• Journal of Digital Contents Society
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• v.19 no.9
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• pp.1689-1697
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• 2018

This paper explored how to design amobile application for Korea's traditional markets based on O2O service and data science technologies. In order to cover a broader scope of customers, diversify the ways to sell products, and increase the profits of Korea's traditional markets, the application bridges online customers with offline stores at traditional markets and augments both convenience and accessibility. Beyond the typical face-to-face interactions between customers and sellers at traditional markets, this application offers mobile payments and personalized recommendations of nearby stores and preferable products using Beacon and datascience technologies. Moreover, it offers multi-language support for foreign customers who are not familiar with Korea's traditional markets and the products sold there. In conclusion, using O2O service, which is a rising trend among prevalent platform technologies, this study proposed a new e-commerce model for Korea's traditional markets to promote market expansion.

• Informatization Policy
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• v.24 no.3
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• pp.91-107
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• 2017

Digital forensics is the process of uncovering and interpreting electronic data and materials found in digital device in relation to crime. The goal of the process is to preserve any evidence in its most original form which shall be having the force of law. The digital forensic market is increasing with a growth of ICT in domestic and global market. Many countries including U.S. are actively performing researched regarding a structured investigation by collecting, identifying and validating the digital information for the purpose of reconstructing past events which so does in academic society in Korea. This paper is to understand overall research trend about digital forensics and derive future strategy by integrating the result of meta-analysis into practices based on five criteria - main theme and topic, analysis phase, technical method for analysis, author's affiliation, and unit of analysis and method. 239 papers are analyzed, which were selected out of 470 papers published for 10 years (2007~2016) in academic journal on the list of KCI (Korea Citation index). The results of this analysis will be used to examine the characteristics of research in the field of digital forensics. The result of this research will contribute to understanding of the research trend and characteristics leading the technology-driven academia, through which measures for further research development and facilitation are suggested.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.29-43
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• 2022

With the advent of the Internet and the development of mobile digital devices such as smartphones and tablet PCs, the communication service paradigm began to shift from existing voice services to data services. Recently, as social network services (SNS) are activated and 4th industrial revolution technologies centered on ICT (Information and Communication Technologies) such as Big Data, Blockchain, Cloud, and 5G/6G are rapidly developed, the amount of shared data type and the amount of data are increasing rapidly. As the transition to a digital society begins actively, the importance of using data information, as well as the economic and social values of personal information are becoming increasingly important. As a result, they are actively discussing policies to revitalize the data information industry around the world and ways to efficiently obtain, analyze, and utilize increasingly diverse and vast data, as well as to protect/guarantee the rights of information subjects (providers) in various fields such as society, culture, economy, and politics.. In this paper, in order to improve the self-determination right of personal information on data produced by information subjects, and further expand the use of safe data and the data economy, a differentiated data trusts system was considered and suggested. In addition, the components and data trusts procedures necessary to efficiently operate the data trusts system in Korea were considered, and the non-profit data trusts system and the for-profit data trusts system were considered as a way to flexibly operate the data trusts system. Furthermore, the legal items necessary for the implementation of the data trusts system were investigated and considered. In this paper, in order to propose a domestic data trusts system, cases related to existing data trusts systems such as the United States, Japan, and Korea were reviewed and analyzed. In addition, in order to prepare legislation necessary for the data trusts system, data-related laws in major countries and domestic legal and policy trends were reviewed to study the rights that conflict or overlap with existing laws, and differences were investigated and considered. The Data trusts system proposed in this paper is a reasonable system that is expected to recognize the asset value of data in the capitalist market economy system, to provide legitimate compensation for data produced by data subjects, and further to contribute greatly to the use of safe data and creation of a new service market.

• Journal of Information Technology Services
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• v.19 no.4
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• pp.85-107
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• 2020

The Internet of Things market, a technology that connects the Internet to various things, is growing day by day. Besides, various smart home services using IoT and AI (Artificial Intelligence) are being launched in homes. Related to this, existing smart home-related studies focus primarily on ICT technology, not on what service improvements should be made in customer positions. In this study, we will use smart home application customer review data to classify functional and design elements of smart home usability value and examine the ways customers think of service improvement. For this, LG Electronics and Samsung Electronics" Smart Home application, the main provider of Smart Home in Korea, customer reviews were crawled to conduct a comparative analysis between them. In this study, the review of IoT home-applications was analyzed to find service improvement insights from customer perspective, and related analysis of text mining, social network analysis and Doc2vec was used to efficiently analyze data equivalent to about 16,000 user reviews. Through this research, we hope that related companies effectively seek ways to improve smart home services that reflect customer needs and are expected to help them establish competitive strategies by identifying weaknesses and strengths among competitors.

• Journal of the Korea Convergence Society
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• v.11 no.10
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• pp.19-24
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• 2020

Artificial intelligence technology, which is the core of the 4th industrial revolution, is making intelligent judgments through deep learning techniques and machine learning that it is impossible to predict if it is applied to stock prediction beyond human capabilities. In US fund management companies, artificial intelligence is replacing the role of stock market analyst, and research in this field is actively underway. In this study, we use BLSTM to reduce errors that occur in unidirectional prediction of the existing LSTM method, reduce errors in predictions by predicting in both directions, and macroscopic indicators that affect stock prices, namely, economic growth rate, economic indicators, interest rate, analyze the trade balance, exchange rate, and volume of currency. To help stock investment by accurately predicting the target price of stocks by analyzing the PBR, BPS, and ROE of individual stocks after analyzing macro-indicators, and by analyzing the purchase and sale quantities of foreigners, institutions, pension funds, etc., which have the most influence on stock prices.

• Cartoon and Animation Studies
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• s.12
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• pp.56-72
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• 2007

The purpose of this study is to analyze the characteristics of animation cluster in Chuncheon. It has been over 10 years since Chuncheon was designated as the cluster raising the animation industry. The Chuncheon cluster is trying to differentiate through managing several unique strategies. In order to realize the micro-regionalism, it focuses on co-production not with domestic companies but with foreign companies. Especially, for establishing the whole concrete production pipe-line, it concerns to make co-production contracts dealing with not only for the main production part but also pre- and post-production parts. Based on these production experience, it is building the production complex in the name of ICT convergence cluster. The changed role of the policy-management organization(Gangwon Information & Multimedia Corporation, GIMC) enables these differentiated strategies by itself. The establishment of the Asian Animation Round(AAR) is recognized as the characteristic of macro-regionalism. Starting from the year of 2006, the AAR tries to place Chuncheon as the hub of animation production in Asia and focuses on constructing the network of animation production countries that have developed their production capabilities through sub-contracts. This type of production and market bloc has not been made before.

• Journal of Digital Convergence
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• v.18 no.11
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• pp.267-272
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• 2020

Macroeconomics are one of the indicators that are preceded and analyzed when analyzing stocks because it shows the movement of a country's economy as a whole. The overall economic situation at the national level, such as national income, inflation, unemployment, exchange rates, currency, interest rates, and balance of payments, has a great affect on the stock market, and economic indicators are actually correlated with stock prices. It is the main source of data for analysts to watch with interest and to determine buy and sell considering the impact on individual stock prices. Therefore, economic indicators that impact on the stock price are analyzed as leading indicators, and the stock price prediction is predicted through deep learning-based prediction, after that the actual stock price is compared. If you decide to buy or sell stocks by analysis of stock prediction, then stocks can be investments, not gambling. Therefore, this research was conducted to enable automated stock trading by using macro-indicators and deep learning algorithms in artificial intelligence.

• The Journal of Society for e-Business Studies
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• v.25 no.2
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• pp.109-126
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• 2020

This study attempts to find out the characteristics of digital currency and currency transformation through the analytical descriptions of the literature. In the early days of the emergence of new currency, market-oriented autonomous monetary adjustment was made along with various attempts by the private sector, and then government-centered central currency management and coordination were made for the national monopoly of profits and power. Digital currency can be seen as the emergence of a new form of money that will bring about paradigm changes. CBDC can be divided into direct and indirect types. CBDC is expected to require a strategic approach by the government or firm as it will bring about changes in the ecosystem of related industries. Libra is a stablecoin designed to minimize price fluctuations, and if it succeeds in commercializing it, it is expected to bring about revolutionary changes in the financial industry around the world.

• Journal of Advanced Navigation Technology
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• v.15 no.4
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• pp.585-590
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• 2011

In the past few years, M2M (Machine-to-Machine) applications have become a hot topic in the wireless industry. While M2M applications can be used for many purposes (smart homes, smart metering/electricity meter reading, fleet management, mobile workforce, automobile insurance, vending machines, etc), and in many sectors (healthcare, agriculture, commercial, industrial, retail, utility, etc.), smart metering applications or smart grids present the biggest growth potential in the M2M market today. M2M platform is the future ubiquitous network technologies which provide the integrated service with the networks and devices. The promising technologies to tackle these problems are the Semantic technologies, for interoperability, and the Agent technologies for management of complex systems. In this paper the information communication technique based on the disaster prevention system's for the M2M, concepts and its requirement technology and application are studied.

• The Journal of Information Systems
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• v.27 no.2
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• pp.95-114
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• 2018

Purpose The recent concern over environmental problems such as greenhouse gas emission and fine dust contributes increasing interest in renewable energies. However the intrinsic characteristics of renewable energies, intermittent and stochastic generation, might cause serious problems to the stability and controllability of power grid. Therefore countermeasures such as virtual power plant (VPP) must be prepared in advance of the spread of uncontrollable distributed renewable energy resources to be one of major energy sources. Design/methodology/approach This study deals with the design concept of the VPP platform. we proposed as a technology solution for achieving the stability of power grid by guaranteeing a single power profile combining multiple distributed power sources with ICT. The core characteristics of VPP should be able to participate in the grid operation by responding to operation instructions from the system operator, KPX, as well as the wholesale electricity market. Findings Therefore this study includes energy storage device(ESS) as a controllable component as well as renewable energy resources such as photovoltaic and wind power generation. Based on this configuration, we discussed core element technologies of VPP and protype design of VPP solution platform according to system requirements. In the proposed solution platform, UX design for the integrated control center and brokerage system were included as well as ancillary service function to respond to KPX's operation instruction with utilizing the capability of ESS. In addition, a simulator was suggested to verify the VPP operations.