• Tuberculosis and Respiratory Diseases
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• v.41 no.2
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• pp.87-96
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• 1994

Background : Since tumor necrosis factor was discovered in 1975, TNF has been well known about its cytotoxic effect on tumor cells in vivo and in vitro. According to the recent improvement of molecular biological techinques, it is possible that exogenous TNF gene is transferred to tumor cells and is expressed in theirs. By virtue of TNF gene transfer, we have expected that TNF expressed in TNF-gene-transferred tumor cells would kill tumor cells in vivo without systemic side effect. The expected mechanisms in which antitumor effects of TNF expressed in TNF-gene-transferred tumor cells are working would be as followings. In the first mechanism, TNF expressed in TNF-gene-transferred tumor cells would kill tumor cells around(like homicide). In the second mechanism, TNF expressed in TNF-gene-transferred tumor cells would kill themselves(like suicide). In the third mechanism, TNF expressed in TNF-gene-transferred tumor cells would recruit immune effector cells and kill tumor cells indirectly. In the last mechanism, TNF expressed in TNF-gene-transferred tumor cells would augment cytokine such as interferon-$\gamma$ to kill tumor cells. Among these four mechanisms of antitumor effect, only the second mechanism has not been established yet. Therefore, to elucidate the second mechanism, We performed this study. Method : We transferred TNF-$\alpha$ gene to NCI-H2058, a human mesothelioma cell line and WEHI164, a murine fibrosarcoma cell line by using retroviral vector(pLT12SNTNF). And, We determined by using MTT assay whether TNF expressed in TNF-gene-transferred tumor cell lines would kill themselves like suicide or not. Then, if TNF-gene-transferred tumor cell lines would not suicide themselves, I would know more about the TNF sensitivity of TNF-gene-transferred tumor cell lines to exogenous TNF also by MTT assay. Result : NCI-H2058 and WEHI164 which were sensitive to TNF, became far less sensitive to endogenous and exogenous TNF after being transferred TNF-$\alpha$ gene to. Conclusion : TNF-gene-transfer to NCI-H2058 and WEHI164 gave them resistance to TNF.

• Tuberculosis and Respiratory Diseases
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• v.57 no.6
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• pp.557-566
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• 2004

Background : To find out effectiveness of multimodality treatments based on induction chemotherapy(CTx) in patients with clinical stage IIIA NSCLC Methods : From 1997 to 2002, 74 patients with clinical stage IIIA NSCLC underwent induction CTx at the hospital of Chungnam National University. Induction CTx included above two cycles of cisplatin-based regimens(ectoposide, gemcitabine, vinorelbine, or taxol) followed by tumor evaluation. In 30 complete resection group, additional 4500-5000cGy radiotherapy(RTx) was delivered in 15 patients with pathologic nodal metastasis. 29 out of 44 patients who were unresectable disease, refusal of operation, and incomplete resection were followed by 60-70Gy RTx in local treatment. Additional 1-3 cycle CTx were done in case of induction CTx responders in both local treatment groups. Results : Induction CTx response rate were 44.6%(complete remission 1.4% & partial response 43.2%) and there was no difference of response rate by regimens(p=0.506). After induction chemotherapy, only 33 out of resectable 55 ones(including initial resectable 37 patients) were performed by surgical treatment because of 13 refusal of surgery by themselves and 9 poor predicted reserve lung function. There were 30(40.5%) patients with complete resection, 2(2.6%) persons with incomplete resection, and 1(1.3%) person with open & closure. Response rate in 27 ones with chest RTx out of non-operation group was 4.8% CR and 11.9% PR. In complete resection group, relapse free interval was 13.6 months and 2 year recur rate was 52%. In non-complete resection(incomplete resection or non-operation) group, disease progression free interval was 11.2 months and 2 year disease progression rate was 66.7%. Median survival time of induction CTx 74 patients with IIIA NSCLC was 25.1months. When compared complete resection group with non-complete resection group, the median survival time was 31.7 and 23.4months(p=0.024) and the 2-year overall survival rate was 80% and 41%. In the complete resection group, adjuvant postoperative RTx subgroup significantly improved the 2-year local control rate(0% vs. 40%, p= 0.007) but did not significantly improve overall survival(32.2months vs. 34.9months, p=0.48). Conculusion : Induction CTx is a possible method in the multimodality treatments, especially followed by complete resection, but overall survival by any local treatment(surgical resection or RTx) was low. Additional studies should be needed to analysis data for appropriate patient selection, new chemotherapy regimens and the time when should RTx be initiated.

• Tuberculosis and Respiratory Diseases
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• v.66 no.3
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• pp.192-197
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• 2009

Background: Despite the benefits of home oxygen therapy in patients suffering chronic respiratory failure, previous reports in Korea revealed lower compliance to oxygen therapy and a shorter time for oxygen use than expected. However, these papers were published before oxygen therapy was covered by the national insurance system. Therefore, this study examined whether there were some changes in compliance, using time and other clinical features of home oxygen therapy after insurance coverage. Methods: This study reviewed the medical records of patients prescribed home oxygen therapy in our hospital from November 1, 2006 to September 31, 2008. The patients were interviewed either in person or by telephone to obtain information related to oxygen therapy. Results: During study period, a total 105 patients started home oxygen therapy. The mean age was 69 and 60 (57%) were male. The mean oxygen partial pressure in the arterial blood was 54.5 mmHg and oxygen saturation was 86.3%. Primary diseases that caused hypoxemia were COPD (n=64), lung cancer (n=14), Tb destroyed lung (n=12) and others. After oxygen therapy, more than 50% of patients experienced relief of their subjective dyspnea. The mean daily use of oxygen was 9.8${\pm}$7.3 hours and oxygen was not used during activity outside of their home (mean time, 5.4${\pm}$3.7 hours). Twenty four patients (36%) stopped using oxygen voluntarily 7${\pm}$4.7 months after being prescribed oxygen and showed a less severe pulmonary and right heart function. The causes of stopping were subjective symptom relief (n=11), inconvenience (n=6) and others (7). Conclusion: The prescription of home oxygen has increased since national insurance started to cover home oxygen therapy. However, the mean time for using oxygen is still shorter than expected. During activity of outside their home, patients could not use oxygen due to the absence of portable oxygen. Overall, continuous education to change the misunderstandings about oxygen therapy, more economic support from national insurance and coverage for portable oxygen are needed to extend the oxygen use time and maintain oxygen usage.

• Journal of Environmental Policy
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• v.13 no.4
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• pp.3-49
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• 2014

Growing interest of stakeholders on corporate responsibilities for environment and tightening environmental regulations are highlighting the importance of environmental management more than ever. However, companies' awareness of the importance of environment is still falling behind, and related academic works have not shown consistent conclusions on the relationship between environmental performance and economic performance. One of the reasons is different ways of measuring these two performances. The evaluation scope of economic performance is relatively narrow and the performance can be measured by a unified unit such as price, while the scope of environmental performance is diverse and a wide range of units are used for measuring environmental performances instead of using a single unified unit. Therefore, the results of works can be different depending on the performance indicators selected. In order to resolve this problem, generalized and standardized performance indicators should be developed. In particular, the performance indicators should be able to cover the concepts of both environmental and economic performances because the recent idea of environmental management has expanded to encompass the concept of sustainability. Another reason is that most of the current researches tend to focus on the motive of environmental investments and environmental performance, and do not offer a guideline for an effective implementation strategy for environmental management. For example, a process improvement strategy or a market discrimination strategy can be deployed through comparing the environment competitiveness among the companies in the same or similar industries, so that a virtuous cyclical relationship between environmental and economic performances can be secured. A novel method for measuring eco-efficiency by utilizing Data Envelopment Analysis (DEA), which is able to combine multiple environmental and economic performances, is proposed in this report. Based on the eco-efficiencies, the environmental competitiveness is analyzed and the optimal combination of inputs and outputs are recommended for improving the eco-efficiencies of inefficient firms. Furthermore, the panel analysis is applied to the causal relationship between eco-efficiency and economic performance, and the pooled regression model is used to investigate the relationship between eco-efficiency and economic performance. The four-year eco-efficiencies between 2010 and 2013 of 23 companies are obtained from the DEA analysis; a comparison of efficiencies among 23 companies is carried out in terms of technical efficiency(TE), pure technical efficiency(PTE) and scale efficiency(SE), and then a set of recommendations for optimal combination of inputs and outputs are suggested for the inefficient companies. Furthermore, the experimental results with the panel analysis have demonstrated the causality from eco-efficiency to economic performance. The results of the pooled regression have shown that eco-efficiency positively affect financial perform ances(ROA and ROS) of the companies, as well as firm values(Tobin Q, stock price, and stock returns). This report proposes a novel approach for generating standardized performance indicators obtained from multiple environmental and economic performances, so that it is able to enhance the generality of relevant researches and provide a deep insight into the sustainability of environmental management. Furthermore, using efficiency indicators obtained from the DEA model, the cause of change in eco-efficiency can be investigated and an effective strategy for environmental management can be suggested. Finally, this report can be a motive for environmental management by providing empirical evidence that environmental investments can improve economic performance.

• Journal of Korean Home Economics Education Association
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• v.25 no.1
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• pp.95-118
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• 2013

The purpose of this study was to analyze the contents of housing related to characters, objectives, and contents of FCS curricular from the 1st to 2009 revised curriculum of secondary school. The data were downloaded from the NCIC homepage(http://www.ncic.re.kr/2012. 04. 08) from the 1st(1955. 08) to 2009 revised curriculum(2012. 03) of secondary school. After examining the characters and objectives of each curriculum, contents of housing was analyzed by units and context elements of middle and high school separately. The titles of the subject, the objectives, the instructions, the leaning spheres, weekly hours, grade and gender of candidates, the emphasis of the instruction, etc. have been changed through the curriculum revision. The 6th curriculum was the main period to open to both genders, the $7^{th}$ was the period to combine with technology, the 2007 version was to change the structure of contents of home economics, and the 2009 version switched technology home economics from mandatory to optional in high school. The character of the courses was presented at the 1st curriculum, but it was left out from the $2^{nd}$ to $5^{th}$ curriculum. From the $6^{th}$ curriculum, the characters were separately given to middle and high school. The character of housing area started to appear only in high school home economics from the $7^{th}$ curriculum. The course objectives were described in all curriculum of both middle and high school. This applies to housing area as well. The course objectives have been modified in order to reflect value changes due to social issues. During each curriculum, contents of housing continued to change in context, course load, and candidates. Reflection of housing trends and social needs were the main causes of the change. 2009 version emphasizes on eco-life and sense of community.

• Journal of Periodontal and Implant Science
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• v.37 no.sup2
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• pp.427-445
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• 2007

To improve osseointegration at the boneto-implant interface, several studies have been carried out to modify titanium surface. Variations in surface texture or microtopography may affect the cellular response to an implant. Osteoblast-like cells attach more readily to a rougher titanium surface, and synthesis of extracellular matrix and subsequent mineralization were found to be enhanced on rough or porous coated titanium. However, regarding the effect of roughened surface by physical and mechanical methods, most studies carried out on the reactions of cells to micrometric topography, little work has been performed on the reaction of cells to nanotopography. The purpose of this study was to examme the response of osteoblast-like cell cultured on blasted surfaces and alkali treated surfaces, and to evaluate the influence of surface texture or submicro-scaled surface topography on the cell attachment, cell proliferation and the gene expression of osteoblastic phenotype using ROS 17/2.8 cell lines. In scanning electron micrographs, the blasted, alkali treated and machined surfaces demonstrated microscopic differences in the surface topography. The specimens of alkali treatment had a submicro-scaled porous sur-face with pore size about 200 nm. The blasted surfaces showed irregularities in morphology with small(<10 ${\mu}m$) depression and indentation among flatter-appearing areas of various sizes. Based on profilometry, the blasted surfaces was significantly rougher than the machined and the alkali treated surfaces (p$TiO_2$) were observed on alkali treated surfaces, whereas not observed on machined and blasted surfaces. The attachment morphology of cells according to time was observed by the scanning electron microscope. After 1 hour incubation, the cells were in the process of adhesion and spreading on the prepared surfaces. After 3 hours, the cells on all prepared surfaces were further spreaded and flattened, however on the blasted and alkali treated surfaces, the cells exhibited slightly irregular shapes and some gaps or spaces were seen. After 24 hours incubation, most cells of the all groups had a flattened and polygonal shape, but the cells were more spreaded on the machined surfaces than the blasted and alkali treated surfaces. The MTT assay indicated the increase on machined, alkali treated and blasted surfaces according to time, and the alkali treated and blasted surfaces showed significantly increased in optical density comparing with machined surfaces at 1 day (p<0.01). Gene expression study showed that mRNA expression level of ${\alpha}\;1(I)$ collagen, alkaline phosphatase and osteopontin of the osteoblast-like cells showed a tendency to be higher on blasted and alkali treated surfaces than on the machined surfaces, although no siginificant difference in the mRNA expression level of ${\alpha}\;1(I)$ collagen, alkaline phosphatase and osteopontin was observed among all groups. In conclusion, we suggest that submicroscaled surfaces on osteoblast-like cell response do not over-ride the one of the surface with micro-scaled topography produced by blasting method, although the microscaled and submicro-scaled surfaces can accelerate osteogenic cell attachment and function compared with the machined surfaces.

• The Korean Journal of Air & Space Law and Policy
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• v.29 no.2
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• pp.109-134
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• 2014

Regulation (EC) No 261/2004 of the European Parliament and of the Council of 11 February 2004 establishing common rules on compensation of assistance to passengers in the event of denied boarding and of cancellation or long delay of flights (Regulation No 261/2004) provides extra protection to air passengers in circumstances of denied boarding, cancellation and long-delay. The Regulation intends to provide a high level of protection to air passengers by imposing obligations on air carriers and, at the same time, offering extensive rights to air passengers. If denied boarding, cancellation and long-delay are caused by reasons other than extraordinary circumstances, passengers are entitled for compensation under Article 7 of Regulation No 261/2004. In Wallentin-Hermann v Alitalia-Linee Aeree Italiane SpA(Case C-549/07, [2008] ECR I-11061), the Court did, however, emphasize that this does not mean that it is never possible for technical problems to constitute extraordinary circumstances. It cited specific examples of where: an aircraft manufacturer or competent authority revealed that there was a hidden manufacturing defect on an aircraft which impacts on safety; or damage was caused to an aircraft as a result of an act of sabotage or terrorism. Such events are not inherent in the normal exercise of the activity of the air carrier concerned and is beyond the actual control of that carrier on account of its nature or origin. One further point arising out of the court's decision is worth mentioning. It is not just necessary to satisfy the extraordinary circumstances test for the airline to be excused from paying compensation. It must also show that the circumstances could not have been avoided even if all reasonable measures had been taken. It is clear from the language of the Court's decision that this is a tough test to meet: the airline will have to establish that, even if it had deployed all its resources in terms of staff or equipment and the financial means at its disposal, it would clearly not have been able - unless it had made intolerable sacrifices in the light of the capacities of its undertaking at the relevant time - to prevent the extraordinary circumstances with which it was confronted from leading to the cancellation of the flight.

• 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.111-126
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• 2017

Recommender systems based on association rule mining significantly contribute to seller's sales by reducing consumers' time to search for products that they want. Recommendations based on the frequency of transactions such as orders can effectively screen out the products that are statistically marketable among multiple products. A product with a high possibility of sales, however, can be omitted from the recommendation if it records insufficient number of transactions at the beginning of the sale. Products missing from the associated recommendations may lose the chance of exposure to consumers, which leads to a decline in the number of transactions. In turn, diminished transactions may create a vicious circle of lost opportunity to be recommended. Thus, initial sales are likely to remain stagnant for a certain period of time. Products that are susceptible to fashion or seasonality, such as clothing, may be greatly affected. This study was aimed at expanding association rules to include into the list of recommendations those products whose initial trading frequency of transactions is low despite the possibility of high sales. The particular purpose is to predict the strength of the direct connection of two unconnected items through the properties of the paths located between them. An association between two items revealed in transactions can be interpreted as the interaction between them, which can be expressed as a link in a social network whose nodes are items. The first step calculates the centralities of the nodes in the middle of the paths that indirectly connect the two nodes without direct connection. The next step identifies the number of the paths and the shortest among them. These extracts are used as independent variables in the regression analysis to predict future connection strength between the nodes. The strength of the connection between the two nodes of the model, which is defined by the number of nodes between the two nodes, is measured after a certain period of time. The regression analysis results confirm that the number of paths between the two products, the distance of the shortest path, and the number of neighboring items connected to the products are significantly related to their potential strength. This study used actual order transaction data collected for three months from February to April in 2016 from an online commerce company. To reduce the complexity of analytics as the scale of the network grows, the analysis was performed only on miscellaneous goods. Two consecutively purchased items were chosen from each customer's transactions to obtain a pair of antecedent and consequent, which secures a link needed for constituting a social network. The direction of the link was determined in the order in which the goods were purchased. Except for the last ten days of the data collection period, the social network of associated items was built for the extraction of independent variables. The model predicts the number of links to be connected in the next ten days from the explanatory variables. Of the 5,711 previously unconnected links, 611 were newly connected for the last ten days. Through experiments, the proposed model demonstrated excellent predictions. Of the 571 links that the proposed model predicts, 269 were confirmed to have been connected. This is 4.4 times more than the average of 61, which can be found without any prediction model. This study is expected to be useful regarding industries whose new products launch quickly with short life cycles, since their exposure time is critical. Also, it can be used to detect diseases that are rarely found in the early stages of medical treatment because of the low incidence of outbreaks. Since the complexity of the social networking analysis is sensitive to the number of nodes and links that make up the network, this study was conducted in a particular category of miscellaneous goods. Future research should consider that this condition may limit the opportunity to detect unexpected associations between products belonging to different categories of classification.

• 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.