• Proceedings of the SAREK Conference
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• 2007.11a
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• pp.34-39
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• 2007

Condensing gas boiler units may make a big role for the reduction of energy consumption in heating industries. In order to decrease the energy consumption of a condensing gas boiler unit, the effective operations and controls of the system are necessary. In this study, mathematical models of a condensing gas boiler system were developed and programmed in order to predict dynamic behaviors of the system. These include dynamic models for a blower, a gas valve, a pump, a burner, a boiler heat exchanger, and a hot water heat exchanger. Control algorithms for the control of a gas valve, a blower, and a pump were also assumed. Simulation results showed good predictions of the dynamic phenomena of a boiler system. Therefore, the simulation program developed for this study may be effectively used for the development of control algorithms of the boiler system.

• Journal of Korean Society for Quality Management
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• v.46 no.4
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• pp.863-876
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• 2018

Purpose: There are several KPI(key performance indicators) models: BSC(balanced scorecard), IPOO(Input-process-output-outcomes) indicators, QCDP(quality-cost-delivery-productivity) indicators. This paper analyze these models and gives some suggestions to help the effective usage of KPI. Methods: This paper reviews and summarize the criteria to evaluate the PI(performance indicators) through literature review. Evaluation and analysis on the PI factors of the KPI developing models is performed by the criteria. Results: Criteria to evaluate the PI, which can be used to evaluate the goodness of PI is suggested. This paper also proposes some suggestions for the KPI models and their factors for the effective development of PI in the organization. Conclusion: This research will help the managers to develop and select useful PI and KPI for their business and processes.

• Journal of Ocean Engineering and Technology
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• v.36 no.3
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• pp.194-210
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• 2022

Recently, an analysis method using machine learning for solving problems in coastal and ocean engineering has been highlighted. Machine learning models are effective modeling tools for predicting specific parameters by learning complex relationships based on a specified dataset. In coastal and ocean engineering, various studies have been conducted to predict dependent variables such as wave parameters, tides, storm surges, design parameters, and shoreline fluctuations. Herein, we introduce and describe the application trend of machine learning models in coastal and ocean engineering. Based on the results of various studies, machine learning models are an effective alternative to approaches involving data requirements, time-consuming fluid dynamics, and numerical models. In addition, machine learning can be successfully applied for solving various problems in coastal and ocean engineering. However, to achieve accurate predictions, model development should be conducted in addition to data preprocessing and cost calculation. Furthermore, applicability to various systems and quantifiable evaluations of uncertainty should be considered.

• Journal of The Korean Association For Science Education
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• v.17 no.3
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• pp.333-343
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• 1997

The purpose of the present study was to investigate an appropriate instructional model in order to remedy students' misconception. As hypotheses of this study, three instructional models, cognitive conflicting, hypothesis testing, and learning cycle models, on biological 'osmosis' concept were tested in 176 high school students. Results of the present study are as follows: 1. All groups used one of three instructional models showed a statistically significant improvement in conceptual change on the 'osmosis' concept between before and after the instruction. In addition, the three hypothesized instructional models were more effective in conceptual change than a traditional expository instruction. 2. There was a statistically significant difference among three experimental groups. Cognitive conflicting model and hypothesis testing model was more effective than learning cycle models. 3. An interviewing after instruction showed that students who had scientific concept on the 'osmosis' through the instruction could effectively apply the concept to other context more than students who had no scientific concept through instruction. The present study indicated that instructional model play an important role on students' conceptual change in science classroom. According to the result of this study, the instruction emphasizing students' active participation in class and scientific reasoning process is more appropriate to remedy misconception that the instruction using students' passive participation in class and expository teaching procedure. This study also indicated that students' concept acquired through instruction is one of important factors to apply it to other context.

• Structural Engineering and Mechanics
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• v.67 no.5
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• pp.527-544
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• 2018

In this paper, the effect of homogenization models on stress analysis is presented for functionally graded plates (FGMs). The derivation of the effective elastic proprieties of the FGMs, which are a combination of both ceramic and metallic phase materials, is of most of importance. The majority of studies in the last decade, the Voigt homogenization model explored to derive the effective elastic proprieties of FGMs at macroscopic-scale in order to study their mechanical responses. In this work, various homogenization models were used to derive the effective elastic proprieties of FGMs. The effect of these models on the stress analysis have also been presented and discussed through a comparative study. So as to show this effect, a refined plate theory is formulated and evaluated, the number of unknowns and governing equations were reduced by dividing the transverse displacement into both bending and shear parts. Based on sinusoidal variation of displacement field trough the thickness, the shear stresses on top and bottom surfaces of plate were vanished and the shear correction factor was avoided. Governing equations of equilibrium were derived from the principle of virtual displacements. Analytical solutions of the stress analysis were obtained for simply supported FGM plates. The obtained results of the displacements and stresses were compared with those predicted by other plate theories available in the literature. This study demonstrates the sensitivity of the obtained results to different homogenization models and that the results generated may vary considerably from one theory to another. Finally, this study offers benchmark results for the multi-scale analysis of functionally graded plates.

• Journal of the Korean School Mathematics Society
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• v.9 no.1
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• pp.1-17
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• 2006

This thesis analyzed the effects of cooperative learning blended with TAI(Team Assisted Individualization) and STAD(Student Team Achievement Division) models on the students' ability of problem solving in mathematics in order to discover what kind of effects would give to their ability of that, and would promote their disposition and attitude to learn mathematics. The results of this study were as follows : First, the learning method blended with TAI and STAD models was more effective in the students' ability of problem solving in mathematics than traditional learning method because of the blended model's characteristics; positive interdependence, individual accountability, team recognition, curriculum materials. Second, the learning method blended with TAI and STAD models was more effective in sub-elements - self-confidence, adaptability, will, curiosity and value - of mathematical disposition than traditional learning method. And the learning method blended with TAI and STAD models was more effective in sub-elements - self-consciousness of mathematics and interests - of mathematical attitude than traditional learning method. In conclusion, the learning method blended with TAI and STAD models could affect to not only the students' ability of problem solving in mathematics but also the students' several affective factors.

• Earthquakes and Structures
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• v.25 no.1
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• pp.27-41
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• 2023

This study focused on nonlinear effective stress site response analysis using two coupled constitutive models, that is, the DM model (Dafalias and Manzari 2004), which incorporated a simple plasticity sand model accounting for fabric change effects, and the PMDY03 model (Khosravifar et al. 2018), that is, a 3D model for earthquake-induced liquefaction triggering and postliquefaction response. A detailed parametric study was conducted to validate the effectiveness of nonlinear site response analysis and porewater pressure (PWP) generation through a true coupled formulation for assessing the initiation of liquefaction at ground level. The coupled models demonstrated accurate prediction of liquefaction triggering, which was in line with established empirical liquefaction triggering relations in published databases. Several limitations were identified in the evaluation of liquefaction using the cyclic stress method, despite its widespread implementation for calculating liquefaction triggering. Variations in shear stiffness, represented by changes in shear wave velocity (Vs1), exerted the most significant influence on site response. The study further indicated that substantial differences in response spectra between nonlinear total stress and nonlinear effective stress analyses primarily occurred when liquefaction was triggered or on the verge of being triggered, as shown by excess PWP ratios approaching unity. These differences diminished when liquefaction occurred towards the later stages of intense shaking. The soil response was predominantly influenced by the higher stiffness values present prior to liquefaction. A key contribution of this study was to validate the criteria used to assess the triggering of level-ground liquefaction using true coupled effective-stress constitutive models, while also confirming the reliability of numerical approximations including the PDMY03 and DM models. These models effectively captured the principal characteristics of liquefaction observed in field tests and laboratory experiments.

• Journal of the Korean Data and Information Science Society
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• v.20 no.5
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• pp.913-917
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• 2009

The measures of leverage in linear regression has been extended to nonlinear regression models. We consider several curvature measures of nonlinearity in an estimation situation. The relationship between measures of leverage and statistical curvature are explored in nonlinear regression models. The circumstances under which the Jacobian leverage reduces to a tangent plane leverage are discussed in connection with the effective residual curvature of the nonlinear model.

• Journal of Korean Society for Quality Management
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• v.32 no.4
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• pp.103-112
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• 2004

Total Quality Management(TQM) in Higher Education Institution(HEI) has been popular since early 1980s. Implementation of TQM, however, has not been easy. The difficulties of the implementation is partially due to the lack of effective TQM models in HEIs. This paper proposed a new model based on PDCA cycle. The paper consists of four chapters. First chapter Introduces the status of TQM in HEIs and implementation problems. Second chapter delineates the models used in HEIs. In third chapter, a new model is suggested. Last chapter is the conclusions.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.202-207
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• 2023

In this paper, we discuss the design and implementation of a recommendation platform actually built in the field. We survey deep learning-based recommendation models that are effective in reflecting individual user characteristics. The recently proposed RNN-based sequential recommendation models reflect individual user characteristics well. The recommendation platform we proposed has an architecture that can collect, store, and process big data from a company's commercial services. Our recommendation platform provides service providers with intuitive tools to evaluate and apply timely optimized recommendation models. In the model evaluation we performed, RNN-based sequential recommendation models showed high scores.