• The Journal of the Korea Contents Association
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• v.22 no.9
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• pp.1-18
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• 2022

This study critically analyzed the user experience (UX) of mobile applications, focusing on the advertising platforms of mobile applications for culture and arts content. This study aims to examine the direction for growth of the related mobile applications and propose alternative approaches to improve usability. In this study, a mobile app named 'Moviepre' was selected, and a heuristic evaluation was performed for in-depth exploration. For the selected case, the UX Honeycomb model was reconstructed to analyze useful, usable, desirable, findable, accessible, and credible elements of the case. First, since the users' preference for the price factor did not show a significant correlation with the usefulness of the content and the interface, it is necessary to make sure that the mobile application has unique values to gain a competitive advantage in the market. Second, by adopting customer path stages for analysis, the result indicated that users continuously interact with the service from the first moment they are aware of the mobile application. Third, if the user feels uncomfortable, it is likely that these factors hinder the establishment of a long-term relationship between the users and the mobile application. Finally, brand identity should be clearly established, and brand image strategy needs to be developed to satisfy users' expectations that high-quality culture and arts content will be available through the mobile application.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.95-117
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• 2022

With the emergence of various media types due to the development of Internet technology, advertisers have difficulty choosing media suitable for corporate advertising strategies. There are challenging to effectively reflect consumer contextual information when advertising media is selected based on traditional marketing strategies. Thus, a recommender system is needed to analyze consumers' past data and provide advertisers with personalized media based on the information consumers needs. Since the traditional recommender system provides recommendation services based on quantitative preference information, there is difficult to reflect various contextual information. This study proposes a methodology that uses deep learning to recommend personalized media to advertisers using consumer contextual information such as consumers' media viewing time, residence area, age, and gender. This study builds a recommender system using media & consumer research data provided by the Korea Broadcasting Advertising Promotion Corporation. Additionally, we evaluate the recommendation performance compared with several benchmark models. As a result of the experiment, we confirmed that the recommendation model reflecting the consumer's contextual information showed higher accuracy than the benchmark model. We expect to contribute to helping advertisers make effective decisions when selecting customized media based on various contextual information of consumers.

• Journal of Life Science
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• v.32 no.9
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• pp.667-677
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• 2022

Dolsan mustard seeds (DMS) were added in whole, crushed, and roasted form at 0.5 g (S-1), 1.0 g (S-2), and 1.5 g (S-3), respectively to broth and heated for 10 or 15 min. After cooling, the quality characteristics were measured. Salinity and pH decreased with boiling time. The antioxidant activities of the experimental broth were measured in terms of total polyphenol content, total flavonoid content, electron donating ability (EDA), 2,2-azino-bis (3-ethyl-benzothizoline-6-sulfonic acid) (ABTS) radical scavenging activity, and ferric reducing antioxidant power (FRAP). The overall, antioxidant activity was higher in broths containing 1.0 g and 1.5 g DMS than in those containing 0.5 g DMS and the activity increased with increasing boiling time. Sinigrin was not detected in the control group, and no significant difference in sinigrin content was noted among broths containing different concentrations of DMS. A high glutamic acid content was detected in the control broth, whereas glutamic acid, aspartic acid, glycine, proline, alanine, and arginine were detected in the broths containing DMS. The free amino acid contents, particularly aspartic acid and glutamic acid contents, were high in umami. Volatile components, such as 2-propenyl-isothiocyanate (ITC), allylthiocyanate, n-butyl ITC, and 3-butenyl ITC, were detected in the DMS-containing broths. Sensory evaluation revealed that a higher amount of DMS added and a longer heating time increased the overall taste preference, and the difference was statistically significant. The purpose of this study was to present basic data on the quality characteristics of DMS-added broths to aid in the development of new products using DMS.

• Journal of Korean society of Dental Hygiene
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• v.22 no.5
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• pp.323-332
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• 2022

Objectives: This study aims to confirm the educational necessity and utilization of VR media. And it was conducted to prepare basic data necessary for the use of VR in various dental hygiene education in the future and the development of innovative practical training courses. Methods: Before and after using VR in oral radiology practice classes, learning interest (4 items), learning commitment (9 items), learning motivation (5 items), educational media preference (4 items), and satisfaction (10 items) were investigated and analyzed. Friedman two way ANOVA by ran a nonparametric analysis corresponding to repeated measures ANOVA was performed. The statistical significance level was 0.05. Results: It was found that there were statistically significant differences in learning interest, learning immersion, and learning motivation according to the type of oral radiology practice education medium (p<0.05). Conclusions: VR is expected that the use of learning media using VR will lead to students' interest, immersion, and learning motivation in class, and that positive learning effects on VR education media can be sufficiently obtained.

• Knowledge Management Research
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• v.23 no.2
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• pp.277-299
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• 2022

The massive card transaction data generated in the tourism industry has become an important resource that implies tourist consumption behaviors and patterns. Based on the transaction data, developing a smart service system becomes one of major goals in both tourism businesses and knowledge management system developer communities. However, the lack of rating scores, which is the basis of traditional recommendation techniques, makes it hard for system designers to evaluate a learning process. In addition, other auxiliary factors such as temporal, spatial, and demographic information are needed to increase the performance of a recommendation system; but, gathering those are not easy in the card transaction context. In this paper, we introduce CTDDTR, a novel approach using card transaction data to recommend tourism services. It consists of two main components: i) Temporal preference Embedding (TE) represents tourist groups and services into vectors through Doc2Vec. And ii) Deep tourism Recommendation (DR) integrates the vectors and the auxiliary factors from a tourism RDF (resource description framework) through MLP (multi-layer perceptron) to provide services to tourist groups. In addition, we adopt RFM analysis from the field of knowledge management to generate explicit feedback (i.e., rating scores) used in the DR part. To evaluate CTDDTR, the card transactions data that happened over eight years on Jeju island is used. Experimental results demonstrate that the proposed method is more positive in effectiveness and efficacies.

• Journal of Ginseng Culture
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• v.5
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• pp.97-114
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• 2023

Despite numerous studies, research on ginseng in aspect of an economic and business perspective are insufficient. Recently, research to reveal the economic cause of ginseng products purchase is drawing attention. The purpose of this study is to analyze empirically the factors of ginseng products purchase by international consumers from a microeconomic perspective. Using the survey data, we empirically investigate the determinants of ginseng products purchase by international consumers visiting Korea. We use a multinomial logistic model to find the determinants that influence the purchase of ginseng products. This study finds the followings. First, the economic factor is an important determinant of ginseng products purchase. The average daily expenditure has a greater impact on ginseng products purchase than household income does. Even though the average daily expenditure is high, they tend to buy less ginseng products when they prefer other products. Second, demographically, gender and age are also important determinants of ginseng products purchase. It has been found that elderly male consumers are more likely to buy ginseng products. Third, international consumers for leisure purposes have a higher probability of buying ginseng products than tourism consumers for other purposes do. Finally, destination attributes such as security (safety), ease of use of mobile/Internet, and ease of finding directions are also important factors affecting ginseng products purchase. In addition, it is found that the convenience of using the mobile/Internet, the ease of finding directions, and the convenience of shopping increase the probability of buying ginseng products by international consumers. This study is meaningful in that it explored the determinants of ginseng products purchase by analyzing individual consumers' ginseng products choices.

• Korean Journal of Poultry Science
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• v.50 no.1
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• pp.51-61
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• 2023

This study was designed to evaluate the effects of feral peach (Prunus persica Batsch var. davidiana Max.) sugar extracts (peach extracts) and Gomchwi (Ligularia fischeri) extracts on physicochemical properties of Woorimatdag 1breast marinated with red pepper sauce during cold storage for 18 days. Experimental groups were divided into five groups; CON: marinated breast with basic red pepper sauce, GP15 and GP30: added with 15% and 30% of peach extracts into CON, respectively, GG5 and GG10: added with 5% and 10% of Gomchwi extracts into CON, respectively. Moisture and fat contents of GP30 were lower than those of CON, GG5, and GG10 (P<0.05). Cholesterol content of GP15 was similar to that of CON, while it was lower than the other treatments. GP15 and GP30 showed significantly lower pH than the others. Especially, GP30 showed significantly lower total aerobic bacteria count than other treatment on day 10. During storage, peach and Gomchwi extracts were not significantly effect on meat shear force. Overall acceptability of GP15 was higher than that of GG10 at day 10 and 15 (P<0.05). These results indicated that the treatment of peach extracts has a tendency to improve the storage stability maintaining the sensory preference of marinated Woorimatdag 1 breast compared to Gomchwi extracts. Further study would be needed to identify the specific flavor-enhancing factors of GP treatments.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.56 no.2
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• pp.204-211
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• 2023

This study investigated the physicochemical properties and palatability-enhancing effects of the alcohol precipitate, in the enzymatic extracts of Sargassum confusum C. Agardh (SC), obsained using the crude enzyme of Shewanella oneidensis PKA 1008. We analyzed the oligosaccharides recovered from the alcohol precipitate using a thin-layer chromatography for SC-degrading extracts, pH, color, reducing sugar, and viscosity. Thin-layer chromatography showed that after treating with the crude enzyme for 60 h, the polysaccharides were degraded into tetramers, dimers, and trimers and pH increased in the alcohol precipitate (EtOH Sedi). In terms of color, the redness and yellowness of alcohol precipitate/supernatant (EtOH Sedi+Super) and the brightness of EtOH Sedi were the highest among enzyme treated for 0 h and 60 h, EtOH Sedi, and EtOH Sedi+Super. In the reducing sugar analysis, EtOH Sedi showed the lowest value of 13.63 ㎍/mL, and the lowest viscosity of 1.13. In terms of the sensory evaluation, EtOH Sedi+Super showed the highest value with respect to the overall preference. These results suggest that the crude enzyme of S. oneidensis PKA 1008 is effective at degrading polysaccharides, and its recovery increases the palatability of the alcohol precipitate.

• Korean Journal of Ecology and Environment
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• v.55 no.2
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• pp.145-155
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• 2022

Koreoleptoxis nodifila (Martens, 1886) is an endangered species only living in the central and north streams of South Korea. However, there is a lack of information on physical habitat characteristics of K. nodifila. We aimed to determine preference ranges for water depth, current velocity, streambed substrate of K. nodifila. The weibull model was used to estimate the habitat suitability based on distribution of individual abundance by physical factors. Optimal depth preferences ranged from 0.53~17.17 cm, current preferences ranged from 48.40~81.03 cm s^-1 and substrate (𝜱_m) preferences ranged from -4.36~ -2.26. Median values of central tendency were determined as follows: water depth 16.73 cm, current velocity 65.23 cm s^-1, substrate -3.51. Mean values of central tendency were determined as follows: water depth 21.32 cm, current velocity 65.65 cm s^-1, substrate -3.63. Mode values of central tendency were determined as follows: water depth 5.17 cm, current velocity 64.77 cm s^-1, substrate -3.24. Based on the habitat suitability analysis, the microhabitat types of K. nodifila were determined as riffle and coarse-grained streambed.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.41-63
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• 2023

As the online e-commerce market growing, the need for a recommender system that can provide suitable products or services to customer is emerging. Recently, many studies using the sentiment score of online review have been proposed to improve the limitations of study on recommender systems that utilize only quantitative information. However, this methodology has limitation in extracting specific preference information related to customer within online reviews, making it difficult to improve recommendation performance. To address the limitation of previous studies, this study proposes a novel recommendation methodology that applies deep learning technique and uses various linguistic factors within online reviews to elaborately learn customer preferences. First, the interaction was learned nonlinearly using deep learning technique for the purpose to extract complex interactions between customer and product. And to effectively utilize online review, cognitive contents, affective contents, and linguistic style matching that have an important influence on customer's purchasing decisions among linguistic factors were used. To verify the proposed methodology, an experiment was conducted using online review data in Amazon.com, and the experimental results confirmed the superiority of the proposed model. This study contributed to the theoretical and methodological aspects of recommender system study by proposing a methodology that effectively utilizes characteristics of customer's preferences in online reviews.