• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.6 no.1
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• pp.25-34
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• 1988

Digital Terrain Model is composed of two basic elements, namely, sampling and interpolation. They represent the procurement of data and the geometric reconstruction of terrain relief respectively. For evaluation DTM data, following two paremeters appear to be the most important factor, that is, the accuracy and efficiency and, in particular, the break point information significantly affect to the accuracy of DTM data. The main objective of this study is to improve the accuracy and efficiency of DTM by applying Progressive Sampling with distinct morphologic information. In this study, the total of 240 individual numerical tests has been implemented and the appropriate computer program is also developed for the test. The result of investigation shows that the Progressive Sampling with break point information improves the accuracy of DTM by 30 percent approximately.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.2
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• pp.117-137
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• 2010

Iris recognition is a biometric technique which uses unique iris patterns between the pupil and sclera. The advantage of iris recognition lies in high recognition accuracy; however, for good performance, it requires the diameter of the iris to be greater than 200 pixels in an input image. So, a conventional iris system uses a camera with a costly and bulky zoom lens. To overcome this problem, we propose a new method to restore a low resolution iris image into a high resolution image using a single image. This study has three novelties compared to previous works: (i) To obtain a high resolution iris image, we only use a single iris image. This can solve the problems of conventional restoration methods with multiple images, which need considerable processing time for image capturing and registration. (ii) By using bilinear interpolation and a constrained least squares (CLS) filter based on the degradation model, we obtain a high resolution iris image with high recognition performance at fast speed. (iii) We select the optimized parameters of the CLS filter and degradation model according to the zoom factor of the image in terms of recognition accuracy. Experimental results showed that the accuracy of iris recognition was enhanced using the proposed method.

• Journal of Microbiology and Biotechnology
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• v.16 no.9
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• pp.1331-1337
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• 2006

A mathematical model has been proposed for the batch culture of Agaricus blazei with mixed carbon sources of glucose and dextrin. In the proposed model, the metabolism of A. blazei was divided into three parts: cell growth, exopolysaccharides (EPS) production, and another EPS production pathway activated by dextrin hydrolysis. Each pathway was described mathematically and incorporated into the mechanistic model structure. Batch cultures were carried out with six different carbon source compositions. Although parameters were estimated by using the experimental data from the two extreme cases such as glucose only and dextrin only, the model represented well the profiles of glucose, cell mass, and EPS concentrations for all the six different carbon source mixtures, showing a good interpolation capability. Of note, the lag in EPS production could be quite precisely predicted by assuming that the glucose-to-cell mass ratio was the governing factor for EPS production.

• Journal of the Korean Solar Energy Society
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• v.38 no.1
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• pp.1-11
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• 2018

In this work, we propose weather prediction models to estimate hourly outdoor temperatures and solar irradiance in the next day using forecasting information. Hourly weather data predicted by the proposed models are useful for setting system operating strategies for the next day. The outside temperature prediction model considers 3-hourly temperatures forecasted by Korea Meteorological Administration. Hourly data are obtained by a simple interpolation scheme. The solar irradiance prediction is achieved by constructing a dataset with the observed cloudiness and correspondent solar irradiance during the last two weeks and then by matching the forecasted cloud factor for the next day with the solar irradiance values in the dataset. To verify the usefulness of the weather prediction models in predicting a short-term building load, the predicted data are inputted to a TRNSYS building model, and results are compared with a reference case. Results show that the test case can meet the acceptance error level defined by the ASHRAE guideline showing 8.8% in CVRMSE in spite of some inaccurate predictions for hourly weather data.

• Journal of Korea Water Resources Association
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• v.43 no.8
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• pp.757-767
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• 2010

This study employs the KED method using the correlations between probability rainfall and topographical factors as single auxiliary variable for assessing the effectiveness of external variables to improve the reliability in the estimation of spatial distribution of probability rainfall. As a result, the KED method gives similar results compared with deterministic spatial interpolation methods and kriging methods in the estimation of rainfall spatial distribution and mean areal rainfall, and as a result of the cross-validations of KED and kriging methods, the KED method using terrain elevation as auxiliary variable gives the best results, which are not significantly different in comparisons with other methods.

• Journal of Climate Change Research
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• v.7 no.4
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• pp.507-512
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• 2016

This study was conducted to classify agroclimatic zones in South Korea. To classify the agroclimatic zones, such climatic factors as amount of rainfall from April to May, amount of rainfall in October, monthly average air temperature in January, monthly average air temperature from April to May, monthly average air temperature from April to September, monthly average air temperature from December to March, monthly minimum air temperature in January, monthly minimum air temperature from April to May, Warmth Index were considered as major influencing factors on the crop growth. Climatic factors were computed from monthly air temperature and precipitation of climatological normal year (1981~2010) at 1 km grid cell estimated from a geospatial climate interpolation method. The agroclimatic zones using k-means cluster analysis method were classified into 6 zones.

• Advances in aircraft and spacecraft science
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• v.6 no.5
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• pp.391-407
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• 2019

Flight trajectory optimization has become an important factor not only to reduce the operational costs (e.g.,, fuel and time related costs) of the airliners but also to reduce the environmental impact (e.g.,, emissions, contrails and noise etc.) caused by the airliners. So far, these factors have been dealt with in the context of 2D and 3D trajectory optimization, which are no longer efficient. Presently, the 4D trajectory optimization is required in order to cope with the current air traffic management (ATM). This study deals with a cubic spline approximation method for solving 4D trajectory optimization problem (TOP). The state vector, its time derivative and control vector are parameterized using cubic spline interpolation (CSI). Consequently, the objective function and constraints are expressed as functions of the value of state and control at the temporal nodes, this representation transforms the TOP into nonlinear programming problem (NLP). The proposed method is successfully applied to the generation of a minimum length optimal trajectories along 4D waypoints, where the method generated smooth 4D optimal trajectories with very accurate results.

• Steel and Composite Structures
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• v.46 no.1
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• pp.33-51
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• 2023

This research presents a multi-material topology optimization for functionally graded material (FGM) and nonFGM with elastic buckling criteria. The elastic buckling based multi-material topology optimization of functionally graded steels (FGSs) uses a Jacobi scheme and a Method of Moving Asymptotes (MMA) as an expansion to revise the design variables shown first. Moreover, mathematical expressions for modified interpolation materials in the buckling framework are also described in detail. A Solid Isotropic Material with Penalization (SIMP) as well as a modified penalizing material model is utilized. Based on this investigation on the buckling constraint with homogenization material properties, this method for determining optimal shape is presented under buckling constraint parameters with non-homogenization material properties. For optimal problems, minimizing structural compliance like as an objective function is related to a given material volume and a buckling load factor. In this study, conflicts between structural stiffness and stability which cause an unfavorable effect on the performance of existing optimization procedures are reduced. A few structural design features illustrate the effectiveness and adjustability of an approach and provide some ideas for further expansions.

• Nuclear Engineering and Technology
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• v.56 no.5
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• pp.1762-1776
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• 2024

A spent nuclear fuel (SNF) analysis module for the Vodo-Vodyanoi Energetichesky Reactor (VVER) was developed and validated in this study. This advancement expands the application area of the existing nodal diffusion code, RAST-V, and reduces the need for additional code during 3D core simulations for SNF analysis, leading to increased efficiency in simulation time. RAST-V uses Lagrange interpolation and a power correction factor derived from the Bateman equation to bypass the re-depletion calculations, which are used to solve the microdepletion chain. This approach improved the efficiency of analysis. To mirror the conditions during the 3D core simulations, the module used history indices related to the moderator temperature, fuel temperature, and boron concentration. The module can predict 1620 isotopes. This paper presents the validation of this isotope inventory prediction and the application of burnup credit. The VVER analysis module was validated using 28 samples discharged from the Novovoronezh-4. Most isotopes were within 10 % of the boundaries of the measurements. This study successfully offers verification results using VVER benchmarks and discusses the application of burnup credit using a VVER-440 cask.

• Journal of Environmental Health Sciences
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• v.38 no.2
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• pp.128-135
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• 2012

Objectives: This study was aimed at determining the optimum coagulation dosage in a high turbid kaolin water sample using streaming current detection (SCD) as an alternative to the jar test. Methods: SCD is able to optimize coagulant dosing by titration of negatively charged particles. Kaolin particles were used to mimic highly turbid water ranging from 50 to 600 NTU, and polyaluminum chloride (PAC, 17%) was applied as a titrant and coagulant. The coagulation consisted of rapid stirring (5 min at 140 rpm), reduced stirring (20 min at 70 rpm), and settling (60 min). To confirm the coagulation effect, a jar test was also compared with the SCD titration results. Results: SCD titration of kaolin water samples showed that the dose of PAC increased as the pH rose. However, supernatant turbidity less than 1 NTU after coagulation was not achieved for high turbid water by SCD titration. Instead, a conversion factor was used to calculate the optimum PAC dosage for high turbid water by correlating a jar test result with that from an SCD titration. Using this approach, we were able to successfully achieve less than 1 NTU in treated water. Conclusions: For high turbid water influent in a water treatment plant, particularly during summer, the application of SCD control by applying a conversion factor can be more useful than a jar test due to the rapid calculation of coagulation dosage. Also, the interpolation of converted PAC dose could successfully achieve turbidity in the treated water of less than 1 NTU. This result indicates that an SCD system can be effectively used in a water treatment plant even for high turbid water during the rainy season.