89 research outputs found

    BRICS and Neighbors

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    ν•™μœ„λ…Όλ¬Έ(석사) -- μ„œμšΈλŒ€ν•™κ΅λŒ€ν•™μ› : κ΅­μ œλŒ€ν•™μ› κ΅­μ œν•™κ³Ό(κ΅­μ œν˜‘λ ₯전곡), 2021.8. κΉ€νƒœκ· .The recognition of South Africa’s role on the African continent is decreasing with its stagnating economic status, along with geopolitical issues. While joining the forum of BRICS in 2010 and serving its third two-year term in the UNSC allowed South Africa to take up the symbolic role of the representative of Africa. However, the rising recognition of China in Africa and the fast-growing regional rival Nigeria challenges South Africa’s quest for hegemony on the continent. Furthermore, South Africa’s influence in the nearest countries, such as Namibia and Botswana, has weakened in areas of trade as well as foreign direct investment. This study analyzes South Africa’s status as the representative of the African continent and seeks to explore the question of whether it still holds the position of a hegemon, or at least as a continental representative, by examining South Africa’s role in the BRICS, UNSC, and the AU in terms of both economic and political issues. The research reveals that South Africa tries to gain back its reputation on the global scale after their successful transition to democracy by precisely structured foreign policies of their presidents. However, they were neither fully successful in becoming recognized as a global leader of the continent, nor were they accepted by the states within the continent due to their fluctuating economic status, hostile neighbors, and continental rival. Furthermore, South Africa was the biggest trade partner within the SADC but with the rising recognition of China and their investment towards overall Africa, South Africa could not position itself as the hegemon of the continent.아프리카 λŒ€λ₯™μ—μ„œ λ‚¨μ•„ν”„λ¦¬μΉ΄κ³΅ν™”κ΅­μ˜ 역할이 지정학적 문제 및 침체된 경제적 μ§€μœ„λ‘œ 인해 μΆ•μ†Œλ˜κ³  μžˆλ‹€. 2010λ…„, 남아프리카곡화ꡭ은 BRICS ν¬λŸΌμ— κ°€μž…ν•˜κ³  3번의 μ•ˆλ³΄λ¦¬ μž„κΈ°λ₯Ό μˆ˜ν–‰ν•˜λ©΄μ„œ 아프리카λ₯Ό λŒ€ν‘œν•˜λŠ” 상징적 역할을 λ§‘μ•˜λ‹€. κ·ΈλŸ¬λ‚˜ μ•„ν”„λ¦¬μΉ΄μ—μ„œ μ€‘κ΅­μ˜ 영ν–₯λ ₯이 높아지고 λŒ€λ₯™ λ‚΄ 경쟁자이며 λΉ λ₯΄κ²Œ μ„±μž₯ν•˜κ³ μžˆλŠ” λ‚˜μ΄μ§€λ¦¬μ•„λ‘œ μΈν•˜μ—¬ 남아프리카곡화ꡭ은 λŒ€λ₯™ νŒ¨κΆŒκ΅­μœΌλ‘œμ„œμ˜ 역할을 μ΄ν–‰ν•˜μ§€ λͺ»ν•˜κ³ μžˆλ‹€. λ‚˜μ•„κ°€ λ‚˜λ―ΈλΉ„μ•„, λ³΄μΈ μ™€λ‚˜ λ“± μΈμ ‘κ΅­μ—μ„œ λ‚¨μ•„ν”„λ¦¬μΉ΄κ³΅ν™”κ΅­μ˜ 영ν–₯λ ₯은 외ꡭ인 μ§μ ‘νˆ¬μžλŠ” λ¬Όλ‘  ꡐ역 λΆ„μ•Όμ—μ„œλ„ μ•½ν•΄μ‘Œλ‹€. λ³Έ μ—°κ΅¬λŠ” 남아프리카곡화ꡭ이 아프리카 λŒ€λ₯™ λŒ€ν‘œλ‘œμ„œμ˜ μ§€μœ„λ₯Ό λΆ„μ„ν•˜κ³ , κ²½μ œΒ·μ •μΉ˜μ  λ¬Έμ œμ™€ BRICS, μ•ˆλ³΄λ¦¬, AUμ—μ„œ λ‚¨μ•„ν”„λ¦¬μΉ΄κ³΅ν™”κ΅­μ˜ 역할을 κ²€ν† ν•΄ 패ꢌꡭ μ§€μœ„λ₯Ό μ—¬μ „νžˆ μœ μ§€ν•˜κ³  μžˆλŠ”μ§€μ— λŒ€ν•œ 문제λ₯Ό νƒκ΅¬ν•˜κ³ μž ν•œλ‹€. 남아프리카곡화ꡭ은 성곡적인 민주주의 μ‚¬νšŒλ₯Ό μ΄λ£©ν•œ ν›„ λŒ€ν†΅λ Ήλ“€μ˜ μ •λ°€ν•œ 외ꡐ정책을 ꡬ쑰화 ν•˜μ˜€λ‹€. 이것은 세계적인 κ΅­κ°€λ‘œ μ§„μž…ν•¨κ³Ό λ™μ‹œμ— μžƒμ€ λͺ…성을 되찾기 μœ„ν•œ 정책을 펼 κ²ƒμ΄λΌλŠ” 연ꡬ κ²°κ³Όκ°€ λ‚˜μ™”λ‹€. κ·ΈλŸ¬λ‚˜ 이듀은 λŒ€λ₯™μ˜ κΈ€λ‘œλ²Œ λ¦¬λ”λ‘œ μΈμ •λ°›λŠ”λ° μ„±κ³΅ν•˜μ§€ λͺ»ν–ˆλ‹€. κ·Έ μ΄μœ λŠ” μ•ˆμ •μ μ΄μ§€ λͺ»ν•œ 경제적 변동, μ λŒ€μ  이웃, λŒ€λ₯™μ˜ 라이벌둜 인해 λŒ€λ₯™ λ‚΄ κ΅­κ°€λ“€μ—κ²Œ λ¦¬λ”λ‘œμ„œ 인정받지 λͺ»ν–ˆκΈ° λ•Œλ¬Έμ΄λ‹€. 무엇보닀 남아프리카곡화ꡭ은 SADC λ‚΄ μ΅œλŒ€ κ΅μ—­κ΅­μ΄μ—ˆμ§€λ§Œ 쀑ꡭ이 아프리카 전체에 λŒ€ν•œ 투자λ₯Ό μ‹œμž‘ν•˜λ©΄μ„œ λŒ€λ₯™μ˜ 패ꢌꡭ으둜 μžλ¦¬λ§€κΉ€ν•  수 μ—†μ—ˆλ‹€.1. Introduction 1 1.1 Argument overview 1 1.2 Historical Background and Influence of the Cold War 2 1.3 Literature review 8 1.4 Research Question and Outline of Thesis 11 2. Research Design 12 2.1 Analytical Framework 12 2.2 Methodology 14 3. Status within BRICS 15 3.1 Formation of BRICS 16 3.2 South Africa's decreasing role on the African Continent 20 3.3 China's Rising Recognition in Africa 33 4. Case Study 47 4.1 Namibia 50 4.2 Botswana 58 5. Thesis Findings 63 5.1 Conclusion 63 5.2 Limitations and further research reference 66 Reference 68석

    Correlation Network Analysis for Deciphering Rust Disease-Triggered Metabolism Using Mass Spectrometry-based Metabolomics

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    ν•™μœ„λ…Όλ¬Έ (박사)-- μ„œμšΈλŒ€ν•™κ΅ λŒ€ν•™μ› : μ•½ν•™κ³Ό, 2017. 2. κΆŒμ„±μ›.ν˜„μž¬κΉŒμ§€μ˜ 감염성 μ§ˆλ³‘ μ—°κ΅¬λŠ”, 병원성 균의 μΉ¨μž… 방법 및 균이 μƒμ„±ν•˜λŠ” μˆ™μ£Όμ— λŒ€ν•œ 자극 물질의 생성에 λŒ€ν•΄ 주둜 μ§‘μ€‘λ˜μ–΄ μžˆλ‹€. κ·ΈλŸ¬λ‚˜, 균의 μΉ¨μž…μ— μ˜ν•œ μˆ™μ£Όμ˜ κ³Όλ―Όλ°˜μ‘μœΌλ‘œλΆ€ν„° μ§ˆλ³‘μ˜ 증상과 같은 병원성 ν‘œν˜„ν˜• λ³€ν™”κ°€ μœ λž˜ν•  수 μžˆλ‹€. 이λ₯Ό 증λͺ…ν•˜κΈ° μœ„ν•˜μ—¬, μ§ˆλŸ‰λΆ„μ„κΈ° 기반 λŒ€μ‚¬μ²΄ν•™μ„ μ μš©ν•˜μ˜€μœΌλ©°, 상관관계 λ„€νŠΈμ›Œν¬ 뢄석을 μ΄μš©ν•˜μ—¬ λŒ€μ‚¬κΈ°μ „ κ°„μ˜ κΈ΄λ°€ν•œ 관계λ₯Ό μΆ”μ ν•˜μ˜€λ‹€. λŒ€μ‚¬κΈ°μ „-병원성 μ—°κ΄€μ„± 연ꡬλ₯Ό μœ„ν•΄ μˆ™μ£ΌμΈ 3μ’…μ˜ μž₯λ―Έκ³Ό 식물과 이듀에 균체λ₯Ό ν˜•μ„±ν•˜μ—¬ 이듀을 λ©”λ§ˆλ₯΄κ²Œ ν•˜λŠ” Gymnosporangium asiaticum에 μ˜ν•œ λŒ€μ‚¬κΈ°μ „ λ³€ν™”λ₯Ό κ΄€μ°°ν•˜μ˜€λ‹€. μ§ˆλŸ‰λΆ„μ„κΈ°λ₯Ό μ‚¬μš©ν•˜μ—¬ λ‹€μˆ˜μ˜ Primary metabolitesλ₯Ό κ²€μΆœν•˜μ˜€μœΌλ©°, λ‹€λ³€λŸ‰ν†΅κ³„λΆ„μ„μ„ 톡해 얻은 μ§€ν‘œλ¬Όμ§ˆλ“€μ„ 기반으둜 ν•˜μ—¬ Pathway enrichmentλ₯Ό μ‹œν–‰ν•˜μ˜€λ‹€. μ΄λ‘œλΆ€ν„° 얻은 상관성 높은 λŒ€μ‚¬κΈ°μ „ μ‚¬μ΄μ˜ 관계λ₯Ό μΆ”μ ν•˜μ—¬, Aminosugar and nucleotide sugar metabolism 의 결핍에 κ΄€μ—¬λ˜μ–΄ μžˆλŠ” λŒ€μ‚¬κΈ°μ „μ„ λ°œκ²¬ν•˜μ˜€λ‹€. 이 λŒ€μ‚¬κΈ°μ „ μ•ˆμ—μ„œ 주둜 λ‹Ήμ•Œμ½”μ˜¬μ˜ 좕적이 ANM의 Supply metabolitesλ₯Ό κ²°ν•μ‹œν‚¨λ‹€λŠ” 것을 PPMCC에 κΈ°λ°˜ν•œ 상관관계 λ„€νŠΈμ›Œν¬ λΆ„μ„μœΌλ‘œλΆ€ν„° κ²€μ¦ν•˜μ˜€μœΌλ©°, κ΅ν˜Έμž‘μš©μ— λŒ€ν•œ κ΄€μ°°λ‘œμ¨ Supply metabolites의 결핍과 λ‹Ήμ•Œμ½”μ˜¬μ˜ 좕적이 연관이 λ˜μ–΄ μžˆμŒμ„ κ²°λ‘ μ§€μ—ˆλ‹€. μ΄λŸ¬ν•œ μˆ™μ£Ό μ€‘μ‹¬μ˜ λŒ€μ‚¬ λ°˜μ‘μ„ 상관관계 λ„€νŠΈμ›Œν¬ λΆ„μ„μœΌλ‘œ κ΄€μ°°ν•˜λŠ” λ°©λ²•μœΌλ‘œμ¨ λŒ€μ‚¬κΈ°μ „μ˜ λ³€ν™” 및 그둜 μΈν•œ 결핍이 νŠΉμ • μ§ˆλ³‘μ›μ΄ 될 수 μžˆμŒμ„ λ³΄μ˜€μœΌλ©°, λŒ€μ‚¬μ²΄ν•™ 연ꡬ에 μ μ ˆν•œ λ„κ΅¬λ‘œ μ‚¬μš©κ°€λŠ₯함을 ν™•μΈν•˜μ˜€λ‹€.I. μ„œλ‘  1 II. 재료 및 방법 6 III. κ²°κ³Ό 및 κ³ μ°° 9 IV. κ²°λ‘  26 V. μ°Έκ³ λ¬Έν—Œ 27 VI. 뢀둝 30 1. GC-MS spectrum of 34 metabolites 31 2. GC-MS 기반 λŒ€μ‚¬μ²΄ν•™ 39 3. MZmine 57 4. Multivariate statistical analysis 62 Abstract 73Docto

    ν™•λ₯ μ  지배 검정방법을 ν™œμš©ν•œ κ΅­μ œμ›μœ κ°€κ²©κ°„ μˆ˜μ΅μ„± 비ꡐ뢄석

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    ν•™μœ„λ…Όλ¬Έ (석사)-- μ„œμšΈλŒ€ν•™κ΅ λŒ€ν•™μ› : κ³΅κ³ΌλŒ€ν•™ μ—λ„ˆμ§€μ‹œμŠ€ν…œκ³΅ν•™λΆ€, 2019. 2. ν—ˆμ€λ…•.λ³Έ μ—°κ΅¬μ˜ λͺ©μ μ€ WTI 유, Brent 유, Dubai 유 κ°€κ²©μ˜ 수읡 뢄포 κ°„ 관계, μ›μœ μ˜ μ„ λ¬Όμƒν’ˆκ³Ό ν˜„λ¬Όμƒν’ˆ κ°€κ²©μ˜ μˆ˜μ΅λΆ„ν¬ κ°„ 관계, λ„€ μ’…λ₯˜μ˜ μ„μœ μ œν’ˆ (휘발유, λ‚œλ°©μœ , 경유, 제트 μ—°λ£Œ) κ°€κ²©μ˜ μˆ˜μ΅λΆ„ν¬ κ°„ 관계λ₯Ό ν™•λ₯ μ  지배관계 접근법 (Stochastic Dominance approach)을 μ μš©ν•˜μ—¬ λΆ„μ„ν•˜λŠ” 것이닀. ν™•λ₯ μ  지배 κ΄€κ³„λž€, 두 ν™•λ₯  λ³€μˆ˜λ₯Ό λΉ„κ΅ν•˜κ³  μœ„κ³„λ₯Ό μ •ν•˜λŠ” 데 μžˆμ–΄ 기쀀을 μ œμ‹œν•˜λŠ” 이둠이닀. ν™•λ₯ μ  지배 (Stochastic Dominance) κ°œλ…μ„ μ μš©ν•œ 수읡 뢄포 비ꡐ 방법은 ν™•λ₯ μ  지배 기쀀이 효용 ν•¨μˆ˜μ— λŒ€ν•œ μ΅œμ†Œν•œμ˜ κ°€μ •λ§Œμ„ ν•„μš”λ‘œ ν•˜κΈ° λ•Œλ¬Έμ— ν™•λ₯ λ³€μˆ˜λ“€ κ°„μ˜ μˆœμ„œμ— κ΄€ν•œ λͺ…ν™•ν•œ 해석을 ν•  수 μžˆλ‹€λŠ” μž₯점을 μ§€λ‹Œλ‹€. μ΄λŸ¬ν•œ 이유둜, 금육 κ²½μ œν•™μ—μ„œλŠ” λ‹€μ–‘ν•œ 투자 λŒ€μƒμ˜ λΆˆν™•μ‹€μ„±μ„ 비ꡐ함에 μžˆμ–΄μ„œ ν™•λ₯ μ  지배 관계가 μ€‘μš”ν•œ κ°œλ…μœΌλ‘œ μ‚¬μš©λœλ‹€. μš°μ„ , λ³Έ μ—°κ΅¬λŠ” ν™•λ₯  지배 κ°œλ…μ„ μ μš©ν•˜μ—¬ WTI 유, Brent 유, Dubai 유의 수읡 뢄포 κ°„ 관계λ₯Ό λΆ„μ„ν•˜κΈ° μœ„ν•΄ 1988λ…„ 12μ›”λΆ€ν„° 2018λ…„ 11μ›”κΉŒμ§€μ˜ μ›”κ°„ ν˜„λ¬Ό 가격 자료λ₯Ό μ‚¬μš©ν•˜μ˜€λ‹€. 뢄석 κ²°κ³Ό, 전체 뢄석 κΈ°κ°„ λ™μ•ˆ WTI 유, Dubai 유의 수읡 뢄포가 Brent 유의 수읡 뢄포λ₯Ό 2μ°¨ ν™•λ₯ μ§€λ°°ν•˜λŠ” κ²ƒμœΌλ‘œ λ‚˜νƒ€λ‚¬λ‹€. 2008λ…„ κΈˆμœ΅μœ„κΈ° 이후 κΈ°κ°„μ—λŠ” WTI 유, Brent 유, Dubai 유 κ°€κ²©μ˜ 수읡 뢄포 κ°„ μ–΄λ– ν•œ ν™•λ₯  지배 관계도 μ‘΄μž¬ν•˜μ§€ μ•Šμ•˜λ‹€. λ‘λ²ˆμ§Έλ‘œ, λ³Έ μ—°κ΅¬λŠ” 1996λ…„ 2μ›”λΆ€ν„° 2018λ…„ 11μ›”κΉŒμ§€μ˜ μ›”κ°„ 가격 자료λ₯Ό μ‚¬μš©ν•˜μ—¬ μ„μœ μ œν’ˆ κ°€κ²©μ˜ 수읡 뢄포 κ°„ 관계λ₯Ό λΆ„μ„ν•˜μ˜€λ‹€. 뢄석 κ²°κ³Ό, 제트 μ—°λ£Œ, λ‚œλ°©μœ μ˜ 수읡 λΆ„ν¬λŠ” 휘발유의 μˆ˜μ΅μ„ 2μ°¨ ν™•λ₯ μ  μ§€λ°°ν•˜μ˜€μœΌλ©° κ²½μœ μ™€ 휘발유 수읡 뢄포 간에도 ν™•λ₯ μ  지배관계가 μ‘΄μž¬ν•˜μ˜€λ‹€. λ§ˆμ§€λ§‰μœΌλ‘œ λ³Έ μ—°κ΅¬λŠ” 1988λ…„ 12μ›”λΆ€ν„° 2018λ…„ 11μ›”κΉŒμ§€μ˜ μ›”κ°„ 자료λ₯Ό μ‚¬μš©ν•˜μ—¬ WTI 유, Brent 유의 μ„ λ¬Όκ³Ό ν˜„λ¬Ό 수읡 뢄포 κ°„ 관계λ₯Ό λΆ„μ„ν•˜μ˜€λ‹€. κ·Έ κ²°κ³Ό, Brentμœ μ™€ WTI유 λͺ¨λ‘ μ„ λ¬Ό 가격 수읡 뢄포가 ν˜„λ¬Ό 가격 수읡 뢄포λ₯Ό 2μ°¨ ν™•λ₯ μ  μ§€λ°°ν•˜λŠ” κ²ƒμœΌλ‘œ λ‚˜νƒ€λ‚¬λ‹€. μ΄λŸ¬ν•œ κ²°κ³ΌλŠ” μœ„ν—˜νšŒν”Ό μ„±ν–₯의 νˆ¬μžμžλ“€μ—κ²Œ μ›μœ  선물이 μ›μœ  ν˜„λ¬Όλ³΄λ‹€ 높은 νš¨μš©μ„ κΈ°λŒ€ν•  수 μžˆλŠ” νˆ¬μžμ²˜κ°€ 될 수 μžˆμŒμ„ ν•¨μ˜ν•œλ‹€.Crude oil is historically one of the most representative assets in financial market, as well as it shows tremendous effects on world economy. Among oil prices, three most renowned and frequently traded benchmark assets are WTI(represents North American market), Brent(represents European market), Dubai(represents Asian market). Numerous papers have studied the relationship between three marker crude prices, including famous arguments about regionalization or integration of world crude oil market(Weiner(1991), Gulen(1999), Charles(2009), etc) and finacial studies about making optimal crude oil portfolio(Daniel(2001), Chang(2011), etc). In a financial point of view, however, No researchers have tried to study the relationship between returns of benchmark oil prices. This study compares returns of three marker crude oil assets using stochastic dominance approach, widely used investment-decision-making method as well as keen ordering rule of distributions. The period for the analysis is from January 3, 2000 to July 31, 2018, and daily data is used. The study compares the returns using spot prices for reasons that futures of Dubai do not exist. Result shows that returns of Dubai crude oil 2nd order-stochastically dominates that of Brent, and returns of Brent also 2nd order-stochastically dominates that of WTI in whole period. It implies that Dubai crude is the best invest asset for risk-averse investors, and Brent crude would be the next option for investment. It is quite interesting point since it show that WTI, the most renowned crude among three benchmarks, would the last option and Dubai, comparatively minor benchmark, would be the best option for risk-averse oil market investors.제 1 μž₯ μ„œ λ‘  1 제 1 절 μ—°κ΅¬μ˜ λ°°κ²½ 및 λͺ©μ  1 제 2 μž₯ ꡭ제 벀치마크 μ›μœ μ™€ μ£Όμš” μ„μœ μ œν’ˆ 5 제 1 절 ꡭ제 벀치마크 μ›μœ  가격 5 제 2 절 μ„μœ μ™€ μ„μœ  μ œν’ˆ 13 제 3 절 휘발유 15 제 4 절 λ””μ € μ—°λ£Œ 22 제 5 절 λ‚œλ°©μœ  27 제 3 μž₯ 수읡과 수읡λ₯ μ˜ μ’…λ₯˜ 30 제 1 절 수읡과 수읡λ₯  30 제 2 절 단일 κΈ°κ°„κ³Ό μ—¬λŸ¬ κΈ°κ°„ 투자 수읡λ₯  31 제 2 절 μ—¬λŸ¬ κΈ°κ°„ 투자의 연평균 수읡λ₯  33 제 4 μž₯ ν™•λ₯ μ  지배관계 검정법 κ΄€λ ¨ μ£Όμš” 연ꡬ 37 제 1 절 후생 κ²½μ œν•™μ—μ„œμ˜ 적용 사둀 38 제 2 절 금육 κ²½μ œν•™μ—μ„œμ˜ 적용 사둀 40 제 3 절 μ‚°μ—…μ‘°μ§λ‘ μ—μ„œμ˜ 적용 사둀 43 제 4 절 λ…Έλ™κ²½μ œν•™μ—μ„œμ˜ 적용 사둀 45 제 5 절 κ΅­μ œκ²½μ œν•™μ—μ„œμ˜ 적용 사둀 46 제 5 μž₯ 뢄석 자료 및 뢄석 방법둠 47 제 1 절 뢄석 자료 47 제 2 절 ν™•λ₯ μ  지배 이둠 및 κ²€μ • 49 제 3 절 ν™•λ₯ μ  지배 관계 53 제 4 절 κ· λ“± ν™•λ₯ λΆ„포에 λŒ€ν•œ 귀무가섀 κ²€μ • 54 제 6 μž₯ 뢄석 κ²°κ³Ό 56 제 7 μž₯ κ²°λ‘  75 μ°Έκ³ λ¬Έν—Œ 78 λΆ€ 둝 85 Abstract 94Maste

    μž₯κΈ°μš”μ–‘λ³΄ν—˜μ΄ μž₯κΈ°μš”μ–‘μ„œλΉ„μŠ€μ™€ μ˜λ£Œμ΄μš©μ— λ―ΈμΉ˜λŠ” 영ν–₯: μΉ˜λ§€λ“±κΈ‰μ„ μ€‘μ‹¬μœΌλ‘œ

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    ν•™μœ„λ…Όλ¬Έ (석사)-- μ„œμšΈλŒ€ν•™κ΅ λ³΄κ±΄λŒ€ν•™μ› 보건학과, 2017. 8. μ΄νƒœμ§„.β–« 연ꡬλͺ©μ  치맀 μ–΄λ₯΄μ‹ λ“€μ΄ μž₯κΈ°μš”μ–‘λ³΄ν—˜ μΉ˜λ§€λ“±κΈ‰μ„ 받은 ν›„, μž₯κΈ°μš”μ–‘ μ„œλΉ„μŠ€ 및 의료 이용이 μ–Όλ§ˆλ‚˜ λ‹¬λΌμ§€λŠ”μ§€, 그리고 이에 따라 인지기λŠ₯κ³Ό κ°€μ‘±μ˜ λΆ€λ‹΄ μ •λ„λŠ” μ–Όλ§ˆλ‚˜ λ³€ν™”ν•˜μ˜€λŠ”μ§€ μ•Œμ•„λ³Έλ‹€. β–« 연ꡬ방법 κ΅­λ―Όκ±΄κ°•λ³΄ν—˜κ³΅λ‹¨μ˜ 2012λ…„-2015년도 λ§žμΆ€ν˜•DBλ₯Ό μžλ£Œμ›μœΌλ‘œ μ΄μš©ν•˜μ˜€λ‹€. 이 μžλ£Œμ›μ—λŠ” λŒ€μƒμžμ˜ 의료이용 및 μž₯κΈ°μš”μ–‘μ„œλΉ„μŠ€ 이용과 λ“±κΈ‰νŒμ • κ²°κ³Όκ°€ ν¬ν•¨λ˜μ–΄ μžˆλ‹€. λ³Έ μ—°κ΅¬μ—μ„œλŠ” μΉ˜λ§€λ“±κΈ‰μž 7,226λͺ…을 ν¬ν•¨ν•˜μ—¬ 총 21,192λͺ…을 λŒ€μƒμœΌλ‘œ 뢄석을 μ§„ν–‰ν•˜μ˜€λ‹€. 뢄석은 이쀑차뢄법(Difference-in-Difference)을 ν™œμš©ν•˜μ—¬, μΈμ§€ν™œλ™ν˜• ν”„λ‘œκ·Έλž¨μ— 의무적으둜 μ°Έμ—¬ν•΄μ•Ό ν•˜λŠ” μΉ˜λ§€λ“±κΈ‰ μ΄μš©μžλ“€μ˜ μΉ˜λ§€λ“±κΈ‰ λ„μž… μ „ν›„ 6κ°œμ›”μ˜ λ³€ν™”λ₯Ό μ•Œμ•„λ³΄μ•˜λ‹€. 이 λ•Œ λ“±κΈ‰μ™Έ νŒμ •μ„ λ°›κ±°λ‚˜ 4λ“±κΈ‰ νŒμ •μ„ 받은 치맀 ν™˜μžλ“€μ„ λŒ€μ‘°κ΅°μœΌλ‘œ ν™œμš©ν•˜μ˜€λ‹€. β–« 연ꡬ결과 치맀 λ“±κΈ‰ μ΄μš©μžλ“€μ€, λ“±κΈ‰μ™Έμžμ— λΉ„ν•˜μ—¬ μ—°κ°„ μž₯κΈ°μš”μ–‘μ„œλΉ„μŠ€ μ΄μš©μ•‘μ€ 512.4λ§Œμ›μ΄ μ¦κ°€ν•˜κ³  μ—°κ°„ μ˜λ£ŒλΉ„λŠ” 74.8λ§Œμ› λ§Œμ›μ΄ 덜 μ¦κ°€ν•˜λŠ” κ²ƒμœΌλ‘œ λ‚˜νƒ€λ‚¬λ‹€. 이듀이 κ°€μž₯ 많이 μ΄μš©ν•œ μ„œλΉ„μŠ€λŠ” μ£Όμ•Όκ°„λ³΄ν˜Έμ™€ λ°©λ¬Έμš”μ–‘μ˜€μœΌλ©°, μ„œλΉ„μŠ€ μ΄μš©μ€ 인지기λŠ₯ κ°œμ„ κ³Ό κ°€μ‘±μ˜ λŒλ΄„ λΆ€λ‹΄ 완화에 긍정적인 νš¨κ³Όκ°€ μžˆλŠ” κ²ƒμœΌλ‘œ λ‚˜νƒ€λ‚¬λ‹€. λ‹€λ§Œ μ΄λŸ¬ν•œ νš¨κ³ΌλŠ” 4λ“±κΈ‰ μ΄μš©μžλ“€μ— λΉ„ν•˜μ—¬ κ·Έ 크기가 μž‘μ€ κ²ƒμœΌλ‘œ λ‚˜νƒ€λ‚¬λ‹€.제 1 μž₯ μ„œ λ‘  1 제 1 절 μ—°κ΅¬μ˜ λ°°κ²½ 1 제 2 절 μ—°κ΅¬μ˜ λͺ©μ  2 제 3 절 μΉ˜λ§€λ“±κΈ‰ ν˜„ν™© 3 제 2 μž₯ 선행연ꡬ κ³ μ°° 7 제 1 절 μ˜λ£ŒλΆ„μ•Ό 선행연ꡬ 7 제 2 절 μ •μ±…λΆ„μ•Ό 선행연ꡬ 11 제 3 μž₯ 연ꡬ 방법 14 제 1 절 뢄석 λŒ€μƒ 14 제 2 절 뢄석 자료 15 제 3 절 뢄석 λͺ¨ν˜• 17 제 4 μž₯ 연ꡬ κ²°κ³Ό 20 제 1 절 뢄석 λŒ€μƒμžμ˜ 일반적 νŠΉμ„± 20 제 2 절 μž₯κΈ°μš”μ–‘μ„œλΉ„μŠ€ 및 의료 μ΄μš©λŸ‰μ˜ λ³€ν™” 26 제 3 절 μž₯κΈ°μš”μ–‘μ„œλΉ„μŠ€ 및 의료 μ΄μš©μ•‘μ˜ λ³€ν™” 32 제 4 절 인지기λŠ₯의 λ³€ν™” 35 제 5 절 λŒλ΄„λΆ€λ‹΄μ˜ λ³€ν™” 38 제 5 μž₯ κ³  μ°° 41 제 1 절 μš”μ•½ 및 정책적 ν•¨μ˜ 41 제 2 절 μ—°κ΅¬μ˜ μ œν•œμ  42 초둝 48Maste

    Cognitive Dysfunctions in Patients With Severe Obstructive Sleep Apnea Syndrome: Neuropsychological Test and Event-Related Potential Study

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    Background: Patients with obstructive sleep apnea syndrome (OSAS) show variety of dysfunctions in cognitions including general cognitive function, attention, and frontal lobe and executive function. However, there is no consensus on the main features of the cognitive dysfunction in OSAS patients. So we performed neuropsychological tests and event-related potential (ERP) studies in patients with severe OSAS to evaluate the cognitive dysfunctions and changes of auditory and visual P300. Methods: Twenty-eight men with severe OSAS (apnea hypopnea index (AHI)=63.1Β±}17.8/hr) and 16 age, sex, educationmatched normal controls (AHI=2.9Β±}1.8/hr) underwent neuropsychological tests and ERP studies. Results: Patients with severe OSAS showed deficits in corsi block forward and backward test during neuropsychological evaluation, and delayed latency and decreased amplitude of auditory P300. There were significant correlations between auditory P300 amplitudes and digit span forward or corsi block forward test scores, and between visual P300 amplitudes and digit symbol test scores. Conclusions: These findings suggest that severe OSAS patients may have deficits in attention and short-term memory, and abnormal auditory P300.OAIID:oai:osos.snu.ac.kr:snu2008-01/102/2014017262/5SEQ:5PERF_CD:SNU2008-01EVAL_ITEM_CD:102USER_ID:2014017262ADJUST_YN:NEMP_ID:A079623DEPT_CD:801CITE_RATE:0DEPT_NM:μ˜ν•™κ³ΌSCOPUS_YN:NCONFIRM:

    μ„œμˆ˜ νŒ¨ν„΄λΆ„μ„μ„ ν†΅ν•œ 슀트레인 μ›¨μ΄λΈŒ κΈ°μ–΄ 기반 λ‘œλ΄‡ νŒ” μ ‘ν•©λΆ€ 진단 ν”„λ ˆμž„μ›Œν¬

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    ν•™μœ„λ…Όλ¬Έ(석사) -- μ„œμšΈλŒ€ν•™κ΅λŒ€ν•™μ› : κ³΅κ³ΌλŒ€ν•™ 기계곡학과, 2021.8. μœ€λ³‘λ™.μ‚°μ—…μš© λ‘œλ΄‡μ€ 슀마트 νŒ©ν† λ¦¬μ˜ 보급에 따라 λ§Žμ€ μ‚°μ—… 뢄야에 걸쳐 μ‚¬μš©λ˜κ³  있으며, κ·Έ μˆ˜μš”λŠ” μ§€μ†μ μœΌλ‘œ λŠ˜μ–΄λ‚˜κ³  μžˆλŠ” 좔세이닀. λ³΅μž‘ν•œ μžλ™ν™” 곡정 λΌμΈλ“€μ˜ μ˜μ‘΄μ„±μœΌλ‘œ 인해 ν•œ 라인의 κ³ μž₯은 μ»€λ‹€λž€ 경제적 손싀을 μ•ΌκΈ°ν•  수 있고, 이에 따라 λ‘œλ΄‡μ˜ 건전성 진단은 μ€‘μš”ν•œ 이슈 둜 μžλ¦¬μž‘μ•˜λ‹€. μ‚°μ—…μš© λ‘œλ΄‡μ€ 크게 μ„Όμ„œλΆ€, μ œμ–΄λΆ€, κ΅¬λ™λΆ€λ‘œ 이루어져 있으며, κ΅¬λ™λΆ€μ˜ 핡심 λΆ€ν’ˆμΈ 슀트레인 μ›¨μ΄λΈŒ κ°μ†κΈ°λŠ” λͺ¨ν„°μ˜ 동λ ₯을 μ—”λ“œ μ΄νŽ™ν„°λ‘œ μ „λ‹¬ν•΄μ£ΌλŠ” κΈ°λŠ₯을 ν•˜κ²Œ λœλ‹€. ν•˜μ§€λ§Œ κ°μ†κΈ°μ˜ μ£Όμš” κ΅¬μ„±μš”μ†ŒμΈ ν”Œλ ‰μŠ€ν”ŒλΌμΈμ€ ν”Όλ‘œνŒŒκ΄΄κ°€ 잘 μΌμ–΄λ‚˜λ©°, 이에 따라 λ°±λž˜μ‰¬ ν˜„μƒμ΄ μΌμ–΄λ‚˜λŠ” 문제λ₯Ό 보인닀. 기쑴에 λ‘œλ΄‡μ˜ 건전성 진단을 μœ„ν•œ λ§Žμ€ 방법이 μ†Œκ°œλ˜μ—ˆμ§€λ§Œ 1) 역학적 λͺ¨λΈμ˜ 근사화 κ³Όμ •μ—μ„œ λΆˆν™•μ‹€μ„±μ΄ μ‘΄μž¬ν•˜μ˜€κ³ , 2) μ§„λ™μ‹ ν˜ΈλŠ” μ™ΈλΆ€ λ…Έμ΄μ¦ˆ 영ν–₯을 많이 λ°›μ•˜μœΌλ©°, 3) 물리적 μ„€λͺ… 및 λͺ¨μ…˜ μ „μ²˜λ¦¬ 과정이 λΆ€μ‘±ν•˜λ‹€λŠ” 단점을 λ³΄μ˜€λ‹€. λ”°λΌμ„œ λ³Έ μ—°κ΅¬μ—μ„œλŠ” λ‘œλ΄‡μ˜ μΆ•μ—μ„œ μƒλŒ€μ μœΌλ‘œ 물리적인 μ™ΈλΆ€ 영ν–₯을 덜 λ°›λŠ” μ „λ₯˜μ‹ ν˜Έλ₯Ό μΈ‘μ •ν•˜μ—¬ λ‘œλ΄‡μ˜ 건전성을 λΆ„μ„ν•˜μ˜€λ‹€. λ˜ν•œ 물리적 해석에 κΈ°λ°˜ν•˜μ—¬ 진단 ν”„λ ˆμž„μ›Œν¬λ₯Ό κ΅¬μ„±ν•˜μ˜€κ³ , 각 λ‹¨κ³„λŠ” 1) λ‘œλ΄‡ λͺ¨μ…˜ 뢄리, 2) λͺ¨ν„° μ „λ₯˜μ˜ μ„œμˆ˜νŒ¨ν„΄ 뢄석 (OPAMC), 3) 톡계적 κ³ μž₯ μ§„λ‹¨μœΌλ‘œ μ„€λͺ…λœλ‹€. 처음으둜, λͺ¨μ…˜ 뢄리 λ‹¨κ³„μ—μ„œλŠ” μΆ•μ˜ νšŒμ „ 속도에 λΉ„λ‘€ν•˜μ—¬ μ „λ₯˜μ‹ ν˜Έμ˜ 주파수 λ³€μ‘°κ°€ μΌμ–΄λ‚˜λŠ” 점에 μ°©μ•ˆν•΄ μ‹ ν˜Έμ˜ μ‹œμ£ΌνŒŒμˆ˜ 뢄석을 μ§„ν–‰ν•˜μ˜€κ³ , μ •κ·œν™” λͺ¨μ…˜ μ‹ ν˜Έλ₯Ό μ΄μš©ν•΄ λ‘œλ΄‡μ˜ μž‘λ™ ꡬ간을 λ‚˜λˆ„μ—ˆλ‹€. λ˜ν•œ λͺ¨μ…˜ λ ˆνΌλŸ°μŠ€μ™€μ˜ 코사인 μœ μ‚¬λ„λ₯Ό μ΄μš©ν•˜μ—¬ λͺ¨μ…˜ 식별 과정을 μ§„ν–‰ν•˜μ˜€κ³ , 총 μž‘λ™ 사이클을 κ³„μ‚°ν•˜κ³  λͺ¨μ…˜ νƒ€μž…μ„ λΆ„λ₯˜ν•˜μ˜€λ‹€. λ‘λ²ˆμ§Έ OPAMC λ‹¨κ³„μ—μ„œλŠ” 레퍼런슀 λͺ¨μ…˜μ— μ‹œκ°„ λ™κΈ°ν™”λœ μ‹ ν˜Έλ₯Ό νžλ²„νŠΈ λ³€ν™˜ 및 포락 μ‹ ν˜Έλ₯Ό κ΅¬ν•˜μ˜€κ³ , μš΄ν–‰ μƒνƒœμ— κΈ°λ°˜ν•œ κΈ°λ³Έ 주파수λ₯Ό μ΄μš©ν•˜μ—¬ 졜적 νŒŒλΌλ―Έν„°λ₯Ό μ΄μš©ν•˜μ—¬ μ„œμˆ˜ νŒ¨ν„΄μ„ μΆ”μΆœν•˜μ˜€λ‹€. λ˜ν•œ νŠΉμ • 좕에 λŒ€ν•˜μ—¬, 정상 μƒνƒœ 및 κ΄€μ°° λŒ€μƒμ˜ μ„œμˆ˜νŒ¨ν„΄μ„ ν™•λ₯  μ§ˆλŸ‰ λΆ„ν¬λ‘œ λ‚˜νƒ€λ‚΄μ—ˆμœΌλ©° κ·Έ 차이λ₯Ό Jensen-Shannon Divergence (JSD)으둜 κ³„μ‚°ν•˜μ—¬ μ„œμˆ˜νŒ¨ν„΄μ˜ 뢄포가 정상 μƒνƒœμ— κΈ°λ°˜ν•˜μ—¬ μ–Όλ§ˆλ‚˜ λ³€ν™”ν–ˆλŠ”μ§€ μ •λŸ‰μ μœΌλ‘œ λ‚˜νƒ€λ‚΄μ—ˆλ‹€. λ§ˆμ§€λ§‰μœΌλ‘œ, ν™•λ₯ μ  κ³ μž₯ 진단 λ‹¨κ³„μ—μ„œλŠ” μ•žμ„œ κ³„μ‚°λœ JSD 뢄포λ₯Ό 잘 λ‚˜νƒ€λ‚Ό 수 μžˆλŠ” 톡계적 μΆ”μ •μΉ˜λ₯Ό μ΄μš©ν•˜μ—¬ κ³ μž₯ 감속기가 κ²°ν•©λœ μΆ•κ³Ό 정상 좕을 νŠΉμ§•μΈμž κ³΅κ°„μ—μ„œ κ΅¬λ³„ν•˜μ˜€κ³ , 차원 μΆ•μ†Œλ₯Ό μ§„ν–‰ν•˜μ—¬ 1차원 κ³΅κ°„μ—μ„œ μ •λŸ‰μ μœΌλ‘œ λ‚˜νƒ€λƒˆλ‹€. μ‹€ν—˜μ€ 2가지 μš΄ν–‰μ‘°κ±΄μ˜ ν†΅μ œλ₯Ό 톡해 κ²€μ¦λ˜μ—ˆλŠ”λ°, λ‘œλ΄‡ μΆ•μ˜ 속도λ₯Ό 20,50,100%둜 μ¦κ°€ν•˜μ˜€κ³ , νŽ˜μ΄λ‘œλ“œλ₯Ό 0, 1, 2kg둜 μ¦κ°€μ‹œν‚€λ©° κ³ μž₯ 및 정상좕을 λΉ„κ΅ν•΄λ³΄μ•˜λ‹€. 결과적으둜 속도가 증가함에 따라 좕에 관계없이 κΈ°λ³Έμ£ΌνŒŒμˆ˜κ°€ λ™μΌν•˜κ²Œ λΉ„λ‘€ν•˜μ—¬ μ¦κ°€ν•˜λŠ” 것을 κ΄€μ°°ν•  수 μžˆμ—ˆκ³ , λΆ„ν•΄κ²°ν•© μ „ν›„λ‘œ κ³ μž₯ μΆ•μ—μ„œ μ„œμˆ˜νŒ¨ν„΄ λΆ„ν¬μ˜ JSDκ°€ 더 큼을 λ³Ό 수 μžˆμ—ˆλ‹€. λ˜ν•œ λͺ¨λ“  μ†λ„μ‘°κ±΄μ—μ„œ 정상좕 및 κ³ μž₯μΆ•μ˜ JSD 뢄포 차이가 ν™•μ—°νžˆ κ΅¬λ³„λ˜λŠ” 것을 λ³Ό 수 μžˆμ—ˆλ‹€. νŽ˜μ΄λ‘œλ“œμ˜ ν†΅μ œ μ‘°κ±΄μ—μ„œλŠ” μ—”λ“œ μ΄νŽ™ν„°μ— λΆ€ν•˜κ°€ μ‘΄μž¬ν•˜μ§€ μ•Šμ„ λ•Œ 정상 및 κ³ μž₯좕이 ν™•μ—°νžˆ κ΅¬λ³„λ˜λŠ” 것을 κ΄€μ°°ν•  수 μžˆμ—ˆλ‹€. μ΄λŠ” νŽ˜μ΄λ‘œλ“œκ°€ 없을 λ•Œ μƒλŒ€μ μœΌλ‘œ 좕에 κ±Έλ¦¬λŠ” ν† ν¬μ˜ λ³€μ‘°κ°€ μ»Έκ³ , κ°μ†κΈ°μ˜ λ°±λž˜μ‰¬κ°€ μ‹ ν˜Έμ˜ μ„œμˆ˜ νŒ¨ν„΄μ— 더 μ„ λͺ…νžˆ λ“œλŸ¬λ‚¨μ„ μ˜λ―Έν–ˆλ‹€. λ³Έ μ—°κ΅¬μ—μ„œλŠ” λͺ¨μ…˜ 뢄리 및 μ„œμˆ˜νŒ¨ν„΄ 뢄석 기법과 이에 ν•„μš”ν•œ 졜적 νŒŒλΌλ―Έν„°λ₯Ό μ œμ•ˆν•¨μœΌλ‘œμ¨ κ³ μž₯ 진단 ν”„λ ˆμž„μ›Œν¬μ„ κ΅¬μ„±ν•˜μ˜€λ‹€. μ—¬κΈ°μ„œ 뢄포에 κΈ°λ°˜ν•œ 결함 진단은 λ‘œλ΄‡ κ³ μž₯을 νŒλ‹¨ν•˜λŠ” 기쀀이 λͺ¨ν˜Έν•˜λ‹€λŠ” 점에 μ°©μ•ˆν–ˆμ„ λ•Œ, μΆ• κ°„ 비ꡐ 뢄석 등을 톡해 λ”μš± 효과적으둜 진단할 수 μžˆμŒμ„ μ˜λ―Έν•˜μ˜€λ‹€. λ˜ν•œ μ΄λŸ¬ν•œ 일련의 과정은 속도 및 νŽ˜μ΄λ‘œλ“œ λ“± λ‹€μ–‘ν•œ μš΄ν–‰μ‘°κ±΄μ—μ„œ κ²€μ¦λ¨μœΌλ‘œμ¨ 신뒰성이 높은 κ²°κ³Όλ₯Ό λ„μΆœν–ˆλ‹€λŠ” μ μ—μ„œ κ·Έ μ˜μ˜κ°€ μžˆλ‹€κ³  λ³Ό 수 μžˆλ‹€.With the fourth industrial revolution, a smart manufacturing system has been adopted in many enterprises and the demand for health assessment of industrial robots has skyrocketed in various industrial sectors. In this context, the conventional study has focused on diagnosing robots based on the physical dynamic model and vibration signal. However, 1) the approximate model had intrinsic modeling uncertainty, 2) the vibration signal could be disturbed by external noise, and 3) the motion preprocessing and physical reasoning of health assessment have not been well organized. In addition, Strain wave gear (SWG) has not been considered of health assessment although it has been used for many years as a speed reducer due to its high performance. Its elastic flexspline has been susceptible to fatigue failure causing gear backlash. In this study, therefore, we measure the motor input current of a robotic arm joint to make it less susceptible to external noise. Also, we propose a diagnosis framework of robots with SWG gearing based on ordinal pattern analysis with optimal parameter selection considering physical interpretation. The framework is composed of the following steps: 1) Motion Segmentation based on Time-Frequency Representation (TFR), 2) Ordinal Pattern Analysis of Motor Current (OPAMC), and 3) Distribution-based fault detection. At first, in the motion segmentation process, the motor current signal is frequency-demodulated using Temporal Fine Structure (TFS) since the robot’s joint speed has a linear relationship with the current signal’s frequency component. Also, the TFS is analyzed in the time-frequency domain to formulate a normalized motion signal which is used to decompose the current signal into multiple segments. Then, the segments are identified into different types of motions based on the similarity with reference motions. Also, the total number of cycles and motion types are calculated in this process. Secondly, in OPAMC, the segments are time-synchronized with reference motion and Hilbert-transformed to get an envelope for ordinal pattern extraction. Using a fundamental frequency of the current signal, the optimal parameter is calculated, and the ordinal patterns are extracted in the form of probability mass function (PMF). Then, the PMF of an observed state is quantitatively compared with a normal state through Jensen-Shannon divergence (JSD). Finally, each JSD distribution among different joints is represented on 3-dimensional feature space through point estimate of mean and variance and Kolmogorov-Smirnov statistics whose dimension is then reduced to 1 dimension scalar through linear discriminant analysis. For validation, it is tested on two cases of control condition, increasing velocity 20, 50, 100% and payload 0,1,2 kg. Also, the optimal parameter for extracting ordinal patterns is compared with actual values to demonstrate its feasibility. On velocity control, the JSD shows to be higher on the faulty reducer, and its distribution shows a distinct difference between normal and faulty joint on all speed conditions. However, on the payload control condition, the JSD is only higher with no payload mounted than the payload on the fault SWG. The payload caused less modulation on torque and motor current, and thus fewer backlash characteristics appeared on ordinal patterns. In this research, a diagnosis framework is proposed with the motion segmentation and optimal parameter in ordinal pattern extraction. Since it is subjective to diagnose the robot with a simple threshold, the comparative analysis among different joints shows to be more efficient in terms of rational health assessment. Also, the framework is validated on various operating conditions such as velocity and payload condition yielding high reliability on the study.Chapter 1. Introduction 1 1.1 Motivation 1 1.2 Scope of research 2 1.3 Thesis layout 3 Chapter 2. Literature review 5 2.1 Robot system and malfunction 5 2.1.1. Closed-loop control 6 2.1.2. Backlash of Strain Wave Gear 7 2.2 Continuous Wavelet Transform 8 2.3 Envelope and Temporal fine structure 11 2.4 Ordinal patterns 14 2.5 Measures of statistic distance 16 2.5.1. Jensen-Shannon Divergence 16 2.5.2. Kolmogorov-Smirnov statistics 17 2.6 Linear Discriminant Analysis 18 Chapter 3. Motion segmentation based on Time-Frequency Representation (TFR) 20 3.1 Fundamental frequency of motor current 20 3.2 Motion segmentation 21 3.3 Identification 23 Chapter 4. Ordinal Pattern Analysis of Motor Current (OPAMC) 25 4.1 Preprocessing 25 4.1.1. Time synchronization 25 4.1.2. Envelope extraction 26 4.2 Ordinal pattern analysis 28 4.2.1. Parameter selection based on TFR 29 4.3 Fault detection 33 4.3.1. Jensen-Shannon Divergence 33 4.3.2. Distribution-based diagnosis 34 Chapter 5. Experiment and Validation. 37 5.1 Experimental setup 37 5.2 Experimental result 39 5.2.1. Case 1: Velocity 20%, 50%, 100% 39 5.2.2. Case 2: Payload 0kg, 1kg, 2kg 49 Chapter 6. Conclusion 54 6.1 Contribution and Future work 55 Bibliography 56 κ΅­λ¬Έ 초둝 62석

    In-situ 쒅합에 μ˜ν•΄ 제쑰된 ν΄λ¦¬ν”Όλ‘€ν΄λ¦¬λΉ„λ‹μ•„μ„Έν…Œμ΄νŠΈ λΈ”λ Œλ“œμ˜ 전기전도도 νŠΉμ„±μ— κ΄€ν•œ 연ꡬ

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    ν•™μœ„λ…Όλ¬Έ(석사)--μ„œμšΈλŒ€ν•™κ΅ λŒ€ν•™μ› :화학곡학과,1998.Maste

    사이버 μ•ˆμ „ κ΄€λ ¨ 법λ₯ μ˜ κ²Œμž„ 이둠적 연ꡬ

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    ν•™μœ„λ…Όλ¬Έ (석사)-- μ„œμšΈλŒ€ν•™κ΅ ν–‰μ •λŒ€ν•™μ› : ν–‰μ •ν•™κ³Ό, 2013. 8. 박상인.μ •λ³΄ν™”μ˜ κΈ‰μ†ν•œ 진전에 따라 κ΅­κ°€μ˜ μ£Όμš” μ‹œμ„€ 및 μ„œλΉ„μŠ€κ°€ 점차 μ •λ³΄ν†΅μ‹ λ§μœΌλ‘œ μ—°κ³„λ˜κ³ , 사이버 곡간 μƒμ˜ 개인과 μ‚¬νšŒ 그리고 κ΅­κ°€ κ°„ μƒν˜Έμ˜μ‘΄λ„λŠ” λ†’μ•„μ Έ κ°€κ³  μžˆλ‹€. μ΄λŠ” ν•œνŽΈμœΌλ‘œ 사이버 ν…ŒλŸ¬λ‘œ μΈν•œ ν”Όν•΄κ°€ κ΅­κ°€ μ „λ°˜μœΌλ‘œ νŒŒκΈ‰λ˜μ–΄ λŒ€κ·œλͺ¨μ˜ ν”Όν•΄, λ‚˜μ•„κ°€ κ΅­κ°€ μ•ˆμ „μ— λŒ€ν•œ μœ„ν˜‘μœΌλ‘œ μ΄μ–΄μ§ˆ κ°€λŠ₯성이 높아지고 μžˆμŒμ„ μ˜λ―Έν•œλ‹€. κ·ΈλŸΌμ—λ„ λΆˆκ΅¬ν•˜κ³  μš°λ¦¬λ‚˜λΌλŠ” 아직 체계적인 κ΅­κ°€ 사이버 μ•ˆμ „ κ΄€λ ¨ 법λ₯  체계λ₯Ό κ΅¬μΆ•ν•˜κ³  μžˆμ§€ λͺ»ν•˜λ‹€. 특히 κ΄€λ ¨ 업무가 μ†Œκ΄€ λΆ€μ²˜λ³„λ‘œ ν•œμ •λœ λ²”μœ„μ—μ„œ κ°œλ³„μ μœΌλ‘œ 이루어지도둝 λ˜μ–΄ μžˆμ–΄ 사이버 ν…ŒλŸ¬μ˜ μ˜ˆλ°©μ€ λ¬Όλ‘ , μ‚¬μ΄λ²„μœ„κΈ° μƒν™©μ—μ„œμ˜ μ‹ μ†ν•˜κ³  체계적인 λŒ€μ‘μ΄ μ–΄λ €μš΄ 싀정이닀. λ³Έ μ—°κ΅¬λŠ” μ΄λŸ¬ν•œ 인식을 기초둜 μ‚¬μ΄λ²„μ•ˆμ „ κ΄€λ ¨ 법λ₯ μ˜ μ œμ •μ΄ λŠ¦μ–΄μ§€κ³  μžˆλŠ” μ΄μœ μ™€ 이에 λŒ€ν•œ ν•΄κ²° λ°©μ•ˆμ— λŒ€ν•˜μ—¬ κ³ μ°°ν•˜κ³ μž ν•˜μ˜€λ‹€. 법λ₯  μ œμ •μ„ μœ„ν•΄μ„œλŠ” λ¨Όμ € ν•΄λ‹Ή 법λ₯ μ˜ λ‚΄μš©μ΄ 효과적인 사이버 μ•ˆμ „ 관리λ₯Ό λ’·λ°›μΉ¨ ν•  수 μžˆλ„λ‘ λ§Œλ“€μ–΄μ Έμ•Ό ν•œλ‹€λŠ” 점이 μ€‘μš”ν•˜λ‚˜, μ΄λŸ¬ν•œ λ‚΄μš©μ˜ λ²•μ•ˆμ΄ ꡭ회의 μ‹¬μ˜λ₯Ό 톡과할 수 μžˆλŠ”μ§€λ„ 큰 관건이라고 ν•  수 μžˆλ‹€. μ΄λŠ” 동 λ²•μ•ˆμ΄ 사이버 μ•ˆμ „ 관리 체계λ₯Ό 총괄할 기관을 κ΅­κ°€μ •λ³΄μ›μœΌλ‘œ κ·œμ •ν•  κ°€λŠ₯성이 λ†’μ•„ 이에 λ”°λ₯Έ 의견 λŒ€λ¦½μ΄ μ˜ˆμƒλ˜κΈ° λ•Œλ¬Έμ΄λ‹€. μ‹€μ œλ‘œ μ§€λ‚œ 제18λŒ€ κ΅­νšŒμ—μ„œ λ°œμ˜λ˜μ—ˆλ˜ γ€Œκ΅­κ°€μ‚¬μ΄λ²„μœ„κΈ°κ΄€λ¦¬λ²•(μ•ˆ)」이 폐기되게 된 것도 주둜 κ΅­κ°€μ •λ³΄μ›μ˜ 역할에 λŒ€ν•œ μ—¬μ•Όμ˜ 의견 차이λ₯Ό μ’νžˆμ§€ λͺ»ν–ˆκΈ° λ•Œλ¬Έμ΄λ‹€. λ”°λΌμ„œ λ³Έ μ—°κ΅¬λŠ” 사이버 μ•ˆμ „ κ΄€λ ¨ 법λ₯  μž…λ²• κ³Όμ •μ—μ„œμ˜ μ—¬μ•Ό μƒν˜Έμž‘μš©μ„ λΆ„μ„ν•˜μ—¬ μ§€λ‚œ μž…λ²• μ‹€νŒ¨ μ‚¬λ‘€μ˜ 원인을 μ•Œμ•„λ³΄κ³ , 이λ₯Ό ν† λŒ€λ‘œ 쟁점 λ²•μ•ˆμ΄ μ œμ •λ˜κΈ° μœ„ν•œ 쑰건을 λ„μΆœν•˜μ˜€λ‹€. μƒμž„μœ„μ›νšŒμ˜ λ²•μ•ˆ 심사 과정은 μ—¬λ‹Ήκ³Ό 야당이 유ꢌ자의 지지λ₯Ό ν™•λ³΄ν•˜κΈ° μœ„ν•˜μ—¬ μ „λž΅μ μΈ 선택에 따라 μƒν˜Έμž‘μš©ν•˜λŠ” κ²Œμž„μœΌλ‘œ λͺ¨ν˜•ν™”ν•  수 μžˆλ‹€. λ”°λΌμ„œ κ²Œμž„ 이둠적 뢄석을 톡해 μž…λ²• κ³Όμ •μ—μ„œ μ–΄λ– ν•œ μ •μΉ˜μ  μš”μ†Œκ°€ μž…λ²• ꡐ착을 μ΄ˆλž˜ν•˜λŠ”μ§€ μΆ”λ‘ ν•  수 μžˆμ—ˆμœΌλ©° 문제 해결에 λŒ€ν•œ λ‹€μŒκ³Ό 같은 μ‹œμ‚¬μ μ„ λ°œκ²¬ν•΄ λ‚Ό 수 μžˆμ—ˆλ‹€. 첫째, ꡭ민듀이 λ²•μ•ˆμ˜ ν•„μš”μ„±μ— λŒ€ν•΄ κ³΅κ°ν•˜λŠ” 정도가 μ»€μ§€λŠ” 경우 λ²•μ•ˆ λ°˜λŒ€μ— λ”°λ₯Έ νŽ˜λ„ν‹°λŠ” μƒλŒ€μ μœΌλ‘œ μ»€μ§€λ―€λ‘œ λ²•μ•ˆ 톡과 κ°€λŠ₯성은 λ†’μ•„μ§ˆ 수 μžˆλ‹€. κ·ΈλŸ¬λ‚˜ μ΄λŸ¬ν•œ ꡭ민의 인식은 μΈμœ„μ μœΌλ‘œ μ „ν™˜ν•˜κΈ° μ–΄λ €μš°λ―€λ‘œ μ‹œκ°„μ΄ 였래 걸릴 뿐만 μ•„λ‹ˆλΌ 였랜 μ‹œκ°„μ΄ μ§€λ‚˜λ„ 인식이 크게 λ³€ν•˜μ§€ μ•Šμ„ κ°€λŠ₯성도 ν¬λ‹€λŠ” λ¬Έμ œκ°€ μžˆλ‹€. λ‘˜μ§Έ, μ •μΉ˜κΆŒμ΄ 슀슀둜 μž₯기적인 μ‹œκ³„λ₯Ό ν™•λ³΄ν•˜κ³  보닀 μ •μ±… 지ν–₯적으둜 바뀐닀면 κ΅­κ°€ μ•ˆλ³΄μ— μ€‘μš”ν•œ λ²•μ•ˆμ— λŒ€ν•΄μ„œ ν•©λ¦¬μ μœΌλ‘œ μ‹¬μ‚¬ν•˜μ—¬ λ²•μ•ˆμ„ ν†΅κ³Όμ‹œν‚¬ 수 μžˆμ„ 것이닀. λ‹€λ§Œ, 이λ₯Ό μœ„ν•΄μ„œλŠ” μ˜μ› 슀슀둜의 λ…Έλ ₯뿐만 μ•„λ‹ˆλΌ λ³΄μ’Œμ§„μ€ λ¬Όλ‘ , μ†Œμ†μ •λ‹Ήμ˜ 지도뢀가 ν•¨κ»˜ λ…Έλ ₯ν•΄μ•Ό ν•œλ‹€. μ…‹μ§Έ, λ²•μ•ˆμ„ λŒ€ν†΅λ Ήμ˜ μž„κΈ° μ΄ˆλ°˜λ³΄λ‹€λŠ” ν›„λ°˜, μ£Όμš”κ΅­μ΄λ‚˜ μš°λ¦¬λ‚˜λΌμ—μ„œ μ‚¬μ΄λ²„ν…ŒλŸ¬κ°€ λ°œμƒν•˜μ—¬ ꡭ민적 관심이 높을 λ•Œμ™€ 같이 λ²•μ•ˆ 톡과에 μœ λ¦¬ν•œ μ‹œκΈ°μ— λ°œμ˜ν•˜λ©΄ λ²•μ•ˆμ΄ 톡과될 κ°€λŠ₯성이 λ†’μ•„μ§ˆ 수 μžˆλ‹€. λ‹€λ§Œ 사이버 ν…ŒλŸ¬μ˜ 예방이 사이버 μ•ˆμ „ κ΄€λ ¨ 법λ₯ μ˜ μ£Όμš” μ·¨μ§€μ΄λ―€λ‘œ μ΄λŸ¬ν•œ λ°©μ•ˆμ€ 법λ₯  μ œμ •μ˜ μ μ‹œμ„±μ„ ν•΄μΉ  수 μžˆλ‹€. λ„·μ§Έ, λ²•μ•ˆμ—μ„œ λ…Όλž€μ˜ 여지가 μžˆλŠ” 뢀뢄을 μˆ˜μ •ν•˜μ—¬ λ°œμ˜ν•œλ‹€λ©΄ 동 λ²•μ•ˆμ— λ°˜λŒ€ν•  μ΄μœ κ°€ μ—†κ²Œ λ˜λ―€λ‘œ 결과적으둜 λ²•μ•ˆμ΄ ν†΅κ³Όλ˜κΈ° μ‰¬μ›Œμ§„λ‹€. ν˜„μ‹€μ μœΌλ‘œ ꡭ가정보원 외에 사이버 μ•ˆμ „ 업무λ₯Ό 총괄할 μ „λ¬Έμ„± 및 λ…Έν•˜μš°λ₯Ό 가진 λΆ€μ²˜λ₯Ό μ°ΎκΈ° νž˜λ“€λ‹€λŠ” μ μ—μ„œλŠ” ꡭ가정보원이 사이버 μ•ˆμ „ 관리 업무λ₯Ό μ΄κ΄„ν•˜λ˜ 이에 λŒ€ν•œ μ μ ˆν•œ 사전·사후적 ν†΅μ œκ°€ κ°€λŠ₯ν•˜λ„λ‘ 일뢀 쑰문을 μˆ˜μ •ν•˜κ±°λ‚˜ μ‹ μ„€ν•˜λŠ” λ°©μ•ˆμ΄ λ°”λžŒμ§ν•  것이닀. ν•œνŽΈ, μž…λ²• κ³Όμ •μ˜ ν™˜κ²½μœΌλ‘œ μž‘μš©ν•˜λŠ” μ •μΉ˜ ꡬ쑰·문화 λ“± κ±°μ‹œμ  μš”μΈμ΄ λ²•μ•ˆμ˜ 톡과 κ°€λŠ₯성에 λ―ΈμΉ˜λŠ” 영ν–₯도 크닀. λ”°λΌμ„œ μ •λ‹Ήμ˜ κΈ°μ†μœΌλ‘œλΆ€ν„° μ˜μ›λ“€μ˜ μžμœ¨μ„±κ³Ό 독립성을 ν™•λ³΄ν•˜μ—¬ 양심에 따라 전체 κ΅­λ―Όκ³Ό κ΅­κ°€ 이읡을 μœ„ν•œ ꡐ차 νˆ¬ν‘œκ°€ κ°€λŠ₯ν•˜λ„λ‘ ν•˜λŠ” λ“± ꡭ회 λ‚΄μ˜ κ±΄μ „ν•œ μ •μΉ˜μ  κ²Œμž„μ˜ κ·œμΉ™μ„ ν™•λ³΄ν•˜λ„λ‘ ν•˜μ—¬μ•Ό ν•œλ‹€.제 1μž₯ μ„œλ‘  1 제 1절 μ—°κ΅¬μ˜ 의의 및 λͺ©μ  1 1. μ—°κ΅¬μ˜ λ°°κ²½κ³Ό 의의 1 2. μ—°κ΅¬μ˜ λͺ©μ  3 제 2절 μ—°κ΅¬μ˜ 방법 4 1. 연ꡬ 문제 4 2. μ—°κ΅¬μ˜ 방법 5 제 2μž₯ 이둠적 λ°°κ²½ 및 μ„ ν–‰ μ—°κ΅¬μ˜ κ²€ν†  8 제 1절 μ—°κ΅¬μ˜ 이둠적 λ°°κ²½ 8 1. μž…λ²• κ³Όμ •μ˜ μ •μΉ˜μ„±μ— κ΄€ν•œ 이둠 8 2. 사이버 ν…ŒλŸ¬ λ“±μ˜ λŒ€μ‘μ— κ΄€ν•œ 이둠 11 제 2절 μ„ ν–‰ μ—°κ΅¬μ˜ κ²€ν†  14 1. μž…λ²• κ³Όμ •μ˜ μ •μΉ˜μ„±μ— κ΄€ν•œ 연ꡬ 14 2. 사이버 ν…ŒλŸ¬ λ“±μ˜ λŒ€μ‘μ— κ΄€ν•œ 연ꡬ 16 3. μ„ ν–‰ μ—°κ΅¬μ˜ ν•œκ³„ 및 λ³Έ μ—°κ΅¬μ˜ 의의 18 제 3μž₯ 법 μ œμ •μ˜ ν•„μš”μ„± 및 μ œμ • λ°©μ•ˆ 20 제 1절 사이버 μ•ˆμ „ κ΄€λ ¨ 법λ₯  μ œμ •μ˜ 좔진 λ°°κ²½ 20 1. 법 μ œμ •μ˜ λ°°κ²½ : 사이버 ν…ŒλŸ¬μ˜ κ°œλ… 및 ν˜„ν™© 20 2. 법 μ œμ •μ˜ ν•„μš”μ„± 24 제 2절 μ£Όμš”κ΅­μ˜ 사이버 μ•ˆμ „ 체계 및 κ΄€λ ¨ 법령 28 1. λ―Έκ΅­ 28 2. 영ꡭ 32 3. 독일 33 4. ν”„λž‘μŠ€ 34 5. 일본 35 6. μ‹œμ‚¬μ  36 제 3절 μš°λ¦¬λ‚˜λΌμ˜ 사이버 μ•ˆμ „ 체계·관련 법령 및 문제점 38 1. μš°λ¦¬λ‚˜λΌ 사이버 μΉ¨ν•΄ λŒ€μ‘ 체계 38 2. κ΄€λ ¨ 법령 ν˜„ν™© 40 3. ν˜„ μ²΄κ³„μ˜ 문제점 43 제 4절 사이버 μ•ˆμ „ κ΄€λ ¨ 법λ₯ μ˜ μ œμ • λ°©ν–₯ 45 1. κ΄€λ ¨ μž…λ²• λ…Έλ ₯ 45 2. μ œμ • 법λ₯ μ•ˆμ˜ κ°œμ„  λ°©ν–₯ 50 제 4μž₯ 법λ₯ μ•ˆ μ œμ •μ˜ κ²Œμž„ 이둠적 κ³ μ°° 56 제 1절 μ „μ œ 및 λͺ¨ν˜•μ˜ μ„€μ • 57 1. κ²Œμž„ 이둠적 λΆ„μ„μ˜ 의의 57 2. μ „μ œ 58 제 2절 μž…λ²• μ‹€νŒ¨ μ‚¬λ‘€μ˜ 뢄석 62 1. 2008λ…„ 발의 λ²•μ•ˆμ˜ μž…λ²• μ‹€νŒ¨ 사둀 62 2. 2006λ…„ 발의 λ²•μ•ˆμ˜ μž…λ²• μ‹€νŒ¨ 사둀 68 3. μž…λ²• μ‹€νŒ¨ μ‚¬λ‘€μ˜ μ‹œμ‚¬μ  73 제 3절 법λ₯  μ œμ • λ°©μ•ˆμ˜ κ²Œμž„ 이둠적 λ„μΆœ 74 1. λͺ¨ν˜•μ˜ μ„€μ • 74 2. κ²Œμž„μ˜ ν•΄ 84 3. 결과의 해석 95 3. μ‹œμ‚¬μ  및 ν•΄κ²° λ°©μ•ˆ 108 제 5μž₯ κ²°λ‘  114 μ°Έκ³  λ¬Έν—Œ 118 뢀둝 123 ABSTRACT 135Maste

    Accompanying lesions and clinical results in the greater tuberosity fracture of the humerus with anterior shoulder dislocation under the age of forty

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    μ˜ν•™κ³Ό/석사λͺ©μ : 상완골 λŒ€κ²°μ ˆ κ³¨μ ˆμ—μ„œ κ²¬κ΄€μ ˆ νƒˆκ΅¬κ°€ λ™λ°˜λœ 경우 λ™λ°˜ 병변을 μ‘°μ‚¬ν•˜κ³  μž„μƒμ  κ²°κ³Όλ₯Ό μ•Œμ•„λ³΄κ³ μž ν•œλ‹€.λŒ€μƒ 및 방법: 2005λ…„ 5μ›”λΆ€ν„° 2008λ…„ 11μ›”κΉŒμ§€ κ²¬κ΄€μ ˆ νƒˆκ΅¬κ°€ λ™λ°˜λœ 상완골 λŒ€κ²°μ ˆ 골절 ν™˜μžμ€‘ 40μ„Έ μ΄ν•˜μ˜ 30λͺ…을 λŒ€μƒμœΌλ‘œ κ΄€μ ˆκ²½μ„ μ‹œν–‰ν•˜μ˜€λ‹€. λ™λ°˜ 병변을 ν™•μΈν•œ ν›„ λ„κ΄€λ‚˜μ‚¬ κ³ μ • λ˜λŠ” λ΄‰ν•©λ‚˜μ‚¬λ₯Ό μ΄μš©ν•˜μ—¬ 고정을 μ‹œν–‰ν•˜μ˜€λ‹€. Constant μ μˆ˜μ™€ Rowe 점수λ₯Ό μ‘°μ‚¬ν•˜μ˜€λ‹€. κ²°κ³Ό: Bankart 병변 2예, 골성 Bankart 병변 4예, Perthes 병변 4예, free ALPSA 병변 2예, GLAD 병변 3예, κ΄€μ ˆλ‚­ νŒŒμ—΄ 6예 κ΄€μ°°λ˜μ—ˆκ³ , νšŒμ „κ·Ό 개 λΆ€λΆ„ νŒŒμ—΄ 5예(16.7%), SLAP type I 2예(6.7%), SLAP type II 병변 1예(3.3%), 이두μž₯건 νŒŒμ—΄ 1예(3.3%)κ°€ κ΄€μ°°λ˜μ—ˆλ‹€. Constant μ μˆ˜λŠ” 술 μ „ 평균 56.30Β±11.83 μ μ—μ„œ 술 ν›„ 평균 94.43Β±7.82 점으둜 μ¦κ°€ν•˜μ˜€κ³ (p=0.034), Rowe μ μˆ˜λŠ” 52.56Β±9.96 μ μ—μ„œ 91.76Β±9.56 점으둜 μ¦κ°€ν•˜μ˜€λ‹€(p=0.026)κ²°λ‘ : κ²¬κ΄€μ ˆ μ „λ°© νƒˆκ΅¬λ₯Ό λ™λ°˜ν•œ λŒ€κ²°μ ˆ κ³¨μ ˆμ—μ„œ κ΄€μ ˆκ²½μ„ μ΄μš©ν•œ λ™λ°˜ 병변 확인과 골절 치료둜 μš°μˆ˜ν•œ μž„μƒ 결과와 κ³¨μœ ν•©μ„ λ³΄μ˜€λ‹€. 2μ°¨ κ΄€μ ˆκ²½ 검사상 Perthes 병변, Free ALPSA 병변, GLAD 병변 및 κ΄€μ ˆλ‚­ νŒŒμ—΄μ€ λ΄‰ν•©μˆ μ„ μ‹œν–‰ν•˜μ§€ μ•Šμ•˜μ§€λ§Œ μžμ—° 치유 λ˜κ±°λ‚˜ 더 이상 μ†μƒμ˜ λ²”μœ„κ°€ μ¦κ°€λ˜μ§€ μ•Šμ•˜κ³  술 ν›„ 이차적인 λΆˆμ•ˆμ •μ„±μ„ μœ λ°œν•˜μ§€ μ•Šμ•˜λ‹€.ope
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