TAILIEUCHUNG - A comprehensive investigation on static and dynamic friction coefficients of wheat grain with the adoption of statistical analysis

This paper deals with studying and modeling static friction coefficient (SFC) and dynamic friction coefficient (DFC) of wheat grain as affected by several treatments. Significance of single effect (SE) and dual interaction effect (DIE) of treatments (moisture content and contact surface) on SFC and, SE, DIE, and triple interaction effect (TIE) of treatments (moisture content, contact surface and sliding velocity) on DFC were determined using statistical analysis methods. Multiple linear regression (MLR) modeling was employed to predict SFC and DFC on different contact surfaces. Predictive ability of developed MLR models was evaluated using some statistical parameters (coefficient of determination (R2 ), root mean square error (RMSE), and mean relative deviation modulus (MRDM)). Results indicated that significant increasing DIE of treatments on SFC was and 3 times greater than significant increasing SE of moisture content and contact surface, respectively. In case of DFC, the significant increasing TIE of treatments was , , and times greater than SE of moisture content, contact surface, and sliding velocity, respectively. It was also found that the SE of contact surface on SFC was times greater than that of moisture content and the SE of contact surface on DFC was times greater than that of moisture content or sliding velocity. According to the reasonable average of statistical parameters (R2 = , RMSE = and MRDM = ), the SFC and DFC could be successfully predicted by suggested MLR models. Practically, it is recommended to apply the models for direct prediction of SFC and DFC, respective to each contact surface, based on moisture content and sliding velocity. | A comprehensive investigation on static and dynamic friction coefficients of wheat grain with the adoption of statistical analysis

• Sinh học
• Analysis of variance
• Duncan’s multiple range test
• Moisture content
• Sliding velocity
• Contact surface
• Profit variance analysis
• Variance analysis
• Cost accounting
• Fundamentals of cost accounting
• Cost analysis
• Cost management systems
• Lecture Basic Statistics
• Bài giảng Thống kê cơ bản
• Repeated measures analysis of variance
• Individual differences
• The denominator of the F‑ratio
• Two factor analysis of variance
• Two factor designs
• Factorial designs
• Fruit yield
• Genetic analysis of variance
• Sponge gourd
• Sponge gourd [Luffa cylindrica (Roem ) L ]
• Analysis of variance fruit yield
• Management control systems
• Statistical techniques
• Statistical techniques in business
• Statistical techniques in economics
• Descriptive statistics
• F distribution
• Statistics for business
• Describing data
• Equal variances
• Basic statistics
• Confidence interval
• Mean performance
• Zea mays L
• Twelve characters studied in maize
• Maize (Zea mays L )
• Diallel analysis
• Combining ability effects
• GCA variance
• SCA variance
• Over environments
• Experimentwise α level
• Measuring effect size
• The scheffe test
• Nuclear engineering and technology
• Analysis of inconsistent source sampling
• Monte carlo weight window variance reduction methods
• Moderate levels of splitting and roulettin
• The consistent adjoint driven importance sampling
• Genetic variance
• Lady finger
• Genetic parameters
• Recessive alleles
• Abelmoschus esculentus L
• Genetic advance
• Genotypic coefficient of variation
• Genotypic variance
• Phenotypic coefficient of variation
• phenotypic variance
• Line × tester
• Yield contributing traits in tomato
• Heterotic expression studies
• BMC Genomics
• Genetic connectedness
• Prediction error of variance
• Variance of unit effect estimates
• Whole genome prediction
• Agricultural species
• Differentially expressed genes
• Between study variance
• Random effects model
• Meta analysis
• Alzheimer’s microarray datasets
• Agricultural science
• Separation of genetic variance components
• Eight faba bean genotypes
• Combining ability
• Twenty eight crosses
• Variance component analysis
• Functional genomics
• Enrichment or depletion analysis
• Regulatory genome
• Splice sites
• DNA methylated regions
• Half diallel
• Yield component
• Half diallel analysis in cowpea
• Analysis of variance for diallel analysis
• Components traits in cowpea
• BMC Bioinformatics
• Mass spectrometry
• Validation biomarkers
• Technical variability
• Experimental design
• Nonparametric statistics
• Additional topics
• Regression analysis
• Multiple variable regression analysis
• Two variable regression analysis
• Quantitative Investment Analysis
• Investment process
• Quantitative methods
• Cash flow
• Mean variance analysis
• Efficient portfolios