• 한국지하수토양환경학회지:지하수토양환경
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• 제12권1호
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• pp.64-72
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• 2007

토양매체중의 오염물질들은 다양한 경로를 통해 인체나 생태계에 노출되어 위해성 문제를 유발하고 있다. 토양위해성평가(Soil Risk Assessment)는 토양오염물질로 인한 악영향의 개연성을 정량적으로 평가하는 과정으로, 유해성 확인(Hazard Identification), 용량-반응평가(Dose-Response Assessment), 노출평가(Exposure Assessment), 그리고 위해도 결정(Risk Characterization)의 4가지 단계적 과정으로 이루어진다. 이중 노출평가과정에서 매우 중요하게 작용하는 노출인자(Exposure Factor)는 토양오염물질의 인체노출량을 산정하는데 필수적인 요소로, 미국, 유럽국가 등 선진국에서는 나라별 상황에 적절한 노출인자를 사용하고 있으나, 우리나라는 아직 국내에 적용하기 적합한 노출 인자에 대한 연구가 매우 부족한 실정이다. 본 연구에서는 토양오염 위해성평가를 위한 국가별 노출인자를 비교분석하고, 이를 토대로 국내상황에 적용가능한 노출인자를 제시하였다. 국가별 노출인자 연구는 미국 Environmental Protection Agency, 영국 Environmental Agency, 네덜란드 RIVM, 호주, 그리고 독일에서 적용되고 있는 노출인자값에 대해 노출인자별로 총괄적인 비교분석을 수행하였다. 또한 국가별 비교분석연구와 국내에서 제시된 노출인자 자료를 종합하여, 국내자료가 없는 경우 외국에서 보편적으로 적용하고 있는 인자값을 국내 적용 타당성을 고려하여 제시하였다. 본 연구에서 고려된 노출인자 조사항목은 평균수명, 노출기간, 노출빈도, 체중, 체표면적(또는 노출체표면적), 피부흡수계수(Skin Absorption Factor), 토양-피부간 흡착계수(Soil-Skin Adherence Factor), 음용수 섭취량, 호흡률, 토양 섭취량 그리고 농작물 섭취량 등이다. 본 연구는 오염토양의 위해성평가를 수행할 때 국내 상황을 고려한 노출평가에 필요한 기반연구가 될 것이다.

• 한국대기환경학회지
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• 제30권1호
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• pp.37-47
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• 2014

In this study, field measurement was carried out for reasonable improvement of asphalt concrete manufacturing facilities' PM emissions estimation method. Through those, this study calculated PM emission factor and tried to estimate PM emissions from asphalt concrete manufacturing facilities suitable for domestic characteristics. As a result, the efficiency of the PM control device was measured as 99.9%. Using this, uncontrolled PM emission factor was calculated. PM emission factor was calculated 10.97 kg/ton at 23 asphalt concrete manufacturing facilities of 22 workplaces. The PM current emission factor of the US Environment Protection Agency (EPA) is 14.4 kg/ton, the factor calculated from this study is about 24% lower than the EPA standard.

• 한국농공학회논문집
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• 제55권3호
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• pp.85-89
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• 2013

In the current domestic, many industrial accidents have happened. And these are analyzed according to several factors. But it is difficult that they evaluate their business safety. Thus, we conducted a study on business specific safety assessment techniques in order that business know their safety level and perform appropriative safety activities. Study methods are survey and AHP (Analytic Hierarchy Process). Each specific weighting factors to calculate the survey was conducted for safety and consulting experts (20 persons). Weight factor was used to AHP decision support as one of the ways through a number of alternatives to the ratings for the Minesota Multiphasic. Factors are each type of industry, specific industrial scale, disaster type and strength, worker age and tenure period, and region. First, survey was conducted with 20 professionals to estimate the weighting factors. Weights between factors using the AHP analysis tool based on the mean values were calculated. Second, last 3 years between the industrial accidents statistics were used to calculate the weights for each of the rating factors in the Occupational Safety and Health Agency. Grade weights between each factor which was based on the rating of each factor was calculated as the average of three years. Finally, the weights between each factor and the grade weights for each factor using the safety level of the enterprise were calculated so that you can evaluate the weighting.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2008년도 춘계학술대회 논문집
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• pp.290-292
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• 2008

we applied Wind Field Module of PHRLM so that disaster prevention agency concerned can effectively estimate the possible strong wind damages by typhoon. In this study, therefore, we estimated wind speed at 300m level using 700hPa wind according to the research method by Franklin(2003), PHRLM(2003), and Vickery and Skerlj(2005). Then we calculated wind speed at 10m level using the estimated wind speed at 300m level, and finally, peak 3.second gust on surface. The case period is from 18LST August 31 to 03LST September 1, 2002, when the typhoon Rusa in 2002 was the most intense. Among disaster prediction models in the US, Wind Field Module of PHRLM in Florida was used for the 2002 typhoon Rusa case. As a result, peak 3.second gust on the surface increased $10\sim20%$ in the typhoon's 700hPa wind speed.

• 전기학회논문지
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• 제63권8호
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• pp.1075-1079
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• 2014

In this paper, we describe the analysis and the compensation method of the g-sensitivity error for MEMS vibratory gyroscopes. Usually, the g-sensitivity error has been ignored in the commercial MEMS gyroscope, but it deserves our attention to apply for the missile application as a tactical grade performance. Thus, it is necessary to compensate for the g-sensitivity error to reach a tactical grade performance. Generally, the g-sensitivity error seems intuitively to be a gyroscope bias error proportional to the linear acceleration. However, we assert that the g-sensitivity error mainly causes not a bias error but a scale-factor error. And we verify that the g-sensitivity scale-factor error occurs due to the non-linearity of parallel plate electrodes. Therefore, we propose the compensation method to remove the g-sensitivity scale-factor error. The experimental result showed that a proposed compensation method improved successfully the performance of the MEMS vibratory gyroscope.

• Journal of Korean Society for Atmospheric Environment
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• 제9권E호
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• pp.358-363
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• 1993

Total particulate mater (TPM), $NO_2$ and $NH_3$ were measured simultaneously in the smoking and non-smoking locations during an eleven month period from March 1986 to January 1987 at three sites in Chicago : Illinois Institute of Technology Cafeteria, Rush-Presbyterian St. Lukes Medical Center Cafeteria and a downtown office building. From this study, the mean concentrations of $NO_2$ and $NH_3$ were not significantly different between the smoking and non-smoking locations at any sampling site ; however, there was a statistical difference for TPM between the smoking and non-smoking locations. Activity factor was useful for describing the contribution from indoor source. The linear regression analysis was reasonable method for discriminating the individual contribution of source to determine the emission factor. The TPM emission factor determined from this technique was in good agreement with value from the literature.

• 대한산업공학회지
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• 제29권1호
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• pp.78-89
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• 2003

Ordering is performed to reduce the amount of fill-ins of the Cholesky factor of a symmetric positive definite matrix. This paper proposes a new ordering algorithm that reduces the fill-ins of the Cholesky factor iteratively by elimination tree rotations and clique separators. Elimination tree rotations have been used mainly to reorder the rows of the permuted matrix for the efficiency of storage space management or parallel processing, etc. In the proposed algorithm, however, they are repeatedly performed to reduce the fill-ins of the Cholesky factor. In addition, we presents a simple method for finding a minimal node separator between arbitrary two nodes of a chordal graph. The proposed reordering procedure using clique separators enables us to obtain another order of rows of which the number of till-ins decreases strictly.

• 품질경영학회지
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• 제33권2호
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• pp.64-73
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• 2005

In this paper, we introduce MTS(Mahalanobis-Taguchi System) Method which is suggested Dr. Taguchi in later 1990. We apply MTS Method for Quality Competitive Appraisal System(QCAS) Model which is executived from 1997 by Agency for Technology and Standards, Ministry of Commerce, Industry and Energy(MOCIE). We can measure company Quality competitive by using MTS. MTS Measure can not be compared statistical sum by calculated QCAS. MTS can be possible distinct subtle which can not distinct using statistical sum. Also MTS Method can seek more strong effect factor among of many factor. If A Company use MTS Method, can find vital factor and level of destination.

• 산업경영시스템학회지
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• 제46권3호
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• pp.41-58
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• 2023

This study identifies the commercialization success factors that can be an important indicator for the transfer and commercialization of national R&D results in the agricultural sector. Unlike other industries, the agricultural sector has a non-systematically scaled and processed industrial structure, and R&D is led by government rather than the private sector. Although the quantitative performance of national agricultural R&D, especially the number of patents and publications, has increased rapidly with the quantitative expansion of the government R&D budget, the technology commercialization of the results of agricultural R&D has been accompanied by difficulties for SMEs. Therefore, this study summarized the success factors for commercialization of state-owned technologies presented in previous studies, and based on them, analysed the success factors for commercialization specific to the agricultural sector. It also conducted a questionnaire survey using Delphi and focus group interviews (FGI) with experts from academia, research and industry, and a survey of agricultural companies to derive success factors for commercialization in the agricultural sector using logistic regression analysis. As a result, five indicators with positive correlation and three indicators with negative correlation within technology characteristics, suppliers, adopters, policy and market factors were finally derived as key factors for agricultural commercialization. In the future, it is expected that independent factor analysis of the food and seed sectors, which have independent industry characteristics from the agricultural sector, will be needed.

• 한국실내디자인학회논문집
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• 제20권3호
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• pp.242-248
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• 2011

According to a study on the accident patterns of older people in 2006 by Korea Consumer Agency (CISS), the number of accidents of the elderly at home reached 486, and the figure has increased every year. As Korea is about to enter into the aged society, it is important to investigate the factors that cause an accident in the welfare facilities for the aged and establish the barrier-free construction standards. The accident influence factors include facility environmental, physical functional, socio demographic and socio psychological factors. In terms of the verification tools, there are Facility Evaluation Index, FIM, MMSE-K and General Feature. In terms of analysis method, in addition, there are real number, percentage, t-test, ANOVA and logistic regression. In conclusion, this paper attempts to reveal correlations among the accident influence factors using the Facility Evaluation Standards (115 items in total) for facility environmental factor, FIM (3 items) for physical functional factor, MMSE-K (6 items) for socio psychological factor and questionnaire (5 items) for socio demographic factor.