• Journal of Environmental Impact Assessment
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• v.28 no.2
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• pp.141-151
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• 2019

Korea has passed the Act on the Integrated Control of Pollutant-Discharging Facilities in 2015, and the integrated environmental management under the BAT standard is underway. To summarize the nature of integrated environmental management, it is the regulation by the integration of the management of the multi-pollutant source and the technical standard of BATs. In general, in environmental economics, regulation-based on technical standards are known to be inefficient. This paper attempts to evaluate the efficiency of BAT standards from an economic point of view. A simple multi-pollutant model demonstrates that the inefficiency of the environmental tax with imperfect information in a single pollutant situation is amplified under multi-pollutant conditions. The simultaneous introduction of BAT and IPPC can be partially explained by this logic. It is also highlighted by the strengthening of BAT standards by EU, as a countermeasure to the potential deterioration of air quality caused by the change of effective environmental taxes accompanying the fuel and emission price changes.

• Health Policy and Management
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• v.29 no.2
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• pp.195-205
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• 2019

Background: The food and food service influence the quality of life and the general health condition of older persons living in long-term care (LTC) facilities. Purchasing good food materials is a ground of good food service. In Korea, the residents in LTC facilities should pay for the cost of food materials and ingredients out of their pocket because it is not covered by LTC insurance. This study explored what factors affect the cost of food materials paid by LTC facility residents and which factor affects most. Methods: We used data from the study on out-of-pocket payment on national LTC insurance, which surveyed 1,552 family caregivers of older residents in LTC facilities. We applied conditional multi-level model, of which the first level represents the characteristics of care receivers and caregivers and its second level reflects those of LTC facilities. Results: We found that the facility residents with college-graduated family caregivers paid 11,545 Korean won more than those with less than elementary-graduated ones. However, the income level of family caregivers did not significantly affect the amount of the food material cost of the residents. The residents in privately owned, large, metropolitan-located facilities were likely to pay more than those in other types of facilities. The amount of the food material cost of the residents was mainly decided by the facility level factors rather than the characteristics of care recipients and their family caregivers (intra-class correlation=82%). Conclusion: These findings suggest that it might be effective to design a policy targeting facilities rather than residents in order to manage the cost of food materials of residents in LTC facilities. Setting a standard price for food materials in LTC facilities, like Japan, could be suggested as a feasible policy option. It needs to inform the choice of LTC users by providing comparable food material cost information. The staffing requirement of nutritionist also needs to be reviewed.

• Journal of Cadastre & Land InformatiX
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• v.49 no.1
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• pp.45-63
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• 2019

Until recently, most people have invested in a traditional portfolio consisting of stocks, bonds and real estates based on the three-division method of properties in Korea. However, this study analyzed the impact of the composition of a portfolio combining representative real estate indirect investment products such as Reits and real estate funds on the investment performance. For this purpose, the empirical analysis using the mean variance model, which is the most appropriate method for the portfolio composition, was used. For variables used in this study, mixed asset portfolios were classified into Portfolio A through Portfolio G depending on the composition of assets, and the price indices selected as Kospi, Krx bond, Reits Trus Y7, Hanwha-Lasal fund, and Office (Seoul). The results are as follows; first Portfolio D, which combined bonds, stocks, Reits and Real Estate funds, and Portfolio G, which added the office, the actual real estate, were shown to have the lowest risk. second, Portfolio B composed of bonds, stocks and Reits and Portfolio D with added real estate funds had the lowest risk while Portfolio F composed of bonds, stocks, offices and real estate funds, and Portfolio G with added Reits were the most profitable. As a result, it has been analyzed that it was more effective to compose a portfolio including Reits and real estate funds, which were real estate indirect investment products that eliminated the illiquidity limitation of real estates than real estates, the traditional three-division method of properties. Therefore, it is possible to minimize the risk of investors and reduce the cost of ownership of the real estate by solving the illiquidity problem that is the biggest disadvantage of the direct investment, In addition, it is considered that it is more necessary to reinvigorate the real estate indirect investment market where small amounts can be invested.

• Journal of Digital Convergence
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• v.17 no.11
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• pp.61-70
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• 2019

The The government has recently announced its mid- to long-term plans for promoting art. With the advent of the 4th industrial revolution, contemporary art contents that are integrated with Intelligent Information Technologies such as Artificial Intelligence (AI), Virtual Reality (VR), and Big Data are being introduced, and social interest in humanities and creative convergence is rising. In addition, the industrialization of the art market is expanding amid the rising popularity of art among the general public and the growing interest of art as an investment replacement system, along with the strengthening of the creative personality education of our Education Ministry. Therefore, it is necessary to establish a strategy for transparency and revitalization of the art market by providing comprehensive information such as search functions, analysis data, and criticism by writer and price. This paper has established an information system plan for the establishment of an online supply system for art transaction information, providing auction transaction information for art market, providing report and news for art market, providing public relations platform, and providing art market analysis service and membership relationship management service. To this end, the future model was established through environmental analysis and focus analysis of the art market, and strategic tasks and implementation plans were established accordingly.

• Trans-
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• v.10
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• pp.73-113
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• 2021

Previous studies show that VR images can influence consumers' attitudes and behaviors by evoking imagination. In this study, we introduce a reality-based closed-loop 3D image (hereafter Virtualgraph). Then we try to see whether such image would increase evocativeness in a mobile commerce environment and whether higher telepresence of the visual image of a product can increase the purchase intention of that product. In order to find the above, we developed a model comprised of constructs containing telepresence, perceived value price, perceived food quality, and vividness of visual imagery questionnaire (VVIQ). We used Virtualgraph application to conduct an experiment, and then conducted an interview as well as a survey. As results of the experiment, survey and interview, we found the followings. First, users evoke imagination better with Virtualgraph than with still images. Second, increased evocativeness affects purchase intention if the perceived quality of fresh food product is satif actory. Third, increased evocativeness makes users value products higher and do even much higher when the perceived quality of fresh food product is good. From the interview, we could find that the experimental group had higher purchase intentions and perceived products as more expensive ones. Also, they perceived images of products clearer and more vivid than did the control group. We also discuss the strategic implications of using Virtualgraph in mobile shopping malls.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.391-404
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• 2021

This study developed a long-term prediction model for the potential yield of garlic based on a genetic algorithm (GA) by utilizing global climate reanalysis data. The GA is used for digging the inherent signals from global climate reanalysis data which are both directly and indirectly connected with the garlic yield potential. Our results indicate that both deterministic and probabilistic forecasts reasonably capture the inter-annual variability of crop yields with temporal correlation coefficients significant at 99% confidence level and superior categorical forecast skill with a hit rate of 93.3% for 2 × 2 and 73.3% for 3 × 3 contingency tables. Furthermore, the GA method, which considers linear and non-linear relationships between predictors and predictands, shows superiority of forecast skill in terms of both stability and skill scores compared with linear method. Since our result can predict the potential yield before the start of farming, it is expected to help establish a long-term plan to stabilize the demand and price of agricultural products and prepare countermeasures for possible problems in advance.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.4
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• pp.163-180
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• 2022

Real estate data can be big data. Because the amount of real estate data is growing rapidly and real estate data interacts with various fields such as the economy, law, and crowd psychology, yet is structured with complex data layers. The existing Relational Database tends to show difficulty in handling various relationships for managing real estate big data, because it has a fixed schema and is only vertically extendable. In order to improve such limitations, this study constructs the real estate data in a Graph Database and verifies its usefulness. For the research method, we modeled various real estate data on MySQL, one of the most widely used Relational Databases, and Neo4j, one of the most widely used Graph Databases. Then, we collected real estate questions used in real life and selected 9 different questions to compare the query times on each Database. As a result, Neo4j showed constant performance even in queries with multiple JOIN statements with inferences to various relationships, whereas MySQL showed a rapid increase in its performance. According to this result, we have found out that a Graph Database such as Neo4j is more efficient for real estate big data with various relationships. We expect to use the real estate Graph Database in predicting real estate price factors and inquiring AI speakers for real estate.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.655-660
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• 2022

This paper analyzes the problem of the economic order quantity (lot size) of a retailer in a two-stage supply chain consisting of a supplier, a retailer(distributor), and a customer. In this two-stage supply chain, the supplier permits the retailer to defer payment for a certain fixed period of time for the purchase cost to be paid by the retailer as a price differentiation strategy with his competitor. In addition, in the case of customer goods such as food and grain, it is common to see that end-customer demand is generally depend on the level of inventory displayed by the retailer. From this perspective, this paper analyzes the inventory problem of retailers under the assumption that the supplier may allow a certain period to suspend payments for the purchase of goods and the end customer demand is a function of the retailer's inventory level increasing with size. In this regard, we need to analyze how much the length of the grace period for product purchase costs affect the retailer's lot-sizing policy. Therefore, we formulate the retailer's annual net profit and analyze the effect of the length of credit period on the retailer's inventory policy numerically.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.697-703
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• 2022

Due to the recent economic downturn caused by Covid-19 and the unstable international situation, many investors are choosing the derivatives market as a means of investment. However, the derivatives market has a greater risk than the stock market, and research on the market of market participants is insufficient. Recently, with the development of artificial intelligence, machine learning has been widely used in the derivatives market. In this paper, reinforcement learning, one of the machine learning techniques, is applied to analyze the scalping technique that trades futures in minutes. The data set consists of 21 attributes using the closing price, moving average line, and Bollinger band indicators of 1 minute and 3 minute data for 6 months by selecting 4 products among futures products traded at trading firm. In the experiment, DNN artificial neural network model and three reinforcement learning algorithms, namely, DQN (Deep Q-Network), A2C (Advantage Actor Critic), and A3C (Asynchronous A2C) were used, and they were trained and verified through learning data set and test data set. For scalping, the agent chooses one of the actions of buying and selling, and the ratio of the portfolio value according to the action result is rewarded. Experiment results show that the energy sector products such as Heating Oil and Crude Oil yield relatively high cumulative returns compared to the index sector products such as Mini Russell 2000 and Hang Seng Index.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.1
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• pp.45-52
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• 2023

The power generation method using expensive diesel has operation problems such as high cost diesel generator and a lack of reserved power due to increase of power demand in some islands, requiring expansion of power generation facilities. To solve this problems, it is necessary to improve the efficiency of power generation facilities through an ORC(Organic Rankin Cycle) system application that uses waste heat as a heat source. Therefore, localized application technology of price competitive and highly reliable ORC power generation system is needed, and optimization technology of generators is having great effect, so this study performed two generator designs to get a high-efficiency generator with an optimized 30kW output. The comparison of simulation data for two designed models showed that a generator with SPM factor of 46.2% had an efficiency of 92.1% and a power ouput of about 23.2kW based on 12,000rpm, a generator with SPM factor of 44.46%, had a power output of 27.9kW and efficiency of 93.6% based on above rpm. For the verification of improved design model with SPM factor of 44.46%, the prototype test system with 110kW motor dynamometer was installed and got to the efficiency of 92.08% with conditions of the rated capacity 25kW at 12,000rpm, the test results of prototype generator showed the validity of generator design.