• The Korean Journal of Pesticide Science
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• v.18 no.3
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• pp.130-140
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• 2014

Recently, some of the previous studies reported that tolclofos-methyl is still exist in ginseng cultivated soil, even though it is has been banned for ginseng. Therefore, the current study was aimed to examine the levels of absorption and translocation of tolclofos-methyl from ginseng cultivated soil to ginseng root and leaf stem for the period of 1 year. For this study, ginseng plants were transplanted in pots and treated with $5.0mg\;kg^{-1}$ of tolclofos-methyl (50% WP). At the end of each interval periods (every three months) the samples (soil, roots and leaf stems) were collected and analyzed the absorption and translocation levels of tolclofos-methyl using gas chromatography and mass spectrometry (GC-MS). The limit of quantitation of tolclofos-methyl was found to be $0.02mg\;kg^{-1}$ and 70.0~120.0% recovery was obtained with coefficient of variation of less than 10% regardless of sample types. In this study, a considerable amount of translocation of tolclofos-methyl residues were found in soil (4.28 to $0.06mg\;kg^{-1}$), root (7.09 to $1.54mg\;kg^{-1}$) and leaf stem (0.79 to $0.69mg\;kg^{-1}$). The results show that the tolclofos-methyl was absorbted and translocated from ginseng cultivated soil to ginseng root and ginseng leaf stem and found to be decreased time-coursely. Secondly, we were also analyzed soil, root and leaf stems samples from Hongcheon, Cheorwon, Punggi and Geumsan by GC-MS/MS (172 pesticides), LC-MS/MS (74 pesticides). In this study, 43 different pesticides were detected ($0.01{\sim}7.56mg\;kg^{-1}$) in soil, root and leaf stem. Further, tolclofos-methyl was detected 4 times separately in root sample alone which is less ($0.01{\sim}0.05mg\;kg^{-1}$) than their maximum residual limit (MRL) in ginseng. Consequently, the results from both studies indicate the residues of tolclofos-methyl found in ginseng cultivated soil and ginseng ensuring their safety level. Moreover, long-term evaluations are needed in order to protect the soil as well as ginseng free from tolclofos-methyl residues.

• Journal of the Korean Society of Food Science and Nutrition
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• v.9 no.1
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• pp.51-58
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• 1980

Sixteen species of algae (4 species of green algae, 5 species of brown algae and 7 species of red algae) were collected from the coast of Chungmu, Gyeongnam, from June to October, 1976. The content of minerals in algae were analyzed by Atometic Absorption Spectrophotometer. The results were as followed 1) The content of Iron and Nickel in green algae were abundant, and those of Lead, Nickel and Manganese in brown algae were low. 2) The content of Cadmium were in the range of 0.58-1.04ppm (average: 0.85ppm) in green algae, 0.32-2.10ppm (average: 1.08ppm) in brown algae and 0.54-1.70ppm (average: 1.04ppm) in red algae. The content of Cadmium were in the range of 0.3-0.6ppm in laver, Porphyra tenera, sea mustard, Undaria pinnatifida, and tangle, Laminaria japonica, but its content was lower than those expected. 3) The content of Lead were in the range of 0.67-1.40ppm (average: 1.03ppm) in green algae, 0.60-1.00ppm (average: 0.82ppm) in brown algae, 0.56-2.40ppm (average: 1.28ppm) in red algae and its content in algae were lower than in fish and shellfish. 4) The content of Copper were in the range of 10.8-24.2ppm (average: 18.95ppm) in green algae, 7.4-24.6ppm (average: 18.16ppm) in brown algae, 6.4-31.2ppm (average: 19.94ppm) in red algae and those content were considerably abundant except for some algae. 5) The content of Nickel were in the range of 5.4-16.6ppm (average: 9.1ppm) in green algae, 1.0-4.4ppm (average: 2.32ppm) in brown algae and 0.7-4.6ppm (average: 2.59ppm) in red algae. 6) The content of Iron were in the range of 686.4-1159.0ppm (average: 916.5ppm) in green algae, 131.0-499.2ppm (average: 310.16ppm) in brown algae and 156.0-530.4ppm (average: 248.2ppm) in red algae. Especially, that of Iron in green algae showed higher value than in any other. 7) The content of Manganese were in the range of 48-221ppm (average: 157.25ppm) in green algae, 12-65ppm (average: 41ppm) in brown algae and 72-162ppm (average: 121ppm) in red algae. Especially, that of Manganese in brown algae showed lower value than in any other. 8) The content of Zinc were in the range of 191.3-451.1ppm (average: 290.05ppm) in green algae, 89.9-374.2ppm (average: 202.64ppm) in brown algae and 106.4-281.4ppm (average: 188.93ppm) in red algae. 9) The content of Magnesium were in the range of 0.48-1.83% (average: 1.27%) in green algae, 1.04-1.71% (average: 1.21%) in brown algae and 0.42-1.24% (average: 0.097%) in red algae. 10) The content of Fluorine were in the range of 29.2-92.7ppm (average: 53.03ppm) in green algae, 33.3-43.5ppm (average: 39.18ppm) in brown algae and 32.4-59.0ppm (average: 44.84ppm) in red algae.

• Korean Journal of Occupational Health Nursing
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• v.13 no.1
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• pp.5-18
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• 2004

This study aims to investigate the use state of the health service computerization system in the occupational nursing field and the occupational nursers' satisfaction level, and provide basic data to promote the development of the health service computerization system for the nursing field. For this study, a questionnaire was provided to 118 occupational nurses who belong to Busan and Gyeongnam branches of KAOHN(Korean Association of Occupational Health Nurses) for 2 months (from Dec. 1, 2002 to Jan. 31, 2003). A tool of Choi Yong-Heui(2000) was used to investigate the satisfaction level of using the health service computerization system. The collected materials were analyzed in real number and percentage, average and standard deviation, t-test and ANOVA by using the SPSS WIN 10.0 program. This study is summarized as follows: 1. The average age was $31.99{\pm}5.58$ old in this study. The married were 54.2%. Participants who graduated from a junior college was 76.9%. The average service period was $4.48{\pm}4.68$ years. In service types, 79.7% of participants served in a health care center. The average service period was $3.22{\pm}2.89$ years. The service place which had 1000 workers or more was 35.6%. 2. Only 20.3% of participants in this study had a computer use education. 3. The field who participants used mostly was communication/internet, $3.29{\pm}.85$ hours in average. 4. 97.1% of occupational fields had computers and peripheral devices: 71.4% in pentium computer, 42.8% in the hard disk capacity of 20-29GB, 60.0% in 15 inch monitors, 86.2% in printers, 18.1% in digital cameras, 12.4% in LAN, and 9.5% in scanners. 80.1% of the occupational fields which were objects of study could use communication. 5. The occupational fields which did not introduced the health service computerization system were 62.8%. The main cause was attributable to entrepreneurs' insufficient recognition 66.6%. 51.5% of the entrepreneurs did not have an introduction plan. 37.2% of participating companies had the health service computerization system. 56.4% of them introduced it since the year 2000. 81.6% of the introduction motivation aimed to the efficiency of health service. The most issue upon introduction was insufficient understanding of a person in charge - 25.6%. The in-house development of the system covered 56.4%. 61.5% of the participants accepted their demands from the first stage of development. The direct effect of computerization showed the increase of 25.9% in the quickness and continuity of service treatment, and 25.9% in the serviceability of statistical treatment. 6. 22.0% of the participants had a computerization system use education. 69.2% of them had a in-house education. An educational method by nurses who used the computerization system was 76.9%. 92.3% of the education was helpful for practical duties. 7. An analysis of the computer use by health service fields showed that the medicine management in a health management field was 15.9%. the work environment measuring management in a work environment filed was 32.9%. the employment. general and special examination management in a heal th management field was 61.1 %. the various reports management in an administrative field was 64%. the health education data preparation management in an educational field was 58.0%. and the medicine and expendables management in an equipment management field was 51.6%. An analysis of the computerization system use showed that the various statistical data manage in a health management field was 13.0%. the work environment measuring management in a health management field was 34.8%. the personal disease management in a health management field was 51.9%. the heal education data preparation management in an educational field was 54.5%. and the equipment management of health care centers in an equipment management field was 52.6%. 8. 31.6% of the participants wanted that health service computerization system would include the generals of health services. 42.4% of the participants thought that first of all. the aggressive interest and investment of employers were required to build the health service computerization system. 9. The participants' satisfaction level on the computerization system use was $3.51{\pm}.57$ points. An analysis by each factor showed $3.62{\pm}.68$ points in a service change factor. $3.15{\pm}.63$ points in a computer program use factor, and $3.45{\pm}.71$ points in a continuous computerization use factor. 10. An analysis of the computerization system use by general characteristics of participants showed that the married (p = .022) had the satisfaction level higher than the unmarried. 11. The satisfaction level of the computerization system use by participants' computer use ability tended to be higher in proportion to the increase of computer use abilities in spreadsheet (F=2.606. p=.048). presentation (F=3.62. p=.012) and communication/internet(F=2.885. p=.0321. Based on the study results mentioned above. I will suggest as follows : The nationwide enlargement and repetition study is required for occupational nurses who serve in occupational nursing fields. The computerization system in a health service field is inferior comparing with other fields. The computerization system standard by business types and characteristics should be prepared through employers's aggressive participation and national support. Therefore various statistical data which occurs in occupational fields will be managed systematically and efficiently. A regular and systematic computer education plan for occupational nurses in charge of health services in the filed is urgently required to efficiently manage and improve the health of on-site workers.

• Journal of radiological science and technology
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• v.28 no.2
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• pp.137-144
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• 2005

To find the personal radiation dose of radiological technologists, a survey was conducted to 623 radiological technologists who had been working at 44 general hospitals in Korea's 16 cities and provinces from 1998 to 2002. A total of 2,624 cases about personal radiological dose that were collected were analyzed by region, year and hospital, the results of which look as follows : 1. The average radiation dose per capita by region and year for the 5 years was 1.61 mSv. By region, Daegu showed the highest amount 4.74 mSv, followed by Gangwon 4.65 mSv and Gyeonggi 2.15 mSv. The lowest amount was recorded in Chungbuk 0.91 mSv, Jeju 0.94 mSv and Busan 0.97 mSv in order. By year, 2000 appeared to be the year showing the highest amount of radiation dose 1.80 mSv, followed by 2002 1.77 mSv, 1999 1.55 mSv, 2001 1.50 mSv and 1998 1.36 mSv. 2. In 1998, Gangwon featured the highest amount of radiological dose per capita 3.28 mSv, followed by Gwangju 2.51 mSv and Daejeon 2.25 mSv, while Jeju 0.86mSv and Chungbuk 0.85 mSv belonged to the area where the radiation dose remained less than 1.0 mSv In 1999, Gangwon also topped the list with 5.67 mSv, followed by Daegu with 4.35 mSv and Gyeonggi with 2.48 mSv. In the same year, the radiation dose was kept below 1.0 mSv. in Ulsan 0.98 mSv, Gyeongbuk 0.95 mSv and Jeju 0.91 mSv. 3. In 2000, Gangwon was again at the top of the list with 5.73 mSv. Ulsan turned out to have less than 1.0 mSv of radiation dose in the years 1998 and 1999 consecutively, whereas the amount increased relatively high to 5.20 mSv. Chungbuk remained below the level of 1.0 mSv with 0.79 mSv. 4. In 2001, Daegu recorded the highest amount of radiation dose among those ever analyzed for 5 years with 9.05 mSv, followed by Gangwon with 4.01 mSv. The area with less than 1.0 mSv included Gyeongbuk 0.99 mSv and Jeonbuk 0.92 mSv. In 2002, Gangwon also led the list with 4.65 mSv while Incheon 0.88 mSv, Jeonbuk 0.96 mSv and Jeju 0.68 mSv belonged to the regions with less than 1.0 mSv of radiation dose. 5. By hospital, KMH in Daegu showed the record high amount of average radiation dose during the period of 5 years 6.82 mSv, followed by GAH 5.88 mSv in Gangwon and CAH 3.66 mSv in Seoul. YSH in Jeonnam 0.36 mSv comes first in the order of the hospitals with least amount of radiation dose, followed by GNH in Gyeongnam 0.39 mSv and DKH in Chungnam 0.51 mSv. There is a limit to the present study in that a focus is laid on the radiological technologists who are working at the 3rd referral hospitals which are regarded to be stable in terms of working conditions while radiological technologists who are working at small-sized hospitals are excluded from the survey. Besides, there are also cases in which hospitals with less than 5 years since establishment are included in the survey and the radiological technologists who have worked for less than 5 years at a hospital are also put to survey. We can't exclude the possibility, either, of assumption that the difference of personal average radiological dose by region, hospital and year might be ascribed to the different working conditions and facilities by medical institutions. It seems therefore desirable to develop standardized instruments to measure working environment objectively and to invent device to compare and analyze them by region and hospital more accurately in the future.

• Journal of Distribution Research
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• v.15 no.4
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• pp.61-85
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• 2010

Introduction: Diffusion is process by which an innovation is communicated through certain channel overtime among the members of a social system(Rogers 1983). Bass(1969) suggested the Bass model describing diffusion process. The Bass model assumes potential adopters of innovation are influenced by mass-media and word-of-mouth from communication with previous adopters. Various expansions of the Bass model have been conducted. Some of them proposed a third factor affecting diffusion. Others proposed multinational diffusion model and it stressed interactive effect on diffusion among several countries. We add a spatial factor in the Bass model as a third communication factor. Because of situation where we can not control the interaction between markets, we need to consider that diffusion within certain market can be influenced by diffusion in contiguous market. The process that certain type of retail extends is a result that particular market can be described by the retail life cycle. Diffusion of retail has pattern following three phases of spatial diffusion: adoption of innovation happens in near the diffusion center first, spreads to the vicinity of the diffusing center and then adoption of innovation is completed in peripheral areas in saturation stage. So we expect spatial effect to be important to describe diffusion of domestic discount store. We define a spatial diffusion model using multinational diffusion model and apply it to the diffusion of discount store. Modeling: In this paper, we define a spatial diffusion model and apply it to the diffusion of discount store. To define a spatial diffusion model, we expand learning model(Kumar and Krishnan 2002) and separate diffusion process in diffusion center(market A) from diffusion process in the vicinity of the diffusing center(market B). The proposed spatial diffusion model is shown in equation (1a) and (1b). Equation (1a) is the diffusion process in diffusion center and equation (1b) is one in the vicinity of the diffusing center. $$\array{{S_{i,t}=(p_i+q_i{\frac{Y_{i,t-1}}{m_i}})(m_i-Y_{i,t-1})\;i{\in}\{1,{\cdots},I\}\;(1a)}\\{S_{j,t}=(p_j+q_j{\frac{Y_{j,t-1}}{m_i}}+{\sum\limits_{i=1}^I}{\gamma}_{ij}{\frac{Y_{i,t-1}}{m_i}})(m_j-Y_{j,t-1})\;i{\in}\{1,{\cdots},I\},\;j{\in}\{I+1,{\cdots},I+J\}\;(1b)}}$$ We rise two research questions. (1) The proposed spatial diffusion model is more effective than the Bass model to describe the diffusion of discount stores. (2) The more similar retail environment of diffusing center with that of the vicinity of the contiguous market is, the larger spatial effect of diffusing center on diffusion of the vicinity of the contiguous market is. To examine above two questions, we adopt the Bass model to estimate diffusion of discount store first. Next spatial diffusion model where spatial factor is added to the Bass model is used to estimate it. Finally by comparing Bass model with spatial diffusion model, we try to find out which model describes diffusion of discount store better. In addition, we investigate the relationship between similarity of retail environment(conceptual distance) and spatial factor impact with correlation analysis. Result and Implication: We suggest spatial diffusion model to describe diffusion of discount stores. To examine the proposed spatial diffusion model, 347 domestic discount stores are used and we divide nation into 5 districts, Seoul-Gyeongin(SG), Busan-Gyeongnam(BG), Daegu-Gyeongbuk(DG), Gwan- gju-Jeonla(GJ), Daejeon-Chungcheong(DC), and the result is shown