• The Journal of the Korea Contents Association
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• v.19 no.7
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• pp.82-90
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• 2019

The purpose of this study was to analyze trends of domestic research on MOOCs(Massive Open Online Courses) for the last 10 years and provides implications for research on education and learning using MOOC. A total of 70 research papers were selected for the analysis. As a result, the research papers on MOOC in Korea have been increasing from 2012 to 2018. Of the 70 research papers, 31 were clearly indicated research subjects, and most of the research was conducted for university students. Regarding the research type, survey research(27.1%) were the most common. The predictors used in the study of MOOCs are demographic characteristics and perceived usefulness and ease of use for independent variables, satisfaction, perceived usefulness and ease of use for the mediators, usage intention and persistence for dependent variables were frequently used. Further implications were discussed for the study.

• The Journal of the Korea Contents Association
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• v.19 no.2
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• pp.491-507
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• 2019

The result of this study was to measure the relative efficiency of 133 colleges in south korea and to investigate the differences in the results of college basic competency evaluation. As a result of the study showed that the average difference of efficiency according to the background variables was no significant according to the scale, location, and college evaluation. but differences in the type of establishment were found to vary significantly in S.E model. In addition, it was analyzed that the efficiency of the college with limited funding for the efficiency distribution is highly distributed, which indicates that it is necessary to continuously improve the existing university methods and to assess whether they are being managed effectively. Finally, the limitations of this study are that it used only quantitative data and that additional indicators could result in different outcomes from the results of this study.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.587-593
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• 2021

In this thesis, we will break away from the classic DDoS response system for large-scale denial-of-service attacks that develop day by day, and effectively endure intelligent denial-of-service attacks by utilizing artificial intelligence-based technology, one of the core technologies of the 4th revolution. A possible service model development plan was proposed. That is, a method to detect denial of service attacks and minimize damage through machine learning artificial intelligence learning targeting a large amount of data collected from multiple security devices and web servers was proposed. In particular, the development of a model for using artificial intelligence technology is to detect a Western service attack by focusing on the fact that when a service denial attack occurs while repeating a certain traffic change and transmitting data in a stable flow, a different pattern of data flow is shown. Artificial intelligence technology was used. When a denial of service attack occurs, a deviation between the probability-based actual traffic and the predicted value occurs, so it is possible to respond by judging as aggressiveness data. In this paper, a service denial attack detection model was explained by analyzing data based on logs generated from security equipment or servers.

• The Journal of the Korea Contents Association
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• v.21 no.8
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• pp.1-9
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• 2021

Deep learning in computer vision has made accelerated improvement over a short period but large-scale learning data and computing power are still essential that required time-consuming trial and error tasks are involved to derive an optimal network model. In this study, we propose a similar image classification performance improvement method based on CR (Confusion Rate) that considers only the characteristics of the data itself regardless of network optimization or data reinforcement. The proposed method is a technique that improves the performance of the deep learning model by calculating the CRs for images in a dataset with similar characteristics and reflecting it in the weight of the Loss Function. Also, the CR-based recognition method is advantageous for image identification with high similarity because it enables image recognition in consideration of similarity between classes. As a result of applying the proposed method to the Resnet18 model, it showed a performance improvement of 0.22% in HanDB and 3.38% in Animal-10N. The proposed method is expected to be the basis for artificial intelligence research using noisy labeled data accompanying large-scale learning data.

• The Journal of the Korea Contents Association
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• v.21 no.8
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• pp.662-674
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• 2021

Metabolic syndrome is closely associated with cardiovascular disease, there is increasing attentions in prevention of metabolic syndrome through prediction. The aim of this study was to systematically review the literature by collecting, analyzing, and synthesizing articles of predicting metabolic syndrome in Koreans. For systemic review, data search was conducted on Global journals Pubmed, WoS and domestic journals DBPia, KISS published in 2011-2020 year. Three keyword 'Metabolic syndrome', 'predict', and 'korea' were used for searching under AND condition. Total 560 articles were searched and the final 22 articles were selected according to the data selection criteria. The most useful variable was WHtR(AUC=0.897), most frequently used analysis method was logistic regression(63.6%), and most accurate analysis method was XGBOOST(AUC=0.879) for predicting metabolic syndrome. Prediction accuracy was slightly improved when sasang constitution types was used. Based on the results of this study, it is believed that various large-scale longitudinal studies for the prediction and management of the Metabolic syndrome in Korean should be followed in the future.

• Journal of the Korea Convergence Society
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• v.12 no.7
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• pp.169-179
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• 2021

This study shows that the two-stage k-means clustering method can improve prediction performance by predicting the stock price, To this end, this study introduces the two-stage k-means clustering algorithm and tests the prediction performance through comparison with various machine learning techniques. It selects the cluster close to the prediction target obtained from the k-means clustering, and reapplies the k-means clustering method to the cluster to search for a cluster closer to the actual value. As a result, the predicted value of this method is shown to be closer to the actual stock price than the predicted values of other machine learning techniques. Furthermore, it shows a relatively stable predicted value despite the use of a relatively small cluster. Accordingly, this method can simultaneously improve the accuracy and stability of prediction, and it can be considered as the new clustering method useful for small data. In the future, developing the two-stage k-means clustering is required for the large-scale data application.

• Journal of Digital Contents Society
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• v.17 no.1
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• pp.51-57
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• 2016

Distributed Computing attempts to harness a massive computing power using a great numbers of idle PCs resource distributed linked to the internet and processes a variety of applications parallel way such as bio, climate, cryptology, and astronomy. In this paper, we develop internet-distributed computing environment, so that we can analyze High Resolution Rainfall Prediction application in meteorological field. For analyze the rainfall forecast in Korea peninsula, we used QPM(Quantitative Precipitation Model) that is a mesoscale forecasting model. It needs to a lot of time to construct model which consisted of 27KM grid spacing, also the efficiency is degraded. On the other hand, based on this model it is easy to understand the distribution of rainfall calculated in accordance with the detailed topography of the area represented by a small terrain model reflecting the effects 3km radius of detail and terrain can improve the computational efficiency. The model is broken down into detailed area greater the required parallelism and increases the number of compute nodes that efficiency is increased linearly.. This model is distributed divided in two sub-grid distributed units of work to be done in the domain of $20{\times}20$ is networked computing resources.

• The Journal of the Korea Contents Association
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• v.19 no.1
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• pp.660-670
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• 2019

The purpose of this study is to elaborate the logical configuration of livelihood benefits for the institutionalized recipients under the renewed custom-tailored benefit system of National Basic Livelihood Security System(NBLSS) and to present appropriate level of benefits in terms of coherency of the system. In July 2015, the NBLSS was reformed to adopt a relative level of benefit standard for the general recipients according to certain amount of ratio of standard median income. However, the benefit for the institutionalized recipients was still based on the cost of necessities of absolute poverty level. It is at this juncture that this study suggests livelihood benefits for the institutionalized recipients reflect standard median income to comply with the reform of the NBLSS. To this end, this study firstly derives basic living items for the institutionalized recipients based on the literature review and FGI. Secondly, it calculates the reflection ratio of livelihood benefits utilizing Household Trend Survey's consumption data under 40%. Finally, it applies equivalence scale of households to adjust the under-represented scale for large size institutions. To continue the reflection ratio method, it is necessary to review the consumption trends and the stability of the reflection ratio periodically.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.88-95
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• 2021

In Korea, which achieved economic growth due to export industries, the economic importance of the foreign port transportation industry is very great. The government took the initiative in fostering the foreign port transportation industry, and as a result, it developed into one of the top 10 foreign port transport countries in the world. However, due to the poor management of the small and medium-sized foreign port transport business and the trade dispute between countries, the foreign port transportation industry has faced a long-term invasion. Therefore, in order for these companies to recover again, they will, among other things, have to reorganize their operational inefficiency to carry out efficient production activities. In this study, we want to analyze the management efficiency of the top 10% companies in the unlisted domestic outbound shipping industry, present the project value of inefficient enterprises, and confirm the reference collection of companies that may be subject to benchmarking. For this purpose, a total of 10 foreign port transportation industry were analysed for efficiency and scale profitability (RTS) of the CCR and BCC models. The analysis showed that there were a total of six entities with BCC efficiency and five entities with CCR efficiency. In addition, there were a total of five entities with both BCC and CCR efficiency.

• Journal of Technology Innovation
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• v.31 no.2
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• pp.173-214
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• 2023

Investments in new technologies have grown significantly in size, and science and technology have a large and complex impact on society at large. With people's great interest in technology, the government has the duty to accurately assess the influence of new technologies on society to facilitate their acceptance in society. For this purpose, technology impact assessment should be performed to facilitate a social consensus. There has been research on the initial methods of technology assessment for 50 years. Following various academic studies and discussions based on numerous new technology response policies, coupled with the examination of trends and changes over time, academia and policymakers around the world have paid attention to the multilateral analysis of the impact of new technologies on future society. This study focuses on research changes such as the stage of forecasting factors that should consider the technology assessment of new technologies, despite differences between the development methods for the assessment between developed countries and South Korea. The analysis yielded three factors of technological understanding of awareness, professionalism, and gender characteristics, in addition to a previously identified factor. The three factors are then suggested as forecasting factors for new technology. The findings of this study provide both academic and policy evidence for technology assessment based on the country's Framework Act on Science and Technology.