• 한국컴퓨터정보학회논문지
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• 제26권10호
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• pp.9-17
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• 2021

인간은 사회적인 동물로서, 대화로써 정보를 얻거나 사회적인 교류를 해왔다. 대화는 두 사람 이상의 작은 모임에서 서로 말을 편하게 주고받는 것으로, 한 사람이 다른 사람에게 가지는 감성에 따라 그 말의 분위기가 달라질 수 있다. 영화에서 인물들과 인물들이 펼치는 이야기는 중요한 요소로 작용하며, 인물들 간의 관계는 이야기와 인물 간의 대사를 이해하는데 꼭 필요하다. 그러나 이런 정보를 영화에서 자동으로 추출하는 방법은 아직까지 연구되지 않아서 관객들에게 제공되고 있지 못하고 있다. 따라서, 영화 속 양상을 자동으로 분석하는 모델이 필요하다. 본 논문에서는 딥 러닝 기법을 활용하여 각 영화 등장 인물들 간의 감성을 측정하여 영화 속 인물들 간의 관계를 효과적으로 분석하는 방법을 제안한다. 제안 방법은 먼저 영화 대본으로부터 주요 인물들을 추출하고, 주요 인물들 간의 대화를 효과적으로 찾는다. 그런 다음, 주요 인물들 간의 관계를 분석하기 위하여, 감성 분석을 수행하여 전체 시간 간격 내 대사의 위치에 따라 가중치를 부여하고 점수를 수집한다. 또한, 실데이터를 이용한 실험을 통하여 제안 기법이 효과적으로 영화 등장 인물들 간의 감성을 분석할 수 있음을 보인다.

• 문화기술의 융합
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• 제7권4호
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• pp.267-272
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• 2021

본 연구는 코로나 사태로 인한 비대면 교양 영어 수업에서 영화 대본 소리 내어 읽기가 유학생들의 영어 능력에 미치는 영향을 알아보는 것을 목적으로 한다. 서울 소재 대학에 다니는 유학생 47명을 대상으로 일주일에 한 번, 15주간, 애니메이션 라푼젤(Tangled)을 이용하여 교양 영어 수업을 진행하였다. 교사의 동영상 수업과 영화 대본 소리 내어 읽기 활동을 격주로 진행하였다. 교사는 쉬운 한국어로 영화 대사의 어휘 설명 및 해석으로 동영상을 제작하여 학습 관리 시스템(LMS)에 게시하였다. 학생들은 소리 내어 읽기 활동은 줌을 통해 교사의 도움을 받으며 개인별 및 조별 소리 내어 읽기를 하였다. 사후 평가에서 사전 평가 대비 읽기와 쓰기 영역 모두에서 유의미한 향상을 보여주었다. 설문에서는 이해도, 만족도, 흥미도, 추천도의 정의적 측면에서 긍정적인 결과가 나타났다.

• 한국환경교육학회지:환경교육
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• 제20권2호
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• pp.25-35
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• 2007

The purpose of this study was to investigate the effect on the achievement of knowledge by animation-based learning program(ALP) in environmental education. The topic covered by ALP was "meaning and kinds of alien animals and plants". Four classes were selected and divided into two groups. The one was control group, and the other was treatment. 121 female the eighth graders(60 control and 61 ALP students) were piloted. Whereas control students learned using Powerpoint presentation-based materials, ALP students learned using web-based flash animations and animated database with images and movie clips. The score of knowledge achievement of ALP students was compared to control group students using ANCOVA, and then the score of ALP students was significantly higher than that of control group students(p<0.05). The ALP using animations and animated database was effective on the understanding of the alien animals and plants.

• International Journal of Computer Science & Network Security
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• 제23권8호
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• pp.101-106
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• 2023

In this busy world actually stress is continuously grow up in research and monitoring social websites. The social interaction is a process by which people act and react in relation with each other like play, fight, dance we can find social interactions. In this we find social structure means maintain the relationships among peoples and group of peoples. Its a limit and depends on its behavior. Because relationships established on expectations of every one involve depending on social network. There is lot of difference between emotional pain and physical pain. When you feel stress on physical body we all feel with tensions, stress on physical consequences, physical effects on our health. When we work on social network websites, developments or any research related information retrieving etc. our brain is going into stress. Actually by social network interactions like watching movies, online shopping, online marketing, online business here we observe sentiment analysis of movie reviews and feedback of customers either positive/negative. In movies there we can observe peoples reaction with each other it depends on actions in film like fights, dances, dialogues, content. Here we can analysis of stress on brain different actions of movie reviews. All these movie review analysis and stress on brain can calculated by machine learning techniques. Actually in target oriented business, the persons who are working in marketing always their brain in stress condition their emotional conditions are different at different times. In this paper how does brain deal with stress management. In software industries when developers are work at home, connected with clients in online work they gone under stress. And their emotional levels and stress levels always changes regarding work communication. In this paper we represent emotional intelligence with stress based analysis using machine learning techniques in social networks. It is ability of the person to be aware on your own emotions or feeling as well as feelings or emotions of the others use this awareness to manage self and your relationships. social interactions is not only about you its about every one can interacting and their expectations too. It about maintaining performance. Performance is sociological understanding how people can interact and a key to know analysis of social interactions. It is always to maintain successful interactions and inline expectations. That is to satisfy the audience. So people careful to control all of these and maintain impression management.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권2호
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• pp.538-561
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• 2020

Recommender Systems (RecSys) have a major role in e-commerce for recommending products, which they may like for every user and thus improve their business aspects. Although many types of RecSyss are there in the research field, the state of the art RecSys has focused on finding the user similarity based on sequence (e.g. purchase history, movie-watching history) analyzing and prediction techniques like Recurrent Neural Network in Deep learning. That is RecSys has considered as a sequence prediction problem. However, evaluation of similarities among the customers is challenging while considering temporal aspects, context and multi-component ratings of the item-records in the customer sequences. For addressing this issue, we are proposing a Deep Learning based model which learns customer similarity directly from the sequence to sequence similarity as well as item to item similarity by considering all features of the item, contexts, and rating components using Dynamic Temporal Warping(DTW) distance measure for dynamic temporal matching and 2D-GRU (Two Dimensional-Gated Recurrent Unit) architecture. This will overcome the limitation of non-linearity in the time dimension while measuring the similarity, and the find patterns more accurately and speedily from temporal and spatial contexts. Experiment on the real world movie data set LDOS-CoMoDa demonstrates the efficacy and promising utility of the proposed personalized RecSys architecture.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제3권7호
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• pp.263-270
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• 2014

본 논문에서는 영화의 흥행을 예측하기 위한 방법을 제안한다. 최근 영화시장이 성장함에 따라 시장의 수요를 예측하기 위한 다양한 연구들이 수행되고 있다. 영화는 비교적 수명주기가 짧은 문화상품이다. 따라서 안정적인 수익을 창출하기 위해 개봉 전 마케팅비용 및 개봉 후 스크린 수 등에 대한 설계가 필요하다. 이를 위해서는 상품의 수요와 경제적인 수익규모에 대한 계산이 선행되어야 한다. 기존 관련 연구들의 경우 예측을 위한 변수로서 주로 영화 자체의 속성들이나 시장에서의 경쟁요인 등을 이용한다. 그러나 정작 상품을 구매하는 주체인 잠재관객들에 대한 비중은 비교적 미비하다. 따라서 본 논문에서는 사람들이 가진 영화에 대한 인지도를 고려하기 위해 트위터를 하나의 설문표본으로서 활용했다. 기존에 사용된 변수들과 트위터에서 추출한 정보를 오프라인 요소와 온라인 요소로 정의하고, 두 요소를 취합하여 기계학습을 적용했다. 실험을 통해 본 논문에서 제시하는 예측기법을 검증했으며, 실험결과 약 95%의 정확도로 영화의 흥행을 예측했다.

• Journal of Power Electronics
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• 제10권6호
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• pp.643-646
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• 2010

An interactive web-based teaching tool for a power semiconductor course at the University of Central Florida is presented in this paper. A novel approach is introduced using Technology Aided Design Tools (TCAD) to generate time-lapsed 2D semiconductor device cross-section embedded in a webpage using $Adobe^{(R)}$ Flash (web design tool) platform to create interactive movies that demonstrate complex device physical phenomenon. Students can step through the interactive movies forward, backward, pausing, or looping. Each step represents a giving bias condition. Current-voltage plots are represented along with the semiconductor device and a visual point is placed on the IV curve to indicate the current bias conditions. The changes are then reflected in the 2D cross-section movie area and the IV plot. This tool was implemented in a classroom setting to augment the lectures or for discovery learning.

• Journal of Information Processing Systems
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• 제15권5호
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• pp.1029-1035
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• 2019

In recent years, artificial intelligence (AI) services have become one of the most essential parts to extend human capabilities in various fields such as face recognition for security, weather prediction, and so on. Various learning algorithms for existing AI services are utilized, such as classification, regression, and deep learning, to increase accuracy and efficiency for humans. Nonetheless, these services face many challenges such as fake news spread on social media, stock selection, and volatility delay in stock prediction systems and inaccurate movie-based recommendation systems. In this paper, various algorithms are presented to mitigate these issues in different systems and services. Convolutional neural network algorithms are used for detecting fake news in Korean language with a Word-Embedded model. It is based on k-clique and data mining and increased accuracy in personalized recommendation-based services stock selection and volatility delay in stock prediction. Other algorithms like multi-level fusion processing address problems of lack of real-time database.

• 한국지구과학회지
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• 제25권8호
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• pp.748-753
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• 2004

;이 연구의 목적은 SF(Science Fiction)영화를 활용한 교육용 웹 콘텐츠를 개발하여 과학 수업에 적용함으로서 학습 효과를 알아보는 데 있다. 중학교 2학년 과학 교과 중 “지구와 별” 단원수업에 활용할 수 있는 SF영화 3종류, “아마겟돈”, “아폴로13”, “토탈리콜”을 선정하고 영화의 내용 중 과학 하습 자료로 활용할 수 있는 WBI용 웹 콘텐츠를 제작하였다. 개발된 학습 자료를 2대 학습 학생들을 대상으로 수업에 적용하고 ‘SF영화를 수업에 활용하는 데 대한 학생들의 인식 변화’와 ‘과학과 관련된 태도 변화’를 조사하였다. 그 결과 수업 전보다 수업 후에 ‘SF영화는 과학 교과 내용과 관련된 것이 많고 웹을 이용한 과학 수업이 효과가 있다’고 응답하였으나(p<0.05), ‘과학과 관련된 태도 변화’에는 유의미한 차이를 보이지 않았다(p>0.05). 그러나 학생들에게 과학에 대한 흥미를 높이고 학습 효과를 증진시키는 데 기여할 수 있음을 알 수 있었다. 또 웹을 이용한 학습은 시간과 장소에 구애받지 않고 보다 쉽게 과학에 접근할 수 있는 효율적인 학습방법이라는 것도 알 수 있었다.

• International Journal of Advanced Culture Technology
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• 제7권4호
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• pp.49-55
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• 2019

In the age of information, newly produced knowledge is mostly written in English. Therefore, there has been a strong demand for English language learning in the EFL context. However, most EFL learners possess a lack of interest and motivation in the text-based reading class. In this educational context, film is one of the most widely used materials in English reading classes considering that modern learners are predominantly familiar with various audiovisual materials. The purpose of this study is to investigate how Korean EFL learners experienced in the film-based reading class. Specifically, this study aims to analyze the EFL students' perceptions about the class and learning strategies that they used during the class. In order to comprehensively interpret the EFL learners' experiences in the classroom, a coding system consisting of five categories was developed: report, emotion, reflection, evaluation, future plans. The results of data analysis showed that the use of movies in English reading classes had positive effects on reading comprehension and inference of word meaning. The most frequently used learning strategies were affective strategies which helped them control their emotion, attitude, motivations and values, whereas memorization strategies were rarely used. In this respect, this study suggests that the use of movies in the EFL reading classroom encourage students' attention and help them obtain and activate schema which is useful in gaining a better understanding of text-based reading materials.