• Smart Media Journal
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• v.10 no.4
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• pp.54-62
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• 2021

As the volume of online e-commerce transactions increases, items diversify and the classification becomes complicated. E-commerce platforms that specialize in dealing only in one area are emerging, and the area is diversifying. Three problems were identified by researching the craft online e-commerce platform, one of the various types of professional e-commerce platforms. First of all, although craft materials are diversified and complex on the platform, the existing craft e-commerce system is fragmented in structure to categorize complex crafts, making it difficult to accurately present search results that meet various criteria. Second, although appearance is the main reason for purchasing artifacts, it is rare for users to categorize them according to appearance, so they have to judge and filter each work directly. Finally, the language entered when searching for artifacts by non-technical experts is not reflected in the language used to categorize artifacts in the taxonomic system, so the language used for searching is highly accurate. Therefore, the purpose of this study is to add and consider complex attributes in the field of technology to meet the search criteria. Properties to be added must include the main appearance in the search for artifacts. In addition, the government aims to develop a taxonomic system that can reflect non-experts' search languages in the search of works through artificial intelligence natural language processing technology.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.3
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• pp.166-178
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• 2023

This study aims to introduce and assess CNN Deep Learning methods to analyze visual landscape images on social media with embedded user perceptions and experiences. This study analyzed visual landscape images by focusing on a healing place. For the study, seven adjectives related to healing were selected through text mining and consideration of previous studies. Subsequently, 50 evaluators were recruited to build a Deep Learning image. Evaluators were asked to collect three images most suitable for 'healing', 'healing landscape', and 'healing place' on portal sites. The collected images were refined and a data augmentation process was applied to build a CNN model. After that, 15,097 images of 'healing' and 'healing landscape' on portal sites were collected and classified to analyze the visual landscape of a healing place. As a result of the study, 'quiet' was the highest in the category except 'other' and 'indoor' with 2,093 (22%), followed by 'open', 'joyful', 'comfortable', 'clean', 'natural', and 'beautiful'. It was found through research that CNN Deep Learning is an analysis method that can derive results from visual landscape image analysis. It also suggested that it is one way to supplement the existing visual landscape analysis method, and suggests in-depth and diverse visual landscape analysis in the future by establishing a landscape image learning dataset.

• Smart Media Journal
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• v.13 no.3
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• pp.9-17
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• 2024

Due to the recent pandemic and the development of ICT technology, the use of non-face-to-face and unmanned systems is expanding, and it is very important to understand emotions in communication in non-face-to-face situations. As emotion recognition methods for various facial expressions are required to understand emotions, artificial intelligence-based research is being conducted to improve facial expression emotion recognition in image data. However, existing research on facial expression emotion recognition requires high computing power and a lot of learning time because it utilizes a large amount of data to improve accuracy. To improve these limitations, this paper proposes a method of recognizing facial expressions using age and gender, which are image meta information, as a method of recognizing facial expressions with even a small amount of data. For facial expression emotion recognition, a face was detected using the Yolo Face model from the original image data, and age and gender were classified through the VGG model based on image meta information, and then seven emotions were recognized using the EfficientNet model. The accuracy of the proposed data classification learning model was higher as a result of comparing the meta-information-based data classification model with the model trained with all data.

• Journal of Internet Computing and Services
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• v.25 no.2
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• pp.79-92
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• 2024

ChatGPT, as a representative chatbot leveraging generative artificial intelligence technology, is used valuable not only in scientific and technological domains but also across diverse sectors such as society, economy, industry, and culture. This study conducts an explorative analysis of user sentiments and needs for ChatGPT by examining global social media discourse on Reddit. We collected 10,796 comments on Reddit from December 2022 to August 2023 and then employed keyword analysis, sentiment analysis, and need-mining-based topic modeling to derive insights. The analysis reveals several key findings. The most frequently mentioned term in ChatGPT-related comments is "time," indicative of users' emphasis on prompt responses, time efficiency, and enhanced productivity. Users express sentiments of trust and anticipation in ChatGPT, yet simultaneously articulate concerns and frustrations regarding its societal impact, including fears and anger. In addition, the topic modeling analysis identifies 14 topics, shedding light on potential user needs. Notably, users exhibit a keen interest in the educational applications of ChatGPT and its societal implications. Moreover, our investigation uncovers various user-driven topics related to ChatGPT, encompassing language models, jobs, information retrieval, healthcare applications, services, gaming, regulations, energy, and ethical concerns. In conclusion, this analysis provides insights into user perspectives, emphasizing the significance of understanding and addressing user needs. The identified application directions offer valuable guidance for enhancing existing products and services or planning the development of new service platforms.

• Informatization Policy
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• v.31 no.1
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• pp.3-31
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• 2024

This study aimed to examine public concerns in South Korea considering the country's unique context, triggered by the advent of generative artificial intelligence such as ChatGPT. To achieve this, comments from 102 YouTube video news related to ethical issues were collected using a Python scraper, and morphological analysis and preprocessing were carried out using Textom on 15,735 comments. These comments were then analyzed using a Correlated Topic Model (CTM). The analysis identified six primary topics within the comments: "Legal and Ethical Considerations"; "Intellectual Property and Technology"; "Technological Advancement and the Future of Humanity"; "Potential of AI in Information Processing"; "Emotional Intelligence and Ethical Regulations in AI"; and "Human Imitation."Structuring these topics based on a correlation coefficient value of over 10% revealed 3 main categories: "Legal and Ethical Considerations"; "Issues Related to Data Generation by ChatGPT (Intellectual Property and Technology, Potential of AI in Information Processing, and Human Imitation)"; and "Fear for the Future of Humanity (Technological Advancement and the Future of Humanity, Emotional Intelligence, and Ethical Regulations in AI)."The study confirmed the coexistence of various concerns along with the growing interest in generative AI like ChatGPT, including worries specific to the historical and social context of South Korea. These findings suggest the need for national-level efforts to ensure data fairness.

• The Korean Journal of Mycology
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• v.26 no.2 s.85
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• pp.265-274
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• 1998

This study was carried out to obtain the basic data for an artificial cultivation of Phellinus sp.. The optimum conditions for the mycelial growth on the different sawdusts (Quercus aliena, Morns alba and Alnus japonica) substrate of an isolated Phellinus sp. were optimized by response surface methodology. The ratio of rice bran addition to sawdust and the suitable moisture content for the mycelial growth in the all sawdust media were about 30% (w/w) and $65{\sim}70%$ (w/v), respectively. The initial pHs for the mycelial growth of Quercus aliena and Morns alba were in the range of $pH\;5{\sim}6$, whereas Alnus japonica was obtained at pH 6. The optimum temperature for the mycelial growth was about $25{\sim}30^{\circ}C$, depending on the different kinds of wood substrates. From the response surface analysis, the values of independent variables of Quercus aliena at stationary points were determined to be 31.01 % (w/w) of rice bran, pH of 5.31 and 69.03% (w/v) of moisture content, and the expected value of mycelial growth was about 8.32 cm. Both the ratio of rice bran addition to sawdust $(X_1)$ and moisture content $(X_3)$ were effective to the mycelial growth. In the case of Morns alba, the ratio of rice bran addition to sawdust, initial pH and moisture content at the stationary points were 28.77% (w/w), 5.28 and 69.8 (w/v),respectively, and the expected mycelial growth of 7.60 cm was obtained. Stationary points for the mycelial growth in the sawdust media of Alnus japonica were 28.74% (w/w) of rice bran, pH of 6. 04 and 66.96% (w/v) of moisture content, and the expected values of mycelial growth was about 5.38 cm. Based on the above results, there was correlations between the mycelial growth and independent variables, and the effect of rice bran $(X_1)$ and initial pH $(X_2)$ for the mycelial growth were higher than the moisture content $(X_3)$. The optimum species of sawdust media for the my celial growth of Phellinus sp. was in the order of Quercus aliena > Morns alba > Alnus japonica.

• The Korean Journal of Mycology
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• v.46 no.3
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• pp.281-294
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• 2018

Molecular analysis using the internal transcribed spacer region sequences revealed that the strains used in this study, which were formerly identified as Panellus serotinus, are Panellus edullis. After Universal Fungal PCR Fingerprinting (UFPF) analysis, eight strains of P. edulis were divided into two groups. We conducted fundamental research on mycelial growth and sawdust cultivation to understand the cultural characteristics of eight wild P. edulis strains collected from Korean forests. All strains showed faster and denser mycelial growth on potato dextrose agar (PDA) than on other media (malt extract agar, Sabouraud dextrose agar). Optimal conditions for mycelial growth were: $20^{\circ}C$ on PDA, $25^{\circ}C$ on potato dextrose broth (PDB), and pH 5~8 on PDB at $25^{\circ}C$. Two strains (NIFoS 2407, 3993) were selected as excellent strains based on mycelial growth and density on PDA. NIFoS 2792 showed high cellulase activities on carboxymethyl cellulose (CMC) agar, and NIFoS 2387 and 2804 exhibited high laccase activities on ABTS-containing agar media. The mycelial growth of P. edulis was the fastest on Quercus acutissima and Q. mongolica sawdust media, and mycelial density was the highest on Quercus spp. sawdust-containing media. Sawdust cultivation of P. edulis was successful. The conditions were 80~85 days of cultivation period after spawn inoculation, 10~11 days for primordial formation at $17{\sim}18^{\circ}C$, and 15~20 days for fruiting growth. NIFoS 2804 and 3993 were selected as good strains in terms of cultivation period and mushroom production. These results could be useful for the artificial cultivation of P. edulis.

• Applied Chemistry for Engineering
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• v.21 no.6
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• pp.659-663
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• 2010

Microalgae has been seen all over the seawater and several species are used for human food. Specially, Nannochloropsis oculata, a photosynthetic microalgae, has been focused for a vast array of valuable nutritious compounds. In order to find high mass Nannochloropsis oculata culture conditions, some of important growth factors of pH, temperature, culture media, and $CO_2$ effect were tested. The optimal growth condition was found to be as follows : 3% artificial seawater, initial pH 8.5, and temperature $25^{\circ}C$. The alga mass and chlorophyll content were dramatically increased by applying 5% flue $CO_2$ gas (1.50 g/L algae in a continuous $CO_2$ flue; 0.76 g/L alga without $CO_2$). It was shown that the chlorophyll biosynthesis was also closely associated with alga growth.

• Journal of the Korean Home Economics Association
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• v.50 no.7
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• pp.67-79
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• 2012

This study analyzed the characteristics of morphing in fashion design through the documentaries on morphing and fashion. The characteristics of morphing in fine art, media, and design area were categorized as reversible metamorphosis, sequential dissolve and blurring of interpolation boundaries. The results were as follow in fashion design. Reversible metamorphosis showed an automatic silhouette transformation by remote control, the metamorphosis of folding method by wearer's own movements and the automatic silhouette transformation by the air pressurizing method. It represented the thoughts of omnipotence as in the feeling of the magical world, the human desire for control in life, the rationalization of magical thinking and imaginative power, the creation of a new dress space and the extension of dress function. Sequential dissolve showed juxtaposition in the same area by the time order, juxtaposition in virtual space through the computer graphics, the series of fashion photography by steel cut of the dress making process and the blending of digital film and fashion design. It represented the approach for the storytelling of fashion show, implication of creative fashion design process and the creation of organic forms and the feeling of fantasy through artificial technology. The blurring of interpolation boundary showed an overlay of different fabrics with transparent boundaries, an overlay of different patterns with transparent boundaries and the blending of fabrics through the visual mixing of color. It represented the obfuscation of the object, the connotation of the space order, the connotation of the extensive and various meanings and the integrative property of objects.

• Korean Journal of Agricultural Science
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• v.15 no.1
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• pp.76-81
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• 1988

This study was done to find out the antifungal activity of two antibacterial antibiotics, Chlorampenicol and Streptomycin sulfate, against Phytophthora n. var. Parasitica, the causal agent of Phytophthora blight of sesame, growing on artificial media. On PDA medium, Chlorampenicol at 10 ppm, Streptomycin sulfate at 25ppm highly inhibited mycerial growth and completely inhibited zoosporangial formation of Phytophthora n. var. parasitica, and Chlorampenicol at 5 ppm, Streptomycin sulfate at 10 ppm slightly inhibited the mycerial growth and zoosporangial formation of the fungus. These antibiotics showed considerably increased inhibitory effect on the fungal growth when they were mixed with other chemical. Protein content in myceria of the fungus was decreased and abnormal growth of mycerial apex was observed by treatment of these antibiotics. Phytotoxicity on sesame seedlings was not observed by application of them.