• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.1031-1039
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• 2022

As one of the hydrological factors closely related to landslides, precipitation indirectly affects slope stability by generating external forces. Groundwater level fluctuations have attracted more attention lately as factors that directly affect slope stability have become more prominent. Therefore, this study attempted to analyze the relationship between variables through changes in precipitation, groundwater levels, and land displacement. A time series-based analysis was conducted using satellite-based precipitation and point-based groundwater levels in conjunction with the PSInSAR technique to simulate land displacement in urban and mountainous areas. There was a sharp rise in groundwater levels in both urban and mountain areas during heavy rainfall, and a continuous decrease in urban areas when rainfall was low. 6 mm of displacements was observed in the mountainous area as a results of soil outflow from the topsoil layer, which was accompanied by an increased groundwater level. Meanwhile, different results were found in urban area. In response to the rise in groundwater level, the land displacement increases due to the expansion of soil skeletons, while the decrease seems to be attributed to anthropogenic influences. Overall, there was no consistent relationship between groundwater levels and land displacement, which appears to be caused by factors other than hydrological factors. Additional consideration of environmental factors could contribute to a deeper understanding of the relationship between the two factors.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.157-172
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• 2024

Autonomous driving technology, when commercialized, has the potential to improve the safety, mobility, and environmental performance of transportation networks. However, safe autonomous driving may be hindered by poor sensor performance and limitations in long-distance detection. Therefore, cooperative autonomous driving that can supplement information collected from surrounding vehicles and infrastructure is essential. In addition, since HDVs, AVs, and CAVs have different ranges of perceivable information and different response protocols, countermeasures are needed for mixed traffic that occur during the transition period of autonomous driving technology. There is a lack of research on traffic flow optimization that considers the penetration rate of autonomous vehicles and the different characteristics of each road segment. The objective of this study is to develop weights based on safety, operational, and environmental factors for each infrastructure control use case and autonomous vehicle MPR. To develop an integrated evaluation index, infra-guidance AHP and hybrid AHP weights were combined. Based on the results of this study, it can be used to give right of way to each vehicle to optimize mixed traffic.

• Journal of Information Technology Applications and Management
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• v.27 no.3
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• pp.19-36
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• 2020

The Internet of things (IoT) is a system of interrelated computed devices, digital machines and any physical objects which are provided with unique identifiers and the potential to transmit data to people or machine (M2M) without requiring human interaction. IoT devices can be used to monitor and control the electrical and electronic systems used in different fields like smart home, smart city, smart healthcare and etc. In this study we introduce four imaginary IoT devices as a learning support assistants according to students' dominant learning styles measured by Honey and Mumford Learning Styles: Activists, Reflectors, Theorists and Pragmatists. This research emphasizes the association between students' strong learning styles and a preference to appropriate IoT devices with specific characteristics. Moreover, different levels of IoT devices' architecture are clearly explained in this study where all the artificial devices are designed based on this structure. Data analysis of experiment were measured by the use of chi square test for association and research results showed the statistical significance of the estimated model and the impacts of each category over the model where we finally got accurate estimates for our research variables. This study revealed the importance of considering the students' dominant learning styles before inventing a new IoT device.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.8057-8063
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• 2015

It is expected that internet of things can be used for various fields such as smart home, smart building and smart city as the representative case of ICT that sensor, communication and interface technologies operate organically and the researches of the technologies regarding internet of things are being carried out in each countries worldwide. However, many problems rise against internet of things continuously in respect of security. Among them, the problem of privacy is the one that should be solved definitely regarding internet of things. If user data does not remain during the process of user authentication, such the privacy problem can be solved. In this paper, we propose the framework of user authentication based on OAuth that is suitable for the environment of internet of things that can solve privacy problem and analyze its security.

• The Journal of Economics, Marketing and Management
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• v.5 no.3
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• pp.1-11
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• 2017

E-infrastructural economy for ICT Living-Labs is a need for economic and cultural changes in various types of cars in accordance with the supply of the electric car. Depending on the number of cases by analyzing the supply and demand of electric vehicles among Korea and Northern Europe countries. it was indirectly proved that it makes economic growth. The research design is analyzed with the data and how to respond quickly to focus on the possibility of potential changes to the infrastructure realization and commercialization of government enterprises or electric cars through the ICT Living-Labs in Nordic countries. The data indicates that the leading commercialization emphasize on the development of the electric economic convergence and scalability for electric vehicle. When It shows the time of the infrastructure as ICT Living-Labs being delayed, it lowered growth target results for the development of the electric car industry in the future. All this is from the reason of opening the E-convergence economy over time. It is required that Korea should prepare E-convergence economy. Public regional energy should be present through the consistent selection of development for energy linking E-economy and E-trans distribution. Korea needs to be many difficulties in building the E- infrastructure for ICT Living-Labs. Unlike the Northern Europe it is to prepare the active support of both government and business. The role of the government discovers that the power generation through the quick selection of the industry, as well as to connect with the growth of the smart cities with the EVs industry.

• Smart Structures and Systems
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• v.33 no.1
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• pp.17-26
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• 2024

The new metro crossing the existing metro will cause the settlement or floating of the existing structures, which will have safety problems for the operation of the existing metro and the construction of the new metro. Therefore, it is necessary to monitor and predict the settlement of the existing metro caused by the construction of the new metro in real time. Considering the complexity and uncertainty of metro settlement, a Gaussian Prior Bayesian Emulator (GPBE) probability prediction model based on Bayesian optimization (BO) is proposed, that is, BO-GPBE. Firstly, the settlement monitoring data are analyzed to get the influence of the new metro on the settlement of the existing metro. Then, five different acquisition functions, that is, expected improvement (EI), expected improvement per second (EIPS), expected improvement per second plus (EIPSP), lower confidence bound (LCB), probability of improvement (PI) are selected to construct BO model, and then BO-GPBE model is established. Finally, three years settlement monitoring data were collected by structural health monitoring (SHM) system installed on Nanjing Metro Line 10 are employed to demonstrate the effectiveness of BO-GPBE for forecasting the settlement.

• Smart Structures and Systems
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• v.15 no.3
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• pp.543-553
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• 2015

The condition of the vehicular bridge network in New York City, as represented by ratings obtained during biennial inspections is reviewed over a period of three decades. Concurrently, the bridges comprising the network are considered as networks of structural elements whose condition defines the overall bridge condition according to New York State assumptions. A knowledge-based matrix of assessments is used in order to determine each element's vulnerability and impact within the network of an individual structure and the network of City bridges. In both networks expansion deck joints emerge as the weak link. Typical joint failures are illustrated. Bridge management options for maintenance, preservation, rehabilitation and replacement are examined in the context of joint performance.

• 한국IT서비스학회:학술대회논문집
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• 2008.05a
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• pp.123-128
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• 2008

생활공간의 혁신적인 발전은 U-City라는 형태로 추진되고 가시화되고 있으며 특히 U-City의 옥외 공간에서 이뤄지는 서비스는 공간이 지능화되고 다양한 형태의 단말을 통해 보다 능동적이고 찾아가는 형태로 제시되고 있다. 그러나 이러한 서비스를 실현하기 위해서는 옥외공간에 다양한 서비스 장비가 설치, 운용되어야 하는데 KT는 이를 효과적으로 구성하고 구현할 수 있는 IT인프라로서 도시 야간 필수 시설물이며 도시미관을 해치지 않는 가로등 형태로 수용하여 서비스 구현에 필요한 장비를 수용하는 지능형 가로등 U-Pole을 개발해오고 있다. 본 논문에서는 U-Pole로 구성된 현장 서비스 제공 플랫폼과 옥외 공간지능화 서비스 사례를 소개하고자 한다.

• International journal of advanced smart convergence
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• v.11 no.2
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• pp.30-37
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• 2022

Because fine dust (PM10) has a close effect on the environment, fine dust generated in the climate and living environment has a bad effect on the human body. In this study, the LSTM model was applied to predict and analyze the effect of fine dust on Gwangju Metropolitan City in Korea. This paper uses prediction values of input variables selected through correlation analysis to confirm fine dust prediction performance. In this paper, data from the Gwangju Metropolitan City area were collected to measure fine dust. The collection period is one year's worth of data was used from january to December of 2021, and the test data was conducted using three-month data from January to March of 2022. As a result of this study, in the as a result of predicting fine dust (PH10) and ultrafine dust (PH2.5) using the LSTM model, the RMSE was 4.61 and the test result value was as low as 4.37. This reason is judged to be the result of the contents of the one-year sample.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.186-191
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• 2023

This study would investigate the generative AIs currently in service in the era of hyperscale AIs and explore measures for the use of generative AIs, focusing on 'ChatGPT,' which has received attention as a leader of generative AIs. Among the various generative AIs, this study selected ChatGPT, which has rich application cases to conduct research, investigation, and use. This study investigated the concept, learning principle, and features of ChatGPT, identified the algorithm of conversational AI as one of the specific cases and checked how it is used. In addition, by comparing various cases of the application of conversational AIs such as Google's Bard and MS's NewBing, this study sought efficient ways to utilize them through the collected cases and conducted research on the limitations of conversational AI and precautions for its use. If connected to city-related databases, it can provide information on city infrastructure, transportation systems, and public services, so residents can easily get the information they need. We want to apply this research to enrich the lives of our citizens.