• Title/Summary/Keyword: 학습의 전이

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Research Trends of Deep Learning-based Mobile Communication Technology (심화 학습 기반 이동통신기술 연구 동향)

  • Kwon, D.S.
    • Electronics and Telecommunications Trends
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    • v.34 no.6
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    • pp.71-86
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    • 2019
  • The unprecedented demands of mobile communication networks by the rapid rising popularity of mobile applications and services require future networks to support the exploding mobile traffic volumes, the real time extraction of fine-rained analytics, and the agile management of network resources, so as to maximize user experience. To fulfill these needs, research on the use of emerging deep learning techniques in future mobile systems has recently emerged; as such, this study deals with deep learning based mobile communication research activities. A thorough survey of the literature, conference, and workshops on deep learning for mobile communication networks is conducted. Finally, concluding remarks describe the major future research directions in this field.

A Study on the Dense Vector Representation of Query-Passage for Open Domain Question Answering (오픈 도메인 질의응답을 위한 질문-구절의 밀집 벡터 표현 연구)

  • Minji Jung;Saebyeok Lee;Youngjune Kim;Cheolhun Heo;Chunghee Lee
    • Annual Conference on Human and Language Technology
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    • 2022.10a
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    • pp.115-121
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    • 2022
  • 질문에 답하기 위해 관련 구절을 검색하는 기술은 오픈 도메인 질의응답의 검색 단계를 위해 필요하다. 전통적인 방법은 정보 검색 기법인 빈도-역문서 빈도(TF-IDF) 기반으로 희소한 벡터 표현을 활용하여 구절을 검색한다. 하지만 희소 벡터 표현은 벡터 길이가 길 뿐만 아니라, 질문에 나오지 않는 단어나 토큰을 검색하지 못한다는 취약점을 가진다. 밀집 벡터 표현 연구는 이러한 취약점을 개선하고 있으며 대부분의 연구가 영어 데이터셋을 학습한 것이다. 따라서, 본 연구는 한국어 데이터셋을 학습한 밀집 벡터 표현을 연구하고 여러 가지 부정 샘플(negative sample) 추출 방법을 도입하여 전이 학습한 모델 성능을 비교 분석한다. 또한, 대화 응답 선택 태스크에서 밀집 검색에 활용한 순위 재지정 상호작용 레이어를 추가한 실험을 진행하고 비교 분석한다. 밀집 벡터 표현 모델을 학습하는 것이 도전적인 과제인만큼 향후에도 다양한 시도가 필요할 것으로 보인다.

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Comparative analysis by pressure ulcer image size using Xception modeling (Xception 모델링을 이용한 욕창이미지 크기별 비교분석)

  • Jin-beom Seo;Ha-na Yoo;Young-bok Cho
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2023.01a
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    • pp.19-20
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    • 2023
  • 전이학습은 영상 분류를 진행한 모델을 사용하여 다른 종류의 영상 분류에 적용하여 문제를 푸는 것을 의미하며, 모델 설계부터 진행한 학습 모델보다 빠른 속도와 높은 정확도를 달성할 수 있다. 또한, 적은 데이터셋에 대하여 학습을 진행하여 좋은 결과를 도출할 수 있는 장점이 존재한다. 본 논문에서는 전이학습으로 사용되는 모델 중 Xception 모델을 사용하며, 욕창 이미지의 모델 입력 크기를 256, 512, 1024의 크기로 설정하여 학습을 진행 후 욕창 이미지 크기별 성능을 비교분석을 진행하고자 한다.

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Cognitive and Affective Domains Outcome of Students in the Department of Dental Hygiene according to Teaching and Learning Methods by Learning Style (학습유형별 교수학습방법에 따른 치위생과 재학생의 인지적·정의적 성과)

  • Kim, Myung-Eun
    • The Journal of the Korea Contents Association
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    • v.21 no.1
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    • pp.363-372
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    • 2021
  • Aim of this study was to confirm the effect of teaching and learning methods on outcomes of learner according to learning style. For this, 22 of dental hygiene students(case group) was treated teaching & learning methods according to learning style while 24 of students(control group) was non treated. Pre-survey were performed before performance of program. Formative Evaluation(FE) was conducted in 2, 3 and 4 week of program respectively and summative evaluation(SE), survey of subject interest(SI) and learning motivation(LM) were conducted in 5 week. The result of study, FE, SI and LM after treatment were increased than before treatment in case group(p<0.05). SI and LM of case group were higher than control group(p<0.05). FE after treatment was increased than before treatment in he assimilator(p<0.05). SI and LM of case groups were higher than control group in assimilator and diverger(p<0.05). The result of correlation analysis, SI was related with SE, FE, LM(p<0.01, p<0.05). Thus, it is necessary to development, application and study of teaching & learning consider to learning style.

An empirical study for the relations between consultant's expertise and consulting knowledge transfer : Focused on FTA consulting (컨설턴트의 전문지식과 컨설팅 지식이전의 관계에 관한 경험적 연구 : FTA컨설팅을 중심으로)

  • Youn, Young-Ho;Na, Do-Sung;Jung, Jin-Teak
    • Journal of Digital Convergence
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    • v.13 no.11
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    • pp.119-132
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    • 2015
  • This study empirically examined which factors facilitate or disturb the learning and practical knowledge transfer in consulting and which factors have most powerful influence on the learning and transfer of consulting knowledge. Analysing 160 data collected from FTA origin managers in export companies, the study findings show the ambiguity(-), complexity(+), consulting competences(+), intervention design and delivery(+), self-efficacy(+) and government subsidies(+) significantly affected on Client's learning, while consultant's expertise(+), consulting involvement(+), transfer culture(+) significantly affected on consulting knowledge transfer, respectively. It showed that consulting competence and causal ambiguity have an greater influence on learning while consultant's expertise has a greater influence on consulting knowledge transfer, respectively. The findings implicate that consulting success depends on rather consultant's factors(consultant's expertise and consulting competence) than client's input factors. To succeed in consulting project, it is important that the consultants effectively develop and apply consulting methods & tools as shared interfaces between consultant and client.

An Analysis of Learning Efficiency of Computer Programming Classes with Peer Tutoring (피어 튜터링을 적용한 컴퓨터 프로그래밍 수업의 학습 효과 분석)

  • Ahn, You-Jung
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2012.01a
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    • pp.243-244
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    • 2012
  • 본 논문에서는 단계별 학습이 필요한 컴퓨터 프로그래밍 수업에 피어 튜터링 제도를 적용하여 정규 수업과 병행하여 운영하고 피어 튜터링에 참여한 학습자들의 참여 전과 후의 성적 변화를 비교해봄으로써 피어 튜터링 제도가 단계별 학습에 얼마나 효과적인지를 분석해본다.

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Financial Market Prediction and Improving the Performance Based on Large-scale Exogenous Variables and Deep Neural Networks (대규모 외생 변수 및 Deep Neural Network 기반 금융 시장 예측 및 성능 향상)

  • Cheon, Sung Gil;Lee, Ju Hong;Choi, Bum Ghi;Song, Jae Won
    • Smart Media Journal
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    • v.9 no.4
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    • pp.26-35
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    • 2020
  • Attempts to predict future stock prices have been studied steadily since the past. However, unlike general time-series data, financial time-series data has various obstacles to making predictions such as non-stationarity, long-term dependence, and non-linearity. In addition, variables of a wide range of data have limitations in the selection by humans, and the model should be able to automatically extract variables well. In this paper, we propose a 'sliding time step normalization' method that can normalize non-stationary data and LSTM autoencoder to compress variables from all variables. and 'moving transfer learning', which divides periods and performs transfer learning. In addition, the experiment shows that the performance is superior when using as many variables as possible through the neural network rather than using only 100 major financial variables and by using 'sliding time step normalization' to normalize the non-stationarity of data in all sections, it is shown to be effective in improving performance. 'moving transfer learning' shows that it is effective in improving the performance in long test intervals by evaluating the performance of the model and performing transfer learning in the test interval for each step.

Relationship between Music Cognitive Skills and Academic Skills (음악의 인지기술과 학습 기술과의 관계)

  • Chong, Hyun Ju
    • Journal of Music and Human Behavior
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    • v.3 no.1
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    • pp.63-76
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    • 2006
  • Melody is defined as adding spatial dimension to the rhythm which is temporal concept. Being able to understand melodic pattern and to reproduce the pattern also requires cognitive skills. Since 1980, there has been much research on the relationship between academic skills and music cognitive skills, and how to transfer the skills learned in music work to the academic learning. The study purported to examine various research outcomes dealing with the correlational and causal relationships between musical and academic skills. The two dominating theories explaining the connection between two skills ares are "neural theory" and "near transfer theory." The theories focus mainly on the transference of spatial and temporal reasoning which are reinforced in the musical learning. The study reviewed the existing meta-analysis studies, which provided evidence for positive correlation between academic and musical skills, and significance of musical learning in academic skills. The study further examined specific skills area that musical learning is correlated, such as mathematics and reading. The research stated that among many mathematical concepts, proportional topics have the strongest correlation with musical skills. Also with reading, temporal processing also has strong relationship with auditory skills and motor skills, and further affect language and literacy ability. The study suggest that skills learned in the musical work can be transferred to other areas of learning and structured music activities may be every efficient for children for facilitating academic concepts.

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Automatic Child Image Classification System Through Transfer Learning (전이학습을 통한 아동 이미지 자동 분류 시스템)

  • Kim, Wooseong;Moon, Mikyeong
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2021.07a
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    • pp.551-552
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    • 2021
  • 인공지능 기술의 발달로 현대사회 사람들은 일상생활에 편리함을 제공받고 업무의 효율성과 생산성이 향상되었다. 대한민국 보육교사들은 수많은 업무로 인해 근무시간 대비 휴식시간과 점심시간이 턱없이 부족하다. 본 논문에서는 보육교사가 일일이 아동들의 사진을 분류하는 업무에 편의성을 제공하여 보다 많은 휴식시간을 보장받고 활용할 수 있도록 전이학습을 통한 아동 이미지 자동 분류 시스템에 대해 기술하고자 한다. 이 시스템을 통해 분류된 아동들의 사진을 매년 제작하는 유아 포토북 제작에도 활용할 수 있을 것으로 기대된다.

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Development of A Macular Degeneration Predictive Model Based on Transfer Learning (전이학습 기반 황반변성 진단모델의 개발)

  • Kim, Kyung-Min;Oh, Se-Jong
    • Proceedings of the Korea Information Processing Society Conference
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    • 2022.11a
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    • pp.43-45
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    • 2022
  • 본 논문은 황반변성 진단 모델 개발을 위해 안저 사진을 이용한 MobileNet2 전이학습 모델 개발과 안정적인 모델 성능을 위한 이미지 증강 방법 및 모델 성능 향상을 위한 파라미터 조정 방법을 제안한다. 보유하고 있는 이미지의 수가 매우 적다고 하더라도 적절한 전이학습 모델을 사용하고 이미지 증강 시 증강 방법과 증강한 이미지와 정상 이미지와의 비율을 적절히 고려할 경우 충분히 안정적인 결과를 얻어낼 수 있다. 또한 파라미터 조정을 통해서 성능 향상을 도모할 수 있다