• Journal of Engineering Education Research
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• v.26 no.4
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• pp.47-57
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• 2023

This paper examines the characteristics of shared universities in Korea and seeks future development directions from the analysis of its operation. This study overviews the current status of students and the characteristics of each major in the DSC Shared University. This provides the future improvement direction and analyzes the survey of attending students. The results shows the most DSC students are engineering students, and they are taking classes centering on the major courses opened by their school. Future direction of shared universities include the recruitment of students from various backgrounds, expansions of enrollment in other schools' curriculum.

• The Journal of the Acoustical Society of Korea
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• v.37 no.6
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• pp.483-488
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• 2018

Far field input utterance is one of the major causes of performance degradation of speaker verification systems. In this study, we used teacher student learning framework to compensate for the performance degradation caused by far field utterances. Teacher student learning refers to training the student deep neural network in possible performance degradation condition using the teacher deep neural network trained without such condition. In this study, we use the teacher network trained with near distance utterances to train the student network with far distance utterances. However, through experiments, it was found that performance of near distance utterances were deteriorated. To avoid such phenomenon, we proposed techniques that use trained teacher network as initialization of student network and training the student network using both near and far field utterances. Experiments were conducted using deep neural networks that input raw waveforms of 4-channel utterances recorded in both near and far distance. Results show the equal error rate of near and far-field utterances respectively, 2.55 % / 2.8 % without teacher student learning, 9.75 % / 1.8 % for conventional teacher student learning, and 2.5 % / 2.7 % with proposed techniques.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.35-43
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• 2021

Recently, there has been a growing interest in zero-shot cross-lingual transfer, which leverages cross-lingual language models (CLLMs) to perform downstream tasks that are not trained in a specific language. In this paper, we point out the limitations of the data-centric aspect of quality estimation (QE), and perform zero-shot cross-lingual transfer even in environments where it is difficult to construct QE data. Few studies have dealt with zero-shots in QE, and after fine-tuning the English-German QE dataset, we perform zero-shot transfer leveraging CLLMs. We conduct comparative analysis between various CLLMs. We also perform zero-shot transfer on language pairs with different sized resources and analyze results based on the linguistic characteristics of each language. Experimental results showed the highest performance in multilingual BART and multillingual BERT, and we induced QE to be performed even when QE learning for a specific language pair was not performed at all.

• Journal of Engineering Education Research
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• v.15 no.6
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• pp.49-57
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• 2012

This paper deals with the individual homework creating and management system. The proposed system can be applied to various types of homeworks such as problem solving, experiment and watching some video material related to lecture. Every authorized student can connect the web server in which the proposed system is implemented and download his assignment which is different from other student's. Also we provide real application examples to show the feasibility and effectiveness of the proposed system regarding 3 types of assignments and expect to help the students to do self-regulated study and improve their professional capability.

• Journal of Digital Contents Society
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• v.14 no.4
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• pp.545-555
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• 2013

Recently student portfolio is widely used as an evaluation method for self-directed performance in engineering education of the university. Especially, as many of the Innovation Centers for Engineering Education and ABEEK held student portfolio competitions, a lot of students in engineering college participate in student portfolio includes the contents and careers of the entire process of university. However, except for courses related to capstone design, there are few regular courses applied to Learning Portfolio in engineering education. Through using Learning Portfolio in courses, students take opportunities of organized collection of learning contents and critical reflection. Under these background study, the regular course in engineering education is may be appropriate for using Learing Portfolio in lecture. In this paper, we present the case study for the Data Structure course opened in the first semester of 2013 which is organized as a Learning Portfolio. According to the results of applying Learning Portfolio to the regular course, it turns out that learners can develope self-directed learning ability in exploring the learning process, and manage a learning process systematically through self-reflection in learning process.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.909-914
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• 2003

• Proceedings of the Korea Water Resources Association Conference
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• 2005.09a
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• pp.360-361
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• 2005

• Proceedings of the Korea Water Resources Association Conference
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• 2005.09a
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• pp.428-429
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• 2005

• Proceedings of the Korea Water Resources Association Conference
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• 2005.09a
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• pp.435-436
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• 2005

• Proceedings of the Korea Water Resources Association Conference
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• 2005.09a
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• pp.628-629
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• 2005