• Journal of Broadcast Engineering
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• v.27 no.5
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• pp.751-761
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• 2022

With the development of digital graphics technology, the metaverse has become a significant trend in the content market. The demand for technology that generates high-quality 3D (dimension) models is rapidly increasing. Accordingly, various technical attempts are being made to create high-quality 3D virtual humans represented by digital humans. 3D volumetric capture is spotlighted as a technology that can create a 3D manikin faster and more precisely than the existing 3D model creation method. In this study, we try to analyze 3D high-precision facial production technology based on practical cases of the difficulties in content production and technologies applied in volumetric 3D and 4D model creation. Based on the actual model implementation case through 3D volumetric capture, we considered techniques for 3D virtual human face production and producted a new metahuman using a graphics pipeline for an efficient human facial generation.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.380-380
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• 2020

가뭄 피해 극복을 위한 인공 함양지 통합관리시스템의 일부로써 지표수-지하수 연계 특성 분석용 의사결정을 전달하는 인공지능 스마트 계측기의 필요성이 꾸준히 제기되어 왔으나 실용성과 효율성을 동시에 갖춘 계측기는 시장에 출시되지 않았다. 기존의 계측기는 단순 측정이 목적이었으며 분석을 위해서는 일정 기간 직접 계측하여 분석하거나, 계측데이터를 원격 망을 통하여 서버로 전송하고 관리자가 데이터를 해석하는 방식을 취하였다. 또한, 수질 계측과 수질의 미소 변동성을 동시에 계측하여 수질 변화상태를 판단 할 수 있는 수질 계측기는 상품화되지 않아 다목적 수질 분석에 한계점을 갖고 있다. 이러한 한계점이 기존의 지하수 수질 계측기로는 불가능한 수중 라돈을 채수 없이 계측 가능하도록 하고, 순간 수질 변화 및 수질 변화 요인분석이 가능한 계측을 위하여 라돈, 전도도, 수위, 수온 및 필름형 pH 센서를 개발하여 적용한 다항목 계측기로 통합하는 연구가 필요한 이유이다. 개발한 계측기는 빅데이터 기반의 지능형 수질 변동성 분석 알고리즘을 내장하고 수직 깊이 방향의 다중심도 계측이 가능하도록 핵심적인 통신 연결성을 확보하였고 다양한 수질에서 견딜 수 있으며 특히 인공함양에서 발생하는 철, 망간에 부식되지 않는 재질을 이용하여 설계한 '지표수-지하수 연계 특성 분석용 다심도 및 인공지능 스마트 계측장치'이다. 본 장치는 기존 지하수 수질 계측기에서는 불가능하였던 순간 수위변화 및 수위변화 요인분석이 가능한 계측을 위하여 초당 측정 샘플링 주파수(10Hz)를 높인 계측회로를 개발하여 적용하였다.

• Asia-Pacific Journal of Business
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• v.13 no.4
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• pp.45-59
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• 2022

Purpose - This study investigates the performance of investment strategies incorporating estimated stock market cycle based on a lead-lag relationship between business cycle and stock market cycle, thereby deriving empirical implications on risk management. Design/methodology/approach - The data period ranges from June 1953 to September 2022 and de-trended short rate, term spread, credit spread, stock market volatility are considered as major input variables to estimate business cycle and stock market cycle by applying probit model. Based on the estimated stock market cycle, two types of strategies are constructed and their performance relative to the benchmark is empirically examined. Findings Two types of strategies based on stock market cycle are considered: The first strategy is to long(short) on stocks when stock market stage is expected to be an expansion(a recession), and the second one is to long on stocks(bonds) when expecting an expansion(a recession). The empirical results show that the strategies based on stock market cycle outperforms a simple buy and hold strategy in both in-sample and out-of-sample investigation. Also the out-of-sample evidence suggests that the second strategy which is in line with asset allocation is more profitable than the first one. Research implications or Originality The strategies considered in this study are based on the estimated stock market cycle which only depends on a few easily available financial variables, thereby making easier to establish such a strategy. It implies that investors enhance investment performance by constructing a relatively simple trading strategies if they set their position on stocks or choose which asset class to buy conditioning on stock market cycle.

• Asia-Pacific Journal of Business
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• v.14 no.1
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• pp.265-279
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• 2023

Purpose - The purpose of this paper is to compare and review behavioral economics models that explain stock price changes after large-scale price shocks in the Korean stock market and to find a suitable model. In this paper, among the theories reviewed, it was confirmed that the anchoring heuristics theory has high explanatory power for stock prices after large-scale stock price fluctuations. Design/methodology/approach - This paper conducts an event study on stock price shocks in which the individual stocks that make up the KOSPI200 index show more than 10% fluctuation on a daily basis. In order to materialize the abstract predictions of heuristics theories in a varifiable form, this paper uses the daily stock price index change as a reference point for availability heuristics, and uses the 52-week highest and lowest price as reference point for anchoring heuristics. Research implications or Originality - As a result of the empirical analysis, the stock price reversals did not consistently appear for changes in the daily index. On the other hand, the stock price drifts consistently appeared around the 52-week highest and the 52-week lowest price. And in the multiple regression analysis that controlled for company-specific and event-specific variables, the results that supported the anchoring heuristics were more evident. These results suggest that it is possible to establish an investment strategy using large-scale price change in Korean stock market.

• International Area Studies Review
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• v.15 no.1
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• pp.219-240
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• 2011

The main purpose of this study is to analyze the effects of stock price and real estate price on the money demand. We investigated the demand for money for 25 money units of 10 countries. To estimate the money demand functions, Johansen's cointegration and ARDL-bounds test were employed. Additionally, Stock and Watson's DOLS method was applied to estimate long-run cointegration vectors. According to the results of cointegration test, stock price and real estate price are crucial in the long-run equilibrium relationship. There were no cointegration relationships among money demand, real income, interest rate, and exchange rate in 12 money unit models. However, by including stock price and real estate price on the tested models, we could find strong cointegration relationships, using ARDL-bounds test. The results of DOLS confirm that stock price and real estate price are effective factors influencing on money demands. Especially, the coefficient of real estate price is statistically significant in the 19 out of 20 money unit models. However, the direction and magnitude of coefficients of asset prices are different across countries and money units.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.76-76
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• 2023

최근 자율주행과 관련한 시장의 관심은 기존 자동차 자율주행에서 선박 자율운항으로 자연스럽게 이동하고 있다. 이에 인공지능 및 빅데이터 등과 같은 최근 기술을 선박 자율주행에 적용하는 자율운항선박(MASS: Maritime Autonomous Surface Ship) 개발이 활발히 진행되고 있으며, 레이더 및 카메라 등과 같은 센서 정보를 선박 자율운항에 적용하여 다양한 선박 운동 및 정보를 획득하는 연구 기술이 집중되고 있다. 이러한 경향에 따라 IMO(International Maritime Organization)과 같은 국제기구에서도 자율운항선박 표준화 본격 논의로 기술표준 선점 경쟁에 참여하고 있다. 이 중 연안 자율운항선박 개발은 IMO에서 주관하는 무인화 핵심기술로 여겨지고 있어, 기존 대양 항해 기술과 함께 연안 항해에 대한 기술 개발의 중요성이 높아지고 있다. 특히 항만 인근 해역에서는 다수의 선박이 입출항함으로 인해 해상에서의 안전과 물류의 효율화가 요구되기 때문에 고도화된 자율운항 기술개발이 필요하다. 하지만 자율운항선박에서의 상황인식 기술은 탑재된 센서의 제한된 시야각 및 기상조건에 따른 인식률이 떨어지는 문제가 생긴다. 이러한 기술적 한계를 극복하기 위해 육상에 설치된 레이더를 활용하여 선박을 탐지할 수 있는 기술이 필요하다. 본 연구에서는 고해상도 육상 레이더를 기반하여 얻어진 레이더 화면상의 물표 정보를 이용해 인공지능 기법에 활용하기 위한 라벨링 자동 생성 방법에 대해 소개한다. 얻어진 물표 정보에 인공지능 기법을 적용하여 선박 길이 정보를 추정하는 기술에 대해 소개한다.

• Journal of the Korea Society of Computer and Information
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• v.29 no.6
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• pp.77-87
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• 2024

In this paper, we propose a study applying the Delphi technique to domestic blockchain experts to determine urgent and pivotal conditions for NFT proliferation. We examine these conditions from a PEST (Political, Economic, Social, and Technological Analysis of the Macro Environment) perspective, as well as the functions of digital assets (measurement, storage, and exchange). Through two rounds of expert surveys on the seven NFT perspectives, we identify 6 activating factors that can help guide future policy-making for the NFT market. These factors have broad implications for the development of new industries using blockchain technology and tokens. The Delphi method employed in this study is a group discussion technique that gathers opinions from experts anonymously through two rounds and to address drawbacks related to expert selection bias and opinion alignment, additional opinion collection and review of projections were conducted in each round.

• Information Systems Review
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• v.22 no.4
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• pp.135-161
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• 2020

With the growth of blockchain and cryptocurrency-related markets, cryptocurrency exchanges are growing as a new industry. However, as the legal and regulatory definitions of cryptocurrencies are still in progress, unlike existing industrial groups, they are not under the supervision of regulatory agencies. As a result, users (i.e., cryptocurrency investors) have suffered two types of damage that could occur from hacking and other accidents on the exchanges. One type of the damage is the loss of assets caused by the extortion of personal information or account and the other is the damage from users who might be involved in external frauds. Both are analyzed in comparison with existing operators whose functions are like the exchanges. The results of this study show that membership (KYC: Know Your Client), log-in, and additional authentication in transactions are on the similar level to those of the operators while the fraud detection system (FDS) and anti-money laundering (AML) of fiat currencies and cryptocurrencies need rapid improvement.

• Asia-Pacific Journal of Business
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• v.15 no.2
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• pp.143-157
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• 2024

Purpose - This paper aims to analyze the relationship and correlation between the stock markets of Korea, the US, China, and Japan before and after the outbreak of COVID-19. Design/methodology/approach - This study conducted an empirical analysis using the stock market data from January 2016 to June 2023 for the representative market indices of Korea, the US, China, and Japan. The analysis employed the VAR model, Granger causality test, impulse response function, and variance decomposition. Findings - Analyzing the relationships of these stock markets before and after the outbreak of COVID-19, we obtained the following results. (i) The influence of the U.S. stock market was found to be absolute regardless of the COVID-19 period, and the rise in the U.S. stock market led to rises in other stock markets. (ii) The Chinese stock market had a significant negative impact on the U.S., Korean, and Japanese stock markets before COVID-19, but this influence disappeared after COVID-19. This suggests that the Chinese market exhibited unique characteristics different from the global market after COVID-19. (iii) Analyzing the period excluding the first quarter of 2020, when global stock market volatility was extremely high due to the spread of COVID-19, we found that the results were very similar to the analysis including the first quarter of 2020. Therefore, it is difficult to argue that the increased uncertainty during this period distorted the relationships among the stock markets of these four countries. Research implications or Originality - We anticipate that these findings will offer valuable insights for both individual and institutional investors, aiding them in portfolio diversification and risk mitigation.

• Journal of the Institute of Convergence Signal Processing
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• v.25 no.1
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• pp.39-45
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• 2024

Recently, the paradigm of the aircraft industry, not only domestically but also globally, has been changing significantly starting with the era of the Fourth Industrial Revolution. With the convergence of new technologies such as ICT and AI, the drone market, centered around the military, is expanding its overall services to include the civilian market. Additionally, drones operate by being equipped with batteries, and for product lines that use batteries, lightening the product is one of the critical factors. This is because the lighter the aircraft, the less battery consumption and maximum efficiency. Therefore, recently, composite materials have been used to reduce the weight of the aircraft. To not only reduce weight but also achieve high functionality, it is being applied to most areas such as propellers, airframes, interior materials, floor plates, driving devices, and battery housings, and is emerging as a core technology. In this paper will utilize ceramic fiber composite materials, which have recently emerged for lightweight. It aims to improve noise and strength by targeting propellers, one of the most important factors in drones. In addition, the performance of the propeller developed through the low-noise design will be verified.