• Proceedings of the Computational Structural Engineering Institute Conference
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• 1993.04a
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• pp.79-85
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• 1993

An integrated structural design system can define and process complex design information that occurs in each of the design stages for flexible cooperation. It can also reduce human error on sequential design steps: preliminary design, analysis and detailed design. Therefore, it's very important to have consistent semantic expression and procedure for structural design information that has complex relationships. In this study, we introduce the object-oriented concepts and object-oriented database thechnique that provides high level semantic expression in order to develop an integrated structural design system.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.12
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• pp.1189-1195
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• 2004

This paper investigates construction of gene (interaction) networks from gene expression time-series data based on evolutionary computation. To illustrate the proposed approach in a comprehensive way, we first assume an artificial gene network and then compare it with the reconstructed network from the gene expression time-series data generated by the artificial network. Next, we employ real gene expression time-series data (Spellman's yeast data) to construct a gene network by applying the proposed approach. From these experiments, we find that the proposed approach can be used as a useful tool for discovering the structure of a gene network as well as the corresponding relations among genes. The constructed gene network can further provide biologists with information to generate/test new hypotheses and ultimately to unravel the gene functions.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.29-34
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• 2005

DNA microarray becomes a major tool for the investigation of global gene expression in all aspects of cancer and biomedical research. DNA microarray experiment generates enormous amounts of data and they are meaningful only in the context of a detailed description of microarrays, biomaterials, and conditions under which they were generated. MicroArray Gene Expression Data (MGED) society has established microarray standard for structured management of these diverse and large amount data. MGED MAGE-OM (MicroArray Gene Expression Object Model) is an object oriented data model, which attempts to define standard objects for gene expression. To assess the relevance of DNA microarray analysis of cancer research it is required to combine clinical and genomics data. MAGE-OM, however, does not have an appropriate structure to describe clinical information of cancer. For systematic integration of gene expression and clinical data, we create a new model, Cancer Genomics Object Model.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.13
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• pp.5149-5152
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• 2015

Cancer-testis antigens (CTAs) are a group of tumor-associated antigens with more than 140 members whose expression has been shown to be limited to gametogenic tissues and placenta among normal tissues. However, malignant tissues of different origins have shown aberrant and elevated expression of these antigens. Such a pattern of expression endows beneficial properties for use as cancer biomarkers as well as immunotherapeutic targets as a result of the immune-privileged status of the testes. CTAs have been shown to be expressed in pediatric brain tumors, different types of sarcomas, leukemias, and lymphomas as well as neuroblastomas. Although data regarding their expression pattern in childhood tumors are not as comprehensive as for adult tumors, it is supposed that CTA-based immunotherapeutic approaches can also be used for pediatric cancers. However, there are limited data about the objective clinical responses following immunotherapy in such patients. Here we try to review the available information.

• Journal of Korea Multimedia Society
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• v.20 no.7
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• pp.1136-1147
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• 2017

In this study, we investigated the effect of users' emoticon usage on their satisfaction with image making and self-expression in MIM communication. We defined internal attraction, social appeal, and communication ability as personal image making factors due to the use of emoticons in MIM communication. And we defined the research hypotheses based on the definition of intimacy, openness, and social reality as relational image making factors. In MIM communication, we analyzed the questionnaire about emoticon users. As a result, emoticon usage was found to have a positive and significant effect on self-expression in relation image making rather than personal image making. The study implies that the use of emoticons can lead to image making in MIM communication and satisfy the satisfaction of self expression.

• Journal of the Semiconductor & Display Technology
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• v.12 no.3
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• pp.53-57
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• 2013

Human emotions are expressed in various ways. It can be expressed through language, facial expression and gestures. In particular, the facial expression contains many information about human emotion. These vague human emotion appear not in single emotion, but in combination of various emotion. This paper proposes a emotional expression algorithm using Active Appearance Model(AAM) and Fuzz k- Nearest Neighbor which give facial expression in similar with vague human emotion. Applying Mahalanobis distance on the center class, determine inclusion level between center class and each class. Also following inclusion level, appear intensity of emotion. Our emotion recognition system can recognize a complex emotion using Fuzzy k-NN classifier.

• Genomics & Informatics
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• v.2 no.1
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• pp.19-29
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• 2004

Gene expression profiles may offer more information than morphology and provide an alternative to morphology- based tumor classification systems. Informative gene selection is finding gene subsets that are able to discriminate between tumor types, and may have clear biological interpretation. Gene selection is a fundamental issue in gene expression based tumor classification. In this report, techniques for selecting informative genes are illustrated and supervised shaving introduced as a gene selection method in the place of a clustering algorithm. The supervised shaving method showed good performance in gene selection and classification, even though it is a clustering algorithm. Almost selected genes are related to leukemia disease. The expression profiles of 3051 genes were analyzed in 27 acute lymphoblastic leukemia and 11 myeloid leukemia samples. Through these examples, the supervised shaving method has been shown to produce biologically significant genes of more than $94\%$ accuracy of classification. In this report, SVM has also been shown to be a practicable method for gene expression-based classification.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.6
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• pp.44-55
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• 2009

Diagnosis of diseases using gene expression data obtained from microarray chip is an active research area recently. It has been done by general machine learning algorithms, because it is difficult to analyze directly. However, recent research results about the analysis based on the interaction between genes is essential for the gene expression analysis, which means the analysis using the traditional machine learning algorithms has limitations. In this paper, we classify the gene expression data using the hyper-network model that considers the higher-order correlations between the features, and then compares the classification accuracies. And also, we present the new hypo-network model that improve the disadvantage of existing model, and compare the processing performances of the existing hypo-network model based on general sequential processor and the improved hypo-network model implemented on parallel processors. In the experimental results, we show that the performance of our model shows improved and competitive classification performance than traditional machine learning methods, as well as, the existing hypo-network model. We show that the performance is maximized when the hypernetwork model is implemented on our parallel processors.

• Archives of design research
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• v.11 no.1
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• pp.209-218
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• 1998

Information is the most important rather then wealth in the information age. According to propagation of the information by new media, this era is called communication innovation age. And away of thought and life style as well as a society system are changing. Propagation by newspaper and TV as well as new media makes new view on value of consumers, and they recognize propensity to consume as needs from emotion rather than economical value. Changes of thoughts make lots of innovation:from one side, modern design to multi-meanimg design, from consuming of products to consuming of the image, from outer object to inner object, from consuming by mass to consuming individually by fashion. It means the possibilities that a meaning could be interpreted variously. Sign is a configuration for communication with discourse, which is the communication between meaning maker and meaning solver. In this study, various expression of sign in advertising were divided into direct expression and metaphoritical expression which was analysed deeply because it was recoquized as proper expression methed in postmodem design.

• Journal of IKEEE
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• v.25 no.3
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• pp.430-436
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• 2021

The non-contact body temperature measurement system is one of the key factors, which is manage febrile diseases in mass facilities using optical and thermal imaging cameras. Conventional systems can only be used for simple body temperature measurement in the face area, because it is used only a deep learning-based face detection algorithm. So, there is a limit to detecting abnormal symptoms of the infants and young children, who have difficulty expressing their opinions. This paper proposes an improved facial expression recognition algorithm for detecting abnormal symptoms in infants and young children. The proposed method uses an object detection model to detect infants and young children in an image, then It acquires the coordinates of the eyes, nose, and mouth, which are key elements of facial expression recognition. Finally, facial expression recognition is performed by applying a selective sharpening filter based on the obtained coordinates. According to the experimental results, the proposed algorithm improved by 2.52%, 1.12%, and 2.29%, respectively, for the three expressions of neutral, happy, and sad in the UTK dataset.