• Journal of the Korean Society of Radiology
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• v.12 no.6
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• pp.727-735
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• 2018

Targeting the radiological technologists working in Gyoungsangnam province, this study was performed to obtain the fundamental data to improve the competency and right awareness of the hospital infection management, and to educate infection management of radiological technologists by analyzing the status, awareness, and performance of the hospital infection management. During April 1, 2018 to April 31, 2015, after we sent out a total of 400 questionnaires for the survey to radiological technologists working at the clinic located in Gyoungsangnam province, 320 questionnaires suitable for research were analysis by using SPSS 18.0 statistical analysis software. As the hospital infection management factors, 5 items for hospital infection and 60 items of the awareness and performance for the hospital infection management were used. 60 items of the awareness and performance for the hospital infection management were consisted hand hygiene, personal hygiene and clothing, medical equipment and supplies, cleaning and waste, examination and environment. And as the sociodemographic characteristics, the gender, marriage, age, level of education, working organization, working period, and working department were used. Consequentially, the awareness for the hospital infection management($4.19{\pm}.60$) and the performance($4.22{\pm}.52$) were confirmed as high level. Using these results, the hospital infection management level of the radiological technologists working in Gyoungsangnam province was found to be high in arareness and performance of hospital infection management. There was a significant correlation between the degree of awareness and performance of radiological technologists for hospital infection management. Furthermore, in the multiple regression analysis of cognitive factors on performance, it was found that 66.1% explanatory power had a significant positive influence. In order to improve the awareness of hospital infection management of radiological technologist working in various departments, the infection management education and improvement of hospital work environment are necessary. And also, It is important to participate actively in hospital infection management and preventive education and to play a pivotal role in securing expertise in hospital infection management.

• Journal of Plant Biotechnology
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• v.35 no.1
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• pp.31-39
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• 2008

We analyzed the current research trends of living modified organisms (LMO) by questionnaires in the interest of making biosaftey laws and policies in Korea. We executed a pre-survey at the Crop Functional Genomics 2004 conference and obtained LMO research information from 423 LMO research organizations, including 32 national research institutes, 314 universities, and 77 industries. We found that the total 59 kinds of hosts including 26 kinds of plants, 15 kinds of animals, and 18 kinds of microbes were used for LMO research and E. coli was the most common host. The risk of the most experimental hosts was below a biosafety level of 1 (73.8%) and 2 (25.9%). LMO development use purpose was implemented in various developmental uses: 51.3% in test and research use, 19% in health and medical use, and 12.9% in agriculture use. The experiment product, waste product, and products of host for LMO development were 327.2, 223.6, and 13.5 in number of plants; 280.6, 52.4, and 8.7 in number of animals; and $8.3\;{\times}\;10^{11}CFU$, $7.7\;{\times}\;10^{11}CFU$, and $6.5\;{\times}\;10^{11}CFU$ in microbes in 2004. The survey results about how to possess the LMO were very unreliable, because only 10.6% of the researchers returned the questionnaires. Consequently, we strongly suggest the scientific organizations as well as scientists should have more interests in biosafety of LMO research and an LMO biosafety management system should be developed for Korea's future biotechnology.

• Journal of environmental and Sanitary engineering
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• v.24 no.2
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• pp.17-30
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• 2009

In Iksan city, there have been a lot of complaints caused by offensive odor from residents living near the public environmental infrastructures and the Iksan industrial complex. To solve these problems, it is important to know the present condition of odor pollution level in these areas, the emission characteristics of malodorous gases in temporal and spatial variations in addition to meteorological components, and the facilities of major sources emitting malodorous compounds. The objectives of this study is to make the odor monitoring network for 20 people who lived and worked in areas where the environmental infrastructures and the Iksan industrial complex are located and their neighboring areas for six months from June 1st to October 31st in 2008 in Iksan and to monitor the temporal and regional frequency and characteristics of odor intensity using direct olfactory methods. As a result of odor monitoring, the highest frequency of sensed odor per month and 20 people for six months was found to be 107 in July, followed by 84 in September, 80 in August, 54 in June, 38 in October, respectively. Odor intensity trend showed a regional trend in the decreasing order of Dongsan-dong, Busong-dong, and Palbong-dong. Odor was widely perceived from night through next morning and considered as the sense of excreta, chemicals, sewage, compost, waste, etc. When high odor intensity was sensed, there were constant meteorological characteristics: relative humidity was 80~90%, wind speed was less than 0.5~1 m/sec, and main wind directions were from the east, the southeast, and the south.

• Journal of Environmental Health Sciences
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• v.47 no.2
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• pp.144-154
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• 2021

Objectives: This study was intended to identify hazard contribution by region, media, and chemical by calculating a hazard-based index using pollutant release and transfer register (PRTR) data. Methods: PRTR data for the period 2011 to 2016 was analyzed to examine the regional trends in toxic releases in terms of quantity and to create a corresponding hazard-based index. For the hazard-based index, the Risk-Screening Environmental Indicators (RSEI) Model was used. Results: The results of the trend analysis show that total releases decreased slightly, but health hazard levels increased consistently. According to the outcome of regional contribution analysis of the hazard-based index, Chungcheongnam-do, Jeollabuk-do and Gyeonggi-do Provinces showed a high ratio in the index for air and water release pollutants, while Gyeongsangbuk-do and Gyeongsangnam-do Provinces showed a high ratio in the index of soil release and waste transfer pollutants. Also, as a result of the analysis of the top ranked substances in the hazard-based index, it was found that chromium, cobalt and its compounds, and ethylene oxide contributed greatly to air release substances, while chromium, benzene, and lead and its compounds contributed greatly to water release substances. Conclusion: These results showed considerable disparities between total release and health hazard levels, especially in the analysis of contribution by regions and by chemical substance. Therefore, the hazard-based index should be used both to support a more comprehensive and robust approach to screening of chemicals for environmental health policy and for management.

• The Korean Journal of Nuclear Medicine Technology
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• v.16 no.2
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• pp.126-130
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• 2012

Purpose : Methode an effective block was investigated to deal with volatile radioactive gas, short lived radioactive waste generated as a result of the routinely produced radiopharmaceuticals FDG (2-deoxy-2-[$^{18}F$]fluoro-D-glucose) and compound with $^{11}C$. Materials and Methods : All components of the radiation stack monitoring and data management system for continuous radioactive gas detection in the air extract system purchase from fixed noble gas monitor of Berthold company. TEDLAR gas sampling bags purchase from the Dongbanghitech company. TEDLAR gas sampling bags (volume: 10 L) connected via paraflex or PTFE tubing and Teflon 3 way stopcock. When installing TEDLAR gas sampling bags in Hot cell on the inside and not radioactive gas concentrations were compared. According to whether the Hot cell inside a activated carbon filter installed, compare the difference in concentration of the radioactive gas $^{18}F$. Comparison of radiation emission concentration difference of module a FASTlab and TRACElab. Results : Activated carbon filter are installed in the Hot cell, a measure of the concentration of radioactive gas was 8 $Bq/m^3$. Without activated carbone filter in the hot cell was 300 $Bq/m^3$. Tedlar bag prior to installation of the radioactive gases a measure of the concentration was 3,500 $Bq/m^3$, $^{11}C$ synthesis of the measured concentration was 27,000 $Bq/m^3$. After installed a Tedlar bag and a measure concentration of the radioactive gases was 300 $Bq/m^3$ and $^{11}C$ synthesis was 1,000$Bq/m^3$. Conclusion : $^{11}C$ radioactive gas that was ejected out of the Hot cell, with the use of a Tedlar gas sampling bag stored inside. A compound of 11C is not absorbed onto activated carbon filter. But can block the release out by storing in a Tedlar gas sampling bag. We was able to reduce the radiation exposure of the worker by efficient radiation protection.

• The Journal of Korean Society for School & Community Health Education
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• v.12 no.3
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• pp.65-87
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• 2011

Objectives: The purpose of this study was to perform basic study on environmental and respiratory diseases in Ulsan and vicinities. Also, this study evaluated the actual state of environmental disease and health education at middle and high schools in Ulsan and surroundings. Methods: For this study, we conducted a survey on the health of the general public, environmental effects, and investigated the characteristics of environmental disease, health and hygiene education, etc. The populations of this study were middle and high school students in Ulsan, Korea. This study investigated the knowledge of environmental disease and health education at schools in Ulsan and vicinities from November 2009 to December 2009. All statistical calculations were performed with Statistical Package for Social Sciences (SPSS) for Windows, and gained the following results by implementing Frequency Analysis, Cross-tabulation Analysis and ANOVA. Results: As more and more environmental diseases are increased, the interest of the people has been increasing on this. The incidence rates of asthma and atopy were represented the top 25% of the country in Korea. The source of heavy metal, PAHs and VOCs in Ulsan includes the Petrochemical Complex at Nam-gu and Ulju-gun, the Nonferrous Metal Industrial Complex at Onsan-eup, Ulju-gun, and the Heavy Industrial Complex at Dong-gu and Buk-gu. Especially, there are a number of fossil fuel combustion facilities such as waste incineration plants and boilers at Nam-gu and the Onsan Industrial Complex. It may help greatly to investigate the characteristics of environmental pollutants such as environmental air pollutant and indoor contaminant to better manage the local student's health. Conclusions: It has been revealed that the hazardous chemicals and environmental contaminants are main substances of cause for asthma, atopy, dermatitis, and allergy disease. Therefore, through with collecting basic data such as environmental disease of inhabitants, health education, conscious and knowledgeable level in parents of students and students, We have to exert to improve knowledge and prevention with health life in school through development of health education program systematically for preventing of environmental disease.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.23-45
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• 2020

Big data is creating in a wide variety of fields such as medical care, manufacturing, logistics, sales site, SNS, and the dataset characteristics are also diverse. In order to secure the competitiveness of companies, it is necessary to improve decision-making capacity using a classification algorithm. However, most of them do not have sufficient knowledge on what kind of classification algorithm is appropriate for a specific problem area. In other words, determining which classification algorithm is appropriate depending on the characteristics of the dataset was has been a task that required expertise and effort. This is because the relationship between the characteristics of datasets (called meta-features) and the performance of classification algorithms has not been fully understood. Moreover, there has been little research on meta-features reflecting the characteristics of multi-class. Therefore, the purpose of this study is to empirically analyze whether meta-features of multi-class datasets have a significant effect on the performance of classification algorithms. In this study, meta-features of multi-class datasets were identified into two factors, (the data structure and the data complexity,) and seven representative meta-features were selected. Among those, we included the Herfindahl-Hirschman Index (HHI), originally a market concentration measurement index, in the meta-features to replace IR(Imbalanced Ratio). Also, we developed a new index called Reverse ReLU Silhouette Score into the meta-feature set. Among the UCI Machine Learning Repository data, six representative datasets (Balance Scale, PageBlocks, Car Evaluation, User Knowledge-Modeling, Wine Quality(red), Contraceptive Method Choice) were selected. The class of each dataset was classified by using the classification algorithms (KNN, Logistic Regression, Nave Bayes, Random Forest, and SVM) selected in the study. For each dataset, we applied 10-fold cross validation method. 10% to 100% oversampling method is applied for each fold and meta-features of the dataset is measured. The meta-features selected are HHI, Number of Classes, Number of Features, Entropy, Reverse ReLU Silhouette Score, Nonlinearity of Linear Classifier, Hub Score. F1-score was selected as the dependent variable. As a result, the results of this study showed that the six meta-features including Reverse ReLU Silhouette Score and HHI proposed in this study have a significant effect on the classification performance. (1) The meta-features HHI proposed in this study was significant in the classification performance. (2) The number of variables has a significant effect on the classification performance, unlike the number of classes, but it has a positive effect. (3) The number of classes has a negative effect on the performance of classification. (4) Entropy has a significant effect on the performance of classification. (5) The Reverse ReLU Silhouette Score also significantly affects the classification performance at a significant level of 0.01. (6) The nonlinearity of linear classifiers has a significant negative effect on classification performance. In addition, the results of the analysis by the classification algorithms were also consistent. In the regression analysis by classification algorithm, Naïve Bayes algorithm does not have a significant effect on the number of variables unlike other classification algorithms. This study has two theoretical contributions: (1) two new meta-features (HHI, Reverse ReLU Silhouette score) was proved to be significant. (2) The effects of data characteristics on the performance of classification were investigated using meta-features. The practical contribution points (1) can be utilized in the development of classification algorithm recommendation system according to the characteristics of datasets. (2) Many data scientists are often testing by adjusting the parameters of the algorithm to find the optimal algorithm for the situation because the characteristics of the data are different. In this process, excessive waste of resources occurs due to hardware, cost, time, and manpower. This study is expected to be useful for machine learning, data mining researchers, practitioners, and machine learning-based system developers. The composition of this study consists of introduction, related research, research model, experiment, conclusion and discussion.