• 한국지반공학회지:지반
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• 제5권2호
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• pp.33-44
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• 1989

본 논문에서는 지진하중시에 원자력구조물에 발생되는 지반-원자력 구조물의 확률론적 동적상호작용에 대하여 연구하였다. 상호작용 해석에는 주파수 영역에서 해석하는 Complex Response Method 를 사용하였으며, 지반의 Near Field 해석에는 유한요소법을 또한 Far Field의 고려에는 여러 전달 경계방법중 무한요소를 형성하여 해석을 수행하였다. 특히 구조들 하부의 지반의 무작위성을고려하 기 위하여 비확정론적 해석방법을 수행하였다. 지반의 제반 Parameter들의 불확정성이 구조물의 거 동에 미치는 영향을 조사하기 위하여 민감도 해석을 수행하였으며, 비확정론적 해석방법으로는 Perturbation 방법과 Rosenblueth의 Tlvo-point Estimate 방법 각각을 이용하여 프로그램을 개발하 였으며 두 방법의 결과에 대한 비교 검토를 하였다. 민감도 해석 결과 지반의 불확정성이 구조물의 거동에 상당히 큰 영향을 미치게 됨을 알 수 있었으며, 상기한 두 방법에 의한 예제해석 결과가 만 족할 만큼 일치하는 결과를 보임을 알 수 있었다.

• 한국대기환경학회지
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• 제13권6호
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• pp.463-474
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• 1997

Metallic elements in dustfall have been known as notable air pollutants directly or indirectly influencing human health and wealth. The first aim of this study was to obtain precise spatial distribution patterns of 5 elements (Pb, Zn, K, Cr, and Al) in dustfall around Suwon area. To predict isometric lines of metal fluxes deposited on unsupervised random sites, the study has applied both spatial statistics as a receptor model and a GIS (geographic information system). Total of 31 sampling sites were selected in the study area (roughly 3 by 3 km grid basis) and dustfall samples were then collected monthly basis by the British deposit gauges from Dec., 1995 to Nov., 1996. The metallic elements in the dustfall were then analyzed by an atomic absorption spectrometer (AAS). On the other hand, a base map overlapped by 7 layers was constructed by using the AutoCAD R13 and ARC/INFO 3.4D. Four different spatial interpolation and expolation techniques such as IDW (inverse distance weighted averaging), TIN (triangulated irregular network), polynomial regression, and kriging technique were examined to compare spatial distribution patterns. Each pattern obtained by each technique was substantally different as varing pollutant types, land of use types, and topological conditions, etc. Thus, our study focused intensively on uncertainty analysis based on a concept of the jackknife and the sum of error distance. It was found that a kriging technique was the best applicalbe in this study area.

• 한국멀티미디어학회논문지
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• 제17권10호
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• pp.1160-1170
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• 2014

Clustering methods are very useful in many fields such as data mining, classification, and object recognition. Both the supervised and unsupervised grouping approaches can classify a series of sample data with a predefined or automatically assigned cluster number. However, there is no constraint on the number of elements for each cluster. Numbers of cluster members for each cluster obtained from clustering schemes are usually random. Thus, some clusters possess a large number of elements whereas others only have a few members. In some areas such as logistics management, a fixed number of members are preferred for each cluster or logistic center. Consequently, it is necessary to design a clustering method that can automatically adjust the number of group elements. In this paper, a k-means based clustering method with a fixed number of cluster members is proposed. In the proposed method, first, the data samples are clustered using the k-means algorithm. Then, the number of group elements is adjusted by employing a greedy strategy. Experimental results demonstrate that the proposed clustering scheme can classify data samples efficiently for a fixed number of cluster members.

• 한국군사과학기술학회지
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• 제23권6호
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• pp.533-541
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• 2020

This study using ABAQUS investigates the nonlinear vibration responses when thermal and random acoustic loads are applied simultaneously to the stiffened composite panels. The nonlinear vibration analyses are performed with changing the number of stiffeners, and layup condition of the skin panel. The panel and stiffeners both are modeled using shell elements. Thermal load (ΔT) is assumed to have the temperature gradient through the thickness direction of the stiffened composite panel. The random acoustic load is represented as stationary white-Gaussian random pressure with zero mean and uniform magnitude over the panels. The thermal postbuckling analysis is conducted using RIKS method, and the nonlinear dynamic analysis is performed using Hilber-HughesTaylor time integration method. When ΔT = 25.18 ℃ and SPL = 105 dB are applied to the stiffened composite panel, the effect of the number of stiffener is investigated, and the snap-through responses are observed for composite panels without stiffeners and with 1 and 3 stiffeners. For investigation of the effect of layup condition of the skin panel, when ΔT = 38.53 ℃ and SPL = 110 dB are applied to the stiffened composite panel, the snap-through responses are shown when the fiber angle of the skin panel is 0°, 30°, and 60°.

• 한국물환경학회지
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• 제35권5호
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• pp.432-438
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• 2019

The purpose of this study is to predict Trophic Diatom Index (TDI) in tributaries of the Han River watershed using the random forest algorithm. The one year (2017) and supplied aquatic ecology health data were used. The data includes water quality(BOD, T-N, $NH_3-N$, T-P, $PO_4-P$, water temperature, DO, pH, conductivity, turbidity), hydraulic factors(water width, average water depth, average velocity of water), and TDI score. Seven factors including water temperature, BOD, T-N, $NH_3-N$, T-P, $PO_4-P$, and average water depth are selected by the Correlation Feature Selection. A TDI prediction model was generated by random forest using the seven factors. To evaluate this model, 2017 data set was used first. As a result of the evaluation, $R^2$, % Difference, NSE(Nash-Sutcliffe Efficiency), RMSE(Root Mean Square Error) and accuracy rate show that this model is compatible with predicting TDI. To be more concrete, $R^2$ is 0.93, % Difference is -0.37, NSE is 0.89, RMSE is 8.22 and accuracy rate is 70.4%. Also, additional evaluation using data set more than 17 times the measured point was performed. The results were similar when the 2017 data set were used. The Wilcoxon Signed Ranks Test shows there was no statistically significant difference between actual and predicted data for the 2017 data set. These results can specify the elements which probably affect aquatic ecology health. Also, these will provide direction relative to water quality management for a watershed that must be continuously preserved.

• Structural Engineering and Mechanics
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• 제80권6호
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• pp.645-655
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• 2021

Performance-based reliability analysis is a practical approach to investigate the seismic performance and stochastic nonlinear response of structures considering a random process. This is significant due to the uncertainties involved in every aspect of the analysis. Therefore, the present study aims to evaluate the performance-based reliability within a stochastic finite element (FE) framework for reinforced concrete (RC) shear walls that are considered as one of the most essential elements of structures. To accomplish this purpose, deterministic FE analyses are conducted for both squat and slender shear walls to validate numerical models through experimental results. The presented numerical analysis is performed by using the ABAQUS FE program. Afterwards, a random-effects investigation is carried out to consider the influence of different random variables on the lateral load-top displacement behavior of RC members. Using these results and through utilizing the Monte-Carlo simulation method, stochastic nonlinear analyses are also performed to generate random FE models based on input parameters and their probabilistic distributions. In order to evaluate the reliability of RC walls, failure probabilities and corresponding reliability indices are calculated at life safety and collapse prevention levels of performance as suggested by FEMA 356. Moreover, based on reliability indices, capacity reduction factors are determined subjected to shear for all specimens that are designed according to the ACI 318 Building Code. Obtained results show that the lateral load and the compressive strength of concrete have the highest effects on load-displacement responses compared to those of other random variables. It is also found that the probability of shear failure for the squat wall is slightly lower than that for slender walls. This implies that 𝛽 values are higher in a non-ductile mode of failure. Besides, the reliability of both squat and slender shear walls does not change significantly in the case of varying capacity reduction factors.

• 한국강구조학회 논문집
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• 제12권5호통권48호
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• pp.581-593
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• 2000

본 연구는 지진하중을 받는 현수교의 수직 동적 해석방법을 발전시켰다. 시간 영역해석, 불규칙 진동 해석 및 스펙트럼 해석의 이론을 체계적으로 정립하였다. 불규칙 진동 해석을 다시 수치적분을 이용하는 방법과 수학적 적분식 및 상관계수를 이용한 방법으로 나누고 각각은 다시 지진하중을 white noise로 가정한 경우와 filtered white noise로 가정한 경우에 대해 CQC 방법과 SRSS 방법을 사용하였다. 현수교의 모델링은 빔, 트러스 및 프레임요소를 사용하였고 케이블과 주탑은 사하중에 의한 기하학적 강성을 고려하였다.

• Journal of Communications and Networks
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• 제8권1호
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• pp.93-105
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• 2006

The domination of the Internet by TCP-based services has spawned many efforts to provide high network utilization with low loss and delay in a simple and scalable manner. Active queue management (AQM) algorithms attempt to achieve these goals by regulating queues at bottleneck links to provide useful feedback to TCP sources. While many AQM algorithms have been proposed, most suffer from instability, require careful configuration of nonintuitive control parameters, or are not practical because of slow response to dynamic traffic changes. In this paper, we propose a new AQM algorithm, hybrid random early detection (HRED), that combines the more effective elements of recent algorithms with a random early detection (RED) core. HRED maps instantaneous queue length to a drop probability, automatically adjusting the slope and intercept of the mapping function to account for changes in traffic load and to keep queue length within the desired operating range. We demonstrate that straightforward selection of HRED parameters results in stable operation under steady load and rapid adaptation to changes in load. Simulation and implementation tests confirm this stability, and indicate that overall performances of HRED are substantially better than those of earlier AQM algorithms. Finally, HRED control parameters provide several intuitive approaches to trading between required memory, queue stability, and response time.

• The Journal of the Acoustical Society of Korea
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• 제15권3E호
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• pp.4-12
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• 1996

In this study, we examine the applicability of an artificial neural network(ANN) for filtering underwater random noise and for identifying underlying signals taken from noisy environment. The approach is to find a way of compressing the input data and then decompressing it using an ANN as in image compressing process. It is well known that random signal is hard to compress while ordered information is not. The use of a limited number of processing elements(PEs) in the hidden layer of an Ann ensures that some of the noise would be removed in the reconstruction process. Two types of the signals, synthesized and measured, are used to examine the effectiveness of the ANN-based filter. After training process is completed, the ANN successfully extracts the underlying signals form the synthesized or measured noisy signals. In particular, compared with the results form without filtering or moving averaged, the ANN-based filter gives much better spectrograms to identify underlying signals from the measured noisy data. This filtering process is achieved without using and kind of highly accurate signal processing technique. More experimentation needs to be followed to develop the ANN-based filtering technique to the level of complete understanding.

• 대한전자공학회논문지
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• 제20권6호
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• pp.18-22
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• 1983

선형 임의 배렬 안테나의 부로브 첨두치 이론을 더욱 확장시켜 투상형 임의 배열 안테나의 에스티메이터를 유도 및 해석하였고, 그 에스티메이터의 이론치와 Moilto Carlo 방법을 이용한 컴퓨터 시뮬레이션 결과치와 비교 검토한 결과 고대오차 0.8dB인 아주 작은 오차를 보임으로서 신뢰도가 0.5이상일 때 부로브첨두치 에스티메이터 경가 미회한 에스티메이터임을 입증하였다.