• Geotechnical Engineering
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• v.5 no.2
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• pp.33-44
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• 1989

In this paper, uncertainties in dynamic soil structure interaction (SSI) of nuclear poi.or plants subjected to seismic loading are studied considering the random characteristics of soils surround- ing the structure. Firstly sensitivity analysis is performed to study the effect of uncertain dynamic soil properties on the response of the structure. Secondly, to take into account the non-neterministic characteristics in analysis caused by random characteristics of the soil properties, Perturbation method and Rosenblueth's Two point estimates were used for this studu. The procedure is based on the comptex response method which is constituted by a combined usage of conventional finite elements for the near field and infinite elements for the far field. Results of the sensitivity analysis show that dynamic soil properties greatly affect the response of the sol.uc- lure. Results of the probabilistic analysis show that the Two-point estimate method produces good agreements with the Perturbation method.

• Journal of Korean Society for Atmospheric Environment
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• v.13 no.6
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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.

• Journal of Korea Multimedia Society
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• v.17 no.10
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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.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.6
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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°.

• Journal of Korean Society on Water Environment
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• v.35 no.5
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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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• v.80 no.6
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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.

• Journal of Korean Society of Steel Construction
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• v.12 no.5 s.48
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• pp.581-593
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• 2000

In this study, vertical dynamic analyses on the suspension bridges under seismic load are developed. Time domain analysis, random vibration analysis, and spectral analysis are formulated theoretically. The random nitration analysis is checked by numerical integration and the mathematical integration with correlation coefficient which include CQC and SRSS method in the conditions of white noise and filtered white noise. Beam, truss and frame elements are used in order to model the suspension bridge. Geometric stiffness due to dead load is considered for cable and tower.

• Journal of Communications and Networks
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• v.8 no.1
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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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• v.15 no.3E
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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.

• Journal of the Korean Institute of Telematics and Electronics
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• v.20 no.6
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• pp.18-22
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• 1983

In this paper, we derive and analyze the peak sidelobe estimator of the planar random array antenna by extending the theory of the linear random array antenna. The computer simula-tions, which are based on Monte Carlo method, are programmed and applied easily to cases where a great number of array elements are involved. The results obtained from the computer simulations show that there is a little difference of the maximum 0.8 dB. Consequently, the peak sidelobe estimator is well consistent with the results of the computer simulations over confidence level 0.5.