• KIPS Transactions on Software and Data Engineering
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• v.9 no.9
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• pp.267-280
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• 2020

Mirror is a physical reflective surface, typically of glass coated with a metal amalgam, and it is to reflect an image clearly. They are available everywhere anytime and become an essential tool for us to observe our faces and appearances. With the advent of modern software technology, we are motivated to enhance the reflection capability of mirrors with the convenience and intelligence of realtime processing, microservices, and machine learning. In this paper, we present a development of Digital Mirror System that provides the realtime reflection functionality as mirror while providing additional convenience and intelligence including personal information retrieval, public information retrieval, appearance age detection, and emotion detection. Moreover, it provides a multi-model user interface of touch-based, voice-based, and gesture-based. We present our design and discuss how it can be implemented with current technology to deliver the realtime mirror reflection while providing useful information and machine learning intelligence.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2001.05a
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• pp.131-135
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• 2001

Recently, Internet is used widely. Many Web sites, however, are not designed based on user's view. So, this research aimed at grasping the user needs and structure of Web site which user used easily. First, to grasp user needs, questionnaires about the motivation, the purpose and the evaluation items of Web page were done. As a result, we found the easiness for the user. Next, we made subjects operated test pages in which the number of classes and the amount of information were changed. We collected the quantitative data of the optimum number of classes, amount of information and retrieval time. As a result, there was a significant difference in each numerical value. The results of this research are available when constructing a web site. so, usability of Web site can be improved by them.

• Korean Journal of Biological Psychiatry
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• v.18 no.2
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• pp.80-89
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• 2011

Pavlovian fear conditioning has been extensively studied for the understanding of neurobiological basis of memory and emotion. Pavlovian fear conditioning is an associative memory which forms when conditioned stimulus (CS) is paired with unconditioned stimulus (US) once or repeatedly. This behavioral model is also important for the understanding of anxiety disorders such as posttraumatic stress disorder. Here we describe the neural circuitry involved in fear conditioning and the molecular mechanisms underlying fear memory formation. During consolidation some memories fade out but other memories become stable and concrete. Emotion plays an important role in determining which memories will survive. Memory becomes unstable and editable again immediately after retrieval. It opens the possibility for us of modulating the established fear memory. It provides us with very efficient tools to improve the efficacy of cognitive-behavior therapy and other exposure-based therapy treating anxiety disorders.

• Korean Journal of Cognitive Science
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• v.21 no.1
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• pp.157-175
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• 2010

Understanding dialogue participant's emotion is important as well as decoding the explicit message in human communication. It is well known that non-verbal elements are more suitable for conveying speaker's emotions than verbal elements. Written texts, however, contain a variety of linguistic units that express emotions. This study aims at analyzing components for constructing an emotion ontology, that provides us with numerous applications in Human Language Technology. A majority of the previous work in text-based emotion processing focused on the classification of emotions, the construction of a dictionary describing emotion, and the retrieval of those lexica in texts through keyword spotting and/or syntactic parsing techniques. The retrieved or computed emotions based on that process did not show good results in terms of accuracy. Thus, more sophisticate components analysis is proposed and the linguistic factors are introduced in this study. (1) 5 linguistic types of emotion expressions are differentiated in terms of target (verbal/non-verbal) and the method (expressive/descriptive/iconic). The correlations among them as well as their correlation with the non-verbal expressive type are also determined. This characteristic is expected to guarantees more adaptability to our ontology in multi-modal environments. (2) As emotion-related components, this study proposes 24 emotion types, the 5-scale intensity (-2~+2), and the 3-scale polarity (positive/negative/neutral) which can describe a variety of emotions in more detail and in standardized way. (3) We introduce verbal expression-related components, such as 'experiencer', 'description target', 'description method' and 'linguistic features', which can classify and tag appropriately verbal expressions of emotions. (4) Adopting the linguistic tag sets proposed by ISO and TEI and providing the mapping table between our classification of emotions and Plutchik's, our ontology can be easily employed for multilingual processing.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2008.10a
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• pp.90-93
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• 2008

In natural language, it is common that repetitive constituents in an expression are to be left out and it is necessary to figure out the constituents omitted at analyzing the meaning of the sentence. This paper is on recognition of boundaries of parallel noun phrases by figuring out constituents omitted. Recognition of parallel noun phrases can greatly reduce complexity at the phase of sentence parsing. Moreover, in natural language information retrieval, recognition of noun with modifiers can play an important role in making indexes. We propose an unsupervised probabilistic model that identifies parallel cores as well as boundaries of parallel noun phrases conjoined by a conjunctive particle. It is based on the idea of swapping constituents, utilizing symmetry (two or more identical constituents are repeated) and reversibility (the order of constituents is changeable) in parallel structure. Semantic features of the modifiers around parallel noun phrase, are also used the probabilistic swapping model. The model is language-independent and in this paper presented on parallel noun phrases in Korean language. Experiment shows that our probabilistic model outperforms symmetry-based model and supervised machine learning based approaches.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.562-566
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• 2009

In this paper, we present a novel system to categorize web image search results using emotional concepts and to browse the results more conveniently and easily. The proposed system can categorize search results into 8 emotional categories based on emotion vector, which obtained by color and pattern features. Here, we use Kobayashi’s emotional categories: {romantic, natural, casual, elegant, chic, classic, dandy and modern}. With search results for a given query, the proposed system can provide categorized images for each emotional category. With 1,000 Yahoo! search images, we compared the proposed method with Yahoo! image search engine in respect of satisfaction, efficiency, convenience and relevance with a user study. Our experimental results show the effectiveness of the proposed method.

• Journal of the Korean Society for information Management
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• v.21 no.4 s.54
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• pp.187-208
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• 2004

In this study, aesthetic impressions were used for a high-level feature of image retrieval. The term, 'aesthetic' has been studied in psychology, art, and literature. It means unconscious, instantaneous parts of visual perception and emotion. The literatures related to aesthetic impressions were reviewed and four kinds of aesthetic impressions were defined operationally : strong impression, soft impression, courteous impression, and refined impression. 66 image files of paintings were sampled randomly from 1100 paintings and low-level color features were extracted from them by a using perceptual color model(Lai, & Tait, 1998). The high-level features of an image, that is, four kinds of aesthetic impressions of each painting were measured by 4 subjects and averaged. In CBIR, 2 subjects performed image retrievals using example queries. They were asked to retrieve images by using the aesthetic impressions or the keywords. In evaluations, subjects showed that they were satisfied with the aesthetic impression-based image retrieval system on the average. And R-precision of the image retrieval with both color features and aesthetic impressions was higher than that of the image retrieval with color features only. But further studies with larger test collections and query sets should be followed for generalization of the result of this study.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.6 no.2
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• pp.95-106
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• 2007

This paper proposes an effective tempo feature extraction method for music information retrieval. The tempo information is modeled by the narrow-band temporal modulation components, which are decomposed into a modulation spectrum via joint frequency analysis. In implementation, the tempo feature is directly extracted from the modified discrete cosine transform coefficients, which is the output of partial MP3(MPEG 1 Layer 3) decoder. Then, different features are extracted from the amplitudes of modulation spectrum and applied to different music information retrieval tasks. The logarithmic scale modulation frequency coefficients are employed in automatic music emotion classification and music genre classification. The classification precision in both systems is improved significantly. The bit vectors derived from adaptive modulation spectrum is used in audio fingerprinting task That is proved to be able to achieve high robustness in this application. The experimental results in these tasks validate the effectiveness of the proposed tempo feature.

• Journal of Internet Computing and Services
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• v.12 no.4
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• pp.107-117
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• 2011

The appearance of Web has brought an substantial revolution to all fields of society such knowledge management and business transaction as well as traditional information retrieval. In this paper, we propose an EFASIT(Extended Fuzzy AHP and SImilarity Technology) model considering the emotion analysis. And we combine the Extended Fuzzy AHP Method(EFAM) with SImilarity Technology(SIT) based on the domain corpus information in order to efficiently retrieve the document on the Web. The proposed the EFASIT model can generate the more definite rule according to integration of fuzzy knowledge of various decision-maker, and can give a help to decision-making, and confirms through the experiment.

• Journal of KIISE:Software and Applications
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• v.26 no.3
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• pp.422-430
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• 1999

멀티미디어 영상검색 중 영상의 내용을 기반으로 한 검색방법에 관한 연구가 활발히 진행되고 있다. 이는 기존의 키워드기반 영상검색 방법에 비해 효율적인 관리와 검색 방법을 제공하고 있다. 그러나 대부분의 방법이 단순한 공학적 방법에 치우쳐 사람의 감성과는 무관한 검색 결과를 제공한다. 이러한 문제점을 해결하기 위해 본 논문에서는 대화형 유전자 알고리즘을 도입하여 검색과정에 사람의 감성을 반영할 수 있는 방법을 제안한다. 이 방법은 구체적으로 표현될 수 있는 영상 뿐 아니라 우울한 느낌의 영상, 즐거운 느낌의 영상과 같은 추상적인 느낌의 영상을 검색할수 있도록 한다. 2000개의 영상으로 이루어진 데이터베이스로 실험한 결과 , 제안한 방법이 유용함을 알 수 있었다.