• Journal of the Korean Society of Environmental Restoration Technology
• /
• v.26 no.6
• /
• pp.205-220
• /
• 2023

This study aimed to analyze the needs and interests of the public on endangered wildlife using complaint big data. We collected 1,203 complaints and their corresponding text data on endangered wildlife, pre-processed them, and constructed a document-term matrix for 1,739 text data. We performed LDA (Latent Dirichlet Allocation) topic modeling and network analysis. The results revealed that the complaints on endangered wildlife peaked in June-August, and the interest shifted from insects to various endangered wildlife in the living area, such as mammals, birds, and amphibians. In addition, the complaints on endangered wildlife could be categorized into 8 topics and 5 clusters, such as discovery report, habitat protection and response request, information inquiry, investigation and action request, and consultation request. The co-occurrence network analysis for each topic showed that the keywords reflecting the call center reporting procedure, such as photo, send, and take, had high centrality in common, and other keywords such as dung beetle, know, absence and think played an important role in the network. Through this analysis, we identified the main keywords and their relationships within each topic and derived the main issues for each topic. This study confirmed the increasing and diversifying public interest and complaints on endangered wildlife and highlighted the need for professional response. We also suggested developing and extending participatory conservation plans that align with the public's preferences and demands. This study demonstrated the feasibility of using complaint big data on endangered wildlife and its implications for policy decision-making and public promotion on endangered wildlife.

• Journal of Digital Convergence
• /
• v.15 no.8
• /
• pp.103-114
• /
• 2017

With the development of IT technology and the establishment of logistics infrastructure, online shopping market and online fresh food market are growing. The purpose of this study is to find a plan to activate Fresh Logistics through online shopping mall using BCG matrix and Importance Performance Analysis for online shopping companies. Firstly, the BCG matrix results Companies in 'cash cow', 'question mark', and 'dog' areas are in need of improvement. In order to improve this situation, it is necessary to activate the Fresh logistics market which is currently growing. Fresh logistics can be activated by investing in the maintenance and strengthening areas and key investment areas by minimizing the expenditure on the non-priority and excess areas according to the results of IPA. Therefore, it is expected that online shopping companies will be improved by activating online shopping market and online fresh logistics market.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.8
• /
• pp.3701-3727
• /
• 2016

Recently Service Function Chaining (SFC) is promising to innovate the network service mode in modern networks. However, a feasible implementation of SFC is still difficult due to the need to achieve functional equivalence with traditional modes without sacrificing performance or increasing network complexity. In this paper, we present a configurable network service chaining (CNSC) mechanism to provide services for network traffics in a flexible and optimal way. Firstly, we formulate the problem of network service chaining and design an effective service chain construction framework based on integrating software-defined networking (SDN) with network functions virtualization (NFV). Then, we model the service path computation problem as an integer liner optimization problem and propose an algorithm named SPCM to cooperatively combine service function instances with a network utility maximum policy. In the procedure of SPCM, we achieve the service node mapping by defining a service capacity matrix for substrate nodes, and work out the optimal link mapping policies with segment routing. Finally, the simulation results indicate that the average request acceptance ratio and resources utilization ratio can reach above 85% and 75% by our SPCM algorithm, respectively. Upon the prototype system, it is demonstrated that CNSC outperforms other approaches and can provide flexible and scalable network services.

• Journal of Navigation and Port Research
• /
• v.40 no.5
• /
• pp.311-316
• /
• 2016

Vietnam is one of Asia's fastest developing economies. A long coastline of nearly 3,500 km provides a comparative advantage for Vietnam in developing a seaport system. Despite accounting for only about 30% of Vietnam's traffic volume, the Northern seaports have rapidly developed over the years. However, the location of the container terminals close to the common hinterland are a cause of fierce competition among container terminals. To outperform rivals and improve competitiveness, it is essential to identify the competitive positions of container terminals. This study analyzes the competitive positioning of container terminals in the northern region of Vietnam between 2005 and 2014 by applying the Boston Consulting Group (BCG) matrix in order to assist terminal operators and policy makers to generate strategic planning as well as to improve priorities for development. Otherwise, the period from 2005-2014 aims to clarify the static and dynamic positioning of container terminals. The results demonstrate that the Hai Phong terminal dominates the market, but the Nam Hai Dinh Vu and Dinh Vu terminals are considered as "star" performers. Quang Ninh, Doan Xa, and Transvina are losing their competitive positions in Northern Vietnam.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.42 no.1
• /
• pp.53-63
• /
• 2017

Managing the quantitative measurement of the data control activities in enterprise wide is important to secure management of data governance. However, research on data governance is limited to concept definitions and components, and data governance research on evaluation models is lacking. In this study, we developed a model of quantitative assessment for data governance including the assessment area, evaluation index and evaluation matrix. We also, proposed a method of developing the model of quantitative assessment for data governance. For this purpose, we used previous studies and expert opinion analysis such as the Delphi technique, KJ method in this paper. This study contributes to literature by developing a quantitative evaluation model for data governance at the early stage of the study. This paper can be used for the base line data in objective evidence of performance in the companies and agencies of operating data governance.

• ETRI Journal
• /
• v.27 no.2
• /
• pp.206-218
• /
• 2005

We measure and compare externalities of IT and R&D capital stocks in different Korean industry sectors using inter-industry input-output tables of 1985, 1990, 1995 and 2000. We also compute the multiplier effects that relate to the directions of future economic effects. The key findings are as follows. First, we observed continuous capital deepening in all nine industries over the period of 1985 to 2000. Second, the backward multipliers of IT capital were the highest in the manufacturing industry. As for inter-industry externalities, the indirect backward multipliers, which exclude intra-industry backward multiplier effects within the industry, were also the highest in the manufacturing industry. Third, the forward multiplier effects of IT capital stock were the most substantial in the construction industry during the 1980s and in the manufacturing industry thereafter. Finally, using the transition multiplier matrix reflecting the backward effects of the two capitals in the past, the economic backward effects, especially the external economic effects, are predicted to increase through 2010 among all industries. The above findings suggest that, in order to maximize the forward and backward effects of the ever-increasing IT capital, we need to formulate an industry policy reducing the cost of capital accumulation in the manufacturing industry through improvement in productivity of the IT industry.

• International journal of advanced smart convergence
• /
• v.9 no.3
• /
• pp.176-182
• /
• 2020

In this paper, to analyze the meaning of middle-aged men's economic activities, TEXTOM was used to analyze them. The data collection period is set from 2017 to 2019. Among the collected data, 100 refined words were converted into a matrix in which the degree of social connection was calculated, and the keyword network analysis was performed again with the NetDraw program. According to the study, middle-aged men put more meaning on their current work and family than their future retirement. Also, the related word commonly included in the top five for all three years was 'work'. Related words commonly included in the top 10 were 'old age', 'family', and 'work', and in 2018 and 2019, 'health' was included in the top 10. As a result of this, the middle-aged men living in the modern age are the generation who keep their families through economic activities and are increasingly interested in health and prepare for retirement. Therefore, policy support for stable economic activities is needed to improve the quality of life for middle-aged men. It is necessary to extend the retirement age, expand jobs and provide effective vocational training so that it can handle its role as the head of a family. In addition, measures should be taken to reduce the wage gap between highly skilled and low-skilled workers.

• Journal of Korean Society of Transportation
• /
• v.30 no.5
• /
• pp.43-59
• /
• 2012

It is generally assumed about trip distribution estimation model that growth factor model's estimation accuracy is higher than that of other models in short-term and that gravity model's estimation accuracy is higher than that of other models in long-term. For validation of such assumptions, this study compares estimation accuracies of each estimation model using 3year(1988, 1992, 2004) O-D tables from Daegu city. Each estimation model's accuracy were compared by mid-size and large-size zone as well as short-term and long-term target years. The results show that the trip distribution estimation model selection by usual assumption is not always right.

• The Journal of Asian Finance, Economics and Business
• /
• v.7 no.7
• /
• pp.241-249
• /
• 2020

The role of money in the modern economy highly determines the intensity and the development of the macroeconomy. The money supply is assumed to be as much as money demand, which reflects the economic character of a country and indicates the growth and development of macroeconomy. In Indonesia, the money supply (M1) is related to the economic dynamics in either the monetary market or the goods market. This research aims at analyzing factors that influence the money supply and to what extent the economic factors affect the money supply in Indonesia. The analysis method used in this research was Vector Autoregressive (VAR) with some variables, such as money supply (M1), interest rate, and Gross Domestic Product (GDP) from the 1st quarter of 2001 until the 1st quarter of 2013. The data collection method was in the form of data compilation from credible sources, such as Bank of Indonesia (BI), Central Bureau of Statistics (CBS), and International Financial Statistics (IFS). To obtain adequate analysis results, several tests were taken, such as unit-root test, Granger causality test, and optimal lag. VAR analysis formulates the correlation among independent variables, so it also sees the study of impulse response and matrix decomposition.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.27 no.4
• /
• pp.41-65
• /
• 2002

We study a multi-component production/inventory system in which individual components are made to meet various demand types. We assume that the demands arrive according to a Poisson process, but there is a fixed probability that a demand requests a particular kit of different components. Each component is produced by a flow line with several stations in which the processing times of each station follow a two-stage Coxian distribution. The production of each component is operated by an independent base-stock policy with blocking. We assume that the time needed to assemble final products follows a general distribution and the capacity of an assembling facility is sufficiently large. The objective of this study is to obtain key performance measures such as the distribution of the number of each orders for each final product and the mean time of fulfilling a customer order. The basic principle of the proposed approximation method is to decompose the original system into a set of subsystems, each subsystem being associated with a flow line. Each subsystem is analyzed in isolation using a Marie's method. An iterative procedure is then used to determine the unknown parameters of each subsystem. Numerical results show that the accuracy of the approximation method is acceptable.