• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.107-113
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• 2002

We examined the psychophysiological effects of navigation in a virtual reality (VR). Subjects were exposed to the VR, and required to detect specific objects. Ten electrophysiological signals were recorded before, during, and after navigation in the VR. Six questionnaires on the VR experience were acquired from 45 healthy subjects. There were significant changes between the VR period and the pre-VR control period in several psychophysiological measurements. During the VR period, eye blink, skin conductance level, and alpha frequency of EEG were decreased but gamma wave were increased. Physiological changes associated with cybersickness included increased heart rate, eye blink, skin conductance response, and gamma wave and decreased photoplethysmogram and skin temperature. These results suggest an attentional change during VR navigation and activation of the autonomic nervous system for cybersickness. These findings would enhance our understanding for the psychophysiological changes during VR navigation and cybersickness.

• Membrane Journal
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• v.14 no.2
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• pp.85-98
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• 2004

The situation of technology Predominance and the distribution of core technology were visually mapped thorough the investigation of technical trend during 20 years, which was provided with the analysis of patent information for the artificial skin. Therefore, it was expected that technology mapping by means of multilateral analysis method allowed a good grasp of current technology trend of the artificial skin and the subdivision into nation and a field of research presents the direction of R&D. In the early R&D stage of artificial skin, the preparation technology of filters implantable into the living body including nursing devices, bandages, and dressings or absorbent pads (A6IF-002/10) was on the rise in research field of artificial skin until 1980's. And then the materials technology for coating prostheses (A6l L-027/00)was leading the core technology of artificial skin. Also, Nowadays the fusion technology connected the material technology with the cultivation technology of undifferentiated human or animal cells/tissues including culture media (C l2N-005/00, C 12N-005/06) was highlighted all over the world.

• Journal of Digital Contents Society
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• v.19 no.7
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• pp.1397-1403
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• 2018

Today, modern people perceive skin care as part of their physical health care, and acne is a common skin disease problem that is found on the face. In this paper, an effective acne detection algorithm using CIE $L^*a^*b^*$ color space has been proposed. It is red when the pixel value of the component image $a^*$ is a positive number, so it is suitable for detecting acne in skin image. First, the skin image based on the RGB color space is subjected to light compensation through color balancing, and converted into a CIE $L^*a^*b^*$ color space. The extracted component image $a^*$ was normalized, and then the skin and acne area were estimated with the threshold values. Experimental results show that the proposed method detects acne more effectively than the conventional method based on brightness information, and the proposed method is robust against the reflected light source.

• Journal of Convergence for Information Technology
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• v.9 no.10
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• pp.264-271
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• 2019

Currently, teenagers value the beauty of appearance due to the proximity of the media. Therefore, acne on the skin is not a serious disease, but if it is managed incorrectly, it will leave scars and marks on the face, which leads to students' depression, stress and loss of confidence. Therefore, this study analyzed how acne skin afects adolescent's stress, depression and self-esteem and recognized that acne is not a simple skin disease but is closely related to mental health. And three hypotheses were established to be more effective in managing acne skin and to be used as basic data for skin care. As a result, it was found that acne development of junior high school students had an actual effect on stress and depression. Acne skin care is considered to be necessary for mental health, not superficial management.

• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.369-377
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• 2022

Recent deep learning-based face synthesis research shows the result of generating a realistic face including overall style or elements such as hair, glasses, and makeup. However, previous methods cannot create a face at a very detailed level, such as the microstructure of the skin. In this paper, to overcome this limitation, we propose a technique for synthesizing a more realistic facial image from a single face label image by controlling the types and intensity of skin microelements. The proposed technique uses Pix2PixHD, an Image-to-Image Translation method, to convert a label image showing the facial region and skin elements such as wrinkles, pores, and redness to create a facial image with added microelements. Experimental results show that it is possible to create various realistic face images reflecting fine skin elements corresponding to this by generating various label images with adjusted skin element regions.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.137-147
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• 2022

Diagnosis and management of skin condition is a very basic and important function in performing its role for workers in the beauty industry and cosmetics industry. For accurate skin condition diagnosis and management, it is necessary to understand the skin condition and needs of customers. In this paper, we developed SCIS, a big data-based skin care information system that supports skin condition diagnosis and management using social media big data for skin condition diagnosis and management. By using the developed system, it is possible to analyze and extract core information for skin condition diagnosis and management based on text information. The skin care information system SCIS developed in this paper consists of big data collection stage, text preprocessing stage, image preprocessing stage, and text word analysis stage. SCIS collected big data necessary for skin diagnosis and management, and extracted key words and topics from text information through simple frequency analysis, relative frequency analysis, co-occurrence analysis, and correlation analysis of key words. In addition, by analyzing the extracted key words and information and performing various visualization processes such as scatter plot, NetworkX, t-SNE, and clustering, it can be used efficiently in diagnosing and managing skin conditions.

• Journal of the Korean Society of Fashion and Beauty
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• v.2 no.2 s.2
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• pp.81-92
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• 2004

This paper examined the utilization pattern of aroma-therapy and relating factors after visiting about 100 skin-care shops registered to the Central Estheticism's Association in Daegu.Kyungbuk areas, in 200. This questionnaire survey was put into practice from September 1st to September 30th, 2003 for one month, study subjects were 643 skin-care-shop users. As for the experience of Aroma-use. while 85.4% of respondents experienced Aroma-use or has been using Aromat, 14.6% had no experience of Aroma-use. As for average frequency of Aroma-use, 32.8% used Aroma one time a week,23.7% everyday, 20.4% one time a month, 12.0% 3 times a week, 11.1% 2 times a week. As for the route of getting information on aroma, 49.5% of Aroma users got the information in skin-care-shop, 28.6% from mass-media such as internet, TV, newspaper, magazine. Regarding the type of preference aromas, 65.4% answered Lavender, 35.3% Rosemary, 35.2% Peppermint, 25.5% Rose, 23.7% Tea tree, 21.1% Jasmin, 19.5% Lemon. As for purposes of Aroma-use, 36.8% answered problematic-skin-control & fatness-control, 33.5% stress-relaxation, 14.8% physical-symptom-relaxation, 12.4% muscle-relaxation, 2.6% other purposes.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.592-595
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• 2009

In this paper, we propose a face detection technique for still pictures which sequentially uses a skin-color model and a support vector machine (SVM). SVM is a learning algorithm for solving the classification problem. Some studies on face detection have reported superior results of SVM over neural networks. The SVM method searches for a face in a picture while changing the size of the window. The detection accuracy and the processing time of SVM vary largely depending on the complexity of the background of the picture or the size of the face. Therefore, we apply a face candidate area detection method using a skin-color model as a preprocessing technique. We compared the method using SVM alone with that of the proposed method in respect to face detection accuracy and processing time. As a result, the proposed method showed improved processing time while maintaining a high recognition rate.

• Biomedical Science Letters
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• v.23 no.2
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• pp.96-103
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• 2017

Nocardia species (spp.) are opportunistic pathogen in immunocompromised hosts. The genus Nocardia contains more than 70 species. Nocardia takedensis has been recently reported as a new species of the genus Nocardia. In this study, we describes the first clinical isolate of N. takedensis from the skin lesion in Busan, Korea. For the identification of clinical isolate to the species level as N. takedensis, classical methods (colony morphology, biochemical characteristics, and antimicrobial susceptibility), molecular method (16S rRNA gene sequencing), and MS (mass spectrometry) analysis were conducted. Clinical isolates grew slowly on the culture media (5% sheep blood agar and chocolate agar) under 5% $CO_2$ condition. Especially, carotene pigmentation was detected well on the media. Using mass spectrometry, Nocardia isolate was not identified to the species level. However, molecular method based on 16S rRNA sequencing confirmed the isolate as N. takedensis correctly. N. takedensis isolate was partial positive for acid-fast bacilli on the Ziehl-Neelsen method. And it was observed to be resistance to amoxicillin/clavulanic acid and ciprofloxacin. Our results provide useful information to develop optimal identification protocol of N. takedensis in clinical diagnostic laboratories.

• Journal of Microbiology and Biotechnology
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• v.21 no.11
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• pp.1199-1202
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• 2011

Infection of surgical wounds is a severe problem. Conventional tissue reattachment methods have limits of incomplete sealing and high susceptibility to infection. Medical adhesives have several advantages over traditional tissue reattachment techniques, but still have drawbacks, such as the probability of infection, low adhesive strength, and high cytotoxicity. Recently, a new medical adhesive (new-adhesive) with high adhesive strength and low cytotoxicity, composed of aldehyded dextran and ${\varepsilon}$-poly(L-lysine), was developed. The antimicrobial activity of the new-adhesive was assayed using agar media and porcine skin. In the agar diffusion method, inoculated microorganisms that contacted the new-adhesive were inactivated, but this was not dependent on the amount of new-adhesive. Similar to the agar media results, the topical antimicrobial effect of new-adhesive was confirmed using a porcine skin antimicrobial assay, and the effect was not due to physical blocking based on comparison with the group whose wounds were wrapped.