• Tunnel and Underground Space
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• v.25 no.1
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• pp.76-85
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• 2015

We have developed a software to predict failure time of the rock slope based on analysis of the data from real time displacement measurements with respect to time. The software consists of four modules that play roles in analytical methods such as inverse velocity method, log time-log velocity method, log velocity-log acceleration method and nonlinear least square method to estimate failure time. VisualBasic.NET on the MS Visual Studio platform was utilized as a development tool to efficiently implement the modules and the graphical user interface of the software. Displacement data obtained from laboratory physical model studies of plane sliding were used to explore the applicability of the software, and to evaluate the possibility of predicting potential slope failure. It seems possible to estimate failure time using developed software for sliding plane having exponential type of deformability.

• Journal of Applied Reliability
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• v.15 no.2
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• pp.90-100
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• 2015

Reliability growth rate (or reliability growth curve slope) have the two cases of trend as a constant or changing one during the reliability growth testing. The changing case is very common situation. The reasons of reliability growth rate changing are that the failures to follow the NHPP (None-Homogeneous Poisson Process), and the solutions implemented during test to break out other problems or not to take out all of the root cause permanently. If the changing were big, the "Goodness of Fit (GOF)" of reliability growth curve to test data would be very low and then reduce the accuracy of assessing result with test data. In this research, we are using Duane model and AMSAA model for assessing test data and projecting the reliability level of complex and repairable system as like construction equipment and vehicle. In case of no changing in reliability growth rate, it is reasonable for reliability engineer to implement the original Duane model (1964) and Crow-AMSAA model (1975) for the assessment and projection activity. However, in case of reliability growth rate changing, it is necessary to find the method to increase the "GOF" of reliability growth curves to test data. To increase GOF of reliability growth curves, it is necessary to find the proper parameter calculation method of interesting reliability growth models that are applicable to the situation of reliability growth rate changing. Since the Duane and AMSAA models have a characteristic to get more strong influence from the initial test (or failure) data than the latest one, the both models have a limitation to contain the latest test data information that is more important and better to assess test data in view of accuracy, especially when the reliability growth rate changing. The main objective of this research is to find the parameter calculation method to reflect the latest test data in the case of reliability growth rate changing. According to my experience in vehicle and construction equipment developments over 18 years, over the 90% in the total development cases are with such changing during the developing test. The objective of this research was to develop the newly assessing method and the process for GOF level increasing in case of reliability growth rate changing that would contribute to achieve more accurate assessing and projecting result. We also developed the new evaluation method for GOF that are applicable to the both models as Duane and AMSAA, so it is possible to compare it between models and check the effectiveness of new parameter calculation methods in any interesting situation. These research results can reduce the decision error for development process and business control with the accurately assessing and projecting result.

• Journal of Korea Water Resources Association
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• v.43 no.8
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• pp.695-707
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• 2010

The frequency and size of typhoon and local severe rainfall are increasing due to the climate change and the damage also increasing from typhoon and severe rainfall. The flood forecasting and warning system to reduce the damage from typhoon and severe rainfall needs forecasted rainfall using radar data and short-term rainfall forecasting model. For this reason, this study examined the applicability of short-term rainfall forecast using translation model with weather radar data to point out that the utilization of flood forecasting in Korea. This study estimated the radar rainfall using Least-square fitting method and estimated rainfall was used as initial field of translation model. The translation model have verified accuracy of forecasted radar rainfall through the comparison of forecasted radar rainfall and observed rainfall quantitatively and qualitatively. Almost case studies showed that accuracy is over 0.6 within 4 hours leading time and mean of correlation coefficient is over 0.5 within 1 hours leading time in Kwanak and Jindo radar site. And, as the increasing the leading time, the forecast accuracy of precipitation decreased. The results of the calculated Mean Area Precipitation (MAP) showed forecast rainfall tend to be underestimated than observed rainfall but the correlation coefficient more than 0.5. Therefore it showed that translation model could be accurately predicted the rainfall relatively. The present results indicate that possibility of translation model application of Korea just within 2 hours leading forecasted rainfall.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.12A
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• pp.1225-1232
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• 2008

In this paper, we describe a compensation method of diurnal effect which is one of the factors giving large effect on the performance when using ground-wave signals like Loran-C for a backup and substitute navigation system of global satellite navigation system such as GPS, and currently many researches of the topics are doing in USA and in Europe. In order to compensate diurnal effect, we find periodic frequency components by using the Least Square Spectral Analysis (LSSA) method at first and then compensate the effect by subtracting the estimated compensation signal, obtained by using the estimated amplitude and phase of the individual frequency component, from the original signal. In this paper, we propose a simple compensation algorithm and analysis the performance through simulations. From the results, it is observed that the amplitude and phase can be estimated with under 5 % and 0.17 % in a somewhat poor receiving situation with 0 dB Signal to Noise Ratio (SNR). Also, we analyze the obtainable performance improvement after compensation by using the measured Loran-C data. From the results, it is observed that we can get about 22 % performance improvement when a moving average with 5 minutes interval is employed.

• Smart Structures and Systems
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• v.31 no.1
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• pp.57-68
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• 2023

Bridge hangers, such as those in suspension and cable-stayed bridges, suffer from cumulative fatigue damage caused by dynamic loads (e.g., cyclic traffic and wind loads) in their service condition. Thus, the identification of damage to hangers is important in preserving the service life of the bridge structure. This study develops a new method for condition assessment of bridge hangers. The tension force of the bridge and the damages in the element level can be identified using the Bayesian optimization method. To improve the number of observed data, the additional mass method is combined the Bayesian optimization method. Numerical studies are presented to verify the accuracy and efficiency of the proposed method. The influence of different acquisition functions, which include expected improvement (EI), probability-of-improvement (PI), lower confidence bound (LCB), and expected improvement per second (EIPC), on the identification of damage to the bridge hanger is studied. Results show that the errors identified by the EI acquisition function are smaller than those identified by the other acquisition functions. The identification of the damage to the bridge hanger with various types of boundary conditions and different levels of measurement noise are also studied. Results show that both the severity of the damage and the tension force can be identified via the proposed method, thereby verifying the robustness of the proposed method. Compared to the genetic algorithm (GA), particle swarm optimization (PSO), and nonlinear least-square method (NLS), the Bayesian optimization (BO) performs best in identifying the structural damage and tension force.

• Journal of Digital Convergence
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• v.12 no.4
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• pp.277-283
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• 2014

Fuzzy modeling is generally using the given data and the fuzzy rules are established by the input variables and the space division by selecting the input variable and dividing the input space for each input variables. The premise part of the fuzzy rule is presented by selection of the input variables, the number of space division and membership functions and in this paper the consequent part of the fuzzy rule is identified by polynomial functions in the form of linear inference and modified quadratic. Parameter identification in the premise part devides input space Min-Max method using the minimum and maximum values of input data set and C-Means clustering algorithm forming input data into the hard clusters. The identification of the consequence parameters, namely polynomial coefficients, of each rule are carried out by the standard least square method. In this paper, membership function of the premise part is dividing input space by using trapezoid-type membership function and by using gas furnace process which is widely used in nonlinear process we evaluate the performance.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.721-730
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• 2020

This study investigates the impact of the country's governance on the revenue efficiency of 108 Islamic banks from 26 countries offering Islamic banking and finance products services. The technical efficiencies of individual Islamic banks have been analyzed using the Data Envelopment Analysis method. The data will be pooled across the selected countries and utilize the intermediation approach. The Ordinary Least Square estimation method is employed to examine the impact of country supervision and regulation on the technical efficiency of Islamic banks. As robustness check, the study examines the impact of the level of bank regulations and supervision on the efficiency of Islamic banks operating in different income-level countries. The results found that the stricter the supervisory power, the less strict capital requirement, the tighter the restrictions on non-banking activities, and the stricter the private monitoring enhance statistically significantly the level of efficiency of Islamic banks. In upgrading the regulations and supervision of the Islamic banks, the existing regulatory framework based on the Basel Committee on Banking Supervision (BCBS) must be complemented with the prescriptions on Islamic banking or Shariah compliance diligently, so that the Islamic banks could be regulated accurately and further improve the technical efficiency of their operations.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.3
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• pp.365-372
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• 2013

In this study, a statistical method for evaluating the fatigue life of a vehicle muffler was used to obtain reliable fatigue data using a limited number of specimens. Cyclic bending tests were conducted using specimens manufactured to be exactly the same as the mufflers installed in cars that are currently in use. To estimate the fatigue life by comparing the data obtained during the fatigue tests, the most suitable probability density function for the normal, lognormal, and Weibull distributions was selected. A goodness-of-fit test was performed on the probability distributions, and then a Weibull distribution using the least square method was selected. By using the selected Weibull distribution, the probability-moment-life curves (P-M-N curve) reflecting the fatigue characteristics were suggested as the data for the reliable design of a muffler.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.5
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• pp.30-38
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• 2006

A new calibration method for five-hole pressure probe is presented. This method provides accuracies better than those based on the traditional regression method. The calibration algorithm uses a single sector interpolation response surface calculated by comparing the regression curve fits with the actual calibration data. A five-hole pressure probe with hemispherical tip was fabricated and calibrated at Reynolds number of $4.11{\times}10^6$/m and flow angle of ${\pm}48$ degrees. Two data prediction models, the least-square regression and a single sector error interpolation, were evaluated. The comparison of these two calibration methods to a five-hole probe is described and discussed. An evaluation of the calibration accuracy is also given.

• The Journal of the Korea Contents Association
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• v.11 no.3
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• pp.48-55
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• 2011

In this paper, we analyze the input-output characteristics of fuzzy inference systems according to the division of entire input spaces and the fuzzy reasoning methods to identify the fuzzy model for nonlinear process. And fuzzy model is expressed by identifying the structure and parameters of the system by means of input variables, fuzzy partition of input spaces, and consequence polynomial functions. In the premise part of the rules Min-Max method using the minimum and maximum values of input data set and C-Means clustering algorithm forming input data into the hard clusters are used for identification of fuzzy model and membership function is used as a series of triangular membership function. In the consequence part of the rules fuzzy reasoning is conducted by two types of inferences. The identification of the consequence parameters, namely polynomial coefficients, of the rules are carried out by the standard least square method. And lastly, we use gas furnace process which is widely used in nonlinear process and we evaluate the performance for this nonlinear process.