• Journal of the Korean Operations Research and Management Science Society
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• v.26 no.4
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• pp.83-97
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• 2001

Net Present Value (NPV) criterion has been the most widely used criterion to evaluate investment opportunities. However, the analysis based on the NPV criterion falls to consider the managerial flexibility of deferring decisions until major uncertainty is resolved. Recently, real options method attracted a lot of attention as a Powerful approach to address the problem. If investment decision is deferred, the value of the investment opportunity increases but opportunity cost increases at the same time. Therefore, it is important to decide the optimal timing how long the decision can be deferred. In this paper, we developed a model deciding the optimal decision timing. Using the real options approach, the model derived the optimal deferring time until a decision is made. Then, the model was applied to a Korean mobile telecommunications company who wants to invest on the wireless resale business. We believe that this model would be very useful to overcome the problem of NPV decision criterion. With this approach, we can make contingent decisions based on the observation of uncertainly resolutions.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.301-305
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• 1996

$\mu$ theory can handle the parametric uncertainty and produces more non-conservative controller than H$_{\infty}$ control theory. However an existing solution of the theory, D-K iteration, creates a controller of huge order and cannot handle the real or mixed real-complex perturbation sets. In this paper, we use genetic algorithms to solve these problems of the D-K iteration method. The Youla parameterization is used to obtain all stabilizing controllers and the genetic algorithms determines the values of the state feedback gain, the observer gain, and Q parameter to minimize $\mu$, the structured singular value, of given system. From an example, we show that this method produces lower order controller which controls a real parameter-perturbed plant than D-K iteration method.

• Proceedings of the KSR Conference
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• 2001.05a
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• pp.347-358
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• 2001

In this paper, we apply NHPP model example to s/w process in order to get to know s/w reliability. The test is constructed by a test zig of commercial product loaded real embedded system s/w. It is established to s/w reliability prediction and estimation of real-time embedded system s/w. It is computed the prediction value of cumulative failures, the failure intensity, the reliability and the estimation value of MTTF, Failure Rate. To the more realization of high reliability in the real-time embedded system s/w, if the embedded system s/w is ensured to the test coverage and constructed to stable s/w process ＆ operating system, we can improve the performance and the reliability characteristic of the real-time embedded system s/w.

• 한국전산유체공학회:학술대회논문집
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• 1999.05a
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• pp.29-34
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• 1999

A two-dimensional Navier-Stokes code based on AUSMPW+ scheme has been developed to simulate the hypersonic flowfield of hypersonic shock-shock interaction. AUSMPW+ scheme is a new hybrid flux splitting scheme, which is improved by introducing pressure-based weight functions to eliminate the typical drawbacks of AUSM-type schemes, such as non-monotone pressure solutions. To study the real gas effects, three different gas models are taken into account in this paper: perfect gas, equilibrium flow and nonequilibrium flow. It has been investigated how each gas model influences on the peak surface loading, such as wall pressure and wall heat transfer, and unsteady flowfield structure in the region of shock-shock interaction. With the results, the value of peak pressure is not sensitive to the real gas effects nor to the wall catalyticity. However, the value of peak heat transfer rates is affected by the real gas effects and the wall catalyticity. The structure of the flowfield also changes drastically in the presence of real gas effects.

• Journal of Korea Technology Innovation Society
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• v.9 no.1
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• pp.84-102
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• 2006

This paper compares four models to value a biotechnology R&D project; option tree model, dynamic discounted cash flow(DCF) model, and option thinking DCF model with general DCF model. Real Options, especially 6-folded option tree model yields boner estimate of value than values using other methods. According to sensitivity analysis, sales of final products, number of investigational new drug developments(INDs) and success rates of each stage are key factors for the value of biotechnology R&D investment.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.28-35
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• 2013

The construction industry has introduced the Leadership in Energy and Environmental Design (LEED) rating system to promote objective evaluations of the sustainability of buildings. Three important values to consider when implementing sustainability are the associated environmental, social, and economic impacts. Recently, researchers have begun to investigate the real estate value of LEED certified buildings in terms of the rental cost, occupancy rate, cost per unit area, and resale value in order to better understand the economic benefits of the LEED rating system. However, the economic benefits also encompass economic effects such as the impact of LEED certified buildings on neighborhood real estate values surrounding the certified buildings. This research examines whether the enhanced real estate value of LEED certified buildings in New York City extends to surrounding commercial buildings, utilizing spatial analysis via a Geographic Information System (GIS) and the hedonic pricing method to derive meaningful economic relationships. The results provide practical insights into the economic effect of LEED certified buildings that will be of interest to city officials and planners, as well as the owners, developers, investors and other stakeholders of surrounding buildings.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.83-88
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• 2022

The purpose of this study is to present an analysis and implications for the metaverse-based virtual real estate transaction service. Through blockchain-based technology and metaverse, the world we live in is expanding naturally. Therefore, changes in the environment and perceptions of market participants are also very important factors. The concept and thinking about the existing asset value change and investment are also changing. This means that you can generate profits through value and investment in intangible assets. The service user aspect is a case of investing in the future value of virtual real estate that if more users participate rather than the present value, the principle of supply and demand will be applied to increase the number of consumers and the price will naturally rise according to the principle of scarcity. The service provider provides a technical platform for the service to directly transact the portion of the virtual area considered of interest directly through the virtual real estate purchase business. As the number of participants increases as well as funds and transaction fees, various revenue models such as advertisements can be discovered and provided. It plays the role of providing jobs and information through new services. As a stakeholder, governments can exploit the emergence of new technologies and products to create people and services and secure economic benefits. Of course, various institutional supports should be provided so that new services can settle in the market while mitigating risk factors. This study is meaningful in that it contributes to the establishment of a domestic metaverse-based environment and related research and is utilized in the study of virtual space real estate services.

• Journal of Digital Contents Society
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• v.7 no.4
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• pp.227-234
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• 2006

While most of the real estate information provided on the web is simply based on the information of the properties like addresses, locations, prices etc, this paper suggests methodologies for the development of a total information system of real estate which can provide, in an one-stop mode, value-added real estate information contents. The total information system of real estate designed in this paper includes a geological information system using a GIS, a property information system using photos and videos, a systemized legal consulting system, a web call center where customers can communicate with real estate experties on the web and lastly marketing analyses system using credit card data.

• Journal of Korea Multimedia Society
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• v.24 no.1
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• pp.95-105
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• 2021

In the case of laptops and tablet PC's that replace desktop, it uses the Windows operating system to provide various functions depending on operating system dependency, the Windows operating system does not support real-time processing because it uses multi-level feedback queue scheduling that extends round-robin scheduling. Also, since the initial value of Local APIC Counter can not be obtained from the Windows 8, the real-time processing function provided through the existing RTiK does not work. In this paper, we calculate Local APIC Counter value by using MSR_FSB_FREQ register to support real-time processing function on tablet PC's. We designed and implemented RTiK+, which provides real-time processing function to guarantee the periodicity by calculating the operation time of accurate timer. In order to verify and evaluate the performance of the implemented the RTiK+, the period was measured by using the Read Time-Stamp Counter(RDTSC) instruction and it was confirmed that it operates normally at 1ms and 0.1ms period.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.79-84
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• 2023

Apache Spark, which provides the fastest processing speed among recent distributed and parallel processing technologies, provides real-time functions and machine learning functions. Although official documentation guides for these functions are provided, a method for fusion of functions to predict a specific value in real time is not provided. Therefore, in this paper, we conducted a study to predict the value of data in real time by fusion of these functions. The overall configuration is collected by downloading stock price data provided by the Python programming language. And it creates a model of regression analysis through the machine learning function, and predicts the adjusted closing price among the stock price data in real time by fusing the real-time streaming function with the machine learning function.