• 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 Environmental Impact Assessment
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• v.27 no.6
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• pp.695-703
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• 2018

This study was conducted to suggest a sustainable farming practice forresource recycling in vegetable gardens of North Korea. In North Korea, farmers are allowed to own private vegetable gardens less than $100m^2$. However, usage of fertilizers in private vegetable gardens is very limited due to economic sanctions by UN security council. If North and South Korea initiated the cooperative action in the near future, agricultural sector would be the highest priority cooperation area. Considering the current North Korean situation in agriculture, we would like to suggest a method for producing organic fertilizer manure. For raw materials for producing manure, we selected corn byproduct, which is the most abundant material, and rabbits' feces, which are easily obtained from individual private farms in North Korea. As we cannot get corn byproducts and rabbits' feces from North Korea, we prepared samples of corn byproducts and rabbits; feces from many places in South Korea. After statistical analysis of variance, there was no significant difference in the T-N contents of corn byproducts from Gyeonggi, Gangwon, Chungnam, Chungbuk, Jeollabuk and Gyeongsangnam-dos, which indicates that the fertilizing quality of corn byproducts does not vary significantly in the spatial scale of South. Korea. In this sense, if we use corn samples from Gyeonggi province, they would not be very different from those of North Korean regions. Physicochemical properties of rabbits' feces were different between those eating feed grains and those eating plants only. Hence, we used rabbits' feces of the rabbits from Yeonchun area, which were fed by plants only. Using three different mixing ratios of corn byproducts and rabbits' feces, composting was conducted for 60 days. The mixing ratio of 1:1 produced the manure with % T-N of 1.98% and OM/N ratio of 31.7 after 30 days of composting, which is comparable to the quality of commercial manure.

• Korean Journal of Psychosomatic Medicine
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• v.27 no.1
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• pp.42-49
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• 2019

Objectives : Living donor liver transplantation (LDLT) is a life-saving therapy for patients with terminal liver disease. Many studies have focused on recipients rather than donors. The aim of this study was to assess the emotional status and personality characteristics of LDLT donors. Methods : We evaluated 218 subjects (126 male, 92 female) who visited Daegu Catholic University Medical Center from August 2012 to July 2018. A retrospective review of their preoperative psychological evaluation was done. We investigated epidemiological data and the Minnesota Multiphasic Personality Inventory-2 questionnaire. Subanalysis was done depending on whether subjects actually underwent surgery, relationship with the recipient, and their gender. Results : Mean age of subjects was $32.19{\pm}10.91years$. 187 subjects received LDLT surgery (actual donors) while 31 subjects didn't (potential donors). Donor-recipient relationship included husband-wife, parent-children, brother-sister etc. Subjects had statistical significance on validity scale L, F, K and all clinical scales compared to the control group. Potential donors had significant difference in F(b), F(p), K, S, Pa, AGGR, PSYC, DISC and NEGE scales compared to actual donors. F, D and NEGE scales were found to be predictive for actual donation. Subanalysis on donor-recipient relationship and gender also showed significant difference in certain scales. Conclusions : Under-reporting of psychological problems should be considered when evaluating living-liver donors. Information about the donor's overall psychosocial background, mental status and donation process should also be acquired.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.7
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• pp.834-846
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• 2017

An increase in the number of retiring experienced pilots as well as drastic graying of new pilots will raise the problems on deepening imbalance of supply and demand of pilots over the next 7 years, which could entail fatal problems for the safety of harbour pilotage. In this study, the improvement plan of legal system to ease imbalance between supply and demand of pilots and help secure more experienced pilots has been proposed. A current state survey and analysis, statistical analysis, questionnaire survey on foreign countries, in-depth consultation with experts, etc., were all carried out to support this research. The conclusions of this study are, firstly, to propose an amendment that the minimum requirement of 5 years of seagoing service as a master to sit for the pilot exam should be relaxed to 2 years(which must include at least 1 year of master's seagoing service within the most recent 5 years) but the minimum requirement of 1 year of pilotage service should be reinforced to 1 year and 6 months to obtain a higher class of pilot certificate. Secondly, it is proposed that an amendment offering an additional 1 point per year over the minimum period of 2 years of seagoing service as a master should be added, with a maximum of 10 points in order to rationalize the additional incentive point system. In order to secure experienced pilots and resolve the legal conflict between the certificate revalidation system and the retirement system, it is also proposed that an amendment be passed revoking the retirement system and limiting the validity of any new certificates only to 68 years of age when issuing or revalidating a certificate, if an applicant is over a certain age. Promotional work, such as collecting opinions from interested parties and generating positive public awareness, should be carried out in the future. It will also be necessary to conduct a study on the training pilot exam system.

• Korean Journal of Environmental Biology
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• v.36 no.3
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• pp.400-411
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• 2018

This study was a survey of the Wonju stream in Wonju city from May 2015 to September 2016. A total of three sites were selected from the upstream area Gwanseol-dong to the downstream area Hojeo-myeon. Physicochemical analysis, aquatic insect changes, cluster analysis, functional group analysis, rarefaction curve, and statistical analysis were compared between 2004 and 2016. A total of 19 species (38.78%) in 2004 and 22 species (36.67%) in 2016 were analyzed, with the largest number belonging to ephemeroptera. The individual ratio ranged from 27,759.2 (ind. $m^{-2}$, 84.30%) in 2004 to 4,573.2 (ind. $m^{-2}$, 41.64%) in 2016, with the highest number involving diptera. As a result of the community analysis, significant differences were detected in the indices of dominance, diversity, evenness, and richness in 2004 and 2016 (p<0.05). Burrowers of the habitat orientation groups showed the greatest variation with an average of -68.00% (${\pm}2.15$) and the collector-gatherers of the functional feeding groups showed the highest variation of -40.12% (${\pm}1.77$). The rarefaction curve analysis suggested that the species was the poorest in the midstream regions in 2004 and 2016. Physical factors and water quality showed a significant correlation with diversity index, evenness index, and the number of individuals. MDS analysis of the similarity of upstream and downstream regions was high in 2004, and low in 2016. The differences were attributed to physicochemical changes such as increase in flow velocity due to improvement of small dams and changes in bottom structure.

• Phonetics and Speech Sciences
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• v.11 no.3
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• pp.9-21
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• 2019

This study aimed to compare the prosodic characteristics of North Korean defectors and South Koreans in three types of sentences (declarative, interrogative, and negative) in two reading tasks (short and dialogue) through acoustic analysis and auditory-perceptual evaluation. In addition, this study examined the relationship between the auditory-perceptual evaluation scores and self-assessment questionnaires on intonation for North Korean defectors. The participants were 15 North Korean defectors and 15 Korean speakers with standard Seoul accents. For statistical analysis, three-way mixed ANOVA and multivariate analysis were performed within the three types of sentences in the reading tasks through acoustic analysis and the Mann-Whitney U Test for auditory-perceptual evaluation. Pearson's product-moment correlation coefficients were also used to identify the correlations between the results of the self-assessment questionnaire on intonation and the auditory-perceptual evaluation. The North Korean defectors were found to have a significantly lower pitch range and auditory-perceptual evaluation score than South Koreans in reading tasks. Moreover, there was a significant correlation between their auditory-perceptual evaluations and self-assessment questionnaires on intonation. The study findings suggest that North Korean defectors, who face many challenges with intonation, showed a tendency to think that their intonation differed from the standard Korean intonation and showed better auditory evaluation results for interrogative sentences.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.43-62
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• 2019

At one time, the anomaly detection sector dominated the method of determining whether there was an abnormality based on the statistics derived from specific data. This methodology was possible because the dimension of the data was simple in the past, so the classical statistical method could work effectively. However, as the characteristics of data have changed complexly in the era of big data, it has become more difficult to accurately analyze and predict the data that occurs throughout the industry in the conventional way. Therefore, SVM and Decision Tree based supervised learning algorithms were used. However, there is peculiarity that supervised learning based model can only accurately predict the test data, when the number of classes is equal to the number of normal classes and most of the data generated in the industry has unbalanced data class. Therefore, the predicted results are not always valid when supervised learning model is applied. In order to overcome these drawbacks, many studies now use the unsupervised learning-based model that is not influenced by class distribution, such as autoencoder or generative adversarial networks. In this paper, we propose a method to detect anomalies using generative adversarial networks. AnoGAN, introduced in the study of Thomas et al (2017), is a classification model that performs abnormal detection of medical images. It was composed of a Convolution Neural Net and was used in the field of detection. On the other hand, sequencing data abnormality detection using generative adversarial network is a lack of research papers compared to image data. Of course, in Li et al (2018), a study by Li et al (LSTM), a type of recurrent neural network, has proposed a model to classify the abnormities of numerical sequence data, but it has not been used for categorical sequence data, as well as feature matching method applied by salans et al.(2016). So it suggests that there are a number of studies to be tried on in the ideal classification of sequence data through a generative adversarial Network. In order to learn the sequence data, the structure of the generative adversarial networks is composed of LSTM, and the 2 stacked-LSTM of the generator is composed of 32-dim hidden unit layers and 64-dim hidden unit layers. The LSTM of the discriminator consists of 64-dim hidden unit layer were used. In the process of deriving abnormal scores from existing paper of Anomaly Detection for Sequence data, entropy values of probability of actual data are used in the process of deriving abnormal scores. but in this paper, as mentioned earlier, abnormal scores have been derived by using feature matching techniques. In addition, the process of optimizing latent variables was designed with LSTM to improve model performance. The modified form of generative adversarial model was more accurate in all experiments than the autoencoder in terms of precision and was approximately 7% higher in accuracy. In terms of Robustness, Generative adversarial networks also performed better than autoencoder. Because generative adversarial networks can learn data distribution from real categorical sequence data, Unaffected by a single normal data. But autoencoder is not. Result of Robustness test showed that he accuracy of the autocoder was 92%, the accuracy of the hostile neural network was 96%, and in terms of sensitivity, the autocoder was 40% and the hostile neural network was 51%. In this paper, experiments have also been conducted to show how much performance changes due to differences in the optimization structure of potential variables. As a result, the level of 1% was improved in terms of sensitivity. These results suggest that it presented a new perspective on optimizing latent variable that were relatively insignificant.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.63-88
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• 2019

The goal of this paper is to investigate changes in North Korea's domestic and foreign policies through automated text analysis over North Korea represented in South Korean mass media. Based on that data, we then analyze the status of text mining research, using a text mining technique to find the topics, methods, and trends of text mining research. We also investigate the characteristics and method of analysis of the text mining techniques, confirmed by analysis of the data. In this study, R program was used to apply the text mining technique. R program is free software for statistical computing and graphics. Also, Text mining methods allow to highlight the most frequently used keywords in a paragraph of texts. One can create a word cloud, also referred as text cloud or tag cloud. This study proposes a procedure to find meaningful tendencies based on a combination of word cloud, and co-occurrence networks. This study aims to more objectively explore the images of North Korea represented in South Korean newspapers by quantitatively reviewing the patterns of language use related to North Korea from 2016. 11. 1 to 2019. 5. 23 newspaper big data. In this study, we divided into three periods considering recent inter - Korean relations. Before January 1, 2018, it was set as a Before Phase of Peace Building. From January 1, 2018 to February 24, 2019, we have set up a Peace Building Phase. The New Year's message of Kim Jong-un and the Olympics of Pyeong Chang formed an atmosphere of peace on the Korean peninsula. After the Hanoi Pease summit, the third period was the silence of the relationship between North Korea and the United States. Therefore, it was called Depression Phase of Peace Building. This study analyzes news articles related to North Korea of the Korea Press Foundation database(www.bigkinds.or.kr) through text mining, to investigate characteristics of the Kim Jong-un regime's South Korea policy and unification discourse. The main results of this study show that trends in the North Korean national policy agenda can be discovered based on clustering and visualization algorithms. In particular, it examines the changes in the international circumstances, domestic conflicts, the living conditions of North Korea, the South's Aid project for the North, the conflicts of the two Koreas, North Korean nuclear issue, and the North Korean refugee problem through the co-occurrence word analysis. It also offers an analysis of South Korean mentality toward North Korea in terms of the semantic prosody. In the Before Phase of Peace Building, the results of the analysis showed the order of 'Missiles', 'North Korea Nuclear', 'Diplomacy', 'Unification', and ' South-North Korean'. The results of Peace Building Phase are extracted the order of 'Panmunjom', 'Unification', 'North Korea Nuclear', 'Diplomacy', and 'Military'. The results of Depression Phase of Peace Building derived the order of 'North Korea Nuclear', 'North and South Korea', 'Missile', 'State Department', and 'International'. There are 16 words adopted in all three periods. The order is as follows: 'missile', 'North Korea Nuclear', 'Diplomacy', 'Unification', 'North and South Korea', 'Military', 'Kaesong Industrial Complex', 'Defense', 'Sanctions', 'Denuclearization', 'Peace', 'Exchange and Cooperation', and 'South Korea'. We expect that the results of this study will contribute to analyze the trends of news content of North Korea associated with North Korea's provocations. And future research on North Korean trends will be conducted based on the results of this study. We will continue to study the model development for North Korea risk measurement that can anticipate and respond to North Korea's behavior in advance. We expect that the text mining analysis method and the scientific data analysis technique will be applied to North Korea and unification research field. Through these academic studies, I hope to see a lot of studies that make important contributions to the nation.

• Journal of Korean Society of Forest Science
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• v.108 no.2
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• pp.147-167
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• 2019

This study was conducted to analyze forest vegetation structure in the Marugeum (Ridge) area of Gitdaebaegibong to Jukryeong, Baekdudaegan. Data were collected in 298 quadrates through a Braun-Blanquet vegetation survey from April, 2018 to October, 2018. Forest vegetation was classified into 13 vegetation units. A Quercus mongolica community was divided into Morus bombycis, Filipendula glaberrima, Fraxinus sieboldiana, Prunus maackii unit and Q. mongolica typical unit. The M. bombycis unit was further classified into a Deutzia glabrata group and M. bombycis typical group. The F. glaberrima unit was subdivided into a Veratrum oxysepalum group, Arundinella hirta group, and F. glaberrima typical group. The F. sieboldiana unit was divided into a Pinus densiflora group, Larix kaempferi group, and F. sieboliana typical group. The relationship between vegetation units and environmental factors was studied through coincidence analysis and CCA. The F. glaberrima unit (VU 6~8) was distributed by elevation above 1,200 m and other vegetation units were distributed below 1,200 m. Results of the CCA analysis showed that the F. glaberrima unit distribution is positively correlated with elevation. As a result of species diversity, the F. glaberrima unit was higher than other vegetation units. A similarity index analysis revealed that the F. sieboldiana unit (VU 9~11) was relatively homogeneous, and the M. bombycis unit (VU 1~5) and A. girta group (VU 7) were relatively heterogeneous. A detrended correspondence analysis determined that the distance between the statistical axes of the M. bombycis and F. glaberrima units was the greatest, which is consistent with the analysis of the similarity index. As a result of interspecific correlation of major woody plants, hydrophilic species were positively correlated, and a negative correlation was found between Q. mongolica and intolerant species such as P. densiflora and L. kaempferi.

• Journal of the Korean Society of Radiology
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• v.13 no.4
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• pp.573-579
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• 2019

The purpose of this study is predicted easily the entrance surface dose (ESD) in chest digital radiography. We used two detector type such as flat-panel detector (FP) and IP (Imaging plate detector). ESD was measured at each exposure condition combined tube voltage with tube current using dosimeter, after attaching on human phantom, it was repeated 3 times. Phantom images were evaluated independently by three chest radiologists after blinding image. Dose-area product (DAP) or exposure index (EI) was checked by Digital Imaging and Communications in Medicine (DICOM) header on phantom images. Statistical analysis was performed by the linear regression using SPSS ver. 19.0. ESD was significant difference between FP and IP($85.7{\mu}Gy$ vs. $124.6{\mu}Gy$, p=0.017). ESD was positively correlated with image quality in FP as well as IP. In FP, adjusted R square was 0.978 (97.8%) and linear regression model was $ESD=0.407+68.810{\times}DAP$. DAP was 4.781 by calculating the $DAP=0.021+0.014{\times}340{\mu}Gy$. In IP, adjusted R square was 0.645 (64.5%) and linear regression model was $ESD=-63.339+0.188{\times}EI$. EI was 1748.97 by calculating the $EI=565.431+3.481{\times}340{\mu}Gy$. In chest digital radiography, the ESD can be easily predicted by the DICOM header information.