• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.2 no.1
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• pp.35-40
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• 2004

Final disposal of radioactive waste generated from Nuclear Power Plant (NPP) requires the detailed information about the characteristics and the quantities of radionuclides in waste package. Most of these radionuclides are difficult to measure and expensive to assay. Thus it is suggested to the indirect method by which the concentration of the Difficult-to-Measure (DTM) nuclide is estimated using the correlations of concentration - it is called the scaling factor - between Easy-to-Measure (Key) nuclides and DTM nuclides with the measured concentration of the Key nuclide. In general, the scaling factor is determined by the log mean average (LMA) method and the regression method. However, these methods are inadequate to apply to fission product nuclides and some activation product nuclides such as 14$^{C}$ and 90$^{Sr}$ . In this study, the artificial neural network (ANN) method is suggested to improve the conventional SF determination methods - the LMA method and the regression method. The root mean squared errors (RMSE) of the ANN models are compared with those of the conventional SF determination models for 14$^{C}$ and 90$^{Sr}$ in two parts divided by a training part and a validation part. The SF determination models are arranged in the order of RMSEs as the following order: ANN model

• Korean Journal of Agricultural Science
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• v.48 no.3
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• pp.515-526
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• 2021

The frequency of typhoons and torrential rainfalls has increased due to climate change, and the concurrent risk of breakage of dams and reservoirs has increased due to structural aging. To cope with the risk of dam breakage, a more accurate emergency action plan (EAP) must be established, and more advanced technology must be developed for the prediction of flooding. Hence, the present study proposes a method for establishing a more effective EAP by performing flood and inundation analyses using one- and two-dimensional models. The probable maximum flood (PMF) under the condition of probable maximum precipitation (PMP) was calculated for the target area, namely the Gyeong-cheon reservoir watershed. The breakage scenario of the Gyeong-cheon reservoir was then built up, and breakage simulations were conducted using the dam-break flood forecasting (DAMBRK) model. The results of the outflow analysis at the main locations were used as the basis for the one-dimensional (1D) and two-dimensional (2D) flood inundation analyses using the watershed modeling system (WMS) and the FLUvial Modeling ENgine (FLUMEN), respectively. The maximum inundation area between the Daehari-cheon confluence and the Naeseong-cheon location was compared for each model. The 1D flood inundation analysis gave an area of 21.3 km², and the 2D flood inundation analysis gave an area of 21.9 km². Although these results indicate an insignificant difference of 0.6 km² in the inundation area between the two models, it should be noted that one of the main locations (namely, the Yonggung-myeon Administrative and Welfare Center) was not inundated in the 1D (WMS) model but inundated in the 2D (FLUMEN) model.

• Asian Oncology Nursing
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• v.4 no.1
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• pp.49-61
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• 2004

Purpose: The purpose of this study was to suggest the projected manpower of oncology nurses & Advanced oncology certified nurses needed in the future. Method: Need models, ratio models and expert opinion were used for projecting the number of oncology nurses & Advanced oncology certified nurses. Resul: 1. The demand for the oncology nurses was estimated 6,043 in the year 2003, 6,548 in the year 2005, and 4,556 in the year 2010. 2. The demand range of the advanced oncology certified nurses centering on the number of hospitalized patients were estimated 358-538 in the year 2003, 388-583 in the year 2005, and 448-672 in the year 2010. 3. The demand range of the middle and long term advanced oncology certified nurses centering on the number of sickbed were estimated 507-787 in the year 2005, 523-810 in the year 2010, and 540-837 in the year 2020. 4. The demand range of the advanced oncology certified nurses centering on the number of organizations were estimated 374 in the year 2003, 399 in the year 2005, 410 in the year 2010. 5. The total demand range, concerning the numbers of hospitalized patients, hospital bed, and organizations are estimated 358-538 in the year 2003, 388-787 in the year 2005, 428-840 in the year 2010, and 540-837 in the year 2020. 6. In the demand of developed country's level oncology nurses are OCN's level 1,495, AOCN's level 102 in the year 2003, OCN's level 1,613, AOCN's level 111 in the year 2005, OCN's level 1,879, AOCN's level 128 in the year 2010 in case of the United States, and in case of Canada, 765 in the year 2003, 826 in the year 2005, and 956 in the year 2010.

• Journal of Gastric Cancer
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• v.14 no.2
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• pp.67-86
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• 2014

Gastric cancer is one of the most common cancers in the world. Animal models have been used to elucidate the details of the molecular mechanisms of various cancers. However, most inbred strains of mice have resistance to gastric carcinogenesis. Helicobacter infection and carcinogen treatment have been used to establish mouse models that exhibit phenotypes similar to those of human gastric cancer. A large number of transgenic and knockout mouse models of gastric cancer have been developed using genetic engineering. A combination of carcinogens and gene manipulation has been applied to facilitate development of advanced gastric cancer; however, it is rare for mouse models of gastric cancer to show aggressive, metastatic phenotypes required for preclinical studies. Here, we review current mouse models of gastric carcinogenesis and provide our perspectives on future developments in this field.

• Journal of Korean Institute of Industrial Engineers
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• v.14 no.1
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• pp.103-117
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• 1988

Replacement demand plays an important role to forecast the total demand of durable goods, while most of the diffusion models deal with only adoption data, namely initial purchase demand. This paper presents replacement demand forecasting models incorporating repurchase rate, multi-ownership, and dynamic product life to complement the existing diffusion models. The performance of replacement demand forecasting models are analyzed and practical guidelines for the application of the models are suggested when life distribution data or adoption data are not available.

• Journal of the Korea Society for Simulation
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• v.5 no.1
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• pp.81-90
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• 1996

In this paper, we propose a new events ordering mechanism for the optimistic distributed simulation of DEVS models. To simulate DEVS models in a distributed environment, a synchronization protocol is required for correct simulation. Time Warp is the most well-known optimistic synchronization protocol for distributed simulation. However, employing the Time Warp protocol in distributed simulation of DEVS models incurs events ordering problem due to the semantic difference between Time Warp and DEVS, Thus, to resolve such semantic difference, we devise the time-and-priority-stamp and $\varepsilon$ -delay schemes. The proposed schemes can order simultaneous events correctly in Time Warp-based distributed simulation of DEVS models.Time Warp and DEVS, Thus, to resolve such semantic difference, we devise the time-and-priority-stamp and $\varepsilon$ -delay schemes. The proposed schemes can order simultaneous events correctly in Time Warp-based distributed simulation of DEVS models.

• Proceedings of the Korea Concrete Institute Conference
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• 2006.11a
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• pp.1-12
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• 2006

For advanced civil engineering structures a service life of hundred up to hundred fifty and even two hundred years is sometimes required. The prediction of the performance of concrete structures over such a long period requires accurate and reliable predictive models. Most of the presently used, mostly experience based models don't have the quality and reliability that is required for reliable long-term predictions. The models designers are searching for should be based on an accurate description of the relevant degradation mechanisms. The starting point of such models is a realistic description of the microstructure of the concrete. In this presentation the need and the role of fundamental microstructural models for predicting the performance of concrete structures will be presented. An example will be given of a microstructural model with a proven potential for long-term predictions. Besides this also the role of models in general, i.e. in the whole design and execution process of concrete structures, will be dealt with. Finally recent trends in concrete research will be presented, like the research on self-healing cement-bases systems.

• Structural Engineering and Mechanics
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• v.34 no.1
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• pp.15-38
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• 2010

In order to predict the shear strengths of reinforced concrete beams, many deterministic models have been developed based on rules of mechanics and on experimental test results. While the constant and variable angle truss models are known to provide reliable bases and to give reasonable predictions for the shear strengths of members with shear reinforcement, in the case of members without shear reinforcement, even advanced models with complicated procedures may show lack of accuracy or lead to fairly different predictions from other similar models. For this reason, many research efforts have been made for more accurate predictions, which resulted in important recent publications. This paper develops probabilistic shear strength models for reinforced concrete beams without shear reinforcement based on deterministic shear strength models, understanding of shear transfer mechanisms and influential parameters, and experimental test results reported in the literature. Using a Bayesian parameter estimation method, the biases of base deterministic models are identified as algebraic functions of input parameters and the errors of the developed models remaining after the bias-correction are quantified in a stochastic manner. The proposed probabilistic models predict the shear strengths with improved accuracy and help incorporate the model uncertainties into vulnerability estimations and risk-quantified designs.

• The KIPS Transactions:PartA
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• v.8A no.2
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• pp.107-116
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• 2001

A multithreaded model is a hybrid one which combines locality of execution of the von Neumann model with asynchronous data availability and implicit parallelism of the dataflow model. Much researches that have been made toward the advanced performance of multithreaded models are about the cache memory which have been proved to be efficient in the von Neumann model. To use an instruction cache or operand cache, the multithreaded models must have cache memories. If cache memories are added to the multithreaded model, they may have the disadvantage of high implementation cost in the mode. To solve these problems, we did not add cache memory but applied the method of executing the caching by using available registers of the multithreaded models. The available register-based caching method is one that use the registers which are not used on the execution of threads. It may accomplish the same effect as the cache memory. The multithreaded models can compute the number of available registers to be used during the process of the register optimization, and therefore this method can be easily applied on the models. By applying this method, we can also remove the access conflict and the bottleneck of frame memories. When we applied the proposed available register-based caching method, we found that there was an improved performance of the multithreaded model. Also, when the available-register-based caching method is compared with the cache based caching method, we found that there was the almost same execution overhead.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.1
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• pp.71-81
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• 2014

It is an important issue to evaluate the effectiveness of chemical warfare through modeling and simulation(M&S) technology. In this paper, we propose the M&S methodology and environment for the chemical warfare for effectiveness analysis. In detail, for modeling perspective, we propose three fundamental component models according to their behaviors, which are a chemical weapon, a detecting device system, and an engaging unit system. Among proposed models, the chemical weapon and the detecting device system models are represented by engineering-level system models, whereas the engaging unit system model are described as an engagement-level system model. For simulation perspective, we apply a hybrid simulation environment using High Level Architecture (HLA) to interoperate with the proposed engineering and engagement-level models. The proposed M&S methodology and environment enables to evaluate the effectiveness of the chemical warfare system considering the doctrines, the performance of device or weapon, and weather factors. To verify the efficiency of the proposed methodology and environment, we experimented three categorized case studies, which are related with those considering factors.