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    ์ด๋ฏธ์ง€ ์บก์…”๋‹์„ ์œ„ํ•œ ์Šค๋งˆํŠธ ๋žœ๋ค์ด๋ ˆ์ด์ง• ๋ฐ์ดํ„ฐ ์ฆ๊ฐ• ๊ธฐ๋ฒ•

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€, 2021. 2. ์ด์ƒ๊ตฌ.Image captioning is a task in machine learning that aims to automatically generate a natural language description of a given image. It is considered a crucial task because of its broad applications and the fact that it is a bridge between computer vision and natural language processing. However, image-caption paired dataset is restricted in both quantity and diversity, which is essential when training a supervised model. Various approaches have been made including semi-supervised and unsupervised learning, but the result is still far from that of supervised approach. While data augmentation can be the solution for data deficiency in the field, existing data augmentation techniques are often designed for image classification tasks and are not suitable for image captioning tasks. Thus, in this paper, we introduce a new data augmentation technique designed for image captioning. The proposed Smart Random Erasing (SRE) is inspired from the Random Erasing augmentation technique, and it complements the drawbacks of Random Erasing to achieve the best performance boost when applied to image captioning. We also derive idea from AutoAugment to automatically search optimal hyperparameters via reinforcement learning. This study shows better results than the traditional augmentation techniques and the state-of-the-art augmentation technique RandAugment when applied to image captioning tasks.์ด๋ฏธ์ง€ ์บก์…”๋‹์ด๋ž€ ์ž…๋ ฅ์ด ์ด๋ฏธ์ง€๋กœ ์ฃผ์–ด์กŒ์„ ๋•Œ, ์ด๋ฏธ์ง€์— ๋Œ€ํ•œ ์ž์—ฐ์–ด ๋ฌ˜์‚ฌ๋ฅผ ์ƒ์„ฑํ•˜๋Š” ๋จธ์‹ ๋Ÿฌ๋‹์˜ ํ•œ ๊ณผ์ œ์ด๋‹ค. ์ด๋ฏธ์ง€ ์บก์…”๋‹์€ ์‹œ๊ฐ์žฅ์• ์ธ์„ ์œ„ํ•œ ๋ณด์กฐ์ž๋ง‰ ์ƒ์„ฑ, ์บก์…˜ ์ƒ์„ฑ์„ ํ†ตํ•œ ๊ฒ€์ƒ‰์—”์ง„ ์„ฑ๋Šฅ ํ–ฅ์ƒ ๋“ฑ ๋ฐฉ๋Œ€ํ•œ ์–ดํ”Œ๋ฆฌ์ผ€์ด์…˜์„ ๊ฐ€์งˆ ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์ž์—ฐ์–ด ์ฒ˜๋ฆฌ์™€ ์ปดํ“จํ„ฐ ๋น„์ „ ๋ถ„์•ผ๋ฅผ ์—ฐ๊ฒฐํ•˜๋Š” ๊ณผ์ œ๋กœ์„œ ์ค‘์š”์„ฑ์„ ์ง€๋‹ˆ๊ณ  ์žˆ๋‹ค. ํ•˜์ง€๋งŒ, ์ด๋ฏธ์ง€ ์บก์…”๋‹ ๋ชจ๋ธ์„ ํ•™์Šตํ•˜๋Š”๋ฐ ํ•„์š”ํ•œ ์ด๋ฏธ์ง€-์บก์…˜์˜ ์Œ์œผ๋กœ๋œ ๋ฐ์ดํ„ฐ์…‹์€ ๋งค์šฐ ํ•œ์ •๋˜์–ด ์žˆ๊ณ , ํ˜„์กดํ•˜๋Š” ๋ฐ์ดํ„ฐ์…‹๋“ค ๋˜ํ•œ ์ƒ์„ฑ๋˜๋Š” ๋ฌธ์žฅ๋“ค์˜ ๋‹ค์–‘์„ฑ์ด ๋ถ€์กฑํ•˜๋ฉฐ ์ด๋ฏธ์ง€ ๋ถ„์•ผ๋„ ๋งค์šฐ ์ œํ•œ์ ์ด๋‹ค. ์ด๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ์ตœ๊ทผ์—” ๋น„์ง€๋„ ํ•™์Šต ๋ชจ๋ธ์˜ ์—ฐ๊ตฌ๋„ ์ง„ํ–‰๋˜์—ˆ์œผ๋‚˜, ํ˜„์žฌ๋กœ์„œ๋Š” ์ง€๋„ ํ•™์Šต ๋ชจ๋ธ์˜ ์„ฑ๋Šฅ์„ ๋”ฐ๋ผ๊ฐ€๊ธฐ์—” ์•„์ง ํ•œ์ฐธ ๋ถ€์กฑํ•˜๋‹ค. ๋ฐ์ดํ„ฐ ๋ถ€์กฑ ๋ฌธ์ œ๋ฅผ ์™„ํ™”ํ•˜๊ธฐ ์œ„ํ•œ ๋˜ ๋‹ค๋ฅธ ๋ฐฉ๋ฒ•์œผ๋กœ๋Š” ๋ฐ์ดํ„ฐ ์ฆ๊ฐ• ๊ธฐ๋ฒ•์ด ์žˆ๋‹ค. ์ตœ๊ทผ ์ด๋ฏธ์ง€ ๋ฐ์ดํ„ฐ ์ฆ๊ฐ• ๊ธฐ๋ฒ•์€ AutoAugment, RandAugment ๋“ฑ ํ™œ๋ฐœํ•˜๊ฒŒ ์—ฐ๊ตฌ๊ฐ€ ์ง„ํ–‰๋˜๊ณ  ์žˆ์œผ๋‚˜, ๋Œ€๋ถ€๋ถ„์˜ ์—ฐ๊ตฌ๋“ค์ด ์ด๋ฏธ์ง€ ๋ถ„๋ฅ˜ ๋ฌธ์ œ๋ฅผ ์œ„ํ•œ ๊ธฐ๋ฒ•๋“ค์ด๊ณ , ์ด๋ฅผ ๊ทธ๋Œ€๋กœ ์ด๋ฏธ์ง€ ์บก์…”๋‹ ๋ฌธ์ œ์— ์ ์šฉํ•˜๊ธฐ์—” ์–ด๋ ค์›€์ด ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์‹คํ—˜์„ ํ†ตํ•ด ๊ธฐ์กด์˜ ๋ฐ์ดํ„ฐ ์ฆ๊ฐ• ๊ธฐ๋ฒ•์ด ๋ฌธ์ œ, ๋ชจ๋ธ, ๋ฐ์ดํ„ฐ์…‹์— ๋”ฐ๋ผ ์„ฑ๋Šฅ์ด ๋งค์šฐ ๋‹ฌ๋ผ์ง„๋‹ค๋Š” ๊ฒƒ์„ ํ™•์ธํ•œ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ๊ธฐ์กด์˜ ๋ฐ์ดํ„ฐ ์ฆ๊ฐ• ๊ธฐ๋ฒ•์„ ๋ฐœ์ „์‹œ์ผœ ์ด๋ฏธ์ง€ ์บก์…”๋‹ ๋ฌธ์ œ์— ์ ํ•ฉํ•œ ์ƒˆ๋กœ์šด ๊ธฐ๋ฒ•์„ ๊ฐœ๋ฐœํ•˜๊ณ , ํ•ด๋‹น ๊ธฐ๋ฒ•์˜ ์„ฑ๋Šฅ์„ ์‹คํ—˜์ ์œผ๋กœ ๊ฒ€์ฆํ•œ๋‹ค.Contents Abstract........................................................... โ…ฐ Contents ........................................................ โ…ฑi Table Contents................................................... iv Figure Contents .................................................. v Chapter 1. Introduction........................................... 1 Chapter 2. Related Work ........................................ 3 2.1 Image Captioning Models.......................................................... 3 2.2 Image Data Augmentation Techniques..................................................... 5 Chapter 3. Smart Random Erasing .............................. 7 3.1 Object Recognition .................................................................... 8 3.2 Object Occlusion......................................................................... 9 3.3 Automatic Hyperparameter Search....................................... 11 Chapter 4. Experiments and Results........................... 13 4.1 Experimental Settings.............................................................. 13 4.2 Evaluation Metrics.................................................................... 14 4.3 Experiment Results and Analysis........................................... 16 4.3.1 Comparison with other DA techniques........................... 17 4.3.2 Comparison with original Random Erasing.................... 21 Chapter 5. Conclusion and Future Work...................... 22 References ...................................................... 24 ์ดˆ๋ก............................................................... 26Maste

    ์•„๋™ ์น˜๊ณผ์ฃผ์น˜์˜ ์‚ฌ์—…์ด ์•„๋™ ๊ตฌ๊ฐ•๊ฑด๊ฐ•์— ๋ฏธ์น˜๋Š” ํšจ๊ณผ : ์„œ์šธ์ง€์—ญ ํ•œ ๋ณด๊ฑด์†Œ๋ฅผ ๋Œ€์ƒ์œผ๋กœ

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    ๋ณด๊ฑด๋Œ€ํ•™์›/์„์‚ฌ2012๋…„๋ถ€ํ„ฐ ์„œ์šธ์‹œ ๊ฑฐ์ฃผ ๋งŒ 18์„ธ ๋ฏธ๋งŒ์˜ ์ทจ์•ฝ๊ณ„์ธต ์•„๋™์˜ ๊ตฌ๊ฐ•๊ฑด๊ฐ•๋ถˆํ‰๋“ฑ์„ ํ•ด์†Œํ•˜๊ณ  ๊ตฌ๊ฐ•๊ฑด๊ฐ•์ฆ์ง„์„ ํ–ฅ์ƒํ•˜๊ธฐ ์œ„ํ•ด โ€˜์•„๋™ ์น˜๊ณผ์ฃผ์น˜์˜ ์‚ฌ์—…โ€™์„ ์šด์˜ํ•˜์˜€๋‹ค. ์‚ฌ์—…์ด ์ง€ํ–ฅํ•˜๋Š” ๋ฐฉํ–ฅ์€ ํฌ๊ด„์„ฑ๊ณผ ์ง€์†์„ฑ์ธ ์˜ˆ๋ฐฉ์ค‘์‹ฌ์˜ ๊ฑด๊ฐ•์ฆ์ง„์„ ์ตœ์šฐ์„ ์œผ๋กœ ํ•˜๋Š” 1์ฐจ ์น˜๊ณผ ์˜๋ฃŒ์˜ ๋ฐฉํ–ฅ๊ณผ ์ผ์น˜ํ•˜๋ฉฐ, ๊ฑด๊ฐ•์ฆ์ง„๊ณผ ์˜ˆ๋ฐฉ์ง„๋ฃŒ์˜ ๊ฐœ์ž…์— ๊ฐ€์žฅ ํšจ๊ณผ์ ์ธ ์•„๋™, ์ฒญ์†Œ๋…„ ์‹œ๊ธฐ์— ์ง‘์ค‘์‹œํ‚ด์œผ๋กœ์จ ๊ทธ ์„ฑ๊ณผ๊ฐ€ ๊ธฐ๋Œ€๋˜๊ณ  ์žˆ๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” ์„œ์šธ์‹œ ์ผ๋ถ€ ์ง€์—ญ์˜ ์•„๋™ ์น˜๊ณผ์ฃผ์น˜์˜ ์‚ฌ์—…์„ ์ง„ํ–‰ํ•˜์—ฌ ์‚ฌ์—… ํ‰๊ฐ€์— ๋„์›€์„ ์ฃผ๊ณ ์ž ํ•˜์˜€๋‹ค. ์‚ฌ์—…์€ ๋Œ€์ƒ์ž๋“ค์˜ ๊ตฌ๊ฐ•๊ฑด๊ฐ•๊ด€๋ จ ๋ฐ”๋ฅธ์ƒํ™œ ์‹ค์ฒœ๋„๋ฅผ ํ–ฅ์ƒํ•˜๊ธฐ ์œ„ํ•ด ๋‚ด์› ์‹œ ๋ฐ˜๋ณต์ ์ธ ๊ตฌ๊ฐ•๋ณด๊ฑด๊ต์œก ๋ฐ ๊ตฌ๊ฐ•๊ฑด๊ฐ•์ฆ์ง„ ์„œ๋น„์Šค๋ฅผ ์ง„ํ–‰ ํ•˜์˜€๊ณ  ์น˜๊ณผ์˜์›์— ์—ฐ๊ณ„ํ•˜์—ฌ ๋ฏธ์ถฉ์กฑ ์น˜๊ณผ์˜๋ฃŒ ์„œ๋น„์Šค๋ฅผ ๋ฐ›์„ ์ˆ˜ ์žˆ๋„๋ก ํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ๋Œ€์ƒ์ž๋Š” ์ด 176๋ช…์œผ๋กœ ๋งŒ 18์„ธ ๋ฏธ๋งŒ๊นŒ์ง€ ์•„๋™ ์น˜๊ณผ์ฃผ์น˜์˜ ์‚ฌ์—… ๋Œ€์ƒ์ž ์ค‘ 2013๋…„์— ๋“ฑ๋กํ•˜์—ฌ ์‚ฌ์—…์— ์ฐธ์—ฌํ•˜๊ณ  2014๋…„์— ์žฌ๋‚ด์›ํ•œ ๋Œ€์ƒ์ž์ด๋‹ค. ์—ฐ๊ตฌ๋Œ€์ƒ์ž์˜ ์ผ๋ฐ˜์  ํŠน์„ฑ์„ ํŒŒ์•…ํ•˜๊ธฐ ์œ„ํ•ด ๊ธฐ์ˆ ๋ถ„์„์„ ์‹œํ–‰ํ•˜์˜€๊ณ , ์‚ฌ์—…์— ์ฐธ์—ฌํ•œ ๋Œ€์ƒ์ž์˜ ์ธ๊ตฌํ•™์  ์š”์ธ, ๊ตฌ๊ฐ•๊ฒ€์ง„, ๊ตฌ๊ฐ•์ฆ์ƒ, ๊ตฌ๊ฐ•๊ฑด๊ฐ•ํ–‰ํƒœ์— ๋”ฐ๋ฅธ ฯ‡2 ๊ฒ€์ •, ANOVA, Two-way ANOVA, ๋‹ค๋ณ€๋Ÿ‰ ํšŒ๊ท€๋ถ„์„์„ ํ†ตํ•ด ๋Œ€์ƒ์ž์˜ ์ง‘๋‹จ๋ณ„ ๋ฏธ์ถฉ์กฑ์ถฉํ•„์š”์ „์น˜์•„์ˆ˜, PHP(patient hygiene performance)์ง€์ˆ˜ ๋ณ€ํ™”๊ฐ’์„ ๋ถ„์„ํ•˜์˜€๋‹ค. ์ธ๊ตฌํ•™์  ์š”์ธ์—์„œ ๋‚จ์ž 86๋ช… ์—ฌ์ž 90๋ช…์ด์—ˆ๊ณ  ์˜๋ฃŒ๋ณด์žฅ ํ˜•ํƒœ๋Š” ๊ฑด๊ฐ•๋ณดํ—˜ ๋Œ€์ƒ์ž 105๋ช… ์˜๋ฃŒ๊ธ‰์—ฌ ๋Œ€์ƒ์ž 71๋ช…์œผ๋กœ ๊ฑด๊ฐ•๋ณดํ—˜ ๋Œ€์ƒ์ž์˜ ์ฐธ์—ฌ์œจ์ด ๋†’์•˜๋‹ค. ๊ตฌ๊ฐ•๊ฒ€์ง„ ๋‚ด์—ญ์—์„œ ์น˜์ฃผ์งˆํ™˜์ด โ€˜์—†๋‹คโ€™ ๋Œ€์ƒ์ž๊ฐ€ ์‚ฌ์—… ํ›„ 86๋ช…์—์„œ 113๋ช…์œผ๋กœ ์ฆ๊ฐ€ํ–ˆ์œผ๋ฉฐ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•˜์˜€๋‹ค. ๋˜ํ•œ ๋ฏธ์ถฉ์กฑ์ถฉ์ „ํ•„์š”์น˜์•„์ˆ˜๊ฐ€ ์‚ฌ์—… ์ „ 0.98๊ฐœ์—์„œ ์‚ฌ์—… ํ›„ 0.33๊ฐœ๋กœ ์ค„์—ˆ๊ณ  ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•œ ์ฐจ์ด๊ฐ€ ์žˆ์—ˆ๋‹ค. ๊ตฌ๊ฐ•๋ณด๊ฑดํ–‰ํƒœ์—์„œ ์–ด์ œ ํ•˜๋ฃจ ๋™์•ˆ ์ด๋ฅผ ๋‹ฆ์€ ํšŸ์ˆ˜๋Š” ํ•˜๋ฃจ์— 2ํšŒ ์ด์ƒ ๋‹ฆ๋Š” ๋Œ€์ƒ์ž๊ฐ€ 52๋ช…์—์„œ 143๋ช…์œผ๋กœ ์ฆ๊ฐ€ํ•˜์˜€๊ณ  ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•œ ์ฐจ์ด๊ฐ€ ์žˆ์—ˆ์œผ๋‚˜ ๊ตฌ๊ฐ•๋ณด๊ฑดํ–‰ํƒœ์™€ ๊ด€๋ จ ์žˆ๋Š” ์‚ฌ์—… ์ „ PHP(patient hygiene performance)์ง€์ˆ˜๋Š” 15.48์ ์—์„œ ์‚ฌ์—… ํ›„16.36์ ์œผ๋กœ PHP(patient hygiene performance)์ง€์ˆ˜๊ฐ€ ํ–ฅ์ƒ๋˜์ง€ ์•Š์•˜๋‹ค. ์ด ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋Š” ์„œ์šธ์‹œ ์•„๋™ ์น˜๊ณผ์ฃผ์น˜์˜ ์‚ฌ์—…์˜ ๋Œ€์ƒ์ž๋ฅผ ์ผ๋ถ€ ๋ถ„์„ํ•œ ๊ฒƒ์œผ๋กœ ์„œ์šธ์‹œ ์‚ฌ์—… ์ „๋ฐ˜์ ์ธ ํ‰๊ฐ€๋ฅผ ์ ์šฉ ํ•˜๋Š” ๋ฐ๋Š” ํ•œ๊ณ„๊ฐ€ ์žˆ์ง€๋งŒ, ์•„๋™ ์น˜๊ณผ์ฃผ์น˜์˜ ์‚ฌ์—…์„ ์šด์˜ํ•˜๋Š” ๋ณด๊ฑด์†Œ ๋‹จ์œ„์˜ ์‚ฌ์—…ํ‰๊ฐ€์— ํ™œ์šฉํ•˜๋Š”๋ฐ ์˜์˜๊ฐ€ ์žˆ๋‹ค. ๋˜ํ•œ ์ด ์—ฐ๊ตฌ์—์„œ 1๋…„ ๋™์•ˆ์˜ ๋Œ€์ƒ์ž๋“ค์—๊ฒŒ ์‚ฌ์—…์„ ์ง„ํ–‰ํ•˜๊ณ  ํšจ๊ณผ๋ฅผ ์—ฐ๊ตฌํ•˜์˜€๊ณ  ๊ตฌ๊ฐ•๊ฑด๊ฐ•์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ๋ถ€๋ชจ์˜ ์ธ๊ตฌํ•™์  ํŠน์„ฑ์„ ํŒŒ์•…ํ•˜๊ธฐ ์œ„ํ•œ ๋…๋ฆฝ๋ณ€์ˆ˜๊ฐ€ ์ ์—ˆ๊ธฐ ๋•Œ๋ฌธ์— ํ–ฅํ›„์—๋Š” ์ฐธ์—ฌ ๋Œ€์ƒ์ž์˜ ๊ตฌ๊ฐ•๋ณด๊ฑด๊ต์œก ์‹œ๊ฐ„, ๋ฐฉ๋ฌธ์ฃผ๊ธฐ, ๋ณดํ˜ธ์ž์˜ ์ธ๊ตฌํ•™์  ํŠน์„ฑ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๊ฐ€ ๋ณด์™„ํ•˜์—ฌ ์‚ฌ์—…์˜ ํšจ๊ณผ๋ฅผ ๊ทน๋Œ€ํ™” ํ•  ์ˆ˜ ์žˆ๋Š”๋ฐ ๋„์›€์„ ์ฃผ์—ˆ์œผ๋ฉด ํ•œ๋‹ค.ope

    Preparation of Sericin/Silica Complex Using Ultrasonication for Pd(โ…ก) Ion Adsorption

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๋ฐ”์ด์˜ค์‹œ์Šคํ…œยท์†Œ์žฌํ•™๋ถ€ ๋ฐ”์ด์˜ค์†Œ์žฌ๊ณตํ•™์ „๊ณต, 2016. 2. ์ด๊ธฐํ›ˆ.์ดˆ์ŒํŒŒ๋Š” ์šฉ์•ก์˜ ํ™œ๋™๋„๋ฅผ ํ–ฅ์ƒ์‹œ์ผœ ๋ฐ˜์‘์˜ ๊ณ„๋ฉด์„ ์ฆ๊ฐ€์‹œํ‚ค๊ณ  ๋ฐ˜์‘ ์†๋„๋ฅผ ๋น ๋ฅด๊ฒŒ ํ•œ๋‹ค๊ณ  ์•Œ๋ ค์ ธ ์žˆ๋‹ค. ์‹คํฌ ๋‹จ๋ฐฑ์งˆ ์ค‘ ์„ธ๋ฆฌ์‹ ์€ ๋ณดํ†ต ์ •๋ จ๊ณผ์ •์—์„œ ๋ฒ„๋ ค์ง€๋Š” ๋‹จ๋ฐฑ์งˆ์ธ๋ฐ, ์ด๋ฅผ ์ด์šฉํ•˜์—ฌ ๊ธˆ์† ์ด์˜จ ํก์ฐฉ ๋ฐ ์‹ค๋ฆฌ์นด ํ•ฉ์„ฑ ๋“ฑ์— ์‘์šฉํ•˜๋Š” ์‚ฌ๋ก€๋“ค์ด ๋ณด๊ณ ๋œ ๋ฐ” ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์‹คํฌ ๋‹จ๋ฐฑ์งˆ์—์„œ ์ถ”์ถœํ•œ ์„ธ๋ฆฌ์‹  ๋‹จ๋ฐฑ์งˆ์„ ์ด์šฉํ•˜์—ฌ ์‹ค๋ฆฌ์นด๋ฅผ ํ•ฉ์„ฑํ•จ์— ์žˆ์–ด ์ดˆ์ŒํŒŒ ์กฐ์‚ฌ๊ฐ€ ์–ด๋– ํ•œ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š”์ง€ ์‚ดํŽด๋ณด์•˜๋‹ค. ์ดˆ์ŒํŒŒ๋ฅผ ์กฐ์‚ฌํ•จ์œผ๋กœ์จ ์‹ค๋ฆฌ์นด๋ฅผ ํ•ฉ์„ฑํ•˜๋Š” ๋ฐ ์†Œ์š”๋˜๋Š” ์‹œ๊ฐ„์„ ๋ณด๋‹ค ๋‹จ์ถ•ํ•  ์ˆ˜ ์žˆ์—ˆ์œผ๋ฉฐ, ์—ด์ค‘๋Ÿ‰ ๋ถ„์„๊ณผ ์ ์™ธ์„  ๋ถ„๊ด‘ ๋ถ„์„, ํ•ต์ž๊ธฐ๊ณต๋ช… ๋ถ„๊ด‘๋ถ„์„์„ ํ†ตํ•˜์—ฌ ์‹ค๋ฆฌ์นด์˜ ์กด์žฌ์™€ ํ–ฅ์ƒ๋œ ์ค‘ํ•ฉ๋„๋ฅผ ๋ณด์ž„์„ ์•Œ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ฃผ์‚ฌ์ „์žํ˜„๋ฏธ๊ฒฝ ์ด๋ฏธ์ง€์—์„œ๋Š” ์ดˆ์ŒํŒŒ ์ฒ˜๋ฆฌ๊ตฐ์—์„œ ๋ณด๋‹ค ๋” ๊ท ์ผํ•˜๊ณ  ์ž‘์€ ํฌ๊ธฐ์˜ ์ž…์ž ํ˜•ํƒœ๊ฐ€ ๊ด€์ฐฐ๋˜์—ˆ๋‹ค. ์„ธ๋ฆฌ์‹ /์‹ค๋ฆฌ์นด ๋ณตํ•ฉ์ฒด ์ƒ์„ฑ๋Ÿ‰๊ณผ ์‹ค๋ฆฌ์นด ํ•จ๋Ÿ‰์„ ์„ธ๋ฆฌ์‹ ๊ณผ ์‹ค๋ฆฌ์นด ์ „๊ตฌ์ฒด ๋น„์œจ, ์ดˆ์ŒํŒŒ ๊ฐ•๋„, ์‹œ๊ฐ„์— ๋”ฐ๋ผ ๋ถ„์„ํ•˜์—ฌ ๊ฐ ์˜ํ–ฅ์ธ์ž์— ๋Œ€ํ•ด ๋ถ„์„ ๊ฒฐ๊ณผ, ์„ธ๋ฆฌ์‹ ์˜ ๋น„์œจ, ์ดˆ์ŒํŒŒ์˜ ๊ฐ•๋„ ๋ฐ ์กฐ์‚ฌ ์‹œ๊ฐ„์ด ์ฆ๊ฐ€ํ• ์ˆ˜๋ก ๋ณตํ•ฉ์ฒด ๋ฐ ์‹ค๋ฆฌ์นด ์ƒ์„ฑ๋Ÿ‰์ด ์ฆ๊ฐ€๋˜์—ˆ๋‹ค. ์ด๋ ‡๊ฒŒ ์ดˆ์ŒํŒŒ๋ฅผ ์กฐ์‚ฌํ•˜์—ฌ ์ œ์กฐ๋œ ์„ธ๋ฆฌ์‹ /์‹ค๋ฆฌ์นด ๋ณตํ•ฉ์ฒด๋ฅผ ์ด์šฉํ•˜์—ฌ ํŒ”๋ผ๋“ ์ด์˜จ ํก์ฐฉ์ œ๋กœ์˜ ์‚ฌ์šฉ๊ฐ€๋Šฅ์„ฑ์„ ์‚ดํŽด๋ณด์•˜๋‹ค. ์„ธ๋ฆฌ์‹ /์‹ค๋ฆฌ์นด ๋ณตํ•ฉ์ฒด์˜ ์˜์ „ํ•˜์ ์„ ์ธก์ •ํ•˜์—ฌ ํก์ฐฉ ์šฉ์•ก์—์„œ์˜ ๋ณตํ•ฉ์ฒด ํ‘œ๋ฉด ์ „ํ•˜์— ๋Œ€ํ•œ ์ •๋ณด๋ฅผ ์–ป์Œ์œผ๋กœ์จ ์—ผ์‚ฐ์šฉ์•ก์—์„œ ์Œ์ด์˜จ์œผ๋กœ ์กด์žฌํ•˜๋Š” ํŒ”๋ผ๋“(โ…ก)์˜ ํก์ฐฉ์ด ์ด๋ก ์ ์œผ๋กœ ๊ฐ€๋Šฅํ•จ์„ ์•Œ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์‹ค์ œ๋กœ ์—๋„ˆ์ง€๋ถ„์‚ฐํ˜• ๋ถ„๊ด‘๋ถ„์„ ๊ฒฐ๊ณผ ์„ธ๋ฆฌ์‹ /์‹ค๋ฆฌ์นด ๋ณตํ•ฉ์ฒด ํ‘œ๋ฉด์— ํŒ”๋ผ๋“ ํก์ฐฉ์ด ๊ด€์ฐฐ๋˜์—ˆ๋‹ค. ํก์ฐฉ์ œ์˜ ํก์ฐฉ ๊ฑฐ๋™์„ ํ‰๊ฐ€ํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ํก์ฐฉ๋“ฑ์˜จ์„ ์„ ์–ป๊ณ ์ž ๋ชจ๋ธ๋ง์„ ์ง„ํ–‰ํ•˜์˜€์„ ๋•Œ, BET๋ชจ๋ธ์ด ๊ฐ€์žฅ ์ ํ•ฉํ•˜๊ฒŒ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋˜ํ•œ ์†๋„๋ก ์ ์œผ๋กœ ๋ถ„์„ํ•˜์˜€์„ ๋•Œ 2๊ฐ€ ๊ธˆ์† ์ด์˜จ ํก์ฐฉ ๋ถ„์„์— ๋งŽ์ด ์ด์šฉ๋˜๋Š” ์œ ์‚ฌ 2์ฐจ ๋ฐ˜์‘์ด ์ ํ•ฉํ•˜์˜€๋‹ค. ์žฌ์‚ฌ์šฉ์„ฑ์„ ํ™•์ธํ•œ ๊ฒฐ๊ณผ, ์•ˆ์ •ํ•œ ๋‹จ๋ฐฑ์งˆ ๋ณตํ•ฉ์ฒด์˜ ํก์ฐฉ์ œ๋กœ์˜ ํ™œ์šฉ๊ฐ€๋Šฅ์„ฑ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์ด์ƒ์˜ ๊ฒฐ๊ณผ๋ฅผ ํ† ๋Œ€๋กœ, ์ดˆ์ŒํŒŒ๋ฅผ ์ด์šฉํ•˜์—ฌ ์„ธ๋ฆฌ์‹ /์‹ค๋ฆฌ์นด์˜ ๋ณตํ•ฉ์ฒด๋ฅผ ์„ฑ๊ณต์ ์œผ๋กœ ๋น ๋ฅธ ์‹œ๊ฐ„ ๋‚ด์— ์ œ์กฐํ•˜์˜€๊ณ , ์ด๋ฅผ ํŒ”๋ผ๋“ ์ด์˜จ ํก์ฐฉ์ œ๋กœ์„œ์˜ ๊ฐ€๋Šฅ์„ฑ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค.์ œ 1 ์žฅ ์„œ๋ก  1 ์ œ 2 ์žฅ ๋ฌธํ—Œ์กฐ์‚ฌ 4 2.1 ์ดˆ์ŒํŒŒ๋ฅผ ์ด์šฉํ•œ ๋ฌด๊ธฐ์žฌ๋ฃŒ ํ•ฉ์„ฑ 4 2.2 ๋‹จ๋ฐฑ์งˆ์„ ์ด์šฉํ•œ ์‹ค๋ฆฌ์นด์˜ ํ•ฉ์„ฑ 5 2.3 ํŒ”๋ผ๋“ ์ด์˜จ ํก์ฐฉ์ œ๋กœ์˜ ์ฒœ์—ฐ๊ณ ๋ถ„์ž ์‘์šฉ 8 ์ œ 3 ์žฅ ์‹คํ—˜ ์žฌ๋ฃŒ ๋ฐ ๋ฐฉ๋ฒ• 11 3.1 ์žฌ๋ฃŒ ๋ฐ ์‹œ์•ฝ 11 3.2 ์‹คํ—˜ ๋ฐฉ๋ฒ• 11 3.2.1 ์„ธ๋ฆฌ์‹ /์‹ค๋ฆฌ์นด ๋ณตํ•ฉ์ฒด์˜ ์ œ์กฐ 11 3.2.2 ์ œ์กฐ๋œ ์„ธ๋ฆฌ์‹ /์‹ค๋ฆฌ์นด ๋ณตํ•ฉ์ฒด์˜ ์ˆ˜์œจ ๋ฐ ํŠน์„ฑ๋ถ„์„ 12 3.2.3 ํŒ”๋ผ๋“ ์ด์˜จ ํก์ฐฉ์ œ๋กœ์˜ ๊ฐ€๋Šฅ์„ฑ ํ‰๊ฐ€ 13 ์ œ 4 ์žฅ ๊ฒฐ๊ณผ ๋ฐ ๊ณ ์ฐฐ 15 4.1 ์ดˆ์ŒํŒŒ๋ฅผ ์ด์šฉํ•œ ์„ธ๋ฆฌ์‹ /์‹ค๋ฆฌ์นด ๋ณตํ•ฉ์ฒด์˜ ์ œ์กฐ 15 4.1.1 ์ดˆ์ŒํŒŒ ์ฒ˜๋ฆฌ๊ตฐ๊ณผ ๋ฏธ์ฒ˜๋ฆฌ๊ตฐ์˜ ํŠน์„ฑ ๋น„๊ต 15 4.1.2 ๋ฐ˜์‘ ์กฐ๊ฑด์— ๋”ฐ๋ฅธ ์„ธ๋ฆฌ์‹ /์‹ค๋ฆฌ์นด ๋ณตํ•ฉ์ฒด์˜ ์ˆ˜์œจ ๋ฐ ์กฐ์„ฑ ๋น„๊ต 26 4.2 ์„ธ๋ฆฌ์‹ /์‹ค๋ฆฌ์นด ๋ณตํ•ฉ์ฒด์˜ ํŒ”๋ผ๋“ ์ด์˜จ ํก์ฐฉ์ œ๋กœ์˜ ์‘์šฉ 32 4.2.1 ํก์ฐฉ๋“ฑ์˜จ์„ ์„ ํ†ตํ•œ ํก์ฐฉ ๊ฑฐ๋™ ํ‰๊ฐ€ 38 4.2.2 ์†๋„๋ก ์  ํก์ฐฉ ๊ฑฐ๋™ ํ‰๊ฐ€ 50 4.2.3 ์„ธ๋ฆฌ์‹ /์‹ค๋ฆฌ์นด ๋ณตํ•ฉ์ฒด์˜ ํก์ฐฉ ์žฌ์‚ฌ์šฉ์„ฑ 55 ์ œ 5 ์žฅ ๊ฒฐ๋ก  59 ์ฐธ๊ณ ๋ฌธํ—Œ 61 Abstract 70Maste

    ์šฐ์‹ฌ์‹ค ์œ ์ถœ๋กœ ํ˜‘์ฐฉ ํ™˜์•„์—์„œ ์ˆ˜์ˆ  ํ›„ ๋ถ„์ง€ ํ๋™๋งฅ ํ˜‘์ฐฉ ํ‰๊ฐ€์— ๋Œ€ํ•œ ํ perfusion scan์˜ ์œ ์šฉ์„ฑ

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์˜ํ•™๊ณผ ์†Œ์•„๊ณผํ•™์ „๊ณต,1995.Maste

    ๊ฐ€์กฑ๋ฐฐ๊ฒฝ์ด ์„ฑ์ธ์ดํ–‰๊ธฐ ๊ฒฝ์ œ์  ํ™œ๋™์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์— ๊ด€ํ•œ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) --์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์‚ฌํšŒ๋ณต์ง€ํ•™๊ณผ,2010.2.Maste

    Parallel Overlapped Antenna using Sum/Difference Mode to emulate Endfire/Broadside Radiation for Millimeter-wave Beamforming Devices

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    Master์ด ๋…ผ๋ฌธ์€ ๊ธฐ์กด์˜ ์•ˆํ…Œ๋‚˜๊ฐ€ ์ค‘์ฒฉ๋˜์–ด ๋ฐฐ์—ด์„ ๊ตฌ์„ฑํ•˜๊ณ , ๋ธŒ๋กœ๋“œ์‚ฌ์ด๋“œ ๋ฐฉ์‚ฌ ๋ฐฉํ–ฅ๊ณผ ์—”๋“œํŒŒ์ด์–ด ๋ฐฉ์‚ฌ ๋ฐฉํ–ฅ์ด ์•ˆํ…Œ๋‚˜์— ํ๋ฅด๋Š” ์ „๋ฅ˜์˜ ์œ„์ƒ ์ฐจ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ์ „ํ™˜ ๋  ์ˆ˜ ์žˆ์Œ์„ ์ œ์‹œํ•œ๋‹ค. ๋˜ํ•œ, ์šฐ๋ฆฌ๋Š” ์—”๋“œํŒŒ์ด์–ด ๋ฐฉ์‚ฌ ์‹œ, ๋ฐœ์ƒํ•˜๋Š” ์—ญ๋ฐฉํ–ฅ ๋ฐฉ์‚ฌ๋Ÿ‰์„ ์–ต์ œํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ์ด ๊ธฐ์ˆ ์€ LTCC ๊ณต์ •์œผ๋กœ ์‹œ๋ฎฌ๋ ˆ์ด์…˜, ์ œ์ž‘ ๋ฐ ์ธก์ •๋˜์—ˆ์œผ๋ฉฐ, ๋น” ์กฐ์ข…์€ 60GHz Wigig ๋ชจ๋“ˆ์„ ์‚ฌ์šฉํ•˜์—ฌ ๊ฒ€์ฆํ•˜์˜€๋‹ค. ๋˜ํ•œ ์ด ๋…ผ๋ฌธ์—์„œ ์ œ์‹œํ•œ ์•ˆํ…Œ๋‚˜ ๊ธฐ์ˆ ์„ ์ด์šฉํ•˜์—ฌ 5G ๋‹จ๋ง๊ธฐ์˜ ๋‘ ์ถ•์„ ์ด๋ฃจ๋Š” ์ด๋™ ์ „ํ™” ๋‹จ๋ง๊ธฐ ๋ฐ HMD (head mounted display device) ์˜ ์ ์šฉ ์˜ˆ๋ฅผ ์ œ์‹œํ•˜์˜€๋‹ค. ์ €์ž๋Š” ์ค‘์ฒฉ๋˜์–ด ๋ฐฐ์—ด๋กœ ๊ตฌ์„ฑ๋œ ํŒจ์น˜ ์•ˆํ…Œ๋‚˜๋ฅผ ์ตœ๊ทผ ํ”Œ๋ž˜๊ทธ์‰ฝ ํœด๋Œ€์ „ํ™”์˜ ํŠธ๋ Œ๋“œ์ธ ๋ฉ”ํƒˆ ํ”„๋ ˆ์ž„ ์ผ€์ด์Šค ๋‚ด์— ์‹ค์žฅํ•˜๊ณ , ๋ฉ”ํƒˆ ํ”„๋ ˆ์ž„์„ ๋„˜์–ด ๋ฐฉ์‚ฌํ•˜๋Š” mmWave 5G ์•ˆํ…Œ๋‚˜๋ฅผ ๋ณด์—ฌ์ฃผ์—ˆ๋‹ค. HMD ์—์„œ๋Š”, ์ œ์•ˆ๋œ ์•ˆํ…Œ๋‚˜๋ฅผ ์ˆ˜์ง์œผ๋กœ ์ ์šฉํ•˜์—ฌ 300๋„ ๋น” ์ปค๋ฒ„๋ฆฌ์ง€๋ฅผ ๊ฐ–๋Š” ํŠน์ง•์„ ๋ณด์—ฌ์ค€๋‹ค.This paper suggests that the existing antennas are connected in parallel and that the direction of broad-side radiation and that of end-fire radiation can be switched using phase difference. Furthermore, we propose a method to suppress the backward radiation that occurs during end-fire radiation. These technologies were simulated, fabricated and measured by the LTCC process, and beam steering was verified using the HRA132 module for 60GHz WiGig. In addition, using the antenna technologies presented in the paper, examples of mobile phones and head mounted display devices (HMDs), which are two major axes of 5G mobile terminals, were mentioned. We show a 5G antenna that radiates beyond a 4G antenna that utilizes the traditional trend metal frame design by applying a patch antenna in parallel to the mobile phone. In the HMD, the proposed antenna is vertically applied and shows a feature with a close 360 degree coverage
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