• Journal of Distribution Science
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• v.12 no.7
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• pp.45-51
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• 2014

Purpose - This study aims to explore the success of Lotte Mart in the global market, as well as examining the factors related to its entry methods. Research design, data, and methodology - This study analyzed the differences between Lotte Mart and E-mart in terms of their market entry methods, based on references and secondary data. This study is based on qualitative research that analyzes actual cases. Based on the results, this study analyzed and discussed actual cases based on references and secondary data, including newspaper interviews on Lotte Mart. Results - Lotte Mart succeeded in adapting to local markets it did this by ensuring the use of both mergers and acquisitions (M&As) and greenfield methods. In contrast, E-mart utilized only greenfield methods. Conclusions - The findings of this study may not be generalized to all industries, as only Lotte Mart was examined using the case analysis method. Therefore, the successful market entry modes of various companies should be explored in terms of FDI.

• International Journal of Automotive Technology
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• v.8 no.5
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• pp.637-650
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• 2007

A new on-line fault detection and isolation(FDI) scheme has been proposed for engines using an adaptive neural network classifier; this paper investigates the robustness of this scheme by evaluating in a wide range of operational modes. The neural classifier is made adaptive to cope with the significant parameter uncertainty, disturbances, and environmental changes. The developed scheme is capable of diagnosing faults in the on-line mode and can be directly implemented in an on-board diagnosis system(hardware). The robustness of the FDI for the closed-loop system with crankshaft speed feedback is investigated by testing it for a wide range of operational modes, including robustness against fixed and sinusoidal throttle angle inputs, change in load, change in an engine parameter, and all changes occurring simultaneously. The evaluations are performed using a mean value engine model(MVEM), which is a widely used benchmark model for engine control system and FDI system design. The simulation results confirm the robustness of the proposed method for various uncertainties and disturbances.

• The Journal of Asian Finance, Economics and Business
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• v.5 no.2
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• pp.15-24
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• 2018

The study examines the magnitude of economic spillover and the impact of foreign direct investment (FDI) inflows on the efficiency of the bank industry in China. This study employs unit root tests, cointegration tests and cointegrating regression analysis, including fully modified ordinary least squares (FMOLS), canonical cointegrating regression (CCR) and dynamic OLS (DOLS) to test the proposed hypotheses. The sample is restricted to the period of time in which monthly data is available and comparable among variables for the period from January 2002 to October 2013 (142 observations). All of the time series data was collected and retrieved from the People's Bank of China, China Monthly Statistics from the National Bureau of Statistics of China, and International Financial Statistics database from International Monetary Fund. The results of the Johansen cointegration test suggest that there is a long-run equilibrium relationship between FDI inflows, foreign exchange rate and banks performance in China. The results of cointegrating regression analysis using FMOLS, CCR and DOLS suggest that M2 supply and FDI inflows are significant at the 0.01 level. The results confirm that FDI inflows in the banking sector are positively related to the increase of banks productivity and performance and short-term loans in China. However, the results suggest that Chinese Yuan currency exchange rate to U.S. dollar is not significant in the banking and financial industry of China.

• Ocean Systems Engineering
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• v.12 no.1
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• pp.87-142
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• 2022

An analysis for the computation of Fatigue Damage Index (FDI) under the effects of the various combination of the ocean loads like random waves, current, platform motion and VIV (Vortex Induced Vibration) for a certain design water depth is a critically important part of the analysis and design of the marine riser platform integrated system. Herein, a 'Computer Simulation Model (CSM)' is developed to combine the advantages of the frequency domain and time domain. A case study considering a steel catenary riser operating in 1000 m water depth has been conducted with semi-submersible. The riser is subjected to extreme environmental conditions and static and dynamic response analyses are performed and the Response Amplitude Operators (RAOs) of the offshore platform are computed with the frequency domain solution. Later the frequency domain results are integrated with time domain analysis system for the dynamic analysis in time domain. After that an extensive post processing is done to compute the FDI of the marine riser. In the present paper importance is given to the nature of the current profile and the VIV. At the end we have reported the detail results of the FDI comparison with VIV and without VIV under the linear current velocity and the FDI comparison with linear and power law current velocity with and without VIV. We have also reported the design recommendations for the marine riser in the regions where the higher fatigue damage is observed and the proposed CSM is implemented in industrially used standard soft solution systems (i.e., OrcaFlex^*TM and Ansys AQWA^**TM), Ms-Excel^***TM, and C++ programming language using its object oriented features.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.83-91
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• 2021

Health is an outset of psychological, social, financial, and physical state. Several macroeconomic factors are entangled with health and mortality. Infant mortality and life expectancy are two keyguard on demographic research context on last few decades. On the other hand, foreign inflows play an unprecedent role for raising economic circulation and providing more opportunities to build a better society. The study aims to investigate the relationship between foreign direct investment (FDI), economic growth, and Bangladesh's health. This study employs time-series data from 1980 to 2018. Results show, with Auto-regressive Distribute Lag (ARDL) model, that there is significant cointegration among variables. Foreign investment and economic output relate significantly and positively to health. On the contrary, education is quasi-linked with a different sign-on different model. For model validation, pitfalls of time-series multicollinearity, heteroscedasiticy, and autocorrelation are not present. Also, CUSUM and CUSUMSQ tests are validating the model as stable and fit for future prediction. Medical assessment and education need more attention from the government as well as the private sector. FDI can play a catalyst role for improving the health sector, raising opportunity in educating and creating a better lifestyle. In order to optimize foreign investment, the government should implement necessary reforms and policies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2168-2187
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• 2021

The smart grid replaces the traditional power structure with information inventiveness that contributes to a new physical structure. In such a field, malicious information injection can potentially lead to extreme results. Incorrect, FDI attacks will never be identified by typical residual techniques for false data identification. Most of the work on the detection of FDI attacks is based on the linearized power system model DC and does not detect attacks from the AC model. Also, the overwhelming majority of current FDIA recognition approaches focus on FDIA, whilst significant injection location data cannot be achieved. Building on the continuous developments in deep learning, we propose a Deep Learning based Locational Detection technique to continuously recognize the specific areas of FDIA. In the development area solver gap happiness is a False Data Detector (FDD) that incorporates a Convolutional Neural Network (CNN). The FDD is established enough to catch the fake information. As a multi-label classifier, the following CNN is utilized to evaluate the irregularity and cooccurrence dependency of power flow calculations due to the possible attacks. There are no earlier statistical assumptions in the architecture proposed, as they are "model-free." It is also "cost-accommodating" since it does not alter the current FDD framework and it is only several microseconds on a household computer during the identification procedure. We have shown that ANN-MLP, SVM-RBF, and CNN can conduct locational detection under different noise and attack circumstances through broad experience in IEEE 14, 30, 57, and 118 bus systems. Moreover, the multi-name classification method used successfully improves the precision of the present identification.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.109-114
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• 2020

The aim of this study is to develop basic artificial neural network models in forecasting the in-sample gross domestic product (GDP) of Malaysia. GDP is one of the main indicators in presenting the macro economic condition of a country as set by the world authority bodies such as the World Bank. Hence, this study uses an artificial neural network-based approach to make predictions concerning the economic growth of Malaysia. This method has been proposed due to its ability to overcome multicollinearity among variables, as well as the ability to cope with non-linear problems in Malaysia's growth data. The selected inputs and outputs are based on the previous literatures as well as the economic growth theory. Therefore, the selected inputs are exports, imports, private consumption, government expenditure, consumer price index (CPI), inflation rate, foreign direct investment (FDI) and money supply, which includes M1 and M2. Whilst, the output is real gross domestic product growth rate. The results of this study showed that the neural network method gives the smallest value of mean error which is 0.81 percent with a total difference of 0.70 percent. This implies that the neural network model is appropriate and is a relevant method in forecasting the economic growth of Malaysia.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.5
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• pp.285-294
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• 2022

Using the ARDL approach, this study examined the impact of macro factors on Vietnam's stock market in the short and long run from 2010 to 2021. The State Bank of Vietnam and the International Monetary Fund provided time series data for this study. Research results show that in the long run, money supply and exchange rate respectively affect the stock market. The money supply had a positive effect on the VN-Index, while the exchange rate showed the opposite effect. However, the study did not find a relationship between world oil price and interest rates on VN-Index in the long run. On the other hand, in the short term, there are relationships between variables; specifically, interest rates and exchange rates have a negative impact on the VN-Index, while the world oil price and the fluctuation of money supply M2 of the previous one and two months showed an impact in the same direction on this index. The differences in the regression results on the impact of exchange rate and oil price on the VN-Index compared to previous studies come from the characteristics of Vietnam's stock market, with the large capitalization of companies in the oil and gas sector, and the structure of Vietnam's economy with export heavily depends on FDI sector.

• Proceedings of the KIEE Conference
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• 2002.07b
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• pp.1181-1183
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• 2002

전력수요의 증대로 발전소 운전에 핵심적인 역할을 담당하는 제어시스템의 중요성이 한층 더 강조되었다. 본 연구에서는 발전기 전압제어를 담당하는 여자시스템의 독특한 형태인 복권형 P-bar 여자시스템과 De-excitation 설비에 대하여 기술하고, Y원자력 발전소에서 경험하였던 De-excitation 설비에 계자방전 인덕터(FDI) 사용함으로써 발전기 계자권선에 축적된 에너지를 방전하는데 계자권선 시정수인 Tdo'이 설계치보다 너무 오래 지속되는 문제점을 검토하고, 이를 해결하기 위한 개선방안을 제시하였으며 이를 유사 발전소에 적용한 결과와 그 효용성을 보였다

• Journal of Technologic Dentistry
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• v.41 no.3
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• pp.187-193
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• 2019

Purpose: The purpose of this study was to compare two-dimensional fitness of the monolithic zirconia prosthesis by using different type of scanner. Methods: No. 26 abutment tooth of FDI system was selected for the study. Using the extraoral scanner and intraoral scanner, the abutment tooth was scanned 10 times and the scanned files were saved as STL files. CAD/CAM system was used to produce the monolithic zirconia prosthesis. marginal and internal gap of the monolithic zirconia prosthesis were measured by digital microscope(x160) and applied silicone replica technique was applied. t-test, a statistical software, was used to perform data analysis. Results: Marginal gap $mean{\pm}SD$ of the monolithic zirconia prosthesis was $33{\pm}7.5{\mu}m$ with extra oral scanner and $34.7{\pm}11.1{\mu}m$ with intraoral scanner. axial gap mean was $40.5{\pm}3.5{\mu}m$ with extra oral scanner and $44.6{\pm}11.6{\mu}m$ with intraoral scanner. occlusal gap mean was $110.1{\pm}25.4{\mu}m$ with extra oral scanner and $64{\pm}9.7{\mu}m$ with intraoral scanner. Conclusion: In this study, fabricating zirconia prosthesis with different type of scanner was clinically applicable.