• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.913-924
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• 2022

In this paper, we presented a database construction of undersea images for the Habitats of Ecklonia cava and Sargassum and conducted an experiment for semantic segmentation using state-of-the-art (SOTA) models such as High Resolution Network-Object Contextual Representation (HRNet-OCR) and Shifted Windows-L (Swin-L). The result showed that our segmentation models were superior to the existing experiments in terms of the 29% increased mean intersection over union (mIOU). Swin-L model produced better performance for every class. In particular, the information of the Ecklonia cava class that had small data were also appropriately extracted by Swin-L model. Target objects and the backgrounds were well distinguished owing to the Transformer backbone better than the legacy models. A bigger database under construction will ensure more accuracy improvement and can be utilized as deep learning database for undersea images.

• Journal of Internet Computing and Services
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• v.23 no.4
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• pp.21-33
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• 2022

Recently, the recommender system has been widely used in various fields such as movies, music, online shopping, and social media, and in the meantime, the recommender model has been developed from correlation analysis through the Apriori model, which can be said to be the first-generation model in the recommender system field. In 2005, many models have been proposed, including deep learning-based models, which are receiving a lot of attention within the recommender model. The recommender model can be classified into a collaborative filtering method, a content-based method, and a hybrid method that uses these two methods integrally. However, these basic methods are gradually losing their status as methodologies in the field as they fail to adapt to internal and external changing factors such as the rapidly changing user-item interaction and the development of big data. On the other hand, the importance of deep learning methodologies in recommender systems is increasing because of its advantages such as nonlinear transformation, representation learning, sequence modeling, and flexibility. In this paper, among deep learning methodologies, RNN, CNN, and GAN-based models suitable for sequential modeling that can accurately and flexibly analyze user-item interactions are classified, compared, and analyzed.

• The Journal of the Convergence on Culture Technology
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• v.7 no.2
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• pp.85-95
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• 2021

Currently, we stand between computers as creative tools and computers as creators. A new genre of movies, which can be called a post-cinema situation, is emerging. This paper aims to diagnose the possibility of the emergence of AI cinema. To confirm the possibility of AI cinema, it was examined through a case study whether the creation of a story, narrative, image, and sound, which are necessary conditions for film creation, is possible by artificial intelligence. First, we checked the visual creation of AI painting algorithms Obvious, GAN, and CAN. Second, AI music has already entered the distribution stage in the market in cooperation with humans. Third, AI can already complete drama scripts, and automatic scenario creation programs using big data are also gaining popularity. That said, we confirmed that the filmmaking requirements could be met with AI algorithms. From the perspective of Manovich's 'AI Genre Convention', web documentaries and desktop documentaries, typical trends post-cinema, can be said to be representative genres that can be expected as AI cinemas. The conditions for AI, web documentaries and desktop documentaries to exist are the same. This article suggests a new path for the media of the 4th Industrial Revolution era through research on AI as a creator of post-cinema.

• Journal of Korea Entertainment Industry Association
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• v.15 no.8
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• pp.107-116
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• 2021

In recent years, the research on audience satisfaction after watching programs has been carried out in various fields. However, there is no precedent for the study of simply analyzing the influencing factors of audience satisfaction with the newly established CCTV-9 channel. For CCTV-9, how to explore the strategy of industrial development based on the needs of the audience in the era of big data is a very important part. This article exploratively focuses on the influencing factors related to CCTV-9 audience satisfaction. Using questionnaires, 101 samples of the satisfaction with the channel of men and women of different ages, education backgrounds, majors, and incomes were collected to test, and 9 hypotheses were tentatively proposed as relevant influencing factors of channel satisfaction. Through empirical analysis, this research searches for the determinants. The reliability and validity of the measurement were properly analyzed, and all hypotheses were statistically tested. The empirical results show that: subject matter, program format, program scheduling, program broadcast time, channel advertising, simulcast series of documentaries, diversified communication platforms, brand image packaging and audience satisfaction are significantly positively correlated.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.57-79
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• 2022

COVID-19, which started in December 2019, has had a great impact on our lives in general, including politics, economy, society, and culture, and activities in sports and arts have also been significantly reduced. In the case of sports, sports for all fields in which ordinary citizens participate were particularly affected, and cases of infection in places closely related to people's lives, such as gyms, table tennis, and badminton clubs, also amplified the social fear of the spread of COVID-19. Therefore, in this study, we analyzed news articles related to sports for all at the time when COVID-19 was first spread, and investigated what issues were emerging and being discussed in the sports for all field under the COVID-19 situation. Specifically, we collected news articles dealt with sports for all issues under the COVID-19 situation from Korea's leading portal news sites and identified key sports for all issues by performing topic modeling on these articles. Through the analysis, we found meaningful issues such as COVID-19 outbreak in sports facilities and support for sports activities. In addition, through wordcloud analysis of these major issues, we visually understood the issues and identified the changes in these issues over time.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.1
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• pp.1-10
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• 2022

In this study, the two horizontal shroud tidal current energy converter, which can generate power even under low flow speed conditions, was developed. In order to determine the shape of the shroud system, a three-dimensional numerical simulation test was conducted, and a 1/6 scale down model was made to perform a hydraulic model experiment. The hydraulic model experiment was performed under four flow conditions, and the flow speed, torque, and RPM were measured for each experimental case. As a result of the numerical simulation test, it was found that the flow speeds passing through the nozzle were increased by about 2~3 times in the cylinder, and when the extension ratio was 2:1, the highest flow speed was shown. In addition, it was found that the flow speeds increased 2.8 times when the diameter ratio between the nozzle and the cylinder was 1.5:1. Meanwhile, as a result of the hydraulic model experiment, it was found that when the tip speed ratio was between 1.75 and 2, the power coefficient was 0.32 to 0.34.

• Journal of Practical Engineering Education
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• v.14 no.1
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• pp.127-136
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• 2022

As manufacturing items have changed in various ways, changes in the mass production of small-scale small-scale production of multiple varieties have become commonplace. As a result, the method of the manufacturing site has also changed, and the "smart factory," which emphasizes the production efficiency aspect using automation lines and big data of factories, is in the spotlight according to the global market economy. The introduction performance of smart factories has a positive effect in terms of production efficiency and is drawing a steep upward curve. In addition to the positive aspects, the aspect that needs to be supplemented in the future is the support and cooperation of specialized smart equipment suppliers, but education on standardized smart factories and the relocation of existing manpower, education, evaluation, and creative production that robots cannot replace Various support measures are also needed for activities. In addition, continuous management and systematic education are required to enter the upper stage. Through the case of companies that have built smart factories, it is intended to emphasize the need for proper use of manpower and support management for settlement and maintenance after introduction and continuous on-the-job training through the comparison of productivity before and after introduction to ensure the effect continues.

• Knowledge Management Research
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• v.23 no.2
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• pp.193-210
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• 2022

The rapid development of mobile technology and the improvement of network speed are providing convenience to various services, and mobile shopping malls are no exception. Although efforts are being made to promote sales by combining various technologies such as customized recommendations using big data and specialized personalization services based on artificial intelligence, most mobile shopping malls have the same detailed page information structure including detailed product information. In this context, in this study, it was determined that the content layout of the product detail page and the mobile product detail page layout tailored to the consumer's preference should be presented according to the consumer's preference. Based on Higgins' Regulatory Focus Theory, a study of consumer propensity revealed that the content layout arrangement on a product detail page, when presented in an F-shape, informs the consumer that it is organized. If presented in a Z-shape, vivid information was recognized, and it was examined whether the product attitude and purchase intention were affected. As a result, when the content layout composition was presented as a layout arrangement in the form of a sense of unity and organization, prevention-focused consumers were positively affected by product attitudes and purchase intentions, and promotion-oriented consumers felt freedom. When presented in an arrangement, it was confirmed that the product attitude and purchase intention were affected.

• Journal of Internet Computing and Services
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• v.24 no.1
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• pp.1-7
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• 2023

Recently, the technology of device-to-device(D2D) communication has been receiving big attention to improve the system performance since the amount of high quality/large capacity data traffic from smart phones and various devices of Internet of Things increase rapidly in 5G/6G based next generation cellular networks. However, even though the system performance of macro cells increase by reusing the frequency, the performance of macro user equipments(MUEs) decrease because of the strong interference from D2D user equipments(DUEs). Therefore, this paper proposes a dynamic channel management(DCM) scheme for DUEs to guarantee the performance of MUEs as the number of DUEs increases in next generation downlink cellular networks. In the proposed D2D DCM scheme, macro base stations dynamically assign subchannels to DUEs based on the interference information and signal to interference and noise ratio(SINR) of MUEs. Simulation results show that the proposed D2D DCM scheme outperforms other schemes in terms of the mean MUE capacity as the threshold of the SINR of MUEs incareases.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.77-82
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• 2023

The Ministry of Agriculture, Food and Rural Affairs established the FarmMap, an digital map of agricultural land. In this study, using deep learning, we suggest the application of farm map reading to farmland such as paddy fields, fields, ginseng, fruit trees, facilities, and uncultivated land. The farm map is used as spatial information for planting status and drone operation by digitizing agricultural land in the real world using aerial and satellite images. A reading manual has been prepared and updated every year by demarcating the boundaries of agricultural land and reading the attributes. Human reading of agricultural land differs depending on reading ability and experience, and reading errors are difficult to verify in reality because of budget limitations. The farmmap has location information and class information of the corresponding object in the image of 5 types of farmland properties, so the suitable AI technique was tested with ResNet50, an instance segmentation model. The results of attribute reading of agricultural land using deep learning and attribute reading by humans were compared. If technology is developed by focusing on attribute reading that shows different results in the future, it is expected that it will play a big role in reducing attribute errors and improving the accuracy of digital map of agricultural land.