• Journal of the Korean Data and Information Science Society
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• v.9 no.2
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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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• v.6 no.1
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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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• v.15 no.12
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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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• v.13 no.10
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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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• v.15 no.3
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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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.05a
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• pp.804-807
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• 2003

Recently, standardization is essential strategic tool for a firm to preoccupy a market. Also WTO TBT(Technical Barriers to Trade) makes importance of standardization greater in telecommunication industry. Therefore countries, not to speak of firms, recognize standards essential strategy to preoccupy markets. In this paper, we will examine the standardization competition between a leader and a follower and their strategies through dynamic incomplete information game model.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.3
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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.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.1
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• pp.117-123
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• 2013

By calculating the spectral efficiency of symmetric balance incomplete block design(BIBD) codes satisfying BER=$10^{-9}$, it can be found that ideal BIBD code design with m=2 and various q's is effective when effective power is high($P_{sr}=-10$ dBm). But BIBD code design with q > 2 and various m's can be effective when effective power is low($P_{sr}=-25$ dBm).

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.5
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• pp.121-127
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• 2013

When input power is small, nonideal symmetric balance incomplete block design(BIBD) code design is effective in the spectral-amplitude-code(SAC) optical code-division multiple-access (OCDMA) system. But the number of simultaneous users is not sufficient. To overcome this property, we propose 2-D BIBD codes, where nonideal BIBD codes are used as spectral code and ideal BIBD codes are used as spatial codes. Analytical results show that the number of simultaneous users increases significantly.

• Journal of Information Technology Applications and Management
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• v.13 no.4
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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.