• Journal of Powder Materials
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• v.11 no.1
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• pp.8-15
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• 2004

The basic concept of functionally gradient materials (FGM) is to fabricate materials type having possibilities of applications in various fields by changing their intrinsic properties with continuous gradient. The present communication has reviewed the developments and applications of various FGMs designed for improved thermo-mechanical properties, in which the thermal protective and wear resistant materials are especially focused. Effects of thermo-mechanical properties and limits of FGMs designed for high temperature applications were mainly understood in terms of residual stress evolved from the design and fabrication. In addition, FGMs applied in structural parts were also introduced and discussed in terms of typical fabrication method for FGMs.

• Geophysics and Geophysical Exploration
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• v.16 no.2
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• pp.97-105
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• 2013

Nuclear magnetic resonance (NMR) logging has become an important technique for formation evaluation, detecting interaction signals between H protons and applied magnetic fields. Measured decay signals called relaxation, contain important information about density of H protons and different decay rate due to its fluid type in the sensitive area. Thus, petrophysical information such as porosity, permeability and wettability can be estimated through the interpretation of the decay signals. Many researches on random walk simulation have been published, since a simulation method based on random walk for solving exponential decays was adapted in the early of 1950. This study first makes a review on NMR simulation researches, explains two most important methods: simulation with or without considering magnetic field gradient. Lastly, the study makes a comparison between NMR simulation responses with and without magnetic field gradient to show the importance to consider magnetic gradient to analyze the effects of magnetic gradients on NMR responses.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.87-92
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• 2021

Bias, variance, error and learning are important factors for performance in modeling a big data based recommendation system. The recommendation model in this system must reduce complexity while maintaining the explanatory diagram. In addition, the sparsity of the dataset and the prediction of the system are more likely to be inversely proportional to each other. Therefore, a product recommendation model has been proposed through learning the similarity between products by using a factorization method of the sparsity of the dataset. In this paper, the generalization ability of the model is improved by applying the max-norm regularization as an optimization method for the loss function of this model. The solution is to apply a stochastic projection gradient descent method that projects a gradient. The sparser data became, it was confirmed that the propsed regularization method was relatively effective compared to the existing method through lots of experiment.

• Journal of Korea Society of Industrial Information Systems
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• v.13 no.1
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• pp.57-67
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• 2008

In this paper, we present an adaptive block matching motion estimation using optical flow. In the proposed algorithm, we calculate the temporal and spatial gradient value for each pixel value from tile differential filter, and estimate the optical flow which is used to decide the location and the size of the search region from the gradient values by least square optical flow algorithm. In particular, the proposed algorithm showed a excellent performance with fast and complex motion sequences. From the computer simulation for various motion characteristic sequences. The proposed algorithm shows a significant enhancement of PSNR over previous blocking matching algorithms.

• Smart Media Journal
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• v.5 no.1
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• pp.88-94
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• 2016

In this paper, we proposed a new object tracking algorithm based on sparse representation to handle the drifting problem. In APG-L1(accelerated proximal gradient) tracking, the sparse representation is applied to model the appearance of object using linear combination of target templates and trivial templates with proper coefficients. Also, the particle filter based on affine transformation matrix is applied to find the location of object and APG method is used to minimize the l1-norm of sparse representation. In this paper, we make use of the trivial template coefficients actively to block the drifting problem. We experiment the various videos with diverse challenges and the result shows better performance than others.

• Journal of the Korea institute for structural maintenance and inspection
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• v.7 no.3
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• pp.175-181
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• 2003

In this reseach, a seepage test is carried out for three kinds of soil using a upward seepage equipment. Reliability about the existing method of pipining investigation were verified making an estimate of the critical velocity, the critical hydraulic gradient, and hydraulic conductivity and so on. Also, sensitive analyses were carried out using Plaxis that is FEM Program about design factors of scour. The height of core had a big infulence on the hydraulic gradient of the embankment's lower part in the result of sensitive anaylsis. Also, second only to the height of core, and the slope of embankment, the width of crest had influence on scour. However, the change of hydraulic gradient in the effluent gateway had a little influence on the crest width of core. Using these results of sensitive analysis on designing, hydraulic gradient in the effluence gateway turned out to be reducing by altering design factors that change of sensitiveness is big, in case of the hydraulic gradient bigger than the standard hydraulic gradient.

• Geophysics and Geophysical Exploration
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• v.25 no.2
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• pp.85-92
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• 2022

An elongated object in one direction can be approximated as a line segment. Here, the closed-form expressions of a line segment's vector magnetic and magnetic gradient tensor are required to interpret responses by a line segment. Therefore, the analytical expressions of the vector magnetic and magnetic gradient tensor are derived. The vector magnetic is converted from the existing gravity gradient tensor using Poisson's relation where the gravity gradient tensor caused by a line segment can be transformed into a vector magnetic. Then, the magnetic gradient tensor is derived by differentiating the vector magnetic with respect to each axis in the Cartesian coordinate system. The synthetic total magnetic data simulated by an iron pile on boreholes are inverted by a nonlinear inversion process so that the physical parameters of the iron pile, including the beginning point, the length, orientation, and magnetization vector are successfully estimated.

• Journal of Broadcast Engineering
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• v.15 no.4
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• pp.474-486
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• 2010

In this paper, we propose a new method for detection moving object contour using spatial and temporal edge. In general, contour pixels of the moving object are likely present around pixels with high gradient value along the time axis and the spatial axis. Therefore, we can detect the contour of the moving objects by finding pixels which have high gradient value in the time axis and spatial axis. In this paper, we introduce a new computation method, termed as temporal edge, to compute an gradient value along the time axis for any pixel on an image. The temporal edge can be computed using two input gray images at time t and t-2 using the Sobel operator. Temporal edge is utilized to detect a candidate region of the moving object contour and then the detected candidate region is used to extract spatial edge information. The final contour of the moving object is detected using the combination of these two edge information, which are temporal edge and spatial edge, and then the post processing such as a morphological operation and a background edge removing procedure are applied to remove noise regions. The complexity of the proposed method is very low because it dose not use any background scene and high complex operation, therefore it can be applied to real-time applications. Experimental results show that the proposed method outperforms the conventional contour extraction methods in term of processing effort and a ghost effect which is occurred in the case of entropy method.

• 전자공학회논문지 IE
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• v.47 no.2
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• pp.27-31
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• 2010

In this paper, a predictor switching algorithm for lossless compression is proposed. It uses adaptively one of two predictors using errors obtained by MED(median edge detector) and GAP(gradient adaptive prediction). The reduced error is measured by existing entropy method. Experimental results show that the proposed algorithm can compress higher than existing predictive methods.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.234-237
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• 2005

강화학습을 위한 많은 방법 중 정책 반복을 이용한 actor-critic 학습 방법이 많은 적용 사례를 통해서 그 가능성을 인정받고 있다. Actor-critic 학습 방법은 제어입력 선택 전략을 위한 actor 학습과 가치 함수 근사를 위한 critic 학습이 필요하다. 본 논문은 critic의 학습을 위해 빠른 수렴성을 보장하는 RLS(recursive least square)를 사용하고, actor의 학습을 위해 정책의 기울기(policy gradient)를 이용하는 새로운 알고리즘을 제안하였다. 그리고 이를 실험적으로 확인하여 제안한 논문의 성능을 확인해 보았다.