• 한국콘텐츠학회논문지
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• 제19권7호
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• pp.526-537
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• 2019

이 연구는 기계학습의 도입이 미디어 산업구조에 어떠한 영향을 미칠 것인가에 대해 산업조직론적 관점에서 살펴보았다. 먼저 기계학습 기법이 미디어 산업에 성공적으로 도입되기 위해서는 각 산업 단계의 조직구성원 사이에서 기계학습 기반 시스템의 필요성에 대한 공감대 형성이 선행되어야 할 것으로 분석된다. 기계학습의 도입은 기존 방송 및 영화산업의 투자 의사결정과정과 제작 과정에 유의미한 변화를 가져올 것이며, 투자 측면에서는 객관적 데이터의 제공으로 인해 효율성이 증대될 것으로 보인다. 또한, 성과가 담보된 장르 및 형식의 콘텐츠에 투자가 집중됨에 따라 다양성이 감소할 가능성이 있다. 제작 측면에서는 창작자의 반복적 행위를 기계학습 시스템이 담당하는 역할을 한다면 생산효율성이 증대될 수 있다.

• 한국게임학회 논문지
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• 제17권4호
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• pp.109-116
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• 2017

보드게임은 많은 수의 말들과 상태공간을 갖고 있다. 그러므로 게임은 학습을 오래하여야 한다. 그러나 강화학습은 학습초기에 학습속도가 느려지는 단점이 있다. 그러므로 학습 도중에 동일한 최선 값이 있을 때, 영향력분포도를 고려한 문제 영역 지식을 활용한 휴리스틱을 사용해 학습의 속도 향상을 시도하였다. 기존 구현된 말과 개선 구현된 말을 비교하기 위해 보드게임을 제작하였다. 그래서 일방공격형 말과 승부를 하게 하였다. 실험 결과 개선 구현된 말의 성능이 학습속도 측면에서 향상됨을 알 수 있었다.

• 대한의용생체공학회:의공학회지
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• 제42권3호
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• pp.100-106
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• 2021

Measuring Intima-media thickness (IMT) with ultrasound images can help early detection of coronary artery disease. As a result, numerous machine learning studies have been conducted to measure IMT. However, most of these studies require several steps of pre-treatment to extract the boundary, and some require manual intervention, so they are not suitable for on-site treatment in urgent situations. in this paper, we propose to use deep learning networks U-Net, Attention U-Net, and Pretrained U-Net to automatically segment the intima-media complex. This study also applied the HE, HS, and CLAHE preprocessing technique to wireless portable ultrasound diagnostic device images. As a result, The average dice coefficient of HE applied Models is 71% and CLAHE applied Models is 70%, while the HS applied Models have improved as 72% dice coefficient. Among them, Pretrained U-Net showed the highest performance with an average of 74%. When comparing this with the mean value of IMT measured by Conventional wired ultrasound equipment, the highest correlation coefficient value was shown in the HS applied pretrained U-Net.

• Educational Technology International
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• 제24권2호
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• pp.203-236
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• 2023

The purpose of this study is to explore the structural relationship between COVID-19-induced sub-dimensions of Online Self-Regulated Learning (OSRL) and satisfaction in online courses conducted in the 'post-COVID-19 era,' as well as to investigate the moderating effects of situational variables such as 'course planning,' 'device type,' and 'course repetition.' To achieve this, the study constructs a measurement model with sub-dimensions of Environment Structuring, Learning Strategy, Help Seeking, and Self-Evaluation as components of OSRL. Participants in this study were selected from university students who enrolled in online courses offered by the Department of Education at University A in the metropolitan area. The research findings reveal several key insights. First, among the sub-dimensions of Online Self-Regulated Learning, Environment Structuring, Learning Strategy, and Self-Evaluation significantly influence satisfaction with online courses. Second, students' satisfaction with online courses significantly influences their intention to continue participating in such courses. Third, 'course planning' during online course hours and 'course repetition' play a moderating role in the relationship between sub-dimensions of Online Self-Regulated Learning and satisfaction. Based on the discussion of these research results, this study concludes by suggesting some future implications and challenges of online courses.

• Journal of information and communication convergence engineering
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• 제21권4호
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• pp.300-305
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• 2023

Audience reactions in response to remote virtual performances must be compressed before being transmitted to the server. The server, which aggregates these data for group insights, requires a distribution code for the transfer. Recently, distributed learning algorithms such as federated learning have gained attention as alternatives that satisfy both the information security and efficiency requirements. In distributed learning, no individual user has access to complete information, and the objective is to achieve a learning effect similar to that achieved with the entire information. It is therefore important to distribute interdependent information among users and subsequently aggregate this information following training. In this paper, we present a new extension technique for minimal code that allows a new minimal code with a different length and Hamming weight to be generated through the product of any vector and a given minimal code. Thus, the proposed technique can generate minimal codes with previously unknown parameters. We also present a scenario wherein these combined methods can be applied.

• 한국보육지원학회지
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• 제18권2호
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• pp.1-18
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• 2022

Objective: A teacher learning community was developed in order to implement a play-centered curriculum at a child care center, and teachers' experiences during the process were explored. Methods: The teacher learning community was carried out for a total of 23 sessions. One researcher and six teachers participated in this study. Data including the transcripts of recordings of the teacher learning community, transcripts of individual teachers' interview recordings, teachers' reflective journals, and social media posts were collected. Data were analyzed according to the qualitative data analysis procedure. Results: The teachers recognized their experiences of the teacher learning community as follows: (1) encouraging and empowering each other to find a way together, (2) self-reflection, communication and sharing with experiences, (3) becoming a teacher who practices change. Conclusion/Implications: The results of this study show the importance and effectiveness of managing the teacher learning community in a way that teachers interact with each other in a collaborative manner within the community based on initiative and spontaneity, and to provide help to each other in the process of understanding and practicing the play-centered curriculum. The teacher learning community supports the professionalism of teachers for the practice of a play-centered curriculum.

• International Journal of Computer Science & Network Security
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• 제22권12호
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• pp.217-228
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• 2022

The study aimed to build an electronic strategy in innovative learning situations for the role of education in combating intellectual currents. A total of 525 Saudi university faculty members and general education teachers were surveyed using two electronic questionnaires. Arithmetic averages and standard deviations, One-way ANOVA, Scheffé's test, Pearson's correlation coefficient, and Cronbach's alpha stability coefficient were used as statistical methods. The study statistically identifies the differences between the study sample at the level of significance (0.05). and the design of a digital application for individual learning to combat deviant intellectual currents to activate them in light of Saudi Vision 2030 by combining the theoretical academic material and turning it into a learning e-game called (crosswords). The game is equipped with hyper media that supports education with entertainment to direct ideas towards the promotion of identity, the development of values towards moderation and the consolidation of intellectual security. Additionally, the learning e-game represents awareness messages in three short films to activate the role of curricula and intellectual awareness centers to apply realistically, innovatively, and effectively.

• 한국지능시스템학회논문지
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• 제17권2호
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• pp.244-251
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• 2007

사용자 의도 파악(intention reading) 기술은 스마트 홈과 같은 복잡한 유비쿼터스(ubiquitous) 환경에서 사용자에게 보다 편리하고 개인화된(personalized) 서비스 제공이 가능하도록 해준다. 또한 학습 기능(learning capability)은 지식 발견(knowledge discovery)의 관점에서 의도 파악 기술의 핵심 요소 기술의 하나로 자리 매김하고 있다 이 논문에서는 스마트 홈(smart home) 환경에서 제공 가능한 개인화된 서비스 중의 하나로, 개인화된 미디어 제어 방법에 대한 내용을 다룬다. 특히, 사람의 행동 패턴과 같은 데이터는 패턴 분류의 관점에서 구분해야 할 클래스(class)에 비해 입력 정보가 불충분한 경우가 많아서 비일관적인(inconsistent) 데이터가 많으므로, 퍼지 논리(fuzzy logic)와 확률 (probability)의 개념을 효과적으로 병행해야 의미 있는 지식을 추출해 낼 수 있다. 이를 위하여 반복 퍼지 지도 클러스터링(IFCS; Iterative Fuzzy Clustering with Supervision) 알고리즘에 기반하여 주어진 데이터 패턴으로부터 확률적 퍼지 룰(probabilistic fuzzy rule)을 얻어 내는 방법에 대해 설명한다. 또한 이를 이용한 다양한 학습 제어 구조를 바탕으로 개인화된 미디어 서비스를 추천해 줄 수 있는 방법에 대해서 설명하도록 하고, 실험 결과를 통해 제안된 시스템의 효용성을 보이도록 한다.

• Journal of Information Processing Systems
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• 제15권5호
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• pp.1119-1130
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• 2019

With the wide spread of Social Network Services (SNS), fake news-which is a way of disguising false information as legitimate media-has become a big social issue. This paper proposes a deep learning architecture for detecting fake news that is written in Korean. Previous works proposed appropriate fake news detection models for English, but Korean has two issues that cannot apply existing models: Korean can be expressed in shorter sentences than English even with the same meaning; therefore, it is difficult to operate a deep neural network because of the feature scarcity for deep learning. Difficulty in semantic analysis due to morpheme ambiguity. We worked to resolve these issues by implementing a system using various convolutional neural network-based deep learning architectures and "Fasttext" which is a word-embedding model learned by syllable unit. After training and testing its implementation, we could achieve meaningful accuracy for classification of the body and context discrepancies, but the accuracy was low for classification of the headline and body discrepancies.

• International journal of advanced smart convergence
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• 제9권4호
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• pp.156-166
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• 2020

In this paper, to improve spectral efficiency and mitigate interference in coordinated millimeter-wave systems, we proposes an optimal user group and beam selection scheme. The proposed scheme improves spectral efficiency by mitigating intra- and inter-cell interferences (ICI). By examining the effective channel capacity for all possible user combinations, user combinations and beams with minimized ICI can be selected. However, implementing this in a dense environment of cells and users requires highly complex computational abilities, which we have investigated applying multiclass classifiers based on machine learning. Compared with the conventional scheme, the numerical results show that our proposed scheme can achieve near-optimal performance, making it an attractive option for these systems.