• Journal of the Korea Institute of Building Construction
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• v.19 no.1
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• pp.67-76
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• 2019

The domestic construction industry is changing according to its preference for demand and supply along with urbanization and economic development. Accordingly, initial risk assessments is more important than before. In particular, demand for lease-based investment products such as commercial and office buildings has surged as a substitute for financial products due to low interest rates of banks. Therefore, the objective is to suggest a basic study on financial analysis model development by applying optimization method in residential officetel. To achieve the objective, first, the previous studies are investigated. Second, the causal loop diagram is structured based on the collected data. Third, the system dynamics method is used to develop cost-income simulation and optimization model sequentially. Finally, the developed model was verifed through analyzing a case project. In the future, the proposed model can be helpful whether or not conduct execution of an officetel development project to the decision makers.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.1
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• pp.137-153
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• 2019

Estimating tunnel construction time and costs are the most fundamental part of a tunnel project planning, which has been generally assessed on a deterministic basis until now. In this paper, excavation cycle time was investigated for two road tunnels and one subway tunnel, and the results were compared with the Standard of Construction Estimate (SE), which is made for the estimation of construction time and cost in a design stage. The results show that the difference in cycle time between SE and actual cycle time is 50%, 7% and 31% respectively for the three tunnels, which means that SE does not reflect practical operation time. The major reasons of the difference are skilled level of tunneling workers, the change of operation sequences for more effective operations, much more complicated working atmosphere in a tunnel than the assumption of SE etc. Finally, even though the results can not be generalized since investigated tunnels are only 3, but it is thought that SE needs to be upgraded into the model able to consider quite common situations through additional tunnel investigation and studies in the future.

• Land and Housing Review
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• v.13 no.3
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• pp.39-55
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• 2022

In this study, we investigate the interrelationship between housing tenure and childbirth by exploiting the correlation probability effect method that accounts for household heterogeneity. Using the newlywed household panel from 2011 to 2022, we find that home ownership has a positive impact on childbirth in newlyweds. Specifically, newlywed households with housing tenure show a 6.2%p higher birth rate and a 5.7%p higher second childbirth than newlywed households living in rented houses. For the case of first childbirth, we employ the probability effect probit model since the endogeneity was not detected between housing tenure and birth rate. We document the differential effects of housing tenure on childbirth in that the first childbirth rate is higher for households without housing tenures. The negative effects on first childbirth could be attributed to the economic burden due to initial housing ownership, while housing tenure could eventually provide housing stability, leading to positive effects on more than one childbirth. Finally, we identify that households with childbirth over the last year show a 4.2%p and 3.9%p lower probabilities of housing tenure in the total sample and second childbirth sample, respectively. This suggests that the increased living cost due to childbirth could delay home ownership.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.123-136
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• 2014

Recently, online shopping has further developed as the use of the Internet and a variety of smart mobile devices becomes more prevalent. The increase in the scale of such shopping has led to the creation of many Internet shopping malls. Consequently, there is a tendency for increasingly fierce competition among online retailers, and as a result, many Internet shopping malls are making significant attempts to attract online users to their sites. One such attempt is keyword marketing, whereby a retail site pays a fee to expose its link to potential customers when they insert a specific keyword on an Internet portal site. The price related to each keyword is generally estimated by the keyword's frequency of appearance. However, it is widely accepted that the price of keywords cannot be based solely on their frequency because many keywords may appear frequently but have little relationship to shopping. This implies that it is unreasonable for an online shopping mall to spend a great deal on some keywords simply because people frequently use them. Therefore, from the perspective of shopping malls, a specialized process is required to extract meaningful keywords. Further, the demand for automating this extraction process is increasing because of the drive to improve online sales performance. In this study, we propose a methodology that can automatically extract only shopping-related keywords from the entire set of search keywords used on portal sites. We define a shopping-related keyword as a keyword that is used directly before shopping behaviors. In other words, only search keywords that direct the search results page to shopping-related pages are extracted from among the entire set of search keywords. A comparison is then made between the extracted keywords' rankings and the rankings of the entire set of search keywords. Two types of data are used in our study's experiment: web browsing history from July 1, 2012 to June 30, 2013, and site information. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The original sample dataset contains 150 million transaction logs. First, portal sites are selected, and search keywords in those sites are extracted. Search keywords can be easily extracted by simple parsing. The extracted keywords are ranked according to their frequency. The experiment uses approximately 3.9 million search results from Korea's largest search portal site. As a result, a total of 344,822 search keywords were extracted. Next, by using web browsing history and site information, the shopping-related keywords were taken from the entire set of search keywords. As a result, we obtained 4,709 shopping-related keywords. For performance evaluation, we compared the hit ratios of all the search keywords with the shopping-related keywords. To achieve this, we extracted 80,298 search keywords from several Internet shopping malls and then chose the top 1,000 keywords as a set of true shopping keywords. We measured precision, recall, and F-scores of the entire amount of keywords and the shopping-related keywords. The F-Score was formulated by calculating the harmonic mean of precision and recall. The precision, recall, and F-score of shopping-related keywords derived by the proposed methodology were revealed to be higher than those of the entire number of keywords. This study proposes a scheme that is able to obtain shopping-related keywords in a relatively simple manner. We could easily extract shopping-related keywords simply by examining transactions whose next visit is a shopping mall. The resultant shopping-related keyword set is expected to be a useful asset for many shopping malls that participate in keyword marketing. Moreover, the proposed methodology can be easily applied to the construction of special area-related keywords as well as shopping-related ones.

• Journal of Korean Society of Transportation
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• v.24 no.5 s.91
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• pp.35-44
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• 2006

Acceleration and deceleration curves have been used for design purposes worldwide. The curve in design level has been regarded as an single deterministic curve to be used for design of climb lanes. It should be noted that the curve was originally made using ideal driving truck and that the curve is applied during design based on the assumption of no difference between ideal and real driving conditions. However. observations show that aged vehicles and lazy behavioring drivers nay make lower performance of vehicles than the ideal performance. The present paper provides the results of truck speeds at climbing lanes then probabilistic variation of acceleration and deceleration corves. For these purposes. a study about identification of vehicle makers, and weights for trucks at freeway toll gates and then observation of vehicle-following speed were performed. The 85%ile results obtained were compared with the deterministic performance curves of 180, 200, and 220 Ib/hp. It was identified that the performance of 85%ile results obtained from vehicle-following-speed observations were lower than one from deterministic performance curves. From these results, it may be concluded that at the beginning Point of climbing lanes additional $16.19{\sim}67.94m$ is necessary and that at the end point of climbing lanes $53.12{\sim}103.24m$ of extension is necessary.

• Journal of Korean Society of Forest Science
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• v.98 no.1
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• pp.55-65
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• 2009

Annex I parties continued its consideration of how to address, the definitions, modalities, rules and guidelines for the treatment of Land Use, Land-use Change and Forestry (LULUCF) in the second commitment period of the Kyoto Protocol by the year of 2009. In the AWG-KP conference held in Accra, Ghana in 2008, four alternatives (gross-net carbon accounting, net-net with base year or base period accounting, net-net with forward looking baseline accounting, and land-based accounting method) for negotiations were decided in order to revise gross-net accounting method applied during the first commitment period of the Kyoto Protocol. In this study, alternative scenarios are set in consideration with reporting system (voluntary or compulsory), discount factors and cap about these three alternatives except for the method of net-net with forward looking baseline accounting, and then estimates the Removal Unit (RMU) among the countries. In the case that article 3.4 activities under the Kyoto Protocol revises from voluntary reporting to mandatory reporting, it is estimated that the loss of RMU would be huge in Russia, Australia, New Zealand, as well as Canada potentially. Net-net with base year or base period carbon accounting and land-based carbon accounting method have big difference of RMU in accordance with the base year or the base period. So the more unfavorable the country with a lot of old-age forests was, the closer the base year or period comes to the commitment period in the context of RMU. If it is getting lowered for the current rate of 85% in discount factors, RMU is getting higher to the whole countries. Therefore in Korea with little potential for afforestation and reforestation, there was the most sensitive response to the change of discount factors. Post-2012 LULUCF hereafter, it is strongly expected for the succession of current carbon accounting system which is voluntary reporting of gross-net carbon accounting and the activity for article 3.4. Other carbon accounting method is hard to accept in aspect that there is big differentiated interests among the countries and it is required enormous cost and time to develop reliable method. Provide for Post-2012 mandatory greenhouse gas reduction, Korea needs to have a competitive negotiation strategies differentiated from Annex I countries. The most reliable alternative would be to lower the discounting factors about the activities for forest management.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.23-46
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• 2017

Although there have been cases of evaluating the value of specific companies or projects which have centralized on developed countries in North America and Europe from the early 2000s, the system and methodology for estimating the economic value of individual technologies or patents has been activated on and on. Of course, there exist several online systems that qualitatively evaluate the technology's grade or the patent rating of the technology to be evaluated, as in 'KTRS' of the KIBO and 'SMART 3.1' of the Korea Invention Promotion Association. However, a web-based technology valuation system, referred to as 'STAR-Value system' that calculates the quantitative values of the subject technology for various purposes such as business feasibility analysis, investment attraction, tax/litigation, etc., has been officially opened and recently spreading. In this study, we introduce the type of methodology and evaluation model, reference information supporting these theories, and how database associated are utilized, focusing various modules and frameworks embedded in STAR-Value system. In particular, there are six valuation methods, including the discounted cash flow method (DCF), which is a representative one based on the income approach that anticipates future economic income to be valued at present, and the relief-from-royalty method, which calculates the present value of royalties' where we consider the contribution of the subject technology towards the business value created as the royalty rate. We look at how models and related support information (technology life, corporate (business) financial information, discount rate, industrial technology factors, etc.) can be used and linked in a intelligent manner. Based on the classification of information such as International Patent Classification (IPC) or Korea Standard Industry Classification (KSIC) for technology to be evaluated, the STAR-Value system automatically returns meta data such as technology cycle time (TCT), sales growth rate and profitability data of similar company or industry sector, weighted average cost of capital (WACC), indices of industrial technology factors, etc., and apply adjustment factors to them, so that the result of technology value calculation has high reliability and objectivity. Furthermore, if the information on the potential market size of the target technology and the market share of the commercialization subject refers to data-driven information, or if the estimated value range of similar technologies by industry sector is provided from the evaluation cases which are already completed and accumulated in database, the STAR-Value is anticipated that it will enable to present highly accurate value range in real time by intelligently linking various support modules. Including the explanation of the various valuation models and relevant primary variables as presented in this paper, the STAR-Value system intends to utilize more systematically and in a data-driven way by supporting the optimal model selection guideline module, intelligent technology value range reasoning module, and similar company selection based market share prediction module, etc. In addition, the research on the development and intelligence of the web-based STAR-Value system is significant in that it widely spread the web-based system that can be used in the validation and application to practices of the theoretical feasibility of the technology valuation field, and it is expected that it could be utilized in various fields of technology commercialization.

• Tuberculosis and Respiratory Diseases
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• v.64 no.6
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• pp.433-438
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• 2008

Background: Measurement of the maximum oxygen uptake in patients with chronic obstructive pulmonary disease (COPD) has been used to determine the intensity of exercise and to estimate the patient's response to treatment during pulmonary rehabilitation. However, cardiopulmonary exercise testing is not widely available in Korea. The 6-minute walk test (6MWT) is a simple method of measuring the exercise capacity of a patient. It also provides high reliability data and it reflects the fluctuation in one' s exercise capacity relatively well with using the standardized protocol. The prime objective of the present study is to develop a regression equation for estimating the peak oxygen uptake ($VO_2$) for men with moderate to very severe COPD from the results of a 6MWT. Methods: A total of 33 male patients with moderate to very severe COPD agreed to participate in this study. Pulmonary function testing, cardiopulmonary exercise testing and a 6MWT were performed on their first visits. The index of work ($6M_{work}$, 6-minute walk distance [6MWD]${\times}$body weight) was calculated for each patient. Those variables that were closely related to the peak $VO_2$ were identified through correlation analysis. With including such variables, the equation to predict the peak $VO_2$ was generated by the multiple linear regression method. Results: The peak $VO_2$ averaged $1,015{\pm}392ml/min$, and the mean 6MWD was $516{\pm}195$ meters. The $6M_{work}$ (r=.597) was better correlated to the peak $VO_2$ than the 6MWD (r=.415). The other variables highly correlated with the peak $VO_2$ were the $FEV_1$ (r=.742), DLco (r=.734) and FVC (r=.679). The derived prediction equation was $VO_2$ (ml/min)=($274.306{\times}FEV_1$)+($36.242{\times}DLco$)+($0.007{\times}6M_{work}$)-84.867. Conclusion: Under the circumstances when measurement of the peak $VO_2$ is not possible, we consider the 6MWT to be a simple alternative to measuring the peak $VO_2$. Of course, it is necessary to perform a trial on much larger scale to validate our prediction equation.