• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.207-221
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• 2023

This study suggests deep neural network models for estimating air temperature with Level 1B (L1B) datasets of GEO-KOMPSAT-2A (GK-2A). The temperature at 1.5 m above the ground impact not only daily life but also weather warnings such as cold and heat waves. There are many studies to assume the air temperature from the land surface temperature (LST) retrieved from satellites because the air temperature has a strong relationship with the LST. However, an algorithm of the LST, Level 2 output of GK-2A, works only clear sky pixels. To overcome the cloud effects, we apply a deep neural network (DNN) model to assume the air temperature with L1B calibrated for radiometric and geometrics from raw satellite data and compare the model with a linear regression model between LST and air temperature. The root mean square errors (RMSE) of the air temperature for model outputs are used to evaluate the model. The number of 95 in-situ air temperature data was 2,496,634 and the ratio of datasets paired with LST and L1B show 42.1% and 98.4%. The training years are 2020 and 2021 and 2022 is used to validate. The DNN model is designed with an input layer taking 16 channels and four hidden fully connected layers to assume an air temperature. As a result of the model using 16 bands of L1B, the DNN with RMSE 2.22℃ showed great performance than the baseline model with RMSE 3.55℃ on clear sky conditions and the total RMSE including overcast samples was 3.33℃. It is suggested that the DNN is able to overcome cloud effects. However, it showed different characteristics in seasonal and hourly analysis and needed to append solar information as inputs to make a general DNN model because the summer and winter seasons showed a low coefficient of determinations with high standard deviations.

• Journal of The Korean Association For Science Education
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• v.43 no.6
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• pp.549-562
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• 2023

The current society is in the VUCA era, where various risks produced by humans are spread along with the development of science and technology. There is a need to increase the level of risk literacy of citizens to strengthen their daily preparedness to respond to these risks. For this on, it is necessary to reconsider the role of science education so that risks can be perceived and responded to scientifically and objectively. Accordingly, in order to investigate the role of science education in a risk society, this study reviewed the history of risk perception and response related to science and analyzed its characteristics. In this process, perception and response to risks arising from blood pressure were analyzed in three contexts (historical context, curriculum context, textbook context). For historical context, journals registered in SCIE were selected as research subjects among journals where research related to the history of knowledge of the heart and cardiovascular system was conducted. Papers with the keywords 'hypertension' and 'history' were selected from the journals, and changes in perception and responses related to blood pressure were compared and analyzed by period. The curriculum context is analyzed from the 1st national curriculum to the 2022 revised curriculum, and content elements and achievement standard related to blood pressure were compared and analyzed. It was confirmed that risks arising from blood pressure were not included from the 1st to the 6th national curriculum, and that risks arising from blood pressure were included from the 7th national curriculum (excluding the 2009 revised curriculum). For the textbook context, the 7th national curriculum BiologyⅠ, the 2015 revised curriculum Life ScienceⅠ, and Health were selected, and through text mining, keywords that representing curriculums and textbooks were selected, and the presentation of risk perception and response was analyzed based on the keywords. And by analyzing the figures and tables presented in the textbook, the characteristics of risk perception and risk response were derived. This study is meaningful in that it was able to confirm the role of risk perception and response in science education.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.271-286
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• 2023

The global COVID-19 pandemic has transformed face masks from situational accessories to indispensable items in daily life, prompting a shift in public perception and behavior. While the relaxation of mandatory mask-wearing regulations is underway, a significant number of individuals continue to embrace face masks, turning them into a form of personal expression and identity. This phenomenon has given rise to the Fashion Mask industry, characterized by unique designs and colors, experiencing rapid growth in the market. However, existing research on masks is predominantly focused on their efficacy in preventing infection or exploring attitudes during the pandemic, leaving a gap in understanding consumer preferences for mask design. We address this gap by investigating consumer perceptions and preferences for two prevalent mask designs-horizontal fold flat masks and vertical fold flat masks. Through a comprehensive approach involving surveys and eye-tracking experiments, we aim to unravel the subtle differences in how consumers perceive these designs. Our research questions focus on determining which design is more appealing and exploring the reasons behind any observed differences. The study's findings reveal a clear preference for vertical fold flat masks, which are not only preferred but also perceived as unique, sophisticated, three-dimensional, and lively. The eye-tracking analysis provides insights into the visual attention patterns associated with mask designs, highlighting the pivotal role of the fold line in influencing these patterns. This research contributes to the evolving understanding of masks as a fashion statement and provides valuable insights for manufacturers and marketers in the Fashion Mask industry. The results have implications beyond the pandemic, emphasizing the importance of design elements in sustaining consumer interest in face masks.

• Journal of Korean Elementary Science Education
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• v.43 no.3
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• pp.433-445
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• 2024

This study aims to compare and analyze the educational contents of the material area in the elementary science curriculums of North and South Korea. The research subjects are materials and motion and energy (partial) areas of the revised science curriculum of South Korea in 2022 and materials around us and science in daily life (partial) areas of the nature and education program of North Korea in 2013. This study compared the elements of the educational content of the material domain between North and South Korea according to the grade. Furthermore, the reflection of the material domain goals of North and South Korea at the international level was analyzed using the evaluation framework of the Trends in International Mathematics and Science Study (TIMSS) 2023 for the material content domains for fourth-grade elementary schools. Four teachers who majored in elementary science education and one expert in science education participated in the analysis. The results are as follows. First, in terms of the properties of matter, the content covered in the curriculum of North and South Korea differed in application period by grade and in the scope and level of content. Second, regarding material change, North Korea did not cover acids and bases but included methods for speeding up dissolution. Third, North Korea reflected the goal of the TIMSS 2023 properties of materials more highly than South Korea. Fourth, similar to the results for the analysis on the properties of materials, North Korea reflected the goal of the TIMSS 2023 for changes of materials more highly than did South Korea. In conclusion, the elements and timing of application of the material contents differed between North and South Korea, and the degree of reflection of goals at the international level was found to be higher for North Korea. In the future, this study hopes that cooperation and research on the development of integrated science and curriculum will occur along with the revitalization of educational exchange between North and South Korea from the perspective of the preparation for unification beyond the ideological conflict between them.

• Journal of Nutrition and Health
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• v.48 no.6
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• pp.476-487
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• 2015

Purpose: This study was conducted to examine the concentration of nutrients in transitional breast milk from Korean lactating mothers and to evaluate daily intakes of their infants based on the Dietary Reference Intakes for Koreans 2010 (KDRIs 2010). Methods: Breast milk samples were collected at 5~15 days postpartum from 100 healthy lactating Korean mothers. Macro- and micro-nutrients, and immunoglobulin (Igs) concentrations in breast milk were analyzed. Results: The mean energy, protein, fat, and carbohydrate concentrations in breast milk were $59.99{\pm}8.01kcal/dL$, $1.47{\pm}0.27g/dL$, $2.88{\pm}0.89g/dL$, and $6.72{\pm}0.22g/dL$. The mean linoleic acid (LA), a-linolenic acid (ALA), arachidonic acid (AA), and docosahexaenoic acid (DHA) concentrations were $181.44{\pm}96.41mg/dL$, $28.15{\pm}8.89mg/dL$, $5.67{\pm}1.86mg/dL$, and $5.74{\pm}2.57mg/dL$. The mean vitamin A, vitamin D, vitamin E, vitamin $B_1$, vitamin $B_2$, vitamin $B_{12}$, and folate concentrations were $2.75{\pm}1.75{\mu}g/dL$, $2.31{\pm}1.12ng/dL$, $0.74{\pm}1.54mg/dL$, $3.02{\pm}1.84mg/dL$, $7.51{\pm}20.96{\mu}g/dL$, $61.78{\pm}26.78{\mu}g/dL$, $63.71{\pm}27.19ng/dL$, and $0.52{\pm}0.26{\mu}g/dL$. The mean concentrations of calcium, iron, potassium, sodium, zinc, and copper were $20.71{\pm}3.34mg/dL$, $0.59{\pm}0.86mg/dL$, $66.71{\pm}10.35mg/dL$, $27.72{\pm}10.16mg/dL$, $0.44{\pm}0.41mg/dL$, and $70.48{\pm}30.41{\mu}g/dL$. The mean IgA and total IgE concentrations were $61.85{\pm}31.97mg/dL$ and $235.00{\pm}93.00IU/dL$. The estimated daily intakes of infants for protein, vitamin D, vitamin E, vitamin $B_2$, vitamin $B_{12}$, iron, potassium, sodium, zinc, and copper were sufficient compared to KDRIs 2010 adjusted by transitory milk intakes. The estimated infants' intakes of energy, fat, carbohydrate, vitamin A, vitamin C, vitamin $B_1$, folate, and calcium did not meet KDRIs 2010 adjusted by transitory milk intakes. Conclusion: In general most estimated nutrient intakes of Korean breast-fed infants in transitory breast milk were sufficient, however some nutrient intakes were not sufficient based on KDRIs 2010. These results warrant conduct of future studies for investigation of important dietary factors associated with nutrients in breast milk to improve the quality of breast milk, which may contribute to understanding nutrition in early life and promoting growth and development of breast-fed infants.

• The Korean Journal of Rehabilitation Nursing
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• v.2 no.2
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• pp.257-270
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• 1999

The purpose of this study is to investigate factors related to the intent of using home nursing of chronic disease patients who got out of a university hospital. For the purpose, the study selected 153 patients who were hospitalized and left K university hospital with diagnoses of cancer, hypertension, diabetes and cerebral vascular accident and ordered to be discharged and performed interviews with them and surveys on their medical records to obtain the following results. For this study a direct-interview survey and medical record review was conducted from June 28 to Aug. 30, 1998. The frequency and mean values were computed to find the characteristics of the study subjects, and $X^2$-test, t-test, factor analysis and multiple logistic regession analysis were applied for the analysis of the data. The following results were obtained. 1) When characteristics of the subjects were examined, men and women occupied for 58.8% and 41.2%, respectively. The subjects were 41.3 years old in aver age and had the monthly aver age earning of 0.99 million won or below, which was the most out of the total subjects at 34.6%. Among the total, 87.6% resided in cities and 12.4 in counties. The most left the hospital with diagnosis of cancer at 51.6%, followed by hyper tension at 24.2%, diabetes at 13.7% and cerebral vascular accident at 7.2%. 2) 93.5% of the selected patients had the intent of using home nursing and 6.5%, didn't. Among those patients having the intent, 85.6% had the intent of paying for home nursing and 14.4%, didn't. The subjects expected that the nursing would be paid 9,143 won in aver age and 47.7% of them preferred national authorities as the main servers. 86.3% of the subjects thought that home nursing business had the main advantage of making it possible to learn nursing methods at home and thereby contributing to improving the ability of patients and their facilities to solve health problems. 3) Relations between the intent of use and characteristics of the subjects such as demography-related social, home environment, disease and physical function characteristics did not show statistically significant differences among one another. Compared to those who had no intent of using home nursing, the group having the intent had more cases of male patients, the age of 39 or below, residence in cities, 5 family member s or more, no existence of home nursing servers, leaving the hospital from a non-hospitalized building, disease development for five months or below, hospitalization for ten days or more, non-hospitalization with in the recent one month, two times or over of hospitalization, leaving the hospital with no demand of special treatment, operation underwent, poor results of treatment, leaving the hospital with demand of rehabilitation services, physical disablement and high evaluation point of daily life. 4) Among those patients having the intent of using home nursing, 47.6% demanded technical nursing and 55.9%, supportive nursing. As technical nursing,' inject into a blood vessel ' and 'treat pustule and teach basic prevention methods occupied for 57.4%, respectively, topping the list. Among demands of supportive nursing, 'observe patients 'status and refer them to hospitals or community resources as available, if necessary' was the most with percent age point of 59.5. Regarding the intent of paying for home nursing, 39.2% of those patients wishing to use the nursing responded paying for technical services and 20.2, supportive services. In detail, 70.0% wanted to pay for a service stated as 'inject into a blood vessel', highest among the former services and 30.7%, a service referred to as 'teaching exercises needed to make the body of patients move', highest among the latter. When this was analyzed in terms of a relation between the need(the need for home nursing) and the demand(the intent of paying for home nursing), The rate of the need to the demand was found two or three times higher in technical nursing(0.82) than in supportive nursing(0.35). In aspects of tech ical nursing, muscle injection(1.26, the 1st rank) was highest in the rate while among aspects of supportive nursing, a service referred to as 'teach exercises needed for making patients move their bodies normally'(0.58, the 1st rank). 5) factors I(satisfaction with hospital services), II(recognition of disease state), III(economy) and IV(period of disease) occupied for 34.4, 13.8, 11.9 and 9.2 percents, respectively among factors related to the intent by the subjects of using home nursing, totaled 59.3%. In conclusion, most of chronic disease patients have the intent of using hospital-based home nursing and satisfaction with hospital services is a factor affecting the intent most. Thus a post-management system is needed to continue providing health management to those patients after they leave the hospital. Further, supportive services should be provided in order that those who are satisfied with hospital services return to their community and live their in dependent lives. Based on these results, the researcher would make the following recommendation. 1) Because home nursing becomes more and more needed due to a sharp increase in chronic disease patients and elderly people, related rules and regulations should be made and implemented. 2) Hospital nurses specializing in home nursing should be cultivated.

• Journal of Science of Art and Design
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• v.11
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• pp.109-152
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• 2007

This thesis started from accepting the criticism and concretely seeking the possibility of visual visuality, in particular, visual physicality or physical visuality through the expression revealed in painting space. This study aims at stressing the role of the body in visual perception and pictorial expression by it by examining the interaction between it and the body. First of all, this study explored perception and the position of the body in the great frame of the historical stream from modernism, through minimalism, through post-minimalism to later art in order to confirm the interaction between visual perception and the body or the change in the intervention of physicality in the stream of contemporary art, and connected them with a discourse on perception and the body. It raised as the grounds for it the discussions which provided the theoretical background about perception. It dealt with the scientific discussions on perceptual physicality by Gestalt psychology in perceptive psychology, and next the discussion of Rudolf Arnheim who exemplified Gestalt psychology mainly on the dimension of visual art. It is significant in explaining the perceptual activeness which is the same as that of M. Merleau-Ponty as a primary debater to solve the questions of perceptual physicality and physical visuality. M. Merleau-Ponty set forth ambiguous perception and the body as its background as the fundamental bases for perceiving the world rather than consciousness proved explicitly. As Hal Foster said, as minimalist phenomenological background they provided appropriate theoretical background to the late art rising against modernist logic. Next, after the 1970s Frank Stella showed a working method and a tendency entirely different from those in the previous period. For example, deconstruction of frame, decentralized spatial expression, dynamic and mixed expression, and allowing real space by overlapping were judged to swing to approval of perceptual physicality. Francis Bacon's painting structure, that is, figure, triptych, aplat and a method of production by accident were understood to well reflect M. Merleau-Ponty's chair logic of chiasme. This study tries to seek the possibility of pictorial expression from works aiming at defining the question of seeing in connection with physicality, the role of the body as the body accumulated and the linking with a real, daily life as the background of the body, and confirm the phase shift.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.75-100
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• 2018

Mobile devices have become an important channel for news content usage in our daily life. However, online news content readers' resistance to online news monetization is more serious than other digital content businesses, such as webtoons, music sources, videos, and games. Since major portal sites distribute online news content free of charge to increase their traffics, customers have been accustomed to free news content; hence this makes online news providers more difficult to switch their policies on business models (i.e., monetization policy). As a result, most online news providers are highly dependent on the advertising business model, which can lead to increasing number of false, exaggerated, or sensational advertisements inside the news website to maximize their advertising revenue. To reduce this advertising dependencies, many online news providers had attempted to switch their 'free' readers to 'paid' users, but most of them failed. However, recently, some online news media have been successfully applying the Pay-What-You-Want (PWYW) payment model, which allows readers to voluntarily pay fees for their favorite news content. These successful cases shed some lights to the managers of online news content provider regarding that the PWYW model can serve as an alternative business model. In this study, therefore, we collected 379 online news articles from Ohmynews.com that has been successfully employing the PWYW model, and analyzed the comparative importance of systematic attributes of online news content on readers' voluntary payment. More specifically, we derived the six systematic attributes (i.e., Type of Article Title, Image Stimulation, Article Readability, Article Type, Dominant Emotion, and Article-Image Similarity) and three or four levels within each attribute based on previous studies. Then, we conducted content analysis to measure five attributes except Article Readability attribute, measured by Flesch readability score. Before conducting main content analysis, the face reliabilities of chosen attributes were measured by three doctoral level researchers with 37 sample articles, and inter-coder reliabilities of the three coders were verified. Then, the main content analysis was conducted for two months from March 2017 with 379 online news articles. All 379 articles were reviewed by the same three coders, and 65 articles that showed inconsistency among coders were excluded before employing conjoint analysis. Finally, we examined the comparative importance of those six systematic attributes (Study 1), and levels within each of the six attributes (Study 2) through conjoint analysis with 314 online news articles. From the results of conjoint analysis, we found that Article Readability, Article-Image Similarity, and Type of Article Title are the most significant factors affecting online news readers' voluntary payment. First, it can be interpreted that if the level of readability of an online news article is in line with the readers' level of readership, the readers will voluntarily pay more. Second, the similarity between the content of the article and the image within it enables the readers to increase the information acceptance and to transmit the message of the article more effectively. Third, readers expect that the article title would reveal the content of the article, and the expectation influences the understanding and satisfaction of the article. Therefore, it is necessary to write an article with an appropriate readability level, and use images and title well matched with the content to make readers voluntarily pay more. We also examined the comparative importance of levels within each attribute in more details. Based on findings of two studies, two major and nine minor propositions are suggested for future empirical research. This study has academic implications in that it is one of the first studies applying both content analysis and conjoint analysis together to examine readers' voluntary payment behavior, rather than their intention to pay. In addition, online news content creators, providers, and managers could find some practical insights from this research in terms of how they should produce news content to make readers voluntarily pay more for their online news content.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.33-56
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• 2017

As Internet usage is becoming more common worldwide and smartphone become necessity in daily life, technologies and applications related to mobile Internet are developing rapidly. The results of the Internet usage patterns of consumers around the world imply that there are many potential new business opportunities for mobile Internet technologies and applications. The location-based service (LBS) is a service based on the location information of the mobile device. LBS has recently gotten much attention among many mobile applications and various LBSs are rapidly developing in numerous categories. However, even with the development of LBS related technologies and services, there is still a lack of empirical research on the intention to use LBS. The application of previous researches is limited because they focused on the effect of one particular factor and had not shown the direct relationship on the intention to use LBS. Therefore, this study presents a research model of factors that affect the intention to use and actual use of LBS whose market is expected to grow rapidly, and tested it by conducting a questionnaire survey of 330 users. The results of data analysis showed that service customization, service quality, and personal innovativeness have a positive effect on the intention to use LBS and the intention to use LBS has a positive effect on the actual use of LBS. These results implies that LBS providers can enhance the user's intention to use LBS by offering service customization through the provision of various LBSs based on users' needs, improving information service qualities such as accuracy, timeliness, sensitivity, and reliability, and encouraging personal innovativeness. However, privacy concerns in the context of LBS are not significantly affected by service customization and personal innovativeness and privacy concerns do not significantly affect the intention to use LBS. In fact, the information related to users' location collected by LBS is less sensitive when compared with the information that is used to perform financial transactions. Therefore, such outcomes on privacy concern are revealed. In addition, the advantages of using LBS are more important than the sensitivity of privacy protection to the users who use LBS than to the users who use information systems such as electronic commerce that involves financial transactions. Therefore, LBS are recommended to be treated differently from other information systems. This study is significant in the theoretical point of contribution that it proposed factors affecting the intention to use LBS in a multi-faceted perspective, proved the proposed research model empirically, brought new insights on LBS, and broadens understanding of the intention to use and actual use of LBS. Also, the empirical results of the customization of LBS affecting the user's intention to use the LBS suggest that the provision of customized LBS services based on the usage data analysis through utilizing technologies such as artificial intelligence can enhance the user's intention to use. In a practical point of view, the results of this study are expected to help LBS providers to develop a competitive strategy for responding to LBS users effectively and lead to the LBS market grows. We expect that there will be differences in using LBSs depending on some factors such as types of LBS, whether it is free of charge or not, privacy policies related to LBS, the levels of reliability related application and technology, the frequency of use, etc. Therefore, if we can make comparative studies with those factors, it will contribute to the development of the research areas of LBS. We hope this study can inspire many researchers and initiate many great researches in LBS fields.

• 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.