• Title/Summary/Keyword: digital currency

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A study on the exportation of the e-clearance system of Korea Customs Service to overseas aiming to lead the global trend of Customs informatization (정보화시대 글로벌 리더로의 도약을 위한 관세청 전자통관시스템 해외수출 전략에 대한 연구)

  • Seo, Jae-Yong;Jo, Jeong-Hun
    • 한국디지털정책학회:학술대회논문집
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    • 2006.06a
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    • pp.45-53
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    • 2006
  • Ever since the computer came into being in early 20th century, rapid development of the information technology has led to the opening of the ubiquitous age where daily works can be done anywhere, anytime, and with any devices. The information technology has drawn attention from Customs around the world as a key means to fulfill multi-faced responsibilities of strengthening regional cooperation in the international trade, simplifying clearance procedures, expediting logistics flow, and ensuring security in the global supply chain. Korea Customs Service, which began the informatization effort by establishing the electronic export declaration system in 1992, completed the 100% electronic clearance system in 2000, with a number of countries now conducting benchmarking studies on the successful use of IT by KCS. This paper is to address the changes brought to the Customs administration in the information age, the progress and achievement of the Customs informatization as a proactive strategy to deal with the changing environment, and the exportation to overseas administration of the e-clearance system of KCS which strives to become the global leader of Customs informatization. The exportation. in particular, will not only lead to increased foreign currency earnings and shared know how, but also create an opportunity to reflect Korea's system in the standardization of Customs procedures around the world.

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A Study on Adoption and Policy Direction of Blockchain Technology in Financial Industry (금융분야의 블록체인기술 활용과 정책방향에 관한 연구)

  • Park, Jeong Kuk;Kim, Injai
    • Journal of Information Technology Services
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    • v.16 no.2
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    • pp.33-44
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    • 2017
  • The financial industry recently introduces several issues for utilizing the blockchain technology as the core infrastructure of future finance. Blockchain, first introduced as the underlying technology of Crypto-currencies, Bitcoin is a technology that can ensure the integrity and reliability of data by verifying, recording, and storing data jointly in the network without a central administration organization or a manager. This blockchain has its potential power as a technology for issuing digital currencies, providing transparency, and securing record management, that is expected to be useful in the financial sector. At the same time, considering the characteristics of financial transactions which emphasize privacy, questions are raised about whether a blockchain structure in which information is distributed and shared among participants can be successful. How will we support to implement the potential of the blockchain in order to change the paradigm of the financial industry? How can we manage the side effects of blockchain effectively? Such a policy discussion is necessary. This study introduces the meaning of the blockchain technology, various utilization attempts, and possible problems facing technology from the viewpoint of financial industry, and suggests a policy direction for utilizing this technology as a catalyst to the progress of the financial industry or as a new technology power.

Structural Influence of SNS Social Capital on SNS Health Information Utilization Level (SNS의 사회적자본이 건강정보 활용수준에 미치는 구조적 영향력)

  • Park, Jaesung;Kim, Kyeong-Na
    • The Korean Journal of Health Service Management
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    • v.14 no.2
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    • pp.1-14
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    • 2020
  • Objectives : The purpose of this study was to test fitness of the structured model of SNS activities for health information. Methods : A structured questionnaire were administered to 500 subjects. A structural equation model was applied to collected data. Results : The response rate was 73.9%. The respondents mostly used Facebook and KakaoStory. They spent 70 minutes per day and 21~30% of this usage was taken by health information. In the variances, those who has religion more actively exchanged information about diseases and medical institutions. The goodness-of-fit of the model was .81(GFI) and .90(CFI). The main path was bridging capital -> bonding capital -> credibility -> SNS activities for health information. The path from quality of sharing information to SNS activities was not significant. It could be explained by the restriction of digital literacy. Conclusions : SNS activities for health information were determined by credibility, currency and bonding social capital. Bridging social capital, indirectly, influenced SNS activities through bonding social capital. Thus building bonding social capital would be a critical success factor for SNS.

Secured Different Disciplinaries in Electronic Medical Record based on Watermarking and Consortium Blockchain Technology

  • Mohananthini, N.;Ananth, C.;Parvees, M.Y. Mohamed
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.3
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    • pp.947-971
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    • 2022
  • The Electronic Medical Record (EMR) is a valuable source of medical data intelligence in e-health systems. The watermarking techniques have been used to authenticate the owner and protect the EMR from illegal copying. The existing distributive strategies, successfully operated to secure the EMR, are found to be inadequate. Blockchain technology, mainly, is employed by a sharing database that allows the digital crypto-currency. It rapidly leads to the magnified expectations acme. In this excitement, the use of consortium adopting the technology based on Blockchain, in the EMR structure, is found improving. This type of consortium adds an immutable share with a translucent record of the entire business and it is accomplished with responsibility, along with faith and transparency. The combination of watermarking and Blockchain technology provides a singular chance to promote a secured, trustworthy electronic documents administration to share with the e-records system. The authors, in this article, present their views on consortium Blockchain technology which is incorporated in the EMR system. The ledger, used for the distribution of the block structure, has team healthcare models based on dissimilar multiple image watermarking techniques.

Convergence analysis about volatility of the stock markets before and after the currency crisis - With a focus on Normal distribution, kurtosis, skewness (외환위기 전후 주식시장의 변동성에 관한 융복합 분석 - 정규분포, 첨도, 왜도를 중심으로)

  • Choi, Jeong-Il
    • Journal of Digital Convergence
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    • v.13 no.8
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    • pp.153-160
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    • 2015
  • The domestic stock market has been subjected to a major change since the September 1997 financial crisis. Foreign capital came repeat themselves in the stock market and bond market, foreign exchange market opening up domestic financial markets after the financial crisis. The domestic stock market has been most affected by domestic capital before the financial crisis. But it has been receiving an absolute influenced by foreign capital after the financial crisis. The purpose of this study is to analyze the trends in the two sections that look at any changes in the volatility of the KOSPI appears after the crisis. To this, obtained a daily weekly monthly normal distribution and kurtosis, skewness degree it should be analyze the tilt phenomenon and variability of the two intervals. This study also predict the future movement of the domestic stock market Based on this, look at the difference between the two sections. Analysis result, after the financial crisis change width has a reduction but direction of the KOSPI has appeared relatively distinct in the medium to long term. Based on this future market seems desirable the mid- to long-term investment looking for direction.

A Study on the Investment Efficiency of Korean ETFs (한국상장지수펀드(ETF)의 투자효율성에 관한 연구)

  • Jung, Hee-Seog
    • Journal of Digital Convergence
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    • v.16 no.5
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    • pp.185-197
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    • 2018
  • The purpose of this study is to analyze the Korean ETF market, which is experiencing a rapid increase in the number of stocks, to identify the degree of investment efficiency and to present investment directions. The methodology and procedure are ETF yield, change trends, correlation and regression analysis of the ETFs traded between 2010 and 2018. As a result, the total return of domestic ETFs was 3.51%, which was lower than the KOSPI growth rate and the return on equity ETFs was 4.03%, which was low. Leverage ETF yields were below 3%, which was low. The return on bond and currency ETFs was less than 1%. The most profitable ETFs were index ETFs, followed by domestic and leveraged ETFs. This study has contributed to establishing considerations when purchasing ETFs from the viewpoint of investors. Future research will present the direction of ETF investment more precisely.

A Research on stock price prediction based on Deep Learning and Economic Indicators (거시지표와 딥러닝 알고리즘을 이용한 자동화된 주식 매매 연구)

  • Hong, Sunghyuck
    • 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.

A study on stock price prediction system based on text mining method using LSTM and stock market news (LSTM과 증시 뉴스를 활용한 텍스트 마이닝 기법 기반 주가 예측시스템 연구)

  • Hong, Sunghyuck
    • Journal of Digital Convergence
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    • v.18 no.7
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    • pp.223-228
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    • 2020
  • The stock price reflects people's psychology, and factors affecting the entire stock market include economic growth rate, economic rate, interest rate, trade balance, exchange rate, and currency. The domestic stock market is heavily influenced by the stock index of the United States and neighboring countries on the previous day, and the representative stock indexes are the Dow index, NASDAQ, and S & P500. Recently, research on stock price analysis using stock news has been actively conducted, and research is underway to predict the future based on past time series data through artificial intelligence-based analysis. However, even if the stock market is hit for a short period of time by the forecasting system, the market will no longer move according to the short-term strategy, and it will have to change anew. Therefore, this model monitored Samsung Electronics' stock data and news information through text mining, and presented a predictable model by showing the analyzed results.

Analysis of the Ripple Effect of the US Federal Reserve System's Quantitative Easing Policy on Stock Price Fluctuations (미국연방준비제도의 양적완화 정책이 주가 변동에 미치는 영향 분석)

  • Hong, Sunghyuck
    • Journal of Digital Convergence
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    • v.19 no.3
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    • pp.161-166
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    • 2021
  • The macroeconomic concept represents the movement of a country's economy, and it affects the overall economic activities of business, government, and households. In the macroeconomy, by looking at changes in national income, inflation, unemployment, currency, interest rates, and raw materials, it is possible to understand the effects of economic actors' actions and interactions on the prices of products and services. The US Federal Reserve System (FED) is leading the world economy by offering various stimulus measures to overcome the corona economic recession. Although the stock price continued to decline on March 20, 2020 due to the current economic recession caused by the corona, the US S&P 500 index began rebounding after March 23 and to 3,694.62 as of December 15 due to quantitative easing, a powerful stimulus for the FED. Therefore, the FED's economic stimulus measures based on macroeconomic indicators are more influencing, rather than judging the stock price forecast from the corporate financial statements. Therefore, this study was conducted to reduce losses in stock investment and establish sound investment by analyzing the FED's economic stimulus measures and its effect on stock prices.

Using High Resolution Satellite Imagery for New Address System (도로명 및 건물번호 부여사업에서 고해상도 위성영상의 활용)

  • Bae, Sun-Hak;Kim, Chang-Hwan;Shin, Young-Chul
    • Journal of the Korean Association of Geographic Information Studies
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    • v.6 no.4
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    • pp.109-121
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    • 2003
  • The point of this research is the use of the high resolution satellite image for local government's new address system, as well as spatially field investigation support and base map error finding. Most local governments use scale 1/1,000 and 1/5,000 digital map for base map and field investigation. But field investigator's knowledge insufficiency and the lack of base map's currency make things too difficult from the beginning of the project. As the way of solving this problem, this research offers the use of the high resolution satellite image in new address system with cadence data of digital base map. Until now satellite image is not suitable for our situation because it has low resolution. But this problem was solved for 1m space resolution satellite image and it is being applied wider and wider. Now vector data and Raster data are integrated for complimenting of each weak point. In this study the use of the high resolution satellite image in new address system is expected to improve the quality of the results and reduce the expenses. In addition the satellite image can use local government's fundamental data.

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