• Korean Journal of Construction Engineering and Management
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• v.20 no.5
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• pp.52-60
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• 2019

The APR1400 is a 1400MWe nuclear power plant developed through national technology development project over a period about 10years. Approximately 65,000 design drawings are produced for APR1400 construction. In order to maintain consistency among numerous drawings, the highest level of design bases drawings (DBDs) are created according to design bases and this is used in the subsequent design. However, DBDs are produced and managed on a document basis and they are managed various field, it was difficult to accurately reflect the design bases information in the subsequent design. Therefore, this study recognizes limitations of the document based DBDs and develops a system that can accurately reflect the design bases information to subsequent design by adopting BIM based design bases integrated information system. Especially, by introducing DBIL(Design Bases Information Layer) concept, DBIL was created and analyzed based on five design bases(Physical protection, Fire protection, Internal missile protection, Internal flood protection, Radiation protection) applied to APR1400. In the final result DBIL set and Datasheet are integrated of room, design bases information, building data(wall, slab, door, window, penetrations). So it can be used for subsequent design automation and design verification. Furthermore, it is expected that APR1400 DBILs data can be used extensively in constructability and design economics analysis through comparison with next generation nuclear power plant.

• Journal of Korean Neurosurgical Society
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• v.62 no.4
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• pp.442-449
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• 2019

Objective : Bone mineral density (BMD) is an important consideration during fusion surgery. Although dual X-ray absorptiometry is considered as the gold standard for assessing BMD, quantitative computed tomography (QCT) provides more accurate data in spine osteoporosis. However, QCT has the disadvantage of additional radiation hazard and cost. The present study was to demonstrate the utility of artificial intelligence and machine learning algorithm for assessing osteoporosis using Hounsfield units (HU) of preoperative lumbar CT coupling with data of QCT. Methods : We reviewed 70 patients undergoing both QCT and conventional lumbar CT for spine surgery. The T-scores of 198 lumbar vertebra was assessed in QCT and the HU of vertebral body at the same level were measured in conventional CT by the picture archiving and communication system (PACS) system. A multiple regression algorithm was applied to predict the T-score using three independent variables (age, sex, and HU of vertebral body on conventional CT) coupling with T-score of QCT. Next, a logistic regression algorithm was applied to predict osteoporotic or non-osteoporotic vertebra. The Tensor flow and Python were used as the machine learning tools. The Tensor flow user interface developed in our institute was used for easy code generation. Results : The predictive model with multiple regression algorithm estimated similar T-scores with data of QCT. HU demonstrates the similar results as QCT without the discordance in only one non-osteoporotic vertebra that indicated osteoporosis. From the training set, the predictive model classified the lumbar vertebra into two groups (osteoporotic vs. non-osteoporotic spine) with 88.0% accuracy. In a test set of 40 vertebrae, classification accuracy was 92.5% when the learning rate was 0.0001 (precision, 0.939; recall, 0.969; F1 score, 0.954; area under the curve, 0.900). Conclusion : This study is a simple machine learning model applicable in the spine research field. The machine learning model can predict the T-score and osteoporotic vertebrae solely by measuring the HU of conventional CT, and this would help spine surgeons not to under-estimate the osteoporotic spine preoperatively. If applied to a bigger data set, we believe the predictive accuracy of our model will further increase. We propose that machine learning is an important modality of the medical research field.

• Korean Journal of Optics and Photonics
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• v.32 no.5
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• pp.235-243
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• 2021

Photobiomodulation (PBM)-based therapy, which uses a phenomenon in which a light source of a specific wavelength band promotes ATP production in mitochondria, has attracted much attention in the fields of biology and medicine because of its effects on wound healing, inflammation reduction, and pain relief. Research on PBM-based therapy has mainly used lasers and light-emitting diodes (LEDs) as light sources and, despite the advantages of organic light-emitting diodes (OLEDs), there have been only a few cases where OLEDs were used in PBM-based therapy. In this research, the skin-care effect of PBM was analyzed using red (λ = 620 nm), green (λ = 525 nm), and blue (λ = 455 nm) OLED lighting modules, and was compared to the PBM effect of LEDs. We demonstrated the PBM-based skin-care effect of the red, green, blue OLED lighting modules by measuring the increase in the amount of collagen type-1 synthesis, the inhibition of melanin synthesis, and the suppression of nitric oxide generation, respectively.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.6
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• pp.553-560
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• 2020

This paper presents an algorithm for identifying and eliminating errors by seagrasses in coastal bathymetry surveying using drone and HD camera. Survey errors due to seagrasses were identified, segmentated and eliminated using a L∗a∗b color space model. Bathymetry survey using a drone and HD camera has many advantages over conventional survey methods such as ship-board acoustic sounder or manual level survey which are time consuming and expensive. However, errors caused by sea bed reflectance due to seagrasses habitat hamper the development of new surveying tool. Seagrasses are the flowering plants which start to grow in November and flourish to maximum density until April in Korea. We developed a new algorithm for identifying seagrasses habitat locations and eliminating errors due to seagrasses to get the accurate depth survey data. We tested our algorithm at Wolpo beach. Bathymetry survey data which were obtained using a drone with HD camera and calibrated to eliminate errors due to seagrasses, were compared with depth survey data obtained using ship-board multi-beam acoustic sounder. The abnormal bathymetry data which are defined as the excess of 1.5 times of a standard deviation of random errors, are composed of 8.6% of the test site of area of 200 m by 300 m. By applying the developed algorithm, 92% of abnnormal bathymetry data were successfully eliminated and 33% of RMS errors were reduced.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.121-129
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• 2021

In this study, we try to minimize the tariff risk by constructing a hazardous cargo screening model by applying Association Rule Mining, one of the data mining techniques. For this, the risk level between supply chains is calculated using the Apriori Algorithm, which is an association analysis algorithm, using the big data of the import declaration form of the Korea Customs Service(KCS). We perform data preprocessing and association rule mining to generate a model to be used in screening the supply chain. In the preprocessing process, we extract the attributes required for rule generation from the import declaration data after the error removing process. Then, we generate the rules by using the extracted attributes as inputs to the Apriori algorithm. The generated association rule model is loaded in the KCS screening system. When the import declaration which should be checked is received, the screening system refers to the model and returns the confidence value based on the supply chain information on the import declaration data. The result will be used to determine whether to check the import case. The 5-fold cross-validation of 16.6% precision and 33.8% recall showed that import declaration data for 2 years and 6 months were divided into learning data and test data. This is a result that is about 3.4 times higher in precision and 1.5 times higher in recall than frequency-based methods. This confirms that the proposed method is an effective way to reduce tariff risks.

• Industry Promotion Research
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• v.6 no.1
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• pp.79-86
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• 2021

Due to the change in the demographic structure, the problem of low birth rate and aging population leads to a serious decrease in human resources, and the necessity of introducing foreign workers is increasing. This study believes that the introduction of foreign workforce is the most effective to expand the working-age population in the era of low birthrate and aging, when demographic changes begin in earnest, and to this end, it sought to devise measures to improve the legal system for migrant workers. As a result of this study, first, the legal system for migrant workers should be unified and improved. It is necessary to establish or unify management agencies so that the 「Immigration Control Act」 and the 「Labor Act」 can establish a cooperative relationship. Second, the 「Immigration Control Act」 should be revised to make it easier for migrant workers to find employment. It is necessary to positively review the employment permit system and acquisition of nationality. Third, there should be no equity or discrimination against migrant workers. Under the principle of mutual benefit, employers and migrant workers should not be equally discriminated against. Fourth, the social insurance system must be added to the legal system of migrant workers. Therefore, the legal system should be reorganized so that migrant workers are not discriminated against in various insurance systems including the four major social insurance systems. In conclusion, the problem of low birthrate and aging population has become a serious social problem due to changes in the demographic structure, and the decrease in the possible generation population has reached a level of concern. The importance of migrant workers' employment and work environment is increasing. Nevertheless, related legal and institutional problems still exist, and measures to improve the legal system for migrant workers are needed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2377-2398
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• 2021

In the recent modernized world, utilization of natural resources (renewable & non-renewable) is increasing drastically due to the sophisticated life style of the people. The over-consumption of non-renewable resources causes pollution which leads to global warming. Consequently, government agencies have been taking several initiatives to control the over-consumption of non-renewable natural resources and encourage the production of renewable energy resources. In this regard, we introduce an IoT powered integrated framework called as green home architecture (GHA) for green score calculation based on the usage of natural resources for household purpose. Green score is a credit point (i.e.,10 pts) of a family which can be calculated once in a month based on the utilization of energy, production of renewable energy and pollution caused. The green score can be improved by reducing the consumption of energy, generation of renewable energy and preventing the pollution. The main objective of GHA is to monitor the day-to-day usage of resources and calculate the green score using the proposed green score algorithm. This algorithm gives positive credits for economic consumption of resources and production of renewable energy and also it gives negative credits for pollution caused. Here, we recommend a green score based tax calculation system which gives tax exemption based on the green score value. This direct beneficiary model will appreciate and encourage the citizens to consume fewer natural resources and prevent pollution. Rather than simply giving subsidy, this proposed system allows monitoring the subsidy scheme periodically and encourages the proper working system with tax exemption rewards. Also, our GHA will be used to monitor all the household appliances, vehicles, wind mills, electricity meter, water re-treatment plant, pollution level to read the consumption/production in appropriate units by using the suitable sensors. These values will be stored in mass storage platform like cloud for the calculation of green score and also employed for billing purpose by the government agencies. This integrated platform can replace the manual billing and directly benefits the government.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.321-331
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• 2021

This study sought to analyze factors influencing high-risk drinking in single-person households. For this, data from the 2018 community health survey were used. Subjects were 32,389 adults above the age of 19 in single-person households. For the data analysis, high-risk drinking groups were extracted according to the high-risk drinking rate index of the survey to arrive at influencing factors and differences in health-related and sociodemographic characteristics. The IBM SPSS 25.0 software was used for analysis and a complex sampling design was applied. The results showed that the high-risk drinking rate of Korea's single-person households was 15.0% (male: 25.8%, female: 5.8%) and age, education under high school level, service-industry employees, smokers, people with depression, high blood pressure, and irregular breakfast eaters appeared as common elements for both genders. Stress appeared to only affect males while being diabetic only affected females. High-risk drinking was higher for males in their 30~40s and women in their 20~30s. The younger generation showed the highest numbers in high-risk drinking and factors like stress or depression appeared to be influencing factors for high-risk drinking. Hence, mental health programs along with customized health policies through health forms and lifestyle changes will be required to lower the high-risk drinking rates of single-person households.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.615-627
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• 2021

With Covid-19, the era of Untact has arrived. Online is bound to develop because face-to-face has become difficult among the threats of the Corona virus. Even in this era, even worship services to God have been offered online. Teenagers, the generation most accustomed to online, seem to easily adapt to online worship. Online youth worship is expected to continue even in the post-corona era. If so, the theological reflection on whether online youth worship is possible is necessary. Through theological reflection, we need to secure theological justification for online youth worship, and strive to make it a better and more accurate online worship service. Online worship tailored to the eye level of youth and online worship that meets the spiritual needs of youth should be planned, prepared, and implemented. This paper presented the theological justification for online youth worship by looking at the definition of worship, elements of worship, places of worship, and history of worship. In addition, while examining the characteristics of adolescence, it suggested why online youth worship is important and necessary. Then, in order to plan online youth worship that is more advanced and more accurate than the online worship currently being conducted in each church, the reality of online youth worship was presented by examining the purposes, contents, and methods of online youth worship.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.6
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• pp.687-695
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• 2021

With the recent occurrence of large-scale earthquakes in Korea, the importance of seismic design has greatly increased. Seismic design standards stipulate that dynamic time history analysis be performed for important or special structures. In the seismic analysis and design of such structures, determining a rational design input seismic wave is a very important factor in ensuring the reliability of the analysis and design. In the seismic design standards, rational design seismic waves must reflect the characteristics of the area (fault) and satisfy the design response spectrum for each seismic performance level. This requirement can be partially satisfied by modifying the actual seismic wave measured in the area (fault) according to the design response spectrum. In this study, a method of correcting and generating seismic wave time histories according to the design response spectrum based on actual measured seismic waves using the harmonic wavelet transform was proposed. To examine the applicability of the proposed technique, the technique was applied to earthquakes of magnitude 5.8 and 5.4, respectively, that occurred in Gyeongju (2016) and Pohang (2017), and the seismic wave time histories corresponding to the design response spectrum were modified and generated.