• The Journal of the Korea Contents Association
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• v.14 no.9
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• pp.582-588
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• 2014

The purpose of this study is to analyze how a joint research network between countries affects the diffusion of technology information and how much countries with high centrality on the network accept new technology and to seek their meaning. With this aim, the joint research network density between countries by year and the number of participating countries were measured using thesis information regarding the secondary battery field and the electric vehicle field, and a regression analysis of relevant variables was conducted. As a result of the analysis, the greater the joint research network density in the secondary battery field, the higher the number of participating countries in a linear relationship. Also, on the joint research network, countries with high degree centrality were discovered to have led development in the mid to large size secondary battery field. Meanwhile, for the electric vehicle field, although there appeared no increase in the network density value, the number of participating countries was found to have increased. This was analyzed that joint research between countries was not a necessary and sufficient condition although it played a crucial role in promoting technology diffusion. Such a result is meaningful in that it verified promoting factors for essential technology diffusion statistically; however, with this research, there exist limitations that the index of a central role on the network was measured only with degree centrality and that only the relationship between two players was measured for network density in interactions between players. Accordingly, it is necessary to carry out research into a method to measure interactions among multiple researchers in the future.

• Journal of the Korea institute for structural maintenance and inspection
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• v.18 no.6
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• pp.90-96
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• 2014

The electrical resistivity of concrete can be related to two processes involved in corrosion of reinforcement: initiation (chloride penetration) and propagation (corrosion rate). The resisistivity of concrete structure exposed to chloride indicates the risk of early corrosion damage, because a low resistivity is related to rapid chloride penetration and to high corrosion rate. Concrete resistivity is a geometry-independent material property that describes the electrical resistance, which is the ratio between applied voltage and resulting current in a unit cell. In previous study, it was realized that the resistivity of concrete depended on the moisture content in the concrete, microstructural properties, and environmental attack such as carbonation. The current is carried by ions dissolved in the pore liquid. While some data exist on the relationship between moisture content on electrical resistivity of concrete, very little research has been conducted to evaluate the effect of chloride on the conduction of electricity through concrete. The purpose of this study is to examine and quantify the effect of chloride content on surface electrical resistivity measurement of concrete. It was obvious that chloride content had influenced the resistivity of concrete and the relationship showed a linear function. That is, concrete with chloride ions had a comparatively lower resistivity. Decreasing rate of resistivity of concrete was clear at early time, however, after 50 days resistivity was constant irrespective of chloride concentration. Conclusively, this paper suggested the quantitive solution to depict the electrical resistivity of concrete with chloride content.

• Journal of the Mineralogical Society of Korea
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• v.30 no.1
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• pp.31-43
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• 2017

This study investigated mineralogy, spectral characteristics and heavy metal contamination including Cd, Ni, Al, Fe, Mn and S for white precipitation in Miin falls based on XRF, XRD, and spectrometer. As a result, Al concentration was abnormally high at all samples, and most of the samples showed high contamination level in Cd and Ni. XRD results detected quartz, kaolinite, rhomboclase, aluminocoquimbite, and gibbsite which infers that heavy metal elements are distributed by adsorption with clay minerals. Spectral characteristics of white precipitation can be described by increasing pattern of reflectance in visible spectrum and decreasing pattern of reflectance in longer wave length including near infrared and shortwave infrared spectrum. The absorption features reveals that spectral characteristics of white precipitation is mainly controlled by kaolinite, rhomboclase, aluminocoquimbite, and gibbsite. The relationship between heavy metal concentration and absorption depth showed high positive correlation for Al concentration and absorption feature at 2202 nm of Al-OH absorption. This spectral characteristics indicates that absorption depth could be effectively used for estimation of heavy metal concentration.

• Journal of the Economic Geographical Society of Korea
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• v.12 no.4
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• pp.521-539
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• 2009

This study investigates the time-space characteristics of the road traffic flows in Seoul and the relationship with land use patterns. For the purpose, we analyze the road traffic data collected at 118 observation sites over Seoul City area since 1993. We examine the time-trend of the annual average traffic flows per day during the last fourteen years. Three different trends are revealed: rapid increase during the time period between 1993 and 1997, maintenance same level after sharp decrease between year 1997 and 1998, and gradual decrease after sharp decrease between year 2003 and 2004. The spatial distribution patterns of road traffic flows have also been changed significantly during the period. The traffic flows in the urban center have been declined gradually, while the traffic flows in the boundary area and southern CBDs have increased dramatically. In order to examine the relationship with the changes in the land-use patterns and road traffic flows, we analyze the changes in the spatial distribution patterns of population and industries. We developed three multiple linear regression models to test the relationships between the changes in the land-use variables and road traffic flows.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.20 no.6
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• pp.564-574
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• 2008

This study investigates a long-term variation of annual maximum surge heights(AMSH) and main characteristics of high surge events, which is influenced by the global warming and intensifying typhoons, using sea level data at Sokcho and Mukho tidal stations over 34 years ($1974{\sim}2007$). It is found that the there is a longterm uptrend of the AMSH at Sokcho (8.3 cm/34yrs) and at Mukho (8.7 cm/34yrs), which is significant within 95% confidence level based on the linear regression. The statistical analysis reveals that 53% of the AMSH occurs during typhoon's event in both tidal stations and the highest surge records are mostly produced by the typhoon. It is concluded that the uptrend in the AMSH is attributed by the increasing typhoon activities globally as well as locally in Korea due to the increased sea surface temperature in tropical oceans. The continuous efforts monitering and predicting the extreme surge events in the future warm environments are required to prevent the growing storm surge damage by the intensified typhoon.

• 한국사회정책
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• v.25 no.4
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• pp.71-104
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• 2018

This paper adopts a distributive performance process model of in-work poverty based on labor markets, households, and welfare states and analyzes the 4-11 waves of the Korean Welfare Panel Study during 2008-15. Previous studies on in-work poverty have focused on the definitions and concepts of in-work poverty by analyzing employment and unemployment persistence and repetition dynamics, but rarely paid attention to institutional distributive performance. In this regard, this study preforms a stepwise analysis of labor markets, households, and welfare states as a process of income generation in labor markets, satisfaction of welfare needs and income pooling at households, and deduction of social security contribution and income tax as well as receipt of public transfer income at welfare states. Results of empirical analysis show that in-work poverty had been on increase during 2008-11, followed by a decrease between 2012-15. At labor market stages, full time status had the most prominent impact on in-work poverty process, while status by employment and contract type have generated a huge variation as well. At household stages, household work intensity and number of earners contributed to reduction of in-work poverty, but the relations did not seen to be straightforward. However, welfare state played little role in lifting employees out of in-work poverty. In terms of institutional distributive process, in-work poverty was prevalent in either household-welfare state stage or labor market-household-welfare stage. Non-vulnerable group in terms of in-risk poverty was around 80% of the sample during the period of analysis, the size of which has remained constant.

• Journal of Climate Change Research
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• v.4 no.2
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• pp.95-104
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• 2013

Average cumulative precipitation in summer have increased by 350 mm compared with 1980s. As precipitation is expected to increase, the risk of landslides by heavy rainfall also is expected to rise. Therefore, establishment of adaptation plan for landslides is urgently needed. In 2011, Korea Ministry of Environment(KME) conducted vulnerability assessment to support establishment of adaptation plan for local governments. However, the result of vulnerability assessment had three limitations. First, KME didn't use standard scenario of Korea Meteorological Administration(KMA). Second, They conducted same standardization method for all variables. Third, They derived relative vulnerability which is not quantitative. The purpose of this study is to improve the limitations of existing vulnerability assessment and identify quantitative criteria to ensure scientific reliability. To achieve this purpose, we carried out three ways of advancement. First, application of new climate scenario, which is RCP 8.5 from KMA. Second, improvement of variables of vulnerability assessment. Third, derivation of quantitative criteria of vulnerability. The findings can support establishment of adaptation plan for local governments more effectively.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.3
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• pp.347-362
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• 2019

Underground excavation using TBM machines has been increasing to reduce complaints caused by noise, vibration, and traffic congestion resulted from the urban underground construction in Korea. However, TBM excavation design and construction still need improvement because those are based on standards of the technologically advanced countries (e.g., Japan, Germany) that do not consider geological environment in Korea at all. Above all, although TBM performance is a main factor determining the TBM machine type, duration and cost of the construction, it is estimated by only using UCS (uniaxial compressive strength) as the ground parameters and it often does not match the actual field conditions. This study was carried out as part of efforts to predict penetration rate suitable for Korean ground conditions. The effective parameters were defined through the correlation analysis between the penetration rate and the geotechnical parameters or TBM performance parameters. The effective parameters were then used as variables of the multiple regression analysis to derive a regression model for predicting TBM penetration rate. As a result, the regression model was estimated by UCS and joint spacing and showed a good agreement with field penetration rate measured during TBM excavation. However, when this model was applied to another site in Korea, the prediction accuracy was slightly reduced. Therefore, in order to overcome the limitation of the regression model, further studies are required to obtain a generalized prediction model which is not restricted by the field conditions.

• Journal of the Korean Society of Urban Environment
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• v.18 no.4
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• pp.547-555
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• 2018

In addition to North America and Europe, Korea is also responding to the toxic damage caused by the production and distribution of chemicals. Methods for assessing bio-toxicity of harmful substances have been widely introduced, but it is required of quantitative and speedy information for modeling. For 6 heavy metals, as zinc, copper, chrome, cadmium, mercury and lead, bio-toxicity assessment and kinetics model were constructed using Vibrio fischeri which is widely used luminous bacteria. The degree of luminescence activity and the toxicity of heavy metals were relative limunescence unit, RLU measured as by using a photomultiplier embedded device. The toxicity was assessed by the concentration levels giving under 20% lethality and lethal concentration, $EC_{50}$. In the results, the toxicity order were followed from mercury, lead, copper, chrome, zinc and cadmium. $EC_{{50},{\infty}}$ obtained by trends of $EC_{50}$ by time follows had highly linear agreement with main parameters of bio-toxicity modelling. The average error rates of the reproduced lethality obtained from DAM and TDM model on the basis of body residue, were 10.2% for mercury, lead, copper, chrome and 20.0 for the all 6 methals.

• Journal of Internet Computing and Services
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• v.23 no.4
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• pp.21-33
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• 2022

Recently, the recommender system has been widely used in various fields such as movies, music, online shopping, and social media, and in the meantime, the recommender model has been developed from correlation analysis through the Apriori model, which can be said to be the first-generation model in the recommender system field. In 2005, many models have been proposed, including deep learning-based models, which are receiving a lot of attention within the recommender model. The recommender model can be classified into a collaborative filtering method, a content-based method, and a hybrid method that uses these two methods integrally. However, these basic methods are gradually losing their status as methodologies in the field as they fail to adapt to internal and external changing factors such as the rapidly changing user-item interaction and the development of big data. On the other hand, the importance of deep learning methodologies in recommender systems is increasing because of its advantages such as nonlinear transformation, representation learning, sequence modeling, and flexibility. In this paper, among deep learning methodologies, RNN, CNN, and GAN-based models suitable for sequential modeling that can accurately and flexibly analyze user-item interactions are classified, compared, and analyzed.