• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.11a
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• pp.796-801
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• 2000

The monitoring and diagnostics of the rotating machinery have been received considerable attention for many years. The objectives are to classify the machinery condition and to find out the cause of abnormal condition. This paper describes a signal classification method for diagnosing the rotating machinery using the artificial neural network and the wavelet transform. In order to extract salient features, the wavelet transform are used from primary noise signals. Since the wavelet transform decomposes raw time-waveform signals into two respective parts in the time space and frequency domain, more and better features can be obtained easier than time-waveform analysis. In the training phase for classification, self-organizing feature map(SOFM) and learning vector quantization(LVQ) are applied, and the accuracies of them are compared with each other. This paper is focused on the development of an advanced signal classifier to automatise the vibration signal pattern recognition. This method is verified by small reciprocating compressors, for refrigerator and normal and abnormal conditions are classified with high flexibility and reliability.

• The Journal of the Acoustical Society of Korea
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• v.13 no.4
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• pp.40-49
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• 1994

In this paper, we propose methods for improving the performance of word recognition system. The ray stratey of the first method is to apply the inertia to the feature vector sequences of speech signal to stabilize the transitions between VQ cdoes. The second method is generating the new observation probabilities using the transition matrix of VQ codes as weights at the observation probability of the output symbol, so as to take into account the time relation between neighboring frames in DHMM. By applying the inertia to the feature vector sequences, we can reduce the overlapping of probability distribution of the response paths for each word and stabilize state transitions in the HMM. By using the transition matrix of VQ codes as weights in conventional DHMM. we can divide the probability distribution of feature vectors more and more, and restrict the feature distribution to a suitable region so that the performance of recognition system can improve. To evaluate the performance of the proposed methods, we carried out experiments for 50 DDD area names. As a result, the proposed methods improved the recognition rate by $4.2\%$ in the speaker-dependent test and $12.45\%$ in the speaker-independent test, respectively, compared with the conventional DHMM.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.4 s.316
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• pp.8-14
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• 2007

Social participation of the elderly and people with disabilities continuously becomes more active due to improvement of social systems and technological development. Various assistive systems, such as intelligence robots and intelligence home systems, have been developed to support the social participation, and obviously contributed to independent lives of the elderly and people with disabilities. These systems, however, usually require expensive special hardware. To relieve a financial burden software-oriented approaches, which utilizes existing hardware such as laptops, can be an alternative. The software should be developed considering users with physical limitation and without much knowledge of computers. This paper suggests software-oriented approaches to solve these problems and describes an actual development procedure of the software with related theories. We also introduce an unified user interface for a special work chair as a real application.

• The Transactions of the Korea Information Processing Society
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• v.4 no.7
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• pp.1749-1758
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• 1997

This paper suggests the development of dynamic forecasting model for short-term power demand based on Radial Basis Function Network and Pal's GLVQ algorithm. Radial Basis Function methods are often compared with the backpropagation training, feed-forward network, which is the most widely used neural network paradigm. The Radial Basis Function Network is a single hidden layer feed-forward neural network. Each node of the hidden layer has a parameter vector called center. This center is determined by clustering algorithm. Theatments of classical approached to clustering methods include theories by Hartigan(K-means algorithm), Kohonen(Self Organized Feature Maps %3A SOFM and Learning Vector Quantization %3A LVQ model), Carpenter and Grossberg(ART-2 model). In this model, the first approach organizes the load pattern into two clusters by Pal's GLVQ clustering algorithm. The reason of using GLVQ algorithm in this model is that GLVQ algorithm can classify the patterns better than other algorithms. And the second approach forecasts hourly load patterns by radial basis function network which has been constructed two hidden nodes. These nodes are determined from the cluster centers of the GLVQ in first step. This model was applied to forecast the hourly loads on Mar. $4^{th},\;Jun.\;4^{th},\;Jul.\;4^{th},\;Sep.\;4^{th},\;Nov.\;4^{th},$ 1995, after having trained the data for the days from Mar. $1^{th}\;to\;3^{th},\;from\;Jun.\;1^{th}\;to\;3^{th},\;from\;Jul.\;1^{th}\;to\;3^{th},\;from\;Sep.\;1^{th}\;to\;3^{th},\;and\;from\;Nov.\;1^{th}\;to\;3^{th},$ 1995, respectively. In the experiments, the average absolute errors of one-hour ahead forecasts on utility actual data are shown to be 1.3795%.

• Journal of Embryo Transfer
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• v.12 no.3
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• pp.293-300
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• 1997

Supplementation of maturation medium with additional granulosa cells has beneficial effect on in vitro maturation of bovine follicular oocytes and their subsequent cleavage and development in vitro. However, maturation system using granulosa cells have some disadvantages that collection of granulosa cells is cumbersome and metabolic activity of the cells is variable according to ovarian cycle or follicular size. We hypothesized that bovine immsture oocytes matured without granulosa cell coculture can fertilize and develop normally if the medium volume per oocyte is reduced during in vitro maturation. Immature oocytes were matured for 24 hours in a TCM199 containing 10% fetal calf serum, anterior pitultary hormone (0.02 AU /ml Antrinⓡ) and estradiol with or without granulosa cells in vitro. In Group 1, 35 to 40 oocytes were matured in a well of 4-well plastic dish containing 500 $\mu$l of maturation medium and granulosa cells, and 9 to 10 oocytes were matured in a 50-$\mu$l drop of maturation medium without granulosa cells in Group 2. After maturation, oocytes were coincubated with sperm for 30 hours in a modified Tyrode's medium (IVF). Inseminated oocytes were cultured in a microdrop (30 $\mu$l) of a synthetic oviduct fluld medium (SOFM) containing BSA, Minimum Essential Medium essential and non-essential amino acids for 9 days. As a preliminary experiment, we investigated the beneficial effect of granulosa cells during maturation on subsequent cleavage and development using the same type of culturedishes (4-well dish). Granulosa cells could not increase embryo cleavage after fertilization but significantly improved (p<0.05) embryo development to expanding blastocyst (Table1 and 2). In Group 1, 68 and 80% of inseminated oocytes have cleaved at 30 hours and 2 days after IVF, respectively, which is similar (p>0.05) to the result of Group 2 (69% at 30 hours and 78% at 2 days after IVF). The oocytes in Group 2 showed 21 and 11% of developmental rates to expanding and hatching blastocysts, respectively, which was not significantly different (p>0.05) from those (20 and 10%, respectively) of oocytes in Group 1. In conclusion, it has been clarified that a microdrop culture system without granulosa cells for in vitro maturation can support bovine embryonic development to blastocyst in vitro as readily as a granulosa cell coculture system.