• Clean Technology
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• v.24 no.2
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• pp.127-134
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• 2018

To reduce the environmental pollution by $NO_x$ from ship engine, International maritime organization (IMO) announced Tier III regulation, which is the emmision regulation of ship's exhaust gas in Emission control area (ECA). Selective catalytic reduction (SCR) process is the most commercial $De-NO_x$ system in order to meet the requirement of Tier III regulation. In generally, commercial ceramic honeycomb SCR catalyst has been installed in SCR reactor inside marine vessel engine. However, the ceramic honeycomb SCR catalyst has some serious issues such as low strength and easy destroution at high velocity of exhaust gas from the marine engine. For these reasons, we design to metallic structured catalyst in order to compensate the defects of the ceramic honeycomb catalyst for applying marine SCR system. Especially, metallic structured catalyst has many advantages such as robustness, compactness, lightness, and high thermal conductivity etc. In this study, in order to support catalyst on metal substrate, coating slurry is prepared by changing binder. we successfully fabricate the metallic structured catalyst with strong adhesion by coating, drying, and calcination process. And we carry out the SCR performance and durability such as sonication and dropping test for the prepared samples. The MFC01 shows above 95% of $NO_x$ conversion and much more robust and more stable compared to the commercial honeycomb catalyst. Based on the evaluation of characterization and performance test, we confirm that the proposed metallic structured catalyst in this study has high efficient and durability. Therefore, we suggest that the metallic structured catalyst may be a good alternative as a new type of SCR catalyst for marine SCR system.

• Journal of the Korean Institute of Gas
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• v.27 no.3
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• pp.19-26
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• 2023

Hydrogen, a clean energy source free of COx emissions, is poised to replace fossil fuels, with its usage on the rise. Despite its high energy content per unit mass, hydrogen faces limitations in storage and transportation due to its low storage density and challenges in long-term storage. In contrast, ammonia offers a high storage capacity per unit volume and is relatively easy to liquefy, making it an attractive option for storing and transporting large volumes of hydrogen. While NH₃ decomposition is an endothermic reaction, achieving excellent low-temperature catalytic activity is essential for process efficiency and cost-effectiveness. The study examined the effects of different zeolite types (5A, NaY, ZSM5) on NH₃ decomposition activity, considering differences in pore structure, cations, and Si/Al-ratio. Notably, the 5A zeolite facilitated the high dispersion of Ni across the surface, inside pores, and within the structure. Its low Si/Al ratio contributed to abundant acidity, enhancing ammonia adsorption. Additionally, the presence of Na and Ca cations in the support created medium basic sites that improved N₂ desorption rates. As a result, among the prepared catalysts, the 15 wt%Ni/5A catalyst exhibited the highest NH₃ conversion and a high H₂ formation rate of 23.5 mmol/g_cat·min (30,000 mL/g_cat·h, 600 ℃). This performance was attributed to the strong metal-support interaction and the enhancement of N₂ desorption rates through the presence of medium basic sites.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.

• Journal of Global Scholars of Marketing Science
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• v.17 no.2
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• pp.31-54
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• 2007

The exchange between buyers and sellers in the industrial market is changing from short-term to long-term relationships. Long-term relationships are governed mainly by formal contracts or informal agreements, but many scholars are now asserting that controlling relationship by using formal contracts under environmental dynamism is inappropriate. In this case, partners will depend on each other's flexibility or interdependence. The former, flexibility, provides a general frame of reference, order, and standards against which to guide and assess appropriate behavior in dynamic and ambiguous situations, thus motivating the value-oriented performance goals shared between partners. It is based on social sacrifices, which can potentially minimize any opportunistic behaviors. The later, interdependence, means that each firm possesses a high level of dependence in an dynamic channel relationship. When interdependence is high in magnitude and symmetric, each firm enjoys a high level of power and the bonds between the firms should be reasonably strong. Strong shared power is likely to promote commitment because of the common interests, attention, and support found in such channel relationships. This study deals with environmental dynamism in high-tech industry. Firms in the high-tech industry regard it as a key success factor to successfully cope with environmental changes. However, due to the lack of studies dealing with environmental dynamism and supply chain commitment in the high-tech industry, it is very difficult to find effective strategies to cope with them. This paper presents the results of an empirical study on the relationship between environmental dynamism and supply chain commitment in the high-tech industry. We examined the effects of consumer, competitor, and technological dynamism on supply chain commitment. Additionally, we examined the moderating effects of flexibility and dependence of supply chains. This study was confined to the type of high-tech industry which has the characteristics of rapid technology change and short product lifecycle. Flexibility among the firms of this industry, having the characteristic of hard and fast growth, is more important here than among any other industry. Thus, a variety of environmental dynamism can affect a supply chain relationship. The industries targeted industries were electronic parts, metal product, computer, electric machine, automobile, and medical precision manufacturing industries. Data was collected as follows. During the survey, the researchers managed to obtain the list of parts suppliers of 2 companies, N and L, with an international competitiveness in the mobile phone manufacturing industry; and of the suppliers in a business relationship with S company, a semiconductor manufacturing company. They were asked to respond to the survey via telephone and e-mail. During the two month period of February-April 2006, we were able to collect data from 44 companies. The respondents were restricted to direct dealing authorities and subcontractor company (the supplier) staff with at least three months of dealing experience with a manufacture (an industrial material buyer). The measurement validation procedures included scale reliability; discriminant and convergent validity were used to validate measures. Also, the reliability measurements traditionally employed, such as the Cronbach's alpha, were used. All the reliabilities were greater than.70. A series of exploratory factor analyses was conducted. We conducted confirmatory factor analyses to assess the validity of our measurements. A series of chi-square difference tests were conducted so that the discriminant validity could be ensured. For each pair, we estimated two models-an unconstrained model and a constrained model-and compared the two model fits. All these tests supported discriminant validity. Also, all items loaded significantly on their respective constructs, providing support for convergent validity. We then examined composite reliability and average variance extracted (AVE). The composite reliability of each construct was greater than.70. The AVE of each construct was greater than.50. According to the multiple regression analysis, customer dynamism had a negative effect and competitor dynamism had a positive effect on a supplier's commitment. In addition, flexibility and dependence had significant moderating effects on customer and competitor dynamism. On the other hand, all hypotheses about technological dynamism had no significant effects on commitment. In other words, technological dynamism had no direct effect on supplier's commitment and was not moderated by the flexibility and dependence of the supply chain. This study makes its contribution in the point of view that this is a rare study on environmental dynamism and supply chain commitment in the field of high-tech industry. Especially, this study verified the effects of three sectors of environmental dynamism on supplier's commitment. Also, it empirically tested how the effects were moderated by flexibility and dependence. The results showed that flexibility and interdependence had a role to strengthen supplier's commitment under environmental dynamism in high-tech industry. Thus relationship managers in high-tech industry should make supply chain relationship flexible and interdependent. The limitations of the study are as follows; First, about the research setting, the study was conducted with high-tech industry, in which the direction of the change in the power balance of supply chain dyads is usually determined by manufacturers. So we have a difficulty with generalization. We need to control the power structure between partners in a future study. Secondly, about flexibility, we treated it throughout the paper as positive, but it can also be negative, i.e. violating an agreement or moving, but in the wrong direction, etc. Therefore we need to investigate the multi-dimensionality of flexibility in future research.

• Journal of the Korean Geographical Society
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• v.29 no.2
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• pp.137-165
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• 1994

Structural adjustment of industry (or industrial restructuring) seems to be inherent in the process of capitalist economic development, which tends to be proceeded with shifts from one stage to another in order to overcome structural crises generated in each stage. The structural adjustment of industry is necessarily accompanied with regional restructuring, since it is not only projected on spece, but also mediated by space. Such a restructuring necessitates industrial and uneven regional devlopment through which capital can seek excessive profits over the rate of socio-spatial average. The industrial restructuring and uneven regional development in the 1980s in Korea can be seen as a process in which capital attempted with a strong support of the govenment to overcome the crises in the end of 1970s and hence to go on rapid economic growth. In this process, capital, especially monopoly capital concentrated into few conglomerates, pursued both extensive expansion and intensive development of industry simultaneously. In results, the Korean economy could eliminate some of peripheral characters and maturate the Fordist accumulation system. The extensive expansion of the Korean industry in the 1980s was stimulated mainly through the enlargement and adjustment of investment for equipment facilities which was planned to exclude or rationalize traditional light industries on some places, and to continue rapid growth of key heavy-chemical industries, especially of fabricated metal industry, on other places. In this process, keeping mainly the existing developmental axis which polarized the Seoul Metroplitan region and the Southeast region in Korea, the enhancing spatial mobiiity of capital and the further differentiating division of labour enforced a tendency of concentration of all types of industry in the Seoul Metropolitan region, and at the same time provoked the diffusion of some industries over Jeolla and Chungchong regions in a considerable extent. The intensive development of industriai structure in the 1980s was pursued through the strategic encouragement of subcontracting small firms mainly which produced assembling components, the technical enhancement and factory (semi-) automation, and the enrichment of service industries for estate management, finance, distribution and retailing which supported and complemented the production of goods. In this process, enabling capital to extend and elaborate its domination over space through the reorganization of regulating systems, the Fordist division of labour generated a socio-spatial hierarchy in the nation-wide scale that characterized: the Seoul Metropolitan region as an overmaturated (or overarching) Fordist region performing the conceptive functions of management, research and development, in which all types of industry (including service industries) tended to be reconcentrated; Kyungsang region as a maturated Fordist region with excutive branches of large conglomerates and with subcontracting firms around them which produced standardized products through the automized production processes in secialized Fordist industries or rationalized traditional industries; and Jeolla and Chungchong regions as newly devloping Fordist regions with newly migrated branches and some subcontracting small firms-in relatively older Fordist industries or partly rationalized traditional industries. From these analyses, it can be argued that the structural adjustment of the Korean industry in the 1980s, which had carried out both through the extensive expansion and the intensive deveiopment, strengthened further uneven regional development process, even though it appears to have reduced apparently the economic and regional disparity by balancing numerically large and small firms and by extending the Fordist industrial space nation-wideiy. And it seems more persuasive to see that the Korean industrial structure in the 1980s maturated the Fordist system of accumulation, but not yet transformed towards the post-Fordist (or the so-called flexible) accumulation system, even though the Korean economy in the 1990s seems to be under a pressure of restructuring towards the latter system.

• Clean Technology
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• v.24 no.4
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• pp.371-379
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• 2018

The objective of this study is to develop a platinum/hexaaluminate pellet catalyst for the decomposition of eco-friendly liquid propellant. Pellet catalysts using hexaaluminate prepared by ultrasonic spray pyrolysis as a support and platinum as an active metal were prepared by two methods. In the case of the pellet catalyst formed by loading the platinum precursor onto the hexaaluminate powder and then adding the binder (M1 method catalyst), the mesopores were well developed in the catalyst after calcination at $550^{\circ}C$. However, when this catalyst was calcined at $1,200^{\circ}C$, the mesopores almost collapsed and only a few macropores existed. On the other hand, in the case of a catalyst in which platinum was supported on pellets after the pellet was produced by extrusion of hexaaluminate (M2 method catalyst), the surface area and the mesopores were well maintained even after calcination at $1,200^{\circ}C$. Also, the catalyst prepared by the M2 method showed better heat resistance in terms of platinum dispersion. The effects of preparation method and calcination temperature of Pt/hexaaluminate pellet catalysts on the decomposition of liquid propellant composed mainly of ammonium dinitramide (ADN) or hydroxyl ammonium nitrate (HAN) were investigated. It was confirmed that the decomposition onset temperature during the decomposition of ADN- or HAN- based liquid propellant could be reduced significantly by using Pt/hexaaluminate pellet catalysts. Especially, in the case of the catalyst prepared by the M2 method, the decomposition onset temperature did not show a large change even when the calcination temperature was raised at $1,200^{\circ}C$. Therefore, it was confirmed that Pt/ hexaaluminate pellet catalyst prepared by M2 method has heat resistance and potential as a catalyst for the decomposition of the eco-friendly liquid propellants.