• Title/Summary/Keyword: domain

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A flexible, full-color OTFT-OLED display

  • Yagi, I.;Hirai, N.;Miyamoto, Y.;Noda, M.;Imaoka, A.;Yasuda, R.;Yoneya, N.;Nomoto, K.;Yumoto, A.;Kasahara, J.
    • 한국정보디스플레이학회:학술대회논문집
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    • 2008.10a
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    • pp.1627-1630
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    • 2008
  • We have demonstrated a flexible and full-color OTFT-OLED display. The display has a top-emitting pixel structure with a resolution of 80 ppi, which can be achieved by developed integration architecture of OTFTs. The 0.3-mm-thick flexible display exhibits peak brightness over 100 nit with a contrast ratio greater than 1000:1.

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An Effect of Sampling Rate to the Time and Frequency Domain Analysis of Pulse Rate Variability (샘플링율이 맥박변이도 시간 및 주파수 영역 분석에 미치는 영향)

  • Yang, Yoon La;Shin, Hangsik
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.65 no.7
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    • pp.1247-1251
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    • 2016
  • This study aims to investigate the effect of sampling frequency to the time domain and frequency domain analysis of pulse rate variability (PRV). Typical time domain variables - AVNN, SDNN, SDSD, RMSSD, NN50 count and pNN50 - and frequency domain variables - VLF, LF, HF, LF/HF, Total Power, nLF and nHF - were derived from 7 down-sampled (250 Hz, 100 Hz, 50 Hz, 25 Hz, 20 Hz, 15 Hz, 10 Hz) PRVs and compared with the result of heart rate variability of 10 kHz-sampled electrocardiogram. Result showed that every variable of time domain analysis of PRV was significant at 25 Hz or higher sampling frequency. Also, in frequency domain analysis, every variable of PRV was significant at 15 Hz or higher sampling frequency.

Improving Adversarial Domain Adaptation with Mixup Regularization

  • Bayarchimeg Kalina;Youngbok Cho
    • Journal of information and communication convergence engineering
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    • v.21 no.2
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    • pp.139-144
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    • 2023
  • Engineers prefer deep neural networks (DNNs) for solving computer vision problems. However, DNNs pose two major problems. First, neural networks require large amounts of well-labeled data for training. Second, the covariate shift problem is common in computer vision problems. Domain adaptation has been proposed to mitigate this problem. Recent work on adversarial-learning-based unsupervised domain adaptation (UDA) has explained transferability and enabled the model to learn robust features. Despite this advantage, current methods do not guarantee the distinguishability of the latent space unless they consider class-aware information of the target domain. Furthermore, source and target examples alone cannot efficiently extract domain-invariant features from the encoded spaces. To alleviate the problems of existing UDA methods, we propose the mixup regularization in adversarial discriminative domain adaptation (ADDA) method. We validated the effectiveness and generality of the proposed method by performing experiments under three adaptation scenarios: MNIST to USPS, SVHN to MNIST, and MNIST to MNIST-M.

WEAK SOLUTION OF AN ARCH EQUATION ON A MOVING BOUNDARY

  • DAEWOOK KIM;SUDEOK SHON;JUNHONG HA
    • Journal of applied mathematics & informatics
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    • v.42 no.1
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    • pp.49-64
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    • 2024
  • When setting up a structure with an embedded shallow arch, there is a phenomenon where the end of the arch moves. To study the so-called moving domain problem, one try to transform a considered noncylindrical domain into the cylindrical domain using the transform operator, as well as utilizing the method of penalty and other approaches. However, challenges arise when calculating time derivatives of solutions in a domain depending on time, or when extending the initial conditions from the non-cylindrical domain to the cylindrical domain. In this paper, we employ the transform operator to prove the existence and uniqueness of weak solutions of the shallow arch equation on the moving domain as clarifying the time derivatives of solutions in the moving domain.

Domain Mapping using Nonlinear Finite Element Formulation

  • Patro, Tangudu Srinivas;Voruganti, Hari K.;Dasgupta, Bhaskar;Basu, Sumit
    • International Journal of CAD/CAM
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    • v.8 no.1
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    • pp.29-36
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    • 2009
  • Domain mapping is a bijective transformation of one domain to another, usually from a complicated general domain to a chosen convex domain. This is directly useful in many application problems like shape modeling, morphing, texture mapping, shape matching, remeshing, path planning etc. A new approach considering the domain as made up of structural elements, like membranes or trusses, is developed and implemented using the nonlinear finite element formulation. The mapping is performed in two stages, boundary mapping and inside mapping. The boundary of the 3-D domain is mapped to the surface of a convex domain (in this case, a sphere) in the first stage and then the displacement/distortion of this boundary is used as boundary conditions for mapping the interior of the domain in the second stage. This is a general method and it develops a bijective mapping in all cases with judicious choice of material properties and finite element analysis. The consistent global parameterization produced by this method for an arbitrary genus zero closed surface is useful in shape modeling. Results are convincing to accept this finite element structural approach for domain mapping as a good method for many purposes.

Linear Time Domain Analysis of Radiation Problems (시간영역법에 의한 강제동요시 동유체력 해석)

  • I.Y.,Gong;K.P.,Rhee
    • Bulletin of the Society of Naval Architects of Korea
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    • v.24 no.4
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    • pp.9-18
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    • 1987
  • The hydrodynamic radiation forces acting on a ship travelling in waves have been conventionally treated by strip theories or by direct three dimensional approaches, most of which have been formulated in frequency domain. If the forward speed of a ship varies with time, or if its path is not a straight line, conventional frequency domain analysis can no more be used, and for these cases time domain analysis may be used. In this paper, formulations are made in time domain with applications to some problems the results of which are known in frequency domain. And the results of both domains are compared to show the characteristics and validity of time domain solutions. The radiation forces acting on a three dimensional body within the framework of a linear theory. If the linearity of entire system is assumed, radiation forces due to arbitrary ship motions can be expressed by the convolution integral of the arbitrary motion velocity and the so called impulse response function. Numerical calculations are done for some bodies of simple shapes and Series-60[$C_B=0.7$] ship model. For all cases, integral equation techniques with transient Green's function are used, and velocity or acceleration potentials are obtained as the solution of the integral equations. In liner systems, time domain solutions are related with frequency domain solutions by Fourier transform. Therefore time domain solutions are Fourier transformed by suitable relations and the results are compared with various frequency domain solutions, which show good agreements.

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2D Finite Difference Time Domain Method Using the Domain Decomposition Method (영역분할법을 이용한 2차원 유한차분 시간영역법 해석)

  • Hong, Ic-Pyo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.17 no.5
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    • pp.1049-1054
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    • 2013
  • In this paper, two-dimensional(2-D) Finite Difference Time Domain(FDTD) method using the domain decomposition method is proposed. We calculated the electromagnetic scattering field of a two dimensional rectangular Perfect Electric Conductor(PEC) structure using the 2-D FDTD method with Schur complement method as a domain decomposition method. Four domain decomposition and eight domain decomposition are applied for the analysis of the proposed structure. To validate the simulation results, the general 2-D FDTD algorithm for the total domain are applied to the same structure and the results show good agreement with the 2-D FDTD using the domain decomposition method.

Protein-Protein Interaction Prediction using Interaction Significance Matrix (상호작용 중요도 행렬을 이용한 단백질-단백질 상호작용 예측)

  • Jang, Woo-Hyuk;Jung, Suk-Hoon;Jung, Hwie-Sung;Hyun, Bo-Ra;Han, Dong-Soo
    • Journal of KIISE:Software and Applications
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    • v.36 no.10
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    • pp.851-860
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    • 2009
  • Recently, among the computational methods of protein-protein interaction prediction, vast amounts of domain based methods originated from domain-domain relation consideration have been developed. However, it is true that multi domains collaboration is avowedly ignored because of computational complexity. In this paper, we implemented a protein interaction prediction system based the Interaction Significance matrix, which quantified an influence of domain combination pair on a protein interaction. Unlike conventional domain combination methods, IS matrix contains weighted domain combinations and domain combination pair power, which mean possibilities of domain collaboration and being the main body on a protein interaction. About 63% of sensitivity and 94% of specificity were measured when we use interaction data from DIP, IntAct and Pfam-A as a domain database. In addition, prediction accuracy gradually increased by growth of learning set size, The prediction software and learning data are currently available on the web site.

Learning Domain Invariant Representation via Self-Rugularization (자기 정규화를 통한 도메인 불변 특징 학습)

  • Hyun, Jaeguk;Lee, ChanYong;Kim, Hoseong;Yoo, Hyunjung;Koh, Eunjin
    • Journal of the Korea Institute of Military Science and Technology
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    • v.24 no.4
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    • pp.382-391
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    • 2021
  • Unsupervised domain adaptation often gives impressive solutions to handle domain shift of data. Most of current approaches assume that unlabeled target data to train is abundant. This assumption is not always true in practices. To tackle this issue, we propose a general solution to solve the domain gap minimization problem without any target data. Our method consists of two regularization steps. The first step is a pixel regularization by arbitrary style transfer. Recently, some methods bring style transfer algorithms to domain adaptation and domain generalization process. They use style transfer algorithms to remove texture bias in source domain data. We also use style transfer algorithms for removing texture bias, but our method depends on neither domain adaptation nor domain generalization paradigm. The second regularization step is a feature regularization by feature alignment. Adding a feature alignment loss term to the model loss, the model learns domain invariant representation more efficiently. We evaluate our regularization methods from several experiments both on small dataset and large dataset. From the experiments, we show that our model can learn domain invariant representation as much as unsupervised domain adaptation methods.

ON THE SHAPE DERIVATIVE IN THE DOMAIN INCLUSION

  • Kim, Hongchul
    • Korean Journal of Mathematics
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    • v.10 no.1
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    • pp.75-87
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    • 2002
  • The shape derivative for the domain functional will be discussed in the situation of domain inclusion. Hadamard's shape structure is sought by using the material derivative in conjunction with the domain imbedding technique.

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