• Clean Technology
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• v.25 no.3
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• pp.256-262
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• 2019

Hydroxylammonium nitrate (HAN)-based liquid propellants are attracting attention as environmentally friendly propellants because they are not carcinogens and the combustion gases have little toxicity. The catalyst used to decompose the HAN-based liquid propellant in a thruster must have both low temperature activity and high heat resistance. The objective of this study is to prepare an Ru/alumina/metal foam catalyst by supporting alumina slurry on the surface of NiCrAl metal foam using a washing coating method and then to support a ruthenium precursor thereon. The decomposition activity of a HAN aqueous solution of the Ru/alumina/metal foam catalyst was evaluated. The effect of the number of repetitive coatings of alumina slurry on the physical properties of the alumina/metal foam was analyzed. As the number of alumina wash coatings increased, mesopores with a diameter of about 7 nm were well-developed, thereby increasing the surface area and pore volume. It was optimal to repeat the wash coating alumina on the metal foam 12 times to maximize the surface area and pore volume of the alumina/metal foam. Mesopores were also well developed on the surface of the Ru/alumina/metal foam catalyst. It was found that the metal form itself without the active metal and alumina can promote the decomposition reaction of the HAN aqueous solution. In the case of the Ru/alumina/metal foam-550 catalyst, the decomposition onset temperature was significantly lowered compared with that of the thermal decomposition reaction, and ${\Delta}P$ could be greatly increased in the decomposition of the HAN aqueous solution. However, when the catalyst was calcined at $1,200^{\circ}C$, the catalytic activity was lowered inevitably because the surface area and pore volume of the catalyst were drastically reduced and Ru was sintered. Further research is needed to improve the heat resistance of Ru/alumina/metal foam catalysts.

• Journal of the Korean Institute of Landscape Architecture
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• v.46 no.6
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• pp.85-96
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• 2018

Developed nations have implemented various policies to reduce greenhouse gases since the 1997 Kyoto Protocol in order to minimize the effects of global warming. Korea should also reduce energy consumption in the industrial sector, and the transportation and building sectors in order to achieve its greenhouse gas reduction target of 37 percent compared to the Business As Usual levels. The government implements various laws and regulations for reducing energy consumption. To reduce energy consumption in the building sector, in particular, the Energy Conservation Design Standards are enforced according to the 'Enforcement Support for Green Building Construction'. The amount of electricity used to maintain room temperature at $28^{\circ}C$ in these buildings have a 30% reduction (measured on the walls and rooftop) in power usage compared to buildings not required to meet these standards. Although the effect of these energy savings on landscaping is proven, this demonstration is not effective for energy saving since it is not a suitable method for the 'Energy Saving Design Standards of Buildings'. For landscaping to be effective as far as a component of energy reduction, the perfusion rate of the building should be calculated based on the thermal conductivity of the component materials for the energy saving designs with respect to the basis of Article 14 of the Green Building Act. Therefore, the purpose of this study is to ensure that the planting-based mats currently being widely used in the landscape industry can have insulating performance suitable for the 'Energy Saving Design Standards' of Buildings according to the 'Enable Green Building Construction Methods'.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.2
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• pp.221-233
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• 2019

In Korea, small and medium sized domestic enterprises(SMEs) play an pivotal role in the national economy, accounting for 99.9% of all enterprises, 87.9% of total employment, and 48.3% of production. and SMEs was driving a real force of the development of national economy in many respects such as innovation, job creation, industrial diversity, balanced regional development. Despite their crucial role in the national development, most of SMEs suffer from a lack of R&D capabilities and equipments as well as funding capacity. Public R&D institutes can provide SMEs with valuable supplementary technological knowledge and help them build technological capacity. so, In order to effectively support SMEs, government and public R&D institutes must be a priority to know about the factors influencing the performance related to technology transfer and technological collaborations. In particular, SMEs are not only taking up a large portion of the national economy, but also their influence in politics and economy so strong that raising the competitiveness of small and medium-sized companies is a national policy goal that must be achieved in order to achieve sustained economic growth. For this reason, it is necessary to look specifically at the relationship between concepts such as the environment, strategy, and organizational culture surrounding the enterprise to enhance the competitiveness of SMEs. The paper analyzes 665 companies to find out which organizational culture affects their performance by classification and type of business of SMEs. This study demonstrated that when SMEs seek consistency in their external environment, strategies, and organizational structure to maintain their continued competitiveness. According to three-way analysis of variance (3-way ANOVA) indicates that classification of industries in SMEs has statistically significant main effects, but the type of business and organizational culture do not have significant effects. However, the company's organizational performance (operating profit) of SMES were found to differ significantly in comparison between groups according to classification standards of industries, and therefore adopted some parts. In addition, an analysis of the effect of interaction between the three independent variables of small and medium-sized enterprises has shown that there are statistically significant interaction effects among classification, types of business, and organizational cultures. The results shows that there is an organizational culture suitable for each industry classification and type of business of an entity, and is expected to be used as a basis for establishing promotion policies related to the incubation and commerciality of small and medium-sized venture companies in the future.

• Journal of Life Science
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• v.31 no.3
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• pp.330-337
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• 2021

This study was conducted to investigate the potential of Stewartia koreana as oral healthcare materials. The antibacterial activity of ethanol extracts from leaves and branches of S. koreana against oral bacteria was confirmed. The leaf and branch extracts (1 mg/disc) showed antibacterial activity against P. gingivalis only among several tested oral bacteria. The leaf extracts showed higher antibacterial activity, with values similar to those of chlorhexidine, which was used as a positive control. The MIC of the leaf extract against P. gingivalis was 0.4 mg/ml and showed bacteriostatic action. The inhibitory effects of the extract on biofilm formation and on gene expression related to biofilm formation by P. gingivalis were determined by biofilm biomass staining, scanning electron microscopy (SEM), and qRT-PCR analysis. The biofilm production rate and cell growth of P. gingivalis in the cultures treated with 0.2-2.0 mg/ml of S. koreana leaf extracts were significantly decreased in a concentration-dependent manner. The inhibitory effect on the formation of P. gingivalis biofilms at concentrations of 1 mg/ml was confirmed by SEM. The qRT-PCR analysis showed concentration-dependent suppression of the fimA and fimB gene expression associated with fimbriae formation in the cultures treated with 0.2-2.0 mg/ml S. koreana leaf extract. These results support the conclusion that S. koreana leaf extracts can be used as oral healthcare materials derived from natural materials, as demonstrated by the antibacterial action and inhibition of biofilm formation of P. gingivalis.

• Korean Journal of Environment and Ecology
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• v.34 no.6
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• pp.558-572
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• 2020

The purpose of this study was to classify the types of degraded areas of Mt. Jirisan section in Baekdudaegan and survey the actual condition of each damage type to use it as basic data for the direction of the restoration of damaged areas according to damage type based on the vegetation information of reference ecosystem. The analysis of the Mt. Jirisan section's actual degraded conditions showed that the total number of patches of degraded areas was 57, and the number of patches and size of degraded areas was higher at the low average altitude and gentle slope. Grasslands (deserted lands) and cultivated areas accounted for a high portion of the damage types, indicating that agricultural land use was a major damage factor. The survey on the conditions of 14 degraded areas showed that the types of damage were classified into the grassland, cultivated area, restoration area, logged-off land, and bare ground. The analysis of the degree of disturbance (the ratio of annual and biennial herb, urbanized index, and disturbance index) by each type showed that the simple single-layer vegetation structure mostly composed of the herbaceous and the degree of disturbance were high in the grassland and cultivated land. The double-layer vegetation structure appeared in the restoration area where the pine seedlings were planted, and the inflow of naturalized plants was especially high compared to other degraded areas due to disturbances caused by the restoration project and the nearby hiking trails. Although the inflow of naturalized plants was low because of high altitude in bare ground, the proportion of annual and biennial herb was high, indicating that all surveyed degraded areas were in early succession stages. The stand ordination by type of damage showed the restoration area on the I-axis, cultivated area, grassland, logged-off land, and bare ground in that order, indicating the arrangement by the damage type. Moreover, the stand ordination of the degraded areas and reference ecosystem based on floristic variation showed a clear difference in species composition. This study diagnosed the status of each damage type based on the reference ecosystem information according to the ecological restoration procedure and confirmed the difference in species composition between the diagnosis result and the reference ecosystem. These findings can be useful basic data for establishing the restoration goal and direction in the future.

• Journal of Korean Society of Forest Science
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• v.100 no.4
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• pp.672-680
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• 2011

The purpose of this study has been carried to develop a criterion for the selection of evaluation factors on Forest Carbon Cycle Community(F.C.C.C) based on the result of survey of 96 participants who were operation managers on mountain eco village(31), relevant experts(33), and officers of local government(32). For analysis of the results of survey, DHP(Delphi Hierarchy Process) method was used which is a combination of Delphi method and AHP(Analytic Hierarchy Process) method. The key factors on selection of a suitable area to launch F.C.C.C. project of Korea Forest Service was selected under three hierarchical classes. Class 1 comprises 3 indices(Physical resource index, Human resource index, Vision index), and Class 2 which contains 10 indices (Existing resource, Surroundings resource, Forest biomass resource, Humanities Social quality, Local resident participation, Leader's ability, External support, Planning of operation, Capability of operation, and Effect of operation). Class 3 is sub-level class of class which possess 38 indices. From the results of analysis, Consistency Index(C.I) of each index in the 3 classes was used as evaluation factor. In Class 1, index 'human resources' showed highest Consistency Index(0.454). In Class 2, index 'forest biomass resources' was the highest Consistency Index(0.376) in 'physical resources' of Class 1, index 'leader's ability' was the highest Consistency Index(0.326) in 'human resources' of Class 1, and index 'planning of operation' was the highest Consistency Index(0.346) in 'vision' of Class 1. In Class 3, relative importance of 38 index including 'Joint ownership land security(C.I.-0.266)' was evaluated. Based on the result of this study, a criterion for the selection of evaluation factors for F.C.C.C was developed and the evaluation criterion is expected to be use to select of a suitable area to launch F.C.C.C. project since 2011.

• The Southeast Asian review
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• v.27 no.4
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• pp.1-40
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• 2017

This study aims to examine the electricity/energy regime of Thailand, the largest energy-hungry country in the Mekong region. This study examined how the electricity/energy regime of Thailand has been shaped and changed up to the present, not only at the national level but also at the sub-regional level covering the Mekong region. Meanwhile, according to the Paris Agreement in 2015, which will get in to effect from 2020, developing countries as well as developed countries have been given voluntary responsibilities and reduction obligations in response to global climate change. Under the post 2020 Climate Change Regime, Thailand also needs to revise its existing electricity/energy policy. We reviewed the recent energy policy of Thailand and evaluated the possibility of transition to a sustainable energy system based on Energy Trilemma's analysis framework. And we examined the roles and impacts of the Thai civil society on the national power and energy planning as well as in the future climate change policy. As a result of the analysis, it can be seen that Thailand's electricity/energy regime has grown rapidly through the support of the West countries under the Cold War era. In particular, Electricity Generating Authority of Thailand(EGAT) played the key role in Thailand's energy policy. In addition, Thailand's geopolitical location and relatively high economic level compared to neighboring countries will continue to be of importance in the future construction of power grids in the region. Meanwhile, in the frame of Energy Trilemma, Thailand has still been vulnerable to environmental sustainability. Thai NGOs have resisted to as well as collaborated with the government to influence the existing electricity/energy policy in the various dimensions but their influence has weakened considerably since the coup in 2014. In conclusion, this study suggests to cooperate with government as well as civil society for sustainable energy transformation of Thailand and Mekong region.

• Korean Journal of Construction Engineering and Management
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• v.22 no.4
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• pp.59-65
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• 2021

Since the 2016 "Housing Act Partial Amendment" and the "2018 Housing Comprehensive Amendment Plan", interest in the pre sale system and post sale system of apartment houses has been on the rise. In order to compare the advantages and disadvantages of the pre sale system and the post sale system of apartment houses, and to establish the basis for the institutional policy of the post sale system, a questionnaire survey method was used for tenants of the apartment house from the public side, and issues of time and cost. The time series analysis method is intended to suggest an appropriate time for payment of contributions. Accordingly, through a review of existing theories and literature, the post sale system of public and private institutions was organized, and through a questionnaire survey, the path to securing pre sale money, product information of the model house, and the degree of awareness of the effect of the post sale system were investigated. For the post sale fund support and payment method, it is necessary to increase the commercial line for existing financiers from the user's point of view, and it is necessary to operate in consideration of the economic power of the pre sale market by region. Both 60% post sale and 80% post sale have a price range of up to KRW 10 million, and the total interest rate is 5.0%, and the annual interest rate is about 2.8% for 60% post sale, and about 2.1% for 80% post sale, which is lower than the current 3.1%. I need an interest rate. The research is a perception survey targeting a total of 5,213 households in a sample of after sale apartments in public institutions. As the actual values are analyzed using a time series on the effects of market supply and demand and market prices, there is a limit to applying them to prospective residents of private apartments. In addition, to respond to first time tenants, a questionnaire survey was conducted on five complexes that have moved in within the last five years.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.42-51
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• 2020

This study was performed to support the 6th forest basic planning by Korea Forest Service as predicting the change of forestland area by the transition of land use type in the future over 35 years in South Korea. It is very important to analyze upcoming forestland area change for future forest planning because forestland plays a basic role to predict forest resources change for afforestation, production and management in the future. Therefore, the transitional interaction between land use types in future of South Korea was predicted in this study using econometrical models based on past trend data of land use type and related variables. The econometrical model based on maximum discounted profits theory for land use type determination was used to estimate total quantitative change by forestland, agricultural land and urban area at national scale using explanatory variables such as forestry value added, agricultural income and population during over 46 years. In result, it was analyzed that forestland area would decrease continuously at approximately 29,000 ha by 2027 while urban area increases in South Korea. However, it was predicted that the forestland area would be started to increase gradually at 170,000 ha by 2050 because urban area was reduced according to population decrement from 2032 in South Korea. We could find out that the increment of forestland would be attributed to social problems such as urban hollowing and localities extinction phenomenon by steep decrement of population from 2032. The decrement and increment of forestland by unbalanced population immigration to major cities and migration to localities might cause many social and economic problems against national sustainable development, so that future strategies and policies for forestland should be established considering such future change trends of land use type for balanced development and reasonable forestland use and conservation.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.103-128
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• 2021

Recently, investors' interest and the influence of stock-related information dissemination are being considered as significant factors that explain stock returns and volume. Besides, companies that develop, distribute, or utilize innovative new technologies such as artificial intelligence have a problem that it is difficult to accurately predict a company's future stock returns and volatility due to macro-environment and market uncertainty. Market uncertainty is recognized as an obstacle to the activation and spread of artificial intelligence technology, so research is needed to mitigate this. Hence, the purpose of this study is to propose a machine learning model that predicts the volatility of a company's stock price by using the internet search volume of artificial intelligence-related technology keywords as a measure of the interest of investors. To this end, for predicting the stock market, we using the VAR(Vector Auto Regression) and deep neural network LSTM (Long Short-Term Memory). And the stock price prediction performance using keyword search volume is compared according to the technology's social acceptance stage. In addition, we also conduct the analysis of sub-technology of artificial intelligence technology to examine the change in the search volume of detailed technology keywords according to the technology acceptance stage and the effect of interest in specific technology on the stock market forecast. To this end, in this study, the words artificial intelligence, deep learning, machine learning were selected as keywords. Next, we investigated how many keywords each week appeared in online documents for five years from January 1, 2015, to December 31, 2019. The stock price and transaction volume data of KOSDAQ listed companies were also collected and used for analysis. As a result, we found that the keyword search volume for artificial intelligence technology increased as the social acceptance of artificial intelligence technology increased. In particular, starting from AlphaGo Shock, the keyword search volume for artificial intelligence itself and detailed technologies such as machine learning and deep learning appeared to increase. Also, the keyword search volume for artificial intelligence technology increases as the social acceptance stage progresses. It showed high accuracy, and it was confirmed that the acceptance stages showing the best prediction performance were different for each keyword. As a result of stock price prediction based on keyword search volume for each social acceptance stage of artificial intelligence technologies classified in this study, the awareness stage's prediction accuracy was found to be the highest. The prediction accuracy was different according to the keywords used in the stock price prediction model for each social acceptance stage. Therefore, when constructing a stock price prediction model using technology keywords, it is necessary to consider social acceptance of the technology and sub-technology classification. The results of this study provide the following implications. First, to predict the return on investment for companies based on innovative technology, it is most important to capture the recognition stage in which public interest rapidly increases in social acceptance of the technology. Second, the change in keyword search volume and the accuracy of the prediction model varies according to the social acceptance of technology should be considered in developing a Decision Support System for investment such as the big data-based Robo-advisor recently introduced by the financial sector.