• The Journal of Society for e-Business Studies
• /
• v.6 no.2
• /
• pp.167-178
• /
• 2001

Key is generally formed using the Random Number. How to make the Random Number is to cast coin or dice as classical method, to form the Real Random Number with Hardware and to make the Pseudo Random Number by means of utilizing mathematical algorithm. This thesis presented NRNG(New Random Number Generator) which put self-development Hardware to use as Key Generation Method and inspected to compare the Real Random Number with the Pseudo Random Number and special properties which PRNG(Pseudo-Random Number Generator) creates.

• Korean Journal of Mathematics
• /
• v.14 no.1
• /
• pp.85-93
• /
• 2006

A good arithmetic random number generator should possess full period, uniformity and independence, etc. To obtain the excellent random number generator, many researchers have found good parameters. Also an initial seed is the important factor in random number generator. But, there is no theoretical guideline for using the initial seeds. Therefore, random number generator is usually used with the arbitrary initial seed. Through the empirical tests, we show that the choice of the initial values for the seed is important to generate good random numbers.

• Proceedings of the Korea Society for Simulation Conference
• /
• 2001.10a
• /
• pp.464-467
• /
• 2001

A good arithmetic random number generator should possess full period, uniformity and independence, etc. To obtain the excellent random number generator, many researchers have found good parameters. Also an initial seed is the important factor in random number generator. But, there is no theoretical guideline for using the initial seeds. Therefore, random number generator is usually used with the arbitrary initial seed. Through the empirical tests, we show that the choice of the initial values for the seed is important to generate good random numbers.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2004.04a
• /
• pp.394-397
• /
• 2004

In this paper, we consider interval number-valued random variables and fuzzy number-valued random variables and discuss Choquet integrals of them. Using these properties, we define the Choquet expected value of fuzzy number-valued random variables which is a natural generalization of the Lebesgue expected value of Lebesgue expected value of fuzzy random variables. Furthermore, we discuss some application of them.

• Proceedings of the Korea Society for Simulation Conference
• /
• 2001.05a
• /
• pp.164-168
• /
• 2001

The Multiple Recursive Generator(MRG) has been considered by many scholars as a very good Random Number generator. For the long period and excellent statistical properties, the method of the combination with random number generators are used. In this paper, for two-combined MRGs, we examine the statistical properties and show the importance of the seeds likewise other random number generators. And we modify the two-combined MRGs and verify the statistical superiority.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2002.12a
• /
• pp.41-45
• /
• 2002

From the paper which it sees a strong random number generator it uses a fuzzy set from 16 method of the statistical test which is a cryptograph random number test it verifies. 16 statistical test of NIST extends in crptograph and engineering whole it is a scale which is important distinguishes the distinction incapable characterstic of the random numbers which are used. To try introduce a fuzzy set the possibility of having a more strong randomness in order to be, it strengthens the function of the random number generator.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2014.11a
• /
• pp.992-993
• /
• 2014

임의 숫자는 여러 분야에서 다양하게 사용되고 있으며, 크게 True Random Number와 Pseudo Random Number로 구분지어 지는데, 대부분의 경우 Pseudo Random Number를 사용하고 있다. 이 경우, 동일한 Seed에 대해서는 항상 동일한 값을 반환하기 때문에, 진정한 임의 숫자라고 하기는 어렵다. 본 논문에서는 임의 숫자에 대한 기본 정의와 더불어 정지 영상을 이용하여 임의 숫자를 생성하는 방법에 대해 알아보고, 기존의 Pseudo Random Number와의 차이점을 설명하도록 하겠다.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.13 no.3
• /
• pp.1147-1152
• /
• 2012

In this paper, it is key issue about analysis of characteristics processing of digital random output stream of hardware random number generator, which is applied in medical area. The output stream of random number generator based on hardware binary random number is effected from factors such as delay, jitter, temperature, and so on. In this paper, it presents about major factor, which effects hardware output random number stream, and the randomness of output stream data, which are combined output stream and postprocessing data such as encryption algorithm, encoding algorithm, is analyzed. the analyzed results are evaluated by major test items of randomness.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.15 no.1
• /
• pp.98-103
• /
• 2005

In this paper, we consider interval number-valued random variables and fuzzy number-valued random variables and discuss Choquet integrals of them. Using these properties, we define the Choquet expected value of fuzzy number-valued random variables which is a natural generalization of the Lebesgue expected value of fuzzy random variables. Furthermore, we discuss some application of them.

• Wind and Structures
• /
• v.3 no.1
• /
• pp.1-10
• /
• 2000

Recently, an efficient and practical method has been developed for the generation of univariate non-Gaussian wind pressure time histories on low building roofs; this methodology requires intermittent exponential random numbers for the simulation. On the other hand, the conventional spectral representation scheme with random phase is found suitable for the generation of univariate Gaussian wind pressure time histories on low building roofs; this simulation scheme requires uniform random numbers. The dependency of these simulation methodologies on the random number generator is one of the items affecting the accuracy of the simultion result; therefore, an attempt has been made to investigate the issue. This note presents the observed sensitivity of random number sets in repetitive simulations of Gaussian and non-Gaussian wind pressures.