• Journal of the Korean Society for Precision Engineering
• /
• v.19 no.1
• /
• pp.48-55
• /
• 2002

This paper deals with the sensing ability of the smart sensor that has the sensing ability to distinguish materials according to the input condition changing. This is a study of dynamic characteristics of sensor. We have developed a new signal processing method that can distinguish among different materials. The smart sensor was developed for recognition of materials. Experiments and analysis were executed to estimate ability to recognize objects according to the input condition. First, we developed the advanced smart sensor. Second, we developed the new method, which has the capability sensing of different materials. Dynamic characteristics of the smart sensor were evaluated relatively through a new $R_{SAI}$ method. According to frequency changing, influence of the smart sensor are evaluated through a new recognition index ($R_{SAI}$) that ratio of sensing ability index. Applications of this method are for finding abnormal conditions of objects (auto-manufacturing), feeling of objects (medical product), robotics, safely diagnosis of structure, etc.

• Korean Journal of Culture and Social Issue
• /
• v.11 no.4
• /
• pp.83-95
• /
• 2005

The purpose of the present study was to investigate the relationship between spatial-erceptual ability and several aspects of driving-related situation awareness(in particular, recognition and prediction). Video clips of real driving were used in both recognition and prediction tasks, and the digit calculation task during driving the simulator was required as the integration task of recognition and prediction. The results showed that the subjects of higher spatial-perceptual ability performed better in recognition task, especially in terms of sensitivity measured in d'(as signal detection theory), prediction task, and digits calculation performance than those of lower spatial-perceptual ability.

• The Transactions of the Korean Institute of Electrical Engineers C
• /
• v.53 no.10
• /
• pp.515-522
• /
• 2004

In this study, we tried to investigate that the advantages of SOM(Self Organizing Map) algorithm such as data accumulation ability and the degradation trend trace ability would be adaptable to the analysis of partial discharge pattern recognition. For the purpose, we analyzed partial discharge data obtained from the typical artificial defects in GIS and XLPE power cable system through SOM algorithm. As a result, partial discharge pattern recognition could be well carried out with an acceptable error by use of Kohonen map in SOM algorithm. Also, it was clarified that the additional data could be accumulated during the operation of the algorithm. Especially, we found out that the data accumulation ability of Kohonen map could make it possible to suggest new patterns, which is impossible through the conventional BP(Back Propagation) algorithm. In addition, it is confirmed that the degradation trend could be easily traced in accordance with the degradation process. Therefore, it is expected to improve on-site applicability and to trace real-time degradation trends using SOM algorithm in the partial discharge pattern recognition

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.27 no.11
• /
• pp.1864-1872
• /
• 2003

Hidden Markov Model(HMM) has been widely used in speech recognition, however, its use in machine condition monitoring has been very limited despite its good potential. In this paper, HMM is used to recognize rotor fault pattern. First, we set up rotor kit under unbalance and oil whirl conditions. Time signals of two failure conditions were sampled and translated to auto power spectrums. Using filter bank, feature vectors were calculated from these auto power spectrums. Next, continuous HMM and discrete HMM were trained with scaled forward/backward variables and diagonal covariance matrix. Finally, each HMM was applied to all sampled data to prove fault recognition ability. It was found that HMM has good recognition ability despite of small number of training data set in rotor fault pattern recognition.

• Journal of The Korean Society of Integrative Medicine
• /
• v.3 no.1
• /
• pp.63-69
• /
• 2015

Purpose: The purpose of this study was to investigate the differences in emotion recognition according to general characteristics of stroke patients. Method: The subjects consisted of 38 stroke patients receiving rehabilitation at S Hospital in Busan. Used the eMETT program to assess emotional cognition. Result: The age and duration of disease showed statistically significant differences in emotion recognition ability score, the gender and lesion showed a statistically significant difference in some emotion(p<.05). Conclusion: The results of this study it can be seen that the difference in emotion recognition ability in accordance with the general characteristics of the stroke. There will be a variety of future research related to standardized research or interventions targeted at stroke patients and normal controls to be carried out.

• Proceedings of the KIEE Conference
• /
• 2004.05a
• /
• pp.123-125
• /
• 2004

Recently, we are getting to interest in a user friendly machine. The emotion is one of most important conditions to be familiar with people. The machine uses sound or image to express or recognize the emotion. This paper deals with the method of recognizing emotion from the sound. The most important emotional component of sound is a tone. Also, the inference ability of a brain takes part in the emotion recognition. This paper finds empirically the emotional components from the speech and experiment on the emotion recognition. This paper also proposes the recognition method using these emotional components and the transition probability.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.49.4-49
• /
• 2001

Digit recognition based on backpropagation neural networks, as an important application of pattern recognition, was attracted much attention. Although it has the advantages of parallel calculation, high error-tolerance, and learning capability, better recognition effects can only be achieved with some specific fixed format input of the digit image. Therefore, digit image preprocessing ability directly affects the accuracy of recognition. Here using Matlab software, the digit image was enhanced by resizing and neutral-rotating the extracted digit image, which improved the digit recognition capability of the backpropagation neural network under practical conditions. This method may also be helpful for recognition of other patterns with backpropagation neural networks.

• Communications of Mathematical Education
• /
• v.29 no.3
• /
• pp.513-532
• /
• 2015

In order to suggest desirable management of college mathematics for freshmen in middle level engineering college, we analyse the change of mathematics recognition between 2011 year and 2015 year freshmen who took college scholastic ability test which are based on the national mathematics curriculum 7th and 7th revision, respectively. In A university, 2011 year and 2015 year engineering freshmen were taken basic mathematical ability test and given the survey for the recognition of mathematics and college mathematics. Research results are as follows: First of all, middle level engineering freshmen were poor at basic mathematical ability. The change of mathematics recognition appeared in the level of mathematics ability and the effort for college mathematics class. Moreover middle level engineering freshmen recognize college mathematics as a basic subject for engineering and hope teacher-directed learning in college mathematics class. For the success of college mathematics in engineering college, this study suggests basic mathematical ability test and the survey for the recognition of mathematics and college mathematics. We also suggest that college mathematics class must be focused on basic mathematical ability improvement and self-directed learning.

• The KSFM Journal of Fluid Machinery
• /
• v.7 no.2 s.23
• /
• pp.41-49
• /
• 2004

Condition monitoring is very important in turbo machinery because single failure could cause critical damages to its plant. So, automatic fault recognition has been one of the main research topics in condition monitoring area. We have used a relatively new fault recognition method, Hidden Markov Model(HMM), for mechanical system. It has been widely used in speech recognition, however, its application to fault recognition of mechanical signal has been very limited despite its good potential. In this paper, discrete HMM(DHMM) was used to recognize the faults of rotor system to study its fault recognition ability. We set up a rotor kit under unbalance and oil whirl conditions and sampled vibration signals of two failure conditions. DHMMS of each failure condition were trained using sampled signals. Next, we changed the setup and the rotating speed of the rotor kit. We sampled vibration signals and each DHMM was applied to these sampled data. It was found that DHMMs trained by data of one rotating speed have shown good fault recognition ability in spite of lack of training data, but DHMMs trained by data of four different rotating speeds have shown better robustness.

• Phonetics and Speech Sciences
• /
• v.3 no.1
• /
• pp.117-123
• /
• 2011

Most individuals with hearing impairment have difficulty in understanding speech in noisy situations. This study was conducted to investigate sentence recognition ability using the Korean Standard-Sentence Lists for Preschoolers (KS-SL-P2) in pre-school age children with cochlear implants and hearing aids. The subjects of this study were 10 pre-school age children with hearing aids, 12 pre-school age children with cochlear implants, and 10 pre-school age children with normal hearing. Three kinds of signal-to-noise (SNR) conditions (+10 dB, +5 dB, 0 dB) were applied. The results for all pre-school age children with cochlear implants and hearing aids presented a significant increase in the score for sentence recognition as SNR increased. The sentence recognition score in speech noise were obtained with the SNR +10 dB. Significant differences existed between groups in terms of their sentence recognition ability, with the cochlear implant group performing better than the hearing aid group. These findings suggest the presence of a sentence recognition test using speech noise is useful for evaluating pre-school age children's listening skill.