• Ocean Systems Engineering
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• v.1 no.3
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• pp.249-261
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• 2011

The stochastic nonlinear dynamic behavior and probability density function of ship rolling are studied using the nonlinear dynamical systems approach and probability theory. The probability density function of the rolling response is evaluated through solving the Fokker Planck Equation using the path integral method based on a Gauss-Legendre interpolation scheme. The time-dependent probability of ship rolling restricted to within the safe domain is provided and capsizing is investigated from the probability point of view. The random differential equation of ships' rolling motion is established considering the nonlinear damping, nonlinear restoring moment, white noise and colored noise wave excitation.

• Structural Engineering and Mechanics
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• v.55 no.3
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• pp.525-534
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• 2015

A new structural dynamic fuzzy reliability analysis under stochastic loads which are applied several times is proposed in this paper. The fuzzy reliability prediction models based on time responses with and without strength degeneration are established using the stress-strength interference theory. The random loads are applied several times and fuzzy structural strength is analyzed. The efficiency of the proposed method is demonstrated numerically through an example. The results have shown that the proposed method is practicable, feasible and gives a reasonably accurate prediction. The analysis shows that the probabilistic reliability is a special case of fuzzy reliability and fuzzy reliability of structural strength without degeneration is also a special case of fuzzy reliability with structural strength degeneration.

• Structural Engineering and Mechanics
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• v.62 no.6
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• pp.703-708
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• 2017

The goal of this study is to evaluate behavior uncertainties of structures by using interval finite element analysis based on interval factor method as a specific non-stochastic tool. The interval finite element method, i.e., interval FEM, is a finite element method that uses interval parameters in situations where it is not possible to get reliable probabilistic characteristics of the structure. The present method solves the uncertainty problems of a 2D solid structure, in which structural characteristics are assumed to be represented as interval parameters. An interval analysis method using interval factors is applied to obtain the solution. Numerical applications verify the intuitive effectiveness of the present method to investigate structural uncertainties such as displacement and stress without the application of probability theory.

• Proceedings of the Korea Concrete Institute Conference
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• 2006.11a
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• pp.877-880
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• 2006

The stochastic nature of the tensile strength of concrete is investigated theoretically and experimentally. The tensile strength of concrete was modeled by a theory based on the failure probability of a crack arbitrarily oriented within a concrete body. According to this model, the stochastic nature of the tensile strength depend on the current stress state. This aspect was checked experimentally using a classical three point bend specimen and a rectangular plate specimen loaded at the center. It has been known that the biaxial strength is no different from the uniaxial strength. However, if the region where the tensile strength is constant gets small, the biaxial tensile strength increases and its stochastical variation decreases.

• Journal of Korea Water Resources Association
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• v.32 no.2
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• pp.197-210
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• 1999

This study examines the duration and severity of droughts by the use of stochastic process considerations. The key annual flow statistics are used to estimate the related statistics of drought probability distributions for various combinations of return period and water demand. This study efforts initially focused on analyzing all the nation streamgage records that were judged to meet certain selection criteria, including those of record length, record quality. These analyses resulted in the determination of those annual flow statistics necessary to define the behavior of drought sequences for the selected streams. Using prior research results, the actual or estimated flow statistics are related to the probability distributions of maximum drought events, through the application of the theory of runs. This has resulted in assigning return periods to drought events at gaged locations, and permits an assessment of the probabilities of observed historical drought within the nation.

• The Journal of the Acoustical Society of Korea
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• v.20 no.3
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• pp.56-62
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• 2001

In this paper, we adopt a missing data theory to speech recognition. It can be used in order to maintain high performance of speech recognizer when the missing data occurs. In general, hidden Markov model (HMM) is used as a stochastic classifier for speech recognition task. Acoustic events are represented by continuous probability density function in continuous density HMM(CDHMM). The missing data theory has an advantage that can be easily applicable to this CDHMM. A marginalization method is used for processing missing data because it has small complexity and is easy to apply to automatic speech recognition (ASR). Also, a spectral subtraction is used for detecting missing data. If the difference between the energy of speech and that of background noise is below given threshold value, we determine that missing has occurred. We propose a new method that examines the reliability of detected missing data using voicing probability. The voicing probability is used to find voiced frames. It is used to process the missing data in voiced region that has more redundant information than consonants. The experimental results showed that our method improves performance than baseline system that uses spectral subtraction method only. In 452 words isolated word recognition experiment, the proposed method using the voicing probability reduced the average word error rate by 12％ in a typical noise situation.

• Smart Structures and Systems
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• v.14 no.4
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• pp.559-567
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• 2014

The model of unit dynamic reliability of repairable k/n (G) system with unit strength degradation under repeated random shocks has been developed according to the stress-strength interference theory. The unit failure number is obtained based on the unit failure probability which can be computed from the unit dynamic reliability. Then, the transfer probability function of the repairable k/n (G) system is given by its Markov property. Once the transfer probability function has been obtained, the probability density matrix and the steady-state probabilities of the system can be retrieved. Finally, the dynamic reliability of the repairable k/n (G) system is obtained by solving the differential equations. It is illustrated that the proposed method is practicable, feasible and gives reasonable prediction which conforms to the engineering practice.

• Magazine of the Korea Concrete Institute
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• v.6 no.5
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• pp.183-192
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• 1994

Seismic safety of RC structure can be evaluated by numerical analysis considering randomness of earthquake motion and hysteretic behavior of reinforced concrete, which is more rational than determirustic analysis. In the safety assessment of aseismatic structures by the deterministic theory, it is not easy to consider th effects of random variables but the reliability theory and random vibration theory are useful to assess seismic safety with considering random effects. This study aims at the evaluation of sesmic damage and risk of the RC frame structure by stochastic response analysis of hysteretic system and then the calculation stages of the prob ability of failure are presented.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.3_4
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• pp.170-186
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• 2004

Recently, for real-time applications such as multimedia and signal processing, it becomes increasingly important to provide a probabilistic guarantee that each task in the application meets its deadline with a given probability. To provide the probabilistic guarantee, an analysis method is needed that can accurately predict the deadline miss probability for each task in a given system. This paper proposes a stochastic analysis method for real-time systems that use priority-driven scheduling, such as Rate Monotonic and Earliest Deadline First, in order to accurately compute the deadline miss probability of each task in the system. The proposed method accurately computes the response time distributions for tasks with arbitrary execution time distributions, and thus makes it possible to determine the deadline miss probability of individual tasks. In the paper. through experiments, we show that the proposed method is highly accurate and outperforms exisiting methods proposed in the literature.

• Journal of the Korea Society of Computer and Information
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• v.25 no.6
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• pp.119-129
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• 2020

Software development activities are influenced by stochastic theory rather than deterministic one due to having process variability. Stochastic methods factor in the uncertainties associated with project activities and provides insight into the expected project outputs as probability distributions rather than as deterministic approximations. Thus, successful software projects systematically manage and balance five objectives based on historical probability: scope, size, cost, effort, schedule, and quality. Although software size estimation having much uncertainty in initial development has traditionally performed using deterministic methods: LOC(Lines Of Code), COCOMO(COnsructive COst MOdel), FP(Function Point), SLIM(Software LIfecycle Management). This research aims to present a function point method based on stochastic distribution and a case study based on Monte Carlo Simulation applying on an automotive electrical and electronics system software development. It is expected that the result of this paper is used as guidance for establishing of function point method in organizations and tools for helping project managers make decisions correctly.