• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.9
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• pp.999-1004
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• 2014

In the present paper, the effects of initial crack location on spatial randomness of fatigue crack growth resistance (FCGR) in friction stir welded (FSWed) AA7075-T651 plates were studied. The objective of this study is to characterize the statistical properties of FCGR for three different types of initial crack location (ICL) specimens. In this work, the FCGR coefficients were treated as a spatial random process. It was found that the FCGR coefficients for all initial crack location specimens closely followed a two parameter Weibull distribution. The shape parameter of the Weibull distribution for BM-ICL specimens showed the largest value of 7.50, and that for the WM-ICL specimens showed the smallest value of 2.61. In addition, the autocorrelation functions for all the ICL specimens followed the exponential function.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.3
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• pp.31-37
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• 2014

It is usual for the officially land price of agricultural field parcels to be determined by real estate appraisers's experienced knowledge and intuition without considering quantitatively physical factors that directly influence agricultural productivity. Solar radiation is the most important predictor of agricultural productivity. GIS based simulation techniques were used to evaluate correlation between the officially land price and solar radiation for agricultural field parcels. The results show that officially land price shows random distribution patterns in relation to solar radiation, which proves that officially land price for agricultural field does not reflect agricultural productivity. It is anticipated that this research output could be used as a valuable reference to support more scientific and objective decision-making in the official pricing process of agricultural field parcels.

• Korean journal of applied entomology
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• v.52 no.3
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• pp.243-248
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• 2013

This study was conducted to understand the settlement process of Ascotis selenaria larvae into citrus orchards with respect to oviposition site and analysis of the spatial distribution pattern of the larvae. A. selenaria eggs were not found on citrus trees in field and green house, but not on citrus trees in the field. A. selenaria larvae showed a significant clump distribution in the greenhouse. In the open citrus field, the index of dispersion was around 1.0 in most cases, with a weak clumping degree. However, the d-statistic was between -1.96 and 1.96, indicating a statistically significant random distribution. In addition, the Green's index (a clumping index) was very low in all cases, even though the clump distribution was accepted. for most samples, the probability distribution of larval frequency in the field satisfied the probability distribution functions of Poisson (random pattern) and the negative binomial (clump pattern) distribution. In addition, the temporal distribution of the larvae in the open field showed a pattern which was formed by colonizers from outside oviposition sites. Further, the difference in larval spatial distribution between field and greenhouse orchards was discussed.

• Journal of the Optical Society of Korea
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• v.17 no.5
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• pp.384-391
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• 2013

We propose a split-encryption scheme on converting original images to multiple ciphertexts. This conversion introduces one random phase-only function (POF) to influence phase distribution of the preliminary ciphertexts. In the encryption process, the original image is mathematically split into two POFs. Then, they are modulated on a spatial light modulator one after another. And subsequently two final ciphertexts are generated by utilizing two-step phase-shifting interferometry. In the decryption process, a high-quality reconstructed image with relative error $RE=7.6061{\times}10^{-31}$ can be achieved only when the summation of the two ciphertexts is Fresnel-transformed to the reconstructed plane. During the verification process, any silhouette information was invisible in the two reconstructed images from different single ciphertexts. Both of the two single REs are more than 0.6, which is better than in previous research. Moreover, this proposed scheme works well with gray images.

• 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 the Korean Graphic Arts Communication Society
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• v.15 no.2
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• pp.57-76
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• 1997

A color halftoning is the process of generating halftone images for the different color plans, for example, cyan, magenta, yellow, and black for a offset printing device. A conventional halftone technique, so called AM screening, is simple and easy to implement, but the halftoned dot patterns by using this method is not free for the moire` fringe. Moire` patterns are caused the power spectrum distribution on low spatial frequency domain. To avoid Moire` patterns, the conventional screen require the different screen angles for each color plans. Recently, Ultra-fine and 7 color printing methods are developed to expend the color gamut. In 7 color printing method must be used the halftone technique of random and blue noise characteristic to avoid Moire` fringe.

• Interaction and multiscale mechanics
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• v.3 no.4
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• pp.333-342
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• 2010

The Pseudo-Excitation Method (PEM) is applied to study the stochastic space vibration responses of train-bridge coupling system. Each vehicle is modeled as a four-wheel mass-spring-damper system with two layers of suspension system possessing 15 degrees-of- freedom. The bridge is modeled as a spatial beam element, and the track irregularity is assumed to be a uniform random process. The motion equations of the vehicle system are established based on the d'Alembertian principle, and the motion equations of the bridge system are established based on the Hamilton variational principle. Separate iteration is applied in the solution of equations. Comparisons with the Monte Carlo simulations show the effectiveness and satisfactory accuracy of the proposed method. The PSD of the 3-span simply-supported girder bridge responses, vehicle responses and wheel/rail forces are obtained. Based on the $3{\sigma}$ rule for Gaussian stochastic processes, the maximum responses of the coupling system are suggested.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.303-303
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• 2000

It is difficult to determine the static axle weight of a vehicle with weigh-in-motion systems which in absence measure instantaneous axle impact forces. The difficulty in determining a static axle weight results from dynamic effects induced by vehicle/road interactions. One method to improve the problem is to quantify a statistical confidence level for measured axle weight. The quarter-car model is used to simulate vehicle motion, Also, the road input to vehicle model can be characterized in statistical terms by PSD (power spectral density) of appropriate amplitude and frequency contents other than an exact spatial distribution. The confidence levels for the measured axle weight can be obtained by the random process analysis using both vehicle model and road input.

• Tunnel and Underground Space
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• v.32 no.6
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• pp.586-597
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• 2022

In this study, a model was developed for the estimating the locational thickness information of the upper clay layer to be used for the consolidation vulnerability evaluation in the Nakdong river estuary. To estimate ground layer thickness information, we developed four spatial estimation models using machine learning algorithms, which are RF (Random Forest), SVR (Support Vector Regression) and GPR (Gaussian Process Regression), and geostatistical technique such as Ordinary Kriging. Among the 4,712 borehole data in the study area collected for model development, 2,948 borehole data with an upper clay layer were used, and Pearson correlation coefficient and mean squared error were used to quantitatively evaluate the performance of the developed models. In addition, for qualitative evaluation, each model was used throughout the study area to estimate the information of the upper clay layer, and the thickness distribution characteristics of it were compared with each other.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.6
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• pp.545-550
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• 2013

In pattern recognition field, data classification is an essential process for extracting meaningful information from data. Adaptive boosting algorithm, known as AdaBoost algorithm, is a kind of improved boosting algorithm for applying to real data analysis. It consists of weak classifiers, such as random guessing or random forest, which performance is slightly more than 50% and weights for combining the classifiers. And a strong classifier is created with the weak classifiers and the weights. In this paper, a research is performed using AdaBoost algorithm for detecting chaff echo which has similar characteristics to precipitation echo and interrupts weather forecasting. The entire process for implementing chaff echo classifier starts spatial and temporal clustering based on similarity with weather radar data. With them, learning data set is prepared that separated chaff echo and non-chaff echo, and the AdaBoost classifier is generated as a result. For verifying the classifier, actual chaff echo appearance case is applied, and it is confirmed that the classifier can distinguish chaff echo efficiently.