180 research outputs found
์ค๊ฐ๋ณํ๋ฅ ์๋ ์ฌํ์์์ ํก๋ฑ๋ฐฉ์ฑ ์์์ ํ๊ดด ๊ฑฐ๋
ํ์๋
ผ๋ฌธ(์์ฌ) -- ์์ธ๋ํ๊ต๋ํ์ : ๊ณต๊ณผ๋ํ ์๋์ง์์คํ
๊ณตํ๋ถ, 2022.2. ์ ์์.Rocks involved with mechanized excavation via moving rock cutting tools are known to be under the influence of intermediate strain rate loading. In the mechanical excavation of rock, the cutting efficiency is affected by discontinuities, while the density of discontinuities and the direction of excavation against discontinuities greatly affect the efficiency of cutting. However, the deformation and fracture behavior of rocks vary depending on the changes in loading rate. It is known that under higher loading rates, rocks show relatively higher strength and low anisotropic behaviors. In this research, strength properties under static and intermediate strain rate loadings were studied using transversely isotropic rocks and artificially made rock-like specimens of similar characteristics. Since the uniaxial compressive strength of transversely isotropic rocks is known to show โUโ form when tested by its angles formed by loading direction and isotropic axis through theoretical and experimental research, this study was to examine the changes of its form under different loading or strain rate loadings.
The specimens of the study were schist from Boryeong area of Korea, cement mortar, and 3D printed materials in form of transversely isotropic behaviors. The cement mortar specimen had been cored from an artificial block which cement mortar had been alternatively layered by two different mixing ratios; 100:0 and 70:30 of commercial cement mix:sand from Jumunjin area of Korea. Each layer was to be of 10 mm in thickness. Objet30Pro of Stratasys was used for 3D printing, while PMMA material was used for the specimen. Grid modeled plane formed of 1mm thickness and height located every 1 mm was removed from the cylinder to express weak layers every 10 mm. Artificial specimens consisting of 0, 15, 30, 45, 60, 75, 90 degrees of transversely isotropic angles were manufactured. Three loading conditions were used for the test, which were 0.0067 mm/s and 10 mm/s of displacement-controlled loading rate for pressure machine and dynamic condition of free fall for drop weight test machine. Through the uniaxial compression test, the maximum strength was measured with specimens with degree of anisotropy near 0 and 90 degrees when the minimum strength was measured near 45 and 60 degrees. All tests had shown the โUโ form and its anisotropic behavior could be found to take less effect as the loading rate increased. An increase of strength proportion to its loading rate, or strain rate, could only be related to the test results from the same testing method.
By the use of Particle Flow Code 3D (PFC3D) by Itasca, a program to perform discrete element method (DEM) analysis, test results were to be reproduced via numerical simulation. Weak planes were expressed using smooth-joint contacts, weakening the bond among particles. The loading rates in the range of quasi-static and intermediate strain rate was used during the simulation. However, change of loading rate under same micro parameters did not show proper simulation results, requiring further studies. As tests proceeded, the result showed the form of โUโ, where the maximum strength was measured near models with degree of anisotropy near 0 and 90 degrees while the minimum strength was measured near 45 and 60 degrees.์์์ ๋์ ๊ฐ๋์ ์ทจ์ฑ ํ๊ดด๊ฑฐ๋์ ๋ณด์ด๋ ํน์ฑ์ ๊ฐ๋๋ค. ์์์ ๊ตด์ฐฉ์ ๋๋ถ๋ถ ๋ฐํ์ ๊ธฐ๊ณ์ ๊ตด์ฐฉ์ผ๋ก ์งํ๋๋ฉฐ ์ด ๊ฒฝ์ฐ ์์์ ๋์ ๋ณํ๋ฅ ์๋์ ๋
ธ์ถ๋๋ค. ํนํ, ์์์ ๊ธฐ๊ณ์ ๊ตด์ฐฉ ์ฅ๋น๋ฅผ ํ์ฉํ ์์์ ๊ตด์ฐฉ์์ ์์์ด ์ ์ญ๊ณต๊ตฌ์ ์ด๋ ํน์ ํ์ ์ ์ํ์ฌ ๊ตด์ฐฉ๋ ์ ์์์ ์ค๊ฐ๋ณํ๋ฅ ์๋์ ํ์ค ์ฌํ๋ฅผ ๋ฐ๋ ๊ฒ์ผ๋ก ๋ณด๊ณ ๋ ๋ฐ ์๋ค. ์๋ฐ์ ๊ธฐ๊ณ์ ๊ตด์ฐฉ์์ ์ ์ญํจ์จ์ ๋ถ์ฐ์๋ฉด์ ์ํ์ ์ํ์ฌ ์ํฅ์ ๋ฐ์ผ๋ฉฐ ํนํ ๋ถ์ฐ์๋ฉด์ ๋ฐ๋ ๋ฐ ๊ตด์ฐฉ ๋ฐฉํฅ๊ณผ ๋ถ์ฐ์๋ฉด์ด ์ด๋ฃจ๋ ๋ฐฉํฅ์ ํฐ ์ํฅ์ ๋ฐ๋๋ค. ๋ฐ๋ฉด, ์ฌํ์๋์ ๋ณํ์ ๋ฐ๋ผ ์์์ ๋ณํ ๋ฐ ํ๊ดด ๊ฑฐ๋์ด ๋ฌ๋ผ์ง๊ฒ ๋๋ฉฐ, ๋์ ์ฌํ์๋์์๋ ์๋์ ์ผ๋ก ๋์ ๊ฐ๋์ ๋ฎ์ ์ด๋ฐฉ์ฑ ํน์ฑ์ด ๋ฐํ๋๋ ๊ฒ์ผ๋ก ์๋ ค์ ธ ์๋ค.
์ด ์ฐ๊ตฌ์์๋ ํก๋ฑ๋ฐฉ์ฑ ์์๊ณผ ์ ์ฌ ์ํํธ์ ์ฌ์ฉํ์ฌ, ์ ํ์ค ์กฐ๊ฑด๊ณผ ์ค๊ฐ ๋ณํ๋ฅ ์๋์ ์์ถํ์ค ์ํ์์ ์ํํธ์ ๊ฐ๋ ํน์ฑ์ ๊ณ ์ฐฐํ๊ณ ์ ํ์๋ค.
ํก๋ฑ๋ฐฉ์ฑ ์์์ ์์ถ๊ฐ๋๋ ํ์ค๋ฐฉํฅ๊ณผ ๋ฑ๋ฐฉ์ถ์ด ์ด๋ฃจ๋ ๊ฐ๋์ ๋ณํ์ ๋ฐ๋ผ Uํ์ ํน์ฑ์ด ๋ํ๋จ์ด ์ด๋ก ์ , ์คํ์ ์ผ๋ก ์๋ ค์ ธ ์๋ ๋ฐ, ํ์ค ์๋, ์ฆ ๋ณํ๋ฅ ์๋๋ฅผ ๋ฌ๋ฆฌํ ๋ ๊ทธ ํํ์ ๋ณํ๋ฅผ ๊ณ ์ฐฐํ๊ณ ์ ํ์๋ค. ์ํํธ์ผ๋ก๋ ๋ณด๋ นํธ์, ํก๋ฑ๋ฐฉ์ฑ์ ๊ฐ๋๋ก ์ ์๋ ์๋ฉํธ๋ชจ๋ฅดํ๋ฅด ๋ฐ 3Dํ๋ฆฐํฐ ์ถ๋ ฅ๋ฌผ์ ์ด์ฉํ์๋ค. ์๋ฉํธ๋ชจ๋ฅดํ๋ฅด ์ํํธ์ ์๋ฉํธ์ ์ฃผ๋ฌธ์งํ์ค์ฌ๋ฅผ ์ค๋๋น 100:0, 70:30๋ก 2์ข
์ ๋ฐฐํฉํ์ฌ 10 mm ๋๊ป์ ๊ตํธ์ธต์ ์ด๋ฃจ๋๋ก ์ ์ํ์์ผ๋ฉฐ, ์ด๋ ์ํํธ์ ์ถ๋ฐฉํฅ๊ณผ ๋ฑ๋ฐฉ์ถ์ด 0, 15, 30, 45, 60, 75, 90๋์ ๊ฐ๋๋ฅผ ๊ฐ๋๋ก ํ์๋ค. 3Dํ๋ฆฐํฐ ์ถ๋ ฅ๋ฌผ์ Stratasys์ฌ Objet 30 Pro ํ๋ฆฐํฐ ๋ฐ ํฌ๋ช
PMMA์ฌ๋ฃ์ธ Veroclear๋ฅผ ์ฌ์ฉํ์ฌ ์ ์ํ์์ผ๋ฉฐ, 1 mm ๊ฐ๊ฒฉ์ ๊ฒฉ์๋ฌด๋ฌ๋ฅผ ์ฐ์ฝ์ธต์ผ๋ก ํ๊ณ ์ด๋ฅผ 10 mm ๊ฐ๊ฒฉ์ผ๋ก ๋ฐฐ์ดํ ํก๋ฑ๋ฐฉ์ฑ ์ํํธ์ผ๋ก ์ ์ํ์์ผ๋ฉฐ ์ด๋ฐฉ์ฑ ๊ฐ๋๋ ์๋ฉํธ๋ชจ๋ฅดํ๋ฅด ์ํํธ๊ณผ ๋์ผํ๋๋ก ํ์๋ค. ํ์ค ์กฐ๊ฑด์ผ๋ก 3๊ฐ์ง๋ฅผ ์ค์ ํ์์ผ๋ฉฐ, ๋ง๋ฅ์ํ๊ธฐ MTSํ์ค๊ธฐ๋ฅผ ์ด์ฉํ ์ ํ์ค๊ณผ ๋ํ์ค(์ฌํ์๋ 0.0067 mm/s, 10 mm/s)์ ๋จ์ถ์์ถ์ํ๊ณผ ์์ ๋ํ์ํ๊ธฐ๋ฅผ ์ด์ฉํ ๋ํ์ค ์ํ์ ์ค์ํ์๋ค. ํ์ค๊ธฐ๊ธฐ ์ํ ๊ฒฐ๊ณผ, 0ยฐ, 90ยฐ์ ๊ฐ๊น์์ง์๋ก ์ต๋ ๊ฐ๋๊ฐ ์ธก์ ๋์์ผ๋ฉฐ 45ยฐ, 60ยฐ์ ๊ฐ๊น์์ง์๋ก ์ต์ ๊ฐ๋๊ฐ์ด ์ธก์ ๋์๋ค. ์ต๋, ์ต์๊ฐ๋์ ๋ณํ ์์์ ์ ์งํ์์ผ๋ ์ ํ์ค(0.0067 mm/s์ฌํ)์์์ ๊ฐ๋๋ณด๋ค ๋ํ์ค(10 mm/s ์ฌํ)์์์ ๊ฐ๋๊ฐ ์ต์๊ฐ๋๋ ์ฝ 15%, ์ต๋๊ฐ๋๋ ์ฝ 3% ์ฆ๊ฐํ์ฌ ๋์ ์ฌํ์๋์์ ์ต์ ๋ฐ ์ต๋๊ฐ๋ ์ฌ์ด์ ํธ์ฐจ๊ฐ ์ค์ด๋ค์์์ ํ์ธํ์๋ค.
PFC3D(Particle Flow Code 3D)๋ฅผ ์ด์ฉํ ์์น๋ชจ์ฌ๋ฅผ ํตํ์ฌ ์ค๋ด ์ํ๊ฒฐ๊ณผ์ ์ฌํ๋ ๊ฒฐ๊ณผ๋ฅผ ๋น๊ตํ์ฌ ์ ๋์ ์ธ ๊ด๊ณ๋ฅผ ๋์ถํ๊ณ ์ ํ์๋ค. ํด์์ ์ ์์ ๊ฐ์์ฅ์น๋ฅผ ์ฌ์ฉํ๋ Quasi-static์์ค์ ๋ณํ๋ฅ ์๋์ธ 0.15 mm/s ์ 0.0015 mm/s์ ์ฌํ์๋๋ก ๊ฐ์ํ์๋ค. ์ค๋ด์คํ์ ๊ฒฐ๊ณผ์ ๋ง์ฐฌ๊ฐ์ง๋ก 45ยฐ, 60ยฐ์ ๊ฐ๊น์์ง์๋ก ๊ฐ๋์ ์ต์๊ฐ์ด ์ธก์ ๋์์ผ๋ฉฐ 0ยฐ, 90ยฐ์ ๊ฐ๊น์์ง์๋ก ๊ฐ๋์ ์ต๋๊ฐ์ด ๊ด์ฐฐ๋์๋ค.1. Introduction 1
2. Literature Review 11
2.1 Static and Dynamic Rock Test 11
2.2 Discrete Element Method 13
3. Test Setup 14
3.1 Types of Specimen 14
3.1.1 Cement Mortar Specimen 16
3.1.2 3D Printed Specimen 18
3.1.3 Rock Specimen 24
3.2 Types of Test 26
3.2.1 Uniaxial Compression 26
3.2.2 Drop Weight 33
4. Test Results and Discussion 35
4.1 Cement Mortar Specimen 35
4.1.1 Static Loading Test 35
4.1.2 Dynamic Loading Test 36
4.1.3 Drop Weight Test 38
4.2 3D Printed Specimen 40
4.2.1 Static Loading Test 40
4.2.2 Dynamic Loading Test 42
4.2.3 Drop Weight Test 43
4.3 Rock Specimen 46
4.3.1 Static Loading Test 46
4.3.2 Dynamic Loading Test 47
4.3.3 Drop Weight Test 49
5. Discrete Element Method 51
5.1 Commercial Program and Smooth-Joint Model Application 51
5.2 Modeling and Micro-Parameter Setting 51
5.3 Results 52
6. Conclusions 56
Reference 59
Abstract (Korean) 63์
Results from Korean Community Health Survey 2020
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ผ๋ฌธ(์์ฌ) -- ์์ธ๋ํ๊ต๋ํ์ : ๋ณด๊ฑด๋ํ์ ๋ณด๊ฑดํ๊ณผ, 2022. 8. ์กฐ์ฑ์ผ.Introduction: The unprecedented public health crisis, COVID-19(Coronavirus disease 2019) was accompanied by social, economic repercussions and was demanding change of the existing Korean medical system. In the process of responding to COVID-19, Korea made a meaningful achievement called โK quarantineโ, in which all efforts were prioritized to prevent infection. In the process, the public health system and local health system were partially suspended or reduced. Also, as the face-to-face interaction was restricted due to concerns about infection, the healthcare utilization rate also decreased significantly. There was no research on whether this decrease in medical use can be interpreted as an increase of unmet healthcare needs (UHNs). It was important to identify the associated factors of UHNs during the COVID-19 pandemic since UHNs can deteriorate the health problem of those who give up healthcare. Additionally, it could increase health inequity if UHNs were concentrated on the low-income population. The aims of this study were to check prevalence of UHNs and identify factors associated with UHNs during the pandemic of COVID-19 in Korea.
Methods: Data from the 2020 Community Health Survey was examined. Dependent variable was whether a respondent had experienced UHNs and independent variables were sociodemographic factors, health-related factors, and COVID-19 related factors. Multiple survey logistic regression analyses were performed after adjusting for all factors to identify factors associated with UHNs.
Results: UHNs decreased from 2019 to 2020 and 5.4% of South Koreans experienced UHNs in 2020. The most frequent reason of UHNs was โAvailabilityโ (48.1%), followed by โAcceptabilityโ (23.3%), โCOVID-19 related- reasonsโ (16.1%), Affordabilityโ (8.7%) and โAccessibilityโ (3.9%) in 2020. Female, younger age, low education level, low-income level, living alone, living in rural and blue-collar workers and other job group who were unemployed including students, housewives, military army were more likely to experience UHNs. And poor rated health, no chronic disease, and depressive symptom (PHQ-9 with score of 10 and above) were associated factors for increased UHNs.
Among COVID-19 related factors, individuals without fear of death, individuals with fear of infection of family, individuals who evaluated neighbors and co-workersโ performance in dealing with COVID-19 as โbadโ and who had no social supports from others during quarantine more likely to experience UHNs.
All sociodemographic and health-related factors that influenced UHNs due to non-COVID-19 related reasons were same as overall UHNs. Fear of death, fear of infection of family and social support are statistically significant factors to UHNs due to non-COVID-19 related reasons. Fear of infection is statistically significant factor to UHNs due to COVID-19. Fear of death and social support are not statistically significant.
Conclusions: Although South Korea has witnessed a steady decrease in UHNs, UHNs due to COVID-19 related reason occurred in 2020. This study identifies that the effects of fear of death and fear of infection on UHNs are different. Low socio-economic groups had higher frequency for โaffordabilityโ, โaccessibilityโ for UHNs and it should be noted that the low socio-economic group was more vulnerable to the pandemic, leading to increased health inequity. This study suggests that a different approach and customized policy are required depending on type of fear and socioeconomic status.์ฝ๋ก๋19๋ผ๋ ์ ๋ก์๋ ๊ณต์ค๋ณด๊ฑด ์๊ธฐ์ํฉ์ ์ฌํ์ , ๊ฒฝ์ ์ ํ์ฅ๊ณผ ํจ๊ป ๋ณด๊ฑด์๋ฃ์ฒด๊ณ์๋ ๋ณํ๋ฅผ ์๊ตฌํ๋ ๊ณ๊ธฐ๊ฐ ๋์๋ค. ์ฐ๋ฆฌ๋๋ผ์ ์ฝ๋ก๋19 ๋์์ ICT๊ธฐ์ ์ ๋ฐํ์ผ๋ก ๋น ๋ฅด๊ณ ์ ํํ ์ง๋จ, ํฌ๊ด์ ์ธ ๊ฒฝ๋ก ์ถ์ , ์ ์ ํ ์น๋ฃ๋ก ์์ฑ๋โK ๋ฐฉ์ญโ ์ด๋ผ๋ ์๋ฏธ ์๋ ์ฑ๊ณผ๋ฅผ ์ฐฝ์ถํ์์ผ๋, ๊ฐ์ผ ์๋ฐฉ๊ณผ ๋ฐฉ์ญ์ ๋ํ ๊ฐ์ฉ์์ ์ง์ค์ผ๋ก ์ธํด ๋ง์ฑ์งํ๊ด๋ฆฌ์ ๊ฑด๊ฐ์ฆ์ง์ ๊ฒฌ์ธํ๋ ๊ณต๊ณต์๋ฃ์ฒด๊ณ์ ์๋น์ค ๊ณต๋ฐฑ์ด๋ ์ถ์๊ฐ ๋ฐ์ํ๊ธฐ๋ ํ๋ค. ๊ฑฐ๋ฆฌ๋๊ธฐ ๋ฐฉ์ญ์ ์ฑ
์ผ๋ก ๋๋ฉด ํ๋์ด ์ ํ๋๋ฉด์ ์๋ฃ์ด์ฉ๋ ํฌ๊ฒ ๊ฐ์ํ์๋๋ฐ ์ด๋ฌํ ์๋ฃ ์ด์ฉ ๊ฐ์๊ฐ ์ค์ ์๋ฃ์ ํ์๊ฐ ์์์์๋ ๋ถ๊ตฌํ๊ณ ์น๋ฃ๋ฅผ ๋ฐ์ง ๋ชปํ ๋ฏธ์ถฉ์กฑ ์๋ฃ์ธ์ง ํฌ๋ฐ๋ฏน ์ด์ ์ ๋ถํ์ํ ์๋ฃ์ด์ฉ์ด ๊ฐ์ํ ๊ฒ์ธ์ง๋ฅผ ํ์ธํ๋ ๊ฒ์ ์๋ฏธ ์๋ ์ฐ๊ตฌ๊ฐ ๋ ๊ฒ์ด๋ค. ๋ฏธ์ถฉ์กฑ ์๋ฃ๋ ์ ์ ํ ์น๋ฃ๋ฅผ ๋ฐ์ง ๋ชปํ ์ฌ๋๋ค์ ๊ฑด๊ฐ์ ์
ํ์ํฌ ์ ์์ผ๋ฉฐ, ๊ฐ๋ํ ์ฌ๋๋ค์๊ฒ ์ง์ค๋๋ค๋ฉด ๊ฑด๊ฐ๋ถํ๋ฑ์ ์ฆ๊ฐ์ํฌ ์ ์๋ค. ์ด๋ฌํ ๊ฑด๊ฐ์ํ์ ์๋ฐฉํ๊ณ ๊ด๋ฆฌํ๊ธฐ ์ํด ๋ฏธ์ถฉ์กฑ ์๋ฃ์ ์ํฅ์ ๋ฏธ์น๋ ์์ธ์ ๊ท๋ช
ํ๋ ๊ฒ์ด ํ์ํ๋ค.
๋ณธ ์ฐ๊ตฌ์๋ ํฌ๋ฐ๋ฏน ์๊ธฐ์ ๋ฐ์ํ ๋ฏธ์ถฉ์กฑ ์๋ฃ ํํฉ์ ์ดํด๋ณด๊ณ , ๋ฏธ์ถฉ์กฑ ์๋ฃ์ ์ด์ ๋ฅผ ์ธ๋ถํํ์ฌ ํฌ๋ฐ๋ฏน์ด ๋ฏธ์ถฉ์กฑ ์๋ฃ ๋ฐ์์ ๋ฏธ์น๋ ์ํฅ์ ํ์ธํ๊ณ ์ ํ์๋ค. ๋ณธ ์ฐ๊ตฌ์ ์ด์ฉํ ์๋ฃ๋ 2020๋
์ง์ญ์ฌํ๊ฑด๊ฐ์กฐ์ฌ ๊ฒฐ๊ณผ ์ป์ด์ง ์ ๊ตญ ์ฑ์ธ ์ฝ 23๋ง๋ช
์ ์๋ต์๋ฃ์ด๋ค. ์กฐ์ฌ์ํ๊ธฐ๊ฐ์ 2020๋
8์ 16์ผ๋ถํฐ 10์ 31์ผ๊น์ง์ด๋ฉฐ, ์ ๊ตญ ์๊ตฐ ๊ตฌ ๋จ์ 255๊ฐ ๋ณด๊ฑด์์ ๊ดํ ์ง์ญ์์ ์ฃผํ์ ํ๊ณผ ์ธ๊ตฌ๊ตฌ์ฑ์ ๊ณ ๋ คํ ๋ณตํฉํ๋ณธ ์ถ์ถ์ ํตํด ์ ์ ํ ๊ฐ๊ตฌ๋ฅผ ๋์์ผ๋ก ๋ง 19์ธ์ด์ ์ฑ์ธ ๊ฐ๊ตฌ์์ ๋ชจ๋ ์กฐ์ฌํ์๋ค. ์ ์ฒด ์๋ต์ 229,269๋ช
์ค ๋ฏธ์ถฉ์กฑ ์๋ฃ๊ฒฝํ์ ๋ฌป๋ ์ง๋ฌธ์ ์๋ตํ์ง ์์ 18,237๋ช
์ ์ ์ธํ 211,032๋ช
(์ฌ์ 116,994๋ช
55.4%)์ ์๋ฃ๋ฅผ ๋ถ์ํ์๋ค.
๋
๋ฆฝ๋ณ์๋ก๋ ์ธ๊ตฌ์ฌํํ์ ํน์ฑ, ๊ฑด๊ฐํํ, ๋ง์ฑ์งํ ์ง๋จ๊ฒฝํ๊ณผ ์ฝ๋ก๋ ๊ฐ์ผ์ฌ๋ถ, ์ฝ๋ก๋์ ๋ํ ์ธ์ ๋ฑ์ ํฌํจํ์์ผ๋ฉฐ ์ข
์๋ณ์๋ก๋ ๋ฏธ์ถฉ์กฑ ์๋ฃ ๊ฒฝํ์ ์ฌ์ฉํ์๋ค.
์ ์ฒด ์๋ต์์ 5.4%๊ฐ ๋ฏธ์ถฉ์กฑ ์๋ฃ๋ฅผ ๊ฒฝํํ๋ค๊ณ ์๋ตํ์ฌ, ์ด๋ 2019๋
๋ณด๋ค ๊ฐ์ํ ์์น์ด๋, ๋ฏธ์ถฉ์กฑ ์๋ฃ ์ด์ ๋ฅผ ์ธ๋ถํํ์ฌ ์ดํด๋ณด๋ฉด ์๊ฐ์ ๊ฐ์ฉ์ฑ (Availability, 48.1%), ์์ฉ์ฑ(Acceptability, 23.3%), ์ฝ๋ก๋ ๊ด๋ จ ์์ธ (COVID-19 related, 16.1%), ์ง๋ถ๋ฅ๋ ฅ(Affordability, 8.7%), ๋ฌผ๋ฆฌ์ ์ ๊ทผ์ฑ (Accessibility, 3.9%)์์ผ๋ก ๋ฏธ์ถฉ์กฑ ์๋ฃ๋ฅผ ๊ฒฝํํ๋ค๊ณ ์๋ตํ์ฌ ์ฝ๋ก๋๋ก ์ธํ ์ด์ ๊ฐ ์ธ๋ฒ์งธ๋ก ๋ง์์ ํ์ธํ์๋ค.
์ธ๊ตฌ ์ฌํํ์ ๋ณ์, ๊ฑด๊ฐ ๊ด๋ จ๋ณ์์ ์ฝ๋ก๋ ๊ด๋ จ๋ณ์๋ฅผ ๋ชจ๋ ๋ณด์ ํ์ฌ ๋ฏธ์ถฉ์กฑ ์๋ฃ์ ์ํฅ์์ธ์ ๋ถ์ํ ๊ฒฐ๊ณผ ์ฌ์ฑ, ์ ์ ์ฐ๋ น, ๋ฎ์ ๊ต์ก์์ค, ๋ฎ์ ์๋์์ค, 1์ธ ๊ฐ๊ตฌ, ์๊ณจ ๊ฑฐ์ฃผ, ์ก์ฒด๋
ธ๋์(Blue collar) ๋ฐ ๊ธฐํ(ํ์, ์ฃผ๋ถ, ๊ตฐ์ธ ๋ฑ)์์, ์ฃผ๊ด์ ๊ฑด๊ฐ์ํ๊ฐ ๋์๊ณ , ์๊ฐ ๋ง์ฑ์งํ์ด ์๋ ๊ฒฝ์ฐ, ์ฐ์ธ์ฆ์ธ๊ฐ ์๋ ๊ฒฝ์ฐ(PHQ-9 10์ ์ด์)์์ ๋ฏธ์ถฉ์กฑ ์๋ฃ๊ฒฝํ์ด ์ฆ๊ฐํ์๋ค. ์ฝ๋ก๋ ๊ฐ์ผ์ผ๋ก ์ธํ ์ฃฝ์์ ๋ํด ๋๋ ค์์ด ์๋ ๊ตฐ์ด ๋๋ ค์์ด ์๋ ๊ตฐ์ ๋นํด ํต๊ณ์ ์ผ๋ก ์ ์ํ๊ฒ ๋ฏธ์ถฉ์กฑ ์๋ฃ๊ฒฝํ์ด ๊ฐ์ํ์์ผ๋, ๊ฐ์กฑ(๊ฑด๊ฐ์ทจ์ฝ์)์ ๊ฐ์ผ์ ๋ํ ๋๋ ค์์ด ์๋ ๊ตฐ์ ๋๋ ค์์ด ์๋ ๊ตฐ์ ๋นํด ๋ฏธ์ถฉ์กฑ ์๋ฃ๊ฒฝํ์ด ๋ ๋์๋ค. ์ด์๊ณผ ์ง์ฅ๋๋ฃ์ ์ฝ๋ก๋ ๋์๋ฅ๋ ฅ์ด ์ ์ ํ์ง ์๋ค๊ณ ํ๋จํ ๊ตฐ, ์๊ฐ ๊ฒฉ๋ฆฌ๋์ ๋์์ ์์ฒญํ ์ ์๋ ์ฃผ๋ณ์ธ์ด ์๋ ๊ตฐ์์ ๋ฏธ์ถฉ์กฑ ์๋ฃ๊ฒฝํ์ด ์ฆ๊ฐํ์๋ค.
๋ฏธ์ถฉ์กฑ ์๋ฃ๋ฅผ ๊ฒฝํํ๊ฒ ๋ ์ด์ ๋ฅผ ์ฝ๋ก๋๋ก ์ธํ ์ด์ ์ ๊ทธ ์ธ์ ์ด์ ๋ก ๋๋์ด ๋ฏธ์ถฉ์กฑ ์๋ฃ ์ํฅ์์ธ์ ํ์ธํ์์ ๋, ์ฝ๋ก๋ ์ด์ธ์ ์ด์ ๋ก ๋ฏธ์ถฉ์กฑ ์๋ฃ๋ฅผ ๊ฒฝํํ ๊ตฐ์ ์ธ๊ตฌ์ฌํํ์ ๋ณ์์ ๊ฑด๊ฐ ๊ด๋ จ ๋ณ์๋ ๋ชจ๋ ๋ฏธ์ถฉ์กฑ ์๋ฃ ๊ด๋ จ์์ธ๊ณผ ๋์ผํ์์ผ๋, ์ฝ๋ก๋ ๊ด๋ จ ์์ธ ์ค ํต๊ณ์ ์ ์์ฐจ๊ฐ ์๋ ์์ธ์ ์ฃฝ์์ ๋ํ ๋๋ ค์, ๊ฐ์กฑ(๊ฑด๊ฐ์ทจ์ฝ์)์ ๊ฐ์ผ์ ๋ํ ๋๋ ค์, ์ด์๊ณผ ์ง์ฅ๋๋ฃ์ ์ฝ๋ก๋ ๋์๋ฅ๋ ฅ ๋ฐ ๊ฒฉ๋ฆฌ ์ ๋์์ ์์ฒญํ ์ ์๋ ์ฃผ๋ณ์ธ์ ์ ๋ฌด์๋ค.
์ฝ๋ก๋๋ก ์ธํ ์ด์ ๋ก ๋ฏธ์ถฉ์กฑ ์๋ฃ๋ฅผ ๊ฒฝํํ ๊ตฐ์ ์ํฅ ์์ธ์ ๊ฒฝ์ฐ ๋ชจ๋ ๊ฑด๊ฐ ๊ด๋ จ ๋ณ์๋ ๋ฏธ์ถฉ์กฑ ์๋ฃ ๊ด๋ จ์์ธ๊ณผ ๋์ผํ์์ผ๋, ์ธ๊ตฌ์ฌํํ์ ํน์ฑ ์ค 1์ธ ๊ฐ๊ตฌ์ฌ๋ถ์ ๊ต์ก์์ค์ ํต๊ณ์ ์ ์์ฐจ๋ ์์๋ค. ๋ํ ์ฃฝ์์ ๋ํ ๋๋ ค์๊ณผ ๊ฒฉ๋ฆฌ ์ ๋์์ ์์ฒญํ ์ ์๋ ์ฃผ๋ณ์ธ์ ์ ๋ฌด๋ ํต๊ณ์ ์ ์์ฐจ๋ ์์์ผ๋ฉฐ ๊ฐ์ผ์ ๋ํ ๋๋ ค์์ด ์๋ ๊ตฐ์์ ๋ฏธ์ถฉ์กฑ ์๋ฃ๊ฒฝํ์ด ๊ฐ์ํ๋ ๊ฒฐ๊ณผ๋ฅผ ๋ณด์ฌ ์ฝ๋ก๋ ์ด์ธ์ ์ด์ ๋ก ์ธํ ๋ฏธ์ถฉ์กฑ ์๋ฃ ์ํฅ ์์ธ๊ณผ๋ ๋ค๋ฅธ ์์์ ๋ณด์๋ค.
๋ณธ ์ฐ๊ตฌ๋ฅผ ํตํ์ฌ ๊ฐ์ผ์ ๋ํ ๋๋ ค์๊ณผ ์ฃฝ์์ ๋ํ ๋๋ ค์์ด ๋ฏธ์ถฉ์กฑ ์๋ฃ์ ๋ฏธ์น๋ ์ํฅ์ด ์๋ก ๋ค๋ฆ์ ํ์ธํ ์ ์์๊ณ , ์ฝ๋ก๋๋ก ์ธํ ์ด์ ์ ์ฝ๋ก๋ ์ด์ธ์ ์ด์ ๋ก ์ธํ ๋ฏธ์ถฉ์กฑ ์๋ฃ์ ์ํฅ ์์ธ์ ์์ดํ์ฌ ๋ฏธ์ถฉ์กฑ ์๋ฃ๊ฐ ๋ฐ์๋ ์ด์ ์ ๋ฐ๋ผ ๋ค๋ฅธ ์ ๊ทผ ๋ฐ ์ ์ฑ
์ด ํ์ํ๋ค๋ ๊ฒ์ ํ์ธํ ์ ์์๋ค.
์ฝ๋ก๋ ํฌ๋ฐ๋ฏน ๊ธฐ๊ฐ ๋์ ์ฌ์ฑ, ๋ฎ์ ๊ต์ก์์ค, ๋ฎ์ ์๋์์ค ๋ฐ 1์ธ ๊ฐ๊ตฌ ๋ฑ ์ทจ์ฝ๊ณ์ธต์ ์ผ๋ฐ๊ตญ๋ฏผ์ ๋นํด ๋ฏธ์ถฉ์กฑ ์๋ฃ๋ฅผ ๋ ๋ง์ด ๊ฒฝํํ์์ผ๋ฉฐ, ์ฌํ์ ์ทจ์ฝ๊ณ์ธต์ด ์ฝ๋ก๋๋ก ์ธํ ๊ฒฝ์ ์ ํ๊ฒฉ์ด ํฌ๊ณ ์ฐ์ธ๊ฐ๊ณผ ์ง๋ณ์ ๋ํ ์ฐ๋ ค๊ฐ ๋ ํฌ๊ธฐ ๋๋ฌธ์ ์ทจ์ฝ๊ณ์ธต์ ๋์ฑ ์ธ๋ถํ๋ ์ ๊ทผ์ด ํ์ํ๊ฒ ๋ค.
๋ณธ ์ฐ๊ตฌ๋ 2020๋
๋์ ์์งํ ๋ฐ์ดํฐ๋ฅผ ๋ฐํ์ผ๋ก ๋ถ์ํ ๊ฒฐ๊ณผ๋ก ์ฅ๊ธฐ๊ฐ ์ง์๋๋ ๊ฐ์ผ๋ณ ์๊ธฐ์๋์ ์๋ฃ์ด์ฉ ํํ ๋ณํ๋ฅผ ํ์ธํ๊ธฐ ์ํด์๋ ๋ณด๋ค ์ฅ๊ธฐ์ ์ฐ๊ตฌ๊ฐ ์ถ๊ฐ์ ์ผ๋ก ํ์ํ๊ฒ ๋ค. ๋ํ ์ฝ๋ก๋ ํฌ๋ฐ๋ฏน ๊ธฐ๊ฐ ๋์์ ๋ฏธ์ถฉ์กฑ ์๋ฃ ๋ฐ์์ด ๋ฐฉ์ญ์ ์ฑ
์ ๋ฐ๋ฅธ ์ด์ ์์ ๋ถํ์ํ ๊ฒ์ฌ์ ์น๋ฃ๊ฐ ์ค์ด๋ ์ํฅ ๋๋ฌธ์ธ์ง ์ค์ ์๋ฃ์ ํ์๊ฐ ์์์์๋ ๋ถ๊ตฌํ๊ณ ์น๋ฃ๋ฅผ ๋ฐ์ง ๋ชปํ ๋ฏธ์ถฉ์กฑ ์๋ฃ์ธ์ง ์ฌ๋ถ๋ฅผ ํ์ธํ ํ์๊ฐ ์๊ฒ ๋ค.Chapter1. Introduction
1.1 COVID-19 and decrease of healthcare utilization
1.2 Unmet healthcare needs (UHNs)
1.3 Objective of this study
Chapter2. Study method
2.1 Data source
2.2 Study design
1) Study population
2) Dependent variables
3) Independent variables
(1) Sociodemographic variables
(2) Health related variables
(3) COVID-19 related variables
2.3 Statistical analysis
Chapter3. Study Result
3.1 Baseline characteristics by UHNs
3.2 Factors associated with UHNs
3.3 Socio-demographic & health-related factors by UHN reasons
3.4 Factors associated with UHNs due to COVID-19 related reasons, non-COVID-19 related reasons
Chapter4. Discussion
4.1 Discussion
4.2 Limitations
4.3 Conclusions
Bibliography
Abstract in Korean์
์ง์ค์ ์ฑ๋ถ์ฐ๊ตฌ
ํ์๋
ผ๋ฌธ (์์ฌ)-- ์์ธ๋ํ๊ต ๋ํ์ : ์ฝํ๋ํ ์ฝํ๊ณผ, 2018. 8. ์ ์ข
ํ.Abstract
Isolation and Structure Determination of Bioactive Constituents from Poncirus trifoliata Raf.
Won-Hee Lee
Natural Products Science Major
College of Pharmacy
Master Course in the Graduate School
Seoul National University
Sortase A (SrtA), a gram-positive transpeptidase, is an important target in reducing bacterial infection. The extract from the fruits of trifoliate orange, Poncirus trifoliata Rafinesque, showed significant Srt A inhibition.
Poncirus trifoliata Raf. is a member of the family Rutaceae and it has been widely used in Korean traditional medicine for the treatment of diverse pathogenic symptoms.
Bioactivity-guided chromatographic separation afforded the isolation of in total twelve compounds, eight coumarins and four flavanone glycosides.
The structures of four novel coumarins were determined by a combination of spectroscopic analyses such as NMR and LC-MS.
The absolute configurations of the new coumarins and known coumarins, previously unassigned, were determined by an application of the 2-methoxy-2-(trifluoromethyl)phenylacetic acid (MTPA) method.
Key words: herbal medicine, Poncirus trifoliata Rafinesque, coumarins, flavanone glycosides, sortase A inhibition
Student number: 2016-29626Introduction . 1
Experimental Section 3
1. General Experimental Procedures 3
2. Plant Material . 3
3. Extraction and Isolation 4
4. Preparation of the (S)- and (R)-ฮฑ-Methoxy-ฮฑtrifluoromethylphenylacetic chloride (MTPA-Cl) Esterification of Compound 1-6 6
Results . 12
1. Compound 1 . 12
2. Compound 2 . 12
3. Compound 3 . 13
4. Compound 4 . 13
5. Compound 5 . 14
6. Compound 6 . 14
7. Compound 7 . 15
8. Compound 8 . 15
9. Compound 9 . 16
10. Compound 10 . 16
11. Compound 11 16
12. Compound 12 . 17
Discussion 40
References . 41
Abstract in Korean . 75Maste
A study on รlvaro Siza's strategy of realizing architectural space inducing spatial experiences - focusing on the public buildings since 1985
ํ์๋
ผ๋ฌธ (์์ฌ)-- ์์ธ๋ํ๊ต ๋ํ์ : ๊ฑด์ถํ๊ณผ, 2012. 8. ์ต๋๋จ.๋ณธ ์ฐ๊ตฌ๋ ์์ ๋ง์ ๋
ํนํ ๊ฐ๊ฐ์ ๊ฐ์ง๊ณ ์ง์ญ์ ๋ฌธํ์ ์ ํต์ ์์ฉํ๋ฉด์๋ ๋ชจ๋๋์ฆ์ ๋ณดํธ์ฑ์ ๊ฒฐํฉํ๋ ํ๋๊ฑด์ถ๊ฐ ์๋ฐ๋ก ์์์ ๊ฑด์ถ์ ๋ํด ์ฌ๋๋ค์ด ์ง์ ์ฒดํํ๋ ์ธก๋ฉด์์ ๋ถ์ํด ๋ณด๊ณ ์ ํ๋ ์๋์์ ์์๋์๋ค.
์์์ ๊ฑด์ถ์ ๋ํ ๊ธฐ์กด์ ์ฐ๊ตฌ๋ค์ ์ ํต๊ณผ ๋ฌธํ์ ์์ฉ, ์ถ์ ๋ฐ์, ์์ ํํ, ๊ฐํฅ์ ์ฃผ๋ ๊ฑด์ถ ๋ฑ ์ถ์์ ์ด๊ณ ๊ฐ๋
์ ์ธ ์ดํ๋ค๋ก ์์์ ๊ฑด์ถ ๋์์ธ ๋ฐฉ๋ฒ์ ๋ํด ์๋ฏธํ๋ฅผ ํ๊ฑฐ๋ ํํ์ ์ ํํ, ํน์ ํํ ์์์ ์น์คํ ๋ถ์ ๋ฑ์ด ๋๋ถ๋ถ์ด์๊ธฐ ๋๋ฌธ์ด๋ค.
์ด์ ๋ณธ ์ฐ๊ตฌ๋ ์์์ ๊ฑด์ถ์ ๋ํด ์ฒดํ์ ์ธก๋ฉด์์ ๋ถ์ํ๊ณ ๊ณต๊ฐ์ ์ฒดํ์ ๊ตฌํํ๋ ๋ฐฉ์๊ณผ ๊ทธ ํน์ง์ ๋ํด ๋ฐํ๋๋ฐ ๋ชฉ์ ์ด ์๋ค.
์์๋ ์์ ์ ๊ฑด์ถ ๊ฐ๋
์ ๋ํด ๋ช
ํํ ์ธ์ด๋ก ๊ท์ ํ์ง ์๊ธฐ ๋๋ฌธ์ ๋จผ์ ์์์ ๊ฑด์ถ์์ ์ฒดํ์ ๊ฐ๋
์ด ๋ฌด์์ธ๊ฐ์ ๋ํด ์ ๋ฆฌํ ํ์๊ฐ ์๋ค. ๋นํ๊ฐ๋ค๊ณผ ์์์ ์ธ์ ์ ํตํด ๋์ถํ, ์์์ ๊ฑด์ถ ๊ณต๊ฐ์์ ์ฒดํ์ ๊ฐ๋
์ ์ฒซ์งธ, ์์ง์์ ํตํ ๊ณต๊ฐ์ ์ฒดํ, ๋์งธ, ์ฌ์ฉ์์ ์ํ ๊ณต๊ฐ์ ํด์, ์
์งธ, ๊ณต๊ฐ์ ์ฐ์์ ๊ด๊ณ์ ์ฒดํ์ด๋ค.
์ด๋ฅผ ํตํด ์์์ ๊ฑด์ถ์ ์ฒดํ์ ์ ๋ฐํ๋ ๊ฑด์ถ์ผ๋ก ์ฌ์ ์ ํ๊ณ ์ด๋ฌํ ๊ณต๊ฐ์ ์ฒดํ์ ์ ๋ฐํ๊ธฐ ์ํ ๊ตฌํ๋ฐฉ์์ ์ธ ๊ฐ์ง๋ก ์ ๋ฆฌํ์๋ค.
์ฒซ์งธ, ์์ง์์ ํตํด ์ฒดํ์ ์ ๋ฐํ๋ ๋ฐฉ์์ผ๋ก๋ ๋งค์ค์ ๋ถ์ , ๋ชจํธํ ์
๊ตฌ, ๋ค์ํ ์ธต์์ ๋ฒฝ์ด ์๋ค.
๋์งธ, ์ฌ์ฉ์์ ํด์์ ์ฌ์ง๋ฅผ ๋จ๊น์ผ๋ก์จ ์ฒดํ์ ์ ๋ฐํ๋ ๋ฐฉ์์ผ๋ก๋ ์๋์ ์ธ ๋ฏธ์์ฑ์ ํตํด ๋ํ๋๋ฉฐ ๋น์์ง ๊ณต๊ฐ๊ณผ ๋น์ ์ํ ๊ณต๊ฐ์ ๋ณํ๊ฐ ์ผ์ด๋๋๋ก ํ๋ ๊ฒ์ด๋ค.
์
์งธ, ์ฐ์์ ๊ด๊ณ์ ์ฒดํ์ ์ ๋ฐํ๋ ๋ฐฉ์์ผ๋ก๋ ๊ณต๊ฐ ๊ฐ ๊ด๊ณ์ ์กฐ์ ์ผ๋ก์, ํํ์ ๋ด๋ถ ๊ณต๊ฐ์ ๋ฐ์ , ์ฐฝ์ ํตํ ์์ฐ์ ์ ์
, ๋์ ์กฐ์ง๊ณผ์ ์กฐํ ๋๋ ๋ฐ์ ์ ๊ด๊ณ๋ฅผ ๋ง๋๋ ๊ฒ์ด๋ค.
์ด๋ฌํ ์ฒดํ์ ์ ๋ฐํ๋ ๊ฑด์ถ ๊ณต๊ฐ ๊ตฌํ๋ฐฉ์์ ํ ๊ฐ์ง ๋ฐฉ์์ด ํ ๊ฐ์ง์ ์๋ฏธ๋ก์๋ง ์์ฉํ๋ ๊ฒ์ด ์๋๋ผ ๋ค๋ฅธ ๊ตฌํ๋ฐฉ์๋ค๊ณผ ์ํธ์์ฉํ์ฌ ์ฌ๋๋ค์ด ๊ณต๊ฐ์ ๋ณตํฉ์ ์ผ๋ก ์ฒดํํ๋๋ก ํ๋ค. ๋ํ ํ๋์ ์ํ์์ ์ฌ๋ฌ ๊ฐ์ง ๋ฐฉ์์ด ๋ณตํฉ์ ์ผ๋ก ์ฌ์ฉ๋๊ธฐ๋ ํ๊ณ ์ฌ์ฉ๋์ง ์๊ธฐ๋ ํ๋๋ฐ ์ด๋ ์์์ ๊ฑด์ถ์ด ๋์ง์ ์กฐ๊ฑด๊ณผ ์ํฉ์ ๋ฐ๋ผ ๋ค๋ฅธ ํด๊ฒฐ ๋ฐฉ๋ฒ์ ๊ฐ๋ ํน์ฑ๊ณผ ๊ด๊ณ๊ฐ ์๋ค.
์ฒดํ์ ์ ๋ฐํ๋ ๊ณต๊ฐ ๊ตฌํ๋ฐฉ์์ ํตํ ์์์ ๊ฑด์ถ ๊ตฌ์ฑ๋ฐฉ์์ ๊ทธ ์ฑ๊ฒฉ์ด ๋ช
ํํ๊ฒ ๊ท์ ๋๋ ๊ฒ์ด ์๋๋ผ ์ฌ๋๋ค์๊ฒ ํด์ํ๊ณ ์ ํํ ์ ์๋ ์ฌ์ง๋ฅผ ๋จ๊ธฐ๋ ๊ฒ์ผ๋ก ๋ํ๋๋ค.
์ฒซ์งธ, ๋ค์ํ ์ํ์ค๋ฅผ ๋ ์ผ๋ก์จ ์ฌ๋๋ค๋ก ํ์ฌ๊ธ ์ ํํ ์ ์๋ ์ฌ์ง๋ฅผ ์ฃผ๊ณ , ๋ถ๋ถ์ ์ธ ์ํ์ค์ ๊ฒฝํ๊ณผ ๊ทธ ํฉ์ ํตํด ์ ์ฒด์ ์ธ ์ฒดํ์ด ํตํฉ๋ ์ ์๋๋ก ํ์ฌ ์ฌ๋๋ง๋ค ๋ค๋ฅธ ์ฒดํ์ด ์์ฑ๋ ์ ์๋๋ก ํ๋ค.
๋์งธ, ๋ฐ๋ณต์ ์ธ ์ฒดํ์ ํตํด ๊ทธ๊ฒ์ ๋งค๊ฐ๋ก ๊ธฐ์ต์ ์ฌ๊ตฌ์ฑ ํ๋๋ก ํ๋ค. ์ด๋ ๊ฐ์ ๊ณต๊ฐ์ ๋ค๋ฅธ ์์ ์์ ๋ฐ๋ณต์ ์ผ๋ก ๊ฒฝํํ ์ ์๋๋ก ํ๊ณ ๊ณตํต์์๋ฅผ ๊ณต๊ฐ์ ๋ฐ๋ผ ๋ณํํ์ฌ ์ฌ์ฉํจ์ผ๋ก์จ ๋ฐ๋ณต์ ์ผ๋ก ์ธ์ํ๋๋ก ํ๋ฉด์๋ ์ฌ๋๋ง๋ค ๊ฒฝํ์ ๋ํด ๋ค๋ฅธ ๊ธฐ์ต์ ๊ฐ๊ฒ ํ๋ค.
์
์งธ, ๋น๊ณผ ์ฐฝ์ ํตํ ๋์์์ ์ํต๊ณผ ๊ณต๊ฐ์ ์ํธ๊ด์
์ ํตํ ์์ฐ๊ณผ์ ์ฐ์์ ๊ด๊ณ๋ฅผ ๋๋ผ๋๋ก ํจ์ผ๋ก์จ ๊ณต๊ฐ์ด ์ฃผ๋ณ ํ๊ฒฝ๊ณผ ์ฌ๋์ ํฅํด ์ด๋ ค์๋ ๋๋์ ๊ฐ์ง๋๋ก ํ๋ค.
์์์ ๊ฑด์ถ์ ๋จ์ํ ํ์์ ์ด๊ณ ๊ฐ๊ฐ์ ์ธ ๊ณต๊ฐ์ ์ฒดํ ์ด์์ผ๋ก ๋์์ ์์ฐ๊ณผ์ ์ํต์ด ์ผ์ด๋ ์ ์๋๋ก ์ ๋ํ๊ณ ์ฌ๋๋ค์ ํ์์ ํด์์ ์ฌ์ง๋ฅผ ๋จ๊ธฐ๋ ์ฌํ์ ์ธ ์ฅ์๋ก์์ ์๋ฏธ๋ฅผ ๊ฐ์ง๋ค.
๋ณธ ์ฐ๊ตฌ์ ํ๊ณ์ ์ผ๋ก๋ ๋ถ์ํ์ ์์์ ์ธ ์์์ ๊ณต๊ฐ์ ์ฒดํ์ ๊ฐ๋
์ด ์์์ ๋นํ๊ฐ๋ค์ ์ธ์ ์ ํตํด ๋์ถํ ๊ฒ์ด๊ธฐ ๋๋ฌธ์ ๊ทธ ๊ฐ๋
์ด ์ ํ์ ์ผ ์ ์๋ค๋ ๊ฒ์ด๋ค. ์ด๋ฌํ ํ๊ณ์ ์ ๊ฑด์ถ ๊ณต๊ฐ์์์ ์ฒดํ์ ๊ดํ ์ฐ๊ตฌ๊ฐ ์ด๋ก ์ ์ด๊ณ ๊ฐ๋
์ ์ธ ์ธก๋ฉด๋ง์ ๋ค๋ฃจ๊ณ ์์ด ์ค์ง์ ์ธ ์ฐจ์์์ ๊ณต๊ฐ์ ๋ถ์ํ ์ ์๋ ํ์ด ๋ง๋ จ๋์ด ์์ง ์๊ธฐ ๋๋ฌธ์ด๊ธฐ๋ ํ๋ค.
ํฅํ ๊ณผ์ ๋ก์ ์ด๋ฌํ ๊ณต๊ฐ์ ์ฒดํ์ ๊ดํ ๊ตฌ์ฒด์ ์ธ ๋ถ์ํ์ด ์ค์ ๋๊ธธ ๊ธฐ๋ํด๋ณธ๋ค. ๋ํ ์์ ๊ฑด์ถ์ ํน์ง์ผ๋ก ์์ฃผ ์ธ๊ธ๋๋ ๋ฌธํ์ ์ ํต์ ๋ฐ์์ ๋ํ ๊ฒ์ด ๊ตฌ์ฒด์ ์ผ๋ก ์ด๋ป๊ฒ ์ฒดํ๋๋๊ฐ์ ๋ํด์๋ ์ค์ง์ ์ธ ์ธก๋ฉด์์ ๋ถ์ํ๋ค๋ฉด ์๋ฏธ๊ฐ ์์ ๊ฒ์ด๋ผ ๋ณธ๋ค.The purpose of study on รlvaro Siza is to analyze his architecture that is not only designed with regional culture and tradition embraced, but also universal Modernism combined with both, from the perspective of peoples spatial experiences.
Unlikely the above, most of the previous studies on the architectural design method that Siza uses are analyzed, signified or formalized using the abstract and conceptual words which bring the idea of tradition and culture embraced, reflection of life, poetic forms and inspiring architecture. This studytherefore, focuses on analyzing his architecture from an experiential aspect and reveal his architectural strategy for realizing spatial experiences.
It is, first, necessary to organize what the concept of spatial experiences is in Sizas architecture for he does not clearly define what his language of architecture is.
Drawn a conclusion from critics and Siza himself, the concept of spatial experiences in his architecture is 1, spatial experiences through circulating 2, interpretation on space by the users and 3, spatial experiences of continuous relationship. Through this conclusion, his architecture is redefined as architecture which induces spatial experiences, and three strategies for realizing such experiences are arranged.
First, the methods which induce spatial experiences through circulating are segmentation of masses, vague entrance and various layered walls making spatial depth.
Second, leaving choices for the users to interpret, it is purposely designed to be unfinished and changing spatially by empty space and light.
Third, adjusting a relationship between spaces, it induces spatial experiences in sequence that makes a reversal of form and internal spaces, penetration of nature through the windows, harmonious or reversal relationship with urban fabrics.
These strategies of inducing spatial experiences do not imply only one meaning but interrelate with other strategies, so people can experience space complexly. He also uses various methods in one project that is related for him to seek the different ways to solve problems according to the condition and situation of site.
As mentioned, Sizas articulation of spaces does not clearly define spatial characteristics but leaves chances for the users to experience and articulate spaces by themselves.
First, designing various spatial sequences, the users can choose to circulate from one space to another and it may differ due to different users circulating spaces in a different sequential order.
Second, it reconstructs memories through repetitive spatial experiences. Each person can experience same space and have different memory through using the transformation of common elements and experiencing repetitively as different views.
Third, space is defined as to be a social place by communicating with city through light, windows, and continual relation with nature through intercourse of space.
Sizas architecture, likewise, means more than phenomenal and sensible spaces to feel and experience. Not only has it encouraged communication between city and nature, but also leaved chances for the users to interpret space as a social place.
It may be the limit of this study that the framework for analysis may not be objective. Thats because there are only theoretical and conceptual approach on spatial experiences in previous studies not on the substantive frameworks. In this aspect, it can be expected for the next study on the framework for analyzing the spatial experiences. And it may have a meaning if a relation between culture, tradition and experience, which is mentioned frequently as a character of Sizas but this study does not contain, is analyzed using actual ways.์ 1 ์ฅ ์๋ก
1.1. ์ฐ๊ตฌ์ ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉ์
1.2. ์ฐ๊ตฌ์ ๋ฐฉ๋ฒ ๋ฐ ๋์
1.2.1. ์ฐ๊ตฌ์ ๋ฐฉ๋ฒ
1.2.2. ์ฐ๊ตฌ์ ๋์
์ 2 ์ฅ ์๋น ๊ณ ์ฐฐ: ์๋ฐ๋ก ์์ ๊ฑด์ถ์ ๋งฅ๋ฝ
2.1. ๊ฑด์ถ์ ์
์ฅ์ ํ์ฑ ๋ฐฐ๊ฒฝ
2.2. ์๋ฐ๋ก ์์ ๊ฑด์ถ์ ๋ํ ๊ธฐ์กด ์ฐ๊ตฌ
2.2.1. ๋นํ์ ์ง์ญ์ฃผ์(Critical Regionalism)
2.2.2. ํ์ค์ ๋ณํ(Transformation)
2.2.3. ์ ์ ์ ํ๋((Mental Activity)
2.2.4. ์ฌ์ฉ์์ ์ํตํ๋ ๊ฑด์ถ
2.2.5. ๊ณต๊ฐ์ ์ฒดํ
2.3. ์๋ฐ๋ก ์์ ๊ฑด์ถ๊ณต๊ฐ์ ์ฒดํ์ ๊ดํ ์ฌ์ธต์ฐ๊ตฌ ํ์
2.3.1. ๊ธฐ์กด ์ฐ๊ตฌ์ ํ๊ณ์ ๋ณด์
2.3.2. ์ฐ๊ตฌ์ ๋์ ๋ฐ ๋ฐฉ๋ฒ ์ ์
์ 3 ์ฅ ์ฒดํ์ ๊ดํ ์๋ฐ๋ก ์์์ ๊ฑด์ถ ์ธ์ด
3.1. ์๋ฐ๋ก ์์์ ์ธ์ ๊ณผ ๋นํ์ ํตํ ๋ถ์ํ ์ค์
3.1.1. ์๋ฐ๋ก ์์ ๊ฑด์ถ์ ์ฒดํ์ ๊ดํ ๋นํ
3.1.2. ์๋ฐ๋ก ์์์ ์ฒดํ์ ๊ดํ ์ธ์
3.1.3. ๋ถ์ํ ์ค์
3.2. ์๋ฐ๋ก ์์ ๊ฑด์ถ ๊ณต๊ฐ์์์ ์ฒดํ์ ๊ฐ๋
3.2.1. ์์ง์์ ํตํ ๊ณต๊ฐ์ ์ฒดํ
3.2.2. ์ฌ์ฉ์์ ์ํ ๊ณต๊ฐ ํด์
3.2.3. ๊ณต๊ฐ์ ์ฐ์์ ๊ด๊ณ ์ฒดํ
3.3. ์๊ฒฐ : ์๋ฐ๋ก ์์์ ์ฒดํ์ ์ ๋ฐํ๋ ๊ฑด์ถ ๊ณต๊ฐ
์ 4 ์ฅ ์๋ฐ๋ก ์์์ ์ฒดํ์ ์ ๋ฐํ๋ ๊ฑด์ถ ๊ณต๊ฐ ๊ตฌํ๋ฐฉ์
4.1. ์์ง์์ ํตํ ๊ณต๊ฐ ์ฒดํ ์ ๋ฐ
4.1.1. ๋งค์ค์ ๋ถ์
4.1.2. ๋ชจํธํ ์
๊ตฌ
4.1.3. ๋ค์ํ ์ธต์์ ๋ฒฝ
4.2. ์๋์ ์ธ ๋ฏธ์์ฑ์ ํตํ ๊ณต๊ฐ ์ฒดํ ์ ๋ฐ
4.2.1. ๋น์์ง ๊ณต๊ฐ
4.2.2. ๋น์ ์ํ ๊ณต๊ฐ์ ๋ณํ
4.3. ๊ณต๊ฐ ๊ฐ ๊ด๊ณ์ ์กฐ์ ์ ํตํ ๊ณต๊ฐ ์ฒดํ ์ ๋ฐ
4.3.1. ํํ์ ๋ด๋ถ ๊ณต๊ฐ์ ๋ฐ์
4.3.2. ์ฐฝ์ ํตํ ์์ฐ์ ์ ์
4.3.3. ๋์ ์กฐ์ง๊ณผ์ ์กฐํ ๋๋ ๋ฐ์
4.4. ์๊ฒฐ: ์ฒดํ์ ์ ๋ฐํ๋ ๊ฑด์ถ ๊ณต๊ฐ ๊ตฌํ๋ฐฉ์์ ํน์ง
์ 5 ์ฅ ์์์ ์ฒดํ์ ์ ๋ฐํ๋ ๊ฑด์ถ๊ตฌํ๊ณต๊ฐ ๊ตฌ์ฑ๋ฐฉ์์ ํน์ง
5.1. ์ํ์ค์ ์กฐ์ ์ ํตํ ๊ณต๊ฐ์ ์ฒดํ ์ ๋ฐ
5.1.1. ๋ค์ํ ์ํ์ค์ ๊ฐ๋ฅ์ฑ
5.1.2. ๋ถ๋ถ์ ํฉ์ผ๋ก์์ ์ํ์ค
5.2. ๊ธฐ์ต์ ์ฌ๊ตฌ์ฑ์ ํตํ ์ฒดํ์ ํตํฉ
5.2.1. ๋ค์ํ ์์ ์์ ๊ฐ์ ๊ณต๊ฐ์ ๋ฐ๋ณต์ ์ฒดํ
5.2.2. ๊ณตํต์์๋ฅผ ํตํ ๋ฐ๋ณต์ ์ธ์
5.3. ์ฐ์์ ๊ด๊ณ์ ์กฐ์ ์ ํตํ ์ฌํ์ ์ฅ์์ ๊ตฌํ
5.3.1. ๋น๊ณผ ์ฐฝ์ ํตํ ๋์์์ ์ฐ์์ ๊ด๊ณ
5.3.2. ๊ณต๊ฐ์ ๊ด์
์ ํตํ ์์ฐ๊ณผ์ ์ฐ์์ ๊ด๊ณ
5.4. ์๊ฒฐ: ์ฌํ์ ์ฅ์๋ก์ ๋ณํ์ ์ฌ์ง
์ 6 ์ฅ ๊ฒฐ๋ก Maste
Coastal path planning algorithm using quadtree and visibility graph
ํ์๋
ผ๋ฌธ(๋ฐ์ฌ) -- ์์ธ๋ํ๊ต๋ํ์ : ๊ณต๊ณผ๋ํ ์กฐ์ ํด์๊ณตํ๊ณผ, 2021.8. ๊นํ์.With the introduction of e-Navigation technology by the International Maritime Organization, it has been recommended for ships to exchange data with maritime centers. For this purpose, the necessary information for ships is electronically exchanged for information exchange, and this information includes route information. Therefore, the vessel must make a voyage plan and transmit it to the maritime center. Maritime center must check that there is no problem in the voyage plan and send the voyage plan to the vessel. Since weather routing system is established for ships sailing the ocean, it is easy to exchange route data between ships and maritime center. However, it is difficult to exchange route data for coastal ships because the navigator decide the route manually using their professional knowledge. In order to compensate the manual route planning along with the digitalization of the route, the demand for an automatic route system in the coast has increased.
Coastal ships include passenger ships, fishing boats, and yachts for various purposes. Vessels must calculate the route to their destination to achieve their objectives. The purpose of this study is to compute a safe and efficient route within a coast with a complex environment. It is necessary to secure the safety of the vessel by providing a route plan in consideration of the changing marine environment to the vessel in operation before departure or in real time. In order to determine a route, information such as shoreline, water depth, weather, and tide is required. Based on this information, many studies on route planning of ships sailing the ocean have been developed, but most of them are focused on reducing fuel consumption and sailing time in open sea. Because the coastline is complex and there are many obstacles in the coast, it is difficult to apply the existing research in coastal environment. In addition, since there are many areas with a large tide difference in Korea, the environment changes frequently during navigation. Therefore, it is necessary to calculate the route within a short time to consider frequent environment change.
In this paper, we propose a novel route planning algorithm for complex offshore environments by integrating the advantages of quadtree and visibility graph. A quadtree is used to improve the inefficient environment representation method such as the uniform grid. The graph is constructed using quadtree and the shortest path is computed on the quadtree based graph. Using the waypoints of the previously computed route, a visibility graph is generated to calculate the optimal route. To find the optimal path, Dijkstra algorithm is used at this time. The proposed algorithm can perform route planning from any angle and establishes a safe route plan by maintaining a certain distance from the coastline. In addition, the fuel consumption is computed in consideration of the weather information according to the departure time of the vessel, and the route with the minimum fuel consumption is planned. To calculate the fuel consumption, the braking power must be computed. The braking power can be calculated from the effective power, which is composed of the ship's resistance and speed. The resistance of the vessel is composed of resistance in still water, additional wind resistance, and additional wave resistance, and the net speed of the vessel. At this time, the additional resistance and the speed of the ship are computed based on ISO 15016. For validation of proposed algorithm, the minimum fuel consumption route and the shortest distance route were compared and evaluated. For performance evaluation, the algorithm proposed in this study was applied to the west and south sea of Korea. It was confirmed that the topology of the minimum fuel consumption route was different from the shortest route due to the influence of the weather information. Overall, it was confirmed that the proposed algorithm can generate the optimal route in complex environment with a short time.๊ตญ์ ํด์ฌ๊ธฐ๊ตฌ(International Maritime Organization)๊ฐ e-Navigation ๊ธฐ์ ์ ๋์
ํ๋ฉด์ ์ ๋ฐ์ด ํด์ ์ผํฐ์ ๋ฐ์ดํฐ๋ฅผ ๊ตํํด์ผ ํ๋ ๊ฒ์ด ํ์ค์ด ๋์๋ค. ์ด๋ฅผ ์ํด ์ ๋ฐ์ด ํญํดํ๋๋ฐ ํ์ํ ์ ๋ณด๋ค์ด ์ ๋ณด ๊ตํ์ ์ํด ์ ์ํ๋๊ณ ์์ผ๋ฉฐ, ์ด๋ฌํ ์ ๋ณด์๋ ํญ๋ก ์ ๋ณด๋ ํฌํจ๋์ด ์๋ค. ๋ฐ๋ผ์ ์ ๋ฐ์ ํญํด ๊ณํ์ ์ธ์ด ๋ค ํด์ ์ผํฐ์ ์ ์กํด์ผ ํ๋ฉฐ, ํด์ ์ผํฐ๋ ํญํด ๊ณํ์ ๋ฌธ์ ๊ฐ ์๋์ง ํ์ธํ๊ณ ์ด๋ฅผ ๋ค์ ์ ๋ฐ์ผ๋ก ๋ณด๋ด์ผ ํ๋ค. ๋์์ ํญํดํ๋ ์ ๋ฐ์ ์๋์ผ๋ก ํญ๋ก๋ฅผ ๊ณ์ฐํ๋ ์์คํ
์ด ๊ตฌ์ถ๋์ด ์๊ธฐ ๋๋ฌธ์ ํญ๋ก์ ๋ฐ์ดํฐ ๊ตํ์ด ์ฉ์ดํ์ง๋ง ์ฐ์์ ํญํดํ๋ ์ ๋ฐ์ ์ ์ฅ ๋ฐ ํญํด์ฌ๊ฐ ์ ๋ฌธ์ ์ง์์ ์ด์ฉํ์ฌ ์์์
์ผ๋ก ํญ๋ก๋ฅผ ๊ฒฐ์ ํ๊ธฐ ๋๋ฌธ์ ํญ๋ก ๋ฐ์ดํฐ ๊ตํ์ด ์ด๋ ต๋ค. ํญ๋ก์ ์ ์ํ์ ํจ๊ป ์์์
์ผ๋ก ํญ๋ก๋ฅผ ๊ณ์ฐํ๋ ๊ณผ์ ์ ๋ณด์ํ๊ธฐ ์ํด ์ฐ์ ๋ด ํญ๋ก๋ฅผ ์๋์ผ๋ก ๊ณ์ฐํ๋ ์์คํ
์ ๋ํ ์๊ตฌ๊ฐ ์ฆ๊ฐํ์์ผ๋ฉฐ, ์ด์ ๊ด๋ จํ์ฌ ํ๋ฐํ ์ฐ๊ตฌ๊ฐ ์งํ๋๊ณ ์๋ค.
์ฐ์ ์ ๋ฐ์ ์ฌ๊ฐ์ , ์ด์ , ์ํธ ๋ฑ์ด ์กด์ฌํ๋ฉฐ ๋ค์ํ ๋ชฉ์ ์ ๊ฐ๊ณ ์๋ค. ์ ๋ฐ์ ๊ฐ๊ฐ์ ๋ชฉ์ ์ ๋ฌ์ฑํ๊ธฐ ์ํด ๋ชฉ์ ์ง๊น์ง์ ๊ฒฝ๋ก๋ฅผ ์ฐ์ ๋ด์์ ๊ณ์ฐํด์ผ ํ๋ค. ๋ณธ ์ฐ๊ตฌ์ ๋ชฉ์ ์ ํ๊ฒฝ์ด ๋ณต์กํ ์ฐ์ ๋ด์์ ์์ ํ ํญ๋ก๋ฅผ ๊ณ์ฐํ๋ ๊ฒ์ด๋ค. ๋ณํํ๋ ํด์ํ๊ฒฝ์ ๊ณ ๋ คํ ๊ฒฝ๋ก ๊ณํ์ ์ถ๋ฐ ์ ํน์ ์ค์๊ฐ์ผ๋ก ์ดํญ ์ค์ธ ์ ๋ฐ์๊ฒ ์ ๊ณตํ์ฌ ์ ๋ฐ์ ์์ ์ ํ๋ณดํด์ผ ํ๋ค. ํญ๋ก๋ฅผ ๊ณํํ๊ธฐ ์ํด ํด์์ , ์์ฌ, ๊ธฐ์, ์กฐ์ ๋ฑ์ ์ ๋ณด๊ฐ ํ์ํ๋ค. ์ด๋ฌํ ์ ๋ณด๋ฅผ ๊ธฐ๋ฐ์ผ๋ก ๋์์ ํญํดํ๋ ์ ๋ฐ์ ํญ๋ก ๊ณํ ์ฐ๊ตฌ๊ฐ ๋ง์ด ๊ฐ๋ฐ๋์์ผ๋, ๋๋ถ๋ถ์ ์ฐ๊ตฌ๋ ์ฐ๋ฃ ์๋ชจ๋๊ณผ ํญํด ์๊ฐ์ ์ค์ด๋๋ฐ ์ด์ ์ ๋ง์ถ๊ณ ์๋ค. ์ฐ์์๋ ํด์์ ์ด ๋ณต์กํ๊ณ ์ฅ์ ๋ฌผ์ด ๋ง๊ธฐ ๋๋ฌธ์ ๊ธฐ์กด์ ์ฐ๊ตฌ๋ฅผ ๊ทธ๋๋ก ์ ์ฉํ๊ธฐ ์ด๋ ต๋ค. ๋ํ, ํ๊ตญ์ ๊ฒฝ์ฐ์๋ ์กฐ์ ์ฐจ๊ฐ ํฐ ์์ญ์ด ๋ง๊ธฐ ๋๋ฌธ์ ํญํด ์ ์ฃผ๋ณ ํ๊ฒฝ์ด ์์ฃผ ๋ณํ๋ฏ๋ก ๋น ๋ฅธ ์๊ฐ ๋ด์ ํญ๋ก๋ฅผ ๊ณ์ฐํด์ผ ํ๋๋ฐ ๊ธฐ์กด ์ฐ๊ตฌ๋ ์ด์ ์ ํฉํ์ง ์๋ค.
๋ณธ ๋
ผ๋ฌธ์์๋ ์ฟผ๋ ํธ๋ฆฌ์ ๊ฐ์์ฑ ๊ทธ๋ํ์ ์ฅ์ ์ ํตํฉํ์ฌ ์ฐ์ ๋ด ๋ณต์กํ ํด์ ํ๊ฒฝ์ ์ํ ์๋ก์ด ๊ฒฝ๋ก ๊ณํ ์๊ณ ๋ฆฌ์ฆ์ ์ ์ํ๋ค. ๊ธฐ์กด์ ๊ท ์ผ ๊ฒฉ์์ ๊ฐ์ ๋นํจ์จ์ ์ธ ํ๊ฒฝ ํํ ๋ฐฉ๋ฒ์ ๊ฐ์ ํ๊ธฐ ์ํด ์ฟผ๋ ํธ๋ฆฌ๋ฅผ ์ฌ์ฉํ์๋ค. ์ฟผ๋ ํธ๋ฆฌ ์์์ ๊ทธ๋ํ๋ฅผ ๊ตฌ์ฑํ๊ณ ์ฟผ๋ ํธ๋ฆฌ์ ์ต๋จ ๊ฒฝ๋ก๋ฅผ ๊ณ์ฐํ๋ค. ์์ ๊ณ์ฐํ ํญ๋ก์ ์จ์ดํฌ์ธํธ๋ฅผ ๊ธฐ๋ฐ์ผ๋ก ๊ฐ์์ฑ ๊ทธ๋ํ๋ฅผ ์์ฑํ์ฌ ์ต์ ๊ฒฝ๋ก๋ฅผ ๊ณ์ฐํ๋ฉฐ, ์ด ๋ Dijkstra ์๊ณ ๋ฆฌ์ฆ์ ์ฌ์ฉํ๋ค. ์ ์ํ ์๊ณ ๋ฆฌ์ฆ์ ๋ชจ๋ ๊ฐ๋์์ ํญ๋ก ๊ณํ์ ์ํํ ์ ์์ผ๋ฉฐ, ํด์์ ์ผ๋ก๋ถํฐ ์ผ์ ๊ฐ๊ฒฉ์ ์ ์งํ์ฌ ์์ ํ ํญ๋ก ๊ณํ์ ์๋ฆฝํ๋ค. ๋ํ, ์ ๋ฐ์ ์ถํญ ์๊ฐ์ ๋ฐ๋ฅธ ๊ธฐ์ ์ ๋ณด๋ฅผ ๊ณ ๋ คํ์ฌ ์ฐ๋ฃ ์๋ชจ๋์ ๊ณ์ฐํ์์ผ๋ฉฐ, ์ฐ๋ฃ ์๋ชจ๋์ด ์ต์๊ฐ ๋๋ ํญ๋ก๋ฅผ ๊ณํํ๋ค. ์ฐ๋ฃ ์๋ชจ๋์ ๊ณ์ฐํ๊ธฐ ์ํด ์ ๋ ๋๋ ฅ์ ๊ณ์ฐํด์ผ ํ๋ฉฐ, ์ ๋ ๋๋ ฅ์ ์ ๋ฐ์ ์ ํญ๊ณผ ์๋์ ๊ณฑ์ผ๋ก ์ด๋ฃจ์ด์ง ์ ํจ ๋๋ ฅ์ผ๋ก๋ถํฐ ๊ณ์ฐํ ์ ์๋ค. ์ ๋ฐ์ ์ ํญ์ ์ ์ ์ค ์ ํญ, ๋ฐ๋ ๋ถ๊ฐ์ ํญ, ํ๋ ๋ถ๊ฐ์ ํญ์ผ๋ก ๊ตฌ์ฑ๋๋ฉฐ, ์ ๋ฐ์ ์๋ ฅ์ ์กฐ๋ฅ๋ฅผ ๋ฐ์ํ์ฌ ์ด๋ฃจ์ด์ง๋ค. ์ด ๋ ๋ถ๊ฐ์ ํญ๊ณผ ์ ๋ฐ์ ์๋ ฅ์ ISO 15016์ ๊ธฐ๋ฐ์ผ๋ก ํ์ฌ ๊ณ์ฐ๋๋ค. ์ด๋ฌํ ๊ณผ์ ์ ์ํํ์ฌ ๊ณ์ฐํ ์ต์ ์ฐ๋ฃ ์๋ชจ๋ ํญ๋ก์ ์ต๋จ ๊ฑฐ๋ฆฌ ํญ๋ก๋ฅผ ๋น๊ต ๋ฐ ํ๊ฐํ์๋ค. ์ฑ๋ฅ ํ๊ฐ๋ฅผ ์ํด ๋ณธ ์ฐ๊ตฌ์์ ์ ์ํ ์๊ณ ๋ฆฌ์ฆ์ ๋ํ๋ฏผ๊ตญ ์ํด์๊ณผ ๋จํด์ ์์ญ์ ๋ํด ์ ์ฉํ์๋ค. ๊ธฐ์ ์ ๋ณด์ ์ํฅ์ผ๋ก ์ต์ ์ฐ๋ฃ ์๋ชจ๋ ํญ๋ก๊ฐ ์ต๋จ ๊ฑฐ๋ฆฌ ํญ๋ก์ ํ์์ด ๋ค๋ฅธ ๊ฒ์ ํ์ธํ๋ค. ์ ๋ฐ์ ์ผ๋ก ์ ์ํ ์๊ณ ๋ฆฌ์ฆ์ด ๊ธฐ์กด ์ฐ๊ตฌ ๋ฐฉ๋ฒ์ ๋นํด ๋น ๋ฅธ ์๊ฐ ์์ ์ต์ ํญ๋ก๋ฅผ ์์ฑํ ์ ์์์ ํ์ธํ์๋ค.1 Introduction 1
1.1 Background 1
1.2 Objective and method 3
1.3 Contributions of this paper 8
1.4 Outline 9
2 Theoretical background 10
2.1 Environment modelling 14
2.1.1 Regular grids 14
2.1.2 Irregular grids 16
2.1.3 Navigation mesh 17
2.1.4 Voronoi diagram 19
2.1.5 Visibility graph 20
2.1.6 Comparison of environment modeling 21
2.2 Path planning methods 24
2.2.1 Graph based methods 24
2.2.2 Sampling based methods 26
2.2.3 Evolutionary methods 29
2.2.4 Comparison of path planning methods 32
3 Related work 33
3.1 Genetic algorithm with navigation mesh 33
3.2 Dijkstra algorithm with Voronoi diagram 34
3.3 A* algorithm with quadtree 35
3.4 Comparison of related works with this thesis 38
4 Data acquisition and preprocess 43
4.1 Topography data 43
4.1.1 Topography and depth 43
4.1.2 Coastline expansion algorithm 46
4.2 Weather data 51
4.2.1 Wave data (KMA) 52
4.2.2 Wind data (KMA) 54
4.2.3 Current data (KMA) 56
4.2.4 Tide data (KHOA) 58
5 Quadtree based graph 60
5.1 Quadtrees 60
5.2 PMR quadtree insertion and split algorithm 67
5.3 Graph construction using PMR quadtree 76
5.4 The shortest path on quadtree based graph 85
6 Visibility graph construction with quadtree 87
6.1 Visibility graph 87
6.2 Visibility graph with quadtree 90
6.3 Improved line of sight algorithm 91
7 Fuel oil consumption estimation 94
7.1 Ship resistance 94
7.2 Ship speed 100
7.3 Fuel oil consumption 101
7.4 Example of fuel oil consumption computation 103
8 Coastal path planning algorithm 107
8.1 Problem definition 107
8.2 Assumptions for route optimization 109
8.3 Procedure of coastal path planning algorithm 109
9 Experimental results 113
9.1 Simulation results in quadtree generation 113
9.2 Simulation results with different draft 115
9.3 Simulation results in south sea of Korea 119
9.4 Simulation results in west sea of Korea 134
9.5 Fuel oil consumption minimization path results 148
9.5.1 First case in west sea of Korea 148
9.5.2 Second case in west sea of Korea 156
9.5.3 Third case in south sea of Korea 161
9.5.4 Second case in south sea of Korea 169
9.6 Long voyage path results 174
10 Conclusion and future works 179
References 181๋ฐ
The Experiences of Young Adult with Hypertension
Purpose: The purpose of this study was to explore the experiences of young adults with hypertension, using phenomenology in order to describe the essence of such experiences and to understand them from the patients' point of view. Methods: Participants in this study were 4 hypertension patients with ages ranging from 20 to 35 years old, living in Seoul city. Data were collected from in-depth interviews done from October to November in 2005. Colazzi method(1978) was used to analyze the data. Results: The 12 themes were extracted in this study ; โDiscovery by accidentโ, โDenial of the diagnosisโ, โA disease unworthy of the young menโ, โGuilty feeling toward their parentsโ, โFear of deathโ, โUnconvinced reasonโ, โWorry about the futureโ, โAttribute all symptoms to the diseaseโ, โWill of not life-long medicationโ, โConcern for fertility problemโ, โNot convinced with current treatment methodโ, โBecoming unimportantโ. Conclusion: The results of this study show that the young adult with hypertension will be in a high risk group of non compliance, so helpful program for them should be developed and the nurses need to pay more attention to the psychosocial aspect of nursing.ope
The Relationships among Trait Anger, Anger Expression, Jab Satisfaction, Job Commitment, and Organizational Performance in Clinical Nurses
Purpose: The purpose of this study was to identify the relationships among trait anger, anger expression, job satisfaction, job commitment, and organizational performance, and especially to verify the effect of anger experience on organizational performance. Method: A descriptive study was conducted using a convenient sample. Data were collected by a self-report questionnaire from 671 clinical nurses in three university hospitals and analyzed by using SPSS 14.0 Win program with descriptive statistics, t-test, ANOVA, pearson correlation coefficient, and stepwise multiple regression. Result: Organizational performance was significantly correlated with trait anger, anger expression-in, anger expression-out, anger control, job satisfaction, and job commitment. Multiple regression analysis showed that organizational performance was significantly predicted by job commitment, job satisfaction, educational level (university graduation), anger control, and working place (operative room), and 34.7% was explained by these variables. Conclusions: Out of anger expression, anger control significantly affected on organizational performance together with job commitment and job satisfaction. From this result, it could be concluded that nursing intervention for anger control have a positive effect on improving organizational performance. Further studies are needed to develop and test the effect of nursing intervention programs for anger control.ope
Development of a clinical protocol for home hospice care for Koreans
As the Korean government's recognition of the importance of hospice service grows, the government has initiated a variety of hospice services in Korea. Each hospice organization has shown a significant difference in its health care delivery methods, constitution and care content. Developing a clinical protocol is essential for establishing standardized hospice services. A preliminary protocol was drawn up by examining the records of terminal patients (n=541) in a home hospice organization while elucidating the health problems as well as classifying them through the Home Health Care Classification (HHCC), and by reviewing the relevant nursing interventions and medical treatments in the literature concerning the clinical protocols. Korea's leading hospice specialty groups participated in four rounds of content validity verification processes in order to establish a protocol. A guideline was developed through a team approach, integrating the opinions of doctors, nurses, ministers, volunteers, patients' families, nutritionists and pharmacists. Eighteen health problems and a total of 223 interventions (173 major treatments and nursing interventions, and 50 optional interventions) were included in the final clinical protocol. This study is expected to contribute to the overall qualitative improvement of home hospice care and the subsequent shortening of documentation time. Evaluation tools and a regulatory feedback system need to be developed in order to maintain consistent evaluation procedures based on the continuous promotion and use of the protocol.ope
The Experiences of Prayer in Christian Patients with Breast Cancer
Purpose: The purpose of this study was to understand the meaning of prayer in Christian patients with breast cancer. Methods: Data collection and analysis were conducted by the Colaizzi analysis of phenomenological method. Data were collected by in-depth interviewing the participants and by further follow-up observations. Sixteen patients participated in this study. Results: The significant statements (188), formulated meanings (42), themes (38), clusters of theme (10), and categories (5) were emerged. The 5 categories were as follows: communication with God, healing and peace, spiritual growth, distrust in prayer, and method of prayer. Conclusion: Further studies need to consider the period of faith, comparison between christian and other religions, and length of diagnosis. A better understanding of the meaning of prayer will lead to a more comprehensive view of the spiritual care for patients with breast cancer, and can lead to guidelines for assessment and intervention to reduce suffering from cancer.ope
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