• Journal of the Korean Society of International Agriculture
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• v.30 no.4
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• pp.257-268
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• 2018

Recently, the international standardization of ISO in the field of Oriental Herbal Medicine has been progressing rapidly under the direction of China's promotion. China's intention to promote international standardization is to extend its influence to the world and beyond the domestic market. The Oriental medicine system in East Asia has similar roots in academic terms, but the medicines that can be supplied and received in each country are different and have developed independently. The international standardization of medicinal herbs is expected to function in a direction that weakens such differentiation and independence. From a commercial point of view, international standardization is no different from creating evaluation criteria for oriental medicinal products, and it is expected that its potential impact on domestic and overseas markets and producers will be large. In particular, the international standardization centered on China can lead to favorable evaluation criteria for China, which may further negatively affect the market competitiveness of domestic raw materials, which have been pushed back by Chinese manufacturers. If the domestic production base is weakened, not only will the farmers suffer but the supply and demand of raw materials will also be manipulated, safety management control will be reduced, and the development of oriental herbal products using domestic raw materials will be hurt. Therefore, in the promotion of international standardization, it is necessary not only to reflect the value of Korean herbal medicine but also to provide strategic responses to protect the domestic production base. However, in the case of recent initiatives, there is no precedent in analyzing influence on the production partners and the related industries. In addition, there are few related papers and reports on the subject, so the publicity process has not been done sufficiently. In response to this, this study will examine the countermeasures against the international standardization of herbal medicines through reviewing its present status and evaluating the agenda of the Korean initiative.

• Economic and Environmental Geology
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• v.54 no.3
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• pp.373-387
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• 2021

In this study, the impact of clustered groundwater usage facilities and the proper amount of groundwater usage in the Daejeong-Hangyeong watershed of Jeju island were evaluated based on the data-driven analysis methods. As the applied data, groundwater level data; the corresponding precipitation data; the groundwater usage amount data (Jeoji, Geumak, Seogwang, and English-education city facilities) were used. The results show that the Geumak usage facility has a large influence centering on the corresponding location; the Seogwang usage facility affects on the downstream area; the English-education usage facility has a great impact around the upstream of the location; the Jeoji usage facility shows an influence around the up- and down-streams of the location. Overall, the influence of operating the clustered groundwater usage facilities in the watershed is prolonged to approximately 5km. Additionally, the appropriate groundwater usage amount to maintain the groundwater base-level was analyzed corresponding to the precipitation. Considering the recent precipitation pattern, there is a need to limit the current amount of groundwater usage to 80%. With increasing the precipitation by 100mm, additional groundwater development of approximately 1,500m³-1,900m³ would be reasonable. All the results of the developed data-driven estimation model can be used as useful information for sustainable groundwater development in the Daejeong-Hangyeong watershed of Jeju island.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.693-704
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• 2021

This study empirically verified the effect of strategic orientation on information technology(IT) competency and corporate performance for organizational members engaged in small and medium-sized enterprises (SMEs). In the research model proposed in this study, strategic orientation affects corporate performance, and IT competency is used as a mediating variable in this process. For this study, a survey was conducted on organizational members working in small and medium-sized manufacturers located in Ulsan Metropolitan City. A total of 320 questionnaires were distributed, and 277 copies were used in this study. The collected data were statistically analyzed using SPSS 24.0. The research results are as follows: First, customer orientation, market orientation, and technology orientation of strategic orientation were found to have a positive (+) effect on both information technology knowledge and information technology operation of IT competency. And it was found that both customer orientation and technology orientation of strategic orientation only affects the information technology infrastructure of IT competency. Second, it was found that customer orientation and technology orientation of strategic orientation had a positive (+) effect on corporate performance, but market orientation had no effect on corporate performance. Third, it was found that information technology knowledge, information technology operation, and information technology infrastructure of IT competency had a positive (+) effect on corporate performance. Fourth, as a result of examining the mediating effect of information technology competency between strategic orientation and corporate performance, information technology knowledge, information technology operation, and information technology infrastructure of IT capability were found to have a partial mediating effect between customer orientation and technology orientation of strategic orientation and corporate performance. These research results suggest that in today's fourth industrial revolution era, customer-oriented and technology-oriented management strategies should be established to improve the competitive advantage and performance of small and medium-sized enterprises(SMEs) in the supply chain with large enterprises, and at the same time information technology capabilities such as information technology knowledge, information technology operation, and information technology infrastructure should be strengthened.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.237-262
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• 2022

There has been a growing interest in IPOs (Initial Public Offerings) due to the profitable returns that IPO stocks can offer to investors. However, IPOs can be speculative investments that may involve substantial risk as well because shares tend to be volatile, and the supply of IPO shares is often highly limited. Therefore, it is crucially important that IPO investors are well informed of the issuing firms and the market before deciding whether to invest or not. Unlike institutional investors, individual investors are at a disadvantage since there are few opportunities for individuals to obtain information on the IPOs. In this regard, the purpose of this study is to provide individual investors with the information they may consider when making an IPO investment decision. This study presents a model that uses machine learning and text analysis to predict whether an IPO stock price would move up or down after the first 5 trading days. Our sample includes 691 Korean IPOs from June 2009 to December 2020. The input variables for the prediction are three tone variables created from IPO prospectuses and quantitative variables that are either firm-specific, issue-specific, or market-specific. The three prospectus tone variables indicate the percentage of positive, neutral, and negative sentences in a prospectus, respectively. We considered only the sentences in the Risk Factors section of a prospectus for the tone analysis in this study. All sentences were classified into 'positive', 'neutral', and 'negative' via text analysis using TF-IDF (Term Frequency - Inverse Document Frequency). Measuring the tone of each sentence was conducted by machine learning instead of a lexicon-based approach due to the lack of sentiment dictionaries suitable for Korean text analysis in the context of finance. For this reason, the training set was created by randomly selecting 10% of the sentences from each prospectus, and the sentence classification task on the training set was performed after reading each sentence in person. Then, based on the training set, a Support Vector Machine model was utilized to predict the tone of sentences in the test set. Finally, the machine learning model calculated the percentages of positive, neutral, and negative sentences in each prospectus. To predict the price movement of an IPO stock, four different machine learning techniques were applied: Logistic Regression, Random Forest, Support Vector Machine, and Artificial Neural Network. According to the results, models that use quantitative variables using technical analysis and prospectus tone variables together show higher accuracy than models that use only quantitative variables. More specifically, the prediction accuracy was improved by 1.45% points in the Random Forest model, 4.34% points in the Artificial Neural Network model, and 5.07% points in the Support Vector Machine model. After testing the performance of these machine learning techniques, the Artificial Neural Network model using both quantitative variables and prospectus tone variables was the model with the highest prediction accuracy rate, which was 61.59%. The results indicate that the tone of a prospectus is a significant factor in predicting the price movement of an IPO stock. In addition, the McNemar test was used to verify the statistically significant difference between the models. The model using only quantitative variables and the model using both the quantitative variables and the prospectus tone variables were compared, and it was confirmed that the predictive performance improved significantly at a 1% significance level.

• Journal of the Society of Disaster Information
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• v.18 no.1
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• pp.182-193
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• 2022

Purpose: By measuring and evaluating the risk of biodiesel through non-volatile residue (NVR) and flash point and explosion limit measurement at a specific temperature according to ASTM test standards, the risk of chemical fire causative substances is identified and a universal evaluation method By derivation and securing the risk-related data of the material, it can be used for the identification and analysis of the cause of the fire, and it can be applied to the risk assessment of other chemical substances Method: In order to measure the risk of biodiesel, it was measured using the non-volatile residue(NVR) measurement method, which measures how much flammable liquid is generated at a specific temperature. Heating was tested by applying KS M 5000: 2009 Test Method 4111. In addition, the flash point was measured using the method specified in ASTM E659-782005, and the energy supply method was measured using the constant temperature method. In addition, the explosion limit measurement was conducted in accordance with ASTM E 681-04 「Standard test method for concentration limits of flammability of chemicals(Vapors and gases)」 test standard. Result: As a result of checking the amount of combustible liquid by the non-volatile residue (NVR)measurement method, the non-volatile residue(NVR) of general diesel when left at 105±2℃ for 3 hours was about 30% (70% of volatile matter) and about 4% of biodiesel. In addition, similar results were obtained for the non-volatile residue(NVR)heating temperature of 150±2℃, 3 hours and 200±2℃ for 1 hour, and white smoke was generated at 200℃ or higher. In addition, similar values were obtained as a result of experimentally checking the explosion (combustion) limits of general diesel, general diesel containing 20% biodiesel, and 100% biodiesel. Therefore, it was confirmed that the flammability risk did not significantly affect the explosion risk. Conclusion: The results of this study suggested the risk judgment criteria for mixtures through experimental research on flammable mixtures for the purpose of securing the effectiveness, reliability, and reproducibility of the details of the criteria for determining dangerous substances in the existing Dangerous Materials Safety Management Act. It will be possible to provide reference data for the judgment criteria for flammable liquids that are regulated in the field. In addition, if the know-how for each test method is accumulated through this study, it is expected that it will be used as basic data in the research on risk assessment of dangerous substances and as a basis for research on the determination of dangerous substances.

• Journal of Korean Society of Disaster and Security
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• v.14 no.4
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• pp.69-80
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• 2021

This study tried to suggest improvement measures by discovering problems or matters requiring improvement among the annual regional safety evaluation systems. Briefly introducing the structure and contents of the study, which is the introduction, describes the regional safety evaluation method newly applied by the Ministry of Public Administration and Security in 2020. Utilization plans were also introduced according to the local safety level that was finally evaluated by the local government. In this paper, various views of previous researchers related to regional safety are summarized and described. In addition, problems were drawn in the composition of the index of local safety, the method of calculating the index, and the application of the current index. Next, the problems of specific regional safety evaluation indicators were analyzed and solutions were presented. First, "Number of semi-basement households" is replaced with "Number of households receiving basic livelihood" of 「Social Vulnerability Index」 in the field of disaster risk factors is replaced with "the number of households receiving basic livelihood". In addition, the "Vinyl House Area" is evaluated by replacing "the number of households living in a Vinyl House, the number of container households, and the number of households in Jjok-bang villages" with data. Second, in the management and evaluation of habitual drought disaster areas, local governments with a water supply rate of 95% or higher in Counties, Cities, and Districts are treated as "missing". This is because drought disasters rarely occur in the metropolitan area and local governments that have undergone urbanization. Third, the activities of safety sheriffs, safety monitor volunteers, and disaster safety silver monitoring groups along with the local autonomous prevention foundation are added to the evaluation of the evaluation index of 「Regional Autonomous Prevention Foundation Activation」 in the field of response to disaster prevention measures. However, since the name of the local autonomous disaster prevention organization may be different for each local government, if it is an autonomous disaster prevention organization organized and active for disaster prevention, it would be appropriate to evaluate the results by summing up all of its activities. Fourth, among the Scorecard evaluation items, which is a safe city evaluation tool used by the United Nations Office for Disaster Risk Reduction(UNDRR), the item "preservation of natural buffers to strengthen the protection functions provided by natural ecosystems" is borrowed, which is closely related to natural disasters. The Scorecard evaluation is an assessment index that focuses on improving the disaster resilience of local governments while carrying out the campaign "Creating cities resilient to climate crises and disasters" emphasized by UNDRR. Finally, the names of "regional safety level" and "local safety index" are similar, so the term of local safety level is changed to "natural disaster safety level" or "natural calamity safety level". This is because only the general public can distinguish the local safety level from the local safety index.

• Journal of Korean Home Economics Education Association
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• v.33 no.4
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• pp.139-157
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• 2021

The purpose of this study is to derive implications for Korean home economics curriculum to emphasize consumer competency of adolescents by analyzing the content components of consumer competency presented in 'consumer life' area of middle school home economics curriculum of 3 states in the U.S. The analysis results and implications are summarized as follows: First, the U.S. home economics curriculum is composed of various contents, including credit management, savings/investment/ insurance, taxes, and financial situation, and financial decision-making, to improve adolescent's understanding of finance. In the next revision of Korean curriculum, for financial stability in prolonged life after retirement, it is would be necessary to include contents on basic financial knowledge and technology for financial information utilization so that students can establish financial plans for different life stages in consideration of various variables such as changes in economic environment, etc. Second, the U.S. home economics curriculum was developed to help students make better purchase decisions by applying economic concepts such as prices and interest rates, economic trends and the impact of demand and supply, purchase methods and contract conditions, etc. However, Korean home economics curriculum only focus on purchase plan and purchase decision-making process. It would be necessary to foster consumer transaction competency by introducing economic concepts suitable middle school level. Third, to emphasize "consumer civic competency", Ohio was focusing on "claim of consumer rights" and Wisconsin was focusing on the "acceptance of consumer responsibility." In order to enhance adolescent's consumer civic competency, it would be necessary for Korean curriculum to balance the claim of right and the acceptance of consumer responsibility in the following term, and to emphasize the contents on consumer policies, laws and consumer advocacy to create a consumer environment where consumer sovereignty is realized.

• Journal of Wetlands Research
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• v.25 no.4
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• pp.297-305
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• 2023

The recycled irrigation is a type of irrigation that uses downstream water to fulfill irrigation demand in the upstream agricultural areas; the used irrigation water returns back to the downstream. The recycled irrigation is advantageous for securing irrigation water for plant growth, but the returned water typically contains high levels of nutrients due to excess nutrients inputs during the agricultural activities, potentially deteriorating stream water quality. Therefore, quantitative assessment on the effect of the recycled irrigation on the stream water quality is required to establish strategies for effective irrigation water supply and water quality management. For this purpose, a watershed model is generally used; however no functions to simulate the effects of the recycled irrigation are provided in the existing watershed models. In this study, we used multi-reservoir model coupled with the Hydrological Simulation Program-Fortran (HSPF) to estimate the effect of the recycled irrigation on the stream water quality. The study area was the Gwangok stream watershed, a subwatershed of Gyeseong stream watershed in Changnyeong county, Gyeongsangnam-do. The HSPF model was built, calibrated, and used to produce time series data of flow and water quality, which were used as hypothetical observation data to calibrate the multi-reservoir model. The calibrated multi-reservoir model was used for simulating the recycled irrigation. In the multi-reservoir model, the Gwangok watershed consisted of two subsystems, irrigation and the Gwangok stream, and the reactions (plant uptake, adsorption, desorption, and decay) within each subsystem, and fluxes of water and materials between the subsystems, were modeled. Using the developed model, three scenarios with different combinations of the operating conditions of the recycled irrigation were evaluated for their effects on the stream water quality.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1031-1042
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• 2023

In this study, a deep learning model was developed to predict the yield of cabbage and radish, one of the five major supply and demand management vegetables, using satellite images of Landsat 8. To predict the yield of cabbage and radish in Gangwon-do from 2015 to 2020, satellite images from June to September, the growing period of cabbage and radish, were used. Normalized difference vegetation index, enhanced vegetation index, lead area index, and land surface temperature were employed in this study as input data for the yield model. Crop yields can be effectively predicted using satellite images because satellites collect continuous spatiotemporal data on the global environment. Based on the model developed previous study, a model designed for input data was proposed in this study. Using time series satellite images, convolutional neural network, a deep learning model, was used to predict crop yield. Landsat 8 provides images every 16 days, but it is difficult to acquire images especially in summer due to the influence of weather such as clouds. As a result, yield prediction was conducted by splitting June to July into one part and August to September into two. Yield prediction was performed using a machine learning approach and reference models , and modeling performance was compared. The model's performance and early predictability were assessed using year-by-year cross-validation and early prediction. The findings of this study could be applied as basic studies to predict the yield of field crops in Korea.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.229-256
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• 2023

The increase in telecommuting and household electricity demand due to the pandemic has led to significant changes in electricity demand patterns. This has led to difficulties in identifying KEPCO's PPA (power purchase agreements) and residential solar power generation and has added to the challenges of electricity demand forecasting and grid operation for power exchanges. Unlike other energy resources, electricity is difficult to store, so it is essential to maintain a balance between energy production and consumption. A shortage or overproduction of electricity can cause significant instability in the energy system, so it is necessary to manage the supply and demand of electricity effectively. Especially in the Fourth Industrial Revolution, the importance of data has increased, and problems such as large-scale fires and power outages can have a severe impact. Therefore, in the field of electricity, it is crucial to accurately predict the amount of power generation, such as renewable energy, along with the exact demand for electricity, for proper power generation management, which helps to reduce unnecessary power production and efficiently utilize energy resources. In this study, we reviewed the renewable energy generation forecasting system, its objectives, and practical applications to construct optimal aggregated power resources using data from 169 power plants provided by the Ministry of Trade, Industry, and Energy, developed an aggregation algorithm considering the settlement of the forecasting system, and applied it to the analytical logic to synthesize and interpret the results. This study developed an optimal aggregation algorithm and derived an aggregation configuration (Result_Number 546) that reached 80.66% of the maximum settlement amount and identified plants that increase the settlement amount (B1783, B1729, N6002, S5044, B1782, N6006) and plants that decrease the settlement amount (S5034, S5023, S5031) when aggregating plants. This study is significant as the first study to develop an optimal aggregation algorithm using aggregated power resources as a research unit, and we expect that the results of this study can be used to improve the stability of the power system and efficiently utilize energy resources.