• Title/Summary/Keyword: MINC

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Development of Methodology for Fracture Network Analysis in the Unsaturated Zone using MINC Approach in TOUGH2 Code (TOUGH2 전산코드의 MINC 기법을 이용한 불포화 암반 내 단열 해석 방법론 개발)

  • Ha, Jaechul;Cheong, Jae-yeol;Kim, Soogin;Yoon, Jeonghyoun
    • The Journal of Engineering Geology
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    • v.26 no.3
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    • pp.325-330
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    • 2016
  • The second phase of low- and intermediate-level waste (LILW) disposal facility is under planned on the sedimentary rock in unsaturated zone. In this study, we created two meshes which were a matrix continuum mesh and a fracture continuum mesh to carry out 2 dimensional numerical modeling for groundwater flow in the unsaturated zone containing fractures focused on the second phase of LILW disposal facility. Two continuum meshes were developed using MINC in meshmaker module of TOUGH2 code. A fracture continuum mesh was included the k-field distribution of the permeability derived from the Discrete Fractured Network (DFN) modeling. To apply the unsaturated zone for the modeling, the gridding steps to generate mesh were developed. Each step to generate a mesh consisted of definition of materials, setting the initial conditions and creating grids using MINC. The methodology development of meshes in this study will be applied for more precise modeling of groundwater flow and mass transport.

NEW BOUNDS FOR PERRON ROOT OF A NONNEGATIVE MATRIX

  • Chen, Jinhai;Li, Weiguo
    • Journal of applied mathematics & informatics
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    • v.23 no.1_2
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    • pp.337-344
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    • 2007
  • In this paper, we obtain some new bounds for Perron root of a nonnegative matrix, which are expressed by easily calculated function in element of matrix. These new results generalize and improve the bounds of G. Frobenius [1] and H. Minc [2], and also extend the known results by Liu [6].

On spanning column rank of matrices over semirings

  • Song, Seok-Zun
    • Bulletin of the Korean Mathematical Society
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    • v.32 no.2
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    • pp.337-342
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    • 1995
  • A semiring is a binary system $(S, +, \times)$ such that (S, +) is an Abelian monoid (identity 0), (S,x) is a monoid (identity 1), $\times$ distributes over +, 0 $\times s s \times 0 = 0$ for all s in S, and $1 \neq 0$. Usually S denotes the system and $\times$ is denoted by juxtaposition. If $(S,\times)$ is Abelian, then S is commutative. Thus all rings are semirings. Some examples of semirings which occur in combinatorics are Boolean algebra of subsets of a finite set (with addition being union and multiplication being intersection) and the nonnegative integers (with usual arithmetic). The concepts of matrix theory are defined over a semiring as over a field. Recently a number of authors have studied various problems of semiring matrix theory. In particular, Minc [4] has written an encyclopedic work on nonnegative matrices.

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Material Image Classification using Normal Map Generation (Normal map 생성을 이용한 물질 이미지 분류)

  • Nam, Hyeongil;Kim, Tae Hyun;Park, Jong-Il
    • Journal of Broadcast Engineering
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    • v.27 no.1
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    • pp.69-79
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    • 2022
  • In this study, a method of generating and utilizing a normal map image used to represent the characteristics of the surface of an image material to improve the classification accuracy of the original material image is proposed. First of all, (1) to generate a normal map that reflects the surface properties of a material in an image, a U-Net with attention-R2 gate as a generator was used, and a Pix2Pix-based method using the generated normal map and the similarity with the original normal map as a reconstruction loss was used. Next, (2) we propose a network that can improve the accuracy of classification of the original material image by applying the previously created normal map image to the attention gate of the classification network. For normal maps generated using Pixar Dataset, the similarity between normal maps corresponding to ground truth is evaluated. In this case, the results of reconstruction loss function applied differently according to the similarity metrics are compared. In addition, for evaluation of material image classification, it was confirmed that the proposed method based on MINC-2500 and FMD datasets and comparative experiments in previous studies could be more accurately distinguished. The method proposed in this paper is expected to be the basis for various image processing and network construction that can identify substances within an image.