• Journal of the Korean Recycled Construction Resources Institute
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• v.1 no.1
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• pp.8-16
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• 2013

Currently, global warming has advanced by the usage of fossil fuels such as coal and petroleum. and the atmosphere temperature in the world of 100 years(1906~2005) has been risen $0.74^{\circ}C{\pm}0.18^{\circ}C$, IPCC announced that the global warming effect of last decade was nearly doubled compared to the changes($0.07^{\circ}C{\pm}0.02^{\circ}C$/10year) in the past 100 years. Moreover, due to the global warming, heat wave, heavy snow, heavy rain, super typhoon, were caused and are increasing to happen in the world continuously causing damages and destruction of social infrastructures, where concrete structures are suffering deterioration by long-term extreme climate changes. to solve these problems, the new construction technology and codes are necessary. In this study, to solve these problems, experiments on a variety of cases considering the temperature and humidity, the main factors of climate factors, were performed, and the cases are decided by temperature and humidity. The specimens were tested in compressive strength test and split tensile test by the curing age(3,7,28 days) morever, performance based design(PBD) method was applied by using the satisfaction curve developed from the experiment date. PBD is the design method that gathers the current experimental analysis and past experimental analysis and develops the material properties required for the structure, and carries out the design of concrete mix, and it is recently studied actively worldwide. Also, it is the ultimate goal of PBD to design and perform on structures have sufficient performance during usage and to provide the problem solving for various situations, Also, it can achieve maximum effect in terms of functionality and economy.

• 한국지구물리탐사학회:학술대회논문집
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• 2000.09a
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• pp.54-69
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• 2000

There are groundwater trouble by high-salinity yield inducing sea-water intrusion in Cheju Island. It is used groundwater-GIS(Well-lnfo) in the maintenance and management of groundwater in Cheju Island to grasp groundwater trouble area and cause of high-salinity yield. For 16 wells certain to yield high-salinity, we logged specific electrical conductivity(EC) and tried to get hold of freshwater and saltwater relationship. As result of distribution of $Cl^-$ by depth, it is showed up groundwater trouble by high-salinity yield in the east coastal area and the partly north coastal area. The reason of high-salinity groundwater yield are low-groundwater level by the structure of geology and low-hydraulic gradient etc. There is necessity for management to development and use of groundwater in the high-salinity area, special management area.

• Journal of the Korean Institute of Landscape Architecture
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• v.45 no.1
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• pp.105-116
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• 2017

Murals in villages revitalize communities and spaces, and are economically efficient. Central and local governments are therefore actively undertaking Mural Village Projects but there are some issues and concerns about the projects for the provision of uniformed landscapes for the regions that are the result of a short-term completion of projects, and instead of cohesion, cause destruction of place identities. In addition, the problem of sustainable landscape management that is the result of low community involvement can be pointed out because the murals are products of government-led projects. The study covered the context of landscape and space change processes from a critical perspective, and focused on Ihwa-dong Mural Village, which is considered the first mural village in Korea and has begun to undergo drastic changes due to attention received from media. The purposes of this study are as follows. First, the study provides data about difference of place identity perception and landscape preference between residents and tourists in Ihwa-dong Mural Village. Second, this paper evaluates the current Mural Village Projects and finds alternative directions to improve the projects by using these data. This paper analyzed tourist hot spots in Ihwa-dong Mural Village by using SNS analysis, a field study and focus group interviews. The difference of place identity perception and landscape preference was examined among three groups: residents, new residents who are invited by Mural Village Projects, and tourists. This study showed that many tourists are focused on landscape areas that were not intentionally constructed projects. In addition, the locations of preferred landscapes and stores overlapped. Meanwhile, using qualitative data analysis, it was found that residents perceived the area as being an under-privileged location, while the murals, a non-daily landscape, largely affected place identity perception of new residents and tourists. For landscape preference, tourists preferred outdoor rest areas, while new residents and residents preferred less. Additionally, new residents and tourists preferred an area's night view while residents made no mention of this. Related to the direction of the projects, three groups showed their dependence on the government. This empirical study is significant from a participatory design perspective and in analyzing the issues for mural villages' landscapes, which are spreading across the nation and proceeding without criticism in urban regeneration. Implications for urban planners and suggestions for the future projects are given.

• Korea journal of population studies
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• v.29 no.1
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• pp.185-207
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• 2006

Predominant explanations of the persistence of sex segregation ill occupations link job choices to profoundly gendered responses to childbearing and other family demands, arguing that women are more likely to seek jobs which are in some sense compatible with motherhood, either because they are family friendly (flexible, low intensity work) or because they are easy to exit and re-enter. In this paper, I examine the effect of occupational sex segregation on job exits into the labor market among women, with a special attention to the role of childbearing and child rearing. I use data from detailed employment histories gathered from the National Longitudinal Survey of Youth (NLSY) in continuous time event history models. My results indicate that women in female dominated jobs are less likely to exit their jobs than women in other types of occupations. Further this relationship is not shaped by motherhood. While mothers or pregnant women are more likely to leave work, mothers in female-dominated occupations are slightly less likely to leave employment than mothers in other occupations. These results are not consistent with the ideas that women's choice of female-dominated occupations expresses a gendered identity and women strategically seek jobs which accommodate maternal roles. Taken together, my findings do not provide support to the idea that women choose female-dominated occupations because they are easier to integrate with motherhood (except for the pregnancy period).

• Spatial Information Research
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• v.6 no.2
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• pp.133-152
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• 1998

This article considers the experimental foundations of geographical phenomena for the distribution of lodging houses and the development of lodging Information Systems in Shin-Chon Area. This system allows the rural students to find their lodging houses conveniently. We examine the geographical reality of lodging houses in Shin-chon area and explores the lodging information system, reflecting how students select the lodging houses. Criteria for selection of lodging houses are travel time to school, interior facilities, rent fee, members, owners of lodging houses, which are collected by field swvey. The lodging information system is built in integration of Visual Basic with spatial data which are created in Mapinfo and Arcview through MapObject, component GIS software. This system provide query tools to efficiently investigate data as well as interactive map display. Also it displays the characteristics of a selected lodging houses using the identify tool on the map.

• 한국지구물리탐사학회:학술대회논문집
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• 1999.08a
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• pp.137-155
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• 1999

Recently, Televiewer(Borehole Acoustic Scanner(Televiewer)) has come to be widely used specially for the general engineering construction design. The Televiewer tool using a focussed acoustic beam is to detect the amplitude and traveltime of each reflected acoustic signal at the wall, resulting in the amplitude- and traveltime image respectively. Fractures can be well detected, because they easily scatter the acoustic energy due to the highly narrow beam. In addition, the drilling work will rough the borehole wall so that the acoustic energy can be scattered simply due to the roughness of the wall. Thus, the amplitude level can be directed associated with the elastic properties(impedance) and the hardness of the rock as well. Meanwhile, the traveltime image provides an information about the borehole shape and can be converted to a high precision 3D caliper log(max. 288 arms). In this paper, based on the high resolution of Televiewer images, general evaluation methods are illustrated to derive very reliable rock parameters.

• Journal of radiological science and technology
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• v.40 no.4
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• pp.647-655
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• 2017

This study was conducted to review the mediating effects of retirement preparation in how the degree of requirements for retirement education and the degree of preparation for retirement education affects quality of life, and how the degree of participation in retirement education which is a moderating variable is moderated. The study findings show that first, in terms of the difference in quality of life across different general characteristics, those who live in a city rather than a Gun, those who had received education of graduate school or higher rather than those with an education of undergraduate university programs or lower, those who were public officers or employees of corporations rather than those who were self-employed had a higher quality of life. The group satisfied with their economic status and health status were found to be more satisfied with their quality of life. Second, a correlation analysis showed that there was a positive correlation between retirement preparation, quality of life, and degree of requirements for retirement preparation. Moreover, there was also a positive correlation between quality of life, retirement education and the degree of requirements for retirement education. There was a positive correlation between retirement education and the degree of requirements for retirement preparation. Third, participation in retirement education moderated the indirect effect that the degree of preparation for retirement education affected quality of life through the degree of retirement preparation. In other words, the degree of requirements for retirement education affects retirement preparation and affects quality of life through the indirect effects of retirement education. As such, the moderated mediating effects of retirement education on retirement preparation was found to be greater. This indicates that quality of life may also vary in accordance with the requirements for retirement education.

• Korean Journal of Soil Science and Fertilizer
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• v.36 no.3
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• pp.163-179
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• 2003

Multifunctionality of agriculture which is not traded on the market now has been an important international issue in that it environmental and public benefits. We carried out to modify and to update the function of upland farming on flood prevention and fostering water resources. Economic values of environmental benefits were evaluated by replacement cost methods. Models to evaluate the function of preventing flood were selected as: (1)precipitation(flood-inducing) - runoff(A), (2) soil depth ${\times}$ soil air phase, (3) precipitation (flood-inducing) - runoff(B), (4) soil depth ${\times}$ effective porosity of soil. Models to estimate the function of fostering water resources were (1) saturated hydraulic conductivity (Ks) ${\times}$ duration of saturation(days) ${\times}$ (1-ratio of water flow directly into river), (2) precipitation ${\times}$ ratio of water fostered by rain resources ${\times}$ (area of upland/total land area), and (3) soil water retention quantity(under standing crop or tree) - SWRQ(in bare soil). Function of preventing flood was $883Mg\;ha^{-1}$ of water per year and 645 million Mg for the whole upland area. Function of fostering water resources was $94.1Mg\;ha^{-1}$ of water per year and 69 million Mg for the whole upland area. The value of flood-preventing function evaluated by replacement cost methods was estimated 1,428 billion won per year as compared to the cost for dam construction. The value of water resource fostering were estimated 8.6 billion won in the price of living water.

• Journal of the Korean Society for information Management
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• v.38 no.3
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• pp.23-39
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• 2021

This study aims to explore research trends in Blockchain studies in South Korea using dynamic topic modeling and network analysis. To achieve this goal, we conducted the university & institute collaboration network analysis, the keyword co-occurrence network analysis, and times series topic analysis using dynamic topic modeling. Through the university & institute collaboration network analysis, we found major universities such as Soongsil University, Soonchunhyang University, Korea University, Korea Advanced Institute of Science and Technology (KAIST) and major institutes such as Ministry of National Defense, Korea Railroad Research Institute, Samil PricewaterhouseCoopers, Electronics and Telecommunications Research Institute that led collaborative research. Next, through the analysis of the keyword co-occurrence network, we found major research keywords including virtual assets (Cryptocurrency, Bitcoin, Ethereum, Virtual currency), blockchain technology (Distributed ledger, Distributed ledger technology), finance (Smart contract), and information security (Security, privacy, Personal information). Smart contracts showed the highest scores in all network centrality measures showing its importance in the field. Finally, through the time series topic analysis, we identified five major topics including blockchain technology, blockchain ecosystem, blockchain application 1 (trade, online voting, real estate), blockchain application 2 (food, tourism, distribution, media), and blockchain application 3 (economy, finance). Changes of topics were also investigated by exploring proportions of representative keywords for each topic. The study is the first of its kind to attempt to conduct university & institute collaboration networks analysis and dynamic topic modeling-based times series topic analysis for exploring research trends in Blockchain studies in South Korea. Our results can be used by government agencies, universities, and research institutes to develop effective strategies of promoting university & institutes collaboration and interdisciplinary research in the field.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.1-17
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• 2019

Because stock price forecasting is an important issue both academically and practically, research in stock price prediction has been actively conducted. The stock price forecasting research is classified into using structured data and using unstructured data. With structured data such as historical stock price and financial statements, past studies usually used technical analysis approach and fundamental analysis. In the big data era, the amount of information has rapidly increased, and the artificial intelligence methodology that can find meaning by quantifying string information, which is an unstructured data that takes up a large amount of information, has developed rapidly. With these developments, many attempts with unstructured data are being made to predict stock prices through online news by applying text mining to stock price forecasts. The stock price prediction methodology adopted in many papers is to forecast stock prices with the news of the target companies to be forecasted. However, according to previous research, not only news of a target company affects its stock price, but news of companies that are related to the company can also affect the stock price. However, finding a highly relevant company is not easy because of the market-wide impact and random signs. Thus, existing studies have found highly relevant companies based primarily on pre-determined international industry classification standards. However, according to recent research, global industry classification standard has different homogeneity within the sectors, and it leads to a limitation that forecasting stock prices by taking them all together without considering only relevant companies can adversely affect predictive performance. To overcome the limitation, we first used random matrix theory with text mining for stock prediction. Wherever the dimension of data is large, the classical limit theorems are no longer suitable, because the statistical efficiency will be reduced. Therefore, a simple correlation analysis in the financial market does not mean the true correlation. To solve the issue, we adopt random matrix theory, which is mainly used in econophysics, to remove market-wide effects and random signals and find a true correlation between companies. With the true correlation, we perform cluster analysis to find relevant companies. Also, based on the clustering analysis, we used multiple kernel learning algorithm, which is an ensemble of support vector machine to incorporate the effects of the target firm and its relevant firms simultaneously. Each kernel was assigned to predict stock prices with features of financial news of the target firm and its relevant firms. The results of this study are as follows. The results of this paper are as follows. (1) Following the existing research flow, we confirmed that it is an effective way to forecast stock prices using news from relevant companies. (2) When looking for a relevant company, looking for it in the wrong way can lower AI prediction performance. (3) The proposed approach with random matrix theory shows better performance than previous studies if cluster analysis is performed based on the true correlation by removing market-wide effects and random signals. The contribution of this study is as follows. First, this study shows that random matrix theory, which is used mainly in economic physics, can be combined with artificial intelligence to produce good methodologies. This suggests that it is important not only to develop AI algorithms but also to adopt physics theory. This extends the existing research that presented the methodology by integrating artificial intelligence with complex system theory through transfer entropy. Second, this study stressed that finding the right companies in the stock market is an important issue. This suggests that it is not only important to study artificial intelligence algorithms, but how to theoretically adjust the input values. Third, we confirmed that firms classified as Global Industrial Classification Standard (GICS) might have low relevance and suggested it is necessary to theoretically define the relevance rather than simply finding it in the GICS.