• Journal of the Microelectronics and Packaging Society
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• v.27 no.2
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• pp.39-44
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• 2020

Recently, numerous researches are being conducted in flexible substrate to apply to wearable devices. Particularly, Conductive substrate researches that can implement the wearable devices on clothing are massive. In this study, we formed fiber substrate spraying CNT and Pd mixed solution on it and plated metal layer with electroless plating. Used SEM equipment and EDS analysis to analysis structure of the plated fiber substrate and discovered Ni layer was created. For check electrical properties, mapping was performed to check surface resistance and distribution of resistance of electroless plated fiber substrate with 4-point probe. It was confirmed that conductivity was improved as the duration of electroless plating was increased, and it was found that distribution of resistance by surface location was uniform. Changes in resistance due to mechanical stress were measured through tensile, bending, and twisting tests. As a result, it was confirmed that resistance change of flexible substrate gradually disappeared as plating time increased. Using UTM (Universal testing machine), it was analyzed mechanical properties of the electroless plated substrate with respect to changes in plating time were improved. In the case of conductive fiber substrate in which electroless plating was performed for 2 hours, tensile strength was increased by 16 MPa than fiber substrate. Based on these results, we found that Ni-CNT-Fabric flexible substrate is adequate for clothing-intergrated conductive substrate and we positively expect that this experiment shows flexible substrate can adapt to and develop not only a wearable device technology but also other fields needing flexibility such as battery, catalyst and solar cell.

• The Journal of the Korea Contents Association
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• v.8 no.2
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• pp.195-204
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• 2008

With the growth of airline management, as well as computer and IT security, the international trade in this modern society has been rapidly increasing, Along with the advancing, airplanes have become a universal means of communication. However, the complications associated with airplane safety have also been brought up as a result, the most concerning of which is terrorism. One of the main counterplans for preventing terrorism is Ground security activities the core of Ground security activities is absolute safety for passengers in both passenger terminal and freight terminal. Subastral security refers to physical protection, proximity control and 100% security search and freight guarding of the passengers' possessions, and the personnel's duties to perform such jobs are be! coming more crucial. On the other hand, Airport security check has bee n gradually developing since the 1960's, when hijacking began to take place. Although the airports have been providing more safe and comfortable services to their customers, terrorism is still happening today. When Ground security activities is minute, the users feel displeasure and discomfort, yet considering solely their convenience can brings problems in achieving safety. Since the 9.11 terror in 2001, the idea of improving and strengthening airport security was reinforced and a considerable amount of estate is being spent today for invention and application of new technology. Various nations, including the United States, have been improving their systems of security through public services; public police department is actively carrying out their duties in airports as well. In San Francisco International Airport, private police department is in charge of collection of data, national events, VIP protection, law enforcement, cooperation within facilities, daily-based patrol and traffic control. Under guidance and supervision of national organizations, such as TSA, general police department interprets X-Rays, operates metal detectors, checks passports or IDs and observes reactions to explosives. Under these circumstances, studies about advancement of cooperation and duties of general police department and private police department necessitated: especially about private police department and their training for searching equipments, decrease in number of turn over rate, invention of technology and prior settlement in estate for security. The privacy of the public, who make up the major population of airport passengers, must also be minimized. In the following research, the activities of police departments in San Francisco International Airport will be analyzed in order to understand recent actions of the United States on airport security.

• Korean Journal of Mineralogy and Petrology
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• v.33 no.4
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• pp.427-437
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• 2020

Manganese nodules, which are evaluated as potential metal resources, have been found in the Arctic Ocean as well as in the abyssal plains of the Pacific and Indian Oceans. Manganese nodules exhibit strong variations in the morphology, internal texture, chemical composition and mineralogy as they grow. The relationship between the texture and chemical elemental composition during the growth process is well documented, but the mineral composition variation during the growth process is not. Because the manganese oxide minerals in nodules are fine-grained and poorly crystalline, quantitative analysis for the mineral composition is challenging for the bulk nodule sample. This study investigated the internal texture and Mn-oxide mineral composition of manganese nodules obtained from the East Siberian Sea. Semi-quantitative analysis was attempted for three main Mn-oxide minerals constituting the manganese nodules (i.e., todorokite, buserite and birnessite) using the peak area ratio of X-ray diffraction analysis graphs. In the East Siberian Sea manganese nodules, birnessite is more abundant than buserite or todorokite, and no correlation is found between the mineral composition and the internal texture. Instead a correlation is found between the relative content of todorokite and the lamellae depth. The todorokite content tends to increase from the surface to the core of the nodules, which can be attributed to a recrystallization process or difference in the growth rate within the nodule. This study shows that semi-quantitative analysis of manganese oxide minerals using the peak area ratio is useful in the mineralogical study of manganese nodules.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.14 no.2
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• pp.69-79
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• 2009

Major and trace elements were analyzed in three core sediments to investigate geochemical characteristics of East Sea sediments and provenance changes during late Quaternary in Ulleung Basin. Comparing with Yellow and South Sea sediments, contents of major elements were generally similar while contents of trace elements were significantly different. Furthermore, within this basin, there were some variabilities in trace element compositions. In the western slope sediments (WS), Mo was enriched over 6 times as much as other sites. On the other hand, Zr, Nb, Hf and Ta were enriched in basin sediments (Basin), and Ca and Cs were enriched in southern slope sediments (SS). After excluding elements derived from biogenic, authigenic and diagenetic origins, the lithogenic elements (K, Ti, Cs, Zr, Nb, Hf and Ta) could be classified into three groups from the comparison of element/Al ratios among cores. The first group consisted of elements (K and Ti) that showed the nearly similar element/Al ratios among three cores. The second group contained Cs which showed significant difference between two slope sediments. The third group elements (Zr, Nb, Hf and Ta) showed highly enriched in basin relative to both slope areas. The depth profiles of metal/Al ratios in basin sediments provided the following interpretation for the compositions of sediment and their variation. From 10,000 yr B.P. to 7,000 yr B.P. two lithogenic components (volcanic ashes and western slope sediments) were mixed and deposited in the basin. After 7,000 yr B.P., however, southern slope sediments were mixed with volcanic ashes and deposited in basin area. This event of source change is nearly close to inflow period of the Tsushima Warm Current to Ulleung Basin. Thus, it might be suggested that element geochemistry in Ulleung basin sediment indicate the change of current system in the study area.

• 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.