• The Journal of the Korea Contents Association
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• v.12 no.8
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• pp.29-36
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• 2012

In CCPM Technique, as the buffer size calculation method, the Cut and Paste(C&P) method and the Root Square Error (RSE) method for all tasks carried out the same treatment, without considering the actual situation and characteristics of the task, the lack of reasonable judgment, is too simple and hasty. In this paper, taking into account the limitations of existing methods, a new method of buffer sizing method based on statistical analysis was introduced. It makes statistical analysis for the relationship between each worker and a variety of tasks, and use the information to predict the next task time. In order to verify the effectiveness of the new method, according to different task difficulty and the number of tasks set up the project. Use C&P, RSE method and new methods to predict the time of the project. Through Monte Carlo Simulation to simulate the project time, a comparison of three methods of performance. The results show that the new method can achieve the managers expect the probability of completion, and for those tasks can be completed ahead of schedule, the new method can save project time.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.8
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• pp.45-52
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• 2013

Coordinated Multi-Point (CoMP) is considered as a technology in the 3rd Generation Partnership Project(3GPP) Long Term Evolution-Advanced (LTE-A) system. In this paper, we design and analyze the performance of the Coordinated Beamforming (CB) technique, which is one major category of CoMP. We perform Monte Carlo simulations with a Heterogeneous Network (HetNet) in LTE-A, and confirm the performance through a graph of the Cumulative Distribution Function (CDF). From the simulation results, we show significant performance gain with the CoMP technique, and better performance when we apply various schemes of scheduling and precoding.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.4
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• pp.394-400
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• 2018

A heterogenous network is the one of key technologies for 5G, where one cell is divided into small cells in order to extend coverage and support high data rates. Divided cells aggravates the intercell interference problem as the cell edge increases. In order to avoid the intercell interference, it is the best to allocate the different spectrum for each cells. However, it also decreases the spectral efficiency. Therefore, the trade-off between the spectral efficiency gain and the signal quality loss by the interference should be considered for an efficient spectrum sharing in the heterogenous network. The adaptive modulation is the method to change the transmitted bit according to the channel quality, which is adopted as the standard in the most practical communication systems. It should be considered to applied the performance analysis into the practical systems. In this paper, the overall cell data rates is analyzed for the heterogenous network under the adaptive modulation. The Monte Carlo simulation results verify the correctness of the analysis.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.6
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• pp.821-826
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• 2013

When the values of design variables change, mode switching can often occur. If the mode of interest is not tracked, the frequencies and modes for design optimization may be miscalculated owing to modes that differ from the intended ones. Thus, mode tracking must be employed to identify the frequencies and modes of interest whenever the values of design variables change during optimization. Furthermore, reliability-based design optimization (RBDO) must be performed for design problems with design variables containing uncertainty. In this research, we perform RBDO considering the mode tracking of a compressive coil spring, i.e., a component of the joint spring that supports a compressor, with design variables containing uncertainty by using only kriging metamodels based on multiple responses approach (MRA) without existing mode tracking methods. The reliability analyses for RBDO are employed using kriging metamodel-based Monte Carlo simulation.

• Journal of the Society of Naval Architects of Korea
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• v.33 no.1
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• pp.98-108
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• 1996

In the reliability analysis of general structures, the limit state equations are implicit and cannot be described in closed form. Thus, sampling methods such as the Crude Monte-Carlo simulation, and probabilistic FEM are often used, but these methods are not so effective in view of computational cost, because a number of structural analysis are required and the derivatives must be calculated for probabilistic FEM. Alternatively the response surface approach, which approximates the limit state surface by using several results of structural analysis in the region adjacent to MPFP, could be applied effectively. In this paper, the central composite design, Bucher-Bourgund method and the approximation method using artificial neural network are studied for the calculation of probability of failure by the response surface method. Through the example comparisons, it is found that Bucher-Bourgund method is very effective and Neural network method for the reliability analysis is comparable with other methods. Specially, the central composite design method is found to be rational and useful in terms of mathematical consistency and accuracy.

• Journal of Korea Game Society
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• v.7 no.2
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• pp.21-32
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• 2007

It is significant to simulate scattering of light within media for realistic image synthesis; however, this requires costly computation. This paper introduces a practical image-space approximation technique for interactive subsurface scattering. We use a general two-pass approach, which creates transmitted irradiance samples onto shadow maps and computes illumination using the shadow maps. We estimate single scattering efficiently using a method similar to common shadow mapping with adaptive deterministic sampling. A hierarchical technique is applied to evaluate multiple scattering, based on a diffusion theory. We further accelerate rendering speed by tabulating complex functions and utilizing level of detail. We demonstrate that our technique produces high-quality images of animated scenes with blurred shadow at hundreds frames per second on graphics hardware. It can be integrated into existing interactive systems easily.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.365-365
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• 2012

이수 및 치수를 위한 수공구조물 설계 및 하천기본계획 수립의 요점은 설계홍수량의 산정에 있으며, 통계적으로 유의성을 가지는 설계홍수량을 산정하기 위해서는 일반적으로 30년 이상 관측된 홍수자료가 요구된다. 우리나라의 경우 대부분의 유역이 미계측 유역이거나 관측년수가 비교적 작은 경우가 많으므로, 상대적으로 자료 연한이 긴 강우자료를 빈도분석한 후 이를 강우-유출 모형에 입력하여 확률홍수량을 추정하는 간접적인 방법이 주로 이용되며 사용된 강우의 빈도가 홍수의 빈도와 동일하다는 가정을 기본으로 한다. 그러나 동일한 강우량이 발생하더라도 강우의 강도, 지속시간, 유역의 선행함수조건 등과 같은 유역 특성에 따라 유출의 특성은 현저히 다르게 나타나며 결국 이러한 특성은 입력자료, 강우-유출 모형, 기후변동성 등과 같은 불확실성 요소로 인식될 수 있다. 따라서 본 연구에서는 이러한 불확실성을 고려할 수 있는 강우-유출 모의기법을 개발하여 이를 통해 홍수빈도곡선을 유도할 수 있는 방법론을 제시하고자 한다. 불확실성 분석을 위해 기존 HEC-1 강우-유출 모형에서 Bayesian MCMC 기법을 적용하여 매개변수들의 사후분포를 추정하여 매개변수들의 최적화 및 불확실성 분석을 수행하였다. 마지막으로 기후변화 영향을 통합한 홍수빈도곡선을 유도하기 위해서 극치강수를 모의하는 것이 필요하며, 본 연구에서는 극치값 재현에 있어서 우수한 성능을 발휘하는 Kernel-Pareto Piecewise분포 기반의 강우모의발생 기법을 적용하여 HEC-1모형과 연동되도록 모형을 개발하였다. 본 연구에서 제안하는 방법론은 기존 홍수빈도곡선 유도 방법에서 불확실성을 분석하기 위해 모든 변수들을 독립사상으로 간주하고 Monte Carlo Simulation을 수행함으로서 매개변수들간의 상호연관성, 상관성, 조건부 확률들을 고려할 수 없었던 점을 Bayesian 모형을 통해 매개변수들간의 조건부 확률을 고려한 매개변수의 사후분포 도출을 가능하게 하여 보다 현실적인 강우-유출 관계 도출이 가능하고 불확실성 구간이 자연적으로 도출됨으로서 향후, 신뢰성 있는 수자원 계획수립에 유용한 자료로 활용이 가능할 것으로 판단된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.153-153
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• 2012

기후변화는 강우량, 기온, 해수면온도 등 많은 수문기상학적 요소에 영향을 끼치고 있으며 이러한 영향에 대한 연구가 활발하게 진행되고 있다. 그 중에서도 수공구조물의 설계에 직접적으로 영향을 끼치는 강우특성에 대한 연구는 기후변화로 야기되는 강우의 비정상성(non-stationary)을 중심으로 이루어지고 있다. 현재 수문설계량은 강우량의 빈도해석을 통해 산정되는데, 이러한 빈도해석은 기본적으로 연최대강우자료의 정상성(stationary)과 독립성(independent)을 가정하고 이루어진다. 그러나 기후변화로 연최대강우자료에 경향성이나 변동성이 나타남에 따라 경향성과 변동성을 고려할 수 있는 빈도해석 기법의 개발에 대한 필요성이 증가하고, 실제로 2000년대에 들어서면서부터 우리나라뿐만 아니라 전 세계적으로 이루어지고 있다. 연최대강우자료의 정상성을 판단하기 위해 강우자료에 대한 경향성 분석을 수행하게 되는데, 경향성 분석을 위해 다양한 통계적 기법들이 적용되고 있다. 그러나 현재 경향성 분석방법의 적용에 대한 뚜렷한 기준이 없어 여러 가지의 경향성 분석 방법을 적용하여 다수의 분석방법별 결과를 종합하여 경향성 유무를 판단하고 있는 실정이며, 동일자료에 대해서도 연구에 따라 다른 결과가 나타나고 있다. 따라서 본 연구에서는 경향성 분석방법의 기각력을 비교검토하여 경향성 분석방법의 적용에 필요한 기준을 제시하고자 한다. 이를 위해 경향성 분석을 위해 널리 사용되고 있는 t-test, Mann-Kendall test, Hotelling-Pabst test를 비교하고자 한다. 여기에서 t-test는 매개변수를 사용하는 매개변수적 방법이고, Mann-Kendall test와 Hotelling-Pabst test는 비매개변수적 방법이다. 귀무가설의 경우 t-test는 경향성이 없다고 가정하고 있는데 반해, Mann-Kendall test와 Hotelling-Pabst test는 경향성이 있다고 가정하고 있다. 기각력 검토를 위해서는 Monte Carlo simulation을 이용하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1559-1565
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• 2021

In this paper, an antenna selection scheme is proposed in massive multi-user multiple input multiple output (MU-MIMO) systems. The proposed antenna selection scheme can achieve almost the same performance as a conventional scheme while significantly reducing the overhead of feedback by using deep reinforcement learning (DRL). Each user compares the channel gains of massive antennas in base station (BS) to the L-largest channel gain, converts them to one-bit binary numbers, and feed them back to BS. Thus, the feedback overhead can be significantly reduced. In the proposed scheme, DRL is adopted to prevent the performance loss that might be caused by the reduced feedback information. We carried out extensive Monte-Carlo simulations to analyze the performance of the proposed scheme and it was shown that the proposed scheme can achieve almost the same average sum-rates as a conventional scheme that is almost optimal.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.12A
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• pp.998-1005
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• 2009

In the uplink of OFDMA (Orthogonal Frequency Division Multiple Access) based M-WiMAX(Mobile-Worldwide Interoperability for Microwave Access) system, linear phase shift is caused by signals transmitted from multiuser with different delay time and thus, MAI (Multiple Access Interference) occurs. MAI degrades the performance of ranging code detection and delay time estimation in the uplink. Therefore, in this paper, we propose ranging algorithm, applying SIC (Successive Interference Cancellation) to the conventional ranging algorithm, to minimize MAI and to improve ranging performance. The proposed ranging algorithm is verified through the Monte Carlo simulation, which shows the improved performance of ranging code detection and delay time estimation compared to the conventional algorithms. Through compared with random access of the 3GPP LTE, we can know limit of ranging performance.