• The Journal of Sustainable Design and Educational Environment Research
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• v.17 no.3
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• pp.54-64
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• 2018

The results of the survey conducted mainly in the Gyeongsangnam-do province are as follows : First, 31.6% (65 schools) of the total elementary schools in the eight Cities Dong Districts of Kyungsangnam-Do Province are larger than the appropriate schools. 51.9% (107 schools) are the most suitable schools. The number of small schools with less than 300 students was 35 (17.0%). Of the 138 elementary schools in City Up-Myun districts, 11.6% (16 schools) account for big schools larger than the appropriate size. The number of schools with adequate size is 18.1% (25 schools), while 97 schools with 70.3% of small schools occupy the majority. Of these, 10.1% (14 schools) account for less than 150 small schools. Second, three large schools (2.2%) are larger than the appropriate schools among the 137 elementary schools in the nine districts of Gyeongsangnam - do, and 17 schools (12.4%) are suitable for small schools. Less than 300 small schools 117 schools (85.4%), of which 111 small schools (81.0%) accounted for the majority. Third, as a result of the analysis by the subdivision into the provinces, municipalities, and counties, small - scale schools accounted for the majority of municipalities and counties. Therefore, considering the local environment, it is necessary to establish appropriate school proper size policy differentiated from municipal school.

• Journal of the Korean earth science society
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• v.40 no.3
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• pp.300-312
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• 2019

The purpose of this study is to develop an astronomical observing education program that enables high school students to inquire the distance of astronomical bodies based on the research methods (observing open clusters and exploring collected big data) using small telescopes and DSLR cameras. After analyzing the 2015 revised science curriculum, we developed science club activity materials and teacher-student learning contents suitable for high school earth science education. A panel of six teachers and researchers of earth science education and astronomy, participated in developing the educational materials. The validity of the program was verified through establishing the agreement among the panels after in-depth discussions and clarifications. The program, developed with 10 lessons in total, showed high satisfactory content validity (CVI, .89) and conformity of school class (Likert's 5 point scales, 4.17). The feedback of the panels and the Delphi analysis continued to improve the quality of the program. The pilot testing result with high school students (N=9) showed that the students' satisfaction rate was high as 4.48. Using the astronomical observational education program of this study is expected to contribute in improving the convergence educational activity, interest, curiosity, and inquiry ability of students in the universe and the astronomical bodies.

• Journal of Internet Computing and Services
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• v.20 no.1
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• pp.17-24
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• 2019

Since the information of $4^{th}$ Industrial Revolution is introduced in WEF (World Economic Forum) in 2016, IoT, AI, Big Data, 5G, Cloud Computing, 3D/4DPrinting, Robotics, Nano Technology, and Bio Engineering have been rapidly developed as business applications as well as technologies themselves. Among the diverse business applications for IoT, wearable devices are recognized as the leading application devices for final customers. This longitudinal study is compared to the results of the 1st study conducted to identify customer needs of activity trackers, and links the identified users' needs with the well-known marketing frame of marketing mix. For this longitudinal study, a survey was applied to university students in June, 2018, and ANOVA were applied for major variables on usable features. Further, potential customer needs were identified and visualized by Word Cloud Technique. According to the analysis results, different from other high tech IT devices, activity trackers have diverse and unique potential needs. The results of this longitudinal study contribute primarily to understand usable features and their changes according to product maturity. It would provide some valuable implications in dynamic manner to activity tracker designers as well as researchers in this arena.

• Journal of Digital Convergence
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• v.18 no.12
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• pp.425-434
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• 2020

Background: Viral infection outbreaks are emerging public health concerns. They often exhibit seasonal patterns that could be predicted by the application of big data and bioinformatic analyses. Purpose: The purpose of this study was to identify trends in diarrhea-causing viruses such as rotavirus (Gr.A), norovirus G-I, and norovirus G-II in Cheonan, Korea. The identified related factors of diarrhea-causing viruses may be used to predict their trend and prevent their infections. Method: A retrospective analysis of 4,009 fecal samples from June 2010 to December 2019 was carried out at Dankook University Hospital in Cheonan. Reverse transcription-PCR (RT-PCR) was employed to identify virus strains. Information about seasonal patterns of infection was extracted and compared with local weather data. Results: Out of the 4,009 fecal samples tested using multiplex RT-PCR (mRT-PCR), 985 were positive for infection with Gr.A, G-I, and G-II. Out of these 985 cases, 95.3% (n = 939) were under 10 years of age. Gr.A, G-I, and G-II showed high infection rates in patients under 10 years of age. Student's t-test showed a significant correlation between the detection rate of Gr.A and the relative humidity. The detection rate of G-II significantly correlated with wind-chill temperature. Conclusion: Climate factors differentially modulate rotavirus and norovirus infection patterns. These observations provide novel insights into the seasonal impact on the pathogenesis of Gr.A, G-I, and G-II.

• Journal of Bio-Environment Control
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• v.30 no.1
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• pp.19-26
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• 2021

In this study, analysis was performed to identify three greenhouses located in the same area using principal component analysis (PCA) and linear discrimination analysis (LDA). The environmental data in the greenhouse were from 3 farms in the same area, and the values collected at 1 hour intervals for a total of 4 weeks from April 1 to April 28 were used. Before analyzing the data, it was pre-processed to normalize the data, and the analysis was performed by dividing it into 80% of the training data and 20% of the test data. As a result of PCA and LDA analysis, it was found that PCA classification accuracy was 57.51% and LDA classification was 67.06%, indicating that it can be classified by greenhouse. Based on the farmhouse data classified in advance, the data of the new environment can be classified into specific groups to determine the tendency of the data. Such data is judged to be a way to increase the utilization of data by facilitating identification.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.2
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• pp.266-274
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• 2021

Ship officers are subject to excessive job stress, which has negative physical and psychological impacts and may adversely affect the smooth supply and demand of human resources. In this study, a mobile web application was developed as a tool for systematic job stress measurement and management of officers and verified through quality evaluation. Requirement analysis was performed by ship officers and staff in charge of human resources of shipping companies, and the results were reflected in the application configuration step. The application was designed according to the waterfall model, which is a traditional software development method, and functions were implemented using JSP and Spring Framework. Performance evaluation on the user interface, confirmed that proper input and output results were implemented, and the respondent results and the database were configured in the administrator interface. The results of evaluation questionnaires for quality evaluation of the interface based on ISO/IEC 9126-2 metric were significant 4.60 for the user interface and 4.65 for the administrator interface in a 5-point scale. In the future, it is necessary to conduct follow-up research on the development of data analysis system through utilization of the collected big-data sets.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.49-59
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• 2022

In this paper, we designed a new enzyme function prediction model PSCREM based on a study that compared and evaluated CNN and LSTM/GRU models, which are the most widely used deep learning models in the field of predicting functions and structures using protein sequences in 2020, under the same conditions. Sequence evolution information was used to preserve detailed patterns which would miss in CNN convolution, and the relationship information between amino acids with functional significance was extracted through overlapping RNNs. It was referenced to feature map production. The RNN family of algorithms used in small CNN-RNN models are LSTM algorithms and GRU algorithms, which are usually stacked two to three times over 100 units, but in this paper, small RNNs consisting of 10 and 20 units are overlapped. The model used the PSSM profile, which is transformed from protein sequence data. The experiment proved 86.4% the performance for the problem of predicting the main classes of enzyme number, and it was confirmed that the performance was 84.4% accurate up to the sub-sub classes of enzyme number. Thus, PSCREM better identifies unique patterns related to protein function through overlapped RNN, and Overlapped RNN is proposed as a novel methodology for protein function and structure prediction extraction.

• The Journal of Society for e-Business Studies
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• v.26 no.4
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• pp.133-154
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• 2021

Today smart phone is the most common media with a vehicle called 'application'. In order to understand how media users select applications and build their repertoire, this study conducted two-step approach using big data from smart phone log for 4 weeks in November 2019, and finally classified 8 media repertoire groups. Each of the eight media repertoire groups showed differences in time spent of mobile application category compared to other groups, and also showed differences between groups in demographic distribution. In addition to the academic contribution of identifying the mobile application repertoire with large scale behavioral data, this study also has significance in proposing a two-step approach that overcomes 'outlier issue' in behavioral data by extracting prototype vectors using SOM (Sefl-Organized Map) and applying it to k-means clustering for optimization of the classification. The study is also meaningful in that it categorizes customers using e-commerce services, identifies customer structure based on behavioral data, and provides practical guides to e-commerce communities that execute appropriate services or marketing decisions for each customer group.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.4
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• pp.517-531
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• 2018

This study was carried out for the purpose of investigating Uzbekistan students's adaptation to Korea college life. Qualitative interviews were conducted in regards to the motivation for college entrance and stresses incurred during college life for 10 Uzbekistan students who were studying at I college located in Incheon. Data from the interviews were analyzed using theme analysis method. Most of the participants in this study got information about Korean colleges through their overseas study exhibitions in their own countries and became Korea college. The results showed that the reasons for college enrollment were (1)preparation for future goals (2)the influence of family. In Uzbekistan, parents play a big role in determining their children's education. Therefore, their decision to study abroad and the role of their parents were significant. The stress they experienced in college life fell into five categories, namely, (1)financial stress (2)stress about studies (3) stress in regards to human relationships (4)stress in regards to their futures and getting a job. In addition, this study discussed how to solve such as problems experienced by Uzbekistan students. And also the role of college and the necessity of providing appropriate support programs were discussed. Finally, the implications of these findings were presented.

• Nuclear Medicine and Molecular Imaging
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• v.42 no.6
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• pp.435-443
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• 2008

Purpose: Gated myocardial perfusion SPECT provides not only myocardial perfusion status but also various functional parameters of left ventricle. We compared left ventricular ejection fraction, end-diastolic volume, LV mass by cardiac SPECT using Quantitative Gated SPECT (QGS), 4D-MSPECT software and standard 2D-echocardiography. Materials and Methods: One hundred fourteen patients (male 51, female 63; 29-85 years old, mean $61.3\;{\pm}\;13.3$ years old) with normal perfusion status on Tc-99m tetrofosmin gated myocardial perfusion SPECT were analyzed retrospectively. Ejection fraction (LVEF), End-diastolic volume (LVED), LV mass (LVM) were calculated using QGS, 4D-MSPECT, and LVEF, LVM using 2D-echocardiography. Statistical analysis including Bland-Altman plot was performed using $MedCalc^{(R)}$ (MedCalc software, Mariakerke, Belgium). Results: The correlation of LVEF between methods was good: 0.95/0.96 (stress/rest) between QGS and 4D-MSPECT, 0.79 between QGS and echocardiography, 0.79 between 4D-MSPECT and echocardiography (p<0.001). Using Bland-Altman plot, the 95% confidence interval of agreement between QGS and 4D-MSPECT ranged from -12.7% to 7.3% / from -12.2% to 6.5% (stress/rest). The agreement between QGS and echocardiography, 4D-MSPECT and echocardiography ranged from -17.4% to 24.0%, and -14.8% to 27.0% respectively. The correlation of LVM between methods was also good: 0.95 between QGS and 4D-MSPECT, 0.76 between QGS and echocardiography, 0.73 between 4D-MSPECT and echocardiography (p<0.001). The 95% confidence interval of agreement between QGS and 4D-MSPECT ranged from -33.8g to 14.1g (stress/rest), The 95% confidence interval of agreement between QGS and echocardiography, 4D-MSPECT and echocardiography ranged from -148.7 g to 21.8. g, and -142.8 g to 35.5 g, respectively. Conclusion: There was a good correlation for LVEF, LVEO, LVM among methods (QGS, 4D-MSPECT, echocardiography), but the variance between methods was big. Therefore, the functional parameters by each method cannot be used interchangeably.