• Journal of Digital Convergence
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• v.16 no.12
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• pp.21-31
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• 2018

In order to utilize HPC in Computational science, It is necessary to learn the knowledge and skills of computer science such as programming, algorithms and data structure. In this paper, we investigate IT education status in Computational science and propose policy directions to improve the HPC education through user survey. To do this, we surveyed the current state of IT subjects among major subjects in physics, chemistry, life sciences, and earth science in domestic universities and surveyed the users' Recognition of HPC education. As a result, the ratio of IT subjects in Computational science was very lower than the ratio of major domain subjects. Despite the high educational needs of universities, the educational level of universities was the lowest. Most users have learned the necessary knowledge and skills through self-study. We recognized the role of the university is the most urgent and important, and the role of professional institutions and online education is also important.

• Journal of The Korean Association of Information Education
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• v.26 no.5
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• pp.327-340
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• 2022

This study applied effective playful learning to increase the learning motivation of non-CS major students to help them achieve learning and to successfully operate online SW liberal arts classes for 560 students. As a result of analyzing the students' reflection journals, most of the students accepted the 'white radish' of dialect names as fun playful learning in the process of learning local variables and global variables. And they were surprised and amazed at discovering unexpected contents in our SW class. It was found that they experienced delight in learning, learning-flow, confidence, and intrinsic motivation. In the final term exam at the end of the semester, it was confirmed that the correct rate of 92% for questions related to local and global variables was higher than the average rate of other questions' correctness of 67.1%.

• Journal of Gifted/Talented Education
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• v.24 no.4
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• pp.597-612
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• 2014

The purpose of this study was to investigate how teachers recognize the differentiation of gifted education in invention to gifted education in science. An online survey was conducted to more than 500 hundred school teachers to ask (1) if gifted education in invention is necessary as an independent area of gifted education, (2) if gifted education in invention should be differentiated in identification, education programs, councelling, facilities and so on to gifted education in science, and (3) what problems gifted education in invention are facing and how we can promote gifted education in invention. Findings by this study are like the following: 1. Almost all teachers, regardless of whether their duty is related to gifted education in invention or not, recognized the necessity of gifted education in invention as an independent area of gifted education, especially from gifted education in science. 2. Teachers recognized the differentiation of gifted education in invention in diverse aspects of gifted education, like identification, educational programming, and so on, especially to gifted education in science. 3. Teachers recognized the shortage of trained teachers as the most critical obstacles to gifted education in invention, and also thought training programs for teachers as the most important means that can promote gifted education in invention.

• Journal of Radiation Protection and Research
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• v.44 no.2
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• pp.64-71
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• 2019

Background: It is very difficult to distinguish between a radioactive contamination source and background radiation from natural radionuclides in the marine environment by means of online monitoring system. The objective of this study was to investigate a statistical process for triggering abnormal level of count rate data measured from our on-line seawater radioactivity monitoring. Materials and Methods: Count rate data sets in time series were collected from 9 monitoring posts. All of the count rate data were measured every 15 minutes from the region of interest (ROI) for $^{137}Cs$ ($E_{\gamma}=661.6keV$) on the gamma-ray energy spectrum. The Shewhart ($3{\sigma}$), CUSUM, and Bayesian S-R control chart methods were evaluated and the comparative analysis of determination methods for count rate data was carried out in terms of the false positive incidence rate. All statistical algorithms were developed using R Programming by the authors. Results and Discussion: The $3{\sigma}$, CUSUM, and S-R analyses resulted in the average false positive incidence rate of $0.164{\pm}0.047%$, $0.064{\pm}0.0367%$, and $0.030{\pm}0.018%$, respectively. The S-R method has a lower value than that of the $3{\sigma}$ and CUSUM method, because the Bayesian S-R method use the information to evaluate a posterior distribution, even though the CUSUM control chart accumulate information from recent data points. As the result of comparison between net count rate and gross count rate measured in time series all the year at a monitoring post using the $3{\sigma}$ control charts, the two methods resulted in the false positive incidence rate of 0.142% and 0.219%, respectively. Conclusion: Bayesian S-R and CUSUM control charts are better suited for on-line seawater radioactivity monitoring with an count rate data in time series than $3{\sigma}$ control chart. However, it requires a continuous increasing trend to differentiate between a false positive and actual radioactive contamination. For the determination of count rate, the net count method is better than the gross count method because of relatively a small variation in the data points.

• The Korean Journal of Applied Statistics
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• v.32 no.2
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• pp.213-227
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• 2019

In this paper, we propose an end-to-end deep learning model combining Bayesian neural network with Korean speech recognition. In the past, Korean speech recognition was a complicated task due to the excessive parameters of many intermediate steps and needs for Korean expertise knowledge. Fortunately, Korean speech recognition becomes manageable with the aid of recent breakthroughs in "End-to-end" model. The end-to-end model decodes mel-frequency cepstral coefficients directly as text without any intermediate processes. Especially, Connectionist Temporal Classification loss and Attention based model are a kind of the end-to-end. In addition, we combine Bayesian neural network to implement the end-to-end model and obtain Monte Carlo estimates. Finally, we carry out our experiments on the "WorimalSam" online dictionary dataset. We obtain 4.58% Word Error Rate showing improved results compared to Google and Naver API.

• Journal of Digital Convergence
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• v.17 no.1
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• pp.9-27
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• 2019

The purpose of this study is to examine consumers' responses to mobile payment services by using a text-mining technique focusing on Samsung Pay as it is used in both online and offline transactions. We conducted text frequency analysis, text clustering analysis, and text network analysis using R programming. The major findings are as follows. First, the most frequently used key words referenced the brand names of the mobile devices, the replacement of traditional wallets and unique functions of Samsung Pay. Second, there was a clear split between positive and negative responses at the macro level. Third, replacement of traditional wallets played a great role in the positive responses and continuous use of mobile payment services. This study provides in-depth understanding of consumer responses toward mobile payment services. It also offers practical implications that may help mobile payment marketers correspond to consumer values and expectations, thus increasing consumer satisfaction.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.209-216
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• 2022

In this paper, we propose an effective software education program to promote employment of the disabled and verify the effectiveness of SW education through pilot operation. In this SW education program, we develop a SW curriculum consisting of the basic course, Unity programming course, and the advanced course, AR/VR digital content development course. The SW education achievement standard develops the basic and advanced course achievement standards in consideration of the level of the virtual reality content production job of the National Competency Standards(NCS) and the SW education achievement standards of youth with visual, hearing, and physical disabilities. SW education materials are developed on a project basis so that one AR/VR digital content can be implemented step by step according to the intellectual level of the disabled based on Unity. SW education pilot training is conducted as online education based on Blended Learning due to COVID-19. In order to derive the SW education effect and each learner's individual SW education academic achievement for the SW education pilot training, a survey is conducted on learners, and the results are analyzed. In the basic course, 77.3% of learners achieved academic achievement above excellent(80-90), and in the advanced course, 48.8% of learners achieved academic achievement above excellent(80-90). These results verify that the SW education program for the disabled developed in this paper is effective in activating employment for the disabled.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.33 no.1
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• pp.301-319
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• 2022

In recent decades, research became more data-intensive in the fast-paced information environment. Researchers are facing new challenges in managing their research data due to the increasing volume of data-driven research and the policies of major funding agencies. Information professionals have begun to offer various data support services such as training, instruction, data curation, data management planning and data visualization. However, the emerging field of data librarians, including specific roles and competencies, has not been clearly established even though librarians are taking on new roles in data services. Therefore, there is a need to identify a set of competencies for data librarians in this growing field. The purpose of this study is to consider varying core competencies for data librarians. This exploratory study examines 95 online recruiting advertisements regarding data librarians posted between 2017 and 2021. This study finds core competencies for data librarians that include skills in technology, communication and interpersonal relationships, training/consulting, service, library management, metadata knowledge and knowledge of data curation. Specific core technology skills include knowledge of statistical software and computer programming. This study contributes to an understanding of core competencies for data librarians to help future information professionals prepare their competencies as data librarians and the instructors who develop and revise curriculum and course materials.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.149-169
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• 2018

Korea is currently accumulating a large amount of data in public institutions based on the public data open policy and the "Government 3.0". Especially, a lot of data is accumulated in the tourism field. However, the academic discussions utilizing the tourism data are still limited. Moreover, the openness of the data of restaurants, hotels, and online tourism information, and how to use SNS Big Data in tourism are still limited. Therefore, utilization through tourism big data analysis is still low. In this paper, we tried to analyze influencing factors on foreign tourists' satisfaction in Korea through numerical data using data mining technique and R programming technique. In this study, we tried to find ways to revitalize the tourism industry by analyzing about 36,000 big data of the "Survey on the actual situation of foreign tourists from 2013 to 2015" surveyed by the Korea Culture & Tourism Research Institute. To do this, we analyzed the factors that have high influence on the 'Satisfaction', 'Revisit intention', and 'Recommendation' variables of foreign tourists. Furthermore, we analyzed the practical influences of the variables that are mentioned above. As a procedure of this study, we first integrated survey data of foreign tourists conducted by Korea Culture & Tourism Research Institute, which is stored in the tourist information system from 2013 to 2015, and eliminate unnecessary variables that are inconsistent with the research purpose among the integrated data. Some variables were modified to improve the accuracy of the analysis. And we analyzed the factors affecting the dependent variables by using data-mining methods: decision tree(C5.0, CART, CHAID, QUEST), artificial neural network, and logistic regression analysis of SPSS IBM Modeler 16.0. The seven variables that have the greatest effect on each dependent variable were derived. As a result of data analysis, it was found that seven major variables influencing 'overall satisfaction' were sightseeing spot attraction, food satisfaction, accommodation satisfaction, traffic satisfaction, guide service satisfaction, number of visiting places, and country. Variables that had a great influence appeared food satisfaction and sightseeing spot attraction. The seven variables that had the greatest influence on 'revisit intention' were the country, travel motivation, activity, food satisfaction, best activity, guide service satisfaction and sightseeing spot attraction. The most influential variables were food satisfaction and travel motivation for Korean style. Lastly, the seven variables that have the greatest influence on the 'recommendation intention' were the country, sightseeing spot attraction, number of visiting places, food satisfaction, activity, tour guide service satisfaction and cost. And then the variables that had the greatest influence were the country, sightseeing spot attraction, and food satisfaction. In addition, in order to grasp the influence of each independent variables more deeply, we used R programming to identify the influence of independent variables. As a result, it was found that the food satisfaction and sightseeing spot attraction were higher than other variables in overall satisfaction and had a greater effect than other influential variables. Revisit intention had a higher ${\beta}$ value in the travel motive as the purpose of Korean Wave than other variables. It will be necessary to have a policy that will lead to a substantial revisit of tourists by enhancing tourist attractions for the purpose of Korean Wave. Lastly, the recommendation had the same result of satisfaction as the sightseeing spot attraction and food satisfaction have higher ${\beta}$ value than other variables. From this analysis, we found that 'food satisfaction' and 'sightseeing spot attraction' variables were the common factors to influence three dependent variables that are mentioned above('Overall satisfaction', 'Revisit intention' and 'Recommendation'), and that those factors affected the satisfaction of travel in Korea significantly. The purpose of this study is to examine how to activate foreign tourists in Korea through big data analysis. It is expected to be used as basic data for analyzing tourism data and establishing effective tourism policy. It is expected to be used as a material to establish an activation plan that can contribute to tourism development in Korea in the future.

• Management & Information Systems Review
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• v.36 no.3
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• pp.131-150
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• 2017

The purpose of this study is to observe the spread pattern of open source software (OSS) while establishing relations with surrounding actors during its operation period. In order to investigate the change pattern of participants in the OSS, we use a netnography on the basis of online data, which can trace the change patterns of the OSS depending on the passage of time. For this, the cases of three OSSs (e.g. jQuery, MooTools, and YUI), which are JavaScript frameworks, were compared, and the corresponding data were collected from the open application programming interface (API) of GitHub as well as blog and web searches. This research utilizes the translation process of the actor-network theory to categorize the stages of the change patterns on the OSS translation process. In the project commencement stage, we identified the type of three different OSS-related actors and defined associated relationships among them. The period, when a master commences a project at first, is refined through the course for the maintenance of source codes with persons concerned (i.e. project growth stage). Thereafter, the period when the users have gone through the observation and learning period by being exposed to promotion activities and codes usage respectively, and becoming to active participants, is regarded as the 'leap of participants' stage. Our results emphasize the importance of promotion processes in participants' selection of the OSS for participation and confirm the crowding-out effect that the rapid speed of OSS development retarded the emergence of participants.