• Journal of the Korean Applied Science and Technology
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• v.40 no.6
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• pp.1547-1556
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• 2023

This study was conducted to check the anti-bacterial ability against Malassezia furfur by mixing Szygium aromaticum and Coptis japonica extracts and to evaluate the antioxidant and anti-inflammatory ability by creating an optimal mixture. Szygium aromaticum and Coptis japonica were extracted with 70% ethanol, 100% methanol, and water to evaluate the antibacterial ability, and it was confirmed that 100% methanol extract of Szygium aromaticum and Coptis japonica water extract had the highest anti-bacterial ability. In addition, when the two extracts were mixed and the anti-bacterial ability was evaluated by ratio, the ratio of 9:1 showed the best activity, and it was confirmed that the antioxidant activity of the mixture was excellent. In Raw 264.7 cells, LPS was used to induce inflammatory responses and confirmed anti-inflammatory activity at 1, 10, 50, and 100 ㎍/mL that did not affect survival, and it was confirmed that NO-production inhibition and IL-6 expression inhibition and COX2 and iNOS protein expression inhibition activity were excellent at 10, 50, and 100 ㎍/mL. Through this study, it is thought that the mixture of Szygium aromaticum100% methanol extract and Coptis japonica water extract can be used as a natural ingredient in functional cosmetics because of its excellent antibacterial and anti-inflammatory effects.

• Journal of Digital Convergence
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• v.16 no.11
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• pp.477-485
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• 2018

Beyond the mid-2010s, there has been increasing cases of using 'Reminiscence' as a trigger for recalling 'Past' in pre-production process of creative contents. In previous researches on this phenomenon, it has been recognized that retro, recall, compassion, and memory are similar. In order to look closely to grasp the psychological tendency of the contents user in detail, the study about 'Reminiscence' was conducted. The researcher analyzed 'Reminiscence' as a process of restructuration based on the experience and desire of the person individual which were derived from the past and further analyzed it as a lack of desire due to the time can never return. The study hopefully can make a balance against the cutting edge content distribution technology biased production tendency.

• Journal of Convergence for Information Technology
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• v.11 no.12
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• pp.236-243
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• 2021

The aim of this study was to evaluate the anti-oxidant and anti-wrinkle effect of the black carrot(BC) extracted by supercritical dioxide(SC-CO₂). DPPH/ABTS radical scavenging and total polyphenol contents were measured to investigate the anti-oxidant activity of the BC supercritical extract. Collagen production and MMP-1 expression were assessed in normal human dermal fibroblasts(NHDF) for anti-wrinkle activity, The black carrot extract showed the highest total phenolic content(9.037±1.123 mg GAE/g extract) and the best antioxidant properties as shown by DPPH and ABTS assay. The supercritical fluid extracts of black carrot exhibited low toxicity to NHDF cells. In addition, the supercritical fluid extracts showed MMP-1 inhibition and type I pro-collagen synthesis inducing activities in a dose-dependent manner, respectively. Therefore, these results suggest that the black carrot is a potential source of high anti-oxidative, solvent-free and anti-aging material with promising applications in cosmetic, food, and beauty-food industries.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.50 no.2
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• pp.103-110
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• 2024

Lipid nanoparticles (LNPs) are a stable and an effective system that protects cell-impermeable biologically active compounds such as nucleic acids, proteins, and peptides against degradation caused by subtle environmental changes. This study focuses on developing LNPs encapsulating gallic acid (GA), an antioxidant, to effectively prolong the half-life of tetrahexyldecyl ascorbate (THDC), a oil-soluble vitamin C derivative. These LNPs were synthesized in small, uniform sizes at room temperature and pressure conditions using a microfluidics chip. Compared to liposomes manufactured under high pressure and high temperature conditions through conventional microfluidizers, LNPs manufactured through microfluidics chips had excellent dispersion and temperature stability, and improved skin absorption as well as improved oxidative stability of fat-soluble vitamin C derivatives. Future studies will focus on ex vivo and in vivo evaluations to study skin improvement to further validate these results.

• 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 Korea Society of Computer and Information
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• v.27 no.9
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• pp.191-203
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• 2022

In this paper, we developed a system that intelligently identifies skin image data from big data collected from social media Instagram and extracts standardized skin sample data for skin condition diagnosis and management. The system proposed in this paper consists of big data collection and analysis stage, skin image analysis stage, training data preparation stage, artificial neural network training stage, and skin image identification stage. In the big data collection and analysis stage, big data is collected from Instagram and image information for skin condition diagnosis and management is stored as an analysis result. In the skin image analysis stage, the evaluation and analysis results of the skin image are obtained using a traditional image processing technique. In the training data preparation stage, the training data were prepared by extracting the skin sample data from the skin image analysis result. And in the artificial neural network training stage, an artificial neural network AnnSampleSkin that intelligently predicts the skin image type using this training data was built up, and the model was completed through training. In the skin image identification step, skin samples are extracted from images collected from social media, and the image type prediction results of the trained artificial neural network AnnSampleSkin are integrated to intelligently identify the final skin image type. The skin image identification method proposed in this paper shows explain high skin image identification accuracy of about 92% or more, and can provide standardized skin sample image big data. The extracted skin sample set is expected to be used as standardized skin image data that is very efficient and useful for diagnosing and managing skin conditions.