• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.2
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• pp.473-480
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• 1996

Automatic fatigue crack length measuring system using DC electrical potential method and the system control program for automatic fatigue testing under random load condition were made in this study. And using these system and control program, fatigue tests were executed under constant and random load condition. As the result, the propagation of crack in random loading can be represented Paris equaiton and log normal probability function. But constant and random load test show different crack propagation properties.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.1
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• pp.26-32
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• 2013

Blind algorithms based on Information potential of output samples and a set of symbols generated in random order at the receiver go through performance degradation when biased impulsive noise is added to the channel since the cost function composed of information potentials has no variable to deal with biased signal. Aiming at the robustness against biased impulsive noise, we propose, in this paper, a modified information potential, and derived related blind algorithms based on augmented filter structures and a set of random-order symbols. From the simulation results of blind equalization for multipath channels, the blind algorithm based on the proposed information potential produced superior convergence performance in the environments of strong biased impulsive noise.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.18 no.2
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• pp.187-193
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• 2009

Dynamic response of an elastic pendulum system under random excitations was studied by using the Lagrangian equations of motion which uses the kinetic and potential energy of a target system. The responses of random excitations were calculated by using Monte Carl simulation which uses the series of random numbers. The procedure of Monte Carlo simulation is generation of random numbers, system model, system output, and statistical management of output. When the levels of random excitations were changed, the expected responses of the pendulum system showed various responses.

• Journal of Internet Computing and Services
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• v.21 no.2
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• pp.49-55
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• 2020

Information theoretic learning (ITL) methods based on random symbols (RS) use a set of random symbols generated according to a target distribution and are designed nonparametrically to minimize the cost function of the Euclidian distance between the target distribution and the input distribution. One drawback of the learning method is that it can not utilize the input power statistics by employing a constant stepsize for updating the algorithm. In this paper, it is revealed that firstly, information potential input (IPI) plays a role of input in the cost function-derivative related with information potential output (IPO) and secondly, input itself does in the derivative related with information potential error (IPE). Based on these observations, it is proposed to normalize the step-size with the statistically varying power of the two different inputs, IPI and input itself. The proposed algorithm in an communication environment of impulsive noise and multipath fading shows that the performance of mean squared error (MSE) is lower by 4dB, and convergence speed is 2 times faster than the conventional methods without step-size normalization.

• Journal of Ocean Engineering and Technology
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• v.15 no.1
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• pp.12-18
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• 2001

This study concentrates on the second-order diffraction problem around circular cylinders in multi-frequency waves. The method of solution is a time-domain Rankine panel method which adopts a higher-order approximation for the velocity potential and wave elevation. In the present study, the multiple second-order quadratic transfer functions are extracted from the second-order time signal generated in random waves, and the comparison with other bench-mark test results shows a good agreement. This approach is directly applicable to prediction of nonlinear forces on offshore structures in random ocean.

• Journal of the Optical Society of Korea
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• v.4 no.1
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• pp.43-47
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• 2000

We studied experimentally a discrete random phase-code multiplexing technique for holographic data storage, which we believe can overcome some disadvantages of conventional random phase-code multiplexing adopting either a diffusion plate or a multimode fiber. Experimental demonstration is presented to show the potential usefulness and some characteristics of the discrete random phase-code multiplexing technique.

• Industrial Engineering and Management Systems
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• v.15 no.2
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• pp.148-155
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• 2016

Existing power plants may consume significant amounts of fuel and require high operating costs, partly because of poor electrical power output estimates. This paper suggests a continuous conditional random field (C-CRF) model to predict more precisely the full-load electrical power output of a base load operated combined cycle power plant. We introduce three feature functions to model association potential and one feature function to model interaction potential. Together, these functions compose the C-CRF model, and the model is transformed into a multivariate Gaussian distribution with which the operation parameters can be modeled more efficiently. The performance of our model in estimating power output was evaluated by means of a real dataset and our model outperformed existing methods. Moreover, our model can be used to estimate confidence intervals of the predicted output and calculate several probabilities.

• International journal of advanced smart convergence
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• v.13 no.3
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• pp.80-88
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• 2024

Breast cancer remains a significant global health burden, necessitating accurate and timely detection for improved patient outcomes. Machine learning techniques have demonstrated remarkable potential in assisting breast cancer diagnosis by learning complex patterns from multi-modal patient data. This study comprehensively evaluates several popular machine learning models, including logistic regression, decision trees, random forests, support vector machines (SVMs), naive Bayes, k-nearest neighbors (KNN), XGBoost, and ensemble methods for breast cancer prediction using the Wisconsin Breast Cancer Dataset (WBCD). Through rigorous benchmarking across metrics like accuracy, precision, recall, F1-score, and area under the ROC curve (AUC), we identify the naive Bayes classifier as the top-performing model, achieving an accuracy of 0.974, F1-score of 0.979, and highest AUC of 0.988. Other strong performers include logistic regression, random forests, and XGBoost, with AUC values exceeding 0.95. Our findings showcase the significant potential of machine learning, particularly the robust naive Bayes algorithm, to provide highly accurate and reliable breast cancer screening from fine needle aspirate (FNA) samples, ultimately enabling earlier intervention and optimized treatment strategies.

• Journal of the Korean Ceramic Society
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• v.36 no.1
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• pp.50-54
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• 1999

We have measured the x-ray photoemission spectroscopy of cation deficient La0.970Mn0.970O3 as a function of temperature. Detailed results on the chemical shifts and changes in Mn 2p and Lp 3d core levels due to variation of temperature have been obtained. The Mn 2p 3/2 and 1/2 main peaks and La 3d core spectrum shift to lower binding energy levels with increasing temperature. This XPS behavior is correlated with the strength of localization of Mn3+. The Jahn-Teller effect due to Mn3+ besides the conventional random potential effects is likely to localize charge carriers in La-.970Mn0.970O3.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.1
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• pp.38-44
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• 2011

Because of the complexity of the underwater environment, the communication has difficulties that can differ significantly from those in air, The signal is degraded by many random noises. Furthermore, the limit of the bandwidth is a big issue in underwater communication. Therefore, the array signal processing can be adapted to improve the signal-to-noise ratio. In this paper, we propose a potential method for underwater communication based upon source tracking techniques. Also, a new tracking model by using a multi-array sonar and detail of the multi-array sonar configuration are shown in this paper. The experiment results demonstrated the receiver configuration is very potential to solve communication problems, especially in the underwater environment.