An evaluation of household tissue softness

TAPPI Journal ◽  
2021 ◽  
Vol 20 (2) ◽  
pp. 91-106
Author(s):  
YUAN-SHING PERNG ◽  
TSER-YING TENG ◽  
CHING-HO CHANG
Keyword(s):  
Correlation Coefficient ◽  
Regression Equations ◽  
Matrix Approach ◽  
Low Correlation ◽  
Reciprocal Matrix ◽  
Two Parameters

This study extends our 2019 paper, a study of the softness of household tissues using a tissue soft-ness analyzer (TSA) and hand-felt panels. It revisits the softness theory of Holger Hollmark by applying a reciprocal matrix approach to measure sheet bulk softness and surface softness, and then make comparisons with the results obtained using a TSA instrument. We ascertained that there was a high correlation of R=0.904 between panel-corrected hand-felt (CHF) softness and TSA softness (TSA-HF); and a low correlation of R=-0.678 between panel-corrected hand-felt surface softness (CHSS) and TSA smoothness (TS-750). Three hunches about TSA measurements were confirmed: 1) Hollmark’s theory was confirmed by a high correlation coefficient (R=0.895) between CHF and CHSS softness, indicating that the two parameters are mutually dependent; 2) TS-750 differs from CHSS and has partial influence on TSA-HF results with a correlation of R = -0.510; and 3) although TS-750 has only limited influences on TSA-HF, further opportunities for their application can be provided using pertinent regression equations.

Chronological Development of Bones and Teeth A twin study

1970 ◽  
Vol 19 (1-2) ◽  
pp. 75-75 ◽  
Author(s):  
L. Gedda ◽  
G. Brenci
Keyword(s):  
Statistical Analysis ◽  
Correlation Coefficient ◽  
Twin Study ◽  
Bone Age ◽  
Dental Age ◽  
Hereditary Component ◽  
Image Position ◽  
Two Parameters

The hereditary component of the chronological development of bones and teeth has been studied, in 40 twin pairs aged 5-7 years, through dental age (defined on account of the mineralization of the permanent dentition's dental buds) and bone age (denned on account of the presence and form of the hand ossification nuclei).The statistical analysis shows a correlation coefficient of 0.95 in MZ and 0.84 in DZ twins for dental age; and of 0.94 in MZ and 0.81 in DZ twins for bone age.The following are therefore the estimates of the hereditary component (based on Holzinger's formula) for the two parameters studied:

Serious Analytical and Conceptual Errors in Bilirubin Binding Studies

PEDIATRICS ◽  
1981 ◽  
Vol 67 (6) ◽  
pp. 935-936
Author(s):  
Charles E. Ahlfors
Keyword(s):  
Correlation Coefficient ◽  
Linear Correlation ◽  
Accurate Method ◽  
Binding Studies ◽  
Low Correlation ◽  
Total Capacity ◽  
Bilirubin Binding

The unexpectedly high and 1:1 correlation among fluorometric, Sephadex, and peroxidase determinations of total and reserve bilirubin binding capacities as reported by Cashore et al1 is quite remarkable considering the serious analytical and conceptual errors in the article, the previously observed lack of linear correlation between the fluorometer and 2-(4'-hydroxybenzene)azobenzoic acid (HABA),2 and the relatively low correlation coefficient (.92) observed when the peroxidase test is compared with itself on different instruments.3 The addition of sufficient bilirubin to near saturation of the first site should make the fluorometer a reasonably accurate method of assessing "true" total capacity (usually thought to be 1 mole of bilirubin bound per mole of albumin).

scholarly journals Pengaruh Pelatihan Kerja Terhadap Kinerja Karyawan Pada PT Kusumatama Mitra Selaras Jakarta

2018 ◽  
Vol 2 (2) ◽  
pp. 239-246
Author(s):  
Rani Kurniasari ◽  
Nurvi Oktiani ◽  
Gema Ramadhanti
Keyword(s):  
Human Resources ◽  
Correlation Coefficient ◽  
Research Method ◽  
Quantitative Methods ◽  
Regression Coefficient ◽  
Coefficient Of Determination ◽  
Regression Equations ◽  
Performance Variables ◽  
Training Variable

ABSTRACT: One of the important factors in improving the quality of Human Resources (HR) is by training and developing employees to achieve company goals. This research method uses quantitative methods, with the technique of determining saturated sampling. The research was conducted through questionnaires to all employees of PT. Kasumatama Mitra Selaras, which is an outsourcing company with a total of 37 respondents. This questionnaire calculation with the technique of calculating the correlation coefficient, the coefficient of determination and multiple linear regression equations. With the SPSS 21 application, the correlation coefficient results are 0.650 and the results are categorized as strong. the determination coefficient can be seen that 0.422 or 42.2% of PT Kusumatama Mitra Selaras performance variables can be influenced by the training variable and the remaining 57.8% is influenced by other factors. Based on the calculation table of the regression equation can be obtained the equation is Y = 13.155 + 0.662 X. From the equation of the function it can be said that if training is constant or is 0 then Y (Performance) is equal to 13.155 with a regression coefficient of 0.662.

scholarly journals Estimation of Stature from Upper Arm Length

2021 ◽  
Vol 11 (5) ◽  
pp. 23-29
Author(s):  
Tripti Shakya ◽  
Deepshikha Mishra ◽  
Prabesh Pandey
Keyword(s):  
Correlation Coefficient ◽  
Strong Relationship ◽  
Cross Sectional Study ◽  
Regression Equation ◽  
Regression Equations ◽  
Strong Positive Correlation ◽  
Upper Arm ◽  
Cross Sectional ◽  
Male And Female ◽  
Upper Arm Length

Introduction: Reconstruction of stature from long bones of the upper extremity is of great medico-legal relevance. Upper arm length (UAL) estimate stature with reasonable accuracy and is reliable factor for predicting stature. There is a strong relationship between stature and UAL and many sets of linear equation have been developed which are easiest and reliable methods for predicting relation between stature and body segments. These derived regression equations are population specific and cannot be applied in other populations. Studies on UAL for estimation of stature is lacking among Nepalese population. Hence, present study was conducted to investigate relationship between stature and UAL and to formulate regression formula for estimation of stature from UAL among Nepalese population. Method: A cross-sectional study was conducted among 150 attendees of patient visiting male and female clinic in Patan hospital, Nepal. Among 150 participants 75 were male and 75 were female. In present study stature, right and left upper arm length was measured. Pearson’s correlation coefficient (r) was calculated. Regression equation was formulated for reconstruction of stature from upper arm length of both sides as well as for both male and female separately. Result: All the measured parameters i.e. stature, right upper arm length and left upper arm length were higher in male than female (p<0.001). Strong positive correlation was found between stature and UAL in both males and females thereby indicating that stature can be estimated from UAL. Conclusion: UAL is a reliable body parameter for predicting stature. It can be of great help to anatomists, clinicians and anthropologists. Key words: Stature, upper arm length, correlation coefficient and regression equation.

scholarly journals The Central Stars Parameters and the Distances to Galactic Planetary Nebulae

2003 ◽  
Vol 209 ◽  
pp. 57-57
Author(s):  
O. I. Sharova
Keyword(s):  
Correlation Coefficient ◽  
Planetary Nebulae ◽  
Critical Value ◽  
Confidence Probability ◽  
Average Value ◽  
Regression Relationship ◽  
Individual Distance ◽  
Two Parameters ◽  
Central Stars

In our paper (Sharova, 1995) a method of determining the distances to galactic planetary nebulae has been based on the recently established (Sharova, 1992) regression relationship between the central stars radius and the temperature. Now our scale is compared to 18 other scales, in four of which the central stars parameters also are used, instead of nebulae ones. The scale distance estimations DS are compared with independently known individual distance D. The values log(DS/D) and their dependence on radius of the nebulae are analysed. Each scale is described by two parameters: a geometrical average value < log DS/D > and the relation ρ/ρc, where ρ is the correlation coefficient for log DS/D — log RN, and ρc is its critical value. If ρ/ρc > 1, the correlation is significant with the confidence probability 95%. For example we obtained the following results: ρ/ρc = 0.153, 0.494, 2.126, 2.228; < DS/D >=0.999, 2.145, 2.126, 1.414 for our scale and for widely known MKH, CKL, VdSZ scales respectively. By both criteria our scale achieves better agreements, on average, with individual estimations of distances than others.

Improving Ligand-Ranking of AutoDock Vina by Changing the Empirical Parameters

2021 ◽  
Author(s):  
T. Ngoc Han Pham ◽  
Trung Hai Nguyen ◽  
Nguyen Minh Tam ◽  
Thien Y Vu ◽  
Nhat Truong Pham ◽  
...  
Keyword(s):  
Hydrogen Bond ◽  
Ligand Binding ◽  
Success Rate ◽  
Binding Affinity ◽  
Correlation Coefficient ◽  
Autodock Vina ◽  
Docking Simulations ◽  
Low Correlation ◽  
Very High ◽  
Ligand Ranking

AutoDock Vina (Vina) achieved a very high docking-success rate, p ̂, but give a rather low correlation coefficient, R, for binding affinity with respect to experiments. This low correlation can be an obstacle for ranking of ligand-binding affinity, which is the main objective of docking simulations. In this context, we evaluated the dependence of Vina R coefficient upon its empirical parameters. R is affected more by changing the gauss2 and rotation than other terms. The docking-success rate p ̂ is sensitive to the alterations of the gauss1, gauss2, repulsion, and hydrogen bond parameters. Based on our benchmarks, parameter set1 has been suggested to be the most optimal. The testing study over 800 complexes indicated that the modified Vina provided higher correlation with experiment R_set1=0.556±0.025 compared with R_Default=0.493±0.028 obtained by the original Vina and R_(Vina 1.2)=0.503±0.029 by Vina version 1.2. Besides, the modified Vina can be also applied more widely, giving R≥0.500 for 32/48 targets, compared with the default package, giving R≥0.500 for 31/48 targets. In addition, validation calculations for 1036 complexes obtained from version 2019 of PDBbind refined structures showed that the set1 of parameters gave higher correlation coefficient (R_set1=0.621±0.016) than the default package (R_Default=0.552±0.018) and Vina version 1.2 (R_(Vina 1.2)=0.549±0.017). The version of Vina with set1 of parameters can be downloaded at https://github.com/sontungngo/mvina. The outcomes would enhance the ranking of ligand-binding affinity using Autodock Vina.

A Modified Model for Prediction of India's Future Energy Requirement

1992 ◽  
Vol 3 (4) ◽  
pp. 371-386 ◽  
Author(s):  
L. Suganthi ◽  
T.R. Jagadeesan
Keyword(s):  
Time Series ◽  
Correlation Coefficient ◽  
Econometric Model ◽  
Carbon Dioxide Emission ◽  
Least Square ◽  
Regression Equations ◽  
Modified Model ◽  
Technological Efficiency ◽  
The Impact ◽  
Watson Statistic

A modified model has been projected in this paper which links environmental quality and technological efficiency with energy and economic factors. A comparison is made between the results obtained from the modified model with a time series and an econometric model using Ordinary Least Square Error (OLSE), square of the correlation coefficient R2 and Durbin Watson statistic. The time series model is built using seven regression equations and the best fit is selected from among them. The econometric model is built with consumption, price and gross national product. In the modified model, two more variables, technological efficiency and carbon dioxide emission are included, which help to determine the impact of these variables on energy consumption. It is found that the modified model gives least squared error and higher correlation coefficient for coal, oil and electricity. Also the Durbin Watson statistic ‘DW’ is found to be higher in two out of the three cases - coal and oil. The requirement of coal, oil and electricity in the year 1995–96 and 2000–01 is determined using the data for the period 70–89.

Study on Population-Farmland-Settlement in West Hainan at Town Scale

2013 ◽  
Vol 726-731 ◽  
pp. 4823-4826 ◽  
Author(s):  
Tie Chou Shi ◽  
Xiao Hong Xu
Keyword(s):  
Population Size ◽  
Correlation Coefficient ◽  
Research Area ◽  
Moderate Correlation ◽  
Settlement Area ◽  
Low Correlation ◽  
Relationship Of ◽  
The Relationship

The paper chooses West Hainan (Dongfang city and Changjiang county) as the research area, takes the towns as the unit, and analyses the change and relationship of population-farmland-settlement from 1950s to 1970s. The research shows that the correlation coefficient of population size and farmland area is 0.313 in 1950s and 0.417 in 1970s in West Hainans 29 towns, the two belong to low correlation, population and farmland have smaller relationship; the correlation coefficient of farmland area and settlement area is 0.454 in 1950s and 0.598 in 1970s, the two belong to moderate correlation, farmland and settlement have substantive relationship; the correlation coefficient of population size and settlement area is 0.794 in 1950s and 0.710 in 1970s, the two belong to high correlation, the relationship between the population and the settlement is very close.

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