• Journal of Communications and Networks
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• 제14권5호
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• pp.566-577
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• 2012

In randomly deployed networks, such as sensor networks, an important problem for each node is to discover its neighbor nodes so that the connectivity amongst nodes can be established. In this paper, we consider this problem by incorporating the physical layer parameters in contrast to the most of the previous work which assumed a collision channel. Specifically, the pilot signals that nodes transmit are successfully decoded if the strength of the received signal relative to the interference is sufficiently high. Thus, each node must extract signal parameter information from the superposition of an unknown number of received signals. This problem falls naturally in the purview of random set theory (RST) which generalizes standard probability theory by assigning sets, rather than values, to random outcomes. The contributions in the paper are twofold: First, we introduce the realistic effect of physical layer considerations in the evaluation of the performance of logical discovery algorithms; such an introduction is necessary for the accurate assessment of how an algorithm performs. Secondly, given the double uncertainty of the environment (that is, the lack of knowledge of the number of neighbors along with the lack of knowledge of the individual signal parameters), we adopt the viewpoint of RST and demonstrate its advantage relative to classical matched filter detection method.

• Journal of Power Electronics
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• 제11권5호
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• pp.719-725
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• 2011

This paper describes a novel Direct Torque Control (DTC) method for adjustable speed Doubly-Fed Induction Machine (DFIM) drives which is supplied by a two-level Space Vector Modulation (SVM) voltage source inverter (DTC-SVM) in the rotor circuit. The inverter reference voltage vector is obtained by using input-output feedback linearization control and a DFIM model in the stator a-b axes reference frame with stator currents and rotor fluxes as state variables. Moreover, to make this nonlinear controller stable and robust to most varying electrical parameter uncertainties, a two layer recurrent Artificial Neural Network (ANN) is used to estimate a certain function which shows the machine lumped uncertainty. The overall system stability is proved by the Lyapunov theorem. It is shown that the torque and flux tracking errors as well as the updated weights of the ANN are uniformly ultimately bounded. Finally, effectiveness of the proposed control approach is shown by computer simulation results.

• 한국농공학회논문집
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• 제54권3호
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• pp.55-63
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• 2012

Soil properties are not random values which is represented by mean and standard deviation but show spatial correlation. Especially, soils are highly variable in their properties and rarely homogeneous. Thus, the accuracy and reliability of probabilistic analysis results is decreased when using only one random variable as design parameter. In this paper, to consider spatial variability of soil property, one-dimensional random fields of coefficient of consolidation ($C_v$) were generated based on a Karhunen-Loeve expansion. A Latin hypercube Monte Calro simulation coupled with finite difference method for Terzaghi's one dimensional consolidation theory was then used to probabilistic analysis. The results show that the failure probability is smaller when consider spatial variability of $C_v$ than not considered and the failure probability increased when the autocorrelation distance increased. Thus, the uncertainty of soil can be overestimated when spatial variability of soil property is not considered, and therefore, to perform a more accurate probabilistic analysis, spatial variability of soil property needed to be considered.

• 한국안전학회지
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• 제29권1호
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• pp.1-6
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• 2014

With increasing number of citizen using subway stations everyday, safety, health and comfort of passengers and occupants became an important social issue. Considering the fact that various physical variables and pollutants are related to indoor air quality (IAQ) which may cause health problem, IAQ need to be closely monitored and controlled in multiple locations in subway stations. This study is a continuation of the previous studies and delay induced in wireless-wired network is experimentally evaluated and the risk involved is assessed. In doing that, a key parameter is identified to be the network delay in different network media. Application of information-theoretic measure to assess the risk in network delay is then discussed. The idea is based on the general principles of engineering design and their applications to quantification of uncertainty in network delay. Experimental results show that more risk is involved in wireless data communication. Efficient and fast conversion of transmission data in both LonWorks/IP server and ZL converter is also noted.

• 한국임상수의학회지
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• 제32권4호
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• pp.319-323
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• 2015

The performance of diagnostic test accuracy is usually summarized by a variety of statistics such as sensitivity, specificity, predictive value, likelihood ratio, and kappa. These indices are most commonly presented when evaluations of competing diagnostic tests are reported, and it is of utmost importance to compare the accuracies of diagnostic tests to decide on the best available test for certain medical disorder. However, it is important to emphasize that specific point values of these indices are merely estimates. If parameter estimates are reported without a measure of uncertainty (precision), knowledgeable readers cannot know the range within which the true values of the indices are likely to lie. Therefore, when evaluations of diagnostic accuracy are reported the precision of estimates should be stated in parallel. To reflect the precision of any estimate of a diagnostic performance characteristic or of the difference between performance characteristics, the computation of confidential interval (CI), an indicator of precision, is widely used in medical literatures in that CIs are more informative to interpret test results than the simple point estimates. The majority of peer-reviewed journals usually require CIs to be specified for descriptive estimates, whereas domestic veterinary journals seem less vigilant on this issues. This paper describes how to calculate the indices and associated CIs using practical examples when assessing diagnostic test performance.

• 한국멀티미디어학회논문지
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• 제11권4호
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• pp.462-470
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• 2008

본 논문은 저대비에 의한 영상 정보의 불확실성이 화소가 가지고 있는 명암도의 모호성과 애매성에 근거한다는 점에서 퍼지 변환 함수를 적용하여 영상 향상을 기하고자 한다. 명암도 분포가 한쪽으로 치우친 저대비 영상의 문제를 해결하고자 k-means 알고리즘을 사용하여 물체와 배경을 구분할 수 있는 자동 임계점을 찾고 이를 기준으로 영상의 밝은 부분과 어두운 부분의 대비 향상을 가져올 수 있도록 퍼지 변환 함수를 적용한다. 퍼지 변환 함수는 영상 향상을 위해 3단계-입력 영상을 퍼지 영역으로 변환시키는 퍼지화 단계와 대비를 향상시키는 대비 강화 단계 그리고 퍼지 영역을 다시 영상 영역으로 변환시키는 비퍼지화 단계로 제시된다. 향상된 영상의 성능을 평가하고자 퍼지성 지수와 엔트로피 지수를 제시하여 이를 히스토그램 균등화 기법과 비교하고 실험결과로 성능의 우수함을 보여준다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2015년도 학술발표회
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• pp.19-19
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• 2015

최근 기후변화로 인해 집중호우 및 게릴라성 폭우의 발생빈도가 증가하고 있다. 또한, 도시화 및 산업화로 인해 불투수지역이 증가하여 첨두강우의 도달시간은 짧아지고, 강우강도는 증가하는 현상을 보이고 있다. 이로 인해 도시유역에서는 우수관의 통수능 부족으로 인한 홍수가 빈번히 발생하고 있다. 본 연구에서는 EPA-SWMM User's manual에서 제공하는 예제 관망도를 이용하여 SWMM 모형 매개변수들 간의 상관관계 분석을 수행하였다. 사전 조사 및 분석을 통해 유역폭, 관조도계수, 불투수유역 조도계수, 투수유역 조도계수, 불투수면적 비율 등 총 5개의 매개변수를 분석 대상으로 선정하였다. 매개변수들 간의 상관관계를 분석한 결과 유역폭-관조도계수, 유역폭불투수유역조도계수, 불투수면저 비율-투수유역 조도계수가 양의 기울기를 가지는 1차 선형함수 형태를 보였다. 즉, 예로 유역폭이 증가하면 관조도계수 또한 증가하는 경향을 보였다. 반대로 유역폭-불투수면적비율, 불투수유역 조도계수-관조도계수의 경우 음의 기울기를 가지는 상관관계를 보였으며 특히, 유역폭-불투수면적비율의 경우 2차 회귀곡선을 가지는 감소경향을 보였다. 본 연구의 결과를 활용하여 향후 우수관 설계를 수행한다면 내수침수 저감에 실무적인 도움을 줄 수 있을 것으로 판단된다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2015년도 학술발표회
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• pp.454-454
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• 2015

본 연구에서는 댐 유역의 설계홍수량을 산정할 시 발생할 수 있는 대표 매개변수의 불확실성에 대하여 분석하였다. 설계홍수량 산정 방법으로는 국내에서 가장 일반적으로 활용되고 있는 강우-유출모형 중 Clark 단위도를 활용하여 확률강우량을 동일 빈도의 홍수량으로 변환하는 방식을 적용하였다. 대상 유역으로는 수문학적 안전성평가가 수행된 국내 댐 유역 중 비교적 실측 호우사상 자료 수가 많은 3개 유역을 선정하였다. 또한 단위도 매개변수 결정 시 자료의 부족으로 최적화 매개변수에 대한 신뢰도 문제가 발생할 수 있으므로 가용 자료수가 증가함에 따른 불확실성의 영향을 분석하기 위해 대상 유역 간의 시간응답 특성을 분석하였다. 이를 통해 상사성이 있는 것으로 판단되는 유역의 호우사상 매개변수를 통합하여 무차원화된 저류상수 $K_x$를 구하였다. 이 $K_x$값을 표준정규분포로 변환하고 Monte Carlo Simulation을 통해 난수를 발생시켜 100개의 무차원 저류상수 $K_x$를 산정하였다. 이 값을 사용하여 설계홍수량을 산정하기 위한 대표 매개변수의 불확실성 분석을 실시하였다. 그 결과 상사성이 있는 것으로 판별된 유역의 호우사상을 통합하는 경우 양질의 호우사상을 다수 확보하고 있는 유역이 추가되면 홍수량 산정결과가 개선되는 것으로 나타났다.

• Nuclear Engineering and Technology
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• 제53권10호
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• pp.3359-3366
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• 2021

An engineered barrier system (EBS) for the deep geological disposal of high-level radioactive waste (HLW) is composed of a disposal canister, buffer material, gap-filling material, and backfill material. As the buffer fills the empty space between the disposal canisters and the near-field rock mass, heat energy from the canisters is released to the surrounding buffer material. It is vital that this heat energy is rapidly dissipated to the near-field rock mass, and thus the thermal conductivity of the buffer is a key parameter to consider when evaluating the safety of the overall disposal system. Therefore, to take into consideration the sizeable amount of heat being released from such canisters, this study investigated the thermal conductivity of Korean compacted bentonites and its variation within a temperature range of 25 ℃ to 80-90 ℃. As a result, thermal conductivity increased by 5-20% as the temperature increased. Furthermore, temperature had a greater effect under higher degrees of saturation and a lower impact under higher dry densities. This study also conducted a regression analysis with 147 sets of data to estimate the thermal conductivity of the compacted bentonite considering the initial dry density, water content, and variations in temperature. Furthermore, the Kriging method was adopted to establish an uncertainty metamodel of thermal conductivity to verify the regression model. The R² value of the regression model was 0.925, and the regression model and metamodel showed similar results.

• Structural Engineering and Mechanics
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• 제69권4호
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• pp.361-369
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• 2019

The determination of Paris' law parameters based on crack growth experiments is an important procedure of fatigue life assessment. However, it is a challenging task because it involves various sources of uncertainty. This paper proposes a novel probabilistic method, termed the S-N Paris law (SNPL) method, to quantify the uncertainties underlying the Paris' law parameters, by finding the best estimates of their statistical parameters from the S-N curve data using a Bayesian approach. Through a series of steps, the SNPL method determines the statistical parameters (e.g., mean and standard deviation) of the Paris' law parameters that will maximize the likelihood of observing the given S-N data. Because the SNPL method is based on a Bayesian approach, the prior statistical parameters can be updated when additional S-N test data are available. Thus, information on the Paris' law parameters can be obtained with greater reliability. The proposed method is tested by applying it to S-N curves of 40H steel and 20G steel, and the corresponding analysis results are in good agreement with the experimental observations.