• The Korean Journal of Applied Statistics
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• v.19 no.2
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• pp.319-330
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• 2006

A signal in real world usually composes of multiple signals having different scales of frequencies. For example sun-spot data is fluctuated over 11 year and 85 year. Economic data is supposed to be compound of seasonal component, cyclic component and long-term trend. Decomposition of the signal is one of the main topics in time series analysis. However when the signal is subject to nonstationarity, traditional time series analysis such as spectral analysis is not suitable. Huang et. at(1998) proposed data-adaptive method called empirical mode decomposition (EMD) . Due to its robustness to nonstationarity, EMD has been applied to various fields. Huang et. at, however, have not considered denoising when data is contaminated by error. In this paper we propose efficient denoising method utilizing cross-validation.

• Journal of Korea Water Resources Association
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• v.34 no.1
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• pp.19-30
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• 2001

A laterally averaged 2-dimensional hydrodynamic model is newly developed. The coordinate system is first transformed to minimize the effects of irregularity of bottom and surface. The advection terms of the governing equations are then discretized by an upwind scheme. By employing an explicit scheme for longitudinal direction and an implicit scheme for vertical direction, the model is free from restriction of temporal step size caused by a relatively small grid ratio. To demonstrate the applicability of the model, calculated time histories of free surface displacements and distributions of velocity and salinity are compared with the field measurements of the Keum River Estuary before construction of the estuary dam. A reasonable agreement is observed between them.

• Journal of the Korea Computer Graphics Society
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• v.17 no.2
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• pp.17-26
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• 2011

This paper presents an interactive progressive image transmission method, which enables a remote user to interactively select and transmit preferred regions from an index image. Our enhanced quadtree decomposition using PSNR-based rules and new implicit quadtree coding provide better rate-distortion performance than previous quadtree coders as well as leading bit plane methods. An adaptive traversal of child nodes is introduced for better visual display of restored images. Depth-first traversal combined with breadth-first traversal of the quadtree to accomplish interactive transmission as presented, results in a method that provides competitive performance at a low level of computational complexity. Moreover, our decoding requires only simple arithmetic which is enabling our method to be used for real-time mobile applications.

• Journal of the Korea Computer Graphics Society
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• v.4 no.1
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• pp.79-88
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• 1998

Till now there are several rendering models for water and simulating other fluids and their dynamics. Especially in order to generate a curved surface of flexible objects such as liquid and snow, the implicit metaball formulation is widely used in favor of its simplicity and flexibility. This paper proposes one excellent method for generating water droplets, which would be deformed in gravitation field. In previous works, a water droplet was simply represented by approximated curved surfaces of a symmetric metaball. Thus the final result of the rendered water droplet was far from a realistic droplet, because they do not consider the gravitational effect in droplets. We propose a new metaball model for rendering water droplets placed on an arbitrary surface considering the gravitation and friction between droplet and plate. Our new metaball model uses a new vector field isosurface function to control the basic scalar metaball with respect to the norm of gravitational force. In several experiments, we could render a photo-realistic water droplets with natural-looking shadows by applying ray-tracing.

• Journal of KIISE:Information Networking
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• v.35 no.1
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• pp.34-45
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• 2008

In dynamic wireless sensor networks where sources and sinks are moving or are created/died, control overheads for route establishment are increased and thus become one of the major factors for energy consumption. This study introduces prefetching and pruning for Directed Diffusion to remove redundant control messages. Prefetching collects path information for each event with "AnyEvent" in advance and gives quick responses without further flooding of requests. Pruning accumulates history information from previous requests and replies, and then stops forwarding a request towards where the event does not exist. Simulation results with ns show that it is possible to build implicit and soft infrastructures within a Directed Diffusion system through these active collection and passive accumulation and they improve energy consumption more as control overhead goes higher.

• Journal of KIISE
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• v.45 no.2
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• pp.165-174
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• 2018

An online community is a virtual group whose members share their interests and hobbies anonymously with nicknames unlike Social Network Services. However, there are malicious user problems such as users who write offensive contents and there may exist data fragmentation problems in which the data of the same user exists in different nicknames. In addition, nicknames are frequently changed in the online community, so it is difficult to identify them. Therefore, in this paper, to remedy these problems we propose a behavior pattern feature vectors for users considering online community characteristics, propose a new implicit behavior pattern called relationship pattern, and identify the nickname of the same user based on Random Forest classifier. Also, Experimental results with the collected real world online community data demonstrate that the proposed behavior pattern and classifier can identify the same users at a meaningful level.

• Journal of the Korea Computer Graphics Society
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• v.26 no.1
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• pp.7-15
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• 2020

In the process of visualizing a point set representing a smooth manifold surface, global illumination techniques can be used to render a realistic scene with various effects of lighting. Thanks to the continuous demand for ray tracing and the development of graphics hardware, dedicated GPUs and programmable pipeline for ray tracing have been introduced in recent years. In this paper, real-time global illumination rendering is studied for a point-set model using ray-tracing GPUs. We apply the moving least-squares (MLS) method to approximate the point set to a smooth implicit surface and render it using global illumination by performing massive ray-intersection tests with the surface and generating shading effects at the intersection point. As a result, a complicated point-set scene consisting of more than 0.5M points can be generated in real-time.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.7
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• pp.1-8
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• 2005

For study on the unsteady wall interference effect, flows around a circular cylinder in closed test-section wind tunnels have been numerically investigated by solving compressible Navier-Stokes equations. The numerical scheme is based on a node-based finite-volume method with the Roe's flux-difference splitting and an implicit time-integration method coupled with dual time-step sub-iteration. The computed results showed that the unsteady pressure gradient over the cylinder is enhanced by the wall interference, and as a result the fluctuations of lift and drag are augmented. The drag is further increased because of the lower base pressure. The vortex shedding frequency is also increased by the wall interference. The pressure on the test section wall shows the harmonics having the shedding frequency contained in the wall effect.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.5
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• pp.685-690
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• 2021

In this paper, we propose a deep learning-based transmit power control scheme to maximize the sum-rates while satisfying the minimum data-rate in downlink non-orthogonal multiple access (NOMA) systems. In downlink NOMA, we consider the co-channel interference that occurs from a base station other than the cell where the user is located, and the user feeds back the signal-to-interference plus noise power ratio (SINR) information instead of channel state information to reduce system feedback overhead. Therefore, the base station controls transmit power using only SINR information. The use of implicit SINR information has the advantage of decreasing the information dimension, but has disadvantage of reducing the data-rate. In this paper, we resolve this problem with deep learning-based training methods and show that the performance of training can be improved if the dimension of deep learning inputs is effectively reduced. Through simulation, we verify that the proposed deep learning-based power control scheme improves the sum-rate while satisfying the minimum data-rate.

• Journal of The Korean Association of Information Education
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• v.20 no.3
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• pp.293-302
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• 2016

It is the latest fashion of interesting with software education in public school environment and also consider as high priority issue of curriculum for college freshman with programming 101 courses. The block-based programming tool is used widely for the beginner and provides several positive features compare than text-based programming language tools. To measure quality of programming code elaborately which is based script language, it is need to very tough manual process. As a result the previously research related with evaluation of block-based script code has been focused very simple methods in which normalize the number of blocks used which is related with programming concept. In such cases in this, it is difficult to measure structural vulnerability of script code and implicit programming concept which does not expose. In this research, the framework is proposed which enable to measure and evaluate quality of code script of block-based programming tools and also provides method to find of vulnerability of script code. In this framework, the quality metrics is constructed to structuralize implicit programming concept and then developed the quality measure and vulnerability model of script to improve level of programming. Consequently, the proposed methods enable to check of level of programming and predict the heuristic target level.