• Title/Summary/Keyword: 한.중 무역

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The Strategy for the Environmental Education through the Practical Arts(TechnologyㆍHome economics) Subject in a viewpoint of the Clothing & Textiles resources (의생활자원 관점에서의 실과(기술ㆍ가정) 환경교육방안에 관한 연구)

  • Chung Mee-Kyung
    • Journal of Korean Home Economics Education Association
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    • v.16 no.3
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    • pp.131-146
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    • 2004
  • The Purpose of this study is to suggest strategies for environmental education through the Practical Arts(TechnologyㆍHome economics) Subject in a viewpoint of the clothing & textiles resources to resolve problems in the clothing life area. For this, this study was carried out through review of literature which is related with the consumption, the environmental problems, the environmental policies, and regulations of the government and new environmental technologies, of clothing & textiles industries and environmental education. The major findings of the study were as follows; 1) The environmental education system model in a viewpoint of the Clothing & Textiles resources was developed. This model system is consisted with interactions on school, government, industry, home and non-government organizations. Thus, the fact that Practical Arts(TechnologyㆍHome economics) Subject were the most effective subject to teaching the environmental education viewpoint of the Clothing & Textiles resources was confirmed. 2) The standards were analysed out to analyse the contents in the clothing area of the Practical Arts(TechnologyㆍHome economics) Subject. It were consist of 4 factors and 12 elements under the factors: Awareness of clothing & textile resources(clothing consumption, production of clothing & textile and environmental problems). Planning and buying of clothing(planning, buying), Management of clothing(understand of textile. human body & environment, laundering and Environmental pollution, arrangement & conservation) Recycling & exhaust of clothing(contribution, redesign, recycling, exhaust) 3) Analysing the current Practical Arts (TechnologyㆍHome economics) subject from the Environmental education in the clothing section, the environmental education related with clothing were taught the most in the middle school course, and environmental contents were concentrated in the recycling factors. but not so much on other factors. 4) After analysing the Practical Arts (TechnologyㆍHome economics) subject, the strategies were suggested for reinforcing the environmental education in the clothing of the Practical Arts(TechnologyㆍHome economics) subject.

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The Study of Establishing the Multi-pass Eurasian Railroads (유라시아 철도의 다중경로 구축에 관한 연구)

  • Hahm, Beom-Hee;Huh, Nam-Kyun;Hurr, Hee-Young
    • Korean Business Review
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    • v.21 no.2
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    • pp.137-170
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    • 2008
  • This study is presenting the logistics strategy in the international logistics markets which makes competition and corporation among north-east Asian countries to establishing the multi-pass Eurasian railroads. The countries located in north-east area of Eurasia like China, Japan, Russia and Korea are paying higher costs and disutility to the transportations and communications due to repeated conflicts and confrontations causes from the politic problems. They are being used surface transportation for most of all logistics between Europe and Asia except special merchandises because of characteristic of cargo to be air, the Silk Road remains vestige only which was main logistic passage to this area since BC. So far the Trans-Siberian Railway is being used by Russia mostly as north of Eurasian transport because of difficulties of service. The Trans-China Railway built in 1992 is not accomplishing as a international logistic passages. It is expected to take a long lead time because of characteristic of resource development and poor logistic infrastructure to the countries like Uzbekistan, double landlocked country, Mongolia and Azerbaijan, the countries do not be adjacent to the sea, even they have great economic jump-up plans through the development of their own resources. The Shanghai Cooperation Organization(SCO) start to sail officially in 2001 is constructed with China, Russia, Tadzhikistan, Kyrgyzstan, Kazakhstan and Uzbekistan as regular members of 6 countries and Mongolia, India, Pakistan, Afghanistan and Iran as observers 5 countries. It is started as a military alliance to protect terror, but now, it is expended to cooperate with the traffic, transportation, trade and share of energies. The Russia is doing their best to activate TSR as a government target to developnorth area equivalently, and economic develop of far-east Siberia. And also it is agreed provisionally to improve and repair of rail road between Nahjin and Hassan to connect TSR and TKR( Trans-Korea Railroad) by Russia, North Korea and South Korea with Russian's aggressive efforts. The development plan of this area is over lapped with GTI(Greater Tumen Initiative) promoted by UNDP, and is a cooperated project by 5 countries of South Korea, Mongolia, China, Russia and North Korea, subject to review the appropriation of energy, tour, environment, rail road connection between Mongolia and China and establishing a ferry route to north-east Asia. It is Japanese situation to pay attention to Russia and China even they have been supplying large-scope of infrastructure in Mongol area without any charges, target to get East Asia Main Rail Road to connect Mongolia and Zalubino of Russia. In case of the program for the Denuclearization of North Korea is not creeping, it will be accelerated to connect the TKR and TSR, TKR and TCR by somehow attending United States, including developing program promoted by UN ESCAP. As the result, Korean peninsular will continue the central role of competition and cooperation as in the past, now and future of north-east Asia, as of geographical-economics and geographical-politics whether it is requested or not wanted by neighbor countries.

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A Study on Consumer Characteristics According to Social Media Use Clusters When Purchasing Agri-food Online (온라인 농식품 구매시 소셜미디어 이용 군집에 따른 소비자특성에 대한 연구)

  • Lee, Myoung-Kwan;Park, Sang-Hyeok;Kim, Yeon-Jong
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.16 no.4
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    • pp.195-209
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    • 2021
  • According to the 2019-2020 social media usage survey conducted by the Seoul e-commerce center, 5 out of 10 consumers have experienced shopping through social media. The cost of traditional advertising media has been reduced and advertising spending on social media has risen by 74%, indicating that social media is becoming a more important marketing element. While the number of users of social media has increased and corporate marketing activities have increased accordingly, research has been conducted in various aspects of marketing such as user motivation for social media, satisfaction, and purchase intention. There was no subdivided study on the differences in the social media usage frequency of consumers in actual purchasing behavior. This study attempted to identify differences in consumer characteristics by cluster in the agrifood purchase situation by grouping them by type according to the frequency of use of social media for consumers who purchase agri-food online. Product involvement, product need, and online purchase channel Consumer characteristics such as demographic distribution, perceived risk, and eating and lifestyle in each cluster were checked for the three agrifood purchase situations including choice, and types for each cluster were presented. To this end, questionnaire data on the frequency of social media use and online agrifood purchase behavior were collected from 245 consumers, and the validity of the measurement variables was secured through factor analysis and reliability analysis. As a result of cluster analysis according to the frequency of social media use, it was divided into three clusters. The first cluster was a group that mainly used open social media, and the second cluster was a group that used both open and closed social media and online shopping malls; The third cluster was a group with low online media usage overall, and the characteristics of each cluster appeared. Through regression analysis, the effect on product involvement, product need, and purchase channel selection when purchasing agri-food online through each of the three clusters was confirmed through regression analysis. As a result of the regression analysis, the characteristic of cluster 1 in the situation of purchasing agri-food online is a male in his 30s living in a rural area who has no reluctance to purchase agri-food on social media or online shopping malls. The characteristics of cluster 2 are mainly consumers who are interested in purchasing health food, and the consumer characteristics are represented. In the case of cluster 3, when purchasing products online, they purchase after considering quality and price a lot, and the consumer characteristics are represented as people who are more confident in purchasing offline than online. Through this study, it is judged that by identifying the differences in consumer characteristics that appear in the agri-food purchase situation according to the frequency of social media use, it can be helpful in strategic judgments in marketing practice on social media customer targeting and customer segmentation.

Eurasian Naval Power on Display: Sino-Russian Naval Exercises under Presidents Xi and Putin (유라시아 지역의 해군 전력 과시: 시진핑 주석과 푸틴 대통령 체제 하에 펼쳐지는 중러 해상합동훈련)

  • Richard Weitz
    • Maritime Security
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    • v.5 no.1
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    • pp.1-53
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    • 2022
  • One manifestation of the contemporary era of renewed great power competition has been the deepening relationship between China and Russia. Their strengthening military ties, notwithstanding their lack of a formal defense alliance, have been especially striking. Since China and Russia deploy two of the world's most powerful navies, their growing maritime cooperation has been one of the most significant international security developments of recent years. The Sino-Russian naval exercises, involving varying platforms and locations, have built on years of high-level personnel exchanges, large Russian weapons sales to China, the Sino-Russia Treaty of Friendship, and other forms of cooperation. Though the joint Sino-Russian naval drills began soon after Beijing and Moscow ended their Cold War confrontation, these exercises have become much more important during the last decade, essentially becoming a core pillar of their expanding defense partnership. China and Russia now conduct more naval exercises in more places and with more types of weapons systems than ever before. In the future, Chinese and Russian maritime drills will likely encompass new locations, capabilities, and partners-including possibly the Arctic, hypersonic delivery systems, and novel African, Asian, and Middle East partners-as well as continue such recent innovations as conducting joint naval patrols and combined arms maritime drills. China and Russia pursue several objectives through their bilateral naval cooperation. The Treaty of Good-Neighborliness and Friendly Cooperation Between the People's Republic of China and the Russian Federation lacks a mutual defense clause, but does provide for consultations about common threats. The naval exercises, which rehearse non-traditional along with traditional missions (e.g., counter-piracy and humanitarian relief as well as with high-end warfighting), provide a means to enhance their response to such mutual challenges through coordinated military activities. Though the exercises may not realize substantial interoperability gains regarding combat capabilities, the drills do highlight to foreign audiences the Sino-Russian capacity to project coordinated naval power globally. This messaging is important given the reliance of China and Russia on the world's oceans for trade and the two countries' maritime territorial disputes with other countries. The exercises can also improve their national military capabilities as well as help them learn more about the tactics, techniques, and procedures of each other. The rising Chinese Navy especially benefits from working with the Russian armed forces, which have more experience conducting maritime missions, particularly in combat operations involving multiple combat arms, than the People's Liberation Army (PLA). On the negative side, these exercises, by enhancing their combat capabilities, may make Chinese and Russian policymakers more willing to employ military force or run escalatory risks in confrontations with other states. All these impacts are amplified in Northeast Asia, where the Chinese and Russian navies conduct most of their joint exercises. Northeast Asia has become an area of intensifying maritime confrontations involving China and Russia against the United States and Japan, with South Korea situated uneasily between them. The growing ties between the Chinese and Russian navies have complicated South Korean-U.S. military planning, diverted resources from concentrating against North Korea, and worsened the regional security environment. Naval planners in the United States, South Korea, and Japan will increasingly need to consider scenarios involving both the Chinese and Russian navies. For example, South Korean and U.S. policymakers need to prepare for situations in which coordinated Chinese and Russian military aggression overtaxes the Pentagon, obligating the South Korean Navy to rapidly backfill for any U.S.-allied security gaps that arise on the Korean Peninsula. Potentially reinforcing Chinese and Russian naval support to North Korea in a maritime confrontation with South Korea and its allies would present another serious challenge. Building on the commitment of Japan and South Korea to strengthen security ties, future exercises involving Japan, South Korea, and the United States should expand to consider these potential contingencies.

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A Study on Commodity Asset Investment Model Based on Machine Learning Technique (기계학습을 활용한 상품자산 투자모델에 관한 연구)

  • Song, Jin Ho;Choi, Heung Sik;Kim, Sun Woong
    • 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.