• Journal of Ocean Engineering and Technology
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• v.26 no.2
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• pp.39-47
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• 2012

The objective of this study was to develop a strength prediction model using a polynomial regression analysis based on the experimental results obtained from ninety samples. As the results of a correlation analysis between various mixing factors and unconfined compressive strength using SPSS (statistical package for the social sciences), the governing factors in the strength of lightweight soil were found to be the crumb rubber content, bottom ash content,and water-cement ratio. After selecting the governing factors affecting the strength through the correlation analysis, a strength prediction model, which consisted of the selected governing factors, was developed using the polynomial regression analysis. The strengths calculated from the proposed model were similar to those resulting from laboratory tests (R2=87.5%). Therefore, the proposed model can be used to predict the strength of lightweight mixtures with various mixing ratios without time-consuming experimental tests.

• Journal of Korean Physical Therapy Science
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• v.31 no.1
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• pp.88-97
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• 2024

Background: This study was to investigate effects of Correlation Analysis between Cervical-Vertebra Angle and Neck Range of Motion, Muscle Strength, Sternocleidomastoid Thickness of Patients with Forward Head Posture Design: Correlation Analysis. Methods: The subjects of this study were a total of 54 people in the forward head position and their ages were between 30 and 50 years old. The subjects cranio-vertebral angles, neck extension, neck flexion, neck rotation angles, neck flexor strength, neck extensor strength, sternocleidomastoid thickness were evaluated through measuring instruments. The thickness of the sternocleidomastoid muscle was measured using an imaging ultrasound diagnostic device (ultra sound, Versana Premier, GE Medical systems, China). CVA was measured by measuring the side photo of the subject was taken with a camera and evaluated.. neck joint range of motion was measured through digital inclinometer for extension, flexion, and neck rotation. neck muscle strength was measured by measuring the using a digital sthenometer. Data analysis in this study was statistically processed using SPSS version 26.0 (IBM SPSS Inc., USA). Correlation analysis was used and the statistical significance level was set at 0.05. Results: The results neck extension(r= 0.70^**), neck flexion(r= 0.67^**), neck rotation(r= 0.56^**), neck extensor muscle strengt(r= 0.85^**), neck flexor muscle strength(r= 0.66^**), sternocleidomastoid thicknes(r= -0.81^**) It indicates that there is a correlation. Conclusion:These results improve the Cervical-vertebra angle of patients with forward head posture should include a program to improve the thickness of the SCM. In the future, study can be used as an evidentiary material for treatment interventions to improve the Cervical-vertebra angle of patients with forward head posture.

• Journal of Korean Clinical Health Science
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• v.3 no.3
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• pp.409-418
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• 2015

Purpose. This study was to investigate the relationship between hand function and characteristics of hand. Methods. Participants were 56 occupational therapy students who studied in M colleges in Gyengsangnam-do, april 20, 2015 from 1 May, and hand circumference and length (vertical, w), the width was measured. A hand grip on the measurement subject was measured by the Grip dynamometer and Pinch gauge. Results. The results was hand length, width, circumference long, broad, thick, and hand strength was a greater correlation emerged. Grip strength was showed a significant correlation to the size and grip strength was also correlated. Conclusion. This study was correlation of length of the hand, a length wide and strength of the finger circumference.

• Computers and Concrete
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• v.5 no.5
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• pp.461-473
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• 2008

The paper explores the potential of Support Vector Machines (SVM) approach in predicting 28-day compressive strength and slump flow of self-compacting concrete. Total of 80 data collected from the exiting literature were used in present work. To compare the performance of the technique, prediction was also done using a back propagation neural network model. For this data-set, RBF kernel worked well in comparison to polynomial kernel based support vector machines and provide a root mean square error of 4.688 (MPa) (correlation coefficient=0.942) for 28-day compressive strength prediction and a root mean square error of 7.825 cm (correlation coefficient=0.931) for slump flow. Results obtained for RMSE and correlation coefficient suggested a comparable performance by Support Vector Machine approach to neural network approach for both 28-day compressive strength and slump flow prediction.

• Proceedings of the Korea Concrete Institute Conference
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• 1996.10a
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• pp.225-231
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• 1996

Prediction of the early-stage strength of concrete is useful for modernized concrete construction. An experiment was attempted on the high-strength of concrete produced by ordinary portland cement under the curing temperatures of 30, 20, $10^{\cire}C$ and the various mixing proportions such as water-binder ratio of 0.30, 0.35 and silica fume content of 10% by weight of cement. It is the aim of this study to investigare and compare the development of concrete strength with maturity and analyze the application of Maturity as a parameter to correlation estimate test results of concrete. They are statistically analyzed to infer the correlation coefficient between the Maturity and the compressive strength of high-strength concrete.

• Computers and Concrete
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• v.4 no.6
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• pp.477-497
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• 2007

The ultrasonic pulse velocity method has been widely used to evaluate the quality of concrete and assess the structural integrity of concrete structures. But its use for predicting strength is still limited since there are many variables affecting the relationship between strength and pulse velocity of concrete. This study is focused on establishing a complicated correlation between known input data, such as pulse velocity and mixture proportions of concrete, and a certain output (compressive strength of concrete) using artificial neural networks (ANN). In addition, the results predicted by the developed multilayer perceptrons (MLP) networks are compared with those by conventional regression analysis. The result shows that the correlation between pulse velocity and compressive strength of concrete at various ages can be well established by using ANN and the accuracy of the estimates depends on the quality of the information used to train the network. Moreover, compared with the conventional approach, the proposed method gives a better prediction, both in terms of coefficients of determination and root-mean-square error.

• Journal of the Korean Wood Science and Technology
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• v.33 no.5 s.133
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• pp.13-20
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• 2005

This paper deals with flexural vibration techniques as a means of predicting bending strength properties for quarter-sawn and flat-sawn planes of red pine containing knots. Dynamic modulus of elasticity $(MOE_d)$ was calculated from resonance frequency obtained from the flexural vibration induced by a magnetic driver in quarter-sawn and flat-sawn planes of red pine containing knots. The dynamic MOE were well correlated to bending strength properties. Their correlation coefficients ranged from 0.866 to 0.800 for the regression between dynamic MOE and static bending MOE or MOR. The difference of the values between quarter-sawn and flat-sawn was very small. These values were higher than correlation between percentage of total knot diameter to total width of red pine specimen $(K_T(%))$ as well as $K_O(%)$ base upon ASTM D 3737 and static bending strength properties (correlation coefficient r = 0.448~0.704), and were similar to those between static bending MOE and bending MOR (r = 0.850). These results indicate that dynamic MOE obtained from resonance frequency induced by flexural vibration of magnetic driver is able to effectively use for predicting of static bending strength of red pine containing knots as well as static MOE.

• Advances in materials Research
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• v.11 no.1
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• pp.75-90
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• 2022

In this paper, functionality of soft computing algorithms such as Group method of data handling (GMDH), Random forest (RF), Random tree (RT), Linear regression (LR), M5P, and artificial neural network (ANN) have been looked out to predict the compressive strength of concrete mixed with marble powder. Assessment of result suggests that, the overall performance of ANN based model gives preferable results over the different applied algorithms for the estimate of compressive strength of concrete. The results of coefficient of correlation were maximum in ANN model (0.9139) accompanied through RT with coefficient of correlation (CC) value 0.8241 and minimum root mean square error (RMSE) value of ANN (4.5611) followed by RT with RMSE (5.4246). Similarly, other evaluating parameters like, Willmott's index and Nash-sutcliffe coefficient value of ANN was 0.9458 and 0.7502 followed by RT model (0.8763 and 0.6628). The end result showed that, for both subsets i.e., training and testing subset, ANN has the potential to estimate the compressive strength of concrete. Also, the results of sensitivity suggest that the water-cement ratio has a massive impact in estimating the compressive strength of concrete with marble powder with ANN based model in evaluation with the different parameters for this data set.

• Tunnel and Underground Space
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• v.25 no.1
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• pp.24-36
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• 2015

The Geochang granite widely used in construction works is one of the most popular dimension stones in Korea. In order to evaluate the physical properties of rock, a lot of laboratory tests for the Geochang granite were conducted to find unit weight, absorption ratio, P wave velocity, S wave velocity, uniaxial compressive strength, Young's modulus, Poisson's ratio, tensile strength, cohesion, friction angle and point load strength index. The uniaxial compressive strength of the Geochang granite was 19.5 times tensile strength and also 8.6 times cohesion, besides P wave velocity was 1.5 times S wave velocity. Correlation analyses were also conducted to find the correlation among 11 different physical properties, where the uniaxial compressive strength showed Pearson correlation coefficient of more than 0.8 with Poisson's ratio, point load strength index and Young's modulus, respectively. Regression analyses were finally conducted by means of both linear and multiple analysis and the brief results including coefficient of determination of more than 0.7 were presented.

• Journal of the Korea Convergence Society
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• v.12 no.8
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• pp.61-66
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• 2021

The purpose of this study was to investigate the relationship between vertical jump and lower extremity muscle strength of elementary school baseball players. This study subjects were conducted with a total of 40 subjects. Vertical jump was measured using a vertical jump gauge, and a hand held dynamometer was used to measure lower extremity muscle strength. For the measurement of lower extremity muscle strength, flexion·extension·adduction·abduction·internal rotaiton·external rotation of both hip joint, flexion·extension of both knee joint, dorsi flexion·plantar flexion of both ankle joint were measured. pearson's correlation analysis was used to analyze the correlation between vertical jump and lower extremity muscle strength. From these results, it was found that the stronger the leg muscles except for the plantar flexion, the higher the vertical jump was, indicating a positive correlation. In future studies, follow-up studies on the relationship between batting ability and vertical jump & lower extremity muscle strength are needed.