• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.5
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• pp.69-76
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• 2016

In this paper, we investigate the system performance of a cooperative relaying system of Non-orthogonal multiple access (NOMA) with successive interference cancellation (SIC), which is considered promising application in fifth generation (5G) cellular networks. Previous studies have focused on the selected relays, however we include the maxmin relay selection and derive analytical outage probability of opportunistic incremental relaying systems. For the realistic mobile environment, the distributions of relays are modeled as a homogeneous Poisson point process (PPP). And maximal ratio combining (MRC) is adapted to improve the system performance at the destination node. Analytical results demonstrate the outage probability improves with the near/far user power ratio, and the cooperative relaying scheme can achieve low outage probability in comparison to the no relaying scheme. It is also conformed that the increase of the intensity of PPP cause higher gains of the spacial diversity and hence the performance improves.

• Journal of Ecology and Environment
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• v.38 no.1
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• pp.15-23
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• 2015

This study was conducted in an effort to provide important clues pertaining to the conservation and restoration of Aporia crataegi by identifying the spatial distribution characteristics of the current habitats, prospective habitats, and future habitats of A. crataegi in accordance with climate changes. To determine the distribution of A. crataegi, data from a total of 36 collecting points throughout South Korea, North Korea, China, Japan, Mongolia, and Russia are used. The spatial distributions of the data were examined through MaxEnt modeling. The distribution probability rates exceeded 75% at 18 locations among the 36 species occurrence locations, with Gangwon province showing the highest distribution probability in South Korea. The precision of the MaxEnt model was remarkably high, with an AUC value of 0.982. The variables that affect the potential distribution of A. crataegi by more than 10% are the degree of temperature seasonality, the amount of precipitation in the warmest quarter, the annual mean temperature, and the amount of precipitation in the driest month, in that order of importance. It was found that the future potential distribution area of A. crataegi continuously moves northward over time up to 2070s. In addition, the area of the potential distribution showing a habitable probability rate that exceeds 75% in northeast Asia was $28,492km^2$, where the area of potential distribution in the north part of Korean peninsula was $20.404km^2$ in size. Thus, it is anticipated that the most important future habitats of A. crataegi in the northeast Asia will be North and South Hamgyeong provinces and Ryanggang province near Mt. Baekdoosan in the northern area of the Korean peninsula.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.25 no.3
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• pp.227-235
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• 2012

The void distribution in concrete materials strongly affects its material properties. Therefore, the identification of spatial distribution of void is important to understand and estimate material behavior. To examine and quantify the void distribution inside lightweight aggregates, CT(computed tomography) image is used. 3D lightweight aggregate images are generated by stacking of cross-sectional images from CT. Spatial distribution of void of aggregate along the direction is visualized on the sphere using probability distribution function. Stiffness of lightweight aggregate for the directions is also examined. It is confirmed that direction-based probability distribution and stiffness from CT images are effective in characterizing void distributions of aggregates.

• Journal of the Earthquake Engineering Society of Korea
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• v.20 no.5
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• pp.341-349
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• 2016

Currently, researches are being actively conducted in assessing seismic performance of nuclear facilities in USA and Europe. In particular, applying this technique of assessing seismic performance to design of isolation systems in nuclear power plants is being performed and then ASCE 4 Draft (2013) is being revised accordingly in the United States. In order to satisfy the probabilistic performance objectives described by seismic responses with certain confidence levels (ASCE 43, 2005), the probability distributions of these responses have to be defined. What is the minimum number of input ground-motions to obtain the probability distribution precise enough to represent the unknown actual distribution? Theoretical basis, for how to determine the minimum number of input ground-motions for given a logarithmic standard deviation to approximate the unknown actual median of the log-normal distribution within a range of error at a certain level of confidence, is introduced by Huang et al. (2008). However, the relationship between the level of confidence and the range of error is not stated in the previous study. In this paper, based on careful reviews on the previous work, the relationship between the level of confidence and the range of error is logically and explicitly stated. Furthermore, this relationship is also applied to derive the minimum number of input ground-motions in order to approximate the unknown actual logarithmic standard deviation. Several recommendations are made for determining the minimum number of input ground-motions in probabilistic assessment on seismic performance of facilities in nuclear power plants.

• Journal of the Korea Institute of Building Construction
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• v.17 no.3
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• pp.287-294
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• 2017

Recently the construction project is becoming large-sized, complicated, and modernize. This has increased the uncertainty of construction risk. Therefore, studies should be followed regarding scientifically identifying the risk factors, quantifying the frequency and severity of risk factors in order to develop a model that can quantitatively evaluate and manage the risk for response the increased risk in construction. To address the problem, this study analyze the probability distribution of risk causes, the probability of occurrence and frequency of the specific risk level through Monte Carlo simulation method based on the accident data caused at construction sites. In the end, this study derives quantitative analysis by analyzing the amount of risk and probability distributions of accident causes. The results of this study will be a basis for future quantitative risk management models and risk management research.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3A
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• pp.189-197
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• 2009

In this study, truck weight data and load effects of single truck on bridges are analyzed for development of new vehicular load model of the reliability-based bridge design code. Rational load model and statistical properties of loads are important for developing reliability-based design code. In this study, truck weight data collected at four locations are used as well as data from four locations in other studies. Truck weight data are collected from WIM or BWIM system, which are known to give reliable data. Typical truck types, dimensions and axle weight distribution are determined. Probability distributions of upper 20% total truck weight are assumed as Extreme Type I and 100 years maximum truck weights are estimated by linear regression on the probability paper. The load effects of trucks having estimated maximum weights are analyzed for span length from 10 m to 200 m.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.25 no.5
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• pp.317-326
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• 2013

Probabilistic design methods can consider uncertainties of design variables and are widely used in the design of vertical breakwaters. The probabilistic design methods include a partial safety factor method, reliabilitybased design method, and performance-based design method. Especially the performance-based design method calculates the accumulated sliding distance during the lifetime of the breakwater or during a design storm. Recently a time-dependent performance-based design method has been developed based on the first-passage probability of individual sliding distance during a design storm. However, because the allowable criteria in the first-passage probability method are not established, the stability of structures cannot be quantitatively evaluated. In this study, the allowable first-passage probabilities for two limit states are proposed by calculating the first-passage probabilities for the cross-sections designed with various water depths and characteristics of extreme wave height distributions. The allowable first-passage probabilities are proposed as 5% and 1%, respectively, for the repairable limit state (allowable individual sliding distance of 0.03 m) and ultimate limit state (allowable individual sliding distance of 0.1 m). The proposed criteria are applied to the evaluation of the effect of wave-height increase due to climate change on the stability of the breakwater.

• Journal of Korean Society of Transportation
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• v.24 no.6 s.92
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• pp.33-43
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• 2006

This research is to the selection of optimal probability distribution as well as the estimation for design hourly factor in consideration of traffic characteristic, such as road function, lane number and AADT. To accomplish the objectives, we are applied to various probability distribution using traffic data that observed at permanent traffic count points in 2005. The parameters or the selected 14 probability distribution were estimated based on the method of maximum likelihood and the validity condition of the estimated parameter The goodness-of-fit test, such as chi-square test. was performed as well as the estimation of design hourly factor. As a result, An appropriate distributions of each case were selected : Pearson V for two lane of rural roads, LogLogistic for the four lane of rural roads, LogLogistic for the urban roads, Extreme value for recreation roads. And optimal K factor are as following : $0.1{\sim}0.2 $ for two lane of rural roads, $0.09{\sim}0.14$ for the four lane of rural roads. $0.07{\sim}0.13$ for the urban roads, $0.1{\sim}0.2$ for recreation roads.

• Journal of Navigation and Port Research
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• v.43 no.3
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• pp.186-196
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• 2019

Berthing energy is majorly influenced by the berthing velocity. It is necessary to design an appropriate berthing velocity for each pier, since excessive berthing velocity can cause berthing accident causing damage to the ship and pier. In this study, as a statistical approach for berthing velocity, the probability distributions suitable for the berthing velocities were confirmed using the K-S test, the A-D test and the Q-Q plot. As a result, the frequency distribution of the berthing velocity was found to be suitable using the Weibull distribution as well as the lognormal distribution. Additionally, the predicted values obtained through estimation of the berthing velocity using the concept of probability of exceedance in this study is proposed as a reference of design berthing velocity. It can be observed that the design berthing velocity is set to be somewhat low so that it does not practically match with the reality. This study and its results can be expected to contribute to the development of a proper design velocity calculation method.

• Journal of the military operations research society of Korea
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• v.6 no.2
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• pp.129-149
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• 1980

In medical follow-up, equipment lifetesting, various military situations, and other fields, one often desires to calculate survival probability as a function of time, p(t). If the observer is able to record the time of occurrence of the event of interest (called a 'death'), then an empirical, non-parametric estimate may simply by obtained from the fraction of survivors after various elapsed times. The estimation is more complicated when the data are truncated, i.e., when the observer loses track of some individuals before death occurs. The product-limit method of Kaplan and Meier is one way of estimating p(t) when the mechanism causing truncation is independent of the mechanism causing death. This paper proposes jackknife estimators of logistic trans-formation and compares it to the product-limit method. A computer simulation is used to generate the times of death and truncation from a variety of assumed distributions.