• Journal of Information Technology Application
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• v.2 no.1
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• pp.1-24
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• 2000

Project management in the Construction field inherently has more uncertainty and more risks relative to ones from other area. This is the very reason for why project management is recognized as the important task to construction companies. For getting better performance in the project management, we need a system that keeps the consistencies in a automatic or semi-automatic manner through the project management stages like as project definition stage, project planning stage, project design and implementation stage. But since the early stages such as definition and planning stages has many unstructured features and also are dependent to unique expertise or experience of a specific company, we have difficulty providing systematic support for the task of these stages. This kind of problem becomes harder to solve especially in the plant construction domain that is our target domain. Therefore, in this paper, we propose and also implement a systematic approach to resolve the problem mentioned for the early project management stages in the plant construction domain. The results of our approach can be used not only for the purpose of the early project management stages but also can be used automatically as an input to commercial project management tools for the middle project management stages. Because of doing in this way, the construction project can be consistently managed from the definition to implementation stage in a seamless manner. For achieving this purpose, we adopt knowledge based inference, CBR, and neural network as major methodologies and we also applied our approach to two real world cases, power plant and drainage treatment plant cases from a leading construction company in Korea. Since these two application cases showed us very successful results, we can say our approach was validated successfully to the plant construction area. Finally, we believe our approach will contribute to many project management problems from more broader construction area.

• The Journal of the Korea Contents Association
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• v.18 no.1
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• pp.132-142
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• 2018

This study attempts to identify the external and internal factors which affect collaboration motives and investigates their respective impacts from the perspective of foreign direct investment(FDI). Although there has been much research on collaboration motives, so far, few studies have associated collaboration motives with FDI. The findings suggest that while price competitiveness and cost structure uncertainty have a positive and significant impact on collaboration motives, the gross added value to property as well as plant and equipment have a significant negative impact. Furthermore, in the case of gross added value to both property and plant and equipment, managers tend to collaborate with others to enhance the value of these factors. For both FDI and non-FDI firms, internal factors such as price competitiveness and investment within three years are significant determinants for the decision to collaborate. The difference between FDI and non-FDI firms is that for the former, the gross added value to property, an internal factor, is a critical factor, while for the latter, the cost structure uncertainty, an external factor, is critical for collaboration. To summarize, this study suggests the following managerial implication: the enhancement of the internal competency of a firm broadens the window of opportunity for collaboration with others, and consequently provides a chance to boost management efficiency.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.5
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• pp.944-958
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• 2011

Soil hydraulic properties such as hydraulic conductivity or water retention which are costly to measure can be indirectly generated by soil pedotransfer function (PTF) using easily obtainable soil data. The field soil structure description which is routinely recorded could also be used in PTF as an input to reduce the uncertainty. The purposes of this study were to use qualitative morphological soil structure descriptions and soil structural index into PTF and to evaluate their contribution in the prediction of soil hydraulic properties. We transformed categorical morphological descriptions of soil structure into quantitative values using categorical principal component analysis (CATPCA). This approach was tested with a large data set from the US National Pedon Characterization database with the aid of a categorical regression tree analysis. Six different PTFs were used to predict the saturated hydraulic conductivity and those results were averaged to quantify the uncertainty. Quantified morphological description was successively used in multiple linear regression approach to predict the averaged ensemble saturated conductivity. The selected stepwise regression model with only the transformed morphological variables and structural index as predictors predicted the $K_{sat}$ with $r^2$ = 0.48 (p = 0.018), indicating the feasibility of CATPCA approach. In a regression tree analysis, soil structure index and soil texture turned out to be important factors in the prediction of the hydraulic properties. Among structural descriptions size class turned out to be an important grouping parameter in the regression tree. Bulk density, clay content, W33 and structural index explained clusters selected by a two step clustering technique, implying the morphologically described soil structural features are closely related to soil physical as well as hydraulic properties. Although this study provided relatively new method which related soil structure description to soil structure index, the same approach should be tested using a datasets containing the actual measurement of hydraulic properties. More insight on the predictive power of soil structure index to estimate hydraulic properties would be achieved by considering measured the saturated hydraulic conductivity and the soil water retention.

• Journal of the Korean Institute of Gas
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• v.22 no.2
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• pp.46-51
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• 2018

Hydrogen sulfide from landfill and sewage treatment plant is a major odor component and causes many civil petitions. Rapidly developing industries release hydrogen sulfide, an odorous gas, to the atmosphere. This study aims to develop a $10{\mu}mol/mol$ concentration level hydrogen sulfide primary standard gas for odor measurement. The hydrogen sulfide gas was prepared at a nominal concentration of $10{\mu}mol/mol$ in nitrogen using the gravimetric method described in ISO 6142. Replicate standard gases were produced in 4 aluminium cylinders, and their concentrations were verified by GC-AED. The uncertainty of production was less than 0.50 %, and the variation of the 4 replicates was 0.22 %. The wall adsorption of hydrogen sulfide in cylinders was 0.10 % at 1500 psi, and the concentration was estimated to be long-term stable for one year. The relative expanded uncertainty of the preparation consistency, adsorption and long-term stability of this hydrogen sulfide standard gas was less than 1.05 % (95 % of confidence level, k=2).

• Journal of Korean Society of Environmental Engineers
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• v.38 no.1
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• pp.42-46
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• 2016

The radioactive iodine ($^{131}I$) presents in the environment through the excrete process of nuclear medicine patients. In the detecting of low level of $^{131}I$ in the public water, the counting uncertainty has an effect on the accuracy and reliability of detecting $^{131}I$ radioactivity concentration. In this study, the contribution of sample amount, radioactivity concentration and counting time to the uncertainty was investigated in the case of public water sample. Sampling points are public water and the effluents of a sewage treatment plant at Sapkyocheon stream, Geumgang river. In each point, 1, 10 and 20 L of liquid samples were collected and prepared by evaporation method. The HPGe (High Purity Germanium) detector was used to detect and analyze emitted gamma-ray from samples. The radioactivity concentration of $^{131}I$ were in the range of 0.03 to 1.8 Bq/L. The comparison of the counting uncertainty of the sample amount, 1 L sample is unable to verify the existence of the $^{131}I$ under 0.5 Bq/L radioactivity concentration. Considering the short half-life of $^{131}I$ (8.03 days), a method for measuring 1 L sample was used. However comparing the detecting and preparing time of 1, 10 L respectively, detecting 10 L sample would be an appropriate method to distinguish $^{131}I$ concentration in the public water.

• Journal of Advanced Marine Engineering and Technology
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• v.35 no.8
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• pp.1132-1140
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• 2011

When the offshore wind power plant is planned to construct, it is important for the wind farm site to figure out the distribution of the weak soil layers that might cause subsidence by the impact of the external moment from the wind plant's load and an oscillating wind load. Coring test is the optimistic method to figure out weak soil layers, but this method have some problem such as condition of the in-situ or economical limitation. In order to make up for the weak points in coring test, the researches using the geostatistics methods is actually done. In this study, setting a fixed coastal area that offshore wind plants construct firstly and Estimation of distribution on the thickness of the weak soil layer through the geostatistic method is conducted. The weak soil layer is sorted by result of the Standard penetration test, geostatistic method is used to ordinary kring and sequential gaussian simulation and compared to both method's result. As a results of study, we found that both methods show similar estimations of deep weak soil layer and we could evaluate quantitatively the uncertainty of the result.

• Journal of Nutrition and Health
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• v.36 no.9
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• pp.950-959
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• 2003

To assess zinc status by dietary intake and urinary excretion of preschool children in Busan and to evaluate the relationship of intakes of food and nutrient with urinary zinc excretion, zinc food frequencies of 40 common foods affecting intakes of zinc by food fequency method, nutrient intake by 24hr recall and 24hr urinary zinc excretion were measured with 97 preschool children. The mean zinc intake was 4.29 mg and 43.0% of RDA. The mean zinc intake per 1,000 kcal was 3.09 mg.97.9％ of subjects had zinc intake less than 75％ of RDA. Grains food group was the primary source of zinc intake and supplied 38.9% of the total daily zinc intake. Altogether, plant food products supplied 49.7% of zinc intake. The mean urinary zinc excretion and zinc excretion per gram of creatinine were 0.19 mg and 1.00 mg respectively. The urinary zinc excretion showed positive significant correlations with height and weight (p < 0.05, p < 0.05) , urine volume and urinary creatinine excretion (p < 0.05, p < 0.001) , urinary zinc excretion per creatinine (p < 0.001) , urinary zinc excretion per weight (p < 0.001) , intakes of energy and carbohydrate (p < 0.05, p < 0.01) and usual intake of zinc from eggs food group (p < 0.05) . In conclusion, these results show that the zinc intake of preschool children is low and that sources of dietary zinc are mainly plant foods, suggesting low bioavailability. So nutritional education is needed in order to inc-rease usual intake of animal food group. Interpretation of urinary zinc excretion data is complicated by current uncertainty about "normal" zinc level at this age group. Further studies are needed to obtain extensive data on urinary zinc excretion for this age group.age group.

• Fire Science and Engineering
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• v.19 no.3 s.59
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• pp.20-27
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• 2005

This paper evaluates the fire safety level of eight pump rooms in the nuclear power plant using a fire model, CFAST We estimate the Conditional Core Damage Probability (CCDP) of each room based on the analyzed results of CFAST Eight rooms located on the primary auxiliary building of the nuclear power plant are high pressure safety injection pump room A/B, low pressure safety injection pump room Am. containment sprdy pump room A/B, and motor-driven auxiliary feed water pump room A/B. The upper layer gas temperature of each room is estimated and the integrity of cable is reviewed. Based on the results, the integrity of the cable located at the upper part of compartment is maintained without thermal damage. The Conditional Core Damage Probability Is reduced to half of the old values. Accordingly, the fire safety assessment for eight pump rooms using the fire model will be capable of reducing the uncertainty and to develop a more realistic model.

• Nuclear Engineering and Technology
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• v.41 no.7
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• pp.945-952
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• 2009

The Three Mile Island Unit 2 (TMI-2) accident provides unique full scale data, thus providing opportunities to check the capability of codes to model overall plant behavior and to perform a spectrum of sensitivity and uncertainty calculations. As part of the TMI-2 analysis benchmark exercise sponsored by the Organization for Economic Cooperation and Development Nuclear Energy Agency (OECD NEA), several member countries are continuing to improve their system analysis codes using the TMI-2 data. The Republic of Korea joined this benchmark exercise in November 2005. Seoul National University has analyzed the TMI-2 accident as well as the currently proposed alternative scenario along with a sensitivity study using the Modular Accident Analysis Program Version 4.03 (MAAP4.03) code in collaboration with the Korea Hydro and Nuclear Power Company. Two input files are required to simulate the TMI-2 accident with MAAP4: the parameter file and an input deck. The user inputs various parameters, such as volumes or masses, for each component. The parameter file contains the information on TMI-2 relevant to the plant geometry, system performance, controls, and initial conditions used to perform these benchmark calculations. The input deck defines the operator actions and boundary conditions during the course of the accident. The TMI-2 accident analysis provided good estimates of the accident output data compared with the OECD TMI-2 standard reference. The alternative scenario has proposed the initial event as a loss of main feed water and a small break on the hot leg. Analysis is in progress along with a sensitivity study concerning the break size and elevation.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.305-312
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• 2010

The aim of this study is to find an analytic solution to the problem of determining the optimal capacity of a batch-storage network to meet demand for finished products in a system undergoing joint random variations of operating time and batch material loss. The superstructure of the plant considered here consists of a network of serially and/or parallel interlinked batch processes and storage units. The production processes transform a set of feedstock materials into another set of products with constant conversion factors. The final product demand flow is susceptible to joint random variations in the cycle time and batch size. The production processes have also joint random variations in cycle time and product quantity. The spoiled materials are treated through regeneration or waste disposal processes. The objective function of the optimization is minimizing the total cost, which is composed of setup and inventory holding costs as well as the capital costs of constructing processes and storage units. A novel production and inventory analysis the PSW (Periodic Square Wave) model, provides a judicious graphical method to find the upper and lower bounds of random flows. The advantage of this model is that it provides a set of simple analytic solutions while also maintaining a realistic description of the random material flows between processes and storage units; as a consequence of these analytic solutions, the computation burden is significantly reduced. The proposed method has the potential to rapidly provide very useful data on which to base investment decisions during the early plant design stage. It should be of particular use when these decisions must be made in a highly uncertain business environment.