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The effect of Exercise on inhibition Blood pressure by Auricular-plaster Vaccaria seeds (이혈첨압왕불유행자(耳穴貼壓王不留行籽)가 운동시 혈압 억제에 미치는 영향)

  • Park, Ji-Soo;Yoon, Young-Sik;Kim, Dong-Jin;Ko, Hee-Jeong;Yum, Dae-Yul;Song, Yung-Sun
    • Journal of Pharmacopuncture
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    • v.13 no.4
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    • pp.63-74
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    • 2010
  • Objectives : The purpose of this study was to investigate effect of Exercise on inhibition Blood pressure by Auricular-plaster Vaccaria seeds Methods : This study picked 40 peoples from 20 May 2009 to 30 June 2009 and experiment them. Attached Vaccaria seeds to auricular acupuncture of the experiment group. Did not attach them to the control group. Them to exercise using a Bike-Ergometer exercise. I measured their blood pressure before the exercise, 15 minutes after the exercise and 30 minutes after the exercise. I compared the difference between the systolic blood pressure and diastolic blood pressure. The method to choose the subjects was Random allocation. Results : 1. Comparing the systolic blood pressure of the experiment group and the control group, the average systolic blood pressure of the experiment group, who did the Bike-Ergometer exercise putting on Auricular-plaster Vaccaria seeds, was 125.45 mmHg before the exercise, 121.20 mmHg 15 minutes after the exercise and 120.30 mmHg 30 minutes after the exercise. Terefore, the group's systolic blood pressure after the exercise was more controlled than the systolic blood pressure before the exercise. The control group's systolic blood pressure increased compared to the beginning. To measure the change before and after the exercise, I carried out paird-t test. The result was statistically significant. 2. Comparing the diastolic blood pressure of the experiment group and the control group, the average diastolic blood pressure of the experiment group, who did the Bike-Ergometer exercise putting on Auricular-plaster Vaccaria seeds, was 81.45 mmHg before the exercise, 79.65 mmHg 15 minutes after the exercise and 79.05 mmHg 30 minutes after the exercise. As a result of carrying out paird-t test to measure the change of the diastolic blood pressure, the change of the dilating blood pressure was statistically significant. However, the difference of the dilating blood pressure between 15 minutes after the exercise and 30 minutes after the exercise was not statistically significant. Comparing the systolic blood pressure and the diastolic blood pressure of the experiment group and the control group, the blood pressure of the experiment group, who did the Bike-Ergometer exercise putting on Auricular-plaster Vaccaria seeds, decreased compared to the beginning and the blood pressure of the control group, who did not put on Auricular-plaster Vaccaria seeds, increased compared to the beginning. Conclusions : The hypothesis was supported that the increase of the systolic and diastolic blood pressure of the experiment group, putting on Auricular-plaster Vaccaria seeds, was more controlled than that of the control group. In future, it can be medically used by verifying the various effects through repeated studies.

Design and Implementation of Clipcast Service via Terrestrial DMB (지상파 DMB를 이용한 클립캐스트 서비스 설계 및 구현)

  • Cho, Suk-Hyun;Seo, Jong-Soo
    • Journal of Broadcast Engineering
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    • v.16 no.1
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    • pp.23-32
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    • 2011
  • Design and Implementation of Clipcast Service via Terrestrial DMB This paper outlines the system design and the implementation process of clipcast service that can send clips of video, mp3, text, images, etc. to terrestrial DMB terminals. To provide clipcast service in terrestrial DMB, a separate data channel needs to be allocated and this requires changes in the existing bandwidth allocation. Clipcast contents can be sent after midnight at around 3 to 4 AM, when terrestrial DMB viewship is low. If the video service bit rate is lowered to 352 Kbps and the TPEG service band is fully used, then 320 Kbps bit rate can be allocated to clipcast. To enable clipcast service, the terminals' DMB program must be executed, and this can be done through SMS and EPG. Clipcast service applies MOT protocol to transmit multimedia objects, and transmits twice in carousel format for stable transmission of files. Therefore, 72Mbyte data can be transmitted in one hour, which corresponds to about 20 minutes of full motion video service at 500Kbps data rate. When running the clip transmitted through terrestrial DMB data channel, information regarding the length of each clip is received through communication with the CMS(Content Management Server), then error-free files are displayed. The clips can be provided to the users as preview contents of the complete VOD contents. In order to use the complete content, the user needs to access the URL allocated for that specific content and download the content by completing a billing process. This paper suggests the design and implementation of terrestrial DMB system to provide clipcast service, which enables file download services as provided in MediaFLO, DVB-H, and the other mobile broadcasting systems. Unlike the other mobile broadcasting systems, the proposed system applies more reliable SMS method to activate the DMB terminals for highly stable clipcast service. This allows hybrid, i.e, both SMS and EPG activations of terminals for clipcast services.

The Adoption and Diffusion of Semantic Web Technology Innovation: Qualitative Research Approach (시맨틱 웹 기술혁신의 채택과 확산: 질적연구접근법)

  • Joo, Jae-Hun
    • Asia pacific journal of information systems
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    • v.19 no.1
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    • pp.33-62
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    • 2009
  • Internet computing is a disruptive IT innovation. Semantic Web can be considered as an IT innovation because the Semantic Web technology possesses the potential to reduce information overload and enable semantic integration, using capabilities such as semantics and machine-processability. How should organizations adopt the Semantic Web? What factors affect the adoption and diffusion of Semantic Web innovation? Most studies on adoption and diffusion of innovation use empirical analysis as a quantitative research methodology in the post-implementation stage. There is criticism that the positivist requiring theoretical rigor can sacrifice relevance to practice. Rapid advances in technology require studies relevant to practice. In particular, it is realistically impossible to conduct quantitative approach for factors affecting adoption of the Semantic Web because the Semantic Web is in its infancy. However, in an early stage of introduction of the Semantic Web, it is necessary to give a model and some guidelines and for adoption and diffusion of the technology innovation to practitioners and researchers. Thus, the purpose of this study is to present a model of adoption and diffusion of the Semantic Web and to offer propositions as guidelines for successful adoption through a qualitative research method including multiple case studies and in-depth interviews. The researcher conducted interviews with 15 people based on face-to face and 2 interviews by telephone and e-mail to collect data to saturate the categories. Nine interviews including 2 telephone interviews were from nine user organizations adopting the technology innovation and the others were from three supply organizations. Semi-structured interviews were used to collect data. The interviews were recorded on digital voice recorder memory and subsequently transcribed verbatim. 196 pages of transcripts were obtained from about 12 hours interviews. Triangulation of evidence was achieved by examining each organization website and various documents, such as brochures and white papers. The researcher read the transcripts several times and underlined core words, phrases, or sentences. Then, data analysis used the procedure of open coding, in which the researcher forms initial categories of information about the phenomenon being studied by segmenting information. QSR NVivo version 8.0 was used to categorize sentences including similar concepts. 47 categories derived from interview data were grouped into 21 categories from which six factors were named. Five factors affecting adoption of the Semantic Web were identified. The first factor is demand pull including requirements for improving search and integration services of the existing systems and for creating new services. Second, environmental conduciveness, reference models, uncertainty, technology maturity, potential business value, government sponsorship programs, promising prospects for technology demand, complexity and trialability affect the adoption of the Semantic Web from the perspective of technology push. Third, absorptive capacity is an important role of the adoption. Fourth, suppler's competence includes communication with and training for users, and absorptive capacity of supply organization. Fifth, over-expectance which results in the gap between user's expectation level and perceived benefits has a negative impact on the adoption of the Semantic Web. Finally, the factor including critical mass of ontology, budget. visible effects is identified as a determinant affecting routinization and infusion. The researcher suggested a model of adoption and diffusion of the Semantic Web, representing relationships between six factors and adoption/diffusion as dependent variables. Six propositions are derived from the adoption/diffusion model to offer some guidelines to practitioners and a research model to further studies. Proposition 1 : Demand pull has an influence on the adoption of the Semantic Web. Proposition 1-1 : The stronger the degree of requirements for improving existing services, the more successfully the Semantic Web is adopted. Proposition 1-2 : The stronger the degree of requirements for new services, the more successfully the Semantic Web is adopted. Proposition 2 : Technology push has an influence on the adoption of the Semantic Web. Proposition 2-1 : From the perceptive of user organizations, the technology push forces such as environmental conduciveness, reference models, potential business value, and government sponsorship programs have a positive impact on the adoption of the Semantic Web while uncertainty and lower technology maturity have a negative impact on its adoption. Proposition 2-2 : From the perceptive of suppliers, the technology push forces such as environmental conduciveness, reference models, potential business value, government sponsorship programs, and promising prospects for technology demand have a positive impact on the adoption of the Semantic Web while uncertainty, lower technology maturity, complexity and lower trialability have a negative impact on its adoption. Proposition 3 : The absorptive capacities such as organizational formal support systems, officer's or manager's competency analyzing technology characteristics, their passion or willingness, and top management support are positively associated with successful adoption of the Semantic Web innovation from the perceptive of user organizations. Proposition 4 : Supplier's competence has a positive impact on the absorptive capacities of user organizations and technology push forces. Proposition 5 : The greater the gap of expectation between users and suppliers, the later the Semantic Web is adopted. Proposition 6 : The post-adoption activities such as budget allocation, reaching critical mass, and sharing ontology to offer sustainable services are positively associated with successful routinization and infusion of the Semantic Web innovation from the perceptive of user organizations.

Research Trend Analysis of Publications in the Journal of Home Economics Education Association Using Network Text Analysis (네트워크 텍스트 분석을 이용한 한국가정과교육학회지 논문의 연구 동향 분석)

  • Lee, Yoon-Jung;Kim, Eun Jeung;Kim, Ji sun
    • Journal of Korean Home Economics Education Association
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    • v.31 no.4
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    • pp.1-18
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    • 2019
  • The purpose of this study was to analyze the research trend in home economics education using network text analysis method. The 586 research articles published in the Journal of Home Economics Education Association between July, 2003 and December 2018 were examined using Neckinger 4, a social network analysis software. The frequency and centrality measures(degree centrality, closeness centrality, and betweenness centrality) were calculated for the words appeared throughout the whole period, and the centrality analysis and LAD(Latent Dirichlet Allocation) were conducted for the four sub-periods. The results are as follows: first, the most frequently appeared words are parents, culture, unit, health, career, consumption, practicality, etc. The words such as parents and management scored high in degree centrality; parents and male students in closeness centrality; and male students and units in betweenness centrality. Second, when divided into four periods, the words such as education, family, purpose, class, middle school, and school appeared most frequently across the periods; but some words such as 'purpose' (in period 3 and 4), or 'process' (in period 4) were salient only in certain periods. Third, the words with high centrality were consistent regardless of the types of centrality within each period. Fourth, the topic analysis using LAD showed that curriculum, textbook, family healthiness, teaching-learning, evaluation, dietary life, appearance management, and consumption were the topics consistently appeared across all periods. The topics have become diversified and deepened. New topics such as teacher training and safety appeared in later periods, possibly due to the curriculum and national policy changes, and housing as a less represented topic is suggested as an area that needs further research attention. This study has implication in that it allows researchers to identify the major research interests and the trends in research by researchers in home economic education.

A Study on the Relationship between Volunteer Experience and Subjective Self-awareness (자원봉사활동 경험과 주관적 자아인식 관계 연구)

  • Jo, Gee-yong;Lim, HyoNam;Kim, Doo-Ree;Kang, Kyung-hee;Kim, Seol-Hee;Kim, Yong-Ha;Lee, Chong-Hyung;Ahn, Sang-Yoon;Kim, Kwang-Hwan;Song, Hyeon-Dong;Hwang, Hey-Jeong;Kim, Moon-Joon;Park, A-rma;Gu, Jin-Hee;Chang, Kyung-Hee
    • Journal of Digital Convergence
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    • v.19 no.5
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    • pp.449-460
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    • 2021
  • The purpose of this study explained the experience of volunteering activities and the relationship of subjective self-awareness in order to examine the social meaning of volunteer activities. For adults aged 20 or older, 312 volunteering experience and social support awareness were analyzed on the level of self-identity by allocation sampling method depending on gender and age. The analysis results of this study were as follows. First, it was found that those who have experienced volunteer activitiies have a relatively simple willingness to participate in professional volunteer activities and those who have experienced volunteer activities. Second, social support and self-identification were different depending on whether they have experienced volunteer activities. Third, age, volunteer participation, willingness to participated in volunteering, and social support were analyzed as explanatory factors predicting self-identification of research participants. Based on the research results, volunteer activities to positively promote self-awareness suggested the need to practice volunteer activities according to the life cycle so that social meaning can be given. As a policy suggestion, the need for volunteer activities was closely analyzed to enable healthy self-forming for well-aging from adulthood to old age to discussed the need for policies and systems to strengthen volunteer motivation as leisure activities.

A Study on the Topography and the Criteria of Choosing the Location-Allocation of Palaces - Focusing on Gyeongbokgung Palace and Changdeokgung Palace - (조선 궁궐 입지 선정의 기준과 지형에 대한 연구 - 경복궁과 창덕궁을 중심으로 -)

  • Kim, Kyoosoon
    • Korean Journal of Heritage: History & Science
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    • v.52 no.3
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    • pp.130-145
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    • 2019
  • The palaces in South Korea are largely divided into primary palaces (法宮) and secondary palaces (離宮). In the early Joseon period, the primary palace was Gyeongbokgung Palace, and the secondary palace was Changdeokgung Palace. Additionally, there is the concept of imperial palaces (正宮). Gyeongbokgung Palace was the primary palace and the imperial palace. The topography of Gyeongbokgung is based on Mt. Baegak, which is the symbol of royal authority. The location of the palaces was chosen to highlight the king's dignity and authority. The three gates and three courts (三門三朝) were positioned on a straight line based on one axis along the ridge of Mt. Baegak to establish the legitimacy, hierarchy, and unity of the kingship. The secondary palace was built according to the demands of the king and the royal family or the political situation. It was created as a royal living space; thus, creating independent and diverse spaces along multiple axes. The primary palace was chosen to be built on the terrain of Yang, and the secondary palace was chosen to be built on the terrain of Yin; the criteria for laying buildings in the palace areas had to be different. The most important point in the formation of Joseon palaces was that the secret vital energy for the king (王氣) originated from the sacred mountain. Important elements of the palace were the secret vital energy chain of feng shui (風水氣脈) and the forbidden stream (禁川). The secret vital energy chain of feng shui was the gateway to the secret vital energy for the king, and the forbidden stream was a method of preventing the king from leaving the palace grounds. Gyeongbokgung Palace, which is on typical feng shui terrain, faithfully reflects the principles of feng shui. On the other hand, the secondary palace was built on incomplete and irregular feng shui terrain. Feng shui was part of the nature and the geography of the ruling classes in the Joseon Dynasty. By examining their geography, I believe that the perfection of traditional culture inheritance and restoration can be improved.

Factors Influencing Satisfaction on Home Visiting Health Care Service of the Elderly based on the degree of chronic diseases (만성질환 유병상태에 따른 노인 방문건강관리 서비스 만족도 영향요인 연구)

  • Seo, Daram;Shon, Changwoo
    • 한국노년학
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    • v.41 no.2
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    • pp.271-284
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    • 2021
  • This study was conducted to derive factors that affect the satisfaction of home visiting health care services and to develop effective community care models by using the results of Seoul's outreach service which is the basis for Korean community care. The population of the study was the elderly aged 65 and 70 who participated in the Seoul's outreach community services 3rd stage (July 2017 - June 2018) and 4th stage (July 2018 to June 2019). 2,200 people were extracted by the proportional allocation method and home visit interviews were conducted on them. Subjects were divided into sub-groups based on chronic disease prevalence, and logistic regression was conducted to derive factors that affect the satisfaction of home visiting health care services. The results demonstrated that the elderly without chronic diseases were more satisfied when they received health education and counseling services, the elderly with one chronic disease were more satisfied when they received Community resource-linked services. In the case of elderly people with two or more chronic diseases, the service satisfaction level is increased when health condition assessment and Community resource-linked services are provided. Regardless of whether or not they have chronic diseases, service delivery time was a factor that increased satisfaction in home visiting health care. And the degree of explanation understanding was a factor that increased satisfaction for both single and complex chronic patients. Home Visiting health care services based on the community is a key component of the ongoing community care. In order to increase the sustainability and effectiveness of community care in the future, Community-oriented health care services based on the degree of chronic diseases of the elderly should be provided. In order to provide more effective services, however, it is necessary (1) to establish a linkage system to share health information of the subject held by the National Health Insurance Service to local governments and (2) to provide capacity-building education for visiting nurses to improve the quality of home visiting health care services. It is hoped that this study will be us ed as bas ic data for the successful settlement of community care.

An Economic Analysis Study of Recycling PET·OPP Laminated Film Waste Generated during DECO Film Manufacturing (DECO 필름 제조시 발생하는 PET·OPP 합성 폐필름 재활용의 경제성 분석 연구)

  • Mi Sook Park;Da Yeon Kim;Soo Jin Yang;Seong You Lee;Chun San Kim;Ok Jin Joung;Yong Woo Hwang
    • Resources Recycling
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    • v.32 no.3
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    • pp.57-67
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    • 2023
  • The treatment of waste plastic has primarily been entrusted to small companies, which has resulted in challenges in obtaining an accurate overview of the current state of affairs and ensuring profitability. Consequently, despite the presence of recycling technology, their practical application has proven to be challenging. In this study, as part of the waste plastic material recycling plan, it is assumed that the PET/OPP laminated waste film is peeled off at the waste film generation site for the second use. The recycling rate of PET/OPP delaminated waste film is assumed to be 2%, 10%, and 30% referring to the figures suggested by "Life-cycle Post Plastic Measures" from the Korean government. In this study, a physical separation method was developed as a recycling approach for waste PET. A result of cost-benefit analysis was conducted to evaluate the economic viability of the recycling process based on changes in the recycling rate. The findings indicated that a recycling rate of waste PET was 30% or higher resulted in a cost-benefit ratio (Benefit-cost ratio, BCR) of 1.32, exceeding the threshold of BCR ≥1, which is considered to meet the minimum requirement for cost-benefit balance. As the government's allocation ratio and unit price are expected to increase in the future, the cost-benefit ratio is expected to increase further. This case is expected to serve as a pilot initiative for waste PET recycling and foster profit creation for businesses in similar industries.

Product Evaluation Criteria Extraction through Online Review Analysis: Using LDA and k-Nearest Neighbor Approach (온라인 리뷰 분석을 통한 상품 평가 기준 추출: LDA 및 k-최근접 이웃 접근법을 활용하여)

  • Lee, Ji Hyeon;Jung, Sang Hyung;Kim, Jun Ho;Min, Eun Joo;Yeo, Un Yeong;Kim, Jong Woo
    • Journal of Intelligence and Information Systems
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    • v.26 no.1
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    • pp.97-117
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    • 2020
  • Product evaluation criteria is an indicator describing attributes or values of products, which enable users or manufacturers measure and understand the products. When companies analyze their products or compare them with competitors, appropriate criteria must be selected for objective evaluation. The criteria should show the features of products that consumers considered when they purchased, used and evaluated the products. However, current evaluation criteria do not reflect different consumers' opinion from product to product. Previous studies tried to used online reviews from e-commerce sites that reflect consumer opinions to extract the features and topics of products and use them as evaluation criteria. However, there is still a limit that they produce irrelevant criteria to products due to extracted or improper words are not refined. To overcome this limitation, this research suggests LDA-k-NN model which extracts possible criteria words from online reviews by using LDA and refines them with k-nearest neighbor. Proposed approach starts with preparation phase, which is constructed with 6 steps. At first, it collects review data from e-commerce websites. Most e-commerce websites classify their selling items by high-level, middle-level, and low-level categories. Review data for preparation phase are gathered from each middle-level category and collapsed later, which is to present single high-level category. Next, nouns, adjectives, adverbs, and verbs are extracted from reviews by getting part of speech information using morpheme analysis module. After preprocessing, words per each topic from review are shown with LDA and only nouns in topic words are chosen as potential words for criteria. Then, words are tagged based on possibility of criteria for each middle-level category. Next, every tagged word is vectorized by pre-trained word embedding model. Finally, k-nearest neighbor case-based approach is used to classify each word with tags. After setting up preparation phase, criteria extraction phase is conducted with low-level categories. This phase starts with crawling reviews in the corresponding low-level category. Same preprocessing as preparation phase is conducted using morpheme analysis module and LDA. Possible criteria words are extracted by getting nouns from the data and vectorized by pre-trained word embedding model. Finally, evaluation criteria are extracted by refining possible criteria words using k-nearest neighbor approach and reference proportion of each word in the words set. To evaluate the performance of the proposed model, an experiment was conducted with review on '11st', one of the biggest e-commerce companies in Korea. Review data were from 'Electronics/Digital' section, one of high-level categories in 11st. For performance evaluation of suggested model, three other models were used for comparing with the suggested model; actual criteria of 11st, a model that extracts nouns by morpheme analysis module and refines them according to word frequency, and a model that extracts nouns from LDA topics and refines them by word frequency. The performance evaluation was set to predict evaluation criteria of 10 low-level categories with the suggested model and 3 models above. Criteria words extracted from each model were combined into a single words set and it was used for survey questionnaires. In the survey, respondents chose every item they consider as appropriate criteria for each category. Each model got its score when chosen words were extracted from that model. The suggested model had higher scores than other models in 8 out of 10 low-level categories. By conducting paired t-tests on scores of each model, we confirmed that the suggested model shows better performance in 26 tests out of 30. In addition, the suggested model was the best model in terms of accuracy. This research proposes evaluation criteria extracting method that combines topic extraction using LDA and refinement with k-nearest neighbor approach. This method overcomes the limits of previous dictionary-based models and frequency-based refinement models. This study can contribute to improve review analysis for deriving business insights in e-commerce market.

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.