• 한국생물공학회:학술대회논문집
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• 2003.10a
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• pp.340-340
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• 2003

• 대한치주과학회:학술대회논문집
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• 2002.11a
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• pp.48-49
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• 2002

• Journal of the Korean Society of Clothing and Textiles
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• v.30 no.7 s.155
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• pp.1126-1134
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• 2006

The purpose of this study was to examine the effect of brand identification of fashion luxury product on brand loyalty and the mediating effect of brand affect. The questionnaire developed through the literature search and a survey was conducted both in on-line and off-line questionnaire simultaneously. Finally 227 data from women who had a buying experience of fashion luxury products were analyzed using frequency, factor analysis, ANOVA, t-test, regression analysis by SPSS for WIN program. The results were as follows. First, the consumers' brand identification was composed of three factors; actual, ideal, social. Second, the brand identification significantly influenced on the brand loyalty. Third, the brand identification significantly influenced on the brand affect. Fourth, the brand affect significantly influenced on the brand loyalty. Fifth, the brand identification had both direct and indirect effects on brand loyalty mediated by brand affect. The results indicated that causal relationship was existed among these three variables.

• Journal of the Korean Society of Clothing and Textiles
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• v.32 no.1
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• pp.88-98
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• 2008

The purpose of this study were to examine the effect of fashion brand personality on the consumer's brand loyalty and to investigate the role of brand identification as mediator. The questionnaire data from 218 women who had purchase experience of fashion luxury brands were collected. Factor analysis and multiple regression analysis were used in data analysis. The results of this study were as follows. First, the consumer's fashion brand personality was composed of eight factors; Status-oriented, appearance-oriented, trend-oriented, leisure-oriented, physical activity-oriented, self achievement-oriented, fun-oriented and relation-oriented factor. Second, brand identification had significantly influence on brand loyalty. Third, fashion brand personality significantly influenced on brand loyalty and brand identification. Especially, the status-oriented, appearance-oriented, trend-oriented and self achievement-oriented fashion brand personality was proved to have a crucial role in brand identification and brand loyalty. Fourth, the status-oriented, appearance- oriented, trend-oriented and self achievement-oriented fashion brand personality had both direct and indirect effects on brand loyalty mediated by brand identification.

• IMMUNE NETWORK
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• v.9 no.1
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• pp.4-7
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• 2009

Although the success of trastuzumab and rituximab for treatment of breast cancer and non-Hodgkins lymphoma, respectively, suggests that monoclonal antibodies(mAbs) will become important therapeutic agents against a wider range of cancers, useful therapeutic Abs are not yet available for the majority of the human cancers because of our lack of knowledge of which antigens (Ags) are likely to become useful targets. We established a procedure for comprehensive identification of such Ags through the extensive isolation of human mAbs that may be therapeutic. Using the phage-display Ab library we isolated a large number of human mAbs that bind to the surface of tumor cells. They were individually screened by immunostaining, and clones that preferentially and strongly stained the malignant cells were chosen. The Ags recognized by those clones were isolated by immunoprecipitation and identified by mass spectrometry(MS). We isolated 2,114 mAbs with unique sequences and identified 25 distinct Ags highly expressed on several carcinomas. Of those 2,114 mAbs 434 bound to specifically to one of the 25 Ags. I am going to discuss how we could select proper target Ags for therapeutic Abs and candidate clones are therapeutic agents.

• Journal of KIISE:Software and Applications
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• v.33 no.5
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• pp.499-507
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• 2006

Recently human gait has been considered as a useful biometric supporting high performance human identification systems. This paper proposes a view-based pedestrian identification method using the dynamic silhouettes of a human body modeled with the Hidden Markov Model(HMM). Two types of gait models have been developed both with an endless cycle architecture: one is a discrete HMM method using a self-organizing map-based VQ codebook and the other is a continuous HMM method using feature vectors transformed into a PCA space. Experimental results showed a consistent performance trend over a range of model parameters and the recognition rate up to 88.1%. Compared with other methods, the proposed models and techniques are believed to have a sufficient potential for a successful application to gait recognition.

• Smart Media Journal
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• v.12 no.2
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• pp.56-65
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• 2023

In broadcasts such as news and coverage programs, voice is modulated to protect the identity of the informant. Adjusting the pitch is commonly used voice modulation method, which allows easy voice restoration to the original voice by adjusting the pitch. Therefore, since broadcast voice modulation methods cannot properly protect the identity of the speaker and are vulnerable to security, a new voice modulation method is needed to replace them. In this paper, using the Lightweight speech de-identification model as the evaluation target model, we compare speech de-identification performance with broadcast voice modulation method using pitch modulation. Among the six modulation methods in the Lightweight speech de-identification model, we experimented on the de-identification performance of Korean speech as a human test and EER(Equal Error Rate) test compared with broadcast voice modulation using three modulation methods: McAdams, Resampling, and Vocal Tract Length Normalization(VTLN). Experimental results show VTLN modulation methods performed higher de-identification performance in both human tests and EER tests. As a result, the modulation methods of the Lightweight model for Korean speech has sufficient de-identification performance and will be able to replace the security-weak broadcast voice modulation.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.16 no.2
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• pp.71-79
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• 2013

The human-associated microbiota is diverse, varies between individuals and body sites, and is important in human health. Microbes in human body play an essential role in immunity, health, and disease. The human microbiome has been studies using the advances of next-generation sequencing and its metagenomic applications. This has allowed investigation of the microbial composition in the human body, and identification of the functional genes expressed by this microbial community. The gut microbes have been found to be the most diverse and constitute the densest cell number in the human microbiota; thus, it has been studied more than other sites. Early results have indicated that the imbalances in gut microbiota are related to numerous disorders, such as inflammatory bowel disease, colorectal cancer, diabetes, and atopy. Clinical therapy involving modulating of the microbiota, such as fecal transplantation, has been applied, and its effects investigated in some diseases. Human microbiome studies form part of human genome projects, and understanding gleaned from studies increase the possibility of various applications including personalized medicine.

• Animal Bioscience
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• v.36 no.6
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• pp.980-989
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• 2023

Objective: Iris pattern recognition system is well developed and practiced in human, however, there is a scarcity of information on application of iris recognition system in animals at the field conditions where the major challenge is to capture a high-quality iris image from a constantly moving non-cooperative animal even when restrained properly. The aim of the study was to validate and identify Black Bengal goat biometrically to improve animal management in its traceability system. Methods: Forty-nine healthy, disease free, 3 months±6 days old female Black Bengal goats were randomly selected at the farmer's field. Eye images were captured from the left eye of an individual goat at 3, 6, 9, and 12 months of age using a specialized camera made for human iris scanning. iGoat software was used for matching the same individual goats at 3, 6, 9, and 12 months of ages. Resnet152V2 deep learning algorithm was further applied on same image sets to predict matching percentages using only captured eye images without extracting their iris features. Results: The matching threshold computed within and between goats was 55%. The accuracies of template matching of goats at 3, 6, 9, and 12 months of ages were recorded as 81.63%, 90.24%, 44.44%, and 16.66%, respectively. As the accuracies of matching the goats at 9 and 12 months of ages were low and below the minimum threshold matching percentage, this process of iris pattern matching was not acceptable. The validation accuracies of resnet152V2 deep learning model were found 82.49%, 92.68%, 77.17%, and 87.76% for identification of goat at 3, 6, 9, and 12 months of ages, respectively after training the model. Conclusion: This study strongly supported that deep learning method using eye images could be used as a signature for biometric identification of an individual goat.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.3
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• pp.193-199
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• 2017

Instead of using only spatial features from a single frame for person re-identification, a combination of spatial and temporal factors boosts the performance of the system. A recurrent neural network (RNN) shows its effectiveness in generating highly discriminative sequence-level human representations. In this work, we implement RNN, three Long Short Term Memory (LSTM) network variants, and Gated Recurrent Unit (GRU) on Caffe deep learning framework, and we then conduct experiments to compare performance in terms of size and accuracy for person re-identification. We propose using GRU for the optimized choice as the experimental results show that the GRU achieves the highest accuracy despite having fewer parameters than the others.