• The Journal of Korean Institute for Practical Engineering Education
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• v.4 no.2
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• pp.171-175
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• 2012

Recently, the research on ICT (Information and Communication Technology), which cognizes and communicates human's emotion through information technology, is increasing. For instance, there are researches on phones and services that perceive users' emotions through detecting people's voices, facial emotions, and biometric data. In short, emotions which were used to be predicted only by humans are, now, predicted by digital equipment instead. Among many ICT researches, research on emotion recognition from face is fully expected as the most effective and natural human interface. This paper studies about sensitivity ICT and examines mechanism of facial expression recognition system as an example of sensitivity ICT.

• IE interfaces
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• v.19 no.3
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• pp.174-180
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• 2006

This paper deals with the robot system of recognizing human's expression from a detected human's face and then showing human's emotion. A face detection method is as follows. First, change RGB color space to CIElab color space. Second, extract skin candidate territory. Third, detect a face through facial geometrical interrelation by face filter. Then, the position of eyes, a nose and a mouth which are used as the preliminary data of expression, he uses eyebrows, eyes and a mouth. In this paper, the change of eyebrows and are sent to a robot through serial communication. Then the robot operates a motor that is installed and shows human's expression. Experimental results on 10 Persons show 78.15% accuracy.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.2
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• pp.147-160
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• 2019

Compared with the research on consumer engagement in brand community, the research on consumer engagement in brand public has been relatively less. This research aimed at exploring how brand public characteristics such as information variety, various communications and no limitation in expressing self affect the brand public engagement. 274 questionnaires answered by Chinese consumers are used to conduct analysis. Principal component analysis is used to test the reliability and validity of each construct, and structural equation model is used to test hypotheses. The study finds the positive effects of information variety on information benefits, those of various communications on social benefits, and also positive roles of no limitation in expressing self to brand-related self-expression motivation. And each of the information benefits, social benefits and brand-related self-expression motivation is proved to positively affect brand public engagement. The study implies that marketers should give attention to characteristics of brand public, and provide the ways by which members of brand public engage the brand. Additionally, marketers should pay more attention to both direct and indirect engagement activities of consumers toward brand public in social media to better understand their target consumers.

• Journal of Korean Clinical Health Science
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• v.8 no.2
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• pp.1436-1443
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• 2020

Purpose: The purpose of this study was to differences in the expression rate of Porphyromonas gingivalis according to smoking status, smoking amount and period of smoking. Methods: At the time of investigation, 30 smokers and non-smokers were recruited among patients with periodontitis with a probing pocket depth(PPD) of 4 mm or more. General information was collected using a self-questionnaire, and the average value was used by a dentist to measure the probing pocket depth of three times each for the first or second molar. Plaque collection and analysis were performed by collecting only subgingival plaque using a conventional method, and the expression rate of P. gingivalis was confirmed using polymerase chain reaction (PCR). For statistical analysis, the SPSS Ver 25.0 program was used. Results: Smoking did not have a significant effect on the expression of P. gingivalis, but it did affect the expression of more type II genotypes (p<0.05). In addition, smokers had more slight periodontal pocket, and the amount and duration of smoking did not affect the expression of P. gingivalis. Conclusions: In the future, it is necessary to reinforce the group of smokers and non-smokers with healthy oral conditions, and to investigate the quantitative difference in the expression rate and genotype of P. gingivalis over time of harmful substances in smoking.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.5
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• pp.1839-1843
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• 2015

Background: MicroRNAs are a class of noncoding RNAs which regulate multiple cellular processes during tumor development. The purpose of this report is to investigate the clinicopathological and prognostic significance of miR-218 in human gliomas. Materials and Methods: Quantitative RT-PCR (qRT-PCR) was conducted to detect the expression of miR-218 in primary normal human astrocytes, three glioma cell lines and 98 paired glioma and adjacent normal brain tissues.Associations of miR-218 with clinicopathological variables of glioma patients were statistically analyzed. Finally, a survival analysis was performed using the Kaplan-Meier method and Cox's proportional hazards model. Results: The expression level of miR-218 in primary normal human astrocytes was significantly higher than that in glioma cell lines (p<0.01). Also, the expression level of miR-218 in glioma tissues was significantly downregulated in comparison with that in the adjacent normal brain tissues (p<0.001). Statistical analyses demonstrated that low miR-218 expression was closely associated with advanced WHO grade (p=0.002) and low Karnofsky performance score (p=0.010) of glioma patients. Kaplan-Meier analysis with the log-rank test showed that patients with low-miR-218 expression had poorer disease-free survival and overall survival (p=0.0045 and 0.0124, respectively). Multivariate analysis revealed that miR-218 expression was independently associated with the disease-free survival (p=0.009) and overall survival (p=0.004) of glioma patients. Conclusions: Our results indicate that miR-218 is downregulated in gliomas and that its status might be a potential valuable biomarker for glioma patients.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.9
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• pp.1516-1524
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• 2018

Objective: Defensins are a large family of antimicrobial peptides and components of the innate immune system that invoke an immediate immune response against harmful pathogens. Defensins are classified into alpha-, beta-, and theta-defensins. Avian species only possess beta-defensins (AvBDs), and approximately 14 AvBDs (AvBD1-AvBD14) have been identified in chickens to date. Although substantial information is available on the conservation and phylogenetics, limited information is available on the expression and regulation of AvBD8 in chicken immune tissues and cells. Methods: We examined AvBD8 protein expression in immune tissues of White Leghorn chickens (WL) by immunohistochemistry and quantitative reverse transcription-polymerase chain reaction (RT-qPCR). In addition, we examined AvBD8 expression in chicken T-, B-, macrophage-, and fibroblast-cell lines and its regulation in these cells after lipopolysaccharide (LPS) treatment by immunocytochemistry and RT-qPCR. Results: Our results showed that chicken AvBD8 protein was strongly expressed in the WL intestine and in macrophages. AvBD8 gene expression was highly upregulated in macrophages treated with different LPS concentrations compared with that in T- and B-cell lines in a time-independent manner. Moreover, chicken AvBD8 strongly interacted with other AvBDs and with other antimicrobial peptides as determined by bioinformatics. Conclusion: Our study provides the expression and regulation of chicken AvBD8 protein in immune tissues and cells, which play crucial role in the innate immunity.

• Journal of Plant Biotechnology
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• v.37 no.2
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• pp.144-152
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• 2010

As the International Rice Genome Sequencing Project (IRGSP) was completed in 2005 and opened to the public, many countries are making a lot of investments in researches on the utilization of sequence information along with system development. Also, the necessity of the functional genomics researches using microarray is increased currently to secure unique genes related with major agricultural traits and analyze metabolic pathways. Microrarray enables efficient analysis of large scale gene expression and related transcription regulation. This review aims to introduce available microarrays made based on rice genome information and current status of gene expression analysis using these microarrays integrated with the databases available to the public. Also, we introduce the researches on the large scale functional analysis of genes related with useful traits and genetic networks. Understanding of the mechanism related with mutual interaction between proteins with co-expression among rice genes can be utilized in the researches for improving major agricultural traits. The direct and indirect interactions of various genes would provide new functionality of rice. The recent results of the various expression profiling analysis in rice will promote functional genomic researches in plants including rice and provide the scientists involved in applications researches with wide variety of expression informations.

• Journal of the Korea Society of Computer and Information
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• v.15 no.4
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• pp.47-55
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• 2010

In this paper, we proposed a recognition system of smile facial expression for smile treatment training. The proposed system detects face candidate regions by using Haar-like features from camera images. After that, it verifies if the detected face candidate region is a face or non-face by using SVM(Support Vector Machine) classification. For the detected face image, it applies illumination normalization based on histogram matching in order to minimize the effect of illumination change. In the facial expression recognition step, it computes facial feature vector by using PCA(Principal Component Analysis) and recognizes smile expression by using a multilayer perceptron artificial network. The proposed system let the user train smile expression by recognizing the user's smile expression in real-time and displaying the amount of smile expression. Experimental result show that the proposed system improve the correct recognition rate by using face region verification based on SVM and using illumination normalization based on histogram matching.

• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.525-536
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• 2004

Gene expression profile is numerical data of gene expression level from organism, measured on the microarray. Generally, each specific tissue indicates different expression levels in related genes, so that we can classify disease with gene expression profile. Because all genes are not related to disease, it is needed to select related genes that is called feature selection, and it is needed to classify selected genes properly. This paper Proposes GA based method for searching optimal ensemble of feature-classifier pairs that are composed with seven feature selection methods based on correlation, similarity, and information theory, and six representative classifiers. In experimental results with leave-one-out cross validation on two gene expression Profiles related to cancers, we can find ensembles that produce much superior to all individual feature-classifier fairs for Lymphoma dataset and Colon dataset.

• Journal of KIISE
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• v.43 no.1
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• pp.54-60
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• 2016

Brain gene expression information is closely related to the structural and functional characteristics of the brain. Thus, extensive research has been carried out on the relationship between gene expression patterns and the brain's structural organization. In this study, Principal Component Analysis was used to extract features of gene expression patterns, and genes were automatically classified by spatial distribution. Voxels were then clustered with classified specific region expressed genes. Finally, we visualized the clustering results for mouse hippocampal region gene expression with the Allen Brain Atlas. This experiment allowed us to classify the region-specific gene expression of the mouse hippocampal region and provided visualization of clustering results and a brain atlas in an integrated manner. This study has the potential to allow neuroscientists to search for experimental groups of genes more quickly and design an effective test according to the new form of data. It is also expected that it will enable the discovery of a more specific sub-region beyond the current known anatomical regions of the brain.