• Interaction and multiscale mechanics
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• 제2권4호
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• pp.375-396
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• 2009

In the present work, the elasto-viscoplastic behavior, interactions between grains, and the texture evolution in polycrystalline materials subjected to finite deformations are modeled using a multiscale analysis procedure within a finite element framework. Computational homogenization is used to relate the grain (meso) scale to the macroscale. Specifically, a polycrystal is modeled by a material representative volume element (RVE) consisting of an aggregate of grains, and a periodic distribution of such unit cells is considered to describe material behavior locally on the macroscale. The elastic behavior is defined by a hyperelastic potential, and the viscoplastic response is modeled by a simple power law complemented by a work hardening equation. The finite element framework is based on a Lagrangian formulation, where a kinematic split of the deformation gradient into volume preserving and volumetric parts together with a three-field form of the Hu-Washizu variational principle is adopted to create a stable finite element method. Examples involving simple deformations of an aluminum alloy are modeled to predict inhomogeneous fields on the grain scale, and the macroscopic effective stress-strain curve and texture evolution are compared to those obtained using both upper and lower bound models.

• Journal of Forest and Environmental Science
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• 제40권1호
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• pp.15-23
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• 2024

This research aimed to assess the possibility of detecting forest degradation using time-series satellite imagery and three different deep learning-based change detection techniques. The dataset used for the deep learning models was composed of two sets, one based on surface reflectance (SR) spectral information from satellite imagery, combined with Texture Information (GLCM; Gray-Level Co-occurrence Matrix) and terrain information. The deep learning models employed for land cover change detection included image differencing using the Unet semantic segmentation model, multi-encoder Unet model, and multi-encoder Unet++ model. The study found that there was no significant difference in accuracy between the deep learning models for forest degradation detection. Both training and validation accuracies were approx-imately 89% and 92%, respectively. Among the three deep learning models, the multi-encoder Unet model showed the most efficient analysis time and comparable accuracy. Moreover, models that incorporated both texture and gradient information in addition to spectral information were found to have a higher classification accuracy compared to models that used only spectral information. Overall, the accuracy of forest degradation extraction was outstanding, achieving 98%.

• The Korean Journal of Ecology
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• 제18권1호
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• pp.55-62
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• 1995

This study was conducted to investigate the distribution pattern of plants on streamside of Kyonganchon, which is a tributary of the Han River, and to determine the relationships between plant distribution and environmental factors. Fifteen study sites were selected along the Kyonganchon, and vegetation distribution pattern and soil environmental factors were determined. The most frequently ocurring species in the study sites were Persicaria thunbergii, Persicaria hydropiper, Echinochloa crus-galli and Bidens frondosa, and among them the two Persicaria species were dominants of the community. Many species showed different distribution along the stream:Chenopodium album, Equisetum arvense and Setaria viridies occurred in the upstream region, while Rumex crispus, Leonurus sibiricus and Rorippa islandica occurred in the middle and downstream regions. Analysis of soil properties showed that organic matter and clay content were higher in the upstream region while sand content was higher in the downstream region. The results of DCA ordination showed that axis one was positively correlated with organic matter and clay content and negatively correlated with sand content, indicating that the distribution pattern of vegetation along the Kyonganchon was determined by elevational gradient from upstream to downstream region or gradient of stream width and water level, and by soil organic matter content and soil texture related to these gradients.

• International Journal of Computer Science & Network Security
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• 제21권1호
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• pp.40-48
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• 2021

Content-Based Image Retrieval (CBIR) system plays a vital role to retrieve the relevant images as per the user perception from the huge database is a challenging task. Images are represented is to employ a combination of low-level features as per their visual content to form a feature vector. To reduce the search time of a large database while retrieving images, a novel image retrieval technique based on feature dimensionality reduction is being proposed with the exploit of metaheuristic optimization techniques based on Genetic Algorithm (GA), Extended Binary Cuckoo Search (EBCS) and Whale Optimization Algorithm (WOA). Each image in the database is indexed using a feature vector comprising of fuzzified based color histogram descriptor for color and Median binary pattern were derived in the color space from HSI for texture feature variants respectively. Finally, results are being compared in terms of Precision, Recall, F-measure, Accuracy, and error rate with benchmark classification algorithms (Linear discriminant analysis, CatBoost, Extra Trees, Random Forest, Naive Bayes, light gradient boosting, Extreme gradient boosting, k-NN, and Ridge) to validate the efficiency of the proposed approach. Finally, a ranking of the techniques using TOPSIS has been considered choosing the best feature selection technique based on different model parameters.

• Korean Journal of Remote Sensing
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• 제34권6_2호
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• pp.1251-1260
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• 2018

High-quality sea-ice surface models generated from aerial images can be used effectively as field data for developing satellite-based remote sensing methods but also as analysis data for understanding geometric variations of Arctic sea-ice. However, the lack of texture information on sea-ice surfaces can reduce the accuracy of image matching. In this paper, we analyze the performance of matching cost functions for homogeneous sea-ice surfaces as a part of high-quality sea-ice surface model generation. The matching cost functions include sum of squared differences (SSD), normalized cross-correlation (NCC), and zero-mean normalized cross-correlation (ZNCC) in image domain and phase correlation (PC), orientation correlation (OC), and gradient correlation (GC) in frequency domain. In order to analyze the matching performance for texture changes clearly and objectively, a new evaluation methodology based on the principle of object-space matching technique was introduced. Experimental results showed that it is possible to secure reliability and accuracy of image matching only when optimal search windows are variably applied to each matching point in textureless regions such as sea-ice surfaces. Among the matching cost functions, NCC and ZNCC showed the best performance for texture changes.

• Journal of Korean Society of Forest Science
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• 제86권4호
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• pp.476-488
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• 1997

The purpose of this study was to figure out the suitable field standards for revegetation measures on cut-slopes in consideration of the environmental factors. The field survey was conducted from 1995 to 1996 on highway cut-slopes. The results obtained could be summarized as follows; The major revegetation measures surveyed were 5 major measures as a whole in descending order of seed-spraying measures, block-sod pitching measures, latticed block pitching measures, hydro-seeding measures with seed-fertilizer-soil materials, and several netting measures on highway cut-slopes. According to the analysis of the environmental factors, the plant coverage was affected several major environmental factors which were soil factors(soil hardness, soil texture, soil and rock condition), and site factors(slope gradient, slope length). From a viewpoint of optimum selection, the major 3 factors(soil factors, slope gradient factors, slope length factors) should be considered for selection of revegetation measures on highway cut-slopes.

• Journal of KIISE:Computer Systems and Theory
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• 제36권5호
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• pp.404-411
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• 2009

We introduce in this paper a new method for smooth foldover-free warping of images, based on the vector field deformation technique proposed by Von Funck et al. It allows users to specify the constraints in two different ways: positional constraints to constrain the position of a point in the image and gradient constraints to constrain the orientation and scaling of some parts of the image. From the user-specified constraints, it computes in the image domain a C1-continuous velocity vector field, along which each pixel progressively moves from its original position to the target. The target positions of the pixels are obtained by solving a set of partial derivative equations with the 4th order Runge-Kutta method. We show how our method can be useful for texture mapping with hard constraints. We start with an unconstrained planar embedding of a target mesh using a previously known method (Least Squares Conformal Map). Then, in order to obtain a texture map that satisfies the given constraints, we use the proposed warping method to align the features of the texture image with those on the unconstrained embedding. Compared to previous work, our method generates a smoother texture mapping, offers higher level of control for defining the constraints, and is simpler to implement.

• Journal of the Korea Computer Graphics Society
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• 제23권3호
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• pp.47-54
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• 2017

In this paper, we propose an improved curvature-based GPU (Graphics Processing Unit) isosurface ray-casting technique. Our method adopts the fast evaluation method proposed by Sigg et al. [1] to find the isosurface, but replaces the computation of the gradient and Hessian with the de Boor algorithm. In this way, we can reduce the number of additional texture fetches from 84 to 27 thus improving the performance by up to ${\approx}30%$, depending on the platforms.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 한국소성가공학회 2004년도 제5회 압연심포지엄 신 시장 개척을 위한 압연기술
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• pp.19-24
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• 2004

Symmetrical and asymmetrical rolling was performed in AA 1050 sheets. Asymmetrical rolling was carried out by using different roll velocities of upper and lower rolls. The effect of the reduction per rolling pass on the formation of textures and microstructures during symmetrical and asymmetrical rolling was studied. In order to intensify the shear deformation, symmetrical and asymmetrical rolling was carried out without lubrication. The strain states associated with rolling were investigated by simulations with the finite element method (FEM). A fairly homogeneous residual shear strain throughout the sheet thickness was observed after asymmetrical rolling. Symmetrical rolling with a high friction gave rise to a strong net shear strain gradient in the sheet thickness.

• Korean Journal of Environment and Ecology
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• 제20권4호
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• pp.415-424
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• 2006

This study was carried out to analyze the characteristics of forest watershed factors by using the quantification theory(I) for evaluation and prediction of the failure hazard area. Present $sediment(m^3/yr/ha)$ of erosion control dams were investigated in 95 sites of erosion control dam constructed during 1986 to 1999 in Gyeongnam province. The results obtained from this study were summarized as follows; General condition of class I(Very hazard area) were as follow; Igneous rock in parent rock, coniferous in forest type, below 20year in stand age, below 30cm in soil depth, SCL in soil texture, $31{\sim}40%$ in gravel contents, $S{\sim}E$ in aspect, $2,501{\sim}3,600m$ in length of main stream, $26{\sim}30$ in number of total streams, $6,601{\sim}10,000m$ in length of total streams, over 3 in stream order, over 16 in number of first streams order and over $31^{\circ}$ of slope gradient. General condition of class IIl(hazard area) were as follow; Metamorphic rock in parent rock, hardwood in forest type, over $21{\sim}24year$ in stand age, $31{\sim}40cm$ in soil depth, SiCL or SCL in soil texture, $11{\sim}20%$ in gravel contents, $S{\sim}W$ in aspect, $1,501{\sim}2,600m$ in length of main stream, $6{\sim}10$ in number of total streams, $3,501{\sim}5,500m$ in length of total streams, 2 in stream order, $6{\sim}10$ in number of first streams order and over $31^{\circ}$ of slope gradient. General condition of class III(Un hazard area) were as follow; Sedimentary rock in parent rock, mixed in forest type, over 25year in stand age, $41{\sim}50cm$ in soil depth, SiCL in soil texture, below 10% in gravel contents, $N{\sim}W$ in aspect, below 500m in length of main stream, below 5 in number of total streams, below 1,000m in length of total treams, below 1 in stream order, below 2 in number of first streams order and below $25^{\circ}$ of slope gradient. The prediction method of suitable for failure hazard area divided into class I, II, and III for the convenience of use. The score of class I evaluated as a very hazard area was over 4.8052. A score of class II was 4.8051 to 2.5602, it was evaluated as a hazard area, and class III was below 2.5601, it was evaluated as a un hazard area.