• Tunnel and Underground Space
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• v.31 no.6
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• pp.400-414
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• 2021

Under high-level radioactive waste repository conditions, bentonite as an engineered barrier material undergoes thermal, hydrological, mechanical, and chemical processes. We report the applications of X-ray Computed Tomography (CT) imaging technique on the characterization and analysis of bentonite over the past decade to provide a reference of the utilization of this technique and the recent research trends. This overview of the X-ray CT technique applications includes the characterization of the bentonite either in pellets or powder form. X-ray imaging has provided a means to extract grain information at the microscale and identify crack networks responsible for the pellets' heterogeneity. Regarding samples of pellets-powder mixtures under hydration, X-ray CT allowed the identification and monitoring of heterogeneous zones throughout the test. Some results showed how zones with pellets only swell faster compared to others composed of pellets and powder. Moreover, the behavior of fissures between grains and bentonite matrix was observed to change under drying and hydrating conditions, tending to close during the former and open during the latter. The development of specializing software has allowed obtaining strain fields from a sequence of images. In more recent works, X-ray CT technique has served to estimate the dry density, water content, and particle displacement at different testing times. Also, when temperature was added to the hydration process of a sample, CT technology offered a way to observe localized and global density changes over time.

• Journal of Christian Education in Korea
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• v.68
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• pp.11-40
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• 2021

The coronavirus pandemic has brought about significant negative changes in our society to the point where it has to be divided into 'Before Corona'(BC) and 'After Corona'(AC). Typical examples include economic difficulties and medical inequality of some social excluded groups as well as individuals who die alone because they are alienated from social networks, and hate and violent discrimination against Asian immigrants, which are rapidly increasing in Western countries in these days. In addition, the pandemic is at a global level, ranging from the vaccine gap between the first and third worlds, triggered by competition for securing vaccines between countries that put their own interests first, the income gap due to changes in the economic environment and financial market, and the bankruptcy of individuals and corporations. In 'all'(pan) and 'people'(demos) became a limit situation that could not be avoided. There is also the opinion that the world could witness the worst catastrophe if the pandemic spreads to poor countries at risk of increasing violence, poverty and famine. The purpose of this paper is to examine the changes in society caused by the Coronavirus pandemic and to suggest the direction of Christian education accordingly. To this end, this paper analyzes the medical, economic, and psychological crises that society faces in the post-corona era. Next, we look at the changes in Christian theology, mission, and worship, which are strongly required for fundamental changes in the context of the pandemic. Based on the above discussion, we propose a new direction for Christian education necessary in the post-corona era.

• Smart Media Journal
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• v.11 no.1
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• pp.67-80
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• 2022

Smart City Technology, which is significant in the era of the 4th industrial revolution, greatly increases the efficiency and productivity of cities nowadays. The purpose of this study is to present a strategic approach for industrial revitalization and overseas export by analyzing the current status of smart city-related companies and discovering high-priority smart city technologies. To this end, the smart city theory and ASEAN smart city were reviewed through prior research, and a survey of companies with domestic smart city technology was conducted. As a result of the survey, it is revealed that companies with smart city technology in Korea are highly willing to export to ASEAN countries. There is a strong desire to export the following technologies: construction, traffic, green·energy, etc. And there was a high willingness to export the following services: IoT, platform, AI, etc. The following solutions have been proposed as solutions to Strategic Plans to Promote the Export: 1) Deregulation and incentives, 2) Global human resource development, 3) Information provision and strengthening of local networks, 4) Financial and public relations support.

• The Journal of Bigdata
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• v.7 no.1
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• pp.173-185
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• 2022

Nowadays, Korean webtoons are leading the global digital comic market. Webtoons are being serviced in various languages around the world, and dramas or movies produced with Webtoons' IP (Intellectual Property Rights) have become a big hit, and more and more webtoons are being visualized. However, with the success of these webtoons, the working environment of webtoon creators is emerging as an important issue. According to the 2021 Cartoon User Survey, webtoon creators spend 10.5 hours a day on creative activities on average. Creators have to draw large amount of pictures every week, and competition among webtoons is getting fiercer, and the amount of paintings that creators have to draw per episode is increasing. Therefore, this study proposes to generate webtoon background images using deep learning algorithms and use them for webtoon production. The main character in webtoon is an area that needs much of the originality of the creator, but the background picture is relatively repetitive and does not require originality, so it can be useful for webtoon production if it can create a background picture similar to the creator's drawing style. Background generation uses CycleGAN, which shows good performance in image-to-image translation, and CartoonGAN, which is specialized in the Cartoon style image generation. This deep learning-based image generation is expected to shorten the working hours of creators in an excessive work environment and contribute to the convergence of webtoons and technologies.

• 한국균학회소식:학술대회논문집
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• 2015.05a
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• pp.59-59
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• 2015

Cryptococcus neoformans causes life-threatening meningoencephalitis in humans, but the treatment of cryptococcosis remains challenging. To develop novel therapeutic targets and approaches, signaling cascades controlling pathogenicity of C. neoformans have been extensively studied but the underlying biological regulatory circuits remain elusive, particularly due to the presence of an evolutionarily divergent set of transcription factors (TFs) in this basidiomycetous fungus. In this study, we constructed a high-quality of 322 signature-tagged gene deletion strains for 155 putative TF genes, which were previously predicted using the DNA-binding domain TF database (http://www.transcriptionfactor.org/). We tested in vivo and in vitro phenotypic traits under 32 distinct growth conditions using 322 TF gene deletion strains. At least one phenotypic trait was exhibited by 145 out of 155 TF mutants (93%) and approximately 85% of the TFs (132/155) have been functionally characterized for the first time in this study. Through high-coverage phenome analysis, we discovered myriad novel TFs that play critical roles in growth, differentiation, virulence-factor (melanin, capsule, and urease) formation, stress responses, antifungal drug resistance, and virulence. Large-scale virulence and infectivity assays in insect (Galleria mellonella) and mouse host models identified 34 novel TFs that are critical for pathogenicity. The genotypic and phenotypic data for each TF are available in the C. neoformans TF phenome database (http://tf.cryptococcus.org). In conclusion, our phenome-based functional analysis of the C. neoformans TF mutant library provides key insights into transcriptional networks of basidiomycetous fungi and ubiquitous human fungal pathogens.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.11 no.3
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• pp.1-15
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• 2016

This study has analyzed predication capabilities leveraging multi-variate model, logistic regression model, and artificial neural network model based on financial information of medium-small sized companies list in KOSDAQ. 83 delisted companies from 2009 to 2012 and 83 normal companies, i.e. 166 firms in total were sampled for the analysis. Modelling with training data was mobilized for 100 companies inlcuding 50 delisted ones and 50 normal ones at random out of the 166 companies. The rest of samples, 66 companies, were used to verify accuracies of the models. Each model was designed by carrying out T-test with 79 financial ratios for the last 5 years and identifying 9 significant variables. T-test has shown that financial profitability variables were major variables to predict a financial risk at an early stage, and financial stability variables and financial cashflow variables were identified as additional significant variables at a later stage of insolvency. When predication capabilities of the models were compared, for training data, a logistic regression model exhibited the highest accuracy while for test data, the artificial neural networks model provided the most accurate results. There are differences between the previous researches and this study as follows. Firstly, this study considered a time-series aspect in light of the fact that failure proceeds gradually. Secondly, while previous studies constructed a multivariate discriminant model ignoring normality, this study has reviewed the regularity of the independent variables, and performed comparisons with the other models. Policy implications of this study is that the reliability for the disclosure documents is important because the simptoms of firm's fail woule be shown on financial statements according to this paper. Therefore institutional arragements for restraing moral laxity from accounting firms or its workers should be strengthened.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1107-1118
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• 2021

Climate change brought on by global warming increased the frequency of flood and drought on the Korean Peninsula, along with the casualties and physical damage resulting therefrom. Preparation and response to these water disasters requires national-level planning for water resource management. In addition, watershed-level management of water resources requires flow duration curves (FDC) derived from continuous data based on long-term observations. Traditionally, in water resource studies, physical rainfall-runoff models are widely used to generate duration curves. However, a number of recent studies explored the use of data-based deep learning techniques for runoff prediction. Physical models produce hydraulically and hydrologically reliable results. However, these models require a high level of understanding and may also take longer to operate. On the other hand, data-based deep-learning techniques offer the benefit if less input data requirement and shorter operation time. However, the relationship between input and output data is processed in a black box, making it impossible to consider hydraulic and hydrological characteristics. This study chose one from each category. For the physical model, this study calculated long-term data without missing data using parameter calibration of the Soil Water Assessment Tool (SWAT), a physical model tested for its applicability in Korea and other countries. The data was used as training data for the Long Short-Term Memory (LSTM) data-based deep learning technique. An anlysis of the time-series data fond that, during the calibration period (2017-18), the Nash-Sutcliffe Efficiency (NSE) and the determinanation coefficient for fit comparison were high at 0.04 and 0.03, respectively, indicating that the SWAT results are superior to the LSTM results. In addition, the annual time-series data from the models were sorted in the descending order, and the resulting flow duration curves were compared with the duration curves based on the observed flow, and the NSE for the SWAT and the LSTM models were 0.95 and 0.91, respectively, and the determination coefficients were 0.96 and 0.92, respectively. The findings indicate that both models yield good performance. Even though the LSTM requires improved simulation accuracy in the low flow sections, the LSTM appears to be widely applicable to calculating flow duration curves for large basins that require longer time for model development and operation due to vast data input, and non-measured basins with insufficient input data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.2
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• pp.279-292
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• 2018

Unlike the global art market which experienced rapid recovery from the impacts of the Global Financial Crisis in 2008, the Korean art market has not yet fully recovered. The gallery-oriented distribution system, vulnerable primary art market functions, and the market structure centered on a small number of collectors make it difficult for young and medium artists to enter the market and, as a result, deepen the economic polarization of artists. In addition, the high price of art works limits market participation by restricting the general public. This study began with the idea that the interest of the public in the art market as well as their participation in the market are urgent. To this end, we noted that public awareness of art transactions can be a starting point for improving the constitution of the fragile art market, focusing on the 'Artist-centered Art Fair' rather than existing art fairs. To examine the contribution of such an art fair to the popularization of the art market, we analyzed the case of the 'Visual Artist Market (VAM)' project of the Korea Arts Management Service. Results found that the 'Artist-centered Art Fair' focuses on providing opportunities for market entry to young and medium artists rather than on the interests of distributors, and promotes the popularization of the art market by promoting low-priced works to the general public. Also, the 'Artist-centered Art Fair' seems to play a primary role in the public sector to foster solid groups of artists as well as to establish healty distribution networks of Korean Art market. However, in the long run, it is necessary to promote sustainable development of the 'Artist-centered Art Fair' through indirect support, such as the provision of a publicity platform or consumer finance support, rather than direct support.

• The Journal of Industrial Distribution & Business
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• v.3 no.1
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• pp.7-16
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• 2012

Despite the enforcement of SSM control laws such as 'the Law of Developing the Distribution Industry (LDDI)' and 'the Law of Promoting Mutual Cooperation between Large and Small/medium Enterprises (LPMC)' stipulating the business adjustment system, the number of super-supermarkets (SSMs) has ever been expanding in Korea. In France, however, Super Centers are being regulated most strongly and directly in the whole Europe viewing that there is not a single SSM in Paris, which is emphasized to be the outcome from French government's regulation exerted on the opening of large scale retail stores. In France, the authority to approve store opening is deeply centralized and the store opening regulation is a socio-economic regulation driven by economic laws whereas EU strongly regulates the distribution industry. To control the French distribution industry, such seven laws and regulations as Commission départementale d'urbanisme commercial guidelines (CDLIC) (1969), the Royer Law (1973), the Doubin Law (1990), the Sapin Law (1993), the Raffarin Law (1996), solidarite et renouvellement urbains (SRU) (2000), and Loi de modernisation de l'économie (LME) (2009) have been promulgated one by one since the amendment of the Fontanet guidelines, through which commercial adjustment laws and regulations have been complemented and reinforced while regulatory measures have been taken. Even in the course of forming such strong regulatory laws, InterMarche, the largest supermarket chain in France, has been in existence as a global enterprise specialized in retail distribution with over 4,000 stores in Europe. InterMarche's business can be divided largely into two segments of food and non-food. As a supermarket chain, InterMarche's food segment has 2,300 stores in Europe and as a hard-discounter store chain in France, Netto has 420 stores. Restaumarch is a chain of traditional family restaurants and the steak house restaurant chain of Poivre Rouge has 4 restaurants currently. In addition, there are others like Ecomarche which is a supermarket chain for small and medium cities. In the non-food segment, the DIY and gardening chain of Bricomarche has a total of 620 stores in Europe. And the car-related chain of Roady has a total of 158 stores in Europe. There is the clothing chain of Veti as well. In view of InterMarche's management strategies, since its distribution strategy is to sell goods at cheap prices, buying goods cheap only is not enough. In other words, in order to sell goods cheap, it is all important to buy goods cheap, manage them cheap, systemize them cheap, and transport them cheap. In quality assurance, InterMarche has guaranteed the purchase safety for consumers by providing its own private brand products. InterMarche has 90 private brands of its own, thus being the retailer with the largest number of distributor brands in France. In view of its IT service strategy, InterMarche is utilizing a high performance IT system so as to obtainas much of the market information as possible and also to find out the best locations for opening stores. In its global expansion strategy of international alliance, InterMarche has established the ALDIS group together with the distribution enterprises of both Spain and Germany in order to expand its food purchase, whereas in the non-food segment, it has established the ARENA group in alliance with 11 international distribution enterprises. Such strategies of InterMarche have been intended to find out the consumer needs for both price and quality of goods and to secure the purchase and supply networks which are closely localized. It is necessary to cope promptly with the constantly changing circumstances through being unified with relevant regions and by providing diversified customer services as well. In view of the InterMarche's positive policy for promoting local partnerships as well as the assistance for enhancing the local economic structure, implications are existing for those retail distributors of our country.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.143-159
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• 2015

Predicting IT trends has been a long and important subject for information systems research. IT trend prediction makes it possible to acknowledge emerging eras of innovation and allocate budgets to prepare against rapidly changing technological trends. Towards the end of each year, various domestic and global organizations predict and announce IT trends for the following year. For example, Gartner Predicts 10 top IT trend during the next year, and these predictions affect IT and industry leaders and organization's basic assumptions about technology and the future of IT, but the accuracy of these reports are difficult to verify. Social media data can be useful tool to verify the accuracy. As social media services have gained in popularity, it is used in a variety of ways, from posting about personal daily life to keeping up to date with news and trends. In the recent years, rates of social media activity in Korea have reached unprecedented levels. Hundreds of millions of users now participate in online social networks and communicate with colleague and friends their opinions and thoughts. In particular, Twitter is currently the major micro blog service, it has an important function named 'tweets' which is to report their current thoughts and actions, comments on news and engage in discussions. For an analysis on IT trends, we chose Tweet data because not only it produces massive unstructured textual data in real time but also it serves as an influential channel for opinion leading on technology. Previous studies found that the tweet data provides useful information and detects the trend of society effectively, these studies also identifies that Twitter can track the issue faster than the other media, newspapers. Therefore, this study investigates how frequently the predicted IT trends for the following year announced by public organizations are mentioned on social network services like Twitter. IT trend predictions for 2013, announced near the end of 2012 from two domestic organizations, the National IT Industry Promotion Agency (NIPA) and the National Information Society Agency (NIA), were used as a basis for this research. The present study analyzes the Twitter data generated from Seoul (Korea) compared with the predictions of the two organizations to analyze the differences. Thus, Twitter data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. To overcome these challenges, we used SAS IRS (Information Retrieval Studio) developed by SAS to capture the trend in real-time processing big stream datasets of Twitter. The system offers a framework for crawling, normalizing, analyzing, indexing and searching tweet data. As a result, we have crawled the entire Twitter sphere in Seoul area and obtained 21,589 tweets in 2013 to review how frequently the IT trend topics announced by the two organizations were mentioned by the people in Seoul. The results shows that most IT trend predicted by NIPA and NIA were all frequently mentioned in Twitter except some topics such as 'new types of security threat', 'green IT', 'next generation semiconductor' since these topics non generalized compound words so they can be mentioned in Twitter with other words. To answer whether the IT trend tweets from Korea is related to the following year's IT trends in real world, we compared Twitter's trending topics with those in Nara Market, Korea's online e-Procurement system which is a nationwide web-based procurement system, dealing with whole procurement process of all public organizations in Korea. The correlation analysis show that Tweet frequencies on IT trending topics predicted by NIPA and NIA are significantly correlated with frequencies on IT topics mentioned in project announcements by Nara market in 2012 and 2013. The main contribution of our research can be found in the following aspects: i) the IT topic predictions announced by NIPA and NIA can provide an effective guideline to IT professionals and researchers in Korea who are looking for verified IT topic trends in the following topic, ii) researchers can use Twitter to get some useful ideas to detect and predict dynamic trends of technological and social issues.