• Journal of the Korean Society of Earth Science Education
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• v.14 no.1
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• pp.33-47
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• 2021

This study developed a big data-based STEAM (Science, Technology, Engineering, Art & Mathematics) program using WWT (World Wide Telescope), focusing on content elements of 'solar system', 'star and universe' in the 2015 revised science curriculum, and in order to find out the effectiveness of the STEAM program, analyzed creative problem solving, STEAM attitude, and STEAM satisfaction by applying it to one middle school 176 students simple random sampled. The results of this study are as follows. First, we developed a program to encourage students to actively and voluntarily participating, utilizing the astronomical data platform WWT. Second, in the paired t-test based on the difference between the pre- and post-scores of the creative problem solving measurement test, significant statistical test results were shown in 'idea adaptation', 'imaging', 'analogy', 'idea production' and 'elaboration' sub-factors except 'attention task' sub-factor (p < .05). Third, in the paired t-test based on the difference between the pre- and post-scores of the STEAM attitude test, significant statistical test results were shown in 'interest', 'communication', 'self-concept', 'self-efficacy' and 'science and engineering career choice' sub-factors except 'consideration' and 'usefulness / value recognition' sub-factors (p < .05). Fourth, in the STEAM satisfaction test conducted after class application, the average values of sub-factors were 3.16~3.90. The results indicated that students' understanding and interest in the science subject improved significantly through the big data-based STEAM program using the WWT.

• Korean small business review
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• v.43 no.1
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• pp.165-186
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• 2021

Startups are undergoing a change throughout the growth process of startups that appear in existing studies as they move away from the existing B2B or B2C frame and expand their target customer groups to O2O, C2C. In this regard, a new type of startup known as unicorns, a unicorn which has grown rapidly in a short period of time, is being created by successfully attracting government support and external investment in recognition of the potential value of the startup. This study examined the relationship between investment attraction and growth after founding for five representative unicorns in the U.S. and Korea. As a result, it was found that private investment in Korea is passive and defensive, and is attracted after the Series A stage, compared to the U.S., where the growth potential of the startup ecosystem is positively evaluated. In addition, it found that government's support policy throughout the startup's growth process is an abstract and comprehensive policy focusing on initial funding for startups. Therefore, it was suggested that the scope of government policies should be expanded to forster startups as unicorns, and that it is necessary to establish and implement differentiated support policies for each growth of the scale-up of startups. This study is significant in that it presented the criteria for the growth stage and support of startups as well as policy support for scale-up through practical case analysis of unicorns.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.5
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• pp.157-166
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• 2022

Exercise is necessary for a healthy life, but it is recommended that it be conducted in a non-face-to-face environment in the context of an epidemic such as COVID-19. However, in the existing non-face-to-face exercise content, it is possible to recognize exercise movements, but the process of interpreting and providing feedback information is not automated. Therefore, in this paper, to solve this problem, we propose a method of creating a formalized rule to track the contents of exercise and the motions that constitute it. To make such a rule, first make a rule for the overall exercise content, and then create a tracking rule for the motions that make up the exercise. A motion tracking rule can be created by dividing the motion into steps and defining a key frame pose that divides the steps, and creating a transition rule between states and states represented by the key frame poses. The rules created in this way are premised on the use of posture and motion recognition technology using motion capture equipment, and are used for logical development for automation of application of these technologies. By using the rules proposed in this paper, not only recognizing the motions appearing in the exercise process, but also automating the interpretation of the entire motion process, making it possible to produce more advanced contents such as an artificial intelligence training system. Accordingly, the quality of feedback on the exercise process can be improved.

• Korean Association of Arts Management
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• no.59
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• pp.5-31
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• 2021

The purpose of this study is to analyze social perceptions and discourses about creating arts in the era of artificial intelligence with making an implication of responding to the emergence of artificial intelligence. We conceptually understand the principles and limitations of creating visual arts using artificial intelligence whilst this paper addresses ai art in the social context by borrowing the theoretical lens from the sociology of arts. This article considers 472 newspapers about artificial intelligence art as the main data, which are interpreted through semantic network analysis. The analysis of this research shows that it is a controversial issue regarding who/which creates the artworks between humans and computers. However, judging from the dominant influence of a group of words representing the recognition of intellectual property rights, we have detected that social awareness is formed around the perspective of considering artificial intelligence creates visual arts rather than artists. In addition, based on the close relationship between the cluster and the cluster reflecting institutional support, we confirm that the discourse about artificial intelligence art is limited to technological development and legal system maintenance. Thus, this study suggests the need for defining artificial intelligence as the medium of art and constructing policy discourses on artificial intelligence art as an artistic genre.

• Journal of the Korean Society of Floral Art and Design
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• no.45
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• pp.13-29
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• 2021

Under the recognition that the technological system of traditional flower design in Korea has been passed down from the past to the present, we extracted the type of design form from the flower decoration of the Joseon Dynasty, analyzed the expression technique, and examined the relationship with the modern traditional flower decoration in this study. As a result, most of the flower design works of the Joseon Dynasty mainly expressed one focal point at the central starting point. One central branch line was mainly used, and cut leaves were mainly used as the base material. Similar to the Joseon Dynasty, one central starting point and a base made of leaves are mainly used In modern flower design. In the frequency of use by expression technique, the stem exposure technique was used the most, and cut flowers and cut stems were used at a similar frequency in all techniques. As plant materials, cut flowers and cut stems were mainly used. In addition, non-plant materials such as feathers, fans, and brushes were also used for decoration. In conclusion, it can be seen that traditional flower decorations in Korea were systematically established in the Joseon Dynasty in terms of expression techniques and high-level flower design works were made. In the future, it will be necessary to study the history of our flower designs in more diverse ways and to develop modern flower designs while preserving historical traditions.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.135-155
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• 2022

This study analyzes patent trends by deriving sub-technical fields of Organic Light-Emitting Diodes (OLEDs) industry, and analyzing technology value, originality, and diversity for each sub-technical field. To collect patent data, a set of international patent classification(IPC) codes related to OLED technology was defined, and OLED-related patents applied from 2005 to 2017 were collected using a set of IPC codes. Then, a large number of collected patent documents were classified into 12 major technologies using the Latent Dirichlet Allocation(LDA) topic model and trends for each technology were investigated. Patents related to touch sensor, module, image processing, and circuit driving showed an increasing trend, but virtual reality and user interface recently decreased, and thin film transistor, fingerprint recognition, and optical film showed a continuous trend. To compare the technological value, the number of forward citations, originality, and diversity of patents included in each technology group were investigated. From the results, image processing, user interface(UI) and user experience(UX), module, and adhesive technology with high number of forward citations, originality and diversity showed relatively high technological value. The results provide useful information in the process of establishing a company's technology strategy.

• The Journal of Society for e-Business Studies
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• v.26 no.4
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• pp.95-118
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• 2021

As the AI speaker business has risen significantly in recent years, the potential for numerous uses of AI speakers has gotten a lot of attention. Consumers have created an environment in which they can express and share their experiences with products through various channels, resulting in a large number of reviews that leave consumers with a variety of candid opinions about their experiences, which can be said to be very useful in analyzing consumers' thoughts. Using this review data, this study aimed to examine the factors driving the continued use of AI speakers. Above all, it was determined whether the seven characteristics associated with the intention to adopt AI identified in prior studies appear in consumer reviews. Based on customer review data on Amazon.com, text mining and social network analysis were utilized to examine Amazon eco-products. CONCOR analysis was used to classify words with similar connectivity locations, and Connection centrality analysis was used to classify the factors influencing the continuous use of AI speakers, focusing on the connectivity between words derived by classifying review data into positive and negative reviews. Consumers regarded personality and closeness as the most essential characteristics impacting the continued usage of AI speakers as a result of the favorable review survey. These two parameters had a strong correlation with other variables, and connectedness, in addition to the components established from prior studies, was a significant factor. Furthermore, additional negative review research revealed that recognition failures and compatibility are important problems that deter consumers from utilizing AI speakers. This study will give specific solutions for consumers to continue to utilize Amazon eco products based on the findings of the research.

• Journal of Digital Convergence
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• v.20 no.5
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• pp.401-410
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• 2022

This study deals with the relationship among trust, attachment and brand loyalty of agricultural products' rice co-brands, which are the staple food of the people. The research method established the hypothesis of the study under the foundation of prior research and developed the survey. The subjects of the study were distributed, retrieved, and analyzed the survey of 163 rice farmers in Buyeo-gun, Chungcheongnam-do. The empirical analysis results show that: First, hypothesis 1 of the brand awareness and image that "rice brand assets will be a positive relationship to trust" were statistically adopted. In particular, statistical t values showed a difference in consumer confidence over recognition>images. Second, hypothesis 2 of the trust of agricultural rice brands will be a positive influence on attachment and loyalty' statistically supported. In this regard, brand trust was higher in loyalty than attachment. Third, the attachment of agricultural products to rice brands will be a positive influence on loyalty,' was statistically supported. The strategic implications of this study are as follows. First, consumers should be given clues of trust(ex, GAP of Natioanl Approval Licesing, Fam Tour) as they distrust the perceived quality of the rice in the market. Second, the effect of the origin of rice is questionable, so the spread of the production power system should prevent the mixing of rice varieties, that is the spread of the production history systems.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.33 no.3
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• pp.239-265
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• 2022

The purpose of this study is to examine the status of RDA adoption in Korea and the perception of university librarians on RDA adoption. For this purpose, the adoption status of two libraries that adopted RDA among domestic libraries was analyzed. In addition, interviews were conducted with eight university librarians, and narrative responses related to the adoption of RDA were collected and analyzed. As a result of the interview survey, the research participants recognized that the concept of RDA is very difficult and abstract, there are few implementation cases where RDA is applied, and that it would be very difficult to adopt RDA due to the personnel and budget conditions of the local library. The RDA adoption method recognized by the research participants is to improve RDA awareness, conduct RDA education, prepare guidelines for constructing hybrid bibliographic records when RDA is adopted, operate an RDA pilot institution, and establish a performance model. In addition, research participants need coordination with companies for implementation, prefer to change a specific point in time rather than batch retroactive conversion, discover success stories, establish RDA-related online channels, build and utilize national authority DB, and use the national budget and system support. In this study, based on the research results, a plan to adopt RDA for university libraries in Korea was presented.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.5
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• pp.780-790
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• 2022

Quantitative risk levels must be presented by analyzing the causes and consequences of accidents and predicting the occurrence patterns of the accidents. For the analysis of marine accidents related to vessel traffic, research on the traffic such as collision risk analysis and navigational path finding has been mainly conducted. The analysis of the occurrence pattern of marine accidents has been presented according to the traditional statistical analysis. This study intends to present a marine accident prediction model using the statistics on marine accidents related to vessel traffic. Statistical data from 1998 to 2021, which can be accumulated by month and hourly data among the Korean domestic marine accidents, were converted into structured time series data. The predictive model was built using a long short-term memory network, which is a representative artificial intelligence model. As a result of verifying the performance of the proposed model through the validation data, the RMSEs were noted to be 52.5471 and 126.5893 in the initial neural network model, and as a result of the updated model with observed datasets, the RMSEs were improved to 31.3680 and 36.3967, respectively. Based on the proposed model, the occurrence pattern of marine accidents could be predicted by learning the features of various marine accidents. In further research, a quantitative presentation of the risk of marine accidents and the development of region-based hazard maps are required.