• Korea Trade Review
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• v.42 no.4
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• pp.69-91
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• 2017

Since the global financial crisis, major countries have been executing policies related to two top-priority goals to create more jobs: revitalization of entrepreneur activity and the cultivation of small and medium-sized companies. In South Korea, the interest of policy makers is increasingly focusing on the role of SMEs that have a technological competitive edge in the realization of a "job-centered creative economy." Due to the nature of the field, the health and medical industry requires a particularly long time until the achievement of industrialization, Also, because of the complex distribution structure, it is essential for related government ministries and institutions to jointly devise strategies. A lack of policy supports for the industry has thus far resulted in its development being relegated for the most part of small and medium-sized companies, which consequently means low global competitiveness. Now is the time for the South Korean government to provide the revolutionary supported options and strategies. This study aims to propose a general policy direction and policy areas for the cultivation of Korea's small and medium-sized companies in the healthcare industry into global small giant companies through an exploration of the German case. It is crucial to first cultivate the international competitiveness of Korean small and medium-sized companies (as in the case of Germany) so that they can grow into global small giant companies. Another important task is the creation of an environment that expedites the qualitative growth of promising SMEs as well as technological development. After securing competitiveness in terms of both product quality and technology in the global health market, substantive policy supports will be necessary to cultivate global small giant companies that are export-based (e.g. job creation effect, sales value added).

• Korean Journal of Culture and Social Issue
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• v.14 no.1_spc
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• pp.319-348
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• 2008

Self-efficacy, achievement goals, task value, and attribution are some of the representative motivation constructs that explain adolescents' cognition, affect, and behavioral patterns in achievement settings. These constructs have won researchers' recognition by demonstrating explanatory and predictive utility that transcends various social and cultural milieus learners are exposed to. Korean adolescents' motivation is generally in line with this universal trend and can be described adequately with these constructs. Nonetheless, there also exist a host of indigenous factors that shape these motivation constructs to be uniquely Korean. The purpose of the present article was to explore some of the socio-cultural factors that appear to wield particularly determining effects on Korean adolescents' academic motivation. Review of the relevant literature identified interdependent self-construal, traditional morals of filial piety, familism, educational fervor, academic elitism, and the college entrance system as important cultural, social, and policy-related such factors. Also discussed in this article were the roles of these factors in creating more immediate psychological learning environments for Korean adolescents, such as parent-child relationships, teacher-student relationships, and classroom goal structures.

• Korean Journal of Culture and Social Issue
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• v.16 no.2
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• pp.103-124
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• 2010

The purpose of the present study was to examine the relationships among private tutoring hours, academic motivation, use of learning strategies, and academic achievement test scores using structural equation modeling. The sample consisted of 3,607 7th graders from Korean middle schools who were included in the Korean Education Longitudinal Study. The results suggest that there was no evidence that the private tutoring hours predicted students' motivation and learning strategy use. It was found that the private tutoring hours predicted achievements in English and Math, but it was negligible in magnitude. As for achievement test scores, academic motivation and the use of learning strategies played more critical role rather than the private tutoring hours.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.6
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• pp.381-389
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• 2023

One of the crucial components in building information modeling (BIM) is data. To systematically manage these data, various research studies have focused on the creation of object breakdown structures and property sets. Specifically, crucial data for managing programs and payments involves work breakdown structures (WBSs) and cost breakdown structures (CBSs), which are indispensable for mapping BIM objects. Achieving this requires disassembling CBS quantities based on 3D objects and WBS. However, this task is highly tedious owing to the large volume of CBS and divergent coding practices employed by different organizations. Manual processes, such as those based on Excel, become nearly impossible for such extensive tasks. In response to the challenge of computing quantities that are difficult to derive from BIM objects, this study presents methods for disassembling length-based quantities, incorporating significant portions of the bill of quantities (BOQs). The proposed approach recommends suitable CBS by leveraging the accumulated history of WBS-CBS mapping databases. Additionally, it establishes a unified CBS code, facilitating the effective operation of CBS databases.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.2
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• pp.81-97
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• 2022

This paper's purpose is to get hold of the recent research trend by analyzing the variables uesd in startups related papers. The startups related papers in this paper are the papers which include 'startups' in the title of the registered papers from the year 2013 to the year 2020. This study's analysis methods are text-mining of all variables and text-network analysis of affected variables. Visualizing tool for network analysis is Gephi. The result of variables' analysis is as follows. First, independent variables consist mainly of variables about startups' internal factors and outside environment, but due to startups' features like early stage company's features, innovative features, most of variables are about enterprise internal competitiveness, marketing 4P strategy, entrepreneurship, coopreation method, transformational leadership, enterprise features, lean startup strategy, enterprise internal communication, value orientation, task conflict, relationship conflict, knowledge sharing, etc. Second, dependent variables are mainly about outcome, and are classified into financial performance and non-financial performance by overall concept. In other words, startups related papers have higher interest in non-financial performance, like management performance, team performance, SCM performance as well as financial performance like sales quantity owing to startups' immaturity in getting good financial performance. Through this study we can find out as follows. Although there are not many officially registered papers dealing with startups, those papers include various themes about stratups. For example, there are trendy themes like lean startups strategy, crowdfunding, influencer and accelerator, etc.

• Quality Improvement in Health Care
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• v.30 no.1
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• pp.33-43
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• 2024

Purpose:The acute hospital accreditation program launched in South Korea has shown positive effects on safety culture and quality of care. However, relative weights have not yet been investigated for accreditation criteria with a hierarchical structure. This study aimed to derive the relative weights of acute-care hospital accreditation criteria. Methods: We conducted an online survey using the analytic hierarchy process (AHP) technique to assess the validity, importance, and urgency of acute hospital accreditation criteria. The AHP online survey link was distributed in November 2022 after obtaining informed consent from 10 experts in hospital accreditation. Results: 'Basic value system' ranked highest, while 'patient care system' ranked second in terms of validity, importance, and urgency. 'Performance management system' had the lowest validity and urgency, while 'organizational management system' carried the lowest importance. Within the 'patient care system' domain, 'surgery and anesthesia sedation management' scored highest in validity and importance, and 'patient care' scored highest in urgency. 'Care delivery system and evaluation' received the lowest scores for all three aspects. In the 'organizational management system' domain, infection control ranked highest in terms of validity, importance, and urgency. The lowest validity was observed for 'management and organizational operation' and the lowest importance and urgency were noted for 'human resource management'. Conclusion: The weights for validity, importance, and urgency, as shown in each domain and chapter, and the number of measurable elements included, are largely inconsistent. This study will contribute to the development of the structure and scientific improvement of accreditation standards.

• The Mathematical Education
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• v.63 no.3
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• pp.393-409
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• 2024

The number line model, which intuitively marks numerical magnitudes in space, is widely utilized to help in understanding the magnitudes that fractions and decimals represent. The study analyzed 6^th graders' understanding of fractions and decimals, their problem solving strategies, and whether individual differences in the flexibility of various strategy uses are associated with the accuracy of numerical representation, calculation fluency, and overall mathematical achievement. As a result of the study, students showed relatively lower accuracy in representing fractions and decimals on a number line compared to natural numbers, especially for fractions with odd denominators compared to even denominators, and for two-digit decimals compared to three-digit decimals. Regarding strategy use, students primarily used benchmark, segmentation, and approximation strategies for fractions, and benchmark, rounding, and transformation strategies for decimals sequentially. Lastly, as students used various representation strategies for fractions, their accuracy in representing fractions and their overall mathematical achievement scores showed significantly better outcomes. Taken together, we suggest the need for careful instruction on different interpretations of fractions, the place value of decimals, and the meaning of zero in decimal places. Moreover, we discuss instructional methods that integrate the number line model and its diverse representation strategies to enhance students' understanding of fractions and decimals.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.6D
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• pp.771-778
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• 2011

Preliminary feasibility study on Busan metro line #1 in Yangsan line (Nopo-Bukjeong) depending on active volume of mass transportation between Yangsan city and Busan city was conducted. As the study concluded that it's valid, the necessity to establish the metro railroad network connecting to Busan, Ulsan and Gyeongnam Province is demanded to improve the transportation issues in Ungsang area vulnerable to metro service and to drive the balanced development between metropolitan cities. In addition, the volume of transportation depending on methods in target areas and road traffic assignment are surveyed to put a stress on the necessity to establish the metro railroad network. As the demand of transportation for alternative lines is predicted, the budget and benefits for construction for each alternative line set for the rough economic analysis depending on traffic volume for each method and traffic assignment results. The total project budget necessary for construction of proposal line #1 set as effective one among target three lines in this project is calculated in 794.32 billion won. Construction accounts for the most expensive in expenses for project and contingency allowances, purchases for vehicles and collateral expense are followed in orders. However, compensation for lands is not counted. In particular, according to economic analysis in proposal #1, ratio of benefit/cost (B/C) is 0.584, net present value (NPV) is -217.47 billion won, the internal rate of return (IRR) is analyzed in 0.604 %. At the current stage, it is not economically feasible, but the B/C is 0.737 in long-term upon construction of Yangsan line between Wolpheong and Yongdang which is proposal line #3. Therefore, when Busan metro basic plan is reorganized to aim the benefit of residents in Ungsang area vulnerable to the metro service, we think it must be necessary to establish the metro railroad network connecting to Busan-Yangsan-Ulsan which is proposal line #2 by extending the existing Sinjeong line and including this task line in high-ranked plan related to metro railroad.

• Journal of The Korean Association For Science Education
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• v.38 no.4
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• pp.541-553
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• 2018

The purpose of this study is to explore the relationship between epistemic goals, epistemic considerations and complexity of reasoning of science high school students in an open inquiry and to explore the context on how open inquiry compares with the characteristics of an authentic scientific inquiry. Two teams were selected as focus groups and a case study was conducted. The findings are as follows: First, the contexts, such as 'sharing the value for the phenomenon understanding, reflection on the value of the research, task characteristics that require collaboration and consensus, and sufficient communication opportunities,' promote epistemic goals and considerations. On the other hand, contexts such as 'lack of opportunity for critical review of related literature and environmental constraints' lowered epistemic sides. Second, epistemic goals and considerations influenced the reasoning complexity. The goal of 'scientific sense making' led to reasoning that pose testable hypotheses based on students' own questions. The high justification considerations led to purposely focusing attention to the control designs and developing creative experimental know-how. The high audience considerations led to defending their findings through argumentation and suggesting future research. On the other hand, the goal of 'doing the lesson' and the low justification considerations led to reasoning that did not interpret the meaning of the data and did not control the limit of experiment. The low audience considerations led to reasoning that did not actively defend their findings and not suggest future research. The results of this study suggest that guidance should provide communication and critical review opportunities.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.177-192
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• 2016

Machine learning is a field of artificial intelligence. It refers to an area of computer science related to providing machines the ability to perform their own data analysis, decision making and forecasting. For example, one of the representative machine learning models is artificial neural network, which is a statistical learning algorithm inspired by the neural network structure of biology. In addition, there are other machine learning models such as decision tree model, naive bayes model and SVM(support vector machine) model. Among the machine learning models, we use SVM model in this study because it is mainly used for classification and regression analysis that fits well to our study. The core principle of SVM is to find a reasonable hyperplane that distinguishes different group in the data space. Given information about the data in any two groups, the SVM model judges to which group the new data belongs based on the hyperplane obtained from the given data set. Thus, the more the amount of meaningful data, the better the machine learning ability. In recent years, many financial experts have focused on machine learning, seeing the possibility of combining with machine learning and the financial field where vast amounts of financial data exist. Machine learning techniques have been proved to be powerful in describing the non-stationary and chaotic stock price dynamics. A lot of researches have been successfully conducted on forecasting of stock prices using machine learning algorithms. Recently, financial companies have begun to provide Robo-Advisor service, a compound word of Robot and Advisor, which can perform various financial tasks through advanced algorithms using rapidly changing huge amount of data. Robo-Adviser's main task is to advise the investors about the investor's personal investment propensity and to provide the service to manage the portfolio automatically. In this study, we propose a method of forecasting the Korean volatility index, VKOSPI, using the SVM model, which is one of the machine learning methods, and applying it to real option trading to increase the trading performance. VKOSPI is a measure of the future volatility of the KOSPI 200 index based on KOSPI 200 index option prices. VKOSPI is similar to the VIX index, which is based on S&P 500 option price in the United States. The Korea Exchange(KRX) calculates and announce the real-time VKOSPI index. VKOSPI is the same as the usual volatility and affects the option prices. The direction of VKOSPI and option prices show positive relation regardless of the option type (call and put options with various striking prices). If the volatility increases, all of the call and put option premium increases because the probability of the option's exercise possibility increases. The investor can know the rising value of the option price with respect to the volatility rising value in real time through Vega, a Black-Scholes's measurement index of an option's sensitivity to changes in the volatility. Therefore, accurate forecasting of VKOSPI movements is one of the important factors that can generate profit in option trading. In this study, we verified through real option data that the accurate forecast of VKOSPI is able to make a big profit in real option trading. To the best of our knowledge, there have been no studies on the idea of predicting the direction of VKOSPI based on machine learning and introducing the idea of applying it to actual option trading. In this study predicted daily VKOSPI changes through SVM model and then made intraday option strangle position, which gives profit as option prices reduce, only when VKOSPI is expected to decline during daytime. We analyzed the results and tested whether it is applicable to real option trading based on SVM's prediction. The results showed the prediction accuracy of VKOSPI was 57.83% on average, and the number of position entry times was 43.2 times, which is less than half of the benchmark (100 times). A small number of trading is an indicator of trading efficiency. In addition, the experiment proved that the trading performance was significantly higher than the benchmark.