• 환경영향평가
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• 제20권1호
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• pp.49-59
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• 2011

The results of comparing $PM_{10}$ concentration between 'Namsan' and 'Yongsan-gu' air quality monitoring stations show similar values with averaged concentration in the whole Seoul. The correlation factors in both sites were 0.865, 0.828 in 2005, 2006, respectively. For 'Bukhansan' and 'Gangbuk-gu' air quality monitoring stations, different from the results mentioned above, they showed clear differences as altitude changes. PM10 concentration in 'Bukhansan' monitoring stations was 10 ${\mu}g/m^3$ lower than 'Gangbuk-gu' monitoring station which is located near the ground. Also, averaged PM10 concentration in 'Bukhansan' and 'Gangbuk-gu' monitoring stations was lower than that in the whole Seoul. When comparing $NO_2$ concentration between 'Namsan' and 'Yongsan-gu' monitoring stations, $NO_2$ concentration in 'Namsan' monitoring station was lower than 'Yongsan-gu' monitoring station. For $NO_2$ concentration in 'Bukhansan', 'Gangbuk-gu' and 'the whole Seoul', there were the same pattern in 'Gangbuk-gu' and the 'the whole Seoul' and low values in 'Bukhansan' monitoring station. The correlation factors of $NO_2$ concentration in 'Bukhansan' and 'Gangbukgu' was 0.525, 0.549 in 2005, 2006, respectively, which stands for low correlationship.

• 한국응용약물학회:학술대회논문집
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• 한국응용약물학회 2002년도 창립10주년기념 및 국립독성연구원 의약품동등성평가부서 신설기념 국재학술대회:생물학적 동등성과 의약품 개발 전략을 위한 국제심포지움
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• pp.240-240
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• 2002

• 대한약학회:학술대회논문집
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• 대한약학회 2001년도 Proceedings of the Pharmaceutical Society of Korea
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• pp.238.1-238.1
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• 2001

• 시스템엔지니어링학술지
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• 제18권2호
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• pp.140-148
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• 2022

Hydrogen is expected to be widely applied in most sectors within the current energy system, such as transportation and logistics, and is expected to be economically and technologically utilized as a power source to achieve vehiclebon emission reduction. In particular, the construction of hydrogen charging station infrastructure will not only support the distribution of hydrogen electric vehicles, but also play an important role in building a hydrogen logistics system. Therefore, This paper suggest additional charging infrastructure areas in Seoul with a focus on supply according to the annual average growth rate (CAGR), centering on Seoul, where hydrogen vehicles are most widely distributed. As of February 2022, hydrogen charging infrastructures were installed in Gangseo-gu, Gangdong-gu, Mapo-gu, Jung-gu, and Seocho-gu in downtown Seoul. Next, looking at the number of hydrogen vehicles by administrative dong in Seoul from 2018 to 2022, Seocho-gu has the most with 246 as of 2022, and Dongjak-gu has the highest average growth rate of 215.4% with a CAGR of 215.4%. Therefore, as a result of CAGR analysis, Dongjak-gu is expected to supply the most hydrogen vehicles in the future, and Seocho-gu currently has the most hydrogen vehicles, so it is likely that additional hydrogen charging infrastructure will be needed between Dongjak-gu and Seocho-gu.

• 한국대기환경학회지
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• 제31권1호
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• pp.83-91
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• 2015

Biomass burning is known to be one of the main sectors emitting greenhouse gases as well as air pollutants. Unfortunately, the inventory of biomass burning sector has not been established well. We estimated greenhouse gas (GHG) and air pollution (AP) integrated emissions from biomass burning sector in Seoul during year 2010. The data of GHG and AP emissions from biomass burning, classified into open burning, residential fireplace and wood stove, meat cooking, fires, and cremation, were obtained from Statistics Korea and Seoul City. Estimation methodologies and emission factors were gathered from reports and published literatures. Estimated GHG and AP integrated emissions during year 2010 were $3,867tonCO_{2eq}$, and 2,320 tonAP, respectively. Major sources of GHG were forest fires ($1,533tonCO_{2eq}$) and waste open burning ($1,466tonCO_{2eq}$), while those of AP were meat cooking (1,240 tonAP) and fire incidence (907 tonAP). Total emissions by administrative district in Seoul, representing similar patterns in both GHG and AP, indicated that Seocho-gu and Gangseo-gu were the largest emitters whereas Jung-gu was the smallest emitter, ranged in $2{\sim}165tonCO_{2eq}$ and 0.1~8.31 tonAP. GHG emissions per $km^2$ showed different results from total emissions in that Gwanak-gu, Jungnang-gu, Gangdong-gu and Seodaemun-gu were the largest emitters, while Seocho-gu and Gangseo-gu were near-averaged emission districts, ranged in $0.2{\sim}21tonCO_{2eq}/km^2$. However, AP emissions per $km^2$ revealed relatively minor differences among districts, ranged in $2.3{\sim}6.1tonAP/km^2$.

• 보건교육건강증진학회지
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• 제29권1호
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• pp.39-57
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• 2012

Objectives: This study was to measure community capacity using individual-level and organizational-level capacity indicators and illuminated the relationship of community capacity and self-rated health status in two regions in Seoul, Korea. Methods: The data from individual surveys were obtained by quota sampling the residents of two autonomous gu in Seoul (N=1,000). The data from organizational surveys were obtained by snowball sampling lists of organizations in the possession of gu offices with a sampling frame (N=153). The survey tools were 6 indicators regarding residents' social capital and a sense of community and 5 indicators regarding community-based organizations and their networks. The analysis methods consisted of the effect of the components of capacity on health status and social network analysis. Results: As for capacity on individual levels, while D-gu was mainly developed inn individual capacity in terms of social interaction, Y-gu was stronger in a sense of community and cohesion among residents. As for capacity on organizational levels, Y-gu was more developed than was D-gu in associational networks. Conclusion: It is necessary to develop health promotion program per community and to strengthen partnerships with and among grassroots organizations based in local communities through the measurement of community capacity.

• 한국조경학회지
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• 제35권1호
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• pp.59-68
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• 2007

This article statistically analyzed contributive levels of district image based on an effect and a similarity index through the evaluation of citizens and suggested the efficient management system of a city image according to the results. For this study, Busan City was selected as a case city by the preceding literature and was investigated concerning district image and city image through a questionnaire. The new evaluation method for analysis of a city image was presented in this process. The results of this research are as follows: 1. Busan City has a substantial positive and culturally unique image, and each of its districts have other image characteristics. for example, the CBD district has a positive image, and the sea shore district has a busy and prosperous image, but the backward sea shore district has an image of stagnancy. 2. The image of Yeonje-gu has the largest effect on the image of Busan. Next in influence are Jung-gu, Saha-gu, Suyoung-gu, respectively. The effect index is closely connected with the variance of evaluative adjectives. 3. Busanjin-gu and Haeundae-gu have similar images to Busan City. Next in similarity are Nam-gu, Jung-gu, Youngdo-gu, Suyoung-gu, respectively. The similarity index is closely connected with the correlation of evaluative adjectives. Busan City and its districts can establish their image strategies with the above analyzed results. This study is meaningful in that a statistical evaluative method was proposed. With continued follow-up research, this study may serve as a systematic and logical model to improve the urban landscape and image.

• 환경영향평가
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• 제25권3호
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• pp.222-232
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• 2016

물발자국은 인간의 활동을 통해 소비되는 직접수와 간접수의 총사용량을 산정함으로써 지속가능한 물이용을 유도하기 위한 효과적 수단으로 활용되고 있다. 본 연구는 서울시의 물이용 관리와 관련한 계획들의 문제점 분석을 통해 물발자국의 도입가능성을 분석하고 장단기적인 측면에서 도입 및 활용방안을 제시하고자 하였다. 또한 서울시 25개 자치구를 대상으로 시뮬레이션을 통해 청색 및 회색 물발자국을 산정하고, 지역별 물발자국의 차이점 분석과 이를 바탕으로 물발자국을 줄이기 위한 대안들을 모색하였다. 물발자국 측면에서의 서울시 물환경시스템에 대한 분석은 크게 청색물발자국과 회색물발자국으로 나누어 수행하였다. 개인이나 공동체가 제품이나 서비스를 생산 소비하기 위해 필요한 지표수와 지하수의 양을 의미하는 청색물발자국을 분석하기 위해서 서울시의 각 행정구역별 지하수의 사용량과 생활용수의 사용량을 합산하여 추정하였다. 각 행정구역별 청색물발자국을 인구수와 세대수 비율로 확인해 본 결과 중구, 종로구 강남구, 용산구, 서초구 등의 순으로 높게 나타났다. 회색물발자국은 각 행정구역별 BOD기준의 오 폐수발생부하량을 배출기준 수질(BOD기준 3.5ppm)로 정화하여 배출할 때 사용되는 물의 양을 추론하여 산출하였다. 각 행정구역별 회색물발자국을 인구수와 세대수 비율로 확인해 본 결과 중구, 종로구 강남구, 용산구, 서초구, 영등포구 등의 순으로 높게 나타났다. 본 연구 결과는 물관리 있어 공급중심의 양적 관리 정책의 한계를 극복하기 위한 일환으로 물발자국의 개념 및 방법의 도입을 제안하였으며 이는 환경적 경제적 사회적으로 보다 탄력적이고 지속가능한 물관리 정책을 모색하는데 중요한 기초자료가 될 것으로 기대된다.

• 대한치과의사협회지
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• 제54권8호
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• pp.613-629
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• 2016

This study assayed regional distribution of dental hospital & dental clinics, the number of population & households per one dental hospital & clinic, operation condition & duration. This study used public data that display from 1946 years(the first dental clinic open in republic of korea) to 2016 years. We collected present condition of 21,686 dental hospital and clinics available in public data portal site on 28. Feb.2016. Data were classified by scale, location, permission year, operation duration of dental hospital & clinics and were analyzed using SPSS 20.0 program. Surveyed on Feb. 2016. Best top 10 regions of permission dental clinics are (1) Gangnam-gu, Seoul(1,337), (2) Seongnamsi, Gyeonggi-do(555), (3) Songpa-gu, Seoul(491), (4) Yeongdeungpo-gu, Seoul(472), (5) Suwon-si, Gyeonggi-do(443), (6) Seocho-gu, Seoul(428), (7) Nowon-gu, Seoul(417), (8) Goyang-si, Gyeonggi-do(413), (9) Jung-gu, Seoul(380), (10) Yongin-si, Gyeonggi-do(353). Whereas best top 10 regions of operating dental clinics are (1) Gangnam-gu, Seoul(581), (2) Seongnamsi, Gyeonggi-do(415), (3) Suwon-si, Gyeonggi-do(382), (4) Seocho-gu, Seoul(320), (5) Changwon-si, Gyeongsangnam-do(303), (6) Songpa-gu, Seoul(295) (7) Goyang-si, Gyeonggi-do(290), (8) Bucheon-si and Yongin-si, Gyeonggi-do(262), (9) Jeonju-si, Jeollabuk-do(224). Average population per one dental hospital & clinic by regional local government are 3,120 people. Best five region of population per one dental hospital & clinic are (1) Sejong-si(5,272), (2) Gangwon-do(4,653), (3) Chungcheongbuk-do(4,513), (4) Gyeongsangbuk-do(4,490), (5) Chungcheongnam-do(4,402). Average households per one dental hospital & clinic by regional local government are 1,316 households. Best three region of households per one dental hospital & clinic are (1) Sejong-si(2,126), (2) Gangwon-do(2,057), (3) Gyeongsangbuk-do(1,946). From 1946 to 1986, permission and operating dental hospital and clinics was steadily increasing. On 1986-1990, 1991-1995, permission, operation and closure of dental hospital and clinics increase rapidly. From the 2011-2015 to 2016(present), permission, operation and closure of dental hospital and clinics is decreasing. Average operating duration of closured dental hospital and clinics are 14.054 years. We need to map of dental hospital and clinics for open and operation of one, base on analyzed results. In an era of 30,000 dentist, we should to be concerned about operation of dental clinics in the light of past operating condition.

• 대한토목학회논문집
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• 제35권4호
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• pp.997-1006
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• 2015

본 연구는 서울시를 대상으로 인공신경망을 활용하여 침수발생가능성과 침수위험지역을 도출하고, 위험지역 내 도시기반시설 현황을 살펴보았다. 분석결과, 강남구, 송파구, 서초구, 서대문구 등에서 침수발생가능성이 높은 위험지역을 많이 포함하고 있었다. 교통시설의 $4.17km^2$이상이 위험지역에 분포하여 우선 관리시설로 나타났고, 강남구 지역은 침수위험이 높은 기반시설을 $0.85km^2$이상 포함하고 있었다. 본 연구는 인공신경망 모델을 침수발생가능성 분석에 활용하여 그 적용가능성을 확인하였으며, 평가결과는 다양한 계획과정에 반영될 수 있을 것이다.