• Physical Therapy Rehabilitation Science
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• 제11권3호
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• pp.311-320
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• 2022

Objective: To investigate the reliability and validity of static balance measurements using an acceleration sensor and a gyroscope sensor in smart phone inertial sensors. Design: Equivalent control group pretest-posttest. Methods: Subjects were forty five healthy adults aged twenty to fifty-years-old who had no disease that could affect the experiment. After pre-test, all participants wore a waist band with smart phone, and conducted six static balance measurements on the force plate twice for 35 seconds each. To investigate the test-retest reliability of both smart phone inertial sensors, we compared the intra-correlation coefficient (ICC 3, 1) between primary and secondary measurements with the calculated root mean scale-total data. To determine the validity of the two sensors, it was measured simultaneously with force plate, and the comparision was done by Pearson's correlation. Results: The test-retest reliability showed excellent correlation for acceleration sensor, and it also showed excellent to good correlation for gyroscope sensor(p<0.05). The concurrent validity of smartphone inertial sensors showed a mostly poor to fair correlation for tandem-stance and one-leg-stance (p<0.05) and unacceptable correlation for the other postures (p>0.05). The gyroscope sensor showed a fair correlation for most of the RMS-Total data, and the other data also showed poor to fair correlation (p<0.05). Conclusions: The result indicates that both acceleration sensor and gyroscope sensor has good reliability, and that compared to force plate, acceleration sensor has unacceptable or poor correlation, and gyroscope sensor has mostly fair correlation.

• 한국임상수의학회지
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• 제27권4호
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• pp.427-434
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• 2010

Correlation is a technique used to measure the strength or the degree of closeness of the linear association between two quantitative variables. Common misuses of this technique are highlighted. Linear regression is a technique used to identify a relationship between two continuous variables in mathematical equations, which could be used for comparison or estimation purposes. Specifically, regression analysis can provide answers for questions such as how much does one variable change for a given change in the other, how accurately can the value of one variable be predicted from the knowledge of the other. Regression does not give any indication of how good the association is while correlation provides a measure of how well a least-squares regression line fits the given set of data. The better the correlation, the closer the data points are to the regression line. In this tutorial article, the process of obtaining a linear regression relationship for a given set of bivariate data was described. The least square method to obtain the line which minimizes the total error between the data points and the regression line was employed and illustrated. The coefficient of determination, the ratio of the explained variation of the values of the independent variable to total variation, was described. Finally, the process of calculating confidence and prediction interval was reviewed and demonstrated.

• 한국태양에너지학회 논문집
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• 제36권1호
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• pp.1-9
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• 2016

To well design the solar energy system, the correlation to calculate and predict solar irradiation is basically needed. So, this study was performed to reveal the relationships between the solar irradiation and four meteorological observation data(dry-bulb temperature, relative humidity, duration of sunshine, and amount of cloud) that didn't show from previous any other researches. And then, we finally proposed the various order non-linear correlation from the measured solar irradiation and four meteorological measurement data using MINITAB. To show the deviation and accuracy of the solar irradiation between measured and calculated, this study compared for the daily total solar insolation. From those results, the calculation error could well predicted about maximum 97% for the daily total solar insolation. But, the coefficients of the proposed correlations didn't show any relationships. So, needs more studies to make the proper one correlation for the country.

• 한국환경과학회지
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• 제31권4호
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• pp.341-356
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• 2022

Electrical Conductivity (EC) or Total Dissolved Solids (TDS) has been often used to evaluate the water quality in some water education program for children and youth. This study attempted to find out whether EC (or TDS) can be used as a water pollution criteria in water education program. To clarify it, we used the water analysis data of July 2019 and January 2020 from Water Environment Information System. Data from 332 points in Han-river were used to investigate correlation between the parameters, such as BOD, COD, TN, TP vs EC. Correlation(r) for all data of BOD vs. EC was 0.347 for July 2019 and 0.483 for January 2020. No correlation was observed for BOD Ia and BOD Ib for July 2019 (r=-0.041, -0.030, respectively) and BOD Ia for January 2020 (r=0.041). Better correlation for all data of COD vs. EC was obtained (r=0.543 for July 2019 and r=0.610 for January 2020). However, no correlation was observed for COD Ia for January 2020. High vlaue of EC or TDS does not always mean water pollution, especially for clean water environment. Thus, EC (or TDS) alone can not be used as a water pollution criteria.

• International Journal of Internet, Broadcasting and Communication
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• 제12권4호
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• pp.26-32
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• 2020

There are many airline customer evaluation data, but they are insufficient in terms of predicting customer satisfaction in practice. In particular, they are generally insufficient in case of verification of data value and development of a customer satisfaction prediction model based on customer evaluation data. In this paper, airline customer satisfaction analysis is conducted through an experiment of correlation analysis between customer evaluation data provided by Google's Kaggle. The difference in accuracy varied according to the three types, which are the overall variables, the top 4 and top 8 variables with the highest correlation. To build an airline customer satisfaction prediction model, they are applied to three classification algorithms of Random Forest, SVM, DNN and conduct a classification experiment. They are divided into training data and verification data by 7:3. As a result, the DNN model showed the lowest accuracy at 86.4%, while the SVM model at 89% and the Random Forest model at 95.7% showed the highest accuracy and performance.

• 대한한의진단학회지
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• 제11권2호
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• pp.128-140
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• 2007

Purpose: We performed this study to examine the correlationship between EEG complexity and impedance cardiography data using correlation analysis. Method: This study performed on 30 healthy subjects(16 males, 14 females). Before and after natural respiration, ICG data were recorded, and EEG raw data were measured by moving windows during 15 minutes. The correlation dimension(D2) was calculated from 15 minutes data. 8 channels EEG data were analysed with 9 index of ICG data by correlation analysis. Result: 1. ACI of impedance cardiography had significant correlationship with ch.4 of EEG complexity(p=0.03). 2. VI of impedance cardiography had significant correlationship with ch.3 of EEG complexity(p=0.034) and ch.4 of EEG complexity(p=0.017). 3. HR, TFC, PEP, LVET, STR of impedance cardiography had no significant correlationship with all of 8 channel EEG complexity. Conclusions: These results suggest that nonlinear analysis of EEG and impedance cardiography have some significant correlationship. And it can make out relationship between brain system and cardiovascular system. In the future, therefore, more study of these fields are necessary.

• 자원환경지질
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• 제33권2호
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• pp.111-116
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• 2000

Indentifying anomaly correlations between data sets is the basis for rationalizig geopotential interpretation and theory. A procedure is presented that constitutes an effective process for identifying correlative features between the two or more geopotential data sets. Anomaly features that show direct, inverse, or no correlations between the data may be separated by applying filters in the frequency domains of the data sets. The correlation filter passes or rejects wavenumbers between co-registered data sets based on the correlation coefficient between common wavenumbers as given by the cosine of their phase difference. This study includes an example of Magsat magnetic anomaly profile that illustrates the usefulness of the procedure for extracting correlative features between the data sets.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2000년도 춘계공동학술대회 논문집
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• pp.601-604
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• 2000

In this paper, we compare the classification performance of both data fusion and clustering algorithms (Data Bagging, Variable Selection Bagging, Parameter Combining, Clustering) to logistic regression in consideration of various characteristics of input data. Four factors used to simulate the logistic model are (1) correlation among input variables (2) variance of observation (3) training data size and (4) input-output function. Since the relationship between input & output is not typically known, we use Taguchi design to improve the practicality of our study results by letting it as a noise factor. Experimental study results indicate the following: Clustering based logistic regression turns out to provide the highest classification accuracy when input variables are weakly correlated and the variance of data is high. When there is high correlation among input variables, variable bagging performs better than logistic regression. When there is strong correlation among input variables and high variance between observations, bagging appears to be marginally better than logistic regression but was not significant.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2008년도 추계 학술발표회
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• pp.980-983
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• 2008

KICT has been carrying out inventory research on the cut slopes of national roads. Inventory research results are basic data used in cut slope management system. Inventory data are classified by general status, cut slope characteristics and inspector opinion. Cut slope inventory data are utilized to figure out dangerous slopes and decide survey ranking of detailed safety diagnostication. This paper will draw dangerous cut slope and more important inventory data in Chungcheongdo via correlation analysis.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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• pp.378-381
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• 2002

We retrieved the aerosol optical thickness $\tau$$_{a}$ over land from Landsat-7/ETM+ image data using the correlation between the visible reflectance and middle IR reflectance. This band correlation method for aerosol retrieval was originally proposed fur MODIS data analysis by Kaufman et al.(1977). The results of retrieved aerosol optical thickness $\tau$$_{a}$ from Landsat-7/ETM+ data were compared with the simultaneous sky observation data at our study site. We found a good agreement between the retrieved and observed values. We presented the distribution maps of the aerosol optical thickness over land, retrieved from Landsat-7/ETM+ image data. Then, the surface reflectance map was also presented. The aerosol optical thickness over sea was retrieved assuming no reflected contribution from sea in the near IR band. In addition, we discussed some limitations when we apply the band correlation method.