• Korean Journal of Remote Sensing
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• v.15 no.2
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• pp.147-158
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• 1999

Remote sensing technique has offered better understanding of our environment for the decades by providing useful level of information on the landcover. In many applications using the remotely sensed data, digital image processing methodology has been usefully employed to characterize the features in the data and develop the models. Random field models, especially Markov Random Field (MRF) models exploiting spatial relationships, are successfully utilized in many problems such as texture modeling, region labeling and so on. Usually, remotely sensed imagery are very large in nature and the data increase greatly in the problem requiring temporal data over time period. The time required to process increasing larger images is not linear. In this study, the methodology to reduce the computational cost is investigated in the utilization of the Markov Random Field. For this, multiresolution framework is explored which provides convenient and efficient structures for the transition between the local and global features. The computational requirements for parameter estimation of the MRF model also become excessive as image size increases. A Bayesian approach is investigated as an alternative estimation method to reduce the computational burden in estimation of the parameters of large images.

• Journal of Korean Society of Transportation
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• v.27 no.2
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• pp.157-168
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• 2009

The random utility theory and the multinomial logit model (including a more recent variant--the mixed multinomial logit) derived from it have constituted a back bone for theoretical and empirical analyses of various travel demand features including mode choice. In their empirical applications, however, it is customary to specify random utilities which are linear in modal attributes such as time and cost, and in socio-economic variables. The linearity helps easy derivation of important information such as value of travel time savings by calculating marginal rate of substitution between time and cost. In this paper the author focuses on the very linearity of the random utilities. Taking into account the fact that the mode chooser is also labour supplier, commodity consumer as well as leisure-seeker, the author sets up a maximization model of the traveller, which encompasses various economic activities of the traveller. The author derive from the model the indifference curve defined on the space of modal attributes, time and cost and investigate under what conditions the random utility of the traveller becomes linear. It turns out that there exist the conditions under which the random utility is really linear in modal attributes, but the property does not hold when the traveller has a corner solution on the space of modal attributes, or when the primary utility function of the traveller is directly affected by labour provided and/or the travel time itself. As a corollary of the analysis, a random utility is suggested, approximated up to the second order of the variables involved for empirical studies of the field.

• Computational Structural Engineering
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• v.10 no.4
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• pp.239-249
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• 1997

The method to distinguish chaotic attractors in the perturbed response behaviors of a piecewise-linear system under combined regular and external randomness is provided and examined. In the noisy fields such as the ocean environment, excitation forces induced by wind, waves and currents contain a finite degree of randomness. Under external random perturbations, the system responses are disturbed, and consequently chaotic signatures in the response attractors are not distinguishable, but rather look just random-like. Mean Poincare map can be utilized to identify such chaotic responses veiled due to the random noise by averaging the noise effect out of the perturbed responses. In this study, the procedure to create mean Poincare map combined with the direct numerical simulations is provided and examined. It is found that mean Poincare maps can successfully distinguish chaotic attractors under stochastic excitations, and also can give the information of limit value of noise intensity with which the chaos signature in system responses vanishes.

• Journal of information and communication convergence engineering
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• v.16 no.3
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• pp.166-172
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• 2018

A pseudo-random sequence generated by using a primitive polynomial, trace function, and Legendre symbol has been researched in our previous work. Our previous sequence has some interesting features such as period, autocorrelation, and linear complexity. A pseudo-random sequence widely used in cryptography. However, from the aspect of the practical use in cryptographic systems sequence needs to generate swiftly. Our previous sequence generated by utilizing a primitive polynomial, however, finding a primitive polynomial requires high calculating cost when the degree or the characteristic is large. It’s a shortcoming of our previous work. The main contribution of this work is to find some relation between the generated sequence and irreducible polynomials. The purpose of this relationship is to generate the same sequence without utilizing a primitive polynomial. From the experimental observation, it is found that there are (p - 1)/2 kinds of polynomial, which generates the same sequence. In addition, some of these polynomials are non-primitive polynomial. In this paper, these relationships between the sequence and the polynomials are shown by some examples. Furthermore, these relationships are proven theoretically also.

• Journal of the Korean GEO-environmental Society
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• v.4 no.3
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• pp.79-88
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• 2003

This paper presents a numerical study of the spatial behavior of a linear absorbing solute in a heterogeneous porous medium. The spatially correlated log-normal hydraulic conductivity field is generated in a given two-dimensional domain by using the geostatistical method (Turning Bands algorithm). The velocity vector field is calculated by applying the two-dimensional saturated groundwater flow equation to the Galerkin finite element method. The simulation of solute transport is carried out by using the random walk particle tracking model with CD(constant displacement) scheme in which the time interval is automatically adjusted. In this study, the spatial behavior of a solute is analyzed by the longitudinal center-of-mass displacement, longitudinal spatial spread moment and longitudinal plume skewness.

• Geomechanics and Engineering
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• v.36 no.4
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• pp.381-390
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• 2024

The introduction of bio-based materials has been recommended in the geotechnical engineering field to reduce environmental pollutants such as heavy metals and greenhouse gases. However, bio-treated soil methods face limitations in field application due to short research periods and insufficient verification of engineering performance, especially when compared to conventional materials like cement. Therefore, this study aimed to develop a machine learning model for predicting the unconfined compressive strength, a representative soil property, of biopolymer-based soil treatment (BPST). Four machine learning algorithms were compared to determine a suitable model, including linear regression (LR), support vector regression (SVR), random forest (RF), and neural network (NN). Except for LR, the SVR, RF, and NN algorithms exhibited high predictive performance with an R² value of 0.98 or higher. The permutation feature importance technique was used to identify the main factors affecting the strength enhancement of BPST. The results indicated that the unconfined compressive strength of BPST is affected by mean particle size, followed by biopolymer content and water content. With a reliable prediction model, the proposed model can present guidelines prior to laboratory testing and field application, thereby saving a significant amount of time and money.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.47.1-47.1
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• 2019

We report the design and vibration analysis for the optomechanical structures of Linear Astigmatism Free - Three Mirror System (LAF-TMS). LAF-TMS is the linear astigmatism free off-axis wide-field telescope with D = 150 mm, F/3.3, and FOV = 5.51° × 4.13°. The whole structure consists of four optomechanical modules. It can accurately mount mirrors and also can survive from vibration environments. The Mass Acceleration Curve (MAC) is adapted to the quasi-static analysis. Modal, harmonic, and random vibration analysis have been performed under the qualification level of the launch system. We evaluate the final results in terms of von Mises stress and Margin of Safety (MoS).

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.3B
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• pp.305-308
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• 2011

In this study, generation methods of 3-D multi-directional random wave are examined using the fully non-linear numerical model with non-reflected wave generation system (LES-WASS-3D). Directional distribution functions obtained by EMLM method are compared for multidirectional random waves generated by various generation methods. As a results, it is revealed that multi-directional wave field can be simulated using LES-WASS-3D.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.2 no.2
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• pp.75-82
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• 1990

A Wave transformation including wave breaking in shallow water region is a non-linear and discontinuous Phenomenon. Therefore, a so-called individual wave analysis (or a wave by wave analysis) rather than spectral approach seems to be adequate to investigate the wave transformation in such regions. In this study, a theoretical joint distribution of wave height, period and wave direction of zero-down crossing waves, which is required in the individual wave analysis in the shallow water region, is derived based on the hypothesis that sea surface is a Gaussian stochastic process and that a band-width of energy spectra is sufficiently narrow. The derived i oint distribution is found to be an effective measure to investigate characteristics of three-dimensional random wave field in shallow water through field measurements.

• Journal of the Korean Statistical Society
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• v.31 no.2
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• pp.177-198
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• 2002

The estimation of variance components or variance ratios in linear model is an important issue in plant or animal breeding fields, and various estimation methods have been devised to estimate variance components or variance ratios. However, many traits of economic importance in those fields are observed as dichotomous or polychotomous outcomes. The usual estimation methods might not be appropriate for these cases. Recently threshold linear model is considered as an important tool to analyze discrete traits specially in animal breeding field. In this note, we consider a hierarchical Bayesian method for the threshold animal model. Gibbs sampler for making full Bayesian inferences about random effects as well as fixed effects is described to analyze jointly discrete traits and continuous traits. Numerical example of the model with two discrete ordered categorical traits, calving ease of calves from born by heifer and calving ease of calf from born by cow, and one normally distributed trait, birth weight, is provided.