• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.76-80
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• 2000

This paper describes a coordinate measuring technique based on optical triangulation using the two images. To overcome the defect of structured light system which measures coordinate point by point, light source is replaced by CCD camera. Pixels in CCD camera were considered as virtual light source. The overall geometry including two camera images is modeled. Using this geometry, the formula for calculating 3D coordinate of specified point is derived. In a word, the ray from a virtual light source was reflected on measuring point and the corresponding image point was made on the other image. Through the simulation result, validation of formula is verified. This method enables to acquire multiple points detection by photographing.

• Journal of Mechanical Science and Technology
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• v.15 no.12
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• pp.1691-1698
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• 2001

In recent years, significant progress has been made in modeling turbulence behavior in plasma and its effect on transport. It has also been made in diagnostics for turbulence measurement; however, there is still a large gap between theoretical model and experimental measurements. Visualization of turbulence can improve the connection to theory and validation of the theoretical model. One method to visualize the flow structures in plasma is a laser Schlieren imaging technique. We have recently applied this technique and investigated the characteristics of a highly underexpanded pulsed plasma jet originating from an electrothermal capillary source. Measurements include temporally resolved laser Schlieren imaging of a precursor blast wave. Analysis on the trajectory of the precursor blast wave shows that it does not follow the scaling expected for a strong shock resulting from the instantaneous deposition of energy at a point. However, the shock velocity does scale as the square root of the deposited energy, in accordance with the point deposition approximation.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.453-456
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• 1992

Diagnostic prototype expert system was developed by analyzing the measured acoustical data of automobile. For the utilities of this system, 1/3 octave filter(band-pass filter) and A/D converter were used for data acquisition and then information was analyzed using signal processing technique and pattern recognition by Hamming network algorithm. In order to raise the reliability of the diagnostic results, fuzzy inference technique was applied and, the results were displayed as graphical method to help the novice in diagnostic field. The validation of this diagnostic system was checked through experiments and it showed and acceptable performance for diagnostic process.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.28 no.5
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• pp.510-517
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• 2004

A fine hot-wire is used both as a heating element and a temperature sensor in transient hot-wire method. The traditional sensor system is unnecessarily big so that it takes large fluid volume to measure the thermal conductivity. To dramatically reduce this fluid volume, a new sensor fabrication and a data processing method are proposed in this article. Contrast to the conventional and most popular two wire sensor, the new sensor system is made up of divided multiple long and short wires. Through validation experiments, it is found that the measured thermal conductivities of the glycerin are exactly same each other between the conventional and proposed new method. Also some technical considerations in arranging the multiple wires are briefly discussed.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.210-215
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• 2003

A fine hot-wire is used both as a heating element and a temperature sensor in transient hot-wire method. The traditional sensor system is unnecessarily big so that it takes large fluid volume to measure the thermal conductivity. To dramatically reduce this fluid volume, a new sensor fabrication and a data processing method are proposed in this article. Contrast to the conventional and most popular two wire sensor, the new sensor system is made up of divided multiple long and short wires. Through validation experiments, it is found that the measured thermal conductivities of the glycerin are exactly same each other between the conventional and proposed new method. Also some technical considerations in arranging the multiple wires are briefly discussed.

• Transactions of the Korean Society of Automotive Engineers
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• v.1 no.3
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• pp.55-62
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• 1993

Autoregressive moving average(ARMA) model which is a time domain parametric modeling method is implemented for modeling and reproducing characteristics of exhaust noise of an automobile in various RPM range. Experiments have been carried out using 9 set of exhaust noise signals measured at 1,000-3,000 RPM range. Characteristics of sampled signals were estimated using ARMA modeling and Akaike's FPE(final prediction error) criterion to define exact model structure and for model validation. The digital filter consisted of the esitmated ARMA(70,1) model parameters was programed to reproduce exhaust noise. The spectral analysis of reproduced noise is very close to original. The results show that our approaching technique for reproducing acoustic characteristics is valid and feasible to apply in the field of noise quality control.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.1
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• pp.55-74
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• 2005

Bankruptcy prediction has drawn a lot of research interests in previous literature, and recent studies have shown that machine learning techniques achieved better performance than traditional statistical ones. This paper employs a relatively new machine learning technique, support vector machines (SVMs). to bankruptcy prediction problem in an attempt to suggest a new model with better explanatory power and stability. To serve this purpose, we use grid search technique using 5-fold cross-validation to find out the optimal values of the parameters of kernel function of SVM. In addition, to evaluate the prediction accuracy of SVM. we compare its performance with multiple discriminant analysis (MDA), logistic regression analysis (Logit), and three-layer fully connected back-propagation neural networks (BPNs). The experiment results show that SVM outperforms the other methods.

• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.5
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• pp.920-938
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• 2015

In the present study, a numerical prediction method on the hydrodynamic interaction force and moment between two ships in shallow and restricted waterway is presented. Especially, the present study proposes a methodology to overcome the limitation of the two dimensional perturbation method which is related to the moored-passing ship interaction. The validation study was performed and compared with the experiment, firstly. Afterward, in order to propose a methodology in terms with the moored-passing ship interaction, further studies were performed for the moored-passing ship case with a Reynolds Averaged Navier-Stokes (RANS) calculation which is using OpenFOAM with Arbitrary Coupled Mesh Interface (ACMI) technique and compared with the experiment result. Finally, the present study proposes a guide to apply the two dimensional perturbation method to the moored-passing ship interaction. In addition, it presents a possibility that the RANS calculation with ACMI can applied to the ship-ship interaction without using a overset moving grid technique.

• Journal of the Korea Safety Management & Science
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• v.8 no.2
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• pp.51-59
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• 2006

So far, there is no technique of quantitative evaluation on danger related to industrial accidents. Therefore, as an endeavor for obtaining technique of quantitative evaluation, this study presents feature analysis of industrial accidents in manufacturing field using QUEST algorithm. In order to analyze feature of industrial accidents, a retrospective analysis was performed in 10,536 subjects (10,313 injured people, 223 deaths). The sample for this work chosen from data related to manufacturing businesses during three years $(2002\sim2004)$ in Korea. The analysis results were very informative since those enable us to know the most important variables such as occurrence type, company size, and occurrence time which can affect injured people. Also, it is found that classification using QUEST algorithm which was performed in this study is very reliable.

• Proceedings of the Korea Association of Information Systems Conference
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• 2000.11a
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• pp.36-44
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• 2000

The purpose of this study is to introduce a more efficient forecasting technique, which could help result the reduction of cost in removing the waste of airline in-flight meals. We will use a neural network approach known to many researchers as the “Outstanding Forecasting Technique”. We employed a multi-layer perceptron neural network using a backpropagation algorithm. We also suggested using other related information to improve the forecasting performances of neural networks. We divided the data into three sets, which are training data set, cross validation data set, and test data set. Time lag variables are still employed in our model according to the general view of time series forecasting. We measured the accuracy of our model by “Mean Square Error”(MSE). The suggested model proved most excellent in serving economy class in-flight meals. Forecasting the exact amount of meals needed for each airline could reduce the waste of meals and therefore, lead to the reduction of cost. Better yet, it could enhance the cost competition of each airline, keep the schedules on time, and lead to better service.