• Corrosion Science and Technology
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• 제7권3호
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• pp.168-172
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• 2008

A new type of electrochemical random signal (electrochemical noise) analysis technique was applied to localized corrosion of anodic oxide film formed 1100 aluminum alloy in $0.5kmol/m^3$ $H_3BO_4/0.05kmol/m^3$ $Na_2B_4O_7$ with $0.01kmol/m^3$ NaCl. The effect of anodic oxide film structure, barrier type, porous type, and composite type on galvanic corrosion resistance was also examined. Before localized corrosion started, incubation period for pitting corrosion, both current and potential slightly change as initial value with time. The incubation period of porous type anodic oxide specimens are longer than that of barrier type anodic oxide specimens. While pitting corrosion, the current and potential were changed with fluctuations and the potential and the current fluctuations show a good correlation. The records of the current and potential were processed by calculating the power spectrum density (PSD) by the Fast Fourier Transform (FFT) method. The potential and current PSD decrease with increasing frequency, and the slopes are steeper than or equal to minus one (-1). This technique allows observation of electrochemical impedance changes during localized corrosion.

• ETRI Journal
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• 제38권1호
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• pp.141-148
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• 2016

This paper proposes a method to estimate directly the incoherent scattered intensity and radar cross section (RCS) from the effective permittivity of a random media. The proposed method is derived from the original concept of incoherent scattering. The incoherent scattered field is expressed as a simple formula. Therefore, to reduce computation time, the proposed method can estimate the incoherent scattered intensity and RCS of a random media. To verify the potential of the proposed method for the desired applications, we conducted a Monte-Carlo analysis using the method of moments; we characterized the accuracy of the proposed method using the normalized mean square error (NMSE). In addition, several medium parameters, such as the density of scatterers and analysis volume, were studied to understand their effect on the scattering characteristics of a random media. The results of the Monte-Carlo analysis show good agreement with those of the proposed method, and the NMSE values of the proposed method and Monte-Carlo analysis are relatively small at less than 0.05.

• 한국환경과학회지
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• 제26권4호
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• pp.521-527
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• 2017

Solar radiation forecasts are important for predicting the amount of ice on road and the potential solar energy. In an attempt to improve solar radiation predictability in Jeju, we conducted machine learning with various data mining techniques such as tree models, conditional inference tree, random forest, support vector machines and logistic regression. To validate machine learning models, the results from the simulation was compared with the solar radiation data observed over Jeju observation site. According to the model assesment, it can be seen that the solar radiation prediction using random forest is the most effective method. The error rate proposed by random forest data mining is 17%.

• 자원환경지질
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• 제17권3호
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• pp.163-169
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• 1984

암석의 대표적 열원치(熱源値)를 사용하여 지각 열류량(熱流量)의 반전(反轉)을 연구하였으며 2-D 모델은 아주 얇은 정방형판(正方形板)이 고려되었다. 포텐샬 이론을 기초로 하여 지각 열류량과 열원 사이의 새로운 관계를 도출하였으며 두가지 경우의 계산결과가 도시되어 있다. Random search 방법과 ridge regression방법이 비교되었으며 지각열류량의 반전(反轉) 연구에서는 random search 방법의 중요성이 발견되었다.

• Ocean Systems Engineering
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• 제1권4호
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• pp.355-372
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• 2011

Based on the fully nonlinear velocity potential theory, the liquid sloshing in a three dimensional tank under random excitation is studied. The governing Laplace equation with fully nonlinear boundary conditions on the moving free surface is solved using the indirect desingularized boundary integral equation method (DBIEM). The fourth-order predictor-corrector Adams-Bashforth-Moulton scheme (ABM4) and mixed Eulerian-Lagrangian (MEL) method are used for the time-stepping integration of the free surface boundary conditions. A smoothing scheme, B-spline curve, is applied to both the longitudinal and transverse directions of the tank to eliminate the possible saw-tooth instabilities. When the tank is undergoing one dimensional regular motion of small amplitude, the calculated results are found to be in very good agreement with linear analytical solution. In the simulation, the normal standing waves, travelling waves and bores are observed. The extensive calculation has been made for the tank undergoing specified random oscillation. The nonlinear effect of random sloshing wave is studied and the effect of peak frequency used for the generation of random oscillation is investigated. It is found that, even as the peak value of spectrum for oscillation becomes smaller, the maximum wave elevation on the side wall becomes bigger when the peak frequency is closer to the natural frequency.

• Wind and Structures
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• 제36권2호
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• pp.133-147
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• 2023

The random vibration of saddle membrane structures under wind load is studied theoretically and experimentally. First, the nonlinear random vibration differential equations of saddle membrane structures under wind loads are established based on von Karman's large deflection theory, thin shell theory and potential flow theory. The probabilistic density function (PDF) and its corresponding statistical parameters of the displacement response of membrane structure are obtained by using the diffusion process theory and the Fokker Planck Kolmogorov equation method (FPK) to solve the equation. Furthermore, a wind tunnel test is carried out to obtain the displacement time history data of the test model under wind load, and the statistical characteristics of the displacement time history of the prototype model are obtained by similarity theory and probability statistics method. Finally, the rationality of the theoretical model is verified by comparing the experimental model with the theoretical model. The results show that the theoretical model agrees with the experimental model, and the random vibration response can be effectively reduced by increasing the initial pretension force and the rise-span ratio within a certain range. The research methods can provide a theoretical reference for the random vibration of the membrane structure, and also be the foundation of structural reliability of membrane structure based on wind-induced response.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.187-192
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• 1992

There are several potential error sources that can affect the estimation of the position of an object using combined vision and acceleration measurements. Two of the major sources, accelerometer dynamics and random noise in both sensor outputs, are considered. Using a second-order model, the errors introduced by the accelerometer dynamics are reduced by the smaller value of damping ratio and larger value of natural frequency. A Kalman filter approach was developed to minimize the influence of random errors on the position estimate. Experimental results for the end-point movement of a flexible beam confirmed the efficacy of the Kalman filter algorithm.

• 한국한의학연구원논문집
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• 제13권1호통권19호
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• pp.147-152
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• 2007

As a result to amplifying 12 samples of 'Sok-dan' through an random amplified polymorphic DNA (RAPD) method using eighteen DEC and URP primers, distinct band forms enabling discrimination of Phlomus umbrosa and Dipsacus asperoides were observable in the UBC 320 primer, UBC 367 primer, UBC 385 primer, UBC 414 primer, UBC 423 primer, URP 3 primer, URP 5 primer and URP 9 primer. The polymorph result amplified with a random primer was evaluated through Gelcompar II, showing a result dividable into two groups. The divided groups were the dried sample group of Dipsacus asperoides and the group of Phlomis umbrosa. In order to recognize the distinction between Dipsaci Radix types, the genetic variation of 'Sok-dan' produced domestically and imported was evaluated through RAPD, and the potential to distinguish these in forms of dried medicine was identified, presenting a method to authentification of Phlomis umbrosa and Dispacus asperoides.

• International journal of advanced smart convergence
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• 제13권2호
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• pp.61-68
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• 2024

In the quest for advancing diabetes diagnosis, this study introduces a novel two-step machine learning approach that synergizes the probabilistic predictions of Logistic Regression with the classification prowess of Random Forest. Diabetes, a pervasive chronic disease impacting millions globally, necessitates precise and early detection to mitigate long-term complications. Traditional diagnostic methods, while effective, often entail invasive testing and may not fully leverage the patterns hidden in patient data. Addressing this gap, our research harnesses the predictive capability of Logistic Regression to estimate the likelihood of diabetes presence, followed by employing Random Forest to classify individuals into diabetic, pre-diabetic or nondiabetic categories based on the computed probabilities. This methodology not only capitalizes on the strengths of both algorithms-Logistic Regression's proficiency in estimating nuanced probabilities and Random Forest's robustness in classification-but also introduces a refined mechanism to enhance diagnostic accuracy. Through the application of this model to a comprehensive diabetes dataset, we demonstrate a marked improvement in diagnostic precision, as evidenced by superior performance metrics when compared to other machine learning approaches. Our findings underscore the potential of integrating diverse machine learning models to improve clinical decision-making processes, offering a promising avenue for the early and accurate diagnosis of diabetes and potentially other complex diseases.

• 한국산업정보학회논문지
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• 제17권7호
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• pp.139-148
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• 2012

분류기의 앙상블 학습은 여러 개의 서로 다른 분류기들의 조합을 통해 만들어진다. 앙상블 학습은 기계학습 분야에서 많은 관심을 끌고 있는 중요한 연구주제이며 대부분의 경우에 있어서 앙상블 모형은 개별 기저 분류기보다 더 좋은 성과를 내는 것으로 알려져 있다. 본 연구는 부도 예측 모형의 성능개선에 관한 연구이다. 이를 위해 본 연구에서는 단일 모형으로 그 우수성을 인정받고 있는 SVM을 기저 분류기로 사용하는 앙상블 모형에 대해 고찰하였다. SVM 모형의 성능 개선을 위해 bagging과 random subspace 모형을 부도 예측 문제에 적용해 보았으며 bagging 모형과 random subspace 모형의 성과 개선을 위해 bagging과 random subspace의 통합 모형을 제안하였다. 제안한 모형의 성과를 검증하기 위해 실제 기업의 부도 예측 데이터를 사용하여 실험하였고, 실험 결과 본 연구에서 제안한 새로운 형태의 통합 모형이 가장 좋은 성과를 보임을 알 수 있었다.