• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.5
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• pp.113-119
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• 2023

Most infrastructure structures were completed during periods of economic growth. The number of infrastructure structures reaching their lifespan is increasing, and the proportion of old structures is gradually increasing. The functions and performance of these structures at the time of design may deteriorate and may even lead to safety accidents. To prevent this repercussion, accurate inspection and appropriate repair are requisite. To this end, demand is increasing for computer vision and deep learning technology to accurately detect even minute cracks. However, deep learning algorithms require a large number of training data. In particular, label images indicating the location of cracks in the image are required. To secure a large number of those label images, a lot of labor and time are consumed. To reduce these costs as well as increase detection accuracy, this study proposed a learning structure based on mean teacher method. This learning structure was trained on a dataset of 900 labeled image dataset and 3000 unlabeled image dataset. The crack detection network model was evaluated on over 300 labeled image dataset, and the detection accuracy recorded a mean intersection over union of 89.23% and an F1 score of 89.12%. Through this experiment, it was confirmed that detection performance was improved compared to supervised learning. It is expected that this proposed method will be used in the future to reduce the cost required to secure label images.

• Composites Research
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• v.36 no.6
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• pp.429-434
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• 2023

In this study, aimed at improving the existing acoustic emission sensor for real time monitoring, a macro-fiber composite (MFC) transducer was employed as the acoustic emission sensor in the gas leak detection system. Prior to implementation, structural analysis was conducted to optimize the MFC's design. Consequently, the flexibility of the MFC facilitated excellent adherence to curved pipes, enabling the reception of acoustic emission (AE) signals without complications. Analysis of AE signals revealed substantial variations in parameter values for both high-pressure and low-pressure leaks. Notably, in the parameters of the Fast Fourier Transform (FFT) graph, the change amounted to 120% to 626% for high-pressure leaks compared to the case without leaks, and approximately 9% to 22% for low-pressure leaks. Furthermore, depending on the distance from the leak site, the magnitude of change in parameters tended to decrease as the distance increased. As the results, in the future, not only will it be possible to detect a leak by detecting the amount of parameter change in the future, but it will also be possible to identify the location of the leak from the amount of change.

• Journal of Cadastre & Land InformatiX
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• v.53 no.2
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• pp.79-92
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• 2023

With a growing interest in the Han River Skyline, which greatly influences Seoul's image, careful consideration of the skyline form has become crucial in the redevelopment plans for apartment complexes along the Han River. The Seoul Metropolitan City government has lifted the height limitations for apartments along the Hang River to cultivate a vibrant skyline. However, traditional skyline analysis often overlooks specific attributes, limiting the provision of precise guidelines for Seoul's unique skyline plans. Despite advancements in Digital Twin technology, only some tools effectively manage urban skylines with preferred shapes. Hence, this study aims to make a substantial contribution to the advancement of a Digital Twin 3D modeling program capable of effectively managing urban skylines. This is achieved through the utilisation of Conjoint Analysis, which assesses the importance of each attribute in determining the preferred skyline shape. Focusing on Apgujeong apartment complexes along the Han River currently undergoing redevelopment or planned for redevelopment, the study analyses the preferred skyline shape to propose standards for the Digital Twin 3D modeling program development. It also suggests that Conjoint Analysis can be beneficial in this process.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.385-391
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• 2023

As the use of electric vehicles has increased to minimize carbon emissions, the analyzing the state and performance of lithium-ion batteries that is instrumental in electric vehicles have been important. Comprehensive analysis using not only the voltage, current and temperature of the battery pack, which can affect the condition and performance of the battery, but also the driving data and charging pattern data of the electric vehicle is required. Therefore, a thorough analysis is imperative, utilizing electric vehicle operation data, charging pattern data, as well as battery pack voltage, current, and temperature data, which collectively influence the condition and performance of the battery. Therefore, collection and preprocessing of battery data collected from electric vehicles, collection and preprocessing of data on driver driving habits in addition to simple battery data, detailed design and modification of artificial intelligence algorithm based on the analyzed influencing factors, and A battery analysis and evaluation model was designed. In this paper, we gathered operational data and battery data from real-time electric buses. These data sets were then utilized to train a Random Forest algorithm. Furthermore, a comprehensive assessment of battery status, operation, and charging patterns was conducted using the explainable Artificial Intelligence (XAI) algorithm. The study identified crucial influencing factors on battery status, including rapid acceleration, rapid deceleration, sudden stops in driving patterns, the number of drives per day in the charging and discharging pattern, daily accumulated Depth of Discharge (DOD), cell voltage differences during discharge, maximum cell temperature, and minimum cell temperature. These factors were confirmed to significantly impact the battery condition. Based on the identified influencing factors, a battery analysis and evaluation model was designed and assessed using the Random Forest algorithm. The results contribute to the understanding of battery health and lay the foundation for effective battery management in electric vehicles.

• Information Systems Review
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• v.23 no.3
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• pp.127-158
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• 2021

Many online travel agencies (OTAs) provide average ratings and time-relevant information or the most recently posted reviews regarding hotels to satisfy customers. To identify these two factors' relative influence on behavioral decision-making processes, we conducted two studies: (1) an experimental research design to explore the relative influence of the two on online review consumption and (2) an empirical approach to examine their relative impact on online review generation. The results show that when review posters observe an inconsistency between average ratings and recent reviews, they tend to deviate from the recent reviews regardless of the overall direction (reactance behavior). Meanwhile, review consumers tend to conform to the opinions presented in recent reviews (herding behavior). Additionally, in both cases, the effects are amplified in case of a negative aberration. Based on the findings, this study provides theoretical and practical implications regarding the relative influences of average rating and recently posted reviews and their different impacts on online review consumption and generation.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.2
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• pp.345-354
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• 2024

In this paper, we propose a triple band WLAN antenna for Wi-Fi 6E band with DGS. The proposed antenna has the characteristics required frequency band and bandwidth by considering the interconnection of two strip lines and three areas on the ground place. The total substrate size is 31 mm (W) × 50 mm (L), thickness (h) 1.6 mm, and the dielectric constant is 4.4, which is made of 22 mm (W₆ + W₄ + W₅) × 43mm (L₁ + L₂ + L₃ + L₅) antenna size on the FR-4 substrate. From the fabrication and measurement results, bandwidths of 340 MHz (1.465 to 1.805 GHz) for 900 MHz band, 480 MHz (2.155 to 2.635 GHz) for 2.4 GHz band and 1950 MHz (4.975 to 6.925 GHz) for 5.0/6.0 GHz band were obtained on the basis of -10 dB. Also, gain and radiation pattern characteristics are measured and shown in the frequency triple band as required.

• Journal of Service Research and Studies
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• v.14 no.2
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• pp.117-137
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• 2024

ESG has become a necessity for all companies, and major Korean banks are actively practicing ESG management. Banks are playing a role in providing ESG finance as intermediaries in the supply of funds. Recently, they have launched ESG digital banking products that offer preferential interest rates for eco-friendly activities in combination with digital technologies. However, indiscriminate provision of preferential interest rates can adversely affect profitability of banks, and they may face the problem of 'Greenwashing' if they do not contribute to improving environmental awareness. Therefore, this study selected ESG digital savings products linked to electricity savings as the subject of the study, and empirically analyzed consumers' environmental awareness and savings behavior through actual data of consumers (N=2,478). The main findings of this study are as follows First, the analysis of the consumer status of ESG digital banking products shows that the 30-50s are the main consumer base, and the MZ generation shows relatively high performance in achieving preferential interest rates through electricity saving practices. Second, consumers' environmental awareness has a significant impact on achieving the goals of ESG banking products. ESG banking products can contribute to environmental awareness while fulfilling the basic function of saving. Third, environmental awareness did not drive consumers' savings contribution behavior, suggesting the need for continued consumer engagement. Based on environmental awareness and the theory of saving behavior, this study provides a theoretical explanation in ESG financial products. The results suggest that the appropriateness of the preferential interest rate design of ESG financial products is important.

• Journal of agricultural medicine and community health
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• v.49 no.2
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• pp.132-145
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• 2024

Objectives: This study compares cases of Dalgubeol Health Care Project, 301 Network Project, and 3 for 1 Project based on program logic models to derive measures for promoting integrated healthcare and welfare services centered around medical institutions. Methods: From January to December 2021, information on the implementation systems and performance of each institution was collected. Data sources included prior academic research, project reports, operational guidelines, official press releases, media articles, and written surveys from project managers. A program logic model analysis framework was applied, structuring the information based on four elements: situation, input, activity, and output. Results: All three projects aimed to address the fragmentation of health and welfare services and medical blind spots. Despite similar multidisciplinary team compositions, differences existed in specific fields, recruitment scale, and employment types. Variations in funding sources led to differences in community collaboration, support methods, and future directions. There were discrepancies in the number of beneficiaries and medical treatments, with different results observed when comparing the actual number of people to input manpower and project cost per beneficiary. Conclusions: To design an integrated health and welfare service provision system centered on medical institutions, securing a stable funding mechanism and establishing an appropriate target population and service delivery system are crucial. Additionally, installing a dedicated department within the medical institution to link activities across various sectors, rather than outsourcing, is necessary. Ensuring appropriate recruitment and stable employment systems is needed. A comprehensive provision system offering services from mild to severe cases through public-private cooperation is suggested.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.173-188
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• 2024

With the advancement of autonomous vehicle (AV) technology, autonomous driving on real roads has become feasible. However, there are challenges in achieving complete autonomy due to perceptual blind areas, which occur when the AV's sensory range or capabilities are limited or impaired by surrounding objects or environmental factors. This study aims to analyze AV accident patterns and safety issues of perceptual blind area that may occur in urban areas, with the goal of developing test scenarios for Level 4+ autonomous driving. It utilized AV accident data from the California Department of Motor Vehicles (DMV) to compare accident patterns and characteristics between AVs and conventional vehicles based on activation status of autonomous mode. It also categorized AV disengagement data to identify types and real-world cases of disengagements caused by perceptual blind areas. The analysis revealed that AVs exhibit different accident types due to their safe driving maneuvers, and three types of perceptual blind area scenarios were identified. The findings of this study serve as crucial foundational data for developing Level 4+ autonomous driving test scenarios, enabling the design of efficient strategies to mitigate perceptual blind areas in various scenarios. This, in turn, is expected to contribute to the effective evaluation and enhancement of AV driving safety on real roads.

• Journal of the Korean Geotechnical Society
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• v.40 no.2
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• pp.95-103
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• 2024

The global increase in population and subsequent scarcity of terrestrial living spaces necessitates exploration of alternative habitats. Research into the development of underwater living areas provides promising avenues for the expansion of human living spaces and the use of marine environments. This study focuses on the failure envelope of suction caisson foundations subjected to combined loads in a marine setting, utilizing finite element analysis. The foundation is assumed to be embedded in clay characterized by a linear increase in undrained shear strength with depth, employing the von Mises constitutive model for the clay. The resulting failure envelope is represented as a tilted ellipse which expands as the undrained shear strength increases, maintaining a constant ratio between the major and minor axes. A comparative analysis of two suction caisson foundations with varying length-to-diameter ratios revealed that this ratio influences the dimensions of the failure envelope, with a tendency for the major-to-minor axis ratio to increase as the length-to-diameter ratio increases. These findings are critical for the design of suction caisson foundations in offshore environments.