• International Journal of Control, Automation, and Systems
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• v.3 no.3
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• pp.493-501
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• 2005

A power plant simulation tool ('PowerSim') has been developed with 10 years experience from the development of a plant simulator for efficient modeling of a power plant. PowerSim is the first developed tool in Korea for plant simulation with various plant component models, instructor station function and the Graphic Model Builder (GMB). PowerSim is composed of a graphic editor using general purpose design software, a netlist converter, component models, the scheduler, Instructor Station and an executive. The graphic editor generates a netlist that shows the connection status of the various plant components from the Simdiagram, which is drawn by Icon Drag method supported by GUI environment of the PowerSim. Netlist Converter normalizes the connection status of the components. Scheduler makes scheduling for the execution of the device models according to the netlist. Therefore, the user makes Simdiagram based on the plant Pipe and Instrument Drawing (P&ID) and inputs the plant data for automatic simulating execution. This paper introduces Graphic Model Builder (GMB), instructor station, executive and the detailed introduction of thermal-hydraulic modeling. This paper will also introduce basic ideas on how the simulation Diagram, based on netlist generated from general purpose design software, is made and how the system is organized. The developed tool has been verified through the simulation of a real power plant.

• Health Policy and Management
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• v.14 no.1
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• pp.89-120
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• 2004

The purpose of this empirical study is to test hypotheses in order to identify the cost drivers that drive indirect costs in general hospitals in Korea. In various cases' studies, it has been suggested that overhead costs are driven by volume and complexity variables, how they are structurally related and how the cost impacts of these variables can be A unique feature of the research is the treatment of complexity as an endogenous variable. It is hypothesized that level of hospital complexity in terms of the number of services provided(i.e., “breath" complexity) and the intensity of individual estimated in practice. overhead services(ie., “depth" complexity) are simultaneous determined with the level of costs needed to support the complexity. Data used in this study were obtained from the Database of Korean Health Industry Development Institute, Health Insurance Review Agency and analyzed using simultaneous equation model, path model. The results found those volume and complexity variables are all statistically signi-ficance drivers of general hospital overhead costs. This study has documented that the level of service complexity is a significant determinant of hospital overhead costs, caution should be exercised in interpreting this as supportive of the cost accounting procedures associated with ABC. with ABC.

• Journal of information and communication convergence engineering
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• v.14 no.2
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• pp.115-121
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• 2016

Currently there is a lack of literature on SPICE-level models of double-gate (DG) tunnel field-effect transistors (TFETs). A DG TFET compact model is presented in this work that is used to develop a SPICE model for DG TFETs implemented with Verilog-A language. The compact modeling approach presented in this work integrates several issues in previously published compact models including ambiguity about the use of tunneling parameters A_k and B_k, and the use of a universal equation for calculating the surface potential of DG TFETs in all regimes of operation to deliver a general SPICE modeling procedure for DG TFETs. The SPICE model of DG TFET captures the drain current-gate voltage (I_ds-V_gs) characteristics of DG TFET reasonably well and offers a definite computational advantage over TCAD. The general SPICE modeling procedure presented here could be used to develop SPICE models for any combination of structural parameters of DG TFETs.

• Proceedings of the Korean Geotechical Society Conference
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• 2006.03a
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• pp.634-643
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• 2006

This study was intended to develop a high reliable technique by statistically processing on-site data with a general linear model, providing the basic data for construction, analysis of stability and establishment of maintenance measures for tunnel portal slopes in the future. This study evaluated the stability of a tunnel portal slope using a quantified technique, which is based on a general linear model. The important scores of each independent variable were allocated by using the ranges of the quantified values, based on the predicted coefficient of regression and the scores for categories of each independent variable were allocated so that those are equally spaced. The quantification model obtained from the results of evaluating the total data used for the quantification process provided precise results. In addition, it is expected that a more detail subdivision of response variables and sufficient data would produce a better stability evaluation standard.

• Journal of Engineering Education Research
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• v.20 no.3
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• pp.32-41
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• 2017

The $4^{th}$ industrial revolution refers to an era where machines capable of outperforming humans are created. In light of the 4th industrial revolution, university students are demanded problem solving abilities, critical thinking abilities, and problem discovering abilities as general and basic abilities. The need for changes in the university level communication education for engineering students remains imperative in this constantly changing social environment. The era where education is conducted only in classrooms is over. This paper discusses the need for diversified education such as the integration of online and offline education, the reinforcement of learning outside of the classroom as well as an education model that transcends formal and informal education such as games and activities that induce self-learning, both intentional and non-intentional learning, and the utilization of mass media and social networking systems. Through providing an education model that assesses and utilizes the data gained from the learning process provided above, this paper widens the perception of future education methods in the 4th industrial revolution.

• Journal of Industrial Technology
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• v.26 no.B
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• pp.63-71
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• 2006

The concerned object of the construction industry is environment. It is one of the main purposes of today's construction that human can live reasonably in nature. This study is about the fish-road connecting hydraulic structure in the river with nature. Chapter 2, starting with the general investigation about fish-road and helps comprehension for relatively general fish-road such as necessity, establishment purpose, history, study example, relating domestic law, design condition, consideration and form of fish-road. Chapter 3, containing the present condition of fish-road facilities in Gangwon-Do and thoughts of the problems and general countermeasures of existing fish-road. Chapter 4, Having Examined compatibility by amount of flowing water through hydraulic model test in the Ice harbor I-type model. chapter 5, Analyzation and arrangement to efficient establishment plan of fish-road and the result of the hydraulic model experiment to be beaconed a little in forward fish-road study. In the hydraulic model test result, when we suppose establishment of 1~3 in slope of 1/20, could know that applicable drought flow of the river is $0.06{\sim}3.0m^3/sec$ in case of Ice harbor I-type which transforming Ice harbor that was invented as studying project of the Ministry of Environment.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.19 no.2
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• pp.137-170
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• 2015

In this paper, we propose and analyze three viral infection models with humoral immunity including an eclipse stage of infected cells. The incidence rate of infection is represented by bilinear incidence and saturated incidence in the first and second models, respectively, while it is given by a more general function in the third one. The neutralization rate of viruses is giv0en by bilinear form in the first two models, while it is given by a general function in the third one. For each model, we have derived two threshold parameters, the basic infection reproduction number which determines whether or not a chronic-infection can be established without humoral immunity and the humoral immune response activation number which determines whether or not a chronic-infection can be established with humoral immunity. By constructing suitable Lyapunov functions we have proven the global asymptotic stability of all equilibria of the models. For the third model, we have established a set of conditions on the threshold parameters and on the general functions which are sufficient for the global stability of the equilibria of the model. We have performed some numerical simulations for the third model with specific forms of the incidence and neutralization rates and have shown that the numerical results are consistent with the theoretical results.

• Nuclear Engineering and Technology
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• v.46 no.6
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• pp.773-782
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• 2014

The general path model (GPM) is one approach for performing degradation-based, or Type III, prognostics. The GPM fits a parametric function to the collected observations of a prognostic parameter and extrapolates the fit to a failure threshold. This approach has been successfully applied to a variety of systems when a sufficient number of prognostic parameter observations are available. However, the parametric fit can suffer significantly when few data are available or the data are very noisy. In these instances, it is beneficial to include additional information to influence the fit to conform to a prior belief about the evolution of system degradation. Bayesian statistical approaches have been proposed to include prior information in the form of distributions of expected model parameters. This requires a number of run-to-failure cases with tracked prognostic parameters; these data may not be readily available for many systems. Reliability information and stressor-based (Type I and Type II, respectively) prognostic estimates can provide the necessary prior belief for the GPM. This article presents the Bayesian updating framework to include prior information in the GPM and compares the efficacy of including different information sources on two data sets.

• Child Health Nursing Research
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• v.18 no.4
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• pp.222-230
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• 2012

Purpose: The purpose of this study was to identify the effect of family stressors, family strains, general family values, family values for hospitalized children and family hardiness on family adaptation based upon McCubbin's family resilience model for families of hospitalized children in China. Methods: A survey using a self-report questionnaire was conducted with 330 hospitalized children's parents. Six instruments were used in this model. The data were analyzed using SPSS WIN 19.0 and AMOS 19.0 program. Results: Family strain had a significant negative direct effect, general family values and family hardiness had a significant positive direct effect, and family values for hospitalized children had a significant positive direct effect and indirect effect on family adaptation of hospitalized children. Conclusion: In this study McCubbin's resilience model and resiliency factors were identified. According to the finding of this study nursing interventions to reduce family stress, enhance family hardiness and consolidate general family values and family values for hospitalized children can help to increase family adaptation in families of hospitalized children. Therefore, the significance of this study is that the results can be used to develop family nursing intervention programs based on family resilience to strengthen family adaptation in families of hospitalized children.

• Psychiatry investigation
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• v.15 no.11
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• pp.1030-1036
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• 2018

Objective In this study, we aimed to develop a model predicting individuals with suicide ideation within a general population using a machine learning algorithm. Methods Among 35,116 individuals aged over 19 years from the Korea National Health & Nutrition Examination Survey, we selected 11,628 individuals via random down-sampling. This included 5,814 suicide ideators and the same number of non-suicide ideators. We randomly assigned the subjects to a training set (n=10,466) and a test set (n=1,162). In the training set, a random forest model was trained with 15 features selected with recursive feature elimination via 10-fold cross validation. Subsequently, the fitted model was used to predict suicide ideators in the test set and among the total of 35,116 subjects. All analyses were conducted in R. Results The prediction model achieved a good performance [area under receiver operating characteristic curve (AUC)=0.85] in the test set and predicted suicide ideators among the total samples with an accuracy of 0.821, sensitivity of 0.836, and specificity of 0.807. Conclusion This study shows the possibility that a machine learning approach can enable screening for suicide risk in the general population. Further work is warranted to increase the accuracy of prediction.