• Title/Summary/Keyword: $l_2$ Norm

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A Pansharpening Algorithm of KOMPSAT-3A Satellite Imagery by Using Dilated Residual Convolutional Neural Network (팽창된 잔차 합성곱신경망을 이용한 KOMPSAT-3A 위성영상의 융합 기법)

  • Choi, Hoseong;Seo, Doochun;Choi, Jaewan
    • Korean Journal of Remote Sensing
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    • v.36 no.5_2
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    • pp.961-973
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    • 2020
  • In this manuscript, a new pansharpening model based on Convolutional Neural Network (CNN) was developed. Dilated convolution, which is one of the representative convolution technologies in CNN, was applied to the model by making it deep and complex to improve the performance of the deep learning architecture. Based on the dilated convolution, the residual network is used to enhance the efficiency of training process. In addition, we consider the spatial correlation coefficient in the loss function with traditional L1 norm. We experimented with Dilated Residual Networks (DRNet), which is applied to the structure using only a panchromatic (PAN) image and using both a PAN and multispectral (MS) image. In the experiments using KOMPSAT-3A, DRNet using both a PAN and MS image tended to overfit the spectral characteristics, and DRNet using only a PAN image showed a spatial resolution improvement over existing CNN-based models.

Estimation of Shear-Wave Velocities of Layered Half-Space Using Full Waveform Inversion with Genetic Algorithm (유전 알고리즘을 활용한 완전파형역산 기법의 층상 반무한 지반 전단파 속도 추정)

  • Lee, Jin Ho;Lee, Se Hyeok
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.34 no.4
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    • pp.221-230
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    • 2021
  • This paper proposes full waveform inversion (FWI) for estimating the physical properties of a layered half-space. An FWI solution is obtained using a genetic algorithm (GA), which is a well-known global optimization approach. The dynamic responses of a layered half-space subjected to a harmonic vertical disk load are measured and compared with those calculated using the estimated physical properties. The responses are calculated using the thin-layer method, which is accurate and efficient for layered media. Subsequently, a numerical model is constructed for a layered half-space using mid-point integrated finite elements and perfectly matched discrete layers. An objective function of the global optimization problem is defined as the L2-norm of the difference between the observed and estimated responses. A GA is used to minimize the objective function and obtain a solution for the FWI. The accuracy of the proposed approach is applied to various problems involving layered half-spaces. The results verify that the proposed FWI based on a GA is suitable for estimating the material properties of a layered half-space, even when the measured responses include measurement noise.

Factors Influencing Dementia Caregivers' Health-related Quality of Life (치매노인 주 부양자의 건강관련 삶의 질 예측인자)

  • Kim, Jung-Soon;Kim, Myoung-Soo;Kim, Soo-Ok;Yoo, Youn-Ja;Won, Dae-Young
    • Research in Community and Public Health Nursing
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    • v.18 no.2
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    • pp.232-241
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    • 2007
  • Purpose: The aim of this study was to explore the health-related quality of life of caregivers for demented elders. Method: The subjects of this study were 170 pairs of demented elders and their caregivers. Socio-demographic characteristics of the demented elders and the caregivers, Barthel index and SF-36 were used in this study. Data analysis procedure included t-test, ANOVA, Pearson correlation coefficient, and hierarchical multiple regression. Results: The score of overall health-related quality of life (HRQoL) was 288.62 in norm-based scoring. The major factors that affect HRQoL of the demented elders' caregivers were burden, the age of the caregiver, ADL and gender of the demented elder, and these factors explained 34.5% of HRQoL. Conclusion: The factors significantly affecting the caregivers' HRQoL were burden, the age of the caregiver and ADL. The effective social support system should be considered in respective nursing interventions to decrease the level of burden and to increase HRQoL in demented elders' caregivers. Further studies and efforts will be needed to investigate preceding factors of burden and HRQoL.

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The Lifespan of Social Hub In Social Networking Sites: The Role of Reciprocity, Local Dominance and Social Interaction

  • Han, Sangman;Magee, Christopher L.;Kim, Yunsik
    • Asia Marketing Journal
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    • v.17 no.1
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    • pp.69-95
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    • 2015
  • This paper examines a highly used social networking site (SNS) by studying the behavior of more than 11 million members over a 20 month period. The importance of the most highly active members to the overall network is demonstrated by the significant fraction of total visits by extremely active members in a given period but such members have surprisingly short lifespans (an average of only 2.5 months) as social hubs. We form and test a number of hypotheses concerning these social hubs and the determinants of their lifespan. We find that the speed of achieving social hub status increases the lifespan of a social hub. The norm of reciprocity is strongly confirmed to be present in the social hub population as visits are reciprocated. We also find that increasing local dominance in terms of activities over neighboring agents leads to a longer lifespan of a social hub. Contrary to expectations, local clustering in the vicinity of social hubs is smaller (rather than larger) than overall clustering. We discuss managerial implications in the paper.

Robust Restoration of Barcode Signals (바코드 신호의 강인한 복원)

  • Lee, Han-A;Lee, Jeong-Tae
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.56 no.10
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    • pp.1859-1864
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    • 2007
  • Existing barcode signal restoration algorithms are not robust to unmodeled outliers that may exist in scanned barcode images due to scratches, dirts, etc. In this paper, we describe a robust barcode signal restoration algorithm that uses the hybrid $L_1-L_2$ norm as a similarity measure. To optimze the similarity measure, we propose a modified iterative reweighted least squares algorithm based on the one step minimization of a quadratic surrogate function. In the simulations and experiments with barcode images, the proposed method showed better robustness than the conventional MSE based method. In addition, the proposed method converged quickly during optimization process.

Face Recognition by Using Factorial Face Code of FP-ICA (FP-ICA의 인수부호에 의한 얼굴인식)

  • Cho, Yong-Hyun;Hong, Seong-Jun
    • Proceedings of the Korea Information Processing Society Conference
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    • 2005.05a
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    • pp.797-800
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    • 2005
  • 본 논문에서는 고정점 알고리즘의 독립성분분석을 이용하여 얼굴영상의 인수부호를 찾아 얼굴을 인식하는 기법을 제안하였다. 여기서 고정점 알고리즘은 뉴우턴법에 기초한 것으로 빠른 특징추출을 위함이고, 독립성분분석의 이용은 통계적으로 독립인 계수로 구성된 인수부호를 효과적으로 추출하기 위함이다. 제안된 기법을 Yale 얼굴영상 데이터베이스로부터 선택된 20개의 $324{\ast}243$ 픽셀의 영상을 대상으로 시뮬레이션한 결과, 기저영상의 개수에 따른 압축성능과 L1- 및 L2-norm의 거리척도에 따른 분류에서 우수한 인식성능이 있음을 확인할 수 있었다.

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FUZZY STABILITY OF AN ADDITIVE-QUADRATIC FUNCTIONAL EQUATION WITH THE FIXED POINT ALTERNATIVE

  • SEO, JEONG PIL;LEE, SUNGJIN;SAADATI, REZA
    • The Pure and Applied Mathematics
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    • v.22 no.3
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    • pp.285-298
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    • 2015
  • In [41], Th.M. Rassias proved that the norm defined over a real vector space V is induced by an inner product if and only if for a fixed positive integer l holds for all x1, ⋯ , x2l ∈ V . For the above equality, we can define the following functional equation Using the fixed point method, we prove the Hyers-Ulam stability of the functional equation (0.1) in fuzzy Banach spaces.

Input-Output Gains of Linear Periodic Time-Varying Systems with Applications to Multirate Signal Processing (다중비 신호처리에 적용한 선형 주기적 시변 시스템의 입출력 이득)

  • 이상철;박계원
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.4 no.5
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    • pp.963-969
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    • 2000
  • In this paper, we define two input-output gains of linear periodic time-varying systems. One is the ratio of output with worst-case l2-norm over all inputs with unit 12-norm. It denotes G($\iota_2,\iota_2$.The other is the ratio of output with worst-case RMS value over all inputs with unit RMS value. It denotes G(RMS, RMS) .It is fact that these two gains are equivalent for linear time-invariant system. In this paper, we prove these two gains are also equivalent for linear periodic time-varying system. In addition, the relationship between two method of obtaining the generalized frequency responses for linear periodic time-varying system is derived. Finally, we apply the defined input-output gains to M-channel filter-bank which is multi-rate signal Processing system, used to speech coding. In the filter-bank, generally, aliasing distortion, magnitude distortion, and phase distortion are present. It is shown that these are kept small if the filter-bank is designed by a method that optimizes the gain G($\iota_2,\iota_2$ of an error system.

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Adaptive Hyperspectral Image Classification Method Based on Spectral Scale Optimization

  • Zhou, Bing;Bingxuan, Li;He, Xuan;Liu, Hexiong
    • Current Optics and Photonics
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    • v.5 no.3
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    • pp.270-277
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    • 2021
  • The adaptive sparse representation (ASR) can effectively combine the structure information of a sample dictionary and the sparsity of coding coefficients. This algorithm can effectively consider the correlation between training samples and convert between sparse representation-based classifier (SRC) and collaborative representation classification (CRC) under different training samples. Unlike SRC and CRC which use fixed norm constraints, ASR can adaptively adjust the constraints based on the correlation between different training samples, seeking a balance between l1 and l2 norm, greatly strengthening the robustness and adaptability of the classification algorithm. The correlation coefficients (CC) can better identify the pixels with strong correlation. Therefore, this article proposes a hyperspectral image classification method called correlation coefficients and adaptive sparse representation (CCASR), based on ASR and CC. This method is divided into three steps. In the first step, we determine the pixel to be measured and calculate the CC value between the pixel to be tested and various training samples. Then we represent the pixel using ASR and calculate the reconstruction error corresponding to each category. Finally, the target pixels are classified according to the reconstruction error and the CC value. In this article, a new hyperspectral image classification method is proposed by fusing CC and ASR. The method in this paper is verified through two sets of experimental data. In the hyperspectral image (Indian Pines), the overall accuracy of CCASR has reached 0.9596. In the hyperspectral images taken by HIS-300, the classification results show that the classification accuracy of the proposed method achieves 0.9354, which is better than other commonly used methods.

SMALL DATA SCATTERING OF HARTREE TYPE FRACTIONAL SCHRÖDINGER EQUATIONS IN DIMENSION 2 AND 3

  • Cho, Yonggeun;Ozawa, Tohru
    • Journal of the Korean Mathematical Society
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    • v.55 no.2
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    • pp.373-390
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    • 2018
  • In this paper we study the small-data scattering of the d dimensional fractional $Schr{\ddot{o}}dinger$ equations with d = 2, 3, $L{\acute{e}}vy$ index 1 < ${\alpha}$ < 2 and Hartree type nonlinearity $F(u)={\mu}({\mid}x{\mid}^{-{\gamma}}{\ast}{\mid}u{\mid}^2)u$ with max(${\alpha}$, ${\frac{2d}{2d-1}}$) < ${\gamma}{\leq}2$, ${\gamma}$ < d. This equation is scaling-critical in ${\dot{H}}^{s_c}$, $s_c={\frac{{\gamma}-{\alpha}}{2}}$. We show that the solution scatters in $H^{s,1}$ for any s > $s_c$, where $H^{s,1}$ is a space of Sobolev type taking in angular regularity with norm defined by ${\parallel}{\varphi}{\parallel}_{H^{s,1}}={\parallel}{\varphi}{\parallel}_{H^s}+{\parallel}{\nabla}_{{\mathbb{S}}{\varphi}}{\parallel}_{H^s}$. For this purpose we use the recently developed Strichartz estimate which is $L^2$-averaged on the unit sphere ${\mathbb{S}}^{d-1}$ and utilize $U^p-V^p$ space argument.