• Journal of Convergence for Information Technology
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• v.12 no.3
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• pp.116-125
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• 2022

The purpose of this study is to analyze whether investor anxiety caused by COVID-19 affects cryptocurrency prices in the COVID-19 pandemic, and to experiment with cryptocurrency price prediction based on a deep learning model. Investor anxiety is calculated by combining Naver's Corona search index and Corona confirmed information, analyzing Granger causality with cryptocurrency prices, and predicting cryptocurrency prices using deep learning models. The experimental results are as follows. First, CCI indicators showed significant Granger causality in the returns of Bitcoin, Ethereum, and Lightcoin. Second, LSTM with CCI as an input variable showed high predictive performance. Third, Bitcoin's price prediction performance was the highest in comparison between cryptocurrencies. This study is of academic significance in that it is the first attempt to analyze the relationship between Naver's Corona search information and cryptocurrency prices in the Corona phase. In future studies, extended studies into various deep learning models are needed to increase price prediction accuracy.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.3
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• pp.1-9
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• 2017

Financial instruments are economic and intangible assets that bring financial company tremendous economic returns when it is a success. Also, It is necessary to protect this because it is a product of effort made by a lot of human resources and materials. However, legal and institutional devices for financial instruments are insufficient currently and 'copying practices' are rampant throughout the industry in korea. This ultimately inhibits the utility and welfare of consumers, but also adversely affects the competitiveness of the financial industry. In order to finance innovation that new financial products and services have appeared, it is necessary to grant the appropriate rights, such as intellectual property rights of financial instruments. And, there is a need for measures to protect it. Thus, this study proposed new way protecting the financial instruments through Intellectual property right. It is the introduction of similar protection system to financial instruments, such as mechanisms that protect database producers in copyright law.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.66.3-67
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• 2021

Low-mass stars form by the gravitational collapse of dense molecular cores. Observations and theories of low-mass protostars both suggest that accretion bursts happen in timescales of ~100 years with high accretion rates, so called episodic accretion. One mechanism that triggers accretion bursts is infalling fragments from the outer disk. Such fragmentation happens when the disk is massive enough, preferentially activated during the embedded phase of star formation (Class 0 and I). Most observations and models focus on the gas structure of the protostars undergoing episodic accretion. However, the dust and ice composition are poorly understood, but crucial to the chemical evolution through thermal and energetic processing via accretion burst. During the burst phase, the surrounding material is heated up, and the chemical compositions of gas and ice in the disk and envelope are altered by sublimation of icy molecules from grain surfaces. Such alterations leave imprints in the ice composition even when the temperature returns to the pre-burst level. Thus, chemical compositions of gas and ice retain the history of past bursts. Infrared spectral observations of the Spitzer and AKARI revealed a signature caused by substantial heating, toward many embedded protostars at the quiescent phase. We present the AKARI IRC 2.5-5.0 ㎛ spectra for embedded protostars to trace down the characteristics of accretion burst across the evolutionary stages. The ice compositions obtained from the absorption features therein are used as a clock to measure the timescale after the burst event, comparing the analyses of the gas component that traced the burst frequency using the different refreeze-out timescales. We discuss ice abundances, whose chemical change has been carved in the icy mantle, during the different timescales after the burst ends.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.2
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• pp.160-167
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• 2023

This study focuses on the development of a Last-Mile delivery service using unmanned vehicles to deliver goods directly to the end consumer utilizing drones to perform autonomous delivery missions and an image-based precision landing algorithm for handoff to a robot in an intermediate facility. As the logistics market continues to grow rapidly, parcel volumes increase exponentially each year. However, due to low delivery fees, the workload of delivery personnel is increasing, resulting in a decrease in the quality of delivery services. To address this issue, the research team conducted a study on a Last-Mile delivery service using unmanned vehicles and conducted research on the necessary technologies for drone-based goods transportation in this paper. The flight scenario begins with the drone carrying the goods from a pickup location to the rooftop of a building where the final delivery destination is located. There is a handoff facility on the rooftop of the building, and a marker on the roof must be accurately landed upon. The mission is complete once the goods are delivered and the drone returns to its original location. The research team developed a mission planning algorithm to perform the above scenario automatically and constructed an algorithm to recognize the marker through a camera sensor and achieve a precision landing. The performance of the developed system has been verified through multiple trial operations within ETRI.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.2
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• pp.102-108
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• 2023

Recently in Korea, YouTube stock channels increased rapidly due to the high social interest in the stock market during the COVID-19 period. Accordingly, the role of new media channels such as YouTube is attracting attention in the process of generating and disseminating market information. Nevertheless, prior studies on the market forecasting power of YouTube stock channels remain insignificant. In this study, the market forecasting power of the information from the YouTube stock channel was examined and compared with traditional news media. To measure information from each YouTube stock channel and news media, positive and negative opinions were extracted. As a result of the analysis, opinion in channels operated by media outlets were found to be leading indicators of KOSPI market returns among YouTube stock channels. The prediction accuracy by using logistic regression model show 74%. On the other hand, Sampro TV, a popular YouTube stock channel, and the traditional news media simply reported the market situation of the day or instead showed a tendency to lag behind the market. This study is differentiated from previous studies in that it verified the market predictive power of the information provided by the YouTube stock channel, which has recently shown a growing trend in Korea. In the future, the results of advanced analysis can be confirmed by expanding the research results for individual stocks.

• Asia-Pacific Journal of Business
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• v.14 no.1
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• pp.73-91
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• 2023

Purpose - The purpose of this study is to re-examine the disclosure effect of stock splits and long-term performance after stock splits using stock split data over the past 10 years, and infer the motivation (signal or opportunism) of stock splits. In addition, we focus on exploring the determinants of the short- and long-term market response to stock splits. Design/methodology/approach - We measure the short-term market response to a stock split and the long-term stock performance after the stock split announcement using the event study method. We analyze whether there is a difference in the long-term and short-term market response to a stock split according to various company characteristics through univariate analysis and regression analysis. Findings - In the case of the entire sample, a statistically significant positive excess return is observed on the stock split announcement date, and the excess return during the 24-month holding period after the stock split do not show a difference from zero. In particular, the difference between short-term and long-term returns on stock splits is larger in companies with a large stock split ratio, small companies, large growth potential, and companies with a combination of financial events after a stock split. Research implications or Originality - The results of this study suggest that at least the signal hypothesis for a stock split does not hold in the Korean stock market. On the other hand, it suggests that there is a possibility that a stock split can be abused by the manager's opportunistic motive, and that this opportunism can be discriminated depending on the size of the stock split, corporate characteristics, and financing plan.

• Knowledge Management Research
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• v.24 no.2
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• pp.1-25
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• 2023

While organizational learning (OL) is vital for ventures to build knowledge bases necessary for successful innovation, less attention has been paid to how learning organizations leverage it for performance improvement. We investigate entrepreneurial orientation's (EO) role in performance-by-learning mechanisms underpinning ventures' innovative initiatives, adopting dyadic performance indicators: technological competitiveness and business performance. Analyzing 218 Korean ventures, our study shows that firms valuing OL, characterized by acquisitive and experimental learning, exhibit high EO, facilitating productive use of knowledge-based resources and enhancing performance. Importantly, EO fully mediates the performance implications of OL. Our findings suggest that a comprehensive learning approach for knowledge acquisition and experimentation provides ventures, often facing smallness and newness liabilities, with a fertile entrepreneurial ground for increased innovation returns.

• The Journal of Bigdata
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• v.7 no.2
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• pp.129-137
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• 2022

With the development of the 4th industry, the logistics industry is evolving into a smart logistics system. However, ship work that transports vehicles is progressing slowly due to various problems. In this paper, we propose an stowage automation algorithm that can be used for cargo loading of vehicle carriers that shortens loading and unloading work time. The stowage automation algorithm returns the shortest distance by searching for a loading space and a movable path in the ship in consideration of the structure of the ship. The algorithm identifies walls, ramps and vehicles that have already been shipped, and can work even with randomly placed. In particular, it is expected to contribute to developing a smart logistics system for vehicle carriers by referring to the ship's master plan to search for vehicle loading and unloading space in each port and predict the shortest movable path.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.1
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• pp.32-41
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• 2023

Recently, many studies are being conducted to extract emotion from text and verify its information power in the field of finance, along with the recent development of big data analysis technology. A number of prior studies use pre-defined sentiment dictionaries or machine learning methods to extract sentiment from the financial documents. However, both methods have the disadvantage of being labor-intensive and subjective because it requires a manual sentiment learning process. In this study, we developed a financial sentiment dictionary that automatically extracts sentiment from the body text of analyst reports by using modified Bayes rule and verified the performance of the model through a binary classification model which predicts actual stock price movements. As a result of the prediction, it was found that the proposed financial dictionary from this research has about 4% better predictive power for actual stock price movements than the representative Loughran and McDonald's (2011) financial dictionary. The sentiment extraction method proposed in this study enables efficient and objective judgment because it automatically learns the sentiment of words using both the change in target price and the cumulative abnormal returns. In addition, the dictionary can be easily updated by re-calculating conditional probabilities. The results of this study are expected to be readily expandable and applicable not only to analyst reports, but also to financial field texts such as performance reports, IR reports, press articles, and social media.

• Journal of English Language & Literature
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• v.53 no.2
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• pp.219-241
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• 2007

This study takes its point of departure from Lacanian psychoanalysis and explores the point that an irremediable gap in the human subject can be illuminated in terms of the Lacanian categories, fantasy, symptom, gaze or voice as cause of desire of the Other. With respect to the category of the symptom, Lacan claims that the Other is always already there in the constitution of the subject, that is, the relation of the subject to the Other that is overwhelming as well as attracting the subject. Chapter II deals with the unthought, excessive ground of the conscious that borders on the subject, as is the case of self-excentric aspect of the man. Indeed, in Lacan's early work, the subject is essentially a relationship to the Other as desire(objet petit a), and there is no such thing as a symptom or fantasy without some subjective involvement. Lacanian unknown real, perpetual excess as the cause of desire animates the subject even as it threatens to blast it apart. The structures that establish the lines of desire in every individual are derived from an ineluctably intersubjective field. The Other is always already there in the constitution of the subject. In the final years of Lacan's teaching we find a kind of universalization of the symptom and almost everything that is becomes in a way symptom. Symptom, embodied in Laura in "Goblin Market," is her only substance, the only positive support of her being. By looking at the Laura's symptom in chapter III we gain an insight into the forbidden domain, into a real space that should be left unseen and unthought. The voice of goblin men therefore functions as a sublime object that is animating as well as dominating element even as it threatens to disintegrate the subject. Objet petit a as a sublime object that must be excluded in reality returns in the real, taking on a certain materiality which has an effect on Laura, that is, animates Laura's desire. Objet petit a is a real object, signifying nothing. In conclusion, the theoretical importance of Lacanian psychoanalysis is the relation between a subject and an Other as Objet petit a.