• Advanced Industrial SCIence
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• v.2 no.4
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• pp.17-27
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• 2023

The purpose of this study is to improve the efficiency of digital conversion by presenting factors that domestic small and medium-sized manufacturers should consider when attempting digital conversion. Using SME data from 2019 to 2021, we analyze the impact of digital transformation on the financialization of enterprises and which digital technologies affect financialization, and further analyze the mediating effect of green technology innovation between digital transformation and business finance. did The results of the study support the negative impact of digital technologies on corporate finance, and cloud computing technologies have been found to significantly inhibit the level of corporate finance. In addition, it was found that green technology innovation plays a mediating role in suppressing corporate financialization by promoting green technology innovation through digital transformation. Digital transformation influences corporate decision-making through green technology innovation, suggesting that the combination of digital technology and green projects should be considered.

• Journal of Industrial Convergence
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• v.21 no.3
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• pp.1-15
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• 2023

Expectations for wireless communication technology are rising as a base technology that promotes innovation in various industries in line with the paradigm of digital transformation in the 21st century beyond the stage of being used only for communication service itself. In this study, in order to compare 6G technological competitiveness between Korea and leading countries, technological competitiveness was confirmed through PFS, CPP, and network analysis based on GaN Integrated Circuit patent data. Korea's 6G technological competitiveness was 0.62 in PFS and 3.93 in CPP, which were 32.8% and 19.9%, respectively, compared to leading countries. In addition, as a result of network analysis, the collaboration rate in the 6G field was 7.2%, and the collaboration ecosystem was very insufficient in most countries. In contrast, it was confirmed that Korea, unlike leading countries, has established a small-scale collaboration ecosystem linked by industry and academia. Thus, it is necessary to establish a strategy for 6G communication technology at the national level so that communication technology can be advanced based on a relatively well-established collaborative ecosystem.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.1
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• pp.74-82
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• 2019

The revolution of industry 4.0 is enabling us to build an intelligent connection society called smart cities. The use of renewable energy in particular solar energy is extremely important for modern society due to the growing power demand in smart cities, but its difficult to monitor and manage in each buildings since need to be deploy low energy sensors and information need to be transfer via wireless sensor network (WSN). The Internet of Things (IoT) / low-power wide-area (LPWA) is an emerging WSN technology, to collect and monitor data about environmental and physical electrical / electronics devices conditions in real time. However, providing power to IoT sensor end devices and other public electrical loads such as street lights, etc is an important challenging role because the sensor are usually battery powered and have a limited life time. In this paper, we proposes an efficient solar energy-based power management scheme for smart city based on IoT technology using LoRa wide-area network (LoRaWAN). This approach facilitates to maintain and prevent errors of solar panel based energy systems. The proposed solution maximizing output the power generated from solar panels system to distribute the power to the load and the grid. In this paper, we proved the efficiency of the proposed system with Simulink based system modeling and real-time emulation.

• Journal of Digital Convergence
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• v.16 no.12
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• pp.459-466
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• 2018

Gendered innovations is a term used by policy makers and academics to refer the process of creating better research and development (R&D) for both men and women. In this paper, we analyze the literatures in image and speech signal processing that can be used in ICT, examine the importance of gendered innovations through case study. Therefore the latest domestic and foreign literature related to image and speech signal processing based on gender research is searched and a total of 9 papers are selected. In terms of gender analysis, research subjects, research environment, and research design are examined separately. Especially, through the case analysis of algorithms of the elderly voice signal processing, machine learning, machine translation technology, and facial gender recognition technology, we found that there is gender bias in existing algorithms, and which leads to gender analysis is required. We also propose a gendered innovations method integrating sex and gender analysis in algorithm development. Gendered innovations in ICT can contribute to the creation of new markets by developing products and services that reflect the needs of both men and women.

• Journal of Astronomy and Space Sciences
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• v.25 no.4
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• pp.435-444
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• 2008

High energy charged particles are trapped by geomagnetic field in the region named Van Allen Belt. These particles can move to low altitude along magnetic field and threaten even low altitude spacecraft. Space Radiation can cause equipment failures and on occasions can even destroy operations of satellites in orbit. Sun sensors aboard Science and Technology Satellite (STSAT-l) was designed to detect sun light with silicon solar cells which performance was degraded during satellite operation. In this study, we try to identify which particle contribute to the solar cell degradation with ground based radiation facilities. We measured the short circuit current after bombarding electrons and protons on the solar cells same as STSAT-1 sun sensors. Also we estimated particle flux on the STSAT-l orbit with analyzing NOAA POES particle data. Our result clearly shows STSAT-l solar cell degradation was caused by energetic protons which energy is about 700keV to 1.5MeV. Our result can be applied to estimate solar cell conditions of other satellites.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.5
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• pp.263-270
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• 2021

In this study, a reliability-based design optimization of a 130-m class fixed-type offshore platform, to be installed in the North Sea, was carried out, while considering environmental, material, and manufacturing uncertainties to enhance its structural safety and economic aspects. For the reliability analysis, and reliability-based design optimization of the structural integrity, unity check values (defined as the ratio between working and allowable stress, for axial, bending, and shear stresses), of the members of the offshore platform were considered as constraints. Weight of the supporting jacket structure was minimized to reduce the manufacturing cost of the offshore platform. Statistical characteristics of uncertainties were defined based on observed and measured data references. Reliability analysis and reliability-based design optimization of a jacket-type offshore structure were computationally burdensome due to the large number of members; therefore, we suggested a method for variable screening, based on the importance of their output responses, to reduce the dimension of the problem. Furthermore, a deterministic design optimization was carried out prior to the reliability-based design optimization, to improve overall computational efficiency. Finally, the optimal design obtained was compared with the conventional rule-based offshore platform design in terms of safety and cost.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1507-1515
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• 2021

If chlorophyll-a is estimated through ocean color remote sensing, it is able to understand the global distribution of phytoplankton and primary production. However, there are missing data in the ocean color observed from the satellites due to the clouds or weather conditions. In thisstudy, the missing data of the GOCI (Geostationary Ocean Color Imager) chlorophyll-a product wasreconstructed by using DINEOF (Data INterpolation Empirical Orthogonal Functions). DINEOF reconstructs the missing data based on spatio-temporal data, and the accuracy was cross-verified by removing a part of the GOCI chlorophyll-a image and comparing it with the reconstructed image. In the study area, the optimal EOF (Empirical Orthogonal Functions) mode for DINEOF wasin 10-13. The temporal and spatialreconstructed data reflected the increasing chlorophyll-a concentration in the afternoon, and the noise of outliers was filtered. Therefore, it is expected that DINEOF is useful to reconstruct the missing images, also it is considered that it is able to use as basic data for monitoring the ocean environment.

• 한국노년학
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• v.38 no.3
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• pp.593-605
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• 2018

This study examines factors that influence older drivers to consider stopping driving in advance and whose advice plays an important role in the driving cessation decision. Data came from a nationally representative cross-sectional survey of community-dwelling older adults (N=2,076). About two thirds reported that they have considered stopping driving (62.8%) and they preferred to decide by themselves (66.0%). Logistic regression results showed that women and residents in urban areas were twice as likely to consider voluntary driving cessation compared to their counterparts. Each one year increase in age contributed to the probability that respondents would consider driving cessation by five percent. Those with greater difficulties in ADLs due to chronic illnesses were also more likely to consider driving cessation. No sociodemographic and health factors were related to whether older drivers preferred to decide by themselves or listen to others. These results imply that policies to promote self-motivation to stop driving among older drivers would be effective. Furthermore, they suggest it could be important to help older drivers plan their driving cessation in advance while still at a young-old age, and that more attention needs to be paid to men and those living in rural areas among older drivers.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.765-779
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• 2022

This study evaluates the accuracy in identifying the burned area in South Korea using multi-temporal data from Sentinel-2 MSI and Landsat 8/9 OLI. Spectral indices such as the Difference Normalized Burn Ratio (dNBR), Relative Difference Normalized Burn Ratio (RdNBR), and Burned Area Index (BAI) were used to identify the burned area in the March 2022 forest fire in Uljin. Based on the results of six indices, the accuracy to detect the burned area was assessed for four satellites using Sentinel-2 and Landsat 8/9, respectively. Sentinel-2 and Landsat 8/9 produce images every 16 and 10 days, respectively, although it is difficult to acquire clear images due to clouds. Furthermore, using images taken before and after a forest fire to examine the burned area results in a rapid shift because vegetation growth in South Korea began in April, making it difficult to detect. Because Sentinel-2 and Landsat 8/9 images from February to May are based on the same date, this study is able to compare the indices with a relatively high detection accuracy and gets over the temporal resolution limitation. The results of this study are expected to be applied in the development of new indices to detect burned areas and indices that are optimized to detect South Korean forest fires.

• Korean Journal of Construction Engineering and Management
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• v.23 no.3
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• pp.45-55
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• 2022

BIM models allow building spaces to be instantiated and recognized as unique objects independently of model elements. These instantiated spaces provide the required semantics that can be leveraged for building code checking, energy analysis, and evacuation route analysis. However, theses spaces or rooms need to be designated manually, which in practice, lead to errors and omissions. Thus, most BIM models today does not guarantee the semantic integrity of space designations, limiting their potential applicability. Recent studies have explored ways to automate space allocation in BIM models using artificial intelligence algorithms, but they are limited in their scope and relatively low classification accuracy. This study explored the use of Graph Convolutional Networks, an algorithm exclusively tailored for graph data structures. The goal was to utilize not only geometry information but also the semantic relational data between spaces and elements in the BIM model. Results of the study confirmed that the accuracy was improved by about 8% compared to algorithms that only used geometric distinctions of the individual spaces.