• 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.

• Asia pacific journal of information systems
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• v.22 no.1
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• pp.29-52
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• 2012

Consumers differ in the way they make a purchase. An audio mania would willingly make a bold, yet serious, decision to buy a top-of-the-line home theater system, while he is not interested in replacing his two-decade-old shabby car. On the contrary, an automobile enthusiast wouldn't mind spending forty thousand dollars to buy a new Jaguar convertible, yet cares little about his junky component system. It is product involvement that helps us explain such differences among individuals in the purchase style. Product involvement refers to the extent to which a product is perceived to be important to a consumer (Zaichkowsky, 2001). Product involvement is an important factor that strongly influences consumer's purchase decision-making process, and thus has been of prime interest to consumer behavior researchers. Furthermore, researchers found that involvement is closely related to perceived risk (Dholakia, 2001). While abundant research exists addressing how product involvement relates to overall perceived risk, little attention has been paid to the relationship between involvement and different types of perceived risk in an electronic commerce setting. Given that perceived risk can be a substantial barrier to the online purchase (Jarvenpaa, 2000), research addressing such an issue will offer useful implications on what specific types of perceived risk an online firm should focus on mitigating if it is to increase sales to a fullest potential. Meanwhile, past research has focused on such consumer responses as information search and dissemination as a consequence of involvement, neglecting other behavioral responses like online merchant selection. For one example, will a consumer seriously considering the purchase of a pricey Guzzi bag perceive a great degree of risk associated with online buying and therefore choose to buy it from a digital storefront rather than from an online marketplace to mitigate risk? Will a consumer require greater trust on the part of the online merchant when the perceived risk of online buying is rather high? We intend to find answers to these research questions through an empirical study. This paper explores the impact of enduring product involvement and perceived risks on required trust level, and further on online merchant choice. For the purpose of the research, five types or components of perceived risk are taken into consideration, including financial, performance, delivery, psychological, and social risks. A research model has been built around the constructs under consideration, and 12 hypotheses have been developed based on the research model to examine the relationships between enduring involvement and five components of perceived risk, between five components of perceived risk and required trust level, between enduring involvement and required trust level, and finally between required trust level and preference toward an e-tailer. To attain our research objectives, we conducted an empirical analysis consisting of two phases of data collection: a pilot test and main survey. The pilot test was conducted using 25 college students to ensure that the questionnaire items are clear and straightforward. Then the main survey was conducted using 295 college students at a major university for nine days between December 13, 2010 and December 21, 2010. The measures employed to test the model included eight constructs: (1) enduring involvement, (2) financial risk, (3) performance risk, (4) delivery risk, (5) psychological risk, (6) social risk, (7) required trust level, (8) preference toward an e-tailer. The statistical package, SPSS 17.0, was used to test the internal consistency among the items within the individual measures. Based on the Cronbach's ${\alpha}$ coefficients of the individual measure, the reliability of all the variables is supported. Meanwhile, the Amos 18.0 package was employed to perform a confirmatory factor analysis designed to assess the unidimensionality of the measures. The goodness of fit for the measurement model was satisfied. Unidimensionality was tested using convergent, discriminant, and nomological validity. The statistical evidences proved that the three types of validity were all satisfied. Now the structured equation modeling technique was used to analyze the individual paths along the relationships among the research constructs. The results indicated that enduring involvement has significant positive relationships with all the five components of perceived risk, while only performance risk is significantly related to trust level required by consumers for purchase. It can be inferred from the findings that product performance problems are mostly likely to occur when a merchant behaves in an opportunistic manner. Positive relationships were also found between involvement and required trust level and between required trust level and online merchant choice. Enduring involvement is concerned with the pleasure a consumer derives from a product class and/or with the desire for knowledge for the product class, and thus is likely to motivate the consumer to look for ways of mitigating perceived risk by requiring a higher level of trust on the part of the online merchant. Likewise, a consumer requiring a high level of trust on the merchant will choose a digital storefront rather than an e-marketplace, since a digital storefront is believed to be trustworthier than an e-marketplace, as it fulfills orders by itself rather than acting as an intermediary. The findings of the present research provide both academic and practical implications. The first academic implication is that enduring product involvement is a strong motivator of consumer responses, especially the selection of a merchant, in the context of electronic shopping. Secondly, academicians are advised to pay attention to the finding that an individual component or type of perceived risk can be used as an important research construct, since it would allow one to pinpoint the specific types of risk that are influenced by antecedents or that influence consequents. Meanwhile, our research provides implications useful for online merchants (both online storefronts and e-marketplaces). Merchants may develop strategies to attract consumers by managing perceived performance risk involved in purchase decisions, since it was found to have significant positive relationship with the level of trust required by a consumer on the part of the merchant. One way to manage performance risk would be to thoroughly examine the product before shipping to ensure that it has no deficiencies or flaws. Secondly, digital storefronts are advised to focus on symbolic goods (e.g., cars, cell phones, fashion outfits, and handbags) in which consumers are relatively more involved than others, whereas e- marketplaces should put their emphasis on non-symbolic goods (e.g., drinks, books, MP3 players, and bike accessories).

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.107-122
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• 2017

Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.

• Journal of the Korean Society of Radiology
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• v.11 no.5
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• pp.303-312
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• 2017

The central goal of Gamma Knife radiosurgery(GKRS) is to maximize the conformity of the prescription isodose surface, and to minimize the radiation effect of the normal tissue surrounding the target volume. There are the various kinds of indices related with the quality of treatment plans such as conformity index, coverage, selectivity, beam-on time, gradient index(GI), and conformity/gradient index(CGI). As the best treatment plan evaluation tool, we must check by all means conformity index, GI, and CGI among them. Specially, GI and CGI related with complication of healthy normal tissue is more indispensible than conformity index. Then author calculated and statistically analysed CGI, the newly defined conformity/gradient index as well as GI being applied widely using the treatment planning system Leksell GammaPlan(LGP) and the verification method Variable Ellipsoid Modeling Technique(VEMT). In the study 10 patients with intracranial lesion treated by GKRS were included. Author computed the indices from LGP and VEMT requiring only four parameters: the prescribed isodose volume, the volume with dose > 30%, the target volume, and the volume of half the prescription isodose. All data were analyzed by paired t-test, which is statistical method used to compare two different measurement techniques. No statistical significance in GI at 10 cases was observed between LGP and VEMT. Differences in GI ranged from -0.14 to 0.01. The newly defined gradient index calculated by two methods LGP and VEMT was not statistically significant either. Author did not find out the statistical difference for the prescribed isodose volume between LGP and VEMT. CGI as the evaluation index for determining the best treatment plan is not significant statistically also. Differences in CGI ranged from -4 to 3. Similarly newly defined Conformity/Gradient index for GKRS was also estimated as the metric for the evaluation of the treatment plans through statistical analysis. Statistical analyses demonstrated that VEMT was in excellent agreement with LGP when considering GI, new gradient index, CGI, and new CGI for evaluating the best plans of GKRS. Due to the application of the fast and easy evaluation tool through LGP and VEMT author hopes CGI and newly defined CGI as well as gradient indices will be widely used.

• Journal of KIISE:Software and Applications
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• v.30 no.9
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• pp.829-842
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• 2003

In this Paper, we propose the new face detection and tracking method based on template matching for real-time applications such as, teleconference, telecommunication, front stage of surveillance system using face recognition, and video-phone applications. Since the main purpose of paper is to track a face regardless of various environments, we use template-based face tracking method. To generate robust face templates, we apply wavelet transform to the average face image and extract three types of wavelet template from transformed low-resolution average face. However template matching is generally sensitive to the change of illumination conditions, we apply Min-max normalization with histogram equalization according to the variation of intensity. Tracking method is also applied to reduce the computation time and predict precise face candidate region. Finally, facial components are also detected and from the relative distance of two eyes, we estimate the size of facial ellipse.

• Journal of Korean Society of Forest Science
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• v.81 no.2
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• pp.156-163
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• 1992

Pinus koraiensis (Pk), P. rigida (Pr) and P. rigida ${\times}$ P. taeda (Pr. t) seedlings in a bare-rooted nursery were artificially inoculated with Pisolithus tinctorius (Pt) and Thelephora terrestris (Tt) to test long term effects of ectomycorrhizal inoculation on host growth. Mycelial inocula of Pt and Tt were mass-cultured in vermiculite-peatmoss mixture and introduced into fumigated nursery soil before seed sowing. Bare-rooted, inoculated seedlings at one to four years of age were outplanted to the field with $P_2O_5$ content of 25 ppm in soil. At the time of outplanting, Pk seedlings(4 years old), Pr seedlings(2 years old), and Pr.t seedlings(1 year old) all infected by Pt were significantly taller by 28%. 26%, and 77%, respectively, than controlled seedlings infected by natural population of mycorrhizal fungi in the non-fumigated plot. Ten years after inoculation or six to nine years after outplanting, Pk seedlings inoculated with Pt were significantly taller by 9% Pr.t seedlings significantly taller by 18%, and Pr slightly Caller by 2%(not significant) than controlled seedlings, suggesting that the stimulatory effect of Pt on host growth gradually declined or became minimal after outplanting. Tt failed to stimulate host growth either in the nursery or in the field, and the survival rate of outplanted seedlings was not different among fungal treatments. Considerable loss of the infected root system during lifting the seedlings for outplanting would be the primary cause of the reduced effect of Pt in the field. Pt infected more than 90% of the fine roots in the fumigated nursery during the first growing season, but Pt assumed to fail to compete successfully with natural population of ectomycorrhizal fungi in the field. It is necessary to select other mycorrhizal fungi which adapt well in both nursery and field.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.8 no.2
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• pp.129-139
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• 2013

This paper is targeted on proposing ameliorating alternative to performance assessment method of GSEM through evaluating the current one, which is initiated by SMBA to induce fair competition among 5 GSEM across the country and accommodate the quality improvement of entrepreneurship education since 2005 after beginning the SMBA support, from the perspective of BSC(Balanced Scorecard) tool. Ultimately, it complements the policy defects of SMBA over GSEM, in particular, in the process of performance assessment and management. This paper carries out two studies as follow. First, throughout reviewing the previous studies relating to BSC applications to non-profit organization, it set out the direction of introducing BSC in assessing performance of GSEM in order to enhance its effectiveness. Second, it evaluate the rationality of performance assessing tools apllied to GSEM by SMBA on the basis of BSC application over non-profit organization, especially in education institution. Research results shows the following implications. First, the current evaluation system over GSEM is just merely assessment itself and not much contributions for the post performance management. Second, The annual evaluation just remains to check up whether the policy goals are met or not. Third, the current evaluation puts much emphasis just on financial inputs and hardware infra, not considering human resources and utilization of government policy and institution. Fourth, the policy goals are unilaterally focused on entrepreneurs. Fifth, the current evaluation systems do not contain any indexes relating to learning and growth perspectives for concerning sustainable and independent growing up. However, lack of empirical testing require this paper to need the further study in the future.

• Korean Journal of Veterinary Research
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• v.41 no.4
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• pp.571-578
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• 2001

To evaluate if the apoptotic fragment assay could be used to estimate the dose prediction after radiation exposure, we examined apoptotic mouse crypt cells per 1,000 cells after whole body $^{60}Co$ $\gamma$-rays and 50MeV ($p{\rightarrow}Be^+$) cyclotron fast neutron irradiation in the range of 0.25 to 1 Gy, respectively. The incidence of apoptotic cell death rose steeply at very low doses up to 1 Gy, and radiation at all doses tigger rapid changes in crypt cells in stem cell region. These data suggest that apoptosis may play an important role in homeostasis of damaged radiosensitive target organ by removing damaged cells. The curve of dose-effect relationship for the data of apoptotic fragments was obtained by the linear-quadratic model $y=0.18+(9.728{\pm}0.887)D+(-4.727{\pm}1.033)D^2$ ($r^2=0.984$) after $\gamma$-rays irradiation, while $y=0.18+(5.125{\pm}0.601)D+(-2.652{\pm}0.7000)D^2$ ($r^2=0.970$) after neutrons in mice. The dose-response curves were linear-quadratic, and a significant dose-response relationship was found between the frequency of apoptotic cell and dose. These data show a trend towards increase of the numbers of apoptotic crypt cells with increasing dose. Both the time course and the radiation dose-response curve for high and low linear energy transfer (LET) radiation modalities were similar. The relative biological effectiveness (RBE) value for crypt cells was 2.072. In addition, there were significant peaks on apoptosis induction at 4 and 6h after irradiation, and the morpholoigcal findings of the irradiated groups were typical apoptotic fragments in crypt cells that were hardly observed in the control group. Thus, apoptosis in crypt cells could be a useful in vivo model for studying radio-protective drug sensitivity or screening test, microdosimetric indicator and radiation-induced target organ injury. Since the apoptotic fragment assay is simple, rapid and reproducible in the range of 0.25 to 1 Gy, it will also be a good tool for evaluating the dose response of radiation-induced organ damage in vivo and provide a potentially valuable biodosimetry for the early dose prediction after accidental exposure.

• Research in Community and Public Health Nursing
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• v.6 no.1
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• pp.55-73
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• 1995

An Effect of Muscle Strength Training Program on Muscle Strength, Muscle Endurance, Instrumental Activities of Daily Living and Quality of Life in the Institutionalized Elderly Recent statistics shows that the aged are the fastest growing segment of our population by increasing life span. The age group of over 60 shows multiple health problems and the most serious handicapping problem of these. are related to the changes in muscular skeletal system. With aging, people lose. their muscle mass and muscle strength resulting from biological changes and physical inactivity. Studies documented a 30-50% loss of muscle mass in an advanced age and thus, ordinary life activities can be seriously affected due to weakened muscle strength. Preservation of muscle strength of lower limb is especially important in the aged. Since it is readily affected from reduced physical activity in old age, sometimes to the detriment of moving or walking. So muscle strength exercise program designed for the elderly to improve leg muscle strength and leg muscle endurance. The research design used was nonequivalent control group pretest - protest design. The purposes of this study were to test the effect of muscle strength exercise program utilizing Leg Press on muscle strength, muscle endurance, instrumental activities of daily living(IADL), cognitive perceptual variables and quality of life. Forty nine subjects participating in this study consisted of twenty four male and twenty five female. Twenty four experimental group subjects were selected from C-institution in Chung Buk province, and twenty five control group subjects were selected from O-institution in Chung Nam province. The mean age of subjects was 72.8 years. Muscle strength training program utilizing Leg Press for the experimental group was carried out three times a week for 9 weeks. The data was collected from August, 1993 to October, 1993. Data were analyzed with $X^2-test$, t-test, ANCOVA test, Kruskal Wallis 1-Way ANOVA test using SPSS PC program. Results were obtained as follows : 1) The experimental group showed significantly higher scores on muscle strength (leg lift strength, back lift strength and grip strength) and muscle endurance than control group after the experiment $\ulcorner$F=52.35(p=.001), F=54.07(p=.001), F=6.97(p=.011), F=18.17(p=.001)$\lrcorner$ 2) Experimental group were significantly higher scores on IADL than control group(F=7.51, p=.009). 3) Experimental group showed significantly higher scores on economical state and self esteem aspects of the quality of life scale than control group $\ulcorner$F=10.59(p=.002), F=6.97(p=.011)$\lrcorner$. But there were no differences in emotional state, physical and functional state and relationship with reatives in the quality of life between groups. 4) Scores on IADL showed a significant difference with the level of muscle strength and muscle endurance $\ulcornerx^2=7.73(p=.025),\;x^2=8.86\;(p=.011)\lrcorner$ 5) Scores on self esteem and physical and functional state aspects of the quality of life scale showed a significant difference with the level of IADL $\ulcornerx^2=11.39(p=.003),\;x^2=9.02(p=.011)\lrcorner$. 6) Scores of experimental group after the experiment in cognitive perceptual variables (perceived benefit on exercise, perceived health status, self efficacy, emotion on exercise) were significantly higher than those of control group $\ulcorner$F=32.09(p=.001), F=5.07(p=.029), F=20.63 (p=.001), F=30.38(p=.001)$\lrcorner$. As a result of this study, the effect of strength training exercise program with Leg. Press had improved muscle strength, muscle endurance, IADL, and the perception of self esteem, physical and funtional state, and economical state. Thus strength training program could be beneficially applied for the prevention of disablity and promotion of health and wellbeing in the aged easily and safely. The subjects in the experimental group have maintained their exercises till six months after the cessation of the experiment. This seem to illustrate that changes in cognitive perceptual variables and the improvement in health status have reinforced motivation for the continuation of voluntary exercises. A further study is necessary to determine the factors affecting maintainance of muscle strength exercise and to assess the effect of weight training program on bone density.

• Journal of the Korean Institute of Landscape Architecture
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• v.46 no.5
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• pp.44-58
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• 2018

Cities face new challenges not only in natural disasters by climate change but also in social and economic fluctuations. With the existing simple reconstruction method, it is difficult to solve the overall problems that a city or region may face. As a new approach to cope with various changes, the concept of resilience is emerging. Resilience is also one of the themes of recent major urban design projects. Design with the concept of resilience is a new strategy that can deal with various changes of urban space, rather than a temporary trend. The purpose of this paper is to explore the design method by analyzing cases where the concept of resilience is employed. We aim to examine what kind of design strategies are needed for the resilience design and how this design process differ in character, as compared to general design projects. Cases for this study include the "Rebuild by Design" competition held in 2013 and the "Resilient by Design/Bay Area Challenge" competition held in 2017. This paper consists of literature reviews and case studies. The latter is divided into two aspects: content analysis based on the theory of resilience and characteristics of the design process. Cases are analyzed through literature reviews and process characteristics of resilience design in response to the general design process. The main categories for urban resilience used as the framework for analysis include: Urban Infrastructure, Social Dynamics, Economic Dynamics, Health and Wellbeing, Governance Networks, and Planning and Institutions. As a result, the aspects of resilience concepts considered and design strategies undertaken by each team were identified. Each team tried to connect all 6 categories to their design strategies, placing special value on the role of governance, a system that enables collaborative design and project persistency. In terms of the design process, the following characteristics were found: planning the whole project process in the pre-project phase, analyzing predictable socioeconomic risk factors in addition to physical vulnerabilities, aiming for landscape-oriented integrated design, and sustainable implementation strategies with specific operations and budget plans. This paper is meaningful to connect the concept of resilience, which has been discussed in various articles, to design strategy, and to explore the possibility of constructing a practical methodology by deriving the characteristics of the resilience design process. It remains a future task to research design strategies that apply the concept of resilience to various types of urban spaces, in addition to areas that are vulnerable to disasters.