• International Journal of Control, Automation, and Systems
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• v.4 no.6
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• pp.748-755
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• 2006

In this paper, a trade-off design and fabrication of IPMC(Ionic Polymer Metal Composites) as an actuator for a flapping device have been described. Experiments for the internal solvent loss of IPMCs have been conducted for various combinations of cation and solvent in order to find out the best combination of cation and solvent for minimal solvent loss and higher actuation force. From the experiments, it was found that IPMCs with heavy water as their solvent could operate longer. Relations between length/thickness and tip force of IPMCs were also quantitatively identified for the actuator design from the tip force measurement of 200, 400, 640, and $800{\mu}m$ thick IPMCs. All IPMCs thicker than $200{\mu}m$ were processed by casting $Nafion^{TM}$ solution. The shorter and thicker IPMCs tended to generate higher actuation force but lower actuation displacement. To improve surface conductivity and to minimize solvent evaporation due to electrically heated electrodes, gold was sputtered on both surfaces of the cast IPMCs by the Physical Vapor Deposition(PVD) process. For amplification of a short IPMC's small actuation displacement to a large flapping motion, a rack-and-pinion type hinge was used in the flapping device. An insect wing was attached to the IPMC flapping mechanism for its flapping test. In this test, the wing flapping device using the $800{\mu}m$ thick IPMC. could create around $10^{\circ}{\sim}85^{\circ}$ flapping angles and $0.5{\sim}15Hz$ flapping frequencies by applying $3{\sim|}4V$.

• Journal of the Ergonomics Society of Korea
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• v.34 no.5
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• pp.473-485
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• 2015

Objective: This study provides strategies of how to effectively convert an invention, created at universities or government-funded research institutes, into a strong patent with the clear understanding of its unique technological characteristics. Background: Regardless of the amount of research funds available in our country and the decent number of intellectual property rights created using the funds, there was a deficit of more than KRW 6 trillion in the technology trade balance related with intellectual property rights in the year of 2014. One of the reasons was that the vast number of patents that were being produced by universities or by government-funded research institutes were merely performance-based patents, namely, so called "patents for patents". Another reason is that developed technology from research and development could not be transformed into a strong patent right properly due to the lack of related knowledge. Method: After reviewing various references mentioned on the patent strategies, the definition of a strong patent and the strategies of producing a strong patent for an invention drawn out from research performance will be supplied. Results: To produce a strong patent right at universities or government funded research institutes, one should use strategies for strong specifications, strategies of product patents and method patents, strategies of patent portfolios, strategies of know-how, strategies of inventions defined by numerical limitation and strategies of parameter inventions for a more strategic approach. Conclusion: Strong patent rights will be produced with the use of effective patent strategies provided in this study. Application: It is estimated that the results of this study will aid the establishment of strong patents for inventions developed by research performance at universities or government-funded research institutions.

• The Research Journal of the Costume Culture
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• v.2 no.1
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• pp.1-27
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• 1994

This result of the study on the costume of Osman Turkey are as following. 1. Empire of Osman Turkey(129∼1922) exerted an almost limites impact and influence on Europe and Asia during their regime 600 years. The distant ancestors of the Osman Turks were nomadic peoples, who wandered I tribal groups through the Central Asia. Therefore their costumes were based on nomadic culture. They had trade with West and East were influenced by Hellenism and Byzantium and grew, to a strong Islamic political power polygamy with which influence their clothing along with other culture. 2. Topkapi Saray was one of he principal residences of the Osman sultans and his court. Late 17 century, Topkapi Saray found many of kaftans of Osman Turks Empires of 14∼17 centuries. Otherwise we studied by the minatures of 16∼17 centuries, Since the Topkapi Saray became a museum in 1924, a program of careful restoration has made it possible to some pars of it to the public, after centuries neglection. 3. Osman Turkey Empire had important role in between West and East(silk-road). Economic, commercial, social and political factor of Turkey led to a development in the art of weaving (kema, kadife, catman, seraser, zerbeft, hatayi, kntnu, atlas)parallel to the rise and development of the Osman Turkey Empire itself, one which raised the art to a level attained nowwhere else in the world. Fabrics woven from gold and silver thread occupied a very important place in the court life of the time. This was due as much to their symbolic as to their material value, reflecting as they did the power, glory and magnificence of the Empire. 4. In order to study Eastern or Western history of costume one must study Turkey history of costume in advance. Also there is a great need of comparison to study of western, central and north eastern area history of costume.

• Journal of Korea Entertainment Industry Association
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• v.15 no.5
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• pp.99-113
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• 2021

This study to verify the influence of the macroeconomic factors to sportainment industry and also to find the value of use. For this, 'Dow Jones Industrial Average (DJIA)', 'West Texas intermediate (WTI)', and 'Gold Price (GP)' were selected from macroeconomic factors, and the 'Stock Price' of NIKE and Adidas for sportainment industry factor. The transaction data for 20 years (5,285 trade days) were analyzed through a two-step extraction process. Durbin-Watson regression analysis was performed to prove the influence and predict. From these analyses, the first, the Macroeconomics factors were found to have a significant effect on the sportainment industry. The second, each different levels of regression equations were found by the time setting, the environmental characteristics of each time period, and mutual relation between factors. Finally, it was found that the regression equation between specific period can be used for the future prediction in sportainment industry.

• Acta Via Serica
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• v.6 no.2
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• pp.117-140
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• 2021

At the beginning of the Roman imperial period, moralizing authors criticized a material from the East that quickly gained popularity among the elites: silk. During Late Antiquity, the trade, production, and use of purple-dyed silks increasingly became the privilege of the emperors. While literature, court poetry, and laws give insights into the discourses surrounding silk, they are rather unspecific concerning silk qualities. This contribution analyzes the scattered descriptions of silks in Greek and Latin texts in a diachronic perspective, with a focus on the 1^st cent. BCE to the 4th cent. CE, paying particular attention to the terminology, products, origins, and qualities of silk. The aim is to build a framework for comparisons with archaeological silk finds and other textile terminologies along the Silk Roads. Here, the silk finds from the oasis city of Palmyra/Tadmor in modern-day Syria, dating from the 1st cent. BCE to the 2nd cent. CE, will be used as a case study for the early imperial period. Taking these silk finds as a comparison, it will be shown that Greek and Latin terminology does not match the variety of silks known in the Mediterranean. Rather, linguistic differentiations focus on the forms in which silk reached the Mediterranean, as skeins, yarns, and fabrics, as well as on the different kinds of silks that were produced in the West, namely pure silk and half-silken fabrics, checkered "scutlata" damasks, purple-dyed, and gold-embellished silks. In contrast, silks from the East were subsumed under the term for "silks from the silk people" or simply "silks". Moreover, ancient authors do not use the terms in the same way. These findings show the limitations of Western silk terminology and the importance of combining archaeological and written sources.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.222-228
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• 2022

In today's era of digital technologies, the problem of religious communication in the cyberspace is being actualized, since the globality and accessibility of the WWW makes it one of the most effective and promising channels for transmitting various kinds of messages, including those of a religious nature. Today, religious organizations and movements pay the closest attention to the virtual media space, not only using it to attract new followers, but also for religious PR, image-making and branding, informing the world about themselves through news from the life of the organization and its followers. An equally important form of electronic communication in the online sphere is currently the interaction of various religious movements and religious cultures in general, or the dialogue of confessions in particular. Research in the digital space makes it possible to identify important trends in religious spheres based on the analysis of the flow of information on the Internet, to demonstrate the specifics of individual media outlets and the consequences of their activities for interreligious dialogue, to study the role of the Internet in changing religious beliefs, the possibility of changing religious identity, retrospective development of religious enlightenment at the turn of the century, to determine the vectors of possible interreligious interaction and discuss the role of digital technologies in the work of religious structures, to state the need to continue an active dialogue between representatives of religious movements, to hold expert seminars on interreligious dialogue on a regular basis, and to record the risks generated by the digital space. Thus, the coronavirus pandemic served as a background and context, a litmus test and a catalyst for accelerating and intensifying interreligious, interfaith dialogue and dialogue between religious organizations and society.

• Economic and Environmental Geology
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• v.47 no.3
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• pp.255-263
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• 2014

Conflict minerals refer to minerals mined in conditions of armed conflict, especially as in the eastern provinces of the Democratic Republic of the Congo. The common conflict minerals are cassiterite, wolframite, coltan(columbite-tantalite ore), and gold, which are mined and extracted from the Eastern Congo. These minerals are essentially used in the manufacture of a variety of devices, including consumer electronics. To end the violent conflict in the Democratic Republic of the Congo (DRC) and in surrounding countries, it is necessary to block the supply route of conflict minerals which has been partially financed by the exploitation and trade of conflict minerals. The Dodd-Frank Wall Street Reform and Consumer Protection Act, passed into law in July 2010 and it contains requirements that U.S. companies report to the Securities and Exchange Commission(SEC) on the origin of conflict minerals and show due diligence of OECD. The goal of the act is to cut direct and indirect funding of armed groups engaged in conflict.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.195-220
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• 2018

In this study, we conducted an empirical analysis of the factors that affect the change of Bitcoin Closing Price. Previous studies have focused on the security of the block chain system, the economic ripple effects caused by the cryptocurrency, legal implications and the acceptance to consumer about cryptocurrency. In various area, cryptocurrency was studied and many researcher and people including government, regardless of country, try to utilize cryptocurrency and applicate to its technology. Despite of rapid and dramatic change of cryptocurrencies' price and growth of its effects, empirical study of the factors affecting the price change of cryptocurrency was lack. There were only a few limited studies, business reports and short working paper. Therefore, it is necessary to determine what factors effect on the change of closing Bitcoin price. For analysis, hypotheses were constructed from three dimensions of consumer, industry, and macroeconomics for analysis, and time series data were collected for variables of each dimension. Consumer variables consist of search traffic of Bitcoin, search traffic of bitcoin ban, search traffic of ransomware and search traffic of war. Industry variables were composed GPU vendors' stock price and memory vendors' stock price. Macro-economy variables were contemplated such as U.S. dollar index futures, FOMC policy interest rates, WTI crude oil price. Using above variables, we did times series regression analysis to find relationship between those variables and change of Bitcoin Closing Price. Before the regression analysis to confirm the relationship between change of Bitcoin Closing Price and the other variables, we performed the Unit-root test to verifying the stationary of time series data to avoid spurious regression. Then, using a stationary data, we did the regression analysis. As a result of the analysis, we found that the change of Bitcoin Closing Price has negative effects with search traffic of 'Bitcoin Ban' and US dollar index futures, while change of GPU vendors' stock price and change of WTI crude oil price showed positive effects. In case of 'Bitcoin Ban', it is directly determining the maintenance or abolition of Bitcoin trade, that's why consumer reacted sensitively and effected on change of Bitcoin Closing Price. GPU is raw material of Bitcoin mining. Generally, increasing of companies' stock price means the growth of the sales of those companies' products and services. GPU's demands increases are indirectly reflected to the GPU vendors' stock price. Making an interpretation, a rise in prices of GPU has put a crimp on the mining of Bitcoin. Consequently, GPU vendors' stock price effects on change of Bitcoin Closing Price. And we confirmed U.S. dollar index futures moved in the opposite direction with change of Bitcoin Closing Price. It moved like Gold. Gold was considered as a safe asset to consumers and it means consumer think that Bitcoin is a safe asset. On the other hand, WTI oil price went Bitcoin Closing Price's way. It implies that Bitcoin are regarded to investment asset like raw materials market's product. The variables that were not significant in the analysis were search traffic of bitcoin, search traffic of ransomware, search traffic of war, memory vendor's stock price, FOMC policy interest rates. In search traffic of bitcoin, we judged that interest in Bitcoin did not lead to purchase of Bitcoin. It means search traffic of Bitcoin didn't reflect all of Bitcoin's demand. So, it implies there are some factors that regulate and mediate the Bitcoin purchase. In search traffic of ransomware, it is hard to say concern of ransomware determined the whole Bitcoin demand. Because only a few people damaged by ransomware and the percentage of hackers requiring Bitcoins was low. Also, its information security problem is events not continuous issues. Search traffic of war was not significant. Like stock market, generally it has negative in relation to war, but exceptional case like Gulf war, it moves stakeholders' profits and environment. We think that this is the same case. In memory vendor stock price, this is because memory vendors' flagship products were not VRAM which is essential for Bitcoin supply. In FOMC policy interest rates, when the interest rate is low, the surplus capital is invested in securities such as stocks. But Bitcoin' price fluctuation was large so it is not recognized as an attractive commodity to the consumers. In addition, unlike the stock market, Bitcoin doesn't have any safety policy such as Circuit breakers and Sidecar. Through this study, we verified what factors effect on change of Bitcoin Closing Price, and interpreted why such change happened. In addition, establishing the characteristics of Bitcoin as a safe asset and investment asset, we provide a guide how consumer, financial institution and government organization approach to the cryptocurrency. Moreover, corroborating the factors affecting change of Bitcoin Closing Price, researcher will get some clue and qualification which factors have to be considered in hereafter cryptocurrency study.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.