• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.126-131
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• 2004

The popularity of flat-panel display(FPD), including plasma display panel(PDP) and liquid-crystal display(LCD), has given rise to the need to streamline their production. In these days, PDP is one of the most popular display devices because of its expansion of manufacturing process and simplicity. Bus electrodes, sustain electrodes, barrier ribs and RGB phosphors are patterned on PDP panel to display an image. Since a minute damage on the pattern can cause a serious defect to display, it is important to inspect the pattern precisely. In this paper, an automatic inspection system of repeated pattern in PDP panel has been introduced to find the defect, such as open, short, dirt, island, and so on. And the inspection system has been operated in the mass production line of PDP.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.7
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• pp.67-73
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• 2020

Shrinkage is inevitable in the curing of resins during the nanoimprint process. The degree of shrinkage that occurs as the resin transforms from a viscous liquid to solid differs depending on the type of resin. However, if the cured material is repeatedly cured using the same material, constant shrinkage can be confirmed. In this study, the pattern of change was observed by repeatedly performing the nanoimprint process using a resin with a constant shrinkage rate. The observed pattern for the change of shape was made using a triangular pyramid-shaped aluminum master mold and a flexible replica mold made from the master. Shrinkage that results from the nanoimprint process occurs linearly in the longitudinal direction of the pattern and can be predicted by simple calculations. The change of the pattern due to shrinkage occurred as expected. If the shrinkage rate remains constant, various patterns can be manufactured with high accuracy by correcting these changes before producing a specific shape. This study confirms that the pattern of the desired angle can be obtained by performing the repeated imprint without having to manufacture a master mold.

• Journal of Physiology & Pathology in Korean Medicine
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• v.34 no.1
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• pp.30-36
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• 2020

This study aimed to investigate heart rate variability (HRV) characteristics of cold pattern with repeated measurement data. Participants were taken from a Daejeon University cohort study from 2015 to 2018. Forty-seven of the participants studied displayed cold pattern while 23 showed signs of non-cold pattern. HRV was measured in supine position for 5 minutes at each year, and an 8-item cold pattern questionnaire was used for the diagnosis of cold pattern. SDNN (standard deviation of the NN intervals) and RMSSD (the square root of the mean squared differences of successive NN intervals) were used as time domain analysis, and TP (total power), VLF (power in very low frequency range), LF (power in low frequency range), HF (power in high frequency range), LF norm (LF power in normalized units), HF norm (HF power in normalized units) and LF/HF were used as frequency domain analysis. In the Mann-Whitney U test, LF norm, HF norm, and LF/HF showed differences between the cold pattern group and non-cold pattern group at every measurement, and in the independent t-test, the differences were also observed at three points except for the baseline (2015). In the repeated measures ANOVA, the interaction effects were not observed in all HRV parameters, but the time period effects were observed in SDNN, RMSSD, TP, VLF, LF and HF. There were significant differences between those two groups in LF norm, HF norm and LF/HF. This study suggests that LF norm, HF norm and LF/HF might be a useful indicator of cold pattern properties.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.14 no.1
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• pp.37-43
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• 2005

Plant pipe has a fatigue life which is induced by repeated stress come from the variation of temperature and pressure. To avoid the fatigue crack of plant pipe which is produced by long term repeated stress, plant operator has to limit the mont of operating transient. This paper introduced the study result about discrimination methodology of plant transient by using the fuzzy pattern recognition. As result of applying the fuzzy pattern recognition to actual plant operation data, it is confirmed that fuzzy pattern recognition methodology can be useful for the comparison of similarity for the transients of similar output but has different time pattern.

• Journal of Fashion Business
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• v.16 no.1
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• pp.52-68
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• 2012

To achieve the aim of this study, 9 different types of samples were made to examine mechanical property according to structured pattern and type of Machi of pullover armhole of WholeGarment(seamless knitwear). With respect to samples, from which comparisons are made and anaylzed among basic characteristics of material, tensile strength & elongation and residual elongation due to repeated extension of armhole connecting part, the following conclusions could be obtained. It's revealed that the tensile strength of Machi part as being armhole connecting part of samples is more affected by Machi type than pattern structure. Of Machi types, it showed stronger tensile strength in the order of Normal(Normal Machi)< Machi_B(unilateral Machi)

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.339-342
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• 2005

We present an efficient block-based motion estimation algorithm with motion analysis. The motion analysis determines a size of search pattern and a maximum repeated count of search pattern. In case of large movement in large image, we reduce search points and the local minimum which caused by low performance. The proposed algorithm employs with searching step of 2. The first step determines an initial search point with neighbor block vector and a size of initial search pattern. The second step determines a size of search pattern and a maximum repeated count with motion analysis. We improve motion prediction accuracy while reducing required computational complexity compared to other fast block-based motion estimation algorithms.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.1
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• pp.77-84
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• 2013

In this paper, we review two-dimensional measuring methods referring to target patterns. The patterns consist of two linearly-repeated patterns or is designed repeatedly in two-dimension. The repeated properties are reflectivity, refractivity, air-gapping distance, capacitance, magnetic reluctance, electrical resistance and sloping gradient, etc. However, the optical methods are generally used for high speed processing and density, and their encoding principles are treated here. In case of two-dimensional pattern, as there is not inherently error between single units encoding the pattern except for the metrology frame errors, the end-effector position of an object accompanying the pattern can be measured with respect of the global frame without via error. Therefore, it is regarded as a substitute for laser interferometer with severe environmental constraints and has been applied to the high-accurate planar actuator.

• Journal of the East Asian Society of Dietary Life
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• v.16 no.6
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• pp.717-723
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• 2006

Chemical characteristics of soybean oil after deep-frying with potato sticks (200 g, 10% w/w of soybean oil) were studied according to the 34 deep-frying times. After consecutive 34 deep-frying, total polyunsaturated FA contents was gradually decreased while the total saturated FA and trans FA were increased. Acid value and peroxide value were increased while iodine value decreased, respectively. The Hunter $L^{\ast}$ value decreased while each $a^{\ast}\;and \;b^{\ast}b$ value were gradually increased. Electronic nose equipped with 12 metal oxide sensors was used for the discrimination of odor pattern of frying oils against the times of deep-trying. The proportions of 1st and 2nd principal component analysis showed 75.97% and 21.23%, respectively. While 6 among total 12 sensors well responded to discrimination of odor in the repented frying oils, suggesting that the odor pattern of each oil after deep-frying would be discriminated against fresh soybean oil, especially after 14 times. From the results, electronic nose could differentiate the degree of quality deterioration of the repeated deep-frying oils.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1263-1270
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• 2010

Sixty patients were divided into three groups. Each group of twenty persons had fed on different diet foods over 5 weeks. Cholesterol had been measured repeatedly five times at an interval of a week during 5 weeks. It resulted from mixed model analysis of repeated measurements data that homogeneous toeplitz covariance matrix pattern was selected as the optimal covariance pattern. The correlations between measurements of different times for the covariance matrix are somewhat highly correlated as 0.64-0.78. Based upon the homogeneous toeplitz covariance pattern model, the time effect was found to be highly significant, but the treatment effect and treatment-time interaction effect were found to be insignificant.

• Journal of KIISE:Software and Applications
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• v.34 no.7
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• pp.585-594
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• 2007

The back propagation algorithm took a long time to learn the input patterns and was difficult to train the additional or repeated learning patterns. So Aleksander proposed the binary neural network which could overcome the disadvantages of BP Network. But it had the limitation of repeated learning and was impossible to extract a generalized pattern. In this paper, we proposed a dynamic 3 dimensional Neuro System which was consisted of a learning network which was based on weightless neural network and a feedback module which could accumulate the characteristic. The proposed system was enable to train additional and repeated patterns. Also it could be produced a generalized pattern by putting a proper threshold into each learning-net's discriminator which was resulted from learning procedures. And then we reused the generalized pattern to elevate the recognition rate. In the last processing step to decide right category, we used maximum response detector. We experimented using the MNIST database of NIST and got 99.3% of right recognition rate for training data.