• Fashion & Textile Research Journal
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• v.3 no.1
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• pp.70-80
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• 2001

This study was designed to investigate actual conditions of textile design education at technical high school in Korea, and to present possible solutions for improving its effectiveness. Inchon Girl's Polytechnic high School was selected as sample of case study because it was the only school which has textile design major. Survey was done through questionnaire and telephone interview. 100 students, 25 graduates, 8 teachers, and 8 managers of textile industry were involved in survey. The data were analyzed by using frequency, t-test, correlation. Statistical analysis resulted in the following suggestions to be considered for maximizing the effectiveness of the textile design education at technical high schools: First, the curriculum should be flexibly reorganized to come up with trends in the market and demands from industry, and also to stimulate and motivate students into the biggest achievements possible. Second, more weight should be given to practical design subjects which have proved to be preferred by students and industry by reducing class hours for non-design subjects or theoretical subjects. Third, equipments and facilities for practical exercise should be open to students anytime needed so that students can improve their practical skills without any restrictions. Fourth, new teachers having majored in textile design at the university should be employed and the existing teachers should be periodically re-educated to keep abreast with new knowledges and technology. Fifth, The solidarity and the connection between schools and companies should be reinforced, not only to provide graduates with more chances to get a job, but also to make education at schools refreshed and updated.

• Journal of the Korean Society of Clothing and Textiles
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• v.42 no.4
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• pp.599-611
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• 2018

This study develops a training program for vocational high school students. This study implemented the ADDIE teaching-learning model and was conducted in the sequence of analyses, design, development, implementation and evaluation. In the analysis phase, the existing studies related to vocational competency training were analyzed along with an analysis of the current education programs and suitability assessment. Based on the analysis, the education program was designed and contents were determined. The program consisted of 5 chapters and 17 unit hours of instruction. Reigeluth's (1987) theory was used as the framework for organizing educational materials in the development phase. The programs were implemented on students and evaluated by students as well as experts. Students evaluated the program in terms of the degree of motivation for learning, comprehension of learning content, perceptions of lessons in classes as well as the advantages and disadvantages of the program. Experts evaluated the program in terms of program validity. The results indicate the developed program was useful for training students vocational competencies as shop managers. This study contributes to the field of fashion education, by presenting an example of systematic development of an educational program in connection with industry.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2480-2496
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• 2020

Considering that high-dose X-ray radiation during CT scans may bring potential risks to patients, in the medical imaging industry there has been increasing emphasis on low-dose CT. Due to complex statistical characteristics of noise found in low-dose CT images, many traditional methods are difficult to preserve structural details effectively while suppressing noise and artifacts. Inspired by the deep learning techniques, we propose a densely connected residual network (DCRN) for low-dose CT image noise cancelation, which combines the ideas of dense connection with residual learning. On one hand, dense connection maximizes information flow between layers in the network, which is beneficial to maintain structural details when denoising images. On the other hand, residual learning paired with batch normalization would allow for decreased training speed and better noise reduction performance in images. The experiments are performed on the 100 CT images selected from a public medical dataset-TCIA(The Cancer Imaging Archive). Compared with the other three competitive denoising algorithms, both subjective visual effect and objective evaluation indexes which include PSNR, RMSE, MAE and SSIM show that the proposed network can improve LDCT images quality more effectively while maintaining a low computational cost. In the objective evaluation indexes, the highest PSNR 33.67, RMSE 5.659, MAE 1.965 and SSIM 0.9434 are achieved by the proposed method. Especially for RMSE, compare with the best performing algorithm in the comparison algorithms, the proposed network increases it by 7 percentage points.

• Journal of the Korea Computer Industry Society
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• v.2 no.12
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• pp.1563-1572
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• 2001

Information wave of 21th century industrial society being undergone a change to knowledge post-industrial society new sense of values and life require. Also, computer is interacting, and adapts spontaneously in current enemy these age by important means on information-oriented society that change rapidly and computer-aided education is essential to improve country competitive power. Grasp computer education actual conditions of vocational high school for positivity that is industrial technology that IT base knowledge information-oriented society requires in this research hereupon, and though students' profession preference wishes to supply pabulum in course education presenting improvement direction of more efficient computer-aided education through investigation, there is the purpose. In present school curriculum, satisfaction about computer connection education responded that have interest much very appeared in general high. Also, computer connection profession preference was expose that research results keep in step and prefers most Information Communication Technology (ICT) field and multi media field that is embossed newly in post-industrial society.

• Fashion & Textile Research Journal
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• v.17 no.3
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• pp.351-363
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• 2015

This research explores diachronic fashion design trends through a structure analysis of a connection network based on fashion show concepts implemented by modern fashion designers from S/S 2009 to F/W 2013. The findings from this research are as follows. First, four categories affect the inspiration and thinking of design: the experience of the designer, social atmosphere and phenomena, natural sensitivity (or formative characteristics of natural objects), and the influence and quality of other fields. Second, in cases where the designers' experiences influenced design inspiration and thinking, designers express personal memories with keywords like high school, grandmother's closet, prom, beauty and the beast, heritage, past, and reminiscence through design elements such as lines, silhouettes, materials, and colors. Third, the representative example of the social atmosphere and phenomena that influenced design inspiration and thinking was the 2008 Global Financial Crisis that reflected the social climate through design concepts of keywords such as Recession, Black, Economy, US, Depression, Gray, Dark Age, White and New York. Fourth, inspired by nature and the formative characteristics in design, the designers employed ornamental elements to collections and design concepts that focused on nature words connected to light, sun, wild, dirt, rock, moss, and trees. Fifth, the designers took their ideas from different fields of personal interest in the arts, science and humanities (sports, architecture, sculpture, painting, and literature) that were decisive in determining materials, design colors and silhouettes. The theme of architecture was analyzed as a central element that had an ongoing impact on the concepts of designers.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.55-66
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• 2017

Korean small and medium sized software companies have tried to export their solutions or services to overseas markets. In 2016, exports of the software industry increased by 6.0% from the previous year, and the value added of the industry was 2.2 times higher than that of the manufacturing industry. From a long-term perspective, it is important to secure a global competitive advantage in order to sustain the export high value-added of the software industry. The obstacles to entry into the overseas market of small to medium enterprises are as follows: first, difficulty in product development and localization of marketing; second, lack of investment for overseas expansion; and finally, competitiveness of software technology. In particular, To overcome such obstacles, Korean small and medium sized software companies should increase the technical perfection and secure software export competitiveness. The paper presents a payment settlement framework enabling adaptive reuse and semiautomatic development of global payment settlement services. The quantitative and qualitative evaluation results are presented with domestic and overseas case studies as follows: Firstly, semi-automatic development is realized successfully by applying the framework. Secondly, it is possible to maintain consistent quality of software and to deliver maintenance services without relying on the internal human resources. Thirdly, it is possible to reduce the project duration of the same development cope to less than 50% by applying the framework. Finally, because it is based on BPMN 2.0, which is a high level design diagram, it is expected that it will be easy to implement through components connection and reduce difficulties in technology transfer and localization. Also, at the time of runtime operation, it will be effective to understand the design idea easily and to carry out additional developments without human resource who participated in the initial project.

• Journal of the Korean Society of Systems Engineering
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• v.15 no.2
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• pp.79-86
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• 2019

Among the government-sponsored projects supported by Ministry of SMEs and Startups(MSS), the financial support of the Consulting Research Institutes of our university is scheduled to be ended this year. In this regard, this study is to develop a profit model for R&D center of Consulting Research Institute that can cultivate the financial independence of R&D center of Consulting Research Institutes and foster technology convergence consulting manpower to strengthen the competitiveness of SMEs in preparation for the Fourth Industrial Revolution. The profit model were derived from the current status of consulting industry and similar organizations, the current status of consulting graduate R&D centers, case studies of other universities, and focus group interviews. In order to select three high profit models and commercialize them, BMC (Biz Model Canvas) was used and business feasibility was examined. Therefore, three profit model of R&D center of Consulting Research Institute are: First, SCB (SME's Consulting Business: Total Solution Provider for SMEs through Technology Convergence Consulting), Second, SNB (SME's Network Business: Experts connection in Consulting Graduate School for Solving Problems and Problems of SMEs / Industry Consolidation) And third, SM (Sustainable Management: Financial independence through structural improvement of Consulting Research Institute), and the road-map was established. As an implementation plan, the company intends to seek financial independence by developing a profit model for R&D center of Consulting Research Institutes and by establishing business goals and strategies, manpower operation plan, organization, and investment plan for three years.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.175-197
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• 2021

Recently, with the development of deep learning technology, research on unstructured data analysis is being actively conducted, and it is showing remarkable results in various fields such as classification, summary, and generation. Among various text analysis fields, text classification is the most widely used technology in academia and industry. Text classification includes binary class classification with one label among two classes, multi-class classification with one label among several classes, and multi-label classification with multiple labels among several classes. In particular, multi-label classification requires a different training method from binary class classification and multi-class classification because of the characteristic of having multiple labels. In addition, since the number of labels to be predicted increases as the number of labels and classes increases, there is a limitation in that performance improvement is difficult due to an increase in prediction difficulty. To overcome these limitations, (i) compressing the initially given high-dimensional label space into a low-dimensional latent label space, (ii) after performing training to predict the compressed label, (iii) restoring the predicted label to the high-dimensional original label space, research on label embedding is being actively conducted. Typical label embedding techniques include Principal Label Space Transformation (PLST), Multi-Label Classification via Boolean Matrix Decomposition (MLC-BMaD), and Bayesian Multi-Label Compressed Sensing (BML-CS). However, since these techniques consider only the linear relationship between labels or compress the labels by random transformation, it is difficult to understand the non-linear relationship between labels, so there is a limitation in that it is not possible to create a latent label space sufficiently containing the information of the original label. Recently, there have been increasing attempts to improve performance by applying deep learning technology to label embedding. Label embedding using an autoencoder, a deep learning model that is effective for data compression and restoration, is representative. However, the traditional autoencoder-based label embedding has a limitation in that a large amount of information loss occurs when compressing a high-dimensional label space having a myriad of classes into a low-dimensional latent label space. This can be found in the gradient loss problem that occurs in the backpropagation process of learning. To solve this problem, skip connection was devised, and by adding the input of the layer to the output to prevent gradient loss during backpropagation, efficient learning is possible even when the layer is deep. Skip connection is mainly used for image feature extraction in convolutional neural networks, but studies using skip connection in autoencoder or label embedding process are still lacking. Therefore, in this study, we propose an autoencoder-based label embedding methodology in which skip connections are added to each of the encoder and decoder to form a low-dimensional latent label space that reflects the information of the high-dimensional label space well. In addition, the proposed methodology was applied to actual paper keywords to derive the high-dimensional keyword label space and the low-dimensional latent label space. Using this, we conducted an experiment to predict the compressed keyword vector existing in the latent label space from the paper abstract and to evaluate the multi-label classification by restoring the predicted keyword vector back to the original label space. As a result, the accuracy, precision, recall, and F1 score used as performance indicators showed far superior performance in multi-label classification based on the proposed methodology compared to traditional multi-label classification methods. This can be seen that the low-dimensional latent label space derived through the proposed methodology well reflected the information of the high-dimensional label space, which ultimately led to the improvement of the performance of the multi-label classification itself. In addition, the utility of the proposed methodology was identified by comparing the performance of the proposed methodology according to the domain characteristics and the number of dimensions of the latent label space.

• 대한공업교육학회지
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• v.41 no.1
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• pp.68-87
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• 2016

This research conducted a survey for total 166 teachers of schools so as to analyze validity and satisfaction for performance objectives of SMB administration subsidy the HRDP and the CEP in Specialized High School. The results of research are as follows. First, teachers recognize that purpose of HRDP is to expand employment of specialized high school and provide human resource of SMB. And, they recognize that HRDP is important to improve school outcomes and makes a positive effect on the improvement of school outcomes. Second, teachers recognize that objectives of HRDP are improvement of student's understanding for SMB, improvement of teacher's understanding for SMB, improvement of SMB's understanding of school, cultivation of student's occupational view, systematization of career guiding program based on employment process, strengthening of industry-academia cooperation education, improvement of the level of student's skill, fulfillment of workplace experience and practice focusing workplace learning, training of customized human resource for SMB, improvement of student's adaptation to the workplace, improvement of employment rate for SMB, expansion of job opportunities for students with SMB, preparation of the base of connection between school and SMB, publicity of school, expansion of opportunities to cooperate between SMB and school, establishment of cooperative system among industrial association and school, introduction and operation of the employment connective model for joint education and employment, strengthening of field professionalism of teachers. However, satisfaction for the achievement of objectives of HRDP except for strengthening of industry-academia cooperation education and improvement of employment rate for SMB is relatively lower than the validity. Third, teachers in charge of human resource training business of middle and small sized company's specialized high school recognize that objectives of CEP are expansion of job opportunities for students with SMB, excavation of good-quality SMB, expansion of opportunities to cooperate between SMB and school, fulfillment of workplace learning, improvement of student's major foundation and in-depth skill, improvement of literacy, math, teamwork and communication abilities for students' job performance, improvement of student's working attitude and student's proper career exploration decision. However, satisfaction for achievement of objectives of CEP is relatively lower than the validity.

• KSBB Journal
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• v.28 no.6
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• pp.339-348
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• 2013

Translational research (TR) as high quality research can accelerate collaboration strongly between biotechnology-based researchers and clinical-research experts for overcoming diseases. TR facilitates basic science translated to clinical efficacy and effectiveness from bench (basic science) to bedside (clinical practice) for the enhancement of human health. Disease-oriented TR programs were defined as unilateral, bilateral and multilateral TR in this patent performance analysis. Patent performance was measured in a R&D project on Health and Medical Technology to enhance the productivity of R&D investment on disease-oriented TR in Health Technology (HT). Patent Map (PM) analysis and Bibliometrics were conducted to collect information for the assessment of research patents of TR programs. Futhermore, PIAS (Patent Information Analysis System) and Thinklear programs were applied for quantitative and qualitative analysis successfully. These indicate that multi-dimensional analysis of patent performance for disease-oriented TR could promote the connection of R&D-IP (Research and Development-Intellectural Property) and R&BD (Research and Business Development) supporting system significantly.