• Journal of Korean Home Economics Education Association
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• v.29 no.2
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• pp.41-52
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• 2017

The purpose of this study was to identify the factors related to allergic diseases based on the health behavior of the youth in multicultural families according to the data from Tenth Korea Youth Risk Behavior Web-Based Survey 2014 (Centers for Disease Control & Prevention). The subjects from 712 multicultural adolescents were analyzed by the SPSS program. For the characteristics of health behavior of the multicultural youth, 267 students (37.5%) have experienced drinking alcohol, 164 students (23.0%) have experienced smoking, and 35 students (4.9%) have experienced taking drugs. Also, 198 students (27.8%) were depressed, 259 students (36.3%) are suffering from stress, and 286 students (40.2%) failed to fully relieve fatigue. In addition, 497 students (69.8%) consider themselves as healthy, 449 students (63.1%) consider themselves as happy, and 251 students (35.3%) consider themselves as overweight. Among the allergic disease of the multicultural youth, 46 middle school students (6.5%) and 35 high school students (4.9%) have asthma, 95 middle school students (13.3%) and 87 high school students (12.2%) have allergic rhinitis, and 67 middle school students (9.4%) and 53 high school students (7.4%) have atopic dermatitis. 47 male students (6.6%) and 34 female students (4.8%) have asthma, 81 male students (11.4%) and 101 female students (14.1%) have allergic rhinitis, and 53 male students (7.4%) and 67 female students (9.4%) have atopic dermatitis. Among the multicultural youth, 81 students (11.4%) have asthma, 182 students (25.5%) have allergic rhinitis, and 120 students (16.8%) have atopic dermatitis. For the allergic diseases from the health behavior of the multicultural youth, depression (p<0.001), alcohol experience (p<0.05), drug experience (p<0.05), health recognition (p<0.05), happiness recognition (p<0.05), and body type recognition (p<0.05) had a statistically significant relationship with asthma. Fatigue recovery recognition (p<0.001), health recognition (p<0.001) and stress recognition (p<0.05) had a statistically significant relationship with allergic rhinitis. Body type recognition (p<0.01), depression (p<0.05), fatigue recovery recognition (p<0.05), health recognition (p<0.05), and happiness recognition (p<0.05) had a statistically significant relationship with atopic dermatitis. Such results show that schools and society need to educate the multicultural youth about health, happiness, and body type recognition which are big factors of allergic diseases. Schools and society also need to be more systematic and continuous in order to help multicultural youth to be have correct recognition of depression, stress and fatigue recovery.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.1-19
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• 2019

Artificial intelligence (AI) is one of the main driving forces leading the Fourth Industrial Revolution. The technologies associated with AI have already shown superior abilities that are equal to or better than people in many fields including image and speech recognition. Particularly, many efforts have been actively given to identify the current technology trends and analyze development directions of it, because AI technologies can be utilized in a wide range of fields including medical, financial, manufacturing, service, and education fields. Major platforms that can develop complex AI algorithms for learning, reasoning, and recognition have been open to the public as open source projects. As a result, technologies and services that utilize them have increased rapidly. It has been confirmed as one of the major reasons for the fast development of AI technologies. Additionally, the spread of the technology is greatly in debt to open source software, developed by major global companies, supporting natural language recognition, speech recognition, and image recognition. Therefore, this study aimed to identify the practical trend of AI technology development by analyzing OSS projects associated with AI, which have been developed by the online collaboration of many parties. This study searched and collected a list of major projects related to AI, which were generated from 2000 to July 2018 on Github. This study confirmed the development trends of major technologies in detail by applying text mining technique targeting topic information, which indicates the characteristics of the collected projects and technical fields. The results of the analysis showed that the number of software development projects by year was less than 100 projects per year until 2013. However, it increased to 229 projects in 2014 and 597 projects in 2015. Particularly, the number of open source projects related to AI increased rapidly in 2016 (2,559 OSS projects). It was confirmed that the number of projects initiated in 2017 was 14,213, which is almost four-folds of the number of total projects generated from 2009 to 2016 (3,555 projects). The number of projects initiated from Jan to Jul 2018 was 8,737. The development trend of AI-related technologies was evaluated by dividing the study period into three phases. The appearance frequency of topics indicate the technology trends of AI-related OSS projects. The results showed that the natural language processing technology has continued to be at the top in all years. It implied that OSS had been developed continuously. Until 2015, Python, C ++, and Java, programming languages, were listed as the top ten frequently appeared topics. However, after 2016, programming languages other than Python disappeared from the top ten topics. Instead of them, platforms supporting the development of AI algorithms, such as TensorFlow and Keras, are showing high appearance frequency. Additionally, reinforcement learning algorithms and convolutional neural networks, which have been used in various fields, were frequently appeared topics. The results of topic network analysis showed that the most important topics of degree centrality were similar to those of appearance frequency. The main difference was that visualization and medical imaging topics were found at the top of the list, although they were not in the top of the list from 2009 to 2012. The results indicated that OSS was developed in the medical field in order to utilize the AI technology. Moreover, although the computer vision was in the top 10 of the appearance frequency list from 2013 to 2015, they were not in the top 10 of the degree centrality. The topics at the top of the degree centrality list were similar to those at the top of the appearance frequency list. It was found that the ranks of the composite neural network and reinforcement learning were changed slightly. The trend of technology development was examined using the appearance frequency of topics and degree centrality. The results showed that machine learning revealed the highest frequency and the highest degree centrality in all years. Moreover, it is noteworthy that, although the deep learning topic showed a low frequency and a low degree centrality between 2009 and 2012, their ranks abruptly increased between 2013 and 2015. It was confirmed that in recent years both technologies had high appearance frequency and degree centrality. TensorFlow first appeared during the phase of 2013-2015, and the appearance frequency and degree centrality of it soared between 2016 and 2018 to be at the top of the lists after deep learning, python. Computer vision and reinforcement learning did not show an abrupt increase or decrease, and they had relatively low appearance frequency and degree centrality compared with the above-mentioned topics. Based on these analysis results, it is possible to identify the fields in which AI technologies are actively developed. The results of this study can be used as a baseline dataset for more empirical analysis on future technology trends that can be converged.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.117-127
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• 2012

Due to the recent expansion of the Web 2.0 -based services, along with the widespread of smartphones, online social network services are being popularized among users. Online social network services are the online community services which enable users to communicate each other, share information and expand human relationships. In the social network services, each relation between users is represented by a graph consisting of nodes and links. As the users of online social network services are increasing rapidly, the SNS are actively utilized in enterprise marketing, analysis of social phenomenon and so on. Social Network Analysis (SNA) is the systematic way to analyze social relationships among the members of the social network using the network theory. In general social network theory consists of nodes and arcs, and it is often depicted in a social network diagram. In a social network diagram, nodes represent individual actors within the network and arcs represent relationships between the nodes. With SNA, we can measure relationships among the people such as degree of intimacy, intensity of connection and classification of the groups. Ever since Social Networking Services (SNS) have drawn increasing attention from millions of users, numerous researches have made to analyze their user relationships and messages. There are typical representative SNA methods: degree centrality, betweenness centrality and closeness centrality. In the degree of centrality analysis, the shortest path between nodes is not considered. However, it is used as a crucial factor in betweenness centrality, closeness centrality and other SNA methods. In previous researches in SNA, the computation time was not too expensive since the size of social network was small. Unfortunately, most SNA methods require significant time to process relevant data, and it makes difficult to apply the ever increasing SNS data in social network studies. For instance, if the number of nodes in online social network is n, the maximum number of link in social network is n(n-1)/2. It means that it is too expensive to analyze the social network, for example, if the number of nodes is 10,000 the number of links is 49,995,000. Therefore, we propose a heuristic-based method for finding the shortest path among users in the SNS user graph. Through the shortest path finding method, we will show how efficient our proposed approach may be by conducting betweenness centrality analysis and closeness centrality analysis, both of which are widely used in social network studies. Moreover, we devised an enhanced method with addition of best-first-search method and preprocessing step for the reduction of computation time and rapid search of the shortest paths in a huge size of online social network. Best-first-search method finds the shortest path heuristically, which generalizes human experiences. As large number of links is shared by only a few nodes in online social networks, most nods have relatively few connections. As a result, a node with multiple connections functions as a hub node. When searching for a particular node, looking for users with numerous links instead of searching all users indiscriminately has a better chance of finding the desired node more quickly. In this paper, we employ the degree of user node vn as heuristic evaluation function in a graph G = (N, E), where N is a set of vertices, and E is a set of links between two different nodes. As the heuristic evaluation function is used, the worst case could happen when the target node is situated in the bottom of skewed tree. In order to remove such a target node, the preprocessing step is conducted. Next, we find the shortest path between two nodes in social network efficiently and then analyze the social network. For the verification of the proposed method, we crawled 160,000 people from online and then constructed social network. Then we compared with previous methods, which are best-first-search and breath-first-search, in time for searching and analyzing. The suggested method takes 240 seconds to search nodes where breath-first-search based method takes 1,781 seconds (7.4 times faster). Moreover, for social network analysis, the suggested method is 6.8 times and 1.8 times faster than betweenness centrality analysis and closeness centrality analysis, respectively. The proposed method in this paper shows the possibility to analyze a large size of social network with the better performance in time. As a result, our method would improve the efficiency of social network analysis, making it particularly useful in studying social trends or phenomena.

• Journal of agricultural medicine and community health
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• v.20 no.1
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• pp.1-13
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• 1995

Based on the questionnaires sent to 270 nurses of public health centers in kyungnam during the period of March 19 to April 11 in 1992, this study was written for the of finding out the grade of satisfaction, obstacles in carrying out duties concerned with nursing services and the change of nurses role needed according to the change of the local public health administration. The first-ranking tasks carried by nurses of public health center are believed to have been family planning activities before the 1970's, nursing services during the 1970's, mother-child health activities during the 1980's, and nursing services during the period of 1990 to 1992. As far as the priority order of all the family planning activities is concerned, the counseling of the insertion of intrauterine contraceptive device, the use of oral pill or the distribution of condom was placed emphasis on before 1970, and publicity activities of family planning after that time. The first priority order of mother-child health activities has been put on the registration of pregnant women since 1970, with prenatal examination and vaccination ranking next to it. The priority order for activities against tuberculosis was laid on finding out and registration of new T.B. patients every year, with patients' control, and medication or injection ranking next to it. As for the priority order of nursing services, traveling medical examination and treatment ranked the first-stressed activity before 1970, with medication and injection ranking next to it. The first priority order management activity of communicable diseases was put on vaccination before 1970, with medication and injection. ranking next. And consultation and education ranked second to it during 1990 to 1992. As for the health services of the aged, traveling examination and treatment ranked the order, with the assistance of medical examination ranking next to it. As far as troubles and obstacles shown in case of family planning, the rate of residents' lack understanding was 28.8%, that of lacking budget 13.6%, and the imperfection of public health administration system 11.9%. In the case of tuberculosis control, residents' lacking understanding was 32.5%, the deficiency of public health administration system 18.2%, over-duty(shortage of hands) 15.6%, and the insufficiency skill and know-how 13.0%. In the case of nursing services, the deficiency of public health administration system was 18.2%, each over-duty(the shortage of hands) and the shortage of facilities and equipment 15.6% respective, and residents' lacking understanding 13.0%. The rate of dissatisfaction with the chance or possibility of promotion for his or her career or capability was shown to be 49.2%, and 65.9% of the health nurses expressed their complaints of the deficiency of the chance of the promotion to a professional or expert. when the public health nurses were asked in the questionably whether they were satisfied or not with current state of equipment and facilities needed for public health service, 49.6% of them answered in the negative. The grade of the satisfaction with the current individual position was shown to be low as much as the status of his or her position was now. 37.6% of those asked in the research answered to have the readiness to switch jobs for the reasons of dissatisfaction and so on with lacking promotion chance as well as bad working condition. Significant correlation between the grade of job satisfaction and the current status of the po as found to be in this research, which showed that the lower the status of position was, the lower the grade of job satisfaction was. But little correlation between the grade of job satisfaction and his or her schooling and career was found. In order to carry out primary health care successfully, it can be said that more education and publicity activities to make public health nurses and residents see it in a new light are requested. In addition to it, it is suggested that the improvement of promotion system for public health nurses and the enlargement of job province should also be taken in consideration of the high dissatisfaction with and complaints of the chance of promotion and the system of position. In order words, it is important that considerations for system improvement enough to make nursing services pleasant and satisfactory should be taken into.