• Informatization Policy
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• v.28 no.2
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• pp.98-113
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• 2021

This study presents implications of the Global Data Law & Policy by comparing national data strategies, data regulations and policies, and governance in South Korea, the United States, the United Kingdom, and the European Union. According to the result of the comparative analysis, the biggest difference is in data governance, in other words, the management and coordination of policies at the pan-government level and data ethics. Therefore, this study proposes the establishment of a presidential special committee on data policy or the creation of a 'National Digital Innovation Office' at the Presidential Secretariat as a national CDO for the governance of data policies. Furthermore, this paper suggests a) to enact 'the Framework Act on the Development of Data Industry' that can regulate data practices in the private sector, b) to institutionalize the data-centric security and data protection, c) to settle the public ethics and personnel management based on data expertise and professional ethics, including explainability and responsibility, and d) the education and training systems.

• Smart Media Journal
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• v.9 no.4
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• pp.9-16
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• 2020

Recently, various studies are being conducted to integrate Image Segmentation into smart factory industries and autonomous driving fields. In particular, Image Segmentation systems using deep learning algorithms have been researched and developed enough to learn from large volumes of data with higher accuracy. In order to use image segmentation in the autonomous driving sector, sufficient amount of learning is needed with large amounts of data and the streaming environment that processes drivers' data in real time is important for the accuracy of safe operation through highways and child protection zones. Therefore, we proposed a novel DFCN algorithm that enhanced existing FCN algorithms that could be applied to various road environments, demonstrated that the performance of the DFCN algorithm improved 1.3% in terms of "loss" value compared to the previous FCN algorithms. Moreover, the proposed DFCN algorithm was applied to the existing U-Net algorithm to maintain the information of frequencies in the image to produce better results, resulting in a better performance than the classical FCN algorithm in the autonomous environment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.579-586
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• 2021

This study examines the application of big data and tasks of tourism based on the case of Jeju Special Self-Governing Province, which used big data for regional tourism policy. Through the use of big data, it is possible to understand rapidly changing tourism trends and trends in the tourism industry in a timely and detailed manner. and also could be used to elaborate existing tourism statistics. In addition, beyond the level of big data analysis to understand tourism phenomena, its scope has expanded to provide a platform for providing real-time customized services. This was made possible by the cooperative governance of industry, government, and academia for data building, analysis, infrastructure, and utilization. As a task, the limitation of budget dependence and institutional problems such as the infrastructure for building personal-level data for personalized services, which are the ultimate goal of smart tourism, and the Personal Information Protection Act remain. In addition, expertise and technical limitations for data analysis and data linkage remain.

• Journal of Convergence for Information Technology
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• v.11 no.3
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• pp.212-219
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• 2021

The current study aimed to find the effects of hair treatment with shea butter on bleached hair and hair protection. The agent for hair treatment with shea butter was developed in different concentration levels (0%,1%,3%,5%) for experimentation. After applying the agent to bleached hair, hair samples were evaluated as follows. Increase in hair thickness was highest in the hair sample that had 5% of shea butter. The amount of amino acids was also highest in the hair sample that contained 5% of shea butter. Comparing the difference of the surface color, hair sample with 5% of shea butter showed low level of L⁎ while the level of a⁎ value that reflects the redness was high and the level of b⁎ value that reflects yellowness was low. Observation through the scanning microscope confirmed the positive effects by showing smoother surfaces in the sample with shea butter than in the bleached hair. This study showed shea butter is considered to be cosmetics to protect damaged hair by bleaching.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.23 no.6
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• pp.75-85
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• 2020

The purpose of this study was to investigate the citizens' perception of urban ecosystem and urban ecosystem education to find out how to plan and create an effective urban ecosystem and how to utilize urban ecosystem education and educational media according to age groups. To this end, an online survey of 416 Suwon citizens was conducted, and based on the responses of the respondents, cross-analysis, multiple-response analysis, and correlation analysis were conducted using the IBM SPSS Statistics Statistical Program. The study found that fewer respondents showed a high understanding of urban ecosystem concepts compared to those who recognized the importance of environmental issues. Nevertheless, most of the respondents were aware of the importance of preserving and protecting the urban ecosystem and responded positively to the inconvenience. In addition, most of the respondents were aware of the need for urban ecosystem education and were found to have different preferred information media depending on age. It has been confirmed that the establishment of facilities such as ecological learning centers and seasonal environmental schools is the top priority among all age groups. Citizens are also aware of the importance of preserving and protecting the urban ecosystem and the need for education, but it is deemed necessary to supplement it because effective urban ecosystem conservation and protection plans and systematic education are not provided that citizens can sympathize with. In addition, it is deemed that various measures should be presented in selecting responsible organizations and educational media that host the education for effective education and promotion of urban ecosystem education according to conduct urban ecosystem education.

• Journal of Korean Society of Forest Science
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• v.110 no.2
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• pp.280-288
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• 2021

Understanding the occurrence characteristics of pine wilt disease (PWD) is essential for determining a suitable strategy to minimize the damage caused by PWD. Thus, in this study, we characterized various environmental conditions, including meteorological factors, geographical factors, and artificial factors influencing the occurrence of PWD. The occurrence data of PWD from May 2016 to April 2018 and spatial data of various environmental factors, including natural and anthropogenic factors, were collected. We evaluated the relative contribution of the environmental variables on the number of dead pine trees by PWD. In this study, among the 17 natural and anthropogenic factors, the factors affecting the occurrence of dead trees by PWD were verified. The results showed that altitude and temperature from May to August, among natural factors, and distance to building and forest road among anthropogenic factors were the most influential factors on the occurrence of PWD.

• Journal of Korean Society of Water and Wastewater
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• v.35 no.6
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• pp.389-403
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• 2021

In this study, dual drainage system based runoff model was established for W-drainage area in G-si, and considering the various rainfall characteristics determined using Huff and Mononobe methods, the degree of flooding in the target area was analyzed and the risk was compared and analyzed through the risk matrix method. As a result, the Monobe method compared to the Huff method was analyzed to be suitable analysis for flooding of recent heavy rain, and the validity of the dynamic risk assessment considering the weight of the occurrence probability as the return period was verified through the risk matrix-based analysis. However, since the definition and estimating criteria of the flood risk matrix proposed in this study are based on the return period for extreme rainfall and the depth of flooding according to the results of applying the dual drainage model, there is a limitation in that it is difficult to consider the main factors which are direct impact on inland flooding such as city maintenance and life protection functions. In the future, if various factors affecting inland flood damage are reflected in addition to the amount of flood damage, the flood risk matrix concept proposed in this study can be used as basic information for preparation and prevention of inland flooding, as well as it is judged that it can be considered as a major evaluation item in the selection of the priority management area for sewage maintenance for countermeasures against inland flooding.

• Korean Journal of Remote Sensing
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• v.38 no.1
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• pp.73-82
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• 2022

Marine fisheries resources face major anthropogenic threat from unregulated fishing activities; thus require precise detection for protection through marine surveillance. Korea developed an efficient land-based small fishing vessel monitoring system using real-time V-Pass data. However, those data directly do not provide information on fishing activities, thus further efforts are necessary to differentiate their activity status. In Korea, especially in Busan, longlining is practiced by many small fishing vessels to catch several types of fishes that need to be identified for proper monitoring. Therefore, in this study we have improved the existing fishing status classification method by applying Hidden Markov Model (HMM) on V-Pass data in order to further classify their fishing status into three groups, viz. non-fishing, longlining and other types of fishing. Data from 206 fishing vessels at Busan on 05 February, 2021 were used for this purpose. Two tiered HMM was applied that first differentiates non-fishing status from the fishing status, and finally classifies that fishing status into longlining and other types of fishing. Data from 193 and 13 ships were used as training and test datasets, respectively. Using this model 90.45% accuracy in classifying into fishing and non-fishing status and 88.23% overall accuracy in classifying all into three types of fishing statuses were achieved. Thus, this method is recommended for monitoring the activities of small fishing vessels equipped with V-Pass, especially for detecting longlining.

• Journal of the Korea Convergence Society
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• v.13 no.4
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• pp.25-37
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• 2022

The government and private companies are endeavoring to help the digital healthcare industry grow. This includes easing regulations on the big data industry such as the amendment of the Data 3 Act. Despite these efforts, however, there have been constant demands for the amendment of laws related to the medical field and for securing medical data transmissions. In this paper, the Data 3 Act of Korea and the legal system related to healthcare are examined. Then the legal, institutional, and technical aspects of the strategies are compared to understand the issues and implications. Based on this, a legal and institutional strategy suitable for the digital healthcare industry in Korea is suggested. Additionally, a direction to improve social perception along with technical measures such as safe de-identification processing and data transmission are also proposed. This study hopes to contribute to the spread of various convergent industries along with the digital healthcare industry.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.6_2
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• pp.699-706
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• 2021

Existing license plate recognition system is used as an optical character recognition method, but a method of using deep learning has been proposed in recent studies because it has problems with image quality and Korean misrecognition. This requires a lot of data collection, but the collection of license plates is not easy to collect due to the problem of the Personal Information Protection Act, and labeling work to designate the location of individual license plates is required, but it also requires a lot of time. Therefore, in this paper, to solve this problem, five types of license plates were created using a virtual Korean license plate generation program according to the notice of the Ministry of Land, Infrastructure and Transport. And the generated license plate is synthesized in the license plate part of collectable vehicle images to construct 10,147 learning data to be used in deep learning. The learning data classifies license plates, Korean, and numbers into individual classes and learn using YOLOv5. Since the proposed method recognizes letters and numbers individually, if the font does not change, it can be recognized even if the license plate standard changes or the number of characters increases. As a result of the experiment, an accuracy of 96.82% was obtained, and it can be applied not only to the learned license plate but also to new types of license plates such as new license plates and eco-friendly license plates.