• Bulletin of the Korean Chemical Society
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• v.30 no.5
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• pp.1139-1142
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• 2009

Refinement of NMR structures by molecular dynamics (MD) simulations with a solvent model has improved the structural quality. In this study, we applied MD refinement with the generalized Born (GB) implicit solvent model to protein structure determined under membrane-like environments. Despite popularity of the GB model, its applications to the refinement of NMR structures of hydrophobic proteins, in which detergents or organic solvents enclose proteins, are limited, and there is little information on the use of another GB parameter for these cases. We carried out MD refinement of crambin NMR structure in dodecylphosphocholine (DPC) micelles (Ahn et al., J. Am. Chem. Soc. 2006, 128, 4398-4404) with GB/Surface area model and two different surface tension coefficients, one for aquatic and the other for hydrophobic conditions. Our data show that, of two structures by MD refinement with GB model, the one refined with the parameter to consider hydrophobic condition had the better qualities in terms of precision and solvent accessibility.

• Smart Structures and Systems
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• v.15 no.5
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• pp.1329-1344
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• 2015

The stiffness of a structure is one of several structural signals that are useful indicators of the amount of damage that has been done to the structure. To accurately estimate the stiffness, an equation of motion containing a stiffness parameter must first be established by expansion as a linear series model, a Taylor series model, or a power series model. The model is then used in multivariate autoregressive modeling to estimate the structural stiffness and compare it to the theoretical value. Stiffness assessment for modeling purposes typically involves the use of one of three statistical model refinement approaches, one of which is the efficient Akaike information criterion (AIC) proposed in this paper. If a newly added component of the model results in a decrease in the AIC value, compared to the value obtained with the previously added component(s), it is statistically justifiable to retain this new component; otherwise, it should be removed. This model refinement process is repeated until all of the components of the model are shown to be statistically justifiable. In this study, this model refinement approach was compared with the two other commonly used refinement approaches: principal component analysis (PCA) and principal component regression (PCR) combined with the AIC. The results indicate that the proposed AIC approach produces more accurate structural stiffness estimates than the other two approaches.

• School Mathematics
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• v.9 no.4
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• pp.467-486
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• 2007

In mathematical modeling activity modeling process is usually an iterative process. When model can not be solved, the model needs to be simplified by treating some variables as constants, or by ignoring some variables. On the other hand, when the results from the model are not precise enough, the model needs to be refined by considering additional conditions. In this study we investigate the role of spreadsheet model in model refinement and modeling process. In detail, we observed that by using spreadsheet model students can solve model which can not be solved in paper-pencil environment. And so they need not go back to model simplification process but continue model refinement. By transforming mathematical model to spreadsheet model, the students can predict or explain the real word situations directly without passing the mathematical conclusions step in modeling process.

• Resources Recycling
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• v.30 no.1
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• pp.14-25
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• 2021

As a demand of high-end steel raises, the importance of secondary refinement process also increases. However, the content of each component in molten steel, slag and inclusions change with the time, meaning the secondary refinement process is not an equilibrium state. Furthermore, many reactions occur between molten steel, slag, inclusion, refractory and alloying element during secondary refinement process. In order to consider the above complex reactions with non-equilibrium state, a few researchers developed kinetic models in secondary refinement process based on the experimental numerical equations. It is important to analyze and review to the previously reported models to develop a precise model. Therefore, in present study, the complex reaction models based on kinetic in secondary refinement process were analyzed, reviewed, and introduced. Moreover, the single reaction models also introduced which would be applied to the complex reaction models.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.39 no.5
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• pp.415-423
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• 2015

In this study, we present a grid refinement model in the lattice Boltzmann method (LBM) for two-dimensional incompressible fluid flow. That is, the model combines the desirable features of the lattice Boltzmann method and stream function-vorticity formulations. In order to obtain an accurate result, very fine grid (or lattice) is required near the solid boundary. Therefore, the grid refinement model is used in the lattice Boltzmann method for stream function-vorticity formulation. This approach is more efficient in that it can obtain the same accurate solution as that in single-block approach even if few lattices are used for computation. In order to validate the grid refinement approach for the stream function-vorticity formulation, the numerical simulations of lid-driven cavity flows were performed and good results were obtained.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.11
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• pp.1844-1853
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• 2001

In the present investigation, it was attempted to design the rolling pass schedule fur a clean steel of 0.1C-1.5Mn-0.25Si with the objective of the austenite grain refinement. As the method of approach, a coupled mathematical modeling technique was proposed which consists of a recrystallization model and a flow stress modes. The validity of the coupled model was examined through comparison with results of continuous and discontinuous compression tests at various temperatures, strains and strain rates. The coupled model was incorporated with the finite element method to set up a systematic design methodology far the rolling path schedule for austenite grain refinement. Two path schedules were obtained and discussed in the paper with regard to rolling path time, average grain size, grain size deviation in thickness, etc.

• Journal of the Korea Society of Computer and Information
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• v.21 no.12
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• pp.97-105
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• 2016

Network-Centric Operational Environment(NCOE) service becomes critical in today's military environment network because reusability of service and interaction are being increasingly important as well in business process. However, the refinement of service by semantic similarity and functional similarity at the business process was not detailed yet. In order to enhance accuracy of refining of business service, in this study, the authors introduce a method for refining service by semantic similarity and functional similarity in BPMN model. The business process are designed in a BPMN model. In this model, candidated services are refined through binding related activities by the analysis result of semantic similarity based on word-net and functional similarity based on properties specification between activities. Then, the services are identified through refining the candidated service. The proposed method is expected to enhance the service identification with accuracy and modularity. It also can accelerate more standardized service refinement developments by the proposed method.

• Journal of the Korean School Mathematics Society
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• v.17 no.4
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• pp.657-677
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• 2014

The present qualitative case study explored the ways in which three middle school students constructed and refined their mathematical models and modeling processes, and factors that had influenced such refinement. The results suggest that students' modeling processes are non-sequential in that the participant students reformulated their initial problem from the real-world problem situation and revised the model when they could not get a satisfactory solution or the acquired solution did not make sense. Moreover, the students' model refinement processes were affected by the following four elements: the types of real-word problem situations, students' metacognitive thinking, communications between teachers and peers, and the role of teachers.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.122-122
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• 2020

Urban flood simulation plays a vital role in national flood early warning, prevention and mitigation. In recent studies on 2-dimensional flood modeling, the integrated run-off inundation model is gaining grounds due to its ability to perform in greater computational efficiency. The adaptive quadtree shallow water numerical technique used in this model implements the adaptive mesh refinement (AMR) in this simulation, a procedure in which the grid resolution is refined automatically following the flood flow. The method discounts the necessity to create a whole domain mesh over a complex catchment area, which is one of the most time-consuming steps in flood simulation. This research applies the dynamic grid refinement method in simulating the recent extreme flood events in Metro Manila, Philippines. The rainfall events utilized were during Typhoon Ketsana 2009, and Southwest monsoon surges in 2012 and 2013. In order to much more visualize the urban flooding that incorporates the flow within buildings and high-elevation areas, Digital Surface Model (DSM) resolution of 5m was used in representing the ground elevation. Results were calibrated through the flood point validation data and compared to the present flood hazard maps used for policy making by the national government agency. The accuracy and efficiency of the method provides a strong front in making it commendable to use for early warning and flood inundation analysis for future similar flood events.

• Journal of the Semiconductor & Display Technology
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• v.12 no.1
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• pp.1-7
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• 2013

Grey-level statistical models have been widely used in many applications for object location and identification. However, conventional models yield some problems in model refinement when training images are not properly aligned, and have difficulties for real-time recognition of arbitrarily rotated models. This paper presents improved grey-level statistical models that align training images using image or feature matching to overcome problems in model refinement of conventional models, and that enable real-time recognition of arbitrarily rotated objects using efficient hierarchical search methods. Edges or features extracted from a mean training image are used for accurate alignment of models in the search image. On the aligned position and orientation, fitness measure based on grey-level statistical models is computed for object recognition. It is demonstrated in various experiments in PCB inspection that proposed methods are superior to conventional methods in recognition accuracy and speed.