• Korean Journal of Construction Engineering and Management
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• v.10 no.3
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• pp.139-147
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• 2009

Accurate construction cost estimation in the initial stage of building project plays a key role for project success and for mitigation of disputes. Total construction cost(TCC) estimation of apartment projects in Vietnam has become more important because those projects increasingly rise in quantity with the urbanization and population growth. This paper presents the application of artificial neural networks(ANNs) in estimating TCC of apartment projects. Ninety-one questionnaires were collected to identify input variables. Fourteen data sets of completed apartment projects were obtained and processed for training and generalizing the neural network(NN). MATLAB software was used to train the NN. A program was constructed using Visual C++ in order to apply the neural network to realistic projects. The results suggest that this model is reasonable in predicting TCCs for apartment projects and reinforce the reliability of using neural networks to cost models. Although the proposed model is not validated in a rigorous way, the ANN-based model may be useful for both practitioners and researchers. It facilitates systematic predictions in early phases of construction projects. Practitioners are more proactive in estimating construction costs and making consistent decisions in initial phases of apartment projects. Researchers should benefit from exploring insights into its implementation in the real world. The findings are useful not only to researchers and practitioners in the Vietnam Construction Industry(VCI) but also to participants in other developing countries in South East Asia. Since Korea has emerged as the first largest foreign investor in Vietnam, the results of this study may be also useful to participants in Korea.

• Journal of Korean Society of Forest Science
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• v.88 no.3
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• pp.400-407
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• 1999

The purpose of thin paper is to test difference of the two question formats, open-ended and dichotomous choice formats, in the contingent valuation method using the estimated recreational benefits. The data were collected from the visitors at the Songnisan National Park. The recreational benefit based on the equivalent variation. The two question formats, but the same content, were asked of the same individuals. In this analysis, it was used travel cost and monthly income as the exogenous variables, which assumed a linear functional form for the WTP equation. The model assumed a bivariate normal distribution on the basis of the probit and tobit model concerning the censored zero WTP. The result showed no differences in the recreational benefits from the different question formats under a same respondent. The mean benefit was estimated 25.556 Won per 5 years per visitors.

• Journal of Korean Society of Transportation
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• v.32 no.4
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• pp.401-409
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• 2014

This study deals with capacity expansion planning of airport infrastructure in view of economic validation that reflect construction costs and social benefits according to the reduction of passengers' delay time. We first forecast the airport peak-demand which has a seasonal and cyclical feature with ARIMA model that has been one of the most widely used linear models in time series forecasting. A discrete event simulation model is built for estimating actual delay time of passengers that consider the passenger's dynamic flow within airport infrastructure after arriving at the airport. With the trade-off relationship between cost and benefit, we determine an economic quantity of conveyor that will be expanded. Through the experiment performed with the case study of Incheon international airport, we demonstrate that our approach can be an effective method to solve the airport expansion problem with seasonal passenger arrival and dynamic operational aspects in airport infrastructure.

• The Journal of Korean Institute of Information Technology
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• v.17 no.7
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• pp.123-131
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• 2019

In this paper, related studies were investigated by dividing them into cost-benefit analysis, security continuity services, and SW-centric calculations. The case analysis was conducted on A institutions in the United States, Japan and South Korea. Based on this, an improvement model was prepared through comparison with the current system. The SCS(Security Continuity Service) performance evaluation system-based information protection service cost calculation model is proposed. This method applies a service level agreement(SLA) and NIST Cybersecurity framework that are highly effective through cost-effectiveness analysis and calculates consideration based on characteristics, performance criteria, and weights by information protection service. This model can be used as a tool to objectively calculate the cost of information protection services at public institutions. It is also expected that this system can be established by strengthening the current recommended statutory level to the enforceability level, improving the evaluation system of state agencies and public institutions, introducing a verification system of information protection services by national certification bodies, and expanding its scope to all systems.

• Management Science and Financial Engineering
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• v.10 no.1
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• pp.25-41
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• 2004

There have been many studies to build a model that can help investors construct optimal portfolio. Most of the previous models, however, are based upon the path-breaking Markowitz model (1959) which is a quantitative model. One of the most important problems with that kind of quantitative model is that, in reality, most of the investors use not only quantitative, but also qualitative information when they select their optimal portfolio. Since collecting both types of information from the markets are time consuming and expensive, making a set of target assets smaller, without suffering heavy loss in the rate of return, would attract investors. To extract only desired assets among all available assets, we need knowledge that identifies investors' preference for the risk of the assets. This study suggests two-layer decision-making rules capable of identifying an investor's risk preference and an architecture applying them to a quantitative portfolio model based on risk and expected return. Our knowledge-based portfolio system is to build an investor's preference-oriented portfolio. The empirical tests using the data from Korean capital markets show the results that our model contributes significantly to the construction of a better portfolio in the perspective of an investor's benefit/cost ratio than that produced by the existing portfolio models.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1790-1806
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• 2015

Utility-based routing is a special type of routing approach using a composite utility metric when making routing decisions in ad hoc and sensor networks. Previous studies on the utility-based routing all use fixed retry limit and a very simple distance related energy model, which makes the utility maximization less efficient and the implementation separated from practice. In this paper, we refine the basic utility model by capturing the correlation of the transmit power, the retry limit, the link reliability and the energy cost. A routing algorithm based on the refined utility model with adaptive transmit power and retry limit allocation is proposed. With this algorithm, packets with different priorities will automatically receive utility-optimal delivery. The design of this algorithm is based on the observation that for a given benefit, there exists a utility-maximum route with optimal transmit power and retry limit allocated to intermediate forwarding nodes. Delivery along the utility-optimal route makes a good balance between the energy cost and the reliability according to the value of the packets. Both centralized algorithm and distributed implementations are discussed. Simulations prove the satisfying performance of the proposed algorithm.

• Management Science and Financial Engineering
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• v.16 no.3
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• pp.21-47
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• 2010

Quantity discounts provide a practical foundation for supply chain inventory policies, improving the supplier's profit and reducing the buyer's inventory cost simultaneously. Traditional quantity-discount research, which deals with inventory coordination between a buyer and a supplier, is extended to a stationary stochastic environment. This research shows that the magnitude of the optimal discounts scheduled by the deterministic quantity discount models may not be large enough to cover the buyer's additional inventory stocking risks under uncertain conditions. As a result, the buyer's total inventory cost may often increase rather than decrease. In contrast, the proposed model allows the supplier to identify the discount level, which shares the buyer's amplified risk associated with temporary overstocking and ensures that both buyer and supplier benefit economically. The performance of the proposed model was tested in the continuous review environments via numerical experiments. The experimental results support the proposed method as a feasible alternative in coordinating inventory decisions under stochastic demand.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.4157-4175
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• 2020

Moving target defense, as a 'game-changing' security technique for network warfare, realizes proactive defense by increasing network dynamics, uncertainty and redundancy. How to select the best countermeasure from the candidate countermeasures to maximize defense payoff becomes one of the core issues. In order to improve the dynamic analysis for existing decision-making, a novel approach of selecting the optimal countermeasure using game theory is proposed. Based on the signal game theory, a multi-stage adversary model for dynamic defense is established. Afterwards, the payoffs of candidate attack-defense strategies are quantified from the viewpoint of attack surface transfer. Then the perfect Bayesian equilibrium is calculated. The inference of attacker type is presented through signal reception and recognition. Finally the countermeasure for selecting optimal defense strategy is designed on the tradeoff between defense cost and benefit for dynamic network. A case study of attack-defense confrontation in small-scale LAN shows that the proposed approach is correct and efficient.

• KEPCO Journal on Electric Power and Energy
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• v.1 no.1
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• pp.67-71
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• 2015

The concept known as Vehicle-to-Grid (V2G) is to provide power to help balance loads by charging at night when demand is low and sending power to the grid when demand is high. Therefore, it is important to model the cost-benefit characteristics of Electric vehicle(EV)'s operation considering the negawatt market in real time. This paper proposes a methodology to formulate the various costs and economic benefits for sending the EV's power back to the grid, including a concept of inconvenience costs caused by operating the EV as a battery. This paper also introduces the general decision-making process based on the cost-benefit analysis in order to simulate the reasonable participation of V2G service. In the case study, it is confirmed by two-case simulations that the proposed approach is useful to help EV owners' decision-making. In the future, it is expected that the proposed methodology can be used as a decision-making guideline to help prepare the EV' power transmission.

• Journal of The Korean Society of Clinical Toxicology
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• v.19 no.1
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• pp.1-7
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• 2021

Purpose: The purpose of this study was to conduct a systematic review to investigate the socio-economic benefits of the poison control center (PCC) and to assess whether telephone counseling at the poison control center affects the frequency of emergency room visits, hospitalization, and length of stay of patients with acute poisoning. Methods: The authors conducted a medical literature search of the PubMed, EMBASE, and Cochrane Library databases. Two reviewers evaluated the abstracts for eligibility, extracted the data, and assessed the study quality using a standardized tool. Key results such as the cost-benefit ratio, hospital stay days, unnecessary emergency room visits or hospitalizations, and reduced hospital charges were extracted from the studies. When meta-analysis was possible, it was performed using RevMan software (RevMan version 5.4). Results: Among 299 non-duplicated studies, 19 were relevant to the study questions. The cost-benefit ratios of PCC showed a wide range from 0.76 to 36 (average 6.8) according to the level of the medical expense of each country and whether the study included intentional poisoning. PCC reduced unnecessary visits to healthcare facilities. PCC consultation shortened the length of hospital stay by 1.82 (95% CI, 1.07-2.57) days. Conclusion: The systematic review and meta-analysis support the hypothesis that the PCC operation is cost-beneficial. However, when implementing the PCC concept in Korea in the future, it is necessary to prepare an institutional framework to ensure a costeffective model.