• Korean Journal of Construction Engineering and Management
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• v.15 no.2
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• pp.71-78
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• 2014

Value Engineering methodology was introduced about 30years ago and has significant achievement in Korea. However, many of workshop still focus on cost down process and do not spend enough time on function analysis and expert cooperation. As a result, limited range of creative ideas were produced. To improve effectiveness of VE workshop, this study developed web-based value engineering process and system. And this study applied it to real case study to evaluate effectiveness of proposed system. Developed VE system also provides automated FAST diagram function and decision-making supporting tools. The authors found that this developed web-based VE system can significantly help to save cost and improve performance of VE workshop by using the appropriate VE process, and quick cooperation between experts. In addition, this study shows an example of a VE case study that applies the web-based VE system process, which led to a very innovative and effective way to lead workshop.

• Journal of the Korea Convergence Society
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• v.11 no.9
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• pp.7-13
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• 2020

With the recent World Health Organization (WHO) Declaration of Pandemic for Coronavirus Disease-19 (COVID-19), COVID-19 is a global concern and many deaths continue. To overcome this, there is an increasing need for sharing information between countries and countermeasures related to COVID-19. However, due to linguistic boundaries, smooth exchange and sharing of information has not been achieved. In this paper, we propose a Neural Machine Translation (NMT) model specialized for the COVID-19 domain. Centering on English, a Transformer based bidirectional model was produced for French, Spanish, German, Italian, Russian, and Chinese. Based on the BLEU score, the experimental results showed significant high performance in all language pairs compared to the commercialization system.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.2
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• pp.47-52
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• 2016

The used digital images in the smart device and small displayer has been a downscaled image. In this paper, the detection of the downscaling image forgery is proposed using the feature vector according to the pixel value's gradients. In the proposed algorithm, AR (Autoregressive) coefficients are computed from pixel value's gradients of the image. These coefficients as the feature vectors are used in the learning of a SVM (Support Vector Machine) classification for the downscaling image forgery detector. On the performance of the proposed algorithm, it is excellent at the downscaling 90% image forgery compare to MFR (Median Filter Residual) scheme that had the same 10-Dim. feature vectors and 686-Dim. SPAM (Subtractive Pixel Adjacency Matrix) scheme. In averaging filtering ($3{\times}3$) and median filtering ($3{\times}3$) images, it has a higher detection ratio. Especially, the measured performances of all items in averaging and median filtering ($3{\times}3$), AUC (Area Under Curve) by the sensitivity and 1-specificity is approached to 1. Thus, it is confirmed that the grade evaluation of the proposed algorithm is 'Excellent (A)'.

• Composites Research
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• v.34 no.5
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• pp.305-310
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• 2021

Mechanical properties of fiber reinforced composites were affected to fiber volume fractions (FVF) and interfacial property by sizing agent conditions. An optimum interface can relieve stress concentration by transferring the mechanical stress from the matrix resin to the reinforcements effectively, and thus can result in the performance of the composites. The interfacial properties and wettability between the epoxy resin and glass fiber (GF) were evaluated for different sizing agent conditions and FVFs. The surface energies of epoxy resin and different sizing agent treated GFs were calculated using dynamic and static contact angle measurements. The work of adhesion, W_a was calculated by using surface energies of epoxy matrix and GFs. The wettability was evaluated via the GF tow capillary test. The interfacial shear strength (IFSS) was evaluated by microdroplet pull-out test. Finally, the optimized GFRP manufacturing conditions could be obtained by using wettability and interfacial property.

• Cross-Cultural Studies
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• v.25
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• pp.421-452
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• 2011

This writing is about an effort to try to preserve and transmit the materials related to Jing-Ju(京劇) who is the Chinese traditional theatrical art. The plan to preserve the materials of performing arts is very important because its collection and preservation about them are much more particular than other genres. China got the great results in this field because of China Jing-Ju Yinpeixiang (中國京劇音配像) project. Jing-Ju Yinpeixiang project is a kind of project to restore and preserve the materials which reproduced Jing-Ju repertoire by inserting the performance method of Yinpeixiang (音配像: put together images to sounds) by later actors and actresses of Jing-Ju in recordings of 1950s to 1960s by remained famous ones. Also, this is the large scale culture project that more than 170 institutions and more than 3000 persons participated in during the total 21 years that it first started in 1985 and was completed in the end of 2006. Thanks to this project, China got to have the almost perfect materials which reproduced live performances to add the images of junior actors and actresses who accurately imitated performances of 115 famous actors and actresses including each type of role, schools and great actors from 1907 to the end of 20th century in their voices. This is the only method to restore the materials in this world and very creative. It's been 15 years since TV broadcasting first showed its fruition to Chinese people. The Chinese government gave the positive judgement on this project and prepared to hold the big event which celebrated itself this year. But very little is known of this process and there is no any study in Korea. This writing tried to clarify what Jing-Ju Yinpeixiang project is, what it has meant to Chinese people and what results it has gotten after it's been 15 years since the first show was on TV.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.2
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• pp.117-126
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• 2019

Legacy study for detecting arrhythmia have mostly used nonlinear method to increase classification accuracy. Most methods are complex to process and manipulate data and have difficulties in classifying various arrhythmias. Therefore it is necessary to classify various arrhythmia based on short-term data. In this study, we propose a feature extraction based on auto regressive modeling and an premature contraction arrhythmia classification method using SVM., For this purpose, the R-wave is detected in the ECG signal from which noise has been removed, QRS and RR interval segment is modelled. Also, we classified Normal, PVC, PAC through SVM in realtime by extracting four optimal segment length and AR order. The detection and classification rate of R wave and PVC is evaluated through MIT-BIH arrhythmia database. The performance results indicate the average of 99.77% in R wave detection and 99.23%, 97.28%, 96.62% in Normal, PVC, PAC classification.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.773-784
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• 2021

The purpose of this study is to confirm the effectiveness of NCS-based education in the field of hair beauty applied in the educational field and to find ways to improve it. To this end, the importance of each NCS competency unit in the field of hair beauty evaluated by senior hair designers and the achievements of new designers evaluated by the IPA method were analyzed to explore the difference between importance-achievement and improvement plans through this. As a result of the study, NCS education in the field of hair beauty was found to be 6 items for improvement, 21 items for maintenance and strengthening, 14 items for long-term improvement, and 1 item for improvement consideration among the existing 41 competency units. In particular, the lack of creativity and the ability to collect and analyze the latest information, which should be improved urgently, appear, confirming the necessity of efforts to develop creative abilities as hair designers in the NCS education field.

• Journal of Digital Convergence
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• v.17 no.10
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• pp.115-126
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• 2019

This study established research hypotheses and conducted empirical analysis to investigate the relationship between research autonomy, self-efficacy, knowledge sharing and job satisfaction and creativity. The 200 questionnaires were analyzed using the SPSS 22.0 statistical program. As a result, research autonomy and self-efficacy not only directly influenced positively on creativity, but also positively influenced on creativity through job satisfaction. In particular, self-efficacy was found to have the greatest influence on job satisfaction and creativity. However, knowledge sharing had a positive(+) effect on job satisfaction, but no effect on creativity. These findings suggest that in order to enhance creativity, it is necessary to prepare a plan to enhance research autonomy, self-efficacy, job satisfaction, and raise awareness about the possibility of creative performance creation through knowledge sharing.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1542-1550
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• 2019

Legacy studies for classifying arrhythmia have been studied to improve the accuracy of classification, Neural Network, Fuzzy, etc. Deep learning is most frequently used for arrhythmia classification using error backpropagation algorithm by solving the limit of hidden layer number, which is a problem of neural network. In order to apply a deep learning model to an ECG signal, it is necessary to select an optimal model and parameters. In this paper, we propose optimal parameter extraction method based on a deep learning. For this purpose, R-wave is detected in the ECG signal from which noise has been removed, QRS and RR interval segment is modelled. And then, the weights were learned by supervised learning method through deep learning and the model was evaluated by the verification data. The detection and classification rate of R wave and PVC is evaluated through MIT-BIH arrhythmia database. The performance results indicate the average of 99.77% in R wave detection and 97.84% in PVC classification.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.12
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• pp.1618-1624
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• 2020

Intestinal obstruction diagnosis method based on X-ray can affect objective diagnosis because it includes subjective factors of the examiner. Therefore, in this paper, a detection method of Intestinal Obstruction from X-Ray image using Hough transform and PCM is proposed. The proposed method uses Hough transform to detect straight lines from the extracted ROI of the intestinal obstruction X-Ray image and bowel obstruction is extracted by using air fluid level's morphological characteristic detected by the straight lines. Then, ROI is quantized by applying PCM clustering algorithm to the extracted ROI. From the quantized ROI, cluster group that includes bowel obstruction's characteristic is selected and small bowel regions are extracted by using object search from the selected cluster group. The proposed method of using PCM is applied to 30 X-Ray images of intestinal obstruction patients and setting the initial cluster number of PCM to 4 showed excellent performance in detection and the TPR was 81.47%.