• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.07a
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• pp.6-7
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• 2011

본 논문에서는 지역적 학습 방법을 활용하는 Average Neighborhood Margin Maximization(ANMM)에 기반하여 피부색과 비피부색 영역을 분리하는 이진 분류의 통계적 접근법을 제안한다. Fisher Linear Discriminant(FLD)와 Average Neighborhood Margin Maximization(ANMM)의 피부색과 비피부색 클래스 내 분산 대비 클래스 간 분산의 비교를 통해 두 클래스 간 분리력 변화를 확인한다. 교사(Supervised) 이진 분류문제에 대하여 Small sample size(SSS) 문제, 가우시안 분포 가정의 문제, 최대 추출 가능 특징 수 제한 문제 등을 해결함과 동시에, 지역적 특성 학습 방법의 도입을 통해 피부색과 비피부색 간 분리력을 향상시킨다.

• Journal of Communications and Networks
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• v.12 no.4
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• pp.317-329
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• 2010

In recent years, many sparse estimation methods, also known as compressed sensing, have been developed. However, most of these methods presume that the measurement matrix is completely known. We develop a new blind maximum likelihood method-the expectation-sparse-maximization (ESpaM) algorithm-for models where the measurement matrix is the product of one unknown and one known matrix. This method is a variant of the expectation-maximization algorithm to deal with the resulting problem that the maximization step is no longer unique. The ESpaM algorithm is justified theoretically. We present as well numerical results for two concrete examples of blind channel identification in digital communications, a doubly-selective channel model and linear time invariant sparse channel model.

• Journal of information and communication convergence engineering
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• v.16 no.4
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• pp.213-220
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• 2018

With the exponential developments of social network, their fundamental role as a medium to spread information, ideas, and influence has gained importance. It can be expressed by the relationships and interactions within a group of individuals. Therefore, some models and researches from various domains have been in response to the influence maximization problem for the effects of "word of mouth" of new products. For example, in reality, more than two related social groups such as commercial companies and service providers exist within the same market issue. Under such a scenario, they called social adversaries competitively try to occupy their market influence against each other. To address the influence maximization (IM) problem between them, we propose a novel IM problem for social adversarial players (IM-SA) which are exploiting the social network attributes to infer the unknown adversary's network configuration. We sophisticatedly define mathematical closed form to demonstrate that the proposed scheme can have a near-optimal solution for a player.

• Journal of Food Hygiene and Safety
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• v.20 no.1
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• pp.13-17
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• 2005

The purpose of the present study was to investigate differences in the sensitizing potential of Rhus Veniciflua(Rhus-II), when tested by the guinea pig maximization test(GPMT) and Freund's complete adjuvant test(FCAT) with an identical, intradermal induction concentration. A new grading classification of the sensitization potential is proposed. The GPMT was conducted according to OECD guideline $\#406$, using a multiple-dose design and test results were analysed with logistic regression analysis. During the induction stage, we injected intradermally each three site 0.1 ml(l mg/animal) test material, 0.1 ml complete Freund's adjuvant and 0.lml the test agent emulsified in the adjuvant. 7 days later, we induced weak sensitization with $10\%$ sodium lauryl sulfate(SLS) and applide 1ml(l0mg/animal) test agent topically on the same site and made a tight occlusion. 14 days later we challenged with 1 ml(l 0mg/animal) of test material on the flank and observed ant 24 hours and 48 hours later. The results were also observed $0\%$ at 24 hours challenge. The results observed 48 hours after challenge were the identical. These data indicated that, although Rhus-II is a no contact allergen. It was reported that the skin sensitization by Rhus-II was not detected the skin sensitization in the guinea pig maximization test (GPMT). Consequently, it was confirmed that Rhus-II had no contact allergic sensitization in guinea pig maximization test.

• Journal of the Korean Operations Research and Management Science Society
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• v.13 no.2
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• pp.66-71
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• 1988

Let B be present value of some sequence. This paper concerns the maximization of the expected utility of the present value B when the utility function is exponential.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.4C
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• pp.397-402
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• 2009

Accurate estimation of time-selective fading channel is a difficult problem in OFDM(Orthogonal Frequency Division Multiplexing) system. There are many channel estimation algorithms that are very weak in noisy channel. For solving this problem, we use EM (Expectation-Maximization) algorithm for iterative optimization of the data. We propose an EM-LPC algorithm to estimate the time-selective fading. The proposed algorithm improves of the BER performance compared to EM based channel estimation algorithm and reduces the iteration number of the EM loop. We simulated the uncoded system. If coded system use the EM-LPC algorithm, the performance are enhanced because of the coding gain. The EM-LPC algorithm is able to apply to another communication system, not only OFDM systems. The image processing of the medical instruments that the demand of accurate estimation can also use the proposed algorithm.

• The Korean Journal of Financial Management
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• v.1 no.1
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• pp.1-27
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• 1985

One of the most important research works in modern business enterpise is the relation between the purpose of business enterprise and decision making behavior of manager. It is because the coincidence of the former and the latter is considered an ideal type in evaluating the result of business management. Here I have set up assumptions in order to solve the above statements: (1) What purpose does the modern business enterprise set up and what kind of economic background does it have? (2) What is the theory of maximization of stock value among the purposes of business enterprise? (3) What kind of decision making do we do in the maximization of stock value in busiess administration? (4) How is the behavior of business financial manager's intention and decision made? The result pursued under the above assumptions shows that business manager's behavior of decision making is affected according to the degree that he gets some information, but basically is determined in consideration of his autonomous standpoint, namely the stability of business enterprise and the stability of manager himself while he faithfully performs his duty which is entrusted by stockholders. Therefore we come to the conclusion that there is a little gap between a manager's behavior of decision-making and the purpose of stock value maximization.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.7C
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• pp.635-643
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• 2007

In this paper, a decision-directed expectation maximization (DEM) algorithm is proposed to improve the performance of channel estimation in OFDM-based cellular systems. The DEM algorithm enables a mobile station (MS) with multiple antennas, located at the cell boundary, to increase the performance of channel estimation using transmit data, without decreasing spectral efficiency. Also, DEM algorithm can apply fast fading without loss of channel estimation performance because that includes channel variation factor in a group. It is verified by computer simulation that the DEM algorithm can reduce computational complexity significantly while improving the performance of channel estimation in fast fading channels, compared with the expectation maximization (EM) algorithm.

• ETRI Journal
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• v.41 no.5
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• pp.626-636
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• 2019

A novel algorithm for joint user selection and optimal power allocation for Stackelberg game-based revenue maximization in a downlink non-orthogonal multiple access (NOMA) network is proposed in this study. The condition for the existence of optimal solution is derived by assuming perfect channel state information (CSI) at the transmitter. The Lagrange multiplier method is used to convert the revenue maximization problem into a set of quadratic equations that are reduced to a regular chain of expressions. The optimal solution is obtained via a univariate iterative procedure. A simple algorithm for joint optimal user selection and power calculation is presented and exhibits extremely low complexity. Furthermore, an outage analysis is presented to evaluate the performance degradation when perfect CSI is not available. The simulation results indicate that at 5-dB signal-to-noise ratio (SNR), revenue of the base station improves by at least 15.2% for the proposed algorithm when compared to suboptimal schemes. Other performance metrics of NOMA, such as individual user-rates, fairness index, and outage probability, approach near-optimal values at moderate to high SNRs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3498-3511
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• 2016

We investigate the channel state information (CSI) in multi-input multi-output (MIMO) cooperative networks that employ the amplify-and-forward transmission scheme. Least squares and expectation conditional maximization have been proposed in the system. However, neither of these two approaches takes advantage of channel sparsity, and they cause estimation performance loss. Unlike linear channel estimation methods, several compressed channel estimation methods are proposed in this study to exploit the sparsity of the MIMO cooperative channels based on the theory of compressed sensing. First, the channel estimation problem is formulated as a compressed sensing problem by using sparse decomposition theory. Second, the lower bound is derived for the estimation, and the MIMO relay channel is reconstructed via compressive sampling matching pursuit algorithms. Finally, based on this model, we propose a novel algorithm so called sparsity adaptive expectation maximization (SAEM) by using Kalman filter and expectation maximization algorithm so that it can exploit channel sparsity alternatively and also track the true support set of time-varying channel. Kalman filter is used to provide soft information of transmitted signals to the EM-based algorithm. Various numerical simulation results indicate that the proposed sparse channel estimation technique outperforms the previous estimation schemes.