• Journal of the Society of Naval Architects of Korea
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• v.51 no.3
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• pp.193-202
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• 2014

This paper presents a new method of sampling the climatic data for infrared signature analysis. Historical hourly data from a stationary marine buoy of KMA(Korean Meteorological Administration) are used to select a small number of sample points (N=100) to adequately cover the range of statistics(PDF, CDF) displayed by the original data set (S=56,670). The method uses a coarse bin to subdivide the variable space ($3^5$=243 bins) to make sample points cover the original data range, and a single-point ranking system to select individual points so that uniform coverage (1/N = 0.01) is obtained for each variable. The principal component analysis is used to calculate a joint probability of the coupled climatic variables. The selected sample data show good agreement to the original data set in statistical distribution and they will be used for statistical analysis of infrared signature and susceptibility of naval ships.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.12
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• pp.2317-2323
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• 2015

In this paper, we analyze the performance of dual-hop amplify-and-forward (AF) relaying in cooperative networks with partial relay selection. An AF relay gain considered in this paper includes channel-noise-assisted relay gain. Leveraging a received signal-to-noise ratio (SNR) model, we derive exact closed-form expressions for the probability density function (pdf) and cumulative distribution function (cdf) of the end-to-end SNR. Moreover, an exact closed-form expression of the ergodic capacity for dual-hop AF relaying with channel-noise-assisted relay gain and partial relay selection is investigated. The analytical results shown in this paper are confirmed by Monte-Carlo simulations.

• Journal of Korean Society of Transportation
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• v.17 no.5
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• pp.33-42
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• 1999

본 논문은 도로투자 사업성분석시 사업주체의 현금흐름을 결정하는 항목들을 고정값(Deterministic Value)이 아닌 확률적으로 추정함으로써, 사업의 재무적 변동으로 인한 위험도를 민간사업자의 견지에서 사업성분석과정에 내재화하는 모형을 개발하는 것이다. 즉, 확률적 비용추정기법으로 국소적으로 활용되던 위험도분석을 재무모형에 내재화함으로써 사업의 재무적 변동을 보다 포괄적으로 분석할 수 있는 틀을 제공한다. 본 연구에서는 몬테카를로 시뮬레이션기법을 이용한 위험도분석(Risk Analysis)을 적용하여 사업성 평가지표와 비용의 확률밀도함수(Probability Density Function : PDF), 누적확률분포함수(Cumulative Distribution Function : CDF)를 산출하고, 그 결과로 해당 사업의 위험도를 고려하여 사업성을 평가한다. 이 모형은 사업의 모든 변동요인을 복합적으로 추정하여 사업기간 내 사업주체의 현금흐름을 분석할 수 있다. 따라서 사업주체는 효용에 따라 합리적인 위험도 관리 목표값(Target Value)을 선정하고, 사업의 위험도를 고려하여 건설비, 예비비를 결정할 수 있다. 본 연구에서 정립된 모형을 서울외곽순환고속도로(일산-퇴계원 구간)와 대전당진고속도로를 대상으로 사례분석을 수행하였다. 그 결과, 대전당진고속도로의 경우 사업성이 없으며, 서울외곽순환고속도로의 경우, 일부 위험도 발생변수를 합리적으로 관리한다면, 사업성이 충분한 것으로 분석되었다. 본 사례분석은 사업의 위험도를 반영한 사업성분석 방법으로 우리나라 민자유치대상고속도로의 사업성분석의 하나의 지침이 될 것이다.

• Journal of Digital Contents Society
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• v.15 no.1
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• pp.129-136
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• 2014

Wi-Fi fingerprinting system is a very popular positioning method used in indoor spaces. The system depends on Wi-Fi Received Signal Strength (RSS) from Access Points (APs). However, the Wi-Fi RSS is changeable by multipath fading effect and interference due to walls, obstacles and people. Therefore, the Wi-Fi fingerprinting system produces low position accuracy. Also, Wi-Fi signals pass through walls. For this reason, the existing system cannot distinguish users' floor. To solve these problems, this paper proposes a LED fingerprinting system for accurate indoor positioning. The proposed system uses a received optical power from LEDs and LED-Identification (LED-ID) instead of the Wi-Fi RSS. In training phase, we record LED fingerprints in database at each place. In serving phase, we adopt a K-Nearest Neighbor (K-NN) algorithm for comparing existing data and new received data of users. We show that our technique performs in terms of CDF by computer simulation results. From simulation results, the proposed system shows that a positioning accuracy is improved by 8.6 % on average.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.2
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• pp.128-137
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• 2018

In this paper, we propose a novel class separability measure for radar signals. To reduce the sensitivity of the relative aspect angle between a target and radar, to evaluate the discriminatory power of radar signals, the proposed method first calculates the correlation coefficients between two radar cross sections (RCSs) or linearly shifts one-dimensional (1D) radar signals (i.e., high-resolution range profiles (HRRPs)), or rotates two 2D radar signals (i.e., inverse synthetic aperture radar (ISAR) images). Then, it uses the maximum correlation coefficient when two radar signals are best aligned. Next, the proposed method obtains new correlation-based discriminant matrices (CDM) using maximum correlation coefficients. Finally, the cumulative distribution function (CDF) in the CDM and the value corresponding to the specific probability in the CDF are obtained, and this value represents the discriminatory power of the radar signal. Experimental results show that the proposed method can accurately measure the target separability.

• Smart Structures and Systems
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• v.17 no.6
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• pp.1087-1105
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• 2016

Traffic load and volume is one of the most important physical quantities for bridge safety evaluation and maintenance strategies formulation. This paper aims to conduct the statistical analysis of traffic volume information and the multimodal modeling of gross vehicle weight (GVW) based on the monitoring data obtained from the weigh-in-motion (WIM) system instrumented on the arch Jiubao Bridge located in Hangzhou, China. A genetic algorithm (GA)-based mixture parameter estimation approach is developed for derivation of the unknown mixture parameters in mixed distribution models. The statistical analysis of one-year WIM data is firstly performed according to the vehicle type, single axle weight, and GVW. The probability density function (PDF) and cumulative distribution function (CDF) of the GVW data of selected vehicle types are then formulated by use of three kinds of finite mixed distributions (normal, lognormal and Weibull). The mixture parameters are determined by use of the proposed GA-based method. The results indicate that the stochastic properties of the GVW data acquired from the field-instrumented WIM sensors are effectively characterized by the method of finite mixture distributions in conjunction with the proposed GA-based mixture parameter identification algorithm. Moreover, it is revealed that the Weibull mixture distribution is relatively superior in modeling of the WIM data on the basis of the calculated Akaike's information criterion (AIC) values.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.3
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• pp.799-808
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• 2016

To find the pattern of personal data leak incidents and confirm which distribution is suitable for, this paper searched the personal data leak incidents reported by the media from 2011 to 2014. Based on result, this research estimated the statistical distribution using the 'K-S Statistics' and tested the 'Goodness-of-Fit'. As a result, the fact that in 95% significance level, the Poisson & Exponential distribution have high 'Goodness-of-Fit' has been proven quantitatively and, this could find it for major personal data leak incidents to occur 12 times in a year on average. This study can be useful for organizations to predict a loss of personal data leak incidents and information security investments and furthermore, this study can be a data for requirements of the cyber-insurance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.4
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• pp.240-246
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• 2013

In heterogeneous networks, the almost blank subframes (ABS) for inter-cell interference coordination (ICIC), which can be protected from the CCI due to unutilized subframes (i.e., ABS) is proposed. However, the analytical model for ABS-based systems has not been fully studied yet. In this paper, we derive a new analytical model to evaluate the performance of ABS-based systems. In an analytic model, we assume that each carrier in multicarrier systems, such as in OFDMA, is subject to large-scale fading, which is independent of other carriers. As a performance measure, we present the cumulative distribution function (CDF) for the effective SINR. We show the accuracy of the analytical model via simulation results.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.11a
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• pp.349-352
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• 2011

모바일 IPTV는 이동통신망을 이용하여 방송서비스를 제공한다. 이동통신망을 통해 원활하게 방송서비스를 제공하기 위해서는 극복해야 할 기술적인 장벽이 몇 가지 존재한다. 그 중 하나로, 사용자가 기지국과 기지국 사이를 이동하는 경우 통신망은 연속적으로 서비스를 제공하기 위해 상대 기지국에 사용자의 정보를 전달하는 핸드오버 절차가 수행된다. 핸드오버 절차가 수행되면 시간의 지연이 발생하는데, 시간 지연은 방송 품질에 영향을 미칠 수 있다. 따라서 핸드오버의 발생에 따른 성능 분석은 원활한 방송 서비스를 제공하는데 있어 필수적인 과정으로 볼 수 있다. 본 논문은 핸드오버 성능을 분석하기 위하여 기본적인 무선 액세스 네트워크의 기능이 이미 구현되어 있는 NLS(Network-level Simulator)를 이용한 모의실험 방법을 제시한다. 하지만, 성능 분석에 필요한 기능이 모두 NLS에 포함되어 있지는 않다. 따라서 본 논문에서는 NLS 중 하나인 QualNet을 이용하여 핸드오버 성능 분석에 필요한 기능을 구현하는 방법을 예로 설명한다. 성능은 핸드오버 지연시간과 지연시간의 CDF(Cumulative Distribution Function) 로서 나타낸다.

• Journal of the Korean Statistical Society
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• v.32 no.3
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• pp.299-309
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• 2003

Let ${\pi}_1,...,{\pi}_{k}$k($\geq$2) independent logistic populations such that the cumulative distribution function (cdf) of an observation from the population ${\pi}_{i}$ is $$F_{i}\;=\; {\frac{1}{1+exp{-\pi(x-{\mu}_{i})/(\sigma\sqrt{3})}}},\;$\mid$x$\mid$<\;{\infty}$$ where ${\mu}_{i}(-{\infty}\; < \; {\mu}_{i}\; <\; {\infty}$ is unknown location mean and ${\delta}^2$ is known variance, i ＝ 1,..., $textsc{k}$. Let ${\mu}_{[k]}$ be the largest of all ${\mu}$'s and the population ${\pi}_{i}$ is defined to be 'good' if ${\mu}_{i}\;{\geq}\;{\mu}_{[k]}\;-\;{\delta}_1$, where ${\delta}_1\;>\;0$, i = 1,...,$textsc{k}$. A selection procedure based on sample median is proposed to select a subset of $textsc{k}$ logistic populations which includes all the good populations with probability at least $P^{*}$(a preassigned value). Simultaneous confidence intervals for the differences of location parameters, which can be derived with the help of proposed procedures, are discussed. If a population with location parameter ${\mu}_{i}\;<\;{\mu}_{[k]}\;-\;{\delta}_2({\delta}_2\;>{\delta}_1)$, i ＝ 1,...,$textsc{k}$ is considered 'bad', a selection procedure is proposed so that the probability of either selecting a bad population or omitting a good population is at most 1­ $P^{*}$.