• The Research Journal of the Costume Culture
• /
• v.16 no.5
• /
• pp.955-962
• /
• 2008

This article is about the naming method for fashion product in cyber shopping mall. For two months, the name of fashion product is listed and analyzed, from BEST 100 category in cyber shopping mall. SPSS ver.10.0 is used and frequency, spearman raw test and t-test are done. The fashion product names are arranged in naming method. There are four kinds of methods for fashion product naming; describing, associating, bundling and style numbering. Describing is most used method both cyber shopping mall. Between marketplace cyber shopping mall and merchant, there is significant difference in composition of naming. Bundling naming method is more used in marketplace cyber shopping mall, and describing and style numbering method is used often in merchant. The words which are composed the name of fashion product are divided in a single word and arranged. The words for describing are classified in noun and adjective. Noun is used for depicting textile and construction and adjective is for touch and image. There is no difference for using words between marketplace and merchant.

• Journal of Environmental Health Sciences
• /
• v.46 no.5
• /
• pp.481-494
• /
• 2020

Objectives: No study has been conducted to review characteristics of humidifier disinfectants (HD) products, such as real numbers, levels and types of HD substances contained, or the volume marketed. We aimed to review the characteristics of HD through a literature review. Methods: We collected literature reporting the names, numbers, and ingredients of HD and discussed them with a focus on the number of HD products and the chemicals used as a disinfectant. Results: A total of eight publications has reported the names of HD brands or types of disinfectants from 2011 to 2020. To date, a total of 40 HD products have been used, excluding four products. Eight HD products used polyhexamethylene guanidine phosphate (PHMG) and 14 used a mixture of chloromethylisothiazolinone (CMIT) and methylisothiazolinone (MIT) as disinfectants. Benzalkonium chloride (BKC) and sodium dichloroisocyanurate (NaDCC) were also used as a disinfectant in several HD products. A total of 19 HD products were associated with the development of HD associated lung injury (HDLI). The Oxy Saksak HD product containing PHMG showed the highest number of HD associated health effects. The type of disinfectant from a total of 14 HD products has not been identified. Conclusions: A total of 40 HD products have been marketed in South Korea since 1994. Further studies should be conducted to identify the association of product characteristics, including type of HD ingredients, with health effects.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.18 no.5
• /
• pp.233-240
• /
• 2023

Nutrition information about food is written on the label paper, which is very inconvenient for visually impaired people to recognize. In order to solve the inconvenience of visually impaired people with nutritional information recognition, this paper proposes a product nutrition information guide system for visually impaired people. In the proposed system, user's image data input through UI, and object recognition is carried out through YOLO v5. The proposed system is a system that provides voice guidance on the names and nutrition information of recognized products. This paper constructs a new dataset that augments the 319 classes of canned/late-night snack product image data using rotate matrix techniques, pepper noise, and salt noise techniques. The proposed system compared and analyzed the performance of YOLO v5n, YOLO v5m, and YOLO v5l models through hyperparameter tuning and learned the dataset built with YOLO v5n models. This paper compares and analyzes the performance of the proposed system with that of previous studies.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.11 no.3
• /
• pp.63-70
• /
• 1997

The objective of this study was to investigate the color preference and the recognition of color names among college students. The study revealed the following: 1) The most favorite colors included blue, purple, white and green in that order; and the least favorite colors included achromatic colors, ocher and red in that order. 2) Brown was the favorite color in furniture while red was the disliked color; In colthing, white was preferred while red was disliked; Red was appropriate for accent colors, and bright colors were for product packages. 3) In regards with seasonal image, yellow, blue, brown and white were associated with spring, summer, fall and winter, respectively; Blue represented self-image most. 4) Black, grey, red and green in that order showed the higest recognitions in color names while indigo, crimson, deep carmine and havy blue showed the lowesR ; Color name recognitions showed the order of achomatic, neutial, warm and cool colors.

• Journal of Haehwa Medicine
• /
• v.25 no.1
• /
• pp.155-163
• /
• 2016

Objectives : Since the Korean pronunciation of the Mantidis Oothea is not unified, it is necessary to unify pronunciation of this particular herb. According to ancient herbal literature, genuine Mantidis Oothea has been regarded as the product which is attached to mulberry tree. However, all forms of Mantidis Oothea need to be used as a medicinal ingredient. Methods : The current study explores pronunciations of the herbal medicinal names, Collection, and the herbal processes of the Mantidis Oothea. There are approximately about 30 herbal manuals dealing with the Mantidis Oothea after Shen Nong's herbal manual(神農本草經) was published. Results & Conclusions : 1. Sangbicho, Sangpyeojo, Sangpyeocho, and other names have been used as a name of medicinal ingredient for the Mantidis Oothea. 2. The Other names of medicinal ingredient for the Mantidis Oothea were Sik woo, Danglangja(螳螂子), Danglanglan(螳螂卵), Danglangso(螳螂巢), Danglangwa(螳螂窩), Danglanggag(螳螂殼), etc.. 3. The name of medicinal ingredient for the Mantidis Oothea should not be pronounced as Sangpyoso but Sangpyocho. 4. The name of medicinal ingredient for the Mantidis Oothea was originated from a type of the egg case, eating habit, therapy of the Mantidis Oothea and so on. 5. Collecting real thing of The Mantidis Oothea does not really matter whether it is attached to the mulberry tree or not. 6. The herbal processes of the Mantidis Oothea is to kill the eggs, so typical methods were to steam, roast, boil with vinegar and so on. In addition, the main effect seemed to be protection from the diarrhea.

• Fire Science and Engineering
• /
• v.28 no.2
• /
• pp.91-97
• /
• 2014

New types of fire accidents appear or the existing types disappeared because of rapidly changing society. We proposed a methodology of extracting new nouns from fire investigation data each of which is an accident report producted by fire investigators. The new nouns could be used in modifying the existing categories for classifying fire accidents. We analysed morphology of the product names and the ignition summaries using the proposed method for the fire accidents classified as the etc sub-category of the category of equipments involved in ignition. In this paper, we found "dryer" as a new sub-category of the agricultural equipment category and "boiler" in the seasonal appliance category from the product names of the fire accidents. We also extracted the new input keywords of "aquarium" and "monitor" in the commercial facilities category and the video, audio apparatus category from the ignition summaries respectively. Using the four subcategories, we reclassified 548 (14.39%) of 3,808 fire accidents assigned to the etc sub-category.

• Journal of Korean society of Dental Hygiene
• /
• v.21 no.3
• /
• pp.203-209
• /
• 2021

The purpose of this study was to investigate the status of exaggerated advertisements in the Korean oral hygiene product market and to urge dental hygienists to play the role of experts. The exaggerated advertisements on the largest online shopping platform in Korea were investigated. Searches were performed with keywords related to oral hygiene, such as "bad breath" and "tartar", and product names of 1,000 products listed at the top were investigated to select the suspicious ones. The situation was found to be grave; for example, a mouthwash capable of preventing coronavirus disease, which lacks scientific evidence, and a self-tartar remover that did not guarantee safety or performance were being sold. Strict government supervision is required, and dental hygienists must be urged to play an active role as oral health experts.

• International conference on construction engineering and project management
• /
• 2005.10a
• /
• pp.1083-1088
• /
• 2005

Current brand strategies applied for name brand apartments seem to have no product differentiation but merely function as a convenient instrument for product image change through naming only. Since proliferating brand names don't have much relevance to their brand concepts at present, long-range brand strategies are definitely needed. We'll inquire, first, the success and failure cases in the brand strategies of other industry. Next, through questionnaire survey, we'll look into the brand concepts of construction firms and their customer satisfaction. Finally we'll present the necessity of indigenous brand culture by use of macroscopic contents development.

• Journal of the Korean Society of Costume
• /
• v.51 no.4
• /
• pp.31-42
• /
• 2001

The purpose of this study was to develop a large representative data base for character goods marketing strategy. The study was to determine character name awareness in relation to segmented distribution regions and such demographic variables as sex and age. The author also analyzed preferred design. A total of 360 questionnaires were distributed and 359 reliable ones were used for statistical analysis. A SAS statistical package including frequency tables and Chi square test and factor analysis and Kendall′s relation analyses was used. The results are as follow : character name awareness involves "character name decognition" based on asking subjects to identify character names from 50 given names. "Tele-tubbies" was found to be a dominant commercial character name as a result of the recognition test, and "Sailer-moon" was found to be a dominant animation character goods as a result of the recognition test. Character recognition was significantly different in the segmented distribution legions, three age groups and different sex groups. People considered design first in purchasing any character goods, and they considered color second in purchasing them. The most favored part of garment far character to be stitch to was the center front in the T-shirt/dress shirt, the center back in the Jumper/jacket, back pocket in the trousers/skirt. The results of a Chi-square test showed that preferred part in the trousers/skirt of character was related with age variables.

• Journal of Intelligence and Information Systems
• /
• v.26 no.1
• /
• pp.1-21
• /
• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.