• Journal of the military operations research society of Korea
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• v.28 no.2
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• pp.56-69
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• 2002

A technique of finding both probability density and distribution function for interkilling times is considered and demonstrated. An important result is that any arbitrary interfiring time random variables fit to this study, The interfiring renewal density function given a certain interfiring probability density function can be applied to obtain the corresponding interkilling renewal density function which helps us to estimate the expected number of killing events in a time period. The numerical inversion of Laplace transformation makes these possible and the results appear to be excellent. In case of ammunition supply is limited, an alternative way of getting the probability density function of time to the killing is investigated. The convolution technique may give us a means of settling for this new problem.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.6
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• pp.291-296
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• 2015

The tire damage classification method is researched on the periodicity detection of ramdomness ultrasonic signals to occur at the driving vehicle tire. Setting method of adaptive threshold is proposed in order to valid pulse detection by tire damage in ultrasonic noise on the road and used low pass filter for decrease signal ramdomness as preprocessing. Time interval of detected pulse is setted the density function depend on the vehicle's speed and the method of tire damage detection is proposed that measuring the first peak's time of time density function.The result of time density function in case of one damage material, the first peak's time is measured within the error limit of tire's rotation period, 169.8ms and 97.9ms and 81.8ms, about the speed of 50km/h and 80km/h and 100km/h. In case of more than one damage material, the sum of each peak's time is measured within the error limit of tire's rotation period about the speed.

• Journal of Korean Society of Disaster and Security
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• v.6 no.3
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• pp.1-8
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• 2013

Based on random vibration theory, a procedure for calculating the dynamic response of the tall building to time-dependent random excitation is developed. In this paper, the fluctuating along- wind load is assumed as time-dependent random process described by the time-independent random process with deterministic function during a short duration of time. By deterministic function A(t)=1-exp($-{\beta}t$), the absolute value square of oscillatory function is represented from author's studies. The time-dependent random response spectral density is represented by using the absolute value square of oscillatory function and equivalent wind load spectrum of Solari. Especially, dynamic mean square response of the tall building subjected to fluctuating wind loads was derived as analysis function by the Cauchy's Integral Formula and Residue Theorem. As analysis examples, there were compared the numerical integral analytic results with the analysis fun. results by dynamic properties of the tall uilding.

• Journal of Korean Society of Transportation
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• v.29 no.3
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• pp.83-91
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• 2011

This paper discusses models for estimating dynamic travel times based on probability theory. The dynamic travel time models proposed in the paper are formulated assuming that the travel time of a vehicle depends on the distribution of the traffic stream condition with respect to the location along a road when the subject vehicle enters the starting point of a travel distance or with respect to the time at the starting point of a travel distance. The models also assume that the dynamic traffic flow can be represented as an exponential distribution function among other types of probability density functions.

• Proceeding of EDISON Challenge
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• 2015.03a
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• pp.138-146
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• 2015

액체 상태의 물질이 매우 급속하게 냉각되면 일반적으로 과냉각액체(supercooled liquid) 상태에 도달한다. 과냉각액체는 더 낮은 온도에서 유리상(glass phase)으로 상전이를 일으킨다고 알려져 있는데, 이때 나타나는 동역학적 불균일성(dynamic heterogeneity)은 상전이를 기술하는데 중요한 역할을 한다. 그러나 일반적인 액체의 상전이를 연구할 때 주로 사용되던 상관함수(correlation function)으로는 이러한 불균일성을 정량적으로 표현하기 어렵기 때문에 동역학적 민감도(dynamic susceptibility)나 multi-time correlation function 등 동역학적 성질(dynamic property)로부터 특징적인 시간 개념 및 거리 개념을 도출하려는 연구가 많이 진행되어 왔다. 본 논문에서는 일반적으로 특징적인 거리 개념을 도출해 내는데 사용되는 4점 밀도 상관함수(four-point density correlation function)인 dynamic susceptibility(${\chi}^4$)가 입자 밀도의 요동(fluctuation)의 상관관계(correlation)가 지속되는 특징적인 시간 개념에 대한 정보 또한 포함하고 있다는 점에 주목하였다. 이에 따라 ${\chi}^4$의 시간에 대한 적분인 ${\tau}_4$를 새롭게 도입하였으며 그 결과로 ${\tau}_4$는 three-time density correlation function으로부터 도출한 ${\tau}_{Dh}$와 같은 축척(scaling)을 가지는 것을 확인하였다. 과냉각액체에 대한 장난감 모형(toy model)의 일종인 "Lennard-Jones potential 하에서 운동하는 서로 다른 두 종류의 입자들"을 연구에 사용하였다.

• Journal of Korean Society on Water Environment
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• v.24 no.3
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• pp.345-353
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• 2008

In order to design storage-based non-point source management facilities, the aspect of statistical features of the entire precipitation time series should be considered since non-point source pollutions are delivered by continuous rainfall runoffs. The 3-parameter mixed exponential probability density function instead of traditional single-parameter exponential probability density function is applied to represent the probabilistic features of long-term precipitation time series and model urban stormwater runoff. Finally, probability density functions of water quality control basin overflow are derived under two extreme intial conditions. The 31-year continuous precipitation time series recorded in Busan are analyzed to show that the 3-parameter mixed exponential probability density function gives better resolution.

• Journal of the Korean Institute of Navigation
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• v.17 no.1
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• pp.91-98
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• 1993

This paper presents a class of Bayes estimation of component steady-state availability . Throughout this paper, we will denote the mean time between failure and the mean time between repair by MTBF and MTBR respectively. In section 2 , we investigated Bayes estimation of the steady-state availability for noninformative prior density function and in section 3, we compute Bayes estimation for conjugate prior density function.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.3
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• pp.41-46
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• 2011

The tire damage classification method is researched by periodicity detection of ultrasonic envelope signals to occur at the driving vehicle tire. Because periodic signals is generated by rotations of the damaged tire, it should convert to pulse for using the density function. After time intervals of pulses are represented by the density function, the dominant periodicity is detected. The threshold to make a pulse is calculated by moving average of envelope signals. The result of time density function in case of one damage material, the first peak's time is equals to tire's rotation period, 162ms and 102ms, about the speed of 50km/h and 80km/h. In case of more than one damage material, the sum of each peak's time is equals to tire's rotation period about the speed.

• International Journal of Naval Architecture and Ocean Engineering
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• v.2 no.3
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• pp.119-126
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• 2010

The response of ship roll oscillation under random ice impulsive loads modeled by Poisson arrival process is very important in studying the safety of ships navigation in cold regions. Under both external and parametric random excitations the evolution of the probability density function of roll motion is evaluated using the path integral (PI) approach. The PI method relies on the Chapman-Kolmogorov equation, which governs the response transition probability density functions at two close intervals of time. Once the response probability density function at an early close time is specified, its value at later close time can be evaluated. The PI method is first demonstrated via simple dynamical models and then applied for ship roll dynamics under random impulsive white noise excitation.

• Structural Engineering and Mechanics
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• v.77 no.3
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• pp.355-368
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• 2021

The time-varying mean (TVM) component of non-stationary wind speeds is commonly extracted utilizing empirical mode decomposition (EMD) in practice, whereas the accuracy of the extracted TVM is difficult to be quantified. To deal with this problem, this paper proposes an approach to identify and extract the optimal TVM from several TVM results obtained by the EMD. It is suggested that the optimal TVM of a 10-min time history of wind speeds should meet both the following conditions: (1) the probability density function (PDF) of fluctuating wind component agrees well with the modified Gaussian function (MGF). At this stage, a coefficient p is newly defined as an evaluation index to quantify the correlation between PDF and MGF. The smaller the p is, the better the derived TVM is; (2) the number of local maxima of obtained optimal TVM within a 10-min time interval is less than 6. The proposed approach is validated by a numerical example, and it is also adopted to extract the optimal TVM from the field measurement records of wind speeds collected during a sandstorm event.