• Journal of Korean Clinical Nursing Research
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• v.26 no.3
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• pp.365-373
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• 2020

Purpose: The purpose of this study was to evaluate the effect of preoperative warming to prevent hypothermia in surgery for patients undergoing total hip replacement arthroplasty under spinal anesthesia. Methods: A randomized experimental study was conducted. Data were collected at an S University hospital in Gyeonggido from December 3, 2019 to March 31, 2020. A random allocation program was used to randomize participants into intervention and control groups. A total of 90 participants were assigned to the study: 30 people were randomized to a pre-warming group using Bair Hugger forced-air warming blankets(Model 505) 30 minutes before surgery, 30 to a pre-warming group 15 minutes before surgery, or 30 to a control group. The findings from 88 participants were analyzed. For data analysis, χ2 test and ANOVA were used utilizing the SPSS 21.0 program. Results: The pre-warming group 30 minutes before surgery had significantly higher body temperature than the control group, from 30 minutes after inducing anesthesia to the end of anesthesia. Body temperature over anesthesia time showed significant differences among the three groups, but there were no statistically significant differences in interactions between time and groups. Conclusion: Warming patients' body for 30 minutes before surgery was effective in maintaining normal body temperature while preventing intraoperative hypothermia.

• The Journal of Bigdata
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• v.5 no.2
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• pp.97-110
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• 2020

The global pandemics occurred in 2020 had a great economic impact on the world, and the impact was especially greater on self-employed people who were heavily affected by the floating population and tourism industry. To solve this problem, each country implemented emergency disaster support policies, and it was difficult to select the criteria and scope. The following research carried out two results. First, after analyzing the impact of global pandemics on the local economy, an economical index was defined that could explain the impact intuitively. Second, we propose linear programming methods to provide optimal budget policy using defined indicators, which present economic shock indicators and optimal years that can be considered quickly and easily by the government. Finally, the limitations and implications of the proposed study model are introduced.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.2
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• pp.140-152
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• 2021

During the shift from gasoline vehicles to electric ones, auto parts manufacturing companies have realized the importance of improvement in the manufacturing process that does not require any layout changes nor extra investments, while maintaining their current production rate. Due to these reasons, for the auto part manufacturing company, I-company, this study has developed the simulation model of the PUSH system to conduct a process analysis in terms of production rate, WIP level, and logistics work's utilization rate. In addition, this study compares the PUSH system with other three manufacturing systems -KANBAN, DBR, and CONWIP- to compare the performance of these production systems, while satisfying the company's target production rate. With respect to lead-time, the simulation results show that the improvement of 77.90% for the KANBAN system, 40.39% for the CONWIP system, and 69.81% for the DBR system compared to the PUSH system. In addition, with respect to WIP level, the experimental results demonstrate that the improvement of 77.91% for the KANBAN system, 40.41% for the CONWIP system, and 69.82% for the DBR system compared to the PUSH system. Since the KANBAN system has the largest impacts on the reduction of the lead-time and WIP level compared to other production systems, this study recommends the KANBAN system as the proper manufacturing system of the target company. This study also shows that the proper size of moving units is four and the priority allocation of bottleneck process methods improves the target company's WIP and lead-time. Based on the results of this study, the adoption of the KANBAN system will significantly improve the production process of the target company in terms of lead-time and WIP level.

• Journal of Trauma and Injury
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• v.33 no.4
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• pp.248-255
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• 2020

Purpose: Trauma incidence and hospitalizations of trauma patients are generally believed to be affected by season and weather. The objective of this study was to explore possible associations of the hospitalization rate of trauma patients with weather and time variables at a single regional trauma center in South Korea. Methods: Trauma hospitalization data were obtained from a regional trauma center in South Korea from January 1, 2017 to December 31, 2019. In total, from 6,788 patients with trauma, data of 3,667 patients were analyzed, excluding those from outside the city where the trauma center was located. Hourly weather service data were obtained from the Korea Meteorological Administration. Results: The hospitalization rate showed positive correlations with temperature (r=0.635) and wind speed (r=0.501), but a negative correlation with humidity (r=-0.620). It showed no significant correlation (r=0.036) with precipitation. The hospitalization rate also showed significant correlations with time of day (p=0.033) and month (p=0.22). Conclusions: Weather and time affected the number of hospitalizations at a trauma center. The findings of this study could be used to determine care delivery, staffing, and resource allocation plans at trauma centers and emergency departments.

• Journal of Korean Academy of Nursing
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• v.51 no.4
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• pp.442-453
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• 2021

Purpose: This study was conducted to assess public awareness and policy challenges faced by practicing nurses. Methods: After collecting nurse-related news articles published before and after 'the Thanks to You Challenge' campaign (between December 31, 2019, and July 15, 2020), keywords were extracted via preprocessing. A three-step method keyword analysis, latent Dirichlet allocation topic modeling, and keyword network analysis was used to examine the text and the structure of the selected news articles. Results: Top 30 keywords with similar occurrences were collected before and after the campaign. The five dominant topics before the campaign were: pandemic, infection of medical staff, local transmission, medical resources, and return of overseas Koreans. After the campaign, the topics 'infection of medical staff' and 'return of overseas Koreans' disappeared, but 'the Thanks to You Challenge' emerged as a dominant topic. A keyword network analysis revealed that the word of nurse was linked with keywords like thanks and campaign, through the word of sacrifice. These words formed interrelated domains of 'the Thanks to You Challenge' topic. Conclusion: The findings of this study can provide useful information for understanding various issues and social perspectives on COVID-19 nursing. The major themes of news reports lagged behind the real problems faced by nurses in COVID-19 crisis. While the press tends to focus on heroism and whole society, issues and policies mutually beneficial to public and nursing need to be further explored and enhanced by nurses.

• The Journal of Information Systems
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• v.30 no.4
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• pp.277-301
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• 2021

Purpose The purpose of this study is to analyze the sentiment responses of the general public to non-face-to-face work using text mining methodology. As the number of non-face-to-face complaints is increasing over time, it is difficult to review and analyze in traditional methods such as surveys, and there is a limit to reflect real-time issues. Approach This study has proposed a method of the research model, first by collecting and cleansing the data related to non-face-to-face work among tweets posted on Twitter. Second, topics and keywords are extracted from tweets using LDA(Latent Dirichlet Allocation), a topic modeling technique, and changes for each section are analyzed through DTM(Dynamic Topic Modeling). Third, the complaints of non-face-to-face work are analyzed through the classification of positive and negative polarity in the COVID-19 section. Findings As a result of analyzing 1.54 million tweets related to non-face-to-face work, the number of IDs using non-face-to-face work-related words increased 7.2 times and the number of tweets increased 4.8 times after COVID-19. The top frequently used words related to non-face-to-face work appeared in the order of remote jobs, cybersecurity, technical jobs, productivity, and software. The words that have increased after the COVID-19 were concerned about lockdown and dismissal, and business transformation and also mentioned as to secure business continuity and virtual workplace. New Normal was newly mentioned as a new standard. Negative opinions found to be increased in the early stages of COVID-19 from 34% to 43%, and then stabilized again to 36% through non-face-to-face work sentiment analysis. The complaints were, policies such as strengthening cybersecurity, activating communication to improve work productivity, and diversifying work spaces.

• Journal of Creative Information Culture
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• v.6 no.1
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• pp.23-30
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• 2020

This study used the text mining method to analyze the research trend of the Journal of Creative Information Culture(JCIC) which is the journal of convergence. The existing research trend analysis method has a limitation in that the researcher's personality is reflected using the traditional content analysis method. In order to complement the limitations of existing research trend analysis, this study used topic modeling. The English abstract of the paper was analyzed from 2015 to 2019 of the JCIC. As a result, the word that appeared most in the JCIC was "education," and eight research topics were drawn. The derived subjects were analyzed by educational subject, educational evaluation, learner's competence, software education and maker culture, information education and computer education, future education, creativity, teaching and learning methods. This study is meaningful in that it analyzes the research trend of the JCIC using text mining.

• Journal of Korea Trade
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• v.23 no.7
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• pp.34-44
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• 2019

Purpose - The purpose of this study is to present what the port of Pyeongtaek, the hub of Korean trade with China, should improve in the current situation, wherein the e-commerce trade volume between Korea and China is increasing due to the development of online technology. Design/methodology - In this study, through prior research and expert interviews on e-commerce and port activation between borders, we derived the main improvement factors for 1) Administration and Systems, 2) Facilities, 3) Transport, and 4) Manpower, and selected 12 detailed variables for the major improvement factors. To identify the relative importance of the major improvement factors, the Analytic Hierarchy Process (AHP) method was applied, and a survey was conducted among 15 related experts. Findings - As a result, among the 12 detailed variables, Composition of Association (0.267) was the first factor to be improved, followed by Incentive Support (0.143) and E-Commerce Cluster (0.131). Based on these analyses, the main implications of this study are, first, in the current situation where the cross-border e-commerce market is growing, Pyeongtaek Port needs to form a consultative body among the government, local governments, and related businesses in connection with cross-border e-commerce and develop various support policies for the e-commerce market. Second, it will have to be able to provide differentiated services from competing ports by establishing e-commerce market-oriented clusters. Originality/value - In existing related studies, various improvements were presented to revitalize trade in line with the growth of the cross-border e-commerce market. However, with regard to most cross-border e-commerce businesses, one-dimensional improvement measures, such as improvement of payment systems, improvement of customs clearance services, and promotion of human resources, are presented in a piecemeal manner. In other words, none of the studies have proposed the importance and priority of each measure in terms of both the forward-looking and efficient allocation of resources, which is the purpose of this study. Therefore, this study contributed politically, practically, and academically by presenting countermeasures for ports to revitalize cross-border e-commerce and presenting strategic priorities using quantitative analysis methods.

• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.785-792
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• 2021

Since the Fourth Industrial Revolution, various changes have occurred in society as a whole due to advance in technologies such as artificial intelligence and big data. The amount of data that can be collect in the process of applying important technologies tends to increase rapidly. Especially in academia, existing generated literature data is analyzed in order to grasp research trends, and analysis of these literature organizes the research flow and organizes some research methodologies and themes, or by grasping the subjects that are currently being talked about in academia, we are making a lot of contributions to setting the direction of future research. However, it is difficult to access whether data collection is necessary for the analysis of document data without the expertise of ordinary programs. In this paper, propose a text mining-based topic modeling Web application model. Even if you lack specialized knowledge about data analysis methods through the proposed model, you can perform various tasks such as collecting, storing, and text-analyzing research papers, and researchers can analyze previous research and research trends. It is expect that the time and effort required for data analysis can be reduce order to understand.

• Journal of The Korean Society of Integrative Medicine
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• v.10 no.2
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• pp.73-83
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• 2022

Purpose : Low back pain (LBP) is reported as a risk of experiencing musculoskeletal disorders due to muscle stiffness and hypokinetics. The lumbar spine in an unstable state causes imbalance and lumbar instability. Therefore, This study examined the effects of lumbar stabilization exercise and self-complex exercise program on pain, function, psychosocial level, static balance ability, and transverse abdominal muscle (TrA) thickness and contraction ratio in patients with lumbar instability. Methods : The design of this is a randomized controlled trial (RCT). Twenty-six LBP patients participated in this study. Screening tests were performed and assigned to the experimental group (n=13) and control group (n=13) using a random allocation program. Both groups underwent a lumbar stabilization exercise program. In addition, the experimental group implemented the self-complex exercise program. All interventions were applied three times per week for four weeks. The quadruple visual analog (QVAS), the Korean version of the Oswestry disability index (K-ODI), Korean version of fear-avoidance belief questionnaire (FABQ), static balance ability, TrA thickness, and contraction ratio were compared to evaluate the effect on intervention. Statistical significance was set at 𝛼=.05. Results : Both groups showed significant differences before and after the intervention in QVAS, K-ODI, FABQ, static balance ability, and TrA thickness in contraction (p<.05). In addition, significant differences in K-ODI and FABQ were observed between the experimental group and control group (p<.05). Conclusion : A lumbar stabilization exercise and self-complex exercise program resulted in reduced dysfunctions, psychosocial stability in patients with lumbar instability. Therefore, Lumbar stabilization exercise and self-complex exercise program for patients with lumbar instability are effective method with clinical significance in improving the function and psychosocial stability.