63 research outputs found

    μ΄μ€‘μ—λ„ˆμ§€ μ „μ‚°ν™”λ‹¨μΈ΅μ΄¬μ˜μˆ μ„ μ΄μš©ν•œ μš”μ˜€λ“œ μ •λŸ‰ν™”: μΈ‘μ • 변이에 κ΄€ν•œ 인자 탐색, μΈ‘μ • λ³€μ΄μ˜ λ²”μœ„ 계산 및 μž„μƒμ  검증

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    ν•™μœ„λ…Όλ¬Έ (박사)-- μ„œμšΈλŒ€ν•™κ΅ λŒ€ν•™μ› : μ˜κ³ΌλŒ€ν•™ μ˜ν•™κ³Ό, 2019. 2. ꡬ진λͺ¨.μ„œλ‘ : 이 μ—°κ΅¬λŠ” μ΄μ€‘μ—λ„ˆμ§€ μ „μ‚°ν™”λ‹¨μΈ΅μ΄¬μ˜μˆ μ„(CT) ν†΅ν•œ μš”μ˜€λ“œ μ •λŸ‰ν™”μ— μ΄μ€‘μ—λ„ˆμ§€ CT μŠ€μΊλ„ˆ, μ˜μƒ νšλ“ νŒŒλΌλ―Έν„°, 그리고 앑체 성상이 λ―ΈμΉ˜λŠ” 영ν–₯을 λΆ„μ„ν•˜κ³ , μΈ‘μ • λ³€μ΄μ˜ λ²”μœ„(measurement variability)λ₯Ό 계산 및 μž„μƒμ μœΌλ‘œ κ²€μ¦ν•˜κ³ μž ν•˜μ˜€λ‹€. 방법: Part Iκ³Ό IIμ—μ„œλŠ” 쒅격동 νŒ¬ν…€μ„ μŠ€μΊ”ν•˜κ³ , μš”μ˜€λ“œ 밀도λ₯Ό(iodine density) μΈ‘μ •ν•˜μ—¬, μ΄μ€‘μ—λ„ˆμ§€ CT μŠ€μΊλ„ˆμ™€ μ˜μƒ νšλ“ νŒŒλΌλ―Έν„°, 앑체 μ„±μƒμ˜ 영ν–₯을 linear-mixed effect model둜 λΆ„μ„ν•˜μ˜€λ‹€. μš”μ˜€λ“œ λ°€λ„μ˜ μΈ‘μ • 변이 λ²”μœ„ λ˜ν•œ κ³„μ‚°ν•˜μ˜€λ‹€. Part IIIμ—μ„œλŠ” μš”μ˜€λ“œ μ •λŸ‰ν™”μ˜ 변이 λ²”μœ„λ₯Ό 톡해 얻은 μ°Έμ‘°μ˜μ¦κ°• κΈ°μ€€κ°’μ˜(cutoff) μž„μƒμ  μœ μš©μ„±μ„ κ°€μŠ΄μƒ˜μ’…κ³Ό κ°€μŠ΄μƒ˜ λ‚­μ’…μœΌλ‘œ 수술적 치료λ₯Ό 받은 ν™˜μž-λŒ€μ‘°κ΅° 연ꡬλ₯Ό 톡해 ν›„ν–₯적으둜 κ²€μ¦ν•˜μ˜€λ‹€. κ²°κ³Ό: Part Iμ—μ„œ μš”μ˜€λ“œ λ°€λ„μ˜ μ ˆλŒ€μ˜€μ°¨λŠ” μ΄μ€‘μ—λ„ˆμ§€ CT μŠ€μΊλ„ˆ λ˜λŠ” 앑체 성상에 영ν–₯을 받지 μ•Šμ•˜λ‹€(P>0.05). μš”μ˜€λ“œ 참값이 0 mg/ml인 경우, 변이 λ²”μœ„λŠ” -0.6 mg/mlμ—μ„œ 0.4 mg/mlμ˜€μœΌλ©°, λ”°λΌμ„œ μ°Έμ‘°μ˜μ¦κ°•μ˜ 기쀀값은 0.4 mg/ml둜 μ •μ˜ν•˜μ˜€λ‹€. Part IIμ—μ„œ κ΄€μ „μ••κ³Ό(P<0.001) κ΄€μ „λ₯˜(P<0.05κ΅ν˜Έμž‘μš© λ³€μˆ˜μ— 따라 P 값에 차이가 있음)λŠ” μš”μ˜€λ“œ μ •λŸ‰κ°’μ— μœ μ˜ν•œ 영ν–₯이 μžˆμ—ˆμœΌλ‚˜, κ·Έ 영ν–₯의 크기, 즉, νšŒκ·€κ³„μˆ˜μ˜ μ ˆλŒ€κ°’μ€ 맀우 μž‘μ•˜λ‹€. μš”μ˜€λ“œλ₯Ό ν¬μ„ν•œ 용맀의 성상 μ—­μ‹œ μœ μ˜ν•œ 영ν–₯이 μžˆμ—ˆμœΌλ©°(P=0.007), λ¬Όκ³Ό μ•„λ―Έλ…Έμ‚° μš©μ•‘ κ°„μ˜ μ΅œμ†Œμ œκ³±ν‰κ· μ˜ μ°¨λŠ” β‰₯5 mg/ml의 농도λ₯Ό κ°–λŠ” νŠœλΈŒμ— λŒ€ν•΄μ„œλŠ” 0.1μ—μ„œ 0.3 mg/mlμ˜€μœΌλ©°, ≀1 mg/ml의 농도λ₯Ό κ°–λŠ” νŠœλΈŒμ—μ„œλŠ” -0.4μ—μ„œ -0.1 mg/mlμ˜€λ‹€. λ³€μˆ˜ 쀑 μŠ€νŽ™νŠΈλŸ΄ λ ˆλ²¨μ€ 츑정에 영ν–₯을 λ―ΈμΉ˜μ§€ μ•Šμ•˜λ‹€ (P=0.647). Part IIIμ—μ„œ μ°Έμ‘°μ˜μ¦κ°• 기쀀값은(0.4 mg/ml) ν™˜μž-λŒ€μ‘°κ΅° μ—°κ΅¬μ—μ„œ κ°€μŠ΄μƒ˜μ’…κ³Ό κ°€μŠ΄μƒ˜ 낭쒅을 κ΅¬λΆ„ν•˜λŠ”λ° μžˆμ–΄ 민감도 100%, νŠΉμ΄λ„ 85.7%, 정확도 90.9%, μ–‘μ„± 예츑λ₯  80.0%, μŒμ„± 예츑λ₯  100%λ₯Ό λ³΄μ˜€λ‹€. κ²°λ‘ : μš”μ˜€λ“œ λ°€λ„λŠ” μ΄μ’…μ—λ„ˆμ§€ CT μ΄¬μ˜κΈ°κ³„μ— 영ν–₯을 받지 μ•ŠλŠ” 츑정값이닀. μš”μ˜€λ“œ λ°€λ„λŠ” CT νšλ“ λ³€μˆ˜μ— μœ μ˜ν•œ 영ν–₯을 λ°›μœΌλ‚˜, 진단적 CT의 λ²”μœ„ λ‚΄μ—μ„œ κ·Έ 영ν–₯의 μ •λ„λŠ” λ―Έλ―Έν•˜λ‹€. μ°Έμ‘°μ˜μ¦κ°• μš”μ˜€λ“œ 밀도 기쀀값은(0.4 mg/ml) κ°€μŠ΄μƒ˜μ’…κ³Ό κ°€μŠ΄μƒ˜ 낭쒅을 μ •ν™•ν•˜κ²Œ ꡬ뢄할 수 μžˆλŠ” μœ μš©ν•œ νŒŒλΌλ―Έν„°μ΄λ‹€.Purpose: To analyze the effect of dual-energy computed tomography (DECT) scanners, acquisition parameters, and fluid characteristics on iodine quantification and to calculate and validate the measurement variability range induced by those variables. Methods: In Part I and II, experimental studies were performed using four mediastinal iodine phantoms. Phantoms were scanned with three different DECT scanners from major vendors using various acquisition parameters and their effects on the measurement of iodine density (IoD) were investigated using linear mixed-effect models. Measurement variability range of IoD was also calculated. In Part III, diagnostic usefulness of the true enhancement cutoff was retrospectively validated in patients who underwent surgical resections for thymic cysts and thymic epithelial tumors. Results: In Part I, absolute error of IoD was not significantly affected by the DECT systems and kind of solvents (P>0.05). Measurement variability range was from -0.6 to 0.4 mg/ml for the true iodine concentration 0 mg/ml. In Part II, tube voltage (P<0.001) and tube current-time product (P<0.05, depending on the interaction terms) had statistically significant effects on IoD. However, the magnitude of their effects was minimal in the range of diagnostic CT scans. Solvents also had significant effects on IoD (P=0.007). Specifically, the difference of least squares means between water and amino acid solution ranged from 0.1 to 0.3 for tubes with iodine concentrations β‰₯5 mg/ml and from -0.4 to -0.1 mg/ml for tubes with iodine concentrations ≀1 mg/ml. Spectral level was not an affecting factor (P=0.647). In Part III, the true enhancement cutoff for IoD, which was 0.4 mg/ml, exhibited diagnostic sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of 100%, 85.7%, 90.9%, 80.0%, and 100%, respectively, for the differentiation of thymic epithelial tumors from thymic cysts. Conclusions: IoD measurement is robust to the DECT scanners from different vendors. IoD is significantly affected by the acquisition parameters, but the magnitude of effects are minimal in the range of diagnostic CT scans. The true enhancement cutoff of 0.4 mg/ml is an accurate parameter for the differentiation of thymic epithelial tumors from thymic cysts.Abstract i Contents iv List of tables and figures v List of Abbreviations vi Introduction 1 Part I. Materials and Methods 4 Part I. Results 14 Part II. Materials and Methods 30 Part II. Results 36 Part III. Materials and Methods 45 Part III. Results 51 Discussion 54 References 65 Abstract in Korean 74Docto

    μ§€λ°©λŒ€λ„μ‹œ λ„μ‹¬μ˜ κΈ°λŠ₯ν™œμ„±ν™”μ™€ μΎŒμ μ„±μ œκ³  λ°©μ•ˆ(A study on the revitalization of activities and the amenities in urban center)

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    λ…ΈνŠΈ : 이 μ—°κ΅¬λ³΄κ³ μ„œμ˜ λ‚΄μš©μ€ κ΅­ν† μ—°κ΅¬μ›μ˜ 자체 μ—°κ΅¬λ¬Όλ‘œμ„œ μ •λΆ€μ˜ μ •μ±…μ΄λ‚˜ κ²¬ν•΄μ™€λŠ” μƒκ΄€μ—†μŠ΅λ‹ˆλ‹€

    곡곡기관 μ§€λ°©μ΄μ „μ‹œμ±…μ˜ 좔진과정 연ꡬ(A study on the regional relocation policy of public agency in capital region)

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    λ…ΈνŠΈ : 이 μ—°κ΅¬λ³΄κ³ μ„œμ˜ λ‚΄μš©μ€ κ΅­ν† μ—°κ΅¬μ›μ˜ 자체 μ—°κ΅¬λ¬Όλ‘œμ„œ μ •λΆ€μ˜ μ •μ±…μ΄λ‚˜ κ²¬ν•΄μ™€λŠ” μƒκ΄€μ—†μŠ΅λ‹ˆλ‹€

    μ§€λ°©μ€‘μ†Œλ„μ‹œ ν™œμ„±ν™” λ°©μ•ˆ 연ꡬ(A study on the revitalization strategy of local small-medium-sized cities)

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    λ…ΈνŠΈ : 이 μ—°κ΅¬λ³΄κ³ μ„œμ˜ λ‚΄μš©μ€ κ΅­ν† μ—°κ΅¬μ›μ˜ 자체 μ—°κ΅¬λ¬Όλ‘œμ„œ μ •λΆ€μ˜ μ •μ±…μ΄λ‚˜ κ²¬ν•΄μ™€λŠ” μƒκ΄€μ—†μŠ΅λ‹ˆλ‹€

    μœ λ™ μ œμ–΄λ₯Ό μœ„ν•œ λ‚˜λ…Έμ„Έμ»¨λ“œ νŽ„μŠ€ DBD ν”ŒλΌμ¦ˆλ§ˆ 앑츄에이터 λͺ¨λΈλ§

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    ν•™μœ„λ…Όλ¬Έ (석사)-- μ„œμšΈλŒ€ν•™κ΅ λŒ€ν•™μ› : 기계항곡곡학뢀, 2016. 2. κΉ€κ·œν™.In the present study, a model of dielectric barrier discharge (DBD) driven by nanosecond pulse was developed for flow control analysis. In general, computational analysis of DBD requires to solve Gausss law for electric field, chemical species continuity equation for plasma including electron, positive ions, negative ions, neutral particles and Navier-Stokes equation for fluid. Considering all these governing equations makes computational cost enormously expensive due to their time scale difference. By using quasi-1-dimensional self-similar equation of DBD plasma, the time cost for plasma analysis was reduced dramatically and plasma parameters such as plasma propagation distance, electric field, electron density and joule heating energy can be calculated. The obtained joule heating energy is then utilized to construct a model of dissipating unsteady energy source into fluid by plasma. The model reflected the increase/decrease of the joule heating energy arise from the physical phenomena of electrical current variations during a pulse period. The obtained unsteady energy source term was coupled with Navier-Stokes equation to analyze the flow disturbances made by DBD actuator which produces propagating micro compression wave. The time-varying position of compression wave generated by DBD plasma actuator predicted by developed model was in agreement with previously reported data from experimental and computational analysis. Also, the developed model was able to predict compression wave propagation due to DBD plasma more accurately compared to a model which used steady energy source term.Chapter 1. Introduction 1 1.1 Motivation 1 1.2 Dielectric Barrier Discharge (DBD) Plasma Actuator 3 Chapter 2. DBD Plasma Actuator Model 7 2.1 Plasma Governing Equation 7 2.2 Quasi 1 Dimensional Self Similar Equation 11 2.3 Unsteady Joule Heating Energy Modeling 13 Chapter 3. Numerical Method 17 3.1 Fluid Governing Equation 17 3.2 Spatial Discretization 19 3.3 Time Integration 22 Chapter 4. Numerical Analysis 27 4.1 Geometry and Grid System 27 4.2 Boundary and Initial Conditions 29 4.3 Results 32 Chapter 5. Conclusions 44 Chapter 6. References 45 κ΅­λ¬Έ 초둝 48Maste

    주거지역 κ°œλ°œλ°€λ„ μ„€μ •λ°©μ•ˆμ— κ΄€ν•œ 연ꡬ(Planning guidance on residential density criteria)

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    λ…ΈνŠΈ : 이 μ—°κ΅¬λ³΄κ³ μ„œμ˜ λ‚΄μš©μ€ κ΅­ν† μ—°κ΅¬μ›μ˜ 자체 μ—°κ΅¬λ¬Όλ‘œμ„œ μ •λΆ€μ˜ μ •μ±…μ΄λ‚˜ κ²¬ν•΄μ™€λŠ” μƒκ΄€μ—†μŠ΅λ‹ˆλ‹€

    μŠ€ν…Œκ±°λ“œ 카이럴 κ±΄λ“€μž„ 이둠을 μ΄μš©ν•œ NLOμ—μ„œμ˜ 파이온 μ§ˆλŸ‰ 계산

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    In part I, we calculate the masses of taste non-Goldstone pions and kaons in staggered chiral perturbation theory through next-to-leading order in the standard power counting. The results can be used to quantitatively understand taste violations in existing lattice data generated with staggered fermions and to extract the u, d, and s quark masses and Gasser-Leutwyler parameters from the experimentally observed spectrum. The expressions for the non-Goldstone masses contain low-energy couplings unique to the non-Goldstone sector. With two exceptions these enter as coefficients of analytic terms; all the new couplings can be fixed by performing spectrum calculations. We report one-loop results for the quenched case and the fully dynamical and partially quenched 1+1+1 and 2+1 flavor cases in the chiral SU(3) and SU(2) theories. In part II, We show the know-how of GPU based supercomputer from the beginning. and also illustrate our GPU version of conjugate gradient solver. To chieve the maximum performance in the program, we implement many different optimization method. The overall performance of our CUDA code for CG is 145 giga flops per GPU (GTX480), which does not include the infiniband network communication. If we include the infiniband communication, the overall performance is 36 giga flops per GPU (GTX480).첫번째 λ‹¨μ›μ—μ„œλŠ” λΉ„-κ³¨λ“œμŠ€ν†€ 파이온과 μΌ€μ΄μ˜¨μ˜ μ§ˆλŸ‰μ„ μŠ€ν…Œκ±°λ“œ μΉ΄μ΄λž„ κ±΄λ“€μž„ 이둠으둜 NLOκΉŒμ§€ 계산을 μˆ˜ν–‰ν•˜μ˜€λ‹€. 이 κ²°κ³ΌλŠ” μŠ€ν…Œκ±°λ“œ 페λ₯΄λ―Έμ˜¨μ„ μ΄μš©ν•œ 격자 κ²Œμ΄μ§€ 이둠 μ—°κ΅¬μ—μ„œ λ°œμƒν•˜λŠ” ν…Œμ΄μŠ€νŠΈ λŒ€μΉ­μ„±μ˜ μœ„λ°˜ 정도λ₯Ό μ΄ν•΄ν•˜λŠ”λ° μ€‘μš”ν•œ μžλ£Œλ‘œμ„œ μ‚¬μš©λœλ‹€. λ˜ν•œ μ—…, λ‹€μš΄, μŠ€νŠΈλ ˆμΈμ§€ 쿼크의 μ§ˆλŸ‰μˆ˜ κ³„μ‚°μ΄λ‚˜ Gasser-Leutwyler κ³„μˆ˜λ₯Ό κ²°μ •ν•˜λŠ”λ°μ—λ„ μ‚¬μš©λ˜μ–΄ 질 수 μžˆλ‹€. ν”Œλ ˆμ΄λ²„ SU(3) 와 SU(2) λŒ€μΉ­μ„± ν•˜μ—μ„œ 세가지(quenched, fully dynamical, partially quenched)의 λ‹€λ₯Έ κ²½μš°μ— λŒ€ν•œ 일차 μ–‘μž 고리 값을 κ³„μ‚°ν•˜μ—¬ λ‚˜νƒ€λ‚΄μ—ˆλ‹€. λ‘λ²ˆμ§Έ λ‹¨μ›μ—μ„œλŠ”, GPU 기반의 μŠˆνΌμ»΄ν“¨ν„° μ œμž‘κ³Όμ •μ„ μ†Œκ°œν•˜μ˜€κ³ , 이 μœ„μ—μ„œ μž‘λ™ν•˜κ²Œλ  CG ν”„λ‘œκ·Έλž¨μ˜ μ œμž‘ 과정에 λŒ€ν•΄ μ†Œκ°œν•˜μ˜€λ‹€. μ΅œλŒ€ν•œμ˜ 컴퓨터 μ„±λŠ₯을 μ–»κΈ° μœ„ν•΄ μ—¬λŸ¬κ°€μ§€ λ‹€λ₯Έ μ΅œμ ν™” 방법듀이 μ‚¬μš©λ˜μ—ˆμœΌλ©° μ„€λ­λ˜μ—ˆλ‹€. μ΄λ ‡κ²Œ μ œμž‘λœ ν”„λ‘œκ·Έλž¨μ€ κ΅¬μΆ•λœ GPU 슈퍼 컴퓨터 μœ„μ—μ„œ μž‘λ™ν•˜λ©°, λ„€νŠΈμ›Œν¬ 병λͺ©μ„ μ œμ™Έν•œ 순수 계산 μ„±λŠ₯은 145 GFLOPSλ₯Ό 보인닀. λͺ¨λ“  λ„€νŠΈμ›Œν¬ μž…μΆœλ ₯을 ν¬ν•¨ν•œ κ²°κ³ΌμΉ˜λŠ” ν•˜λ‚˜μ˜ GTX 480 κ·Έλž˜ν”½ μΉ΄λ“œμ—μ„œ 36FLOPS의 μ„±λŠ₯을 λ³΄μ˜€λ‹€.Docto

    μ „μ•• μ˜μ‘΄μ„± ν¬νƒ€μŠ˜ 채널 4.1κ³Ό μ‚¬λžŒ μœ„μ•” μ„Έν¬μ˜ 증식

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    Thesis(masters) --μ„œμšΈλŒ€ν•™κ΅ λŒ€ν•™μ› :μˆ˜μ˜ν•™κ³Ό(μˆ˜μ˜λ³‘λ¦¬ν•™μ „κ³΅),2010.2.Maste
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