• Journal of the Korea Society of Computer and Information
• /
• v.25 no.4
• /
• pp.165-172
• /
• 2020

In this paper we propose an uses on-device-based edge computing technology and big data analysis methods through the use of on-device-based edge computing technology and analysis of big data, which are distributed computing paradigms that introduce computations and storage devices where necessary to solve problems such as transmission delays that occur when data is transmitted to central centers and processed in current general smart factories. However, even if edge computing-based technology is applied in practice, the increase in devices on the network edge will result in large amounts of data being transferred to the data center, resulting in the network band reaching its limits, which, despite the improvement of network technology, does not guarantee acceptable transfer speeds and response times, which are critical requirements for many applications. It provides the basis for developing into an AI-based facility prediction conservation analysis tool that can apply deep learning suitable for big data in the future by supporting intelligent facility management that can support productivity growth through research that can be applied to the field of facility preservation and smart factory industry with integrated hardware technology that can accommodate these requirements and factory management and control technology.

• Journal of the Korean Society of Earth Science Education
• /
• v.14 no.2
• /
• pp.173-192
• /
• 2021

The purpose of this study is to analyze the previous research on geological fieldwork from 2000 to 2020, examine the tasks that have been focused on, and suggest directions and implications for future geological fieldwork research. The data was conducted for the thesis searched on ScienceON and RISS in relation to geological fieldwork and journals listed in the Korean Citation Index(KCI), and the study title was analyzed using the semantic network analysis. For analysis, the data that had been pre-processed was visualized as a network by semantic network analysis, and frequency and centrality were analyzed. The centrality analysis was based on degree centrality and eigenvector centrality, and all analyzes were performed by dividing the entire study period into four periods: 2000-2005, 2006-2010, 2011-2015, and 2016-2020. As a result, research on geological fieldwork focused more on the development of geological field courses, and in particular, jeju island was actively discussed as a learning site. Also, the study was conducted on students rather than teachers, and among them, high school students showed high frequency and centrality. In addition, it can be seen that studies on the educational effect of geological fieldwork were discussed, either in connection with programs such as STEAM, free-semester program, or indirect geological fieldwork methods such as web, flash panorama, and 3D. This study is meaningful in that it suggests the direction of future research by looking back on the research on geological fieldwork that has been done so far.

• Journal of the Korea Convergence Society
• /
• v.12 no.10
• /
• pp.63-70
• /
• 2021

Generating a super-resolution meteological data by using a high-resolution deep neural network can provide precise research and useful real-life services. We propose a new technique of generating improved training data for super-resolution deep neural networks. To generate high-resolution meteorological data with domain specific knowledge, Lambert conformal conic projection and objective analysis were applied based on observation data and ERA5 reanalysis field data of specialized institutions. As a result, temperature and humidity analysis data based on domain specific knowledge showed improved RMSE by up to 42% and 46%, respectively. Next, a super-resolution generative adversarial network (SRGAN) which is one of the aritifial intelligence techniques was used to automate the manual data generation technique using damain specific techniques as described above. Experiments were conducted to generate high-resolution data with 1 km resolution from global model data with 10 km resolution. Finally, the results generated with SRGAN have a higher resoltuion than the global model input data, and showed a similar analysis pattern to the manually generated high-resolution analysis data, but also showed a smooth boundary.

• The Journal of Bigdata
• /
• v.6 no.1
• /
• pp.51-62
• /
• 2021

In the field of medical artificial intelligence, there have been a lot of researches on disease prediction and classification algorithms that can help doctors judge, but relatively less interested in artificial intelligence that can help medical consumers acquire and judge information. The fact that more than 150,000 questions have been asked about which hospital to go over the past year in NAVER portal will be a testament to the need to provide medical information suitable for medical consumers. Therefore, in this study, we wanted to establish a classification model that classifies 8 medical subjects for symptom text directly described by patients which was collected from NAVER portal to help consumers choose appropriate medical subjects for their symptoms. In order to ensure the validity of the data involving patients' subject matter, we conducted similarity measurements between objective symptom text (typical symptoms by medical subjects organized by the Seoul Emergency Medical Information Center) and subjective symptoms (NAVER data). Similarity measurements demonstrated that if the two texts were symptoms of the same medical subject, they had relatively higher similarity than symptomatic texts from different medical subjects. Following the above procedure, the classification model was constructed using a ridge regression model for subjective symptom text that obtained validity, resulting in an accuracy of 0.73.

• Korean Journal of Remote Sensing
• /
• v.37 no.5_2
• /
• pp.1307-1315
• /
• 2021

The Changjiang Diluted Water (CDW) spreads over the East China Sea every summer and significantly affects the sea surface salinity changes in the seas around Jeju Island and the southern coast of Korea peninsula. Sometimes its effect extends to the eastern coast of Korea peninsula through the Korea Strait. Specifically, the CDW has a significant impact on marine physics and ecology and causes damage to fisheries and aquaculture. However, due to the limited field surveys, continuous observation of the CDW in the East China Sea is practically difficult. Many studies have been conducted using satellite measurements to monitor CDW distribution in near-real time. In this study, an algorithm for estimating Sea Surface Salinity (SSS) in the East China Sea was developed using the Geostationary Ocean Color Imager (GOCI). The Multilayer Perceptron Neural Network (MPNN) method was employed for developing an algorithm, and Soil Moisture Active Passive (SMAP) SSS data was selected for the output. In the previous study, an algorithm for estimating SSS using GOCI was trained by 2016 observation data. By comparison, the train data period was extended from 2015 to 2020 to improve the algorithm performance. The validation results with the National Institute of Fisheries Science (NIFS) serial oceanographic observation data from 2011 to 2019 show 0.61 of coefficient of determination (R²) and 1.08 psu of Root Mean Square Errors (RMSE). This study was carried out to develop an algorithm for monitoring the surface salinity of the East China Sea using GOCI and is expected to contribute to the development of the algorithm for estimating SSS by using GOCI-II.

• The Journal of the Korea Contents Association
• /
• v.21 no.9
• /
• pp.149-163
• /
• 2021

The 4th industrial revolution refers to the next-generation industrial revolution led by information and communication technologies such as artificial intelligence (AI), Internet of Things (IoT), robot technology, drones, autonomous driving and virtual reality (VR) and it also has made a significant impact on the development of the advertising industry. However, the world is rapidly changing to a non-contact, non-face-to-face living environment to prevent the spread of COVID 19. Accordingly, the role of the 4th industrial revolution and advertising is changing. Therefore, in this study, text analysis was performed using Big Kinds to examine the 4th industrial revolution and changes in advertising before and after COVID 19. Comparisons were made between 2019 before COVID 19 and 2020 after COVID 19. Main topics and documents were classified through LDA topic model analysis and Word2vec, a deep learning technique. As the result of the study showed that before COVID 19, policies, contents, AI, etc. appeared, but after COVID 19, the field gradually expanded to finance, advertising, and delivery services utilizing data. Further, education appeared as an important issue. In addition, if the use of advertising related to the 4th industrial revolution technology was mainstream before COVID 19, keywords such as participation, cooperation, and daily necessities, were more actively used for education on advanced technology, while talent cultivation appeared prominently. Thus, these research results are meaningful in suggesting a multifaceted strategy that can be applied theoretically and practically, while suggesting the future direction of advertising in the 4th industrial revolution after COVID 19.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.9 no.9
• /
• pp.1-16
• /
• 2019

This study was carried out to develop a physics education program for foreign students of university in Korea to improve their ability to major in the field and to prevent them from becoming dropout. The subjects of the study are five Chinese students attending a natural science and engineering college. Prior to the development of the physics education program, the researchers developed basic physics textbooks for the foreign students and questionaries for diagnosis and summative evaluation, and utilized them to apply a total of seven classes. After the application of the classes, the results of the student's diagnosis and summative evaluation, the teacher's diaries, the observer's diaries, and the transcripts were analyzed by triangulation method. In addition, Nvivo12 was used for the analysis of the teacher's and observer's diaries to help with qualitative analysis. The results of the study are as follows: First, the oder and contents of physics education program for students of the natural science and engineering college were presented in detail, and basic physics textbooks and tools for diagnosis and summative assessment were developed. Second, as a result of the analysis of the diagnosis and summative assessment results of the program, the students' basic physics achievement improved by an average of 40 points due to the application of the developed program. Third, as a result of the application of the program using Nvivo12, meaningful node and actual cases were extracted. There were 10 types of nodes created such as understanding of the students, teaching method, rate of the participation, level differences, language problems, relevance to majors, curriculum and methods of education in the country of origin, cooperative learning, and interest inducement. The researcher provided suggestions on physics education methods for students of science and engineering colleges in Korea based on the related cases.

• The Journal of the Korea Contents Association
• /
• v.19 no.8
• /
• pp.500-512
• /
• 2019

Recently, almost all industries are focusing on improving the competency of related industry workers, and it is necessary to design a systematic educational activity plan that constructs, operates and evaluates learning experiences for knowledge, technology and literacy development required in the industrial field. This study performed a questionnaire survey on students' satisfaction with 2015 and 2014 curriculum and national competency standards (NCS)-based one which has been applied since March 2016 against those from Department of Beauty & Cosmetology, 'C' University. For data analysis, frequency analysis, qualitative analysis and SWOT analysis were conducted, and the results found the followings: The NCS-based curriculum which has been applied since 2016 is more advanced than 2015 and 2014 curriculum in terms of strength, weakness, risk and opportunity. In addition, their satisfaction with curriculum was more than average with 47.9-57.2%. Meanwhile, when asked their favorite time to decide their academic major, 79.5% answered, '2nd semester of the 1st year'. They were very dissatisfied with the fact that their academic major is decided in the second year. It is anticipated that the NCS-based 2-year curriculum for Dept. of Beauty & Cosmetology is redesigned through analysis of students' satisfaction and by reflecting their opinions. It is also expected that the reorganization of the curriculum in a more practical and systematic manner would increase students' satisfaction and generate workforce for cosmetology industry.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.8
• /
• pp.250-263
• /
• 2019

This study was conducted to develop an online education program for visiting health nurses on National Health Examination. The study period was from November 2016 to December 2017. The program was developed in stages using rapid prototyping methodology. 1) Learners' needs were identified through literature review and focus group interviews (FGIs) with visiting health nurses and stake-holders in the field. 2) The contents of the education program including counseling strategies regarding the heath of visiting health nurses were developed. 3) Online education materials were developed and piloted amongst learners. 4) The contents of educational programs were classified into eight learning modules, and online education drafts were pilot tested. 5) Based on feedback from learners, this program was revised and a web-based continuing education program for community nurses was developed. These education programs effectively assisted nurses with counseling regarding health examinations during visiting health nursing care. Therefore, the online continuing education program may be a very effective educational approach to improving nurses competency.

• The Journal of the Korea Contents Association
• /
• v.19 no.2
• /
• pp.11-21
• /
• 2019

It has been about 20 years since the English subject was formally taught in public elementary schools in Korea. The present research aims to analyze the studies regarding 'primary English' implemented in Korea during the time period. I have investigated 6,467 theses or research papers in total that were published in Korea with the help of the corpus programs Utagger and WordSmith Tools. The results show that for the last 20 years the number of overall studies appears to have increased since the year 1997, although the recent trend seems to be in recession. The research scope ranges from 'teaching-learning interaction' to 'curriculum' and 'assessment', which have been steadily investigated for 20 years. Furthermore, researchers sometimes appear to have followed the English education policy by conducting particular investigations like 'immersion program' or 'native English speaking teachers' in a certain time period. Recently, researchers started to have interest in the cutting-edge ICT. In conclusion, the academic field of 'primary English' in Korea has grown in quantity, and the spectrum of research areas has been expanded for the past 20 years. It is hoped that the results of this research will help set a new direction for future research.