• 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.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.28 no.3
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• pp.171-174
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• 2022

Cosmetic packing materials tend to be difficult to recycle when discarded due to the cosmetic industry's pursuit of aesthetics, functionality, and high value-added design. Pump packaging, which is widely used for the good preservation and discharge of cosmetics contents, is difficult to be separated and recycled because of a metal spring, which is in charge of pump resilience. In this study, a polypropylene spring was developed to replace the existing metal spring to improve the recyclability of the pump packaging for cosmetics, and was uni-materialized by applying to the cosmetic packing materials with 0.2 ml of discharge amount. In addition, performance test was conducted to verify the equivalence with the existing metal spring pumps as grounds for the commercialization of metal-free uni material pump packaging. The decompression leak test showed no leakage and displayed 14.8~17.5 N of pressing strength, 2.3~8.8 % of deviation in dispensing volume, and 4 occasions of pumping for initial discharge.

• Journal of Chest Surgery
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• v.40 no.3 s.272
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• pp.159-167
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• 2007

Background: Vocabularies originating from Chinese characters constitute an important common factor in the medical terminologies used 3 eastern Asian countries; Korea, China and Japan. This study was performed to comparatively analyze the medical terminologies of these 3 countries in the field of cardiopulmonary bypass (CPB) and; thereby, facilitate further understanding among the 3 medical societies. Material and Method: A total of 129 English terms (core 85 and related 44) in the field of CPB were selected and translated into each country's official terminology, with help from Seoul National University Hospital (Korea), Tokyo Michi Memorial Hospital(Japan), and Yanbian Welfare Hospital and Harbin Children Hospital (China). Dictionaries and CPB textbooks were also cited. In addition to the official terminology used in each country, the frequency of use of English terms in a clinical setting was also analyzed. Result and Conclusion: Among the 129 terms, 28 (21.7%) were identical between the 3 countries, as based on the Chinese characters. 86 terms were identical between only two countries, mostly between Korea and Japan. As a result, the identity rate in CPB terminology between Korea and Japan was 86.8%; whereas, between Korea and China and between Japan and China the rates were both 24.8%. The frequency of use of English terms in clinical practices was much higher in Korea and Japan than in China. Despite some inherent limitations involved in the analysis, this study can be a meaningful foundation in facilitating mutual understanding between the medical societies of these 3 eastern Asian countries.

• Journal of the Korean Society of Food Science and Nutrition
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• v.36 no.1
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• pp.14-19
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• 2007

This study was conducted to analyze the antioxidant activity and xanthine oxidase inhibitory effect of hot-water extracts from Elaeagnus multiflora Thunb. to provide fundamental data for the development of functional materials. The antioxidative activities of hot-water extracts from E. multiflora Thunb. were analyzed by electron donating ability (EDA) using 1,1-diphenyl-2-picryl hydrazyl (DPPH), superoxide dismutase (SOD) -like activity by pyrogallol and nitrite scavenging ability. EDA of extracts from unripe, ripe, and overripe fruits were 77.7%, 36.0%, and 23.7% at 100 ${\mu}g/mL$, respectively, and EDA of extract in unripe fruits was higher than those of others. At 1,000 $\mu$g/mL, the SOD-like activities were 32.8%, 11.2% and 5.0% for unripe, ripe, and overripe fruits, respectively. The SOD-like activity was increased along with the increase of unripe and ripe extract concentrations. The nitrite scavenging ability of unripe fruit extracts in 100, 300, 500 ${\mu}g/mL$ of extraction solution in pH 1.2 and 3.0 was higher than those of others. The nitrate scavenging ability of all extracts was decreased according to the increase of pH. Xanthine oxidase inhibitory activities of unripe, ripe and overripe fruits were 30.0%, 28.2%, and 18.2% at 1,000 ${\mu}g/mL$, respectively.

• The Korean Journal of Applied Statistics
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• v.22 no.2
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• pp.261-270
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• 2009

Current financial crisis triggered by shaky U.S. banking system adds to the emphasis on the importance of the volatility in controlling and understanding financial time series data. The ARCH and GARCH models have been useful in analyzing economic time series volatilities. In particular, multivariate GARCH(MGARCH, for short) provides both volatilities and conditional correlations between several time series and these are in turn applied to computations of hedge-ratio and VaR. In this short article, we try to assess various MGARCH models with respect to the back-testing performances in VaR study. To this end, 14 korean stock prices are analyzed and it is found that MGARCH outperforms rolling window, and BEKK and CCC are relatively conservative in back-testing performance.

• Resources Recycling
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• v.20 no.1
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• pp.14-27
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• 2011

In order to review the End-of Life Vehicle(ELV) recycling system and recycling business of dismantlers in Japan, scheme of the automobile recycling law, status of ELV recycling, exports of used cars, ELV marketing business of dismantler and upgrading of used parts net work were studied. On the other hand, field survey in details for dismantling works were conducted at West-Japan Auto Recycling Co.. Although the ELV recycling system has been operating smoothly without any noticeable trouble, recycling business is running under severe circumstance. Exports of used cars have been increasing day by day through worldwide 176 countries. Finally, reuse parts of ELV concerning innovation marketing was discussed.

• KIISE Transactions on Computing Practices
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• v.23 no.11
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• pp.625-631
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• 2017

The stock price prediction for stock markets remains an unsolved problem. Although there have been various overtures and studies to predict the price of stocks scientifically, it is impossible to predict the future precisely. However, stock price predictions have been a subject of interest in a variety of related fields such as economics, mathematics, physics, and computer science. In this paper, we will study fluctuation patterns of stock prices and predict future trends using the Deep learning. Therefore, this study presents the three deep learning models using Tensorflow, an open source framework in which each learning model accepts different input features. We expand the previous study that used simple price data. We measured the performance of three predictive models increasing the number of priced-based input features. Through this experiment, we measured the performance change of the predictive model depending on the price-based input features. Finally, we compared and analyzed the experiment result to evaluate the impact of the price-based input features in stock price prediction.

• Journal of Distribution Science
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• v.17 no.9
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• pp.117-125
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• 2019

Purpose - We investigate how to increase consumer incentives to buy public offering funds, resulting in activating the public offering fund market. In particular, this study aims to find ways to expand diversity and to improve efficiency of public offering fund. The public fund market of Korea has been stagnant in recent years. However, the public offering fund market plays a very significant role in terms of consumer welfare. Since only a few wealthy investors can participate in the private equity market, the stagnation in the public offering fund market usually reduces the opportunity of consumer's buying funds thus ultimately affecting their future wealth. Research design, data, and methodology - To attain our purpose, the 'factor-based portfolio strategy' has been considered. It is an alternative portfolio strategy, which composites the advantages of the passive management and active management. For our empirical anaylsis, we used global stock distribution market data over the period of 1991 and 2016. Then we constructed portfolios based on firm-size, firm-value, and momentum. Finally, a regression model was set, then hypotheses were tested, analyzing the performances. Results - First, among the 15 factor-based portfolios of global, Europe, Asia-Pacific(ex Japan), US and Japan, in eight portfolios, positive excess returns are observed at 5% significance level. Further, there is another portfolio with positive excess return at 10% significance level. Second, most of the portfolios with significant excess performance show positive relationship with the market portfolio. However, the firm-value based portfolio in Asia-Pacific region shows no relationship, and the firm-value based portfolio in US shows negative relationship. Third, we confirmed that the two firm-value factor portfolios in Asia-Pacific region and US, not having positive relationship with market portfolio, provide significant excess returns. Conclusions - In this paper, we provide empirical evidences supporting that the factor-based portfolios expand the diversity of funds and improve the efficiency of investment performance. However, there is no guarantee that the efficiency will continue in the future. In addition, various constraints and costs must be considered. Nevertheless, our novel findings in the advanced financial market such as US and Asia-Pacific are very interesting and offers important implications.

• Korean Management Science Review
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• v.30 no.1
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• pp.73-89
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• 2013

This paper develops an investment algorithm based on Markowitz's Portfolio Selection Theory, using historical stock return data, and empirically evaluates the performance of the proposed algorithm in the U.S. and the Hong Kong stock markets. The proposed investment algorithm is empirically tested with the 30 constituents of Dow Jones Industrial Average in the U.S. stock market, and the 30 constituents of Hang Seng Index in the Hong Kong stock market. During the 6-year investment period, starting on the first trading day of 2006 and ending on the last trading day of 2011, growth rates of 12.63% and 23.25% were observed for Dow Jones Industrial Average and Hang Seng Index, respectively, while the proposed investment algorithm achieved substantially higher cumulative returns of 35.7% in the U.S. stock market, and 150.62% in the Hong Kong stock market. When compared in terms of Sharpe ratio, Dow Jones Industrial Average and Hang Seng Index achieved 0.075 and 0.155 each, while the proposed investment algorithm showed superior performance, achieving 0.363 and 1.074 in the U.S. and Hong Kong stock markets, respectively. Further, performance in the U.S. stock market is shown to be less sensitive to an investor's risk preference, while aggressive performance goals are shown to achieve relatively higher performance in the Hong Kong stock market. In conclusion, this paper empirically demonstrates that an investment based on a mathematical model using objective historical stock return data for constructing optimal portfolios achieves outstanding performance, in terms of both cumulative returns and Sharpe ratios.