• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 2003.12a
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• pp.211-220
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• 2003

본 논문은 신뢰 할 수 없는 네트워크를 통해서도 사용자를 인증하거나 키를 교환하는 것에 적합한 패스워드 인증 프로토콜을 제안한다. 기본 아이디어는 패스워드 검증정보의 램덤성(randomness)을 증가시키기 위하여, 패스워드를 분할한 후 이에 대한 각 패스워드 지식을 확대(amplification)하는 구조로 설계된다. 또한 서버측 파일을 암호화하여 보관함으로써 서버 파일 타협 공격에 강인하도록 구성하였다. 더불어 검증정보 및 서버의 암호화키가 다수의 서버들에게 분산되도록 설계된 방식을 제안한다.

• Journal of Korean Vacuum Science & Technology
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• v.2 no.2
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• pp.57-62
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• 1998

The resonance frequencies, shunt impedances and Q-values for the higher-order modes in our designed cavity are calculated by the computer codes URMEL and MAFIA. A new computer code is developed to calculate the complex tune shifts for the randomness of the higher-order mode frequencies due to the construction errors of a cavity. The results with the construction errors are compared to those fo without error cases for the dipole mode and quadrupole mode.

• Journal of Advanced Marine Engineering and Technology
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• v.29 no.3
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• pp.319-324
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• 2005

This paper reports the performance of Wind-PV(Photovoltaic) hybrid system. The output power of PV is affected by the environmental factors such as solar radiation and cell temperature. Also, the output power of wind system is generated with wind power. Integration of Wind and PV resources, which are generally complementary, usually reduce the capacity of the battery. This paper includes discussion on system reliability, power quality and effects of the randomness of the wind and the solar radiation on system design.

• Journal of the Korean Statistical Society
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• v.5 no.1
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• pp.61-77
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• 1976

The first aim of this study is to provide QC engineers with the right method of cipher of SQC-charts and to help learn how to analyse SQC-charts. The second aim is to maximize the utility of SQC-charts by introducing some Distribution-free Statistical Tests which is experted to provide some methods of test for null hypothese $(H_0)$ concerning the randomness of manufacturing processes.

• Bulletin of the Korean Mathematical Society
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• v.59 no.2
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• pp.507-528
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• 2022

We propose a path integral method to construct a time stepwise local volatility for the stock index market under Dupire's model. Our method is focused on the pricing with the Monte Carlo Method (MCM). We solve the problem of randomness of MCM by applying numerical integration. We reconstruct this task as a matrix equation. Our method provides the analytic Jacobian and Hessian required by the nonlinear optimization solver, resulting in stable and fast calculations.

• Geomechanics and Engineering
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• v.14 no.6
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• pp.589-600
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• 2018

For foundations in permafrost regions, the displacement characteristics are uncertain because of the randomness of temperature characteristics and mechanical parameters, which make the structural system have an unexpected deviation and unpredictability. It will affect the safety of design and construction. In this paper, we consider the randomness of temperature characteristics and mechanical parameters. A stochastic analysis model for the uncertain displacement characteristic of foundations is presented, and the stochastic coupling program is compiled by Matrix Laboratory (MATLAB) software. The stochastic displacement fields of an embankment in a permafrost region are obtained and analyzed by Neumann stochastic finite element method (NSFEM). The results provide a new way to predict the deformation characteristics of foundations in permafrost regions, and it shows that the stochastic temperature has a different influence on the stochastic lateral displacement and vertical displacement. Construction disturbance and climate warming lead to three different stages for the mean settlement of characteristic points. For the stochastic settlement characteristic, the standard deviation increases with time, which imply that the results of conventional deterministic analysis may be far from the true value. These results can improve our understanding of the stochastic deformation fields of embankments and provide a theoretical basis for engineering reliability analysis and design in permafrost regions.

• Journal of KIISE:Computer Systems and Theory
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• v.37 no.6
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• pp.354-367
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• 2010

There are many methods for analyzing patterns in time series data. Although stock data represents a time series, there are few studies on stock pattern analysis and prediction. Since people believe that stock price changes randomly we cannot predict stock prices using a scientific method. In this paper, we measured the degree of the randomness of stock prices using Kolmogorov complexity, and we showed that there is a strong correlation between the degree and the accuracy of stock price prediction using our semi-global alignment method. We transformed the stock price data to quantized string sequences. Then we measured randomness of stock prices using Kolmogorov complexity of the string sequences. We use KOSPI 690 stock data during 28 years for our experiments and to evaluate our methodology. When a high Kolmogorov complexity, the stock price cannot be predicted, when a low complexity, the stock price can be predicted, but the prediction ratio of stock price changes of interest to investors, is 12% prediction ratio for short-term predictions and a 54% prediction ratio for long-term predictions.

• Journal of the Korean Society for Advanced Composite Structures
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• v.1 no.2
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• pp.29-35
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• 2010

In addition to the Young's modulus, the Poisson's ratio is also at the center of attention in the field stochastic finite element analysis since the parameters play an important role in determining structural behavior. Accordingly, the sole effect of this parameter on the response variability is of importance from the perspective of estimation of uncertain response. To this end, a formulation to determine the response variability in laminate composite plates due to the spatial randomness of Poisson's ratio is suggested. The independent contributions of random Poisson's ratiocan be captured in terms of sub-matrices which include the effect of the random parameter in the same order, which can be attained by using the Taylor's series expansion about the mean of the parameter. In order to validate the adequacy of the proposed formulation, several example analyses are performed, and then the results are compared with Monte Carlo simulation (MCS). A good agreement between the suggested scheme and MCS is observed showing the adequacy of the scheme.

• Computers and Concrete
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• v.26 no.2
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• pp.127-136
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• 2020

There is an inherent randomness for concrete microstructure even with the same manufacturing process. Meanwhile, the concrete material under the aqueous environment is usually not fully saturated by water. This study aimed to develop a stochastic micromechanical framework to investigate the probabilistic behavior of the unsaturated concrete from microscale level. The material is represented as a multiphase composite composed of the water, the pores and the intrinsic concrete (made up by the mortar, the coarse aggregates and their interfaces). The differential scheme based two-level micromechanical homogenization scheme is presented to quantitatively predict the concrete's effective properties. By modeling the volume fractions and properties of the constituents as stochastic, we extend the deterministic framework to stochastic to incorporate the material's inherent randomness. Monte Carlo simulations are adopted to reach the different order moments of the effective properties. A distribution-free method is employed to get the unbiased probability density function based on the maximum entropy principle. Numerical examples including limited experimental validations, comparisons with existing micromechanical models, commonly used probability density functions and the direct Monte Carlo simulations indicate that the proposed models provide an accurate and computationally efficient framework in characterizing the material's effective properties. Finally, the effects of the saturation degrees and the pore shapes on the concrete macroscopic probabilistic behaviors are investigated based on our proposed stochastic micromechanical framework.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.5
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• pp.2375-2393
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• 2016

Key agreement is paramount in secure wireless communications. A promising approach to address key agreement schemes is to extract secure keys from channel characteristics. However, because channels lack randomness, it is difficult for wireless networks with stationary communicating terminals to generate robust keys. In this paper, we propose a Robust Secure Key Agreement (RSKA) scheme from Received Signal Strength (RSS) in stationary wireless networks. In order to mitigate the asymmetry in RSS measurements for communicating parties, the sender and receiver normalize RSS measurements and quantize them into q-bit sequences. They then reshape bit sequences into new l-bit sequences. These bit sequences work as key sources. Rather than extracting the key from the key sources directly, the sender randomly generates a bit sequence as a key and hides it in a promise. This is created from a polynomial constructed on the sender's key source and key. The receiver recovers the key by reconstructing a polynomial from its key source and the promise. Our analysis shows that the shared key generated by our proposed RSKA scheme has features of high randomness and a high bit rate compared to traditional RSS-based key agreement schemes.