐ„ ์˜์—ญ์—์„œ ํ•„์—ฐ์ ์œผ๋กœ ๋ฐœ์ƒํ•˜๋Š” ์ž์—ฐ์Šค๋Ÿฌ์šด ํ˜„์ƒ์œผ๋กœ ์น˜๋ถ€ํ•ด๋ฒ„๋ฆฌ๋Š” ์‹œ๊ฐ์ด ์ง€๋ฐฐ์ ์ด์—ˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์—ฌ๋Ÿฌ ์ฃผ์ฒด๋“ค ๊ฐ„์˜ ์‹ค์งˆ์ ์ธ ๋…ผ์˜๋„ ๋ถ€์กฑํ•˜๋ฉฐ, ์ด๋Ÿฌํ•œ ๋ฌธ์ œ๋ฅผ ๋‹ค๋ฃฌ ์ฒด๊ณ„์ ์ธ ์กฐ์‚ฌ๋‚˜ ์—ฐ๊ตฌ ๋ฐ ์ •์ฑ… ์ œ์‹œ ๋˜ํ•œ ๋ฏธํกํ•œ ๊ฒƒ์ด ํ˜„์‹ค์ด๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ์—ฐ๊ตฌ๋Š” ์ด์™€ ๊ฐ™์€ ์‹ ใ†๊ตฌ๋„์‹œ์˜ ์ง€์—ญ ๋ถ„ํ™” ํ˜„์ƒ์— ๋Œ€ํ•œ ํ˜•์„ฑ๊ณผ์ • ๋ฐ ์š”์ธ์„ ํŒŒ์•…ํ•˜๊ณ , ์ด๋“ค ์ง€์—ญ ๊ฐ„์˜ ๋„์‹œ์„œ๋น„์Šค์˜ ๊ฒฉ์ฐจ๋ฅผ ๊ฐ๊ด€์ ์œผ๋กœ ์‚ฐ์ •ํ•˜์—ฌ ๋ถ„์„ํ•œ ํ›„ ์ด์™€ ๊ด€๋ จํ•œ ํ–ฅํ›„ ๋„์‹œ ์ •์ฑ…์—์˜ ์‹œ์‚ฌ์ ์„ ๋„์ถœํ•ด ๋ณด๊ธฐ ์œ„ํ•œ ๋ชฉ์ ์„ ๊ฐ€์ง€๊ณ  ์ง„ํ–‰๋˜์—ˆ๋‹ค. ์ด๋ฅผ ์œ„ํ•˜์—ฌ ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๋จผ์ € ๋ฌผ๋ฆฌ์  ์ธก๋ฉด, ๊ฒฝ์ œ์  ์ธก๋ฉด, ์‚ฌํšŒ์  ์ธก๋ฉด, ๊ต๋ฅ˜์  ์ธก๋ฉด์˜ ๋ถ„์„ ์ง€ํ‘œ๋ฅผ ๊ฐ๊ฐ ์„ค์ •ํ•˜๊ณ  ์‹ ๋„์‹œ๊ฐ€ ์กฐ์„ฑ๋˜๊ธฐ ์ด์ „๋ถ€ํ„ฐ ์ตœ๊ทผ๊นŒ์ง€์˜ ์•ฝ 20์—ฌ ๋…„๊ฐ„์˜ ์ง€ํ‘œ๋“ค์˜ ๋ณ€ํ™”์™€ ๊ณต๊ฐ„ ๋ถ„ํฌ ํŒจํ„ด์„ GIS ๋ฐ ๊ณต๊ฐ„์ž๊ธฐ์ƒ๊ด€๋ถ„์„์„ ํ†ตํ•˜์—ฌ ๊ทœ๋ช…ํ•˜์˜€๋‹ค. ๋‹ค์Œ์œผ๋กœ ์‹ ใ†๊ตฌ๋„์‹œ์˜ ๋„์‹œ์„œ๋น„์Šค ๊ฒฉ์ฐจ ๋ถ„์„์„ ์œ„ํ•˜์—ฌ, ๊ณต๊ณต์˜์—ญ์—์„œ๋Š” ๊ต์œก, ๊ณต์›, ๋Œ€์ค‘๊ตํ†ต, ๋ฌธํ™”์„œ๋น„์Šค๋ฅผ ๋ฏผ๊ฐ„ ์˜์—ญ์—์„œ๋Š” ์ƒ์—…๊ณผ ์˜๋ฃŒ์„œ๋น„์Šค๋ฅผ ๋ถ„์„ ๋Œ€์ƒ์œผ๋กœ ์„ค์ •ํ•˜๊ณ  ์ˆ˜์ •๋œ ํ™•๋ฅ ์  ์ค‘๋ ฅ๋ชจํ˜•์„ ์ ์šฉํ•˜์—ฌ ๊ฐ ์ง€์—ญ์— ์ œ๊ณต๋˜๊ณ  ์žˆ๋Š” ๋„์‹œ์„œ๋น„์Šค ์–‘์„ ๊ฐ๊ด€์ ์œผ๋กœ ์‚ฐ์ •ํ•˜์—ฌ ๋น„๊ตํ•˜๊ณ  ๊ณต๊ฐ„๋ถ„์„์„ ์‹ค์‹œํ•˜์˜€๋‹ค. ์ด๋Ÿฌํ•œ ๊ณผ์ •์„ ํ†ตํ•ด ๋„์ถœํ•œ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋ฅผ ์š”์•ฝํ•ด ๋ณด๋ฉด ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ๋จผ์ € ์‹ ๋„์‹œ ์กฐ์„ฑ ์ดํ›„ ์‹ ใ†๊ตฌ๋„์‹œ์˜ ์ง€์—ญ ๋ถ„ํ™” ํŠน์„ฑ์„ ๋ฌผ๋ฆฌ์  ์ธก๋ฉด์—์„œ ์‚ดํŽด๋ณธ ๊ฒฐ๊ณผ, ๊ธฐ์กด ๊ตฌ๋„์‹œ๊ฐ€ ์ •์ƒ์ ์œผ๋กœ ์„ฑ์žฅใ†ํ™•์žฅํ•ด๊ฐ€๋Š” ๊ณผ์ •์—์„œ ์ด์™€ ์ธ์ ‘ํ•˜์—ฌ ๋Œ€๊ทœ๋ชจ์˜ ์ธ์œ„์ ์ธ ๋„์‹œ๊ณต๊ฐ„๊ตฌ์กฐ๊ฐ€ ๋‹จ๊ธฐ๊ฐ„์— ์ƒ๊ฒจ๋‚˜๊ฒŒ ๋˜๊ณ , ์ด๋Ÿฌํ•œ ๊ณต๊ณต์— ์˜ํ•œ ๊ตฌ๋„์‹œ์™€์˜ ๊ณต๊ฐ„ ๋‹จ์ ˆ๋กœ ์ธํ•˜์—ฌ ๊ตฌ๋„์‹œ๋Š” ๋„์‹œ๊ตฌ์กฐ์ ์œผ๋กœ ํ™•์žฅ์˜ ๋ฐฉํ–ฅ์„ฑ์„ ์žƒ๊ฒŒ ๋˜๊ณ  ์ •์ฒด๋˜๋Š” ํ˜•ํƒœ๋ฅผ ๋ณด์ด๊ฒŒ ๋œ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋˜ํ•œ ์‹ ใ†๊ตฌ๋„์‹œ๊ฐ„์˜ ๊ฐ€๋กœ ๊ตฌ์„ฑ๊ณผ ๋„์‹œ ์กฐ์ง์˜ ํ˜•ํƒœ์™€ ๊ทœ๋ชจ์˜ ์ฐจ์ด๊ฐ€ ๊ฒฐ๊ตญ ๋‘ ๋„์‹œ ๋ฌผ๋ฆฌ์  ๊ณต๊ฐ„ ๊ตฌ์กฐ์ƒ์˜ ์ฐจ์ด๋ฅผ ๋‚ณ๊ฒŒ ๋˜๊ณ , ์ด๋Ÿฌํ•œ ์ฐจ์ด๋Š” ์‚ฌ๋žŒ๋“ค์ด ์‹ฌ๋ฆฌ์ ์œผ๋กœ ์„ฑ๋‚จ์‹œ๋ผ๋Š” ํ–‰์ •๊ตฌ์—ญ ์•ˆ์— ๋ถ„๋‹น์ด๋ผ๋Š” ๋˜ ํ•˜๋‚˜์˜ ๋„์‹œ๊ฐ€ ์กด์žฌํ•˜๋ฉฐ ๊ตฌ๋„์‹œ์™€ ์‹ ๋„์‹œ๋Š” ๋ณ„๊ฐœ์˜ ๋„์‹œ๋ผ๋Š” ์ธ์‹์„ ๊ฐ–๊ฒŒ ํ•˜๋Š” ์ค‘์š”ํ•œ ์š”์ธ ์ค‘์˜ ํ•˜๋‚˜์ž„์„ ์•Œ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋‘ ๋ฒˆ์งธ, ๊ฒฝ์ œ์  ์ธก๋ฉด์—์„œ ํ† ์ง€์ด์šฉ์˜ ๊ฒฝ์šฐ ์‹ ใ†๊ตฌ๋„์‹œ๋Š” ์—ฌ๋Ÿฌ ํ† ์ง€์ด์šฉ์˜ ์ ˆ๋Œ€์  ๋ฉด์ ์˜ ์ฐจ์ด ๋ฟ ์•„๋‹ˆ๋ผ ์ธ๋‹น ๋ฉด์ ์—์„œ๋„ ์ƒ๋‹นํ•œ ๊ฒฉ์ฐจ๋ฅผ ๋ณด์ด๊ณ  ์žˆ์œผ๋ฉฐ ์„œ๋กœ ์—ฐ๊ด€์„ฑ์ด ์—†์ด ๋งˆ์น˜ ๊ฐ๊ฐ์˜ ๋…๋ฆฝ์ ์ธ ๊ฐœ์ฒด์ฒ˜๋Ÿผ ๋ณ€ํ™”ํ•˜๋Š” ํ˜•ํƒœ๋ฅผ ๋ณด์ด๊ณ  ์žˆ์—ˆ๋‹ค. ๋‹ค๋งŒ ๊ฒฝ๊ธฐ๋„ ํ‰๊ท ๊ฐ’์˜ ๋ณ€ํ™”์™€ ๋น„๊ตํ•ด ๋ณด์•˜์„ ๋•Œ๋Š” ์‹ ใ†๊ตฌ๋„์‹œ๊ฐ„์˜ ์ƒ๋Œ€์  ์ฐจ์ด๊ฐ€ ํƒ€ ๋„์‹œ์™€์˜ ์ ˆ๋Œ€์  ์ฐจ์ด์™€ ๋ฐ˜๋“œ์‹œ ์ผ์น˜ํ•˜๋Š” ๊ฒƒ์€ ์•„๋‹ˆ๋ผ๋Š” ๊ฒƒ์„ ์•Œ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ง€๊ฐ€์˜ ๋ณ€ํ™”์—์„œ๋Š” ๋ถ„๋‹น ์ƒ์—…์ง€์—ญ์˜ ์„ ํ˜ธ๋„ ๋ฐ ๊ฐ€์น˜๋Š” ์‹ ๋„์‹œ ๊ฑด์„ค ํ›„ ์•ฝ 10๋…„ ๋™์•ˆ์€ ๊ตฌ๋„์‹œ๋ณด๋‹ค ๋‚ฎ์•˜์ง€๋งŒ, ๊ทธ ์ดํ›„์—๋Š” ๊ตฌ๋„์‹œ๋ณด๋‹ค ๋†’์•„์ ธ์„œ ์ „ํ†ต์ ์ธ ์ค‘์‹ฌ์ง€์—ญ์„ ๋Œ€์ฒดํ•˜๊ฒŒ ๋œ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋˜ํ•œ ์‹ ๋„์‹œ ์ค‘์‹ฌ์ง€์—ญ์˜ ๊ฐ€์น˜ ์ƒ์Šน์ด ์ฃผ๋ณ€ ๊ตฌ๋„์‹œ ์ง€์—ญ๋ณด๋‹ค ๋†’์•„์ง€๋Š” ์‹œ๊ธฐ๊ฐ€ ํŒ๊ต ์‹ ๋„์‹œ์˜ ๊ฒฝ์šฐ์— ๋ถ„๋‹น๋ณด๋‹ค ๋” ์งง์œผ๋ฉฐ, ์‹ ๋„์‹œ ์กฐ์„ฑ์ดํ›„ ์ง€๊ธˆ๊นŒ์ง€ ๊ตฌ๋„์‹œ์˜ ํ† ์ง€์˜ ๊ฐ€๊ฒฉ์€ ์ •์ƒ์ ์ธ ์‹œ์žฅ ์ƒํ™ฉ๋ณด๋‹ค ํƒ€ ๋„์‹œ๋“ค๊ณผ ๋น„๊ตํ•ด์„œ ํ›จ์”ฌ ์ƒ์Šนํ•œ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ฃผํƒ์˜ ๋ณ€ํ™”์—์„œ๋Š” ์‹ ใ†๊ตฌ๋„์‹œ๊ฐ„์˜ ์ฃผํƒ ๊ณต๊ธ‰์˜ ์ฐจ์ด๊ฐ€ ์ง€์†์ ์œผ๋กœ ์ปค์ง€๊ณ  ์žˆ์—ˆ๊ณ , ์‹ ๋„์‹œ ์ง€์—ญ์€ ์•„ํŒŒํŠธ ์ค‘์‹ฌ์œผ๋กœ ๊ตฌ๋„์‹œ ์ง€์—ญ์€ ๋น„์•„ํŒŒํŠธ ์ค‘์‹ฌ์˜ ์ƒ๋ฐ˜๋œ ๋„์‹œํ™˜๊ฒฝ์„ ํ˜•์„ฑํ•ด์™”์œผ๋ฉฐ ์ด๋Ÿฌํ•œ ์–‘์ƒ์€ ์‹œ๊ฐ„์ด ์ง€๋‚ ์ˆ˜๋ก ๋”์šฑ ์‹ฌํ™”๋˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋˜ํ•œ ์ฃผํƒ ๊ฐ€๊ฒฉ๊ณผ ์ž„๋Œ€๋ฃŒ ์ธก๋ฉด์—์„œ๋Š” ์‹ ใ†๊ตฌ๋„์‹œ๊ฐ„ ํฐ ์ฐจ์ด๋ฅผ ์œ ์ง€ํ•ด์˜ค๊ณ  ์žˆ์—ˆ๊ณ  ์ตœ๊ทผ์˜ ์–‘์ƒ์€ ์ „์ฒด ์ฃผํƒ ๊ฐ€๊ฒฉ๊ณผ ์ž„๋Œ€๋ฃŒ ์ˆ˜์ค€์„ ์ƒ, ์ค‘, ํ•˜๋กœ ๋‚˜๋ˆ„์–ด ๋ณผ ๋•Œ ์ƒ์œ„ ์ง€์—ญ์€ ํŒ๊ต, ์ค‘์œ„ ์ง€์—ญ์€ ๋ถ„๋‹น, ํ•˜์œ„ ์ง€์—ญ์€ ๊ตฌ๋„์‹œ ์ง€์—ญ์œผ๋กœ ๋ช…ํ™•ํ•˜๊ฒŒ ๋ถ„ํ™”๋˜์–ด ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์‚ฌ์—…์ฒด์™€ ๊ณ ์šฉ์˜ ๋ณ€ํ™”์—์„œ๋Š” ์ „์ฒด์ ์œผ๋กœ ๊ทธ ์ค‘์‹ฌ์ด ๊ตฌ๋„์‹œ์—์„œ ๋ถ„๋‹น์œผ๋กœ ์˜ฎ๊ฒจ๊ฐ€๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ์œผ๋ฉฐ ๊ณต๊ฐ„์ ์œผ๋กœ ์‹ ใ†๊ตฌ๋„์‹œ ์ง€์—ญ ๊ฐ„ ๋ถ„ํ™” ํ˜„์ƒ์ด 2000๋…„ ์ดํ›„๋ถ€ํ„ฐ ๋ณธ๊ฒฉ์ ์œผ๋กœ ์‹ฌํ™”๋˜๊ธฐ ์‹œ์ž‘ํ•˜์—ฌ ์ตœ๊ทผ์—๋Š” ๊ทธ ์–‘์ƒ์ด ๋”์šฑ ๋šœ๋ ทํ•˜๊ฒŒ ๋‚˜ํƒ€๋‚˜๊ณ  ์žˆ์—ˆ๋‹ค. ๋˜ํ•œ ์ œ์กฐ์—…์ด๋‚˜ ๊ธˆ์œต์—…๊ณผ ๊ฐ™์ด ๋„์‹ฌ CBD๋ฅผ ๊ตฌ์„ฑํ•˜๋Š” ํ•ต์‹ฌ์ ์ธ ๊ธฐ๋Šฅ์ด ์‹ ๋„์‹œ ์กฐ์„ฑ์œผ๋กœ ์ธํ•˜์—ฌ ๊ตฌ๋„์‹œ ์ง€์—ญ์—์„œ ์ƒ๋‹น๋ถ€๋ถ„ ์ด๋™ํ–ˆ๊ฑฐ๋‚˜ ์‚ฌ๋ผ์กŒ์œผ๋ฉฐ, ๊ทธ ๊ฒฐ๊ณผ ์ตœ๊ทผ์—๋Š” ๋„์†Œ๋งค์—…์ด๋‚˜ ์Œ์‹ ๋ฐ ์ˆ™๋ฐ•์—…๊ณผ ๊ฐ™์€ ์ผ๋ถ€ ๊ธฐ๋Šฅ๋งŒ์ด ๋‚จ๊ฒŒ ๋œ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์„ธ ๋ฒˆ์งธ, ์‚ฌํšŒ์  ์ธก๋ฉด์—์„œ๋Š” ๊ตฌ๋„์‹œ ์ง€์—ญ์€ ํŠน์ • ์ง€์—ญ์— ์ธ๊ตฌ๊ฐ€ ๋ฐ€์ง‘๋˜๋Š” ์–‘์ƒ์ด ์ตœ๊ทผ๊นŒ์ง€ ์ด์–ด์ง€๊ณ  ์žˆ์œผ๋ฉฐ, ์‹ ๋„์‹œ ์ง€์—ญ์˜ ๊ฒฝ์šฐ ๊ตฌ๋„์‹œ ๋ณด๋‹ค ๋‚ฎ์€ ์ธ๊ตฌ๋ฐ€๋„๋กœ ์‹ ๋„์‹œ ์ „ ์ง€์—ญ์— ๊ณ ๋ฅด๊ฒŒ ๋ถ„ํฌํ•˜๋Š” ๊ฒฝํ–ฅ์„ ๋ณด์ด๊ณ  ์žˆ์—ˆ๋‹ค. ๋˜ํ•œ ์ตœ๊ทผ์˜ ๋ถ„๋‹น๊ณผ ํŒ๊ต๋Š” ์ธ๊ตฌ ๊ตฌ์„ฑ ์ƒ ๊ฐ•ํ•œ ๋™์งˆ์„ฑ์„ ๊ฐ€์ง€๊ณ  ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ๋ณด์ด๋ฉฐ, ์ด๋กœ ์ธํ•œ ๊ตฌ๋„์‹œ์™€์˜ ์ง€์—ญ ๋ถ„ํ™” ํ˜„์ƒ์€ ๋”์šฑ ๋šœ๋ ทํ•ด์ง€๋Š” ์–‘์ƒ์„ ๋ณด์˜€๋‹ค. ๊ณ„์ธต์˜ ๋ณ€ํ™”์—์„œ๋Š” ์‹ ๋„์‹œ ์กฐ์„ฑ ์ดˆ๊ธฐ์—๋Š” ๊ตฌ๋„์‹œ์˜ ์†Œ๋“ ์ฆ๊ฐ€ ์–‘์ƒ์— ์•ฝ๊ฐ„์˜ ๋ณ€ํ™”๊ฐ€ ์žˆ๊ธฐ๋Š” ํ•˜์ง€๋งŒ, ์žฅ๊ธฐ์  ๊ด€์ ์—์„œ๋Š” ์ด๋“ค์˜ ์†Œ๋“ ๊ฒฉ์ฐจ ์–‘์ƒ์ด ์ „ํ˜€ ๊ฐœ์„ ๋˜์ง€ ์•Š์€ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋˜ํ•œ ์‹ ๋„์‹œ ๊ฑฐ์ฃผ๊ณ„์ธต์ด ๊ณ ์†Œ๋“์ธต๊ณผ ์ตœ์ €์†Œ๋“์ธต์œผ๋กœ๋งŒ ํ•œ์ •๋จ์œผ๋กœ์„œ ์ƒ๋Œ€์ ์œผ๋กœ ์ค‘์‚ฐ์ธต์ด ์‹ ๋„์‹œ ์ง€์—ญ์— ๊ฑฐ์ฃผํ•  ๊ธฐํšŒ๊ฐ€ ์ ์–ด์ง€๊ฒŒ ๋˜์–ด, ์žฅ๊ธฐ์ ์œผ๋กœ ์‹ ใ†๊ตฌ๋„์‹œ์˜ ์–‘๊ทนํ™”๊ฐ€ ์‹ฌํ™”๋˜๋Š” ๊ฒฐ๊ณผ๋ฅผ ๊ฐ€์ ธ์˜จ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ๊ณ„์ธต์˜ ๊ณต๊ฐ„์  ๋ถ„ํฌ ํŒจํ„ด ์—ญ์‹œ ์†Œ๋“์— ๋”ฐ๋ผ ๊ตฌ๋„์‹œ์™€ ๋ถ„๋‹นใ†ํŒ๊ต์˜ ์‹ ๋„์‹œ ์ง€์—ญ์œผ๋กœ ๋‚˜๋ˆ„๋Š” ์ด๋ถ„ํ™”์  ํ˜„์ƒ์ด ๋”์šฑ ๋šœ๋ ทํ•ด์ง€๊ณ  ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋„ค ๋ฒˆ์งธ, ๊ต๋ฅ˜์  ์ธก๋ฉด์—์„œ๋Š” ์‹ ใ†๊ตฌ๋„์‹œ๊ฐ„ ํ†ต๊ทผ๊ณผ ํ†ตํ•™ ํ†ตํ–‰๋Ÿ‰ ๋ชจ๋‘ 1995๋…„ ์ดํ›„ ์ง€์†์ ์œผ๋กœ ๊ฐ์†Œํ•˜๊ณ  ์žˆ์—ˆ์œผ๋ฉฐ, ์ตœ๊ทผ์—๋Š” ๊ฑฐ์˜ ๋ฐœ์ƒํ•˜์ง€ ์•Š๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ด๋Š” ์ „์ฒด์ ์œผ๋กœ ์‹ ๋„์‹œ ์กฐ์„ฑ ์ดํ›„ ์ง€๊ธˆ๊นŒ์ง€ ์‹œ๊ฐ„์ด ์ง€๋‚˜๋”๋ผ๋„ ์‹ ใ†๊ตฌ๋„์‹œ๊ฐ„์˜ ์ผ์ž๋ฆฌ์™€ ๊ต์œก์˜ ๊ต๋ฅ˜๋ฅผ ํ†ตํ•œ ์—ฐ๊ณ„์„ฑ์€ ์ „ํ˜€ ๊ฐœ์„ ๋˜์ง€ ์•Š์•˜์œผ๋ฉฐ ์˜คํžˆ๋ ค ๋” ์•…ํ™” ๋œ ๊ฒƒ์„ ์˜๋ฏธํ•œ๋‹ค. ๋‹ค์„ฏ ๋ฒˆ์งธ, ์‹œ๊ธฐ๋ณ„ ๋„์‹œ๊ตฌ์กฐ๋ชจ๋ธ์„ ๋„์ถœํ•˜์—ฌ ๊ทธ ํŠน์„ฑ์„ ์‚ดํŽด๋ณธ ๊ฒฐ๊ณผ ์ค‘์‹ฌ์—…๋ฌด์ง€์—ญ์€ 2000๋…„์ด ์ง€๋‚˜๊ณ  ๋ถ„๋‹น์ง€์—ญ์œผ๋กœ ์™„์ „ํžˆ ์ด๋™ํ•˜์˜€์œผ๋ฉฐ, ํŒ๊ต ์ง€์—ญ์œผ๋กœ ํ™•์žฅํ•˜๋Š” ํ˜•ํƒœ๋ฅผ ๋ณด์ด๊ณ  ์žˆ์—ˆ๋‹ค. ๋˜ํ•œ ๊ณ ์†Œ๋“์ธต ์ฃผ๊ฑฐ ์ง€์—ญ์€ ๊ตฌ๋„์‹œ์—์„œ ๋ถ„๋‹น์œผ๋กœ ๋‹ค์‹œ ํŒ๊ต๋กœ ์ด๋™ํ–ˆ์œผ๋ฉฐ ์ตœ๊ทผ ๊ตฌ๋„์‹œ ์ง€์—ญ์€ ๋ชจ๋“  ์ฃผ๊ฑฐ ์ง€์—ญ์ด ์ €์†Œ๋“์ธต ์ฃผ๊ฑฐ์ง€๋Œ€๋กœ ๋ฐ”๋€Œ๊ฒŒ ๋˜์—ˆ๋‹ค. ์—ฌ์„ฏ ๋ฒˆ์งธ, ์‹ ใ†๊ตฌ๋„์‹œ๊ฐ„์˜ ๋„์‹œ์„œ๋น„์Šค์˜ ์ง€์—ญ ๊ฐ„ ๊ฒฉ์ฐจ๋ฅผ ๋ถ„์„ํ•ด๋ณธ ๊ฒฐ๊ณผ ์ „์ฒด์ ์œผ๋กœ ๊ณต๊ณต์˜์—ญ๊ณผ ๋ฏผ๊ฐ„์˜์—ญ ๋ชจ๋‘์—์„œ ์‹ ๋„์‹œ ์ง€์—ญ์˜ ๊ฒฝ์šฐ ๊ทธ ์กฐ์„ฑ๋œ ์‹œ๊ธฐ์™€๋Š” ๊ด€๊ณ„์—†์ด ๋ถ„๋‹น๊ณผ ํŒ๊ต ์ „ ์ง€์—ญ์— ๊ฑธ์ณ ๊ณ ๋ฅด๊ฒŒ ๋„์‹œ์„œ๋น„์Šค๋ฅผ ์ œ๊ณต ๋ฐ›๊ณ  ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚œ ๋ฐ˜๋ฉด, ๊ตฌ๋„์‹œ ์ง€์—ญ์€ ์‹ ๋„์‹œ์™€์˜ ์ƒ๋Œ€์  ์ฐจ์ด๋„ ํด ๋ฟ ์•„๋‹ˆ๋ผ ๊ตฌ๋„์‹œ ๋‚ด์—์„œ๋„ ์ œ๊ณต๋˜๋Š” ๋„์‹œ ์„œ๋น„์Šค ์ˆ˜์ค€์˜ ์ง€์—ญ์  ํŽธ์ฐจ๊ฐ€ ํฐ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ํŠนํžˆ ์ด๋Ÿฌํ•œ ๊ฒฉ์ฐจ๋Š” ๊ณต๊ณต ์˜์—ญ๋ณด๋‹ค๋Š” ๋ฏผ๊ฐ„ ์˜์—ญ์—์„œ ๋” ํฌ๊ฒŒ ๋‚˜ํƒ€๋‚ฌ์œผ๋ฉฐ ๊ณต๊ฐ„ ๋ถ„ํฌ ํŒจํ„ด ์ƒ์œผ๋กœ๋Š” ์ตœ๊ทผ์˜ ์†Œ๋“ ๊ณ„์ธต์˜ ๊ณต๊ฐ„ ๋ถ„ํฌ ํŒจํ„ด๊ณผ ๋งค์šฐ ์œ ์‚ฌํ•˜๊ฒŒ ๋‚˜ํƒ€๋‚˜๋Š” ๊ฒƒ์„ ์•Œ ์ˆ˜ ์žˆ์—ˆ๋‹ค.I. ์„œ๋ก  1 1. ์—ฐ๊ตฌ์˜ ๋ฐฐ๊ฒฝ 1 2. ์—ฐ๊ตฌ์˜ ๋ชฉ์  6 3. ์—ฐ๊ตฌ์˜ ๋ฒ”์œ„ 6 3.1. ๊ณต๊ฐ„์  ๋ฒ”์œ„ 6 3.2. ์‹œ๊ฐ„์  ๋ฒ”์œ„ 8 3.3. ๋‚ด์šฉ์  ๋ฒ”์œ„ 8 4. ์—ฐ๊ตฌ์˜ ์ฃผ์š” ๋‚ด์šฉ ๋ฐ ํ๋ฆ„ 9 II. ์ด๋ก ์  ๋ฐฐ๊ฒฝ 15 1. ์‹ ใ†๊ตฌ๋„์‹œ์˜ ํ˜•์„ฑ ๋ฐ ์„ฑ์žฅ 15 1.1. ๋Œ€์ƒ์ง€์˜ ์—ญ์‚ฌ์  ๋ฐฐ๊ฒฝ 15 1.2. ์—ฐ๊ตฌ ๋Œ€์ƒ์ง€์˜ ์ •์˜ ๋ฐ ๊ตฌ๋ถ„ 17 2. ์ด๋ก ์  ๊ณ ์ฐฐ 18 2.1. ์‹ ๋„์‹œ์™€ ๊ตฌ๋„์‹œ์˜ ๊ฐœ๋… ๋ฐ ๊ด€๊ณ„ 18 2.2. ๋„์‹œ๊ณต๊ฐ„๊ตฌ์กฐ์™€ ์ง€์—ญ ๋ถ„ํ™” 21 2.3. ๋„์‹œ ๋ถˆ๊ท ํ˜•์˜ ๊ฐœ๋… ๋ฐ ์›์ธ 27 2.4. ๋„์‹œ์„œ๋น„์Šค์˜ ์ •์˜ ๋ฐ ๋ถ„๋ฅ˜ 29 3. ์„ ํ–‰ ์—ฐ๊ตฌ ๊ฒ€ํ†  31 3.1. ๊ธฐ์กด ์—ฐ๊ตฌ ๋™ํ–ฅ 31 3.2. ์‹œ์‚ฌ์  36 III. ๋ถ„์„์˜ ํ‹€ ์„ค์ • 41 1. ์‚ฌ๋ก€์ง€์—ญ ์„ ์ • 41 2. ์‹ ใ†๊ตฌ๋„์‹œ์˜ ์ง€์—ญ ๋ถ„ํ™” ๋ถ„์„์˜ ์ง€ํ‘œ ๋ฐ ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• 43 2.1. ์ด๋ก  ๋ฐ ์„ ํ–‰์—ฐ๊ตฌ์— ๋‚˜ํƒ€๋‚œ ์ง€ํ‘œ๋“ค์˜ ์ข…ํ•ฉ์  ๊ฒ€ํ†  43 2.2. ๋ถ„์„ ์ง€ํ‘œ์˜ ์„ ์ • 45 2.3. ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• 46 3. ๋„์‹œ์„œ๋น„์Šค ๊ฒฉ์ฐจ ๋ถ„์„์˜ ์ง€ํ‘œ ๋ฐ ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• 49 3.1. ๋ถ„์„ ์ง€ํ‘œ์˜ ์„ค์ • 49 3.2. ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• 53 4. ์—ฐ๊ตฌ ๋ฐ์ดํ„ฐ 59 IV. ์‹ ใ†๊ตฌ๋„์‹œ์˜ ์ง€์—ญ ๋ถ„ํ™”์™€ ๊ณต๊ฐ„ ๊ตฌ์กฐ 63 1. ๋ฌผ๋ฆฌ์  ์ธก๋ฉด 63 1.1. ๋„์‹œ๊ตฌ์กฐ 64 1.2. ๋„์‹œ์กฐ์ง 68 2. ๊ฒฝ์ œ์  ์ธก๋ฉด 70 2.1. ํ† ์ง€ 70 2.2. ์ฃผํƒ 83 2.3. ์‚ฐ์—… 94 3. ์‚ฌํšŒ์  ์ธก๋ฉด 108 3.1. ์ธ๊ตฌ 108 3.2. ๊ณ„์ธต 117 4. ๊ต๋ฅ˜์  ์ธก๋ฉด 129 4.1. ๋ถ„์„์˜ ๊ฐœ์š” 129 4.2. ํ†ตํ–‰ ๋ถ„์„ 132 4.3. ํ†ตํ–‰ ๋ถ„์„์˜ ์ข…ํ•ฉ 139 5. ์ข…ํ•ฉ 140 5.1. ๋ถ„์„ ๊ฒฐ๊ณผ์˜ ์š”์•ฝ ๋ฐ ์‹œ์‚ฌ์  140 5.2. ์ข…ํ•ฉ์  ๋„์‹œ๊ตฌ์กฐ๋ชจ๋ธ์˜ ๋„์ถœ 141 V. ์‹ ใ†๊ตฌ๋„์‹œ์˜ ๋„์‹œ์„œ๋น„์Šค ๊ฒฉ์ฐจ ๋ถ„์„ 147 1. ๊ณต๊ณต์˜์—ญ์˜ ๋„์‹œ์„œ๋น„์Šค 147 1.1. ๊ต์œก์„œ๋น„์Šค 147 1.2. ๊ณต์›์„œ๋น„์Šค 152 1.3. ๋Œ€์ค‘๊ตํ†ต์„œ๋น„์Šค 156 1.4. ๋ฌธํ™”์„œ๋น„์Šค 160 1.5. ์ข…ํ•ฉ ๋ถ„์„ 163 2. ๋ฏผ๊ฐ„์˜์—ญ์˜ ๋„์‹œ์„œ๋น„์Šค 167 2.1. ์ƒ์—…์„œ๋น„์Šค 167 2.2. ์˜๋ฃŒ์„œ๋น„์Šค 170 2.3. ์ข…ํ•ฉ ๋ถ„์„ 174 3. ์ข…ํ•ฉ์  ์‹œ์‚ฌ์  177 VI. ๊ฒฐ๋ก  183 1. ์—ฐ๊ตฌ ๊ฒฐ๊ณผ์˜ ์š”์•ฝ 183 2. ํ–ฅํ›„ ๋„์‹œ ์ •์ฑ…์—์˜ ์‹œ์‚ฌ์  186 3. ์—ฐ๊ตฌ์˜ ์˜์˜ ๋ฐ ํ•œ๊ณ„ 188 ์ฐธ๊ณ ๋ฌธํ—Œ 190 ๋ถ€๋ก 196 Abstract 213Docto

    ์ž์ฒด ์„ ํƒ์†Œ์ž ๊ธฐ๋Šฅ์„ ๊ฐ€์ง„ ์งˆํ™”๋ง‰ ๊ธฐ๋ฐ˜์˜ ์ €ํ•ญ๋ณ€ํ™”๋ฉ”๋ชจ๋ฆฌ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› ๊ณต๊ณผ๋Œ€ํ•™ ์ „๊ธฐยท์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€, 2017. 8. ๋ฐ•๋ณ‘๊ตญ.The drastic rise of the internet of things (IoT), cloud computing, and big data centers is generating an urgent demand for high-performance/low-power memory. However, conventional charge-based memories, such as flash memory and dynamic random access memory (DRAM), are rapidly approaching their scaling limits. As an alternative, resistive switching in a dielectric film sandwiched between top and bottom electrodes (BEs) has attracted great interest for next-generation non-volatile memory applications, due to its low power consumption, fast switching time, and superb scalability down to the atomic level. Among a variety of resistance materials, silicon-based dielectrics (e.g., Si, SiOx, and SiNx) have recently drawn great deal of attention from many researchers, owing to their good compatibility to conventional Si CMOS processes. Especially, SiNx-based resistive memory shows better switching performance than the SiOx-based devices, thanks to their abundant defects. In spite of recent advances in resistive memories, some key challenges such as overshoot current and sneak current in crossbar arrays still need to be overcome. In introductory part, the advantage of silicon nitride-based RRAM with Si bottom electrode is also described. In addition, the overshoot current and sneak current path issues in cross-point RRAM are discussed and a possible soultion is also presented. In this dissertation, the self-selection SiNx-based RRAM devices are proposed and their resistive switching characterization and mechanism were discussed. Firstly, the resistive switching characteristics of SiN-based RRAM with MIS structure was investigated. The different reset transitions are observed depending on the LRS resistance. The smooth gradual reset switching offers potential application for a synaptic device in neuromorphic system. Next, the SiNx-based RRAM with tunnel barrier shows built-in nonlinearity without an additional selector device. The high selectivity in the device with tunnel barrier can be explained by the fact that the electric field depedent nonlinear carrier injection. For another approach, the diode-like resistive switching is achieved by controling dopant concentration in silicon BE. high rectification ratio (>105) between forward and reverse currents for unipolar switching mode is demonstrated. Also, the forming polarity and nonlinearity in bipolar switching mode is discussed. The high selectivity and self-rectifying characteristics of SiNx-based RRAM cell would be one of the most virtuous merits in the high-density crossbar array.Chapter 1 Introduction 1 1.1 RRAM technology and its possible applications 1 1.2 Challenges of RRAM 7 1.3 SiN-based RRAM with metal-insulator-semiconductor (MIS) 10 Chapter 2 Resistive switching of Ni/SiNx/highly doped Si devices - 13 2.1 Experimental 13 2.2 Results and discussion 15 Chapter 3 Resistive switching of the device with tunnel barrier 28 3.1 Experimental 28 3.2 Results and discussion- 32 Chapter 4 High rectifying unipolar resistive switching in Ni/SiNx/p-Si memory devices 41 4.1 Experimental - 41 4.2 Results and discussion- 44 Chapter 5 Rectifying and nonlinear bipolar resistive switching in Ni/SiNx/p-Si memory devices 53 5.1 Experimental - 53 5.2 Results and discussion- 55 Chapter 6 Conclusions - 70 Bibliography 73 List of Publications- 81 Abstract in Korean 88Docto

    Quantitative Measurement Method for Possible Rib Fractures in Chest Radiographs

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    OBJECTIVES: This paper proposes a measurement method to quantify the abnormal characteristics of the broken parts of ribs using local texture and shape features in chest radiographs. METHODS: OUR MEASUREMENT METHOD COMPRISES TWO STEPS: a measurement area assignment and sampling step using a spline curve and sampling lines orthogonal to the spline curve, and a fracture-ness measurement step with three measures, asymmetry and gray-level co-occurrence matrix based measures (contrast and homogeneity). They were designed to quantify the regional shape and texture features of ribs along the centerline. The discriminating ability of our method was evaluated through region of interest (ROI) analysis and rib fracture classification test using support vector machine. RESULTS: The statistically significant difference was found between the measured values from fracture and normal ROIs; asymmetry (p < 0.0001), contrast (p < 0.001), and homogeneity (p = 0.022). The rib fracture classifier, trained with the measured values in ROI analysis, detected every rib fracture from chest radiographs used for ROI analysis, but it also classified some unbroken parts of ribs as abnormal parts (8 to 17 line sets; length of each line set, 2.998 ยฑ 2.652 mm; length of centerlines, 131.067 ยฑ 29.460 mm). CONCLUSIONS: Our measurement method, which includes a flexible measurement technique for the curved shape of ribs and the proposed shape and texture measures, could discriminate the suspicious regions of ribs for possible rib fractures in chest radiographs.ope

    ์„ฑ๋‚จ์‹œ์žฅ ์„ ๊ฑฐ์‚ฌ๋ก€๋ฅผ ์ค‘์‹ฌ์œผ๋กœ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ๊ฑด์„คํ™˜๊ฒฝ๊ณตํ•™๋ถ€, 2020. 8. ์ •์ฐฝ๋ฌด.์ด ์—ฐ๊ตฌ๋Š” ๋„์‹œ๊ณ„ํš ๊ด€๋ จ ๊ณต์•ฝ, ๊ณต์•ฝ ์†Œ์š”์˜ˆ์‚ฐ, ๊ฐœ๋ฐœ๊ณต์•ฝ๊ณผ ์œ ๊ถŒ์ž ๊ฐ„์˜ ์ง€๋ฆฌ์  ๊ฑฐ๋ฆฌ ๋“ฑ์ด ์ง€๋ฐฉ์„ ๊ฑฐ์—์„œ ๋“ํ‘œ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ๊ณต๊ณต์„ ํƒ๋ก ์  ๊ด€์ ์—์„œ ๋ถ„์„ํ•ด ๋ด„์œผ๋กœ์จ, ๋„์‹œ๊ณ„ํš์„ ๋น„๋กฏํ•œ ๊ด€๋ จ ๋ถ„์•ผ์— ๋Œ€ํ•œ ์‹œ์‚ฌ์ ์„ ๋ฐœ๊ฒฌํ•˜๋Š” ๊ฒƒ์„ ๋ชฉ์ ์œผ๋กœ ํ•œ๋‹ค. ์ด ์—ฐ๊ตฌ์—๋Š” ์ค‘์•™์„ ๊ฑฐ๊ด€๋ฆฌ์œ„์›ํšŒ๊ฐ€ ๊ณตํ‘œํ•˜๋Š” ์ง€๋ฐฉ์„ ๊ฑฐ ๋ฐ์ดํ„ฐ ๋ฐ ์ง€์ž์ฒด์žฅ ํ›„๋ณด์ž์˜ ๊ณต์•ฝ์ž๋ฃŒ๋Š” ๋ฌผ๋ก , ๋„์‹œ๊ณ„ํš ๊ด€๋ จ ๋น…๋ฐ์ดํ„ฐ ๋“ฑ์ด ํ™œ์šฉ๋˜์—ˆ์œผ๋ฉฐ, ์—ฐ๊ตฌ์— ์ ์šฉ๋œ ํ†ต๊ณ„ ๋ฐฉ๋ฒ•์€ ๊ธฐ์ˆ ํ†ต๊ณ„, t-๊ฒ€์ฆ, ํšŒ๊ท€๋ถ„์„ ๋“ฑ์ด๋‹ค. ์—ฐ๊ตฌ๊ฐ€์„ค์˜ ์ƒ๋‹น ๋ถ€๋ถ„์€ ์ฑ„ํƒ๋˜์—ˆ์œผ๋‚˜, ์ผ๋ถ€ ๊ธฐ๊ฐ๋œ ๋‚ด์šฉ๋„ ํฌํ•จ๋˜์–ด ์žˆ๋Š”๋ฐ, ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋ฅผ ์š”์•ฝํ•ด ๋ณด๋ฉด ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ์ฒซ์งธ, ์ง€์—ญ์ฃผ๋ฏผ์€ ์ฃผํƒ์ •์ฑ…์— ๋Œ€ํ•œ ์š”๊ตฌ๊ฐ€ ๊ฐ€์žฅ ๋†’๊ณ  ๋‹ค์Œ์œผ๋กœ ์‚ฌํšŒ๋ณต์ง€ ์ •์ฑ…์ด ๋’ค๋ฅผ ์ž‡๊ณ  ์žˆ๋‹ค. ์ง€์ž์ฒด์žฅ ํ›„๋ณด์ž์˜ ๋„์‹œ๊ณ„ํš ๊ด€๋ จ ๊ณต์•ฝ์€ ์ง€์—ญ์ฃผ๋ฏผ์˜ ์ฃผ๊ฑฐ ๊ด€๋ จ ๋ถˆ๋งŒ๊ณผ ์š”๊ตฌ์‚ฌํ•ญ์„ ์ƒ๋‹น ๋ถ€๋ถ„ ๋ฐ˜์˜ํ•˜๊ณ  ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋‘˜์งธ, ์ง€์ž์ฒด์žฅ ํ›„๋ณด์ž์˜ ๋“ํ‘œ์œจ ๋ณ€๋™์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ๋„์‹œ์ •๋น„ ๋ฐ ์ฃผ๊ฑฐ๊ฐœ์„  ์ง€์› ๊ด€๋ จ ์„ธ๋ถ€ ๊ณต์•ฝ์—๋Š” ์žฌ๊ฐœ๋ฐœ ์ง€์›, ์†Œ๊ทœ๋ชจ ์ •๋น„ ์ง€์›, ๋…ธํ›„ ์•„ํŒŒํŠธ ๊ฐœ์„ (๋ฆฌ๋ชจ๋ธ๋ง ํฌํ•จ) ์ง€์› ๋“ฑ์ด ์žˆ์Œ์ด ํ™•์ธ๋˜์—ˆ๋‹ค. ๋‹ค๋งŒ, ์žฌ๊ฐœ๋ฐœ ์ง€์›๊ณผ ์†Œ๊ทœ๋ชจ ์ •๋น„ ์ง€์› ๊ณต์•ฝ์€ ๋ถ€์ (-)์ธ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ๊ฒƒ์œผ๋กœ ๋ณด์—ฌ์„œ ํ•ด์„์— ์‹ ์ค‘ํ•  ํ•„์š”๊ฐ€ ์žˆ๋‹ค. ์…‹์งธ, ์ง€์ž์ฒด์žฅ ํ›„๋ณด์ž์˜ ๋“ํ‘œ์œจ ๋ณ€๋™์— ์œ ์˜ํ•œ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ๋„์‹œ๊ธฐ๋ฐ˜์‹œ์„ค ๊ด€๋ จ ์„ธ๋ถ€ ๊ณต์•ฝ์œผ๋กœ๋Š” ์ง€ํ•˜์ฒ ์—ญ ๊ฐœ์„ , ๋ฒ„์Šค๊ตํ†ต ๊ฐœ์„ , ์–ด๋ฆฐ์ด์ง‘ ์‹ ์„ค, ์ฃผ์ฐจ์žฅ ํ™•์ถฉ, ์‹œ๋ฆฝ์˜๋ฃŒ์› ๊ฑด๋ฆฝ, ์ง€์—ญํŽธ์˜์‹œ์„ค ๊ฑด๋ฆฝ, ๊ณต์› ๊ฐœ์„ , ๋„๋กœ ์†Œ์Œ ๋ฐฉ์ง€, ๊ฐœ๋ฐœ๊ทœ์ œ ์™„ํ™” ๋“ฑ๊ณผ ๊ฐ™์€ ๊ฒƒ๋“ค์ด ์žˆ๋‹ค. ๋‹ค๋งŒ, ์‹œ๋ฆฝ์˜๋ฃŒ์› ๊ฑด๋ฆฝ๊ณผ ๊ฐ™์ด ์ „์ฒด ์ฃผ๋ฏผ์—๊ฒŒ๋Š” ํŽธ์ต์ด ํฌ์ง€๋งŒ, ์ธ๊ทผ ์ง€์—ญ์ฃผ๋ฏผ์ด ๊ธฐํ”ผํ•˜๋Š” ์‹œ์„ค์˜ ๊ฒฝ์šฐ์—๋Š” ํ•ด๋‹น ๊ณต์•ฝ์ด ์žˆ๋Š” ์ง€์—ญ์—์„œ๋Š” ๋“ํ‘œ์œจ ๋ณ€๋™์— ๋ถ€์ (-) ์š”์ธ์ด ๋  ์ˆ˜ ์žˆ๋‹ค๋Š” ๊ฒƒ์ด ํ™•์ธ๋˜์—ˆ์œผ๋ฉฐ, ์ด๋Ÿฌํ•œ ๋‹˜๋น„์‹œ์„ค์€ ์—ญ์˜ ๊ฑฐ๋ฆฌ ์กฐ๋ฝ ํšจ๊ณผ๊ฐ€ ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋„ท์งธ, ๋„์‹œ๊ณ„ํš ๊ด€๋ จ ๊ณต์•ฝ ์†Œ์š”์˜ˆ์‚ฐ ๊ทœ๋ชจ์— ๋”ฐ๋ผ ๋“ํ‘œ์œจ๊ณผ ๋“ํ‘œ ๊ฒฝ์Ÿ๋„์— ์œ ์˜ํ•œ ์˜ํ–ฅ์ด ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ํŠนํžˆ, ๋“ํ‘œ์œจ 1%P๋ฅผ ์ฆ๊ฐ€์‹œํ‚ค๊ธฐ ์œ„ํ•ด์„œ๋Š” ๊ณต์•ฝ์˜ˆ์‚ฐ์ด ์•ฝ 237์–ต ์› ์ •๋„ ์ถ”๊ฐ€๋˜์–ด์•ผ ํ•˜๋ฉฐ, ๊ณต์•ฝ์˜ˆ์‚ฐ์„ ๊ธฐ์ค€์œผ๋กœ ๋ณผ ๋•Œ ์œ ๊ถŒ์ž๊ฐ€ ํ–‰์‚ฌํ•˜๋Š” 1ํ‘œ์˜ ํšจ์šฉ๊ฐ€์น˜๋Š” ์•ฝ 236๋งŒ ์› ์ •๋„๋˜๋Š” ๊ฒƒ์œผ๋กœ ์ถ”์ •๋œ๋‹ค. ๊ทธ๋ฆฌ๊ณ , ๊ณต์•ฝ์˜ˆ์‚ฐ ๊ทœ๋ชจ๊ฐ€ ์ผ์ • ์ˆ˜์ค€์„ ๋„˜์–ด์„œ๋ฉด ๋“ํ‘œ์œจ์˜ ๊ธฐ์šธ๊ธฐ์— ์™„๋งŒํ•ด์ง€๋Š” ๊ฒฝํ–ฅ์ด ์žˆ์œผ๋ฉฐ, ๊ณต์•ฝ์˜ ๊ตฌ์ฒด์„ฑ ์—ฌ๋ถ€์— ๋”ฐ๋ผ ํ›„๋ณด์ž ๊ฐ„์— ๋“ํ‘œ์œจ์— ์ฐจ์ด๊ฐ€ ๋ฐœ์ƒํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋‹ค์„ฏ์งธ, ๋Œ€๊ทœ๋ชจ ๋„์‹œ๊ธฐ๋ฐ˜์‹œ์„ค ํˆฌ์ž์ง€์—ญ์œผ๋กœ๋ถ€ํ„ฐ ์œ ๊ถŒ์ž์˜ ๊ฑฐ๋ฆฌ๋Š” ๋“ํ‘œ์œจ ๋ณ€๋™์— ๋Œ€ํ•ด ๊ฑฐ๋ฆฌ ์กฐ๋ฝ์„ฑ์„ ๋ณด์ด๊ณ  ์žˆ์œผ๋ฉฐ, ํŽธ์ต์˜ ์ˆ˜ํ˜œ ๋ฒ”์œ„๊ฐ€ ๋„“์€ ์‚ฌ์—…์— ๋Œ€ํ•œ ๊ฑฐ๋ฆฌ์กฐ๋ฝ์„ฑ์˜ ๊ธฐ์šธ๊ธฐ๋Š” ๊ทธ๋Ÿฌํ•œ ํŽธ์ต์˜ ์ˆ˜ํ˜œ ๋ฒ”์œ„๊ฐ€ ์ข์€ ๊ฒฝ์šฐ์— ๋น„ํ•ด ๋” ํฐ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ผ๋ฐ˜์ ์œผ๋กœ, ์ง€์—ญ์ฃผ์˜ ๋˜๋Š” ์ •๋‹น์ง€์ง€๊ฐ€ ์œ ๊ถŒ์ž์˜ ํˆฌํ‘œํ–‰ํƒœ์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์ฃผ์š” ์š”์ธ์œผ๋กœ ์ธ์ •๋˜๊ณ  ์žˆ์ง€๋งŒ, ์ด ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด์„œ ๋„์‹œ๊ณ„ํš ๊ด€๋ จ ๊ณต์•ฝ, ๊ณต์•ฝ์˜ˆ์‚ฐ, ๊ทธ๋ฆฌ๊ณ  ๊ฐœ๋ฐœ์‚ฌ์—…์˜ ํŽธ์ต์ˆ˜ํ˜œ ๋ฒ”์œ„์— ๋Œ€ํ•œ ๊ฑฐ๋ฆฌ ์กฐ๋ฝ์„ฑ ๋“ฑ๊ณผ ๊ฐ™์€ ์š”์ธ๋„ ์ง€๋ฐฉ์„ ๊ฑฐ์—์„œ๋Š” ์ค‘์š”ํ•œ ์˜ํ–ฅ์š”์ธ์ด๋ผ๋Š” ์ ์ด ๊ทœ๋ช…๋˜์—ˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ , ์ด ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด์„œ ๋„์‹œ๊ณ„ํš ๊ด€๋ จ ๊ณต์•ฝ์˜ ์ง€๋ฆฌ์  ์†์„ฑ๊ณผ ์œ ๊ถŒ์ž์˜ ํˆฌํ‘œํ–‰ํƒœ ๊ฐ„์˜ ์˜ํ–ฅ ๊ด€๊ณ„์— ๊ด€ํ•œ ์—ฐ๊ตฌ์˜ ์ค‘์š”์„ฑ์ด ํ™•์ธ๋˜์—ˆ๋‹ค๋Š” ์ ์—์„œ, ํ–ฅํ›„ ๋„์‹œ๊ณ„ํšํ•™ ๋˜๋Š” ์„ ๊ฑฐ์ง€๋ฆฌํ•™ ๋ถ„์•ผ์˜ ์—ฐ๊ตฌ์— ํ•™๋ฌธ์ ์œผ๋กœ ๊ธฐ์—ฌํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€ํ•œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜, ์ด ์—ฐ๊ตฌ๋Š” ๊ธฐ์กด ์—ฐ๊ตฌ์—์„œ ์ผ๋ฐ˜์ ์œผ๋กœ ํฌํ•จํ•˜๊ณ  ์žˆ๋Š” ์œ ๊ถŒ์ž์˜ ์‚ฌํšŒ๊ฒฝ์ œ์  ๋ฐฐ๊ฒฝ ์š”์ธ์ด ์„ ๊ฑฐ ๊ฒฐ๊ณผ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ๊ฒ€ํ† ํ•  ์ˆ˜ ์—†์—ˆ๋‹ค๋Š” ํ•œ๊ณ„๊ฐ€ ์žˆ์œผ๋ฏ€๋กœ, ํ–ฅํ›„ ์—ฐ๊ตฌ์—์„œ๋Š” ์ด๋Ÿฌํ•œ ๋ถ€๋ถ„์„ ๋ณด์™„ํ•  ์ˆ˜ ์žˆ๋Š” ์—ฐ๊ตฌ๊ฐ€ ๋‚˜์˜ฌ ์ˆ˜ ์žˆ๊ธฐ๋ฅผ ๊ธฐ๋Œ€ํ•œ๋‹ค. ํŠนํžˆ, ์ด ์—ฐ๊ตฌ๋Š” ์„ฑ๋‚จ์‹œ๋ผ๋Š” ์ง€์—ญ์  ์ œํ•œ๊ณผ ์ œ6๊ธฐ ์ง€๋ฐฉ์„ ๊ฑฐ๋ผ๊ณ  ํ•˜๋Š” ์‹œ๊ฐ„์  ์ œํ•œ์„ ๋ฐ”ํƒ•์œผ๋กœ ํ•˜๊ณ  ์žˆ์–ด์„œ, ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋ฅผ ์ผ๋ฐ˜ํ™”ํ•˜๋Š” ๋ฐ ํ•œ๊ณ„๊ฐ€ ์žˆ๋‹ค๋Š” ์ ์— ์œ ์˜ํ•  ํ•„์š”๊ฐ€ ์žˆ๋‹ค.The aim of this study is to analyze the effect of urban planning-related promises, budgets for promises, geographical distances between development promises, and voters on the votes in local elections from a public choice perspective, as well as to discover the implications for related areas including urban planning. In this study, local election data published by the Central Election Management Committee, along with the promise data of candidates for local governments and big data related to urban planning, were used. A large part of the research hypothesis was adopted, but some rejected content was also included. The results of the study are summarized as follows. First, local residents have the highest demand for housing policies, followed by social welfare policies. It was found that the promises of candidates for local governments reflect the residents' complaints and needs on urban planning. Second, it was confirmed that the detailed promises related to urban maintenance and residential improvement support, which affected the change of vote ratio among local government candidates, included redevelopment support, small-scale maintenance support, and improvement of old apartments (including remodeling). However, the promise of redevelopment support and small-scale maintenance support seemed to have a negative effect and needed to be carefully interpreted. Third, detailed promises related to urban infrastructure that significantly affected the change of vote ratio among local government candidates included improving subway stations, enhancing bus transportation, setting up daycare centers, expanding parking lots, building municipal medical centers, constructing local convenience facilities, upgrading parks, preventing road noise, and developing regulations. However, it has been confirmed that although the benefits, such as the construction of a municipal medical center in the case of facilities avoided by local residents, are advantageous for all residents, they can be seen as negative factors in the change of vote ratio in the area where the promise was presented. These Nimbi facilities were found to have a negative distance decay effect. Fourth, it was found that there was a significant effect on the vote ratio and the degree of vote competition according to the amount of budget required for urban planning promises. In particular, the promised budget should be added to about 23.7 billion won in order to increase the 1%P in the vote ratio. Based on the promised budget, it was estimated that the utility value of the vote exercised by a voter was approximately 2.36 million won. In addition, there was a tendency for the vote ratio slope to soften and, according to the specificity of the promise, there was a difference in the vote ratio between candidates when the scale of the promised budget exceeded a certain level. Fifth, the distance of voters from large-scale urban infrastructure investment zones showed distance decay with respect to the change in vote ratio and, for projects with a wide range of benefits, the slope of distance decay was found to be greater than for the narrow range. In general, regionalism or political party support was recognized as a major factor influencing the voter's voting behavior. However, this study has shown that urban planning-related promises, promised budgets, and distance decay to the range of benefits for development projects were also important influence factors in local elections. In addition, the importance of the study on the relationship between the geographical attributes of urban planning-related promises and the voter's voting behavior was confirmed through this study, which was expected to contribute academically to the study of urban planning or electoral geography in the future. However, this study is limited in that it was not possible to examine the effect of the socio-economic background factors of the electorate generally included in previous studies on the election results. It is expected that future studies may come up with studies that can complement these areas. In particular, it should be noted that this study is based on the regional limitation of Seongnam city and the temporal limitation of the 6th local election, so there is a constraint in generalizing the results of the study.์ œ1์žฅ ์„œ๋ก  1 ์ œ1์ ˆ ์—ฐ๊ตฌ์˜ ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉ์  1 ์ œ2์ ˆ ์—ฐ๊ตฌ์˜ ๋ฒ”์œ„ ๋ฐ ๊ตฌ์„ฑ 4 1. ์—ฐ๊ตฌ์˜ ๋ฒ”์œ„ 4 2. ์—ฐ๊ตฌ์˜ ๊ตฌ์„ฑ 6 3. ์šฉ์–ด์˜ ์ •์˜ 7 ์ œ2์žฅ ์ด๋ก ์  ๋ฐฐ๊ฒฝ ๋ฐ ์„ ํ–‰์—ฐ๊ตฌ ๊ณ ์ฐฐ 9 ์ œ1์ ˆ ์ด๋ก ์  ๋ฐฐ๊ฒฝ 9 1. ๊ณต๊ณต์„ ํƒ๋ก  9 1) ๊ณต๊ณต์„ ํƒ๋ก ์˜ ๊ธฐ๋ณธ ๊ฐ€์ • 10 2) ๊ณต๊ณต์„ ํƒ๋ก ์˜ ์ฃผ์š” ์Ÿ์  12 3) ๊ณต๊ณต์„ ํƒ๋ก ๊ณผ ์„ ๊ฑฐ 15 2. ๊ฑฐ๋ฆฌ ์กฐ๋ฝ์„ฑ 16 ์ œ2์ ˆ ์„ ํ–‰์—ฐ๊ตฌ ๊ณ ์ฐฐ 18 1. ์ •์น˜์ธ์˜ ํ–‰ํƒœ ๊ด€๋ จ ์—ฐ๊ตฌ 19 2. ์œ ๊ถŒ์ž์˜ ํ–‰ํƒœ ๊ด€๋ จ ์—ฐ๊ตฌ 23 3. ์„ ๊ฑฐ๊ณต์•ฝ๊ณผ ๋“ํ‘œ์œจ ๊ด€๋ จ ์—ฐ๊ตฌ 27 4. ๊ฑฐ๋ฆฌ ์กฐ๋ฝ์„ฑ๊ณผ ์„ ๊ฑฐ ๊ด€๋ จ ์—ฐ๊ตฌ 29 ์ œ3์ ˆ ์—ฐ๊ตฌ์˜ ํ•„์š”์„ฑ 32 ์ œ3์žฅ ์—ฐ๊ตฌ๋ฐฉ๋ฒ• 35 ์ œ1์ ˆ ์—ฐ๊ตฌ๋ฌธ์ œ 35 ์ œ2์ ˆ ์—ฐ๊ตฌ๊ฐ€์„ค 37 ์ œ3์ ˆ ์—ฐ๊ตฌ์„ค๊ณ„ 47 1. ์—ฐ๊ตฌ์ž๋ฃŒ 47 1) ์ง€๋ฐฉ์„ ๊ฑฐ ๋“ํ‘œ์œจ ์ž๋ฃŒ 47 2) ์‚ฌํšŒ์กฐ์‚ฌ ํ†ต๊ณ„์ž๋ฃŒ 49 3) ๊ด€๋ จ ์‚ฌ๋ก€์™€ ๋น…๋ฐ์ดํ„ฐ 50 2. ๋ณ€์ˆ˜์˜ ๊ตฌ์„ฑ 51 3. ๋ถ„์„์˜ ํ‹€ 52 ์ œ4์žฅ ๋„์‹œ๊ณ„ํš ๊ด€๋ จ ๊ณต์•ฝ์˜ ์˜ํ–ฅ ๋ถ„์„ 53 ์ œ1์ ˆ ์ง€์—ญ์ฃผ๋ฏผ์˜ ์š”๊ตฌ๋ถ„์„๊ณผ ๋„์‹œ๊ณ„ํš ๊ด€๋ จ ๊ณต์•ฝ 53 1. ์ง€์—ญ์ฃผ๋ฏผ์˜ ์ฃผ๊ฑฐ์™€ ์‹œ์ •์— ๋Œ€ํ•œ ์š”๊ตฌ๋ถ„์„ 53 1) ์ฃผ๊ฑฐ๋งŒ์กฑ๋„์™€ ๋ถˆ๋งŒ์š”์ธ 53 2) ์‹œ์ • ๊ด€์‹ฌ๋„์™€ ์š”๊ตฌ์‚ฌํ•ญ 56 2. ๋„์‹œ๊ณ„ํš ๊ด€๋ จ ๊ณต์•ฝ์˜ ๋น„๊ต 58 ์ œ2์ ˆ ๋„์‹œ์ •๋น„ ๋ฐ ์ฃผ๊ฑฐ๊ฐœ์„  ๊ด€๋ จ ๊ณต์•ฝ 60 1. ๊ณต์•ฝ์˜ ์˜ํ–ฅ๋ ฅ ๋ถ„์„ 60 2. ๋ถ„์„ ๊ฒฐ๊ณผ์˜ ํ•ด์„ 63 1) ์„ธ๋ถ€ ๊ณต์•ฝ ๊ฒ€์ฆ 63 2) ๊ฒฝ์Ÿ์ž์™€ ๋™์ผ ๊ณต์•ฝ์˜ ํšจ๊ณผ 65 3) ์ „๊ธฐ์™€ ๋™์ผ ๊ณต์•ฝ์˜ ํšจ๊ณผ 66 ์ œ3์ ˆ ๋„์‹œ๊ธฐ๋ฐ˜์‹œ์„ค ๊ด€๋ จ ๊ณต์•ฝ 68 1. ๊ณต์•ฝ์˜ ์˜ํ–ฅ๋ ฅ ๋ถ„์„ 68 2. ๋ถ„์„ ๊ฒฐ๊ณผ์˜ ํ•ด์„ 70 1) ์„ธ๋ถ€ ๊ณต์•ฝ ๊ฒ€์ฆ 70 2) ๋‹˜๋น„์‹œ์„ค์˜ ํšจ๊ณผ 71 ์ œ4์ ˆ ๋„์‹œ๊ณ„ํš ๊ด€๋ จ ๊ณต์•ฝ์˜ˆ์‚ฐ 74 1. ๊ณต์•ฝ์˜ˆ์‚ฐ์ด ๋“ํ‘œ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 74 1) ๊ณต์•ฝ์˜ˆ์‚ฐ์˜ ์‚ฐ์ •๊ณผ์ • 74 2) ๊ณต์•ฝ์˜ˆ์‚ฐ์˜ ์˜ํ–ฅ๋ ฅ ๊ฒ€์ฆ 75 2. ๋“ํ‘œ ์ „๋žต์˜ˆ์‚ฐ ๊ทœ๋ชจ์™€ ํˆฌํ‘œ ํšจ์šฉ๊ฐ€์น˜ ์ถ”์ • 77 1) ์ •์น˜์ธ์˜ ๋“ํ‘œ ์ „๋žต์˜ˆ์‚ฐ ๊ทœ๋ชจ ์ถ”์ • 77 2) ์œ ๊ถŒ์ž ํˆฌํ‘œ์˜ ํšจ์šฉ๊ฐ€์น˜ ์ถ”์ • 78 3. ๊ณต์•ฝ ์˜ˆ์‚ฐ๊ทœ๋ชจ์™€ ๊ตฌ์ฒด์„ฑ์— ๋”ฐ๋ฅธ ๋“ํ‘œ์œจ ๊ณก์„ ์˜ ๋น„๊ต 80 1) ์˜ˆ์‚ฐ๊ทœ๋ชจ์— ๋”ฐ๋ฅธ ๋“ํ‘œ์œจ ๊ณก์„ ์˜ ๊ธฐ์šธ๊ธฐ ๋ณ€ํ™” 80 2) ๊ณต์•ฝ์˜ ๊ตฌ์ฒด์„ฑ ์—ฌ๋ถ€์— ๋”ฐ๋ฅธ ๋“ํ‘œ์œจ ๋น„๊ต 82 ์ œ5์ ˆ ๋Œ€๊ทœ๋ชจ ๊ฐœ๋ฐœ๊ณต์•ฝ ์‚ฌ๋ก€์™€ ๊ฑฐ๋ฆฌ ์กฐ๋ฝ์„ฑ ๋ถ„์„ 84 1. ๋„์‹œ๊ฐœ๋ฐœ ๊ด€๋ จ ๋Œ€๊ทœ๋ชจ ๊ณต์•ฝ ์‚ฌ๋ก€ 84 1) ์‹ ๋ถ„๋‹น์„  ๋ฏธ๊ธˆ ํ™˜์Šน์—ญ ์‹ ์„ค ์‚ฌ์—… 85 2) ๋ถ„๋‹น์ˆ˜์„œ ๊ฐ„ ๊ณ ์†๋„๋กœ ๊ณต์›ํ™” ์‚ฌ์—… 87 2. ๋Œ€๊ทœ๋ชจ ๊ฐœ๋ฐœ๊ณต์•ฝ๊ณผ ๊ฑฐ๋ฆฌ ์กฐ๋ฝ์„ฑ 89 1) ๋ฏธ๊ธˆ ํ™˜์Šน์—ญ 90 2) ๋„๋กœ ๊ณต์›ํ™” 91 3. ๋ถ„์„ ๊ฒฐ๊ณผ์˜ ํ•ด์„ 92 ์ œ5์žฅ ๊ฒฐ ๋ก  96 ์ œ1์ ˆ ์š”์•ฝ ๋ฐ ๊ฒฐ๋ก  96 ์ œ2์ ˆ ์—ฐ๊ตฌ์˜ ํ•œ๊ณ„ 100 ์ฐธ๊ณ ๋ฌธํ—Œ 102 Abstract 118Docto

    The synthetic peptide on titanium surface enhances osteogenesis

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์น˜์˜ํ•™๊ณผ, 2017. 2. ๊ตฌ์˜.Introduction The oligopeptide including PHSRN and RGD sequence of fibronectin (F20) promoted cellular activity like adhesion, migration, proliferation and differentiation with various cells. In this study, the biologic effect to cellular activity of F20 on titanium (Ti) surface was investigated with the synthetic oligopeptide and evaluated as a biomolecule to improve the surface characteristics of dental implant. Materials and Methods The change of surface characteristics after applying synthetic F20 on machined and SLA Ti surface through adsorption was investigated with confocal laser scanning microscopy (CLSM) observation. The stromal cell line ST2 was used for cell source. The quality of coating was evaluated with fluorescence microscopy and confirmed with measuring of fluorescence intensity. SEM and CLSM observation for cell adhesion, cell migration assembly kit for cell migration, Picogreen assay for cell proliferation, real time PCR and ALP activity assay for differentiation, and immunoblot and ALP staining and real time PCR for molecular mechanism was used for evaluation, respectively. Results The change of roughness with the coating of F20 was not remarkable. The surface characteristic of machined and SLA Ti was different after adsorption and observed with CLSM. Cell attachment was more enhanced on machined surface with F20 than SLA. The difference was more prominent in early stage after applying F20. Migration of ST2 cell was enhanced with F20 treatment in 6, 24 h. Cell proliferation and differentiation was stimulated with F20 apply. The extracellular signal-regulated kinase (Erk) signaling pathway was activated with F20 and confirmed with inhibitor U0126 apply. Conclusions From the findings of this study, F20 can be considered to promote osteoblast activity and stimulate differentiation through Erk signaling pathway. F20 can be a choice of biomaterials to improve surface modification of dental implant.I. Introduction 1 II. Materials and Methods 4 III. Results 10 IV. Discussion 15 V. References 18Docto

    Automation of Spine Curve Assessment in Frontal Radiographs Using Deep Learning of Vertebral-tilt Vector

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    In this paper, an automated and visually explainable system is proposed for a scoliosis assessment from spinal radiographs, which deals with the drawback of manual measurements, which are known to be time-consuming, cumbersome, and operator dependent. Deep learning techniques have been successfully applied in the accurate extraction of Cobb angle measurements, which is the gold standard for a scoliosis assessment. Such deep learning methods directly estimate the Cobb angle without providing structural information of the spine which can be used for diagnosis. Although conventional segmentationbased methods can provide the spine structure, they still have limitations in the accurate measurement of the Cobb angle. It would be desirable to build a clinician-friendly diagnostic system for scoliosis that provides not only an automated Cobb angle assessment but also local and global structural information of the spine. This paper addresses this need through the development of a hierarchical method which consisting of three major parts. (1) A confidence map is used to selectively localize and identify all vertebrae in an accurate and robust manner, (2) vertebral-tilt field is used to estimate the slope of an individual vertebra, and (3) the Cobb angle is determined by combining the vertebral centroids with the previously obtained vertebral-tilt field. The performance of the proposed method was validated, resulting in circular mean absolute error of 3:51 and symmetric mean absolute percentage error of 7:84% for the Cobb angle.ope

    False Femoral Neck Fracture Detected during Shaft Nailing: A Mach Band Effect

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    Femoral neck fractures are associated with femoral shaft fractures in 1% to 9% of cases. Undisplaced neck fractures are susceptible to displacement during shaft nailing. We report the case of a 57-year-old male patient in whom we performed standard intramedullary nailing for a femoral shaft fracture. In doing so, we identified a vertical radiolucent line at the femoral neck, which was thought to be further displacement of a hidden silent fracture or an iatrogenic fracture that developed during nail insertion. Consequently, we decided to switch to reconstructive femoral nailing. Postoperative hip imaging failed to show the femoral neck fracture that we saw in the operating room. Here, we discuss the aforementioned case and review the literature concerning this artifact.ope
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