This study is a basic study to effectively develop a mathematics experience object, an important tool and educational tool in mathematics education. Recently, as mathematics education based on action theory is emphasized, various mathematics experience objects are being developed. It is also used through various after-school activities in the school. However, there are insufficient cases in which a mathematics experience teaching tools is developed and used as a tool for explaining mathematics concepts in mathematics classrooms. Also, the mathematical background of the mathematics experience teaching tools used by students is unclear. For this reason, the mathematical understanding of the toolst for mathematics experience is also very insufficient. Therefore, in this study, a development model is proposed as a systematic method for developing a mathematics experience teaching tools. Also, in this study, we developed 'the Great Common Divisor' mathematics experience teaching tool according to the development model. Through the model proposed through this study and the actual mathematics experience teaching tool, the development of various tools for mathematical experience will be practically implemented. In addition, it is expected that various tools for experiencing mathematics based on mathematical foundations will be developed.
Purpose - This study quantifies sources of trade balance dynamics over the business cycle in Korea. Specifically, we quantify the relative importance of domestic and foreign factors on trade balance dynamics using a small open economy real business cycle (SOE-RBC) model and provide policy implications for stabilization policies. Aggregate productivity and interest rate spreads are considered domestic factors affecting the trade balance. A world interest rate (the U.S. interest rate) is considered a foreign factor. Design/methodology - Following Neumeyer and Perri (2005), we build the SOE-RBC model with three types of shocks: aggregate productivity, interest rate spread, and world interest shocks. The model is estimated by the generalized method of moments (GMM) using relevant business cycle statistics. The estimated model is used for quantifying the relative importance of domestic and foreign factors on trade balance dynamics in Korea. Findings - Our main findings can be summarized as follows: 85.64% of the trade balance fluctuations in Korea are explained by domestic factors, the remaining 14.35% by foreign factors. Particularly, trade balance dynamics are mostly accounted for by the change in aggregate productivity shocks (85.58%). World interest rate shocks considerably explain trade balance (14.35%), whereas the role of interest rate spread shocks that represent domestic risks is limited (0.08%). Although aggregate productivity is key in explaining trade balance dynamics in Korea, interest rates still have an essential role. This is because aggregate productivity changes induce interest rate spread variations and, thus, the trade balance significantly. The results suggest that government policies mitigating fluctuations in aggregate productivity would be effective for stabilization policies in Korea by reducing the trade balance volatility. Originality/value - Existing studies on the emerging market business cycle examine mostly Latin American countries, and the main object of the studies is the volatility of consumption rather than trade balance dynamics. Conversely, our study examines Korea rather than Latin American countries. Additionally, we examine sources of trade balance dynamics, which are relatively more important in Korea, rather than those of the volatility of consumption. Hence, we estimate the model to explicitly match moments related to trade balance in the data.
Purpose - This paper's aim is to investigate whether or not gross profitability explains the cross-sectional variation of the stock returns in the Korean stock market. Gross profitability is an alternative profitability measure proposed by Novy-Marx in 2013 to predict cross-sectional variation of stock returns in the US. He shows that the gross profitability adds explanatory power to the Fama-French 3 factor model. Interestingly, gross profitability is negatively correlated with the book-to-market ratio. By confirming the gross profitability premium in the Korean stock market, we may provide some implications regarding the well-known value premium. In addition, our empirical results may provide opportunities for the fund distribution industry to promote brand new styles of funds. Research design, data, and methodology - For our empirical analysis, we collect monthly market prices of all the companies listed on the Korea Composite Stock Price Index (KOSPI) of the Korea Exchanges (KRX). Our sample period covers July1994 to December2014. The data from the company financial statementsare provided by the financial information company WISEfn. First, using Fama-Macbeth cross-sectional regression, we investigate the relation between gross profitability and stock return performance. For robustness in analyzing the performance of the gross profitability strategy, we consider value weighted portfolio returns as well as equally weighted portfolio returns. Next, using Fama-French 3 factor models, we examine whether or not the gross profitability strategy generates excess returns when firmsize and the book-to-market ratio are controlled. Finally, we analyze the effect of firm size and the book-to-market ratio on the gross profitability strategy. Results - First, through the Fama-MacBeth cross-sectional regression, we show that gross profitability has almost the same explanatory power as the book-to-market ratio in explaining the cross-sectional variation of the Korean stock market. Second, we find evidence that gross profitability is a statistically significant variable for explaining cross-sectional stock returns when the size and the value effect are controlled. Third, we show that gross profitability, which is positively correlated with stock returns and firm size, is negatively correlated with the book-to-market ratio. From the perspective of portfolio management, our results imply that since the gross profitability strategy is a distinctive growth strategy, value strategies can be improved by hedging with the gross profitability strategy. Conclusions - Our empirical results confirm the existence of a gross profitability premium in the Korean stock market. From the perspective of the fund distribution industry, the gross profitability portfolio is worthy of attention. Since the value strategy portfolio returns are negatively correlated with the gross profitability strategy portfolio returns, by mixing both portfolios, investors could be better off without additional risk. However, the profitable firms are dissimilar from the value firms (high book-to-market ratio firms); therefore, an alternative factor model including gross profitability may help us understand the economic implications of the well-known anomalies such as value premium, momentum, and low volatility. We reserve these topics for future research.
The purpose of this work is to explore the role of international entrepreneurship(IE) in explaining internationalization process of Korean ventures and to structure the model of IE with the logics of effectuation. The internationalization of entrepreneurial company is regarded as the realization of entrepreneurship which find out and use opportunities across borders in this point of view, and the realization process gets more realistic and applicable to the internationalization of ventures by effectuation. So we constructed the new concepts of the generating-internationalization-outcome capability(GIOC), which is the effectual capability allowing ventures to go international despite their lack of internal resources and experiences. Its sub-capabilities of GIOC are extemporaneous coping capability, perform-resource-in-hand capability and network-use capability. The empirical analyses of the relations among the capabilities and the performances of internationalization are performed in order to prove the rationale of the model, which provides finally significant evidences of the relationships. The key contribution of this study is that it highlights the important role of IE in internationalization of ventures and shows the possible role of effectuation in explaining the realization process of IE.
The purpose of this study was to examine the effects of job characteristics and health on accident experience by analyzing the data of transportation workers according to age. The analysis used data from 'the fourth Korean Working Conditions Survey(KWCS)'. A total of 1,997 transport workers data were finally analyzed, and correlation analysis, crossover analysis and logistic regression analysis were performed. It was confirmed that there was no correlation between the age of the transport workers and the accident experience. In the relationship between the characteristics of transportation workers and the experience of the accident, it was found that, in the case of older workers, there was a significant effect in the order of 'at mistake someone else hurt', 'musculoskeletal problem', 'cardiovascular problem' and 'repetitive movements of hands or arms', the model explaining power was 56.9%(p <.01). In the case of non-older workers, it was found that 'depression and anxiety disorder', 'relationship between job and safety', 'at mistake someone else hurt' and 'labor union', the model explaining power was 21.8%(p <.01). Therefore, in order to promote prevent accidents of transportation workers in future, it is necessary to consider various variables such as health and job characteristics besides age.
Kim, Tae Ho;Shin, Yea Cheol;Lim, Sam Jin;Park, Jun Tae
Journal of the Korean Society of Safety
/
v.28
no.2
/
pp.78-83
/
2013
The traffic culture index is used as a major index in evaluating the traffic safety services of local governments and also serve as important data for the planning and implementation of traffic safety services. However, as the traffic culture index gradually became a standard for comparison among local governments, in part, certain cases arose which questioned the grounds for selecting variables for the index and the validity of the index in terms of its influential relationship between evaluation items. This study analyzed the index's influential relationship by utilizing a PLS structural equation model based on the evaluation results of the 2011 traffic culture index. A variable-linking model was created which recognized the relativity taking into account of the indirect effects between latent variables and this model was proven to be a model suitable in explaining the traffic culture index with a 97.8% explanation power. It was found that traffic safety(0.530), driving behavior(0.527), pedestrian behavior(0.187) and vulnerable road users(0.147), in such order, had an effect on the traffic culture index. It was also found that human casualties due to traffic accidents under "traffic safety" and traffic light compliance rate under "driving behavior" had an important effect. The study showed that motor vehicle share in illegal parking in school zones did not have a valid explanation power regarding "vulnerable road users".
Objectives: This study was conducted to determine, by reviewing the literature, whether treatment of Helicobacter pylori infection in patients with non-ulcer dyspepsia affects symptoms. Methods: We retrieved the literature using MEDLINE search, with nonulcer dyspepsia and Hericobacter pylori and treatment as key words, which were reported from 1984 to 1998, and manual literature search. The criteria for inclusion was as follows; 1) The paper should have confirmed nonulcer dyspepsia as case definition. 2) The paper should have peformed a randomized, blind trial. 3) Confirmation of Helicobacter pylori eradication should be done 4 weeks after treatment. 4) studies with no information on measurement of symptoms after treatment were not accepted. The percentage of patients with symptom improvement after eradication therapy for Helicobacter pylori infection was calculated. Cumulative odds ratio was compared by fixed effect model and random effect model as sensitivity and funnel plot was used to evaluate publication bias. Results: The overall effect size of symptom improvement was calculated by cumulative odds ratio. Cumulative odds ratio of random effect model was 4.16(95% CI: 1.55-11.19). Before integrating each effect sizes into common effect size, the homogeneity test was conducted and random effect model was selected(Cochran's Q=41.08 (d.f=10, p<0.001)). The heterogeneity across studies was evaluated and the different methodological aspects of studies led to differences between study results Conclusions: The results suggest that the eradication of Helicobacter pylori in patients with non-ulcer dyspepsia results more symptom improvement. In studios that shows the opposite results there are methodological aspects explaining the heterogeneity.
This paper describes an experiment of concrete and specific group work learning system based on the traditional Jigsaw group work learning model. Jigsaw model has two groups of students such as random group and expert group so that a course can make progress on explaining and lecturing all members of class after each student can be a member of expert group of course topic. We design and implement Web-based training system to support collaboration and Interaction among students of a course based on Jigsaw model The Web- based learning system makes each group going up to the expert level of a course subject by supporting various study menu and provides equal opportunity of improving social abilities such as leadership, communication skill, trust, and trouble-settling by taking part in collaboration activities.
Invasive blood pressure (IBP) is measured for the patient's real time arterial pressure (ABP) to monitor the critical abrupt disorders of the cardiovascular system. It can be used for the estimation of cardiac output and the opening and closing time detection of the aortic valve. Although the unexplained inflections on ABP make it difficult to find the mathematical relations with other cardiovascular parameters, the estimations based on ABP for other data have been accepted as useful methods as they had been verified with the statistical results among vast patient data. Previous windkessel models were composed with systemic resistance and vascular compliance and they were successful at explaining the average systolic and diastolic values of ABP simply. Although it is well-known that the blood pressure reflection from peripheral arteries causes complex inflection on ABP, previous models do not contain any elements of the reflections because of the complexity of peripheral arteries' shapes. In this study, to simulate a reflection wave of blood pressure, a new mathematical model was designed with four elements that were the impedance of aorta, the compliance of aortic arch, the peripheral resistance, and the compliance of peripheral arteries. The parameters of the new model were adjusted to have three types of arterial blood pressure waveform that were measured from a patient. It was used to find the relations between the inflections and other cardiovascular parameters such as the opening-closing time of aortic valve and the cardiac output. It showed that the blood pressure reflection can bring wide range errors to the closing time of aortic valve and cardiac output with the conventional estimation based on ABP and that the changes of one-stroke volumes can be easily detected with previous estimation while the changes of heart rate can bring some error caused by unexpected reflections.
Back ground: Nurses now occupy one third of all hospital human resources. Therefore, efficient management of nursing manpower is getting more important. While it is very clear that nursing workload requirement analysis and patient severity classification should be done first for the efficient allocation of nursing workforce, these processes have been conducted manually with ad hoc rule. Purposes: This study was tried to make a predict model for patient classification according to nursing need. We tried to find the easier and faster method to classify nursing patients that can help efficient management of nursing manpower. Methods: The nursing patient classifications data of the hospitalized cancer patients in one of the biggest cancer center in Korea during 2003.1.1-2003.12.31 were assessed by trained nurses. This study developed a prediction model and analyzing nursing needs by data mining techniques. Patients were classified by three different data mining techniques, (Logistic regression, Decision tree and Neural network) and the results were assessed. Results: The data set was created using 165,073 records of 2,228 patients classification database. Main explaining variables were as follows in 3 different data mining techniques. 1) Logistic regression : age, month and section. 2) Decision tree : section, month, age and tumor. 3) Neural network : section, diagnosis, age, sex, metastasis, hospital days and month. Among these three techniques, neural network showed the best prediction power in ROC curve verification. As the result of the patient classification prediction model developed by neural network based on nurse needs, the prediction accuracy was 84.06%. Conclusion: The patient classification prediction model was developed and tested in this study using real patients data. The result can be employed for more accurate calculation of required nursing staff and effective use of labor force.
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