Study on the Relationship between Nominal Filtration Accuracy and Absolute Filtration Accuracy of the Automobile Engine Oil Filter Materials

2012 ◽  
Vol 476-478 ◽  
pp. 2213-2218 ◽  
Author(s):  
Jian Yong Feng ◽  
Jian Chun Zhang ◽  
Hua Zhang ◽  
Da Xiang Yang
Keyword(s):  
Linear Regression ◽  
Experimental Testing ◽  
Regression Equation ◽  
Engine Oil ◽  
Practical Significance ◽  
Linear Regression Equation ◽  
Automobile Engine ◽  
Filter Materials ◽  
The Absolute ◽  
The Relationship

The filtration effect of automobile engine oil filter materials have two different expression index,such as nominal filtration accuracy and absolute filtration accuracy.In fact,the nominal filtration accuracy is labeled by manufacturer,however,the absolute filtration accuracy is needed experiment testing only to know.After testing the absolute filtration accuracy of these ten kinds of oil filter materials,it is turned out that there is an obvious difference between these two filtration accuracy.So this paper is based on the results of the two filtration precision and established a linear regression equation of absolute filtration accuracy=2.922+0.631×nominal filtration accuracy.If only knowing of the nominal filtration accuracy of oil filter materials,then the absolute filtration accuracy can be computed from the linear regression equation instead of experimental testing of absolute filtration accuracy.What’s more,this linear regression equation is easy and simple and has some application value and practical significance.

scholarly journals Relationship between Cognitive Style and Habits of Mind

2019 ◽  
Vol 2 (1) ◽  
pp. 23
Author(s):  
Hayatun Nufus ◽  
Rezi Ariawan
Keyword(s):  
Linear Regression ◽  
Cognitive Style ◽  
Significance Test ◽  
Regression Equation ◽  
Coefficient Of Determination ◽  
Habits Of Mind ◽  
Linear Regression Equation ◽  
Research Subjects ◽  
Analysis Technique ◽  
The Relationship

This research is a correlational study that examines the relationship between cognitive style and habits of mind. The research subjects involved 4th semester students in the Department of Mathematics Education at the Faculty of Tarbiyah and Teacher Training of UIN Suska Riau which consisted of students with heterogeneous academic abilities. Cognitive style data was collected using the GEFT question instrument with test techniques. Habits of mind data were collected using a questionnaire instrument with a questionnaire distribution technique. The data analysis technique begins with the Pearson Product Moment correlation test which is continued with the significance test and the calculation of the magnitude of the relationship that occurs using the coefficient of determination. Because the data is positively correlated, it continues with determining the linear regression equation. The results showed that there was a significant weak correlation between cognitive style and habits of mind with a relationship score of 6% and a linear regression equation y '= 36.35 + 0.31 x.

scholarly journals Ethnomathematics: Predicting the Average Height of the Bali Mula Ancestors using Linear Regression

2019 ◽  
Vol 8 (1) ◽  
pp. 1
Author(s):  
Jero Budi Darmayasa ◽  
Wahyudin W ◽  
Tatang Mulyana
Keyword(s):  
Linear Regression ◽  
Index Finger ◽  
Cultural Anthropology ◽  
Predictor Variable ◽  
Regression Equation ◽  
Average Height ◽  
Linear Regression Equation ◽  
Finger Length ◽  
Initial Stage ◽  
The Relationship

This research is a study of Ethnomathematics. In this case, we view Ethnomathematics as an intersection between mathematics, mathematical modelling, and cultural anthropology. The purpose of this study is to determine the average height of <em>Bali Mula</em> ancestors communities in the area of Ancient Caldera Batur. We use exploration, observation, experimentation, documentation, and interviews method. In the initial stage of the study, we determine the relationship between the finger length index and the height body of <em>Bali Mula</em> male. The linear regression equation expresses the relationship, which is a length of the index finger as a predictor variable. Moreover, measure the pillars width of some houses <em>Saka Roras</em> and substituting it, we have the regression equation. Consequently, we estimate the average height of the <em>Bali Mula </em>ancestors in Kintamani area are 165 cm. Since it contains linier regression concepts, prediction the average height of <em>Bali Mula</em> ancestors from their traditional homes may be used as the context in mathematical (statistical) learning at school or university.

Proton NMR Analysis of Octane Number for Motor Gasoline: Part III

1992 ◽  
Vol 46 (3) ◽  
pp. 498-503 ◽  
Author(s):  
M. Ichikawa ◽  
N. Nonaka ◽  
H. Amano ◽  
I. Takada ◽  
S. Ishimori ◽  
...  
Keyword(s):  
Linear Regression ◽  
Octane Number ◽  
Additional Data ◽  
Regression Equation ◽  
Linear Regression Equation ◽  
Visual Estimation ◽  
High Olefin ◽  
Automobile Gasoline ◽  
Pmr Spectra ◽  
The Relationship

A method to evaluate the octane number of automobile gasoline by proton magnetic resonance (PMR) spectrometry has been studied. Twelve samples of marketed winter gasoline, whose octane numbers and compositions were identified according to the ASTM standards, and high-olefin gasoline were used to supplement the insufficient coverage of a previous report with additional data. Then, a linear regression equation regarding the relationship between the octane number and PMR data was prepared from the PMR spectra of the 21 samples used for the previous report, whose octane numbers were known, and the 12 samples used this time. Further, the appropriateness of the regression equation was assessed. This report concerns the results of a study in which the scope of the previous study, lacking sufficient data, has been supplemented with additional data to improve the accuracy of the visual estimation of the octane number using the pattern recognition method. Also, a linear regression equation was obtained and found useful for octane number estimation.

On: “Analysis of the Relationship between Acoustic Reflectivity and Sediment Porosity” by R. W. Faas (GEOPHYSICS, August 1969, p. 546–553)

Geophysics ◽  
1971 ◽  
Vol 36 (3) ◽  
pp. 613-615 ◽  
Author(s):  
Abner Blackman
Keyword(s):  
Linear Regression ◽  
Observational Data ◽  
Regression Equation ◽  
Linear Regression Equation ◽  
Empirical Relationships ◽  
The Relationship

Faas states that a linear regression equation relating sediment porosity and acoustic reflectivity was derived empirically from data previously published by several investigators. The distinction between empirically and theoretically derived relationships is important because empirically derived relationships can be used for predictive purposes with far greater confidence than theoretical ones. The weight of observational data stands behind empirical relationships, while theoretical relationships are untested by observation.

Relationship between Life Change and Illness in Coping versus Sensitive Persons

1981 ◽  
Vol 48 (3) ◽  
pp. 711-714 ◽  
Author(s):  
Eric J. Cooley ◽  
James C. Keesey
Keyword(s):  
Social Support ◽  
College Students ◽  
Linear Regression ◽  
Social Supports ◽  
Regression Equation ◽  
Life Change ◽  
Linear Regression Equation ◽  
The Relationship

A linear regression equation for the relationship between life change and illness for 281 college students was used to select subjects from the quartile showing less illness than predicted (coping subjects, n = 34) and from the quartile showing more illness than predicted (sensitive subjects, n = 20). Comparisons between groups on the number and use of social supports and on the K, 1, 2, and 3 scales of the MMPI showed no significant differences in social support. The sensitive subjects were higher on scales 1 and 3 of the MMPI but not different on K or 2. The results were discussed in terms of strategies for dealing with stress which are reflected in a 1, 3 elevation on the MMPI.

scholarly journals Relationship between Cognitive Style and Habits of Mind

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Hayatun Nufus ◽  
Rezi Ariawan
Keyword(s):  
Linear Regression ◽  
Cognitive Style ◽  
Significance Test ◽  
Regression Equation ◽  
Coefficient Of Determination ◽  
Habits Of Mind ◽  
Linear Regression Equation ◽  
Research Subjects ◽  
Analysis Technique ◽  
The Relationship

This research is a correlational study that examines the relationship between cognitive style and habits of mind. The research subjects involved 4th semester students in the Department of Mathematics Education at the Faculty of Tarbiyah and Teacher Training of UIN Suska Riau which consisted of students with heterogeneous academic abilities. Cognitive style data was collected using the GEFT question instrument with test techniques. Habits of mind data were collected using a questionnaire instrument with a questionnaire distribution technique. The data analysis technique begins with the Pearson Product Moment correlation test which is continued with the significance test and the calculation of the magnitude of the relationship that occurs using the coefficient of determination. Because the data is positively correlated, it continues with determining the linear regression equation. The results showed that there was a significant weak correlation between cognitive style and habits of mind with a relationship score of 6% and a linear regression equation y '= 36.35 + 0.31 x.

scholarly journals Relationship between selenium concentration in blood and liver of cattle.

2018 ◽  
Vol 53 (3) ◽  
pp. 272
Author(s):  
G. CHRISTODOULOPOULOS (Γ. ΧΡΙΣΤΟΔΟΥΛΟΠΟΥΛΟΣ) ◽  
N. ROUBIES (Ν. ΡΟΥΜΠΙΕΣ) ◽  
H. KARATZIAS (Χ. ΚΑΡΑΤΖΙΑΣ) ◽  
A. PAPASTERIADIS (Α. ΠΑΠΑΣΤΕΡΙΑΔΗΣ)
Keyword(s):  
Linear Regression ◽  
Linear Correlation ◽  
Liver Tissue ◽  
Selenium Concentration ◽  
Regression Equation ◽  
Linear Regression Equation ◽  
Total Blood ◽  
Tissue Selenium ◽  
Cattle Blood ◽  
The Relationship

The objective of this study was to investigate the relationship between total blood selenium concentration and liver tissue selenium concentration in cattle. Blood and liver samples were collected from 205 individuals brought to slaughter houses. The results had shown that there is a linear correlation between the concentration of selenium in total blood of cattle (X) and its concentration in the liver (Y). The linear regression equation was: Y=0.194+3.951± (0.265***) X (0.009 pg/ml < X < 0.219 pg/ml, 0.110 μg/g DM < Y < 1.512 μg/g DM) (r2=0.523, ***P<0.001, n=205).

Coronal Suture Pathology and Synostotic Progression in Rabbits with Congenital Craniosynostosis

1996 ◽  
Vol 33 (5) ◽  
pp. 369-378 ◽  
Author(s):  
Mark P. Mooney ◽  
Timothy D. Smith ◽  
Annie M. Burrows ◽  
Herbert L. Langdon ◽  
Cynthia E. Stone ◽  
...  
Keyword(s):  
Linear Regression ◽  
Inbred Strain ◽  
Rabbit Model ◽  
Regression Equation ◽  
Histologic Examination ◽  
Coronal Suture ◽  
Linear Regression Equation ◽  
Cross Sectional ◽  
High Tension ◽  
Single Focus

The purpose of the present study was to describe coronal suture pathology and cross sectional synostotic progression in an inbred strain of rabbits with congenital craniosynostosis. Calvaria from 102 perinatal rabbits (39 unaffected; 63 bilateral or unilateral synostosis) were collected at fetal days 21 (n = 12), 25 (n = 20), 27 (n = 22), 30 (term) (n = 32), and 3 days post-term (n = 16) for gross morphologic and histologic examination. Synostotic foci, the extent of relative bony bridging, and suture morphology were evaluated qualitatively and quantitatively. Of the 204 coronal sutures examined, 91 sutures were synostosed, and 113 were patent. All synostosed sutures showed similar foci by day 25, which originated as bony bridges in the middle of each suture on the ectocortic surface. Bony bridging width increased significantly (p < .001) from day 25 through 3 days post-term, and was best described by a linear regression equation. Osteogenic front areas of synostosed sutures were up to 2.5 times greater than patent sutures in term fetuses. Findings demonstrate that coronal suture synostosis in the congenital rabbit model (1) begins early during suture morphogenesis (before 25 days of gestation); (2) consistently radiates from a single focus corresponding to a normal interdigitating region (i.e., a high-tension environment); (3) varies in onset and rate as evidenced by low R2 value between age and extent of bony bridging; and (4) is the result of early hyperostosis of the osteogenic fronts and sutural agenesis. A number of possible pathogenetic mechanisms are discussed.

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