• Journal of The Geomorphological Association of Korea
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• v.24 no.3
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• pp.27-45
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• 2017

At the upper part of terrace deposits at Jeongdongjin area, there is a structure in which reddish brown and grayish white layers laying horizontally. Previous studies have reported the existence of these structures within the deposits and suggested the theoretical background related to the formation process. However, the analysis of physical properties and chemical composition such as particle size, classification, etc. of the materials constituting the reddish brown and grayish white layers is scarcely done. In this study, the physico - chemical properties of gray - white and reddish brown beds are investigated. The mean grain size of the particles was less than $4{\varphi}$ in both layers and the reddish brown layer was more coarse. The results shows that the sorting of the grayish white layer is better. The chemical composition of both layers shows that the average concentration of $SiO_2$, $Al_2O_3$ and $K_2O$ of the grayish white layer was higher than those of the reddish brown layer. The concentration of $Fe_2O_3$ of reddish brown lyaer was 3 times higher than those of the grayish white layer. The degree of chemical weathering (CIA) is 90 or so in both the reddish brown and grayish white layers, indicating a significant level of chemical weathering. In conclusion, reddish brown layers had been formed by the processes related to the migration of iron and the migration of water that induced aggregation after the formation of sediments (psudo-gleization). In this study area, a vertical layer of grayish white which cuts off horizontal reddish brown and grayish white color was found. The vertical layer or wedge similar to a ice-wedge or columnar structure that in a cold environment, and there is a difference in shape and size. The vertical layer appears to have occurred three or more cycles. The vertical layers begin to form at a certain height within the outcrop and descend downwards, which of course is difficult to see as directing certain times.

• Fashion & Textile Research Journal
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• v.23 no.2
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• pp.273-289
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• 2021

This study aimed to examine the appearance of heated clothing in relation to fashion trends by analyzing constructive components of clothing using product images and actual products. A total of 91 images of domestic and foreign heated clothing products were collected, and a product analysis conducted with six parameters of item classification, namely, concept and image, silhouette, color, number of heating elements, and heating parts. In addition, an in-depth analysis was carried out with 11 products among them, while focusing on further detailed components of the design and heating system. As a result, the overall exterior design of domestic products has been changed from outdoor clothing to daily clothing reflecting the current design trend. Compared with domestic products, foreign products showed a diverse assortment and a greater number of heating regions per individual item of clothing. The current heating system commonly consists of a heating element, power source, controller board, and wires, although the existence and type of switches differed from product to product. To develop a more efficiently heated clothing to expand the market, the design, ease of use, safety, consumer preference, heating functionality, and durability should be considered. Along with design recommendations for future heated clothing, this study also provides a practical guide to the technical aspects of the design of the components of heated clothing.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.230-240
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• 2022

Sharing of online videos via internet is an emerging and important concept in different types of applications like surveillance and video mobile search in different web related applications. So there is need to manage personalized web video retrieval system necessary to explore relevant videos and it helps to peoples who are searching for efficient video relates to specific big data content. To evaluate this process, attributes/features with reduction of dimensionality are computed from videos to explore discriminative aspects of scene in video based on shape, histogram, and texture, annotation of object, co-ordination, color and contour data. Dimensionality reduction is mainly depends on extraction of feature and selection of feature in multi labeled data retrieval from multimedia related data. Many of the researchers are implemented different techniques/approaches to reduce dimensionality based on visual features of video data. But all the techniques have disadvantages and advantages in reduction of dimensionality with advanced features in video retrieval. In this research, we present a Novel Intent based Dimension Reduction Semi-Supervised Learning Approach (NIDRSLA) that examine the reduction of dimensionality with explore exact and fast video retrieval based on different visual features. For dimensionality reduction, NIDRSLA learns the matrix of projection by increasing the dependence between enlarged data and projected space features. Proposed approach also addressed the aforementioned issue (i.e. Segmentation of video with frame selection using low level features and high level features) with efficient object annotation for video representation. Experiments performed on synthetic data set, it demonstrate the efficiency of proposed approach with traditional state-of-the-art video retrieval methodologies.

• Journal of Korea Multimedia Society
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• v.25 no.8
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• pp.1167-1174
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• 2022

With the sustainable development and transformation of the city, public art as a business card of the famous city of culture has become a hot topic of research. The intervention of public art in public space not only brings users a sense of space experience, but also becomes a unique carrier of urban and rural image making. Although there is much research on the classification, aesthetics and function of public art, there is few quantitative research on user satisfaction. This paper takes the basic features of airport public art as a research object and the basic features of airport public art as the theoretical basis to study the impact of the basic characteristics of airport public art on user satisfaction. Research methods were based on questionnaire data of 247 people, in which models and hypotheses were tested using SPSS 21.0 software, based on the induction and extraction of nine influential factors in the basic characteristics of public art. The study found that public interpretation, media patterns, color perception, modeling form, place perception, city image and memory have significant positive effects on user satisfaction. The sharedness of public art, cognition and communication in public culture and spatial relations do not affect satisfaction. Conclusion, inspiration and prospect provide suggestions for designers and reference data and theoretical support for public art evaluation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.3
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• pp.1-8
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• 2022

Recently, Google MedeiaPipe presents a novel approach for neural network-based hair segmentation from a single camera input specifically designed for real-time, mobile application. Though neural network related to hair segmentation is relatively small size, it produces a high-quality hair segmentation mask that is well suited for AR effects such as a realistic hair recoloring. However, it has undesirable segmentation effects according to hair styles or in case of containing noises and holes. In this study, the energy function of the test image is constructed according to the estimated prior distributions of hair location and hair color likelihood function. It is further optimized according to graph cuts algorithm and initial hair region is obtained. Finally, clustering algorithm and image post-processing techniques are applied to the initial hair region so that the final hair region can be segmented precisely. The proposed method is applied to MediaPipe hair segmentation pipeline.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.50.1-50.1
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• 2021

The Gaia mission opens a new window to study the kinematics and dynamics of young stellar systems in detail. The kinematic properties of young stars provide vital constraints on the formation process of their host systems. Here, we present a kinematic study of the two associations Monoceros OB1 (Mon OB1) and R1 (Mon R1). Member candidates are first selected from the published list of member candidates, a compilation of OB star catalogues, and the classification of young stellar objects with the AllWISE data. According to the conventional wisdom, we selected a total of 728 members with similar proper motions at almost the same distance. Mon OB1 and Mon R1 have high levels of substructures that are also kinematically distinct. We identify six stellar groups in these associations, of which five show a pattern of expansion. In addition, the signature of rotation is found in two stellar groups of Mon OB1. Star formation history is inferred from a color-magnitude diagram. As a result, star formation in Mon OB1 has been sustained for several million years, while Mon R1 formed at almost the same epoch as the recent star formation in Mon OB1. Some old members in the outskirt of Mon OB1 have outward motions, which rules out the previously proposed outside-in star formation scenario. Star-forming regions including Mon OB1 and Mon R1 are found along a large arc-like gas structure. Hence, the formation of these two associations may originate from the hierarchical star formation along filaments in a turbulent molecular cloud.

• Animal Bioscience
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• v.36 no.10
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• pp.1465-1487
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• 2023

The purpose of this study was to investigate the recent development of meat analog, industrialization, and the related legal changes worldwide. Summarizing the current status of the industrialization of meat analog, studies on plant-based meat, mycoprotein, and edible insects were mainly conducted to investigate their sensory properties (texture, taste, flavor, and color resembling meat), nutritional and safety evaluations, acquisition method of meat alternatives, and commercialization. Cultured meat is mainly studied for developing muscle satellite cell acquisition and support techniques or materials for the formation of structures. However, these technologies have not reached the level for active industrialization. Even though there are differences in the food categories and labeling between countries, it is common to cause confusion or to relay false information to consumers; therefore, it is important to provide accurate information. In this study, there were some differences in the food classification and food definition (labeling) contents for each country and state depending on the product shape or form, raw materials, and ingredients. Therefore, this study can provide information about the current research available on meat alternatives, improve regulation, and clarify laws related to the meat analog industry, which can potentially grow alongside the livestock industry.

• Journal of Fashion Business
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• v.27 no.3
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• pp.50-62
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• 2023

The e-commerce fashion market has experienced a remarkable growth, leading to an overwhelming availability of shared information and numerous choices for users. In light of this, chatbots have emerged as a promising technological solution to enhance personalized services in this context. This study aimed to develop user-product attributes for a chatbot-based personalized fashion recommendation service using big data text mining techniques. To accomplish this, over one million consumer reviews from Coupang, an e-commerce platform, were collected and analyzed using frequency analyses to identify the upper-level attributes of users and products. Attribute terms were then assigned to each user-product attribute, including user body shape (body proportion, BMI), user needs (functional, expressive, aesthetic), user TPO (time, place, occasion), product design elements (fit, color, material, detail), product size (label, measurement), and product care (laundry, maintenance). The classification of user-product attributes was found to be applicable to the knowledge graph of the Conversational Path Reasoning model. A testing environment was established to evaluate the usefulness of attributes based on real e-commerce users and purchased product information. This study is significant in proposing a new research methodology in the field of Fashion Informatics for constructing the knowledge base of a chatbot based on text mining analysis. The proposed research methodology is expected to enhance fashion technology and improve personalized fashion recommendation service and user experience with a chatbot in the e-commerce market.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.6
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• pp.85-96
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• 2023

This study proposes a method for forest vegetation monitoring using high-resolution aerial imagery captured by unmanned aerial vehicles(UAV) and deep learning technology. The research site was selected in the forested area of Mountain Dogo, Asan City, Chungcheongnam-do, and the target species for monitoring included Pinus densiflora, Quercus mongolica, and Quercus acutissima. To classify vegetation species at the pixel level in UAV imagery based on characteristics such as leaf shape, size, and color, the study employed the semantic segmentation method using the prominent U-net deep learning model. The research results indicated that it was possible to visually distinguish Pinus densiflora Siebold & Zucc, Quercus mongolica Fisch. ex Ledeb, and Quercus acutissima Carruth in 135 aerial images captured by UAV. Out of these, 104 images were used as training data for the deep learning model, while 31 images were used for inference. The optimization of the deep learning model resulted in an overall average pixel accuracy of 92.60, with mIoU at 0.80 and FIoU at 0.82, demonstrating the successful construction of a reliable deep learning model. This study is significant as a pilot case for the application of UAV and deep learning to monitor and manage representative species among climate-vulnerable vegetation, including Pinus densiflora, Quercus mongolica, and Quercus acutissima. It is expected that in the future, UAV and deep learning models can be applied to a variety of vegetation species to better address forest management.

• Korean Journal of Environment and Ecology
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• v.34 no.1
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• pp.1-8
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• 2020

This study conducted a full survey of the goral population using sensor cameras to identify the exact habitat of the gorals that inhabit Odaesan National Park and for restoration and habitat management-focused conservation projects following the population growth. We surveyed Odaesan National Park for a year in 2018 and selected18 grids (2km×2km) first based on the survey results. We then further divided each grid into four small grids (1km×1km) and installed a total of 62 sensor cameras in 38 small girds divided by four grids(1km×1km). The survey resulted in a total of 5,096 photographed wild animals, 2,268 of which were gorals, and the analysis by the classification table of goral (horn shape (Ⓐ), ring pattern (Ⓑ), ring formation ratio (Ⓒ), and facial color (Ⓓ)) identified a total of 95 animals. The ratio of male and female was 35 males (36.8%), 46 females (48.4%), and 14 sex unknowns (14.7%), while the ratio of female and male excluding sex unknowns was 4 (male):6 (female). The horn shape (Ⓐ) and face color (Ⓓ) were the important factors for distinguishing male and female and identifying individuals. The analysis of the correlation of 81 individuals, excluding 14 individuals of unknown sex, showed a significant difference (r=-0.635, p<0.01). Since the goral population in Odaesan National Park has reached a minimum viable population, it is necessary to change the focus of the management policy of Odaesan National Park from restoration to conservation.