• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.2C
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• pp.217-225
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• 2009

Tone injection scheme has been known as one of peak to average power ratio (PAPR) reduction methods deployable to multi-carrier system like orthogonal frequency division multiplexing (OFDM). The basic idea in tone injection scheme is to enforce the constellation size larger so that each of original constellation points is mapped into the preassigned distinct locations. According to the tone injection scheme, it increases symbol power highly induced inherently by expanding constellation to get optimal PAPR reduction. In the other hand, to get optimal power increase, the PAPR would be reduced insufficiently with limited tone injection signal. To withstand these problems, this paper consider the reduction of the PAPR and power increase problem simultaneously, Toward this, the tone injection scheme accomplished by employing the weighted sum genetic algorithm which has been utilized to solve multi-objective optimization problem (MOOP). The simulation results verifies that the proposed scheme can control the effective PAPR performance and alleviation of power increase flexibly by the weight value at the expense of relatively low complexity.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.87-97
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• 2004

In this paper, we propose an algorithm for interlaced-to-progressive conversion by the weighted summation of the information collected from spatial do-interlacing method, in which the weighted edge based line average is applied, and the temporal method in which the motion compensation is employed by using hi-directional BMA (block matching algorithm). We employed time-recursive and motion adaptive processing as motion detection is involved. Also, a median filter is used to deal with limitation of the linear summation in which only an intermediate of values being involved is determined. The main goal of the approach is to overcome the shortcomings of each of the do-interlacing techniques without significant increment of the computational complexity, and the proposed method is apt to implement in hardware for real-time processing.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.1
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• pp.50-58
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• 2018

Intermittent demand is a demand with a pattern in which zero demands occur frequently and non-zero demands occur sporadically. This type of demand mainly appears in spare parts with very low demand. Croston's method, which is an initiative intermittent demand forecasting method, estimates the average demand by separately estimating the size of non-zero demands and the interval between non-zero demands. Such smoothing type of forecasting methods can be suitable for mid-term or long-term demand forecasting because those provides the same demand forecasts during the forecasting horizon. However, the smoothing type of forecasting methods aims at short-term forecasting, so the estimated average forecast is a factor to decrease accuracy. In this paper, we propose a forecasting method to improve short-term accuracy by improving Croston's method for intermittent demand forecasting. The proposed forecasting method estimates both the non-zero demand size and the zero demands' interval separately, as in Croston's method, but the forecast at a future period adjusted by binomial weight according to occurrence probability. This serves to improve the accuracy of short-term forecasts. In this paper, we first prove the unbiasedness of the proposed method as an important attribute in forecasting. The performance of the proposed method is compared with those of five existing forecasting methods via eight evaluation criteria. The simulation results show that the proposed forecasting method is superior to other methods in terms of all evaluation criteria in short-term forecasting regardless of average size and dispersion parameter of demands. However, the larger the average demand size and dispersion are, that is, the closer to continuous demand, the less the performance gap with other forecasting methods.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.551_552
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• 2009

본 논문에서는 수요반응 프로그램 설계 시 프로그램의 효과를 평가할 때 사용되는 CBL (Customer Baseline Load)의 추정방법으로 일기보정을 고려한 가중이동평균법 (Weighted Moving Average)을 제시하였다. 또한 제안된 방법을 PJM에서 관리하는 지역 전력 수요 데이터를 이용한 사례연구 수행 결과를 예시하였다.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1731_1732
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• 2009

This paper presents a stability analysis of networked control systems with packet dropouts. The packet dropouts are modeled as a linear function of the stochastic variable satisfying Bernoulli random binary distribution and weighted moving average (WMA). The observer based controller scheme is designed to exponentially mean square stabilize the NCS. Simulation results is provided to show the applicability of the proposed method.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.04a
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• pp.303-312
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• 1994

The problem of optimally allocating available communication channels in a cellular mobile system with nonuniform traffic distribution is considered. This problem is to minimize the weighted average blocking probability subject to cochannel interference constraints. We use the concept of pattern to deal with the problem more conveniently. Using Lagrangian relaxation and subgradient optimization techniques, we obtain high-quality solutions with information about their deviations from true optimal solutions. Computational experiments show that our method works very well.

• Korean Journal of Hydrosciences
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• v.7
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• pp.125-137
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• 1996

The subject of the paper is the selection of the number and location of raingauge stations among existing ones for the computation of mean areal precipitation and for use as input of real-time flow prediction models. The weighted average method developed by National Weather Service was used to compute MAP over the Boone River basin in Iowa with a 40 year daily data set. Two different searching methods were used to find local optimal solutions. An operational rainfall-runoff model was used to determine the optimal location and number of stations for flow prediction.

• Journal of Digital Contents Society
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• v.14 no.2
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• pp.275-282
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• 2013

In medical image processing field, object recognition is usually carried out by computerized processing of various input information such as brightness, shape, and pattern. If the information mentioned does not make sense, however, many limitations could occur with object recognition during computer processing. Therefore, this paper suggests effective object recognition method based on the magnetic resonance (MR) theory to resolve the basic limitations in computer processing. We propose the efficient method of robust gray-white matter segmentation by texture analysis through the Susceptibility Weighted Imaging (SWI) for contrast enhancement. As a result, an average area difference of 5.2%, which was higher than the accuracy of conventional region segmentation algorithm, was obtained.

• Journal of Korean Tunnelling and Underground Space Association
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• v.10 no.4
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• pp.349-360
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• 2008

In this paper, the modeling procedure of random field with an elasto-plastic finite element algorithm and probability of failure on closely-spaced tunnel were investigated. Local average subdivision (LAS) method which can generate discrete random variables fast and accurately as well as change the resolution in certain region was used. And correlated value allocating and weighted average method were suggested to implement geometrical characteristics of tunnel. After the probability of failure on the test problem was thoroughly investigated using random finite element method, the results were compared with the deterministic strength reduction factor method and single random variable method. Of particular importance in this work, is the conclusion that the probability of failure determined by simplified probabilistic analysis, in which spatial variability is ignored by assuming perfect correlation, can be estimated from the safety factor determined by strength reduction factor method. Also, single random variable method can lead to unconservative estimates of the probability of failure.

• The KIPS Transactions:PartA
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• v.18A no.5
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• pp.215-224
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• 2011

In this paper, a mechanism connecting all weighted migration routes with minimum cost with EGOSST is proposed. Weighted migration routes may be converted to weighted input edges considered as not only traces but also traffics or trip frequencies of moving object on communication lines, roads or railroads. Proposed mechanism can be used in more wide and practical area than mechanisms considering only moving object traces. In our experiments, edge number, maximum weight for input edges, and detail level for grid are used as input parameters. The mechanism made connection cost decrease average 1.07% and 0.43% comparing with the method using weight minimum spanning tree and weight steiner minimum tree respectively. When grid detail level is 0.1 and 0.001, while each execution time for a connecting solution increases average 97.02% and 2843.87% comparing with the method using weight minimum spanning tree, connecting cost decreases 0.86% and 1.13% respectively. This shows that by adjusting grid detail level, proposed mechanism might be well applied to the applications where designer must grant priority to reducing connecting cost or shortening execution time as well as that it can provide good solutions of connecting migration routes with weights.