• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.5
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• pp.53-63
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• 2019

To provide a hand gesture interface through deep learning in mobile environments, research on the light-weighting of networks is essential for high recognition rates while at the same time preventing degradation of execution speed. This paper proposes a method of real-time recognition of written characters in the air using a finger on mobile devices through the light-weighting of deep-learning model. Based on the SSD (Single Shot Detector), which is an object detection model that utilizes MobileNet as a feature extractor, it detects index finger and generates a result text image by following fingertip path. Then, the image is sent to the server to recognize the characters based on the learned OCR model. To verify our method, 12 users tested 1,000 words using a GALAXY S10+ and recognized their finger with an average accuracy of 88.6%, indicating that recognized text was printed within 124 ms and could be used in real-time. Results of this research can be used to send simple text messages, memos, and air signatures using a finger in mobile environments.

• Journal of the Korea Fashion and Costume Design Association
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• v.23 no.2
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• pp.17-28
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• 2021

The baby-tech industry, which combines IT with existing parenting product, is attracting increasing amounts of attention. Consequently various types of baby products incorporating functionality and design are being launched. In recent years, particularly as the market segments increases for babywearing products, parenting products that account for the child's comfort and parents' convenience are required. Therefore, this study examines the characteristics and consumer perception of babywear products, which are important for the emotional stability, development, and rearing of children. The study utilizes text mining and a network analysis by collecting unstructured text data. An examination of the network, based on the frequency of keywords for each babywear product and the degree of the connection to the centering index, revealed that consumers value convenience and price when purchasing products. The consumer perception and consideration factors that appear individually according to the product were also identified. In addition, studying body parts with high TF-IDF values revealed a difference in the body parts considered by consumers for each product. Lastly, through the visualization data based on the keywords that appeared in public, commonly appearing keywords, and those that appeared individually were examined. Through SNS, product characteristics as well as a new parenting culture that shared child-rearing routines were confirmed. This study suggests planning and marketing directions for the development of babywear products that meet consumer needs.

• Korea Trade Review
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• v.45 no.5
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• pp.37-53
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• 2020

This study aims to provide the implications of research development by comparing domestic and international studies conducted on the subject of FTA. To this end, among the papers written during the period from 2000 to July 23, 2020, papers whose title is searched by FTA (Free Trade Agreement) were selected as research data. In the case of domestic research, 1,944 searches from the Korean Citation Index (KCI) and 970 from the Web of Science and SCOPUS were selected for international research, and the research trend was analyzed through keywords and abstracts. Frequency analysis and word embedding (Word2vec) were used to analyze the data and visualized using t-SNE and Scattertext. The results of the analysis are as follows. First, in the top 30 keywords of domestic and international research, 16 out of 30 were found to be the same. In domestic research, many studies have been conducted to analyze the outcomes or expected effects of countries that have concluded or discussed FTAs with Korea, on the other hand there are diverse range of study subjects in international research. Second, in the word embedding analysis, t-SNE was used to visually represent the research connection of the top 60 keywords. Finally, Scattertext was used to visually indicate which keywords were frequently used in studies from 2000 to 2010, and from 2011 to 2020. This study is the first to draw implications for academic development through abstract and keyword analysis by applying various text mining approaches to the FTA related research papers. Further in-depth research is needed, including collecting a variety of FTA related text data, comparing and analyzing FTA studies in different countries.

• Journal of Korean Society of Archives and Records Management
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• v.24 no.1
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• pp.89-109
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• 2024

The study analyzed the research trends of domestic and international record information services from 2003 to 2022. A total of 136 academic papers registered in the Korea Citation Index (KCI) and 74 from the Library, Information Science & Technology Abstracts (LISTA) were examined by quantitative and qualitative content analysis to understand the research status of 20 years from various angles, such as publication year, research type, researcher type, subject, and purpose. Frequency analysis, co-occurrence frequency analysis, centrality analysis, and topic modeling were performed by applying text mining techniques. Results showed that domestic papers demonstrated a research flow focused on specific institutions or records, and user-centered satisfaction surveys and content-centered studies were conducted. Moreover, foreign papers confirmed various evaluation-oriented and information provision studies, such as data, resources, and collections, along with the research trend focusing on the relationship between archivists and users. The management of information resources was identified as a common topic in both domestic and foreign papers, but it is possible to identify that domestic research focuses on maintaining the quality of domestic information resources, while foreign research focuses on the storage and retrieval of information.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.14
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• pp.6033-6038
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• 2015

Background: Experience of lung cancer includes negative impacts on both physical and psychological health. Pain is one of the negative experiences of lung cancer. Cognitive behavioral therapy techniques are often recommended as treatments for lung cancer pain. The objective of this review was to synthesize the evidence on the effectiveness of cognitive behavioral therapy techniques in treating lung cancer pain. This review considered studies that included lung cancer patients who were required to 1) be at least 18 years old; 2) speak and read English or Thai; 3) have a life expectancy of at least two months; 4) experience daily cancer pain requiring an opioid medication; 5) have a positive response to opioid medication; 6) have "average or usual" pain between 4 and 7 on a scale of 0-10 for the day before the clinic visit or for a typical day; and 7) able to participate in a pain evaluation and treatment program. This review considered studies to examine interventions for use in treatment of pain in lung cancer patients, including: biofeedback, cognitive/attentional distraction, imagery, hypnosis, and meditation. Any randomized controlled trials (RCTs) that examined cognitive behavioral therapy techniques for pain specifically in lung cancer patients were included. In the absence of RCTs, quasi-experimental designs were reviewed for possible conclusion in a narrative summary. Outcome measures were pain intensity before and after cognitive behavioural therapy techniques. The search strategy aimed to find both published and unpublished literature. A three-step search was utilised by using identified keywords and text term. An initial limited search of MEDLINE and CINAHL was undertaken followed by analysis of the text words contained in the title and abstract, and of the index terms used to describe the article. A second search using all the identified keywords and index terms was then undertaken across all included databases. Thirdly, the reference list of all identified reports and articles were searched for additional studies. Searches were conducted during January 1991- March 2014 limited to English and Thai languages with no date restriction. Materials and Methods: All studies that met the inclusion criteria were assessed for methodological quality by three reviewers using a standardized critical appraisal tool from the Joanna Briggs Institute (JBI). Three reviewers extracted data independently, using a standardized data extraction tool from the Joanna Briggs Institute (JBI). Ideally for quantitative data meta-analysis was to be conducted where all results were subject to double data entry. Odds ratios (for categorical data) and weighted mean differences (for continuous data) and their 95% confidence intervals were to be calculated for analysis and heterogeneity was to be assessed using the standard Chi-square. Where statistical pooling was not possible the finding were be presented in narrative form. Results: There were no studies located that met the inclusion requirements of this review. There were also no text and opinion pieces that were specific to cognitive behavioral therapy techniques pain and lung cancer patients.Conclusions: There is currently no evidence available to determine the effectiveness of cognitive behavioural therapy techniques for pain in lung cancer patients.

• The Korean Journal of Applied Statistics
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• v.33 no.5
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• pp.639-653
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• 2020

Baker et al. (Quarterly Journal of Economics, 134, 1593-1636, 2016) developed an Economic Policy Uncertainty (EPU) index for South Korea in the same way as the U.S. EPU Index. However, the South Korean EPU index of Baker et al. (2016) has limitations as it did not fully reflect South Korean situation in terms of keyword selection and the selection of newspapers. We develop monthly South Korean economic policy uncertainty indexes with different keywords and news media. Various analyses have been conducted in order to examine the usefulness of the newly compiled indexes.

• Journal of KIISE:Databases
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• v.36 no.1
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• pp.50-62
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• 2009

In wireless and mobile environments, data broadcasting is recognized as an effective way for data dissemination due to its benefits to bandwidth efficiency, energy-efficiency, and scalability. In this paper, we address the problem of delayed query processing raised by tree-based index structures in wireless broadcast environments, which increases the access time of the mobile clients. We propose a novel distributed index structure and a clustering strategy for streaming XML data which enable energy and latency-efficient broadcast of XML data. We first define the DIX node structure to implement a fully distributed index structure which contains tag name, attributes, and text content of an element as well as its corresponding indices. By exploiting the index information in the DIX node stream, a mobile client can access the wireless stream in a shorter latency. We also suggest a method of clustering DIX nodes in the stream, which can further enhance the performance of query processing over the stream in the mobile clients. Through extensive performance experiments, we demonstrate that our approach is effective for wireless broadcasting of XML data and outperforms the previous methods.

• Journal of the Korean Society of Safety
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• v.38 no.3
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• pp.69-76
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• 2023

The purpose of the rules on the Occupational Safety and Health Standards (hereafter safety and health rules) is to regulate the safety and health measures stipulated in the Occupational Safety and Health Act and the specific instructions necessary for their implementation. However, the safety and health rules are extensive and complexly connected, making navigation difficult for users. In order for users to readily access safety and health rules, this study analyzed the frequency, distribution, and significance of terms included in the overall rules. First, the term distribution index was created based on the frequency and distribution of words extracted through text mining. The term distribution index derives from whether a word appears only in a specific chapter or across all rules. This allows users to effectively explore terms to be followed in a specific working environment and terms to be complied with in the overall working environment. Next, the related words of the previously derived terms were visualized through t-SNE and the Word2Vec algorithm. This can help prioritize the things that need to be managed first, focusing on key terms without checking the overall rules. Moreover, this study can help users explore safety and health rules by allowing them to understand the distribution of words and visualize related terms.

• Journal of Korea Society of Industrial Information Systems
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• v.26 no.6
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• pp.119-133
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• 2021

Research has been conducted in many fields to identify research trends using text mining, but in the field of emotional labor, no research has been conducted using text mining to identify research trends. This study uses text mining to deeply analyze 1,465 papers at the Korea Citation Index (KCI) from 2004 to 2019 containing the subject word 'emotional labor' to understand the trend of emotional labor researches. Topics were extracted by LDA analysis, and IDM analysis was performed to confirm the proportion and similarity of the topics. Through these methods, an integrated analysis of topics was conducted considering the usefulness of topics with high similarity. The research topics are divided into 11 categories in descending order: stress of emotional labor (12.2%), emotional labor and social support (12.0%), customer service workers' emotional labor (10.9%), emotional labor and resilience (10.2%), emotional labor strategy (9.2%), call center counselor's emotional labor (9.1%), results of emotional labor (9.0%), emotional labor and job exhaustion (7.9%), emotional intelligence (7.1%), preliminary care service workers' emotional labor (6.6%), emotional labor and organizational culture (5.9%). Through topic modeling and trend analysis, the research trend of emotional labor and the academic progress are analyzed to present the direction of emotional labor research, and it is expected that a practical strategy for emotional labor can be established.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.4
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• pp.549-566
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• 2022

Recently, artificial intelligence (AI) technology has progressed rapidly, and industries using this technology are significantly increasing. Further, analysis research using text mining, which is an application of artificial intelligence, is being actively developed in the field of social science research. About 125 laws, including joint laws, have been enacted under the Ministry of Oceans and Fisheries in various sectors including marine environment, fisheries, ships, fishing villages, ports, etc. Research on the laws under the Ministry of Oceans and Fisheries has been progressively conducted, and is steadily increasing quantitatively. In this study, the domestic research trends were analyzed through text mining, targeting the research papers related to laws of the Ministry of Oceans and Fisheries. As part of this research method, first, topic modeling which is a type of text mining was performed to identify potential topics. Second, co-occurrence network analysis was performed, focusing on the keywords in the research papers dealing with specific laws to derive the key themes covered. Finally, author network analysis was performed to explore social networks among authors. The results showed that key topics have been changed by period, and subjects were explored by targeting Ship Safety Law, Marine Environment Management Law, Fisheries Law, etc. Furthermore, in this study, core researchers were selected based on author network analysis, and the tendency for joint research performed by authors was identified. Through this study, changes in the topics for research related to the laws of the Ministry of Oceans and Fisheries were identified up to date, and it is expected that future research topics will be further diversified, and there will be growth of quantitative and qualitative research in the field of oceans and fisheries.