• Journal of the Korean Society for Railway
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• v.11 no.1
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• pp.45-53
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• 2008

With the growing international consensus regarding sustainable development of transportation, the plan of transportation infrastructure needs to meet various requirements toward enhancing environmental conditions. Accordingly, the upcoming long-term plan of high-speed rail network has to be reflecting the sustainability of transportation systems. In this paper, we demonstrate an application of methodologies based on multi-attribute utility theory for determining priorities of sustainable high-speed rail investment. The proposed methodologies identify indicators for sustainable transportation systems such as economic, environmental, and social ones and then, evaluate priority for planning a long-term sustainable high-speed rail network by comparing the relative importance among indicators. This will help transportation agencies to prioritize high-speed rail investment toward sustainable transportation systems.

• Journal of the Korean Geographical Society
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• v.36 no.4
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• pp.402-417
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• 2001

This study empahsized the nature of spatial patterns, characteristics and embeddeness of foreign business service firms in Korea utilizing questionnaire survey and interview data. Foreign business services firms are active in forming interfirm networks with clients and supply firms in Korea for widening the market share in Korea. But a low proportion of foreign firms is engaged in academies-industry linkages, government organizations, research institutes, and trade associations. Knowledge transfer and interaction also shows low level of network and the regional development of foreign firms is still in the process of developing, not quite embedded yet. Policy guidances and instituional supports are very essential to strenthen interfirm network and collective learning process of foreing firms in Korea lather than mechanical accumulation of investments. Thus, regional foreign direct investment policy should be targeted towards the incrementation of the potential of foreign firms as a knowledge-intensive industry.

• Korea Trade Review
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• v.46 no.1
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• pp.169-187
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• 2021

This paper analyzes the feasibility of using machine learning and deep learning methods to forecast the income and employment using the strategic industries as well as investment, export, and exchange rates. The decision tree, artificial neural network, support vector machine, and deep learning models were used to forecast the income and employment in Busan. The following were the main findings of the comparison of their predictive abilities. First, the decision tree models predict the income and employment well. The forecasting values for the income and employment appeared somewhat differently according to the depth of decision trees and several conditions of strategic industries as well as investment, export, and exchange rates. Second, since the artificial neural network models show that the coefficients are somewhat low and RMSE are somewhat high, these models are not good forecasting the income and employment. Third, the support vector machine models show the high predictive power with the high coefficients of determination and low RMSE. Fourth, the deep neural network models show the higher predictive power with appropriate epochs and batch sizes. Thus, since the machine learning and deep learning models can predict the employment well, we need to adopt the machine learning and deep learning models to forecast the income and employment.

• Korea Trade Review
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• v.45 no.6
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• pp.23-43
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• 2020

This study aims at analyzing the interactions between two of the most significant trade stakeholders in Korea, the Trade Ministry and the Legislature, using text network analysis. Tackling seven Action and Plan Reports for Requests from Parliamentary Inspection released by the National Assembly, this paper conducts a topic modelling analysis, particularly focusing on the reports for the three trade-related institutes: the MOTIE headquarter, Korea Trade Insurance Corporation, Korea Trade and Investment Promotion Agency. According to the analysis, such traditional topics of the MOTIE as enterprise, industry, business, management, development were frequently appeared in the reports. Trade-related topics including export, trade, commerce, investment, overseas, domestic, dispute, cooperation, efficiency, negotiation, service, promotion were repeatedly shown. Lastly, a case study on 2019 Parliamentary Inspection Report showed specific trade-related topics and relevant contents that raised issues in that year. This analysis implies that the text data driven from the Parliamentary Inspection Reports between the MOTIE and the National Assembly, can be established as so called 'trade policy information system' which are valuable not only for the two but also the rest of the trade stakeholders in Korea.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.303-309
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• 2022

Software Defined Networking (SDN) is a novel approach that have accelerated the development of numerous technologies such as policy-based access control, network virtualization, and others. It allows to boost network architectural flexibility and expedite the return on investment. However, this increases the system's complexity, necessitating the expenditure of dollars to assure the system's security. Network Function Virtualization (NFV) opens up new possibilities for network engineers, but it also raises security concerns. A number of Internet service providers and network equipment manufacturers are grappling with the difficulty of developing and characterizing NFVs and related technologies. Through Moodle's efforts to maintain security, this paper presents a detailed review of security-related challenges in software-defined networks and network virtualization services.

• East Asian Economic Review
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• v.20 no.2
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• pp.229-275
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• 2016

We study the effect of the high-skilled emigration rate on the growth rate of the source countries. We incorporate the foreign direct investment and the policy variables into the panel model and also their interactions with the high-skilled emigration rate, as they are related to the network externality that may be created by the high-skilled emigrants working abroad. We apply the static fixed-effects model and compare it with the results obtained in the dynamic panel model with system generalized methods of moments estimators. We find the negative effect of the high-skilled emigration rate by itself and in its interaction with the foreign direct investment only in the dynamic model. However, we find positive coefficient for the interaction of the high-skilled emigration rate and the civil liberties index, which holds across the static and dynamic specifications. This implies that the effect of the high-skilled emigration rate on the growth rate of the source countries can be positive, and the extent is larger for countries with 'poor' civil liberties. The developing countries with low levels of foreign direct investment inflows and 'poor' civil liberties can best benefit from the high levels of skilled emigration outward. Through finding significant interactions with other variables, we confirm that the high-skilled emigration should be considered along with other related variables in measuring its impact on growth. The implications offer suggestions for the international trade and aid policies.

• Knowledge Management Research
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• v.19 no.1
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• pp.97-118
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• 2018

The finance-investment industry is currently focusing on research related to artificial intelligence and big data, moving beyond conventional theories of financial engineering. However, the case of equity optimization portfolio by using an artificial intelligence, big data, and its performance is rarely realized in practice. Thus, the purpose of this study is to propose process improvements in equity selection, information analysis, and portfolio composition, and lastly an improvement in portfolio returns, with the case of an equity optimization model based on quantitative research by an artificial intelligence. This paper is an empirical study of the portfolio based on an artificial intelligence technology of "D" asset management, which is the largest domestic active-quant-fiduciary management in accordance with the purpose of this paper. This study will apply artificial intelligence to finance, analyzing financial and demand-supply information and automating factor-selection and weight of equity through machine learning based on the artificial neural network. Also, the learning the process for the composition of portfolio optimization and its performance by applying genetic algorithms to models will be documented. This study posits a model that the asset management industry can achieve, with continuous and stable excess performance, low costs and high efficiency in the process of investment.

• Journal of Korea Port Economic Association
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• v.17 no.1
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• pp.91-111
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• 2001

This study was conducted in order to develop inter-local cooperation strategies between the City of Incheon, in Korea, and three provinces in northeastern China. We begin with a description of the history of and prospects for trade between Korea and China, an explanation of the current economic status of Incheon, statistics on the economy, trade and investment trends in the region, and information on the ports of the three Chinese provinces. The following strategies are suggested for inter-local cooperation based on the current circumstances. First, cooperative industrial strategies and economic investment for promoting the mutual concerns and interests of China and Korea were developed. Second, a practical way of utilizing the Incheon Industrial Park located in Dandong, China, was devised to stimulate industrial and investment cooperation. Third, a method of building a network among major ports in Korea and other Northeast Asian port cities was developed. Fourth, an international logistics transportation system that makes connection between sea, land and air easier through logistics standardization was suggested in preparation fur the changing environment of logistics brought about by the opening of the new Incheon International Airport. Fifth, methods of Improving port facilities are suggested. And, finally, the role and necessity of the Incheon City Interchange Center in executing inter-local cooperation strategies is described.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.8
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• pp.4133-4145
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• 2017

Advances in science and technology are driving us to the better life but also forcing us to make more investment at the same time. Therefore, the government has provided the investment to carry on the promising futuristic technology successfully. Indeed, a lot of resources from the government have supported into the science and technology R&D projects for several decades. However, the performance of the public investments remains unclear in many ways, so thus it is required that planning and evaluation about the new investment should be on data driven decision with fact based evidence. In this regard, the government wanted to know the trend and issue of the science and technology with evidences, and has accumulated an amount of database about the science and technology such as research papers, patents, project reports, and R&D information. Nowadays, the database is supporting to various activities such as planning policy, budget allocation, and investment evaluation for the science and technology but the information quality is not reached to the expectation because of limitations of text mining to drill out the information from the unstructured data like the reports and papers. To solve the problem, this study proposes a practical text mining methodology for the science and technology trend analysis, in case of aerospace technology, and conduct text mining methods such as ontology development, topic analysis, network analysis and their visualization.

• Journal of Korea Port Economic Association
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• v.22 no.1
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• pp.175-198
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• 2006

This paper presents a network capacity model that can be used as an analytical tool for strategic planning and resource allocation for multimodal transportation systems. In the context of freight transportation, the multimodal network capacity problem (MNCP) is formulated as a mathematical model of nonlinear bi-level optimization problem. Given network configuration and freight demand for multiple origin-destination pairs, the MNCP model is designed to determine the maximum flow that the network can accommodate. To solve the MNCP, a heuristic solution algorithm is developed on the basis of a linear approximation method. A hypothetical exercise shows that the MNCP model and solution algorithm can be successfully implemented and applied to not only estimate the capacity of multimodal network, but also to identify the capacity gaps over all individual facilities in the network, including intermodal facilities. Transportation agencies and planners would benefit from the MNCP model in identifying investment priorities and thus developing sustainable transportation systems in a manner that considers all feasible modes as well as low-cost capacity improvements.