• KIPS Transactions on Software and Data Engineering
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• v.6 no.1
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• pp.1-8
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• 2017

Given a multi-dimensional dataset of tuples, a skyline query returns a subset of tuples which are not 'dominated' by any other tuples. Skyline query is very useful in Big data analysis since it filters out uninteresting items. Much interest was devoted to the MapReduce-based parallel processing of skyline queries in large-scale distributed environment. There are three requirements to improve parallelism in MapReduced-based algorithms: (1) workload should be well balanced (2) avoid redundant computations (3) Optimize network communication cost. In this paper, we introduce MR-SEAP (MapReduce sample Skyline object Equality Angular Partitioning), an efficient angular space partitioning based skyline query processing using sampling-based pruning, which satisfies requirements above. We conduct an extensive experiment to evaluate MR-SEAP.

• Journal of Advanced Navigation Technology
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• v.4 no.2
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• pp.114-131
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• 2000

An airline should consider the number of seats or size of aircraft, when it composes fleet or selects a type of aircraft for some routes. There are two major factors considered for this choice problem under the assumption that the objectives of an airline is a profit maximization: the operating cost and revenue from the aircraft operated. This research tries to solve the problem of aircraft size selection by airline. The study applies four steps to get optimal choice of aircraft size: (1) cost analysis for the relationship between airline operation cost and aircraft size: (2) market share and revenue analysis: (3) flight segment-level analysis, based on the derived cost, demand and revenue functions: and (4) network-level analysis to see how airlines make choice of aircraft size systematically at a network level. An airline can accommodate the increasing air travel demand by either increasing operation frequency, or increasing aircraft size that is represented by seat capacity, or both. Airport runway capacity and productivity depend on the size of aircraft used at airport. This paper presents the understanding of how airlines make decisions on the size of aircraft to operate, how they will adjust their choices when airport capacity is constrained, and how public regulation such as policy for landing fees could influence airlines' aircraft choice.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.47-64
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• 2021

The global spread of COVID-19 around the world has not only affected many parts of our daily life but also has a huge impact on many areas, including the economy and society. As the number of confirmed cases and deaths increases, medical staff and the public are said to be experiencing psychological problems such as anxiety, depression, and stress. The collective tragedy that accompanies the epidemic raises fear and anxiety, which is known to cause enormous disruptions to the behavior and psychological well-being of many. Long-term negative emotions can reduce people's immunity and destroy their physical balance, so it is essential to understand the psychological state of COVID-19. This study suggests a method of monitoring medial news reflecting current days which requires striving not only for physical but also for psychological quarantine in the prolonged COVID-19 situation. Moreover, it is presented how an easier method of analyzing social media networks applies to those cases. The aim of this study is to assist health policymakers in fast and complex decision-making processes. News plays a major role in setting the policy agenda. Among various major media, news headlines are considered important in the field of communication science as a summary of the core content that the media wants to convey to the audiences who read it. News data used in this study was easily collected using "Bigkinds" that is created by integrating big data technology. With the collected news data, keywords were classified through text mining, and the relationship between words was visualized through semantic network analysis between keywords. Using the KrKwic program, a Korean semantic network analysis tool, text mining was performed and the frequency of words was calculated to easily identify keywords. The frequency of words appearing in keywords of articles related to COVID-19 emotions was checked and visualized in word cloud 'China', 'anxiety', 'situation', 'mind', 'social', and 'health' appeared high in relation to the emotions of COVID-19. In addition, UCINET, a specialized social network analysis program, was used to analyze connection centrality and cluster analysis, and a method of visualizing a graph using Net Draw was performed. As a result of analyzing the connection centrality between each data, it was found that the most central keywords in the keyword-centric network were 'psychology', 'COVID-19', 'blue', and 'anxiety'. The network of frequency of co-occurrence among the keywords appearing in the headlines of the news was visualized as a graph. The thickness of the line on the graph is proportional to the frequency of co-occurrence, and if the frequency of two words appearing at the same time is high, it is indicated by a thick line. It can be seen that the 'COVID-blue' pair is displayed in the boldest, and the 'COVID-emotion' and 'COVID-anxiety' pairs are displayed with a relatively thick line. 'Blue' related to COVID-19 is a word that means depression, and it was confirmed that COVID-19 and depression are keywords that should be of interest now. The research methodology used in this study has the convenience of being able to quickly measure social phenomena and changes while reducing costs. In this study, by analyzing news headlines, we were able to identify people's feelings and perceptions on issues related to COVID-19 depression, and identify the main agendas to be analyzed by deriving important keywords. By presenting and visualizing the subject and important keywords related to the COVID-19 emotion at a time, medical policy managers will be able to be provided a variety of perspectives when identifying and researching the regarding phenomenon. It is expected that it can help to use it as basic data for support, treatment and service development for psychological quarantine issues related to COVID-19.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.2
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• pp.885-892
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• 2012

Coastal zone management indicators are being used as an important means of decision making in the process of policy establishment for integrated coastal management and implementation, and these indicators are very useful tools that enable the evaluation of the coastal zone management from an integrated perspective, the understanding and analysis of interactions according to each department. Accordingly, most of organizations in international society and advanced coastal states tend to develop coastal zone management indicator system in order to check current coastal environment, social and economic status, also to grasp effectiveness of the coastal zone management policy. In this research, therefore, the characteristics of coastal zone management indicator system was drawn through understanding of strength and weakness, and conducting comparative analysis of the coastal zone management indicator system according to each level having classified domestic and international coastal zone management indicator system into three aspects at large: natural and environmental aspect; social and economic aspect; and network aspect. As a result, following features were drawn as the common characteristics among the cases in the advanced coastal states: the management means for realization of sustainable coastal zone management; scientific decision making tools for various stakeholders; evaluation means for effectiveness of coastal zone integrated management; and dualization of coastal zone management indicator system; etc. Lastly, based on these common values revealed in the domestic and international coastal management indicator system, a suggestion for correct establishment of the domestic coastal management indicators was proposed in the regional aspect.

• Journal of the Korea Society for Simulation
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• v.25 no.2
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• pp.41-49
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• 2016

Counter Fire Operations can be characterized as having a system of systems that key features include situational awareness, command and control systems and highly responsive strike achieved by precision weapons. Current modeling methodology cannot provide an appropriate methodology for a system of systems and utilizes modeling and simulation tools to implement analytic options which can be time consuming and expensive. We explain developing methodology and tools for the effectiveness analysis of the counter fire operations under Network Centric Warfare Environment and suggest how to support a efficient decision making with the methodology and tools. Theater Counter Fire Operations tools consist of Enemy block, ISR block, C2 block and Shooter block. For the convenience of using by domain expert or non simulation expert, it is composed of the environments that each parameter and algorithm easily can be altered by user.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.1647-1656
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• 2007

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 propose 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, social, and transportation-related ones and then, explain the way how to evaluate the overall sustainability by comparing the relative importance among indicators. This will help transportation agencies to prioritize high-speed rail investment toward sustainable transportation systems.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.4
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• pp.107-117
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• 2011

Smartphones are widely used as a mobile communication devices with more advanced computing ability and connectivity than a contemporary feature phone. As the market expands, many brand-new smartphones are released and chosen by (potential) smartphone users. In spite of smartphone's popularity, little research of the factors affecting the evaluation of smartphones and their influences on smartphone choice have been performed. Therefore, we aim to analyze evaluation factors of smartphone selection and use in this research. We use Fuzzy Analytic Hierarchy Process method, a Multi-Criteria Decision Making (MCDM) model, to find the relative importance among the factors considering the fuzziness of pair-wise comparison using AHP. After reviewing related works and interviewing the focus group, we extract the five independent factors influencing the choice and use of a smartphone. Pair-wise comparison and triangle fuzzy numbers are used to calculate the relative importance of factors. We analyze not only the whole interviewees' responses, but the differences between smartphone users and non-users. Practical implications are delivered in concluding remarks.

• The Journal of Society for e-Business Studies
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• v.19 no.1
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• pp.145-157
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• 2014

The advent of ubiquitous connectivity from smart devices and network is changing the lifestyles of workers and work patterns. However, the smart work for the knowledge workers and mobile workers is not yet popular due to not enough services in supporting smart work and difficulties in employing smart work. For these reasons, it is necessary to study the current smart work industry to provide the bases for incubating smart work industry and increasing the smart work adoption. In this study, first, we reviewed and analyzed the smart work services. And then, we classified the smart work industry based on their services. Second, we conducted a survey study to identify the factors that affect on the adoption of smart work. Finally, we provided the current adoption rate of smart work services and discussed the Willing-To-Use, cost, and barriers from the smart work adoption.

• Journal of the Korea Convergence Society
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• v.12 no.7
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• pp.45-51
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• 2021

In accordance with the rapid non-face-to-face environment and mobile first strategy, the explosive increase and creation of many structured/unstructured data every year demands new decision making and services using big data in all fields. However, there have been few reference cases of using the Hadoop Ecosystem, which uses the rapidly increasing big data every year to collect and load big data into a standard platform that can be applied in a practical environment, and then store and process well-established big data in a relational database. Therefore, in this study, after collecting unstructured data searched by keywords from social network services based on Hadoop 2.0 through three virtual machine servers in the Spring Framework environment, the collected unstructured data is loaded into Hadoop Distributed File System and HBase based on the loaded unstructured data, it was designed and implemented to store standardized big data in a relational database using a morpheme analyzer. In the future, research on clustering and classification and analysis using machine learning using Hive or Mahout for deep data analysis should be continued.

• 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.