• The Transactions of the Korean Institute of Electrical Engineers P
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• v.67 no.4
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• pp.183-190
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• 2018

Predicting accurate electricity prices is an important task in the electricity trading market. To address the electricity price forecasting problem, various approaches have been proposed so far and it is known that linear regression-based approaches are the best. However, the use of such linear regression-based methods is limited due to low accuracy and performance. In traditional linear regression methods, it is not practical to find a nonlinear regression model that explains the training data well. If the training data is complex (i.e., small-sized individual data and large-sized features), it is difficult to find the polynomial function with n terms as the model that fits to the training data. On the other hand, as a linear regression model approximating a nonlinear regression model is used, the accuracy of the model drops considerably because it does not accurately reflect the characteristics of the training data. To cope with this problem, we propose a new electricity price forecasting method that divides the entire dataset to multiple split datasets and find the best linear regression models, each of which is the optimal model in each dataset. Meanwhile, to improve the performance of the proposed method, we modify the proposed localized linear regression method in the map and reduce way that is a framework for parallel processing data stored in a Hadoop distributed file system. Our experimental results show that the proposed model outperforms the existing linear regression model. Specifically, the accuracy of the proposed method is improved by 45% and the performance is faster 5 times than the existing linear regression-based model.

• The Korean Journal of Health Service Management
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• v.8 no.1
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• pp.113-123
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• 2014

The purpose this study was to investigate the relationship between Upper extremity's function and Activities of Daily Living(ADL) in stroke patients. The participants were 112 stroke patients who underwent occupational therapy. Data were analyzed using descriptive statistics, Pearson's correlation coefficient, and multiple linear regression analysis. The results are as foolows. MFT of both unaffected upper limbs and affected upper limbs were significantly correlated with total MBI score. The all area of MFT on the affected upper limbs were significantly correlated with sub-item of MBI. And finger manipulation area of MFT on the unaffected upper limbs were significantly correlated with sub-item of MBI. Significant factors influencing MBI, both unaffected upper limbs and affected upper limbs total score. Significant factors influencing sub-items of MBI, the function of affected upper limbs by MFT were MBI all sub items exculsive bowel, bladder control and the function of unaffected upper limbs by MFT were personal hygiene, bathing, feeding, toilet, bowel & bladder control, chair/bed transfer of MBI sub items. Above results show that ADL is highly correlated with affected upper limbs and unaffected upper limbs function in the stroke patients.

• The Korean Journal of Rehabilitation Nursing
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• v.20 no.1
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• pp.33-41
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• 2017

Purpose: This study is a descriptive study to analyze the relationship between the cognitive function, body image and pain, and the influencing factors on the daily life performance of brain injured patients. Methods: The study subjects were 119 inpatients with brain injury who gave informed consent. The activities of daily living (ADLs), cognitive function, pain and body image were measured by Modified Barthel Index (K-MBI), K-MMSE (Mini-Mental State Examination), Visual Analog Scale (VAS), Semantic Differential Method (SDM), respectively. Results: ADLs was significantly associated with body image, cognitive function, and pain. Multiple regression analysis showed that paralysis, consciousness, cognitive function, and pain were significant factors influencing ADLs. Overall, approximately 48% of total variability in the ADLs could be explained by the 4 variables ($R^2=.477$, p<.001). Conclusion: To improve ADLs of brain injury patients, a deeper understanding of paralysis, consciousness, cognitive function, and pain of patients is required and active nursing invention should be conducted.

• International Journal of High-Rise Buildings
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• v.5 no.2
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• pp.95-103
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• 2016

One of the key problems in the design of high-rise commercial complex is how to guide reasonable pedestrian distribution in commercial space. In this study, pedestrian distribution in three high-rise commercial complexes in Shanghai and Hong Kong was studied using spatial configuration analysis software Space Syntax and quantification of physical elements in commercial spaces, such as functional attractiveness, entrances, escalators, level variations and passage width. Additionally, in an attempt to integrate functions with spatial integration and spatial depth, two combination variables, the spatial coefficient of function (IF) and spatial depth coefficient of function (F/D), were proposed. The results of the correlation analysis and multiple regression analyses reflected the following: (1) Regarding the influence on pedestrian distribution, there was a synergistic and complementary relationship between function and space; (2) The comprehensive flow distribution analytic model could successfully interpret flow distribution in high-rise commercial complexes and its R Square ranged up to about 70% in the three cases; (3) The spatial coefficient of function (IF) and spatial depth coefficient (F/D) could effectively integrate functions and spatial configuration, which could help close the gap between over-emphasis on function in commercial research and the lack of consideration of function in space-syntax analysis.

• Journal of the Korean Data and Information Science Society
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• v.20 no.2
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• pp.321-328
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• 2009

In regression analysis, the ordinary least squares estimates of regression coefficients become poor, when the correlations among predictor variables are high. This phenomenon, which is called multicollinearity, causes serious problems in actual data analysis. To overcome this multicollinearity, many methods have been proposed. Ridge regression, shrinkage estimators and methods based on principal component analysis (PCA) such as principal component regression (PCR) and latent root regression (LRR). In the last decade, many statisticians discussed sensitivity analysis (SA) in ordinary multiple regression and same topic in PCR, LRR and logistic principal component regression (LPCR). In those methods PCA plays important role. Many statisticians discussed SA in PCA and related multivariate methods. We introduce the method of PCR and LRR. We also introduce the methods of SA in PCR and LRR, and discuss the properties of SA in PCR and LRR.

• Journal of Positioning, Navigation, and Timing
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• v.4 no.2
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• pp.79-85
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• 2015

Existing Differential GPS (DGPS) pseudorange correction (PRC) generation techniques based on a virtual reference station cannot effectively assign a weighting factor if the baseline distance between a user and a reference station is not long enough. In this study, a virtual reference station DGPS PRC generation technique was developed based on an enhanced inverse distance weighting method using an exponential function that can maximize a small baseline distance difference due to the dense arrangement of DGPS reference stations in South Korea, and its positioning performance was validated. For the performance verification, the performance of the model developed in this study (EIDW) was compared with those of typical inverse distance weighting (IDW), first- and second-order multiple linear regression analyses (Planar 1 and 2), the model of Abousalem (1996) (Ab_EXP), and the model of Kim (2013) (Kim_EXP). The model developed in the present study had a horizontal accuracy of 53 cm, and the positioning based on the second-order multiple linear regression analysis that showed the highest positioning accuracy among the existing models had a horizontal accuracy of 51 cm, indicating that they have similar levels of performance. Also, when positioning was performed using five reference stations, the horizontal accuracy of the developed model improved by 8 ~ 42% compared to those of the existing models. In particular, the bias was improved by up to 27 cm.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.3
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• pp.103-113
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• 2019

The effectiveness of monetary policy critically depends upon how well the transmission mechanism functions, so that the desired impact on output and inflation is achieved. The purpose of this paper is to study the transmission mechanism of monetary policy by analyzing the impact on inflation and output during multiple indicator regime (1998-99 to 2014) in an emerging economy-India. The Inflation Targeting Regime is also briefly outlined alongwith the impact on output and inflation. Using quarterly data for the period 1997 to 2017, the paper uses weighted average call money market rate as a proxy for the policy rate and evaluates the strength of the interest rate channel. We use a conventional Structural vector auto regression (SVAR) methodology to evaluate the efficacy and show the impluse response functions. Our results find that changes in the policy rate impact output growth steeply with a lag of about two quarters and the impact on inflation is maximized after three quarters. The study concludes that the monetary policy in India has a significant impact on output and inflation in the short-to-medium-run. After the policy shock, the fall in the output growth rate is of greater magnitude than the fall in inflation.

• Korean Journal of Health Education and Promotion
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• v.8 no.1
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• pp.87-97
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• 1991

The purpose of this study is to identify the important marriage variables influencing fertilty. The data on which this study is based was selected from the survey data which was nation-widely collected from 2,824 married women in 1989 as the Korean. Family Function Study performed by the Korea Institute for Population and Health. The data was analyzed by the methods such as Cross Tabulation, Pearson's Correlation, and Multiple Regression. And the data analysis was processed by SPSS. The results are as follows. 1. There are differences in fertility according to the socioeconomic factor. The higher the educational level of a married woman is the lower the fertility level. And if the decision of marriage was made by herself, the fertility level is significantly low. As the duration of living in a large city is longer and the educational level of her husband is higher, the fertility level is low. 2. There are differences is fertility according to the demographic factor. As the first marriage age of her and her husband, the fertility level was low. And when a couple doesn't live with the husband's parents and the size of a family is small, the fertility level is low. 3. Finally the factors affecting fertility were analyzed by the Stepwised Multiple Regression. The result shows that as the educational level of a married woman is higher, she herself decides the marriage, the first marriage level of her is higher, the size of a family is small, her husband is higher, the fertility level is low.

• The Korean Journal of Rehabilitation Nursing
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• v.12 no.1
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• pp.39-46
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• 2009

Purpose: The purpose of this study was to identify the level of burden and social support of mothers with Cerebral Palsy (CP) children, and to determine whether providing social support is an effective strategy to relieve the burden of those mothers. Method: From October to November 2007, the data were collected from 63 mothers with CP children who were admitted and treated for CP at Y rehabilitation center in Seoul. The data were analyzed with t-test, ANOVA, Scheffe's test, Pearson's Correlation Coefficient, and Stepwise Multiple Regression using SPSS 12.0. Results: Burden of mothers was related to the Gross Motor Function Classification System (GMFCS) of the CP children. Social support was negatively correlated and GMFCS was positively correlated with burden of mothers. Social support and GMFCS was statistically significantly related with burden of mothers with CP children by multiple regression analysis. Conclusion: There was a significantly negative correlation between social support and burden. It demonstrated that social support, an important factor relating to burden imposed on mothers of CP children, can be considered as an intervening variable which can contribute to decrease of burden. In addition, applying developmental screening measures are needed to decrease disability severity.

• The Journal of Korean Academy of Orthopedic Manual Physical Therapy
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• v.16 no.2
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• pp.67-75
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• 2010

Purpose: The purpose of this is to identify the relationship among the age, body mass index(BMI) and exercise frequency(EF) with knee joint position sense in korean healthy women. Methods: Healthy women of 328 who participated in this study were tested knee joint position sense; reposition error was measured with a Myrin goniometer. Each reposition error was analyzed using descriptive statics, pearson correlation coefficients, and stepwise multiple regression. Results: The mean reposition error by age groups was significant decrease getting older. The mean reposition error by BMI groups was significant decrease getting higher. And the mean reposition error by EF groups was significant decrease getting lower. The knee joint position sense showed a significantly correlation with age(r=0.36, p=.00), BMI(r=0.34, p=.00) and EF(r=-0.50, p=.00). The most powerful predictor of knee joint position sense was EF. The reposition error according to stepwise multiple regression is $3.36+(-2.64){\times}EF+0.13{\times}age$, and account for 46%($R^2=0.46$) of the variance in the knee joint position sense. Conclusion: The older the women are, for prevent of knee injuries due to decreased joint position sense, regular exercise is essential factor.