• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2006.04a
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• pp.209-212
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• 2006

Using sulfur sotope analysis of dissolved sulfate in surface water, we have investigated the source of sulfate in order to identify the abandoned metallic mines, which have the potential of heavy metal contamination within watershed. The range of the sulfur isotope values for dissolved sulfate in stream waters (DD-1 and 2) are similar to those of sulfides from the Dunjun mine, which suggests that oxidation of sulfides is the principal source of $SO_4^{2-}$ in these stream waters. Also, heavier sulfur isotopes in waters near Baekjun and Hamchang mines imply the possibility of contamination in waters by these metallic mines.

• Proceedings of the SCSK Conference
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• 2003.09b
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• pp.448-455
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• 2003

Because cosmetics are applied directly to human skin, contamination of such products by microorganisms should be carefully avoided. Since cosmetics are usually kept at room temperature and contain large amounts of nitrogen and carbon sources, they may easily become contaminated by a variety of microorganisms, such as bacteria, filamentous fungi, and yeasts. The rapid and accurate identification of these microorganisms is essential to prevent further expansion of such contamination and the damage it causes. However, more than 30 days and laboratory skills are usually necessary in order to identify microorganisms in cosmetic materials. These time and labor constraints may allow further damage of the cosmetic products and thereby harm the consumer.(omitted)

• Journal of Environmental Health Sciences
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• v.40 no.6
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• pp.469-476
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• 2014

Objectives: The purpose of this study was to identify the stains causing infections in dental clinics by analyzing bacterial contamination, as well as to suggest improvements for infection control in dental clinics. Methods: In this study, a questionnaire survey of 47 dental hospitals and clinics located in Gyeonggi-do and Incheon, South Korea was administered from June 2013 to September 2013 and used to investigate the practice rates of infection control by dental hygienists and to analyze the bacterial contamination levels in dental offices. Results: In the studied institutions, the bacterial contamination levels of water lines were $20.9{\times}10^3$ colony forming units (CFU)/mL for three-way syringes, $12.7{\times}10^3CFU/mL$ for high-speed handpieces and $9.8{\times}10^3CFU/mL$ for gargling water. The bacterial contamination levels of surfaces were $44.9{\times}10^3CFU/mL$ in cuspidors, higher than in unit chairs ($2.9{\times}10^3CFU/mL$) and light handles ($6.7{\times}10^3CFU/mL$). The mean bacterial cell count of water lines and surfaces was relatively high in all establishments founded 11 years ago or more, and the mean bacterial cell count of waterline handpieces was $6.27{\times}10^3CFU/mL$ in establishments founded between one and five years ago, $11.16{\times}10^3CFU/mL$ six to ten years ago and $20.04{\times}10^3CFU/mL$ 11 years ago or more, which suggests that earlier foundation is associated with higher bacterial contamination levels with a statistical difference (p<0.01). Similarly, the mean bacterial cell count of cuspidors using water from water lines was also $70.16{\times}10^3CFU/mL$ in at least 11-year-old establishments, statistically significantly higher among in one- to five-year-old ($4.61{\times}10^3CFU/mL$) and six- to ten-year-old clinics ($47.89{\times}10^3CFU/mL$) (p<0.05). Conclusion: This study may be utilized to improve the bacterial contamination levels in dental offices by controlling the characteristics and environmental factors of dental offices that affect the microbial contamination of waterlines and surfaces in such institutions.

• Journal of the Korean Society of Radiology
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• v.18 no.2
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• pp.171-177
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• 2024

In this study, two general X-ray device, CT, and MRI inspection devices were selected from general hospitals in the Daejeon area and an experiment was conducted to predict the level of infection by measuring the surface contamination of the inspection devices at different times and to use it as basic data for infection prevention. As a result, the surface contamination level by time zone for general X-ray devices and MRI examination devices was in the order of 13H > 8H > 16H, and for CT examination devices, it was 13H > 16H > 8H, which appeared to be influenced by the number of tests. In addition, the surface contamination results for each part of the test device showed that the highest ATP contamination value was found on the stand bucky handle for the general X-ray device, the headrest for the CT examination device, and the operation switch for the MRI examination device, which was closely related to the number of contacts. As a result of comparing before and after disinfection, all devices showed a significant decrease after disinfection. Based on the results of the experiment, it is believed that it can be used as basic data to identify the level of contamination in radiology laboratories and prevent infectious diseases.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.3106-3106
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• 2001

Imaging spectrometry or hyperspectral imaging is a recent development that makes possible quantitative and qualitative measurement for food quality and safety. This paper presents the research results that a hyperspectral imaging system can be used effectively for detecting fecal (from duodenum, cecum, and colon) and ingesta contamination on poultry carcasses from the different feed meals (wheat, mile, and corn with soybean) for poultry safety inspection. A hyperspectral imaging system has been developed and tested for the identification of fecal and ingesta surface contamination on poultry carcasses. Hypercube image data including both spectral and spatial domains between 430 and 900 nm were acquired from poultry carcasses with fecal and ingesta contamination. A transportable hyperspectral imaging system including fiber optically fabricated line lights, motorized lens control for line scans, and hypercube image data from contaminated carcasses with different feeds are presented. Calibration method of a hyperspectral imaging system is demonstrated using different lighting sources and reflectance panels. Principal Component and Minimum Noise Fraction transformations will be discussed to characterize hyperspectral images and further image processing algorithms such as image band ratio of dual-wavelength images and its histogram stretching with thresholding process will be demonstrated to identify fecal and ingesta materials on poultry carcasses. This algorithm could be further applied for real-time classification of fecal and ingesta contamination on poultry carcasses in the poultry processing line.

• Journal of muscle and joint health
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• v.26 no.3
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• pp.241-250
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• 2019

Purpose: This study was conducted to identify influencing factors on the performance of healthcare-associated infection control and microbiological hand contamination among caregivers at a tertiary hospital. Methods: The participants of this study were 59 caregivers woring at a tertiary hospital. Data were collected from July 1 to 30, 2018. Data were analyzed using descriptive statistics, t-test, ANOVA, Scheffé test, Pearson's correlation coefficients and stepwise multiple regression by SPSS 23.0 Win program. Results: Multiple regression analysis revealed that factors influencing performance of healthcare-associated infection control were awareness (β=.63, p<.001) and the experience of infection-related education (β=-3.40, p=.042). Regression equations describing the performance of healthcare-related infection control were found to be appropriate (F=27.29, p<.001) and accounted for 68% of variance. Factors affecting the degree of microbiological hand contamination were work experience (β=-0.28, p=.026) and healthcare-related infection performance (β=-0.28, p=.029). A regression equation describing the microbiological hand contamination was appropriate (F=6.10, p=.004) and accounted for 42% of variance. Conclusion: The findings of this study suggest that it is necessary to increase performance of healthcare-associated infection control by caregivers. Also, educations for preventing healthcare-associated infection and guidelines for increasing compliance with healthcare-associated infection control are recommended to improve performance of healthcare-associated infection control.

• Safety and Health at Work
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• v.2 no.3
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• pp.273-281
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• 2011

Objectives: Studies examining healthcare workers' exposure to antineoplastic drugs have focused on the drug preparation or drug administration areas. However, such an approach has probably underestimated the overall exposure risk as the drugs need to be delivered to the facility, transported internally and then disposed. The objective of this study is to determine whether drug contamination occurs throughout a facility and, simultaneously, to identify those job categories that are potentially exposed. Methods: This was a multi-site study based in Vancouver, British Columbia. Interviews were conducted to determine the departments where the drugs travel. Subsequent site observations were performed to ascertain those surfaces which frequently came into contact with antineoplastic drugs and to determine the job categories which are likely to contact these surfaces. Wipe samples were collected to quantify surface contamination. Results: Surface contamination was found in all six stages of the hospital medication system. Job categories consistently found to be at risk of exposure were nurses, pharmacists, pharmacy technicians, and pharmacy receivers. Up to 11 job categories per site may be at risk of exposure at some point during the hospital medication system. Conclusion: We found drug contamination on select surfaces at every stage of the medication system, which indicates the existence of an exposure potential throughout the facility. Our results suggest that a broader range of workers are potentially exposed than has been previously examined. These results will allow us to develop a more inclusive exposure assessment encompassing all healthcare workers that are at risk throughout the hospital medication system.

• Tribology and Lubricants
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• v.36 no.6
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• pp.385-390
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• 2020

It rains heavily, such as long rain and typhoons, during a typical rainy season in Korea. In this season, several fuel contamination accidents by water and vehicular problems caused by water contaminated fuel occur. Many research groups have studied the effects of water contaminated fuel on vehicles and environment. However the characteristics of water contaminated fuel have not been studied. In this study, we prepared diesel samples with a constant ratio of water (0~30 volume %) using an emulsifier. Then, we analyzed these diesel samples for their representative fuel properties. In the analytical results, diesel with 30% water showed an increase in fuel properties such as density (823→883 kg/㎥), kinematic viscosity (2.601→6.345 ㎟/s), flash point (47→56℃), pour point (-22→2℃), CFPP (cold filter plugging point) (-17→20℃) and copper corrosion number (1a→2a). The low temperature characteristics, such as low pour point and CFPP, blocks the fuel filter in the cold season. In addition, water contaminated diesel decreases lubricity (190→410 ㎛) under high frequency reciprocating rig (HFRR) and derived cetane number (54.81→34.25). The low lubricity of fuel causes vehicle problem such as pump and injector damage owing to severe friction. In addition, the low cetane diesel fuel increases exhaust gases such as NOx and particulate matters (PM) owing to incomplete combustion. This study can be used to identify the problems caused by water contamination to vehicle and fuel facilities.

• Environmental and Resource Economics Review
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• v.17 no.1
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• pp.165-196
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• 2008

This paper reports a quantitative meta analysis of the economic impacts of localized noxious and contaminated sites. Using either hedonic property value or stated preference methods, economists have studied the effects of contamination or noxious activities, or the benefits realized from their elimination, on real estate prices at more than 40 sites. In support of wise public and private investments in environmental quality, most of these studies aim to inform decision makers about the benefits of remediation and cleanup. Their results vary considerably, but there has been no previous systematic effort to analyze the differences and identify shared insights. This study uses established methods of meta analysis to identify points of agreement and differences in this body of literature. The studies are characterized by the type of site, modeling approach, geographic extent of impacts, data features, and other key factors that underlie their value estimates. The impact estimates are normalized as proportional effects on property values. This study attempts to discover whether the estimated economic impacts of contamination or noxious activity differ according to these characteristics of the studies, and whether anything general can be said about the economic consequences of site contamination and remediation. Bivariate, multivariate, and logit techniques are applied to the data. The results suggest that the property value is the most sensitive to water base contamination, published case studies result in systematically greater environmental value than those in unpublished reports, and real estate markets show responses to environmental condition changes.

• Economic and Environmental Geology
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• v.56 no.3
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• pp.331-341
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• 2023

When creating a soil contamination map using geostatistical techniques, there are various sources that can affect prediction errors. In this study, a grid-based soil contamination map was created from the sampling data of heavy metal concentrations in soil in abandoned mine areas using Ordinary Kriging. Five factors that were judged to affect the prediction error of the soil contamination map were selected, and the variation of the root mean squared error (RMSE) between the predicted value and the actual value was analyzed based on the Leave-one-out technique. Then, using a machine learning algorithm, derived the top three factors affecting the RMSE. As a result, it was analyzed that Variogram Model, Minimum Neighbors, and Anisotropy factors have the largest impact on RMSE in the Standard interpolation. For the variogram models, the Spherical model showed the lowest RMSE, while the Minimum Neighbors had the lowest value at 3 and then increased as the value increased. In the case of Anisotropy, it was found to be more appropriate not to consider anisotropy. In this study, through the combined use of geostatistics and machine learning, it was possible to create a highly reliable soil contamination map at the local scale, and to identify which factors have a significant impact when interpolating a small amount of soil heavy metal data.