• Journal of Korean Society of Coastal and Ocean Engineers
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• v.31 no.3
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• pp.158-169
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• 2019

A probabilistic model that can predict the residual useful lifetime of structure is formulated by using the gamma process which is one of the stochastic processes. The formulated stochastic model can take into account both the sampling uncertainty associated with damages measured up to now and the temporal uncertainty of cumulative damage over time. A method estimating several parameters of stochastic model is additionally proposed by introducing of the least square method and the method of moments, so that the age of a structure, the operational environment, and the evolution of damage with time can be considered. Some features related to the residual useful lifetime are firstly investigated into through the sensitivity analysis on parameters under a simple setting of single damage data measured at the current age. The stochastic model are then applied to the rubble-mound breakwater straightforwardly. The parameters of gamma process can be estimated for several experimental data on the damage processes of armor rocks of rubble-mound breakwater. The expected damage levels over time, which are numerically simulated with the estimated parameters, are in very good agreement with those from the flume testing. It has been found from various numerical calculations that the probabilities exceeding the failure limit are converged to the constraint that the model must be satisfied after lasting for a long time from now. Meanwhile, the expected residual useful lifetimes evaluated from the failure probabilities are seen to be different with respect to the behavior of damage history. As the coefficient of variation of cumulative damage is becoming large, in particular, it has been shown that the expected residual useful lifetimes have significant discrepancies from those of the deterministic regression model. This is mainly due to the effect of sampling and temporal uncertainties associated with damage, by which the first time to failure tends to be widely distributed. Therefore, the stochastic model presented in this paper for predicting the residual useful lifetime of structure can properly implement the probabilistic assessment on current damage state of structure as well as take account of the temporal uncertainty of future cumulative damage.

• Korean Journal of Environmental Biology
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• v.37 no.1
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• pp.19-30
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• 2019

To investigate the characteristics of seasonal environment and phytoplankton community structure in the coastal area of Dokdo, a survey of Dokdo around waters was conducted during the four seasons. Phytoplankton of 4 phylum 72 species in four seasons were collected in Dokdo around water. The seasonal mean abundance of phytoplankton were $3.32{\times}10^4cells\;L^{-1}$ in winter, $1.04{\times}10^4cells\;L^{-1}$ in spring, $0.28{\times}10^4cells\;L^{-1}$ in summer, and $4.86{\times}10^4cells\;L^{-1}$ in autumn in Dokdo around water. During winter, the diatoms Chaetoceros spp. had dominated. During spring, when the nutrients in the euphotic layer were depleted, the nano-flagellates and Cryptomonas appeared at surface layer. In summer, the abundance of phytoplankton was relatively low, which lead to occurrence of diatoms such as genus of Chaetoceros, Rhizosolenia, and Skeletonema. In autumn, Pseudo-nitzschia spp. was the most dominant species and tropical species such as Amphisolenia sp. and Ornithocercus magnificus were observed, implying that they may have introduced within warm water current such as Kurosiwo Current. Therefore, although natural phytoplankton communities in the vicinity water of Dokdo are mainly influenced by Tsushima Warm Current branched Kurosiwo Current, their population dynamics was affected on the spatio-temporal change of physicochemical factors by short-term wind events, namely "island effect". Long-term survey research is needed to facilitate food-web response in marine ecosystem associated with phytoplankton biomass and physicochemical factors including the warm water current in oligotrophic offshore water of Dokdo, which may have significant role for sustainable use of Dokdo.

• Clean Technology
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• v.25 no.3
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• pp.231-237
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• 2019

The BOD removal efficiency according to HRT of the continuous inflow SBR process was decreased from 92.1 ~ 96.0% at HRT 9 ~ 15 h to 86.9 ~ 90.7% at HRT 6 h, but a stable removal efficiency was shown up to HRT 6 h. The T-N removal rate was decreased to 80.1 ~ 87.9% at HRT 12 ~ 15 h, to 71.9 ~ 87.0% at HRT 9 h, and to 60.1 ~ 65.7% at HRT 6 h. As a result of the test of removing organic matter and nitrogen, the optimum HRT of the continuous inflow SBR reactor is determined as 9 h. The TCODcr removal efficiency was 88.4 ~ 96.0% and the TBOD removal efficiency was 92.1 ~ 98.1% as a result of examination of organic matter removal efficiency according to a change in the recycling rate (1 ~ 5Q) at HRT 9 h, suggesting that the a change in the recycling rate has a minimal effect on the removal of organic matter. The T-N removal efficiency was 70.3 ~ 80.4% at 1 ~ 2Q, 77.2 ~ 85.6% at 3Q and 61.5 ~ 80.8% at 4 ~ 5Q according to a change in the recycling rate. The TP removal efficiency was reduced to 75.0 ~ 84.6% at 1 ~ 4Q and to 63.3 ~ 72.4% at 5Q. This is presumably because the release and ingestion of phosphorus (P) by microorganisms is not performed smoothly at 5Q or more. Therefore, the optimum recycling rate for removing organic matter and nutrients was found to be 3Q.

• Korean Journal of Remote Sensing
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• v.35 no.3
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• pp.347-358
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• 2019

Lambertian cloud model (Lambertian Cloud Model) is the simplified cloud model which is used to effectively retrieve the vertical ozone distribution of the atmosphere where the clouds exist. By using the Lambertian cloud model, the optical characteristics of clouds required for radiative transfer simulation are parametrized by Optical Centroid Cloud Pressure (OCCP) and Effective Cloud Fraction (ECF), and the accuracy of each parameter greatly affects the radiation simulation accuracy. However, it is very difficult to generalize the vertical ozone error due to the OCCP error because it varies depending on the radiation environment and algorithm setting. In addition, it is also difficult to analyze the effect of OCCP error because it is mixed with other errors that occur in the vertical ozone calculation process. This study analyzed the ozone retrieval error due to OCCP error using two methods. First, we simulated the impact of OCCP error on ozone retrieval based on Optimal Estimation. Using LIDORT radiation model, the radiation error due to the OCCP error is calculated. In order to convert the radiation error to the ozone calculation error, the radiation error is assigned to the conversion equation of the optimal estimation method. The results show that when the OCCP error occurs by 100 hPa, the total ozone is overestimated by 2.7%. Second, a case analysis is carried out to find the ozone retrieval error due to OCCP error. For the case analysis, the ozone retrieval error is simulated assuming OCCP error and compared with the ozone error in the case of PROFOZ 2005-2006, an OMI ozone profile product. In order to define the ozone error in the case, we assumed an ideal assumption. Considering albedo, and the horizontal change of ozone for satisfying the assumption, the 49 cases are selected. As a result, 27 out of 49 cases(about 55%)showed a correlation of 0.5 or more. This result show that the error of OCCP has a significant influence on the accuracy of ozone profile calculation.

• Journal of the Mineralogical Society of Korea
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• v.32 no.1
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• pp.41-49
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• 2019

Probing the Na environments in Na silicate and aluminosilicate glasses is essential to the macroscopic properties of melts in the Earth. In particular, exploring the atomic structure of Na silicate and aluminosilicate glasses reveals Na-O distance, which plays an important role in transport properties of melts. Here we report the local environment around Na using $^{23}Na$ magic angle spinning (MAS) NMR. We also obtain $^{23}Na$ isotropic chemical shift (${\delta}_{iso}$) of Na silicate and aluminosilicate glasses with varying composition using Dmfit program. The Q mas 1/2 model simulates the experimental results with three simulated peaks while the CzSimple model simulates with one peak. The ${\delta}_{iso}$ decreases with increasing $SiO_2$ content in Na silicate and aluminosilicate glasses. The ${\delta}_{iso}$ increases with increasing $Na_2O$ content in Na-Ca silicate and Na aluminosilicate glasses when the $SiO_2$ content is fixed. Considering the ${\delta}_{iso}$ of Na aluminosilicate glasses available in the previous studies, together with the current simulation results, we confirm that the ${\delta}_{iso}$ has positive correlation with Al / (Al + Si). Those experimental results were reproduced better using Q mas 1/2 model. The disorder of Na in Na silicate and aluminosilicate glasses can be revealed through the simulation of 1D $^{23}Na$ MAS NMR spectra using Dmfit program in a short time.

• Journal of Korea Water Resources Association
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• v.52 no.5
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• pp.349-360
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• 2019

The purpose of this study is to evaluate the stream flow and water quality (SS, T-N, and T-P) behavior of Nakdong river basin ($23,609.3km^2$) by simulating the dam and weir operation scenarios using SWAT (Soil and Water Assessment Tool). The operation senarios are the simultaneous release for all dam and weirs (scenario 1), simultaneous release for all weirs (scenario 2), and sequential release for the weirs with one month interval from upstream weirs (scenario 3). Before evaluation, the SWAT was calibrated and validated using 11 years (2005-2015) daily multi-purpose dam inflow at 5 locations (ADD, IHD, HCD, MKD, and MYD), multi-function weir inflow at 7 locations (SHW, GMW, CGW, GJW, DSW, HCW, and HAW), and monthly water quality monitoring data at 6 locations (AD-4, SJ-2, EG, HC, MK-4, and MG). For the two dam inflow and dam storage, the Nash-Sutcliffe efficiency (NSE) was 0.56~0.79, and the coefficient of determination ($R^2$) was 0.68~0.90. For water quality, the $R^2$ of SS, T-N, and T-P was 0.64~0.79, 0.51~0.74, and 0.53~0.72 respectively. For the three scenarios of dam and weir release combination suggested by the ministry of environment, the scenario 1 and 3 operations were improved the stream water quality (for T-N and T-P) within the 3 months since the time of release, but it showed the negative effect for 3 months after compared to scenario 2.

• Journal of Korean Home Economics Education Association
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• v.33 no.3
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• pp.143-157
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• 2021

This study analyzed and verified the effects of a dietary education program for Korean young adults in single-person households. The dietary education program was conducted for five weeks (from November 10 to December 8, 2020) for Korean young adults in single-person households living in Seongbuk-gu, via four face-to-face education sessions and one online education session, including both theoretical lectures and practice. The effect of the dietary education program was analyzed through the Nutrition Quotient (NQ) questionnaire for adults provided by the Korean Nutrition Society, a dietary evaluation checklist questionnaire developed by the researchers, and photovoices. The average of 'Nutrition' score increased from 51.81 to 53.20, but there was no statistically significant difference. However, there was a significant change in the 'Moderation' category (p<0.05). As for the researcher-developed dietary evaluation, the average of the 'Importance' area rose from 3.77 to 3.99, but there was no statistically significant difference. The average of the 'Practice' area rose from 3.03 to 3.57, significant results were found (p<0.05). When the pre-/post-tests were compared by the sub-categories, four elements of 'Importance', i.e., balanced meals and avoided foods, and all five elements of 'Practice' were significantly improved (p<0.05). A total of 200 photovoices were analyzed according to Social Cognitive Theory. As a result of the analysis, the deterrents that help people eat healthy homemade food were 48% environmental factors, 30% behavioral factors, and 22% individual cognitive factors. The deterrents found to hinder participants from eating healthy homemade food were 72% environmental factors and 14% individual cognitive and behavioral factors. The results suggest that the dietary education program for Korean young adults in single-person households can be an effective tool that promotes self-motivation, behavioral changes, and improvements of the surrounding environment.

• Korea Science and Art Forum
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• v.37 no.4
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• pp.297-308
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• 2019

Air pollution due to the fine dust level updating every day, and the problem of indoor air pollution due to ventilation difficulties and indoor discharge pollutants is also serious. In order to improve the indoor air quality, the air purification effect using the plants is prominent. In this study was started to investigated the living environment of modern people, the risk of indoor air pollution and the improvement function of plants, and to activate plant application. The purpose of this study is to analyze the main functions and design status of domestic and overseas plant - related applications, and to understand the actual use of modern plant applications and to help them learn more convenient plant - related knowledge. Therefore, this paper attempted to establish a basis for suggesting a new plant application by conducting a survey on the health effects of indoor air pollution and user awareness of plant - related applications. The results and contents of the study are as follows. First, as a theoretical review, indoor air pollution is more dangerous to modern people who have a high proportion of indoor living time and adversely affects their health. In order to solve such a problem, it has been shown that air conditioning and stress reduction can be effectively achieved by placing plants in the indoor space. Second, the analysis of the previous study shows the risk of indoor air pollution and its adverse effects on health. In addition, I have been able to find some researches related to the improvement of the indoor air by using the air purifying plants, and I can see the improvement of the user's behavior through the development or improvement of the application. Third, as a result of the survey on the status of domestic and overseas plant application, the main function of the application having high installation number was watering notification, provision of basic information of plants, and most of the functions were plant discerment through cameras. Fourth, most of the survey respondents have either raised or raised plants. Those who have little experience with plant applications have also shown positive feedback in the future on the use of plant-related applications. In addition, due to social problems such as air pollution, air purification using plants and functional plants showed high interest. Based on these results, we propose the need for a multi-functional plant application that can improve the indoor air pollution and facilitate the provision of information related to it.

• (The)Study of the Eastern Classic
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• no.73
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• pp.249-279
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• 2018

This paper analyzes the 'strategy' of Sunzi's art of war and verifies the modern application value of it by combining the 'strategy' of the art of war with modern enterprise management. The army adopts 'war strategy' with the aim of minimizing the loss and sacrifice caused by the war and winning in the shortest time. Enterprise aims to maximize profits at the lowest cost and adopt 'business strategy'. Three factors of art of war's strategic, the 'power', 'adaptation', 'trickery', are similar to the 'internal resources analysis', 'external environment analysis' and 'information management' of the modern enterprise's management. In the process of establishing strategic plan, the art of war emphasizes 'strategy of winning' including 'prophet', 'estimates' and 'maneuvering', in the modern enterprise management, 'prophet' is shown as 'competitor analysis' of the '3C analysis' and 'benchmarking learning'. 'Estimates' is shown as 'SWOT analysis' and '4P's analysis'. 'Maneuvering' is shown as 'market positioning strategy' and 'market preemption strategy'. In the stage of implementing the strategy, 'surprise attack strategy', 'strategy of void and actuality' and 'dividing and integrating strategy' of the art of war are shown as follows in modern enterprises ; 'Surprise attack strategy' is shown as 'differentiation strategy' and 'concentration strategy', 'Strategy of void and actuality' is shown as 'information management' and 'rational market positioning strategy'. 'Dividing and integrating strategy' is shown 'diversification strategy', 'concentration strategy', 'change management', 'basic competition strategy', 'synergy effect' and etc. In terms of strategic results, the 'victory of war' of the art or war is shown as 'competitive advantage' and 'maximization of profits' in modern enterprise management strategy. In a word, although there are different names and expressions between the strategy of Sunzi's art of war and modern enterprise, but their connotation is the same. We can see that the art of war which was written in about B.C.500, has left a high utilization value for modern enterprise in rapid environmental change and intense competition.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.103-128
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• 2021

Recently, investors' interest and the influence of stock-related information dissemination are being considered as significant factors that explain stock returns and volume. Besides, companies that develop, distribute, or utilize innovative new technologies such as artificial intelligence have a problem that it is difficult to accurately predict a company's future stock returns and volatility due to macro-environment and market uncertainty. Market uncertainty is recognized as an obstacle to the activation and spread of artificial intelligence technology, so research is needed to mitigate this. Hence, the purpose of this study is to propose a machine learning model that predicts the volatility of a company's stock price by using the internet search volume of artificial intelligence-related technology keywords as a measure of the interest of investors. To this end, for predicting the stock market, we using the VAR(Vector Auto Regression) and deep neural network LSTM (Long Short-Term Memory). And the stock price prediction performance using keyword search volume is compared according to the technology's social acceptance stage. In addition, we also conduct the analysis of sub-technology of artificial intelligence technology to examine the change in the search volume of detailed technology keywords according to the technology acceptance stage and the effect of interest in specific technology on the stock market forecast. To this end, in this study, the words artificial intelligence, deep learning, machine learning were selected as keywords. Next, we investigated how many keywords each week appeared in online documents for five years from January 1, 2015, to December 31, 2019. The stock price and transaction volume data of KOSDAQ listed companies were also collected and used for analysis. As a result, we found that the keyword search volume for artificial intelligence technology increased as the social acceptance of artificial intelligence technology increased. In particular, starting from AlphaGo Shock, the keyword search volume for artificial intelligence itself and detailed technologies such as machine learning and deep learning appeared to increase. Also, the keyword search volume for artificial intelligence technology increases as the social acceptance stage progresses. It showed high accuracy, and it was confirmed that the acceptance stages showing the best prediction performance were different for each keyword. As a result of stock price prediction based on keyword search volume for each social acceptance stage of artificial intelligence technologies classified in this study, the awareness stage's prediction accuracy was found to be the highest. The prediction accuracy was different according to the keywords used in the stock price prediction model for each social acceptance stage. Therefore, when constructing a stock price prediction model using technology keywords, it is necessary to consider social acceptance of the technology and sub-technology classification. The results of this study provide the following implications. First, to predict the return on investment for companies based on innovative technology, it is most important to capture the recognition stage in which public interest rapidly increases in social acceptance of the technology. Second, the change in keyword search volume and the accuracy of the prediction model varies according to the social acceptance of technology should be considered in developing a Decision Support System for investment such as the big data-based Robo-advisor recently introduced by the financial sector.