• Korean Journal of Construction Engineering and Management
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• v.19 no.4
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• pp.93-101
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• 2018

A city is like a living organism that is born, grows and become extinct within an ecosystem. In recent years, more and more cities have been planned by designers rather than spontaneously growing over time. This planning means that if a city is not appropriately designed at the beginning, it is very hard to fix or adjust it later. A poor urban design inconveniences many people, and forces them to adjust to it. For this reason, it is important to design a city as optimally as possible at the design phase. One of the reasons why a city is not designed optimally is complexity. Previous urban design methods have attempted to resolve the complexity by using a top-down problem-solving method based on the experience and knowledge of the urban planner. However, such an approach does not have the organic characteristics of a bottom-up problem-solving method of an artificial life, based on the creation principle of the ecosystem. Therefore, in this study the general principle of artificial life, which can provide a solution to the bigger problems that accumulate as a result of the solutions to small units of problems, is adopted. This enables us to draw various urban design alternatives, and it proves that the alternatives, despite being drawn through a limited modeling method, have almost no differences from those designed by an expert, and its possibilities of future development has also been verified.

• 한국노년학
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• v.37 no.3
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• pp.549-565
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• 2017

A high-quality workforce is essential to delivering the high-quality care for the older people who are beneficiaries of long term care insurance. Providing adequate education and ongoing training opportunities could be one answer that may lead to the ultimate goal of improving the quality of long-term care services. Thus this study aimed to examine a workforce crisis and difficulties that care workers face in current education system, especially in contents and administration aspects and draw out suitable solutions or improvement measures. The focus group interview approach was chosen to reflect opinions of long-term care workers, directors of the education system in long-term care facilities and managers. The findings from the focus group interviews were analyzed by theme and classified into several categories by common subjects:'Training contents', 'Training environment', 'Administrator', 'Compulsory training', 'Care givers supply', 'Working condition'. Also, four content areas were presented as follows:'Job training', 'Dementia care training', 'Administration system', 'Workforce'. The caregivers demand very practical training programmes and trainers with a lot of field experience. Improving the working condition and treatments for them leeds to expand the opportunity of the on-going training.

• SUVANNABHUMI
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• v.10 no.2
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• pp.181-213
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• 2018

How to study Southeast Asia (SEA)? The need to explore and identify methodologies for studying SEA are inherent in its multifaceted subject matter. At a minimum, the region's rich cultural diversity inhibits both the articulation of decisive defining characteristics and the training of scholars who can write with confidence beyond their specialisms. Consequently, the challenges of understanding the region remain and a consensus regarding the most effective approaches to studying its history, identity and future seem quite unlikely. Furthermore, "Area Studies" more generally, has proved to be a less attractive frame of reference for burgeoning scholarly trends. This paper will propose a new tool to help address these challenges. Even though the science of artificial intelligence (AI) is in its infancy, it has already yielded new approaches to many commercial, scientific and humanistic questions. At this point, AI has been used to produce news, generate better smart phones, deliver more entertainment choices, analyze earthquakes and write fiction. The time has come to explore the possibility that AI can be put at the service of the study of SEA. The paper intends to lay out what would be required to develop SEABOT. This instrument might exist as a robot on the web which might be called upon to make the study of SEA both broader and more comprehensive. The discussion will explore the financial resources, ownership and timeline needed to make SEABOT go from an idea to a reality. SEABOT would draw upon artificial neural networks (ANNs) to mine the region's "Big Data", while synthesizing the information to form new and useful perspectives on SEA. Overcoming significant language issues, applying multidisciplinary methods and drawing upon new yields of information should produce new questions and ways to conceptualize SEA. SEABOT could lead to findings which might not otherwise be achieved. SEABOT's work might well produce outcomes which could open up solutions to immediate regional problems, provide ASEAN planners with new resources and make it possible to eventually define and capitalize on SEA's "soft power". That is, new findings should provide the basis for ASEAN diplomats and policy-makers to develop new modalities of cultural diplomacy and improved governance. Last, SEABOT might also open up avenues to tell the SEA story in new distinctive ways. SEABOT is seen as a heuristic device to explore the results which this instrument might yield. More important the discussion will also raise the possibility that an AI-driven perspective on SEA may prove to be even more problematic than it is beneficial.

• Journal of Trauma and Injury
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• v.23 no.2
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• pp.68-74
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• 2010

Purpose: The purpose of this study is, first, to analyze the risk factors that influence the severity of injury in pediatric multiple trauma patients and, second, to present solutions for the problems related to the treatment of such patients. Our living situations are so complicated that the danger of accidents is truly open to children who are not prepared. We need to draw attention to the increased numbers of various accidents involving children. Methods: We studied patients who visited the Emergency Medical Center at Chosun University Hospital from January 1, 2006, to December 31, 2008. Using medical records, we evaluated the general characteristics: the mechanism of injury, the vital signs, the revised trauma score (RTS), the injury severity score (ISS), and the hemoglibin value, which was checked at the time of visit, and the presence or the absence of emergent on regular surgery. We divided the level of injury as follows: light level (1-8 points), mid level (9-15 points), and serious level (above 16 points). We analyzed the medical data by using SPSS 17.0 for windows. Results: The average age of the patients examined was 8.6 years. The number of 6- to 11-year-old patients was 96, which was the largest, but the degree of injury severity was the highest among infant (0-2 years), according to ISS 7.95(${\pm}6.85$). The frequency of accidents was highest on sunny days, and most accidents occurred from 16:00 to 20:00. The cause of multiple trauma for children was the greatest in the traffic accident, (95 patients, 49.0%). In addition, the trauma caused by traffic accidents showed the highest ISS value ($9.02{\pm}6.42$) and the most serious degree (P=0.004). The ISS level of injury ($8.40{\pm}6.64$) for patients moved from a secondary hospital was higher than that ($6.49{\pm}5.57$) for patients who visited the medical center directly. The severity of injury was highest for patients who used a 119 ambulance ($8.84{\pm}5.80$). According to the injured parts of body, Injuries to the arms and the feet most frequent (79 patients, 40.7%), but the level of injury was the highest for internal organs and chest, $16.42{\pm}8.56$ and $11.23{\pm}6.97$, respectively. Conclusion: We used Abbreviated Injury Scale (AIS) in order to examine the characteristics by injured body part for pediatric multiple trauma patients. Because the degree of injury was the highest for internal organs or the chest, we need to more seriously examine and provide for patients who are suspected of having injuries to the internal organs or the chest. We need to quickly determine the need for surgery in patients with serious injuries to the arms and the feet, which is the greatest in frequency. In particular, we need to consider the surgical care of patients who are not very high in the severity of injury to their brains.

• The Journal of Korean Philosophical History
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• no.39
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• pp.29-52
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• 2013

Philosophy of respect righteousness advocated by Nammyung points to what first needs to be done to drive social changes. It is consistent with the Confucianism, which views the world from within oneself. After all, developing a proper view of the society starts from looking at oneself in the right perspective. The view that personal cultivation can develop into cultivation and eventually reform of the entire society is also present in Confucius' belief that one can only be at peace after disciplining oneself and observe good manners only after perseverance. Also, one can lead the world in peace only after disciplining one's body and mind. In other words, it suggests that individuals and the community where they belong to are not independent from one another. Rather, individuals gather to create a society and righteous individuals are the basis for righteous society. These principles of social system in Confucianism can be understood as a mutual or layered division and integration. The society is not conflicted with individuals or the nation but rather perceived as moral communities to co-exist. Hence, power of execution observed in the philosophy of respect and righteousness by Nammyung is identical to power of execution applied to the society. The power of execution shows up as 'the execution of righteousness' in Nammyung's philosophy of respect and righteousness. It is also demonstrated in the acts by Nammyung's disciples when the nation was at crisis. This is what differentiates Nammyung's new-Confucianism in Joseon Dynasty from Toegye or Yulgok as he tried to deliver 'the execution of righteousness.' It does not mean that neo-Confucian scholars did not emphasize the importance of execution, but Nammyung, in particular, warned how deceitful ideological or inner-directed thinking can be since they fail to come up with concrete solutions to social issues. In summary, Nammyung's moral discipline and training based on respect and righteousness cannot be evaluated in a state of vacuum separate from social and historical aspects but under the context of enlightening virtue and social execution. This can draw the conclusion that Nammyung's execution of respect and righteousness is in the starting point of the realistic 'theory of social reform' for creating a better world.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.39-55
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• 2019

Recently banks and large financial institutions have introduced lots of Robo-Advisor products. Robo-Advisor is a Robot to produce the optimal asset allocation portfolio for investors by using the financial engineering algorithms without any human intervention. Since the first introduction in Wall Street in 2008, the market size has grown to 60 billion dollars and is expected to expand to 2,000 billion dollars by 2020. Since Robo-Advisor algorithms suggest asset allocation output to investors, mathematical or statistical asset allocation strategies are applied. Mean variance optimization model developed by Markowitz is the typical asset allocation model. The model is a simple but quite intuitive portfolio strategy. For example, assets are allocated in order to minimize the risk on the portfolio while maximizing the expected return on the portfolio using optimization techniques. Despite its theoretical background, both academics and practitioners find that the standard mean variance optimization portfolio is very sensitive to the expected returns calculated by past price data. Corner solutions are often found to be allocated only to a few assets. The Black-Litterman Optimization model overcomes these problems by choosing a neutral Capital Asset Pricing Model equilibrium point. Implied equilibrium returns of each asset are derived from equilibrium market portfolio through reverse optimization. The Black-Litterman model uses a Bayesian approach to combine the subjective views on the price forecast of one or more assets with implied equilibrium returns, resulting a new estimates of risk and expected returns. These new estimates can produce optimal portfolio by the well-known Markowitz mean-variance optimization algorithm. If the investor does not have any views on his asset classes, the Black-Litterman optimization model produce the same portfolio as the market portfolio. What if the subjective views are incorrect? A survey on reports of stocks performance recommended by securities analysts show very poor results. Therefore the incorrect views combined with implied equilibrium returns may produce very poor portfolio output to the Black-Litterman model users. This paper suggests an objective investor views model based on Support Vector Machines(SVM), which have showed good performance results in stock price forecasting. SVM is a discriminative classifier defined by a separating hyper plane. The linear, radial basis and polynomial kernel functions are used to learn the hyper planes. Input variables for the SVM are returns, standard deviations, Stochastics %K and price parity degree for each asset class. SVM output returns expected stock price movements and their probabilities, which are used as input variables in the intelligent views model. The stock price movements are categorized by three phases; down, neutral and up. The expected stock returns make P matrix and their probability results are used in Q matrix. Implied equilibrium returns vector is combined with the intelligent views matrix, resulting the Black-Litterman optimal portfolio. For comparisons, Markowitz mean-variance optimization model and risk parity model are used. The value weighted market portfolio and equal weighted market portfolio are used as benchmark indexes. We collect the 8 KOSPI 200 sector indexes from January 2008 to December 2018 including 132 monthly index values. Training period is from 2008 to 2015 and testing period is from 2016 to 2018. Our suggested intelligent view model combined with implied equilibrium returns produced the optimal Black-Litterman portfolio. The out of sample period portfolio showed better performance compared with the well-known Markowitz mean-variance optimization portfolio, risk parity portfolio and market portfolio. The total return from 3 year-period Black-Litterman portfolio records 6.4%, which is the highest value. The maximum draw down is -20.8%, which is also the lowest value. Sharpe Ratio shows the highest value, 0.17. It measures the return to risk ratio. Overall, our suggested view model shows the possibility of replacing subjective analysts's views with objective view model for practitioners to apply the Robo-Advisor asset allocation algorithms in the real trading fields.