• Korean Journal of Mineralogy and Petrology
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• v.35 no.1
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• pp.1-12
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• 2022

Stone has been used for various purposes, such as for building stones, megaliths, ornamental stones, hunting and grinding throughout history. The global stone production amounted to around 153 million tons in 2018 excluding quarry waste, up 0.8% on year. Of them, stone residues accounted for 71%. The worldwide stone trading decreased 1.5 million tons to 56.5 million tons in 2018. The average price of stone was 34.1 USD per square meter, down 2.5% from the previous year. It's down 7% when only considering trading between the world's top twelve exporters. But in the three leading countries, Italy, Greece and Brazil, the price saw a sharp increase. In 2018, stone imports and exports totaled 815 million square meters, raising over 20 billion USD of revenue. Imports were largely led by six countries: China, Italy, Turkey, India, Brazil, Spain and Portugal, from largest to smallest.) In terms of stone use per 1,000 population, it was 117 square meters in 2001, and it increased to 264 square meters in 2017 and 266 square meters in 2018. The volume more than doubled during the period, but it has been declining slightly in recent years. China, India, Saudi Arabia and Belgium were the only countries that the stone use per 1,000 population exceeded 1,000 square meters. The increase rate was steepest in China, India and the United States, from largest to smallest. The global stone production is likely to grow to 69.85 million tons by 2025, despite the global economic downturn.

• Journal of Korea Entertainment Industry Association
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• v.14 no.3
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• pp.191-200
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• 2020

Companies are seeking to maximize profits through exports and imports in the ultra-fast, ultra-high-speed modern society. It is only possible to sustain its survival if it targets the global market, not based on any specific region. The K-POP group is also targeting overseas markets in a manner similar to the various global strategies used when companies make inroads into foreign markets, including exports, contracts and direct investment. The K-POP group is engaged in various forms of activities, ranging from simple forms of performance (export) that are visited and staged by an invitation from a certain foreign country to series performances (license) by an invitation from a local promoter and tour performances using its capabilities. The K-POP group is seeking to go beyond the art of single-stage performances and make a systematic plan and make inroads into foreign countries in the form of direct investment suitable for each foreign country. The K-POP group made inroads into overseas markets in the form of simple performances from the late 1990s to 2005, when 'Korean Wave' was first introduced. Group H.O.T., etc. are typical examples. Since then, it has sought to enter overseas markets in the form of franchises by accepting overseas members by 2018, starting with Super Junior in 2005. Since then, the K-POP group in the form of joint investment attempted as group IZ*ONE in 2018 appeared, and a voice story came out in September 2018 when South Korea's JYP Entertainment and Tencent of China joined forces. Unlike K-POP Group, which has entered foreign markets with a global strategy based on the existing export method (H.O.T.), 'Boystory' is a representative group that is made with joint investment, which is a direct investment method. In February 2020, RBW released 'D1Verse,' a five-member group selected by Vietnam's reality show, as a joint investment-type group. This shows the possibility that domestic and foreign companies will release a group in the form of joint investment in order to pursue both globalization and localization.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1463-1478
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• 2022

Maritime transport accounts for 99.7% of the exports and imports of the Republic of Korea; therefore, developing a vessel monitoring system for efficient operation is of significant interest. Several studies have focused on tracking and monitoring vessel movements based on automatic identification system (AIS) data; however, ships without AIS have limited monitoring and tracking ability. High-resolution optical satellite images can provide the missing layer of information in AIS-based monitoring systems because they can identify non-AIS vessels and small ships over a wide range. Therefore, it is necessary to investigate vessel monitoring and small vessel classification systems using high-resolution optical satellite images. This study examined the possibility of developing ship monitoring systems using Compact Advanced Satellite 500-1 (CAS500-1) satellite images by first training a deep learning model using satellite image data and then performing detection in other images. To determine the effectiveness of the proposed method, the learning data was acquired from ships in the Yellow Sea and its major ports, and the detection model was established using the You Only Look Once (YOLO) algorithm. The ship detection performance was evaluated for a domestic and an international port. The results obtained using the detection model in ships in the anchorage and berth areas were compared with the ship classification information obtained using AIS, and an accuracy of 85.5% and 70% was achieved using domestic and international classification models, respectively. The results indicate that high-resolution satellite images can be used in mooring ships for vessel monitoring. The developed approach can potentially be used in vessel tracking and monitoring systems at major ports around the world if the accuracy of the detection model is improved through continuous learning data construction.

• Journal of Life Science
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• v.27 no.11
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• pp.1369-1375
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• 2017

The purpose of this study was to investigate the cellular characterization of phospholipase C-${\delta}1$ in olive flounders (Paralichthys olivaceus). In general, phospholipase C signaling pathways are distributed in nuclei at plasma membranes and in cytoplasms, although the pathways' nuclear localization mechanisms are unclear. P. olivaceus duplicates type-A PoPLC-${\delta}1$ (PoPLC-${\delta}1A$), which has a high similarity to the human isoform PLC-${\delta}$; type-B PoPLC-${\delta}1$ (PoPLC-${\delta}1B$ [Sf]), which has a low similarity to the human isoform PLC-${\delta}$ and the alternative splice variant PoPLC-${\delta}1B$ (Lf), which has a nuclear localization signal (NLS) and a nuclear export signal (NES) for nuclear imports and exports, respectively. This study confirmed the effects of the cellular localization and translocation of GFP-tagged PoPLC-${\delta}1A$, PoPLC-${\delta}1B$ (Sf) and PoPLC-${\delta}1B$ (Lf). It administered treatments of $Ca^{2+}$ ionophore ionomycin and endoplasmic reticulum (ER)-$Ca^{2+}$ pump inhibitor thapsigargin to hirame natural-embryo (HINAE) cells. A laser-scanning confocal microscope was used. GFP-tagged PoPLC-${\delta}1A$ was distributed to the cellular organelles, rather than to the cytoplasms and cytomembranes, when PoPLC-${\delta}1B$ (Lf) and PoPLC-${\delta}1B$ (Sf) were localized at the plasma membranes. The treatments of ionomycin and thapsigargin showed the accumulation of PoPLC-${\delta}1A$ in the nuclei when PoPLC-${\delta}1B$ (Lf) nucleocytoplasmic shuttling and PoPLC-${\delta}1B$ (Sf) nucleocytoplasmic shuttling were not observed. The results were the first evidence that PoPLC-${\delta}1A$, which contains functional, intact NES sequences, has a main role in nucleocytoplasmic shuttling and translocation in fish.

• KDI Journal of Economic Policy
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• v.14 no.2
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• pp.29-54
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• 1992

Recent studies on the economic effects of trade liberalization and economic integration have emphasized the significant gains associated with product differentiation and scale economies. Securing access to markets in other countries will make it possible to increase product variety and capture scale economies, thus, expanding the gains from trade. Liberalization is also expected to introduce foreign competition into the previously closed market. Concurrently, the liberalization will improve the competitive market environment for firms selling in the domestic market. Firms will be pressed to either exit or reduce cost. The output per firm, then, will increase due to the exit of rival firms, and the average total cost will decline due to the economies of scale. 'Rationalization' of the production process will eventually follow. This paper addresses the economic effects of (counterfactual) bilateral tariff elimination between Korea and Japan. It computationally assesses the gains from liberalization as well as the resource allocations and welfare effects associated with the tariff reduction. The endogenous determination of the key parameters distinguishes this paper from others. The firm's perceived elasticity of demand and elasticity of substitution in the present model are calibrated to be consistent with the base year data. Korea, Japan, and the rest of the world are modeled explicitly. The sectoral coverage of the model includes twenty-three tradable product categories based on three-digit SITC industries and seven nontradable categories based on one-digit SITC industries. Product categories are also classified into perfectly competitive and imperfectly competitive ones. In the imperfectly competitive industries, product differentiation exists at the firm level, while the perfectly competitive industries are characterized by national product differentiation. The simulation results of bilateral tariff reduction are reported. Tariff elimination tends to increase intra-industry trade flows so that the total amount of exports and imports of both countries expand. Yet, Japan is expected to increase the bilateral trade surplus in the wake of the mutual tariff reduction. Terms-of-trade for Korea will not change, while for Japan it will deteriorate. Equivalent variations reflecting the change in consumer surplus (welfare) will favor Korean consumers. Total output, however, will not change substantially, recording 0.5 and 0.6% for Japan and Korea, respectively. An interesting finding in the analysis is that the gains from increased competition and scale efficiency are not as prevailing as expected in theory.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.60 no.3
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• pp.318-332
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• 2015

The maize production in South-eastern Asian countries showed a continuous increase with increasing poultry-livestock from the beginning of the 1990s to early 2010. Also the need for a new variety development of each contries was increased rapidly in the same period. Single-Cross hybrid varieties have been developed and supplied from 2001 instead of multi-cross maize varieties since 1992 in Indonesia. In Cambodia, CP group is mainly manufacturing feeds with most of the forage maize from farmers who are growing its seeds from the company. Cambodian main cultivars are varieties of multinational corporations such as DK8868 from Monsanto, NK6326, NK7328 from Syngenta and CP333 from CP group including local business company. Vietnam is the main maze importing country in South-Eastern Asia which had imported 13 times scale of amount compared to exports in average from 1990 to 2011. Vietnamese government has developed a range of varieties for improving their efficiency in production, such as the LVN-10 with political investments. Their production has been reached to 80% of the total. According to the 2012 MIFAFF (Ministry for Food, Agriculture, Forestry and Fisheries) data in Korea, domestic edible maize cultivation area was approximately 15,000ha. It showed 74,399 tons of production, 3.8% of food self-sufficiency in maize and around 0.9% of grain self-sufficiency rate. The consumption of grain is mostly rely on imports in Korea. To overcome the limit of the domestic seed market and increase maize self-sufficiency, the need to develop maze varieties for world-class is increasing at present through analyzing the market trend and prospect of the seed industry in South-eastern Asia.

• KDI Journal of Economic Policy
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• v.12 no.3
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• pp.153-172
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• 1990

The present paper investigates the potential value of strategic antitrust policy in an oligopolistic international market. The market is characterized by a non-cooperative Cournot-Nash equilibrium and by asymmetry in costs among firms in the world market. The model is useful for two reasons. First, it is important in the context of policy-making to examine the conditions under which it may be beneficial to relax antitrust law to enhance competitiveness. Second, the explicit derivation of the level of cost-saving required for a gain in total domestic surplus provides an empirical rule for excluding industries that do not satisfy the requirements for a socially beneficial antitrust exemption. Results of the analysis include a criterion that tells how the cost-saving and concentration effects of a merger offset each other. The criterion is derived from fairly general assumptions on demand functions and is simple enough to be applied as a part of the merger guidelines. Another interesting policy implication of our analysis is that promoting mergers would not be a beneficial strategy in a net importing industry where cost-saving opportunities are thin. Cost-saving domestic mergers are more likely to increase national welfare in exporting industries. The best candidate industries for application of strategic antitrust policy are those with the following characteristics: (i) a large potential for efficiency enhancement; (ii) high market concentration at the world but not the domestic level; (iii) a high ratio of exports to imports. Recently, many policymakers and economists in Korea have also come to believe that the appropriate antitrust policy in an era of increased foreign competition may actually be to encourage rather than to prohibit domestic mergers. The Industry Development Act of 1986 and the proposed bill for Mergers and Conversions in the Financial Industry of 1990 reflect this changing perspective on antitrust policy. Antitrust laws may burden domestic firms in the sense that they have a more constrained strategy set. Expenditures to avoid antitrust attacks could also increase costs for domestic firms. But there is no clear evidence that the impact of antitrust policy is significant enough to harm the competitiveness of domestic firms. As a matter of fact, it is necessary for domestic financial institutions to become large in scale in this era of globalization. However, the absence of empirical evidence for efficiency enhancement from mergers suggests caution in the relaxation of antitrust standards.

• 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.

• Strategy21
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• s.46
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• pp.239-276
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• 2020

The failure of early economic sanctions aimed at hurting the overall economies of targeted states called for a more sophisticated design of economic sanctions. This paved way for the advent of 'smart sanctions,' which target the supporters of the regime instead of the public mass. Despite controversies over the effectiveness of economic sanctions as a coercive tool to change the behavior of a targeted state, the transformation from 'comprehensive sanctions' to 'smart sanctions' is gaining the status of a legitimate method to impose punishment on states that do not conform to international norms, the nonproliferation of weapons of mass destruction in this particular context of the paper. The five permanent members of the United Nations Security Council proved that it can come to an accord on imposing economic sanctions over adopting resolutions on waging military war with targeted states. The North Korean nuclear issue has been the biggest security threat to countries in the region, even for China out of fear that further developments of nuclear weapons in North Korea might lead to a 'domino-effect,' leading to nuclear proliferation in the Northeast Asia region. Economic sanctions had been adopted by the UNSC as early as 2006 after the first North Korean nuclear test and has continually strengthened sanctions measures at each stage of North Korean weapons development. While dubious of the effectiveness of early sanctions on North Korea, recent sanctions that limit North Korea's exports of coal and imports of oil seem to have an impact on the regime, inducing Kim Jong-un to commit to peaceful talks since 2018. The purpose of this paper is to add a variable to the factors determining the success of economic sanctions on North Korea: preventing North Korea's evasion efforts by conducting illegal transshipments at sea. I first analyze the cause of recent success in the economic sanctions that led Kim Jong-un to engage in talks and add the maritime element to the argument. There are three conditions for the success of the sanctions regime, and they are: (1) smart sanctions, targeting commodities and support groups (elites) vital to regime survival., (2) China's faithful participation in the sanctions regime, and finally, (3) preventing North Korea's maritime evasion efforts.