• Journal of the Korean Data Analysis Society
• /
• v.20 no.6
• /
• pp.3015-3024
• /
• 2018

This study investigates the recent asymmetric effect of news on stock return volatility in Asian five stock markets - Japan, Korea, Singapore, Taiwan, and Malaysia - since 2000. This study uses the GJR-M model which shows a different effect of a good and bad news on volatility. Empirical results show that the unexpected negative return has a more crucial effect on stock return volatility than the unexpected positive one does in all five stock markets. This implies that the bad news of the stock markets gives a more remarkable effect on volatility than good news does. This study finds that it is very important for market participants and regulation practitioners to distinguish between positive and negative return shocks in the stock markets since bad news might have a larger impacts on volatility than good news.

• Safety and Health at Work
• /
• v.11 no.4
• /
• pp.479-484
• /
• 2020

Background: The purpose of this study is to examine the combined effects of organizational climate (OC) with emotional labor (EL) on turnover intention in Korean firefighters. Methods: The data were obtained from the study Firefighters Research: Enhancement of Safety and Health. A total of 4,860 firefighters whose main duty was providing "emergency medical aid" were included. To examine the effects of OC on the relationships between five subscales of EL and turnover intention, four groups were created using various combinations of OC ("good" vs. "bad") and EL ("normal" vs. "risk"): (1) "good" and "normal" (Group I), (2) "bad" and "normal" (Group II), (3) "good" and "risk" (Group III), and (4) "bad" and "risk" (Group IV). Multivariate logistic regression analyses were performed to estimate the risk of turnover intention for the combinations of OC and EL. Results: The results showed turnover intention was significantly higher in the group with "bad" OC (17.7%) than in that with "good" OC (7.6%). Combined effects of OC and EL on turnover intention were found in all five subscales with the exception of Group I for emotional demands and regulation. Groups II, III, and IV were more likely to experience risks of turnover intention than Group I (p for trend <0.001). Conclusions: A positive and cooperative OC plays a role in decreasing the risk of turnover intention and in attenuating the negative effects of EL on turnover intention in firefighters.

• Communications of the Korean Mathematical Society
• /
• v.15 no.4
• /
• pp.697-706
• /
• 2000

If an arithmetic progression F of length 2n and the number k with 2k$\leq$n are give, can we find two monic polynomials with the same degrees whose set of all zeros form F such that both the number of bad pairs and the number of nonreal zeros are 2k? We will consider the case that both the number of bad pairs and the number of nonreal zeros are two. Moreover, we will see the fundamental relation between the number of bad pairs and the number of nonreal zeros, and we will show that the polynomial in x where the coefficient of x(sup)k is the number of sequences having 2k bad pairs has all zeros real and negative.

• Proceedings of the KIEE Conference
• /
• 1993.07a
• /
• pp.131-133
• /
• 1993

In the power system state estimation, the J(x)-index test and normalized residuals $r_N$ have been used to detect the presence of bad measurements and identify their location. But, these methods require the complete re-estimation of system states whenever bad data is identified. This paper presents back-propagation neural network model using autoregressive filter for identification of bad measurements. The performances of neural network method are compared with those of conventional methods and simulation results show the good performance in the bad data identification based on the neural network under sample power system.

• KIPS Transactions on Software and Data Engineering
• /
• v.8 no.12
• /
• pp.465-472
• /
• 2019

Today, in many area the rise of software necessity there has been increasing the issue of the impotance of Good Software. Our reality in software industrial world has been happening to frequently change requirements at any stage of software life cycle. Furthermore this frequent changing will be increasing the design complexity, which will result in being the lower quality of software against our purpose the original design goals. To solve this problem, we suggest how to improve software design through refactoring based on reverse engineering. This is our way of diverse approaches to visually identify bad smell patterns in source code. We expect to improve software quality through refactoring on even frequently changing requirements.

• The Korean Journal of Applied Statistics
• /
• v.31 no.2
• /
• pp.265-285
• /
• 2018

In this study, we applied a deep neural network model to predict four grades of fine dust $PM_{10}$, 'Good, Moderate, Bad, Very Bad' and two grades, 'Good or Moderate and Bad or Very Bad'. The deep neural network model and existing classification techniques (such as neural network model, multinomial logistic regression model, support vector machine, and random forest) were applied to fine dust daily data observed from 2010 to 2015 in six major metropolitan areas of Korea. Data analysis shows that the deep neural network model outperforms others in the sense of accuracy.

• Journal of the Korean Society of Fisheries and Ocean Technology
• /
• v.31 no.1
• /
• pp.93-106
• /
• 1995

This paper describes the development of moving watched chamber. For the most part, the watched chamber have been located in the inner-bay. But, there are many problems of sea-water pollution. Therefore, the watched chamber must be relocated to undeveloped coastal area. The watched chamber which is located in the bay has a bit of damage by bad weather. But, the moving watched chamber would be exposed to bad water. It is desirable to improve the system of chamber. If we make a good design of the moving watched chamber with studying of waves and hydrodynamics, it would be possible to culture fish at the coastal sea area. When a fixed system is changed into a movable one, we can obtain the following advantages: 1. The possibility of diminishing the sea water pollution, easying the overcrowded state in a inner-bay farm, and relieved of limitation caused by bad conditions such as waves, red tides and terrains. 2. It would be easy not only to move the watched chamber system in accordance with weather conditions or occurrence of red tides, but also to select good sites for watched chamber fishes. 3. Transportation and good supervision with the automated design system can results with the effectiveness which increases the amount of aquatic products.

• Korean Journal of Childcare and Education
• /
• v.14 no.1
• /
• pp.249-268
• /
• 2018

Objective: The purpose of this study was to examine the effects of preschooler's temperament on peer play activity, focusing on the mediation of mothers' social interaction parenting behaviors Methods: 1695 mothers of preschoolers completed questionnaires on children's temperament and peer play behaviors, and mothers' parenting behaviors. Data were analyzed by regression analyses by SPSS 18.0. Results: First, preschoolers' sociability exerted positive effects on good peer play behaviors(play interaction) and negative effects on the bad peer play behaviors (disruption, disconnection) and both were partially mediated by mothers' social interaction parenting behaviors. Second, preschoolers' emotionality exerted negative effects on good peer play behaviors and positive effects on the bad peer play behaviors and both were partially mediated by mothers' social interaction parenting behaviors. Preschoolers' activity exerted positive effects on good peer play behaviors and negative effects on the bad peer play behaviors and both were partially mediated by mothers' social interaction parenting behaviors. Conclusion/Implications: These findings provide preliminary evidence that mothers' social interaction parenting behavior partially mediate the effects of preschoolers' temperament on peer play behaviors. Implications for the use of intervention targeting specific temperament have been discussed.

• Fashion & Textile Research Journal
• /
• v.6 no.5
• /
• pp.549-557
• /
• 2004

The purpose of this study is to investigate design properties affecting in evaluated image by adult women's town wear in un-limited circumstance. The stimulus, adult women's town wear, were collected from shopping mall, department stores and churches and evaluated by 20's 150 people. Through the estimations, the 76 pictures of 'good image' and 65 pictures of 'bad image', were selected and analyzed by classification categories. The results were as follows : 1) 'Good Image' is classified 6 groups which are like active casual, feminine casual, adult casual, modern, sporty casual, and elegance. 2) "Bad Image' is classified 5 groups which are like easy casual, active casual, soft casual, modern casual, and feminine casual. 3) Central code of adult women's town wear from 'Good Image' are simple, bright, and harmony and 'Bad Image' are complicate, heavy, and inharmony. The coordination, how to wear, is very important to evaluate image of women's town wear with other properties. Also, body shape appeared by important variable in evaluation.

• The Journal of Asian Finance, Economics and Business
• /
• v.7 no.8
• /
• pp.281-287
• /
• 2020

In capital budgeting practices, investment project evaluations based on the net present value (NPV) and the internal rate of return (IRR) represent the traditional evaluation techniques. Compared with the traditional methods, the modified internal rate of return (MIRR) gives the opportunity to evaluate an investment in certain projet, while taking the changes in cash flows over time and issuing shares such as dividing shares, bonuses, and dividend for each end of the investment year into account. Therefore, this study aims to evaluate an investment in the Malaysian construction sector utilizing financial data for 39 public listed companies operating in the Malaysian construction sector over the period from Jan 1, 2007, to December 30, 2018, based on the MIRR method. Stochastic was studied in this study to estimate the estimated probability by applying the Markov chain model to the MIRR method where the transition matrix has two possible movements of either Good (G) or Bad (B). it is found that the long-run probability of getting a good investment is higher than the probability of getting a bad investment in the long-run, where were the probabilities of good and bad are 0.5119, 0.4881, respectively. Hence, investment in the Malaysian construction sector is recommended.