• Therapeutic Science for Rehabilitation
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• v.13 no.1
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• pp.9-21
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• 2024

Objective : The purpose of this study was to confirm the characteristics and quality of a single-subject research that conducted interventions to improve activities of daily living (ADL) in stroke patients. Methods : 'Stroke,' 'activities of daily living,' and 'single-subject studies' were searched as keywords among papers published in the last 15 years between 2009 and 2023 among Research Information Sharing Service, DBpia, and e-articles. A total of nine papers were examined for the characteristics and quality before analysis. Results : The independent variables applied to improve ADL included constraint-induced therapy, mental practice for performing functional activities, virtual reality-based task training, subjective postural vertical training without visual feedback, bilateral upper limb movement, core stability training program, traditional occupational therapy and neurocognitive rehabilitation, smooth pursuit eye movement, neck muscle vibration, and occupation-based community rehabilitation. Assessment of Motor and Process Skills was the most common evaluation tool for measuring dependent variables, with four articles, and Modified Barthel Index and Canadian Occupational Performance Measure were two articles each. As a result of confirming the qualitative level of the analyzed papers, out of a total of nine studies, seven studies were at a high level, two at a moderate level, and none were at a low level. Conclusion : Various types of rehabilitation treatments have been actively applied as intervention methods to improve the daily life activities of stroke patients; the quality level of single-subject studies applying ADL interventions was reliable.

• Strategy21
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• s.46
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• pp.239-276
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• 2020

The failure of early economic sanctions aimed at hurting the overall economies of targeted states called for a more sophisticated design of economic sanctions. This paved way for the advent of 'smart sanctions,' which target the supporters of the regime instead of the public mass. Despite controversies over the effectiveness of economic sanctions as a coercive tool to change the behavior of a targeted state, the transformation from 'comprehensive sanctions' to 'smart sanctions' is gaining the status of a legitimate method to impose punishment on states that do not conform to international norms, the nonproliferation of weapons of mass destruction in this particular context of the paper. The five permanent members of the United Nations Security Council proved that it can come to an accord on imposing economic sanctions over adopting resolutions on waging military war with targeted states. The North Korean nuclear issue has been the biggest security threat to countries in the region, even for China out of fear that further developments of nuclear weapons in North Korea might lead to a 'domino-effect,' leading to nuclear proliferation in the Northeast Asia region. Economic sanctions had been adopted by the UNSC as early as 2006 after the first North Korean nuclear test and has continually strengthened sanctions measures at each stage of North Korean weapons development. While dubious of the effectiveness of early sanctions on North Korea, recent sanctions that limit North Korea's exports of coal and imports of oil seem to have an impact on the regime, inducing Kim Jong-un to commit to peaceful talks since 2018. The purpose of this paper is to add a variable to the factors determining the success of economic sanctions on North Korea: preventing North Korea's evasion efforts by conducting illegal transshipments at sea. I first analyze the cause of recent success in the economic sanctions that led Kim Jong-un to engage in talks and add the maritime element to the argument. There are three conditions for the success of the sanctions regime, and they are: (1) smart sanctions, targeting commodities and support groups (elites) vital to regime survival., (2) China's faithful participation in the sanctions regime, and finally, (3) preventing North Korea's maritime evasion efforts.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.123-139
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• 2019

The job classification system of major job sites differs from site to site and is different from the job classification system of the 'SQF(Sectoral Qualifications Framework)' proposed by the SW field. Therefore, a new job classification system is needed for SW companies, SW job seekers, and job sites to understand. The purpose of this study is to establish a standard job classification system that reflects market demand by analyzing SQF based on job offer information of major job sites and the NCS(National Competency Standards). For this purpose, the association analysis between occupations of major job sites is conducted and the association rule between SQF and occupation is conducted to derive the association rule between occupations. Using this association rule, we proposed an intelligent job classification system based on data mapping the job classification system of major job sites and SQF and job classification system. First, major job sites are selected to obtain information on the job classification system of the SW market. Then We identify ways to collect job information from each site and collect data through open API. Focusing on the relationship between the data, filtering only the job information posted on each job site at the same time, other job information is deleted. Next, we will map the job classification system between job sites using the association rules derived from the association analysis. We will complete the mapping between these market segments, discuss with the experts, further map the SQF, and finally propose a new job classification system. As a result, more than 30,000 job listings were collected in XML format using open API in 'WORKNET,' 'JOBKOREA,' and 'saramin', which are the main job sites in Korea. After filtering out about 900 job postings simultaneously posted on multiple job sites, 800 association rules were derived by applying the Apriori algorithm, which is a frequent pattern mining. Based on 800 related rules, the job classification system of WORKNET, JOBKOREA, and saramin and the SQF job classification system were mapped and classified into 1st and 4th stages. In the new job taxonomy, the first primary class, IT consulting, computer system, network, and security related job system, consisted of three secondary classifications, five tertiary classifications, and five fourth classifications. The second primary classification, the database and the job system related to system operation, consisted of three secondary classifications, three tertiary classifications, and four fourth classifications. The third primary category, Web Planning, Web Programming, Web Design, and Game, was composed of four secondary classifications, nine tertiary classifications, and two fourth classifications. The last primary classification, job systems related to ICT management, computer and communication engineering technology, consisted of three secondary classifications and six tertiary classifications. In particular, the new job classification system has a relatively flexible stage of classification, unlike other existing classification systems. WORKNET divides jobs into third categories, JOBKOREA divides jobs into second categories, and the subdivided jobs into keywords. saramin divided the job into the second classification, and the subdivided the job into keyword form. The newly proposed standard job classification system accepts some keyword-based jobs, and treats some product names as jobs. In the classification system, not only are jobs suspended in the second classification, but there are also jobs that are subdivided into the fourth classification. This reflected the idea that not all jobs could be broken down into the same steps. We also proposed a combination of rules and experts' opinions from market data collected and conducted associative analysis. Therefore, the newly proposed job classification system can be regarded as a data-based intelligent job classification system that reflects the market demand, unlike the existing job classification system. This study is meaningful in that it suggests a new job classification system that reflects market demand by attempting mapping between occupations based on data through the association analysis between occupations rather than intuition of some experts. However, this study has a limitation in that it cannot fully reflect the market demand that changes over time because the data collection point is temporary. As market demands change over time, including seasonal factors and major corporate public recruitment timings, continuous data monitoring and repeated experiments are needed to achieve more accurate matching. The results of this study can be used to suggest the direction of improvement of SQF in the SW industry in the future, and it is expected to be transferred to other industries with the experience of success in the SW industry.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.105-129
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• 2020

This study uses corporate data from 2012 to 2018 when K-IFRS was applied in earnest to predict default risks. The data used in the analysis totaled 10,545 rows, consisting of 160 columns including 38 in the statement of financial position, 26 in the statement of comprehensive income, 11 in the statement of cash flows, and 76 in the index of financial ratios. Unlike most previous prior studies used the default event as the basis for learning about default risk, this study calculated default risk using the market capitalization and stock price volatility of each company based on the Merton model. Through this, it was able to solve the problem of data imbalance due to the scarcity of default events, which had been pointed out as the limitation of the existing methodology, and the problem of reflecting the difference in default risk that exists within ordinary companies. Because learning was conducted only by using corporate information available to unlisted companies, default risks of unlisted companies without stock price information can be appropriately derived. Through this, it can provide stable default risk assessment services to unlisted companies that are difficult to determine proper default risk with traditional credit rating models such as small and medium-sized companies and startups. Although there has been an active study of predicting corporate default risks using machine learning recently, model bias issues exist because most studies are making predictions based on a single model. Stable and reliable valuation methodology is required for the calculation of default risk, given that the entity's default risk information is very widely utilized in the market and the sensitivity to the difference in default risk is high. Also, Strict standards are also required for methods of calculation. The credit rating method stipulated by the Financial Services Commission in the Financial Investment Regulations calls for the preparation of evaluation methods, including verification of the adequacy of evaluation methods, in consideration of past statistical data and experiences on credit ratings and changes in future market conditions. This study allowed the reduction of individual models' bias by utilizing stacking ensemble techniques that synthesize various machine learning models. This allows us to capture complex nonlinear relationships between default risk and various corporate information and maximize the advantages of machine learning-based default risk prediction models that take less time to calculate. To calculate forecasts by sub model to be used as input data for the Stacking Ensemble model, training data were divided into seven pieces, and sub-models were trained in a divided set to produce forecasts. To compare the predictive power of the Stacking Ensemble model, Random Forest, MLP, and CNN models were trained with full training data, then the predictive power of each model was verified on the test set. The analysis showed that the Stacking Ensemble model exceeded the predictive power of the Random Forest model, which had the best performance on a single model. Next, to check for statistically significant differences between the Stacking Ensemble model and the forecasts for each individual model, the Pair between the Stacking Ensemble model and each individual model was constructed. Because the results of the Shapiro-wilk normality test also showed that all Pair did not follow normality, Using the nonparametric method wilcoxon rank sum test, we checked whether the two model forecasts that make up the Pair showed statistically significant differences. The analysis showed that the forecasts of the Staging Ensemble model showed statistically significant differences from those of the MLP model and CNN model. In addition, this study can provide a methodology that allows existing credit rating agencies to apply machine learning-based bankruptcy risk prediction methodologies, given that traditional credit rating models can also be reflected as sub-models to calculate the final default probability. Also, the Stacking Ensemble techniques proposed in this study can help design to meet the requirements of the Financial Investment Business Regulations through the combination of various sub-models. We hope that this research will be used as a resource to increase practical use by overcoming and improving the limitations of existing machine learning-based models.

• Korean Journal of Heritage: History & Science
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• v.45 no.4
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• pp.140-157
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• 2012

The result of a study on the useful trend of plants related to landscape and how to plant and cultivate through 'ImwonGyeongjaeji Manhakji'of Seoyugu is as follows: First, 'ImwonGyeongjaiji Manhakji', composed of total 5 volumes (General, Fruit trees, vegetables and creeper, plants, others) is a representative literature related to landscape which described the names of plants and varieties, soil condition, how to plant and cultivate, graft, how to prevent the insect attack etc systematically. Second, he recorded the tree planting as Jongjae(種栽) or Jaesik(栽植), and the period to plant the trees as Jaesusihoo(栽樹時候), transplanting as Yijae(移栽), making the fence as Jakwonri(作園籬), the names of varietieis as Myeongpoom(名品), the suitable soil as Toeui(土宜), planting and cultivation as Jongye(種藝), treatment as Euichi(醫治), protection and breeding as Hoyang(護養), garden as Jeongwon(庭園) or Wonpo(園圃), garden manager as Poja(圃者) or Wonjeong(園丁). Third, the appearance frequency of plants was analyzed in the order of flowers, fruits, trees, and creepers and it showed that the gravity of deciduous trees was 3.7 times higher than that of evergreen trees. The preference of flower and trees, fruit trees and deciduous trees and broad-leaved trees includes (1) application of the species of naturally growing trees which are harmonized with the natural environment (2) Aesthetic value which enables to enjoy the beauty of season, (3) the trend of public welfare to take the flowers and fruits, (4) the use of symbolic elements based on the value reference of Neo-Confucianism etc. Fourth, he suggested the optimal planting period as January(上時) and emphasized to transplant by adding lots of fertile soil and cover up the seeds with soil as high as they are buried in accordance with the growing direction and protect them with a support. That is, considering the fact that he described the optimal planting period as January by lunar calendar, this suggests the hints in judging the planting period today. For planting the seeds, he recommended the depth with 1 chi(寸 : approx. 3.3cm), and for planting a cutting, he recommended to plant the finger-thick branch with depth 5 chi(approx. 16.5cm) between January and February. In case of graft of fruit trees, he described that if used the branch stretched to the south, you would get a lot of fruit and if cut the branches in January, the fruits would be appetizing and bigger. Fifth, the hedge(fence tree) is made by seeding the Jujube tree(Zizyphus jujuba var. inermis) in autumn densely and transplanting the jujube tree with 1 ja(尺 : approx. 30cm) interval in a row in next autumn and then binding them with the height of 7 ja(approx. 210cm) in the spring of next year. If planted by mixing a Elm tree(Ulmus davidiana var. japonica) and a Willow(Salix koreensis), the hedge whose branch and leaves are unique and beautiful like a grating can be made. For the hedge(fence tree), he recommended Trifoliolate orange(Poncitus trifoliata), Rose of sharon(Hibiscus syriacus), Willow(Salix koreensis), Spindle tree(Euonymus japonica), Cherry tree(Prunus tomentosa), Acanthopanax tree(Acanthopanax sessiliflorus), Japanese apricot tree(Prunus mume), Chinese wolf berry(Lycium chinense), Cornelian tree(Cornus officinalis), Gardenia(Gardenia jasminoides for. Grandiflora), Mulberry(Morus alba), Wild rosebush(Rosa multiflora) etc.

• Asia Marketing Journal
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• v.13 no.2
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• pp.99-130
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• 2011

In recent years, a new way of differentiating product design has emerged -better known as 'masterpiece marketing,' this is a strategy where famous art pieces are borrowed on to product designs. Because the recent trends of well-being and LOHAS have encouraged the consumers' desires to enjoy culture and live a more opulent lifestyle, famous and notable paintings have grown to be more of "approachable masterpieces" to the public. As a strategy intended to develop a new consumerism, while still prioritizing customers' values and their satisfaction, companies have been drawn to this new type of marketing. The current consumption society has converted renowned art pieces from simply works of 'high culture' to a further way of marketing, aimed to differentiate products and dominate the market. Though many products have had masterpieces applied to their designs and have been noticed for their marketability, there has been less systematic research done on the scientific background behind this marketing approach. This research focused on the art pieces' fundamental nature of inducing emotions in the viewer, and hypothesized about how the evaluation of a product may be influenced by the affect provoked by the art piece used. To be more specific, if art pieces with different levels of pleasure and arousal -the two axis of emotion suggested by existing research on emotion -were used on each product, the goal was to see how the different levels influenced the consumer's assessment of the products, focusing on product's type as well as the evaluation of their attributes. First, a pretest was done to verify the relationship between the emotion provoked by the art piece and the consumer's preference. There were two types of surveys, each with five drawings from the ten that were assumed to differ in levels of the two axis of emotion. The survey was composed of questions asking for positive emotion, negative emotion, level of arousal, and preference. The correlation between the measurements of positive and negative emotions was -0.792, so an integrated entry was used in the analysis by subtracting the measurement of negative emotions from that of positive emotions. The first hypothesis that paintings that provoke positive emotions will be more preferred than paintings that bring out negative emotions was supported; and through this research, paintings that were to be used for the products were selected. The second pretest was conducted to settle on an item that would be used in the research. Items meant to measure utilitarian and hedonic attributes of milk and chocolate, the two products to be used in the research, were extracted. Because milk is a utilitarian product with strong practical attributes while chocolate is a hedonic product with strong hedonic attributes, these two were selected to be used in this research. The first study was executed to see if there is a difference in attitude about products that have different painting on their designs, which either induces positive or negative emotions. It was also to verify whether this difference in attitude was mediated by the viewer's preference for the art piece. This study showed that when positive emotion inducing painting was used, the product was better evaluated compared to the product with a painting that provokes a negative emotion, thus supporting the second hypothesis. It was also supported that the effect of affect on product evaluation was mediated by preference for the art piece. The second study was done to see the influence of the level of arousal on the evaluation of the product's attributes. Art pieces that differ in the level of arousal were selected through the pretest, and later it verified the hypothesis that the level of arousal has an effect on the assessment of the attributes of the product. In the case of milk, a utilitarian product, the fourth hypothesis that a high-arousal painting will better evaluated for its hedonic attributes was supported, as well as the fifth, which hypothesized that a low-arousal painting will receive a higher assessment for its utilitarian attributes. However, for chocolate, a hedonic product, both fourth and fifth hypotheses were not supported. This study is significant for the following basis: first, it verified the importance of the emotion induced by the painting on the evaluation of the product's attributes, by applying a systematic and scientific method. Second, it expanded from the existing research on positive/negative emotions to confirm the additional influence of the state of arousal on product evaluation.