• Title/Summary/Keyword: Regression Analysis Model

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The Impact of Capital Structure on Firm's Profitability: A Case Study of the Rubber Industry in Vietnam

  • CO, Huong Thi Thanh;UONG, Trang Thi Mai;NGUYEN, Cong Van
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.7
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    • pp.469-476
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    • 2021
  • This study aims to examine and measure the impact of capital structure on the profitability of companies in emerging markets. The research sample includes eighteen rubber companies listed on the Vietnam stock exchange from 2015-2019. After collecting the research data, it was imported into excel to calculate the criteria for the research model. By using Stata 16 software, the study selected a data processing model and evaluated the relevance of the regression analysis model. The research results show that the profitability of listed rubber companies in Vietnam (measured by return on equity (ROE) has a positive relationship with the debt-to-asset ratio but has a negative relationship with the long-term debt-to-asset ratio. The results also show a positive impact of firm size and revenue growth on profitability while liquidity and the ratio of tangible fixed assets to total assets do not affect significantly. These results are consistent with most of the previously published studies. However, in contrast to many previous studies, our study shows that the long-term debt-to-assets ratio has a negative effect on profitability while the debt-to-asset ratio has a positive effect. This is entirely consistent with the characteristics of long-term debt use in emerging markets.

Estimation model of shear strength of soil layer using linear regression analysis (선형회귀분석에 의한 토층의 전단강도 산정모델)

  • Lee, Moon-Se;Kim, Kyeong-Su
    • Proceedings of the Korean Geotechical Society Conference
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    • pp.1065-1078
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    • 2009
  • The shear strength has been managed as an important factor in soil mechanics. The shear strength estimation model was developed to evaluate the shear strength using only a few soil properties by the linear regression analysis model which is one of the statistical methods. The shear strength is divided into two part; one is the internal friction angle ($\Phi$) and the other is the cohesion (c). Therefore, some valid soil factors among the results of soil tests are selected through the correlation analysis using SPSS and then the model are formulated by the linear regression analysis based on the relationship between factors. Also, the developed model is compared with the result of direct shear test to prove the rationality of model. As the results of analysis about relationship between soil properties and shear strength, the internal friction angle is highly influenced by the void ratio and the dry unit weight and the cohesion is mainly influenced by the void ratio, the dry unit weight and the plastic index. Meanwhile, the shear strength estimated by the developed model is similar with that of the direct shear test. Therefore, the developed model may be used to estimate the shear strength of soils in the same condition of study area.

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A Case Study on the Improvement of Display FAB Production Capacity Prediction (디스플레이 FAB 생산능력 예측 개선 사례 연구)

  • Ghil, Joonpil;Choi, Jin Young
    • Journal of the Society of Korea Industrial and Systems Engineering
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    • v.43 no.2
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    • pp.137-145
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    • 2020
  • Various elements of Fabrication (FAB), mass production of existing products, new product development and process improvement evaluation might increase the complexity of production process when products are produced at the same time. As a result, complex production operation makes it difficult to predict production capacity of facilities. In this environment, production forecasting is the basic information used for production plan, preventive maintenance, yield management, and new product development. In this paper, we tried to develop a multiple linear regression analysis model in order to improve the existing production capacity forecasting method, which is to estimate production capacity by using a simple trend analysis during short time periods. Specifically, we defined overall equipment effectiveness of facility as a performance measure to represent production capacity. Then, we considered the production capacities of interrelated facilities in the FAB production process during past several weeks as independent regression variables in order to reflect the impact of facility maintenance cycles and production sequences. By applying variable selection methods and selecting only some significant variables, we developed a multiple linear regression forecasting model. Through a numerical experiment, we showed the superiority of the proposed method by obtaining the mean residual error of 3.98%, and improving the previous one by 7.9%.

Enhancement of Artillery Simulation Training System by Neural Network (신경망을 이용한 포병모의훈련체계 향상방안)

  • Ryu, Hai-Joon;Ko, Hyo-Heon;Kim, Ji-Hyun;Kim, Sung-Shick
    • Journal of the military operations research society of Korea
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    • v.34 no.1
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    • pp.1-11
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    • 2008
  • A methodology for the improvement of simulation based training system for the artillery is proposed in this paper. The complex nonlinear relationship inherent among parameters in artillery firing is difficult to model and analyze. By introducing neural network based simulation, accurate representation of artillery firing is made possible. The artillery training system can greatly benefit from the improved prediction. Neural networks learning is conducted using the conjugate gradient algorithm. The evaluation of the proposed methodology is performed through simulation. Prediction errors of both regression analysis model and neural networks model are analyzed. Implementation of neural networks to training system enables more realistic training, improved combat power and reduced budget.

Development of Estimation of Model for Mechanical Properties of Steel Fiber Reinforced Concrete according to Aspect Ratio and Volume Fraction of Steel Fiber (강섬유의 형상비와 혼입률에 따른 강섬유 보강 콘크리트 보의 역학적 특성 추정 모형 개발)

  • Kwak, Kae-Hwan;Hwang, Hae-Sung;Sung, Bai-Kyung;Jang, Hwa-Sup
    • Journal of The Korean Society of Agricultural Engineers
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    • v.48 no.3
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    • pp.85-94
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    • 2006
  • Practially useful method of steel fiber for construction work is presented in this study. The most important purpose of this study is to develop a model which can predict mechanical behavior of the structure according to aspect ratio and volume fraction of steel fiber. Experiments on compressive strength, elastic modulus, and splitting strength were performed with self-made cylindrical specimens of variable aspect ratios and volume fractions. The experiment showed that compressive strength was not in direct proportion to volume fraction which doesn't seem to have great influence over compressive strength. However, splitting strength showed almost direct proportion to aspect ratio and volume fraction. Improvement of optimal efficiency was confirmed when the aspect ratio was 70. Experiments on flexural strength, fracture energy, and characteristic length were carried out with self-manufactured beams with notch. As a result, increases of flexural strength, fracture energy, and characteristic length according to increase of volume fraction tend to be prominent when aspect ratio is 70. The steel fiber improves concrete to be more ductile and tough. Moreover, regression analysis was the performed and predictable model was developed after determining variables. With comparison and analysis of suggested estimated values and measured data, reliance of the model was verified.

A study on the Reason of China's Anti-Dumping inspection against South Korea (중국(中國)의 대한(對韓) 반(反)덤핑조사(調査) 요인(要因)에 관한 실증(實證) 연구(硏究) - 철강(鐵鋼).석유화학(石油化學).제지(製紙) 산업(産業) 중심(中心) -)

  • Sim, Yoon-Soo
    • THE INTERNATIONAL COMMERCE & LAW REVIEW
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    • v.30
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    • pp.145-174
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    • 2006
  • An anti-dumping has become the trade policy of choice for developing countries as well as advanced countries, hence it is the impending issue to the export-oriented countries including Korea. After colligating the analysis on the trade and industrial policy between Korea and China as well as the analysis on the preceding research, the main reasons of anti-dumping were selected as followings; an unemployment rate, real GDP growth rate and consumer price increase as internal factors, and trade balance, regional coefficient and trade specification index as external factors. Then, the research on how the above seven variable factors can affect the number of anti-dumping measures was accomplished. For the empirical analysis, the above information was used after reorganizing them by on the quarterly basis. Through the use of the correlation analysis, backward elimination of multiple regression analysis model and time-series analysis, it has appeared that the unemployment rate appeared to be the most important factors of anti-dumping measures in addition to the increase rate of trade balance. The variable such as the unemployment rate is uncontrollable for us, so it is appropriate to establish and operate an preemptive monitoring system based on the increasing rate of the amount of export and increasing rate of trade surplus.

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A Study on the Influence of a Sewage Treatment Plant's Operational Parameters using the Multiple Regression Analysis Model

  • Lee, Seung-Pil;Min, Sang-Yun;Kim, Jin-Sik;Park, Jong-Un;Kim, Man-Soo
    • Environmental Engineering Research
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    • v.19 no.1
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    • pp.31-36
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    • 2014
  • In this study, the influence of the control and operational parameters within a sewage treatment plant were reviewed by performing multiple regression analysis on the effluent quality of the sewage treatment. The data used for this review are based on the actual data from a sewage treatment plant using the media process within the year 2012. The prediction models of chemical oxygen demand ($COD_{Mn}$) and total nitrogen (T-N) within the effluent of the 2nd settling tank based on the multiple regression analysis yielded the prediction accuracy measurements of 0.93 and 0.84, respectively; and it was concluded that the model was accurately predicting the variances of the actual observed values. If the data on the energy spent on each operating condition can be collected, then the operating parameter that conserves energy without violating the effluent quality standards of COD and T-N can be determined using the regression model and the standardized regression coefficients. These results can provide appropriate operation guidelines to conserve energy to the operators at sewage treatment plants that consume a lot of energy.

Association between Blood Mercury and Drinking Soju and Beer in Korea (소주 및 맥주 음주와 혈중 수은과의 관계에 관한 연구)

  • Cho, Jun Ho
    • Journal of Environmental Health Sciences
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    • v.44 no.4
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    • pp.348-359
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    • 2018
  • Objectives: The purpose of this study was to investigate the relationship between frequency of alcohol drinking and blood mercury concentration in Korea. Methods: This was a cross-sectional study that used data from the Korean National Health and Nutrition Examination Survey. Among them, 3,174 persons were selected for the final study. Results: The concentration of mercury in the blood increased as the frequency of drinking soju or beer increased. Similarly, in the multiple-linear regression analysis model, the frequency of soju drinking was identified as an independent variable showing a statistically significant positive linearity (p<0.001). After controlling for confounding factors, comparing those drinking 'more than twice a week' with those who almost do not drink alcohol, the adjusted ORs for exposure to high concentrations of mercury were 3.24 (95% CI, 2.10-4.99) for drinking soju and 2.07 (95% CI, 1.33-3.22) for drinking beer. The interaction effect between 'soju drinking' and 'spicy pollack and seafood stew' was not statistically significant (p=0.098) for evaluating the interaction effect between the two variables. Conclusions: The concentration of mercury in the blood increased as the frequency of drinking of soju or beer increased. The higher the frequency of alcohol drinking, the more likely is the blood mercury to be included in the high-concentration group. The results of this study can be used as important scientific evidence for the field of environmental health related to alcohol drinking and blood heavy metal exposure in Korea.

A Study on the Effects of SME's Technology Planning Competency on the Success of Commercialization (중소기업의 기술기획 역량이 기술사업화 성공에 미치는 영향에 관한 연구)

  • Lee, Jongmin;Noh, Meansun;Chung, Sunyang
    • Journal of Technology Innovation
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    • v.21 no.1
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    • pp.253-278
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    • 2013
  • SMEs in Korea have increased their investment in R&D as they have recognized the importance of technology development. However, Korean SMEs have been lacking in technological competencies and commercialization capabilities. Also, SMEs often have difficulties in technology planning and preliminary research in R&D process. Under this background, this paper analyses the effects of SMEs' technology planning competency on the success of their commercialization, as their low technological competencies are due to the low capabilities of technology planning. The result shows that SMEs' cooperation partnership and market orientation are significant determinants to the success of their technology commercialization. The study used logistic regression analysis model.

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Relationships Among Stress Coping Strategies, Emotion Regulation Ability, and Behavior Problems in Children from Low-income and Middle-income Families (아동의 스트레스 대처전략과 정서조절 능력 및 행동문제: 저소득층 아동과 일반아동 비교)

  • Kim, Byeng-Og;Lee, Jin-Suk
    • Korean Journal of Human Ecology
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    • v.17 no.6
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    • pp.1051-1063
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    • 2008
  • This study was to investigate the relationships between stress coping strategies, emotion regulation ability and behavior problems with children from low-income families and middle-income families. Subjects were 171 children from low-income families and 228 children from middle-income families, 4th - 6th grade in elementary school. The major findings are followings: (1) The level of emotion regulation ability in children from low-income families was lower and active stress coping strategies were less than children from middle-income families. In the behavior problem, children from low-income families were higher than children from middle-income families. (2) The stress coping strategies(active/ social support) in children from low-income families were related with internal behavior problem(anxiety /withdrawal). And the emotion regulation ability was related to the children's behavior problem. (3) Regression analysis model showed that emotion-regulation ability was the most influential factor to the children's behavior problem, and children from low-income families with aggressive coping strategy showed hyperactive behavior problem. So, the education/therapy programs for children from low-income families have to be developed and practiced in schools, local children centers and so on.