• Environmental and Resource Economics Review
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• v.28 no.2
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• pp.307-326
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• 2019

The electric vehicle is a representative measure to reduce greenhouse gas and local air pollutants in the transportation sector. Most countries provide purchase subsidies and tax reductions to promote electric vehicle sales. The electric vehicles have been considered as zero-emission vehicles(ZEV) in light of the fact that there has been no pollutant emission during driving. However, recent studies have pointed out that the pollutant emitted from the process of generating electricity used for charging the electric vehicles need to be treated as emissions of the electric vehicles. Furthermore, the environmental benefits of electric vehicle replacing the internal combustion vehicle vary with the power mix. In line with the recent studies, this study analyzes the impact of electric vehicles based on the current power mix and future energy transition scenarios in Korea. To estimate the precise air pollutants emission profile, this study uses hourly electricity generation and TMS emission data for each power plant from 2015 to 2016. The estimation results show that the electric vehicles under the current power mix generate the environmental benefits of only -0.41~10.83 won/km. Also, we find that the environmental benefit of electric vehicle will significantly increase only when the ratio of the coal-fired power plant is reduced to a considerable extent.

• Tunnel and Underground Space
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• v.33 no.6
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• pp.483-494
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• 2023

Measurement of the physical properties of rocks or minerals is an important factor in determining the distribution of the underground medium as well as mineral resource investigations. Resistivity and induced polarization, which are widely used in Korea, are methods for measuring electrical properties, which are representative properties of obtaining subsurface information. In order to precisely analyze the exploration data obtained from various sites, it is important to accurately measure the material properties. Electrical properties of rock is measured using two-electrode or four-electrode method. Compared to the four-electrode method, the two-electrode method is generally used because it is very easy to contact the sample and the electrode, but there is a problem in that the impedance of the electrode and the sample is measured together. In this study, the time-domain the induced polarization effects were measured using the 2-electrode method and the 4-electrode method for artificial samples mixed with graphite and cement having induced polarization characteristics, and the results were compared. Although the 4-electrode method has difficulties in installing potential electrodes, it was confirmed that it is effective in measuring electrical properties because it can reduce the problem caused by the impedance of potential electrodes compared to the 2-electrode method.

• Journal of the Korean earth science society
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• v.42 no.2
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• pp.175-184
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• 2021

Fold axis of fold, a representative ductile deformation structure, is important for collecting information on the 3D fold structure and the orientation of maximum horizontal principal stress at the time of deformation. For this reason, several fold axis measurement methods based on the fold-related structural elements have been suggested and used even in areas where it is impossible to measure it directly. Thus, these various measurement methods are briefly introduced here, and the measured data with different methods are compared to estimate these methods' reliability. For this purpose, we acquired fold axes at six sites across the Manhang formation of the Pyeongan supergroup and limestones of the Joseon supergroup in Danyang, Chungcheongbuk-do, where fold structures are well developed. The data from the different methods are generally consistent, indicating practical applicability. Most of the fold axes from the measured sites show NNNE or NE trends indicating WNW-ESE or NW-SE trending maximum horizontal principal stress, except for the one site with a WNW trend. The WNW-ESE trending fold axis might be related to a different orogeny or secondary folding. The minor difference in the trends between N-NNE and NE was interpreted as being due to different scale; however, further research is needed to confirm this.

• Journal of the Korean GEO-environmental Society
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• v.20 no.1
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• pp.67-74
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• 2019

Frost heave is one of the representative engineering characteristics in cold regions. In South Korea, which is located in seasonal frost area, structural damage caused by frost heave and thaw happens and the need for research on the frost heave is increasing. In this paper, newly developed transparent temperature-controllable cell is used to focus on the frost heave. Frost susceptible artificial soil is used to analyze water intake rate which is one of the important factors in frost susceptibility criteria. Frost heave rate and water intake rate have similar behavior after heave by freezing of pore water converges. O-ring installed in the upper pedestal to measure water intake rate generates side friction between the inner wall of the freezing cell and O-ring, thereby hindering frost heave. Therefore, the frost susceptibility criteria using the water intake rate is not reliable. It is appropriate to use frost heave rate which has similar behavior with water intake rate. Frost heave tests were performed under two different specimen heights. Overburden pressure, temperature gradient and dry unit weight were set under similar state. Based on laboratory testing results, frost heave is independent on the specimen height.

• Smart Media Journal
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• v.12 no.10
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• pp.93-101
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• 2023

Climate change has emerged as a global problem, with frequent temperature increases, droughts, and floods, and it is predicted that it will have a great impact on the characteristics and productivity of crops. Cnidium officinale is used not only as traditionally used herbal medicines, but also as various industrial raw materials such as health functional foods, natural medicines, and living materials, but productivity is decreasing due to threats such as continuous crop damage and climate change. Therefore, this paper proposes a model that can predict the physiologically active ingredient index according to the climate change scenario of Cnidium officinale, a representative medicinal crop vulnerable to climate change. In this paper, data was first augmented using the CTGAN algorithm to solve the problem of data imbalance in the collection of environment information, physiological reactions, and physiological active ingredient information. Column Shape and Column Pair Trends were used to measure augmented data quality, and overall quality of 88% was achieved on average. In addition, five models RF, SVR, XGBoost, AdaBoost, and LightBGM were used to predict phenol and flavonoid content by dividing them into ground and underground using augmented data. As a result of model evaluation, the XGBoost model showed the best performance in predicting the physiological active ingredients of the sacrum, and it was confirmed to be about twice as accurate as the SVR model.

• Journal of Internet Computing and Services
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• v.8 no.3
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• pp.19-32
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• 2007

This paper present a new face recognition method based on LVQ neural net to construct a real time face recognition system. The previous researches which used PCA, LDA combined neural net usually need much time in training neural net. The supervised LVQ neural net needs much less time in training and can maximize the separability between the classes. In this paper, the proposed method transforms the input face image by PCA and LDA sequentially into low-dimension feature vectors and recognizes the face through LVQ neural net. In order to make the system robust to external light variation, light compensation is performed on the detected face by max-min normalization method as preprocessing. PCA and LDA transformations are applied to the normalized face image to produce low-level feature vectors of the image. In order to determine the initial centers of LVQ and speed up the convergency of the LVQ neural net, the K-Means clustering algorithm is adopted. Subsequently, the class representative vectors can be produced by LVQ2 training using initial center vectors. The face recognition is achieved by using the euclidean distance measure between the center vector of classes and the feature vector of input image. From the experiments, we can prove that the proposed method is more effective in the recognition ratio for the cases of still images from ORL database and sequential images rather than using conventional PCA of a hybrid method with PCA and LDA.

• The Journal of Korean Philosophical History
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• no.37
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• pp.47-70
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• 2013

The purpose of this paper is to figure out T'oegye's philosophy and its characteristics in comparison with Zhuzi's. T'oegye is well-known as the representative of Neo-confucianism in Korea. But his posterior scholars and even contemporary scholars have various viewpoints about his philosophy. So they give him some different evaluation. After Zhuzi's death 300 years later, T'oegye has accepted Zhuzi's philopophical thoughts. In addition, he has added his own philosophical insights on them. First, he indicates concretely the metaphysical activity of li through lidong that Zhuzi has mentioned in some measure. Second, under the ontological aspect of li, he explains that Four beginnings come from li. It implies that li manifests and qi follows. Finally he points out lidao--i.e. li manifests itself, about wuge in his epistemology. Here we can say that whatever his metaphysics/the theory of mind and heart, and epistemology, the whole system of T'oegye's philosophy has its theoretical coherence. He has succeeded Zhuzi's philopophical thoughts thoroughly and furthermore developed Neo-confucian theory in East Asia that has not made before.

• Journal of Korea Water Resources Association
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• v.56 no.12
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• pp.845-853
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• 2023

Recently, along with the increase in chemical accidents, the number of accidents-related disasters has been increasing continuously since 2012, and when looking at the hydrogen fluoride incident which is a representative example of domestic chemical incidents, there is insufficient technology applicable to the incident site. The result was that the damage spread. Therefore, in this paper, we will adapt the water pollution accident response system to a location-based approach, and introduce a measurement method for alternative index tracking using a GPS electronic floater of a location-based index measurement method for real-time response in the water environment when a chemical incident occurs. The research target area is Gumi City, which is the area where the hydrogen fluoride incident occurred, and Gamcheon is selected, and alternative tracking using GPS electronic floater is conducted in the corresponding target area through water quality and flow measurement. As a result, it is possible to measure water quality and flow at the same time in tracker experiments using GPS electronic floater based on the research results, it is believed that using GPS electronic floater will be of great help in disaster response systems for spill incidents in the river.

• Journal of Korea Multimedia Society
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• v.14 no.10
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• pp.1252-1261
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• 2011

In this paper, we propose the comparison method of pattern similarity for video segmentation algorithm. The shot boundary type is categorized as 2 types, abrupt change and gradual change. The representative examples of gradual change are dissolve, fade-in, fade-out or wipe transition. The proposed method consider the problem to detect shot boundary as 2-class problem. We concentrated if the shot boundary event happens or not. It is essential to define similarity between frames for shot boundary detection. We proposed 2 similarity measures, within similarity and between similarity. The within similarity is defined by feature comparison between frames belong to same shot. The between similarity is defined by feature comparison between frames belong to different scene. Finally we calculated the statistical patterns comparison between the within similarity and between similarity. Because this measure is robust to flash light or object movement, our proposed algorithm make contribution towards reducing false positive rate. We employed color histogram and mean of sub-block on frame image as frame feature. We performed the experimental evaluation with video dataset including set of TREC-2001 and TREC-2002. The proposed algorithm shows the performance, 91.84% recall and 86.43% precision in experimental circumstance.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.307-332
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• 2022

One of the most intensively conducted research areas in business application study is a bankruptcy prediction model, a representative classification problem related to loan lending, investment decision making, and profitability to financial institutions. Many research demonstrated outstanding performance for bankruptcy prediction models using artificial intelligence techniques. However, since most machine learning algorithms are "black-box," AI has been identified as a prominent research topic for providing users with an explanation. Although there are many different approaches for explanations, this study focuses on explaining a bankruptcy prediction model using a counterfactual example. Users can obtain desired output from the model by using a counterfactual-based explanation, which provides an alternative case. This study introduces a counterfactual generation technique based on a genetic algorithm (GA) that leverages both domain knowledge (i.e., causal feasibility) and feature importance from a black-box model along with other critical counterfactual variables, including proximity, distribution, and sparsity. The proposed method was evaluated quantitatively and qualitatively to measure the quality and the validity.