• Nutrition Research and Practice
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• v.16 no.sup1
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• pp.21-36
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• 2022

BACKGROUND/OBJECTIVES: The long-term health impacts of dietary sugar have begun to be reported. The committee on the 2020 Dietary Reference Intakes for Koreans for sugar intended to update the scientific evidence on the association of added sugar intake with health outcomes, including mortality. This study evaluated the evidence on the association of dietary sugar with the all-cause and cardiovascular disease mortality from cohort studies. SUBJECTS/METHODS: The PubMed and ScienceDirect databases were searched until July 2021. The search terms were based on multiple combinations of keywords, such as added sugar, beverage, and mortality, included in the title or abstract. Two authors independently assessed the eligibility criteria of study selection and extracted the information from each selected article for this systematic review. RESULTS: The literature search identified 276 articles. Seventeen cohort studies met the inclusion criteria and were included in this systematic review. This study extracted information on the cohort and participants, dietary assessment methods, exposure and its comparison groups, health outcomes, and risk measures. Five articles reported added sugar intake, and 15 articles reported the food sources of the added sugar in the association with mortality. Increased mortality was observed in higher added sugar intake and a lower intake of less than 5% of energy, while higher discrepancies between gender, age groups, and countries were noted. In addition, nutritious sugary foods and beverages did not increase mortality. CONCLUSIONS: A 'U' or 'J' shaped relationship between the added sugar intake and mortality was estimated. The observed discrepancy indicated the need for more evidence to establish the dose-response relationship for Koreans.

• Journal of Korean Academy of Rural Health Nursing
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• v.18 no.2
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• pp.113-124
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• 2023

Purpose: The number of households vulnerable to isolation increases rapidly as social ties decrease, raising concerns about the associated increase in lonely deaths. This study aimed to identify issues related to lonely deaths by analyzing South Korean news articles; and to provide evidence for their use in preventing and managing lonely deaths via community nursing. Methods: This exploratory study analyzed the structure and trends of meaning of lonely deaths by identifying the association between keywords in news articles and lonely deaths. In this study, we searched for all news articles on lonely deaths, covering the period from January 1, 2010, to May 31, 2023. Data preprocessing and purification were conducted, followed by top-keyword extraction, keyword network analysis and topic modeling. The retrieved articles were analyzed using R and Python software. Results: Four main topics were identified: "discovering and responding to lonely death cases", "lonely deaths ending in lonely funerals", "supportive policies to prevent lonely deaths among of older adults", and "local government activities to prevent lonely deaths and support vulnerable populations." Conclusion: Based on these findings, it can be concluded that lonely death is a complex social phenomenon that can be prevented if society shows concern and care. Education related to lonely deaths should be included in nursing curricula for concrete action plans and professional development.

• Journal of Korean Physical Therapy Science
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• v.30 no.4
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• pp.92-110
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• 2023

Background: Digital therapeutics are software medical devices that provide evidence-based treatments to prevent, manage, and treat disease. Digital therapies have recently been shown to be effective in motivating children with cerebral palsy as a tool in neuropsychological therapy. Digital therapies improve postural control, balance and gait in children with cerebral palsy. Therefore, this study aims to investigate the effects of digital therapies on balance and gait in children with cerebral palsy and to provide guidelines for prescribing digital therapies for children with cerebral palsy. Design: A Systematic Review Methods: This study searched for English-language articles published in medical journals from January 2000 to July 2023 using PubMed and MEDLINE based on the year of initiation of the digital therapy. The search terms used in the study were 'digital technology' OR 'digital therapeutic' OR 'mobile application' OR 'mobile health' OR 'virtual reality' OR 'game' AND 'cerebral palsy', 'balance' 'gait' as the main keywords. The final article was assigned an evidence level and a Physiotherapy Evidence Database (PEDro) score to assess the quality of clinical trials studies. Results: The digital therapies applied to improve balance and gait in children with cerebral palsy are game-based virtual reality training and the Nintendo Wii Fit program. Both digital therapy interventions had a significant effect on improving balance in children with cerebral palsy, and virtual reality training significantly improved balance and gait. However, there were no significant improvements in balance and gait within two weeks of treatment, regardless of the type of digital intervention. Conclusion: The study suggests that this data will be important in building the evidence base for the effectiveness of digital therapies on balance and gait in children with cerebral palsy and in advancing clinical protocols.

• Spatial Information Research
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• v.23 no.3
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• pp.35-44
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• 2015

Recently, the government aims to discover and provide services to citizens on the development strategy for activating the U-City. So, this study aims to offer a service discovery direction by analyzing the service issues and trends. The target is newspaper article about U-City Service from 2009 to 2014. Prepared 723 newspaper article for analysis. Next step is frequency analysis of keyword and used that result for Network analysis and measure of information. Network analysis can show result through "Degree Centrality", "Betweenness Centrality" and "Closeness Centrality". As a result, "Information", "IT", "Environment", "Technology", "Center" is higher than another. These 5 keywords are important factors for driving the U-City the past six years. Information measurement results, Already U-City were put an emphasis on building the infrastructure and able to identify a trend that provided the center of the public service. Those Service field are "Tour(2009)", "Crime prevention and Disaster Prevention(2010)", "Facility Management(2011)", "administration(2012)" and "Facility Management(2013, 2014)". Result of this study found implications what on citizen participation. So, services field on the existing infrastructure should be discovered and provided. Finally, this study can expected to be a reference in the local government planning for U-City.

• Journal of Society of Occupational Therapy for the Aged and Dementia
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• v.12 no.2
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• pp.67-74
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• 2018

Objective : The purpose of this study is to quantitatively analyze the role of occupational therapy in long - term care insurance for the elderly using text mining, one of the big data analysis techniques. Method : For the analysis of newspaper articles, "Long - Term Care Insurance for the Elderly + Occupational Therapy for the Elderly" was collected after the period from 2007 to 208. Naver, which has a high share of the domestic search engine, utilized the database of Naver News by utilizing Textom, a web crawling tool. After collecting the article title and original text of 510 news data from the collection of the elderly long term care insurance + occupational therapy search, we analyzed the article frequency and key words by year. Result : In terms of the frequency of articles published by year, the number of articles published in 2015 and 2017 was the highest with 70 articles (13.7%), and the top 10 terms of the key word analysis showed the highest frequency of 'dementia' (344) In terms of key words, dementia, treatment, hospital, health, service, rehabilitation, facilities, institution, grade, elderly, professional, salary, industrial complex and people are related. Conclusion : In this study, it is meaningful that the textual mining technique was used to more objectively confirm the social needs and the role of the occupational therapist for the dementia and rehabilitation in the related key keywords based on the media reporting trend of the elderly long - term care insurance for 11 years. Based on the results of this study, future research should expand research field and period and supplement the research methodology through various analysis methods according to the year.

• Journal of Practical Engineering Education
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• v.15 no.1
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• pp.97-105
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• 2023

Recently, with the development of artificial intelligence technology, many technologies for user convenience are being developed. Among them, interest in autonomous vehicles is increasing day by day. Currently, many automobile companies are aiming to commercialize autonomous vehicles. In order to lay the foundation for the government's new and reasonable policy establishment to support commercialization, we tried to analyze changes and perceptions of public opinion through news article data. Therefore, in this paper, 35,891 news article data mentioning terms similar to 'autonomous vehicles' over the past three years were collected and network analyzed. As a result of the analysis, major keywords such as 'autonomous driving', 'AI', 'future', 'Hyundai Motor', 'autonomous driving vehicle', 'automobile', 'industrial', and 'electric vehicle' were derived. In addition, the autonomous vehicle industry is developing into a faster and more diverse platform and service industry by converging with various industries such as semiconductor companies and big tech companies as well as automobile companies and is paying attention to the convergence of industries. To continuously confirm changes and perceptions in public opinion, it is necessary to analyze perceptions through continuous analysis of SNS data or technology trends.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.57-71
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• 2013

Over a billion people in the world generate new news minute by minute. People forecasts some news but most news are from unexpected events such as natural disasters, accidents, crimes. People spend much time to watch a huge amount of news delivered from many media because they want to understand what is happening now, to predict what might happen in the near future, and to share and discuss on the news. People make better daily decisions through watching and obtaining useful information from news they saw. However, it is difficult that people choose news suitable to them and obtain useful information from the news because there are so many news media such as portal sites, broadcasters, and most news articles consist of gossipy news and breaking news. User interest changes over time and many people have no interest in outdated news. From this fact, applying users' recent interest to personalized news service is also required in news service. It means that personalized news service should dynamically manage user profiles. In this paper, a content-based news recommendation system is proposed to provide the personalized news service. For a personalized service, user's personal information is requisitely required. Social network service is used to extract user information for personalization service. The proposed system constructs dynamic user profile based on recent user information of Facebook, which is one of social network services. User information contains personal information, recent articles, and Facebook Page information. Facebook Pages are used for businesses, organizations and brands to share their contents and connect with people. Facebook users can add Facebook Page to specify their interest in the Page. The proposed system uses this Page information to create user profile, and to match user preferences to news topics. However, some Pages are not directly matched to news topic because Page deals with individual objects and do not provide topic information suitable to news. Freebase, which is a large collaborative database of well-known people, places, things, is used to match Page to news topic by using hierarchy information of its objects. By using recent Page information and articles of Facebook users, the proposed systems can own dynamic user profile. The generated user profile is used to measure user preferences on news. To generate news profile, news category predefined by news media is used and keywords of news articles are extracted after analysis of news contents including title, category, and scripts. TF-IDF technique, which reflects how important a word is to a document in a corpus, is used to identify keywords of each news article. For user profile and news profile, same format is used to efficiently measure similarity between user preferences and news. The proposed system calculates all similarity values between user profiles and news profiles. Existing methods of similarity calculation in vector space model do not cover synonym, hypernym and hyponym because they only handle given words in vector space model. The proposed system applies WordNet to similarity calculation to overcome the limitation. Top-N news articles, which have high similarity value for a target user, are recommended to the user. To evaluate the proposed news recommendation system, user profiles are generated using Facebook account with participants consent, and we implement a Web crawler to extract news information from PBS, which is non-profit public broadcasting television network in the United States, and construct news profiles. We compare the performance of the proposed method with that of benchmark algorithms. One is a traditional method based on TF-IDF. Another is 6Sub-Vectors method that divides the points to get keywords into six parts. Experimental results demonstrate that the proposed system provide useful news to users by applying user's social network information and WordNet functions, in terms of prediction error of recommended news.

• Journal of Environmental Policy
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• v.4 no.1
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• pp.39-67
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• 2005

In order to properly define the terms such as soil, soil contamination, soil contamination site and remediation, which are the key terms under the Soil Environment Conservation Act(SECA) in Korea, we analyzed the legal definitions of the similar key words in legislations of the developed western countries. The selected countries were the United States of America, the United Kingdom, the Netherlands, Germany, and Denmark. The legal definitions of these keywords were very much diversified due to different levels of soil contamination, as well as different industrial, social, and legal backgrounds in each country. However, fair suggestions for definitions of the key terms in SECA were derived from the comparative analyses of these countries. First and foremost, SECA should provide a definition of 'soil' which includes a concept of the natural soil layer produced from soil mineralization processes. Groundwater and sublayer of the groundwater would. be excluded in the boundary of the soil with regards to the Groundwater Act of Korea. Definition of 'soil contamination' of SECA should include a concept of risk assessment(soil contaminants, pathway, and receptors), purpose of land use, and the acquired limitation levels of soil contaminants. Soil contamination activity either industrial or anthropogenic in SECA article2-1, could be substituted for a concept of soil risk assessment. Definition of 'soil contamination site' could derive from amalgamating the concepts of i) soil contamination in conjunction with contaminants, ii) risk assessment, iii) a concept of land use, and iv) knowing limitation of contamination site designation. Definition of 'remediation of contaminated site' should include the objective, intention, action, methodology and limit of the remediation. These suggested definitions would increase the efficacy of soil environment conservation policies, which includes the survey of the potentially contaminated area, remediation, and removal of the site.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.575-583
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• 2021

This study aims to analyze Taekwondo trends according to news articles by year by applying topic modeling. In order to examine the Taekwondo trend through media reports, articles including news articles and Taekwondo specialized media articles were collected through Big Kinds of the Korea Press Foundation. The search period was divided into three sections: before 2000, 2001~2010, and 2011~2020. A total of 12,124 items were selected as research data. For topic analysis, pre-processing was performed, and topic analysis was performed using the LDA algorithm. In this case, python 3 was applied for all analysis. First, as a result of analyzing the topics of media articles by year, 'World' was the most common keyword before 2000. 'South and North Korea' was next common and 'Olympic' was the third commonest topic. From 2001 to 2010, 'World' was the most common topic, followed by 'Association' and 'World Taekwondo'. From 2011 to 2020, 'World', 'Demonstration', and 'Kukkiwon' was the most common topic in that order. Second, as a result of analyzing news articles before 2000 by topic modeling, topics were divided into two categories. Specifically, Topic 1 was selected as 'South-North Korea sports exchange' and Topic 2 was selected as 'Adoption of Olympic demonstration events'. Third, as a result of analyzing news articles from 2001 to 2010 by topic modeling, three topics were selected. Topic 1 was selected as 'Taekwondo Demonstration Performance and Corruption', Topic 2 was selected as 'Muju Taekwondo Park Creation', and Topic 3 was selected as 'World Taekwondo Festival'. Fourth, as a result of analyzing news articles from 2011 to 2020 by topic modeling, three topics were selected. Topic 1 was selected as 'Successful Hosting of the 2018 Pyeongchang Winter Olympics', Topic 2 was selected as 'North-South Korea Taekwondo Joint Demonstration Performance', and Topic 3 was selected as '2017 Muju World Taekwondo Championships'.

• Journal of the Korean Society for information Management
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• v.34 no.3
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• pp.109-124
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• 2017

Through a wide variety of disciplines, practices on data access and re-use have been increased recently. In fact, there has been an emerging phenomenon that researchers tend to use the data sets produced by other researchers and give scholarly credit as citation. With respect to this practice, in 2012, Thomson Reuters launched Data Citation Index (DCI). With the DCI, citation to research data published by researchers are collected and analyzed in a similar way for citation to journal articles. The purpose of this study is to identify the characteristics and intellectual structure of sociology field based on research data, which is one of actively data-citing fields. To accomplish this purpose, two data sets were collected and analyzed. First, from DCI, a total of 8,365 data were collected in the field of sociology. Second, a total of 12,132 data were collected from Web of Science with a topic search with 'Sociology'. As a result of the co-word analysis of author provided-keywords for both data sets, the intellectual structure of research data-based sociology was composed of two areas and 15 clusters and that of article-based sociology was composed with three areas and 17 clusters. More importantly, medical science area was found to be actively studied in research data-based sociology and public health and psychology are identified to be central areas from data citation.