• Coupled systems mechanics
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• v.7 no.2
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• pp.211-232
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• 2018

In this work we present an upscaling technique for multi-scale computations based on a stochastic model calibration technique. We consider a coarse-scale continuum material model described in the framework of generalized standard materials. The model parameters are considered uncertain, and are determined in a Bayesian framework for the given fine scale data in a form of stored energy and dissipation potential. The proposed stochastic upscaling approach is independent w.r.t. the choice of models on coarse and fine scales. Simple numerical examples are shown to demonstrate the ability of the proposed approach to calibrate coarse scale elastic and inelastic material parameters.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.448-449
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• 2022

In the image upscaling field, the method using deep learning is showing better results than using the interpolation method. And for hologram upscaling, using deep learning is showing better results than general interpolation. In this paper, the network structure and learning results are analyzed. The learning results are compared by adjusting the depth of the network and the number of channels at the same weight.

• Coupled systems mechanics
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• v.11 no.5
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• pp.411-438
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• 2022

In this paper, we present the parameter identification for inelastic and multi-scale problems. First, the theoretical background of several fundamental methods used in the upscaling process is reviewed. Several key definitions including random field, Bayesian theorem, Polynomial chaos expansion (PCE), and Gauss-Markov-Kalman filter are briefly summarized. An illustrative example is given to assimilate fracture energy in a simple inelastic problem with linear hardening and softening phases. Second, the parameter identification using the Gauss-Markov-Kalman filter is employed for a multi-scale problem to identify bulk and shear moduli and other material properties in a macro-scale with the data from a micro-scale as quantities of interest (QoI). The problem can also be viewed as upscaling homogenization.

• Journal of the Korea Computer Graphics Society
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• v.29 no.5
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• pp.31-40
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• 2023

As display resolution increases, many apps also tend to include high-resolution texture maps. Recent advancements in deep-learning-based image super-resolution techniques make it possible to automate high-resolution texture generation. However, there is still a lack of comprehensive analysis of the application of these techniques to texture maps. In this paper, we selected three recent super-resolution techniques, namely BSRGAN, Real-ESRGAN, and SwinIR (classical and real-world image SR), and applied them to upscale texture maps. We then conducted a quantitative and qualitative analysis of the experimental results. The findings revealed various artifacts after upscaling, which indicates that there are still limitations in directly applying super-resolution techniques to texture-map upscaling.

• Journal of Korean Society of Forest Science
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• v.100 no.3
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• pp.455-465
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• 2011

In order to assess and mitigate climate change, the role of forest biomass as carbon sink has to be understood spatially and quantitatively. Since existing forest statistics can not provide spatial information about forest resources, it is needed to predict spatial distribution of forest biomass under an alternative scheme. This study focuses on developing an upscaling method that expands forest variables from plot to landscape scale to estimate spatially explicit aboveground biomass(AGB). For this, forest stand variables were extracted from National Forest Inventory(NFI) data and used to develop AGB regression models by tree species. Dominant/codominant height and crown density were used as explanatory variables of AGB regression models. Spatial distribution of AGB could be estimated using AGB models, forest type map and the stand height map that was developed by forest type map and height regression models. Finally, it was estimated that total amount of forest AGB in Danyang was 6,606,324 ton. This estimate was within standard error of AGB statistics calculated by sample-based estimator, which was 6,518,178 ton. This AGB upscaling method can provide the means that can easily estimate biomass in large area. But because forest type map used as base map was produced using categorical data, this method has limits to improve a precision of AGB map.

• Journal of Environmental Science International
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• v.28 no.2
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• pp.259-266
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• 2019

Two main sources of data, meteorological data and land surface characteristics, are essential to effectively run a distributed rainfall-runoff model. The specification and averaging of the land surface characteristics in a suitable way is crucial to obtaining accurate runoff output. Recent advances in remote sensing techniques are often being used to derive better representations of these land surface characteristics. Due to the mismatch in scale between digital land cover maps and numerical grid sizes, issues related to upscaling or downscaling occur regularly. A specific method is typically selected to average and represent the land surface characteristics. This paper examines the amount of flooding by applying the FLO-2D routing model, where vegetation heterogeneity is manipulated using the Manning's roughness coefficient. Three different upscaling methods, arithmetic, dominant, and aggregation, were tested. To investigate further, the rainfall-runoff model with FLO-2D was facilitated in Yongdam catchment and heavy rainfall events during wet season were selected. The results show aggregation method provides better results, in terms of the amount of peak flow and the relative time taken to achieve it. These rwsults suggest that the aggregation method, which is a reasonably realistic description of area-averaged vegetation nature and characteristics, is more likely to occur in reality.

• Journal of Environmental Policy
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• v.6 no.3
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• pp.115-145
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• 2007

This study was performed for developing upscaling Environmental Conservation Value Assessment Map(ECVAM) of National Land in South Korea and presenting the application method of ECVAM. This ECVAM adopted the least indicator method and uses a Geographic Information System(GIS). This map is made through evaluation of 67 items. As a result, the construction of ECVAM was defined as a process of identifying land use to scientifically assess the physical and environmental value of land and classify conservation value into several grades for the sustainable management of environmental resources. After applying ECVAM criteria of five degrees to the whole of study area, Grade I, showing the highest conservation value, accounted for 29.3% by land area of ECVAM. Grades II, III, IV and V likewise accounted for, respectively, 21.7%, 17.2%, 7.1% and the lowest conservation value of 24.7%. other result, ECVAM and land suitability assessment agreement rate is Grade I 33.05%, Grades II, III, IV and V likewise accounted for 12.92%, 15.05%, 36.93% and last value of 53.28% This study set up "the realization of the improvement ECVAM" as the vision of the advancing strategy. In order to accomplish the vision, this study established the purpose as follow; constructing strategic assessment value relation to ECVAM based on knowledge, arranging the foundation to upscaling assessment value And this study devised preparatory plans to achieve the vision and the purpose as next; construction on base theme map by 1:5,000 scalie, base on land register theme map and precision land cover map. Therefore, for applying the result of this study to the upscaling Environmental Conservation Value Assessment Map(ECVAM), it considers regularly the systematic categorization of preceding item, consideration issue of national environmental geographic information using the ECVAM.

• Journal of Korean Society of Forest Science
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• v.111 no.3
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• pp.435-449
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• 2022

Forest canopy height is an indispensable vertical structure parameter that can be used for understanding forest biomass and carbon storage as well as for managing a sustainable forest ecosystem. Plot-based field surveys, such as the national forest inventory, have been conducted to provide estimates of the forest canopy height. However, the comprehensive nationwide field monitoring of forest canopy height has been limited by its cost, lack of spatial coverage, and the inaccessibility of some forested areas. These issues can be addressed by remote sensing technology, which has gained popularity as a means to obtain detailed 2- and 3-dimensional measurements of the structure of the canopy at multiple scales. Here, we reviewed both international and domestic studies that have used remote sensing technology approaches to estimate the forest canopy height. We categorized and examined previous approaches as: 1) LiDAR approach, 2) Stereo or SAR image-based point clouds approach, and 3) combination approach of remote sensing data. We also reviewed upscaling approaches of utilizing remote sensing data to generate a continuous map of canopy height across large areas. Finally, we provided suggestions for further advancement of the Korean forest canopy height estimation system through the use of various remote sensing technologies.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1295-1296
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• 2007

A lot of researches about dye-sensitized solar cell (DSC) are recently being conducted. Because DSC has several advantages to pass the limits of silicon solar cells such as a low manufacturing expense, a simple manufacturing process and its transparency. But most researches on DSC are still conducted about the unit cell and laboratory-centered. That is, present researches on DSC are not practical. Therefore, researches about large area cells and modules have to be prerequisites for DSC to have the practicality. Characteristics of large area DSC are so different from those of small area DSC in aspect of fill factor and efficiency. In this study, we made an experiment on finding suitable size of DSC that has the most effective power according to the variation of active area. In detail, the experiment was conducted about the optimum ratio of length to width and we introduced the ratio of active area to non-active area to find the active area which has the best output. Because small DSC doesn‘t have the best output in comparison with total area of cell although the smaller DSC has the better efficiency. As a result, we achieved the optimum ratio of length to width of 8:3 and active area of $8cm^2$ as the optimum size for upscaling DSC.

• Computers and Concrete
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• v.5 no.4
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• pp.295-328
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• 2008

A previously published multiscale model for early-age cement-based materials [Pichler, et al.2007. "A multiscale micromechanics model for the autogenous-shrinkage deformation of early-age cement-based materials." Engineering Fracture Mechanics, 74, 34-58] is extended towards upscaling of viscoelastic properties. The obtained model links macroscopic behavior, i.e., creep compliance of concrete samples, to the composition of concrete at finer scales and the (supposedly) intrinsic material properties of distinct phases at these scales. Whereas finer-scale composition (and its history) is accessible through recently developed hydration models for the main clinker phases in ordinary Portland cement (OPC), viscous properties of the creep active constituent at finer scales, i.e., calcium-silicate-hydrates (CSH) are identified from macroscopic creep tests using the proposed multiscale model. The proposed multiscale model is assessed by different concrete creep tests reported in the open literature. Moreover, the model prediction is compared to a commonly used macroscopic creep model, the so-called B3 model.