• Journal of the Korean Mathematical Society
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• v.51 no.6
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• pp.1209-1220
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• 2014

We prove global gradient estimates in weighted Orlicz spaces for weak solutions of nonlinear elliptic equations in divergence form over a bounded non-smooth domain as a generalization of Calder$\acute{o}$n-Zygmund theory. For each point and each small scale, the main assumptions are that nonlinearity is assumed to have a uniformly small mean oscillation and that the boundary of the domain is sufficiently flat.

• Bulletin of the Korean Mathematical Society
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• v.57 no.4
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• pp.1003-1031
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• 2020

We consider the following Dirichlet initial boundary value problem with a gradient absorption and a nonlocal source $$\frac{{\partial}u}{{\partial}t}-div({\mid}{\nabla}u{\mid}^{p-2}{\nabla}u)={\lambda}u^k{\displaystyle\smashmargin{2}{\int\nolimits_{\Omega}}}u^sdx-{\mu}u^l{\mid}{\nabla}u{\mid}^q$$ in a bounded domain Ω ⊂ ℝ^N, where p > 1, the parameters k, s, l, q, λ > 0 and µ ≥ 0. Firstly, we establish local existence for weak solutions; the aim of this part is to prove a crucial priori estimate on |∇u|. Then, we give appropriate conditions in order to have existence and uniqueness or nonexistence of a global solution in time. Finally, depending on the choices of the initial data, ranges of the coefficients and exponents and measure of the domain, we show that the non-negative global weak solution, when it exists, must extinct after a finite time.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.2
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• pp.77-85
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• 2010

Fingerprint image quality checking is one of the most important issues in on-line fingerprint recognition because the recognition performance is largely affected by the quality of fingerprint images. In the past, many related fingerprint quality checking methods have typically considered the local quality of fingerprint. However, It is necessary to estimate the global quality of fingerprint to judge whether the fingerprint can be used or not in on-line recognition systems. Therefore, in this paper, we propose both local and global-based methods to calculate the fingerprint quality. Local fingerprint quality checking algorithm considers both the condition of the input fingerprints and orientation estimation errors. The 2D gradients of the fingerprint images were first separated into two sets of 1D gradients. Then，the shapes of the PDFs(Probability Density Functions) of these gradients were measured in order to determine fingerprint quality. And global fingerprint quality checking method uses neural network to estimate the global fingerprint quality based on local quality values. We also analyze the matching performance using FVC2002 database. Experimental results showed that proposed quality check method has better matching performance than NFIQ(NIST Fingerprint Image Quality) method.

• Geomechanics and Engineering
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• v.37 no.4
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• pp.395-418
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• 2024

The epicentral region of earthquakes is typically where liquefaction-related damage takes place. To determine the maximum distance, such as maximum epicentral distance (R_e), maximum fault distance (R_f), or maximum hypocentral distance (R_h), at which an earthquake can inflict damage, given its magnitude, this study, using a recently updated global liquefaction database, multiple ML models are built to predict the limiting distances (R_e, R_f, or R_h) required for an earthquake of a given magnitude to cause damage. Four machine learning models LSTM (Long Short-Term Memory), BiLSTM (Bidirectional Long Short-Term Memory), CNN (Convolutional Neural Network), and XGB (Extreme Gradient Boosting) are developed using the Python programming language. All four proposed ML models performed better than empirical models for limiting distance assessment. Among these models, the XGB model outperformed all the models. In order to determine how well the suggested models can predict limiting distances, a number of statistical parameters have been studied. To compare the accuracy of the proposed models, rank analysis, error matrix, and Taylor diagram have been developed. The ML models proposed in this paper are more robust than other current models and may be used to assess the minimal energy of a liquefaction disaster caused by an earthquake or to estimate the maximum distance of a liquefied site provided an earthquake in rapid disaster mapping.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.7
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• pp.2027-2046
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• 2024

Reconfigurable Intelligent Surface (RIS) is an innovative technique to precisely control the phase of incident signals with the help of low-cost passive reflective elements. It shows excellent potential in the sixth generation of mobile communication systems, which not only extends wireless coverage but also boosts channel capacity. Considering that multipath propagation and a high number of antennas are involved in RIS in assisted mega multiple-input multiple-output (MIMO) systems, it suffers from severe channel fading and multipath effects, which in turn lead to signal instability and degradation of transmission performance. To overcome this obstacle, this essay suggests an improved gradient optimization algorithm to dynamically and optimally adjust the phase of the reflective elements to counteract channel fading and multipath effects as a strategy. In order to overcome the optimization problem of falling into local minima, this paper proposes an adaptive learning rate algorithm based on Adagrad improvement, which searches for the global optimal solution more efficiently and improves the robustness of the optimization algorithm. The suggested technique helps to enhance the estimate of channel efficiency of RIS-assisted large MIMO systems, according to simulation results.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.309-312
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• 1999

This paper proposed a novel method for pseudo-on-line scheme using look-up table based on the genetic algorithm The technique is an pseudo-on-line method that optimally estimate the parameters of FPID controller for systems with non-linearity using the genetic algorithm which does not use the gradient and finds the global optimum of an unconstraint optimization problem. The proposed controller is applied to speed control of 3-phase induction motor and its computer simulation is carried out. Simulation results show that the proposed method is more excellent then conventional FPID and PID controllers.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2386-2388
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• 2000

This paper proposes a novel method with pseudo-on-line scheme using look-up table based on the genetic algorithm. The technique is a pseudo-on-line method that optimally estimate the parameters of fuzzy PID(FPID) controller for systems with non-linearity using the genetic algorithm which does not use the gradient and finds the global optimum of an un-constraint optimization problem. The proposed controller(GFPID) is applied to speed control of 3-phase induction motor and its computer simulation is carried out. Simulation results show that the proposed method is more excellent than conventional FPID and PID controllers.

• Journal of Korea Multimedia Society
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• v.3 no.4
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• pp.356-364
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• 2000

Block based fast motion estimation algorithm use the fixed search pattern to reduce the search point, and are based on the assumption that the error in the mean absolute error space monotonically decreases to the global minimum. Therefore, in case of many local minima in a search region we are likely to find local minima instead of the global minimum and highly rely on the initial search points. This situation is evident in the motion boundary. In this paper we define the candidate regions within the search region using the motion information of the neighbor blocks and we propose the multiple local search method (MLSM) which search for the solution throughout the candidate regions to reduce the possibilities of isolation to the local minima. In the MLSM we mark the candidate region in the search point map and we avoid to search the candidate regions already visited to reduce the calculation. In the simulation results the proposed method shows more excellent results than that of other gradient based method especially in the search of motion boundary. Especially, in PSNR the proposed method obtains similar estimate accuracy with the significant reduction of search points to that of full search.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.4
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• pp.163-170
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• 2013

In general, images of outdoor scenes often contain degradation due to dust, water drop, haze, fog, smoke and so on, as a result they cause the contrast reduction and color fading. Haze removal is not easier problem due to the inherent ambiguity between the haze and the underlying scene. So, we propose a novel method to solve single scene dehazing problem using the region segmentation based on graph algorithm that has used a gradient value as a cost function. We segment the scene into different regions according to depth-related information and then estimate the global atmospheric light. The medium transmission can be directly estimated by the threshold function of graph-based segmentation algorithm. After estimating the medium transmission, we can restore the haze-free scene. We evaluated the degree of the visibility restoration between the proposed method and the existing methods by calculating the gradient of the edge between the restored scene and the original scene. Results on a variety of outdoor haze scene demonstrated the powerful haze removal and enhanced image quality of the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1159-1181
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• 2016

This study introduces an image-based 2D-to-3D conversion system that provides significant stereoscopic visual effects for humans. The linear and atmospheric perspective cues that compensate each other are employed to estimate depth information. Rather than retrieving a precise depth value for pixels from the depth cues, a direction angle of the image is estimated and then the depth gradient, in accordance with the direction angle, is integrated with superpixels to obtain the depth map. However, stereoscopic effects of synthesized views obtained from this depth map are limited and dissatisfy viewers. To obtain impressive visual effects, the viewer's main focus is considered, and thus salient object detection is performed to explore the significance region for visual attention. Then, the depth map is refined by locally modifying the depth values within the significance region. The refinement process not only maintains global depth consistency by correcting non-uniform depth values but also enhances the visual stereoscopic effect. Experimental results show that in subjective evaluation, the subjectively evaluated degree of satisfaction with the proposed method is approximately 7% greater than both existing commercial conversion software and state-of-the-art approach.