• The Journal of the Acoustical Society of Korea
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• v.26 no.5
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• pp.194-198
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• 2007

In this paper, we apply a discriminative weight training to a statistical model-based voice activity detection(VAD). In our approach, the VAD decision rule is expressed as the geometric mean of optimally weighted likelihood ratios(LRs) based on a minimum classification error(MCE) method which is different from the previous works in that different weights are assigned to each frequency bin which is considered more realistic. According to the experimental results, the proposed approach is found to be effective for the statistical model-based VAD using the LR test.

• Journal of the Korean School Mathematics Society
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• v.6 no.1
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• pp.1-17
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• 2003

In this paper, we study the methods of improving an ability of a creative solving mathematical problem belonging to an educational system which every province office of education has adopted for the mathematically talented students. Especially, we give an attention on a preferential reaction in teaching styles according to student's LQ., the relationship between student's LQ. and an ability of creative solving mathematical problems, and seeking for an appropriative teaching methods of the improvement ability of a creative solving problem. As results, we have the followings; 1. The group having excellent students who have a higher intelligential ability prefers inquiry learning which is composed of several sub-groups to a teacher-centered instruction. 2. The correlation coefficient between student's LQ. and an ability creative solving of mathematical is not high. 3. Although the contents and the model of thematic inquiry learning don't have a great influence on the divergent thinking (ex. fluency, flexibility, originality), they affect greatly the convergent thinking - a creative mathematical - problem solving ability. Accordingly, our results show that we should use a variety of mathematical teaching materials apart from our regular textbooks used in schools to improve a creative mathematical problem solving ability in the process of thematic inquiry learning. Also we can see that an inquiry learning which stimulates student's participation and discussion can be a desirable model in the thematic mathematical classroom activities.

• Journal of Practical Engineering Education
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• v.14 no.3
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• pp.523-533
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• 2022

During the COVID-19 pandemic, the use of video classes and real-time online education has increased, but the lack of interaction between instructors and learners remains a challenging problem to be resolved. This paper designs and implements a learning support system that utilizes a digital human to improve faculty-student interaction, which plays an important role in increasing the educational effect and satisfaction of real-time online classes. In this paper, a digital human participates in a class as a virtual learner and asks questions raised by other learners through an anonymous chat system to the instructor on behalf of the learners. In addition, as a class facilitator, the digital human analyzes the lecturer's speech in real time and provides it to the learner in the form of a summary of the class, thereby facilitating faculty-student interaction. In order to confirm that the proposed system can be used in actual online real-time classes, we apply our system to Zoom classes. Experimental results show that facilitated Q&A and real-time class summaries are successfully provided through our digital human-based learning support system.

• The Journal of the Korea Contents Association
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• v.21 no.10
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• pp.115-126
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• 2021

The purpose of this study is to closely analyze the case of blended-learning in order to provide a diverse and flexible learning environment while maintaining the nature of face-to-face classes, and to identify the learning environment that supports blended-learning in each class step and the educational experience of students. The experience and satisfaction of blended learning were investigated in various ways: course evaluation, LMS activity evaluation, and questionnaire before and after the class. As a result, the blended-learning is better than the traditional face-to-face classes, in providing real-time feedback, opportunities for various interactions, and textual conversations, anytime and anywhere. In addition, as a result of the preliminary survey, as a measure to solve the opinion that concentration was reduced due to problems such as networks and felt uncomfortable in the communication part, the theory and lectures of the design practice class were conducted non-face-to-face. The individual Q&A and feedback were conducted face-to-face and non-face-to-face. As a result of the follow-up survey, it was found that concentration and efficiency could be improved. This opens up possibilities for active use of the online environment in design practice classes.

• Journal of Korean Tunnelling and Underground Space Association
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• v.11 no.2
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• pp.151-162
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• 2009

This study proposes a new methodology for quantitative rock classification in unsampled rock zone, which occupies the most of tunnel design area. This methodology is to train an ANN (artificial neural network) by using results from a drilling investigation combined with electric resistivity survey in sampled zone, and then apply the trained ANN to making a prediction of grade of rock classification in unsampled zone. The prediction is made at the center point of a shifting window by using a number of electric resistivity values within the window as input reference information. The ANN training in this study was carried out by the RPROP (Resilient backpropagation) training algorithm and Early-Stopping method for achieving a generalized training. The proposed methodology is then applied to generate a rock grade distribution on a real tunnel site where drilling investigation and resistivity survey were undertaken. The result from the ANN based prediction is compared with one from a conventional kriging method. In the comparison, the proposed ANN method shows a better agreement with the electric resistivity distribution obtained by field survey. And it is also seen that the proposed method produces a more realistic and more understandable rock grade distribution.

• Journal of the Korea Convergence Society
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• v.11 no.11
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• pp.33-39
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• 2020

In the field of Natural Language Processing, Various research such as Translation, POS Tagging, Q&A, and Sentiment Analysis are globally being carried out. Sentiment Analysis shows high classification performance for English single-domain datasets by pretrained sentence embedding models. In this thesis, the classification performance is compared by Korean E-commerce online dataset with various domain attributes and 6 Neural-Net models are built as BOW (Bag Of Word), LSTM[1], Attention, CNN[2], ELMo[3], and BERT(KoBERT)[4]. It has been confirmed that the performance of pretrained sentence embedding models are higher than word embedding models. In addition, practical Neural-Net model composition is proposed after comparing classification performance on dataset with 17 categories. Furthermore, the way of compressing sentence embedding model is mentioned as future work, considering inference time against model capacity on real-time service.

• School Mathematics
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• v.10 no.2
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• pp.259-277
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• 2008

Conventional assessments only provide a single summary score that indicates the overall performance level or achievement level of a student in a single learning area. For assessments to be more effective, test should provide useful diagnostic information in addition to single overall scores. Cognitive diagnosis modeling provides useful information by estimating individual knowledge states by assessing whether an examinee has mastered specific attributes measured by the test(Embretson, 1990; DiBello, Stout, & Rousses, 1995; Tatsuoka, 1995). Attributes are skills or cognitive processes that are required to perform correctly on a particular item. By the results of this study, students, parents, and teachers would be able to see where a student stands with respect to mastering the attributes. Such information could be used to guide the learner and teacher toward areas requiring more study. By being able to assess where they stand in regard to the attributes that compose an item, students can plan a more effective learning path to be desired proficiency levels. It would be very helpful to the examinee if score reports can provide the scale scores as well as the skill profiles. While the scale scores are believed to provide students' math ability by reporting only one score point, the skill profiles can offer a skill level of strong, weak or mixed for each student for each skill.

• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.157-164
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• 2020

In 2020, due to COVID-19, all universities in Korea were conducting non-face-to-face classes. The purpose of this study is to study what factors affect academic achievement under such non-face-to-face instruction, especially for engineering students where practical training is important. Validity of the statistical hypothesis defined in this study by applying a structural equation model using questionnaires about academic achievement for engineering students at University D for this study. In addition, I would like to suggest what factors should be considered in non-face-to-face classes, especially in engineering colleges. As a result of the study, it was found that students' Q&A, feedback and e-learning system had a direct influence on academic achievement. In addition, it was confirmed that they had an indirect influence on academic achievement through the parameters of theory class and practical class.

• Journal of Engineering Education Research
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• v.2 no.1
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• pp.24-28
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• 1999

The information technology is becoming very essential in our daily lives. Internet environment, especially, has been seriously affecting the area of education. The cost-effectiveness analysis is required as universities are investing quite much in the development of internet infrastructure. This study shows a simple statistical result on the utilization of internet equipments. It is found that the enough availability is not provided to the students who are going to use equipments for the purpose of study as a big portion of them are occupied by the users for the purpose of amusement.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.317-320
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• 2005

본 논문에서는 퍼지 로직을 이용하여 로봇의 여러 환경변수에 따라 로봇들의 행동을 적절히 선택하는 알고리즘을 제시한다. 전략 및 전술 알고리즘으로 많이 알려진 Modular Q-학습 알고리즘은 개체의 수에 따른 상태수를 지수 함수적으로 증가시킬 뿐만 아니라, 로봇이 협력하기 위해 중재자모듈이라는 별도의 알고리즘을 필요로 한다. 그러나 앞으로 제시하는 로봇 행동의 퍼지 적정성을 고려한 로봇축구 전략 및 전술 알고리즘은 환경 변수에 따라 로봇 행동의 적절성을 퍼지 로직을 통하여 얻어내게 하였으며, 이를 이용함으로써 다수 로봇의 상호작용도 고려할 수 있게 하였다.