• Journal of the military operations research society of Korea
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• v.22 no.2
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• pp.166-181
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• 1996

Aircraft survivability is determined by the susceptibility and the vulnerability. The aircraft susceptibility and vulnerability depend upon the hardware and software factors. Each of the hardware and software factors consisted of the qualitative and quantitative attributes varies according to the time of the mission. In order to establish the mathermatical model to analyze and evaluate the aircraft survivability, qualitative factors have to be transformed into quantitative factors. Even if many researches in the area of dynamic concept analysis and conversion of qualitative factors into the quantitative factors has been insufficient. This research enhances these insufficient area by developing a reliable aircarft survivability analysis method. The major areas of this research are as follows. First, a method for the conversion of the qualitative factors into the quantitative factors is developed by combining the Fuzzy Set Theory concept and the Delphi Technique. Second, by using the stochastic network diagram for the dynamic survivability analysis, the aircraft survivability and the probability of kill are calculated from the state probability for the situation during mission. The advantage of the analysis technique developed in this research includes ease of use and flexibility. In other words, in any given aircraft's mission execution under any variable probability density function, the developed computer program is able to analyze and evaluate the aircraft survivability.

• Journal of Korean Society of Transportation
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• v.27 no.6
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• pp.167-176
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• 2009

Several travel demand management schemes have been used for controlling overloaded traffics on urban area. To maximize efficiency of the travel management, traffic manager has to set target level that we try to arrive in advance, and then to find optimal variable to attain this goal. In this regard, this paper presents two travel demand management models, expressed by mathematical program, and also presents their solution algorithms. The first is to find optimal travel demand for origin-destination (OD) pair, based on average travel time between the OD pair, and the second is based on the ratio of volume over capacity on congested area. An example is given to test the models.

• Water for future
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• v.27 no.2
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• pp.129-137
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• 1994

The surface hydrology of large land areas is susceptible to several preferred stable states with transitions between stable states induced y stochastic fluctuation. This comes about due to the close coupling of land surface and atmospheric interaction. An interesting and important issue is the duration of residence in each mode. Mean transtion times between the stable modes are analyzed for different model parameters or climatic types. In an example situation of this differential equation exhibits a bimodal probability distribution of soil moisture states. Uncertainty analysis regarding the model parameters is performed using a Monte-Carlo simulation method. The method developed in this research may reveal some important characteristics of soil moisture or precipitation over a large area, in particular, those relating to abrupt changes in soil moisture or precipitation having extremely variable duration.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.2
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• pp.59.1-59.1
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• 2011

I present an analysis of the long-term evolution of the fluxes of six active galactic nuclei (AGN) - 0923+392, 3C 111, 3C 273, 3C 345, 3C 454.3, and 3C 84 - in the frequency range 80 - 267 GHz using archival calibration data of the IRAM Plateau de Bure Interferometer. Our dataset spans a long timeline of ~14 years with 974 - 3027 flux measurements per source. We find strong (factors ~2-8) flux variability on timescales of years for all sources. The flux density distributions of five out of six sources show clear signatures of bi- or even multimodality. Our sources show mostly steep (alpha~0.5-1), variable spectral indices that indicate outflow dominated emission; the variability is most probably due to optical depth variations. The power spectra globally correspond to red-noise spectra with five sources being located between the cases of white and flicker noise and one source (3C 111) being closer to the case of random walk noise. For three sources the low-frequency ends of their power spectra appear to be upscaled in spectral power by factors ~2-3 with respect to the overall powerlaws. We conclude that the source emission cannot be described by uniform stochastic emission processes; instead, a distinction of "quiescent" and (maybe multiple) "flare" states of the source emission appears to be necessary.

• Journal of the Korea Society of Computer and Information
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• v.8 no.1
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• pp.156-165
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• 2003

The purpose of this study is concerned with possibilistic decision making model (PDMM) that can be used to help CEO and information systems managers decide which information systems should be selected. The application of IT which has influence on rapidly changed environment of enterprise plays an important role in enterprise's activity. When enterprise outsource IT, it is very important to select vendors that reflect goals and constraints of organization. For this purpose, mathematical model in which possibilistic programming is applied is suggested in this study. Although many researches have conducted in conventional programming and stochastic programming. they are still limited in solving practical problems and imprecise/uncertain situations. Multiple decision making model in which impreciseness of input variable is considered can be constructed in PDMM.

• Journal of Communications and Networks
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• v.18 no.3
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• pp.340-350
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• 2016

The performance of large-scale cognitive radio (CR) networks with secondary users sustained by opportunistically harvesting radio-frequency (RF) energy from nearby primary transmissions is investigated. Using an advanced RF energy harvester, a secondary user is assumed to be able to collect ambient primary RF energy as long as it lies inside the harvesting zone of an active primary transmitter (PT). A variable power (VP) transmission mode is proposed, and an energy-based opportunistic spectrum access (OSA) strategy is considered, under which a secondary transmitter (ST) is allowed to transmit only if its harvested energy is larger than a predefined transmission threshold and it is outside the guard zones of all active PTs. The transmission probability of the STs is derived. The outage probabilities and the throughputs of the primary and the secondary networks, respectively, are characterized. Compared with prior work, the throughput can be increased by as much as 29%. The energy-based OSA strategy can be generally applied to a non-CR setup, where distributed power beacons (PBs) are deployed to power coexisting wireless signal transmitters (WSTs) in a wireless powered sensor network.

• Industrial Engineering and Management Systems
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• v.1 no.1
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• pp.87-92
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• 2002

A stochastic process {$A_n$, n = 1, 2, ...} is an arithmetic process (AP) if there exists some real number, d, so that {$A_n$ + (n-1)d, n =1, 2, ...} is a renewal process (RP). AP is a stochastically monotonic process and can be used for modeling a point process, i.e. point events occurring in a haphazard way in time (or space), especially with a trend. For example, the vents may be failures arising from a deteriorating machine; and such a series of failures id distributed haphazardly along a time continuum. In this paper, we discuss estimation procedures for an AP, similar to those for a geometric process (GP) proposed by Lam (1992). Two statistics are suggested for testing whether a given process is an AP. If this is so, we can estimate the parameters d, ${\mu}_{A1}$ and ${\sigma}^{2}_{A1}$ of the AP based on the techniques of simple linear regression, where ${\mu}_{A1}$ and ${\sigma}^2_{A1}$ are the mean and variance of the first random variable $A_1$ respectively. In this paper, the procedures are, for the most part, discussed in reliability terminology. Of course, the methods are valid in any area of application, in which case they should be interpreted accordingly.

• Structural Engineering and Mechanics
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• v.34 no.1
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• pp.15-38
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• 2010

In order to predict the shear strengths of reinforced concrete beams, many deterministic models have been developed based on rules of mechanics and on experimental test results. While the constant and variable angle truss models are known to provide reliable bases and to give reasonable predictions for the shear strengths of members with shear reinforcement, in the case of members without shear reinforcement, even advanced models with complicated procedures may show lack of accuracy or lead to fairly different predictions from other similar models. For this reason, many research efforts have been made for more accurate predictions, which resulted in important recent publications. This paper develops probabilistic shear strength models for reinforced concrete beams without shear reinforcement based on deterministic shear strength models, understanding of shear transfer mechanisms and influential parameters, and experimental test results reported in the literature. Using a Bayesian parameter estimation method, the biases of base deterministic models are identified as algebraic functions of input parameters and the errors of the developed models remaining after the bias-correction are quantified in a stochastic manner. The proposed probabilistic models predict the shear strengths with improved accuracy and help incorporate the model uncertainties into vulnerability estimations and risk-quantified designs.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.34 no.2
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• pp.41-48
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• 2018

Carbonation is one of the major detrimental factors to the reinforced concrete structures owing to penetration of atmospheric CO2 through the micro pores, thereby it reduces the durability of the concrete. The maintenance periods and cost for concrete according to the coefficient variation of different finishing materials is documented in literature. However, it is required to carry out the systematic and well planned studies. Therefore, keeping them in mind, surface repair was carried out to the carbonated concrete and the maintenance cost was calculated to measure the durability life after repair with different variable. The deterministic and probabilistic methods were applied for durability and repair cost of the concrete. In the existing deterministic model, the cost of repair materials increases significantly when the concrete structure reaches its service life. In present study using a stochastic model, the maintenance period and cost was evaluated. According to obtained results, there was no significant difference in the number of maintenance of the coefficient variation. The initial durability has a great influence on the maintenance time and cost of the structure. Unlike the deterministic model, the probabilistic cost estimating model reduces the number of maintenance to the target service life expectancy.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.208-208
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• 2020

지구온난화와 하천환경의 변화로 수질 오염이 심각해지고 녹조 현상 등의 피해가 증가하고 있다. 특히, 기후변화로 인해 온도와 강우량의 변동성이 동시에 증가하고 있어 하천의 수환경 관리측면에서 어려움이 증가하고 있다. 최근 하천 개발 사업으로 인한 인공 구조물 축조로 하천의 오염도 변화는 중요한 논점으로 대두되었으며, 그에 따라 정확한 수질 전망이 요구되고 있다. 녹조평가에 있어 주요 대리변수(proxy variable)로 chlorophyll-a(Chl-a)가 사용되고 있지만, Chl-a는 규조류와 남조류(cyanobacteria) 모두에서 발견되는 지표로서, 녹조의 유해성을 Chl-a 수질 지표만을 사용하여 판단하기에는 한계가 있다. Chl-a뿐만 아니라 수질에 대한 유량, 온도, 영양염류 등의 영향 또한 기존 연구에서 밝혀진 바 있다. 하지만 기존의 물리기반의 결정론적모형은 수질의 추계학적(stochastic) 특성을 반영하는데 제한적이며, 다양한 수문기상학적 조건을 고려한 시나리오 기반의 분석을 수행하는데 한계가 있다. 따라서 본 연구에서는 특정 지점의 보 건설 이후 수문기상 자료를 이용하여 유해 남조류 개체수와 관계있는 수문기상학적 요인을 평가하고 최종적으로 Bayesian Poisson Regression 기반의 중·장기 녹조 예측 모형을 개발하였으며, 해설결과에 대한 불확실성 정보도 제공할 수 있도록 하였다.