• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.6
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• pp.8-12
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• 2017

This paper presents the mobile phone case for self-power generation and recharge for emergency calls or text messages at the discharge of a battery. If the user shakes his smart phone case, the interaction of electromagnetic coil and permanent magnet in an electric generator produces electric energy, which charges the lithium-ion battery. This enables the user to give a few calls or text messages. In addition, the vibration energy from humans walking at a frequency of 2 ~ 3Hz charges the battery. The electric generator was simulated using MAXWELL, a commercial electromagnetic analysis program, to analyze the electric power generation. Finally a prototype of the mobile phone case for self-power generation was built based on the analysis and its performance was verified.

• Women's Health Nursing
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• v.26 no.3
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• pp.205-212
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• 2020

Purpose: This study aimed to identify the components of preterm birth (PTB) through women's personal narratives and to visualize clinical symptom expressions (CSEs). Methods: The participants were 11 women who gave birth before 37 weeks of gestational age. Personal narratives were collected by interactive unstructured storytelling via individual interviews, from August 8 to December 4, 2019 after receiving approval of the Institutional Review Board. The textual data were converted to PDF and analyzed using the MAXQDA program (VERBI Software). Results: The participants' mean age was 34.6 (±2.98) years, and five participants had a spontaneous vaginal birth. The following nine components of PTB were identified: obstetric condition, emotional condition, physical condition, medical condition, hospital environment, life-related stress, pregnancy-related stress, spousal support, and informational support. The top three codes were preterm labor, personal characteristics, and premature rupture of membrane, and the codes found for more than half of the participants were short cervix, fear of PTB, concern about fetal well-being, sleep difficulty, insufficient spousal and informational support, and physical difficulties. The top six CSEs were stress, hydramnios, false labor, concern about fetal wellbeing, true labor pain, and uterine contraction. "Stress" was ranked first in terms of frequency and "uterine contraction" had individual attributes. Conclusion: The text network analysis of narratives from women who gave birth preterm yielded nine PTB components and six CSEs. These nine components should be included for developing a reliable and valid scale for PTB risk and stress. The CSEs can be applied for assessing preterm labor, as well as considered as strategies for students in women's health nursing practicum.

• Journal of the Korea Convergence Society
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• v.6 no.5
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• pp.131-142
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• 2015

The aim of study is to present a better teaching strategy to reduce writing errors of Chinese learners of Korean language after finding out what reasons of errors were after analyzing of their writing errors in Korean language. Analyzed contents were writhing in Korean language of 'how I think Korean', 'about Chinese and Korean culture', 'friends' and analyzed what errors were occurred. The vocabulary errors frequencies were counted by the criteria which was set by a researcher. The results were as follows. The frequency of substitute error was the most and were followed by spelling error, wrong type error, omission error and adding error. It is suggested when we teach Korean Language to Chinese learners and develop text for them, the vocabularies should be presented with examples of how to be used in context instead of presenting only vocabulary on the text. It would be a better way to reduce writing errors of Chinese learners of Korean language.

• Research in Community and Public Health Nursing
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• v.29 no.2
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• pp.244-256
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• 2018

Purpose: This study tried to understand discourses of life-sustaining treatments in general daily and healthcare newspapers. Methods: A text-network analysis was conducted using the NetMiner program. Firstly, 572 articles from 11 daily newspapers and 258 articles from 8 healthcare newspapers were collected, which were published from August 2013 to October 2016. Secondly, keywords (semantic morphemes) were extracted from the articles and rearranged by removing stop-words, refining similar words, excluding non-relevant words, and defining meaningful phrases. Finally, co-occurrence matrices of the keywords with a frequency of 30 times or higher were developed and statistical measures-indices of degree and betweenness centrality, ego-networks, and clustering-were obtained. Results: In the general daily and healthcare newspapers, the top eight core keywords were common: "patients," "death," "LST (life-sustaining treatments)," "hospice palliative care," "hospitals," "family," "opinion," and "withdrawal." There were also common subtopics shared by the general daily and healthcare newspapers: withdrawal of LST, hospice palliative care, National Bioethics Review Committee, and self-determination and proxy decision of patients and family. Additionally, the general daily newspapers included diverse social interest or events like well-dying, euthanasia, and the death of farmer Baek Nam-ki, whereas the healthcare newspapers discussed problems of the relevant laws, and insufficient infrastructure and low reimbursement for hospice-palliative care. Conclusion: The discourse that withdrawal of futile LST should be allowed according to the patient's will was consistent in the newspapers. Given that newspaper articles influence knowledge and attitudes of the public, RNs are recommended to participate actively in public communication on LST.

• Journal of Fashion Business
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• v.25 no.3
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• pp.90-107
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• 2021

This study concludes that communication based on interaction between broadcasting hosts and consumers is differently characterized by fashion live commerce types. Subcategories of the types of fashion live commerce were created and used in the analyses of domestic consumer awareness. Three subcategories were created: The department store type, Designer brand type, and Influencer host type. Comments representing consumers' awareness that appear immediately during real-time broadcasting were collected and used for the analyses. The frequency and TF-IDF-based top keywords were selected to analyze the semantic network and CONCOR, and the top keywords were analyzed by deriving the values of degree of centrality. The analysis identified that a group of product attributes and a group of live commerce offered value were common between the three types. As for the group characteristics classified by type, for the department store types, brand attributes, benefits, and values from pursuing the products were identified. For designer brand types, a group of viewers' responses and inquiries were identified. It is interpreted that the satisfaction value gained from hosts with product expertise has been clustered. Influencer host types have affirmed a group of external product values. A close relationship is formed and it is thought to have led a group of values to trust the external image of the product. This study carries significance in analyzing real-time comment data from consumers using fashion live commerce to empirically reveal the characteristics of each type.

• International journal of advanced smart convergence
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• v.11 no.4
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• pp.206-215
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• 2022

For a long time, traditional culture has been regarded as one of the sources of the inspiration, method and language of Chinese writing. In this article, we studied the medium- and long-term impact of a traditional Chinese culture seminar attended by college students on the output of creative writing. The seminar included traditional Chinese philosophy, history, literature, art, etc. It spanned three years (22 months) and held lectures lasting for approximately two hours once a week. The subjects of the prospective cohort study included 130 first-year college students who participated in the seminar and 130 controls. From September 2016 to June 2018, 72 lectures were held. We measured the creative writing output from the first lecture (September 2016) to December 2021 (64 months in total), including novels, essays, poems, and plays. Two indicators, the total number of words (TNW) and the quality of yield (QY), were evaluated by a 15-member panel. Although the TNW and QY of the participants and their controls were similar before the seminar, we found that the participants have higher TNW and QY than the controls after participating in the seminar. The difference in TNW became significant after month 51 (p<0.05), and the difference in QY became significant after month 46 (p<0.05). After these dates, the differences stabilized. In addition, text analysis indicates that by month 64, traditional cultural elements in the works of the participating group had a higher frequency (p<0.001). The research shows that the traditional culture seminar not only enhanced the yield of college students' creative writing but also improved the quality of their work. The traditional cultural elements enriched the works of the seminar participants.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.2
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• pp.61-73
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• 2021

This study aimed to identify the landscape perception and landscape characteristics of users by utilizing SNS data generated by their experiences. Therefore, how to recognize the main places and scenery appearing on the island, and what are the characteristics of the main scenery were analyzed using online text data and photo data. Text data are text mining and network structural analysis, while photographic data are landscape identification models and color analysis. As a result of the study, First, as a result of frequency analysis of Bakji·Banwol-do topics, we were able to derive keywords for local landscapes such as 'Purple Bridge', 'Doori Village', and location, behavior, and landscape images by analyzing them simultaneously. Second, the network structure analysis showed that the connection between key and undrawn keywords could be more specifically analyzed, indicating that creating landscapes using colors is affecting regional activation. Third, after analyzing the landscape identification model, it was found that artificial elements would be excluded to create preferred landscapes using the main targets of "Purple Bridge" and "Doori Village", and that it would be effective to set a view point of the sea and sky. Fourth, Bakji·Banwol-do were the first islands to be created under the theme of color, and the colors used in artificial facilities were similar to the surrounding environment, and were harmonized with contrasting lighting and saturation values. This study used online data uploaded directly by visitors in the landscape field to identify users' perceptions and objects of the landscape. Furthermore, the use of both text and photographic data to identify landscape recognition and characteristics is significant in that they can specifically identify which landscape and resources they prefer and perceive. In addition, the use of quantitative big data analysis and qualitative landscape identification models in identifying visitors' perceptions of local landscapes will help them understand the landscape more specifically through discussions based on results.

• Journal of Internet of Things and Convergence
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• v.9 no.2
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• pp.19-31
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• 2023

The importance of barrier free is being highlighted worldwide. This study attempted to identify barrier-free research trends using text mining. Through this, it was intended to help with research and policies to create a barrier free environment. The analysis data is 227 papers published in domestic academic journals from 1996 when barrier free research began to 2022. The researcher converted the title, keywords, and abstract of an academic thesis into text, and then analyzed the pattern of the thesis and the meaning of the data. The summary of the research results is as follows. First, barrier-free research began to increase after 2009, with an annual average of 17.1 papers being published. This is related to the implementation guidelines for the barrier-free certification system that took effect on July 15, 2008. Second, results of barrier-free text mining i) As a result of word frequency analysis of top keywords, important keywords such as barrier free, disabled, design, universal design, access, elderly, certification, improvement, evaluation, and space, facility, and environment were searched. ii) As a result of TD-IDF analysis, the main keywords were universal design, design, certification, house, access, elderly, installation, disabled, park, evaluation, architecture, and space. iii) As a result of N-Ggam analysis, barrier free+certification, barrier free+design, barrier free+barrier free, elderly+disabled, disabled+elderly, disabled+convenience facilities, the disabled+the elderly, society+the elderly, convenience facilities+installation, certification+evaluation index, physical+environment, life+quality, etc. appeared in a related language. Third, as a result of the CONCOR analysis, cluster 1 was barrier-free issues and challenges, cluster 2 was universal design and space utilization, cluster 3 was Improving Accessibility for the Disabled, and cluster 4 was barrier free certification and evaluation. Based on the analysis results, this study presented policy implications for vitalizing barrier-free research and establishing a desirable barrier free environment.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.10
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• pp.363-372
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• 2022

Since the recent COVID-19 Pandemic, the ransomware fandom has intensified along with the expansion of remote work. Currently, anti-virus vaccine companies are trying to respond to ransomware, but traditional file signature-based static analysis can be neutralized in the face of diversification, obfuscation, variants, or the emergence of new ransomware. Various studies are being conducted for such ransomware detection, and detection studies using signature-based static analysis and behavior-based dynamic analysis can be seen as the main research type at present. In this paper, the frequency of ".text Section" Opcode and the Native API used in practice was extracted, and the association between feature information selected using K-means Clustering algorithm, Cosine Similarity, and Pearson correlation coefficient was analyzed. In addition, Through experiments to classify and detect worms among other malware types and Cerber-type ransomware, it was verified that the selected feature information was specialized in detecting specific ransomware (Cerber). As a result of combining the finally selected feature information through the above verification and applying it to machine learning and performing hyper parameter optimization, the detection rate was up to 93.3%.

• Journal of Life Science
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• v.33 no.8
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• pp.663-679
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• 2023

This review analyzes research trends related to new drug development using artificial intelligence from 2010 to 2022. This analysis organized the abstracts of 2,421 studies into a corpus, and words with high frequency and high connection centrality were extracted through preprocessing. The analysis revealed a similar word frequency trend between 2010 and 2019 to that between 2020 and 2022. In terms of the research method, many studies using machine learning were conducted from 2010 to 2020, and since 2021, research using deep learning has been increasing. Through these studies, we investigated the trends in research on artificial intelligence utilization by field and the strengths, problems, and challenges of related research. We found that since 2021, the application of artificial intelligence has been expanding, such as research using artificial intelligence for drug rearrangement, using computers to develop anticancer drugs, and applying artificial intelligence to clinical trials. This article briefly presents the prospects of new drug development research using artificial intelligence. If the reliability and safety of bio and medical data are ensured, and the development of the above artificial intelligence technology continues, it is judged that the direction of new drug development using artificial intelligence will proceed to personalized medicine and precision medicine, so we encourage efforts in that field.