• Proceedings of the KIPE Conference
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• 1998.07a
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• pp.143-148
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• 1998

A dynamic electrical parameter monitoring device was designed to simultaneously record the instantaneous value of voltage, current, power, and resistance during spot welding. The data obtained using this technique have been analyzed in term of the relationships of these parameters to the phenomena occuring during the formation(surface break-down, nugget formation and mechanical collapse) of spot weld. Finally, a database implementation is undertaken to develop techniques for improving weld quality of the resistance spot welder.

• MALSORI
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• v.55
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• pp.119-130
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• 2005

The aim of this paper is to investigate some acoustical characteristics of the voice quality features from the emotional speech database. Six different parameters are measured and compared for 6 different emotions (normal, happiness, sadness, fear, anger, boredom) and from 6 different speakers. Inter-speaker variability and intra-speaker variability are measured. Some intra-speaker consistency of the parameter change across the emotions are observed, but inter-speaker consistency are not observed.

• Proceedings of the KSPS conference
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• 2003.05a
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• pp.145-148
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• 2003

In this paper, we carried out comparative study about various feature parameters for the effective speaker recognition such as LPC, LPCC, MFCC, Log Area Ratio, Reflection Coefficients, Inverse Sine, and Delta Parameter. We also adopted cepstral liftering and cepstral mean subtraction methods to check their usefulness. Our recognition system is HMM based one with 4 connected-Korean-digit speech database. Various experimental results will help to select the most effective parameter for speaker recognition.

• 한국연소학회:학술대회논문집
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• 2003.05a
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• pp.57-62
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• 2003

A general procedure of obtaining reliable one-step kinetics model for hydrocarbon mixture from the fully detailed chemistry is described iin this study. One-step theoretical formulation of the induction parameter model IPM uses a theoretical reconstruction of the induction time database obtained from a detailed kinetics library. Non-dimensional induction time calculations is compared with that of detailed kinetics. The IPM was latter implemented to fluid dynamics code and applied for the numerical simulation of detonation wave propagation. The numerical results including the numerical smoked-foil record show the all the details of the detonation wave propagation characteristics at the cost around 1/100 of the detailed kinetics calculation.

• Journal of Korean Society of Steel Construction
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• v.10 no.1 s.34
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• pp.37-45
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• 1998

The relational database system on fatigue strength was constructed, and the properties of fatigue life distribution were examined to analyze reliability and safety of metallic materials. Data manipulations were efficiently performed in relational fatigue strength database system using dependency diagram. Regardless of the distribution of fatigue strength, the proposed method, the Robust method and the complementary error function method using probability distribution, successfully estimated parameters of the 3-parameter Weibull distribution. The proposed criterion for estimating non-failure probability showed good results regardless of censoring time. The fatigue life distribution function described as a function of parameters of the Weibull distribution and applied stress ratio produced P-S-N characteristics reasonably.

• International Journal of Aeronautical and Space Sciences
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• v.16 no.3
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• pp.425-436
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• 2015

This paper presents the procedures used for estimating the stability and control derivatives of a general aviation canard aircraft from flight data. The maximum likelihood estimation method which accounts for both process and measurement noise was used for the flight data analysis of a four seat canard aircraft, the Firefly. Without relying on the parameter estimation method, several aerodynamic derivatives were obtained by analyzing the steady state flight data. A wind tunnel test, a flight test of a 1/4 scaled remotely controlled model aircraft, and the prediction of aerodynamic coefficients using the USAF Stability and Control Digital Data Compendium (DATCOM), Advanced Aircraft Analysis (AAA), and Computer Fluid Dynamics (CFD) were performed during the development phase of the Firefly and the results were compared with flight determined derivatives of a full scaled flight prototype. A correlation between the results from each method could be used for the design of the canard aircraft as well as for building the aerodynamic database.

• Korean Journal of Geomatics
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• v.5 no.1
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• pp.21-26
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• 2005

According to revisions of survey law taking effect on January 1, 2003, the Korean geodetic datum has been changed from a local geodetic to a world geodetic system. In this study, the datum transformation parameters especially for the maritime geographical data are determined. From database constructed through MGIS, a total of 492 coordinate pairs were selected and used in the parameter determination after outlier testing. Based on the parameter estimation, the Molodensky model is selected for datum transformation. For higher accuracy, Application of network optimization and a least squares collocation with Gaussian model has resulted in the accuracy better than 15 cm in coordinate transformation.

• Nuclear Engineering and Technology
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• v.53 no.4
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• pp.1199-1209
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• 2021

The detection of unexpected loose parts in the primary coolant system in a nuclear power plant remains an extremely important issue. It is essential to develop a methodology for the localization and mass estimation of loose parts owing to the high prediction error of conventional methods. An effective approach is presented for the localization and mass estimation of a loose part using machine-learning and deep-learning algorithms. First, a methodology was developed to estimate both the impact location and the mass of a loose part at the same times in a real structure in which geometric changes exist. Second, an impact database was constructed through a series of impact finite-element analyses (FEAs). Then, impact parameter prediction modes were generated for localization and mass estimation of a simulated metallic loose part using machine-learning algorithms (artificial neural network, Gaussian process, and support vector machine) and a deep-learning algorithm (convolutional neural network). The usefulness of the methodology was validated through blind tests, and the noise effect of the training data was also investigated. The high performance obtained in this study shows that the proposed methodology using an FEA-based database and deep learning is useful for localization and mass estimation of loose parts on site.

• Journal of The Korean Astronomical Society
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• v.37 no.4
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• pp.137-141
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• 2004

We have estimated the fractal dimension of the molecular clouds in the Antigalactic Center based on the $^{12}CO$ (J = 1- 0) and $^{13}CO$ (J = 1- 0) database obtained using the 14m telescope at Taeduk Radio Astronomy Observatory. Using a developed code within IRAF, we were able to identify slice-clouds, and determined the dispersions of two spatial coordinates as well as perimeters and areas. The fractal dimension of the target region was estimated to be D = 1.34 for low resolution $^{12}CO$ (J = 1 - 0) database, and D = 1.4 for higher resolution $^{12}CO$ (J = 1 - 0) and $^{13}CO$ (J = 1 - 0) database, where $P {\propto} A^{D/2}$. The sampling rate (spatial resolution) of observed data must be an important parameter when estimating fractal dimension. Our database with higher resolution of 1 arcminute, which is corresponding to 0.2 pc at a distance of 1.1 kpc, gives us the same estimate of fractal dimension to that of local dark clouds. Fractal dimension is apparently invariant when varying the threshold temperatures applied to cloud identification. According to the dispersion pattern of longitudes and latitudes of identified slice-clouds, there is no preference of elongation direction.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.46-51
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• 2004

his paper presents a novel design technique for the TS fuzzy classifier via linear matrix inequalities(LMI). To design the TS fuzzy classifier built by the TS fuzzy model, the consequent parameters are determined to maximize the classifier's performance. Differ from the conventional fuzzy classifier design techniques, convex optimization technique is used to resolve the determination problem. Consequent parameter identification problems are first reformulated to the convex optimization problem. The convex optimization problem is then efficiently solved by converting linear matrix inequality problems. The TS fuzzy classifier has the optimal consequent parameter via the proposed design procedure in sense of the minimum classification error. Simulations are given to evaluate the proposed fuzzy classifier; Iris data classification and Wisconsin Breast Cancer Database data classification. Finally, simulation results show the utility of the integrated linear matrix inequalities approach to design of the TS fuzzy classifier.