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    ๋‹ค์ค‘ ์„ผ์„œ ํ•ญ๋ฒ•์‹œ์Šคํ…œ์„ ์œ„ํ•œ ์—ฐํ•ฉํ˜• ๋ถˆ๋ณ€ ํ™•์žฅ์นผ๋งŒํ•„ํ„ฐ

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ํ•ญ๊ณต์šฐ์ฃผ๊ณตํ•™๊ณผ, 2022.2. ๋ฐ•์ฐฌ๊ตญ.This thesis presents the federated invariant extended Kalman filter (IEKF) using multiple measurements. IEKF has superior estimation performance compared to EKF through the definition of state variables on matrix Lie group while using the framework of the EKF. The IEKF enables trajectory independent estimation when left- or right-invariant measurements are used with proper invariant error selection. As a result, the IEKF ensures the convergence and accuracy of estimation, even when the estimation error is large. Most IEKF studies assumed the use of single aiding measurement. However, navigation systems often use multiple aiding sensors to improve estimation performance in applications. When left- and right-invariant measurements are used simultaneously, implementing the LIEKF or RIEKF with a centralized filter structure causes some terms of the measurement matrix dependent on the current estimates, which results in IEKF losing its trajectory independent advantage. On the other hand, when a decentralized filter structure, especially a federated filter structure, is applied, the estimation becomes trajectory independent through separate update of each measurement in the local filters. This thesis proposes a fusion method of IEKF using the federated filter structure for simultaneous use of left- and right-invariant measurements. The performance of the proposed fusion method is validated through simulations. The error convergence and accuracy of the proposed method and the centralized IEKF are compared.๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ๋‹ค์ˆ˜์˜ ๋ณด์ • ์„ผ์„œ๋ฅผ ์‚ฌ์šฉํ•˜๋Š” ํ•ญ๋ฒ• ์‹œ์Šคํ…œ์„ ์œ„ํ•œ ์—ฐํ•ฉํ˜• ๋ถˆ๋ณ€ ํ™•์žฅ ์นผ๋งŒํ•„ํ„ฐ์˜ ๊ตฌํ˜„์„ ์ œ์•ˆํ•œ๋‹ค. ๋ถˆ๋ณ€ ํ™•์žฅ ์นผ๋งŒํ•„ํ„ฐ๋Š” ์ผ๋ฐ˜์ ์ธ ํ™•์žฅ ์นผ๋งŒํ•„ํ„ฐ์˜ ํ”„๋ ˆ์ž„์›Œํฌ๋Š” ๊ทธ๋Œ€๋กœ ์‚ฌ์šฉํ•˜๋ฉด์„œ ์ƒํƒœ๋ณ€์ˆ˜๋ฅผ ํ–‰๋ ฌ ๋ฆฌ ๊ทธ๋ฃน ์ƒ์—์„œ ์ •์˜ํ•˜์—ฌ ํ™•์žฅ ์นผ๋งŒํ•„ํ„ฐ ๋Œ€๋น„ ์šฐ์ˆ˜ํ•œ ์ถ”์ • ์„ฑ๋Šฅ์„ ๊ฐ€์ง„๋‹ค. ์ขŒ๋ถˆ๋ณ€ ํ˜น์€ ์šฐ๋ถˆ๋ณ€ ์ธก์ •์น˜๋ฅผ ์‚ฌ์šฉํ•  ๋•Œ ์ด์— ์ ํ•ฉํ•œ ๋ถˆ๋ณ€ ์˜ค์ฐจ ์ •์˜๋ฅผ ์„ ํƒํ•˜์—ฌ ๊ตฌํ˜„ํ•œ๋‹ค๋ฉด ๊ถค์  ๋…๋ฆฝ์ ์ธ ์ถ”์ •์ด ๊ฐ€๋Šฅํ•˜๋‹ค. ๋Œ€๋ถ€๋ถ„์˜ ๋ถˆ๋ณ€ ํ™•์žฅ ์นผ๋งŒํ•„ํ„ฐ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋“ค์€ ๋‹จ์ผ ๋ณด์ • ์„ผ์„œ์˜ ์‚ฌ์šฉ์„ ๊ฐ€์ •ํ•œ๋‹ค. ๊ทธ๋Ÿฐ๋ฐ ์‹ค์ œ ์ ์šฉ์— ์žˆ์–ด, ํ•ญ๋ฒ• ์‹œ์Šคํ…œ์€ ์ถ”์ • ์„ฑ๋Šฅ์„ ํ–ฅ์ƒํ•˜๊ธฐ ์œ„ํ•ด ๋‹ค์ˆ˜์˜ ๋ณด์ • ์„ผ์„œ๋ฅผ ์‚ฌ์šฉํ•˜๋Š” ๊ฒฝ์šฐ๊ฐ€ ๋งŽ๋‹ค. ์ขŒ๋ถˆ๋ณ€ ์ธก์ •์น˜์™€ ์šฐ๋ถˆ๋ณ€ ์ธก์ •์น˜๊ฐ€ ๋ชจ๋‘ ์‚ฌ์šฉ๋˜๋Š” ์ƒํ™ฉ์ด๋ผ๋ฉด, ์ค‘์•™์ง‘์ค‘ํ˜• ์ขŒ๋ถˆ๋ณ€ ํ™•์žฅ ์นผ๋งŒํ•„ํ„ฐ์™€ ์šฐ๋ถˆ๋ณ€ ํ™•์žฅ ์นผ๋งŒํ•„ํ„ฐ๋Š” ๋ชจ๋‘ ์ถ”์ •์น˜์— ์˜ํ–ฅ์„ ๋ฐ›๋Š” ์ธก์ •์น˜ ํ–‰๋ ฌ์„ ์‚ฌ์šฉํ•˜๊ฒŒ ๋œ๋‹ค. ์ด๋กœ ์ธํ•ด ๋ถˆ๋ณ€ ํ™•์žฅ์นผ๋งŒํ•„ํ„ฐ๊ฐ€ ๊ฐ–๋Š” ๊ฐ€์žฅ ํฐ ์žฅ์ ์ธ ๊ถค์  ๋…๋ฆฝ ํŠน์„ฑ์„ ์žƒ๋Š”๋‹ค. ๋ฐ˜๋ฉด์— ์—ฐํ•ฉํ˜• ํ•„ํ„ฐ ๊ตฌ์กฐ๋ฅผ ์‚ฌ์šฉํ•˜๋ฉด ๊ฐ ์ธก์ •์น˜์— ํ• ๋‹น๋œ ๊ตญ์†Œ ํ•„ํ„ฐ์—์„œ ์ ์ ˆํ•œ ํ•„ํ„ฐ๋กœ ๊ฐ ์ธก์ •์น˜๋ฅผ ์ฒ˜๋ฆฌํ•  ์ˆ˜ ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ์ด ๋…ผ๋ฌธ์—์„œ๋Š” ๋ถˆ๋ณ€ ํ™•์žฅ ์นผ๋งŒํ•„ํ„ฐ์˜ ์—ฐํ•ฉํ˜• ๊ตฌ์กฐ ๊ตฌํ˜„์„ ์ œ์•ˆํ•œ๋‹ค. ๋ฆฌ ๊ทธ๋ฃน์˜ ์„ฑ์งˆ์„ ๊ณ ๋ คํ•˜๋Š” ์ ์ ˆํ•œ ์œตํ•ฉ ๋ฐฉ์‹์„ ์‚ฌ์šฉํ•œ ๊ตฌ์กฐ๋ฅผ ์ œ์•ˆํ•˜๋ฉฐ, ๊ทธ ์„ฑ๋Šฅ์„ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ํ†ตํ•ด ํ™•์ธํ•œ๋‹ค. ์ œ์•ˆํ•œ ๋ฐฉ์‹๊ณผ ์ค‘์•™์ง‘์ค‘ํ˜• ๋ถˆ๋ณ€ ํ™•์žฅ ์นผ๋งŒํ•„ํ„ฐ๋ฅผ ์ˆ˜๋ ด์„ฑ๊ณผ ์ถ”์ • ์ •ํ™•๋„์˜ ๊ด€์ ์—์„œ ๋น„๊ตํ•˜์˜€๋‹ค.Chapter 1 Introduction 1 1.1 Motivation 1 1.2 Objectives and contributions 3 Chapter 2 Related Works 5 2.1 Invariant extended Kalman filter (IEKF) 5 2.2 Federated filter 7 Chapter 3 Framework of invariant EKF 9 3.1 Mathematical preliminaries 9 3.2 States and model 10 3.2.1 Matrix Lie group states 10 3.2.2 Process model 12 3.2.3 Measurement model 15 3.2.4 Adjoint 16 3.3 IEKF for inertial navigation 17 3.3.1 IMU states and error states 17 3.3.2 Process model 20 3.3.3 Measurement model 22 3.3.4 Adjoint transformation 27 Chapter 4 IEKF Using Multiple Measurements 28 4.1 Centralized filter implementation 29 4.1.1 Centralized LIEKF 30 4.1.2 Centralized RIEKF 32 4.2 Federated filter implementation 34 4.2.1 Overall structure 34 4.2.2 Fusion process 39 4.3 Numerical simulations 40 4.3.1 Convergence test 43 4.3.2 Comparison of centralized IEKF and EKF 48 4.3.3 Comparison of IEKF and the proposed method 52 Chapter 5 Conclusion 60 5.1.1 Conclusion and summary 60 5.1.2 Future works 61 Bibliography 62 ๊ตญ๋ฌธ์ดˆ๋ก 68์„

    Comparison of urinary hippuric acid, toluene and o-cresol as biological exposure indicies for workers exposed t

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    ์‚ฐ์—…๋ณด๊ฑดํ•™๊ณผ/์„์‚ฌ[ํ•œ๊ธ€] ์œ ๊ธฐ์šฉ์ œ๋Š” ์—ฌ๋Ÿฌ ์‚ฐ์—…์žฅ์—์„œ ํ•„์ˆ˜์ ์ธ ๊ฒƒ์œผ๋กœ ๊ทธ ์šฉ๋„๊ฐ€ ๋‹ค์–‘ํ•˜๋ฉฐ ์‚ฌ์šฉ๋Ÿ‰์€ ์ ์  ์ฆ๊ฐ€ํ•˜๊ณ  ์žˆ๋‹ค. ํŠนํžˆ ํ†จ๋ฃจ์—”์€ ๋ฒค์  ์˜ ๋Œ€์ฒด๋ฌผ์งˆ๋กœ ์‚ฌ์šฉ๋Ÿ‰์ด ์ฆ๊ฐ€๋จ์— ๋”ฐ๋ผ ๋งŽ์€ ์ž‘์—…์žฅ์—์„œ ์ด๋ฅผ ์ทจ๊ธ‰ํ•˜๊ณ  ์žˆ๋Š” ๊ทผ๋กœ์ž๋“ค์˜ ์ง์—…์  ๋…ธ์ถœ๊ธฐํšŒ๊ฐ€ ๋งค์šฐ ๋†’์€ ์ƒํ™ฉ์ด๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ํ†จ๋ฃจ์—”์— ๋…ธ์ถœ๋˜๋Š” ๊ทผ๋กœ์ž๋“ค์„ ๋Œ€์ƒ์œผ๋กœ ์ƒ๋ฌผํ•™์ ๋ชจ๋‹ˆํ„ฐ๋ง ๋ฐฉ๋ฒ•์œผ๋กœ์„œ ์š”์ค‘ ๋งˆ๋‡จ์‚ฐ, ์š”์ค‘ ํ†จ๋ฃจ์—”, ์š”์ค‘ ์˜ค๋ฅดํ† -ํฌ๋ ˆ์กธ๊ณผ ๋…ธ์ถœ ๊ทผ๋กœ์ž์˜ ๊ฐœ์ธ๋ณ„ ํŠน์„ฑ์— ๋”ฐ๋ฅธ ์ฐจ์ด, ๊ธฐ์ค‘ ํ†จ๋ฃจ์—” ๊ฐœ์ธ ๋…ธ์ถœ ๋†๋„์™€์˜ ์ƒ๊ด€์„ฑ, ์ƒ์ฒด์‹œ๋ฃŒ์˜ ์ฑ„์ทจ์‹œ์ ์— ๋”ฐ๋ฅธ ๋…ธ์ถœ ์ง€ํ‘œ์˜ ์ฐจ์ด๋ฅผ ์•Œ์•„๋ณด๊ณ ์ž ํ•˜์˜€์œผ๋ฉฐ ๊ฒฐ๊ณผ๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ์ฒซ์งธ, ์—ฐ๊ตฌ๋Œ€์ƒ์ž์˜ ๊ฐœ์ธ๋ณ„ ํŠน์„ฑ(์—ฐ๋ น, BMI, ์•ˆ์‹ํ–ฅ์‚ฐ ํ•จ์œ  ์Œ์‹ ์„ญ์ทจ ์—ฌ๋ถ€, ์Œ์ฃผ, ํก์—ฐ, ์•ฝ๋ฌผ๋ณต์šฉ, ์ปคํ”ผ ์Œ์šฉ)์— ๋”ฐ๋ฅธ ์ƒ๋ฌผํ•™์  ๋…ธ์ถœ์ง€ํ‘œ ๋ฐฐ์„ค ๋†๋„์—๋Š” ์š”์ค‘ ๋งˆ๋‡จ์‚ฐ, ์š”์ค‘ ํ†จ๋ฃจ์—”, ์š”์ค‘ ์˜ค๋ฅดํ† -ํฌ๋ ˆ์กธ ๋ชจ๋‘ ํ†ต๊ณ„ํ•™์ ์œผ๋กœ ์œ ์˜ํ•œ ์ฐจ์ด๊ฐ€ ์—†์—ˆ๋‹ค. ๋‘˜์งธ, ๊ธฐ์ค‘ ํ†จ๋ฃจ์—”์— ๋Œ€ํ•œ ๊ฐœ์ธ ๋…ธ์ถœ๋†๋„์™€ ์š”์ค‘ ๋งˆ๋‡จ์‚ฐ์€ ์ƒ๊ด€๊ณ„์ˆ˜๊ฐ€ r=0.596์œผ๋กœ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•œ ์ƒ๊ด€๊ด€๊ณ„๊ฐ€ ์žˆ์—ˆ์ง€๋งŒ(p<0.05), ์š”์ค‘ ํ†จ๋ฃจ์—”๊ณผ ์š”์ค‘ ์˜ค๋ฅดํ† -ํฌ๋ ˆ์กธ์€ ๊ฐ๊ฐ r=-0.051 , r=0.037๋กœ ์ƒ๊ด€๊ด€๊ณ„๊ฐ€ ๋‚ฎ๊ณ  ํ†ต๊ณ„์ ์œผ๋กœ๋„ ์œ ์˜ ํ•˜์ง€ ์•Š์•˜์œผ๋ฉฐ ๋˜ํ•œ 10ppm๋ฏธ๋งŒ๊ตฐ์—์„œ๋„ ๊ธฐ์ค‘ ํ†จ๋ฃจ์—” ๊ฐœ์ธ ๋…ธ์ถœ๋†๋„์™€ ์ƒ๋ฌผํ•™์  ๋…ธ์ถœ์ง€ํ‘œ์™€์˜ ์ƒ๊ด€์„ฑ์€ ์„ธ ์ง€ํ‘œ ๋ชจ๋‘ ํ†ต๊ณ„ํ•™์ ์œผ๋กœ ์œ ์˜ํ•˜์ง€ ์•Š์•˜๋‹ค. ์…‹์งธ, ๊ธฐ์ค‘ ํ†จ๋ฃจ์—”์˜ ๊ฐœ์ธ ๋…ธ์ถœ ๋†๋„์— ๋”ฐ๋ฅธ ์ž‘์—… ์ „ ๋ฐ ์ž‘์—… ํ›„์˜ ์ƒ๋ฌผํ•™์  ๋…ธ์ถœ์ง€ํ‘œ์˜์ฐจ์ด๋Š” ์ „์ฒด์ ์œผ๋กœ ์š”์ค‘ ๋งˆ๋‡จ์‚ฐ, ์š”์ค‘ ํ†จ๋ฃจ์—”, ์š”์ค‘ ์˜ค๋ฅดํ† -ํฌ๋ ˆ์กธ ๋ชจ๋‘ ์ž‘์—… ํ›„๊ฐ€ ์ž‘์—… ์ „๋ณด๋‹ค ๋†’๊ฒŒ ๋‚˜์™”์œผ๋ฉฐ ํ†ต๊ณ„ํ•™์ ์œผ๋กœ ์œ ์˜ํ•˜์˜€๋‹ค.(p<0.05). ๊ทธ๋Ÿฌ๋‚˜ ๋†๋„๊ตฐ๋ณ„ ๋น„๊ต์—์„œ 1pp m ๋ฏธ๋งŒ ๊ตฐ์—์„œ๋Š” ์š”์ค‘ ํ†จ๋ฃจ์—”๊ณผ ์š”์ค‘ ์˜ค๋ฅดํ†  ํฌ๋ ˆ์กธ์ด ์ž‘์—… ์ „ ๋ฐ ์ž‘์—… ํ›„์˜ ์ฐจ์ด๊ฐ€ ํ†ต๊ณ„ํ•™์ ์œผ๋กœ ์œ ์˜ํ•˜์˜€๊ณ  ์š”์ค‘ ๋งˆ๋‡จ์‚ฐ์€ ํ†ต๊ณ„ํ•™์ ์œผ๋กœ ์œ ์˜ํ•˜์ง€ ์•Š์•˜๋‹ค. ๋ณธ ์—ฐ๊ตฌ๊ฒฐ๊ณผ ์—ฐ๊ตฌ๋Œ€์ƒ์ž์˜ ๊ฐœ์ธ๋ณ„ ํŠน์„ฑ(์—ฐ๋ น, BMI, ์•ˆ์‹ํ–ฅ์‚ฐ ํ•จ์œ  ์Œ์‹ ์„ญ์ทจ ์—ฌ๋ถ€, ์Œ์ฃผ, ํก์—ฐ, ์•ฝ๋ฌผ ๋ณต์šฉ, ์ปคํ”ผ ์Œ์šฉ)์€ ๊ฐ๊ฐ์˜ ์š”์ค‘ ๋Œ€์‚ฌ์‚ฐ๋ฌผ ๋ฐฐ์„ค์— ์˜ํ–ฅ์„ ์ฃผ์ง€ ์•Š์•˜๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ž‘์—… ์ „ ๋ฐ ์ž‘์—… ํ›„์˜ ๋ฐฐ์„ค๋Ÿ‰์— ์ฐจ์ด๊ฐ€์žˆ์–ด ์ž‘์—… ์ข…๋ฃŒ์‹œ์˜ ์‹œ๋ฃŒ ์ฑ„์ทจ๊ฐ€ ๋…ธ์ถœ ํ‰๊ฐ€์—์ค‘์š”ํ•˜์˜€๋‹ค. ๋˜ํ•œ ์„ธ๊ฐ€์ง€ ์š”์ค‘ ๋Œ€์‚ฌ์‚ฐ๋ฌผ์ค‘ ์š”์ค‘ ๋งˆ๋‡จ์‚ฐ์€ ๊ธฐ์ค‘ ํ†จ๋ฃจ์—”๊ณผ ์ƒ๊ด€์„ฑ์ด ๋†’์•˜์œผ๋‚˜ ์š”์ค‘ ํ†จ๋ฃจ์—” ๋ฐ ์š”์ค‘ ์˜ค๋ฅดํ† -ํฌ๋ ˆ์กธ์€ 1ppm์˜ ์ € ๋†๋„๊ตฐ์—์„œ ์š”์ค‘ ๋งˆ๋‡จ์‚ฐ์„ ๋ณด์™„ํ•  ์ˆ˜ ์žˆ๋Š” ์š”์ค‘์ƒ๋ฌผํ•™์  ๋…ธ์ถœ์ง€ํ‘œ๋ผ๊ณ  ์ƒ๊ฐ๋˜๋ฉฐ ์•ž์œผ๋กœ ์ด์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๊ฐ€ ๋”์šฑ ํ•„์š”ํ•˜๋‹ค. [์˜๋ฌธ] Organic solvents, which are very necessary in many industrial fields, have various uses and are now increasingly consumed. Especially, as toluene is widely used as a substitute material for benzene, the chances of workers' occupational exposure to toluene are becoming higher than ever before. This study was performed to compare the urinary hippuric acid, toluene and o-cresol as indices for biological exposure for workers exposed to toluene in air the statistical differences of various individual characteristics, the correlations between each biological exposure index and the concentration of individual exposure to toluene in air, and the statistical differences of the indices depending on sampling time points. The results of the study are as follows; 1. Factors such as age, BMI, benzoic acid containing foods, alcohol, smoking, drug , coffee did not affect the excretion of urinary hippuric acid, urinary toluene and urinary o-cresol. 2. For urinary hippuric acid, the correlation with the individual exposure concentration to tolune in air was statistically significant (r=0.596, p<0.05) and the correlations for urinary toluence and o-cresol were r=-0.051 and r=0.037, respectively, thus the correlations were not statistically significant and low. Besides in cases lower than 10ppm, the correlation between the concentration of individual exposure to air-toluene and three biological monitoring indicies was not statistically significant. 3. Deffrence of biological exposure indecise in the begining of work and end of shift to indivisual exposure to toluene in air were statistically significant that the urinary hippuric acid, toluene, and o-cresol in end of shift were higher than begining of work. However, in cases lower than 1ppm, deffrence of the urinary toluene and o-cresol were statistically significant in the begining of work and end of shift, but urinary hippuric acid was not. We concluded that, while the individual characteristics(e.g., age, body mass index, benzoic acid containing foods, alcohol, smoking, drug, coffee) did not affect the excretion of urinary hippuric acid, toluene and o-cresol. But excretions changes through the begining of work and the end of shift have the statistical significant, so sampling time at the end of shift was vary important. Although the excretion of urinary hippuric acid showed significant correlation with the exposure to toluene in air, urinary toluene and o-cresol was recommended to be used as a subsidiary index in very low concentration of toluene in air.ope

    Case report of renal cell carcinoma in automobile manufacturing factory worker due to trichloroethylene exposure in Korea

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    BACKGROUND: The aim of this paper was report first case of renal cell carcinoma developed in a worker who worked in an automobile manufacture line which handles trichloroethylene in Korea. CASE PRESENTATION: To clarify the relationship between the onset of renal cell carcinoma in 52-years old male worker and the exposure to trichloroethylene, document studies and work environment measurement were done. Past work environment exposure data were reviewed and medical history and surgery records of the worker were also reviewed. The patient had no personal risk factor related to renal cell carcinoma except for his smoking habit of quarter a pack per day for twenty years, and since trichloroethylene was not part of measurement criteria, past work environment risk assessment data could not verify the exposure. The exposure level is deduced by analyzing material exposure level of work environments which has similar processes in data from revised research of chemical exposure standard and work environment validity assessment. Evaluation Committee of Epidemiologic Survey decided that there are relevant relationship between the exposure and the disease, though we do not have exact data during that period, most experts agree that in every factories they used trichloroethylene without any direction. CONCLUSIONS: From the relevant medical history and the results of the usage of trichloroethylene in the relevant industries, and initial discovery of renal cell carcinoma at health inspection sonogram in 2001, it can be concluded that suggests significant causal relationship between the exposure to trichloroethylene and renal cell carcinoma onset, thus reporting it to be the first domestic case declared to be occupational disease.ope

    A Descriptive Study on Violence by Customer against โ€˜Daeriโ€™ Drivers in Korea

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    Objectives: The purpose of this study was to research โ€˜Daeriโ€™ drivers who work for drunken customers as a substitute driver. This was the first study in Korea to investigate assault and verbal abuse experienced while employed as a โ€˜Daeriโ€™ driver. Methods: In this study, we conducted a survey to investigate people who work as โ€˜Daeriโ€™ drivers. The survey was performed from September 1 to 7, 2014. The participants were 166 adult men and women who work as full-time โ€˜Daeriโ€™ drivers. Results: Participants who experienced physical violence and assault from the customers to the point of disturbing safe driving in a year were 36.1% of total respondents. People who experienced verbal abuse to the point of disturbing safe driving in a year totaled 80.4% of respondents. In addition, there were also qualitative research results. Conclusions: Acts that impede safe driving are a danger to both passengers and drivers. By protecting the safety of โ€˜Daeriโ€™ drivers, we will be able to protect the safety of citizens. Therefore, it is necessary to make an effort to protect โ€˜Daeriโ€™ drivers from customer violence. Furthermore, it is also necessary to research policy to emplace a legal system that can protect โ€˜Daeri' drivers.ope

    Design of High-Speed Power-Efficient Optical Transmitter With Push-Pull Driving Technique

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :๊ณต๊ณผ๋Œ€ํ•™ ์ „๊ธฐยท์ •๋ณด๊ณตํ•™๋ถ€,2019. 8. ์ •๋•๊ท .Data usage dramatically increases by year due to Internet of Things (IoT) and 5G networks. Even though required data keeps going up, backbone network of wireline such as data center has to transmit and receive data without or less errors. However, electrical wireline interface is difficult to process data for the data surge due to skin effects and dielectric loss in the copper channel at high frequency. Therefore, the significance of high-speed and power-efficient optical links utilizing optical fibers keeps increasing owing to its low loss even delivering data for the long distance. Following this trends, this thesis is focused on transmitter side of optical links. Push-pull driving technique, which is suitable for high-speed and power-efficient network, is proposed and utilized. Based on this technique, 32Gb/s NRZ driver with large output swing, which drives Mach-Zehnder modulator (MZM) or electro-absorption modulator (EAM), has been implemented with the power efficiency of 6.28pJ/b in 65nm CMOS process. It achieves an active area of 0.086mm2. Also, 4-channel HDMI active optical cable (AOC) transmitter chips achieving 12Gb/s per channel is fabricated in 180nm CMOS process using push-pull driving scheme with the total area of 1.62mm2. In the subsequent section, optical transmitters with clocking architecture have been proposed. Vertical-cavity surface-emitting laser (VCSEL), which has low cost for fabrication and high ability for integration, are utilized for clocked optical transmitters. Both forwarded and embedded clocking architectures have been employed for the future optical interface between application-specific integrated circuit (ASIC) and optical links. As a result, 56Gb/s VCSEL PAM-4 transmitter with forwarded clocking and 64Gb/s VCSEL PAM-4 transmitter with embedded clocking have been implemented in 65nm CMOS process. Figure of merits for power efficiency are 2.12pJ/b and 2.69pJ/b, respectively. Both chips occupy the area of 0.133mm2 and 0.278mm2, respectively.๋‹ค๊ฐ€์˜ค๋Š” IoT์™€ 5G ๋ฌด์„ ๋ง์œผ๋กœ ์ธํ•ด ํ•ด๋งˆ๋‹ค ๋ฐ์ดํ„ฐ์˜ ์‚ฌ์šฉ๋Ÿ‰์€ ๊ธ‰๊ฒฉํžˆ ์ฆ๊ฐ€ํ•˜๊ณ  ์žˆ๋‹ค. ์š”๊ตฌ๋˜๋Š” ๋ฐ์ดํ„ฐ์˜ ์–‘์ด ๊ณ„์† ์ฆ๊ฐ€๋˜๋Š” ๊ฐ€์šด๋ฐ, ์œ ์„  ๋ง์—์„œ๋Š” ํ•œ์ •๋œ ์ž์›์œผ๋กœ ์—๋Ÿฌ ์—†์ด ํ˜น์€ ์ ์€ ์—๋Ÿฌ๋กœ ์ „์†ก์„ ํ•ด์•ผ ํ•œ๋‹ค. ํ•˜์ง€๋งŒ, ๊ธฐ์กด์˜ ์œ ์„  ๋„คํŠธ์›Œํฌ๋กœ๋Š” ๊ณ ์† ์ฃผํŒŒ์ˆ˜์—์„œ์˜ ํ‘œํ”ผํšจ๊ณผ์™€ ์œ ์ „์ฒด์˜ ์†์‹ค๋กœ ์ธํ•ด ๊ตฌ๋ฆฌ ์„ ์—์„œ ๋ฐ์ดํ„ฐ๋ฅผ ์ฒ˜๋ฆฌํ•˜๋Š” ๊ฒƒ์€ ์‰ฝ์ง€ ์•Š๋‹ค. ๋”ฐ๋ผ์„œ, ์žฅ๊ฑฐ๋ฆฌ๋ฅผ ์†์‹ค ์—†์ด ๊ณ ์†์˜ ๋ฐ์ดํ„ฐ๋ฅผ ๋ณด๋‚ผ ์ˆ˜ ์žˆ๋Š” ๊ด‘์„ฌ์œ ๋ฅผ ํ™œ์šฉ์˜ ์ค‘์š”ํ•จ์€ ์ปค์ง€๊ณ  ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ํ๋ฆ„์„ ๋”ฐ๋ฅด๋ฉฐ, ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ๊ด‘ํ†ต์‹ ์˜ ์†ก์‹ ๋ถ€์— ์ดˆ์ ์„ ๋งž์ถ”์—ˆ๋‹ค. ๊ณ ์† ์ €์ „๋ ฅ์— ์ ํ•ฉํ•œ ํ‘ธ์‰ฌ-ํ’€ ๊ตฌ๋™ ๊ธฐ์ˆ ์ด ์ œ์•ˆ๋˜๊ณ  ์‚ฌ์šฉ๋˜์—ˆ๋‹ค. ํ•ด๋‹น ๊ธฐ์ˆ ์„ ๊ธฐ๋ฐ˜์œผ๋กœ ํฐ ์Šค์œ™์„ ๊ฐ€์ง€๋ฉฐ 6.28pJ/b์˜ ํšจ์œจ์„ฑ์„ ๊ฐ€์ง„ 32Gb/s ๋งˆํฌ-์  ๋” ๊ด‘ ๋ณ€์กฐ๊ธฐ/์ „๊ณ„-ํก์ˆ˜ ๊ด‘ ๋ณ€์กฐ๊ธฐ๊ฐ€ 65๋‚˜๋…ธ CMOS ๊ณต์ •์œผ๋กœ ์„ค๊ณ„๋˜์—ˆ๋‹ค. ํ•ด๋‹น ์นฉ์€ 0.086mm2์˜ ์ž‘์šฉ๋ฉด์ ์„ ์ง€๋‹ˆ๊ณ  ์žˆ๋‹ค. ๋˜ํ•œ, ์ฑ„๋„๋‹น 12Gb/s์˜ ์†๋„๋ฅผ ์ง€๋‹Œ 4-์ฑ„๋„ HDMI AOC ๋“œ๋ผ์ด๋ฒ„ ์—ญ์‹œ 180๋‚˜๋…ธ ๊ณต์ •์„ ์ด์šฉํ•˜์—ฌ ์„ค๊ณ„ํ•˜์˜€๋‹ค. ๋งˆ์ฐฌ๊ฐ€์ง€๋กœ ํ‘ธ์‰ฌ-ํ’€ ๊ตฌ๋™ ๊ธฐ์ˆ ์„ ์‚ฌ์šฉํ–ˆ์œผ๋ฉฐ ์ด ๋ฉด์ ์€ 1.62mm2์˜€๋‹ค. ํ›„์† ์„น์…˜์—์„œ๋Š” ํด๋ฝ์„ ๊ฐ€์ง„ ๊ด‘ ์†ก์‹ ๊ธฐ๊ฐ€ ์ œ์•ˆ๋˜์—ˆ๋‹ค. ๊ฐ’์‹ธ๊ณ  ์ง‘์ ๋„๊ฐ€ ๋†’์€ ๋ฉด๋ฐœ๊ด‘ ๋ ˆ์ด์ ธ๊ฐ€ ๋ณธ ์„น์…˜์—์„œ ์ด์šฉ๋˜์—ˆ๋‹ค. ํด๋ฝ ์ „์†กํ˜•, ํด๋ฝ ๋‚ด์žฅํ˜• ์†ก์‹ ๊ธฐ๊ฐ€ ์ฐจ์„ธ๋Œ€ ๊ด‘ํ†ต์‹ ์„ ์œ„ํ•ด ์ ์šฉ๋˜์—ˆ๋‹ค. ๊ทธ ๊ฒฐ๊ณผ 56Gb/s 4-๋ ˆ๋ฒจ ์ง„ํญ๋ณ€์กฐ๊ฐ€ ๊ฐ€๋Šฅํ•œ ๋ฉด๋ฐœ๊ด‘ ๋ ˆ์ด์ €๋ฅผ ๊ตฌ๋™ํ•˜๋Š” ํด๋ฝ ์ „์†กํ˜• ๊ด‘ ์†ก์‹ ๊ธฐ์™€ 64Gb/s 4-๋ ˆ๋ฒจ ์ง„ํญ๋ณ€์กฐ๊ฐ€ ๊ฐ€๋Šฅํ•œ ๋ฉด๋ฐœ๊ด‘ ๋ ˆ์ด์ €๋ฅผ ๊ตฌ๋™ํ•˜๋Š” ํด๋ฝ ๋‚ด์žฅํ˜• ๊ด‘ ์†ก์‹ ๊ธฐ๊ฐ€ ์„ค๊ณ„๋˜์—ˆ๋‹ค. ์ „๋ ฅํšจ์œจ์„ฑ์€ ๊ฐ๊ฐ 2.12pJ/b์™€ 2.69pJ/b ์ด๋ฉฐ 0.133mm2์™€ 0.278mm2์˜ ์ž‘์šฉ๋ฉด์ ์„ ๊ฐ–๊ณ  ์žˆ๋‹ค. ๋‹ค๊ฐ€์˜ค๋Š” IoT์™€ 5G ๋ฌด์„ ๋ง์œผ๋กœ ์ธํ•ด ํ•ด๋งˆ๋‹ค ๋ฐ์ดํ„ฐ์˜ ์‚ฌ์šฉ๋Ÿ‰์€ ๊ธ‰๊ฒฉํžˆ ์ฆ๊ฐ€ํ•˜๊ณ  ์žˆ๋‹ค. ์š”๊ตฌ๋˜๋Š” ๋ฐ์ดํ„ฐ์˜ ์–‘์ด ๊ณ„์† ์ฆ๊ฐ€๋˜๋Š” ๊ฐ€์šด๋ฐ, ์œ ์„  ๋ง์—์„œ๋Š” ํ•œ์ •๋œ ์ž์›์œผ๋กœ ์—๋Ÿฌ ์—†์ด ํ˜น์€ ์ ์€ ์—๋Ÿฌ๋กœ ์ „์†ก์„ ํ•ด์•ผ ํ•œ๋‹ค. ํ•˜์ง€๋งŒ, ๊ธฐ์กด์˜ ์œ ์„  ๋„คํŠธ์›Œํฌ๋กœ๋Š” ๊ณ ์† ์ฃผํŒŒ์ˆ˜์—์„œ์˜ ํ‘œํ”ผํšจ๊ณผ์™€ ์œ ์ „์ฒด์˜ ์†์‹ค๋กœ ์ธํ•ด ๊ตฌ๋ฆฌ ์„ ์—์„œ ๋ฐ์ดํ„ฐ๋ฅผ ์ฒ˜๋ฆฌํ•˜๋Š” ๊ฒƒ์€ ์‰ฝ์ง€ ์•Š๋‹ค. ๋”ฐ๋ผ์„œ, ์žฅ๊ฑฐ๋ฆฌ๋ฅผ ์†์‹ค ์—†์ด ๊ณ ์†์˜ ๋ฐ์ดํ„ฐ๋ฅผ ๋ณด๋‚ผ ์ˆ˜ ์žˆ๋Š” ๊ด‘์„ฌ์œ ๋ฅผ ํ™œ์šฉ์˜ ์ค‘์š”ํ•จ์€ ์ปค์ง€๊ณ  ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ํ๋ฆ„์„ ๋”ฐ๋ฅด๋ฉฐ, ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ๊ด‘ํ†ต์‹ ์˜ ์†ก์‹ ๋ถ€์— ์ดˆ์ ์„ ๋งž์ถ”์—ˆ๋‹ค. ๊ณ ์† ์ €์ „๋ ฅ์— ์ ํ•ฉํ•œ ํ‘ธ์‰ฌ-ํ’€ ๊ตฌ๋™ ๊ธฐ์ˆ ์ด ์ œ์•ˆ๋˜๊ณ  ์‚ฌ์šฉ๋˜์—ˆ๋‹ค. ํ•ด๋‹น ๊ธฐ์ˆ ์„ ๊ธฐ๋ฐ˜์œผ๋กœ ํฐ ์Šค์œ™์„ ๊ฐ€์ง€๋ฉฐ 6.28pJ/b์˜ ํšจ์œจ์„ฑ์„ ๊ฐ€์ง„ 32Gb/s ๋งˆํฌ-์  ๋” ๊ด‘ ๋ณ€์กฐ๊ธฐ/์ „๊ณ„-ํก์ˆ˜ ๊ด‘ ๋ณ€์กฐ๊ธฐ๊ฐ€ 65๋‚˜๋…ธ CMOS ๊ณต์ •์œผ๋กœ ์„ค๊ณ„๋˜์—ˆ๋‹ค. ํ•ด๋‹น ์นฉ์€ 0.086mm2์˜ ์ž‘์šฉ๋ฉด์ ์„ ์ง€๋‹ˆ๊ณ  ์žˆ๋‹ค. ๋˜ํ•œ, ์ฑ„๋„๋‹น 12Gb/s์˜ ์†๋„๋ฅผ ์ง€๋‹Œ 4-์ฑ„๋„ HDMI AOC ๋“œ๋ผ์ด๋ฒ„ ์—ญ์‹œ 180๋‚˜๋…ธ ๊ณต์ •์„ ์ด์šฉํ•˜์—ฌ ์„ค๊ณ„ํ•˜์˜€๋‹ค. ๋งˆ์ฐฌ๊ฐ€์ง€๋กœ ํ‘ธ์‰ฌ-ํ’€ ๊ตฌ๋™ ๊ธฐ์ˆ ์„ ์‚ฌ์šฉํ–ˆ์œผ๋ฉฐ ์ด ๋ฉด์ ์€ 1.62mm2์˜€๋‹ค. ํ›„์† ์„น์…˜์—์„œ๋Š” ํด๋ฝ์„ ๊ฐ€์ง„ ๊ด‘ ์†ก์‹ ๊ธฐ๊ฐ€ ์ œ์•ˆ๋˜์—ˆ๋‹ค. ๊ฐ’์‹ธ๊ณ  ์ง‘์ ๋„๊ฐ€ ๋†’์€ ๋ฉด๋ฐœ๊ด‘ ๋ ˆ์ด์ ธ๊ฐ€ ๋ณธ ์„น์…˜์—์„œ ์ด์šฉ๋˜์—ˆ๋‹ค. ํด๋ฝ ์ „์†กํ˜•, ํด๋ฝ ๋‚ด์žฅํ˜• ์†ก์‹ ๊ธฐ๊ฐ€ ์ฐจ์„ธ๋Œ€ ๊ด‘ํ†ต์‹ ์„ ์œ„ํ•ด ์ ์šฉ๋˜์—ˆ๋‹ค. ๊ทธ ๊ฒฐ๊ณผ 56Gb/s 4-๋ ˆ๋ฒจ ์ง„ํญ๋ณ€์กฐ๊ฐ€ ๊ฐ€๋Šฅํ•œ ๋ฉด๋ฐœ๊ด‘ ๋ ˆ์ด์ €๋ฅผ ๊ตฌ๋™ํ•˜๋Š” ํด๋ฝ ์ „์†กํ˜• ๊ด‘ ์†ก์‹ ๊ธฐ์™€ 64Gb/s 4-๋ ˆ๋ฒจ ์ง„ํญ๋ณ€์กฐ๊ฐ€ ๊ฐ€๋Šฅํ•œ ๋ฉด๋ฐœ๊ด‘ ๋ ˆ์ด์ €๋ฅผ ๊ตฌ๋™ํ•˜๋Š” ํด๋ฝ ๋‚ด์žฅํ˜• ๊ด‘ ์†ก์‹ ๊ธฐ๊ฐ€ ์„ค๊ณ„๋˜์—ˆ๋‹ค. ์ „๋ ฅํšจ์œจ์„ฑ์€ ๊ฐ๊ฐ 2.12pJ/b์™€ 2.69pJ/b ์ด๋ฉฐ 0.133mm2์™€ 0.278mm2์˜ ์ž‘์šฉ๋ฉด์ ์„ ๊ฐ–๊ณ  ์žˆ๋‹ค.Chapter 1 Introduction 1 1.1. Motivation 1 1.2. Thesis Organization 3 Chapter 2 Background of Optical Link 4 2.1. Overview 4 2.2. Basic Principles of Optical Transmission 7 2.3. Basis of Data Center 13 2.4. Design Challenges of Optical Link in Data Center 16 2.4.1. Required Bandwidth of the Data Center Interconnects 16 2.4.2. Power Budget of the Data Center 17 2.4.3. Future Data Center 18 2.5. Basis of Optical Components for Transmitter 20 2.5.1. Modulator 20 2.5.2. VCSEL 22 Chapter 3 High-Speed Optical Driver Implementations With Power-Efficient Push-Pull Driving Scheme 24 3.1. Overview 24 3.2. Push-Pull Technique in Current-Mode Driver 26 3.3. Mach-Zehnder/Electro-Absorption Modulator Driver 29 3.3.1. Previous Works 30 3.3.2. Proposed MZM/EAM Driver 31 3.3.3. Measurement Results 38 3.4. HDMI 4-Channel Driver for AOCs 45 3.4.1 Previous Works 46 3.4.2 Proposed HDMI AOC 49 3.4.3 Measurement Results 56 Chapter 4 High-Speed Clocked Optical Transmitter Implementations With Power-Efficient Techniques 64 4.1 Overview 64 4.2 System Comparison of High-Speed Transmitter 66 4.3 Proposed Clocked Optical Transmitter 70 4.3.1 Previous Works 70 4.3.2 Proposed Forwarded Clocked Optical Transmitter 71 4.3.3 Measurement Results 73 4.3.4 Proposed Embedded Clocked Transmitter 78 4.3.5 Measurement Results 85 Chapter 5 Conclusions 93 Appendix A 95 Bibliography 97 ์ดˆ๋ก 104Docto

    The correlation between salivary and serum cortisol concentrations in fire fighters

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    This studies were measure the cortisol from salivary and serum of fire-fighters, who are relatively always exposed to highly dangerous and unsafe working conditions in which they should bring a fire under control or rescue people in danger situations et cetera, therefore both physically and mentally stressed-out, and comparatively analyzed the correlation between the two cortisol levels. The salivary and serum samples of 133 active fire fighters. These were collected at 8:30am, when leaving for work. The salivary cortisol analysis was carried out with enzyme immunoassay, and the serum cortisol analysis utilized chemiluminescence immunoassay. On the morning of testing, the salivary cortisol concentration was 1.92ยฑ0.73(0.51-5.85)ใŽ/ใŽ—, while the cortisol concentration of serum was 14.93ยฑ4.23(4.45~25.85)ใŽ/ใŽ—. Results were grouped according to ages, smoking, drinking habit, and duly type. Higher smoking and drinking produced a statistically significant increase in salivary and serum cortisol concentration. Cortisol concentrations according to type or duty followed by emergency rescue, fire suppression, rescue, miscellaneous. There is a statistically significant correlation between salivary and serum cortisol concentrations. The results show that a significant correlation between salivary and serum cortisol concentrations exists in fire fighters. It is judged that noninvasive methods salivary cortisol could be used in place of serum cortisol to measure cortisol levels when considering factors such as convenience of sample collection and cost.ope

    Autonomic dysfunction of overweight combined with low muscle mass

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    OBJECTIVE: To examine the relationship between overweight combined with low muscle mass and the cardiac autonomic nervous system using heart rate variability (HRV) in healthy workers. METHODS: A total of 1,150 workers were included, with a mean age of 43.55 ยฑ 11.45 years. The subjects were classified as low muscle mass if their appendicular skeletal muscle mass was below the 50th percentile of the study sample. Similarly, subjects were classified as overweight if their body mass index was above 25 kg/m(2). Electrocardiography recordings were obtained for 5 min, and the time-domain and frequency-domain indices of HRV were analyzed. RESULTS: Compared with the high muscle mass and non-overweight (HMM) group, the low-frequency power and the standard deviation of normal-to-normal intervals were significantly decreased in both the overweight and high muscle mass (OHMM) group and the overweight and low muscle mass (OLMM) group. The significantly decreased high-frequency (HF) power and square root of the mean squared differences of successive differences, which reflects efferent parasympathetic activity, was indicative of reduced parasympathetic modulation in the OHMM and OLMM groups. In addition, the OLMM group had a lower HF power than did the OHMM group. CONCLUSIONS: This study suggests that HRV is reduced in overweight combined with low muscle mass group than overweight and HMM group.ope
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