• Journal of ILASS-Korea
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• v.19 no.3
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• pp.115-122
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• 2014

As a demand for an automobile increases, air pollution and a problem of the energy resources come to the fore in the world. Consequently, governments of every country established ordinances for green-house gas reduction and improvement of air pollution problem. Especially, as international oil price increases, engine using clean energy are being developed competitively with alternative transportation energy sources development policy as the center. Bio ethanol, one of the renewable energy produced from biomass, gained spotlight for transportation energy sources. Studies are in progress to improve fuel supply methods and combustion methods which are key features, one of the engine technologies. DI(Direct Injection), which can reduce fuel consumption rate by injecting fuel directly into the cylinder, is being studied for Green-house gas reduction and fuel economy enhancement at SI(Spark Ignition). GDI(Galoine Direct Injection) has an advantage to meet the regulations for fuel efficiency and $CO_2$ emissions. However it produces increased number of ultrafine particles, that yet received attention in the existing port-injection system, and NOX. As fuel is injected into the cylinder with high-pressure, a proper injection strategy is required by characteristics of a fuel. Especially, when alcohol type fuel is considered. In this study, we tried to get a base data bio-ethanol mixture in GDI, and combustion for optimization. We set fuel mixture rate and fuel injection pressure as parameters and took a picture with a high speed camera after gasoline-ethanol mixture fuel was injected into a constant volume combustion chamber. We figured out spraying characteristic according to parameters. Also, we determine combustion characteristics by measuring emissions and analyzing combustion.

• Journal of the Economic Geographical Society of Korea
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• v.16 no.4
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• pp.647-669
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• 2013

Depletion of fossil fuels and sharp rise of international oil price as well as climate worming and frequent environmental disasters have required to strengthen resource(esp. energy) and environmental policy and discourse. And hence highly influential discourses and policies such as the concept of sustainable development and strategy for carbon regulation have been developed and pursued world-widely. But these concept and strategy have seemed to be subsumed in the process of neoliberalism, so as to have little effective results. This leads us to energy transition and energy autonomy or autarky as alternative strategic and normative concepts. Daegu has shown strong interests in urban energy problems relatively earlier than other cities, and developed the so-call 'Solar City' project. But it could not properly tackled with the problems, while tending to meet with the global imperatives. This paper considers urban energy problems and energy policy of Daegu with its significance and limitations, and suggests 4 principles for urban energy transition and autonomy with some concrete alternative measures; that is, the transition from fossil and nuclear energy to renewable energy, the transition from supply-led policy to demand side focusing policy, the transition from central governing energy system to locally distributed one, and the transition from market-dependent management to citizen-participatory energy governance.

• Journal of Digital Convergence
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• v.14 no.7
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• pp.145-154
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• 2016

The purpose of this study was to carry out comparative analysis on the world major liner shipping companies' ship investment strategy using Fuzzy-AHP model. In this study, the ship investment factors were firstly selected by literature review and finally adopted them by in-depth interview with experts who had working experiences over 15 years in the field of shipping business. As suggested in the previous research, the liner shipping companies have been classified into four types such as 'ship investment irrelevant to market trend'(Type1), 'ship investment before market rise'(Type2), 'market decline after participation in excessive orders'(Type3), 'avoidance of ship investment during market rise'(Type4) and the comparative analysis were conducted among four ship investment types. According to the results of analysis, ship investment priority in Type1 was freight rates(0.132), price of used ship(0.121) and fleet(0.103). The priority in Type2 was freight rates(0.134), need for ship owner(0.113) and public funding(0.109). Type3 put its priority in freight rates(0.173), fleet(0.169) and the changes in international circumstances(0.121). Type4 considered freight rates(0.239), fleet(0.232) and oil price(0.150) as its priority.

• International Journal of Naval Architecture and Ocean Engineering
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• v.6 no.2
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• pp.187-205
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• 2014

The global price of oil, which is both finite and limited in quantity, has been rising steadily because of the increasing requirements for energy in both developing and developed countries. Furthermore, regulations have been strengthened across all industries to address global warming. Many studies of hull resistance, propulsion and operation of ships have been performed to reduce fuel consumption and emissions. This study examined the design parameters of the propeller boss cap fin (PBCF) and hub cap for 6,000TEU container ships to improve the propulsion efficiency. The design parameters of PBCF have been selected based on the geometrical shape. Computational fluid dynamics (CFD) analysis with a propeller open water (POW) test was performed to check the validity of CFD analysis. The design of experiment (DOE) case was selected as a full factorial design, and the experiment was analyzed by POW and CFD analysis. Analysis of variance (ANOVA) was performed to determine the correlation among design parameters. Four design alternatives of PBCF were selected from the DOE. The shape of a propeller hub cap was selected as a divergent shape, and the divergent angle was determined by the DOE. Four design alternatives of PBCF were attached to the divergent hub cap, and the POW was estimated by CFD. As a result, the divergent hub cap with PBCF has a negative effect on the POW, which is induced by an increase in torque coefficient. A POW test and cavitation test were performed with a divergent hub cap with PBCF to verify the CFD result. The POW test result showed that the open water efficiency was increased approximately 2% with a divergent hub cap compared to a normal cap. The POW test result was similar to the CFD result, and the divergent hub cap with the PBCF models showed lower open water efficiency. This was attributed to an increase in the torque coefficient just like the CFD results. A cavitation test was performed using the 2 models selected. The test result showed that the hub vortex is increased downstream of the propeller.

• Journal of Navigation and Port Research
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• v.38 no.1
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• pp.81-87
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• 2014

Today, it is a trend that the demand of offshore plants is constantly growing, along with the advances in technology which are thoroughly needed to the rise of international oil price as well as offshore energy development. In addition, The main sectors of ship building, sale & purchase and chartering market regarding various kind of offshore supporting vessels that supports the business of offshore energy development is now maintaining its steady growth. However, in domestic case, the contract of time charter occasions regarding the offshore support vessel are almost non-existing situation. Thus, the relevant practical study regarding to implementation of various kinds of legal disputes and applicable laws that can be properly applied in time charter and the field of sale & purchase needs to be conducted actively. Therefore, the concept of this study has included the wide comparisons of other special provisions with the existing time-charter by making its base on "Supply Time 2005" which is the worldwide standard form of time charter in offshore support vessel market and its investigation, aiming to provide practical guidance and procedure for implementation of arbitration and applicable law issues which can be applied in legal disputes between parties.

• Journal of the Korea Convergence Society
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• v.9 no.7
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• pp.231-240
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• 2018

Automobile industry is facing a variety of risks, including the rise of international oil price and the increase of car prices. In addition to the government's deregulation, efforts should be made to improve management aiming at higher production efficiency. In this study, we established a model for evaluating the procurement logistics based on the Fuzzy-AHP-TOPSIS by using the factors that are actually used in real companies aimed at the improvement of procurement logistics. A total of three automobile factories of Company G were chosen as the evaluation subject. In the result of the Fuzzy-AHP analysis that was conducted on a sample of three car factories, solving the long-term quality problems, minimizing the stop time due to the shortage of materials, preventing the of equipment accident, and solving the short-term quality problems were proven to be the most important factors. TOPSIS analysis result indicated that Factory B had the best procurement logistics. Our study has significance that it can contribute to the improvement of efficiency in the automobile industry as the evaluation model suggested in this study can be used for regular evaluation related to the procurement logistics in the future.

• Journal of the Mineralogical Society of Korea
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• v.23 no.3
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• pp.199-209
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• 2010

Coal gasification technology in the sector of domestic clean coal technologies is being into the limelight since recent dramatic rise of international oil price. In this study, we used a low rank coal from Inner Mongolia, China as a starting material for gasification. Various properties including optical, mineralogical, X-ray spectroscopic, X-ray diffraction, and drying property were measured and tested in order to estimate the suitability of the coal to gasification. The coal was identified as a brown coal of lignite group from the measurement of vitrinite reflectance. The coal has very low slagging and fouling potentials, and the ignition temperature is about $250^{\circ}C$. The major impurities consist of quartz, siderite, and clay minerals. Additionally, the coal had moisture content above 28%. Tests for finding effective drying method showed that the microwave drying is more effective than thermal drying.

• Korean Journal of Construction Engineering and Management
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• v.19 no.3
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• pp.89-96
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• 2018

This study derived big issues in overseas construction through big data analysis. To derive big issues in overseas construction, candidate groups of big issues were identified through big data analysis targeting 53,759 issues including 39,436 issues from major portal sites, 10,387 issues from daily newspapers, and 336 issues in construction magazines from Oct. 1, 2016 to Sep. 30, 2017. The main results are as follows: First, the main issues of overseas construction for the past one year showed that markets were concentrated in Middle East Asia and most of them were low-price order plant projects, which revealed the limitations. Although orders of overseas construction were slightly upward in the first half of 2017 compared to previous year, overseas construction orders are still unstable due to uncertainties in the international affairs and drops in oil prices. Second, the interest topics based on the 8th core keywords of overseas construction among the overseas construction issues for the past one year showed that region (29.9%), corporation environment (22.0%), profitability (17.0%), organizations (15.1%), projects (5.2%), market environment (3.6%), policy and system (3.6%), and education (3.5%) in the order of interest. Third, 10 core issues that have expandability and persistence of discourse were extracted out of 30 issue candidates with regard to eight keywords. Based on the extracted issues, detailed analysis on each of the core issues in overseas construction and correlation analysis between 10 core issues were conducted.

• Journal of Biosystems Engineering
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• v.41 no.4
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• pp.328-336
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• 2016

Purpose: The heat culture areas of greenhouses have been continuously increasing. In the face of international oil price fluctuations, development of energy saving technologies is becoming essential. To save energy, auxiliary heat source and thermal insulation technologies are being developed, but they lack cost-efficiency. The present study was conducted to save energy by developing a conceptually new semi-basement type greenhouse. Methods: A semi-basement type greenhouse, was designed and constructed in the form of a three quarter greenhouse as a basic structure, which is an advantageous structure to inflow sunlight. To evaluate the performance of the developed greenhouse, a similar structured general greenhouse was installed as a control plot, and heating tests were conducted under the same crop growth conditions. Results: Although shadows appeared during the winter in the semi-basement type greenhouse due to the underground drop, the results of crop growth tests indicated that there were no differences in crop growth and development between the semi-basement type greenhouse and the control greenhouse, indicating that the shadows did not affect the crop up to the height of the crop growing point. The amount of fuel used for heating from January to March was almost the same between the two greenhouses for tests. The heating load coefficients of the experimental greenhouses were calculated as $3.1kcal/m^2{\cdot}^{\circ}C{\cdot}h$ for the semi-basement type greenhouse and $2.9kcal/m^2{\cdot}^{\circ}C{\cdot}h$ for the control greenhouse. Since the value is lower than the double layer PE (polyethylene) film greenhouse value of $3.5kcal/m^2{\cdot}^{\circ}C{\cdot}h$ from a previous study, Tthe semi-basement type greenhouse seemed to have energy saving effects. Conclusions: The semi-basement type greenhouse could be operated with the same fuel consumption as general greenhouses, even though its underground portion resulted in a larger volume, indicating positive effects on energy saving and space utilization. It was identified that the heat losses could be reduced by installing a thermal curtain of multi-layered materials for heat insulation inside the greenhouse for the cultivation of horticultural products by installing thermal curtain of multi-layered materials for heat insulation inside the greenhouse, it was identified that the heat losses could be reduced.

• 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.