• Journal of Digital Convergence
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• v.20 no.2
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• pp.163-174
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• 2022

Despite the great interest in the metaverse from academia and industry, research so far has been focused on a specific area, and the background of the study is in the recognition that research is necessary from the perspective of the entire metaverse ecosystem. The purpose of this study was to derive the metaverse research framework and each component to study from the perspective of the metaverse ecosystem, and to study the development stage of the metaverse ecosystem. From an academic point of view, the ecosystem components were derived through the Metaverse IDC-Platform, a framework for applying Michael Porter's diamond model to the metaverse. From a practical point of view, the four components of the metaverse ecosystem interact with each other in terms of metaverse application and development. As the basis of this study, it can be used strategically because it is possible to identify areas for reinforcement in academia and industry and provide basic data for insight by closely examining the strengths and weaknesses of each component. The contribution of research is that it has created a foundation for research that has been limited to specific areas from an ecosystem perspective, unlike before.

• 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.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.3
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• pp.163-190
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• 2023

This study analyzed the effect of technology preparation and technology acceptance factors on the intention of public library librarians to use artificial intelligence-based technology using the technology acceptance model. To this end, a survey was conducted on public library librarians, and a total of 202 survey data were used for statistical analysis. As a result of the hypothesis test, first, optimism has a significant positive (+) effect on perceived usefulness, and discomfort has a significant negative (-) effect. Optimism and innovation on perceived ease of use were found to have a significant positive (+) effect, and discomfort was found to have a significant negative (-) effect. Second, perceived ease of use was found to have a significant positive (+) effect on perceived usefulness, and both perceived usefulness and perceived ease of use had a significant positive (+) effect on the intention to use. Third, optimism was found to have a significant positive (+) effect on the intention to use, and anxiety was found to have a significant negative (-) effect. This study is expected to provide basic data on the use of artificial intelligence technology in the future by empirically analyzing public library librarians' perceptions of artificial intelligence-based technology.

• The Korean Journal of Coaching Psychology
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• v.7 no.2
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• pp.47-74
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• 2023

The purpose of this study was to test the effectiveness of a group coaching program to promote metacognitive learning ability in an academic context for adult learners enrolled at a distance university. The topics and objectives of the group coaching program focused on understanding and applying the elements of 'metacognitive knowledge', and each session was conducted online by integrating 'planing-monitoring-regulating', an element of 'metacognitive regulation', into the REGROW model of coaching. To verify the effectiveness of the program, research participants were recruited from adult university students enrolled in A Cyber University and assigned to the experimental and control groups. The experimental group was given the program, while the control group was given the program after the completion of the study. Metacognitive learning ability level and academic self-efficacy were tested before and after the program for both groups, and a satisfaction survey was conducted for the experimental group. Analyses of the data revealed that the experimental group showed higher scores on both the overall and sub-scales of perceived metacognitive learning ability and academic self-efficacy compared to the control group. Participants in the experimental group also reported high satisfaction with the program, increased knowledge of metacognition, awareness and application of metacognitive strategies, and found the group coaching approach beneficial. Based on these findings, implications, and suggestions for future research are presented.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.3
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• pp.85-96
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• 2023

This study developed and evaluated a safe route guidance service for electric personal assistive mobility device used mainly by the mobility impaired people to improve their mobility. Thirteen underlying factors affecting the mobility of electric personal assistive mobility device have been derived through a survey with the mobility impaired people and employees in related organizations in Busan Metropolitan City. After assigning safety scores to individual factors and identifying the relevant factors along routes of interest with an object detection AI model, the safe route for electric personal assistive mobility device was provided through an optimal path-finding algorithm. As a result of comparing the general route of T-map and the recommended route of this study for the identical routes, the latter had relatively fewer obstacles and the gentler slope than the former, implicating that the recommended route is safer than the general one. As future works, it is necessary to enhance the function of a route guidance service based on the real-time location of users and to conduct spot investigations to evaluate and verify its social acceptability.

• Journal of IKEEE
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• v.27 no.3
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• pp.340-344
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• 2023

In this paper, we propose a study on the development of deep learning structure to secure visibility of outdoor LED display board according to weather change. The proposed technique secures the visibility of the outdoor LED display board by automatically adjusting the LED luminance according to the weather change using deep learning using an imaging device. In order to automatically adjust the LED luminance according to weather changes, a deep learning model that can classify the weather is created by learning it using a convolutional network after first going through a preprocessing process for the flattened background part image data. The applied deep learning network reduces the difference between the input value and the output value using the Residual learning function, inducing learning while taking the characteristics of the initial input value. Next, by using a controller that recognizes the weather and adjusts the luminance of the outdoor LED display board according to the weather change, the luminance is changed so that the luminance increases when the surrounding environment becomes bright, so that it can be seen clearly. In addition, when the surrounding environment becomes dark, the visibility is reduced due to scattering of light, so the brightness of the electronic display board is lowered so that it can be seen clearly. By applying the method proposed in this paper, the result of the certified measurement test of the luminance measurement according to the weather change of the LED sign board confirmed that the visibility of the outdoor LED sign board was secured according to the weather change.

• Journal of IKEEE
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• v.27 no.3
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• pp.345-349
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• 2023

In this paper, we propose a study on the development of deep learning structure for defective pixel detection of next-generation smart LED display board using imaging device. In this research, a technique utilizing imaging devices and deep learning is introduced to automatically detect defects in outdoor LED billboards. Through this approach, the effective management of LED billboards and the resolution of various errors and issues are aimed. The research process consists of three stages. Firstly, the planarized image data of the billboard is processed through calibration to completely remove the background and undergo necessary preprocessing to generate a training dataset. Secondly, the generated dataset is employed to train an object recognition network. This network is composed of a Backbone and a Head. The Backbone employs CSP-Darknet to extract feature maps, while the Head utilizes extracted feature maps as the basis for object detection. Throughout this process, the network is adjusted to align the Confidence score and Intersection over Union (IoU) error, sustaining continuous learning. In the third stage, the created model is employed to automatically detect defective pixels on actual outdoor LED billboards. The proposed method, applied in this paper, yielded results from accredited measurement experiments that achieved 100% detection of defective pixels on real LED billboards. This confirms the improved efficiency in managing and maintaining LED billboards. Such research findings are anticipated to bring about a revolutionary advancement in the management of LED billboards.

• Journal of the Korean Geotechnical Society
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• v.25 no.5
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• pp.53-64
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• 2009

Many slope failures are induced by rainfall infiltration. A lot of recent researches are therefore focused on rainfall-induced slope instability and the rainfall infiltration is recognized as the important triggering factor. The rainfall infiltrates into the soil slope and makes the matric suction lost in the slope and even the positive pore water pressure develops near the surface of the slope. They decrease the resisting shear strength. In Korea, a few public institutions suggested conservative slope design guidelines that assume a fully saturated soil condition. However, this assumption is irrelevant and sometimes soil properties are misused in the slope design method to fulfill the requirement. In this study, a more relevant slope stability evaluation method is suggested to take into account the real rainfall infiltration phenomenon. Unsaturated soil properties such as shear strength, soil-water characteristic curve and permeability for Korean weathered soils were obtained by laboratory tests and also estimated by artificial neural network models. For real-time assessment of slope instability, failure warning criteria of slope based on deterministic and probabilistic analyses were introduced to complement uncertainties of field measurement data. The slope stability evaluation technique can be combined with field measurement data of important factors, such as matric suction and water content, to develop an early warning system for probably unstable slopes due to the rainfall.

• Korea Science and Art Forum
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• v.19
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• pp.735-745
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• 2015

This study is about the marketing mix of convention destination, aims to examine convention destination image and loyalty. In order to study the marketing mix more scientifically, this paper select those indexes which can promote the destination image but also can guide the access loyalty of exhibition participants. In addition, in order to understand the influence of marketing mix of convention destination which includes products, place, price, promotion, people, on destination image and loyalty, this research analyses the beneficial effect among variables. Based on previous research, the marketing mix of convention destination export products, place, price, promotion, people, convention image exports Cognitive images and Emotional images. The results show that, assuming that the beneficial effect of convention marketing mix on cognitive images was established partly, the beneficial effect of convention marketing mix on emotional images was established partly, the beneficial effect of marketing mix of convention destination on loyalty was established partly, the beneficial effect of cognitive images of convention destination on loyalty was established, he beneficial effect of emotional images of convention destination on loyalty was established. Based on the results of the study, a comprehensive strategic management on arketing mix of convention destination, played a profound impact on forming the image of the participants and enlivening the convention destination.

• Korea Science and Art Forum
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• v.29
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• pp.279-292
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• 2017

This study was started by recognizing that visual storytelling(VST) is an important factor that determines the success of the work. The goal of this study is to analyze the VST study approaching from the narrative and visual dimension by analyzing the conflict intensity and VST factor. Therefore, in this paper, we analyzed the conflicts of the theater animation(4) that succeeded in the worldwide success and attempted the VST interpretation by approaching it technically. The results and contents of the study are as follows. Firstly, based on the narrative theory of Sung bong-Sun and Robert McKee, we classified the conflict scenes and found the kinds of conflicts. In addition, based on the 5B model, a total of 108 conflict shots were extracted. Secondly, through expert experiment, we found the conflict intensity of conflict shots. Thirdly, the visual elements of fifteen significant conflicts were extracted from internal and super individual conflicts. Fourth, as a result of the experiment, it was confirmed that the reliability of the visual elements in the inner and super personal conflicts was in the range of 100-83.33%, and the frequency of usage was found to be widely distributed in 5.88-70.59% and 5-70%. This means that the VST expression, which relied on the sense of the artist, can be engineered. Finally, I expect that it will be the basis of the development of the VST Tool which can predict the conflict expression of the work in the animation pre - production stage successfully.