• Journal of Biomedical Engineering Research
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• v.24 no.3
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• pp.175-181
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• 2003

Studies of muscle fatigue have mostly been checked under isometric exercise. However EMG signals from isotonic exercise generate uncontrollable noise, so there were difficulties in gathering reliable median frequency and muscle fatigue index if frequency analysis was equally applied in isometric exercise. This study tried to compare the differences of muscle fatigue determinant variables in terms of median frequency searching methods of EMG signal, which was estimated in isotonic exercise. To accomplish this, we determined median frequency by using different FFT intervals and overlapping ration of consecutive FFT sections under the same EMG signal, and then searched for a linear regression line, and compared initial median frequency, slope, and muscle fatigue index which were variables under the linear regression line. In result of comparison, initial median frequency was more elevated as FFT exercise interval became larger. The slope of the linear regression line showed distinguishable decreasing tendency as FFT intervals were larger and overlapping sections were smaller. Significant tendency of muscle fatigue index in FFT interval was shown by high muscle fatigue index in specific FFT intervals.

• Journal of Veterinary Clinics
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• v.27 no.4
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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.

• Journal of The Korean Society of Clinical Toxicology
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• v.18 no.2
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• pp.130-135
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• 2020

Purpose: Taking large amounts of glyphosate is life-threatening, but the amounts of glyphosate taken by patients for suicide are not known precisely. The purpose of this study was to find the predictors of large amounts of glyphosate ingestion. Methods: This retrospective study analyzed patients presenting to an emergency department with glyphosate intoxication between 2010 and 2019, in a single tertiary hospital. The variables associated with the intake amounts were investigated. The parameters were analyzed by multivariate variate logistic regression analyses and the receiver operating characteristic (ROC) curve. Results: Of the 28 patients with glyphosate intoxication, 15 (53.6%) were in the large amounts group. Univariate analysis showed that metabolic acidosis, lactic acid, and corrected QT (QTc) interval were significant factors. In contrast, multivariate analysis presented the QTc interval as the only independent factor with intoxication from large amounts of glyphosate. (odds ratio, 95% confidence interval: 1.073, 1.011-1.139; p=0.020) The area under the ROC curve of the QTc interval was 0.838. Conclusion: The QTc interval is associated significantly with patients who visit the emergency department after being intoxicated by large amounts of glyphosate. These conclusions will help in the initial triage of patients with glyphosate intoxication.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.2
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• pp.117-122
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• 2004

The fatigue life in wheels was predicted by simulating the experimental method using Finite-Element analysis. Based on a high frequency fatigue property, calculations of the stresses in wheels were performed by simulating the rotating bending fatigue test. Wheels made of an aluminum alloy(A356.2) were tested using a bending fatigue tester. Results from bending fatigue test showed a linear correlation between bending moment and stress amplitude. Consequently, Finite-Element calculations were performed by a linear analysis. In order to find stress-cycles curves, spoke parts of wheel were tested using a rotary bending fatigue tester. Also, highly accurate Finite-Element analysis requires regression lines and confidence intervals from these results. In conclusion, if the fatigue data related to the material and manufacturing procedure are reliable, the prediction on fatigue lift in wheels can be carried out with high accuracy.

• Preventive Nutrition and Food Science
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• v.13 no.2
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• pp.104-111
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• 2008

As a way to account for the variability of the primary model parameters in the secondary modeling of microbial growth, three different regression approaches were compared in determining the confidence interval of the temperature-dependent primary model parameters and the estimated microbial growth during storage: bootstrapped regression with all the individual primary model parameter values; bootstrapped regression with average values at each temperature; and simple regression with regression lines of 2.5% and 97.5% percentile values. Temperature dependences of converted parameters (log $q_o$, ${\mu}_{max}^{1/2}$, log $N_{max}$) of hypothetical initial physiological state, maximum specific growth rate, and maximum cell density in Baranyi's model were subjected to the regression by quadratic, linear, and linear function, respectively. With an advantage of extracting the primary model parameters instantaneously at any temperature by using mathematical functions, regression lines of 2.5% and 97.5% percentile values were capable of accounting for variation in experimental data of microbial growth under constant and fluctuating temperature conditions.

• Journal of Families and Better Life
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• v.22 no.6 s.72
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• pp.99-109
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• 2004

This study investigated the motivation of the institutional elderly to participate in the leisure programs the participation motivation and their leisure life satisfaction. A survey questionnaire was administered to 265 elderly in an institution for the elderly. The data was analyzed using frequency analysis, factor analysis, and regression analysis. Major findings are as follows: First, the motivation to participate in leisure programs on the part of the institutionalized elderly tended to be more external than internal. Second, regression analysis indicated that the main internal factors that affected participation were health condition, interaction with roommate, gender. education level, and interaction with institution's staff. The major external factors that affected the participation were health condition, interaction with colleagues, gender, and education level. Finally, the results of the regression analysis indicated that the main internal factors that affected the leisure life satisfaction were, intrinsic motivation to participate in leisure programs, interaction with their roommate, gender, and education level.

• Journal of the Korean Solar Energy Society
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• v.37 no.1
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• pp.81-90
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• 2017

We have analyzed the performance of 58 kWp photovoltaic (PV) power systems installed in Jeddah, Saudi Arabia. Performance ratio (PR) of 3 PV systems with 3 desert-type PV modules using monitoring data for 1 year showed 85.5% on average. Annual degradation rate of 5 individual modules achieved 0.26%, the regression model using monitoring data for the specified interval of one year showed 0.22%. Root mean square error (RMSE) of 6 big data analysis models for power output prediction in May 2016 was analyzed 2.94% using a support vector regression model.

• The Journal of the Acoustical Society of Korea
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• v.31 no.1
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• pp.51-61
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• 2012

In this research, we have analyzed the trend of radiation pattern variation in relation to the change of design variables such as source interval and source number for conformal array transducers arranged in equi-angle, equi-interval, and geodesic dome forms. Through statistical multiple regression analysis of the results, we derived functional forms of the side lobe level and the beamwidth in terms of the design variables. Futhermore, the structure of the array transducer was optimized to achieve the smallest side lobe level while satisfying the requirements on beam width by the GA (genetic algorithm) method. Based on the optimized results, we have determined the equi-interval form as the optimal array geometry among the three conformal array geometries.

• Journal of Preventive Medicine and Public Health
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• v.39 no.6
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• pp.455-461
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• 2006

Objectives : Prolongation of the heart rate-corrected QT (QTc) interval has been reported to be associated with cardiovascular morbidity and mortality. However, few studies have examined the relationship between the QTc interval and cardiovascular risk factors in young healthy people, The aim of this study was to examine the associations between the QTc interval and cardiovascular risk factors in young healthy adults. Methods : This study was performed as part of the Kangwha study, which started in 1986, and is an on-going follow-up study on blood pressure and related cardiovascular risk factors. In follow-up examinations during 2005, cardiovascular risk factors, including anthropometrics, blood pressure, blood chemistry and carotid ultrasonography, were measured, and questionnaires on health behaviors completed by 127 men and 149 women aged 25 years. The QTc interval was measured on the resting 12-lead electrocardiogram using an automatic analysis program. Results : The mean QTc interval was significantly longer in women $(419{\pm}17ms)$ than in men $(405{\pm}17ms)$ (p<0.001). A significant positive correlation was found between the QTc interval and waist-hip ratio (p=0.030) in men. Women showed a positive correlation between the QTc interval and systolic blood pressure (p=0.017). On a multiple regression analysis, the QTc interval was positively associated with the waist-hip ratio in men (p=0.012) and with the systolic blood pressure (p=0.020) in women. Conclusions : In young healthy Korean adults, the QTc interval was independently associated with the waist-hip ratio in men and with the systolic blood pressure in women.

• The Transactions of the Korean Institute of Power Electronics
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• v.26 no.4
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• pp.241-248
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• 2021

A battery state-of-health (SOH) estimation algorithm using a machine learning-based linear regression method is proposed for estimating battery aging. The proposed algorithm analyzes the change trend of the open-circuit voltage (OCV) curve, which is a parameter related to SOH. At this time, a section with high linearity of the SOH and OCV curves is selected and used for SOH estimation. The SOH of the aged battery is estimated according to the selected interval using a machine learning-based linear regression method. The performance of the proposed battery SOH estimation algorithm is verified through experiments and simulations using battery packs for electric vehicles.