• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.4
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• pp.611-617
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• 1997

In this paper a new fading model is proposed, which is well consistent with the real environment of smart antenna applications since it is spatially and temporally correlated simultaneously. The new model(STCFM: Spatially and Temporally Correlated Fading Model) is derived statistically in spatio-temporal domain so that it can provide high accuracy in the evaluation of the smart antenna system. As will be seen, the simulation results agree well with the theory.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.237-253
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• 2019

For massive multiple-input multiple-output (MIMO) circumstances with time division duplex (TDD) protocol, pilot contamination becomes one of main system performance bottlenecks. This paper proposes an uplink pilot sequence assignment to alleviate this problem for spatially correlated massive MIMO circumstances. Firstly, a single-cell TDD massive MIMO model with multiple terminals in the cell is established. Then a spatial correlation between two channel response vectors is established by the large-scale fading variables and the angle of arrival (AOA) span with an infinite number of base station (BS) antennas. With this spatially correlated channel model, the expression for the achievable system capacity is derived. To optimize the achievable system capacity, a problem regarding uplink pilot assignment is proposed. In view of the exponential complexity of the exhaustive search approach, a pilot assignment algorithm corresponding to the distinct channel AOA intervals is proposed to approach the optimization solution. In addition, simulation results prove that the main pilot assignment algorithm in this paper can obtain a noticeable performance gain with limited BS antennas.

• Journal of the Korean Statistical Society
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• v.29 no.2
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• pp.231-245
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• 2000

This paper considers a linear regression model with space and time data in where the disturbances follow spatially correlated error components. We provide the best linear unbiased predictor for the one way error components. We provide the best linear unbiased predictor for the one way error component model with spatial autocorrelation. Further, we derive two diagnostic test statistics for the assessment of model specification due to spatial dependence and random effects as an application of the Lagrange Multiplier principle.

• Structural Engineering and Mechanics
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• v.65 no.5
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• pp.633-644
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• 2018

This paper presents the results of an assessment of the seismic fragility of a long, curved multi-frame bridge under multi-support earthquake excitations. To achieve this aim, the numerical model of columns retrofitted with elliptical steel jackets was developed and validated using existing experimental results. A detailed nonlinear numerical model of the bridge that can capture the inelastic response of various components was then created. Using nonlinear time-history analyses for a set of stochastically generated spatially variable ground motions, component demands were derived and then convolved with new capacity-based limit state models to obtain seismic fragility curves. The comparison of failure probabilities obtained from uniform and multi-support excitation analyses revealed that the consideration of spatial variability significantly reduced the median value of fragility curves for most components except for the abutments. This observation indicates that the assumption of uniform motions may considerably underestimate seismic demands. Moreover, the spatial correlation of ground motions resulted in reduced dispersion of demand models that consequently decreased the dispersion of fragility curves for all components. Therefore, the spatial variability of ground motions needs to be considered for reliable assessment of the seismic performance of long multi-frame bridge structures.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.434-437
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• 2016

In this paper, we consider a measurement allocation problem for gathering reliable data from a spatially correlated sensor field. We allocate the probability of each sensor's being measured considering its marginal contribution in entire data gathering; higher measurement probability is given to a sensor that gives higher reilable data. First we establish a correlation model considering limit in each sensor's transmission power, noise in the process of measurement and transmission, and attenutations in wireless channel. Then we evaluate the reliability of gathered data by estimating distortion error in sink node. We model the measurement allocation problem in spatially correlated sensor field into a cooperative game, and quantifiy each sensor's marginal contribution using Shapley Value. Then, the probability of each sensor's being measured is given in proportion to the Shapley Value.

• Proceedings of the IEEK Conference
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• 2000.06e
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• pp.134-137
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• 2000

We applied the ICA method to separate the ventricle and tissue components and to extract left ventricular input function from the H$_2$$^{15}$ O myocardial PET under the assumption that the elementary activities of ventricular pools and myocardium were spatially independent, and that the mixture of them composed dynamic PET frames. ICA-generated left ventricular input functions were compared with the ROI-generated ones, and also with the invasively derived arterial blood samples. Moreover, the rMBF calculated with the ICA-generated input functions and single compartment model was correlated with the results obtained with the radiolabeled microspheres.

• Earthquakes and Structures
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• v.26 no.5
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• pp.401-416
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• 2024

Long-span structures, such as bridges, can experience different seismic excitations at the supports due to spatially variability of ground motion. Regarding current bridge designing codes, it is just EC 2008 that suggested some regulations to consider it and in the other codes almost ignored while based on some previous studies it is found that the effect of mentioned issue could not be neglected. The current study aimed to perform a comprehensive study about the effect of spatially varying ground motions on the dynamic response of a reinforced concrete bridge under asynchronous input motions considering soil-structure interactions. The correlated ground motions were generated by an introduced method that contains all spatially varying components, and imposed on the supports of the finite element model under different load scenarios. Then the obtained results from uniform and non-uniform excitations were compared to each other. In addition, the effect of soil-structure interactions involved and the corresponding results compared to the previous results. Also, to better understand the seismic response of the bridge, the responses caused by pseudo-static components decompose from the total response. Finally, an incremental dynamic analysis was performed to survey the non-linear behavior of the bridge under assumed load scenarios. The outcomes revealed that the local site condition plays an important role and strongly amplifies the responses. Furthermore, it was found that a combination of wave-passage and strong incoherency severely affected the responses of the structure. Moreover, it has been found that the pseudo-static component's contribution increase with increasing incoherent parameters. In addition, regarding the soil condition was considered for the studied bridge, it was found that a combination of spatially varying ground motions and soil-structure interactions effects could make a very destructive scenarios like, pounding and unseating.

• The Korean Journal of Applied Statistics
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• v.28 no.2
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• pp.353-360
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• 2015

Various statistical models have been proposed over the last decade for spatially correlated Gaussian outcomes. The spatial linear mixed model (SLMM), which incorporates a spatial effect as a random component to the linear model, is the one of the most widely used approaches in various application contexts. Employing link functions, SLMM can be naturally extended to spatial generalized linear mixed model for non-Gaussian outcomes (SGLMM). We review popular SGLMMs on non-Gaussian spatial outcomes and demonstrate their applications with available public data.

• Journal of the Korean GEO-environmental Society
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• v.8 no.4
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• pp.27-39
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• 2007

This paper investigates numerically characteristics of the fluid flow in spatially correlated variable-aperture fractures under effective normal stress conditions. Spatially correlated aperture distributions are generated by using the geostaistical method (i.e. Turning Bands algorithm). In order to represent a nonlinear relationship between the effective normal stress and the fracture aperture, a simple mechanical formula is combined with a local flow model. Obtained numerical results indicate that the fluid flow is significantly affected by the geometry of aperture distribution varying according to the applied effective normal stress as well as the spatial correlation length of aperture distribution. Moreover, by using results simulated in this study, the modified Louis formula representing the relationship between the effective normal stress and the effective permeability of fracture is proposed.

• Journal of information and communication convergence engineering
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• v.16 no.1
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• pp.38-42
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• 2018

In this paper, we consider measurement allocation problem in a spatially correlated sensor field. Our goal is to determine the probability of each sensor's being measured based on its contribution to the estimation reliability; it is desirable that a sensor improving the estimation reliability is measured more frequently. We consider a spatial correlation model of a sensor field reflecting transmission power limit, noise in measurement and transmission channel, and channel attenuation. Then the estimation reliability is defined distortion error between event source and its estimation at sink. Motivated by the correlation nature, we model the measurement allocation problem into a cooperative game, and then quantify each sensor's contribution using Shapley value. Against the intractability in the computation of exact Shapley value, we deploy a randomized method that enables to compute the approximate Shapley value within a reasonable time. Besides, we envisage a measurement scheduling achieving the balance between network lifetime and estimation reliability.