• Geomechanics and Engineering
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• v.21 no.2
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• pp.103-109
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• 2020

The inflow rate is of interest in the design of underground structures such as tunnels and buried pipes below the groundwater table. Soil permeability governing the inflow rate significantly affects the hydro-geological behavior of soils but is difficult to estimate due to its wide range of distribution, nonlinearity and anisotropy. Volume changes induced by stress can cause nonlinear stress-strain behavior, resulting in corresponding permeability changes. In this paper, the nonlinearity and anisotropy of permeability are investigated by conducting Rowe cell tests, and a nonlinear permeability model considering anisotropy was proposed. Model modification and parameter evaluation for field application were also addressed. Significance of nonlinear permeability was illustrated by carrying out numerical analysis of a tunnel. It is highlighted that the effect of nonlinear permeability is significant in soils of which volume change is considerable, and particularly appears in the short-term flow behavior.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.689-698
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• 2020

The aim of this article is to determine the influence of factors on the capital structure of construction companies listed on the Hanoi Stock Exchange. The data of the article were collected and calculated from the financial statements of 54 construction companies listed on Hanoi Stock Exchange from 2012 to 2019. With the application of E-view software in quantitative analysis to build panel data regression model (panel data), the article has built a regression model to determine the relationship of intrinsic factors affecting the capital structure of construction companies listed on Hanoi Stock Exchange. In the study, dependent variable is capital structure, determined by the debt-to-equity ratio. Profitability, coefficient of solvency, size, loan interest rate, structure of tangible assets, and growth are independent variables. The results showed that the two factors of growth and firm size positively affect the capital structure, the profitability factor has the opposite effect on capital structure. Factors of short-term debt solvency, average loan interest rate and tangible asset structure have no correlation with capital structure. The findings of this article are useful for business administrators, helping business managers make the right financial decisions to make capital structure decisions in their own conditions.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.23-34
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• 2020

The paper revisits the author's previous paper to examine short-run and long-run dynamic relationships between macroeconomic variables and stock prices in Korea. The data is updated to the period for which monthly data are available from January 1986 to June 2018 (390 observations) retrieved from the Bank of Korea. The results of Johansen cointegration test indicate that at least one cointegrating equation exists, confirming there is a long-run equilibrium relationship between macroeconomic variables and stock prices in Korea. The results of vector error correction estimates confirm that: 1) the coefficient of the error correction term is significant with a negative sign, which is, a long-run dynamic relationship is observed between macroeconomic variables and stock prices; 2) for short-run dynamics, the nominal exchange rate of the Korean won per the US dollar is positively related to stock prices, while interest rates are negatively related to stock prices in the short-run; 3) the coefficient of global financial crises is insignificant, that is, the changes of stock prices are determined largely by their own dynamics in the model. The results suggest only that the global financial crises neither cause instability in the cointegrating vector, nor affect significant changes in the endogenous variables in the model.

• The Journal of Industrial Distribution & Business
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• v.9 no.8
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• pp.41-50
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• 2018

Purpose - As an important participant in the financial markets, the commercial bank will be impacted by the interest rate marketization. Owing to the special condition of China, this paper tries to explore the impact of operating mechanisms between interest rate marketization and the profitability of the commercial Bank. Research design, data and methodology - This paper applies time series data from 2005 to 2016. Due to the short period of time series, autocorrelation often occurs. Therefore, the fully modified least squares(FMOLS) will be used to conduct an empirical analysis. The reason is that it can move off the autocorrelation between variables and disturbance term. And FMOLS also can make estimated cointegrating parameters closed to normal distribution. More importantly, in order to avoid spurious regressions, the Augmented Dickey-Fuller Test will be used to verify the stationarity of all variables. The total return of asset is treated as the profitability of commercial bank. The net interest spread is treated as a measurement of interest rate marketization. Both are regarded as dependent variables. The non-interest income or gross revenues and impaired loans or gross loans are treated as independent variables. The sixteen representative listed commercial banks are divided into three categories (state-owned, share-holding and city-owned) to conduct an estimation. Results - Via empirical analysis, the findings show that the net interest spread has a positive effect on the profitability of the commercial bank. More specifically, 1% increase in the net interest spread will lead 0.157% increase in the profitability of state-owned commercial bank, 0.269% increase in the profitability of share-holding commercial bank and 0.263% increase in the profitability of city-owned commercial bank. If regarding the sixteen listed commercial city as a whole, 1% increase in the net interest spread will lead 0.267% increase in the profitability of the commercial bank. Conclusions - As the interest rate marketization, the importance of interest rate on the profitability of commercial bank has become more and more significant. The empirical evidences also prove that the net interest spread can bring about the change of the commercial bank's profitability. Therefore, policy-makers of commercial banks should fully understand the operating mechanism between them.

• Journal of Cadastre & Land InformatiX
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• v.52 no.2
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• pp.211-231
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• 2022

This study attempted to identify the effects of macroeconomic variables such as the All Industry Production Index, Consumer Price Index, CD Interest Rate, and KOSPI on apartment lease prices divided into nationwide, Seoul, metropolitan, and region, and to present a methodological prediction model of apartment lease prices by region using Long Short Term Memory (LSTM). According to VAR analysis results, the nationwide apartment lease price index and consumer price index in Lag1 and 2 had a significant effect on the nationwide apartment lease price, and likewise, the Seoul apartment lease price index, the consumer price index, and the CD interest rate in Lag1 and 2 affect the apartment lease price in Seoul. In addition, it was confirmed that the wide-area apartment jeonse price index and the consumer price index had a significant effect on Lag1, and the local apartment jeonse price index and the consumer price index had a significant effect on Lag1. As a result of the establishment of the LSTM prediction model, the predictive power was the highest with RMSE 0.008, MAE 0.006, and R-Suared values of 0.999 for the local apartment lease price prediction model. In the future, it is expected that more meaningful results can be obtained by applying an advanced model based on deep learning, including major policy variables

• Journal of Digital Convergence
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• v.18 no.7
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• pp.223-228
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• 2020

The stock price reflects people's psychology, and factors affecting the entire stock market include economic growth rate, economic rate, interest rate, trade balance, exchange rate, and currency. The domestic stock market is heavily influenced by the stock index of the United States and neighboring countries on the previous day, and the representative stock indexes are the Dow index, NASDAQ, and S & P500. Recently, research on stock price analysis using stock news has been actively conducted, and research is underway to predict the future based on past time series data through artificial intelligence-based analysis. However, even if the stock market is hit for a short period of time by the forecasting system, the market will no longer move according to the short-term strategy, and it will have to change anew. Therefore, this model monitored Samsung Electronics' stock data and news information through text mining, and presented a predictable model by showing the analyzed results.

• Journal of Korean Institute of Industrial Engineers
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• v.14 no.1
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• pp.91-101
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• 1988

Break-even analysis is a simple and useful tool in decisions and planning activities though its use is somewhat limited to short-term analysis. The subject is discussed in the fields of engineering economics, production management, cost and managerial accounting, finance, marketing, and so on. Conventional break-even analysis suits the case of stable price and low interest rate. In this paper, we try to overcome the limit by considering following factors, namely, time value of money, depreciation, tax, and capital gains. Also, considering learning effect, we increase applicability to a new project which raises certain changes such as a replacement of production process, an employee turnover, etc. Thus, we suggest a model which has a dynamic break-even quantity per period for the project. Furthermore, we examine the effect of inflation in break-even analysis.

• KDI Journal of Economic Policy
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• v.12 no.4
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• pp.3-20
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• 1990

The multisector model is designed to analyze and forecast structural change in industrial output, employment, capital and relative price as well as macroeconomic change in aggregate income, interest rate, etc. This model has 25 industrial sectors, containing about 1,300 equations. Therefore, this model is characterized by detailed structural disaggregation at the sectoral level. Individual industries are based on many of the economic relationships in the model. This is what distinguishes a multisector model from a macroeconomic model. Each industry is a behavioral agent in the model for industrial investment, employment, prices, wages, and intermediate demand. The strength of the model lies in the simulating the interactions between different industries. The result of its simulation will be introduced in the next paper. In this paper, we only introduce the structure of the multisector model and the coefficients of the equations. The multisector model is a dynamic model-that is, it solves year by year into the future using its own solutions for earlier years. The development of a dynamic, year-by-year solution allows us to combine the change in structure with a consideration of the dynamic adjustment required. These dynamics have obvious advantages in the use of the multisector model for industrial planning. The multisector model is a medium-term and long-term model. Whereas a short-term model can taken the labor supply and capital stock as given, a long-term model must acknowledge that these are determined endogenously. Changes in the medium-term can be analyzed in the context of long-term structural changes. The structure of this model can be summarized as follow. The difference in domestic and world prices affects industrial structure and the pattern of international trade; domestic output and factor price affect factor demand; factor demand and factor price affect industrial income; industrial income and relative price affect industrial consumption. Technical progress, as measured in terms of total factor productivity and relative price affect input-output coefficients; input-output coefficients and relative price determine the industrial input cost; input cost and import price determine domestic price. The differences in productivity and wage growth among different industries affect the relative price.

• Journal of Digital Convergence
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• v.19 no.8
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• pp.319-325
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• 2021

With the advancement of wireless technology and the rapid growth of the infrastructure of mobile communication technology, systems applying AI-based platforms are drawing attention from users. In particular, the system that understands users' tastes and interests and recommends preferred items is applied to advanced e-commerce customized services and smart homes. However, there is a problem that these recommendation systems are difficult to reflect in real time the preferences of various users for tastes and interests. In this research, we propose a Fuzzy-AHP-based movies recommendation system using the Gated Recurrent Unit (GRU) language model to address a problem. In this system, we apply Fuzzy-AHP to reflect users' tastes or interests in real time. We also apply GRU language model-based models to analyze the public interest and the content of the film to recommend movies similar to the user's preferred factors. To validate the performance of this recommendation system, we measured the suitability of the learning model using scraping data used in the learning module, and measured the rate of learning performance by comparing the Long Short-Term Memory (LSTM) language model with the learning time per epoch. The results show that the average cross-validation index of the learning model in this work is suitable at 94.8% and that the learning performance rate outperforms the LSTM language model.

• The Journal of the Convergence on Culture Technology
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• v.5 no.2
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• pp.183-188
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• 2019

This study analyzed the effects of short-term interest rates, exchange rates and international oil prices on international grain prices using the EGARCH-GED model. The yield before one month of the international grain prices itself was found to have a significant effect on international grain prices for most periods. During the entire analysis period, none of the economic variables appeared to have a significant effect on international grain prices, whereas during the exchange fall period, only oil prices were shown to have a significant effect on international grain prices. In addition, during the pre-crisis period, interest rates, exchange rates and oil prices did not all have a significant effect, but during the post-crisis period only oil prices had a significant effect on international grain prices. It turns out that the factors affecting international grain prices are changing with the passage of time.