48 research outputs found

    μŒμ„± 의미 μ§€κ°μ‹œμ˜ κ³ λ“± μ–Έμ–΄ μ„±λΆ„ 처리 λ””μ½”λ”©

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    ν•™μœ„λ…Όλ¬Έ(석사) -- μ„œμšΈλŒ€ν•™κ΅λŒ€ν•™μ› : μžμ—°κ³Όν•™λŒ€ν•™ ν˜‘λ™κ³Όμ • λ‡Œκ³Όν•™μ „κ³΅, 2022. 8. μ •μ²œκΈ°.High-level linguistic processing in the human brain remains incompletely understood and constitutes a challenging topic in speech neuroscience. While most studies focused on decoding low-level phonetic components using intracranial recordings of the human brain during speech perception, few studies have attempted to decode high-level syntactic or semantic features. If any, most of the research targeting semantic decoding is conducted with picture naming tasks, which only deal with visual language rather than spoken language. The presenting study is focused on better characterizing the neural representations of processing spoken language perception, namely speech perception. Especially not on the lower-level language components such as phonemes or phonetics, but the higher-level components such as syntax and semantics. Since it is widely accepted that the tripartite nature of language processing consists of phonology, syntax, and semantics, a strategical method for analyzing speech perception tasks that can reject the intervention of phonetic factors was mandatory. Therefore, we conducted a question-and-answer speech task containing four questions revolving around two semantic categories (alive, body parts) with phonetically controlled words. Intracranial neural signals were recorded during the question-and-answer speech task using electrocorticography (ECoG) electrodes for 14 epilepsy patients. Post hoc brain activity analysis was conducted for three subjects who answered correctly to every trial (144 trials in total) to ensure the analyzed data contained only brain signals collected during the correct semantic processing. The decoding results suggest that absolute and relative spectral neural feature trends occur across all participants in particular time windows. Furthermore, the spatial aspect of the neural features that yield the best decoding accuracy verifies the current biophysiological brain language model explaining the circular nature of word meaning comprehension in the left hemisphere language network.μΈκ°„μ˜ κ³ λ“± μ„±λΆ„ μ–Έμ–΄ μ²˜λ¦¬μ™€ κ΄€λ ¨ν•œ λ‘λ‡Œ ν™œλ™μ„ ν•΄λ…ν•˜λŠ” μ—°κ΅¬λŠ” μ‹ κ²½μ–Έμ–΄ν•™ λΆ„μ•Όμ—μ„œλ„ 아직 깊이 μ—°κ΅¬λ˜μ§€ μ•Šμ€ λΆ„μ•Ό 쀑 ν•˜λ‚˜μ΄λ‹€. 침슡적 전극을 톡해 얻은 λ‡Œν”Όμ§ˆ λ‡ŒνŒŒλ₯Ό μ΄μš©ν•œ λŒ€λΆ€λΆ„μ˜ μ–Έμ–΄ λ””μ½”λ”© μ—°κ΅¬λŠ” μŒμ†Œλ‚˜ 음절 μˆ˜μ€€μ˜ ν•˜μœ„ μ–Έμ–΄ μ„±λΆ„μ—μ„œ μ§„ν–‰λ˜μ–΄ μ™”κ³ , ν†΅μ‚¬λ‚˜ μ˜λ―Έμ™€ 같은 κ³ λ“± μ–Έμ–΄ 성뢄에 λŒ€ν•œ λ””μ½”λ”© μ—°κ΅¬λŠ” λ“œλ¬Όλ‹€. λ“œλ¬Όκ²Œ μ§„ν–‰λœ κ³ λ“± μ–Έμ–΄ μ„±λΆ„ λ””μ½”λ”© 연ꡬ λ˜ν•œ λŒ€λ‹€μˆ˜κ°€ μ‹œκ°μ  μ–Έμ–΄ 처리λ₯Ό μ—°κ΅¬ν•œ 결과듀이며, μ†Œλ¦¬ μ–Έμ–΄ λ””μ½”λ”© μ—°κ΅¬λŠ” νƒœλ™ 단계에 머무λ₯΄κ³  μžˆλ‹€. λ³Έ μ—°κ΅¬λŠ” μ†Œλ¦¬ μ–Έμ–΄ μ§€κ°μ‹œμ˜ λ‘λ‡Œ ν™œμ„±μ„ λΆ„μ„ν•˜μ—¬ κ·Έ 처리 κ³Όμ •μ˜ λ‡ŒνŒŒ μ‹ ν˜Έ νŠΉμ„±μ„ 규λͺ…ν•˜κ³ μž ν•œλ‹€. 특히 인간 μŒμ„± μ–Έμ–΄μ˜ ν•˜μœ„ ꡬ성 μ„±λΆ„λ³΄λ‹€λŠ” 톡사와 의미 μœ„μ£Όμ˜ κ³ λ“± ꡬ성 성뢄을 μ²˜λ¦¬ν•˜λŠ” 데에 κ΄€μ—¬ν•˜λŠ” λ‡ŒνŒŒμ˜ μ‹œκ°„μ , 주파수적, 곡간적 νŠΉμ„±μ— μ§‘μ€‘ν•˜μ—¬ 뢄석을 μ§„ν–‰ν•˜μ˜€λ‹€. μ–Έμ–΄ 처리의 주된 μ„Έ 가지 μš”μ†ŒλŠ” β€˜μŒμ†Œ (phonetics)’, β€˜ν†΅μ‚¬ (syntactics)’, β€˜μ˜λ―Έ (semantics)β€™λΌλŠ” 점을 κ³ λ €ν•˜μ—¬, μŒμ†Œ μ†Œμ€€μ˜ λ‡ŒνŒŒ ν™œλ™μ„ ν†΅μ œν•  수 μžˆλŠ” μ‹€ν—˜ νŒ¨λŸ¬λ‹€μž„μ„ κ΅¬μƒν•˜μ˜€μœΌλ©°, κ΅¬μ²΄μ μœΌλ‘œλŠ” λ‘κ°œμ˜ λ‹€λ₯Έ 의미 λ²”μ£Ό (생λͺ…, 신체)에 λŒ€ν•΄μ„œ λ¬»λŠ” μŒμ†Œμ μœΌλ‘œ λ™λ“±ν•œ 단어가 ν¬ν•¨λœ μ§ˆλ¬Έμ„ λ“€λ €μ€€ ν›„ 의미λ₯Ό νŒŒμ•…ν•΄ λŒ€λ‹΅ν•˜λŠ” κ³Όμ •μ˜ λ‡ŒνŒŒλ₯Ό κΈ°λ‘ν•˜λŠ” μ‹€ν—˜μ„ μ§„ν–‰ν•˜μ˜€λ‹€. λ‡ŒνŒŒ μ‹ ν˜ΈλŠ” κ²½λ§‰ν•˜ μ „κ·Ή μ‚½μž…μˆ  (Electrocorticography, ECoG)을 톡해 14λͺ…μ˜ λ‡Œμ „μ¦ ν™˜μžλ‘œλΆ€ν„° 침슡적 λ°©μ‹μœΌλ‘œ μΈ‘μ •λ˜μ—ˆλ‹€. λ‡ŒνŒŒ λ””μ½”λ”© λΆ„μ„μ—λŠ” ν”Όν—˜μžμ˜ λ‘λ‡Œκ°€ μ˜³μ€ λ°©μ‹μœΌλ‘œ μ²˜λ¦¬ν•œ κ³ λ“± μ–Έμ–΄ 성뢄이 반영된 μ‹€ν—˜λ§Œμ„ ν¬ν•¨ν•˜κΈ° μœ„ν•΄μ„œ λͺ¨λ“  μ‹€ν—˜μ—μ„œ μ˜³μ€ λŒ€λ‹΅μ„ ν•œ μ„Έ λͺ…μ˜ ν™˜μžλ§Œμ„ λŒ€μƒμœΌλ‘œ ν•˜μ—¬ 뢄석을 μ§„ν–‰ν•˜μ˜€λ‹€. λ””μ½”λ”© 뢄석 κ²°κ³Ό μ„Έ λͺ…μ˜ ν™˜μžμ— 걸쳐 핡심 단어 (β€˜κ²ƒμ€β€™, β€˜λ¬΄μ—‡μž…λ‹ˆκΉŒβ€™) μŒμ„± 지각 이후 νŠΉμ • μ‹œκ°„λŒ€μ—μ„œ νŠΉμ • μ£ΌνŒŒμˆ˜λŒ€μ˜ λ‡ŒνŒŒκ°€ μ–‘ κ·Ήλ‹¨μ˜ 의미λ₯Ό 높은 μˆ˜μ€€μ˜ 정확도(%)둜 λΆ„λ₯˜ν•˜λŠ” 데에 μ‚¬μš©λ  수 μžˆλ‹€λŠ” 것을 λ°ν˜”λ‹€. λ˜ν•œ μ΄λŸ¬ν•œ 높은 정확도λ₯Ό κΈ°λ‘ν•œ λ‡ŒνŒŒμ˜ νŠΉμ„±μ—λŠ” λͺ¨λ“  ν™˜μžμ— 걸쳐 μ ˆλŒ€μ  ν˜Ήμ€ μƒλŒ€μ  νŠΈλ Œλ“œκ°€ κ΄€μ°°λ˜λ©°, κ΄€μ°°λ˜λŠ” λ‡ŒνŒŒμ˜ 곡간적 νŠΉμ„±μ€ ν˜„μž¬ ν†΅μš©λ˜λŠ” 신경언어학적 μ–Έμ–΄ 처리 λͺ¨λΈμ΄ μ„€λͺ…ν•˜λŠ” μŒμ„± μ–Έμ–΄ 처리 방식과 일λ§₯상톡함을 λ°ν˜”λ‹€.Abstract β…° 1. Introduction 1 2. Materials and Methods 4 3. Results 8 4. Discussion 12 References 15 List of Figures 20 Supplementary information 28 Abstract in Korean 36석

    Nikhil Pal Singh, Black is a Country: Race and the Unfinished Struggle for Democracy. Cambridge, Mass.; London: Harvard University Press, 2004. 285 pages.

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    1990λ…„λŒ€ λ―Έκ΅­μ‚¬νšŒλŠ” μΈμ’…μ˜ λ¬Έμ œμ— μžˆμ–΄μ„œ λ’·κ±ΈμŒμ§ˆ μΉ˜λŠ” λͺ¨μŠ΅μ„ 보이곀 ν–ˆλ‹€. 예λ₯Ό λ“€λ©΄, 적극적인 차별 철폐 μ‘°μ²˜κ°€ μ—­μ°¨λ³„μ΄λΌλŠ” 여둠이 ν˜•μ„±λ˜λ”λ‹ˆ 과거에 μ–΄λ ΅κ²Œ 일ꡬ어낸 μ œλ„μ μΈ μž₯μΉ˜λ“€μ΄ μ œκ±°λ˜μ—ˆλ‹€. ν•œνŽΈμ—μ„œλŠ” 인쒅차별을 μ–ΈκΈ‰ν•˜λŠ” 것 μžμ²΄κ°€ 마치 μ‹œλŒ€μ°©μ˜€μ μΈ λ°œμƒμΈ κ²ƒμœΌλ‘œ μΉ˜λΆ€λ˜μ—ˆλ‹€. 흑인은 μ—†κ³  미ꡭ인만이 μžˆμ„ λΏμ΄λΌλŠ” 이 μž…μž₯은, κ²‰μœΌλ‘œ λ“œλŸ¬λ‚˜λŠ” ν‰λ“±μ˜ λ…Όλ¦¬μ™€λŠ” λ‹€λ₯΄κ²Œ μ‚¬νšŒκ²½μ œμ  λΆˆν‰λ“±μ„ μ™Έλ©΄ λ˜λŠ” μ‹¬ν™”μ‹œν‚€λŠ” 효과λ₯Ό λ‚³κ³  μžˆμ—ˆλ‹€. λ‹‰νž νŒ” μ‹±μ˜ μ €μ„œλŠ” λ―Έκ΅­ ν‘μΈμ˜ μ €ν•­μ˜ 역사λ₯Ό μƒˆλ‘­κ²Œ μ‘°λͺ…ν•˜μ—¬ 90λ…„λŒ€λΆ€ν„° νŒ½λ°°ν•œ 인쒅적 μƒ‰λ§Ήμ˜ 논리에 일침을 κ°€ν•œλ‹€. 보닀 넓은 μ˜λ―Έμ—μ„œμ˜ 민주주의λ₯Ό μ΄λ£©ν•˜κ³ μž λ…Έλ ₯ν•΄μ˜¨ λ―Έκ΅­ ν‘μΈμ˜ μ—¬κ°€λŠ” 미ꡭ의 ꡭ가이념에 λΆ€ν•©ν•˜λŠ” λ°©μ‹μœΌλ‘œ μž¬ν•΄μ„λ˜κ³  νŽΈμž…λ˜μ–΄μ˜¨ κ²½ν–₯이 μžˆλ‹€. κ·Έ λŒ€ν‘œμ μΈ 예둜 20μ„ΈκΈ° μ€‘λ°˜μ˜ ν‘μΈλ―ΌκΆŒμš΄λ™μ„ λ“€ 수 μžˆλ‹€. ν‘μΈλ―ΌκΆŒ μš΄λ™μ— λŒ€ν•œ 보편적인 μ—­μ‚¬μ„œμˆ μ— λ”°λ₯΄λ©΄ μ΄λŠ” 1950λ…„λŒ€ μ€‘λ°˜μ— μ‹œμž‘λ˜μ–΄ 1960λ…„λŒ€ μ€‘λ°˜κΉŒμ§€ μ§€μ†λœ μ‚¬νšŒμš΄λ™μœΌλ‘œμ¨ λ―Έκ΅­ 남뢀에 λ‚¨μ•„μžˆλ˜ μ•…μŠ΅ 인쒅뢄리λ₯Ό μ² νν•˜λŠ” κ²°κ³Όλ₯Ό λ‚³μ•˜κ³  미ꡭ의 민주주의 μ •μ‹ μ˜ 승리λ₯Ό λ³΄μ—¬μ£ΌλŠ” 사건이닀. 더 λ‚˜μ•„κ°€ ν˜„μž¬ λ―Έκ΅­μ—λŠ” κ·Έ μ–΄λ– ν•œ 법적 μΈμ’…μ°¨λ³„λ‘œ μ‘΄μž¬ν•˜μ§€ μ•ŠμœΌλ©°, 미ꡭ은 λͺ¨λ“  μ‹œλ―Όμ΄ 본래의 μΆœμ‹ μ„ 버리고 미ꡭ인이 λ˜μ–΄ λ™λ“±ν•˜κ²Œ μ‚΄μ•„κ°€λŠ” μœ μΌλ¬΄μ΄ν•œ κ΅­κ°€λΌλŠ” 것이닀

    Linear proportional-integral control of turbulent channel ow for skin-friction reductionLinear proportional-integral control of turbulent channel ow for skin-friction reduction

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    ν•™μœ„λ…Όλ¬Έ (박사)-- μ„œμšΈλŒ€ν•™κ΅ λŒ€ν•™μ› : 기계항곡곡학뢀, 2015. 2. μ΅œν•΄μ²œ.In the present study, proportional (P) and proportional-integral (PI) feedback control methods are applied to a turbulent channel flow when ReΟ„ = 140 as a means of drag reduction. The control strategy comes from the opposition control method proposed by Choi, Moin & Kim (J. Fluid Mech., Vol. 262, 1994, pp. 75-110) which is a proportional control method with a fixed control gain. The wall-normal velocity at a sensing plane above the wall is measured as a sensing parameter, and blowing/suction is provided at the wall based on the control strategies. The performance of the control methods is investigated by the direct measurement of the drag in a direct numerical simulation while varying the sensing plane location y+ s , the proportional gain Ξ±, and the integral gain Ξ². For the P control, as ys+ increases, the drag decreases, reaches the minimum at an optimum sensing position and increases significantly. The effects of Ξ± are also investigated. As Ξ± increases the sensing velocity fluctuations decrease as 1/(1 + Ξ±), resulting in drag decreases. With smaller Ξ±, the amount of drag reduction becomes smaller while the range of ys+ reducing drag becomes wider. With large Ξ± (Ξ± > 1), the drag increases significantly. Thus, other control strategies, such as I control, are needed for more drag reduction. The PI control results in greater drag reduction than the P control when the sensing plane locates very close to the wall (ys+ < 10). The sensing velocity fluctuations, considered as an error in the control, approach zero with the PI control, while they do not go to zero with the P control. From the frequency spectra of sensing velocity fluctuations, it is found that the P control reduces the fluctuations at all frequency range, furthermore the I component of the control effectively reduces the sensing velocity fluctuations at low frequency range. The performance of the control methods is also investigated in a linearized flow model. From the frequency response of the system, it is found that the I component of the control effectively reduces the sensing velocity fluctuations at low frequency. Furthermore, the performance of control methods is investigated by testing the ability of suppressing the transient energy growth of disturbances in the linearized flow model. The variation of the maximum transient energy growth by the control methods in a linearized flow model is very similar to the drag variation in a turbulent channel flow. When the sensing plane locates very near the wall (ys+ 10), the maximum transient growth ratio increases significantly with the PI control. This indicates that the linearized flow model can be used as a guideline for control designs for drag reduction.Abstract Contents List of Figures Nomenclature Chapter 1 Introduction 2 Control methods 3 Flow control of turbulent channel flow 3.1 Introduction 3.2 Numerical method 3.3 Results and discussion 3.3.1 Proportional control 3.3.2 Proportional-Integral control control 3.4 Summaries 4 Flow control of Linearized flow model 4.1 Introduction 4.2 Mathematical formulations 4.2.1 Linearized Navier-Stokes equations 4.2.2 State-space representation 4.3 Transient energy growth of disturbances 4.4 Results and discussion 4.4.1 Eigenmodes of the linearized flow system 4.4.2 Frequency response 4.4.3 Transient energy growth of disturbances 4.5 Summaries 5 Summary and Conclusion References Appendix A Transient growth of disturbances in near-wall region of turbulent channel flow A.1 Introduction A.2 Mathematical formulations A.3 Results A.4 ConclusionsDocto

    Local Good Governance: A Research Framework

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    κ΅Ώ κ±°λ²„λ„ŒμŠ€μ— λŒ€ν•œ μ„ μ–Έμ οΌŒ λ‹Ήμœ„μ  μ£Όμž₯을 λ„˜μ–΄ κ³Όμ—° 무엇이 κ΅Ώ κ±°λ²„λ„ŒμŠ€μ΄κ³ οΌŒ μ–΄λ–»κ²Œ κ°κ΄€μ μœΌλ‘œ κ΅Ώ κ±°λ²„λ„ŒμŠ€μ˜ μ„±νŒ¨λ₯Ό κ°€λŠ ν•  수 있으며, μ–΄λ–€ 쑰건 ν•˜μ—μ„œ κ΅Ώ κ±°λ²„λ„ŒμŠ€κ°€ κ°€λŠ₯ν•œμ§€μ— λŒ€ν•œ 본격적인 μ—°κ΅¬λŠ” λΆ€μ‘±ν•˜λ‹€.01제 보닀 ꡬ체적, κ²½ν—˜μ  뢄석에 κΈ°μ΄ˆν•œ κ΅Ώ κ±°λ²„λ„ŒμŠ€ 연ꡬ가 ν•„μš”ν•œ 상황이닀 λ³Έ 논문은 μ΄λŸ¬ν•œ λ¬Έμ œμ˜μ‹ ν•˜μ— λ‘œν‚¬ κ±°λ²„λ„ŒμŠ€-즉 μ§€λ°©μžμΉ˜ μ°¨μ›μ˜ κ±°λ²„λ„ŒμŠ€-λ₯Ό λŒ€μƒμœΌλ‘œ κ΅Ώ κ±°λ²„λ„ŒμŠ€ 연ꡬλ₯Ό μœ„ν•œ 뢄석틀을 μ œμ‹œν•˜λŠ” 것을 λͺ©μ μœΌλ‘œ ν•˜κ³  μžˆλ‹€. 이λ₯Ό μœ„ν•˜μ—¬ μš°μ„  λ‘œν‚¬ κ±°λ²„λ„ŒμŠ€ κ΄€λ ¨ κ΅­λ‚΄μ™Έ 연ꡬ듀을 κ²€ν† ν•˜μ—¬ 둜컬 κ±°λ²„λ„ŒμŠ€μ˜ 기본적인 κ°œλ…κ³Ό μ£Όμž₯을 μ‚΄νŽ΄λ³΄κ³  κ΅Ώ κ±°λ²„λ„ŒμŠ€ μ§€ν‘œ κ΄€λ ¨κ΅­λ‚΄ κΈ°μ‘΄ 연ꡬ듀을 λΉ„νŒμ μœΌλ‘œ λΆ„μ„ν•˜κ³  μžˆλ‹€. μ΄λŸ¬ν•œ κΈ°μ‘΄ 연ꡬ에 λŒ€ν•œ 검토와 λΉ„νŒμ  뢄석에 κΈ°μ΄ˆν•˜μ—¬ 둜컬 κ΅Ώ κ±°λ²„λ„ŒμŠ€ 연ꡬλ₯Ό μœ„ν•œ λΆ„μ„νˆ΄οΌŒ κ΅Ώ κ±°λ²„λ„ŒμŠ€ μ§€ν‘œοΌŒ κΈ°μ€€οΌŒ κ°€μ΄λ“œλΌμΈ 및 가섀을 μ œμ‹œν•˜κ³  λ³Έ λ…Όλ¬Έμ˜ 둜컬 κ΅Ώ κ±°λ²„λ„ŒμŠ€ 뢄석틀을 ν•œκ΅­μ˜ 둜컬 κ±°λ²„λ„ŒμŠ€ κΈ°μ‘΄ 사둀에 재적용 ν•΄λ΄„μœΌλ‘œμ„œ κ·Έ μœ μš©μ„±μ„ μ˜ˆμ‹œν•˜κ³  결둠을 λ§Ίκ³  μžˆλ‹€. This paper proposes a research framework for the empirical analysis of good governance, particularly at the local level. It first reviews existing literature on local governance and discusses basic conceptual issues on local good governance. It then criticizes and sheds light on the limits of empirical studies on good governance indicators. It then provides an analytic framework on local good governance and key indicators, guidelines and hypotheses to be utilized for future empirical research. The finally illustrates the utility of the framework by applying it to two successful cases of local governance in South Korea.이 논문은 2008년도 μ •λΆ€μž¬μ›(κ΅μœ‘μΈμ μžμ›λΆ€ ν•™μˆ μ—°κ΅¬μ‘°μ„±μ‚¬μ—…)으둜 ν•œκ΅­ν•™μˆ μ§„ν₯μž¬λ‹¨μ˜ 지원을 λ°›μ•„ μ—°κ΅¬λ˜μ—ˆμŒ(KRF-2008-321-B00003

    Biochemical characterization of histone modifying enzymes

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    ν•™μœ„λ…Όλ¬Έ(석사)--μ„œμšΈλŒ€ν•™κ΅ λŒ€ν•™μ› :κ³Όν•™κ΅μœ‘κ³Ό 생물전곡,2007.Maste

    λΉ„μ„ ν˜• μœ ν•œ μš”μ†Œ 해석을 μœ„ν•œ λ“±κ°€ κ°•μ„± ν–‰λ ¬ 기법 기반의 νŒŒλΌλ©”νŠΈλ¦­ μΆ•μ†Œ λͺ¨λΈ

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    ν•™μœ„λ…Όλ¬Έ (박사)-- μ„œμšΈλŒ€ν•™κ΅ λŒ€ν•™μ› : 기계항곡곡학뢀, 2016. 8. 쑰맹효.κΈ°ν•˜ λΉ„μ„ ν˜• 및 재료 λΉ„μ„ ν˜• 거동을 κ³ λ €ν•œ ꡬ쑰 ν•΄μ„μ—μ„œ μ΅œμ’… λ³€ν˜•μ„ λ„μΆœν•˜κΈ° μœ„ν•΄μ„œλŠ”, λ‚΄λ ₯ 벑터와 κ°•μ„± 행렬을 반볡적으둜 λ„μΆœν•˜λ©° λ³€ν˜•μ„ κ°±μ‹ ν•΄ λ‚˜μ•„κ°€λŠ” 과정을 거쳐야 ν•œλ‹€. μ΄λŠ” λΉ„μ„ ν˜•μ„±μ„ κ³ λ €ν•œ 정적 및 동적 해석에 μžˆμ–΄μ„œ 계산 μ‹œκ°„μ΄ κΈ‰μ¦ν•˜λŠ” κΉŒλ‹­μ΄λ‹€. λ”°λΌμ„œ 효과적인 해석을 μœ„ν•˜μ—¬ λ‹€μ–‘ν•œ μΆ•μ†Œ λͺ¨λΈ 기법듀이 μ œμ•ˆλ˜μ–΄ μ™”μ§€λ§Œ κ·Έ νš¨μœ¨μ„±μ΄ 높지 μ•Šλ‹€. λ³΄ν†΅μ˜ μΆ•μ†Œ 기법은 각각 μ‹œμŠ€ν…œ ν–‰λ ¬μ˜ 크기λ₯Ό 쀄이고, 쀄어든 크기의 μ‹œμŠ€ν…œ 행렬을 톡해 효율적으둜 응닡을 λ„μΆœν•  수 μžˆλ„λ‘ ν•œλ‹€. 즉, μΆ•μ†Œ 기법을 μ μš©ν•˜κΈ° μœ„ν•΄μ„œλŠ” μ‹œμŠ€ν…œ 행렬을 미리 ꡬ좕해야 ν•˜λŠ” 것이닀. λΉ„μ„ ν˜• ν•΄μ„μ˜ 경우 λ³€ν˜•μ— 따라 μ‹œμŠ€ν…œ ν–‰λ ¬μ˜ ꡬ좕을 λ°˜λ³΅ν•΄μ•Ό ν•˜λ©°, 이에 μ†Œμš”λ˜λŠ” μ‹œκ°„μ΄ μƒλ‹Ήν•˜λ‹€. κ·ΈλŸ¬λ‚˜ 기쑴의 μΆ•μ†Œ 기법은 μ‹œμŠ€ν…œ 응닡 λ„μΆœκ³Ό κ΄€λ ¨λœ νš¨μœ¨μ„±λ§Œ 높이며, ν–‰λ ¬ ꡬ좕에 μ†Œμš”λ˜λŠ” μ‹œκ°„μ€ κ·ΈλŒ€λ‘œ λ‚¨λŠ”λ‹€. λ“±κ°€ κ°•μ„± ν–‰λ ¬ 기법(Stiffness Evaluation)을 ν™œμš©ν•˜λ©΄ λΉ„μ„ ν˜• μ‹œμŠ€ν…œ ν–‰λ ¬ κ΅¬μΆ•μ˜ νš¨μœ¨μ„±μ„ 높일 수 μžˆλ‹€. ν•΄λ‹Ή 기법은 λΉ„μ„ ν˜• μ‹œμŠ€ν…œμ˜ λ‚΄λ ₯ 벑터λ₯Ό λ‹€ν•­ν•¨μˆ˜λ₯Ό ν™œμš©ν•œ λ“±κ°€ λͺ¨λΈλ‘œ λ‚˜νƒ€λ‚Έλ‹€. 일단 ν•΄λ‹Ή λ‹€ν•­ν•¨μˆ˜μ˜ κ³„μˆ˜λ“€μ„ λ„μΆœν•΄ λ†“μœΌλ©΄, λ³€ν˜•μ˜ 갱신을 μ¦‰κ°μ μœΌλ‘œ κ³ λ €ν•˜μ—¬ λ‚΄λ ₯ 벑터와 κ°•μ„± 행렬을 계산할 수 μžˆμœΌλ―€λ‘œ ν–‰λ ¬ ꡬ좕에 μ†Œμš”λ˜λŠ” μ‹œκ°„μ„ 크게 쀄일 수 μžˆλ‹€. λ¬Έμ œλŠ” λ“±κ°€ λͺ¨λΈ ꡬ좕에 μ†Œμš”λ˜λŠ” μ‹œκ°„μ΄ μ‹œμŠ€ν…œ 크기의 3μŠΉμ— λΉ„λ‘€ν•˜μ—¬ λŠ˜μ–΄λ‚˜κΈ° λ•Œλ¬Έμ—, νš¨μœ¨μ μ΄μ§€ μ•Šλ‹€λŠ” 것이닀. λ³Έ μ—°κ΅¬μ—μ„œλŠ” μœ ν•œ μš”μ†Œμ˜ 연결성을 κ³ λ €ν•˜μ—¬ κ°œμ„ ν•œ μƒˆλ‘œμš΄ λ“±κ°€ κ°•μ„± ν–‰λ ¬ 기법(SEECStiffness Evaluation based on Element Connectivity)을 μ œμ•ˆν•œλ‹€. μœ ν•œ μš”μ†Œμ˜ 연결성을 μ΄μš©ν•˜λ©΄, λ‹€ν•­ν•¨μˆ˜μ˜ ꡬ성 및 ν•΄λ‹Ή κ³„μˆ˜λ“€μ˜ λ„μΆœμ„ ꡭ뢀적 및 λ³‘λ ¬μ μœΌλ‘œ 진행할 수 μžˆλ‹€. 적합직ꡐ뢄해법(PODProper Orthogonal Decomposition)을 ν™œμš©ν•œ μΆ•μ†Œ λͺ¨λΈ λ˜ν•œ μ—°λ™λ˜μ–΄ νš¨μœ¨μ„±μ„ 높인닀. λ“±κ°€ κ°•μ„± ν–‰λ ¬ κΈ°λ²•μ˜ κ³„μˆ˜λ“€μ„ μš”μ†Œ 연결성을 κ³ λ €ν•˜μ—¬ 효과적으둜 μ‚°μΆœν•œ λ’€, μΆ•μ†Œ 기법을 μ—°λ™ν•˜λ©΄ 정확도 및 νš¨μœ¨μ„±μ„ λ™μ‹œμ— 확보할 수 μžˆλ‹€. 이 μ œμ•ˆ 기법을 SEECROM으둜 μΉ­ν•œλ‹€. SEECROM은 각 μœ ν•œ μš”μ†Œμ˜ νŠΉμ„±μ„ ν™œμš©ν•˜μ—¬ κ΅­λΆ€μ μœΌλ‘œ κ΅¬μ„±λœλ‹€λŠ” νŠΉμ„±μ„ κ°–κΈ° λ•Œλ¬Έμ—, νŒŒλΌλ©”νŠΈλ¦­ κΈ°λ²•μ˜ 적용이 μš©μ΄ν•œ μž₯점도 κ°–λŠ”λ‹€. μ œμ•ˆ κΈ°λ²•μ˜ 효율 및 정확성은 κΈ°ν•˜ λΉ„μ„ ν˜•μ„±μ„ κ°€μ§€λŠ” μ‰˜ ꡬ쑰물의 동적 해석과 μ΄ˆνƒ„μ„± 재료λ₯Ό κ°€μ§€λŠ” λΉ„μ„ ν˜• ꡬ쑰의 정적/동적 해석에 μ μš©ν•˜μ—¬ κ²€μ¦ν•˜μ˜€λ‹€. μ œμ•ˆ 기법은 μœ μ—° 닀물체 동역학에도 μ μš©ν•  수 μžˆλ‹€. λ³΄ν†΅μ˜ μœ μ—° 닀물체 동역학은 μƒλŒ€ 절점 μ’Œν‘œκ³„λ₯Ό ν™œμš©ν•˜μ—¬ ν•΄μ„ν•˜λ©°, κ·Έ 경우 μ‹œμŠ€ν…œ ν–‰λ ¬μ˜ λΉ„μ„ ν˜•μ„±μ΄ κ°•μ„± 행렬이 μ•„λ‹Œ μ§ˆλŸ‰ 행렬에 λ‚˜νƒ€λ‚œλ‹€. κ΄€μ„±λ ₯κ³Ό κ΄€λ ¨ν•˜μ—¬ μΆ”κ°€λ˜λŠ” 행렬도 κ³ λ €ν•˜μ—¬μ•Ό ν•˜κΈ° λ•Œλ¬Έμ—, 동적 ꡬ쑰 해석을 기반으둜 개발된 μΆ•μ†Œ 기법을 μœ μ—° 닀물체 동역학 λ¬Έμ œμ— κ·ΈλŒ€λ‘œ ν™œμš©ν•˜κΈ°μ—λŠ” 어렀움이 μžˆλ‹€. μ ˆλŒ€ 절점 μ’Œν‘œκ³„λ₯Ό 기반으둜 ν•˜λŠ” ANCF(Absolute Nodal Coordinate Formulation) κΈ°λ²•μ˜ 경우, μœ ν•œ μš”μ†Œ 기법을 μ μš©ν•œ 지배 방정식이 λΉ„μ„ ν˜• 동적 ꡬ쑰 해석 λͺ¨λΈκ³Ό μœ μ‚¬ν•œ ν˜•μ‹μ„ κ°–λŠ”λ‹€. λ”°λΌμ„œ ANCF 기법을 ν™œμš©ν•˜λ©΄ ꡬ쑰 해석을 기반으둜 개발된 SEECROM을 μœ μ—° 닀물체 동역학에 μ μš©ν•  수 μžˆλ‹€. μ œμ•ˆ 기법과 νŒŒλΌλ©”νŠΈλ¦­ 기법을 4절 기ꡬλ₯Ό ν¬ν•¨ν•œ μ£Όμš”ν•œ μœ μ—° 닀물체 동역학 μ˜ˆμ œλ“€μ— μ μš©ν•˜κ³  κ·Έ νš¨μœ¨μ„±κ³Ό 정확성을 검증할 수 μžˆμ—ˆλ‹€. νŒŒλΌλ©”νŠΈλ¦­ 기법이 적용된 SEECROM은 λΉ„μ„ ν˜• μ‹œμŠ€ν…œ ꡬ쑰의 졜적 섀계 λ¬Έμ œμ—λ„ 적용이 μš©μ΄ν•˜λ‹€. ν˜„μž¬ λΉ„μ„ ν˜• μ‹œμŠ€ν…œμ˜ μΆ•μ†Œ 기법에 λŒ€ν•œ 연ꡬ가 진행 쀑인 단계라, 이λ₯Ό 졜적 섀계 λ¬Έμ œμ— μ μš©ν•˜λŠ” μ—°κ΅¬λŠ” 아직 ν™œλ°œν•˜μ§€ μ•Šμ€ 뢄야이닀. SEECROM은 λ‹€μ–‘ν•œ μ’…λ₯˜μ˜ λΉ„μ„ ν˜• μ‹œμŠ€ν…œμ„ 효율적으둜 μΆ•μ†Œν•˜λ©°, νŒŒλΌλ©”νŠΈλ¦­ κΈ°λ²•μ˜ 적용 λ˜ν•œ μœ μš©ν•˜κΈ°μ— μ•žμœΌλ‘œ λ‹€μ–‘ν•œ 졜적 섀계 문제λ₯Ό 효과적으둜 λ‹€λ£° 수 μžˆμ„ 것이라 μ˜ˆμƒλœλ‹€. λ³Έ μ—°κ΅¬μ—μ„œλŠ” λΉ„μ„ ν˜• 재료 거동을 κ°–λŠ” ꡬ쑰 μ‹œμŠ€ν…œκ³Ό 4절 기ꡬ의 μœ μ—° 닀물체 동역학 μ‹œμŠ€ν…œμ˜ ꡬ쑰 섀계 문제λ₯Ό 예제둜 λ“€μ–΄ μ œμ•ˆ κΈ°λ²•μ˜ 효과λ₯Ό κ²€μ¦ν•˜μ˜€λ‹€. μ œμ•ˆ 기법은 μš”μ†Œ 및 μ ˆμ μ„ 기반으둜 μˆ˜ν–‰λ˜λŠ” λ‹€μ–‘ν•œ λΉ„μ„ ν˜• λ¬Έμ œμ— 적용이 κ°€λŠ₯ν•  것이닀. λΉ„μ„ ν˜•μ„±μ„ κ°€μ§€λŠ” λŒ€ν˜• μ‹œμŠ€ν…œ, 닀물리 μ—°μ„± μ‹œμŠ€ν…œ, μƒμš© ν”„λ‘œκ·Έλž¨μ„ ν™œμš©ν•œ 효율적인 해석 및 μ„€κ³„λ‘œμ˜ ν™•μž₯이 κΈ°λŒ€λœλ‹€.To solve material/geometric nonlinear structural systems, iterative evaluation of internal forces and tangent stiffness matrices is required. This increases the computation time for nonlinear static/dynamic analysis. Although various reduced-order modeling techniques have been proposed to effectively solve nonlinear structural analysis problems, problems arise in the reduction of the system matrices. Since most reduction methods only reduce the system matrix after the stiffness and mass matrix construction process, the construction itself proceeds in full domain. In most cases of nonlinear analysis, the construction of system matrix takes a large amount of computation time, comparable to the computation time of the solving process. Although this problem can be tackled with STiffness Evaluation Procedure (STEP), which uses polynomial formulations to describe nonlinear internal forces, the construction time of the reduced model increases rapidly with the cubic power of the system size. In this paper, Stiffness Evaluation method based on Element Connectivity (SEEC) is proposed. The element connectivity of the finite element models is used to evaluate the nonlinear stiffness coefficients. The proposed method minimizes the effect of the system size when the computational model is constructed. In addition, the Reduced Order Modeling (ROM) technique using Proper Orthogonal Decomposition (POD) is applied to enhance the efficiency of the SEEC method, which is referred to as SEECROM. This enables effective analysis and design of large-scale problems. Moreover, SEECROM is easily characterized by design parameters. The parameterization is readily achieved with element-wise nature of the proposed method. SEECROM is successfully demonstrated for structural dynamic analysis of geometrically nonlinear shell structures under the perturbation of external loads. SEECROM-Parameterization is also successfully demonstrated for static and dynamic analysis of hyperelastic materials that have material and geometric nonlinearities. In the case of flexible multibody systems, nonlinearities are caused by the rigid motions of the structure rather than the deformation of the flexible parts. Since the approaches to the multibody dynamics are different from the structural dynamics, the reduction methods which have been developed for the structural analyses cannot be utilized in direct manner. However, this can be achieved with the aid of Absolute Nodal Coordinate Formulation (ANCF), which takes the analogous format to the governing finite element formulation of structural dynamics. SEECROM method is combined to ANCF to form an efficient reduced model of the flexible multibody system. A number of examples are provided for the verification of the proposed reduction method and its parameterization. For the application to the optimization of nonlinear structures, it is vital that reduced order models be efficiently parameterized for the design parameters. SEECROM-Parameterization fits easily to the optimization problems concerning nonlinear systems. To show the validity of the proposed methodology, two sample optimization problems are subjected to a static structural system with a hyperelastic material and a multibody dynamic system.1. INTRODUCTION 1 2. STIFFNESS EVALUATION 6 2.1. Stiffness Evaluation Methods 6 2.2. Stiffness Evaluation Methods with Reduced-Order Modeling 9 3. STIFFNESS EVALUATION BASED ON ELEMENT CONNECTIVITY 11 3.1. Determination of Displacement Combination 11 3.2. Evaluation of Stiffness Coefficients 14 3.2.1. Sampling 14 3.2.2. Minimum Norm Least Squares 16 3.3. Computation of Tangent Stiffness 20 4. REDUCED ORDER MODELING USING SEEC 25 4.1. Proper Orthogonal Decomposition 26 4.2. Proper Orthogonal Decomposition with SEEC 27 4.3. Application of SEECROM 28 5. PARAMETERIZATION BASED ON SEECROM 39 5.1. Parameterization Strategy of SEECROM 39 5.2. Application of SEECROM-Parameterization 42 5.2.1. Static Analysis of Neo-Hookean Hyperelastic Material 43 5.2.2. Dynamic Analysis of Neo-Hookean Hyperelastic Material 44 6. APPLICATION TO MULTIBODY DYNAMICS 53 6.1. Motivation 53 6.2. ANCF Formulations 57 6.3. Reduced-Order Modeling of ANCF Model with SEECROM 60 6.3.1. Application of SEECROM to ANCF Beam Elements 60 6.3.2. Application of SEECROM 61 6.4. Parameterization of ANCF model with SEECROM 66 6.4.1. Parameterization Strategy of SEECROM 66 6.4.2. Application of SEECROM-Parameterization 67 7. APPLICATION TO OPTIMIZATION PROCESS 95 7.1. Motivation 95 7.2. Optimization of nonlinear system 98 7.3. SEECROM-Parameterization for optimization of nonlinear system 100 7.3.1. Optimization procedure using SEECROM-Parameterization 100 7.3.2. Numerical examples 105 8. CONCLUSIONS 133 REFERENCES 135 APPENDIX A 139 κ΅­λ¬Έ μš”μ•½ 145Docto

    Emily Dickinsons Changing Poetics Eui

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    λ³Έκ³ λŠ” 에밀리 λ””ν‚¨μŠ¨μ˜ μœ‘ν•„μ›κ³  μ—°κ΅¬μ˜ μ„±κ³Όλ₯Ό μ κ²€ν•˜κ³  κ·Έ μ„±κ³Όλ₯Ό 기반으둜 λ””ν‚¨μŠ¨μ˜ μ‹œν•™μ„ μƒˆλ‘­κ²Œ μ‘°λͺ…ν•œλ‹€. 기쑴의 λ””ν‚¨μŠ¨ μ—°κ΅¬μžλ“€μ€ λ””ν‚¨μŠ¨μ˜ μ›κ³ λ¬ΆμŒμ„ 졜고의 μ„±μ·¨λ‘œ ν‰κ°€ν–ˆλ‹€. κ·ΈλŸ¬λ‚˜ μœ‘ν•„μ›κ³  μ—°κ΅¬λŠ” λ””ν‚¨μŠ¨μ˜ μ°½μž‘κΈ°λ²•μ΄ μ΅œμ†Œν•œ μ„Έ 단계λ₯Ό 거치며 λ³€ν™”ν–ˆμŒμ„ μ‹€μ¦μ μœΌλ‘œ λ„μΆœν–ˆλ‹€. 이λ₯Ό 근거둜 λ””ν‚¨μŠ¨μ˜ μ‹œν•™λ„ λ³€ν™”ν–ˆμŒμ„ μ§μž‘ν•  수 μžˆμœΌλ‚˜, μœ‘ν•„μ›κ³  μ—°κ΅¬μžλ“€μ€ 싀증적 방법둠에 치우쳐 μ›κ³ μ˜ λ¬Όμ§ˆμ„±κ³Ό μ‹œμ  의미λ₯Ό μ—°λ™ν•˜λ €λŠ” λ…Έλ ₯이 λΆ€μ‘±ν•˜λ‹€. λ””ν‚¨μŠ¨μ˜ μ‹œν•™μ€ μ›€μ§μ΄λŠ” κ²ƒμ΄λΌλŠ” μ „μ œ ν•˜μ— λ³Έκ³ λŠ” ꡬ체적인 사둀λ₯Ό λΆ„μ„ν•˜μ—¬ μœ‘ν•„μ›κ³ μ˜ 물질적 νŠΉμ„±μ΄ μ‹œμ  의미λ₯Ό κ°•ν™”ν•˜κ³  λ•Œλ‘œλŠ” λ³€μ§ˆν•˜λŠ” 방식을 μΆ”μ ν•œλ‹€. μš°μ„  λ””ν‚¨μŠ¨μ΄ 원고λ₯Ό λ¬ΆλŠ” ν–‰μœ„λ₯Ό ν¬κΈ°ν•œ κ³Όλ„κΈ°μ˜ 증폭된 μžμ˜μ‹μ„ μ‘°λͺ…ν•œλ‹€. κ°œλ³„ μ‹œλŠ” μ‹œν€€μŠ€λ‘œλΆ€ν„° ν’€λ €λ‚¨μœΌλ‘œμ¨ μƒˆλ‘œμš΄ 미학적 κ°€λŠ₯성을 λͺ¨μƒ‰ν•˜κ²Œ λœλ‹€. κ·Έ λ‹€μŒ λ‹¨κ³„μ—μ„œ λ””ν‚¨μŠ¨μ€ μΌμƒμ—μ„œ λ°œμƒν•˜λŠ” μ’…μž‡μ‘°κ°μ— μ‹œμƒμ„ μ μ—ˆλŠ”λ°, 이 원고에 λŒ€ν•œ 기쑴의 ν‰κ°€λŠ” 맀우 뢀정적이닀. κ·ΈλŸ¬λ‚˜ λ³Έκ³ λŠ” 이 μ‹œκΈ°μ˜ λ””ν‚¨μŠ¨ μ›κ³ μ—μ„œ 완성에 λŒ€ν•œ μ˜μ‹μ μΈ κ±°λΆ€λ₯Ό 읽어내고, ν›„κΈ° μ‹œν•™μ„ νƒˆλ§₯락화에 λŒ€ν•œ μ™„κ°•ν•œ μ €ν•­μœΌλ‘œ ν•΄μ„ν•œλ‹€. ν•΄μ²΄ν•œ νŽΈμ§€λ΄‰νˆ¬μ— λ””ν‚¨μŠ¨μ΄ 남긴 글은 100년이 μ§€λ‚œ μ˜€λŠ˜λ‚ μ—λ„ νŽΈμ§€λ΄‰νˆ¬μ˜ λͺ¨μŠ΅μœΌλ‘œ λ…μž μ•žμ— λͺ¨μŠ΅μ„ λ“œλŸ¬λƒ„μœΌλ‘œμ¨ λ””ν‚¨μŠ¨μ˜ 미학적 μ „λž΅μ˜ μœ„λ ₯을 λ°©μ¦ν•œλ‹€. 결둠적으둜 λ³Έ 연ꡬ가 μ£Όμž₯ν•˜λŠ” λ°”λŠ” κΈ°μ‘΄ 독법을 νŒŒκΈ°ν•΄μ•Ό ν•œλ‹€λŠ” 것도 μ•„λ‹ˆκ³  λͺ¨λ“  λ””ν‚¨μŠ¨ ν•™μžκ°€ μ•„μΉ΄μ΄λΈŒλ‘œ ν–₯ν•΄μ•Ό ν•œλ‹€λŠ” 것도 μ•„λ‹ˆλ‹€. 두 μ§„μ˜μ΄ ν˜‘λ ₯ν•  λ•Œ λΉ„λ‘œμ†Œ 싀증적 증거가 μœ μ˜λ―Έν•œ ν•΄μ„μœΌλ‘œ 이어져 λ””ν‚¨μŠ¨μ˜ μ‹œμ„Έκ³„λ₯Ό μ‘°λͺ…ν•˜λŠ” 톡합적인 μž‘μ—…μ΄ κ°€λŠ₯ν•  것이닀.This essay challenges the idea that Emily Dickinsons fascicles represent a highpoint in her poetic creativity. Scholars who have studied Dickinsons manuscripts have uncovered the full trajectory of Dickinsons changing poetics. After producing forty fascicles, Dickinson gradually stopped binding the sheets of stationery on which she had transcribed her poems. Understanding this as a conscious aesthetic decision sheds new light on Dickinsons post-fascicle writing. The unbound bifolum sheets of the middle period reveal Dickinsons acute self-consciousness about her decision not to bind her poems. Poems from this period show that Dickinson was fascinated by the aesthetic possibilities and challenges presented by not binding her poems. In the final decade of her life, Dickinson dispensed with formal stationery altogether, electing to write on scrap pieces of paper. This phase of her writing is understudied because the critical consensus until recent years has been that these scraps are not quite poems. By examining two envelope poems, this essay reveals that Dickinson worked against the possibilities of abstraction and transference by refusing to finish her poems. In this final stage, her experimentation extended to include the very material on which she wrote. This essay concludes that the findings of Dickinson manuscript studies need to be embraced by scholars to appreciate the full scope of Dickinsons creative practice and to gain a contextualized understanding of individual poems

    Purification and Characterization of Ξ²-Glucosidase from Seeds of Pumpkin (Cucurbita moschata)

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    ν•™μœ„λ…Όλ¬Έ (석사)-- μ„œμšΈλŒ€ν•™κ΅ λŒ€ν•™μ› : 농생λͺ…곡학뢀(μ‹ν’ˆμƒλͺ…곡학전곡), 2013. 2. μž₯νŒμ‹.The objective of this study was purification and characterization of Ξ²-glucosidase (EC 3.2.1.21), catalyzing the hydrolysis of Ξ²-glucosidic bonds, from Pumpkin seed (Cucurbita moschata). The Ξ²-glucosidase was purified by fast protein liquid chromatography using Hitrap DEAE-sepharose FF, Hitrap Q-sepharose XL, and HiPrep 16/60 Sephacryl S-100 Hiresolution column. The 8.24-fold purified enzyme had a specific activity of 16.62x10^(-2) unit/mg protein against p-nitrophenyl-Ξ²-D-glucopyranoside (pNPG). Sodium dodecyl sulfate-polyacrylamide gel electrophoretic (SDS-PAGE) analysis showed Ξ²-glucosidase from pumpkin seed was dimeric structure with molecular mass of 48.1 kDa, the sum of 28.8 and 19.3 kDa. The molecular mass estimated by SDS-PAGE was analogous with that of 42.8 kDa estimated by gel permeation chromatography using Sephacryl S-100 Hiresolution column. The optimum temperature and pH of the enzyme were 70Β°C and pH 4.0, respectively. The enzyme was stable in the range of pH 2.0 to 10.0 and under 60Β°C, respectively. The Km, Vmax, and kcat of Ξ²-glucosidase employing p-nitrophenyl-Ξ²-D-glucopyranoside (pNPG) as substrate were 2.22 mM, 0.078 unit/mg protein, and 13.29 min^(-1), respectively. From the result of zymogram analysis, the enzyme had the activity in the condition not that subunits were departed but that subunits were associated. It was composed of 364 amino acids, and the secondary structure of Ξ²-glucosidase from seeds of pumpkin (Cucurbita moschata) consists of Ξ±-helix (26.10%), antiparallel Ξ²-sheet (20.17%), parallel Ξ²-sheet (8.22%), Ξ²-turn (18.16%), and random coil (27.34%) in the stable condition and it was affected by temperature and pH. There is a possibility that the enzyme have the characteristics of pH reversible inactivation according to the study of the effect on the enzyme activity and stability. The purified Ξ²-glucosidase could cleave Ξ²-glucosidic bonds in phytochemicals and enhance the bioavailability of phytochemicals. Moreover, it was found that pumpkin seed-derived Ξ²-glucosidase has exceptional stability at wide range of pH in pre-experiment. Therefore the purified Ξ²-glucosidase could be applied to the food industry and pharmaceutical industry.1. Introduction 1 2. Materials and Methods 5 2-1. Materials 5 2-2. Preparation of crude enzyme 6 2-3. Purification using fast protein liquid chromatography 7 2-4. Analysis of Ξ²-glucosidase activity and protein concentration 9 2-5. Polyacrylamide gel electrophoresis 11 2-6. Determine of molecular mass 12 2-7. Effects of temperature and pH on the enzyme 12 2-8. Enzyme kinetics 13 2-9. Zymography 14 2-10. Amino acid analysis 14 2-11. Circular dichroism 15 3. Results and Discussion 17 3-1. Purification of Ξ²-glucosidase seeds of pumpkin (Cucurbita moschata) 17 3-2. Characterization of Ξ²-glucosidase from seeds of pumpkin (Cucurbita moschata) 22 3-2-1. Determination of molecular mass 22 3-2-2. Effects of pH and temperature on the enzyme 24 3-2-3. Enzyme kinetics 30 3-3. Effects of interaction between subunits on the enzyme activity 32 3-4. Structural characteristics of Ξ²-glucosidase from seeds of pumpkin (Cucurbita moschata) 35 4. Conclusion 42 5. References 44 ꡭ문초둝 47Maste

    "It ain`t yo` fault, huck" : the limits of intention in adventures of Huckleberry Finn

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    Thesis (master`s)--μ„œμšΈλŒ€ν•™κ΅ λŒ€ν•™μ› :μ˜μ–΄μ˜λ¬Έν•™κ³Ό 문학전곡,2003.Maste
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