25 research outputs found
์กฐ์์ฅ์ ๋ก ์ง๋จ๋ ๋์กธ์ค ํ ํํจ์จ์ฆ์ ๋ฆฌ์ค๋ฒ๋ง ์์ฑ ์น๋ฃ ํจ๊ณผ: ์ฆ๋ก๋ณด๊ณ
Post-stroke parkinsonism usually presents with bradykinesia, resting tremor, and movement
disabilities and reportedly responds poorly to rehabilitative and pharmacological treatment
in contrast to Parkinsonโs disease. However, we encountered a patient with subarachnoid
hemorrhage caused by a ruptured anterior communicating artery aneurysm who developed
parkinsonism, which manifested with hypokinetic hypophonic dysarthria and masked facies.
Brain 18F-fluorodeoxyglucose positron emission tomography/computed tomography revealed
decreased glucose metabolism in the bilateral basal ganglia. He underwent 18 sessions of
Lee Silverman Voice Treatment (LSVT) for 60 min, once daily, and he gradually increased the
previously prescribed doses of levodopa and benserazide to 200 mg and 50 mg, respectively,
three times a day. The patientโs dysarthria improved from moderate to mild dysarthria. His
masked facies also improved remarkably 6 weeks after admission. Along with levodopa
administration, LSVT could be suggested as an effective treatment tool for hypophonic
dysarthria due to post-stroke parkinsonism.ope
Atomoxetine (Strattera)-Induced Pathologic Laughing in a Patient With Pontine Hemorrhage: A Case Report
Objectives: Pathologic laughing, characterized by episodes of abrupt and inappropriate laughter occurring irrespective of a person's emotional feelings, has been reported in patients with neurologic deficits. Some pharmacotherapies, including selective serotonin reuptake inhibitors, are effective in alleviating pathologic laughing. However, contrary to previous reports, we report a case of pathologic laughing that developed after a patient with pontine hemorrhage was administered atomoxetine (Strattera).
Case presentation: A 55-year-old man was diagnosed with acute intracerebral hemorrhage in the right pons and midbrain. The patient showed mild cognitive impairment, and he was administered 10 mg of atomoxetine once daily as a cognitive enhancer. On the day of atomoxetine administration, he suddenly developed episodes of inappropriate laughter that was uncontrollable. The Pathological Laughter and Crying Scale showed a score of 4 of 54 on the day he started taking atomoxetine, and his score was 18 on the second day. He was administered atomoxetine for 3 consecutive days, but it was stopped on the fourth day. His laughing diminished, and his score improved to 5. His smiling expression and a score of 1 on the scale lasted for 1 week. On day 8 of drug discontinuation, his score was zero and all symptoms disappeared.
Conclusions: Previously, no single medication has been reported to cause pathologic laughing. Atomoxetine is a stimulant that increases norepinephrine and dopamine levels in the prefrontal cortex. This report suggests that, unlike what is known thus far, norepinephrine and dopamine might play a crucial role in the development of pathologic laughing.restrictio
๋ ์ด์ ๋ถ๊ด ๊ธฐ์ ์ ํ์ฉํ ์ค์๊ฐ ๋น์ ์ด ํ์ฌ์ฉ ์ฑ๋ถ ๋ถ์ ๊ธฐ๋ฒ ์ฐ๊ตฌ
ํ์๋
ผ๋ฌธ (๋ฐ์ฌ)-- ์์ธ๋ํ๊ต ๋ํ์ : ๊ธฐ๊ณํญ๊ณต๊ณตํ๋ถ, 2015. 2. ์ฌ์ฌ์ต.๋ ์ด์ ์ ๋ ํ๋ผ์ฆ๋ง ๋ถ๊ด๋ถ์๋ฒ (LIBS : Laser-Induced Breakdown Spectroscopy) ์ ์ํ์ ๋ ์ด์ ๋ฅผ ์กฐ์ฌํ์ ๋ ๋ฐ์ํ๋ ํ๋ผ์ฆ๋ง๋ฅผ ํ์ฉํ ์ค์๊ฐ ๋น์ ์ด ์ฑ๋ถ ๋ถ์ ๊ธฐ๋ฒ์ด๋ค. ๋ ์ด์ ์๋์ง๋ฅผ ์ง์ค์์ผ 109 W/cm2 ์ด์์ ๋์ ์๋์ง ๋ฐ๋๋ก ์กฐ์ฌํ๋ฉด ์ํ์ด ๊ณ ์จ ๊ณ ์์ ํ๋ผ์ฆ๋ง ํํ๋ก ๋ถ๊ดด๋๋ค. ํ๋ผ์ฆ๋ง๋ ์ด์จ, ์์, ์ ์, ๋ถ์ ๋ฑ์ด ๊ณต์กดํ๋ ์ํ๋ก, ์ฌ๊ธฐ๋ ๋ฌผ์ง์ด ์๋์ง๋ฅผ ์๊ณ ์์ ํ ์ํ๋ก ๋๋์ ๊ฐ๋ฉด์ ์์์ ์ฑ๋ถ๊ณผ ์ฌ๊ธฐ ์ํ์ ๋ฐ๋ผ ํน์ ํ ํ์ฅ์ ๋น์ ๋ฐฉ์ถํ๋ค. ์ด๋ ๋ฐฉ์ถ๋ ๋น์ ํ์ฅ์ ๋ถ์ํ์ฌ ๋ฌผ์ง์ ๊ตฌ์ฑ ์ฑ๋ถ์ ์ ์ฑโข์ ๋์ ์ผ๋ก ๋ถ์ํ ์ ์๋ค.
LIBS๋ ์ค์๊ฐ์ผ๋ก ๋ฌผ์ง์ ์ฑ๋ถ ๋ถ์์ด ๊ฐ๋ฅํ๊ณ , ์ํ์ ์ ์ฒ๋ฆฌ ๊ณผ์ ์์ด ๋น์ ์ด์ผ๋ก ๊ฒ์ถํ ์ ์๋ ๊ธฐ๋ฒ์ด๋ผ๋ ์ ์์ ์ฐ์ฃผ ํ์ฌ ์ฐฉ๋ฅ์ ์ ๋ก๋ฒ์ ํ์ฌ๋์ด ํ์ฌ ์๋ฌด๋ฅผ ์ํํ ์ ์๋ค. ๋ณธ ์ฐ๊ตฌ์์๋ LIBS ๊ธฐ์ ์ ์ฐ์ฃผ ํ์ฉ์ ์ํ ๊ธฐ์ด ์ฐ๊ตฌ๋ฅผ ์ํํ์๋ค.
์ค์ ์ฐ์ฃผ ํ์ฌ์ LIBS ๊ธฐ์ ์ ์ ์ฉํ๊ณ ์๋ NASA์ ์ ๋ณด๋ฅผ ๋ฐํ์ผ๋ก ์ฐ์ฃผ ํ์ฌ ํ์ฌ์ฒด์ ์๊ตฌ๋๋ LIBS ๊ท๊ฒฉ์ ๊ท๋ช
ํ๊ณ , ์ฐ์ฃผ ํ๊ฒฝ์ ๋ชจ์ฌํ๋ ์ง๊ณต ์ฑ๋ฒ๋ฅผ ๊ตฌ์ถํจ์ผ๋ก์จ ์ค์ ์ด์ฉ ํ๊ฒฝ์ ๊ณ ๋ คํ ์ฐ๊ตฌ์ ๊ธฐ๋ฐ์ ๋ง๋ จํ์๋ค. ๋ ์ด์ ์ ์ํธ์ ํน์ฑ์ ๋ํ ์ ํธ ์ํฅ์ ํ์
ํ๊ณ , ์ด๋ฅผ ๋ฎ์ ์๋ ฅ ์กฐ๊ฑด์ ์ ์ฉํ์ฌ ๋ณํํ๋ ์ด์ฉ ํ๊ฒฝ์์๋ ํน์ฑ์ ์์ธก์ด ๊ฐ๋ฅํ๋๋ก ๋ฐ์ดํฐ ๋ฒ ์ด์ค๋ฅผ ๊ตฌ์ถํ์๋ค. ์์ ๊ฒฐ๊ณผ๋ ์์คํ
์ด์ฉ ์กฐ๊ฑด๊ณผ ๊ทธ์ ๋ํ ๊ฒฐ๊ณผ๋ฅผ ๋ฌผ๋ฆฌํํ์ ์ธ ๊ด์ ์์ ๋ถ์ํจ์ผ๋ก์จ LIBS ์ฐ๊ตฌ ๋ถ์ผ์ ํ์ฌ๊น์ง ์๋ ค์ ธ ์์ง ์์๋ ๊ฒฐ๋ก ์ ๋์ถํ์๋ค.
ํ์ฌ ๋์ ๋ฌผ์ง์ ๋๋ ๋ถ์์ ์ํ์ฌ ์ฐ์ฃผ ํ์ฌ์ ์ ํฉํ ํ์ค๋ฌผ์ง์ ํ์ฉํ์ฌ ์๋ ฅ, ์์, ์ํธ์ ํน์ฑ์ ๋ํ ๊ฒ๋์ ์ ์์ฑํ๊ณ ํน์ฑ์ ๊ท๋ช
ํจ์ผ๋ก์จ ์ ๋ ๋ถ์ ๋ฐ์ดํฐ ๋ฒ ์ด์ค๋ฅผ ๊ตฌ์ถํ์๊ณ ํน์ฑ์ ์์ธกํ ์ ์๋๋ก ํ์๋ค. ํนํ ๊ธฐ์กด์ ์ฐ๊ตฌ์ ๋ค๋ฅด๊ฒ 6๊ฐ์ง์ ๊ทธ๋ฃน์ผ๋ก ๋ถ๋ฅ๋ ๋ค์ํ ํ์ค ๋ฌผ์ง์ ์ฌ์ฉํจ์ผ๋ก์จ ์ ๋ ๋ถ์ ์ ๊ฐ์ฅ ํฐ ๋ฌธ์ ๊ฐ ๋๋ ๋งคํธ๋ฆญ์ค ํจ๊ณผ๋ฅผ ๊ทน๋ณตํ์ฌ ์ ํ๋๋ฅผ ํฅ์์์ผฐ๋ค. ๋ํ ๋จ๋ณ๋/๋ค๋ณ๋ ๊ธฐ๋ฒ์ ์ํ ์ ๋ ๋ถ์์ ํตํ์ฌ ๊ฒ๋์ ์ ์๊ด๊ณ์๋ฅผ ํฅ์์ํด์ผ๋ก์จ ๋งคํธ๋ฆญ์ค ํจ๊ณผ์ ์ํ ์ค์ฐจ๋ฅผ ๋ณด์ ํ ์ ์์๋ค.
์ค์ ํ์ฌ๋ฅผ ์ํ์ฌ 5~7 m ์๊ฑฐ๋ฆฌ ๊ฒ์ถ ์ฐ๊ตฌ๊ฐ ์ํ๋์์ผ๋ฉฐ, ์ต์ข
์ ์ผ๋ก ์ํํ๋ LIBS ์ฅ๋น๋ฅผ ์ ์ํ์ฌ ์ํํ ์ฅ๋น์ ์ฑ๋ฅ์ ๊ฒ์ฆํ๊ณ ํ์ฌ์ฒด๋ก์จ์ LIBS ์์คํ
ํ์ฉ ๊ฐ๋ฅ์ฑ์ ํ์ธํ์๋ค.
์ค์ ํ์ฌ ํ๊ฒฝ์ ํด๋นํ๋ ์ ์ ์กฐ๊ฑด์์๋ ํ๋ผ์ฆ๋ง๊ฐ ๊ธ๊ฒฉํ ํฝ์ฐฝํ์ฌ ์๋ฉธํ๋ ๋ฌธ์ ๊ฐ ์๋ค. ์ด๋ฌํ ๋ฌธ์ ์ ์ ํด๊ฒฐํ๊ณ ์ ์์์์ ๊ฒ์ถ ์ฑ๋ฅ์ ํฅ์์ํค๊ธฐ ์ํ์ฌ ํ๋ผ์ฆ๋ง์ ํฝ์ฐฝ์ ๋ฌผ๋ฆฌ์ ์ผ๋ก ๋ง๊ณ ํฝ์ฐฝ ๋ฐฉํฅ์ ์ ์ดํ๊ธฐ ์ํ confinement ๊ธฐ๋ฒ ์ฐ๊ตฌ๊ฐ ์ํ๋์๋ค. ๊ธฐ์กด์๋ 0.1 torr ์ดํ์ ์๋ ฅ ํ๊ฒฝ์์๋ ICCD ๊ฒ์ถ๊ธฐ๋ฅผ ์ฌ์ฉํด์ผ ํ๋ผ์ฆ๋ง ๊ฒ์ถ์ด ๊ฐ๋ฅํ์๋๋ฐ, confinement ๊ธฐ๋ฒ์ ๋์
ํจ์ผ๋ก์จ CCD ๊ฒ์ถ๊ธฐ๋ฅผ ํ์ฉํ ์ ์ ๊ฒ์ถ์ด ๊ฐ๋ฅํ์๋ค. ๋ํ ์ ํธ ์ธ๊ธฐ๊ฐ ํฌ๊ฒ ํฅ์๋์๊ณ , ๋ฎ์ ์๋์ง๋ก๋ ๊ฒ์ถ์ด ๊ฐ๋ฅํ๊ฒ ๋จ์ผ๋ก์จ ์ ์ฒด ์์คํ
์ ์ํํ ๊ฐ๋ฅ์ฑ์ ํ์ธํ์๋ค.
LIBS์ ์์ฉ ๋ฒ์๋ก๋ ๋ฐ์ด์ค ์ฐ๋ฃ ๊ฐ๋ฐ ๊ณผ์ ์์ ์ค๊ฐ ๊ณต์ ์ฅ๋น์ ์์์ ์ผ๊ธฐํ๋ ์ผ์์ ํฉ์ ๊ฒ์ถ ๋ฐฉ๋ฒ์ด ์ฃผ๋ชฉ๋ฐ๊ณ ์๋ ๊ฐ์ด๋ฐ LIBS๋ฅผ ๋ฐ์ด์ค ์ฐ๋ฃ ๊ฐ๋ฐ์ ์ ๋ชฉํ ์ ์๋ค. ๋
น์ ์ฐ์
์ ์ค์์ฑ์ด ๋๋๋๋ฉด์ ๊ทธ๋์ ์์ ์ฑ์ ์ค์์ํ์ฌ ๊ท์ ํ์ง ์์๋ ํญ๊ณต ๋งค์ฐ์ ๊ท์ ๊ฐ ์ด๋ฃจ์ด์ง ์๊ธฐ์ด๋ฏ๋ก ํญ๊ณต ๋งค์ฐ์ ์ค์๊ฐ ๊ฒ์ถ์ ์์ฉ๋์ด ๋งค์ฐ ๊ท์ ๋ฐ ํ๊ฒฝ ์ค์ผ ๋ฐฉ์ง๋ฅผ ๊ฐ๋ฅํ๊ฒ ํ๋ค. ๋ํ ๊ณ ์๋์ง ์ํ ๋ฌผ์ง ๊ฒ์ถ. ๋
์ฑ ๋ฌผ์ง ๋ถ์์ ํตํ ์ ์ดโข๊ด๋ฆฌ ๋ฐ ๋๊ธฐ ์ค ์ค๊ธ์ ์
์์ ์ค์๊ฐ ๋ถ์, ๊ทธ๋ฆฌ๊ณ ์น์, ์ํํ ์กฐ์ง, ์ธ์ฒด ํผ๋ถ, ์ธ์ฒด ๋ชจ๋ฐ, ๋ฐํ
๋ฆฌ์ ์ฐ๊ตฌ์ ์ด๋ฅด๊ธฐ๊น์ง ๋ค์ํ ์์ฒด ๊ณตํ ์ฐ๊ตฌ์ LIBS ์ฑ๋ถ ๋ถ์๋ฒ์ด ์์ฉ๋๊ณ ์๋ค. ๋ํ ๋ฒ์ฃ์์ฌํ์ ์ธ ์ธก๋ฉด์์ ์ง๋ฌธ ๋ถ์์๋ ์ ์ฉ์ด ๊ฐ๋ฅํ๋ค.
๋ณธ ์ฐ๊ตฌ๋ฅผ ํตํ์ฌ LIBS ์์คํ
์ ํ์ฌ ํ์ฌ์ฒด๋ก ํ์ฉํ ์ ์๋ ๊ฐ๋ฅ์ฑ์ ๋ค๊ฐ๋๋ก ๊ฒ์ฆํ์๋ค. ๋ํ ์์์ ์ธ๊ธํ ๋ค์ํ ํ์ฉ ๋ถ์ผ์ ์์ด์ ๋ณธ ์ฐ๊ตฌ์ ๊ฒฐ๊ณผ๋ ๋ชฉ์ ์ ์ ํฉํ ์์คํ
์ค๊ณ๋ฅผ ์ํ ์ผ๋ จ์ ์ฐธ๊ณ ์๋ฃ๊ฐ ๋ ์ ์๋ค.The Laser-Induced Breakdown Spectroscopy (LIBS) has great advantages as an analytical technique, namely real-time rapid analysis without sample preparation and stand-off detection capability, ideal for mobile chemical sensor for space exploration. In this research, we investigated the LIBS specification required to build the payload for space exploration and prepared the basis for real circumstances analysis by building a vacuum chamber for space environment. We also built a database to understand the effect of LIBS signals with respect to the properties of laser and samples and to predict the plasma signal under the working circumstances that changed through the application of low pressure condition. Moreover, we built a database of quantitative analysis by drawing the calibration curves with the effects of pressure, elements and samples utilizing the certified reference materials (CRMs) which are appropriate for the space exploration and investigated the characteristics of the samples. Researches of stand-off detection were carried out for further understanding of space science by considering the environmental condition. The confinement method was devised to enhance the signal for optimum plasma detection at space environment. The results obtained through this research will allow more precise mapping compared to widely used conventional elemental analyzing method in space exploration and provide a guideline for design of various LIBS experiments.LIST
ABSTRACTโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ..i
LISTโฆโฆโฆโฆโฆโฆโฆโฆโฆ..โฆโฆโฆโฆโฆโฆโฆโฆโฆ.โฆโฆโฆโฆโฆโฆ...โฆโฆ...iii
LIST OF FIGURESโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ............vii
LIST OF TABLES..โฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ.............xi
PREFACEโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆxii
CHAPTER 1
INTRODUCTIONโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ.1
1.1 Motivation and purposeโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ.โฆโฆ.......1
1.2 Laser-material interaction.โฆโฆโฆโฆโฆโฆโฆโฆ..โฆโฆโฆโฆโฆโฆ..5
1.3 Laser-Induced Breakdown Spectroscopy (LIBS) for space exploration.โฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ.8
CHAPTER 2
EXPERIMENTAL APPARATUSโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ...โฆโฆ.14
2.1 Laserโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ15
2.2 Spectrometer and detectorโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ.โฆโฆโฆ..17
2.3 Other equipmentsโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ.โฆโฆ...19
2.4 Summaryโฆโฆ.โฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ21
CHAPTER 3
FUNDAMENTAL STUDY ON EMISSION SIGNAL CONSIDERING EXPERIMENTAL PARAMETERโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ..22
3.1 Background and objectiveโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ...22
3.2 Experimental conditionโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ23
3.3 Collinear double pulse testโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ..โฆ24
3.4 Effect of sample and detector angleโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ.28
3.4.1 Sample angle variationโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ..28
3.4.2 Detector angle variationโฆโฆโฆโฆโฆโฆโฆโฆ............31
3.5 Optimizing the wavelength of laserโฆโฆโฆโฆโฆโฆโฆ...โฆ.โฆโฆ34
CHAPTER 4
QUANTITATIVE ANALYSISโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ................37
4.1 Background and objectiveโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ...37
4.2 Experimental conditionโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ40
4.3 LIBS spectraโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ.โฆโฆโฆโฆ...43
4.4 Principal component analysis (PCA)....โฆโฆโฆโฆ..โฆโฆโฆโฆโฆ44
4.5 Univariate analysisโฆ..โฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ.โฆโฆโฆโฆ...47
4.6 Multivariate analysisโฆโฆโฆโฆ.โฆโฆโฆโฆโฆโฆโฆ..โฆโฆโฆโฆโฆ57
CHAPTER 5
PLASMA CHARACTERISTICS BY ENVIRONMENTAL CONDITION...63
5.1 Background and objectiveโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ...63
5.2 Experimental conditionโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ64
5.3 Effect of ambient pressure from the elemental lifetime perspective.โฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ.โฆโฆ...65
5.3.1 Characteristics of lifetime with pressure changeโฆ...67
5.3.2 Analysis of elemental boiling point and electronegativityโฆโฆโฆโฆโฆโฆโฆโฆ..โฆโฆโฆโฆโฆโฆ...โฆ69
CHAPTER 6
DESIGN OF STAND-OFF DEVICE FOR SPACE EXPLORATIONโฆโฆโฆ74
6.1 Background and objectiveโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ...74
6.2 Experimental conditionโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ...75
6. 3 Stand-off detectionโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ.76
6.4 Design of portable stand-off device. โฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ..78
CHAPTER 7
SIGNAL ENHANCEMENT AT LOW PRESSUREโฆโฆโฆโฆโฆโฆโฆโฆโฆ...80
7.1 Background and objectiveโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ...80
7.2 Experimental conditionโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ83
7.3 Effective energy delivery at low pressureโฆโฆโฆโฆโฆโฆโฆโฆ...85
7.4 Low pressure effectโฆ...โฆโฆโฆโฆโฆโฆโฆโฆ..โฆโฆ.โฆโฆโฆโฆ...88 7.5 Hard-to-detect element โ Sulfur detectionโฆโฆโฆ..โฆโฆโฆโฆโฆ94
7.6 Effect of a confining window materialโฆโฆโฆโฆโฆ.โฆโฆโฆโฆ...96
CHAPTER 8
CONCLUSIONโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ...99
REFERENCES...โฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ...101
Abstract in Koreanโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ.111Docto
A Study on the Determinants of U.S. Grains Futures Price
ํ์๋
ผ๋ฌธ (๋ฐ์ฌ)-- ์์ธ๋ํ๊ต ๋ํ์ : ๋๊ฒฝ์ ์ฌํํ๋ถ ๋์
์์๊ฒฝ์ ํ์ ๊ณต, 2016. 8. ๊นํํธ.2000๋
๋ ํ๋ฐ ์ดํ ๊ณก๋ฌผ ์ ๋ฌผ์์ฅ์ด ๋ถ์์ ํด์ ธ ์ ๋ฌผ๊ฐ๊ฒฉ์ด ๊ธ๋ฑ๊ณผ ๊ธ๋ฝ์ ๋ฐ๋ณตํ๋ ๋ฑ ํฐ ํญ์ผ๋ก ๋ณํํ๊ณ ๋ณ๋์ฃผ๊ธฐ๊ฐ ๋นจ๋ผ์ง๋ฉด์ ์ ๋ฌผ์์ฅ์ ๋ถํ์ค์ฑ์ด ํ๋๋ ๊ฒฐ๊ณผ ๊ฐ๊ฒฉ ์์ธก์ด ์ด์ ๊ณผ๋ ๋นํ ๋ฐ ์์ด ์ด๋ ค์์ก๋ค. ์ต๊ทผ์ ๊ณก๋ฌผ ์ ๋ฌผ๊ฐ๊ฒฉ ๋ถํ์ค์ฑ์ ์ผ๊ธฐํ ์ฃผ ์์ธ์ ๊ท๋ช
ํ๊ธฐ ์ํด ์ ๋ง์ ์ฐ๊ตฌ๋ค์ด ๊ตญ๋ด์ธ์์ ์ํ๋์๊ณ , ์ธ๋ฑ์คํ๋ ํ์ฑํ๋ก ์ธํ ํฌ๊ธฐ์ ์์์ ์ฆ๊ฐ, ๋ฏธ๊ตญ ์์ ์ํ์กฐ์น ์ดํ ๊ฑฐ์๊ฒฝ์ ๋ณ์(๊ธ๋ฆฌ, ํ์จ, ์ ๊ฐ)์ ์ํฅ, ๋ฐ์ด์ค์ฐ๋ฃ ์ ์ฑ
, ์ ํฅ๊ตญ์ ๊ฒฝ์ ์ฑ์ฅ์ผ๋ก ์ธํ ์ก๋ฅ ์์ ์ฆ๊ฐ, ์ด์๊ธฐํํ์์ด ์์ธ์ผ๋ก ์ง๋ชฉ๋์๋ค.
๋ณธ๊ณ ๋ ๋ฏธ๊ตญ ๊ณก๋ฌผ ์ ๋ฌผ๊ฐ๊ฒฉ ๊ฒฐ์ ์์ธ๋ค์ ๋ํด ํฌ๊ด์ ์ธ ๋น๊ต๋ถ์์ ์ํํ๊ธฐ ์ํด ์ฒซ์งธ, ๊ธฐ๋ ๊ณต๊ธ๋์ ์ํฅ์ ๋ฏธ์น๋ ์์ธ(์ ๊ฐ, ๊ธฐํ)๊ณผ ๊ธฐ๋ ์์๋์ ์ํฅ์ ๋ฏธ์น๋ ์์ธ(ํ์จ, ๋ฐ์ด์ค์ฐ๋ฃ, ์ ํฅ๊ตญ ์์) ์ค ์ด๋ ์์ธ์ด ๋ ์ค์ํ ๊ณก๋ฌผ ์ ๋ฌผ๊ฐ๊ฒฉ ๊ฒฐ์ ์์ธ์ด ๋๋์ง, ๋์งธ, ํฌ๊ธฐ์ ์์ธ์ด ๊ณก๋ฌผ ์ ๋ฌผ๊ฐ๊ฒฉ์ ์ด๋ค ์ํฅ์ ๋ฏธ์น๋์ง ์ค๋ฌผ์ ์์ธ๊ณผ ๋น๊ตํ์ฌ ํ์ธํด ๋ณด์๋ค.
๋ถ์ ๋ฐฉ๋ฒ์ผ๋ก ํ์ ๋ ๋ณ์๋ง์ ๊ณ ๋ คํ๋ ๋จ์ผ ๋ชจํ์ ์ ์ฝ์ ๊ทน๋ณตํ ์ ์๋ ๋ฒ ์ด์ง์ ๋ชจํํ๊ท ๋ฒ์ ํ์ฉํ์ฌ ์ค์ฆ๋ถ์ํ์๋๋ฐ, BMA ๋ถ์๋ชจํ ์ค์ ์ ๋ฐ์ํ ์ ์๋ ์์ฐจ๊ตฌ์กฐ์ ์ ํฉ์ฑ ๋ฌธ์ ๋ฅผ ๊ฒํ ํ๊ธฐ ์ํ์ฌ ๊ณก๋ฌผ ๊ฐ๊ฒฉ ๋ถ์ผ ์ ํ์ฐ๊ตฌ์์ ๊ธฐ์กด์ ๋๋ฆฌ ํ์ฉ๋๊ณ ์๋ VAR๋ชจํ์ ํตํ ์ถ์ ๊ฒฐ๊ณผ์ ์์ธก๋ ฅ์ ๋ถ์ยทํ๊ฐํ์๋ค. ๋ถ์ ๊ฒฐ๊ณผ BMA๋ ๊ณก๋ฌผ ์ ๋ฌผ๊ฐ๊ฒฉ๋ถ์ผ์์ VAR์ ๋นํด ์ค์ฅ๊ธฐ ์์ธก์๊ณ์์ ์์ธก๋ ฅ์ด ์ฐ์ํ ๊ฒ์ผ๋ก ๋ํ๋ฌ๋ค. ๋ํ BMA๋ ์ธ์๋ณ์๋ฅผ ๋๊ท๋ชจ๋ก ํฌํจํ ์ ์์ผ๋ฏ๋ก ํฅํ ๊ณก๋ฌผ ์ ๋ฌผ๊ฐ๊ฒฉ๊ณผ ์ฐ๊ด์ด ์๋ ๋ณ์๋ฅผ ๋ฐ๊ตดํ์ฌ ํฌ์
ํจ์ผ๋ก์จ ์์ธก๋ ฅ์ ๊ฐ์ ํ ์ฌ์ง๋ ์ถฉ๋ถํ ์๋ค.
๋ณธ๊ณ ๋ ๋ํ ์ ํ์ฐ๊ตฌ์ ์ฐจ๋ณํ๋๋ ๋ถ์์๋ฃ์ ๋ชจํ์ ๋ค์๊ณผ ๊ฐ์ด ๊ตฌ์ถํ์๋ค. ์ฒซ์งธ, ์์ ์ํ์กฐ์น ์ดํ์ ์ต๊ทผ ์๋ฃ๋ฅผ ์ด์ฉํ์๊ณ , ๋์งธ, ๊ฑฐ์๊ฒฝ์ ๋ณ์๊ฐ ์ ๋ฌผ์์ฅ์ ๋ฏธ์น๋ ์ํฅ์ ๊ธ๋ฆฌ, ๋ฌ๋ฌํ๊ฐ์น, ์ ๊ฐ๋ฅผ ํตํด ํฌ๊ด์ ์ผ๋ก ์ธก์ ํจ์ผ๋ก์จ ๋จํธ์ ์ธ๊ณผ๊ด๊ณ๋ฅผ ๋ถ์ํ ๊ธฐ์กด ์ ํ์ฐ๊ตฌ์ ์ฐจ๋ณ์ฑ์ ๋์๊ณ , ์
์งธ, ์ฅ์์, ๋ฐ ์ฝฉ ๋ชจํ์ ๊ฐ๊ฐ ์ค์ ํจ์ผ๋ก์จ ์ต๊ทผ ์ธ๋ฑ์คํ๋ ๊ด๋ จ ์ ํ์ฐ๊ตฌ์์ ์์์ฌ์ํ ์ ์ฒด, ๋๋ ๊ณก๋ฌผ ์ ์ฒด๊ฐ ์ข
ํฉ์ ์ผ๋ก ๋ฐ๋ ์ํฅ(aggregate effect)๋ง ๊ฐ๋ ํ ์ ์์๋ ๊ฒ๊ณผ๋ ๋ฌ๋ฆฌ ์ธ๋ฑ์คํ๋(๋น์์
์๋งค์ํฌ์ง์
)๊ฐ ๊ฐ ๊ณก๋ฌผ ์ ๋ฌผ๊ฐ๊ฒฉ์ ๋ฏธ์น๋ ์ํฅ์ ๊ตฌ์ฒด์ ์ผ๋ก ์ถ์ ํ์๋ค. ๋ํ ๋ท์งธ, ๋ฏธ๊ตญ ๋ฐ์ด์ค์ฐ๋ฃ ์ ์ฑ
์ด ๊ณก๋ฌผ๊ฐ๊ฒฉ์ ๋ฏธ์น๋ ์ํฅ์ ์ธก์ ํ๊ธฐ ์ํด ์ํ์ฌ๊ณผ ๋ฐ์ด์ค๋์ ค ์์๋์ ๋ฐ์ด์ค์ฐ๋ฃ ์ง์์ ์ฑ
(๋ณด์กฐ๊ธ, ์๋ฌด์๋น๋)์ ๋ฐ์ํ๋ ๋๋ฆฌ๋ณ์๋ก ๊ตฌ์ถํ์๋ค. ๋ค์ฏ์งธ, ๋ณธ๊ณ ์์๋ ์ค๊ตญ(๋ณธํ , ํ์ฝฉ, ๋๋ง)์ ๋ฏธ๊ตญ์ฐ ๋ผ์ง๊ณ ๊ธฐ ์๊ฐ ์์
๋์ ์ค๊ตญ ๊ฒฝ์ ์ฑ์ฅ์ผ๋ก ์ธํด ์ฆ๊ฐํ๋ ์ก๋ฅ ์์์ ๋๋ฆฌ๋ณ์๋ก ๊ตฌ์ถํจ์ผ๋ก์จ ๊ฒฝ์ ํ๋์ง์๋ BDI๋ฅผ ์ด์ฉํ ์ ํ์ฐ๊ตฌ๋ณด๋ค ๊ณก๋ฌผ๋ถ๋ฌธ์์ ์ผ์ด๋๋ ์ํฅ์ ๊ตฌ์ฒด์ ์ด๊ณ ์ง์ ์ ์ผ๋ก ์ธก์ ํ์๋ค. ์ฌ์ฏ์งธ, ๊ธฐํ๋ณํ์ ์ํฅ ์ธก์ ์ ๋๋ฏธ๋ณ์๋ฅผ ์ด์ฉํ ๋ถ์์์ ๋ํ๋๋ ํ๊ณ๋ฅผ ๊ทน๋ณตํ๊ธฐ ์ํด ์ฐ์๋ณ์์ธ ๋จ๋ฐฉ์ง๋๊ณ์๋ฅผ ์ด์ฉํ์๋ค.
๋ณธ ์ฐ๊ตฌ๊ฒฐ๊ณผ ๊ฐ ๊ฒฐ์ ์์ธ์ ๋ํด ์ํฅ์ ํ์ค์ฑ๊ณผ ํฌ๊ธฐ๋ฅผ ํ์ธํ ์ ์์๋ค. ๊ธฐ๋๊ณต๊ธ๋์ ์ํฅ์ ๋ฏธ์น๋ ์์ธ(์ ๊ฐ, ๊ธฐํ)๊ณผ ๊ธฐ๋ ์์๋์ ์ํฅ์ ๋ฏธ์น๋ ์์ธ(ํ์จ, ๋ฐ์ด์ค์ฐ๋ฃ, ์ ํฅ๊ตญ ์์)์ผ๋ก ์ค์ ํ ์์ธ๋ค์ ๋น๊ตยท ํ๊ฐํ ๊ฒฐ๊ณผ ์ด์ค ์ ๊ฐ๋ง ์ฅ์์, ๋ฐ, ์ฝฉ ์ ๋ฌผ๊ฐ๊ฒฉ์ ๋ํด ๋ก๋ฒ์คํธํ ์ํฅ์ ๋ฏธ์น๋ ์์ธ์ผ๋ก ๋์ถ๋์๋ค. ๋ฐ๋ผ์ ๊ณก๋ฌผ ์ ๋ฌผ๊ฐ๊ฒฉ์ ์๋์ง๊ฐ๊ฒฉ๊ณผ ์ฐ๊ณ(linkage)๊ฐ ์๋ ๊ฒ์ด ํ์ธ๋์๊ณ , ์ ์ ๊ฐ๋ ๊ณ ์ ๊ฐ ์ถฉ๊ฒฉ์ ๊ณก๋ฌผ ์์ฅ์ผ๋ก ์ ์ด๋ ํ๋ฅ ์ด ๋งค์ฐ ๋์ ๊ฒ์ผ๋ก ์์ํ ์ ์๋ค. ํํธ ์ ๊ฐ๊ฐ ๊ณก๋ฌผ ์ ๋ฌผ๊ฐ๊ฒฉ์ ๋ฏธ์น๋ ์ํฅ์ ํฌ๊ธฐ๋ฅผ ์ถ์ ๋ ๊ณ์๋ก ํ์ธํด ๋ณด๋ฉด ์ฅ์์์ ๋ฐ์ ๊ฒฝ์ฐ ๋ค๋ฅธ ์์ธ๋ค์ ๋นํด ํฌ๋ ์ฝฉ์ ๊ฒฝ์ฐ ๋ฌ๋ฌํ ๊ฐ์น๋ณด๋ค ์ ์ ๊ฒ์ผ๋ก ๋์ถ๋์๋ค.
๋ณธ ์ฐ๊ตฌ๋ ๋ํ ํฌ๊ธฐ์ ์์ธ๊ณผ ์ค๋ฌผ์ ์์ธ์ด ๊ณก๋ฌผ ์ ๋ฌผ๊ฐ๊ฒฉ์ ๋ฏธ์น๋ ์ํฅ์ ํฌ๊ด์ ์ผ๋ก ๋น๊ตยทํ๊ฐํด ๋ณด์๋๋ฐ, ๋ถ์๊ฒฐ๊ณผ ํฌ๊ธฐ์ ์์์ ์ฆ๊ฐ๋ ๊ณก๋ฌผ ์ ๋ฌผ๊ฐ๊ฒฉ์ ์์น์ํค๋ ๊ฒ์ด ์๋๋ผ ์คํ๋ ค ์์ ํ์ํค๋ ๊ฒ์ผ๋ก ๋ํ๋ฌ๋ค. ํํธ ๊ธ๋ฆฌ ์์น์ ๊ณก๋ฌผ ๊ฐ๊ฒฉ์ ํ๋ฝ์ํค๋ ๊ฒ์ผ๋ก ๋์ถ๋์๋๋ฐ, ์์ ์ธ๊ธํ ๋ฐ์ ๊ฐ์ด ๋น์์
์๋งค์ํฌ์ง์
๊ณผ ๊ณก๋ฌผ ์ ๋ฌผ๊ฐ๊ฒฉ์ ์์ ๊ด๊ณ๊ฐ ์๋ ๊ฒ์ผ๋ก ๋์ถ๋์์ผ๋ฏ๋ก, ๋ณธ๊ณ ์ ์ฐ๊ตฌ๊ฒฐ๊ณผ ๋์ถ๋ ๊ฒฐ๋ก ์ ์ํ๋ฉด ๊ธ๋ฆฌ๊ฐ ๊ฐ๊ฒฉ์ ์ํฅ์ ๋ฏธ์น ๊ฒฝ๋ก๋ ํฌ๊ธฐ์ ์์๊ฐ ์๋๋ผ ์ค๋ฌผ ์์๋ฅผ ํตํ ๊ฒ์ด๋ค. ์ฆ, ๊ธ๋ฆฌ ํ๋ฝ์ ์ค๋ฌผ์์ฅ์์ ์ฌ๊ณ ๋ณด์ ๋น์ฉ์ ํ๋ฝ์ํค๋ฏ๋ก ์ฌ๊ณ ์ฉ ์์๋์ ์ฆ๊ฐ์ํจ ๊ฒฐ๊ณผ ๊ฐ๊ฒฉ์ ์์น์ํจ ๊ฒ์ผ๋ก ํด์ํ ์ ์๋ค. ๋ฐ๋ผ์ ํฅํ ๋ฏธ ์ฐ์ค์ด ๊ธ๋ฆฌ๋ฅผ ๋์ผ ๊ฒฝ์ฐ ๊ณก๋ฌผ ์ ๋ฌผ์์ฅ์ ๊ฐ๊ฒฉ์์น ์ํฅ์ ๋ฐ์ ๊ฒ์ผ๋ก ์์ํ ์ ์์ผ๋, ์ด๋ ์ฌ๋ฌ ์ ํ์ฐ๊ตฌ์ ์ฃผ์ฅ๊ณผ๋ ๋ฌ๋ฆฌ ๊ธ๋ฆฌ๊ฐ ์ค๋ฌผ ์ฌ๊ณ ์์๋์ ๋ณ๋์ํด์ผ๋ก์จ ์ ๋ฌผ๊ฐ๊ฒฉ์ ์ํฅ์ ๋ฏธ์น๋ ๊ฒ์ผ๋ก ํ๋จํ ์ ์๋ค.
๋ณธ๊ณ ์ ์ฐ๊ตฌ๊ฒฐ๊ณผ์ ๊ทผ๊ฑฐํ๋ฉด ํฅํ ๋ฏธ ์ฐ์ค์ด ๊ธ๋ฆฌ๋ฅผ ๋์ผ ๊ฒฝ์ฐ ํนํ ์ฅ์์์ ๋ฐ ์ ๋ฌผ์์ฅ์ ๋์ ํ๋ฅ ๋ก ๊ฐ๊ฒฉ์์น ์ํฅ์ ๋ฐ์ ๊ฒ์ผ๋ก ์์ํ ์ ์๋ค. ํํธ ๋ณธ ์ฐ๊ตฌ๊ฒฐ๊ณผ๊ฐ ์ด์ ์ ์ฐ๊ตฌ์ ์ฐจ๋ณ๋๋ ์ ์ ํตํ์ ์ฑ
์ด ๊ณก๋ฌผ ์ ๋ฌผ์์ฅ์ ๋ฏธ์น๋ ์ํฅ์ด ๊ฑฐํ, ์ฆ ํฌ๊ธฐ์ ์์์ ์ผ์์ ์ฆ๊ฐ๊ฐ ์๋ ์ค๋ฌผ ์ฌ๊ณ ์์๋ฅผ ๋งค๊ฐ๋ก ํ์ฌ ์ด๋ฃจ์ด์ง๋ค๋ ๊ฒ์ ๊ณ๋์ ๋ถ์์ ํตํด ๋ฐํ ๊ฒ์ด๋ค.
๋ณธ ์ฐ๊ตฌ์ ๊ฒฐ๊ณผ๋ ๊ณก๋ฌผ์ ์์
์์กด๋๊ฐ ๋งค์ฐ ๋์ ์ฐ๋ฆฌ๋๋ผ์์ ๊ณก๋ฌผ๊ฐ๊ฒฉ์ ์กฐ๊ธฐ์ ์์ธกํ ๋ ๊ฐ ์์ธ์ ์ด๋ป๊ฒ ๊ณ ๋ คํด์ผ ํ ๊ฒ์ธ๊ฐ์ ๋ํด ์ฌ๋ฌ ๊ฐ์ง ์์ฌ์ ์ ๋จ๊ธด๋ค. ์ข
ํฉํด ๋ณด๋ฉด 2000๋
๋ ํ๋ฐ ์ดํ ๊ณก๋ฌผ ์ ๋ฌผ๊ฐ๊ฒฉ์ ๋ถํ์ค์ฑ์ด ํ๋๋ ์ฃผ ์์ธ์ ๊ณก๋ฌผ ๊ฐ๊ฒฉ๊ณผ ์ ๊ฐ์ ์ฐ๊ณ๋ก ์ธํด ์๋์ง ๋ถ๋ฌธ์ ๋ณ๋์์ธ๋ค์ด ๊ณก๋ฌผ ๋ถ๋ฌธ์ผ๋ก ํ๊ธ๋ ๊ฒ, ๊ทธ๋ฆฌ๊ณ ๋ฏธ๊ตญ ๊ธ์ต์๊ธฐ์ ๊ฑฐ์๊ฒฝ์ ์ ์ฑ
์ผ๋ก ์ธํด ๊ธ๋ฆฌ์ ๋ฌ๋ฌํ๊ฐ์น๊ฐ ๋ณ๋ํ ๋ณตํฉ์ ์ธ ๊ฒฐ๊ณผ๋ผ๊ณ ๊ฒฐ๋ก ์ ๋ด๋ฆด ์ ์์ ๊ฒ์ด๋ค. ๋ณธ๊ณ ์ ์ฐ๊ตฌ๊ฒฐ๊ณผ๋ ๊ณก๋ฌผ ๊ฐ๊ฒฉ ์์ธก์ ๋ถํ์ค์ฑ์ ๊ฐ์ ํ๊ธฐ ์ํด ์ฌ๋ฌ ์ ๋ณด๋ค์ ํ์ฉํ ์ ์๋ ์ค์ฆ์ ๊ทผ๊ฑฐ๊ฐ ๋ ์ ์์ ๊ฒ์ด๋ค.After the late 2000s, the change cycle length of grains futures price is shortened and the boom and the bust repeats, which makes grains price outlook unprecedentedly difficult. Numerous studies are conducted to find out the main cause of the recent increase of uncertainty in grains futures price and the followings are pointed out: increase of speculative demand due to index fundchange of macroeconomic factors (interest rate, dollar value, and oil price) due to US quantitative easingbiofuel policyincrease of meat demand due to economic growth of Chinaand abnormal climate.
The aim of this paper is to answer the following questions. First, which is relatively more important determinant of US grains futures price between expected supply (oil price and climate) and expected demand (dollar value, biofuel policy, and meat demand of China)? Second, how does speculative factors influence grains futures price in comparison with the tangible factors?
The estimating method is Bayesian Model Averaving, which overcomes the weakness of single model consisting of restricted number of regressors. To consider the time lag structure, Vector Auto Regressive models, which are frequently utilized in the grains futures price outlook, are estimated so as to evaluate BMAs predictive performance in comparison with VAR. As a result, it is discovered that BMA have less mean square prediction error compared to VAR in the long run. Therefore, BMA has the full potential of complementary use in the study of grains futures price as BMA can include unlimited number of informative variables and there is a plenty of room to improve its predictive performance by discovering regressors highly related to grains futures price.
According to the study results, the certainty and the size of impact of each determinant for each grain is discovered as followings. The robust determinants are oil price and interest rate and others only have stochastic effects. Corn futures price has greatest impact from expected supply (oil price) and the certainty of getting the impact is also high. Wheat futures price has great and almost certain impact from oil price and has greatest and less certain impact from lagged dollar index. Soybeans futures prices have greatest impact from dollar index, however, the impact is only stochastic.
It is also discovered that the increase of noncommercial net long position does not raise grains futures price but rather stabilizes it. Interest rate is found to be negatively correlated to grains futures price but the channel of the interest rate is not speculative demand since it is shown that noncommercial net long position is negatively related to grains futures price. Therefore, higher interest rate affects grains futures price via increasing tangible demand by lowering stock cost.
In summary, there is a high probability that grains futures price respond to the change of oil price and interest rate and lower probability that grains futures price be influenced from other determinants. The result of this study provides both the certainty and the size of the impact from determinants for corn, wheat and soybeans futures prices, which would serve as an empirical evidence of utilizing various information in the grains futures market and helps resolve the uncertainty in the grains price outlook.์ 1์ฅ ์๋ก 1
์ 1์ ์ฐ๊ตฌ์ ๋ฐฐ๊ฒฝ๊ณผ ํ์์ฑ 1
์ 2์ ์ ํ์ฐ๊ตฌ 6
์ 3์ ์ฐ๊ตฌ์ ๋ฒ์ 9
์ 4์ ์ฐ๊ตฌ์ ๋ด์ฉ๊ณผ ๊ตฌ์ฑ 13
์ 2์ฅ ๊ณก๋ฌผ ์ ๋ฌผ๊ฐ๊ฒฉ ๊ฒฐ์ ์์ธ 14
์ 1์ ์์ ์ํ์ ๊ฑฐ์๊ฒฝ์ ๋ณ์์ ์ํฅ 14
์ 2์ ์ธ๋ฑ์คํ๋์ ํฌ๊ธฐ์ ์์์ ์ํฅ 19
์ 3์ ๋ฐ์ด์ค์ฐ๋ฃ ์ฐ์
๊ณผ ์ ์ฑ
24
์ 4์ ์ค๊ตญ์ ๊ฒฝ์ ์ฑ์ฅ๊ณผ ์ก๋ฅ์๋น๋ ์ฆ๊ฐ 31
์ 5์ ๊ธฐํ๋ณํ์ ์ํฅ 39
์ 3์ฅ ๋ถ์๋ฐฉ๋ฒ๊ณผ ์๋ฃ 44
์ 1์ ๊ณก๋ฌผ ์ ๋ฌผ๊ฐ๊ฒฉ ๊ฒฐ์ ์ฒด๊ณ 44
์ 2์ ๋ถ์์๋ฃ 48
์ 3์ ๋ฒ ์ด์ง์ ๋ชจํ ํ๊ท 54
์ 1ํญ ๋ฒ ์ด์ง์ ๋ถ์๊ณผ ๊ณ ์ ์ ๊ณ๋๊ฒฝ์ ํ์ ๋น๊ต 54
์ 2ํญ ๋ฒ ์ด์ง์ ๋ชจํ ํ๊ท 58
์ 3ํญ ์ค์ฆ๋ชจํ์ ๊ตฌ์ถ 62
์ 4์ ๋ฒกํฐ์๊ธฐํ๊ท๋ชจํ 65
์ 1ํญ ๊ฐ์ 65
์ 2ํญ ์ค์ฆ๋ชจํ์ ๊ตฌ์ถ 67
์ 5์ ์์ธก๋ ฅ ํ๊ฐ 69
์ 4์ฅ ๋ถ์ ๊ฒฐ๊ณผ 70
์ 1์ BMA ๋ถ์๊ฒฐ๊ณผ 70
์ 2์ VAR ๋ถ์๊ฒฐ๊ณผ 81
์ 3์ ์์ธก๋ ฅ ํ๊ฐ 95
์ 5์ฅ ์์ฌ์ ๊ณผ ๊ฒฐ๋ก 98
์ 1์ ๊ฒฐ๊ณผ์ ํด์๊ณผ ์์ฌ์ 98
์ 2์ ๊ฒฐ๋ก 105
์ฐธ๊ณ ๋ฌธํ 108
๋ถ๋ก: ์ฅ์์, ๋ฐ, ์ฝฉ์ ์ํ๊ธฐ์ ์ ๋ฌผ๊ณ์ฝ ์ 114Docto
Automatic control of a miniature vehicle using GPS-RTK and single axis gyro
ํ์๋
ผ๋ฌธ(์์ฌ)--์์ธ๋ํ๊ต ๋ํ์ :๊ธฐ๊ณํญ๊ณต๊ณตํ๋ถ,2007.Maste
Therapeutic monitoring of busulfan in patients undergoing hematopoietic stem cell transplantation
Thesis(master`s)--์์ธ๋ํ๊ต ๋ํ์ :์ฝํ๊ณผ ์์์ฝํ์ ๊ณต,2004.Maste
ํ๊ตญ ํ์์ ๊ฐ์กฑ๋ฐฐ๊ฒฝ๊ณผ ํ์ ์ฑ์ทจ๋์ ๊ดํ ์ฐ๊ตฌ
ํ์๋
ผ๋ฌธ (์์ฌ)-- ์์ธ๋ํ๊ต ๊ตญ์ ๋ํ์ : ๊ตญ์ ํ๊ณผ, 2014. 8. ์๊ธฐ์.This study investigates the family dynamics of the South Korean student and provides empirical evidence that family background and academic achievement are closely related. The research is based on an academic survey of 357 undergraduates from high achieving and low achieving tertiary institutions, conducting in 2007 and 2012. The first part of this thesis outlines the importance of education in South Korea and the research background. A literature review shows that much of the previous studies on family background and academic achievement have focused on single groups of achievers, and are based on American or European contexts. This study investigates the South Korean family during the notoriously tough 3rd year of high school. The family characteristics of higher and lower academic achievers are examined under four categories: financial capital, human capital, social capital, and personal effort. Following the conceptual framework and hypothesis section come the results of the survey. Various analytical procedures have been conducted for this study using statistical software. Results indicate a positive correlation between a students academic achievement and family wealthparents education leveland parental involvement. Each of these categories is further investigated with sub-categories such as place of residence, mothers employment status, and birth order. Results show that the higher achiever is usually the firstborn child whose father is highly-educated and mother is highly-educated but stays at home during the final year of high school. Either one of the parents may have received higher education from overseas. The family may also live in a lucrative neighborhood and belong to the upper-middle income bracket, being able to pay for costly private education and allowing the mother to stay at home. A summary of the findings concludes this study along with implications and propositions for future research.Chapter 1. Introduction โฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ 1
1.1 Research Background โฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ 1
1.2 Research Questions โฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ 3
1.3 Significance of Research โฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ 4
Chapter 2. Method & Data โฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ 5
Chapter 3. Literature Review โฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ 9
3.1 Family Background and Academic Achievement โฆโฆโฆโฆโฆโฆโฆ 9
3.2 Non-Family Factor and Academic Achievement โฆโฆโฆโฆโฆโฆโฆ 12
Chapter 4. Conceptual Framework & Hypothesis โฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ 14
Chapter 5. Results โฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ 19
5.1 Financial Capital: Family Wealth โฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ 19
5.1.1 Perceived Income Bracket โฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ 19
5.1.2 Place of Residence โฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ 22
5.1.3 Type of Residence โฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ 25
5.1.4 Study-Abroad Experience โฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ 27
5.2 Human Capital: Parents Education Level โฆโฆโฆโฆโฆโฆโฆโฆโฆ 34
5.2.1 Father: Years of Education โฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ 34
5.2.2 Mother: Years of Education โฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ 43
5.2.3 Parents Overseas Education โฆโฆโฆโฆโฆโฆโฆโฆโฆ 44
5.3 Social Capital: Parental Involvement โฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ 45
5.3.1 Mothers Employment Status โฆโฆโฆโฆโฆโฆโฆโฆโฆ 46
5.3.2 Parent-Student Conversation โฆโฆโฆโฆโฆโฆโฆโฆโฆ 49
5.3.3 Number of Siblings โฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ 50
5.3.4 Birth Order โฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ 51
5.4 Personal Effort โฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ 52
5.4.1 Hours of Sleep โฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ 52
5.4.2 Hagwon Fees โฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ 54
5.4.3 Private Tutoring Fees โฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ 55
Chapter 6. Conclusion โฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ 57
6.1 Summary of Findings โฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ 57
6.2 Implications of Research โฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ 59
6.3 Limitations & Propositions for Future Research โฆโฆโฆโฆโฆโฆโฆ 60
References โฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ 61
๊ตญ๋ฌธ์ด๋ก (Abstract in Korean) โฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆโฆ 66Maste
์ 2๊ธ ์๋์์ ๊ตฌ์น๋ถ ๋ณตํฉ๋ ์ง์ ๋ฏธ์ธ๋ณ์ฐ ๋์ถ์ ๊ดํ ์ฐ๊ตฌ
ํ์๋
ผ๋ฌธ(์์ฌ)--์์ธ๋ํ๊ต ๋ํ์ :์น์ํ๊ณผ ์น๊ณผ๋ณด์กดํ์ ๊ณต,2002.Maste
AI and Text-Mining Applications for Analyzing Contractorโs Risk in Invitation to Bid (ITB) and Contracts for Engineering Procurement and Construction (EPC) Projects
Contractors responsible for the whole execution of engineering, procurement, and construction (EPC) projects are exposed to multiple risks due to various unbalanced contracting methods such as lump-sum turn-key and low-bid selection. Although systematic risk management approaches are required to prevent unexpected damage to the EPC contractors in practice, there were no comprehensive digital toolboxes for identifying and managing risk provisions for ITB and contract documents. This study describes two core modules, Critical Risk Check (CRC) and Term Frequency Analysis (TFA), developed as a digital EPC contract risk analysis tool for contractors, using artificial intelligence and text-mining techniques. The CRC module automatically extracts risk-involved clauses in the EPC ITB and contracts by the phrase-matcher technique. A machine learning model was built in the TFA module for contractual risk extraction by using the named-entity recognition (NER) method. The risk-involved clauses collected for model development were converted into a database in JavaScript Object Notation (JSON) format, and the final results were saved in pickle format through the digital modules. In addition, optimization and reliability validation of these modules were performed through Proof of Concept (PoC) as a case study, and the modules were further developed to a cloud-service platform for application. The pilot test results showed that risk clause extraction accuracy rates with the CRC module and the TFA module were about 92% and 88%, respectively, whereas the risk clause extraction accuracy rates manually by the engineers were about 70% and 86%, respectively. The time required for ITB analysis was significantly shorter with the digital modules than by the engineers.11Nsciescopu