• Proceedings of the KSME Conference
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• 2004.11a
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• pp.1756-1760
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• 2004

Circulating Fluidized-Bed (CFB) boilers which have been operated in Korea were manufactured by the design technology of foreign leading companies. As they are not active to transfer their technology, domestic companies don't have the enough ability to design it independently yet. Doosan Heavy Industries & Construction Co. Ltd. and Korean Institute of Energy Research are trying to develop and improve the particle re-circulating device among the components of CFB boiler. Our purpose is to control the amount of particles leaving the re-circulating system by adjusting utility air and reuse the heat of circulating particles. The results of experiments with cold model system show that a fluidization state in the particle re-circulating device is very stable when the amount of utility air is supplied to its wind box with 2.29 times of minimum fluidization velocity. Also the amount of particles entering the riser don't increase linearly when the amount of utility air is supplied over 2.5 times of minimum fluidization velocity. Now we are testing its functional run with the hotstate experiment set-up.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5731-5754
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• 2019

In this paper, we redesign, implement, and evaluate ShareSafe (Based on SecGraph), an open-source secure graph data sharing/publishing platform. Within ShareSafe, we propose De-anonymization Quantification Module and Recommendation Module. Besides, we model the attackers' background knowledge and evaluate the relation between graph data privacy and the structure of the graph. To the best of our knowledge, ShareSafe is the first platform that enables users to perform data perturbation, utility evaluation, De-A evaluation, and Privacy Quantification. Leveraging ShareSafe, we conduct a more comprehensive and advanced utility and privacy evaluation. The results demonstrate that (1) The risk of privacy leakage of anonymized graph increases with the attackers' background knowledge. (2) For a successful de-anonymization attack, the seed mapping, even relatively small, plays a much more important role than the auxiliary graph. (3) The structure of graph has a fundamental and significant effect on the utility and privacy of the graph. (4) There is no optimal anonymization/de-anonymization algorithm. For different environment, the performance of each algorithm varies from each other.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.12
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• pp.597-602
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• 2002

The restructuring of power industry is still going on all over the world for last several decades. Many kinds of restructuring model have been studied, proposed, and applied. Among those models, power pool is more popular than other. This paper assumes the power pool market structure having competitive generation sector, and a new method is presented to build a bidding strategy in that market. The utilities participating in the market have the perfect information of their cost and price functions, but they don't know which strategy to be chosen by others. To define one's strategy as a vector, we make utility's cost/price functions into discrete step functions. An utility knows only his own strategy, so he estimates the other's cost/price functions into discrete step functions. An utility knows only his own strategy, so he estimates the other's strategy using Nash equilibrium or stochastic methods. And he also has to forecast the system demand. According to this forecasting result, his payoffs can be changed. Considering these all conditions, we formulate a bidding game problem and apply noncooperative game theory to that problem for the optimal strategy or solution. Some restrictive assumption are added for simplification of solving process. A numerical example is given in Case Study to show essential features and concrete results of this approach.

• Proceedings of the Technology Innovation Conference
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• 1999.06a
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• pp.245-265
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• 1999

MAUT and AHP are widely used for quantification of subjective judgements in various fields of decision making. This study focuses on the introduction and application of MAUT/AHP method which is a hybrid of MAUT and AHP techniques in R&D project priority setting. This hybrid model can clarify each factors' contribution using MAUT method and can reduce the number of pairwise comparisons of AHP method. This study applies AMUT/AHP method to the evaluation of R&D projects in a Government - funded research institute. To evaluate R&D projects, six evaluation factors are derived. SMART(Simple MultiAttribute Rating Technique) and DVM(Difference Value Measurement ) out of many MAUT methods are used to design the utility function ad AHP is used to allocate the weights among evaluation factors. The major findings of this study can be summarized as follows. First, the SMART/AHP and the DVM/AHP have the same results with the SMART and the DVM, and they are different results with AHP. It is very hard to decide which one is better. Second, MAUT/AHP's strength is analyzed. MAUT reflects utility values of evaluators to alternatives and AHP results objective and consistent weights of factors through pariwise comparisons. Third, its possible application fields are proposed. It is applicable to subjective decision making problems with high complexity and inter-independent factors.

• Proceedings of the KIEE Conference
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• 2001.11b
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• pp.57-59
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• 2001

The restructuring of power industry is still going on all over the world for last several decades. Many kinds of restructuring model has been studied, proposed, and applied. Among those models, power pool is more popular than others. This paper assumes the power pool market structure having competitive generation sector and a new method is presented to build bidding strategy in that market. The utilities participating in the market have the perfect information on their cost and price functions, but they don't know the strategy to be chosen by others. To define one's strategy as a vector, we make utility's cost/price function into discrete step function. An utility knows only his own strategy, so he estimates the other's strategy using stochastic methods. For considering these conditions, we introduce the Bayesian rules and noncooperative game theory concepts. Also additional assumptions are included for simplification of solving process. Each utility builds the strategy to maximize his own expected profit function using noncooperative Bayesian game. A numerical example is given in case study to show essential features of this approach.

• Proceedings of the KOR-KST Conference
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• 2000.02a
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• pp.25-47
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• 2000

In route guidance systems fastest-path routing has typically been adopted because of its simplicity. However, empirical studies on route choice behavior have shown that drivers use numerous criteria in choosing a route. The objective of this study is to develop computationally efficient algorithms for identifying a manageable subset of the nondominated (i.e. Pareto optimal) paths for real-time vehicle routing which reflect the drivers' preferences and route choice behaviors. We propose two pruning algorithms that reduce the search area based on a context-dependent linear utility function and thus reduce the computation time. The basic notion of the proposed approach is that ⅰ) enumerating all nondominated paths is computationally too expensive, ⅱ) obtaining a stable mathematical representation of the drivers' utility function is theoretically difficult and impractical, and ⅲ) obtaining optimal path given a nonlinear utility function is a NP-hard problem. Consequently, a heuristic two-stage strategy which identifies multiple routes and then select the near-optimal path may be effective and practical. As the first stage, we utilize the relaxation based pruning technique based on an entropy model to recognize and discard most of the nondominated paths that do not reflect the drivers' preference and/or the context-dependency of the preference. In addition, to make sure that paths identified are dissimilar in terms of links used, the number of shared links between routes is limited. We test the proposed algorithms in a large real-life traffic network and show that the algorithms reduce CPU time significantly compared with conventional multi-criteria shortest path algorithms while the attributes of the routes identified reflect drivers' preferences and generic route choice behaviors well.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.3892-3912
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• 2021

The recent rapid growth of mobile network traffic places multi-access edge computing in an important position to reduce network load and improve network capacity and service quality. Contrasting with traditional mobile cloud computing, multi-access edge computing includes a base station cooperative cache layer and user cooperative cache layer. Selecting the most appropriate cache content according to actual needs and determining the most appropriate location to optimize the cache performance have emerged as serious issues in multi-access edge computing that must be solved urgently. For this reason, a cache placement algorithm based on comprehensive utility in big data multi-access edge computing (CPBCU) is proposed in this work. Firstly, the cache value generated by cache placement is calculated using the cache capacity, data popularity, and node replacement rate. Secondly, the cache placement problem is then modeled according to the cache value, data object acquisition, and replacement cost. The cache placement model is then transformed into a combinatorial optimization problem and the cache objects are placed on the appropriate data nodes using tabu search algorithm. Finally, to verify the feasibility and effectiveness of the algorithm, a multi-access edge computing experimental environment is built. Experimental results show that CPBCU provides a significant improvement in cache service rate, data response time, and replacement number compared with other cache placement algorithms.

• Asia Marketing Journal
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• v.18 no.3
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• pp.47-63
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• 2016

Rational choice theory holds that the alternative with largest expected utility in the choice set should always be chosen. However, it is often observed that an alternative with the largest expected utility is not always chosen while the choice task itself being avoided. Such a choice phenomenon cannot be explained by the traditional expected utility maximization principle. The current study posits shows that such a phenomenon can be attributed to the gap between the expected perceived gain (or loss) and the expected perceived value. This study mathematically analyses the relationship between the expectation of an alternative's gains or losses over the reference point and its expected value, when the perceived gains or losses follow continuous probability distributions. The proposed expected value (EV) function can explain the effects of loss aversion and uncertainty on the evaluation of an alternative based on the prospect theory value function. The proposed function reveals why the expected gain of an alternative should exceed some positive threshold in order for the alternative to be chosen. The model also explains why none of the two equally or similarly attractive options is chosen when they are presented together, but either of them is chosen when presented alone. The EV function and EG-EV curve can extract and visualize the core tenets of the prospect theory more clearly than the value function itself.

• Progress in Superconductivity and Cryogenics
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• v.8 no.2
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• pp.20-24
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• 2006

Recently, utility network is becoming more and more complicated and huge due to IT and OA devices. In addition to, demands of power conversion devices which have non-linear switching devices are getting more and more increased. Consequently, because of the non-linear power semiconductor devices, current harmonics are unavoidable. Sometimes those current harmonics flow back to utility network and become one of the main reasons which can make the voltage distortion. Also, it makes noise and heat loss. On the other hands, voltage sag from sudden increasing loads is also one of the terrible problems inside of utility network. In order to compensate the current harmonics and voltage sag problem, AF(active filter) systems could be a good solution method. SMES is a very good promising source due to it's high response time of charge and discharge. Therefore, the combined AF and SMES system can be a wonderful device to compensate both harmonics current and voltage sag. However, SMES needs a superconducting magnetic coil. Because of using this superconducting magnetic coil, quench problem caused by unexpected reasons have always been unavoidable. Therefore, to solve out mentioned above, this paper presents a decisive method using shunt and series active filter system combined with SMES. Especially, authors analyzed the change of original energy capacity of SMES regarding to the size of resistance caused by quench of superconducting magnetic coil.

• Journal of Korean Society of Transportation
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• v.26 no.1
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• pp.145-153
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• 2008

Existing shortest-path algorithms mainly consider a single attribute. But traveler actually chooses a route considering not single attribute but various attributes which are synthesized travel time, route length, personal preference, etc. Therefore, to search the optimal path, these attributes are considered synthetically. In this study route searching algorithm which selects the maximum utility route using discrete choice model has developed in order to consider various attributes. Six elements which affect route choice are chosen for the route choice model and parameters of the models are estimated using survey data. A multinomial logit models are developed to design the function of route choice model. As a result, the model which has route length, delay time, the number of turning as parameter is selected based on the significance test. We use existing shortest path algorithm, which can reflect urban transportation network such as u-turn or p-turn, and apply it to the real network.