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    ๋‹ค์ค‘์‚ฌ์šฉ์ž ๋‹ค์ค‘์•ˆํ…Œ๋‚˜ ์‹œ์Šคํ…œ์„ ์œ„ํ•œ SVD ๊ธฐ๋ฐ˜์˜ ์œ ๋‹ˆํ„ฐ๋ฆฌ ํ”„๋กœ์„ธ์‹ฑ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ „๊ธฐ์ •๋ณด๊ณตํ•™๋ถ€, 2013. 8. ์ด๊ด‘๋ณต.๋‹ค์ค‘ ์‚ฌ์šฉ์ž ๋‹ค์ค‘ ์•ˆํ…Œ๋‚˜ ํ”„๋กœ์„ธ์‹ฑ์€ ๋™์‹œ์— ์—ฌ๋Ÿฌ ๋ช…์˜ ์‚ฌ์šฉ์ž์—๊ฒŒ ์„œ๋น„์Šค๋ฅผ ์ œ๊ณตํ•จ์œผ๋กœ์จ ์ปค๋‹ค๋ž€ ์…€ ์šฉ๋Ÿ‰ ์ฆ๋Œ€๋ฅผ ์–ป์„ ์ˆ˜ ์žˆ๋Š” ๊ธฐ์ˆ ๋กœ ์ง€๋‚œ 10๋…„ ๊ฐ„ 3GPP-LTE Advanced, IEEE 802.16m, IEEE 802.11ac ๋“ฑ์˜ ์ฐจ์„ธ๋Œ€ ๋ฌด์„  ํ†ต์‹  ํ‘œ์ค€์— ์ƒ๋‹นํ•œ ๊ด€์‹ฌ์„ ๋ฐ›์•„์™”๋‹ค. ์ด ํ•™์œ„ ๋…ผ๋ฌธ์—์„œ๋Š” ํ˜„์‹ค์ ์ธ ๊ตฌํ˜„์„ ๊ณ ๋ คํ•˜์—ฌ ์ ์€ ๊ณ„์‚ฐ๋Ÿ‰๊ณผ ๋‹ค์–‘ํ•œ ๋ฌด์„  ํ†ต์‹  ์‹œ์Šคํ…œ์— ์ ์šฉ ๊ฐ€๋Šฅ์„ฑ์„ ์ง€๋‹Œ ๋‹ค์ค‘ ์‚ฌ์šฉ์ž ๋‹ค์ค‘ ์•ˆํ…Œ๋‚˜ ํ”„๋กœ์„ธ์‹ฑ ๋ฐฉ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ํŠนํžˆ ๋‹ค๋ฅธ ๋‘ ๋ฌด์„  ํ†ต์‹  ์‹œ์Šคํ…œ์ธ ์…€๋ฃฐ๋ผ ์‹œ์Šคํ…œ๊ณผ ๋ฌด์„ ๋žœ ์‹œ์Šคํ…œ์— ์ ์šฉํ•˜์—ฌ ์ œ์•ˆํ•˜๋Š” ๋‹ค์ค‘ ์‚ฌ์šฉ์ž ๋‹ค์ค‘ ์•ˆํ…Œ๋‚˜ ํ”„๋กœ์„ธ์‹ฑ ๋ฐฉ๋ฒ•์˜ ํ‰๊ท ์ ์ธ ์ด ์ „์†ก๋ฅ ์„ ํ‰๊ฐ€ํ•˜๊ณ  ์ด๋ฅผ part I๊ณผ part II์— ๊ฐ๊ฐ ์„ค๋ช…ํ•œ๋‹ค. ํ•™์œ„ ๋…ผ๋ฌธ์˜ part I์—์„œ๋Š” ์…€๋ฃฐ๋ผ ์‹œ์Šคํ…œ์— ์ดˆ์ ์„ ๋งž์ถ˜๋‹ค. ์…€๋ฃฐ๋ผ ์‹œ์Šคํ…œ์€ ์‚ฌ์šฉ์ž์˜ ์ฑ„๋„ ์ •๋ณด๋ฅผ ํ”ผ๋“œ๋ฐฑํ•˜๊ธฐ ์œ„ํ•ด ์ ์€ ์–‘์˜ ํ”ผ๋“œ๋ฐฑ ๋น„ํŠธ๊ฐ€ ํ• ๋‹น๋˜์–ด ์žˆ๋‹ค. ํ˜„์‹ค์ ์ธ ๊ตฌํ˜„ ๊ฐ€๋Šฅ์„ฑ์„ ๋†’์ด๊ธฐ ์œ„ํ•ด ์ ์€ ๊ณ„์‚ฐ๋Ÿ‰์„ ํ•„์š”๋กœ ํ•˜๋Š” ์„ ํ˜• ๋น”ํฌ๋ฐ ๋‹ค์ค‘ ์‚ฌ์šฉ์ž ๋‹ค์ค‘ ์•ˆํ…Œ๋‚˜ ํ”„๋กœ์„ธ์‹ฑ ๋ฐฉ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ์ œ์•ˆํ•˜๋Š” ์„ ํ˜• ๋น”ํฌ๋ฐ ๋‹ค์ค‘ ์‚ฌ์šฉ์ž ๋‹ค์ค‘ ์•ˆํ…Œ๋‚˜ ํ”„๋กœ์„ธ์‹ฑ ๋ฐฉ๋ฒ•์€ ์„ ํ˜ธ๋น” ์ƒ‰์ธ ํ”ผ๋“œ๋ฐฑ, ์‚ฌ์šฉ์ž ์„ ํƒ ์•Œ๊ณ ๋ฆฌ์ฆ˜, ๋น”ํฌ๋ฐ ๋งคํŠธ๋ฆญ์Šค ํ˜•์„ฑ ๋ฐฉ๋ฒ•์ด ํฌํ•จ๋˜์–ด ์žˆ๋‹ค. ๋จผ์ €, ์„ ํ˜ธ๋น” ์ƒ‰์ธ ํ”ผ๋“œ๋ฐฑ ๋ฐฉ๋ฒ•์€ ํŠนํžˆ ์ ์€ ์–‘์˜ ํ”ผ๋“œ๋ฐฑ์„ ์‚ฌ์šฉํ•˜๋Š” ์‹œ์Šคํ…œ์—์„œ ์‚ฌ์šฉ์ž์˜ ์ฑ„๋„ ์ƒํƒœ์™€ ์ธ์ ‘ ์‚ฌ์šฉ์ž์™€์˜ ๊ฐ„์„ญ์˜ ์˜ํ–ฅ์— ๊ด€ํ•œ ์ •๋ณด๋ฅผ ํšจ๊ณผ์ ์œผ๋กœ ๊ธฐ์ง€๊ตญ์—๊ฒŒ ์ „๋‹ฌํ•œ๋‹ค. ๋˜ํ•œ, ์‚ฌ์šฉ์ž ์„ ํƒ ๋ฐฉ๋ฒ•์€ ์‚ฌ์šฉ์ž์˜ ์ˆ˜๊ฐ€ ๊ธฐ์ง€๊ตญ์˜ ์•ˆํ…Œ๋‚˜ ์ˆ˜ ๋ณด๋‹ค ๋งŽ์€ ๊ฒฝ์šฐ ๋‹ค์ค‘ ์‚ฌ์šฉ์ž ๋‹ค์ด๋ฒ„์‹œํ‹ฐ๋ฅผ ํ™œ์šฉํ•˜์—ฌ ํ‰๊ท ์ ์ธ ์ด ์ „์†ก๋ฅ ์„ ํ–ฅ์ƒ์‹œํ‚จ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ ๋น”ํฌ๋ฐ ๋งคํŠธ๋ฆญ์Šค ํ˜•์„ฑ ๋ฐฉ๋ฒ•์€ ์‚ฌ์šฉ์ž๋กœ๋ถ€ํ„ฐ์˜ ํ”ผ๋“œ๋ฐฑ ์ •๋ณด๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ SVD ๋™์ž‘์„ ํ†ตํ•ด ์‰ฝ๊ฒŒ ๋น”ํฌ๋ฐ ๋งคํŠธ๋ฆญ์Šค๊ฐ€ ๊ณ„์‚ฐ๋˜๊ธฐ ๋•Œ๋ฌธ์— ๊ธฐ์กด ๋‹ค์ค‘ ์‚ฌ์šฉ์ž ๋‹ค์ค‘ ์•ˆํ…Œ๋‚˜ ํ”„๋กœ์„ธ์‹ฑ์— ๋น„ํ•ด ๊ณ„์‚ฐ์ƒ์˜ ๋ณต์žก๋„๋ฅผ ํฌ๊ฒŒ ์ค„์ผ ์ˆ˜ ์žˆ๋‹ค. ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ํ†ตํ•œ ์ˆ˜์น˜ ๊ฒฐ๊ณผ๋ฅผ ํ†ตํ•ด ์ œ์•ˆํ•˜๋Š” SVD ๊ธฐ๋ฐ˜์˜ ๋‹ค์ค‘ ์‚ฌ์šฉ์ž ๋‹ค์ค‘ ์•ˆํ…Œ๋‚˜ ํ”„๋กœ์„ธ์‹ฑ ๋ฐฉ๋ฒ•์ด ๊ธฐ์กด ํ”„๋กœ์„ธ์‹ฑ ๋ฐฉ๋ฒ•์— ๋น„ํ•ด ๋” ๋†’์€ ํ‰๊ท  ์ด ์ „์†ก๋ฅ  ์–ป์„ ์ˆ˜ ์žˆ๋‹ค๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. part II์—์„œ๋Š” AP๊ฐ€ ๋‹ค์ค‘ ์‚ฌ์šฉ์ž ๋‹ค์ค‘ ์•ˆํ…Œ๋‚˜ ๊ธฐ์ˆ ์„ ํ†ตํ•ด ์—ฌ๋Ÿฌ ์‚ฌ์šฉ์ž์—๊ฒŒ ๋™์‹œ์— ๋ฐ์ดํ„ฐ๋ฅผ ์ „์†กํ•  ์ˆ˜ ์žˆ๋Š” IEEE 802.11ac ๊ธฐ๋ฐ˜์˜ ๋ฌด์„ ๋žœ ์‹œ์Šคํ…œ์ด ๊ณ ๋ ค๋˜์—ˆ๋‹ค. ๊ณ ๋ ค๋œ ๋ฌด์„ ๋žœ ์‹œ์Šคํ…œ์€ part I์—์„œ์˜ ์…€๋ฃฐ๋ผ ์‹œ์Šคํ…œ๊ณผ๋Š” ๋‹ฌ๋ฆฌ ์‚ฌ์šฉ์ž ์ฑ„๋„ ์ •๋ณด ํ”ผ๋“œ๋ฐฑ์„ ์œ„ํ•ด ๋งŽ์€ ์–‘์˜ ํ”ผ๋“œ๋ฐฑ ๋น„ํŠธ๊ฐ€ ํ• ๋‹น๋˜์—ˆ์œผ๋ฉฐ, Givens rotation์ด๋ผ๋Š” ํšจ๊ณผ์ ์ธ ํ”ผ๋“œ๋ฐฑ ๋ฐฉ๋ฒ•์„ ์‚ฌ์šฉํ•˜์—ฌ ํ”ผ๋“œ๋ฐฑ ์ •๋ณด์˜ ์˜ค๋ฒ„ํ—ค๋“œ๋ฅผ ์ค„์ผ ์ˆ˜ ์žˆ๋‹ค. ๊ทธ ๊ฒฐ๊ณผ ์ ์€ ์–‘์˜ ํ”ผ๋“œ๋ฐฑ ํ• ๋‹น์— ์˜ํ•ด ์•ผ๊ธฐ๋˜๋Š” ์ฑ„๋„ ์–‘์žํ™” ์˜ค๋ฅ˜๋ฅผ ๋ฌด์‹œํ•  ์ˆ˜ ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๋ฌด์„ ๋žœ ์‹œ์Šคํ…œ์—์„œ๋Š” ์‹ฌ๊ฐํ•œ ์„ฑ๋Šฅ ์ €ํ•˜๋ฅผ ์ผ์œผํ‚ค๋Š” ๊ธด ํ”ผ๋“œ๋ฐฑ ์ง€์—ฐ์ด (ํ˜„์‹ค์ ์œผ๋กœ 200 ms์ด์ƒ) ๋ฐœ์ƒํ•  ์ˆ˜ ์žˆ๋‹ค. ์ด์™€ ๋”๋ถˆ์–ด ๋ฌด์„ ๋žœ ํ‘œ์ค€์—์„œ ๋‹ค์ค‘ ์‚ฌ์šฉ์ž ๋‹ค์ค‘ ์•ˆํ…Œ๋‚˜ ํ”„๋กœ์„ธ์‹ฑ ๊ตฌํ˜„์„ ์œ„ํ•ด ์ƒˆ๋กญ๊ฒŒ ์ •์˜ํ•œ ๊ทธ๋ฃน ์‹๋ณ„ ๋ฐ ์‚ฌ์šฉ์ž ์Šค์ผ€์ฅด๋ง์œผ๋กœ ์ธํ•ด ๊ธฐ์กด์— ์…€๋ฃฐ๋ผ ์‹œ์Šคํ…œ์— ์ œ์•ˆ๋˜์—ˆ๋˜ ์‚ฌ์šฉ์ž ์„ ํƒ ๋ฐฉ๋ฒ• ๋“ฑ์„ ์ง์ ‘ ์ ์šฉํ•˜๊ธฐ ํž˜๋“ค๋‹ค. part II์—์„œ๋Š” ์ด๋Ÿฌํ•œ ์ƒˆ๋กœ์šด ๋‚ด์šฉ์„ ๊ณ ๋ คํ•˜์—ฌ ํšจ๊ณผ์ ์ด๊ณ  ํ˜„์‹ค์ ์ธ ์‚ฌ์šฉ์ž ์Šค์ผ€์ฅด๋ง ๋ฐฉ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ์ œ์•ˆํ•œ ์Šค์ผ€์ฅด๋ง ๋ฐฉ๋ฒ•์€ ์ ์€ ๊ณ„์‚ฐ๋Ÿ‰์„ ๊ฐ€์ง€๊ณ  ์žˆ์œผ๋ฉฐ ํ‰๊ท  ์ด ์ „์†ก๋ฅ ์„ ํ–ฅ์ƒ์‹œํ‚ฌ ์ˆ˜ ์žˆ๋‹ค. ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ํ†ตํ•œ ์ˆ˜์น˜ ๊ฒฐ๊ณผ๋ฅผ ํ†ตํ•ด ์‚ฌ์šฉ์ž ์Šค์ผ€์ค„๋ง์„ ํ†ตํ•œ ์ œ์•ˆํ•œ SVD ๊ธฐ๋ฐ˜์˜ ๋‹ค์ค‘ ์‚ฌ์šฉ์ž ๋‹ค์ค‘ ์•ˆํ…Œ๋‚˜ ํ”„๋กœ์„ธ์‹ฑ ๋ฐฉ๋ฒ•์€ ๊ธฐ์กด์˜ ํ”„๋กœ์„ธ์‹ฑ์— ๋น„ํ•ด ํ›จ์”ฌ ์ข‹์€ ์„ฑ๋Šฅ์„ ๋‚˜ํƒ€๋ƒ„์„ ๋ณด์—ฌ์ฃผ๊ณ , ํŠนํžˆ ์ž‘์€ SNR ์˜์—ญ๊ณผ ๊ธด ํ”ผ๋“œ๋ฐฑ ์ง€์—ฐ ํ™˜๊ฒฝ์—์„œ ์ƒ๋‹นํ•œ ์„ฑ๋Šฅ ์ด๋“์ด ์žˆ์Œ์„ ํ™•์ธํ•˜์˜€๋‹ค.Over the last decade, multiple-user multiple-input multiple-output (MU-MIMO) processing has gained considerable attention in the wireless communication standards such as 3GPP-LTE Advanced, IEEE 802.16m, and IEEE 802.11ac. MU-MIMO processing is capable of simultaneously supporting multiple users and therefore attains large cell capacity increase. In this dissertation, MU-MIMO processing with low-computational complexity and applicability to diverse wireless communication systems is proposed for practical interests. For evaluating average sum-rate of the proposed MU-MIMO processing, two different wireless communication systems, cellular systems and wireless local area network (WLAN) systems, are considered in Parts I and II. In Part I of this dissertation, we focus on cellular systems where low feedback bits are allocated to report user channel information. For practical downlink MU-MIMO processing, we propose a linear beamforming MU-MIMO processing with low-computational complexity that includes preferred-beam index feedback, user selection algorithms, and beamforming matrix construction method. The preferred-beam index feedback efficiently conveys information on both the channel states of users and the effect of interuser interference especially in low-rate feedback environments. The proposed user selection algorithms exploits multiuser diversity to improve average sum-rate for the case when the number of users exceeds the number of transmit antennas. The proposed beamforming matrix construction method easily computes unitary beamforming matrix based on the feedback information using singular value decomposition (SVD) operation, which results in significant computational complexity reduction compared to the conventional methods. Simulation results show that the proposed SVD-based unitary MU-MIMO processing achieves higher average sum-rate particularly at low-rate feedback, while the computational complexity is kept reasonable. In Part II of this dissertation, IEEE 802.11ac-based WLAN systems are considered where Access Point (AP) can transmit multiple data streams to different users in parallel by MU-MIMO processing. Unlike cellular systems, the considered WLAN systems assign high-rate bits to feedback user channel information and utilize an efficient feedback mechanism using Givens rotation that reduces the overhead of feedback information. As a result, a channel quantization error caused by low-rate feedback could be negligible. In WLAN systems, however, there may be long feedback delay, more than 200 ms in reality, that leads to severe performance degradation. In addition, WLAN systems are difficult to directly apply conventional user selection algorithms including the proposed one in Part I since group identification (ID) and user scheduling that WLAN standard newly defines for MU-MIMO processing should be considered. Based on these features, we propose an efficient and a practical user selection algorithm with low-computational complexity. Simulation results also present that the proposed MU-MIMO processing combined with the proposed user selection algorithm considerabley outperforms conventional MU-MIMO processing such as zero-forcing beamforming (ZFBF) especially in low signal to noise ratio (SNR) region and/or long feedback delay.Abstract Contents List of Figures List of Tables 1 Introduction 1.1 SVD-Based Unitary MU-MIMO Processing in Cellular Systems 1.2 SVD-Based Unitary MU-MIMO Processing in WLAN Systems 1.3 Outline of Dissertation 2 SVD-Based Unitary MU-MIMO Processing in Cellular Systems 2.1 System Model 2.2 Proposed SVD-Based Unitary MU-MIMO Processing 2.2.1 User Feedback 2.2.2 User Selection 2.2.3 Construction of Unitary Beamforming Matrix 2.2.4 User Data Decoding 2.3 Simulation Results 2.4 Summary 3 SVD-Based Unitary MU-MIMO Processing in WLAN Systems 32 3.1 System Model 3.2 Proposed SVD-Based MU-MIMO Processing 3.2.1 Channel Sounding and User Feedback 3.2.2 User Grouping and User Scheduling 3.3 Simulation Results 3.4 Summary 4 Conclusion and Future Work 58 4.1 Conclusion 4.2 Future WorkDocto

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    ็ซถ็ˆญ่€…์— ์˜ํ•œ ๆ–ฐ่ฃฝๅ“ ไบ‹ๅ‰็™ผ่กจ๊ฐ€ ๆ—ฃๅญ˜ไผๆฅญ์˜ ๅๆ‡‰์— ๋ฏธ์น˜๋Š” ๅฝฑ้Ÿฟ์— ๊ด€ํ•œ ็ก็ฉถ : ๆ–ฐ่ฃฝๅ“ไบ‹ๅ‰็™ผ่กจ์˜ ไฟก่™Ÿๆจกๅž‹์„ ไธญๅฟƒ์œผ๋กœ

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธๅคงๅญธๆ ก ๅคงๅญธ้™ข :็ถ“็‡Ÿๅญธ็ง‘ ็ถ“็‡Ÿๅญธๅฐˆๆ”ป,1997.Maste

    Histomorpaologic study on supernumerary tooth.

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    ์น˜์˜ํ•™๊ณผ/์„์‚ฌ[ํ•œ๊ธ€] ๊ณผ์ž‰์น˜๋Š” ์ž„์ƒ์—์„œ ํ”ํžˆ ๊ด€์ฐฐ ๋˜๋ฉฐ ๋งน์ถœ ์—ฌ๋ถ€์™€ ๊ด€๊ณ„์—†์ด ์ฃผ๋ณ€์น˜์•„ ๋ฐ ์ฃผ์œ„ ์กฐ์ง์— ๋ณ€ํ˜•์„ ์œ ๋ฐœํ•  ์ˆ˜ ์žˆ์œผ๋‚˜ ์•„์ง ๋ช…ํ™•ํ•˜๊ฒŒ ๋ฐํ˜€์ง„ ์›์ธ์€ ์—†์œผ๋ฉฐ 3๋ฒˆ์งธ์˜ ์น˜ํŒ์—์„œ ํ˜•์„ฑ๋œ๋‹ค๋Š” ๊ฒฌํ•ด ๋ฐ ์˜๊ตฌ์น˜ ์ž์ฒด์—์„œ ๋ถ„๋ฆฌ๋˜์–ด ํ˜•์„ฑ๋œ๋‹ค๋Š” ๊ฒฌํ•ด ๋“ฑ์ด ์žˆ๋‹ค. ํ˜„์žฌ๊นŒ์ง€ ๊ณผ์ž‰์น˜์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋Š” ๊ณผ์ž‰์น˜์˜ ์›์ธ๋ก , ๋ฐœ๋ณ‘๋ฅ , ํ•ฉ๋ณ‘์ฆ ๊ทธ๋ฆฌ๊ณ  ์น˜๋ฃŒ์˜ ์ ‘๊ทผ๋ฐฉ๋ฒ• ๋“ฑ์— ๋Œ€ํ•œ ๊ฒƒ์ด๋ฉฐ ๊ณผ์ž‰์น˜ ๋ฐœ์น˜์˜ ํ•„์š”์„ฑ, ๋ฐœ์น˜์‹œ๊ธฐ ๊ทธ๋ฆฌ๊ณ  ๊ณผ์ž‰์น˜์— ์˜ํ•œ ํ•ฉ๋ณ‘์ฆ์— ๋Œ€ํ•ด์„œ ์•„์ง๊นŒ์ง€ ๋งŽ์€ ๋…ผ๋ž€์ด ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ๋ฌธํ—Œ๋“ค ์ค‘ ๊ณผ์ž‰์น˜์˜ ๋ณ‘๋ฆฌ์กฐ์งํ•™์ ์ธ ๋Œ€ํ•ด์„œ๋Š” ๋“œ๋ฌผ์ง€๋งŒ ๋ณ‘๋ฆฌ์กฐ์งํ•™์ ์ธ ์—ฐ๊ตฌ๋Š” ๊ณผ์ž‰์น˜์˜ ๊ตฌ์กฐ๋ฅผ ๋‹ค๋ฅธ ์น˜์•„์™€ ๋น„๊ตํ•จ๊ณผ ๋™์‹œ์— ์ฃผ์œ„์กฐ์ง์— ๋ฏธ์น  ์ˆ˜ ์žˆ๋Š” ํ•ฉ๋ณ‘์ฆ์˜ ์›์ธ์„ ์ฐพ๋Š”๋‹ค๋Š” ์ ์—์„œ ์ž„์ƒ์ ์œผ๋กœ ์˜๋ฏธ๋ฅผ ๊ฐ€์งˆ ์ˆ˜ ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” 5์„ธ์—์„œ 11์„ธ์˜ ํ™˜์•„๋ฅผ ๋Œ€์ƒ์œผ๋กœ ์™ธ๊ณผ์ ์œผ๋กœ ๋ฐœ๊ฑฐ๋œ ๋งค๋ณต ๊ณผ์ž‰์น˜ 24๊ฐœ์™€ ์น˜๋‚ญ 16๊ฐœ์— ๋Œ€ํ•œ ๋ณ‘๋ฆฌ์กฐ์งํ•™์ ์ธ ์ž๋ฃŒ๋ฅผ ์ œ๊ณตํ•˜๊ณ ์ž ๊ด‘ํ•™ํ˜„๋ฏธ๊ฒฝ์œผ๋กœ ๊ด€์ฐฐํ•˜์—ฌ ๋‹ค์Œ๊ณผ ๊ฐ™์€ ๊ฒฐ๊ณผ๋ฅผ ์–ป์—ˆ๋‹ค. 1. ๊ณผ์ž‰์น˜ ์น˜๋‚ญ์˜ 38%์—์„œ ํ‡ด์ถ• ์น˜์„ฑ์ƒํ”ผ๊ฐ€ ๊ด€์ฐฐ๋˜์—ˆ์œผ๋ฉฐ 13%์—์„œ ๋‚ญ์ข…๋ณ€ํ™” ์†Œ๊ฒฌ์„ ๋ณด์˜€๋‹ค. 2. ๊ณผ์ž‰์น˜์˜ ์น˜๊ด€ ๋ฐ ์น˜๊ทผ๋ถ€์œ„์—์„œ 46%์—์„œ ํก์ˆ˜์–‘์ƒ์ด ๊ด€์ฐฐ ๋˜์—ˆ์œผ๋ฉฐ ํก์ˆ˜๋œ ๋ถ€์œ„๋Š” ์ƒ์•„์งˆ์ƒ์ด๋‚˜ ์„ํšŒํ™” ์กฐ์ง์œผ๋กœ ๋Œ€์ฒด๋˜์–ด ์žˆ์—ˆ๋‹ค. 3. ๊ณผ์ž‰์น˜ ์น˜๋‚ญ์˜ 19%์—์„œ ๋‹จํ•ต์„ธํฌ๊ฐ€ ์นจ์œค๋˜์—ˆ๊ณ  19%์—์„œ ์น˜์ฃผ์ธ๋Œ€๋กœ ๋ถ„ํ™”๋˜๋Š” ์†Œ๊ฒฌ์„ ๋ณด์˜€๋‹ค. 4. ๊ณผ์ž‰์น˜ ์น˜๋‚ญ์˜ 63%์—์„œ ์ ์•ก์„ฑ ๋ณ€ํ™”๋ฅผ ๋‚˜ํƒ€๋ƒˆ์œผ๋ฉฐ 38%์—์„œ ์น˜์„ฑ์„ธํฌ ์ž”์กด์„ ๋ณด์˜€๋‹ค. ์œ„ ๊ฒฐ๊ณผ๋กœ ๋ฏธ๋ฃจ์–ด ๋ณผ ๋•Œ ๊ณผ์ž‰์น˜ ์ฃผ๋ณ€์—์„œ ๋†’์€ ๋นˆ๋„๋กœ ํ‡ด์ถ• ์น˜์„ฑ์ƒํ”ผ์„ธํฌ๊ฐ€ ๊ด€์ฐฐ๋˜๋Š” ๊ฒƒ์€ ๋‚ญ์ข…์œผ๋กœ ๋ฐœ์ „๋  ๋†’์€ ์ž ์žฌ์„ฑ์„ ๋‚˜ํƒ€๋‚ด๊ณ  ์žˆ์œผ๋ฉฐ ๋˜ํ•œ ์น˜์ฃผ์ธ๋Œ€๋กœ ๋ถ„ํ™”๋œ ์–‘์ƒ๊ณผ ๋‹จํ•ต์„ธํฌ์˜ ๊ด€์ฐฐ์€ ๋งค๋ณต๋œ ๊ณผ์ž‰์น˜๊ฐ€ ๋”์šฑ ๊นŠ์ด ๋งค๋ณต๋  ๊ฐ€๋Šฅ์„ฑ์„ ๋‚˜ํƒ€๋‚ด๋ฏ€๋กœ ๊ณผ์ž‰์น˜์˜ ์™ธ๊ณผ์  ๋ฐœ์น˜๋ฅผ ๊ฒฐ์ •ํ•  ๋•Œ ์ด๋Ÿฌํ•œ ์ ์„ ๊ณ ๋ คํ•ด์•ผ ํ•œ๋‹ค. -------------------- ํ•ต์‹ฌ๋˜๋Š” ๋ง : ๋งค๋ณต, ๊ณผ์ž‰์น˜, ์น˜๋‚ญ, ํ˜„๋ฏธ๊ฒฝํ•™์ ์ธ ์†Œ๊ฒฌ [์˜๋ฌธ] Supernumerary teeth are frequent disease which can cause functional and esthetic problems on neighboring teeth and peridontal tissue. But the etiologies of development of supernumerary teeth are still unknown but development of third dental lamina and separation of permanent tooth bud are believable. Many reports have been written on supernumerary teeth but they were focused on frequencies, treatments and locations. Few document can be found on histopatholocial studies of the supernumerary teeth. This study contains light microscopic observations of impacted supernumerary teeth which were surgically extracted from patients age from 5 years to 11 years. Pathohistological studies may compare the structures of supernumerary tooth to other permanent tooth and deciduous tooth, also may find the causes of complication to neighboring tooth. Following results were made; 1. Reduced enamel epithelium was observed on 38% of supernumerary teeth and 13% had cystic change. 2. Forty six percentage of supernumerary teeth showed replacement resorption. They were observed on crown and root portion and replaced with dentinoids and calcified materials. 3. Monocytes were observed on 19% of dental follicle and 19% had periodental ligament differentiation . 4. Myxoid changes occured on 63% of dental follicle and odontogenic cell rests were observed on 38% of dental follicle. From these results, reduced enamel epithelium frequently has high potential on causing cystic changes. Monocyte infiltration and PDL differentiation may drift mesiodens into deeper portions therefore early extraction of supernumerary teeth is considered.ope

    SVD-Based Unitary Processing for Low-Rate Feedback Multiuser MIMO Systems

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) --์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์ „๊ธฐ. ์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€,2009.8.Maste

    ISO 26262 ๊ธฐ๋Šฅ ์•ˆ์ „ ์š”๊ตฌ์‚ฌํ•ญ์„ ์œ„ํ•œ ROS์˜ ๊ฐœ์„ ๋œ ํ†ต์‹  ๋ฉ”์ปค๋‹ˆ์ฆ˜

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์œตํ•ฉ๊ณผํ•™๋ถ€, 2017. 2. ํ™์„ฑ์ˆ˜.์ตœ๊ทผ์˜ ์ž๋™์ฐจ ์‚ฐ์—…์—์„œ๋Š” ์ „์žฅ๋ถ€ํ’ˆ๋“ค์˜ ๊ธฐ๋Šฅ์•ˆ์ „ ์ค‘์š”์„ฑ์ด ๋ถ€๊ฐ๋˜๊ณ  ์žˆ๋‹ค. ๋งค๋…„ ์ž๋™์ฐจ ์ œ์กฐํšŒ์‚ฌ๋“ค์€ ์ตœ์ฒจ๋‹จ ์šด์ „ ๋ณด์กฐ ์‹œ์Šคํ…œ์ด ํƒ‘์žฌ๋œ ์‹ ์ œํ’ˆ์„ ๊ฒฝ์Ÿ์ ์œผ๋กœ ์ถœ์‹œํ•˜๊ณ  ์žˆ๊ณ , ์ฐจ๋Ÿ‰ ๋‚ด์—๋Š” ์ด๋Ÿฌํ•œ ์‹œ์Šคํ…œ์„ ์œ„ํ•œ ECU(Electronic Control Unit)์™€ ๋‹ค์–‘ํ•œ ์„ผ์„œ ๋“ฑ ์ „์ž์žฅ๋น„์˜ ๋น„์ค‘์ด ๋†’์•„์ง์€ ๋ฌผ๋ก  ์ „์ž์žฅ๋น„๋ฅผ ์ง€์›ํ•˜๊ธฐ ์œ„ํ•œ ์ฐจ๋Ÿ‰์šฉ ์†Œํ”„ํŠธ์›จ์–ด์˜ ํฌ๊ธฐ์™€ ๋ณต์žก์„ฑ์ด ์ฆ๊ฐ€ํ•˜๊ณ  ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ์ƒํ™ฉ์„ ํšจ์œจ์ ์ด๊ณ  ์˜ฌ๋ฐ”๋ฅด๊ฒŒ ๊ด€๋ฆฌํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ISO 26262 ๊ตญ์ œํ‘œ์ค€์ด ์ œ์•ˆ๋˜์—ˆ๋‹ค. ISO 26262๋Š” ์ „์žฅ๋ถ€ํ’ˆ ๋ฐ ์ „์žฅ์‹œ์Šคํ…œ์˜ ์˜ค์ž‘๋™์ด ๋ฐœ์ƒํ•  ๊ฐ€๋Šฅ์„ฑ๊ณผ ์ด๋กœ ์ธํ•œ ์‚ฌ๊ณ ๋ฐœ์ƒ์˜ ์œ„ํ—˜์ด ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์— ๋Œ€ํ•œ ๋ถ„์„ ํ‰๊ฐ€๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ๊ฐ๊ฐ์˜ ์ „์žฅ์‹œ์Šคํ…œ์— ์ž๋™์ฐจ ์•ˆ์ „์„ฑ ์š”๊ตฌ์ˆ˜์ค€(Automotive Safety Integrity Level, ASIL)์„ ๋ถ€์—ฌํ•˜๊ณ  ๊ฐ ์ˆ˜์ค€๋ณ„ ๋งŒ์กฑํ•ด์•ผ ํ•  ์š”๊ตฌ์‚ฌํ•ญ์„ ์ œ์•ˆํ•˜๋ฉฐ, ์ „์žฅ๋ถ€ํ’ˆ ๋ฐ ์ „์žฅ ์‹œ์Šคํ…œ์˜ ๋ชจ๋“  ์ƒ์• ์ฃผ๊ธฐ์—์„œ ์•ˆ์ „์„ฑ์„ ํ™•๋ณดํ•˜๊ณ  ๊ด€๋ฆฌํ•  ์ˆ˜ ์žˆ๋Š” ํ‘œ์ค€ํ™”๋œ ๊ฐœ๋ฐœ ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•œ๋‹ค. ํ•œํŽธ, ๋กœ๋ด‡ ์˜คํผ๋ ˆ์ดํŒ… ์‹œ์Šคํ…œ(Robot Operating System, ROS)์€ ๋กœ๋ด‡์— ํƒ‘์žฌ๋˜๋Š” ์†Œํ”„ํŠธ์›จ์–ด์˜ ๋น ๋ฅด๊ณ  ํŽธ๋ฆฌํ•œ ์ž‘์„ฑ์„ ์ง€์›ํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ๊ฐœ๋ฐœ๋˜์—ˆ๋‹ค. ๋‹ค์–‘ํ•œ ๋ผ์ด๋ธŒ๋Ÿฌ๋ฆฌ ์ œ๊ณต๊ณผ ํ™œ๋ฐœํ•œ ๊ฐœ๋ฐœ ์ง€์› ์ปค๋ฎค๋‹ˆํ‹ฐ ๋“ฑ ๊ธฐ์กด์˜ ์ž๋™์ฐจ ํ”Œ๋žซํผ์—์„œ ์ œ๊ณตํ•ด ์ฃผ์ง€ ๋ชปํ•˜๋Š” ๊ฐœ๋ฐœ ํŽธ์˜์„ฑ์œผ๋กœ ์ธํ•ด ๊ทผ๋ž˜์—๋Š” ์ž์œจ์ฃผํ–‰์ฐจ๋Ÿ‰ ์‹œ๋‚˜๋ฆฌ์˜ค ๋“ฑ ๊ธฐ์กด ์ „์žฅ์‹œ์Šคํ…œ์—์„œ ์ œ๊ณตํ•˜์ง€ ์•Š๋˜ ๋ณต์žกํ•œ ๊ธฐ๋Šฅ์„ ์†์‰ฝ๊ฒŒ ๊ฐœ๋ฐœํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ์ฃผ์š” ์ž๋™์ฐจ ์ œ์กฐ์‚ฌ๋“ค์ด ์ƒˆ๋กœ์šด ์ž๋™์ฐจ ํ”Œ๋žซํผ์œผ๋กœ ์ ์ฐจ ๋„์ž…ํ•˜๊ณ  ์žˆ๋‹ค. ํ•˜์ง€๋งŒ, ROS๋Š” ์†Œํ”„ํŠธ์›จ์–ด์˜ ๋น ๋ฅด๊ณ  ํŽธ๋ฆฌํ•œ ์ž‘์„ฑ์— ์ดˆ์ ์„ ๋งž์ถ”์—ˆ๊ธฐ ๋•Œ๋ฌธ์— ์ž๋™์ฐจ ํ”Œ๋žซํผ์œผ๋กœ์„œ ๋ฐ˜๋“œ์‹œ ๊ฐ–์ถ”์–ด์•ผ ํ•  ์•ˆ์ „ ๊ธฐ๋Šฅ์— ๋Œ€ํ•œ ๊ณ ๋ ค๊ฐ€ ๊ธฐ์กด์˜ ์ž๋™์ฐจ ํ”Œ๋žซํผ๋“ค์— ๋น„ํ•ด ์ƒ๋Œ€์ ์œผ๋กœ ๋ฏธ๋น„ํ•˜๋‹ค. ์ด ๋…ผ๋ฌธ์—์„œ๋Š” ROS์˜ ์•ˆ์ „ ๋ฉ”์ปค๋‹ˆ์ฆ˜๋“ค๊ณผ ISO 26262์— ์ •์˜๋œ ์†Œํ”„ํŠธ์›จ์–ด ์˜ค๋ฅ˜ ๊ตฌ๋ถ„์„ ๋น„๊ตํ•˜๊ณ , ํ˜„์žฌ์˜ ROS๊ฐ€ ๋งŒ์กฑํ•˜์ง€ ๋ชปํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋ถ„์„๋œ ์„ธ ๊ฐ€์ง€ ์ •๋ณด๊ตํ™˜ ์˜ค๋ฅ˜์— ๋Œ€ํ•œ ๊ฐœ์„ ๋œ ์•ˆ์ „๊ธฐ๋Šฅ์„ ์ œ์•ˆํ•˜์—ฌ ROS๊ฐ€ ISO 26262์— ์ •์˜๋œ ์†Œํ”„ํŠธ์›จ์–ด ์˜ค๋ฅ˜๋ฅผ ๋ชจ๋‘ ๋Œ€์ฒ˜ํ•  ์ˆ˜ ์žˆ๋„๋ก ํ•œ๋‹ค.์ œ 1 ์žฅ ์„œ ๋ก  1 ์ œ 2 ์žฅ ๋ฐฐ ๊ฒฝ 6 2.1 ROS 6 2.2 ISO 26262 10 2.3 ROS์˜ ์•ˆ์ „ ๊ธฐ๋Šฅ 13 ์ œ 3 ์žฅ ๋ฌธ์ œ์ •์˜ 24 3.1 ์‹œ์Šคํ…œ ๋ชจ๋ธ 24 3.2 ISO 26262 ์†Œํ”„ํŠธ์›จ์–ด ์˜ค๋ฅ˜ ๊ตฌ๋ถ„๊ณผ ROS ์•ˆ์ „ ๊ธฐ๋Šฅ ๋น„๊ต 26 3.3 ROS ์ •๋ณด ๊ตํ™˜ ๋ชจ๋ธ์˜ ํ•œ๊ณ„์™€ ์ œ์•ฝ 28 ์ œ 4 ์žฅ ์•ˆ์ „์„ฑ ๊ฐœ์„ ๋œ ROS ํ†ต์‹  ๋ฉ”์ปค๋‹ˆ์ฆ˜ 32 4.1 Safety Enhanced Node Metadata Supervision 33 4.2 Safety Reinforced Message 36 4.3 ์ œ์•ˆํ•œ ๊ธฐ๋ฒ• ๋ถ„์„ 38 ์ œ 5 ์žฅ ์‹คํ—˜ ๋ฐ ๊ฒ€์ฆ 41 5.1 ์‹คํ—˜ ํ™˜๊ฒฝ 41 5.2 ์‹คํ—˜ ๊ตฌ์„ฑ 42 5.3 ์‹คํ—˜ ํ‰๊ฐ€ 43 ์ œ 6 ์žฅ ๊ด€๋ จ์—ฐ๊ตฌ 46 ์ œ 7 ์žฅ ๊ฒฐ ๋ก  52 ์ฐธ๊ณ ๋ฌธํ—Œ 53 Abstract 56Maste

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    -based High Temperature Superdonductors

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    ์ค‘ํ•™๊ต ์ˆ˜ํ•™๊ต๊ณผ์„œ์™€ ๊ณผํ•™๊ต๊ณผ์„œ์˜ ๊ณตํ†ต ์šฉ์–ด ๋น„๊ตยท๋ถ„์„

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์ˆ˜ํ•™๊ต์œก๊ณผ,2006.Maste
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