• Journal of Digital Convergence
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• v.17 no.12
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• pp.45-57
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• 2019

The digital economy has created a new platform-based business model and raised the issue of the international taxation system in line with rapid economic development. Voices of fair taxation have also grown due to tax breaks to countries with low tax rates, problems caused by the gap between traditional and digital companies, and problems of business-oriented taxation systems. As a result, the international movement to lay the foundation for the international taxation system based on the business model suitable for the digital economy has become active. The stances of foreign organizations and countries are different, and the necessity of domestic policy introduction is increasing when cooperation at the international level is needed. This study was conducted to analyze the policy network and to help decision making. The results of the study showed that there were differences among domestic stakeholders depending on the actors. The EU suggested SDP in the long term, Digital Service Tax in the short term, and OECD suggested SEP in the long term. It was found that a careful approach to decision making and an in-depth study of the policy process are necessary.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.153-169
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• 2011

Today using Internet environment is considered absolutely essential for establishing corporate marketing strategy. Companies have promoted their products and services through various ways of on-line marketing activities such as providing gifts and points to customers in exchange for participating in events, which is based on customers' membership data. Since companies can use these membership data to enhance their marketing efforts through various data analysis, appropriate website membership management may play an important role in increasing the effectiveness of on-line marketing campaign. Despite the growing interests in proper membership management, however, there have been difficulties in identifying inappropriate members who can weaken on-line marketing effectiveness. In on-line environment, customers tend to not reveal themselves clearly compared to off-line market. Customers who have malicious intent are able to create duplicate IDs by using others' names illegally or faking login information during joining membership. Since the duplicate members are likely to intercept gifts and points that should be sent to appropriate customers who deserve them, this can result in ineffective marketing efforts. Considering that the number of website members and its related marketing costs are significantly increasing, it is necessary for companies to find efficient ways to screen and exclude unfavorable troublemakers who are duplicate members. With this motivation, this study proposes an approach for managing duplicate membership based on the social network analysis and verifies its effectiveness using membership data gathered from real websites. A social network is a social structure made up of actors called nodes, which are tied by one or more specific types of interdependency. Social networks represent the relationship between the nodes and show the direction and strength of the relationship. Various analytical techniques have been proposed based on the social relationships, such as centrality analysis, structural holes analysis, structural equivalents analysis, and so on. Component analysis, one of the social network analysis techniques, deals with the sub-networks that form meaningful information in the group connection. We propose a method for managing duplicate memberships using component analysis. The procedure is as follows. First step is to identify membership attributes that will be used for analyzing relationship patterns among memberships. Membership attributes include ID, telephone number, address, posting time, IP address, and so on. Second step is to compose social matrices based on the identified membership attributes and aggregate the values of each social matrix into a combined social matrix. The combined social matrix represents how strong pairs of nodes are connected together. When a pair of nodes is strongly connected, we expect that those nodes are likely to be duplicate memberships. The combined social matrix is transformed into a binary matrix with '0' or '1' of cell values using a relationship criterion that determines whether the membership is duplicate or not. Third step is to conduct a component analysis for the combined social matrix in order to identify component nodes and isolated nodes. Fourth, identify the number of real memberships and calculate the reliability of website membership based on the component analysis results. The proposed procedure was applied to three real websites operated by a pharmaceutical company. The empirical results showed that the proposed method was superior to the traditional database approach using simple address comparison. In conclusion, this study is expected to shed some light on how social network analysis can enhance a reliable on-line marketing performance by efficiently and effectively identifying duplicate memberships of websites.

• Journal of the Korean Geographical Society
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• v.48 no.2
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• pp.259-271
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• 2013

This paper addresses the efficient facility placements to adopt a super WiFi network, taking significant considerations as the next generation 'information highway'. Since the super WiFi has a wider geographic coverage by utilizing the white spaces of TV broadcasting which are empty and available frequencies for the wireless communications, it would play an important role in releasing digital divide of the internet access for low populated or mountainous areas. The purpose of this paper is to explore systematic and efficient spatial plans for the super WiFi. For doing this, we applied optimal location covering models to Gurye-gun, Jeonlanamdo. From the application, we presented optimal locations for super WiFi facilities and significant analytical results, such as the tradeoff between the number of facilities and coverage and marginal coverage for establishing super WiFi network. The results of this research would be usefully utilized for decision makers who wish to adopt a super WiFi, to extend wireless networks in a city or build a regional infrastructure of wireless facilities.

• Journal of The Korean Association For Science Education
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• v.38 no.3
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• pp.343-354
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• 2018

In this study, the first experience of the whole research process of a novice scientist (student A) who participated in the Undergraduate Research Program (URP) was analyzed. The data were collected through observation, interviews, and document analysis with the cultural historical activity theory being used as a theoretical lens. At the beginning of novice's research, the mentor guided him in setting a research goal and provided mediating artifacts. Student A formed a research team based on the vertical relationship without a shared mental model. Two major contradictions occurred and they were the sources of changes of student A's activity system. The first contradiction was between the mentor's educational philosophy and the mentee's educational needs, which was resolved in a way that student A asked and used the mentor's network to obtain his needs about task-specific details. The second contradiction arose because the team members wanted horizontal relationship while student A wanted to stick to the vertical relationship. After student A accepted the opinions of the team members, they cooperatively changed the division of labor in the activity system. Student A decided to become a scientist and not a physics teacher, even if his major is physics education after finishing his URP research process. His URP experience also created and expanded his network in the academic field, and his negative attitude toward collaboration changed positively. Through the analysis of the structure and changes in the activity system of URP research, implications for instructional method and support system of the apprenticeship can be obtained.

• Korean Journal of Construction Engineering and Management
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• v.6 no.4 s.26
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• pp.80-90
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• 2005

Activity durations retain probabilistic and stochastic natures due to diverse factors causing the delay or acceleration of activity completion. These natures make the final project duration to be a random variable. These factors are the major source of financial risk. Extending the Stochastic Project Scheduling Simulation system (SPSS) developed in previous research; this research presents a method to estimate how the final project duration behaves when activity durations change randomly. The final project cost is estimated by considering the fluctuation of indirect cost, which occurs due to the delay or acceleration of activity completion, along with direct cost assigned to an activity. The final project cost is estimated by considering how indirect cost behaves when activity duration change. The method quantifies the amount of contingency to cover the expected delay of project delivery. It is based on the quantitative analysis to obtain the descriptive statistics from the simulation outputs (final project durations). Existing deterministic scheduling method apply an arbitrary figures to the amount of delay contingency with uncertainty. However, the stochastic method developed in this research allows computing the amount of delay contingency with certainty and certain degree of confidence. An example project is used to illustrate the quantitative analysis method using simulation. When the statistical location and shape of probability distribution functions defining activity durations change, how the final project duration and cost behave are ascertained using automated sensitivity analysis method

• Journal of Korea Port Economic Association
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• v.23 no.3
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• pp.53-77
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• 2007

This paper is designed to look for a specialized strategies by drawing the special features of Busan New Port from both a comparative analysis of major factors of harbor competitiveness and a SWOT analysis of Busan New Port and Yangshan Port, one of the biggest competitive ports in Northeast Asia, so that Busan New Port may preoccupy a status as the hub port of the area. The researcher would like to suggest the following measures to make Busan New Port serve as the central port of Northeast Asia on the basis of the findings; Korea should push ahead with creating a railroad transportation linking with Eurasia Contient, secure the amount of goods and resources with the help of the early development of the surrounding complex of the port, make a considerable progress in the level of port service, come up with a differentiation strategies for harbor marketing activities and improve its productivity.

• The Journal of Bigdata
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• v.4 no.2
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• pp.159-173
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• 2019

Last-Mile delivery optimization plays a key role in the urban supply chain operation, which is the most expensive and time-consuming and most complicated part of the whole delivery process. The urban consolidation center (UCC) is regarded as a significant asset for supporting customer demand in the last-mile delivery service. It is the key benefit of UCC to improve the load balance of vehicles and to reduce the total traveling distance by finding the better route with the well-organized multi-leg vehicle journey in the urban area. This paper presents the model using multiple scenario analysis integrated with mathematical optimization techniques using Geographic Information System (GIS). The model aims to find the best solution for the distribution network consisted of DC and UCC, which is applied to the case of Ulaanbaatar Mongolia. The proposed methodology integrates two sub-models, location-allocation model and vehicle routing problem. The multiple scenarios devised by selecting locations of UCC are compared considering the general performance and delivery patterns together. It has been adopted to make better decisions the quantitative metrics such as the economic value of capital cost, operating cost, and balance of using available resources. The result of this research may help the manager or public authorities who should design the distribution network for the last mile delivery service optimization using UCC within the urban area.

• Korean Journal of Agricultural and Forest Meteorology
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• v.6 no.2
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• pp.107-117
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• 2004

If doubtlessly contributes much to agriculture and rural development. The roles can be summarized as; 1. to activate rural areas and to provide more comfortable and safe rural life with equivalent services to those in urban areas, facilitating distance education, tole-medicine, remote public services, remote entertainment etc. 2. To initiate new agricultural and rural business such as e-commerce, real estate business for satellite officies, rural tourism and virtual corporation of small-scale farms. 3. To support policy-making and evaluation on optimal farm production, disaster management, effective agro-environmental resource management etc., providing tools such as GIS. 4. To improve farm management and farming technologies by efficient farm management, risk management, effective information or knowledge transfer etc., realizing competitive and sustainable farming with safe products. 5. To provide systems and tools to secure food traceability and reliability that has been an emerging issue concerning farm products since serious contamination such as BSE and chicken flu was detected. 6. To take an important and key role for industrialization of farming or lam business enterprise, combining the above roles.

• Journal of Internet Computing and Services
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• v.17 no.6
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• pp.53-59
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• 2016

Recently, huge stream data have been generated in real time from various applications such as wireless sensor networks, Internet of Things services, and social network services. For this reason, to develop an efficient method have become one of significant issues in order to discover useful information from such data by processing and analyzing them and employing the information for better decision making. Since stream data are generated continuously and rapidly, there is a need to deal with them through the minimum access. In addition, an appropriate method is required to analyze stream data in resource limited environments where fast processing with low power consumption is necessary. To address this issue, the sliding window model has been proposed and researched. Meanwhile, one of data mining techniques for finding meaningful information from huge data, pattern mining extracts such information in pattern forms. Frequency-based traditional pattern mining can process only binary databases and treats items in the databases with the same importance. As a result, frequent pattern mining has a disadvantage that cannot reflect characteristics of real databases although it has played an essential role in the data mining field. From this aspect, high utility pattern mining has suggested for discovering more meaningful information from non-binary databases with the consideration of the characteristics and relative importance of items. General high utility pattern mining methods for static databases, however, are not suitable for handling stream data. To address this issue, sliding window based high utility pattern mining has been proposed for finding significant information from stream data in resource limited environments by considering their characteristics and processing them efficiently. In this paper, we conduct various experiments with datasets for performance evaluation of sliding window based high utility pattern mining algorithms and analyze experimental results, through which we study their characteristics and direction of improvement.

• Smart Media Journal
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• v.11 no.11
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• pp.49-62
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• 2022

Recently, with the development of Smart City Solutions such as Big data, AI, IoT, Autonomous driving, and Digital twins around the world, the proliferation of various smart devices and social media, and the record of the deeds that people have left everywhere, the construction of Smart Cities using the "Big Data" environment in which so much information and data is produced that it is impossible to gauge the scale is actively underway. The Purpose of this study is to construct an objective and systematic analysis Model based on Big Data to improve the transportation convenience of citizens and formulate efficient policies in Urban Information and Public Transportation accessibility in sustainable Smart Cities following the 4th Industrial Revolution. It is also to derive the methodology of developing a Big Data-Based public transport accessibility and policy management Platform using a sustainable Urban Public DB and a Private DB. To this end, Detailed Living Areas made a division and the accessibility of basic living amenities of Gwangju Metropolitan City, and the Public Transportation system based on Big Data were analyzed. As a result, it was Proposed to construct a Big Data-based Urban Information and Public Transportation accessibility Platform, such as 1) Using Big Data for public transportation network evaluation, 2) Supporting Transportation means/service decision-making based on Big Data, 3) Providing urban traffic network monitoring services, and 4) Analyzing parking demand sources and providing improvement measures.