• Journal of the Korean Data and Information Science Society
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• 제9권2호
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• pp.211-218
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• 1998

This paper deals with the problem of obtaining some Bayes estimators of exponential reliability in a time censored sampling with incomplete information. Some Bayes estimators are proposed and studied under squared error loss and Harris loss.

• Journal of the Korean Data and Information Science Society
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• 제6권1호
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• pp.39-51
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• 1995

This paper deals with the problem of obtaining some Bayes estimators of Rayleigh reliability function in a time censored sampling with incomplete information. Using the priors about a reliability function some Bayes estimators are proposed and studied under squared error loss and Harris loss.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권12호
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• pp.4567-4583
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• 2021

This study proposes an analytical approximation algorithm based on extreme value theory (EVT) for the inverse of the power of the incomplete Gamma function. First, the Gumbel function is used to approximate the power of the incomplete Gamma function, and the corresponding inverse problem is transformed into the inversion of an exponential function. Then, using the tail equivalence theorem, the normalized coefficient of the general Weibull distribution function is employed to replace the normalized coefficient of the random variable following a Gamma distribution, and the approximate closed form solution is obtained. The effects of equation parameters on the algorithm performance are evaluated through simulation analysis under various conditions, and the performance of this algorithm is compared to those of the Newton iterative algorithm and other existing approximate analytical algorithms. The proposed algorithm exhibits good approximation performance under appropriate parameter settings. Finally, the performance of this method is evaluated by calculating the thresholds of space-time block coding and space-frequency block coding pattern recognition in multiple-input and multiple-output orthogonal frequency division multiplexing. The analytical approximation method can be applied to other related situations involving the maximum statistics of independent and identically distributed random variables following Gamma distributions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권10호
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• pp.5260-5275
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• 2019

In the process of constructing the traditional offensive and defensive game theory model, these are some shortages for considering the dynamic change of security risk problem. By analysing the critical indicators of the incomplete information game theory model, incomplete information attack and defense game theory model and the mathematical engineering method for solving Bayes-Nash equilibrium, the risk-averse income function for information assets is summarized as the problem of maximising the return of the equilibrium point. To obtain the functional relationship between the optimal strategy combination of the offense and defense and the information asset security probability and risk probability. At the same time, the offensive and defensive examples are used to visually analyse and demonstrate the incomplete information game and the Harsanyi conversion method. First, the incomplete information game and the Harsanyi conversion problem is discussed through the attack and defense examples and using the game tree. Then the strategy expression of incomplete information static game and the engineering mathematics method of Bayes-Nash equilibrium are given. After that, it focuses on the offensive and defensive game problem of unsafe information network based on risk aversion. The problem of attack and defense is obtained by the issue of maximizing utility, and then the Bayes-Nash equilibrium of offense and defense game is carried out around the security risk of assets. Finally, the application model in network security penetration and defense is analyzed by designing a simulation example of attack and defense penetration. The analysis results show that the constructed income function model is feasible and practical.

• Journal of the Korean Data and Information Science Society
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• 제15권3호
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• pp.555-563
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• 2004

In classification and discrimination, we often face with incomplete group variable arising typically from many missing values and/or incredible cases. This paper suggests the use of K-means clustering for pre-adjusting incompleteness and in turn classification based on generalized statistical distance is performed. For illustrating the proposed procedure, simulation study is conducted comparatively with CART in data mining and traditional techniques which are ignoring incompleteness of group variable. Simulation study manifests that our methodology out-performs.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2003년도 춘계종합학술대회
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• pp.804-807
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• 2003

최근 정보통신 산업에서 일어나고 있는 기술 및 제품 경쟁은 표준화 경쟁이라고 해도 과언이 아닐 정도로 표준 획득은 시장을 선점하기 위하여 핵심 요소로 정보통신기술 변화의 흐름은 표준화를 지향하고 있다. 더욱이 WTO TBT(Technical Barries to Trade)의 발효는 범세계적으로 하나의 표준을 지향해 나아감에 따라 국제표준(Global Standards)의 중요성은 크게 증대되고 있다. 이에 기업은 물론 각 국가는 표준을 핵심 전략으로 인식하고, 다양한 전략적 접근을 통하여 시장선점 나아가 표준획득을 위해 치열한 경쟁을 하고 있다. 본 고에서는 게임이론 중 상대 경기자의 유형(type)을 알 수 없는 동적 불비정보게임(Dynamic Incomplete Information Game)을 이용하여, 정보통신 산업 내 먼저 네트워크를 형성한 선도기업과 이에 대하여 선도기업의 기술과의 호환을 추구하고자 진입한 추종기업간의 경쟁을 분석하고, 이를 통하여 선도기업과 추종기업 간 표준화 경쟁에 있어서 최선의 경쟁 전략을 분석해 보고자 한다.

• 한국경영과학회지
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• 제23권3호
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• pp.63-73
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• 1998

The paper deals with interactive multiple criteria decision making procedure when decision maker (DM) specifies her or his preference in incomplete ways. Usually DM is willing or able to provide only incomplete information, because of time pressure and lack of knowledge or data. Under incomplete information on utility and attribute weight, the pairwise dominance checks result in strict or weak dominance values. Considering only strict dominance values sometimes fails to Prioritize alternatives because of fuzziness of preference information. Further there exists some information loss useful if used, otherwise. In this paper, we consider the outranking concept which implies the willingness of DM's taking some risk under the least favorable situation because she has enough reasons to admit the results. By comparing the magnitude of net preference degree of alternatives which is defined by difference between outrankings and outranked degree of each alternative, we can prioritize alternatives.

• 전자공학회논문지
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• 제50권1호
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• pp.117-123
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• 2013

본 논문은 symmetric balance incomplete block design(BIBD) code의 BER=$10^{-9}$을 만족하는 spectral efficiency를 구하였다. 이 계산 결과 effective power가 큰 경우 ($P_{sr}=-10$ dBm)는 m=2로 고정시키고 q값을 변화시키는 ideal BIBD code구성이 효율적이었다. 이와 반대로 effective power가 작은 경우 ($P_{sr}=-25$ dBm)는 ideal BIBD code 구성 보다는 q > 2인 값을 취하고 m값을 변화시키는 설계가 더 효율적임을 알 수 있었다.

• 전자공학회논문지
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• 제50권5호
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• pp.121-127
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• 2013

작은 입력신호의 spectral-amplitude-code(SAC) optical code-division multiple-access (OCDMA) 시스템에는 nonideal symmetric balance incomplete block design(BIBD) code의 사용이 효율적이나 충분한 사용자를 수용하지 못하는 단점이 있다. 이를 극복하기 위하여 본 논문에서는 ideal BIBD code를 공간 코드로 사용하고 nonideal code를 파장 코드로 사용하는 two-dimensional(2-D) BIBD code를 제안한다. 사용자 수에 따른 bit error-rate(BER) 분석을 통하여 제안하는 2-D BIBD code가 1-D BIBD code에 비하여 최대사용자 수를 현저하게 증가시킬 수 있음을 알 수 있다.

• Journal of Information Technology Applications and Management
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• 제13권4호
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• pp.273-290
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• 2006

This study suggests a frequency matrix technique to predict personal credit rate more efficiently using incomplete data sets. At first this study test on multiple discriminant analysis and logistic regression analysis for predicting personal credit rate with incomplete data sets. Missing values are predicted with mean imputation method and regression imputation method here. An artificial neural network and frequency matrix technique are also tested on their performance in predicting personal credit rating. A data set of 8,234 customers in 2004 on personal credit information of Bank A are collected for the test. The performance of frequency matrix technique is compared with that of other methods. The results from the experiments show that the performance of frequency matrix technique is superior to that of all other models such as MDA-mean, Logit-mean, MDA-regression, Logit-regression, and artificial neural networks.