• Korean Journal of Construction Engineering and Management
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• v.16 no.5
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• pp.114-122
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• 2015

Real estate development requires significant amount of capital investment. The project duration has been increased according to its enlarged size. For this reason, cost overrun and time delay are important risk factors that should be managed properly. As a method to hedge the risk, varoius real option methods have been presented. However, conventional project value assesment methods such as NPV(Net Present Value) have weakness to support decision making by reflecting dynamic situations in terms of variation of cost and time. Furthermore, the decision making process is serious of actions rather than discrete event. The purpose of this paper is to present a multiple real option valuation method to overcome the deterministic aspect of real option presented in previous research and practice. The method is developed as following: firstly, to select the model that can be applied in the real estate development project through a survey from previous literature on real options analysis; secondly, to apply data from office development case in order to verify the model by applying conventional real option and multiple real option valuation. According to analysis result, multiple real option provides enhanced values comparing to NPV and single real option.

• Journal of Korea Technology Innovation Society
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• v.5 no.2
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• pp.141-151
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• 2002

Many technology investment projects can be considered as set of sequential options. A compound real option can be used for evaluating sequential technology investment decisions under significant uncertainty and measuring its value. In this paper, the formula developed by Geske and Johnson(1984) and Buraschi and Dumas(2001) was applied to evaluate the technology investment with related double real option. Also double real option was com-pared with net present value method and multiple linear regression model was used to assess the partial effects of risk free rate and log-term volatility on its value.

• International conference on construction engineering and project management
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• 2007.03a
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• pp.563-572
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• 2007

Transportation infrastructure is critical to economic growth of a country such as China. Careful evaluation of investments in traffic infrastructure projects is therefore pertinent. As traditional evaluation methods do not consider the uncertainty of future cash flows and mobility during project execution, the real option approach is gradually gaining recognition in the context of valuing construction and infrastructure projects. However, many of the cases only evaluate individual options separately although multiple options often exist in a typical large infrastructure project. Using a highway project in China as a case study, this paper first evaluates a deferment option and a growth option embedded in the project. Subsequently, the values are combined using the fuzzy analytical hierarchy process. It is found that the combined value is less than the sum of the two option values. This finding is consistent with the theoretical observations given in past real option literature despite the use of a different approach.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2000.11a
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• pp.259-277
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• 2000

In this paper, we suggest theoretical grounds on the problem of R&D portfolio with different option premiums utilizing the Real Options Model, which has received intensified attention as the method of assessment of R&D project with high risk. Even though there have been many studies focused on the evaluation of option value of single project from technology valuation's perspective. there are few study on the portfolio of multiple technology investment by option value using. This paper bears practical importance by showing simple examples with the option value of investment alternatives and the valuation of related risk, the construction of optimum portfolio in technology investment alternatives.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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• pp.16-22
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• 2019

After Dantzig and Rasmer introduced Vehicle Routing Problem in 1959, this field has been studied with numerous approaches so far. Classical Vehicle Routing Problem can be described as a problem of multiple number of homogeneous vehicles sharing a same starting node and having their own routes to meet the needs of demand nodes. After satisfying all the needs, they go back to the starting node. In order to apply the real world problem, this problem had been developed with additional constraints and pick up & delivery model is one of them. To enhance the effectiveness of pick up & delivery, hub became a popular concept, which often helps reducing the overall cost and improving the quality of service. Lots of studies have suggested heuristic methods to realize this problem because it often becomes a NP-hard problem. However, because of this characteristic, there are not many studies solving this problem optimally. If the problem can be solved in polynomial time, optimal solution is the best option. Therefore, this study proposes a new mathematical model to solve this problem optimally, verified by a real world problem. The main improvements of this study compared to real world case are firstly, make drivers visit every nodes once except hub, secondly, make drivers visit every nodes at the right time, and thirdly, make drivers start and end their journey at their own homes.

• The Transactions of the Korea Information Processing Society
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• v.1 no.3
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• pp.357-366
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• 1994

The IEEE 802.4 token bus has been widely accepted as the standard for factory local area networks. The priority option of the 802.4 standard supports multiple classes of traffic by using a set of timers to control information exchange. The performance of the 802.4 priority mechanism in industrial real time control is examined. A timer assignment technique is presented for such applications. The timers are set to satisfy the worst case access delay requirements of real time control applications. Other applications that are not time constrainted can be supported simultaneously. In fact under certain conditions, such applications can also be guaranteed a minimum bandwidth allocation. Simulation results are used to evaluate the timer assignment and utililization.

• Asia Marketing Journal
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• v.15 no.3
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• pp.159-172
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• 2013

In the present study, we apply the multiple cue probability learning (MCPL) paradigm to examine consumer learning from feedback in repeated trials. This paradigm is useful in investigating consumer learning, especially learning the relationships between the overall quality and attributes. With this paradigm, we can analyze what people learn from repeated trials by using the lens model, i.e., whether it is knowledge or consistency. In addition to introducing this paradigm, we aim to demonstrate that knowledge people gain from repeated trials with feedback is robust enough to weaken one of the most often examined contextual effects, the asymmetric dominance effect. The experiment consists of learning session and a choice task and stimuli are sport rafting boats with motor engines. During the learning session, the participants are shown an option with three attributes and are asked to evaluate its overall quality and type in a number between 0 and 100. Then an expert's evaluation, a number between 0 and 100, is provided as feedback. This trial is repeated fifteen times with different sets of attributes, which comprises one learning session. Depending on the conditions, the participants do one (low) or three (high) learning sessions or do not go through any learning session (no learning). After learning session, the participants then are provided with either a core or an extended choice set to make a choice to examine if learning from feedback would weaken the asymmetric dominance effect. The experiment uses a between-subjects experimental design (2 × 3; core set vs. extended set; no vs. low vs. high learning). The results show that the participants evaluate the overall qualities more accurately with learning. They learn the true trade-off rule between attributes (increase in knowledge) and become more consistent in their evaluations. Regarding the choice task, there is a significant decrease in the percentage of choosing the target option in the extended sets with learning, which clearly demonstrates that learning decreases the magnitude of the asymmetric dominance effect. However, these results are significant only when no learning condition is compared either to low or high learning condition. There is no significant result between low and high learning conditions, which may be due to fatigue or reflect the characteristics of learning curve. The present study introduces the MCPL paradigm in examining consumer learning and demonstrates that learning from feedback increases both knowledge and consistency and weakens the asymmetric dominance effect. The latter result may suggest that the previous demonstrations of the asymmetric dominance effect are somewhat exaggerated. In a single choice setting, people do not have enough information or experience about the stimuli, which may lead them to depend mostly on the contextual structure among options. In the future, more realistic stimuli and real experts' judgments can be used to increase the external validity of study results. In addition, consumers often learn through repeated choices in real consumer settings. Therefore, what consumers learn from feedback in repeated choices would be an interesting topic to investigate.

• Journal of Korean Neurosurgical Society
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• v.62 no.3
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• pp.353-360
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• 2019

Epilepsy surgery that eliminates the epileptogenic focus or disconnects the epileptic network has the potential to significantly improve seizure control in patients with medically intractable epilepsy. Magnetic resonance-guided laser interstitial thermal therapy (MRgLITT) has been an established option for epilepsy surgery since the US Food and Drug Administration cleared the use of MRgLITT in neurosurgery in 2007. MRgLITT is an ablative stereotactic procedure utilizing heat that is converted from laser energy, and the temperature of the tissue is monitored in real-time by MR thermography. Real-time quantitative thermal monitoring enables titration of laser energy for cellular injury, and it also estimates the extent of tissue damage. MRgLITT is applicable for lesion ablation in cases that the epileptogenic foci are localized and/or deep-seated such as in the mesial temporal lobe epilepsy and hypothalamic hamartoma. Seizure-free outcomes after MRgLITT are comparable to those of open surgery in well-selected patients such as those with mesial temporal sclerosis. Particularly in patients with hypothalamic hamartoma. In addition, MRgLITT can also be applied to ablate multiple discrete lesions of focal cortical dysplasia and tuberous sclerosis complex without the need for multiple craniotomies, as well as disconnection surgery such as corpus callosotomy. Careful planning of the target, the optimal trajectory of the laser probe, and the appropriate parameters for energy delivery are paramount to improve the seizure outcome and to reduce the complication caused by the thermal damage to the surrounding critical structures.

• Environmental and Resource Economics Review
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• v.28 no.1
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• pp.39-59
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• 2019

The Korean Demilitarized Zone (DMZ) has the great ecosystem as all the artificial activities in DMZ have been prohibited over half a century. The ecosystem should be conserved even after the reunification of Korea and hence the conservation plan should be established not after the reunification but before it. It requires a considerable budget to conserve DMZ, considering management of ecology resource, recovery, and research. The objective of this paper is to analyze a fund-raising measure for DMZ conservation, using economic incentives mechanism when multiple developers participate in the auction to get the right to develop North Korean regions, have private information about their sunk costs and pay a part of their profits for the fund. First, we analyze the real option model to decide the optimal investment time. Second, we construct the auction for bidders not to misrepresent their private information, based on Bayesian Nash equilibrium.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.4
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• pp.219-228
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• 2013

The surveillance imaging equipments are functioning to observe the shape of the target in real time or to measure its location precisely. The roles of such equipments are becoming more important in today's weapon systems.The aforementioned imaging equipments can be classified based on the modes of operations such as fixed, installed on cars, or composite of those. Also, according to different concepts of sensor operation, a separate type uses independent housing for each sensor whereas in a composite type a set of multiple sensors are housed into a unit altogether. The sensors in general have magnetism, thereby introducing the possible negative effects, particularly in the composite types, in locating the reference position, which is carried out by the digital compass. The use of shielding material/housing could be an option but results in increased weight and reduced portability, restricting its use in composite type equipments. As such, the objective of this paper is to study on how to reduce such magnetic effects on the position location. To do so, in the absence of magnetic shielding, a variety of sensor positions were first modeled. By combing the result with the fact that the functions of PAN & Tilt are used in the equipments, a new position location algorithm is proposed. The use of the new algorithm can automate the position location process as compared to the manual process of the existing approach. In the algorithm developed, twelve locations are measured in connection with both the azimuth and elevation angles in comparison to the six locations alone around the azimuth angle. As a result, it turns out that the measurement range has been widened but the measurement time reduced. Also, note that the effect of errors the operators may make during measurement could be reduced.