• Journal of the Society of Disaster Information
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• v.17 no.3
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• pp.640-654
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• 2021

Purpose: Normal education operation was difficult in the national disaster situation of Coronavirus Infection-19. Non-face-to-face education can be an alternative to face to face education, but it is not easy to provide the same level of education. In this study, the professor of disaster management field will identify problems that can occur in the overall operation and progress of non-face-to-face education and seek ways to improve non-face-to-face education. Method: Non-face-to-face real-time education was largely categorized into pre-class, in-class, post-class, and evaluation, and case studies were conducted through the professor's case studies. Result&Conclusion: The results of the survey are as follows: First, pre-class, it was worth considering providing a non-face-to-face educational place for professors, and the need for prior education on non-face-to-face educational equipment and systems was required. In addition, it seems necessary to make sure that education is operated smoothly by giving enough notice on classes and to make efforts to develop non-face-to-face education programs for practical class. Second, communication between professor and learner, and among learners can be an important factor in non-face-to-face mid classes. To this end, it is necessary to actively utilize debate-type classes to lead learners to participate in education and enhance the educational effect through constant interaction. Third, non-face-to-face post classes, policies on the protection of privacy due to video records should be prepared to protect the privacy of professors in advance, and copyright infringement on educational materials should also be considered. In addition, it is necessary to devise various methods for fair and objective evaluation. According to the results of the interview, in the contents, which are components of non-face-to-face education, non-face-to-face education requires detailed plans on the number of students, contents, and curriculum suitable for non-face-to-face education from the design of the education. In the system, it is necessary to give the professor enough time to fully learn and familiarize with the function of the program through pre-education on the program before the professor gives non-face-to-face classes, and to operate the helpdesk, which can thoroughly check the pre-examination before non-face-to-face education and quickly resolve the problem in case of a problem.

• Korean Journal of Heritage: History & Science
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• v.54 no.3
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• pp.150-167
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• 2021

Since the advent of tertiary curriculum, middle school history education has been focused on political history, but many students perceive history as a simple memorization subject and complain about difficulties in abstract learning. The researcher saw this problem as caused by the history curriculum, and carried out this study for the purpose of proposing a revitalization of cultural property education in the middle school history curriculum. First, through the analysis of prior research, the usefulness of cultural property education, such as nurturing creative talent and realizing interactive history classes, was revealed, and the problems of the current political history-centered middle school history curriculum were pointed out. Afterwards, as a result of conducting an opinion survey on middle school 3rd grade students and social studies teachers, it was found that first, both middle school students and their teachers thought that the current political history-centered history had much room for improvement. Second, all groups agreed on the necessity of cultural property education in history education. However, in reality, it was found that it was not easy to sufficiently educate students about cultural property in a political history-centered curriculum. Third, teachers thought that it was necessary to improve the current history curriculum in order to enhance cultural property education. Based on these findings, the researcher suggested an improvement plan for the 2015 revised history curriculum. First, in the 'nature of the subject' section, cultural properties and historical materials should be included, and in the 'objective' section, politics, economy, society, and culture should be included. Contents related to cultural properties should be added to the sub-themes in the 'content system and achievement standards', and cultural properties-related contents should be further reinforced in the achievement standards, 'teaching, learning and evaluation'. It was suggested that this section should include cultural property learning and historical material learning, and guidance on teaching and learning methods of cultural property education should be added. If these aspects are reflected in the 2022 revised curriculum that is currently being developed, cultural property education will be improved, and more lively history education will be provided to students.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.199-230
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• 2021

Innovative new products and services are being launched through the convergence between heterogeneous industries, and social interest and investment in convergence industries such as AI, big data-based future cars, and robots are continuously increasing. However, in the process of commercialization of convergence new products and services, there are many cases where they do not conform to the existing regulatory and legal system, which causes many difficulties in companies launching their products and services into the market. In response to these industrial changes, the current government is promoting the improvement of existing regulatory mechanisms applied to the relevant industry along with the expansion of investment in new industries. This study, in these convergence industry trends, aimed to analysis the existing regulatory system that is an obstacle to market entry of innovative new products and services in order to preemptively predict regulatory issues that will arise in emerging industries. In addition, it was intended to establish a regulatory impact analysis system to evaluate adequacy and prepare improvement measures. The flow of this study is divided into three parts. In the first part, previous studies on regulatory impact analysis and evaluation systems are investigated. This was used as basic data for the development direction of the regulatory impact framework, indicators and items. In the second regulatory impact analysis framework development part, indicators and items are developed based on the previously investigated data, and these are applied to each stage of the framework. In the last part, a case study was presented to solve the regulatory issues faced by actual companies by applying the developed regulatory impact analysis framework. The case study included the autonomous/electric vehicle industry and the Internet of Things (IoT) industry, because it is one of the emerging industries that the Korean government is most interested in recently, and is judged to be most relevant to the realization of an intelligent information society. Specifically, the regulatory impact analysis framework proposed in this study consists of a total of five steps. The first step is to identify the industrial size of the target products and services, related policies, and regulatory issues. In the second stage, regulatory issues are discovered through review of regulatory improvement items for each stage of commercialization (planning, production, commercialization). In the next step, factors related to regulatory compliance costs are derived and costs incurred for existing regulatory compliance are calculated. In the fourth stage, an alternative is prepared by gathering opinions of the relevant industry and experts in the field, and the necessity, validity, and adequacy of the alternative are reviewed. Finally, in the final stage, the adopted alternatives are formulated so that they can be applied to the legislation, and the alternatives are reviewed by legal experts. The implications of this study are summarized as follows. From a theoretical point of view, it is meaningful in that it clearly presents a series of procedures for regulatory impact analysis as a framework. Although previous studies mainly discussed the importance and necessity of regulatory impact analysis, this study presented a systematic framework in consideration of the various factors required for regulatory impact analysis suggested by prior studies. From a practical point of view, this study has significance in that it was applied to actual regulatory issues based on the regulatory impact analysis framework proposed above. The results of this study show that proposals related to regulatory issues were submitted to government departments and finally the current law was revised, suggesting that the framework proposed in this study can be an effective way to resolve regulatory issues. It is expected that the regulatory impact analysis framework proposed in this study will be a meaningful guideline for technology policy researchers and policy makers in the future.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.157-173
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• 2021

With the development of information technology, the amount of available information increases daily. However, having access to so much information makes it difficult for users to easily find the information they seek. Users want a visualized system that reduces information retrieval and learning time, saving them from personally reading and judging all available information. As a result, recommendation systems are an increasingly important technologies that are essential to the business. Collaborative filtering is used in various fields with excellent performance because recommendations are made based on similar user interests and preferences. However, limitations do exist. Sparsity occurs when user-item preference information is insufficient, and is the main limitation of collaborative filtering. The evaluation value of the user item matrix may be distorted by the data depending on the popularity of the product, or there may be new users who have not yet evaluated the value. The lack of historical data to identify consumer preferences is referred to as data sparsity, and various methods have been studied to address these problems. However, most attempts to solve the sparsity problem are not optimal because they can only be applied when additional data such as users' personal information, social networks, or characteristics of items are included. Another problem is that real-world score data are mostly biased to high scores, resulting in severe imbalances. One cause of this imbalance distribution is the purchasing bias, in which only users with high product ratings purchase products, so those with low ratings are less likely to purchase products and thus do not leave negative product reviews. Due to these characteristics, unlike most users' actual preferences, reviews by users who purchase products are more likely to be positive. Therefore, the actual rating data is over-learned in many classes with high incidence due to its biased characteristics, distorting the market. Applying collaborative filtering to these imbalanced data leads to poor recommendation performance due to excessive learning of biased classes. Traditional oversampling techniques to address this problem are likely to cause overfitting because they repeat the same data, which acts as noise in learning, reducing recommendation performance. In addition, pre-processing methods for most existing data imbalance problems are designed and used for binary classes. Binary class imbalance techniques are difficult to apply to multi-class problems because they cannot model multi-class problems, such as objects at cross-class boundaries or objects overlapping multiple classes. To solve this problem, research has been conducted to convert and apply multi-class problems to binary class problems. However, simplification of multi-class problems can cause potential classification errors when combined with the results of classifiers learned from other sub-problems, resulting in loss of important information about relationships beyond the selected items. Therefore, it is necessary to develop more effective methods to address multi-class imbalance problems. We propose a collaborative filtering model using CGAN to generate realistic virtual data to populate the empty user-item matrix. Conditional vector y identify distributions for minority classes and generate data reflecting their characteristics. Collaborative filtering then maximizes the performance of the recommendation system via hyperparameter tuning. This process should improve the accuracy of the model by addressing the sparsity problem of collaborative filtering implementations while mitigating data imbalances arising from real data. Our model has superior recommendation performance over existing oversampling techniques and existing real-world data with data sparsity. SMOTE, Borderline SMOTE, SVM-SMOTE, ADASYN, and GAN were used as comparative models and we demonstrate the highest prediction accuracy on the RMSE and MAE evaluation scales. Through this study, oversampling based on deep learning will be able to further refine the performance of recommendation systems using actual data and be used to build business recommendation systems.

• The Journal of Korean Society for Radiation Therapy
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• v.30 no.1_2
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• pp.169-176
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• 2018

Purpose : The purpose of this study is to evaluate clinical applicability of Co-60 ViewRay treatment plan to increase the skin dose in case of high skin dose is required such as Malignant Fungating Wound By measuring the presence / absence of Bolus application and skin dose by the treatment device and comparing it Materials and Methods : Nine inner measuring points of 2.5 cm lattice arrangement and all 13 measuring points including upper and lower left and right measuring points touching the chest and skin were marked. After CT was taken, each treatment plan was formulated through Eclipse and ViewRay-TPS, and a Fixed beam-IMRT treatment plan was formulated so that the left chest V2Gy=95 % is delivered. Before measurement QED detector was calibrated and the QED detector was positioned at the 13 measurement points displayed on Phantom and surface dose of each treatment planner was measured using 5 mm Bolus application using True-beam and View-ray before and after, measure three times and compare each before applying 5 mm Bolus. Results : The surface dose of the Co-60 ViewRay and the linear accelerator appeared at $76.8%{\pm}5.2%$ vs. $67.3{\pm}%7.5%$ and the surface dose after application of 5 mm Bolus was $87.6%{\pm}8.9%$ vs. $80.3%{\pm}10.2%$ It was measured at 10.2 % (p<0.001). Conclusion : As a result of the surface dose measurement of each treatment instrument, Co-60 ViewRay confirmed that the surface dose reached 95.6 % of 6 MV Linac with conventional 5 mm bolus, despite not using Bolus (p<0.001). Also, by utilizing magnetic resonance images for each treatment, it is possible to observe the change in the treatment site without the problem of exposure, it is easy to formulate an adaptive treatment plan and it is easy to secure the skin dose, so the size In the case of Malignant Fungating Wound patients who need fast skin changes and need high skin doses, Co-60 ViewRay is considered to be more useful than linear accelerators.

• Korean Journal of Psychosomatic Medicine
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• v.28 no.2
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• pp.177-184
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• 2020

Objectives : Postpartum depression is known to occur in 10-15% of mothers. The concentration of cytokine varies depending on stress, depression, pregnancy and general medical conditions. We hypothesized that the concentration of cytokines may be related to reproduction and childbirth, and that women with postpartum depression would show alterations in cytokines levels. Methods : A total of 104 pregnant women were selected as subjects, and 60 non-pregnant women were selected as normal controls. Symptoms of depression were evaluated in the pregnant study subjects using the diagnostic criteria outlined in the Edinburgh Postnatal Depression Scale (EPDS). The pregnant subjects were divided into three groups perinatal non-depression controls (n=61), postpartum depression-recovery (n=18), and postpartum depression (n=25). Results : The plasma concentration of TGF-β1, IGF-1 was higher in the pregnant group than in non-pregnant controls (TGF-β1 ; p<0.01, IGF-1 ; p=0.026). At 24 weeks of pregnancy and 6 weeks of delivery, there were no significant differences in the plasma concentration of TGF-β1, IGF-1, β-NGF, IL-2, IL-4, IL-6, IFN-γ, TNF-α between the three groups. There was no statistically significant difference in all three groups during the course of depression in pregnant women. Conclusions : This study found significant difference in plasma cytokines concentrations between non-pregnant controls and perinatal non-depression controls.

• Journal of Wetlands Research
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• v.24 no.4
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• pp.345-353
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• 2022

A wastewater treatment plant (WWTP) is a major gateway for the engineered nano-particles (ENPs) entering the water bodies. However existing studies have reported that many WWTPs exceed the No Observed Effective Concentration (NOEC) for ENPs in the effluent and thus they need to be designed or operated to more effectively control ENPs. Understanding and predicting ENPs behaviors in the unit and \the whole process of a WWTP should be the key first step to develop strategies for controlling ENPs using a WWTP. This study aims to provide a modeling tool for predicting behaviors and removal efficiencies of ENPs in a WWTP associated with process characteristics and major operating conditions. In the developed model, four unit processes for water treatment (primary clarifier, bioreactor, secondary clarifier, and tertiary treatment unit) were considered. Additionally the model simulates the sludge treatment system as a single process that integrates multiple unit processes including thickeners, digesters, and dewatering units. The simulated ENP was nano-sized TiO₂, (nano-TiO₂) assuming that its behavior in a WWTP is dominated by the attachment with suspendid solids (SS), while dissolution and transformation are insignificant. The attachment mechanism of nano-TiO₂ to SS was incorporated into the model equations using the apparent solid-liquid partition coefficient (Kd) under the equilibrium assumption between solid and liquid phase, and a steady state condition of nano-TiO₂ was assumed. Furthermore, an MS Excel-based user interface was developed to provide user-friendly environment for the nano-TiO₂ removal efficiency calculations. Using the developed model, a preliminary simulation was conducted to examine how the solid retention time (SRT), a major operating variable affects the removal efficiency of nano-TiO₂ particles in a WWTP.

• Journal of Korean Society of Forest Science
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• v.109 no.4
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• pp.512-520
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• 2020

We assessed the nectar source potential of a prospective honey plant, Idesia polycarpa, by analyzing nectar volume, free sugar content, and free amino acid content. Idesia polycarpa is a dioecious tree; the males bloom approximately four days earlier than females, and the blooming period is approximately 17 days-from March 14th to March 30th. Upon investigating the patterns of nectar secretion, it was found that male flowers peak on the third day of blooming at 5.0 ± 2.5 μL, and female flowers peak on the second day of blooming, at 1.1 ± 0.4 μL. There was a significant difference between males and females in the total nectar volume (9.7 ± 2.9 μL for males and 1.7 ± 0.5 μL for females) and the dried nectar volume (2.2 ± 0.6 μL for males, 0.8 ± 0.3 μL for females) during the blooming period. The free sugar content of floral nectar was 54.6 ± 15.4 ㎍/μL for males and 20.5 ± 4.9 ㎍/μL for females, and the sugar content per flower was higher in males (170.7 ± 15.4 ㎍) than in females (24.9 ± 5.5 ㎍). Our analysis of the amino acid content showed that 20.4 ± 3.9 mg/L (comprised of 19 amino acids) is produced in male flowers and 3.2 ± 0.1 mg/L (11 amino acids) in female flowers. In the male flower, the main amino acid was glutamine, followed by asparagine and proline, whereas in the female nectar, asparagine was the main amino acid, followed by glutamic acid and glutamine. Idesia polycarpa blooms after the blooming period of a major honey plant, Robinia pseudoacacia, and its nectar volume and nectar characteristics, such as free sugar content and amino acid content, make it a viable honey plant.

• The Journal of Korean Society for Radiation Therapy
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• v.32
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• pp.53-59
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• 2020

Purpose: The purpose of this study is to compare and analyze the difference between the MLC log file-based software (Mobius) and the conventional phantom-ionization chamber (ArcCheck) dose verification method according to the change of target volume. Material and method: Radius 0.25cm, 0.5cm, 1cm, 2cm, 3cm, 4cm, 5cm, 6cm, 7cm, 8cm, 9cm, 10cm with a Sphere-shaped target Twelve plans were created and dose verification using Mobius and ArcCheck was conducted three times each. The irradiated data were compared and analyzed using the point dose error value and the gamma passing rate (3%/3mm) as evaluation indicators. Result: Mobius point dose error values were -9.87% at a radius of 0.25cm and -4.39% at 0.5cm, and the error value was within 3% at the remaining target volume. The gamma passing rate was 95% at a radius of 9cm and 93.9% at 10cm, and a passing rate of more than 95% was shown in the remaining target volume. In ArcCheck, the average error value of the point dose was about 2% in all target volumes. The gamma passing rate also showed a pass rate of 98% or more in all target volumes. Conclusion: For small targets with a radius of 0.5cm or less or a large target with a radius of 9cm or more, considering the uncertainty of DQA based on MLC log files, phantom-ionized DQA is used in complementary ways to include point dose, gamma index, DVH, and target coverage. It is believed that it is desirable to verify the dose delivery through a comprehensive analysis.

• Economic and Environmental Geology
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• v.54 no.1
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• pp.21-33
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• 2021

The purpose of this study is to determine the order of priority for the use of amendments, matching the optimal amendment to the specific site in Korea. This decision-making process must prioritize the stabilization and economic efficiency of amendment for heavy metals and metalloid based on domestic site contamination scenarios. For this study, total 5 domestic heavy metal contaminated sites were selected based on different pollution scenarios and 13 amendments, which were previously studied as the soil stabilizer. Batch extraction experiments were performed to quantify the stabilization efficiency for 8 heavy metals (including As and Hg) for 5 soil samples, representing 5 different pollution scenarios. For each amendment, the analyses using XRD and XRF to identify their properties, the toxicity characteristics leaching procedure (TCLP) test, and the synthetic precipitation leaching procedure (SPLP) test were also conducted to evaluate the leaching safety in applied site. From results of batch experiments, the amendments showing > 20% extraction lowering efficiency for each heavy metal (metalloid) was selected and the top 5 ranked amendments were determined at different amount of amendment and on different extraction time conditions. For each amendment, the total number of times ranked in the top 5 was counted, prioritizing the feasible amendment for specific domestic contaminated sites in Korea. Mine drainage treatment sludge, iron oxide, calcium oxide, calcium hydroxide, calcite, iron sulfide, biochar showed high extraction decreasing efficiency for heavy metals in descending order. When the economic efficiency for these amendments was analyzed, mine drainage treatment sludge, limestone, steel making slag, calcium oxide, calcium hydroxide were determined as the priority amendment for the Korean field application in descending order.