• Land and Housing Review
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• v.14 no.1
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• pp.83-97
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• 2023

The study aims to provide an academic basis for the preservation and restoration of abandoned paddy wetland and the enhancement of its carbon accumulation function. First, the temporal change of the wetlands was analysed, and a typological classification system for wetlands was attempted with the goal of carbon reduction. The types of wetland were classified based on three variables: hydrological environment, vegetation, and carbon accumulation, with a special attention on the function of carbon accumulation. The types of abandoned paddy wetlands were classified into 12 categories based on hydrologic variables- either high or low levels of water inflow potential-, vegetation variables with either dominance of aquatic plants or terrestrial plants, and three carbon accumulation variables including organic matter production, soil organic carbon accumulation, and decomposition. It was found that the development period of abandoned paddy analyzed with aerial photographs provided by the National Geographic Information Institute happened between 2010 and 2015. In the case of the wetland in Daejeon 1 (DJMN01) farming stopped by 1990 and it appeared to be a similar structure to natural wetlands after 2010 . Over the past 40 years the abandoned paddy wetland changed to a high proportion of forests and agricultural lands. As time went by, such forests and agricultural lands tended to decrease rapidly and the lands were covered by artificial grass and other types of forests.

• Journal of the Korea Institute of Building Construction
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• v.22 no.6
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• pp.619-630
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• 2022

The concrete mix design and compressive strength evaluation are used as basic data for the durability of sustainable structures. However, the recent diversification of mixing factors has created difficulties in calculating the correct mixing factor or setting the reference value concrete mixing design. The purpose of this study is to design a predictive model of bidirectional analysis that calculates the mixing elements of ternary concrete using deep learning, one of the artificial intelligence techniques. For the DNN-based predictive model for calculating the concrete mixing factor, performance evaluation and comparison were performed using a total of 8 models with the number of layers and the number of hidden neurons as variables. The combination calculation result was output. As a result of the model's performance evaluation, an average error rate of about 1.423% for the concrete compressive strength factor was achieved. and an average MAPE error of 8.22% for the prediction of the ternary concrete mixing factor was satisfied. Through comparing the performance evaluation for each structure of the DNN model, the DNN5L-2048 model showed the highest performance for all compounding factors. Using the learned DNN model, the prediction of the ternary concrete formulation table with the required compressive strength of 30 and 50 MPa was carried out. The verification process through the expansion of the data set for learning and a comparison between the actual concrete mix table and the DNN model output concrete mix table is necessary.

• Journal of the Korean Geotechnical Society
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• v.38 no.11
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• pp.69-86
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• 2022

The railway is widely used to transport passengers and freight due to its punctuality and large transport capacity. The recent remarkable development in construction technology enables various subsea railway tunnels for continent-continent or continent-island connectivity. In Korea, design and construction experience is primarily based on the successful completion of the Boryeong subsea tunnel (2021) and the Gadeok subsea tunnel (2010). However, frequent earthquakes with diverse magnitudes, globally induced and continuously increased the awareness of seismic risks and the frequency of domestic earthquakes. The effect of an earthquake on the subsea tunnel is very complicated. However, ground conditions and seismic waves are considered the main factors. This study simulated four ground types of 3-dimensional numerical models, such as soil, rock, composite, and fractured zone, to analyze the effect of ground type and seismic wave. A virtual subsea railway shield tunnel considering external water pressure was modeled. Further, three different seismic waves with long-term, short-term, and both periods were studied. The dynamic analyses by finite difference method were performed to investigate the displacement and stress characteristics. Consequently, the long-term period wave exhibited a predominant lateral displacement response in soil and the short-term period wave in rock. The artificial wave, which had both periodic characteristics, demonstrated predominant in the fractured zone. The effect of an earthquake is more noticeable in the stress of the tunnel segment than in displacement because of confining effect of ground and structural elements in the shield tunnel. 

• Journal of Korea Water Resources Association
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• v.55 no.11
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• pp.903-911
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• 2022

Groundwater, one of the resources for supplying water, fluctuates in water level due to various natural factors. Recently, research has been conducted to predict fluctuations in groundwater levels using Artificial Neural Network (ANN). Previously, among operators in ANN, Gradient Descent (GD)-based Optimizers were used as Optimizer that affect learning. GD-based Optimizers have disadvantages of initial correlation dependence and absence of solution comparison and storage structure. This study developed Gradient Descent combined with Harmony Search (GDHS), a new Optimizer that combined GD and Harmony Search (HS) to improve the shortcomings of GD-based Optimizers. To evaluate the performance of GDHS, groundwater level at Icheon Yullhyeon observation station were learned and predicted using Multi Layer Perceptron (MLP). Mean Squared Error (MSE) and Mean Absolute Error (MAE) were used to compare the performance of MLP using GD and GDHS. Comparing the learning results, GDHS had lower maximum, minimum, average and Standard Deviation (SD) of MSE than GD. Comparing the prediction results, GDHS was evaluated to have a lower error in all of the evaluation index than GD.

• Knowledge Management Research
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• v.23 no.2
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• pp.193-210
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• 2022

The rapid development of mobile technology and the improvement of network speed are providing convenience to various services, and mobile shopping malls are no exception. Although efforts are being made to promote sales by combining various technologies such as customized recommendations using big data and specialized personalization services based on artificial intelligence, most mobile shopping malls have the same detailed page information structure including detailed product information. In this context, in this study, it was determined that the content layout of the product detail page and the mobile product detail page layout tailored to the consumer's preference should be presented according to the consumer's preference. Based on Higgins' Regulatory Focus Theory, a study of consumer propensity revealed that the content layout arrangement on a product detail page, when presented in an F-shape, informs the consumer that it is organized. If presented in a Z-shape, vivid information was recognized, and it was examined whether the product attitude and purchase intention were affected. As a result, when the content layout composition was presented as a layout arrangement in the form of a sense of unity and organization, prevention-focused consumers were positively affected by product attitudes and purchase intentions, and promotion-oriented consumers felt freedom. When presented in an arrangement, it was confirmed that the product attitude and purchase intention were affected.

• The Mathematical Education
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• v.62 no.3
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• pp.303-326
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• 2023

Mathematics is a discipline with a strong systemic structure, and learning deficits in previous stages have a great influence on the next stages of learning. Therefore, it is necessary to frequently check whether students have learned well and to provide immediate feedback, and for this purpose, intelligent tutoring system(ITS) can be used in math education. For this reason, it is necessary to reveal how the intelligent tutoring system is effective in personalized adaptive learning. The purpose of this study is to investigate the functions and applications of intelligent tutoring system for personalized adaptive learning in mathematics. To achieve this goal, literature reviews and surveys with students were applied to derive implications. Based on the literature reviews, the functions of intelligent tutoring system for personalized adaptive learning were derived. They can be broadly divided into diagnosis and evaluation, analysis and prediction, and feedback and content delivery. The learning and lesson plans were designed by them and it was applied to fifth graders in elementary school for about three months. As a result of this study, intelligent tutoring system was mostly supporting personalized adaptive learning in mathematics in several ways. Also, the researcher suggested that more sophisticated materials and technologies should be developed for effective personalized adaptive learning in mathematics by using intelligent tutoring system.

• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.2
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• pp.141-155
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• 2023

Monitoring technology based on electrical resistivity is widely used for non-destructive data collection and health analysis of underground structures and tunnels. Vulnerable sections such as fault zone generates many problems during construction of the tunnel. These problems cause displacement and stress changes of the ground. Therefore, it is necessary to predict the state of the fault zone section to ensure the mechanical stability of the underground structure. Monitoring the size of joints and the porosity of the fillings is essential for rocks. Previous studies have not considered the variety of fillings in rock joints. In this study, electrical resistivity tests were conducted according to the particle mixing state of the sandy fillings. When the size of fillings is decreased at the constant porosity, the electrical resistivity tends to increase. The results of this study are expected to be useful as basic electrical resistivity data for predicting the ground conditions and evaluation of the ground behavior that is containing sandy fillings in the rock joint for tunnels.

• Journal of Service Research and Studies
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• v.12 no.1
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• pp.1-24
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• 2022

This study was conducted to derive a new model for popular democracy in the modern society. The problem is exacerbated as the original model of democracy, isonomia, has faded and modern democracy is operated as a democracy in which the masses rule. Democracy is exposing a bigger problem due to the economic inequality caused by the majority rule and the capitalist economic system. Popular democracy, in which all the masses are equally qualified as sovereigns, is a structure in which cunning politicians can easily seize power if the voters are not wise. Isonomia is a system in which free people who solve economic problems on their own and have honesty, courage, dedication, sacrifice and sincerity set laws with the same qualifications, and keep the laws themselves, is a system that depends heavily on the conscience and virtue of free people. Modern popular democracy embodies the absolute equality of the sovereign regardless of economic power, but without the spirit of sacrifice and dedication to the community, those who can win popularity by wrapping themselves up as if they are sacrificial and capable people may seize power. This study presents a service-oriented democracy as a system that can maintain the merits of modern popular democracy while embodying the essence of isonomia. The system was implemented focusing on the qualifications for virtue, such as honesty, courage, sacrifice, integrity, etc., fair to all regardless of wealth. Human imperfections have been supplemented by the use of artificial intelligence. The assumption about the nature of the sovereign and public officials' agents was newly established, and the winner-take-allism problem was solved. This study proved that both the philosophy of Isonomia and the merits of Democracy can be realized through service-oriented democracy based on the common principle of humanity and the philosophy of service. Service-oriented democracy can be called revision democracy.

• Journal of Service Research and Studies
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• v.11 no.2
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• pp.1-19
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• 2021

This study was conducted to derive a model of a sustainable politics and administration system that will enhance human happiness. A new long-term sustainable development model has been established based on the experience of the politics and administration system over the past thousands of years. Currently, the democratic political system and the bureaucratic administrative system dominate, but they are facing many problems. In this study, we analyzed the politics and administration system experienced by human society, and derived a model of a politics and administration system that is ideal for the present and future societies and is sustainable in the long term. The necessary condition should be a model that can solve the problems of the current politics and administration system. It must be a model that is faithful to the characteristics and essence of modern society. And as a sufficient condition to ensure long-term sustainability, it must be based on the common principles of human society. After analyzing the problems of the current system and analyzing the conditions required for the new system, the axioms that are the basis of the politics and administration system were presented. Based on the axioms, the structure and operation model of a new politics and administration system were derived. The derived model was named as a servicism politics and administration system. It is a dynamic model in which two opposing opponents recognize each other's contradictions and balance them dialectically in the space-time dimension.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.15-30
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• 2023

Recently, various services using artificial intelligence(AI) are emerging in the media field as well However, most of the video editing, which involves finding an editing point and attaching the video, is carried out in a passive manner, requiring a lot of time and human resources. Therefore, this study proposes a methodology that can detect the edit points of video according to whether person in video are spoken by using Video Swin Transformer. First, facial keypoints are detected through face alignment. To this end, the proposed structure first detects facial keypoints through face alignment. Through this process, the temporal and spatial changes of the face are reflected from the input video data. And, through the Video Swin Transformer-based model proposed in this study, the behavior of the person in the video is classified. Specifically, after combining the feature map generated through Video Swin Transformer from video data and the facial keypoints detected through Face Alignment, utterance is classified through convolution layers. In conclusion, the performance of the image editing point detection model using facial keypoints proposed in this paper improved from 87.46% to 89.17% compared to the model without facial keypoints.