• Korean Association of Arts Management
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• no.58
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• pp.205-239
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• 2021

This study explores the importance of semantic web-based network construction in art data archiving, as well as its meaning and value in the context of arts management along with its potential for future application. The study focuses on oral history obtained from the Arko Arts Archives that contained records of the lives and artistic views of early artists. In this study, the possibility of applying semantic web-based technology to materials concerning culture and the arts was discussed in five aspects based on the results of the case analysis. First, checking the relationship and discovering hidden artists are possible by revealing relationships between characters. Second, understanding and studying society and culture at a given time is possible by interpreting the contextual meaning of information. Third, art exploration can be done broadly and deeply, encompassing various genres from the perspective of the consumer. Fourth, through art construction, history can be reconstructed using a new and rich method. Fifth, expanding the scope beyond the boundaries of art is possible through convergence and collaboration of programs that handle big data. The network data can be used in various methods, such as art history research, art planning, and creation, throughout the art ecosystem. The results of the study suggest that digitizing a large quantity of data concerning culture and the arts is meaningful in arts management as well as identifying and analyzing the relationship network among data clusters using semantic web-based technology.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.66-75
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• 2021

The research is centered towards analyzing the usage status of YouTube platform and the nature of content supplied to YouTube by selecting Korean two Traffic Broadcastings Based on TBS(Traffic Broadcasting System) and TBN(Traffic Broadcasting Network). TBS operates 'Citizen's Broadcasting', which has 1.1 million subscribers among 13 YouTube channels, as its main channel. TBN has only 15,000 subscribers to its main 'TBN Tong', and YouTube channels in 12 local networks. TBS which has a dedicated YouTube manpower, is far ahead of TBN in terms of YouTube channel management and content composition. Both broadcasters are passive about creating new media content due to job stability. For the development of the YouTube platform for these two broadcasters, organizational changes within traffic broadcasting and changes in the perception of members are required, and live broadcasting and discovery of star creators are required. In the changing media environment two traffic broadcastings need a program distribution strategy that can be included in various media platforms.

• Korean Journal of Psychosomatic Medicine
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• v.30 no.2
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• pp.55-65
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• 2022

Although humans exist as Homo Empathicus, human society is actually constantly divided and conflicted between groups. The human empathy response is very sensitive to the justice of others, and depending on the level of others' justice, they may feel empathy or schadenfreude to the suffering of them. However, our empathy to others' suffering are not always fair, and have inherent limitations of ingroup-biased empathy. Depending on whether the suffering other persons belongs to an ingroup or an outgroup, we may feel biased empathy or biased schadenfreude to them without even realizing it. Recent advances in information and communication technology facilitate biased access to ingroup-related SNS or ingroup media, thereby deepening the establishment of a more biased semantic information network related groups. These processes, through interacting with the inherent limitation of empathy, can form a vicious cycle of more biased ingroup empathy and ingroup-related activities, and accelerate divisions and conflicts. This research investigated the properties and limitations of empathy by reviewing studies on the neural mechanism of empathy. By examining the relationship between empathy and justice from a neuroscientific point of view, this research tried to illuminate the modern society of division and conflict in a different dimension from the classical perspective of social science.

• Korean Journal of Psychosomatic Medicine
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• v.30 no.2
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• pp.172-178
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• 2022

Objectives : Although subclinical depression symptoms are associated with suicidal idea, most research have focused on clinical depression such as major depressive disorder or dysthymia. The aim of this study is to investigate network structure of depressive symptom and to reveal which symptoms are associated with suicidal ideation. Methods : We used part of data from the seventh Korea National Health and Nutrition Examination Survey. Participants were between 19 and 65 years of age (N=8,741). Network analysis with Isingfit model is used to reveal network structure of depressive symptoms and most central symptom and edges assessed by patient health questionnaire (PHQ-9). Results : The most two central symptoms were psychomotor activity and suicidal ideation. The strongest edge was psychomotor activity-suicidal ideation. Suicidal ideation also has strong association with depressive mood and worthlessness. Conclusions : These results suggest that psychomotor activity and suicidal ideation can serve as treatment target for subclinical depression and psychomotor activity, worthlessness and depressed mood may be important factor for early intervention of suicidal ideation.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.6
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• pp.41-49
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• 2022

The Internet Engineering Task Force (IETF) has standardized RPL (IPv6 Routing Protocol for Low-power Lossy Network) as a routing protocol for Low Power and Lossy Networks (LLNs), a low power loss network environment. RPL creates a route through an Objective Function (OF) suitable for the service required by LLNs and builds a Destination Oriented Directed Acyclic Graph (DODAG). Existing studies check the residual energy of each node and select a parent with the highest residual energy to build a DODAG, but the energy exhaustion of the parent can not avoid the network disconnection of the children nodes. Therefore, this paper proposes EC-RPL (Enhanced Connectivity-RPL), in which ta node leaves DODAG in advance when the remaining energy of the node falls below the specified energy threshold. The proposed protocol is implemented in Contiki, an open-source IoT operating system, and its performance is evaluated in Cooja simulator, and the number of control messages is compared using Foren6. Experimental results show that EC-RPL has 6.9% lower latency and 5.8% fewer control messages than the existing RPL, and the packet delivery rate is 1.7% higher.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.4
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• pp.181-203
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• 2022

This study analyzed domestic and foreign literature and examined cases of foreign Community of Practice(CoP) of experts to find out what benefits researchers can gain from participating in their CoP, how the CoP was established, and how data is shared within the CoP. In addition, this study discussed on how to establish a CoP of experts in Korea for sharing and using research data. By participating in the CoP of experts, members can be provided with the opportunity to build an experts' network and have a chance to meet with various experts, to acquire and share their expertise and information, to receive help from other experts, to learn about their expertise, and to have opportunities for professional experiences. In addition, this study discussed 4 factors such as operation method and management system, memberships and number of members, activities, and management of data and repository for establishing a CoP of experts for sharing and using research data. This study provides a knowledge base for building a CoP of experts in Korea.

• Clean Technology
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• v.28 no.4
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• pp.278-284
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• 2022

This study presents an excellent planar heater based on low-dimensional composites. By optimizing the ratio of 1D carbon nanotubes (CNT) and 2D MXene (Ti₃C₂T_X), it is possible to create a planar heater that has superior electrical conductivity and high heat generation characteristics. Low-dimensional composites were prepared by mixing CNT paste and MXene solution with eco-friendly waterborne polyurethane (WPU). In order to find the optimal mixing ratio for the MXene-CNT-WPU composites, samples with MXene to CNT weight ratios of 3:1, 1:1, 1:3, 1:7, and 1:14 were investigated. In addition to these different weight ratios, 5 wt% WPU was equally applied to each sample. It was confirmed that the higher the weight ratio of CNT, the lower the sheet resistance and the higher the heating temperature. In particular, when the MXene-CNT-WPU planar heater was fabricated by mixing MXene and CNT at a weight ratio of 1:7 and 1:14, the heating temperature was higher than the heating temperature of a CNT-WPU planar heater. These characteristics are due to the optimized mixture of the 1D materials (CNT) and the 2D materials (MXene) causing the formation of a flat surface and a dense network structure. The low-dimensional composites manufactured with the optimized mixing ratios found in this study are expected to be applied in flexible electronic devices.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.1
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• pp.51-58
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• 2023

In this paper, we propose an organ segmentation technique for the automatic extraction of medical diagnostic indicators from X-ray images. In order to calculate diagnostic indicators of heart disease and spinal disease such as VHS(vertebral heart scale) and Cobb angle, it is necessary to accurately segment the thoracic spine, carina, and heart in a chest X-ray image. A deep neural network model in which the high-resolution representation of the image for each layer and the structure converted into a low-resolution feature map are connected in parallel was adopted. This structure enables the relative position information in the image to be effectively reflected in the segmentation process. It is shown that learning performance can be improved by combining the OCR module, in which pixel information and object information are mutually interacted in a multi-step process, and the channel attention module, which allows each channel of the network to be reflected as different weight values. In addition, a method of augmenting learning data is presented in order to provide robust performance against changes in the position, shape, and size of the subject in the X-ray image. The effectiveness of the proposed theory was evaluated through an experiment using 145 human chest X-ray images and 118 animal X-ray images.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.11
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• pp.403-410
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• 2022

Non-Fungible Tokens (NFTs) created on the basis of blockchain have their own unique value, so they cannot be forged or exchanged with other tokens or coins. Using these characteristics, NFTs can be issued to digital assets such as images, videos, artworks, game characters, and items to claim ownership of digital assets among many users and objects in cyberspace, as well as proving the original. However, interest in NFTs exploded from the beginning of 2020, causing a lot of load on the blockchain network, and as a result, users are experiencing problems such as delays in computational processing or very large fees in the mining process. Additionally, all actions of users are stored in the blockchain, and digital assets are stored in a blockchain-based distributed file storage system, which may unnecessarily expose the personal information of users who do not want to identify themselves on the Internet. In this paper, we propose an NFT platform using cloud computing, access gate, conversion table, and cloud ID to improve usability and privacy problems that occur in existing system. For performance comparison between local and cloud systems, we measured the gas used for smart contract deployment and NFT-issued transaction. As a result, even though the cloud system used the same experimental environment and parameters, it saved about 3.75% of gas for smart contract deployment and about 4.6% for NFT-generated transaction, confirming that the cloud system can handle computations more efficiently than the local system.

• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.1091-1104
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• 2022

Climate change is predicted to increase the frequency and intensity of rainfall worldwide, and the pattern is changing due to inundation damage in urban areas due to rapid urbanization and industrialization. Accordingly, the impact assessment of climate change is mentioned as a very important factor in urban planning, and the World Meteorological Organization (WMO) is emphasizing the need for an impact forecast that considers the social and economic impacts that may arise from meteorological phenomena. In particular, in terms of traffic, the degradation of transport systems due to urban flooding is the most detrimental factor to society and is estimated to be around £100k per hour per major road affected. However, in the case of Korea, even if accurate forecasts and special warnings on the occurrence of meteorological disasters are currently provided, the effects are not properly conveyed. Therefore, in this study, high-resolution analysis and hydrological factors of each area are reflected in order to suggest the depth of flooding of urban floods and to cope with the damage that may affect vehicles, and the degree of flooding caused by rainfall and its effect on vehicle operation are investigated. decided it was necessary. Therefore, the calculation formula of rainfall-immersion depth-vehicle speed is presented using various machine learning techniques rather than simple linear regression. In addition, by applying the climate change scenario to the rainfall-inundation depth-vehicle speed calculation formula, it predicts the flooding of urban rivers during heavy rain, and evaluates possible traffic network disturbances due to road inundation considering the impact of future climate change. We want to develop technology for use in traffic flow planning.