• Journal of Biomedical Engineering Research
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• v.22 no.5
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• pp.425-430
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• 2001

The Purpose of this study was to find the way of discriminating EEG for some mental activity. which are not characterized within linear spectral analysis but with non-linear analysis . We lave investigated the way of characterizing EEG changes during emotional and cognitive states in healthy volunteered subjects who responded to three designed status. in which the subjects were relaxing with ease and eyes closed. listening to music and computing a simple subtraction with eyes closed. Especially, we estimated EEG dimensional complexity by Skinner s Point-wise correlation dimension(PD2) method for each mental states. As a result it has been found that the subjects, who responded that the\ulcorner had concentrated well during the arithmetic task. show higher PD2 in their non-linear EEG measures. in comparison with the subjects who responded that they had not concentrated during the task This highness of PD2 is also significant in statistical analysis. A subject who had the highest score in evaluating the intensity of induced emotion during emotional task shows significantly lower PD2 in statistical analysis than other subjects who had lower scores. Linear spectral analysis was also performed on these data. However, they did not show and significant difference. Only non-linear dynamical analysis shows the significant different result on these mental status.

• Journal of Internet Computing and Services
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• v.21 no.3
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• pp.123-131
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• 2020

Along with the rapid development of artificial intelligence technology, natural language processing, which deals with human language, is also actively studied. In particular, BERT, a language model recently proposed by Google, has been performing well in many areas of natural language processing by providing pre-trained model using a large number of corpus. Although BERT supports multilingual model, we should use the pre-trained model using large amounts of Korean corpus because there are limitations when we apply the original pre-trained BERT model directly to Korean. Also, text contains not only vocabulary, grammar, but contextual meanings such as the relation between the front and the rear, and situation. In the existing natural language processing field, research has been conducted mainly on vocabulary or grammatical meaning. Accurate identification of contextual information embedded in text plays an important role in understanding context. Knowledge graphs, which are linked using the relationship of words, have the advantage of being able to learn context easily from computer. In this paper, we propose a system to extract Korean contextual information using pre-trained BERT model with Korean language corpus and knowledge graph. We build models that can extract person, relationship, emotion, space, and time information that is important in the text and validate the proposed system through experiments.

• Journal of Korea Multimedia Society
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• v.10 no.10
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• pp.1310-1318
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• 2007

First of all, What was the modeling technique used to model 3D-Game character? It's a technique developed along several years, by experience... here is the bases Low polygons characters I always work in low polygon for two reasons -You can easily modify a low-poly character, change shapes, make morph for facial expressions etc -You can easily animate a low-poly character When the modeling is finished, Second, In these days, Computer hardware technologies have been bring about that expansion of various 3D digital motion pictured information and development. 3D digital techniques can be used to be diversity in Animation, Virtual-Reality, Movie, Advertisement, Game and so on. Besides, as computing power has been better and higher, the development of 3D Animations and Character are required gradually. In order to satisfy the requirement, Research about how to make 3D Game modeling that represents Character's emotions, sensibilities, is beginning to set its appearance. 3D characters in 3D Games are the core for the communications of emotion and the informations through their facial expression and characteristic motions, Sounds to Users. All concerning about 3D motion and facial expression are getting higher with extension of frequency in use. Therefore, in this study we suggest the effective method of modeling for 3D character and which are based on 2D Graphics.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.2
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• pp.174-188
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• 2004

In the life environment changed with not only the quality and the price of the products but also the material abundance, it is the most crucial factor for the strategy of product sales to investigate consumer's sensibility and preference degree. In this perspective, it is necessary to design and merchandise the products in cope with each consumer's sensibility and needs as well as its functional aspects. In this paper, we propose the Fashion Design Recommender Agent System (FDRAS-pro) for textile design applying collaborative filtering personalization technique as one of the methods of material development centered on consumer's sensibility and preference. For a collaborative filtering system based on textile, Representative-Attribute Neighborhood is adopted to determine the number or neighbors that will be used for preferences estimation. Pearson's Correlation Coefficient is used to calculate similarity weights among users. We build a database founded on the sensibility adjectives to develop textile designs by extracting the representative sensibility adjectives from users' sensibility and preferences about textile designs. FDRAS-pro recommends textile designs to a customer who has a similar propensity about textile. To investigate the sensibility and emotion according to the effect of design factors, fertile designs were analyzed in terms of 9 design factors, such as, motif source, motif-background ratio, motif variation, motif interpretation, motif arrangement, motif articulation, hue contrast, value contrast, chroma contrast. Finally, we plan to conduct empirical applications to verify the adequacy and the validity of our system.