• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.1
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• pp.131-138
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• 2000

This paper works on development of an algorithm for mapping of cerebral perfusion parameters using the gamma-variate curve fitting. The signal intensity variate curve according to time measured in each pixel of perfusion MRI is nonlinear, and various hemodynamic parameters are not computed accurately. Levenberg-Marquardt algorithm(LMA), nonlinear optimum algorithm with high convergent speed and stability, is used to compute them. That is, the signal intensity variate curve is fitted by the gamma-variate function. Various hemodynamic parameters - Cerebral Blood Volume(C.B.V), Mean Transit Time(M.T.T), Cerebral Blood Flow(C.B.F), Time-to-Peak(T.T.P), Bolus Arrival Time(B.A.T), Maximum Slope(M.S) - are computed using LMA.

• Journal of the Korean Society for Nondestructive Testing
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• v.29 no.5
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• pp.466-472
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• 2009

An acoustic leak monitoring system(ALMS) using acoustic emission(AE) technique was applied for leakage detection of nuclear power plant's pipeline which is operated in high temperature and pressure condition. Since this system only monitors the existence of leak using the root mean square(RMS) value of raw signal from AE sensor, the difficulty occurs when the characteristics of leak size and shape need to be evaluated. In this study, dual monitoring system using AE sensor and accelerometer was introduced in order to solve this problem. In addition, artificial neural network(ANN) with Levenberg.Marquardt(LM) training algorithm was also applied due to rapid training rate and gave the reliable classification performance. The input parameters of this ANN were extracted from varying signal received from experimental conditions such as the fluid pressure inside pipe, the shape and size of the leak area. Additional experiments were also carried out and with different objective which is to study the generation and characteristic of lamb and surface wave according to the pipe thickness.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.39-42
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• 2004

We have designed a portable electronic nose(e-nose) system using an array of commercial gas sensors for recognition and analyzing the various odours. In this paper, we have implemented a portable e-nose system using an array gas sensors and personal digital assistants(PDA) for recognizing and analyzing volatile organic compounds(VOCs) in the field. Field screening for pollutants has been a target of instrumental development for number of year. A portable e-nose system can be substantial benefit to rapidly localize the spacial extent of a pollution or to find pollutants source. And, by using PDA, E-nose have a better function such as the easy user-interface and data transfer by internet from on- site to remote computer. We adapted the Levenberg-Marquardt algorithm based on the back-propagation and proposed the method that could be predicted concentration levels of VOCs gases after classification by separating neural network into two parts.

• Journal of Advanced Marine Engineering and Technology
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• v.27 no.5
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• pp.641-647
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• 2003

The use of infrared range-finder sensor as the environment recognition system for mobile robot have the advantage of low sensing cost compared with the use of other vision sensor such as laser finder CCD camera. However, it is not easy to find the previous works on the use of infrared range-finder sensor for a mobile robot because of the non-linear characteristic of that. This paper describes the error due to non-linearity of a sensor and the correction of it using neural network. The neural network consists of multi-layer perception and Levenberg-Marquardt algorithm is applied to learning it. The effectiveness of the proposed algorithm is verified from experiment.

• Journal of the Korean Society for Precision Engineering
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• v.34 no.1
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• pp.23-27
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• 2017

This paper aims to develop a prediction model for the product quality of a casting process. Prediction of the product quality utilizes an artificial neural network (ANN) in order to renovate the manufacturing technology of the root industry. Various aspects of the research on the prediction algorithm for the casting process using an ANN have been investigated. First, the key process parameters have been selected by means of a statistics analysis of the process data. Then, the optimal number of the layers and neurons in the ANN structure is established. Next, feed-forward back propagation and the Levenberg-Marquardt algorithm are selected to be used for training. Simulation of the predicted product quality shows that the prediction is accurate. Finally, the proposed method shows that use of the ANN can be an effective tool for predicting the results of the casting process.

• Proceedings of the IEEK Conference
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• 2001.06a
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• pp.173-176
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• 2001

Several dielectric as well as conducting cylinders buried in the lossy half space are reconstructed from the scattered fields measured along the interface between the air and the lossy ground. Iterative inversion method by using the hybrid optimization algorithm combining the genetic and the Levenberg-Marquardt algorithm enables us to find the positions, the sizes, and the medium parameters such as the permittivities and the conductivities of the buried cylinders as well as those of the background lossy half space. Illposedness of the inversion caused by the errors in the measured scattered fields are regularized by filtering the evanescent modes of the scattered fields out.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.11
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• pp.124-131
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• 2001

Fault diagnosis of an assembled small motor relies usually on human experts hearing ability. The quality of diagnosis depends, however, heavily on physical conditions of the human experts. A fault diagnosis system for assembled small motors is developed using artificial neural network (ANN) in this paper. It is consisted of sound sampling device and fault diagnosis software package. Six parameters are defined to characterize the sampled sound waves. The Levenberg-Marquardt Backpropagation (LMBP) Algorithm is used to diagnose the fault of assembled small motors. Experimental results for more than two hundred small motors verify the performance of the developed system.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.762-766
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• 2003

In this paper, we present a new approach to solve the problem of estimating the camera 3-D location and orientation from a matched set of 3-D model and 2-D image features. An iterative least-square method is used to solve both rotation and translation simultaneously. Because conventional methods that solved for rotation first and then translation do not provide good solutions, we derive an error equation using roll-pitch-yaw angle to present the rotation matrix. To minimize the error equation, Levenberg-Marquardt algorithm is introduced with uniform sampling strategy of rotation space to avoid stuck in local minimum. Experimental results using real images are presented.

• Journal of Astronomy and Space Sciences
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• v.27 no.4
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• pp.279-288
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• 2010

To study properties of the pulsation in the infrared emission for long period variables, we have collected and analyzed the infrared observational data at M band for 12 OH/IR stars. We present the light curves using the data that cover about 30 years including recent observations of ISO and Spitzer. We use Marquardt-Levenberg algorithm to determine the pulsation periods and amplitudes and compare them with previous results of infrared and radio investigations. Generally, the newly determined pulsation parameters show much less errors because of the larger database. We find that the relationship between the pulsation period and amplitudes at M band is fairly well fitted with a simple linear equation in a wide period range. For OH 42.3-0.1, we find some evidences that the object could be a post-asymptotic giant branch star.

• Journal of Astronomy and Space Sciences
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• v.26 no.3
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• pp.279-286
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• 2009

To study properties of the variation of the infrared emission of OH/IR stars, we collect and analyze the infrared observational data in K band for nine OH/IR stars. We use the observational data obtained for about three decades including recent data from the two micron all sky survey (2MASS) and the deep near infrared survey of the southern sky (DENIS). We use Marquardt-Levenberg algorithm to determine the pulsation period and amplitude for each star and compare them with previous results of infrared and radio investigations.