• Journal of the Korean Society for Nondestructive Testing
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• v.17 no.4
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• pp.248-261
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• 1997

Ultrasonic pattern recognition is the most effective approach to the problem of discriminating types of flaws in weldments based on ultrasonic flaw signals. In spite of significant progress in the research on this methodology, it has not been widely used in many practical ultrasonic inspections of weldments in industry. Hence, for the convenient application of this approach in many practical situations, we develop an intelligent ultrasonic signature classification software which can discriminate types of flaws in weldments based on their ultrasonic signals using various tools in artificial intelligence such as neural networks. This software shows the excellent performance in an experimental problem where flaws in weldments are classified into two categories of cracks and non-cracks. This performance demonstrates the high possibility of this software as a practical tool for ultrasonic flaw classification in weldments.

• Korean Journal of Food Science and Technology
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• v.34 no.1
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• pp.136-139
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• 2002

The discrimination of the agricultural origin, especially locally produced of imported products such as black rices was investigated by using electronic nose. Volatile components from these products were discriminated by six metal oxide sensors without pretreatment. Pattern recognition was carried out. Principal component analysis showed the differences between imported and locally produced ones. The number of 57 from 69 species of black rices were recognized as locally produced one (83.33%) and 11 from 13 species one (imported black rices) was correctly discriminated. Unknown habitat of black rice could be identified by artificial neural network system whether the imported or not. Also commercial electronic nose (E-nose 5000) that was combined with metal oxide sensor and conducting polymer sensor showed 92.75% (locally produced black rices) and 92.31% (imported one) of discrimination.

• Korean Parent-Child Health Journal
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• v.1
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• pp.56-74
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• 1998

The language of the newborn, like that of adults, is one of gesture, posture, and expression(Lewis, 1980). Helping parents understand and respond to their newborn's cues will make caring for their baby more enjoyable and may well provide the foundation for a communicative bond that will last lifetime. Infant state provides a dynamic pattern reflecting the full behavioral repertoire of the healthy infant(Brazelton, 1973, 1984). States are organized in a predictable emporal sequence and provide a basic classification of conditions that occur over and over again(Wolff, 1987). They are recognized by characteristic behavioral patterns, physiological changes, and infants' level of responsiveness. Most inportantly, however, states provide caregivers a framework for observing and understanding infants' behavior. When parents know how to determine whether their infant is sleep, awake, or drowsy, and they know the implications, recognition of states has for both the infant's behavior and for their caregiving, then a lot of hings about taking care of a newborn become much easier and more rewarding. Most parents have the skills and desire to do what is best for their infant. The skills 7373parents bring to the interaction are: the ability to read their infant's cues: to stimulate the baby through touch, movement, talking, and looking at: and to respond in a contingent manner to the infant's signals. Among the crucial skills infants bring to the interaction are perceptual abilities: hearing and seeing, the capacity to look at another for a period of time, the ability to smile, be consoled, adapt their body to holding or movement, and be regular and predictable in responding. Research demonstrates that the absence of these skills by either partner adversely affects parent-infant interaction and later development. Observing early parent-infant interactions during the hospital stay is important in order to identify parent-infant pairs in need of continued monitoring(Barnard, et al., 1989).

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.8
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• pp.196-202
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• 2013

Basal cell carcinoma (BCC) is the most common skin cancer and its incidence is increasing rapidly. In this paper, we propose a diagnosis method of basal cell carcinoma by Raman spectra of skin tissue using the NMF(non-negative matrix factorization) algorithm. After preprocessing steps, measured Raman spectra is used classification experiments. The weight and the basis can be obtained in a simple matrix operation and a column vector of the matrix decompsed by the NMF. Linear combination of bases and weights, it is possible to approximate the average of Raman spectra. The classification method is to select the class which to minimize the root mean square of the difference of the linear combination and the objective spectrum. According to the experimental results, the proposed method shows the promising results to diagnosis BCC. In addition, it confirmed that the proposed method compared with the previous research result could be effectively applied in the analysis of the Raman spectra.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.5
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• pp.1-6
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• 2016

Image rotation is one of main pre-processing step in image processing or image pattern recognition. It is implemented with rotation matrix multiplication. However it requires lots of floating point arithmetic operations and trigonometric function calculations, so it takes long execution time. We propose a new high speed image rotation algorithm without two major time-consuming operations. It use just 2 shear translation operations, so it is very fast. In addition, we apply a parallel computing technique with CUDA. CUDA is a massively parallel computing architecture using prevailed GPU recently. As GPU is a dedicated graphic processor, it is exellent for parallel processing of pixels. We compare the proposed algorithm with the conventional rotation one with various size images. Experimental results show that the proposed algorithm is superior to the conventional rotation ones.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.11
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• pp.79-88
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• 1999

In this paper we address the tracking method which tracks only target object in image sequence including moving object. We use a contour tracking algorithm based on intensity and motion boundaries. The motion of the moving object contour in the image is assumed to be well describable by an affine motion model with a translation, a change in scale and a rotation. The moving object contour is represented by B-spline, the position and motion of which is estimated along the image sequence. we use pattern recognition to identify target object. In order to use linear Kalman Filters we decompose the estimation process into two filters. One is estimating the affine motion parameters and the other the shape of moving object contour. In some experiments with dial plate we show that this method enables us to obtain the robust motion estimates and tracking trajectories even in case of including obstructive object.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.141-148
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• 2011

Support vector machines have been extensively studied and utilized in pattern recognition area for years. One of interesting applications of this technique is music/speech classification for a standardized codec such as 3GPP2 selectable mode vocoder. In this paper, we propose a novel approach that improves the speech/music classification of support vector machines. While conventional support vector machine optimization techniques apply during training phase, the proposed technique can be adopted in classification phase. In this regard, the proposed approach can be developed and employed in parallel with conventional optimizations, resulting in synergistic boost in classification performance. We first analyze the impact of kernel width parameter on the classifications made by support vector machines. From this analysis, we observe that we can fine-tune outputs of support vector machines with the kernel width parameter. To make the most of this capability, we identify strong correlation among neighboring input frames, and use this correlation information as a guide to adjusting kernel width parameter. According to the experimental results, the proposed algorithm is found to have potential for improving the performance of support vector machines.

• Journal of the Korean Society of Clothing and Textiles
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• v.18 no.4
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• pp.549-559
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• 1994

The purpose of this study was to study accumlated residual soils which may be one of the causes for yellowing of worn cloths. Wear and wash tests of white cotton undershirts were repeated at 30 households sellected at random over a period of 60 days. Laundry conditions were similar to home laundry habits in a fact-finding survey, using a powdery heavy duty detergent containing no enzymes or enzymes. The subjects in this study were survey of laundry actual condition, the undershirts from prior to and after the final washing was measured residual soils, $L^*a^*b^*$ value and mellowness index of CIE system. D3ta were analysed by simple correlation analysis of wear and wash cycle, residual soils, whiteness The results obtained were summarized as follows: 1. Using pattern of washing machine, Presoaking was no singinificant differnece in general characteristics of survey respondent. Laundry frequency was significant difference in income level, occupation of housewives whether or not. Use of cold and hot water was significant difference in residence shape. 2. The analyzed consequences of recognition and actual behavior in connection with laundry were found variables each other to have independence or not. 3. Amount of residual sebum soils is using non-enzyme detergent were much more than in using enzyme detergent, increased linearly with increase of the number of wear and wash cycles. 4. Residual protein soils with increase of the number wear and wash cycles less than in laundering more easy than sebum soils. Since accumulated residual sebum soils were much more than residual protein soils. 5. Increase of residual soils was raised mellowness index and diminshed whiteness. yellowness index of residual sebum soils was higher than protein soils. If increase of whiteness will be incresed, amount of residual sebum soils will be decreased sebum soils. Because amount of residual sebum soils much more than protein soils, yellowness index of residual sebum soils was more higher than that of protein soils.

• Journal of Korean society of Dental Hygiene
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• v.13 no.6
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• pp.1047-1055
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• 2013

Objectives : The purpose of this study was to evaluate the overall oral health knowledge and toothbrushing pattern of school dental clinic students in school dental clinics and to provide the basic data for the oral health. Methods : The subjects were 290 elementary school students visiting school dental clinics in Busan Metropolitan city. The data were collected from July 3, 2012 to July 19, 2013. Results : The visit rate of school dental clinics was 40.3%. Girl students brushing three times a day accounted for 47.3% and boy students brushing twice a day accounted for 58.5%(p<0.05). Students using rolling brushing method accounted for 35.4% and 8% of the students did not know the rolling method. Brushing method response consisted of circular motion(21.6%) and rolling method(30.8%). Brushing more than 3 minutes accounted for 46.5%(p<0.001) and 30.8% of the students chose rotation brushing method(p<0.001). Conclusions : It is very important for the elementary school students to learn the right oral health education and oral health knowledge.

• Mass Spectrometry Letters
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• v.3 no.3
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• pp.74-77
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• 2012

Organic acid (OA) profiling analysis was performed in culture media from Lactobacillus pentosus K34 (L. pentosus K34) and Pediococcus lolli PL24 (P. lolli PL24) by gas chromatography-mass spectrometry (GC-MS) following methoxime/tert-butyldimethylsilyl derivatives. 12 OAs were positively identified in culture media. Most of OA levels from L. pentosus K34 of hetero lactic fermentation were found to be higher when compared with those from P. lolli PL24 of homo lactic fermentation, which may explain different OA metabolism in each strain. In addition, the distorted dodecagonal star patterns were readily distinguishable, and the characteristics of each strain were well represented. The present study demonstrates that the OA metabolic profiling method by GC-MS combined with star pattern recognition is useful for the monitoring study of characteristic OA metabolism in various microorganisms.