• Journal of Intelligence and Information Systems
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• v.15 no.2
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• pp.15-31
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• 2009

The next generation IT environment is expected to be an open computing environment based on Grid computing technologies, which allow users to access to any type of computing resources through networks. The open computing environment has benefits in aspects of resource utilization, collaboration, flexibility and cost reduction. Due to the variation in performance of open computing resources, however, resource allocation simply based on users' budget and time constraints often fails to meet the Service Level Agreement(SLA). This paper proposes the Mean-Absolute Deviation(MAD) portfolio optimization approach, in which service brokers consider the uncertainty of performance of resources, and compose resource portfolios that minimize the uncertainty. In order to investigate the effect of this approach, we simulate an open computing environment with varying uncertainty levels, users' constraints, and brokers' optimization strategies. The simulation result concludes threefolds. First, the MAD portfolio optimization improves the success ratio of delivering the required performance to users. Second, the success ratio depends on the accuracy in predicting the variability of performance. Thirdly, the measured variability can also help service brokers expand their service to cost-critical users by discounting the access cost of open computing resources.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2013.06a
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• pp.163-165
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• 2013

IMO(International Maritime Organization) is existed the movement for revising ISM Code so that the maintenance history and the trouble information given trading in a ship can be transferred. An empirical analysis was made on the influence that will have upon shipping industry through surveying on the recognition on ISM Code revision in employees of the relevant field and on the expected problems given being amended ISM Code as the above. In conclusion, the positive effect is judged to be more in the aspect of ship safety, which is the aim of ISM Code, rather than the negative effect, which may take place given being revised ISM Code. In other words, the clean market can be formed through this because fairness is maintained on both sides given trading in a ship by which opening the maintenance record and the trouble history is applied equally to a buyer and a seller. Ships can be reduced a loss of time and cost in preventing similar problems and seeking solution that may appear in important equipments, through this maintenance record. Also, based on these materials, it comes to be available for analyzing a risk of ship and preventing and managing a risk, thereby being increased ability of maintenance and repair in a ship, resulting in being judged to likely contributing to ship safety and environmental-pollution prevention.

• Journal of Energy Engineering
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• v.23 no.2
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• pp.83-92
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• 2014

This paper attempts to conduct a comparative analysis on the economic effects of integrated-energy and manufactured gas supply sectors. To this end, an input-output (I-O) analysis is applied using most recently published 2011 I-O table. In particular, the two sectors are specified as exogeneous to identify the economic effects on own and other sectors. Production-inducing effect, value-added creation effect, and employment-inducing effect are quantified based on demand-driven model. Supply shortage effect and price pervasive effect are analyzed employing supply-driven model and Leontief price model, respectively. The results show that production-inducing effect, value-added creation effect, and employment-inducing effect of integrated-energy and manufactured gas supply sectors are estimated to be 1.5461 vs. 1.0297, 0.4759 vs. 0.1941, and 2.2885 vs. 0.4053 respectively. Price pervasive effects of the 10% increase in integrated-energy and manufactured gas supply sectors are computed to be 0.0127% and 0.1585%, respectively. This information can be utilized in forecasting the economic effects of introducing integrated-energy or manufactured gas as a heating source and the impacts of a rise in price of integrated-energy or manufactured gas on price level of other sectors.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.28-34
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• 2020

A reservoir is defined as an artificial facility that stores and controls water during floods and droughts. Korea has constructed and managed reservoirs all over the country to benefit farming communities. The importance of reservoirs has decreased gradually due to urbanization and the spread of tap water, but the importance of water is increasing because of the recent shortage of water and the resulting rise in the price of water resources. Therefore, this study suggests countermeasures through an analysis of the used threshold for agricultural reservoirs. To this end, the forecast of rainfall up to 2100 was first analyzed using flood estimates and RCP scenarios through rainwater data collection. The increase in the RCP 8.5 scenario, the largest increase in the probability rainfall, was calculated by adding it to the current probability rainfall, and it was predicted that the marginal height of Odong Dam would reach its limit in 2028. Therefore, as a countermeasure against this, the measures to secure effective water storage were suggested through measures, such as lowering the height of Yeosu and installing movable beams. Overall, it is expected that effective management of the reservoirs used for agriculture will be possible in the future.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.51-61
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• 2008

Most of Korea's 15 local airports, with the exception Jeju, Gimpo and Gimhae airports, have been several billion Won in the red each year. It has been reported that one of the causes of the poor financial performance is inaccurate air traffic demand predictions. Under the situation, the entry of low-cost carrier air service using turbo-prop airplanes into the domestic airlines market gets a wide range of support, which is expected to promote the convenience of consumers and help to activate local airports. In this study, the authors (1) suggest a high-speed transport demand model among existing airlines, Korea Train Express (KTX) and low-cost carrier air service; (2) try to make low-cost air carrier demand predictions for a route between Seoul and Daegu through a stated-preference survey; and (3), examine possible effectiveness of selected policy measures by establishing an estimation model. First, fare has a strong influence for mode choice between high-speed transport modes when considering the entry of low-cost carrier air service between Seoul and Daegu. Even low-cost carrier air service fare is set at 38,000 won, which is considerably low compared with that of KTX, in the regions where the total travel time is the same for both low-cost carrier air service and KTX, the probability of selecting low-cost carrier air service is 0.1, which shows little possibility of modal change between high speed transportation means. It is suggested that the fare of low-cost air service between Seoul and Daegu should be within the range of from of 38,000 to 44,000 Won; if it is higher, the demand is likely to be lower than expected.

• Journal of Korean Society of Transportation
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• v.28 no.2
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• pp.65-75
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• 2010

When the cost-benefit analysis is applied for social discount rate(SDR), the choice of SDR to be used in analysis is critical. One of the important issues when public investment project evaluate what is the SDR theory, so there have studied about SDR and no exact answer it so far. In this study, there are three of SDR theories that be estimated social time preference rate, social investment returns and the weighted average method from 1990s, 2000 to 2003 and 2004 to 2008.. First, social time preference method computes consumer's interest rate and the model of Pearce and Ulph(1999). Second, social investment returns method computes private returns of capital. Third, the weighted average method computes the model of Squire, L., Herman G. van der Tak(1975) and private consumption expense and the private investment expense. SDR is estimated in the rage between 2.4% and 3.9% from 2004 to 2008. It is not appropriate that the interest rate was unstable. But it is consider for social equity from present to future generations. Considering this things, downward need to the value of current SDR 5.5%.

• Food Engineering Progress
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• v.15 no.2
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• pp.97-115
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• 2011

A review about the application of response surface methodology in the optimization of food technology is presented. The theoretical principles of response surface methodology and steps for its application are described. The response surface methodologies : three-level full factorial, central composite, Box-Behnken, and Doehlert designs are compared in terms of characteristics and efficiency. Furthermore, recent references of their uses in food technology are presented. A comparison between the response surface designs (three-level full factorial, central composite, Box-Behnken and Doehlert design) has demonstrated that the Box-Behnken and Doehlert designs are slightly more efficient than the central composite design but much more efficient than the three-level full factorial designs.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.121-129
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• 2021

In this study, we try to minimize the tariff risk by constructing a hazardous cargo screening model by applying Association Rule Mining, one of the data mining techniques. For this, the risk level between supply chains is calculated using the Apriori Algorithm, which is an association analysis algorithm, using the big data of the import declaration form of the Korea Customs Service(KCS). We perform data preprocessing and association rule mining to generate a model to be used in screening the supply chain. In the preprocessing process, we extract the attributes required for rule generation from the import declaration data after the error removing process. Then, we generate the rules by using the extracted attributes as inputs to the Apriori algorithm. The generated association rule model is loaded in the KCS screening system. When the import declaration which should be checked is received, the screening system refers to the model and returns the confidence value based on the supply chain information on the import declaration data. The result will be used to determine whether to check the import case. The 5-fold cross-validation of 16.6% precision and 33.8% recall showed that import declaration data for 2 years and 6 months were divided into learning data and test data. This is a result that is about 3.4 times higher in precision and 1.5 times higher in recall than frequency-based methods. This confirms that the proposed method is an effective way to reduce tariff risks.

• Journal of Navigation and Port Research
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• v.46 no.3
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• pp.289-296
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• 2022

The purpose of this study was to investigate the inter-correlation between crude oil prices and Dry Bulk Freight rates. Eco-friendly shipping fuels has being actively developed to reduce carbon emission. However, carbon neutrality will take longer than anticipated in terms of the present development process. Because of OVID-19 and the Russian invasion of Ukraine, crude oil price fluctuation has been exacerbated. So we must examine the impact on Dry Bulk Freight rates the oil prices have had, because oil prices play a major role in shipping fuels. By using the VAR (Vector Autoregressive) model with monthly data of crude oil prices (Brent, Dubai and WTI) and Dry Bulk Freight rates (BDI, BCI and (BP I) 2008.10~2022.02, the empirical analysis documents that the oil prices have an impact on Dry bulk Freight rates. From the analysis of the forecast error variance decomposition, WTI has the largest explanatory relationship with the BDI and Dubai ranks seoond, Brent ranks third. In conclusion, WTI and Dubai have the largest impact on the BDI, while there are some differences according to the ship-type.

• 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.