• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.4
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• pp.91-98
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• 2012

This paper implements 2X2 MIMO Long Term Evolution (LTE) base station using Software defined radio (SDR) technology. The implemented base station system processes baseband signals on a Graphics Processor Unit(GPU). GPU is a high-speed parallel processor which provides very important advantage of using a very powerful C-based programming environment that is Compute Unified Device Architecture (CUDA). The implemented software-based base station system processes baseband signals through GPU. It utilizes USRP2 as its RF transceiver. In order to guarantee a real-time processing of LTE baseband signals, we have adopted well-known signal processing algorithms such as frame synchronization algorithms, ML detection, etc. using GPU operating in parallel processing.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2003.04a
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• pp.180-183
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• 2003

Recently, the pollution of soil and groundwater becomes a serious social problem, and geophysical exploration methods have been introduced as a remedial investigation method of subsurface. Digital technologies such as personal computer have revolutionized our ability to acquire large volumes of data in a short term, and to produce more reliable results for subsurface image. Also, color graphics easily visualizes the survey results in a more understandable manner, and it is widely used for not only characterizing the contaminated subsurface but also monitoring contaminant and remedial process. In this paper, electrical resistivity survey were carried out In order to understand characteristics of waste landfills, and the applicability of geophysical prospecting to site assessment of waste landfill was also tested. According to the result, electrical resistivity survey were effective in estimating distribution of the leachate plume.

• Journal of the Korean Chemical Society
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• v.62 no.2
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• pp.99-105
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• 2018

In this paper, we present fortified instructional methods that contributed in improving students' interest toward the expository organic chemistry laboratory course. Reformed TA (Teaching assistant) training and allocation method, a thorough course orientation session, text-light/graphics-heavy results PPT reports, and journal article templated-term papers have improved students' satisfaction in the organic chemistry laboratory course. These methods could be implemented while maintaining the traditional organic chemistry laboratory instruction styles and hence could be broadly applicable.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2444-2463
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• 2020

Significant detection of video can more rationally allocate computing resources and reduce the amount of computation to improve accuracy. Deep learning can extract the edge features of the image, providing technical support for video saliency. This paper proposes a new detection method. We combine the Convolutional Neural Network (CNN) and the Deep Bidirectional LSTM Network (DB-LSTM) to learn the spatio-temporal features by exploring the object motion information and object motion information to generate video. A continuous frame of significant images. We also analyzed the sample database and found that human attention and significant conversion are time-dependent, so we also considered the significance detection of video cross-frame. Finally, experiments show that our method is superior to other advanced methods.

• Journal of the Korea Computer Graphics Society
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• v.22 no.3
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• pp.63-73
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• 2016

Animation contents are gradually growing every year, but production period and budget for making one animation contents is insufficient as of now. In particular, in case of animation series that are broadcasted on television, many episodes should be made within a short period of production term. Hence, production pipeline of full three-dimensional animation is frequently chosen in this case. However, another problem emerges as the full three-dimensional animation also requires a lot of time for making high-quality background and for rendering. Composed animation is a production pipeline that attempts to solve such problem. It is a pipeline of producing animation by composing computer graphic (CG) character and real background. It requires relatively small number of human resources compared to the full three-dimensional animation pipeline. Hence, it has an advantage in that natural-looking image can be produced under efficient structure and time for rendering can also be reduced. This paper proposes an efficient process of producing composed animation by using miniature set and three-dimensional computer graphic.

• Journal of the Korea Computer Graphics Society
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• v.17 no.4
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• pp.31-40
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• 2011

Projector-based visual systems are widely used for VR and experience display applications. But the illumination irregularity on the screen surface due to the screen material and its light reflection properties sometimes deteriorates the user experience. This phenomenon is particularly troublesome when the participants of the head tracking VR system such as CAVE or the motion generation experience system continually move around the system. One of reason to illumination irregularity is projector-screen specular reflection component to participant's eye's position and it's analysis needs high computation complexity. Similar to calculate specular lighting term using GPU's programmable shader, Our research adjusts every pixel's brightness in runtime with given 3D screen space model to reduce illumination irregularity. For doing that, Angle-based brightness compensate function are considered for specific screen installation and modified it for GPU-friendly compute and access. Two aspects are implemented, One is function access transformation from angular form to product and the other is piecewise linear interpolate approximation.

• The Journal of the Korea Contents Association
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• v.5 no.5
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• pp.115-123
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• 2005

Game industry will be one of the fastest developed industries in the 21st century. It is the outcome derived from the development of hardware such as the accumulated technology and computer in the 20th century. The development of computer graphics and hardware technique has let games have more realistic expression. The reality shown in games has influences over the movement of 3-dimensional game character as well as its background. The animation of character has been influenced by animator's level of skill, but it was problematic to have unnatural movement and long-term production time. In this regard, this study will compare the most widely used animation techniques such as Key-Frame method and Motion-Capture method each other and try to figure out which one is the most appropriate and effective method in 3 dimensional game character animation.

• Journal of the Korea Computer Graphics Society
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• v.29 no.4
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• pp.7-16
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• 2023

For decades, creating a desired locomotive motion in a goal-oriented manner has been a challenge in character animation. Data-driven methods using generative models have demonstrated efficient ways of predicting long sequences of motions without the need for explicit conditioning. While these methods produce high-quality long-term motions, they can be limited when it comes to synthesizing motion for challenging novel scenarios, such as punching a random target. A state-of-the-art solution to overcome this limitation is by using a GAN Discriminator to imitate motion data clips and incorporating reinforcement learning to compose goal-oriented motions. In this paper, our research aims to create characters performing combat sports such as boxing, using a novel reward design in conjunction with existing GAN-based approaches. We experimentally demonstrate that both the Adversarial Motion Prior [3] and Adversarial Skill Embeddings [4] methods are capable of generating viable motions for a character punching a random target, even in the absence of mocap data that specifically captures the transition between punching and locomotion. Also, with a single learned policy, multiple task controllers can be constructed through the TimeChamber framework.

• Journal of the Korea Computer Graphics Society
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• v.23 no.3
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• pp.65-75
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• 2017

As a 360-degree image carries information of all directions, it often has too much information. Moreover, in order to investigate a 360-degree image on a 2D display, a user has to either click and drag the image with a mouse, or project it to a 2D panorama image, which inevitably introduces severe distortions. In consequence, investigating a 360-degree image and finding an object of interest in such a 360-degree image could be a tedious task. To resolve this issue, this paper proposes a method to find a region of interest and produces a 2D naturally looking image from a given 360-degree image that best matches a description given by a user in a natural language sentence. Our method also considers photo composition so that the resulting image is aesthetically pleasing. Our method first converts a 360-degree image to a 2D cubemap. As objects in a 360-degree image may appear distorted or split into multiple pieces in a typical cubemap, leading to failure of detection of such objects, we introduce a modified cubemap. Then our method applies a Long Short Term Memory (LSTM) network based object detection method to find a region of interest with a given natural language sentence. Finally, our method produces an image that contains the detected region, and also has aesthetically pleasing composition.

• The KIPS Transactions:PartA
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• v.14A no.4
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• pp.191-196
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• 2007

In the field of computer graphics, Navier-Stokes equations would be used for realistic simulations of smokes and currents. However, implementations derived from these equations are hard to achieve for real-time simulations, mainly due to its massive and complex calculations. Thus, there have been various attempts to approximate these equations for real-time simulation of smokes and others. When the advection terms of the equations are approximated by the Semi-Lagrange methods, the fluid density can be rapidly reduced and small-scale vorticity phenomena are easy to be missed, mainly due to the numerical losses over time. In this paper, we propose an improved numerical method to approximately calculate the advection terms, and thus eliminate these problems. To calculate the advection terms, our method starts to set critical regions around the target grid points. Then, among the grid points in a specific critical region, we search for a grid point which will be advected to the target grid point, and use the velocity of this grid point as its advection vector. This method would reduce the numerical losses in the calculation of densities and vorticity phenomena, and finally can implement more realistic smoke simulations. We also improve the overall efficiency of vector calculations and related operations through GPU-based implementation techniques, and thus finally achieve the real-time simulation.