• Journal of the Korea Fashion and Costume Design Association
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• v.18 no.4
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• pp.125-139
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• 2016

This study looked into how Colleges of Education around the country about how they are composing the curriculum to achieve the goal of Home Economics Subjects' national teachers training, how National Teacher's Examination's questions are set and which correlation is between university's curriculum composition and National Teacher's Examination questions and they were mainly focused on clothing area. For this study, 11 Colleges of Education's Home Management Major's curriculum and clothing area of Home Economic Subjects' National Teacher's Examination's questions from 2010~2016 were analyzed, and it will be summarized in the following. First, in College of Education's Home Management department, clothing area is organized with minimum of 4 to maximum of 12 different subjects. 'Textiles and Care for Textiles' and 'Design for Clothing' which is needed for the very basic subject completion for certificate to become a Home Economic Subject's teacher were included in all the university's curriculums and depending on the department's characteristics, 1~10 extra subjects were composited. Second, there were 34 questions on the exam of National Teacher's Examination in Home Economic subjects, and the results were 10~12 out of 80 each year according to the record of recent 7 years which is from 2010 to 2016. In the Clothing Area, 31 questions included various materials such as pictures, graphs, dialogues, explanations, examples and others, and 19 questions had more than 2 data overlapping. Third, as a result of looking into the correlation between the questions of Curriculum of Clothing Area of College and National Teacher's Examination, there were most questions from the curriculum of basic subject of completion. This means, 18 questions were related to 'Textiles and Care for Textiles' and 'Design for Clothing' and there was 8 questions related to 'Construction of Clothing' which was the second most. The result of this study will help effecting setting exam questions for Home Economic Subject's National Teacher's Examination and Home Management's Curriculum of Clothing Area College being amended.

• Proceedings of the Korean Society of Organic Agriculture Conference
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• 2009.12a
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• pp.281-281
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• 2009

Although national and regional environmentally friend agriculture (EFA) and food development programmes such as the Life-Food Development Plan (LFDP) have been established in Korea, some policy measures in these programmes seem to be unsuitable for Korean organic farming development. Policy measures tend to support external input purchases of organic fertilizers rather than market development actions such as providing consumer information, research, education, training and statistical data collection. The development of an organic action plan (OAP) for Korea is therefore considered essential for the sustainable future of organic farming in Korea. The purposes of OAP are 1) to define and set the clear goals/targets for the organic sector development, 2) to integrate various organic stakeholders and public institutions in partnership, 3)to focus on specific issues with tailored measures and 4) to integrate and develop different policy measures (Stolze, 2005). Most EU member state countries have developed their own OAPs and each reflects its own priorities with regard to organic sector development. This study compares and contrasts the Welsh, England and EU OAP with the Korean Jeonnam Life-Food Development Plan (LFDP) in order to facilitate the development of the organic food and farming sector in Korea. Early action plan, for example, the first Welsh OAP(1999) focused support on developing the supply of organic products whereas later action plans (e.g. England OAPs in 2002 and 2004 and the second Welsh OAP in 2005) focussed more on developing consumer demands for organic products. The EU OAP (2004) also aims at market support related to consumer demand and then organic farming production for its environmental and other social benefits. OAPs not only provide specific issue-solving tools but also perform a role as providing a focus for organic sector development as a whole. The Korean LFDP provides issue-solving tools but plays no regulatory role such as policy development, harmonizing various policy measures and conflicting factors and providing evaluation tools for further development. A national-level OAP could also facilitate international trade of organic products. To achieve better harmonized and sustainable approaches for the Korean organic industry, National- as well as regional- regulatory policy systems are urgently required in the form of an Organic Action Plan.

• Journal of the Korean Society for Library and Information Science
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• v.25
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• pp.83-150
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• 1993

Traditionally, the emphasis of the information services had been placed on the information provider's knowledge of information sources or information systems. However, in view of the increasing complexity of the information environment. and changes taking place in information professions the evaluation of the information services has callded for further research in interpersonal communication aspects of the librarian user interface especially that which links to user satisfaction. This experimental study was carried out for the purpose of exploring the implications of nonverbal behaviors in measuring user satisfaction in the light of the fact that the meaning of nonverbal clues includes more than verbal communication especially in dealing with variable barriers even though they operate at low levels of awareness. In this sense, among the wide range of nonverbal communication areas in particular kinesics, artifacts and the proximics were examined to suggest alternative model which can be applied effectively in our specific set of information work environment. Two major university libraries and two research libraries in Korea were chosen and visited for the anlysis and per each refernce/information interview the librarian's nonverbal behaviors were checked on the observer's checklist and the qustionnaires completed by the user at a time. On the basis of these data firstly, the relation of user satisfaction concerned with the librarian's nonverbal communication to user satisfaction with information services was analyzed and the possible communication barriers were investigated. In addition, the effect of training the information librarian with positive nonverbal communication skills on the user's satisfaction was analyzed in a SAS computer program in the area of kinesics. On the other hand, the effect of other nonverbal behaviors such as proximics and artifacts known very important clues to improving a complex human interaction was discussed along with their experimental results. In conclusion, it was found that most of users were not sensitive to the importance of nonverbal behaviors exposed by the information librarian, but it was proved that the ultimate user satisfaction and the satisfaction of the librarian's nonverbal behaviors are correlated positively, Moreover, nonverbal behaviors displayed by the trained librarian toward the user had a considerable effect on the user's evalution of information services compared with those by the untrained. These findings imply that in order to control the librarian's nonverbal behaviors and to help the user overcome his barriers the information librarian as a specialist needs to assure and modify willilingly his communication behavior. Without making effective use of such nonverbal communication, information librarian could not expect to meet the user's information needs either. However, when these positive nonverbal behaviors are applied it would be highly desirable to be aware of cultural and contextual differences. With regard to increasing information services success the applicable nonverbal communication model for library management and education can be suggested as below.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.123-136
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• 2005

We propose a recognition system for superimposed patterns based on selective attention model and SVM which produces better performance than artificial neural network. The proposed selective attention model includes attention layer prior to SVM which affects SVM's input parameters. It also behaves as selective filter. The philosophy behind selective attention model is to find the stopping criteria to stop training and also defines the confidence measure of the selective attention's outcome. Support vector represents the other surrounding sample vectors. The support vector closest to the initial input vector in consideration is chosen. Minimal euclidean distance between the modified input vector based on selective attention and the chosen support vector defines the stopping criteria. It is difficult to define the confidence measure of selective attention if we apply common selective attention model, A new way of doffing the confidence measure can be set under the constraint that each modified input pixel does not cross over the boundary of original input pixel, thus the range of applicable information get increased. This method uses the following information; the Euclidean distance between an input pattern and modified pattern, the output of SVM, the support vector output of hidden neuron that is the closest to the initial input pattern. For the recognition experiment, 45 different combinations of USPS digit data are used. Better recognition performance is seen when selective attention is applied along with SVM than SVM only. Also, the proposed selective attention shows better performance than common selective attention.

• Journal of the Korean Society of Fashion and Beauty
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• v.3 no.2 s.2
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• pp.55-64
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• 2005

The purpose of this study is to investigate consumers' knowledge and preference towards functional cosmetics. Through the beauty advisors' surveys, their own selling styles and consumer behaviors recognized by beauty advisors were analyzed. It was intended to help extend and strengthen the functional cosmetic market which has continued to grow rapidly since the approved goods under cosmetic law in 2001. For this study, the data was collected through questionnaires the professional consumer counselors confirmed from Korean women over the age. of twenty old living in the Seoul and Kyoungki areas. After pre-research was implemented on 45 women, 328 samples were analyzed as final samples. In addition,46 samples, which were collected through the questionnaires from beauty advisors were analyzed. Samples were analyzed by frequency, percentage, T-test, ANOVA using the SPSS program. The results of study were as follows: First consumers recognized whether functional cosmetics or not. According to the beauty advisor's surveys, consumers regard the functional cosmetic boundary as being wider than real functional cosmetic boundary according to cosmetic law. So, there is a gap between consumers' opinions and real law. Second, regarding the purchasing channels, the largest channel is the cosmetic store. As far as consumers are concerned the most important factor when buying cosmetics, is the suitability of their own skin types. The second factor is product quality and the third factor is price. Functional cosmetics non-experienced group are more concerned with price compared to experienced group. Related to purchasing products, functional cosmetics experienced group buy set products compared to non-experienced group buy one product. Third, the ultraviolet filter cosmetics portion is the largest in the functional cosmetics market the second largest portion is bleaching cosmetics and the third largest portion is the anti-senility cosmetics. However, Most preferred by consumers is the anti-senility cosmetics. Moreover, preference for ultraviolet filter cosmetics is the least. Finally, the level of satisfaction for functional cosmetics is high and dissatisfaction is low. Consumers feel that beauty advisors are simply pushing high priced products without recognizing the consumers' real needs. In conclusion, to develop the functional cosmetic market continually in the future, it needs to extend various products and advertise them until consumers are more aware.

• Journal of the Society of Disaster Information
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• v.14 no.3
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• pp.360-366
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• 2018

Purpose: This study operation of Joint inter-agency Chemical Emergency Preparedness Center and contribute to the reduction of chemical accidents that occur continuously. Method: The Joint inter-agency Chemical Emergency Preparedness Center functions and Chemical accident statistics data of the ('13~'17) were utilized. Results: The number of chemical accidents is decreasing from 113 in '15, 78 in '16, 87 in '17(latest five years 469 chemical accidents). The Joint inter-agency Chemical Emergency Preparedness Center is located in the industrial complex that handling a large amount of chemical, and performs functions such as prompt response, probation & investigation, accident prevention training, safety patrol. It is believed that it contributes to the decreasing of chemical accident by local control accident prevention function. Conclusion: Decreasing the safety management according to the Chemicals control act('15.1.1). The Joint inter-agency Chemical Emergency Preparedness Center('14.1 set up manage organization), which is operated as a mission to prepare respond to chemical accidents, plays a role.

• The Korean Journal of Applied Statistics
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• v.30 no.1
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• pp.41-55
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• 2017

This study predicts the average scores of top 150 PGA golf players on 132 PGA Tour tournaments (2013-2015) using data mining techniques and statistical analysis. This study also aims to predict the Top 10 and Top 25 best players in 4 different playoffs. Linear and nonlinear regression methods were used to predict average scores. Stepwise regression, all best subset, LASSO, ridge regression and principal component regression were used for the linear regression method. Tree, bagging, gradient boosting, neural network, random forests and KNN were used for nonlinear regression method. We found that the average score increases as fairway firmness or green height or average maximum wind speed increases. We also found that the average score decreases as the number of one-putts or scrambling variable or longest driving distance increases. All 11 different models have low prediction error when predicting the average scores of PGA Tournaments in 2015 which is not included in the training set. However, the performances of Bagging and Random Forest models are the best among all models and these two models have the highest prediction accuracy when predicting the Top 10 and Top 25 best players in 4 different playoffs.

• The Journal of the Acoustical Society of Korea
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• v.40 no.5
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• pp.530-536
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• 2021

Recently, due to the development of deep learning, end-to-end speech recognition, which directly maps graphemes to speech signals, shows good performance. Especially, among the end-to-end models, conformer shows the best performance. However end-to-end models only focuses on the probability of which grapheme will appear at the time. The decoding process uses a greedy search or beam search. This decoding method is easily affected by the final probability output by the model. In addition, the end-to-end models cannot use external pronunciation and language information due to structual problem. Therefore, in this paper conformer with lexicon transducer is proposed. We compare phoneme-based model with lexicon transducer and grapheme-based model with beam search. Test set is consist of words that do not appear in training data. The grapheme-based conformer with beam search shows 3.8 % of CER. The phoneme-based conformer with lexicon transducer shows 3.4 % of CER.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.1-12
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• 2022

Traditional methods of measuring corneal ulcers were difficult to present objective basis for diagnosis because of the subjective judgment of the medical staff through photographs taken with special equipment. In this paper, we propose a method to detect the ulcer area on a pixel basis in corneal ulcer images using a semantic segmentation model. In order to solve this problem, we performed the experiment to detect the ulcer area based on the DeepLab model which has the highest performance in semantic segmentation model. For the experiment, the training and test data were selected and the backbone network of DeepLab model which set as Xception and ResNet, respectively were evaluated and compared the performances. We used Dice similarity coefficient and IoU value as an indicator to evaluate the performances. Experimental results show that when 'crop & resized' images are added to the dataset, it segment the ulcer area with an average accuracy about 93% of Dice similarity coefficient on the DeepLab model with ResNet101 as the backbone network. This study shows that the semantic segmentation model used for object detection also has an ability to make significant results when classifying objects with irregular shapes such as corneal ulcers. Ultimately, we will perform the extension of datasets and experiment with adaptive learning methods through future studies so that they can be implemented in real medical diagnosis environment.

• Nuclear Engineering and Technology
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• v.55 no.1
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• pp.339-352
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• 2023

Prediction of the time-related traits of pebble flow inside pebble-bed HTGRs is of great significance for reactor operation and design. In this work, an image-driven approach with the aid of a convolutional neural network (CNN) is proposed to predict the remaining time of initially loaded pebbles and the time interval of paired flow images of the pebble bed. Two types of strategies are put forward: one is adding FC layers to the classic classification CNN models and using regression training, and the other is CNN-based deep expectation (DEX) by regarding the time prediction as a deep classification task followed by softmax expected value refinements. The current dataset is obtained from the discrete element method (DEM) simulations. Results show that the CNN-aided models generally make satisfactory predictions on the remaining time with the determination coefficient larger than 0.99. Among these models, the VGG19+DEX performs the best and its CumScore (proportion of test set with prediction error within 0.5s) can reach 0.939. Besides, the remaining time of additional test sets and new cases can also be well predicted, indicating good generalization ability of the model. In the task of predicting the time interval of image pairs, the VGG19+DEX model has also generated satisfactory results. Particularly, the trained model, with promising generalization ability, has demonstrated great potential in accurately and instantaneously predicting the traits of interest, without the need for additional computational intensive DEM simulations. Nevertheless, the issues of data diversity and model optimization need to be improved to achieve the full potential of the CNN-aided prediction tool.