• Title/Summary/Keyword: 국제적 표준화

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An Initial Study on the Reliability Assurance in PET/CT Standardized Uptake Values (PET/CT 에서 표준섭취계수(SUV)의 신뢰성 확보를 위한 초기연구)

  • Park, Hoon-Hee;Kim, Jung-Yul;Lee, Seung-Jae;Park, Min-Soo;NamKoong, Hyuk;Lim, Han-Sang;Oh, Ki-Baek;Kim, Jae-Sam;Lee, Chang-Ho;Jin, Gye-Hwan
    • The Korean Journal of Nuclear Medicine Technology
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    • v.13 no.3
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    • pp.31-42
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    • 2009
  • Purpose: As the number of domestic medical institutions installing PET/CT is increasing rapidly, the transfer of PET/CT images among medical institutions is also increasing. Thus, it is necessary to collect the comparative SUV data from several medical institutions' PET/CT systems through a phantom study which semi-quantitatively compares the SUV on one bed, the change scale of the SUV on the slices, and the time of measuring. The phantom study to find differences among the SUVs from various PET/CT offers the opportunity to obtain the reliability of the SUV in PET/CT images. Materials and Methods: Ten PET/CT systems from medical institutions in Korea were used. To obtain the accurate data, the study has been using the radiation detector of Korea Research Institute of Standards and Science to verify. The internal structures of NEMA $phantom^{TM}$ were removed and Six thousand milliliters of distilled water which has 1mCi of $^{18}F$-FDG put into the phantom. The water was properly integrated with $^{18}F$-FDG using magnetic stirrer. The images were acquired at 60, 70, 80, 90, 100, 110 and 120-minutes for 3 minute each. Two hundred square centimeters of region of interests were placed and analyzed. To confirm the usefulness, the correction-table came out from patients' data. Results: The coefficient of variability of the SUV from -11.0 to 9.90 % fell into the range of international standards(${\pm}10%$) along with the SUV on a bed, the change scale of the SUV on the slices, and the time of measuring, except one PET/CT system. Using the data of the differences among the SUVs, we came to withdraw the correction-table ranging from 0.803 to 1.246. The correction-table was confirmed its usefulness through Linear Regression Analysis which was applied to normal cases. Conclusions: Although studies have been made on the variation of the SUV, there is little attention on the standardization of the SUV. Based on this study of the quantitatively comparable data about the SUV accommodating the correction-table, it would help to have more corrective diagnosis.

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Human Thermal Sensation and Comfort of Beach Areas in Summer - Woljeong-ri Beach, Gujwa-eup, Jeju-si, Jeju Special Self-Governing Province - (여름철 해변지역의 인간 열환경지수 및 열쾌적성 - 제주특별자치도 제주시 구좌읍 월정리 해변 -)

  • Park, Sookuk;Sin, Jihwan;Jo, Sangman;Hyun, Cheolji;Kang, Hoon
    • Journal of the Korean Institute of Landscape Architecture
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    • v.44 no.4
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    • pp.100-108
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    • 2016
  • The climatic index for tourism(CIT) has recently been advanced, which includes complete human energy balance models such as physiological equivalent temperature(PET) and universal thermal climate index(UTCI). This study investigated human thermal sensation and comfort at Woljung-ri Beach, Jeju, Republic of Korea, in spring and summer 2015 for landscape planning and design in beach areas. Microclimatic data measurements and human thermal sensation/comfort surveys from ISO 10551 were conducted together. There were 869 adults that participated. As a result, perceptual and thermal preference that consider only physiological aspects had high coefficients of determination($r^2$) with PET in linear regression analyses: 92.8% and 87.6%, respectively. However, affective evaluation, personal acceptability and personal tolerance, which consider both physiological and psychological aspects, had low $r^2s$: 60.0%, 21.1% and 46.4%, respectively. However, the correlations between them and PET were all significant at the 0.01 level. The neutral PET range in perceptual for human thermal sensation was $25{\sim}27^{\circ}C$, but a PET range less or equal to 20% dissatisfaction, which was recommended by ASHRAE Standard 55, could not be achieved in perceptual. Only PET ranges in affective evaluation and personal tolerance affected by both aspects were qualified for the recommendation as $21{\sim}32^{\circ}C$ and $17{\sim}37^{\circ}C$, respectively. Therefore, the PET range of $21{\sim}32^{\circ}C$ is recommended to be used for the human thermal comfort zone of beach areas in landscape planning and design as well as tourism and recreational planning. PET heat stress level ranges on the beach were $2{\sim}5^{\circ}C$ higher than those in inland urban areas of the Republic of Korea. Also, they were similar to high results of tropical areas such as Taiwan and Nigeria, and higher than those of western and middle Europe and Tel Aviv, Israel.

Yearly Update of the List of Plant Diseases in Korea (6.2 Edition, 2024) (한국식물병명목록의 연간 현황 보고(6.2판, 2024년 개정본))

  • Jaehyuk Choi;Seon-Hee Kim;Young-Joon Choi;Gyoung Hee Kim;Ju-Yeon Yoon;Byeong-Yong Park;Hyun Gi Kong;Soonok Kim;Sekeun Park;Chang-Gi Back;Hee-Seong Byun;Jang Kyun Seo;Jun Myoung Yu;Dong-Hyeon Lee;Mi-Hyun Lee;Bong Choon Lee;Seung-Yeol Lee;Seungmo Lim;Yongho Jeon;Jaeyong Chun;Insoo Choi;In-Young Choi;Hyo-Won Choi;Jin Sung Hong;Seung-Beom Hong
    • Research in Plant Disease
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    • v.30 no.2
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    • pp.103-113
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    • 2024
  • Since 2009, the Korean Society of Plant Pathology has established the Committee on Common Names of Plant Disease to systematically review and determine plant disease names and related terminologies. The committee published the 6th edition of the List of Plant Diseases in Korea (LPDK) in 2022, and the list has been made publicly accessible online. The online database has significantly enhanced user accessibility, expedited update processes, and improved interoperability with other databases. As a result, the 6.1 edition of the list was released by online LPDK in 2023, detailing new disease names added over the preceding year and revisions to existing names. Subsequently, in 2024, the 6.2 edition was published, encompassing 6,765 diseases caused by 2,503 pathogen taxa across 1,432 host species. The public release of the online database has, however, introduced several challenges and tasks. Addressing these issues necessitates the development of modern, standardized nomenclature guidelines and a robust system for the registration of new disease names. Open communication and collaboration among the diverse members of the Korean Society of Plant Pathology are required to ensure the reliability of the LPDK.

Comparison and Decision of Exposure Coefficient for Calculation of Snow Load on Greenhouse Structure (온실의 적설하중 산정을 위한 노출계수의 비교 및 결정)

  • Jung, Seung-Hyeon;Yoon, Jae-Sub;Lee, Jong-Won;Lee, Hyun-Woo
    • Journal of Bio-Environment Control
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    • v.24 no.3
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    • pp.226-234
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    • 2015
  • To provide the data necessary to determine exposure coefficients used for calculating the snow load acting on a greenhouse, we compared the exposure coefficients in the greenhouse structure design standards for various countries. We determined the exposure coefficient for each region and tried to improve on the method used to decide it. Our results are as follows: After comparing the exposure coefficients in the standards of various countries, we could determine that the main factors affecting the exposure coefficient were terrain roughness, wind speed, and whether a windbreak was present. On comparing national standards, the exposure coefficients could be divided into three groups: exposure coefficients of 0.8(0.9) for areas with strong winds, 1.0(1.1) for partially exposed areas, and 1.2 for areas with dense windbreaks. After analyzing the exposure coefficients for 94 areas in South Korea according to the ISO4355 standard, all of the areas had two coefficients (1.0 and 0.8), except Daegwallyeong (0.5) and Yeosu (0.6), which had one coefficient each. In South Korea, the probability of snow is greater inland than in coastal areas and there are fewer days with a maximum wind velocity > $5m{\cdot}s^{-1}$ inland. When determining the exposure coefficients in South Korea, we can subdivide the country into three regions: coastal areas with strong winds have an exposure coefficient of 0.8; inland areas have a coefficient of 1.0; and areas with dense windbreaks have an exposure coefficient of 1.2. Further research that considers the number of days with a wind velocity > $5m{\cdot}s^{-1}$ as the threshold wind speed is needed before we can make specific recommendations for the exposure coefficient for different regions.