• Proceedings of the Korean Information Science Society Conference
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• 2004.04a
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• pp.691-693
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• 2004

Mobile Ad hoc network은 stationary infrastructure의 도움 없이 이동 노드들이 필요 시 multi-hop wireless links network 형태를 구성하여 통신이 이루어지게 하는 network이다. 따라서 효율적인 라우팅 프로토콜의 개발이 중요한 issue인데 최근에는 routing overhead가 적은 on-demand 프로토콜이 주목을 받고 있다. On-demand 프로토콜은 새로운 route을 구성하기 위해서 query packet을 broadcasting하게 되는데, 특히 노드들의 mobility가 많은 mobile ad hoc network(MANET)의 경우에는 더욱더 자주 발생하게 되는데, blind broadcasting은 neighbor 노드들 간의 radio transmission region overlap에 의해 redundancy, contention, collision 같은 broadcast storm 문제를 발생시키게 된다. 본 논문은 on-demand 프로토콜의 broadcast storm 문제를 해결하기 위해 Neighbor Topology을 고려 한 Dynamic Adaptation Query flooding scheme을 제시한다. 또한 Dynamic Adaptive Query flooding scheme은 broadcast storm 문제 해결뿐만 아니라 network의 congestion을 감소시켜 data packet의 성능 향상에도 기여 할 것이다.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.25 no.3
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• pp.101-107
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• 2017

Demand for air transportation in Korea keeps increasing, and the number of airport operations also grows as a result. The major two airports in Korea, Incheon International Airport and Gimpo International Airport, share the metropolitan airspace, which is crowd with air traffic. As air traffic increases in the metropolitan airspace, the demand for the airport operations would outnumber the capacities of these airports. However, there is a room to efficiently manage the shortage of the airport capacity due to the different distributions of operations in these airports. This study presents a dynamic slot allocation that allows exchanging slots according to the traffic demand. The dynamic allocation mitigates the airports' capacity problem but the airspace capacity itself should be increased in order to tackle the problem fundamentally.

• Journal of Information Technology Applications and Management
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• v.24 no.2
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• pp.81-96
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• 2017

Forecasting long-term mobile service demand is inevitable to establish an effective frequency management policy despite the lack of reliability of forecast results. The statistical forecasting method has limitations in analyzing how the forecasting result changes when the scenario for various drivers such as consumer usage pattern or market structure for mobile communication service is changed. In this study, we propose a dynamic model of the mobile communication service market using system dynamics technique and forecast the future demand for long-term mobile communication subscriber based on the dynamic model, and also experiment on the change pattern of subscriber demand under various scenarios.

• Earthquakes and Structures
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• v.14 no.3
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• pp.203-214
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• 2018

Predictive demand and collapse fragility functions are two essential components of the probabilistic seismic demand analysis that are commonly developed based on statistics with enormous, costly and time consuming data gathering. Although this approach might be justified for research purposes, it is not appealing for practical applications because of its computational cost. Thus, in this paper, Bayesian regression-based demand and collapse models are proposed to eliminate the need of time-consuming analyses. The demand model developed in the form of linear equation predicts overall maximum inter-story drift of the lowto mid-rise regular steel moment resisting frames (SMRFs), while the collapse model mathematically expressed by lognormal cumulative distribution function provides collapse occurrence probability for a given spectral acceleration at the fundamental period of the structure. Next, as an application, the proposed demand and collapse functions are implemented in a seismic fragility analysis to develop fragility and consequently seismic demand curves of three example buildings. The accuracy provided by utilization of the proposed models, with considering computation reduction, are compared with those directly obtained from Incremental Dynamic analysis, which is a computer-intensive procedure.

• Journal of Korean Society of Transportation
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• v.25 no.4
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• pp.99-108
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• 2007

This paper presents an elastic demand stochastic user equilibrium traffic assignment that could not be easily tackled. The elastic demand coupled with a travel performance function is known to converge to a supply-demand equilibrium, where a stochastic user equilibrium (SUE) is obtained. SUE is the state in which all equivalent path costs are equal, and thus no user can reduce his perceived travel cost. The elastic demand SUE traffic assignment can be formulated based on a dynamic system, which is a means of describing how one state develops into another state over the course of time. Traditionally it has been used for control engineering, but it is also useful for transportation problems in that it can describe time-variant traffic movements. Through the Lyapunov Function Theorem, the author proves that the model has a stable solution and confirms it with a numerical example.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.4
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• pp.475-483
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• 1998

Structural changes in an economy system bring about serious problems in establishing economic policies. The boom of middle-east export, the oil shock, and the recent dollar crisis in Korean economy are such examples. Hence, it is necessary to identify and estimate those structural changes. This study focuses on an output and price and analyzes structural changes in aggregate demand and supply. The aggregate demand and supply structures are described by conventional dynamic simultaneous equations model, where each structural change is represented by dummy variables and estimated by the proposed Bayesian method. By applying this model to Korean output and price, structural changes in the aggregate demand and supply are analyzed.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2004.06a
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• pp.386-395
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• 2004

The Korean fuel cycle scenario has been modeled by using the dynamic analysis method. For once-through fuel cycle model, the nuclear power plant construction plan was considered, and the nuclear demand growth rate from the year 2016 was assumed to be 1%. After setup the once-thorough fuel cycle model, the DUPIC and fast reactor scenarios were modeled to investigate the environmental effect of each fuel cycle. Through the calculation of the amount of spent fuel, and the amounts of plutonium and minor actinides were estimated and compared to those of the once-through fuel cycle. The results of the once-through fuel cycle shows that the demand grows to 64 GWe and the total amount of the spent fuel would be 100 kt in the year 2100, while the total spent fuel can be reduced by 50% when the DUPIC scenario is implemented

• Journal of Energy Engineering
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• v.26 no.2
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• pp.80-92
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• 2017

This paper attempts to estimate the diesel fuel demand function in Korea using panel data panel data of 16 major cities or provinces which consist of diesel demands, diesel market prices and gross value added from the year 1998 to 2015. I apply panel GLS(generalized least square) model, fixed effect model, random effect model and dynamic panel model to estimating the parameters of the diesel fuel demand function. The results show that short-run price elasticities of the diesel fuel demand are estimated to be -0.2146(panel GLS), -0.2886(fixed effect), -0.2854(random effect), -0.1905(dynamic panel) respectively. And short-run income elasticities of the diesel fuel demand are estimated to be 0.7379(panel GLS), 0.4119(fixed effect), 0.7260(random effect), 0.4166(dynamic panel) respectively. The short-run price and income elasticities explain that demand for diesel fuel is price- and income-inelastic. The long-run price and income elasticities are estimated to be -0.4784, 1.0461 by dynamic panel model, which means that demand for diesel fuel is price-inelastic but income-elastic in the long run. In addition I apply dummy variable model to estimate the effect of 16 major cities or provinces on diesel demands. The results show that diesel demands is affected 10 regions on the basis of Seoul.

• The Journal of Fisheries Business Administration
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• v.40 no.1
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• pp.133-152
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• 2009

The purpose of this paper is to model price formation and analyze demand structures for fishes under the restriction of Korean fisheries regulations. This study suggests the model that the price of fish is formed by its quantity, expenditure, and habit persistence. In economic literature, such a fishery market demand is called the inverse demand with dynamic habit persistence. Based upon a static differential price formation model, the paper has generalized it dynamically incorporating habit persistence effects. The empirical results show that all the species have values less than one and (-) sign of price flexibilities, thus being price inflexible. The estimated habit adjustment coefficients are significant at the level of 1%. Especially, TAC species have the smaller values of them than those of other main fish species. The contribution and results are summarized as follows. First, the fishery market demand has a strong dynamic effects from habit persistence. Second, the fishery market demand structure could be analyzed in a way different from the ordinary demand analysis, which is based upon price flexibility, scale flexibility, and cross adjustment flexibility. Third, the limitation of this paper is that it ignores the increasing stock effects by catching restrictions, thus raising consumers' benefit in the future.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.3
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• pp.81-93
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• 2005

This paper models supply chain uncertainties in the dynamic Newsboy Problem context. The system consists of one supplier and one retailer who place an order to the supplier every period. Demand uncertainty is modeled as stochastic period demand, and supply uncertainty as the uncertainty in quantities delivered by the supplier. The supplier delivers exactly the amount ordered by the retailer with probability of $\beta$ and the amount minus K with probability of $(1-\beta)$ We formulate the problem as a dynamic programming problem and derive the first-order optimality condition. Through a numerical study, we measure the extent to which the cost decrease due to the reduction in supply uncertainty depends on the level of demand uncertainty. One of the most important findings In this paper is that this cost decrease is relatively small if demand uncertainty is kept high, and vice versa. We also backup this numerical result by analyzing the distribution of ending Inventory under the supply and demand uncertainties.