• Proceedings of the Korean Information Science Society Conference
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• 2012.06c
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• pp.51-53
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• 2012

데이터 마이닝의 문서분류 기술에서 발전된 오피니언 마이닝은 이제 국외뿐만 아니라 국내의 학계 및 기업에서 중요한 관심분야로 자리잡아가고 있다. 오피니언 마이닝의 핵심은 문서에서 감정 단어를 추출하여 긍정/부정 여부를 얼마나 정확하게 자동적으로 판별하느냐를 평가하는 것이다. 국내에서도 이에 관련된 많은 연구가 이루어 졌으나 아직 실용적으로 적용할 만큼의 정확한 분류 정확도 보이지 않고 있다. 그 이유는 한국어의 경우 비문법적 표현, 감정단어의 다양성 등으로 인해 문서의 극성을 판별하기가 쉽지 않기 때문이다. 본 논문에서는 문법적 요소를 최대한 배제하고 단어 패턴의 빈도만을 고려한 영화평 분류기법을 제안한다. 제안된 방법에서는 문서를 단어들의 리스트로 추상화하여 패턴들의 빈도로 학습한 후 적절한 스코어 함수를 적용하여 문서의 극성을 판별한다. 또한 실험을 통해 제안된 기법의 정확도를 평가한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.806-808
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• 2019

인터넷 기술의 발전에 힘입은 전자상거래의 급격한 발전에 따라 소비자들의 소비습관은 오프라인에서 온라인으로 빠르게 바뀌었다. 이에 따라, 구매한 상품에 대한 평가를 작성하는 것 또한 만연해지면서 소비자들에게 구매 결정의 중요한 요인으로 작용하기 시작하였고 실제 판매량에도 직접적인 영항을 끼치기 시작하였다. 그러나, 현재 전자상거래 시스템에서는 상품에 대한 평가를 한눈에 알아볼 수 있는 기능이 부재하고 있어 소비자의 소비 전략과 판매 전략측면에서의 비효율을 야기하고 있다. 따라서, 본 논문에서는 LSTM 을 기반으로 한 딥러닝 모델을 이용해 감정분석을 하여 온라인 상품평을 긍정/부정에 따라 자동으로 분류하고자 한다. 이를 통해, 효율적인 반응 분석을 위한 기술 개발의 기반을 마련하여 소비자와 판매자 모두에게 더 나아진 전략 수립의 기회를 제공할 것으로 기대한다.

• Journal of Software Assessment and Valuation
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• v.17 no.2
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• pp.19-29
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• 2021

Blockchain technology fulfills the reliance requirement and is now entering a new stage of performance. However, the current blockchain technology has significant disadvantages in scalability and latency because of its architecture. Therefore, to adopt blockchain technology to real industry, we must overcome the performance issue by redesigning blockchain architecture. This paper introduces several element technologies and a novel blockchain architecture TPAC, that preserves blockchain's technical advantage but shows more stable and faster transaction processing performance and low latency.

• Journal of Software Assessment and Valuation
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• v.17 no.1
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• pp.93-99
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• 2021

The demand for online education has rapidly increased due to the influence of COVID-19. One of the biggest challenges in engineering education is how to efficiently conduct experiments online. In this paper, for the virtual experimental system for microcontroller application that is essential for education in the field of electrical, electronic, and control engineering, we described the microcontroller functional modeling and implementation with Java language. The usefulness of the developed microcontroller module has been verified through educational field application.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.63-73
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• 2008

Recent years have seen an explosion of interest in interactive agents motivating human learners to engage in edutainment systems which are designed to be entertaining and educational at the same time. Especially, work on socio-emotional processes has focus on understanding of human's social behavior in training and entertainment a applications. In contrast with work on social emotion, where research groups have developed detailed models of emotional processes, models of personality have emphasized shallow surface behavior. Here, we build on computational appraisal models of emotion to better characterize dispositional differences in how people come to understand social situations. Known as explanatory style, this dispositional factor plays a key role in social interactions and certain socio-emotional disorders, such as depression. Building on appraisal and attribution theories, we model key conceptual variables underlying the explanatory style, and enable agents to exhibit different explanatory tendencies with respect to their personalities. Furthermore, we developed an interactive AR agent based on our framework and applied it into an interactive teaming system that allows participants to explore individual differences in the explanation of social events, with the goal of encouraging the development of perspective laking and emotion-regulatory skills.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.12
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• pp.1871-1876
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• 2010

The reduction of vehicle interior noise has been the main interest of NVH engineers. The driver's perception of the vehicle noise is strongly affected by the psychoacoustic characteristics of the noise and the SPL. The existing methods to evaluate the SQ for vehicle interior noise are linear regression analysis of subjective SQ metrics by statistics and the estimation of subjective SQ values by neural network. However, these methods strongly depend on jury tests, this leads to difficulties. To reduce the important of the jury tests, we suggest a new method using the Mahalanobis distance for SQ evaluation. And, the optimal characteristic values that influenced the results of sound quality evaluation on the basis by main effect. Finally, we developed a new method based on the MD method to evaluate sound quality. The result of noise evaluation revealed that the sound quality could be well improved by changing the structural characteristics of the vehicle.

• Proceedings of the Korea Society of Design Studies Conference
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• 1999.05a
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• pp.26-27
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• 1999

오늘날 디자인의 존재가치는 인간을 위해 형성되는 것으로서 충분히 평가받고 있는 분야이며, 심리학적 측면에서는 인간의 감정을 형성시키는 환경의 한 요소로서 중요하게 평가되어진다. 특히 광고디자인은 대중문화의 근간을 이루고 있는 광고에 심미적 기능을 부여하는 것으로서 대중의 시지각에 미치는 영향이 매우 크다. (중략)

• Communications of Mathematical Education
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• v.34 no.3
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• pp.215-234
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• 2020

With the advent of the AI, the need to use AI in the field of education is widely recognized. The purpose of this study is to shed light on how prospective mathematics teachers perceive the need for AI and the role of teachers in future mathematics education. As a result, with regard to teaching, prospective teachers recognized that the use of AI in school mathematics is a demand of a new era, that various types of lesson can be implemented, and that accurate knowledge and information can be delivered. On the other hand, they recognized that AI has limitations in having cognitive and emotional interactions with students. As for mathematics learning, the prospective teachers recognized that AI can provide individualized learning, be used for supplementary learning outside of school, and stimulate students' interest in learning. However, they also said that learning through AI could undermine students' ability to think on their own. With regard to assessment, the prospective teachers recognized that AI is objective, fair and can reduce teachers' workload, but they also said that AI has limitations in evaluating students' abilities in constructed-response items and in process-focused assessment. The roles of teachers that the prospective teachers think were to conduct a lesson, emotional interaction, unstructured assessment, and counseling, and those of AI were individualized learning, rote learning, structured assessment, and administrative works.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2009.05a
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• pp.75-78
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• 2009

본 연구에서는 세 가지의 각성상태(긴장, 중립, 이완감정)가 3-back 과제 수행능력에 어떠한 영향을 미치는지 관찰하고자 한다. 10명의 남자 (평균 $25.7{\pm}1.5$ 세) 대학생과 10명의 여자 (평균 $24.5{\pm}1.8$ 세) 대학생이 본 실험에 참여하였다. 집단 검사를 통해 추출된 사진을 이용하여 긴장, 중립, 이완의 세 종류의 각성상태를 유발하여 3-back 과제 수행 능력 측정 실험을 수행하였다. Rest 1 (2분), 감성유발사진제시 1 (2분), 3-back Task 1 (2분), 감성유발사진제시 2 (2분), 3-back Task2 (2분), Rest2 (2분)의 5단계로 실험이 진행되었다. 또한 제시된 감정 사진으로 적절한 arousal level 이 유발되었는지를 확인하기 위해 GSR 신호를 측정하였고, 실험 종료 후 주관적 평가를 실시하였다. 3-back 과제의 정답률은 중립감정일 때 가장 컸고, 이완, 긴장 감정 순서였다. 또한 통계적으로 유의하지는 않았지만 중립감정일 때 반응시간이 가장 빠른 경향을 보였다. 본 연구결과로부터 인지 처리와 무관하게 유발된 각성의 증가나 감소는 과제 수행능력을 감소시킬 수 있다는 사실을 유추할 수 있다.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.9-14
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• 2004

Rational sense is affected by emotion. If we add the factor of estimated emotion by environment information into robots, we may get more intelligent and human-friendly robots. However, various sensory information and pattern classification are prescribed for robots to learn emotion so that the networks are suitable for the necessity of robots. Neural network has superior ability to extract character of system but neural network has defect of temporal cross talk and local minimum convergence. To solve the defects, many kinds of modular neural networks have been proposed because they divide a complex problem into simple several subproblems. The modular neural network, introduced by Jacobs and Jordan, shows an excellent ability of recomposition and recombination of complex work. On the other hand, the recurrent network acquires state representations and representations of state make the recurrent neural network suitable for diverse applications such as nonlinear prediction and modeling. In this paper, we applied recurrent network for the expert network in the modular neural network structure to learn data pattern based on emotional assessment. To show the performance of the proposed network, simulation of learning the environment and behavior pattern is proceeded with the real time implementation. The given problem is very complex and has too many cases to learn. The result will show the performance and good ability of the proposed network and will be compared with the result of other method, general modular neural network.