• Proceedings of the Microbiological Society of Korea Conference
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• 2002.10a
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• pp.3-14
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• 2002

Functional genomics aims at uncovering useful information carried on genome sequences and at using it to understand the mechanisms of biological function. Elucidating the unknown biological functions of new genes based upon the genomics rationales will greatly speed up the extensive understanding of biocatalysis and biodegradation in biological world including microorganisms. DNA microarrays generate a system for the simultaneous measurement of the expression level of thousands of genes in a single hybridization assay. Their data mining (transcriptome) strategy has two categories: differential gene expression and coordinated gene expression. Furthermore, measurement of proteins (proteome) generates information on how the transcribed sequences end up as functional characteristics within the cell, and quantitation of metabolites yields information on how the functional proteins act to produce energy and process substrates (metabolome). Various composite functional genomics databases containing genetic, enzymatic and metabolic information have been developed and will contribute to the understanding of the life blue print and the new discoveries and practices in biocatalysis and biodegradation that could enrich their industrial and environmental applications.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.184-185
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• 2018

Face Song Player, which is a system that recognizes the facial expression of an individual and plays music that is appropriate for such person, is presented. It studies information on the facial contour lines and extracts an average, and acquires the facial shape information. MUCT DB was used as the DB for learning. For the recognition of facial expression, an algorithm was designed by using the differences in the characteristics of each of the expressions on the basis of expressionless images.

• Journal of Information Technology Applications and Management
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• v.27 no.5
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• pp.23-33
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• 2020

As the 4G and 5G Internet technologies become more common and developed, an environment for uploading and watching videos is created and spread, in addition to simply uploading posts. Watching and sharing daily life among media contents called Vlog, are very common more than ever. This means that individual users could access Vlog easily and the situation could be new trend. Additionally, academic research about Volg is increasing. We analyzed three independent variables affecting a perceived enjoyment we set up the dependent variable. Information search, self-expression, and social need are set as independent variables and social interaction is set as the control variable. Information search and self-expression are significant effect to perceived enjoyment except social need. In particular, social interaction as a control variable has effect to all relationships.

• Journal of Information Processing Systems
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• v.19 no.1
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• pp.1-16
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• 2023

Synthetic data generation is generally used in performance evaluation and function tests in data-intensive applications, as well as in various areas of data analytics, such as privacy-preserving data publishing (PPDP) and statistical disclosure limit/control. A significant amount of research has been conducted on tools and languages for data generation. However, existing tools and languages have been developed for specific purposes and are unsuitable for other domains. In this article, we propose a regular expression-based data generation language (DGL) for flexible big data generation. To achieve a general-purpose and powerful DGL, we enhanced the standard regular expressions to support the data domain, type/format inference, sequence and random generation, probability distributions, and resource reference. To efficiently implement the proposed language, we propose caching techniques for both the intermediate and database queries. We evaluated the proposed improvement experimentally.

• Journal of Korea Society of Industrial Information Systems
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• v.7 no.3
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• pp.23-31
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• 2002

In this paper we propose a new feature vector for recognition of the facial expression based on Gibbs distributions which are well suited for representing the spatial continuity. The extracted feature vectors are invariant under translation rotation, and scale of an facial expression imege. The Algorithm for recognition of a facial expression contains two parts： the extraction of feature vector and the recognition process. The extraction of feature vector are comprised of modified 2-D conditional moments based on estimated Gibbs distribution for an facial image. In the facial expression recognition phase, we use discrete left-right HMM which is widely used in pattern recognition. In order to evaluate the performance of the proposed scheme, experiments for recognition of four universal expression (anger, fear, happiness, surprise) was conducted with facial image sequences on Workstation. Experiment results reveal that the proposed scheme has high recognition rate over 95%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.2
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• pp.92-99
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• 2014

This paper proposes the method of facial expression recognition based on decision tree structure. In the image of facial expression, ASM(Active Shape Model) and LBP(Local Binary Pattern) make the local features of a facial expressions extracted. The discriminant features gotten from local features make the two facial expressions of all combination classified. Through the sum of true related to classification, the combination of facial expression and local region are decided. The integration of branch classifications generates decision tree. The facial expression recognition based on decision tree shows better recognition performance than the method which doesn't use that.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.4
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• pp.201-212
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• 2013

The purpose of this study are to show a new possibility of identity design to be used as tools of users identity expression, designing digital contents by studying on the methods to express users identities successfully in the digital contents design, and to present the possibility to expand the area of identity design. Digital contents are a communication media in it self, but this study tried to consider the digital contents as a tool of users communication or expression. The identity expression, which are not only makes communications efficient but also lets products and companies acknowledged by users, is one of the most indispensable factors in products competitive power in both the present and the future. However, no define methods of identity expression are settled as well as recognized by users properly and accurately yet, so that this study focuses on that point. Therefore, This study is advanced in the direction of establishing the concept of digital identity for an expansion of the media toward the identity expression in design as well as making researchers in successful identity expression ways by means of actual design, more than a graphic image making that simply decorates a digital contents. The point of this study is to show a new concept of identity design that expresses users identities so as to suggest another possibility of identity design.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.41-47
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• 2022

In this paper, we propose a new and simple self-supervised learning method that predicts the middle image of a face image sequence for automatic expression recognition. Automatic facial expression recognition can achieve high performance through deep learning methods, however, generally requires a expensive large data set. The size of the data set and the performance of the algorithm are tend to be proportional. The proposed method learns latent deep representation of a face through self-supervised learning using an existing dataset without constructing an additional dataset. Then it transfers the learned parameter to new facial expression reorganization model for improving the performance of automatic expression recognition. The proposed method showed high performance improvement for two datasets, CK+ and AFEW 8.0, and showed that the proposed method can achieve a great effect.

• The KIPS Transactions:PartA
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• v.14A no.2
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• pp.85-90
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• 2007

This paper presents a facial animation and expression control method that enables the animator to select any facial frames from the facial expression space, whose expression transfer paths the system can setup automatically. Our system creates the facial expression space from approximately 2500 captured facial frames. To create the facial expression space, we get distance between pairs of feature points on the face and visualize the space of expressions in 2D space by using the Multidimensional scaling(MDS). To setup most suitable expression transfer paths, we classify the facial expression space into four field on the basis of any facial expression state. And the system determine the state of expression in the shortest distance from every field, then the system transfer from the state of any expression to the nearest state of expression among thats. To complete setup, our system continue transfer by find second, third, or fourth near state of expression until finish. If the animator selects any key frames from facial expression space, our system setup expression transfer paths automatically. We let animators use the system to create example animations or to control facial expression, and evaluate the system based on the results.

• Proceedings of the IEEK Conference
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• 2002.06c
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• pp.25-28
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• 2002

This paper introduce a personalized facial expression recognition system. Many previous works on facial expression recognition system focus on the formal six universal facial expressions. However, it is very difficult to make such expressions for normal person without much effort and training. And in these days, the personalized service is also mainly focused by many researchers in various fields. Thus, we Propose a novel facial expression recognition system with fuzzy neural networks and robust image processing.