• The KIPS Transactions:PartA
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• v.13A no.7 s.104
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• pp.639-646
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• 2006

Data compression technologies enable us to store and transfer large amount of data efficiently, and become more and more important due to increasing data size and the network traffic. Moreover, as a result of the increase of computing power, volumetric data produced from various applied science and engineering fields has been getting much larger. In this Paper, we present a volume compression scheme which exploits Daubeches wavelet transform. The proposed scheme basically supports lossy compression for 3D volume data, and provides unit-wise random accessibility. Since our scheme shows far lower error rates than the previous compression methods based on Haar filter, it could be used well for interactive visualization applications as well as large volume data compression requiring image fidelity.

• Structural Engineering and Mechanics
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• v.28 no.3
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• pp.281-294
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• 2008

In this paper, linear elastic isotropic structures under the effects of both stochastic operators and stochastic excitations are studied. The analysis utilizes the spectral stochastic finite elements (SSFEM) with its two main expansions namely; Neumann and Homogeneous Chaos expansions. The random excitation and the random operator fields are assumed to be second order stochastic processes. The formulations are obtained for the system solution of the two dimensional problems of plane strain and plate bending structures under stochastic loading and relevant rigidity using the previously mentioned expansions. Two finite element programs were developed to incorporate such formulations. Two illustrative examples are introduced: the first is a reinforced concrete culvert with stochastic rigidity subjected to a stochastic load where the culvert is modeled as plane strain problem. The second example is a simply supported square reinforced concrete slab subjected to out of plane loading in which the slab flexural rigidity and the applied load are considered stochastic. In each of the two examples, the first two statistical moments of displacement are evaluated using both expansions. The probability density function of the structure response of each problem is obtained using Homogeneous Chaos expansion.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.167.2-167.2
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• 2012

경희대학교와 UC Berkeley, Imperial College London에서 공동으로 진행하는 TRIO-CINEMA Mission(TRiplet Ionosphere Observatory-Cubesat for Ion, Neutral, Electron and MAgnetic fields)은 총 3기의 초소형 위성으로 구성되어 있다. 3기의 위성은 고도 650~800km 상공의 태양동주기 궤도운동을 예상하고 있으며, 지구 근접공간의 입자 검출과 자기장 측정의 과학 임무를 맡게 된다. TRIO-CINEMA 비행 모델(Flight Model)의 환경시험은 진동시험과 열진공시험으로 진행되었다. 진동시험은 X, Y, Z 세 축에 대해 Sine 과 Random 모드로 진행되었다. TRIO-CINEMA가 탑재 될 러시아의 드네프르 로켓의 요구사항은 각 축에서 20Hz 이상의 고유진동수, Sine의 경우 최대 0.8G와 4oct/min Sweep Rate, Random의 경우 5.2Grms 와 35초의 지속시간에서의 안정성을 만족하는 것이다. 시험 결과 TRIO-CINEMA가 요구사항을 모두 만족시키는 것을 확인하였다. 또한, 열 주기 시험(Thermal Cycling Test)을 진행하여 우주공간에서 위성 시스템이 정상 동작하는지에 대한 신뢰성을 검증하였다. 열주기 시험은 미국 MIL표준 값을 참고하여 $10^{-6}Torr$에서 $-20{\sim}30^{\circ}C$의 온도를 주었으며, 시험을 진행하는 동안과 시험 후에 위성이 정상작동 함을 확인하였다. 이에 본 연구의 시험 방법과 그 결과를 기술하였다.

• Earthquakes and Structures
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• v.13 no.1
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• pp.79-87
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• 2017

Seismic analysis of local site conditions is fundamental for a reliable site seismic hazard assessment. It plays a major role in mitigation of seismic damage potential through the prediction of surface ground motion in terms of amplitude, frequency content and duration. Such analysis requires the determination of the transfer function, which is a simple tool for characterizing a soil profile by estimating its vibration frequencies and its amplification potential. In this study, numerical simulations are carried out and are then combined with a statistical study to allow the characterization of design sites classified by the Algerian Building Seismic Code (RPA99, ver 2003), by average transfer functions. The mean transfer functions are thereafter used to compute RPA99 average site factors. In this regard, coming up seismic fields are simulated based on Power Spectral Density Functions (PSDF) defined at the rock basement. Results are also used to compute average site factor where, actual and synthetic time histories are introduced. In absence of measurement data, it is found that the proposed approach can be used for a better soil characterization.

• Smart Media Journal
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• v.10 no.2
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• pp.55-60
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• 2021

In this research, we design and perform experiment to investigate whether neuronal activity patterns elicited while solving game tasks are spontaneously reactivated in during sleep. In order to recognize human activity EEG-fMRI signals are used at the same time. Experimental results shows that reward for the success of tasks performed before sleeping have an effect on sleep brain activity. The study uncovers a neural mechanism whereby rewarded life experiences are preferentially replayed and consolidated while we sleep.

• Geomechanics and Engineering
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• v.24 no.2
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• pp.167-178
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• 2021

Spatial variability is an inherent uncertainty of soil properties. Current reliability analyses generally incorporate random field theory and Monte Carlo simulation (MCS) when dealing with spatial variability, in which the computational efficiency is a significant challenge. This paper proposes a KL-FORM algorithm to improve the computational efficiency. In the proposed KL-FORM, Karhunen-Loeve (KL) expansion is used for discretizing random fields, and first-order reliability method (FORM) is employed for reliability analysis. The KL expansion and FORM can be used in conjunction, through adopting independent standard normal variables in the discretization of KL expansion as the basic variables in the FORM. To illustrate the effectiveness of this KL-FORM, it is applied to a case study of a strip footing in spatially variable unsaturated soil under rainfall, in which the bearing capacity of the footing is computed by numerical simulation. This case study shows that the KL-FORM is accurate and efficient. The parametric analyses suggest that ignoring the spatial variability of the soil may lead to an underestimation of the reliability index of the footing.

• Journal of Korean Society of Rural Planning
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• v.28 no.4
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• pp.105-117
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• 2022

This study tested SVM(support vector machine), RF(random forest), and ANN(artificial neural network) machine-learning models that can predict net irrigation water requirements in paddy fields. For the Jeonju and Jeongeup meteorological stations, the net irrigation water requirement was calculated using K-HAS from 1981 to 2021 and set as the label. For each algorithm, twelve models were constructed based on cumulative precipitation, precipitation, crop evapotranspiration, and month. Compared to the CE model, the R² of the CEP model was higher, and MAE, RMSE, and MSE were lower. Comprehensively considering learning performance and learning time, it is judged that the RF algorithm has the best usability and predictive power of five-days is better than three-days. The results of this study are expected to provide the scientific information necessary for the decision-making of on-site water managers is expected to be possible through the connection with weather forecast data. In the future, if the actual amount of irrigation and supply are measured, it is necessary to develop a learning model that reflects this.

• Earthquakes and Structures
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• v.22 no.3
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• pp.219-230
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• 2022

Knowing that the variability of soil properties is an important source of uncertainty in geotechnical analyses, we will study in this paper the effect of this variability on the seismic response of a structure within the framework of Soil Structure Interaction (SSI). We use the proposed and developed model (N2-ISS, Mekki et al., 2014). This approach is based on an extension of the N2 method by determining the capacity curve of the fixed base system oscillating mainly in the first mode, then modified to obtain the capacity curve of the system on a flexible basis using the concept of the equivalent nonlinear oscillator. The properties of the soil that we are interested in this paper will be the shear wave velocity and the soil damping. These parameters will be modeled at first, as independent random fields, then, the two parameters will be correlated. The results obtained showed the importance of the use of random field in the study of SSI systems. The variability of soil damping and shear wave velocity introduces significant uncertainty not only in the evaluation of the damping of the soil-structure system but also in the estimation of the displacement of the structure and the base-shear force.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.20 no.3
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• pp.291-299
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• 2008

The present study is to estimate the effects of diffracted wave fields in a harbor and around harborentrance due to random waves, when a navigation channel is dredged in the vicinity of the a harbor entrance. The cross sections of harbor boundary are considered to be partial or full reflection in this study. The numerical simulation has been performed by the boundary element method, which is to discrete segments of pit- and harbor- boundary with the algorism of auto generated elements. The incident wave conditions are specified using discretized forms of the Mitsuyasu's frequency spectrum and directional function. The results of the present numerical simulation agreed well with those of the published experimental data. It is shown that the ratios of wave height reduction are about 20% for the case of fully reflecting boundary, and 10% for the case of partially reflecting boundary by the effect of placing a pit, respectively.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.2
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• pp.153-158
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• 2017

In this paper, we take into account topology optimization problems considering spatial randomness in the material property of elastic modulus. Based on 88 lines MATLAB Code, Monte Carlo analysis has been performed for MBB(messerschmidt-$b{\ddot{o}}lkow$-blohm) model using 5,000 random sample fields which are generated by using the spectral representation scheme. The random elastic modulus is assumed to be Gaussian in the spatial domain of the structure. The variability of the volume fraction of the material, which affects the optimum topology of the given problem, is given in terms of correlation distance of the random material. When the correlation distance is small, the randomness in the topology is high and vice versa. As the correlation distance increases, the variability of the volume fraction of the material decreases, which comply with the feature of the linear static analysis. As a consequence, it is suggested that the randomness in the material property is need to be considered in the topology optimization.