• The Journal of Industrial Distribution & Business
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• v.11 no.2
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• pp.25-31
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• 2020

Purpose: The AEO (Authorized Economic Operator) program, created in 2001 in the United States due to 9.11 terrorist's attack, fundamentally changed the trade environment. Korea, which introduced AEO program in 2009, has become one of the world's top countries in the program by ranking 6th in the number of AEO certified companies and the world's No. 1 in MRA (Mutual Recognition Agreement) conclusions. In this paper, we examined what trade-economic and non-economic effects the AEO program and its MRA have in Korea. Research design, data and methodology: In this study we developed a model to verify the impact between utilization of AEO and trade-economic effects of the AEO and its MRA. After analyzing the validity and reliability of the model through Structural Equation Model we conducted a survey to request AEO companies to respond their experience on the effects of AEO program and MRA. As a result, 196 responses were received from 176 AEO companies and utilized in the analysis. Results: With regard to economic effects, the AEO program and the MRA have not been directly linked to financial performance, such as increased sales, increased export and import volumes, reduced management costs, and increased operating profit margins. However, it was analyzed that the positive effects of supply chain management were evident, such as strengthening self-security, monitoring and evaluating risks regularly, strengthening cooperation with trading companies, enhancing cargo tracking capabilities, and reducing the time required for export and import. Conclusions: When it comes to the trade-economic effects of AEO program and its MRA, AEO companies did not satisfy with direct effects, such as increased sales and volume of imports and exports, reduced logistics costs. However, non-economic effects, such as reduced time in customs clearance, freight tracking capability, enhanced security in supply chain are still appears to be big for them. In a rapidly changing trade environment the AEO and MRA are still useful. Therefore the government needs to encourage non-AEO companies to join the AEO program, expand MRA conclusion with AEO adopted countries especially developing ones and help AEO companies make good use of AEO and MRA.

• KIEAE Journal
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• v.16 no.3
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• pp.137-143
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• 2016

Purpose: Apartment housing should conduct a cyclic repair to keep and maintain the building performance since they are constructed. Therefore, the repair plan would be provided for long term period which explains the repair time, items and repair cost. Residents of apartment housing are responsible to pay for the repair activities. For repair cost, residents would reserve the money for repair little by little continuously until the required repair time because the repair cost takes a big burden for residents and lots of money a time. But, there is no systematic approach to provide the long term repair cost because it is no proper forecast of the repair cost to the upcoming repair time. In this study, it aimed at providing the monthly accumulation of the long term repair cost with the survey data in Seoul. Method: For these, the surveyed data are classified into 6 categories and number of data are 1,918. In addition, it developed the repair cost model for the 24 repair works and the cumulation function which is reflected with the each cost model. Result: This study are shown as follows : First, among the various estimation for the repair cost, the power function has a goodness of fit in statistics. Second, the monthly accumulation would be 12,840 won/household in size of $100,000m^2$ management area and $81.7won/m^2$ in size of the 1,000 household number during 40 years.

• Journal of Yeungnam Medical Science
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• v.41 no.2
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• pp.86-95
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• 2024

Background: This study aimed to investigate the impact of coronavirus disease 2019 (COVID-19) on the development of major mental disorders in patients visiting a university hospital. Methods: The study participants were patients with COVID-19 (n=5,006) and those without COVID-19 (n=367,162) registered in the database of Keimyung University Dongsan Hospital and standardized with the Observational Medical Outcomes Partnership Common Data Model. Data on major mental disorders that developed in both groups over the 5-year follow-up period were extracted using the FeederNet computer program. A multivariate Cox proportional hazards model was used to estimate the hazard ratio (HR) and 95% confidence interval (CI) for the incidence of major mental disorders. Results: The incidences of dementia and sleep, anxiety, and depressive disorders were significantly higher in the COVID-19 group than in the control group. The incidence rates per 1,000 patient years in the COVID-19 group vs. the control group were 12.71 vs. 3.76 for dementia, 17.42 vs. 7.91 for sleep disorders, 6.15 vs. 3.41 for anxiety disorders, and 8.30 vs. 5.78 for depressive disorders. There was no significant difference in the incidence of schizophrenia or bipolar disorder between the two groups. COVID-19 infection increased the risk of mental disorders in the following order: dementia (HR, 3.49; 95% CI, 2.45-4.98), sleep disorders (HR, 2.27; 95% CI, 1.76-2.91), anxiety disorders (HR, 1.90; 95% CI, 1.25-2.84), and depressive disorders (HR, 1.54; 95% CI, 1.09-2.15). Conclusion: This study showed that the major mental disorders associated with COVID-19 were dementia and sleep, anxiety, and depressive disorders.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.722-728
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• 2012

Urban sewer systems has a limitation of capacity of rainwater storage and problem of occurrence of untreated sewage, so adopting a storage facility for sewer flooding prevention and urban non-point pollution reduction has a big attention. The Korea Ministry of Environment has recently introduced a new concept of "multi-functional storage facility", which is crucial not only in preventive stormwater management but also in dealing with combined sewer overflow and sanitary sewer discharge, and also has been promoting its adoption. However, reserving a space for a single large-scale storage facility might be difficult especially in urban areas. Thus, decentralized construction of small- and midium-sized storage facilities and its operation have been introduced as an alternative way. In this paper, we propose a model predictive control scheme for an optimized operation of distributed storage facilities and sewer networks. To this aim, we first describe the mathematical model of each component of networks system which enables us to analyze its detailed dynamic behavior. Second, overflow locations and volumes will be predicted based on the developed network model with data on the external inflow occurred at specific locations of the network. MPC scheme based on the introduced particle swarm optimization technique then produces the optimized the gate setting for sewer network flow control, which minimizes sewer flooding and maximizes the potential storage capacity. Finally, the operational efficacy of the proposed control scheme is demonstrated by simulation study with virtual rainstorm event.

• The Mathematical Education
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• v.61 no.2
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• pp.257-271
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• 2022

As information and communication technologies are being developed so rapidly, education research is actively conducted to provide optimal learning for each student using big data and artificial intelligence technology. In this study, using the mathematics learning data of elementary school 5th to 6th graders conducting blended mathematics classes, we tried to find out what factors predict mathematics academic achievement and developed an artificial intelligence model that predicts mathematics academic performance using the results. Math learning propensity, LMS data, and evaluation results of 205 elementary school students had analyzed with a random forest model. Confidence, anxiety, interest, self-management, and confidence in math learning strategy were included as mathematics learning disposition. The progress rate, number of learning times, and learning time of the e-learning site were collected as LMS data. For evaluation data, results of diagnostic test and unit test were used. As a result of the analysis it was found that the mathematics learning strategy was the most important factor in predicting low-achieving students among mathematics learning propensities. The LMS training data had a negligible effect on the prediction. This study suggests that an AI model can predict low-achieving students with learning data generated in a blended math class. In addition, it is expected that the results of the analysis will provide specific information for teachers to evaluate and give feedback to students.

• Smart Media Journal
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• v.6 no.4
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• pp.58-64
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• 2017

Modern society is characterized by rapid increase in world population, aging of the rural population, decrease of cultivation area due to industrialization. The food problem is becoming an important issue with the farmers and becomes rural. Recently, the researches about the field of the smart farm are actively carried out to increase the profit of the rural area. The existing smart farm researches mainly monitor the cultivation environment of the crops in the greenhouse, another way like in the case of poor quality t is being studied that the system to control cultivation environmental factors is automatically activated to keep the cultivation environment of crops in optimum conditions. The researches focus on the crops cultivated indoors, and there are not many studies applied to the cultivation environment of crops grown outside. In this paper, we propose a method to improve the harvestability of poor areas by monitoring the areas with bad harvests by using big data analysis, by precisely predicting the harvest timing of fruit trees growing in orchards. Factors besides for harvesting include fruit color information and fruit weight information We suggest that a harvest correlation factor data collected in real time. It is analyzed using the Apache Spark engine. The Apache Spark engine has excellent performance in real-time data analysis as well as high capacity batch data analysis. User device receiving service supports PC user and smartphone users. A sensing data receiving device purpose Arduino, because it requires only simple processing to receive a sensed data and transmit it to the server. It regulates a harvest time of fruit which produces a good quality fruit, it is needful to determine a poor harvest area or concentrate a bad area. In this paper, we also present an architectural model to determine the bad areas of fruit harvest using strong data analysis.

• The Journal of Engineering Geology
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• v.32 no.2
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• pp.221-239
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• 2022

Unknown geotechnical characteristics are key challenges in the design of piles for the plant, civil and building works. Although the N-values which were read through the standard penetration test are important, those N-values of the whole area are not likely acquired in common practice. In this study, the N-value is predicted by means of regression analysis with artificial intelligence (AI). Big data is important to improve learning performance of AI, so circular augmentation method is applied to build up the big data at the current study. The optimal model was chosen among applied AI algorithms, such as artificial neural network, decision tree and auto machine learning. To select optimal model among the above three AI algorithms is to minimize the margin of error. To evaluate the method, actual data and predicted data of six performed projects in Poland, Indonesia and Malaysia were compared. As a result of this study, the AI prediction of this method is proven to be reliable. Therefore, it is realized that the geotechnical characteristics of non-boring points were predictable and the optimal arrangement of structure could be achieved utilizing three dimensional N-value distribution map.

• Health Policy and Management
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• v.33 no.1
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• pp.3-18
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• 2023

Background: A chronic disease management program including patient education, recall and remind service, and reduction of out-of-pocket payment was implemented in Korea through a chronic care model. This study aimed to assess the effect of a community-based intervention program for improving medication adherence of patients with diabetes mellitus in rural areas of Korea. Methods: We applied a non-equivalent control group design using Korean National Health Insurance Big Data. Hongcheon County has been continuously adopting this program since 2012 as an intervention region. Hoengseong County did not adopt such program. It was used as a control region. Subjects were a cohort of patients with diabetes mellitus aged more than 65 years but less than 85 years among residents for 11 years from 2010 to 2020. After 1:1 matching, there were 368 subjects in the intervention region and 368 in the control region. Indirect indicators were analyzed using the difference-in-difference regression according to Andersen's medical use model. Results: The increasing percent point of diabetic patients who continuously received insurance benefits for more than 240 days from 2010 to 2014 and from 2010 to 2020 were 2.6%p and 2.7%p in the intervention region and 3.0%p and 3.9%p in the control region, respectively. The number of dispensations per prescription of diabetic patient in the intervention region increased by approximately 4.61% by month compared to that in the control region. Conclusion: The intervention program encouraged older people with diabetes mellitus to receive continuous care for overcoming the rule of halves in the community. More research is needed to determine whether further improvement in the continuity of comprehensive care can prevent the progression of cardiovascular diseases.

• Journal of Technologic Dentistry
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• v.33 no.2
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• pp.129-136
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• 2011

Purpose: The purpose of this study was to investigate the transmittance differences of zirconium core due to thickness within the visible light spectrum. Methods: 36 specimens were divided into 3 groups (0.6mm, 0.8mm, 1.0mm) which have each 12 specimens. The size of specimens was 10mm high and 10mm wide. The transmittance of specimens are measured by spectrophotometer Model Cary 500 that can measure infrared-ray, visible wave and ultraviolet-ray. Results: The results shows that there was no significant difference between specimen's thickness and transmittance. Conclusion: The individual's color perception is personal and there are numerous factors that influence on it. In general, human eye can perceive the color of thing only within visible light spectrum but in this experiment through spectrophotometer there was no big difference between specimen's thickness and transmittance. To sum up, The most important factors were a layed porcelain structure and its thickness rather than core thickness in the porcelain crown.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.9
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• pp.1334-1340
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• 2017

In this paper, a tie-plate shape is optimized by using the numerical technique to reduce the stray load loss of the tie-plate which is a mechanical structure for assembling and supporting of the transformer core. The eddy current loss of the structure is calculated by an electromagnetic field FEM program and the results are compared with 4 different shapes of tie-plates. Since the thickness of the tie-plate is very thin, and the skin depth is very small, the number of FE elements for 3-D transformer model is too big to solve. So, the surface impedance boundary condition (SIBC) is used to reduce the system matrix size and its computing time. To verify the method a 2.5 MVA 22,900/380V distribution transformer is simulated using one objective function and three design variables with some constraints. The final optimized tie-plate has three slots of 6 mm width and 23 mm gap, and the loss is reduced by 75 %. Consequently, the proposed algorithm seems to be considerably applicable to electric machinery as well as power transformer.