• Journal of Power System Engineering
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• v.4 no.2
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• pp.40-45
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• 2000

Some engineering materials are often known to have considerable spatial variation in their resisting strength and other properties. The objective of this study is to investigate the averaging effect and the applicability of extremal statistic for the statistical size effect. In the present study, it is assumed that the material property is a stationary random process in space. The theoretical autocorrelation function of the material strength are discussed for several correlation lengths. And, in order to investigate the statistical size effect, the material properties was simulated by using the non-Gaussian random process method. The material properties were plotted on the Weibull probability papers. The main results are summarized as follows: The autocorrelation function of the material properties are almost independent of the averaging length. The variance decreases with increasing the averaging length. As correlation length is smaller, the slope is larger. And also, it was found that Weibull statistics based on the weakest-link model could not explain the spatial variation of material properties with respect to the size effect satisfactory.

• Korean Journal of Remote Sensing
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• v.17 no.4
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• pp.335-344
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• 2001

Texture is extensively studied in a variety of image processing applications such as image segmentation and classification because it is an important property to perceive regions and surfaces. This paper focused on the analysis and synthesis of textured single and multiband images using Markov Random Field model considering the existent spatial correlation. Especially, for multiband images, the cross-channel correlation existing between bands as well as the spatial correlation within band should be considered in the model. Although a local interaction is assumed between the specified neighboring pixels in MRF models, during the maximization process, short-term correlations among neighboring pixels develop into long-term correlations. This result in exhibiting phase transition. In this research, the role of temperature to obtain the most probable state during the sampling procedure in discrete Markov Random Fields and the stopping rule were also studied.

• Journal of Advanced Marine Engineering and Technology
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• v.32 no.6
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• pp.955-963
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• 2008

In this paper, we propose an improved practical encryption and fault-tolerance decryption method using a non-negative value key and random function obtained with a white noise by using iterative phase wrapping method. A phase wrapping operating key, which is generated by the product of arbitrary random phase images and an original phase image. is zero-padded and Fourier transformed. Fourier operating key is then obtained by taking the real-valued data from this Fourier transformed image. Also the random phase wrapping operating key is made from these arbitrary random phase images and the same iterative phase wrapping method. We obtain a Fourier random operating key through the same method in the encryption process. For practical transmission of encryption and decryption keys via Internet, these keys should be intensity maps with non-negative values. The encryption key and the decryption key to meet this requirement are generated by the addition of the absolute of its minimum value to each of Fourier keys, respectively. The decryption based on 2-f setup with spatial filter is simply performed by the inverse Fourier transform of the multiplication between the encryption key and the decryption key and also can be used as a current spatial light modulator technology by phase encoding of the non-negative values. Computer simulations show the validity of the encryption method and the robust decryption system in the proposed technique.

• Communications for Statistical Applications and Methods
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• v.8 no.2
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• pp.499-505
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• 2001

Kim and Baek (2000) tested the spatial randomness for he earthquake occurrence in the Korean Peninsula by using the nearest-neighbor test statistics and empirical distribution functions. The K-function, however, has obvious advantages over the methods used in Kim and Baek (2000), such as it does not depend on the shape of the study region and is an effective summary of spatial dependence over a wide range of scales. We applied the K-function method for testing the randomness to both of the historical and the instrumental seismicity data. It was found that he earthquake occurrences for historical and instrumental seismicity data are not random and clustered rather than scattered.

• Spatial Information Research
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• v.11 no.3
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• pp.227-240
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• 2003

The primary focus of this study is to provide a general methodology which can be utilized to understand and analyze environmental issues such as long term ecosystem dynamics and land use/cover change by development of 2D dynamic landscape models and model-based simulation. Change processes in land cover and ecosystem function can be understood in terms of the spatial and temporal distribution of land cover resources. In development of a system to understand major processes of change and obtain predictive information, first of all, spatial heterogeneity is to be taken into account because landscape spatial pattern affects on land cover change and interaction between different land cover types. Therefore, the relationship between pattern and processes is to be included in the research. Landscape modeling requires different approach depending on the definition, assumption, and rules employed for mechanism behind the processes such as spatial event process, land degradation, deforestration, desertification, and change in an urban environment. The rule-based models are described in the paper for land cover change by natural fires. Finally, a case study is presented as an example using spatial modeling and simulation to study and synthesize patterns and processes at different scales ranging from fine-scale to global scale.

• Journal of Ocean Engineering and Technology
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• v.17 no.2
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• pp.54-59
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• 2003

The characteristics of the parameters for the probability distribution of fatigue crack growth life, using the non-Gaussian random process simulation method is investigated. In this paper, the material resistance to fatigue crack growth is treated as a spatial random process, which varies randomly on the crack surface. Using the previous experimental data, the crack length equals the number of cycle curves that are simulated. The results are obtained for constant stress intensity factor range conditions with stress ratios of R=0.2, three specimen thickness of 6, 12 and 18mm, and the four stress intensity level. The probability distribution function of fatigue crack growth life seems to follow the 3-parameter Wiubull,, showing a slight dependence on specimen thickness and stress intensity level. The shape parameter, $\alpha$, does not show the dependency of thickness and stress intensity level, but the scale parameter, $\beta$, and location parameter, ${\gamma}$, are decreased by increasing the specimen thickness and stress intensity level. The slope for the stress intensity level is larger than the specimen thickness.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2002.10a
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• pp.301-306
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• 2002

The characteristics of parameters for the probability distribution of fatigue crack growth lives by the non-Gaussian random process simulation method is investigated. In this paper, the material resistance to fatigue crack growth is treated as a spatial random process, which varies randomly on the crack surface. Using the previous experimental data, the crack length - the number of cycles curves are simulated. The results are obtained for constant stress intensity factor range conditions with stress ratio of R=0.2, three specimen thickness of 6, 12 and 18mm, and the four stress intensity level. The probability distribution function of fatigue crack growth lives seems to follow the 3-parameter Wiubull and shows a slight dependence on specimen thickness and stress intensity level. The shape parameter, ${\alpha}$, does not show the dependency of thickness and stress intensity level, but the scale parameter, ${\beta}$, and location parameter, ${\upsilon}$, are decreased by increasing the specimen thickness and stress intensity level. The slope for the stress intensity level is larger than the specimen thickness.

• Communications for Statistical Applications and Methods
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• v.19 no.1
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• pp.193-211
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• 2012

This paper deals with robust nonparametric regression analysis when the regressors are functional random fields. More precisely, we consider $Z_i=(X_i,Y_i)$, $i{\in}\mathbb{N}^N$ be a $\mathcal{F}{\times}\mathbb{R}$-valued measurable strictly stationary spatial process, where $\mathcal{F}$ is a semi-metric space and we study the spatial interaction of $X_i$ and $Y_i$ via the robust estimation for the regression function. We propose a family of robust nonparametric estimators for regression function based on the kernel method. The main result of this work is the establishment of the asymptotic normality of these estimators, under some general mixing and small ball probability conditions.

• Computers and Concrete
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• v.12 no.1
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• pp.91-107
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• 2013

Corrosion of RC bridge decks eventually leads to delamination, severe cracking and spalling of the concrete cover. This is a prevalent deterioration mechanism and demands for the most costly repair interventions during the service life of bridges worldwide. On the other hand, decisions for repairs are usually made whenever the extent of a limit crack width, reported in routine visual inspections, exceeds an acceptable threshold level. In this paper, while random fields are applied to account for spatial variation of governing parameters of the corrosion process, an analytical model is used to simulate the corrosion induced crack width. However when dealing with random fields, the Monte Carlo simulation is apparently an inefficient and time consuming method, hence the utility of neural networks as a surrogate in simulation is investigated and found very promising. The proposed method can be regarded as an invaluable tool in decision making concerning maintenance of bridges.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.9
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• pp.1691-1699
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• 1992

The experimental results of fatigue crack propagation under constant amplitude loading show that intra-and inter-specimen variability exist. In this paper, a stochastic model for the estimation of mean and variance of crack propagation life is presented To take into account the intra-specimen variability, the material resistance against crack propagation is treated as an 1-dimensional spatial stochastic process, i. e. random field, varying along the propagation path. For the inter-specimen variability, C in paris equation is assumed to be a random variable. Compared with experimental results reported, the present method well estimate the variation in fatigue crack propagation life. And it is confirmed that the thicker the specimen thickness is, the less the variation of propagation life is.